Journal articles
Duckworth A, Gibbons MA, Beaumont RN, Wood AR, Almond H, Lunnon K, Lindsay MA, Scotton CJ, Tyrrell J (In Press). A Mendelian randomisation study of smoking causality in IPF compared with COPD.
Abstract:
A Mendelian randomisation study of smoking causality in IPF compared with COPD
AbstractIn a normal year, the fatal lung disease Idiopathic Pulmonary Fibrosis (IPF) accounts for ∼1% of UK deaths. Smoking is a recognised risk factor for IPF but the question of causality remains unanswered. Here, we used data from the UK Biobank (UKBB) and the well-established genetic technique of Mendelian randomisation (MR) methods to investigate whether smoking is causal for IPF compared with COPD, where causality is established.We looked at observational associations in unrelated Europeans, with 871 IPF cases, 11,413 COPD cases and 366,942 controls. We performed analyses using one-sample MR to test for inferred smoking causality in ever smokers using genetic variants that have a previously demonstrated association with smoking heaviness.Strong associations between disease status and ever having smoked were found in both IPF (OR = 1.52; 95%CI:1.32-1.74; P=2.4×10−8) and COPD (OR= 5.77; 95%CI:5.48-6.07; P<1×10−15). Using MR, a one allele increase in smoking volume genetic risk score was associated with higher odds of COPD in ever smokers, (OR = 4.32; 95%CI:3.37-5.54; P<1×10−15), but no association was seen in IPF (OR=0.55; 95%CI: 0.17-1.81; P=0.33). No association was found between the genetic risk score and disease prevalence in never smokers with IPF (OR = 1.00; 95%CI:0.98-1.02; P=1.00) or COPD (OR = 1.00; 95%CI:0.99-1.01; P=0.53).Although both IPF and COPD are observationally associated with smoking, our analysis provides evidence inferring that the association is causal in COPD but there is no such evidence in IPF. This suggests that other environmental exposures also need consideration in IPF.
Abstract.
Green HD, Jones A, Evans JP, Wood AR, Beaumont RN, Tyrrell J, Frayling TM, Smith C, Weedon MN (In Press). A genome wide association study of frozen shoulder identifies a common variant of <i>WNT7B</i> and diabetes as causal risk factors.
Abstract:
A genome wide association study of frozen shoulder identifies a common variant of WNT7B and diabetes as causal risk factors
AbstractFrozen shoulder is a painful condition that often requires surgery and affects up to 5% of individuals aged 40-60 years. Little is known about the causes of the condition, but diabetes is a strong risk factor. To begin to understand the biological mechanisms involved, we aimed to identify genetic variants associated with frozen shoulder and to use Mendelian randomization to test the causal role of diabetes.We performed a genome wide association study (GWAS) of frozen shoulder in the UK Biobank using data from 2064 cases identified from ICD-10 codes. We used data from FinnGen for replication. We used one-sample and two-sample Mendelian randomization approaches to test for a causal association of diabetes with frozen shoulder.We identified a single genome-wide significant locus (lead SNP rs62228062; OR=1.34 [1.28-1.41], p=2×10−16) that contained WNT7B. A recent transcriptome study identified WNT7B as amongst the most enriched transcripts in anterior capsule tissue in patients undergoing arthroscopic capsulotomy surgery for frozen shoulder suggesting WNT7B as a potential causal gene at the locus. The lead SNP was also strongly associated with Dupuytren’s contracture (OR=2.61 [2.50, 2.72], p<1×10−100). The Mendelian randomization results provided evidence that type 1 diabetes is a causal risk factor for frozen shoulder (OR=1.04 [1.02-1.07], p=6×10−5). There was no evidence that obesity was causally associated with frozen shoulder, suggesting that diabetes influences risk of the condition through glycemic rather than mechanical effects.We have identified the first genetic variant associated with frozen shoulder. WNT7B is a potential causal gene at the locus. Diabetes is a likely causal risk factor. Our results provide evidence of biological mechanisms involved in this common painful condition.
Abstract.
Liu J, Richmond RC, Bowden J, Barry C, Dashti HS, Daghlas I, Lane JM, Jones SE, Wood AR, Frayling TM, et al (In Press). Assessing the causal role of sleep traits on glycated haemoglobin: a Mendelian randomization study.
Abstract:
Assessing the causal role of sleep traits on glycated haemoglobin: a Mendelian randomization study
ABSTRACTObjectiveTo examine the effects of sleep traits on glycated haemoglobin (HbA1c).DesignObservational multivariable regression (MVR), one-sample Mendelian randomization (1SMR), and two-sample summary data Mendelian randomization (2SMR).SettingUK Biobank (UKB) prospective cohort study and genome-wide association studies from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC).ParticipantsIn MVR and 1SMR, participants were adults (mean (SD) age 57 (8) years; 54% female) from the UKB (n=336,999); in 2SMR, participants were adults (53 (11) years; 52% female) from MAGIC (n=46,368). All participants were adults of European ancestry.ExposuresSelf-reported insomnia frequency (usually vs sometimes or rarely/never); sleep duration: 24-hour sleep duration (hours/day); short sleep (≤6 hours vs 7-8 hours) and long sleep (≥9 hours vs 7-8 hours); daytime sleepiness and daytime napping (each consisting of 3 categories: never/rarely, sometimes, usually); chronotype (5 categories from definite morning to definite evening preference).Main outcome measureHbA1c in standard deviation (SD) units.ResultsAcross MV, 1SMR, 2SMR, and their sensitivity analyses we found a higher frequency of insomnia (usually vs sometimes or rarely/never) was associated with higher HbA1c (MVR: 0.053 SD units, 95% confidence interval (0.046 to 0.061), 1SMR: 0.52, (0.42 to 0.63), 2SMR: 0.22, (0.10 to 0.35)). Results remained significant but point estimates were somewhat attenuated after excluding people with diagnosed diabetes. For other sleep traits, there was less consistency with significant associations when using some, but not all methods.ConclusionsThis study suggests that insomnia increases HbA1c levels. These findings could have important implications for developing and evaluating strategies that improve sleep habits to reduce hyperglycaemia and prevent diabetes.SUMMARY BOXWhat is already known on this topicIn observational data, insomnia, short sleep duration, and evening preference are associated with higher risk for type 2 diabetes.Mendelian randomization (MR) studies have not found evidence of a causal effect of short sleep on type 2 diabetes or glycaemic traits but have indicated an effect of insomnia on type 2 diabetes. It is unclear whether insomnia influences HbA1c levels, a marker of long-term hyperglycaemia, in the general population.Recently identified genetic variants robustly associated with insomnia, sleep duration, daytime sleepiness, napping, and chronotype can be used in MR studies to explore causal effects of these sleep traits on HbA1c levels.What this study addsThis study suggests that a higher frequency of insomnia increases HbA1c levels in the general population and after excluding people with diabetes.We found no robust evidence for causal effects of other sleep traits on HbA1c levels.These findings improve our understanding of the impact of sleep traits on HbA1c levels and have important implications for developing and evaluating strategies that improve sleep habits to reduce hyperglycaemia and prevent diabetes.
Abstract.
Nongmaithem SS, Beaumont RN, Dedaniya A, Wood AR, Ogunkolade B-W, Hassan Z, Krishnaveni GV, Kumaran K, Potdar RD, Sahariah SA, et al (In Press). Associations of genetic scores for birth weight with newborn size and later Anthropometric traits and cardiometabolic risk markers in South Asians.
Abstract:
Associations of genetic scores for birth weight with newborn size and later Anthropometric traits and cardiometabolic risk markers in South Asians
AbstractWe recently reported genetic variants associated with birth weight and their effect on future cardiometabolic risk in Europeans. Despite a higher burden of low birth weight and cardiometabolic disorders, such studies are lacking in South Asians. We generated fetal and maternal genetic scores (fGS and mGS) from 196 birth weight-associated variants identified in Europeans and conducted association analysis with various birth measures and serially measured anthropometric and cardiometabolic traits from seven Indian and Bangladeshi cohorts. Although fGS and mGS were comparable to Europeans, birth weight was substantially smaller suggesting strong environmental constraints on fetal growth in South Asians. Birth weight increased by 50.7g and 33.6g per standard deviation fGS (P=9.1×10−11) and mGS (P=0.003) in South Asians. The fGS was further associated with childhood body size and head circumference, fasting glucose, and triglycerides in adults (P<0.01). Our study supports a common genetic mechanism partly explaining associations between early development and later cardiometabolic health in different populations, despite phenotypic and environmental differences.
Abstract.
Beaumont R, Kotecha SJ, Wood AR, Knight BA, Sebert S, McCarthy MI, Hattersley AT, Järvelin M-R, Timpson NJ, Freathy RM, et al (In Press). Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies.
PLoS GeneticsAbstract:
Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies
Babies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) 90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced environment-related growth-restriction or overgrowth, respectively, and babies who are heritably small or large. However, the relative proportions within each group are unclear. We assessed the extent to which common genetic variants underlying variation in birth weight influence the probability of being SGA or LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 11,951 babies and 5,182 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model.
Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal=0.75 (0.71,0.80) and 1.32 (1.26,1.39); ORmaternal=0.81 (0.75,0.88) and 1.17 (1.09,1.25), respectively per 1 decile higher GS). We found evidence that the smallest 3% of babies had a higher BW GS, on average, than expected from their observed birth weight (assuming an additive. polygenic model: Pfetal=0.014, Pmaternal=0.062). Higher maternal SBP GS. was associated with higher odds of SGA P=0.005.
We conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies.
Abstract.
Oram RA, Weedon M, Wood A, Beaumont R, Tyrrell J (In Press). Development and Standardization of an Improved Type 1 Diabetes Genetic Risk Score for Use in Newborn Screening and Incident
Diagnosis. Diabetes Care
Howe LD, Kanayalal R, Beaumont RN, Davies AR, Frayling TM, Harrison S, Jones SE, Sassi F, Wood AR, Tyrrell J, et al (In Press). Effects of body mass index on relationship status, social contact, and socioeconomic position: Mendelian Randomization study in UK Biobank.
Abstract:
Effects of body mass index on relationship status, social contact, and socioeconomic position: Mendelian Randomization study in UK Biobank
AbstractObjectiveTo assess whether body mass index (BMI) has a causal effect on social and socioeconomic factors, including whether both high and low BMI can be detrimental.DesignMendelian Randomization, using genetic variants for BMI to obtain unconfounded estimates, and non-linear Mendelian Randomization.SettingUK Biobank.Participants378,244 men and women of European ancestry, mean age 57 (SD 8 years).Main outcome measuresTownsend deprivation index, income, age completed full time education, degree level education, job class, employment status, cohabiting relationship status, participation in leisure and social activities, visits from friends and family, and having someone to confide in.ResultsHigher BMI was causally associated with higher deprivation, lower income, fewer years of education, lower odds of degree-level education and skilled employment. For example, a 1 SD higher genetically-determined BMI (4.8kg/m2 in UK Biobank) was associated with £1,660 less income per annum [95%CI: £950, £2,380]. Non-linear Mendelian Randomization provided evidence that both low BMI (bottom decile, <22kg/m2) and high BMI (top seven deciles, >24.6kg/m2) can increase deprivation and reduce income. In men only, higher BMI was related to lower participation in leisure and social activities. There was no evidence of causal effects of BMI on visits from friends and family or in having someone to confide in. Non-linear Mendelian Randomization analysis showed that low BMI (bottom three deciles, <23.5kg/m2) reduces the odds of cohabiting with a partner or spouse for men, whereas high BMI (top two deciles, >30.7kg/m2) reduces the odds of cohabitation with a partner or spouse for women.ConclusionsBMI affects social and socioeconomic outcomes, with both high and low BMI being detrimental for some measures of SEP. This suggests that in addition to health benefits, maintaining healthy ranges of BMI across the population could have benefits both for individuals and society.
Abstract.
Duckworth A, Gibbons MA, Allen RJ, Almond H, Beaumont RN, Wood AR, Lunnon K, Lindsay MA, Wain LV, Tyrrell J, et al (In Press). Evidence that Telomere Length is Causal for Idiopathic Pulmonary Fibrosis but not Chronic Obstructive Pulmonary Disease: a Mendelian Randomisation Study.
Abstract:
Evidence that Telomere Length is Causal for Idiopathic Pulmonary Fibrosis but not Chronic Obstructive Pulmonary Disease: a Mendelian Randomisation Study
SummaryBackgroundIdiopathic pulmonary fibrosis (IPF) is a fatal lung disease accounting for 1% of UK deaths. In the familial form of pulmonary fibrosis, causal genes have been identified in ∼30% of cases, and a majority relate to telomere maintenance. Prematurely shortened leukocyte telomere length has also been associated with IPF, as well as chronic obstructive pulmonary disease (COPD), a disease with a similar demographic and shared risk factors. Using Mendelian randomisation (MR), our study aimed to determine whether short telomeres cause IPF or COPD.MethodsWe performed an MR study for telomere length causality in IPF and COPD with up to 1,369 IPF cases, 14,103 COPD cases and 435,866 controls of European ancestry in UK Biobank. Initial studies using polygenic risk scores followed by two-sample MR analyses were carried out using seven genetic variants previously associated with telomere length, with replication analysis in an IPF cohort of 2,668 IPF cases and 8,591 controls and a COPD cohort of 15,256 cases and 47,936 controls.FindingsMeta-analysis of the two-sample MR results provided evidence that shorter telomeres cause IPF, with a genetically instrumented one standard deviation shorter telomere length associated with 5.81 higher odds of IPF ([95% CI: 3.56-9.50], P=2.19×10−12. Despite being an age-related lung disease with overlapping risk, there was no evidence that telomere length caused COPD (OR 1.07, [95% CI 0.90-1.27], P = 0.46).InterpretationCellular senescence is hypothesised as a major driving force in both IPF and COPD; telomere shortening may be a contributory factor in IPF, suggesting divergent mechanisms in COPD. This enables greater focus in telomere-related diagnostics, treatments and the search for a cure in IPF. Therapies manifesting improvements in telomere length, including safe telomere activation therapy, may warrant investigation.
Abstract.
Dashti HS, Daghlas I, Lane JM, Huang Y, Udler MS, Wang H, Ollila HM, Jones SE, Kim J, Wood AR, et al (In Press). Genetic determinants of daytime napping and effects on cardiometabolic health.
Abstract:
Genetic determinants of daytime napping and effects on cardiometabolic health
AbstractDaytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remains unclear. Here, we performed a genome-wide association study of self-reported daytime napping in the UK Biobank (n=452,633) and identified 123 loci of which 60 replicated in 23andMe research participants (n=541,333). Findings included missense variants in established drug targets (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Signals were concordant with accelerometer-measured daytime inactivity duration and 33 signals colocalized with signals for other sleep phenotypes. Cluster analysis identified 3 clusters suggesting distinct nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization showed potential causal links between more frequent daytime napping and higher systolic blood pressure, diastolic blood pressure, and waist circumference.
Abstract.
Jones SE, van Hees VT, Mazzotti DR, Marques-Vidal P, Sabia S, van der Spek A, Dashti HS, Engmann J, Kocevska D, Tyrrell J, et al (In Press). Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour.
Nature CommunicationsAbstract:
Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour
Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P
Abstract.
Wright C, Tuke M, Frayling T, Weedon M, Murray A, Tyrrell J, Ruth K, Beaumont R, Wood A (In Press). Large copy number variants in UK Biobank caused by clonal haematopoiesis may confound penetrance estimates. American Journal of Human Genetics
Graham SE, Clarke SL, Wu K-HH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al (2023). Author Correction: the power of genetic diversity in genome-wide association studies of lipids.
Nature,
618(7965), E19-E20.
Author URL.
Hawkes G, Yengo L, Vedantam S, Marouli E, Beaumont RN, GIANT Consortium, Tyrrell J, Weedon MN, Hirschhorn J, Frayling TM, et al (2023). Identification and analysis of individuals who deviate from their genetically-predicted phenotype.
PLoS Genet,
19(9).
Abstract:
Identification and analysis of individuals who deviate from their genetically-predicted phenotype.
Findings from genome-wide association studies have facilitated the generation of genetic predictors for many common human phenotypes. Stratifying individuals misaligned to a genetic predictor based on common variants may be important for follow-up studies that aim to identify alternative causal factors. Using genome-wide imputed genetic data, we aimed to classify 158,951 unrelated individuals from the UK Biobank as either concordant or deviating from two well-measured phenotypes. We first applied our methods to standing height: our primary analysis classified 244 individuals (0.15%) as misaligned to their genetically predicted height. We show that these individuals are enriched for self-reporting being shorter or taller than average at age 10, diagnosed congenital malformations, and rare loss-of-function variants in genes previously catalogued as causal for growth disorders. Secondly, we apply our methods to LDL cholesterol. We classified 156 (0.12%) individuals as misaligned to their genetically predicted LDL cholesterol and show that these individuals were enriched for both clinically actionable cardiovascular risk factors and rare genetic variants in genes previously shown to be involved in metabolic processes. Individuals whose LDL-C was higher than expected based on the genetic predictor were also at higher risk of developing coronary artery disease and type-two diabetes, even after adjustment for measured LDL-C, BMI and age, suggesting upward deviation from genetically predicted LDL-C is indicative of generally poor health. Our results remained broadly consistent when performing sensitivity analysis based on a variety of parametric and non-parametric methods to define individuals deviating from polygenic expectation. Our analyses demonstrate the potential importance of quantitatively identifying individuals for further follow-up based on deviation from genetic predictions.
Abstract.
Author URL.
Shekari S, Stankovic S, Gardner EJ, Hawkes G, Kentistou KA, Beaumont RN, Mörseburg A, Wood AR, Prague JK, Mishra GD, et al (2023). Penetrance of pathogenic genetic variants associated with premature ovarian insufficiency.
Nat Med,
29(7), 1692-1699.
Abstract:
Penetrance of pathogenic genetic variants associated with premature ovarian insufficiency.
Premature ovarian insufficiency (POI) affects 1% of women and is a leading cause of infertility. It is often considered to be a monogenic disorder, with pathogenic variants in ~100 genes described in the literature. We sought to systematically evaluate the penetrance of variants in these genes using exome sequence data in 104,733 women from the UK Biobank, 2,231 (1.14%) of whom reported at natural menopause under the age of 40 years. We found limited evidence to support any previously reported autosomal dominant effect. For nearly all heterozygous effects on previously reported POI genes, we ruled out even modest penetrance, with 99.9% (13,699 out of 13,708) of all protein-truncating variants found in reproductively healthy women. We found evidence of haploinsufficiency effects in several genes, including TWNK (1.54 years earlier menopause, P = 1.59 × 10-6) and SOHLH2 (3.48 years earlier menopause, P = 1.03 × 10-4). Collectively, our results suggest that, for the vast majority of women, POI is not caused by autosomal dominant variants either in genes previously reported or currently evaluated in clinical diagnostic panels. Our findings, plus previous studies, suggest that most POI cases are likely oligogenic or polygenic in nature, which has important implications for future clinical genetic studies, and genetic counseling for families affected by POI.
Abstract.
Author URL.
Yengo L, Vedantam S, Marouli E, Sidorenko J, Bartell E, Sakaue S, Graff M, Eliasen AU, Jiang Y, Raghavan S, et al (2022). A saturated map of common genetic variants associated with human height.
Nature,
610(7933), 704-712.
Abstract:
A saturated map of common genetic variants associated with human height.
Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.
Abstract.
Author URL.
Liu J, Richmond RC, Bowden J, Barry C, Dashti HS, Daghlas I, Lane JM, Jones SE, Wood AR, Frayling TM, et al (2022). Assessing the Causal Role of Sleep Traits on Glycated Hemoglobin: a Mendelian Randomization Study.
Diabetes Care,
45(4), 772-781.
Abstract:
Assessing the Causal Role of Sleep Traits on Glycated Hemoglobin: a Mendelian Randomization Study.
OBJECTIVE: to examine the effects of sleep traits on glycated hemoglobin (HbA1c). RESEARCH DESIGN AND METHODS: This study triangulated evidence across multivariable regression (MVR) and one- (1SMR) and two-sample Mendelian randomization (2SMR) including sensitivity analyses on the effects of five self-reported sleep traits (i.e. insomnia symptoms [difficulty initiating or maintaining sleep], sleep duration, daytime sleepiness, napping, and chronotype) on HbA1c (in SD units) in adults of European ancestry from the UK Biobank (for MVR and 1SMR analyses) (n = 336,999; mean [SD] age 57 [8] years; 54% female) and in the genome-wide association studies from the Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC) (for 2SMR analysis) (n = 46,368; 53 [11] years; 52% female). RESULTS: Across MVR, 1SMR, 2SMR, and their sensitivity analyses, we found a higher frequency of insomnia symptoms (usually vs. sometimes or rarely/never) was associated with higher HbA1c (MVR 0.05 SD units [95% CI 0.04-0.06]; 1SMR 0.52 [0.42-0.63]; 2SMR 0.24 [0.11-0.36]). Associations remained, but point estimates were somewhat attenuated after excluding participants with diabetes. For other sleep traits, there was less consistency across methods, with some but not all providing evidence of an effect. CONCLUSIONS: Our results suggest that frequent insomnia symptoms cause higher HbA1c levels and, by implication, that insomnia has a causal role in type 2 diabetes. These findings could have important implications for developing and evaluating strategies that improve sleep habits to reduce hyperglycemia and prevent diabetes.
Abstract.
Author URL.
Mirshahi UL, Colclough K, Wright CF, Wood AR, Beaumont RN, Tyrrell J, Laver TW, Stahl R, Golden A, Goehringer JM, et al (2022). Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts.
Am J Hum Genet,
109(11), 2018-2028.
Abstract:
Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts.
The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for >80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.
Abstract.
Author URL.
Weedon MN, Jones SE, Lane JM, Lee J, Ollila HM, Dawes A, Tyrrell J, Beaumont RN, Partonen T, Merikanto I, et al (2022). The impact of Mendelian sleep and circadian genetic variants in a population setting.
PLoS Genet,
18(9).
Abstract:
The impact of Mendelian sleep and circadian genetic variants in a population setting.
Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants in these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. No carriers for variants reported in NPSR1 or PER2 were identified. We found no association between variants analyzed and extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being "definitely a morning person", P = 4x10-8; and had a 57-minute earlier midpoint sleep, P = 5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population.
Abstract.
Author URL.
Cresswell M, Casanova F, Beaumont RN, Wood AR, Ronan N, Hilton MP, Tyrrell J (2022). Understanding Factors That Cause Tinnitus: a Mendelian Randomization Study in the UK Biobank.
Ear Hear,
43(1), 70-80.
Abstract:
Understanding Factors That Cause Tinnitus: a Mendelian Randomization Study in the UK Biobank.
OBJECTIVES: to investigate the causal role of established risk factors and associated conditions to tinnitus and tinnitus severity in the UK Biobank. DESIGN: the prospective cohort study with large dataset of >500,000 individuals. The analytical sample of 129,731 individuals in the UK Biobank of European descent. Participants were recruited from National Health Service registries, baseline age range between 37 and 73 years, response rate to baseline survey 6%. Participants were asked subjective questions about tinnitus and its severity. Previously observed associations (n = 23) were confirmed in the UK Biobank using logistic and ordinal regression models. Two-sample Mendelian randomization approaches were then used to test causal relationships between the 23 predictors and tinnitus and tinnitus severity. The main outcome measures were observational and genetic association between key demographics and determinants and two tinnitus outcomes (current tinnitus and tinnitus severity). RESULTS: Prevalence of tinnitus was 20% and severe tinnitus 3.8%. The observational results are consistent with the previous literature, with hearing loss, older age, male gender, high BMI, higher deprivation, higher blood pressure, smoking history, as well as numerous comorbidities being associated with higher odds of current tinnitus. Mendelian randomization results showed causal correlations with tinnitus. Current tinnitus was predicted by genetically instrumented hearing loss (odds ratio [OR]: 8.65 [95% confidence interval (CI): 6.12 to 12.23]), major depression (OR: 1.26 [95% CI: 1.06 to 1.50]), neuroticism (OR: 1.48 [95% CI: 1.28 to 1.71]), and higher systolic blood pressure (OR: 1.01 [95% CI:1.00 to 1.02]). Lower odds of tinnitus were associated with longer duration in education (OR: 0.74 [95% CI: 0.63 to 0.88]), higher caffeine intake (OR: 0.89 [95% CI: 0.83 to 0.95]) and being a morning person (OR: 0.94 [95% CI: 0.90 to 0.98]). Tinnitus severity was predicted by a higher genetic liability to neuroticism (OR: 1.15 [95% CI: 1.06 to 1.26]) and schizophrenia (OR: 1.02 [95% CI: 1.00 to 1.04]). CONCLUSIONS: Tinnitus data from the UK Biobank confirm established associated factors in the literature. Genetic analysis determined causal relationships with several factors that expand the understanding of the etiology of tinnitus and can direct future pathways of clinical care and research.
Abstract.
Author URL.
Porcu E, Sadler MC, Lepik K, Auwerx C, Wood AR, Weihs A, Sleiman MSB, Ribeiro DM, Bandinelli S, Tanaka T, et al (2021). Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome.
Nat Commun,
12(1).
Abstract:
Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome.
Comparing transcript levels between healthy and diseased individuals allows the identification of differentially expressed genes, which may be causes, consequences or mere correlates of the disease under scrutiny. We propose a method to decompose the observational correlation between gene expression and phenotypes driven by confounders, forward- and reverse causal effects. The bi-directional causal effects between gene expression and complex traits are obtained by Mendelian Randomization integrating summary-level data from GWAS and whole-blood eQTLs. Applying this approach to complex traits reveals that forward effects have negligible contribution. For example, BMI- and triglycerides-gene expression correlation coefficients robustly correlate with trait-to-expression causal effects (rBMI = 0.11, PBMI = 2.0 × 10-51 and rTG = 0.13, PTG = 1.1 × 10-68), but not detectably with expression-to-trait effects. Our results demonstrate that studies comparing the transcriptome of diseased and healthy subjects are more prone to reveal disease-induced gene expression changes rather than disease causing ones.
Abstract.
Author URL.
Martin S, Cule M, Basty N, Tyrrell J, Beaumont RN, Wood AR, Frayling TM, Sorokin E, Whitcher B, Liu Y, et al (2021). Genetic Evidence for Different Adiposity Phenotypes and Their Opposing Influences on Ectopic Fat and Risk of Cardiometabolic Disease.
Diabetes,
70(8), 1843-1856.
Abstract:
Genetic Evidence for Different Adiposity Phenotypes and Their Opposing Influences on Ectopic Fat and Risk of Cardiometabolic Disease.
To understand the causal role of adiposity and ectopic fat in type 2 diabetes and cardiometabolic diseases, we aimed to identify two clusters of adiposity genetic variants: one with "adverse" metabolic effects (UFA) and the other with, paradoxically, "favorable" metabolic effects (FA). We performed a multivariate genome-wide association study using body fat percentage and metabolic biomarkers from UK Biobank and identified 38 UFA and 36 FA variants. Adiposity-increasing alleles were associated with an adverse metabolic profile, higher risk of disease, higher CRP, and higher fat in subcutaneous and visceral adipose tissue, liver, and pancreas for UFA and a favorable metabolic profile, lower risk of disease, higher CRP and higher subcutaneous adipose tissue but lower liver fat for FA. We detected no sexual dimorphism. The Mendelian randomization studies provided evidence for a risk-increasing effect of UFA and protective effect of FA for type 2 diabetes, heart disease, hypertension, stroke, nonalcoholic fatty liver disease, and polycystic ovary syndrome. FA is distinct from UFA by its association with lower liver fat and protection from cardiometabolic diseases; it was not associated with visceral or pancreatic fat. Understanding the difference in FA and UFA may lead to new insights in preventing, predicting, and treating cardiometabolic diseases.
Abstract.
Author URL.
Dashti HS, Daghlas I, Lane JM, Huang Y, Udler MS, Wang H, Ollila HM, Jones SE, Kim J, Wood AR, et al (2021). Genetic determinants of daytime napping and effects on cardiometabolic health.
Nat Commun,
12(1).
Abstract:
Genetic determinants of daytime napping and effects on cardiometabolic health.
Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference.
Abstract.
Author URL.
Tyrrell J, Zheng J, Beaumont R, Hinton K, Richardson TG, Wood AR, Davey Smith G, Frayling TM, Tilling K (2021). Genetic predictors of participation in optional components of UK Biobank.
Nat Commun,
12(1).
Abstract:
Genetic predictors of participation in optional components of UK Biobank.
Large studies such as UK Biobank are increasingly used for GWAS and Mendelian randomization (MR) studies. However, selection into and dropout from studies may bias genetic and phenotypic associations. We examine genetic factors affecting participation in four optional components in up to 451,306 UK Biobank participants. We used GWAS to identify genetic variants associated with participation, MR to estimate effects of phenotypes on participation, and genetic correlations to compare participation bias across different studies. 32 variants were associated with participation in one of the optional components (P
Abstract.
Author URL.
Heald AH, Martin S, Fachim H, Green HD, Young KG, Malipatil N, Siddals K, Cortes G, Tyrrell J, Wood AR, et al (2021). Genetically defined favourable adiposity is not associated with a clinically meaningful difference in clinical course in people with type 2 diabetes but does associate with a favourable metabolic profile.
Diabetic Medicine,
38(9).
Abstract:
Genetically defined favourable adiposity is not associated with a clinically meaningful difference in clinical course in people with type 2 diabetes but does associate with a favourable metabolic profile
AbstractAimsChange in weight, HbA1c, lipids, blood pressure and cardiometabolic events over time is variable in individuals with type 2 diabetes. We hypothesised that people with a genetic predisposition to a more favourable adiposity distribution could have a less severe clinical course/progression.MethodsWe involved people with type 2 diabetes from two UK‐based cohorts: 11,914 individuals with GP follow‐up data from the UK Biobank and 723 from Salford. We generated a ‘favourable adiposity’ genetic score and conducted cross‐sectional and longitudinal studies to test its association with weight, BMI, lipids, blood pressure, medication use and risk of myocardial infarction and stroke using 15 follow‐up time points with 1‐year intervals.ResultsThe ‘favourable adiposity’ genetic score was cross‐sectionally associated with higher weight (effect size per 1 standard deviation higher genetic score: 0.91 kg [0.59,1.23]) and BMI (0.30 kg/m2 [0.19,0.40]), but higher high‐density lipoprotein (0.02 mmol/L [0.01,0.02]) and lower triglycerides (−0.04 mmol/L [−0.07, −0.02]) in the UK Biobank at baseline, and this pattern of association was consistent across follow‐up.There was a trend for participants with higher ‘favourable adiposity’ genetic score to have lower risk of myocardial infarction and/or stroke (odds ratio 0.79 [0.62, 1.00]) compared to those with lower score. A one standard deviation higher score was associated with lower odds of using lipid‐lowering (0.91 [0.86, 0.97]) and anti‐hypertensive medication (0.95 [0.91, 0.99]).ConclusionsIn individuals with type 2 diabetes, having more ‘favourable adiposity’ alleles is associated with a marginally better lipid profile long‐term and having lower odds of requiring lipid‐lowering or anti‐hypertensive medication in spite of relatively higher adiposity.
Abstract.
Anderson EL, Richmond RC, Jones SE, Hemani G, Wade KH, Dashti HS, Lane JM, Wang H, Saxena R, Brumpton B, et al (2021). Is disrupted sleep a risk factor for Alzheimer's disease? Evidence from a two-sample Mendelian randomization analysis.
Int J Epidemiol,
50(3), 817-828.
Abstract:
Is disrupted sleep a risk factor for Alzheimer's disease? Evidence from a two-sample Mendelian randomization analysis.
BACKGROUND: it is established that Alzheimer's disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD. METHODS: We used the largest published genome-wide association studies of self-reported and accelerometer-measured sleep traits (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness), and AD. Mendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters on AD risk. RESULTS: Overall, there was little evidence to support a causal effect of sleep traits on AD risk. There was some suggestive evidence that self-reported daytime napping was associated with lower AD risk [odds ratio (OR): 0.70, 95% confidence interval (CI): 0.50-0.99). Some other sleep traits (accelerometer-measured 'eveningness' and sleep duration, and self-reported daytime sleepiness) had ORs of a similar magnitude to daytime napping, but were less precisely estimated. CONCLUSIONS: Overall, we found very limited evidence to support a causal effect of sleep traits on AD risk. Our findings provide tentative evidence that daytime napping may reduce AD risk. Given that this is the first MR study of multiple self-report and objective sleep traits on AD risk, findings should be replicated using independent samples when such data become available.
Abstract.
Author URL.
Kocevska D, Lysen TS, Dotinga A, Koopman-Verhoeff ME, Luijk MPCM, Antypa N, Biermasz NR, Blokstra A, Brug J, Burk WJ, et al (2021). Sleep characteristics across the lifespan in 1.1 million people from the Netherlands, United Kingdom and United States: a systematic review and meta-analysis.
Nat Hum Behav,
5(1), 113-122.
Abstract:
Sleep characteristics across the lifespan in 1.1 million people from the Netherlands, United Kingdom and United States: a systematic review and meta-analysis.
We aimed to obtain reliable reference charts for sleep duration, estimate the prevalence of sleep complaints across the lifespan and identify risk indicators of poor sleep. Studies were identified through systematic literature search in Embase, Medline and Web of Science (9 August 2019) and through personal contacts. Eligible studies had to be published between 2000 and 2017 with data on sleep assessed with questionnaires including ≥100 participants from the general population. We assembled individual participant data from 200,358 people (aged 1-100 years, 55% female) from 36 studies from the Netherlands, 471,759 people (40-69 years, 55.5% female) from the United Kingdom and 409,617 people (≥18 years, 55.8% female) from the United States. One in four people slept less than age-specific recommendations, but only 5.8% slept outside of the 'acceptable' sleep duration. Among teenagers, 51.5% reported total sleep times (TST) of less than the recommended 8-10 h and 18% report daytime sleepiness. In adults (≥18 years), poor sleep quality (13.3%) and insomnia symptoms (9.6-19.4%) were more prevalent than short sleep duration (6.5% with TST
Abstract.
Author URL.
Graham SE, Clarke SL, Wu K-HH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al (2021). The power of genetic diversity in genome-wide association studies of lipids.
Nature,
600(7890), 675-679.
Abstract:
The power of genetic diversity in genome-wide association studies of lipids.
Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.
Abstract.
Author URL.
Chen J, Spracklen CN, Marenne G, Varshney A, Corbin LJ, Luan J, Willems SM, Wu Y, Zhang X, Horikoshi M, et al (2021). The trans-ancestral genomic architecture of glycemic traits.
Nat Genet,
53(6), 840-860.
Abstract:
The trans-ancestral genomic architecture of glycemic traits.
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P
Abstract.
Author URL.
O'Loughlin J, Casanova F, Jones SE, Hagenaars SP, Beaumont RN, Freathy RM, Watkins ER, Vetter C, Rutter MK, Cain SW, et al (2021). Using Mendelian Randomisation methods to understand whether diurnal preference is causally related to mental health.
Mol Psychiatry,
26(11), 6305-6316.
Abstract:
Using Mendelian Randomisation methods to understand whether diurnal preference is causally related to mental health.
Late diurnal preference has been linked to poorer mental health outcomes, but the understanding of the causal role of diurnal preference on mental health and wellbeing is currently limited. Late diurnal preference is often associated with circadian misalignment (a mismatch between the timing of the endogenous circadian system and behavioural rhythms), so that evening people live more frequently against their internal clock. This study aims to quantify the causal contribution of diurnal preference on mental health outcomes, including anxiety, depression and general wellbeing and test the hypothesis that more misaligned individuals have poorer mental health and wellbeing using an actigraphy-based measure of circadian misalignment. Multiple Mendelian Randomisation (MR) approaches were used to test causal pathways between diurnal preference and seven well-validated mental health and wellbeing outcomes in up to 451,025 individuals. In addition, observational analyses tested the association between a novel, objective measure of behavioural misalignment (Composite Phase Deviation, CPD) and seven mental health and wellbeing outcomes. Using genetic instruments identified in the largest GWAS for diurnal preference, we provide robust evidence that early diurnal preference is protective for depression and improves wellbeing. For example, using one-sample MR, a twofold higher genetic liability of morningness was associated with lower odds of depressive symptoms (OR: 0.92, 95% CI: 0.88, 0.97). It is possible that behavioural factors including circadian misalignment may contribute in the chronotype depression relationship, but further work is needed to confirm these findings.
Abstract.
Author URL.
Casanova F, Wood AR, Yaghootkar H, Beaumont RN, Jones SE, Gooding KM, Aizawa K, Strain WD, Hattersley AT, Khan F, et al (2020). A Mendelian Randomization Study Provides Evidence That Adiposity and Dyslipidemia Lead to Lower Urinary Albumin-to-Creatinine Ratio, a Marker of Microvascular Function.
Diabetes,
69(5), 1072-1082.
Abstract:
A Mendelian Randomization Study Provides Evidence That Adiposity and Dyslipidemia Lead to Lower Urinary Albumin-to-Creatinine Ratio, a Marker of Microvascular Function.
Urinary albumin-to-creatinine ratio (ACR) is a marker of diabetic nephropathy and microvascular damage. Metabolic-related traits are observationally associated with ACR, but their causal role is uncertain. Here, we confirmed ACR as a marker of microvascular damage and tested whether metabolic-related traits have causal relationships with ACR. The association between ACR and microvascular function (responses to acetylcholine [ACH] and sodium nitroprusside) was tested in the SUMMIT study. Two-sample Mendelian randomization (MR) was used to infer the causal effects of 11 metabolic risk factors, including glycemic, lipid, and adiposity traits, on ACR. MR was performed in up to 440,000 UK Biobank and 54,451 CKDGen participants. ACR was robustly associated with microvascular function measures in SUMMIT. Using MR, we inferred that higher triglyceride (TG) and LDL cholesterol (LDL-C) levels caused elevated ACR. A 1 SD higher TG and LDL-C level caused a 0.062 (95% CI 0.040, 0.083) and a 0.026 (95% CI 0.008, 0.044) SD higher ACR, respectively. There was evidence that higher body fat and visceral body fat distribution caused elevated ACR, while a metabolically "favorable adiposity" phenotype lowered ACR. ACR is a valid marker for microvascular function. MR suggested that seven traits have causal effects on ACR, highlighting the role of adiposity-related traits in causing lower microvascular function.
Abstract.
Author URL.
Sharp SA, Jones SE, Kimmitt RA, Weedon MN, Halpin AM, Wood AR, Beaumont RN, King S, van Heel DA, Campbell PM, et al (2020). A single nucleotide polymorphism genetic risk score to aid diagnosis of coeliac disease: a pilot study in clinical care.
Alimentary Pharmacology & Therapeutics,
52(7), 1165-1173.
Abstract:
A single nucleotide polymorphism genetic risk score to aid diagnosis of coeliac disease: a pilot study in clinical care
SummaryBackgroundSingle nucleotide polymorphism–based genetic risk scores (GRS) model genetic risk as a continuum and can discriminate coeliac disease but have not been validated in clinic. Human leukocyte antigen (HLA) DQ gene testing is available in clinic but does not include non‐HLA attributed risk and is limited by discrete risk stratification.AimsTo accurately characterise both HLA and non‐HLA coeliac disease genetic risk as a single nucleotide polymorphism–based GRS and evaluate diagnostic utility.MethodsWe developed a 42 single nucleotide polymorphism coeliac disease GRS from a European case‐control study (12 041 cases vs 12 228 controls) using HLA‐DQ imputation and published genome‐wide association studies. We validated the GRS in UK Biobank (1237 cases) and developed direct genotyping assays. We tested the coeliac disease GRS in a pilot clinical cohort of 128 children presenting with suspected coeliac disease.ResultsThe GRS was more discriminative of coeliac disease than HLA‐DQ stratification in UK Biobank (receiver operating characteristic area under the curve [ROC‐AUC] = 0.88 [95% CIs: 0.87‐0.89] vs 0.82 [95% CIs: 0.80‐0.83]). We demonstrated similar discrimination in the pilot clinical cohort (114 cases vs 40 controls, ROC‐AUC = 0.84 [95% CIs: 0.76‐0.91]). As a rule‐out test, no children with coeliac disease in the clinical cohort had a GRS below 38th population centile.ConclusionsA single nucleotide polymorphism–based GRS may offer more effective and cost‐efficient testing of coeliac disease genetic risk in comparison to HLA‐DQ stratification. As a comparatively inexpensive test it could facilitate non‐invasive coeliac disease diagnosis but needs detailed assessment in the context of other diagnostic tests and against current diagnostic algorithms.
Abstract.
Dashti HS, Vetter C, Lane JM, Smith MC, Wood AR, Weedon MN, Rutter MK, Garaulet M, Scheer FAJL, Saxena R, et al (2020). Assessment of MTNR1B Type 2 Diabetes Genetic Risk Modification by Shift Work and Morningness-Eveningness Preference in the UK Biobank.
Diabetes,
69(2), 259-266.
Abstract:
Assessment of MTNR1B Type 2 Diabetes Genetic Risk Modification by Shift Work and Morningness-Eveningness Preference in the UK Biobank.
Night shift work, behavioral rhythms, and the common MTNR1B risk single nucleotide polymorphism (SNP), rs10830963, associate with type 2 diabetes; however, whether they exert joint effects to exacerbate type 2 diabetes risk is unknown. Among employed participants of European ancestry in the UK Biobank (N = 189,488), we aimed to test the cross-sectional independent associations and joint interaction effects of these risk factors on odds of type 2 diabetes (n = 5,042 cases) and HbA1c levels (n = 175,156). Current shift work, definite morning or evening preference, and MTNR1B rs10830963 risk allele associated with type 2 diabetes and HbA1c levels. The effect of rs10830963 was not modified by shift work schedules. While marginal evidence of interaction between self-reported morningness-eveningness preference and rs10830963 on risk of type 2 diabetes was seen, this interaction did not persist when analysis was expanded to include all participants regardless of employment status and when accelerometer-derived sleep midpoint was used as an objective measure of morningness-eveningness preference. Our findings suggest that MTNR1B risk allele carriers who carry out shift work or have more extreme morningness-eveningness preference may not have enhanced risk of type 2 diabetes.
Abstract.
Author URL.
Lin S, Green HD, Hendy P, Heerasing NM, Chanchlani N, Hamilton B, Walker GJ, Heap GA, Hobart J, Martin RJ, et al (2020). Clinical Features and Genetic Risk of Demyelination Following Anti-TNF Treatment.
J Crohns Colitis,
14(12), 1653-1661.
Abstract:
Clinical Features and Genetic Risk of Demyelination Following Anti-TNF Treatment.
BACKGROUND: Anti-TNF exposure has been linked to demyelination events. We sought to describe the clinical features of demyelination events following anti-TNF treatment and to test whether affected patients were genetically predisposed to multiple sclerosis [MS]. METHODS: We conducted a case-control study to describe the clinical features of demyelination events following anti-TNF exposure. We compared genetic risk scores [GRS], calculated using carriage of 43 susceptibility loci for MS, in 48 cases with 1219 patients exposed to anti-TNF who did not develop demyelination. RESULTS: Overall, 39 [74%] cases were female. The median age [range] of patients at time of demyelination was 41.5 years [20.7-63.2]. The median duration of anti-TNF treatment was 21.3 months [0.5-99.4] and 19 [36%] patients were receiving concomitant immunomodulators. Most patients had central demyelination affecting the brain, spinal cord, or both. Complete recovery was reported in 12 [23%] patients after a median time of 6.8 months [0.1-28.7]. After 33.0 months of follow-up, partial recovery was observed in 29 [55%] patients, relapsing and remitting episodes in nine [17%], progressive symptoms in three [6%]: two [4%] patients were diagnosed with MS. There was no significant difference between MS GRS scores in cases (mean -3.5 × 10-4, standard deviation [SD] 0.0039) and controls [mean -1.1 × 10-3, SD 0.0042] [p = 0.23]. CONCLUSIONS: Patients who experienced demyelination events following anti-TNF exposure were more likely female, less frequently treated with an immunomodulator, and had a similar genetic risk to anti-TNF exposed controls who did not experience demyelination events. Large prospective studies with pre-treatment neuroimaging are required to identify genetic susceptibility loci.
Abstract.
Author URL.
Fussey JM, Beaumont RN, Wood AR, Vaidya B, Smith J, Tyrrell J (2020). Does Obesity Cause Thyroid Cancer? a Mendelian Randomization Study.
J Clin Endocrinol Metab,
105(7), e2398-e2407.
Abstract:
Does Obesity Cause Thyroid Cancer? a Mendelian Randomization Study.
BACKGROUND: the incidence of thyroid cancer is rising, and relatively little is known about modifiable risk factors for the condition. Observational studies have suggested a link between adiposity and thyroid cancer; however, these are subject to confounding and reverse causality. Here, we used data from the UK Biobank and Mendelian randomization approaches to investigate whether adiposity causes benign nodular thyroid disease and differentiated thyroid cancer. METHODS: We analyzed data from 379 708 unrelated participants of European ancestry in the UK Biobank and identified 1812 participants with benign nodular thyroid disease and 425 with differentiated thyroid carcinoma. We tested observational associations with measures of adiposity and type 2 diabetes mellitus. One and 2-sample Mendelian randomization approaches were used to investigate causal relationships. RESULTS: Observationally, there were positive associations between higher body mass index (odds ratio [OR], 1.15; 95% confidence interval [CI], 1.08-1.22), higher waist-hip ratio (OR, 1.16; 95% CI, 1.09-1.23), and benign nodular thyroid disease, but not thyroid cancer. Mendelian randomization did not support a causal link for obesity with benign nodular thyroid disease or thyroid cancer, although it did provide some evidence that individuals in the highest quartile for genetic liability of type 2 diabetes had higher odds of thyroid cancer than those in the lowest quartile (OR, 1.45; CI, 1.11-1.90). CONCLUSIONS: Contrary to the findings of observational studies, our results do not confirm a causal role for obesity in benign nodular thyroid disease or thyroid cancer. They do, however, suggest a link between type 2 diabetes and thyroid cancer.
Abstract.
Author URL.
Green HD, Beaumont RN, Wood AR, Hamilton B, Jones SE, Goodhand JR, Kennedy NA, Ahmad T, Yaghootkar H, Weedon MN, et al (2020). Genetic evidence that higher central adiposity causes gastro-oesophageal reflux disease: a Mendelian randomization study.
International Journal of Epidemiology,
49(4), 1270-1281.
Abstract:
Genetic evidence that higher central adiposity causes gastro-oesophageal reflux disease: a Mendelian randomization study
Abstract
.
. Background
. Gastro-oesophageal reflux disease (GORD) is associated with multiple risk factors but determining causality is difficult. We used a genetic approach [Mendelian randomization (MR)] to identify potential causal modifiable risk factors for GORD.
.
.
. Methods
. We used data from 451 097 European participants in the UK Biobank and defined GORD using hospital-defined ICD10 and OPCS4 codes and self-report data (N = 41 024 GORD cases). We tested observational and MR-based associations between GORD and four adiposity measures [body mass index (BMI), waist–hip ratio (WHR), a metabolically favourable higher body-fat percentage and waist circumference], smoking status, smoking frequency and caffeine consumption.
.
.
. Results
. Observationally, all adiposity measures were associated with higher odds of GORD. Ever and current smoking were associated with higher odds of GORD. Coffee consumption was associated with lower odds of GORD but, among coffee drinkers, more caffeinated-coffee consumption was associated with higher odds of GORD. Using MR, we provide strong evidence that higher WHR and higher WHR adjusted for BMI lead to GORD. There was weak evidence that higher BMI, body-fat percentage, coffee drinking or smoking caused GORD, but only the observational effects for BMI and body-fat percentage could be excluded. This MR estimated effect for WHR equates to a 1.23-fold higher odds of GORD per 5-cm increase in waist circumference.
.
.
. Conclusions
. These results provide strong evidence that a higher waist–hip ratio leads to GORD. Our study suggests that central fat distribution is crucial in causing GORD rather than overall weight.
.
Abstract.
Fussey JM, Beaumont RN, Wood AR, Vaidya B, Smith J, Tyrrell J (2020). Mendelian randomization supports a causative effect of TSH on thyroid carcinoma.
Endocr Relat Cancer,
27(10), 551-559.
Abstract:
Mendelian randomization supports a causative effect of TSH on thyroid carcinoma.
Evidence from observational studies suggest a positive association between serum thyroid-stimulating hormone (TSH) levels and differentiated thyroid carcinoma. However, the cause-effect relationship is poorly understood and these studies are susceptible to bias and confounding. This study aimed to investigate the causal role of TSH in both benign thyroid nodules and thyroid cancer in up to 451,025 UK Biobank participants, using a genetic technique, known as Mendelian randomization (MR). Hospital Episode Statistics and Cancer Registry databases were used to identify 462 patients with differentiated thyroid carcinoma and 2031 patients with benign nodular thyroid disease. MR methods using genetic variants associated with serum TSH were used to test causal relationships between TSH and the two disease outcomes. Mendelian randomization provided evidence of a causal link between TSH and both thyroid cancer and benign nodular thyroid disease. Two-sample MR suggested that a 1 s.d. higher genetically instrumented TSH (approximately 0.8 mIU/L) resulted in 4.96-fold higher odds of benign nodular disease (95% CI 2.46-9.99) and 2.00-fold higher odds of thyroid cancer (95% CI 1.09-3.70). Our results thus support a causal role for TSH in both benign nodular thyroid disease and thyroid cancer.
Abstract.
Author URL.
Locke JM, Latten MJ, Datta RY, Wood AR, Crockard MA, Lamont JV, Weedon MN, Oram RA (2020). Methods for quick, accurate and cost-effective determination of the type 1 diabetes genetic risk score (T1D-GRS).
Clin Chem Lab Med,
58(4), e102-e104.
Author URL.
Butler TJ, Estep KN, Sommers JA, Maul RW, Moore AZ, Bandinelli S, Cucca F, Tuke MA, Wood AR, Bharti SK, et al (2020). Mitochondrial genetic variation is enriched in G-quadruplex regions that stall DNA synthesis in vitro.
Hum Mol Genet,
29(8), 1292-1309.
Abstract:
Mitochondrial genetic variation is enriched in G-quadruplex regions that stall DNA synthesis in vitro.
As the powerhouses of the eukaryotic cell, mitochondria must maintain their genomes which encode proteins essential for energy production. Mitochondria are characterized by guanine-rich DNA sequences that spontaneously form unusual three-dimensional structures known as G-quadruplexes (G4). G4 structures can be problematic for the essential processes of DNA replication and transcription because they deter normal progression of the enzymatic-driven processes. In this study, we addressed the hypothesis that mitochondrial G4 is a source of mutagenesis leading to base-pair substitutions. Our computational analysis of 2757 individual genomes from two Italian population cohorts (SardiNIA and InCHIANTI) revealed a statistically significant enrichment of mitochondrial mutations within sequences corresponding to stable G4 DNA structures. Guided by the computational analysis results, we designed biochemical reconstitution experiments and demonstrated that DNA synthesis by two known mitochondrial DNA polymerases (Pol γ, PrimPol) in vitro was strongly blocked by representative stable G4 mitochondrial DNA structures, which could be overcome in a specific manner by the ATP-dependent G4-resolving helicase Pif1. However, error-prone DNA synthesis by PrimPol using the G4 template sequence persisted even in the presence of Pif1. Altogether, our results suggest that genetic variation is enriched in G-quadruplex regions that impede mitochondrial DNA replication.
Abstract.
Author URL.
Sulc J, Mounier N, Günther F, Winkler T, Wood AR, Frayling TM, Heid IM, Robinson MR, Kutalik Z (2020). Quantification of the overall contribution of gene-environment interaction for obesity-related traits.
Nat Commun,
11(1).
Abstract:
Quantification of the overall contribution of gene-environment interaction for obesity-related traits.
The growing sample size of genome-wide association studies has facilitated the discovery of gene-environment interactions (GxE). Here we propose a maximum likelihood method to estimate the contribution of GxE to continuous traits taking into account all interacting environmental variables, without the need to measure any. Extensive simulations demonstrate that our method provides unbiased interaction estimates and excellent coverage. We also offer strategies to distinguish specific GxE from general scale effects. Applying our method to 32 traits in the UK Biobank reveals that while the genetic risk score (GRS) of 376 variants explains 5.2% of body mass index (BMI) variance, GRSxE explains an additional 1.9%. Nevertheless, this interaction holds for any variable with identical correlation to BMI as the GRS, hence may not be GRS-specific. Still, we observe that the global contribution of specific GRSxE to complex traits is substantial for nine obesity-related measures (including leg impedance and trunk fat-free mass).
Abstract.
Author URL.
Ruth KS, Day FR, Tyrrell J, Thompson DJ, Wood AR, Mahajan A, Beaumont RN, Wittemans L, Martin S, Busch AS, et al (2020). Using human genetics to understand the disease impacts of testosterone in men and women. Nature Medicine, 26(2), 252-258.
Casanova F, Tyrrell J, Beaumont RN, Ji Y, Jones SE, Hattersley AT, Weedon MN, Murray A, Shore AC, Frayling TM, et al (2019). A genome-wide association study implicates multiple mechanisms influencing raised urinary albumin-creatinine ratio.
Hum Mol Genet,
28(24), 4197-4207.
Abstract:
A genome-wide association study implicates multiple mechanisms influencing raised urinary albumin-creatinine ratio.
Raised albumin-creatinine ratio (ACR) is an indicator of microvascular damage and renal disease. We aimed to identify genetic variants associated with raised ACR and study the implications of carrying multiple ACR-raising alleles with metabolic and vascular-related disease. We performed a genome-wide association study of ACR using 437 027 individuals from the UK Biobank in the discovery phase, 54 527 more than previous studies, and followed up our findings in independent studies. We identified 62 independent associations with ACR across 56 loci (P 0.8) coinciding with signals for at least 16 related metabolic and vascular traits, suggested multiple pathways leading to raised ACR levels. After excluding variants at the CUBN locus, known to alter ACR via effects on renal absorption, an ACR genetic risk score was associated with a higher risk of hypertension, and less strongly, type 2 diabetes and stroke. For some rare genotype combinations at the CUBN locus, most individuals had ACR levels above the microalbuminuria clinical threshold. Contrary to our hypothesis, individuals carrying more CUBN ACR-raising alleles, and above the clinical threshold, had a higher frequency of vascular disease. The CUBN allele effects on ACR were twice as strong in people with diabetes-a result robust to an optimization-algorithm approach to simulating interactions, validating previously reported gene-diabetes interactions (P ≤ 4 × 10-5). In conclusion, a variety of genetic mechanisms and traits contribute to variation in ACR.
Abstract.
Author URL.
Wright CF, West B, Tuke M, Jones SE, Patel K, Laver TW, Beaumont RN, Tyrrell J, Wood AR, Frayling TM, et al (2019). Assessing the Pathogenicity, Penetrance, and Expressivity of Putative Disease-Causing Variants in a Population Setting.
American Journal of Human Genetics,
104(2), 275-286.
Abstract:
Assessing the Pathogenicity, Penetrance, and Expressivity of Putative Disease-Causing Variants in a Population Setting
More than 100,000 genetic variants are classified as disease causing in public databases. However, the true penetrance of many of these rare alleles is uncertain and might be over-estimated by clinical ascertainment. Here, we use data from 379,768 UK Biobank (UKB) participants of European ancestry to assess the pathogenicity and penetrance of putatively clinically important rare variants. Although rare variants are harder to genotype accurately than common variants, we were able to classify as high quality 1,244 of 4,585 (27%) putatively clinically relevant rare (MAF < 1%) variants genotyped on the UKB microarray. We defined as “clinically relevant” variants that were classified as either pathogenic or likely pathogenic in ClinVar or are in genes known to cause two specific monogenic diseases: maturity-onset diabetes of the young (MODY) and severe developmental disorders (DDs). We assessed the penetrance and pathogenicity of these high-quality variants by testing their association with 401 clinically relevant traits. 27 of the variants were associated with a UKB trait, and we were able to refine the penetrance estimate for some of the variants. For example, the HNF4A c.340C>T (p.Arg114Trp) (GenBank: NM_175914.4) variant associated with diabetes is T (p.Arg799Trp) variant that causes Xeroderma pigmentosum were more susceptible to sunburn. Finally, we refute the previous disease association of RNF135 in developmental disorders. In conclusion, this study shows that very large population-based studies will help refine our understanding of the pathogenicity of rare genetic variants.
Abstract.
Thompson WD, Tyrrell J, Borges MC, Beaumont RN, Knight BA, Wood AR, Ring SM, Hattersley AT, Freathy RM, Lawlor DA, et al (2019). Association of maternal circulating 25(OH)D and calcium with birth weight: a mendelian randomisation analysis. PLoS Medicine, 16
Lane JM, Jones SE, Dashti HS, Wood AR, Aragam KG, van Hees VT, Strand LB, Winsvold BS, Wang H, Bowden J, et al (2019). Biological and clinical insights from genetics of insomnia symptoms.
Nature GeneticsAbstract:
Biological and clinical insights from genetics of insomnia symptoms
Insomnia is a common disorder linked with adverse long-term medical and psychiatric outcomes. The underlying pathophysiological processes and causal relationships of insomnia with disease are poorly understood. Here we identify 57 loci for self-reported insomnia symptoms in the UK Biobank (n = 453,379) and confirm their impact on self-reported insomnia symptoms in the HUNT study (n = 14,923 cases, 47,610 controls), physician-diagnosed insomnia in Partners Biobank (n = 2,217 cases, 14,240 controls), and accelerometer-derived measures of sleep efficiency and sleep duration in the UK Biobank (n = 83,726). Our results suggest enrichment of genes involved in ubiquitin-mediated proteolysis and of genes expressed in multiple brain regions, skeletal muscle, and adrenal gland. Evidence of shared genetic factors is found between frequent insomnia symptoms and restless legs syndrome, aging, cardio-metabolic, behavioral, psychiatric and reproductive traits. Evidence is found for a possible causal link between insomnia symptoms and coronary artery disease, depressive symptoms and subjective well-being.
Abstract.
Pilling L, Tamosauskaite J, Jones G, Wood A, Jones L, Kuo C-L, Kuchel G, Ferrucci L, Melzer D (2019). Common conditions associated with hereditary haemochromatosis genetic variants: cohort study in UK Biobank. BMJ
Budu-Aggrey A, Brumpton B, Tyrrell J, Watkins S, Modasli E, Celis-Morales C, Ferguson L, Vie G, Palmer T, Fritsche L, et al (2019). Evidence of a causal relationship between body mass index and psoriasis: a mendelian randomization study. PLoS Medicine
Bovijn J, Jackson L, Censin J, Chen CY, Laisk T, Laber S, Ferreira T, Pulit SL, Glastonbury CA, Smoller JW, et al (2019). GWAS Identifies Risk Locus for Erectile Dysfunction and Implicates Hypothalamic Neurobiology and Diabetes in Etiology.
American Journal of Human Genetics,
104(1), 157-163.
Abstract:
GWAS Identifies Risk Locus for Erectile Dysfunction and Implicates Hypothalamic Neurobiology and Diabetes in Etiology
Erectile dysfunction (ED) is a common condition affecting more than 20% of men over 60 years, yet little is known about its genetic architecture. We performed a genome-wide association study of ED in 6,175 case subjects among 223,805 European men and identified one locus at 6q16.3 (lead variant rs57989773, OR 1.20 per C-allele; p = 5.71 × 10−14), located between MCHR2 and SIM1. In silico analysis suggests SIM1 to confer ED risk through hypothalamic dysregulation. Mendelian randomization provides evidence that genetic risk of type 2 diabetes mellitus is a cause of ED (OR 1.11 per 1-log unit higher risk of type 2 diabetes). These findings provide insights into the biological underpinnings and the causes of ED and may help prioritize the development of future therapies for this common disorder.
Abstract.
Green HD, Beaumont RN, Thomas A, Hamilton B, Wood AR, Sharp S, Jones SE, Tyrrell J, Walker G, Goodhand J, et al (2019). Genome-Wide Association Study of Microscopic Colitis in the UK Biobank Confirms Immune-Related Pathogenesis.
J Crohns Colitis,
13(12), 1578-1582.
Abstract:
Genome-Wide Association Study of Microscopic Colitis in the UK Biobank Confirms Immune-Related Pathogenesis.
BACKGROUND AND AIMS: the causes of microscopic colitis are currently poorly understood. Previous reports have found clinical associations with coeliac disease and genetic associations at the human leukocyte antigen [HLA] locus on the ancestral 8.1 haplotype. We investigated pharmacological and genetic factors associated with microscopic colitis in the UK Biobank. METHODS: in total, 483 European UK Biobank participants were identified by ICD10 coding, and a genome-wide association study was performed using BOLT-LMM, with a sensitivity analysis performed excluding potential confounders. The HLA*IMP:02 algorithm was used to estimate allele frequency at 11 classical HLA genes, and downstream analysis was performed using FUMA. Genetic overlap with inflammatory bowel disease [Crohn's disease and ulcerative colitis] was investigated using genetic risk scores. RESULTS: We found significant phenotypic associations with smoking status, coeliac disease and the use of proton-pump inhibitors but not with other commonly reported pharmacological risk factors. Using the largest sample size to date, we confirmed a recently reported association with the MHC Ancestral 8.1 Haplotype. Downstream analysis suggests association with digestive tract morphogenesis. By calculating genetic risk scores, we also report suggestive evidence of shared genetic risk with Crohn's disease, but not with ulcerative colitis. CONCLUSIONS: This report confirms the role of genetic determinants in the HLA in the pathogenesis of microscopic colitis. The genetic overlap with Crohn's disease suggests a common underlying mechanism of disease.
Abstract.
Author URL.
Ji Y, Yiorkas AM, Frau F, Mook-Kanamori D, Staiger H, Thomas EL, Atabaki-Pasdar N, Campbell A, Tyrrell J, Jones SE, et al (2019). Genome-Wide and Abdominal MRI Data Provide Evidence That a Genetically Determined Favorable Adiposity Phenotype is Characterized by Lower Ectopic Liver Fat and Lower Risk of Type 2 Diabetes, Heart Disease, and Hypertension.
Diabetes,
68(1), 207-219.
Abstract:
Genome-Wide and Abdominal MRI Data Provide Evidence That a Genetically Determined Favorable Adiposity Phenotype is Characterized by Lower Ectopic Liver Fat and Lower Risk of Type 2 Diabetes, Heart Disease, and Hypertension.
Recent genetic studies have identified alleles associated with opposite effects on adiposity and risk of type 2 diabetes. We aimed to identify more of these variants and test the hypothesis that such favorable adiposity alleles are associated with higher subcutaneous fat and lower ectopic fat. We combined MRI data with genome-wide association studies of body fat percentage (%) and metabolic traits. We report 14 alleles, including 7 newly characterized alleles, associated with higher adiposity but a favorable metabolic profile. Consistent with previous studies, individuals carrying more favorable adiposity alleles had higher body fat % and higher BMI but lower risk of type 2 diabetes, heart disease, and hypertension. These individuals also had higher subcutaneous fat but lower liver fat and a lower visceral-to-subcutaneous adipose tissue ratio. Individual alleles associated with higher body fat % but lower liver fat and lower risk of type 2 diabetes included those in PPARG, GRB14, and IRS1, whereas the allele in ANKRD55 was paradoxically associated with higher visceral fat but lower risk of type 2 diabetes. Most identified favorable adiposity alleles are associated with higher subcutaneous and lower liver fat, a mechanism consistent with the beneficial effects of storing excess triglycerides in metabolically low-risk depots.
Abstract.
Author URL.
Jones SE, Lane JM, Wood AR, van Hees VT, Tyrrell J, Beaumont RN, Jeffries AR, Dashti HS, Hillsdon M, Ruth KS, et al (2019). Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms.
Nature CommunicationsAbstract:
Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms
Using genome-wide data from 697,828 UK Biobank and 23andMe participants, we increase the number of identified loci associated with being a morning person, a behavioural indicator of a person’s underlying circadian rhythm, from 24 to 351. Using data from 85,760 individuals with activity-monitor derived measures of sleep timing we demonstrate that the chronotype loci influence sleep timing: the mean sleep timing of the 5% of individuals carrying the most morningness alleles is 25 minutes earlier than the 5% carrying the fewest. The loci are enriched for genes involved in circadian regulation, cAMP, glutamate and insulin signalling pathways, and those expressed in the retina, hindbrain, hypothalamus, and pituitary. Using Mendelian Randomisation, we show that being a morning person is causally associated with better mental health but does not affect BMI or risk of Type 2 diabetes. This study offers insights into circadian biology and its links to disease in humans.
Abstract.
Wang H, Lane JM, Jones SE, Dashti HS, Ollila HM, Wood AR, van Hees VT, Brumpton B, Winsvold BS, Kantojärvi K, et al (2019). Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes.
Nature Communications,
10(1).
Abstract:
Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes
Excessive daytime sleepiness (EDS) affects 10–20% of the population and is associated with substantial functional deficits. Here, we identify 42 loci for self-reported daytime sleepiness in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirm the aggregate effect of a genetic risk score of 42 SNPs on daytime sleepiness in independent Scandinavian cohorts and on other sleep disorders (restless legs syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). However, individual daytime sleepiness signals vary in their associations with objective short vs long sleep, and with markers of sleep continuity. The 42 sleepiness variants primarily cluster into two predominant composite biological subtypes - sleep propensity and sleep fragmentation. Shared genetic links are also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing.
Abstract.
Dashti HS, Jones SE, Wood AR, Lane JM, van Hees VT, Wang H, Rhodes JA, Song Y, Patel K, Anderson SG, et al (2019). Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates.
Nat Commun,
10(1).
Abstract:
Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates.
Sleep is an essential state of decreased activity and alertness but molecular factors regulating sleep duration remain unknown. Through genome-wide association analysis in 446,118 adults of European ancestry from the UK Biobank, we identify 78 loci for self-reported habitual sleep duration (p
Abstract.
Author URL.
Richmond RC, Anderson EL, Dashti HS, Jones SE, Lane JM, Strand LB, Brumpton B, Rutter MK, Wood AR, Straif K, et al (2019). Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study.
BMJ,
365Abstract:
Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study.
OBJECTIVE: to examine whether sleep traits have a causal effect on risk of breast cancer. DESIGN: Mendelian randomisation study. SETTING: UK Biobank prospective cohort study and Breast Cancer Association Consortium (BCAC) case-control genome-wide association study. PARTICIPANTS: 156 848 women in the multivariable regression and one sample mendelian randomisation (MR) analysis in UK Biobank (7784 with a breast cancer diagnosis) and 122 977 breast cancer cases and 105 974 controls from BCAC in the two sample MR analysis. EXPOSURES: Self reported chronotype (morning or evening preference), insomnia symptoms, and sleep duration in multivariable regression, and genetic variants robustly associated with these sleep traits. MAIN OUTCOME MEASURE: Breast cancer diagnosis. RESULTS: in multivariable regression analysis using UK Biobank data on breast cancer incidence, morning preference was inversely associated with breast cancer (hazard ratio 0.95, 95% confidence interval 0.93 to 0.98 per category increase), whereas there was little evidence for an association between sleep duration and insomnia symptoms. Using 341 single nucleotide polymorphisms (SNPs) associated with chronotype, 91 SNPs associated with sleep duration, and 57 SNPs associated with insomnia symptoms, one sample MR analysis in UK Biobank provided some supportive evidence for a protective effect of morning preference on breast cancer risk (0.85, 0.70, 1.03 per category increase) but imprecise estimates for sleep duration and insomnia symptoms. Two sample MR using data from BCAC supported findings for a protective effect of morning preference (inverse variance weighted odds ratio 0.88, 95% confidence interval 0.82 to 0.93 per category increase) and adverse effect of increased sleep duration (1.19, 1.02 to 1.39 per hour increase) on breast cancer risk (both oestrogen receptor positive and oestrogen receptor negative), whereas evidence for insomnia symptoms was inconsistent. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy. CONCLUSIONS: Findings showed consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of increased sleep duration on breast cancer risk.
Abstract.
Author URL.
Warrington NM, Beaumont RN, Horikoshi M, Day FR, Helgeland Ø, Laurin C, Bacelis J, Peng S, Hao K, Feenstra B, et al (2019). Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.
Nat Genet,
51(5), 804-814.
Abstract:
Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.
Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
Abstract.
Author URL.
Pulit SL, Stoneman C, Morris AP, Wood AR, Glastonbury CA, Tyrrell J, Yengo L, Ferreira T, Marouli E, Ji Y, et al (2019). Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry.
Hum Mol Genet,
28(1), 166-174.
Abstract:
Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry.
More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.
Abstract.
Author URL.
Tuke MA, Ruth KS, Wood AR, Beaumont RN, Tyrrell J, Jones SE, Yaghootkar H, Turner CLS, Donohoe ME, Brooke AM, et al (2019). Mosaic Turner syndrome shows reduced penetrance in an adult population study.
Genet Med,
21(4), 877-886.
Abstract:
Mosaic Turner syndrome shows reduced penetrance in an adult population study.
PURPOSE: Many women with X chromosome aneuploidy undergo lifetime clinical monitoring for possible complications. However, ascertainment of cases in the clinic may mean that the penetrance has been overestimated. METHODS: We characterized the prevalence and phenotypic consequences of X chromosome aneuploidy in a population of 244,848 women over 40 years of age from UK Biobank, using single-nucleotide polymorphism (SNP) array data. RESULTS: We detected 30 women with 45,X; 186 with mosaic 45,X/46,XX; and 110 with 47,XXX. The prevalence of nonmosaic 45,X (12/100,000) and 47,XXX (45/100,000) was lower than expected, but was higher for mosaic 45,X/46,XX (76/100,000). The characteristics of women with 45,X were consistent with the characteristics of a clinically recognized Turner syndrome phenotype, including short stature and primary amenorrhea. In contrast, women with mosaic 45,X/46,XX were less short, had a normal reproductive lifespan and birth rate, and no reported cardiovascular complications. The phenotype of women with 47,XXX included taller stature (5.3 cm; SD = 5.52 cm; P = 5.8 × 10-20) and earlier menopause age (5.12 years; SD = 5.1 years; P = 1.2 × 10-14). CONCLUSION: Our results suggest that the clinical management of women with 45,X/46,XX mosaicism should be minimal, particularly those identified incidentally.
Abstract.
Author URL.
Justice AE, Karaderi T, Highland HM, Young KL, Graff M, Lu Y, Turcot V, Auer PL, Fine RS, Guo X, et al (2019). Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.
Nature Genetics,
51(3), 452-469.
Abstract:
Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution
Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF
Abstract.
Tuke MA, Ruth KS, Wood AR, Beaumont RN, Tyrrell J, Jones SE, Yaghootkar H, Turner CLS, Donohoe ME, Brooke AM, et al (2019). Response to Prakash et al.
Genet Med,
21(8), 1884-1885.
Author URL.
Tyrrell J, Mulugeta A, Wood AR, Zhou A, Beaumont RN, Tuke MA, Jones SE, Ruth KS, Yaghootkar H, Sharp S, et al (2019). Using genetics to understand the causal influence of higher BMI on depression.
Int J Epidemiol,
48(3), 834-848.
Abstract:
Using genetics to understand the causal influence of higher BMI on depression.
BACKGROUND: Depression is more common in obese than non-obese individuals, especially in women, but the causal relationship between obesity and depression is complex and uncertain. Previous studies have used genetic variants associated with BMI to provide evidence that higher body mass index (BMI) causes depression, but have not tested whether this relationship is driven by the metabolic consequences of BMI nor for differences between men and women. METHODS: We performed a Mendelian randomization study using 48 791 individuals with depression and 291 995 controls in the UK Biobank, to test for causal effects of higher BMI on depression (defined using self-report and Hospital Episode data). We used two genetic instruments, both representing higher BMI, but one with and one without its adverse metabolic consequences, in an attempt to 'uncouple' the psychological component of obesity from the metabolic consequences. We further tested causal relationships in men and women separately, and using subsets of BMI variants from known physiological pathways. RESULTS: Higher BMI was strongly associated with higher odds of depression, especially in women. Mendelian randomization provided evidence that higher BMI partly causes depression. Using a 73-variant BMI genetic risk score, a genetically determined one standard deviation (1 SD) higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.09, 1.28, P = 0.00007) and women only (OR: 1.24, 95% CI: 1.11, 1.39, P = 0.0001). Meta-analysis with 45 591 depression cases and 97 647 controls from the Psychiatric Genomics Consortium (PGC) strengthened the statistical confidence of the findings in all individuals. Similar effect size estimates were obtained using different Mendelian randomization methods, although not all reached P
Abstract.
Author URL.
Frayling TM (2018). A Common Allele in FGF21 Associated with Sugar Intake is Associated with Body Shape, Lower Total Body-Fat Percentage, and Higher Blood Pressure. Cell Reports, 23(2), 327-336.
Flannick J, Fuchsberger C, Mahajan A, Teslovich TM, Agarwala V, Gaulton KJ, Caulkins L, Koesterer R, Ma C, Moutsianas L, et al (2018). Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.
Sci Data,
5Abstract:
Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.
This corrects the article DOI: 10.1038/sdata.2017.179.
Abstract.
Author URL.
van Hees VT, Sabia S, Jones SE, Wood AR, Anderson KN, Kivimaki M, Frayling TM, Pack AI, Bucan M, Trenell MI, et al (2018). Estimating sleep parameters using an accelerometer without sleep diary.
SCIENTIFIC REPORTS,
8 Author URL.
Jun G, Manning A, Almeida M, Zawistowski M, Wood AR, Teslovich TM, Fuchsberger C, Feng S, Cingolani P, Gaulton KJ, et al (2018). Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees.
Proceedings of the National Academy of Sciences of the United States of America,
115(2), 379-384.
Abstract:
Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees
A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.
Abstract.
Beaumont RN, Warrington NM, Cavadino A, Tyrrell J, Nodzenski M, Horikoshi M, Geller F, Myhre R, Richmond RC, Paternoster L, et al (2018). Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics.
Hum Mol Genet,
27(4), 742-756.
Abstract:
Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics.
Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P
Abstract.
Author URL.
Moore AZ, Ding J, Tuke MA, Wood AR, Bandinelli S, Frayling TM, Ferrucci L (2018). Influence of cell distribution and diabetes status on the association between mitochondrial DNA copy number and aging phenotypes in the InCHIANTI study.
Aging Cell,
17(1).
Abstract:
Influence of cell distribution and diabetes status on the association between mitochondrial DNA copy number and aging phenotypes in the InCHIANTI study.
Mitochondrial DNA copy number (mtDNA-CN) estimated in whole blood is a novel marker of mitochondrial mass and function that can be used in large population-based studies. Analyses that attempt to relate mtDNA-CN to specific aging phenotypes may be confounded by differences in the distribution of blood cell types across samples. Also, low or high mtDNA-CN may have a different meaning given the presence of diseases associated with mitochondrial damage. We evaluated the impact of blood cell type distribution and diabetes status on the association between mtDNA-CN and aging phenotypes, namely chronologic age, interleukin-6, hemoglobin, and all-cause mortality, among 672 participants of the InCHIANTI study. After accounting for white blood cell count, platelet count, and white blood cell proportions in multivariate models, associations of mtDNA-CN with age and interleukin-6 were no longer statistically significant. Evaluation of a statistical interaction by diabetes status suggested heterogeneity of effects in the analysis of mortality (P
Abstract.
Author URL.
Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, Frayling TM, Hirschhorn J, Yang J, Visscher PM, et al (2018). Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry.
Hum Mol Genet,
27(20), 3641-3649.
Abstract:
Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry.
Recent genome-wide association studies (GWAS) of height and body mass index (BMI) in ∼250000 European participants have led to the discovery of ∼700 and ∼100 nearly independent single nucleotide polymorphisms (SNPs) associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in ∼450000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N ∼700000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3290 and 941 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of P
Abstract.
Author URL.
Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, et al (2018). Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.
Nat Genet,
50(1), 26-41.
Abstract:
Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
Abstract.
Author URL.
Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, et al (2018). Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.
Nat Genet,
50(5), 766-767.
Abstract:
Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.
In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
Abstract.
Author URL.
Mahajan A, Wessel J, Willems SM, Zhao W, Robertson NR, Chu AY, Gan W, Kitajima H, Taliun D, Rayner NW, et al (2018). Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.
Nat Genet,
50(4), 559-571.
Abstract:
Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.
We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P
Abstract.
Author URL.
Locke JM, Saint-Martin C, Laver TW, Patel KA, Wood AR, Sharp SA, Ellard S, Bellanné-Chantelot C, Hattersley AT, Harries LW, et al (2018). The Common HNF1A Variant I27L is a Modifier of Age at Diabetes Diagnosis in Individuals with HNF1A-MODY.
Diabetes,
67(9), 1903-1907.
Abstract:
The Common HNF1A Variant I27L is a Modifier of Age at Diabetes Diagnosis in Individuals with HNF1A-MODY.
There is wide variation in the age at diagnosis of diabetes in individuals with maturity-onset diabetes of the young (MODY) due to a mutation in the HNF1A gene. We hypothesized that common variants at the HNF1A locus (rs1169288 [I27L], rs1800574 [A98V]), which are associated with type 2 diabetes susceptibility, may modify age at diabetes diagnosis in individuals with HNF1A-MODY. Meta-analysis of two independent cohorts, comprising 781 individuals with HNF1A-MODY, found no significant associations between genotype and age at diagnosis. However after stratifying according to type of mutation (protein-truncating variant [PTV] or missense), we found each 27L allele to be associated with a 1.6-year decrease (95% CI -2.6, -0.7) in age at diagnosis, specifically in the subset (n = 444) of individuals with a PTV. The effect size was similar and significant across the two independent cohorts of individuals with HNF1A-MODY. We report a robust genetic modifier of HNF1A-MODY age at diagnosis that further illustrates the strong effect of genetic variation within HNF1A upon diabetes phenotype.
Abstract.
Author URL.
Wood AR, Jonsson A, Jackson AU, Wang N, van Leewen N, Palmer ND, Kobes S, Deelen J, Boquete-Vilarino L, Paananen J, et al (2017). A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Physiology of Type 2 Diabetes Variants.
Diabetes,
66(8), 2296-2309.
Abstract:
A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Physiology of Type 2 Diabetes Variants.
Understanding the physiological mechanisms by which common variants predispose to type 2 diabetes requires large studies with detailed measures of insulin secretion and sensitivity. Here we performed the largest genome-wide association study of first-phase insulin secretion, as measured by intravenous glucose tolerance tests, using up to 5,567 individuals without diabetes from 10 studies. We aimed to refine the mechanisms of 178 known associations between common variants and glycemic traits and identify new loci. Thirty type 2 diabetes or fasting glucose-raising alleles were associated with a measure of first-phase insulin secretion at P < 0.05 and provided new evidence, or the strongest evidence yet, that insulin secretion, intrinsic to the islet cells, is a key mechanism underlying the associations at the HNF1A, IGF2BP2, KCNQ1, HNF1B, VPS13C/C2CD4A, FAF1, PTPRD, AP3S2, KCNK16, MAEA, LPP, WFS1, and TMPRSS6 loci. The fasting glucose-raising allele near PDX1, a known key insulin transcription factor, was strongly associated with lower first-phase insulin secretion but has no evidence for an effect on type 2 diabetes risk. The diabetes risk allele at TCF7L2 was associated with a stronger effect on peak insulin response than on C-peptide-based insulin secretion rate, suggesting a possible additional role in hepatic insulin clearance or insulin processing. In summary, our study provides further insight into the mechanisms by which common genetic variation influences type 2 diabetes risk and glycemic traits.
Abstract.
Author URL.
Manning A, Highland HM, Gasser J, Sim X, Tukiainen T, Fontanillas P, Grarup N, Rivas MA, Mahajan A, Locke AE, et al (2017). A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population is Associated with Fasting Insulin Levels and Type 2 Diabetes Risk.
Diabetes,
66(7), 2019-2032.
Abstract:
A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population is Associated with Fasting Insulin Levels and Type 2 Diabetes Risk.
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.
Abstract.
Author URL.
Scott RA, Scott LJ, Mägi R, Marullo L, Gaulton KJ, Kaakinen M, Pervjakova N, Pers TH, Johnson AD, Eicher JD, et al (2017). An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.
Diabetes,
66(11), 2888-2902.
Abstract:
An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.
To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
Abstract.
Author URL.
Macé A, Tuke MA, Deelen P, Kristiansson K, Mattsson H, Nõukas M, Sapkota Y, Schick U, Porcu E, Rüeger S, et al (2017). CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits.
Nat Commun,
8(1).
Abstract:
CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits.
There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m2). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m2 for each Mb of total deletion burden (P = 2.5 × 10-10, 6.0 × 10-5, and 2.9 × 10-3). Our study provides evidence that the same genes (e.g. MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.
Abstract.
Author URL.
Tyrrell J, Wood AR, Ames RM, Yaghootkar H, Beaumont RN, Jones SE, Tuke MA, Ruth KS, Freathy RM, Davey Smith G, et al (2017). Gene-obesogenic environment interactions in the UK Biobank study.
Int J Epidemiol,
46(2), 559-575.
Abstract:
Gene-obesogenic environment interactions in the UK Biobank study.
BACKGROUND: Previous studies have suggested that modern obesogenic environments accentuate the genetic risk of obesity. However, these studies have proven controversial as to which, if any, measures of the environment accentuate genetic susceptibility to high body mass index (BMI). METHODS: We used up to 120 000 adults from the UK Biobank study to test the hypothesis that high-risk obesogenic environments and behaviours accentuate genetic susceptibility to obesity. We used BMI as the outcome and a 69-variant genetic risk score (GRS) for obesity and 12 measures of the obesogenic environment as exposures. These measures included Townsend deprivation index (TDI) as a measure of socio-economic position, TV watching, a 'Westernized' diet and physical activity. We performed several negative control tests, including randomly selecting groups of different average BMIs, using a simulated environment and including sun-protection use as an environment. RESULTS: We found gene-environment interactions with TDI (Pinteraction = 3 × 10 -10 ), self-reported TV watching (Pinteraction = 7 × 10 -5 ) and self-reported physical activity (Pinteraction = 5 × 10 -6 ). Within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73 m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. The interactions were weaker, but present, with the negative controls, including sun-protection use, indicating that residual confounding is likely. CONCLUSIONS: Our findings suggest that the obesogenic environment accentuates the risk of obesity in genetically susceptible adults. of the factors we tested, relative social deprivation best captures the aspects of the obesogenic environment responsible.
Abstract.
Author URL.
Yaghootkar H, Bancks MP, Jones SE, McDaid A, Beaumont R, Donnelly L, Wood AR, Campbell A, Tyrrell J, Hocking LJ, et al (2017). Quantifying the extent to which index event biases influence large genetic association studies.
Hum Mol Genet,
26(5), 1018-1030.
Abstract:
Quantifying the extent to which index event biases influence large genetic association studies.
As genetic association studies increase in size to 100 000s of individuals, subtle biases may influence conclusions. One possible bias is 'index event bias' (IEB) that appears due to the stratification by, or enrichment for, disease status when testing associations between genetic variants and a disease-associated trait. We aimed to test the extent to which IEB influences some known trait associations in a range of study designs and provide a statistical framework for assessing future associations. Analyzing data from 113 203 non-diabetic UK Biobank participants, we observed three (near TCF7L2, CDKN2AB and CDKAL1) overestimated (body mass index (BMI) decreasing) and one (near MTNR1B) underestimated (BMI increasing) associations among 11 type 2 diabetes risk alleles (at P < 0.05). IEB became even stronger when we tested a type 2 diabetes genetic risk score composed of these 11 variants (-0.010 standard deviations BMI per allele, P = 5 × 10- 4), which was confirmed in four additional independent studies. Similar results emerged when examining the effect of blood pressure increasing alleles on BMI in normotensive UK Biobank samples. Furthermore, we demonstrated that, under realistic scenarios, common disease alleles would become associated at P < 5 × 10- 8 with disease-related traits through IEB alone, if disease prevalence in the sample differs appreciably from the background population prevalence. For example, some hypertension and type 2 diabetes alleles will be associated with BMI in sample sizes of >500 000 if the prevalence of those diseases differs by >10% from the background population. In conclusion, IEB may result in false positive or negative genetic associations in very large studies stratified or strongly enriched for/against disease cases.
Abstract.
Author URL.
Marouli E, Graff M, Medina-Gomez C, Lo KS, Wood AR, Kjaer TR, Fine RS, Lu Y, Schurmann C, Highland HM, et al (2017). Rare and low-frequency coding variants alter human adult height.
Nature,
542(7640), 186-190.
Abstract:
Rare and low-frequency coding variants alter human adult height.
Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
Abstract.
Author URL.
Pilling LC, Atkins JL, Duff MO, Beaumont RN, Jones SE, Tyrrell J, Kuo C-L, Ruth KS, Tuke MA, Yaghootkar H, et al (2017). Red blood cell distribution width: Genetic evidence for aging pathways in 116,666 volunteers.
PLoS One,
12(9).
Abstract:
Red blood cell distribution width: Genetic evidence for aging pathways in 116,666 volunteers.
INTRODUCTION: Variability in red blood cell volumes (distribution width, RDW) increases with age and is strongly predictive of mortality, incident coronary heart disease and cancer. We investigated inherited genetic variation associated with RDW in 116,666 UK Biobank human volunteers. RESULTS: a large proportion RDW is explained by genetic variants (29%), especially in the older group (60+ year olds, 33.8%,
Abstract.
Author URL.
Flannick J, Fuchsberger C, Mahajan A, Teslovich TM, Agarwala V, Gaulton KJ, Caulkins L, Koesterer R, Ma C, Moutsianas L, et al (2017). Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.
Sci Data,
4Abstract:
Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
Abstract.
Author URL.
McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood AR, Teumer A, Kang HM, Fuchsberger C, Danecek P, Sharp K, et al (2016). A reference panel of 64,976 haplotypes for genotype imputation.
Nat Genet,
48(10), 1279-1283.
Abstract:
A reference panel of 64,976 haplotypes for genotype imputation.
We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.
Abstract.
Author URL.
Chen G-B, Lee SH, Robinson MR, Trzaskowski M, Zhu Z-X, Winkler TW, Day FR, Croteau-Chonka DC, Wood AR, Locke AE, et al (2016). Across-cohort QC analyses of GWAS summary statistics from complex traits.
Eur J Hum Genet,
25(1), 137-146.
Abstract:
Across-cohort QC analyses of GWAS summary statistics from complex traits.
Genome-wide association studies (GWASs) have been successful in discovering SNP trait associations for many quantitative traits and common diseases. Typically, the effect sizes of SNP alleles are very small and this requires large genome-wide association meta-analyses (GWAMAs) to maximize statistical power. A trend towards ever-larger GWAMA is likely to continue, yet dealing with summary statistics from hundreds of cohorts increases logistical and quality control problems, including unknown sample overlap, and these can lead to both false positive and false negative findings. In this study, we propose four metrics and visualization tools for GWAMA, using summary statistics from cohort-level GWASs. We propose methods to examine the concordance between demographic information, and summary statistics and methods to investigate sample overlap. (I) We use the population genetics Fst statistic to verify the genetic origin of each cohort and their geographic location, and demonstrate using GWAMA data from the GIANT Consortium that geographic locations of cohorts can be recovered and outlier cohorts can be detected. (II) We conduct principal component analysis based on reported allele frequencies, and are able to recover the ancestral information for each cohort. (III) We propose a new statistic that uses the reported allelic effect sizes and their standard errors to identify significant sample overlap or heterogeneity between pairs of cohorts. (IV) to quantify unknown sample overlap across all pairs of cohorts, we propose a method that uses randomly generated genetic predictors that does not require the sharing of individual-level genotype data and does not breach individual privacy.
Abstract.
Author URL.
Tyrrell J, Richmond RC, Palmer TM, Feenstra B, Rangarajan J, Metrustry S, Cavadino A, Paternoster L, Armstrong LL, De Silva NMG, et al (2016). Genetic Evidence for Causal Relationships Between Maternal Obesity-Related Traits and Birth Weight. JAMA, 315(11), 1129-1129.
Yaghootkar H, Lotta LA, Tyrrell J, Smit RAJ, Jones SE, Donnelly L, Beaumont R, Campbell A, Tuke MA, Hayward C, et al (2016). Genetic Evidence for a Link Between Favorable Adiposity and Lower Risk of Type 2 Diabetes, Hypertension, and Heart Disease.
Diabetes,
65(8), 2448-2460.
Abstract:
Genetic Evidence for a Link Between Favorable Adiposity and Lower Risk of Type 2 Diabetes, Hypertension, and Heart Disease.
Recent genetic studies have identified some alleles that are associated with higher BMI but lower risk of type 2 diabetes, hypertension, and heart disease. These "favorable adiposity" alleles are collectively associated with lower insulin levels and higher subcutaneous-to-visceral adipose tissue ratio and may protect from disease through higher adipose storage capacity. We aimed to use data from 164,609 individuals from the UK Biobank and five other studies to replicate associations between a genetic score of 11 favorable adiposity variants and adiposity and risk of disease, to test for interactions between BMI and favorable adiposity genetics, and to test effects separately in men and women. In the UK Biobank, the 50% of individuals carrying the most favorable adiposity alleles had higher BMIs (0.120 kg/m(2) [95% CI 0.066, 0.174]; P = 1E-5) and higher body fat percentage (0.301% [0.230, 0.372]; P = 1E-16) compared with the 50% of individuals carrying the fewest alleles. For a given BMI, the 50% of individuals carrying the most favorable adiposity alleles were at lower risk of type 2 diabetes (odds ratio [OR] 0.837 [0.784, 0.894]; P = 1E-7), hypertension (OR 0.935 [0.911, 0.958]; P = 1E-7), and heart disease (OR 0.921 [0.872, 0.973]; P = 0.003) and had lower blood pressure (systolic -0.859 mmHg [-1.099, -0.618]; P = 3E-12 and diastolic -0.394 mmHg [-0.534, -0.254]; P = 4E-8). In women, these associations could be explained by the observation that the alleles associated with higher BMI but lower risk of disease were also associated with a favorable body fat distribution, with a lower waist-to-hip ratio (-0.004 cm [95% CI -0.005, -0.003] 50% vs. 50%; P = 3E-14), but in men, the favorable adiposity alleles were associated with higher waist circumference (0.454 cm [0.267, 0.641] 50% vs. 50%; P = 2E-6) and higher waist-to-hip ratio (0.0013 [0.0003, 0.0024] 50% vs. 50%; P = 0.01). Results were strengthened when a meta-analysis with five additional studies was conducted. There was no evidence of interaction between a genetic score consisting of known BMI variants and the favorable adiposity genetic score. In conclusion, different molecular mechanisms that lead to higher body fat percentage (with greater subcutaneous storage capacity) can have different impacts on cardiometabolic disease risk. Although higher BMI is associated with higher risk of diseases, better fat storage capacity could reduce the risk.
Abstract.
Author URL.
Ruth KS, Beaumont RN, Tyrrell J, Jones SE, Tuke MA, Yaghootkar H, Wood AR, Freathy RM, Weedon MN, Frayling TM, et al (2016). Genetic evidence that lower circulating FSH levels lengthen menstrual cycle, increase age at menopause and impact female reproductive health.
Hum Reprod,
31(2), 473-481.
Abstract:
Genetic evidence that lower circulating FSH levels lengthen menstrual cycle, increase age at menopause and impact female reproductive health.
STUDY QUESTION: How does a genetic variant in the FSHB promoter, known to alter FSH levels, impact female reproductive health? SUMMARY ANSWER: the T allele of the FSHB promoter polymorphism (rs10835638; c.-211G>T) results in longer menstrual cycles and later menopause and, while having detrimental effects on fertility, is protective against endometriosis. WHAT IS KNOWN ALREADY: the FSHB promoter polymorphism (rs10835638; c.-211G>T) affects levels of FSHB transcription and, as a result, circulating levels of FSH. FSH is required for normal fertility and genetic variants at the FSHB locus are associated with age at menopause and polycystic ovary syndrome (PCOS). STUDY DESIGN, SIZE, DURATION: We used cross-sectional data from the UK Biobank to look at associations between the FSHB promoter polymorphism and reproductive traits, and performed a genome-wide association study (GWAS) for length of menstrual cycle. PARTICIPANTS/MATERIALS, SETTING, METHODS: We included white British individuals aged 40-69 years in 2006-2010, in the May 2015 release of genetic data from UK Biobank. We tested the FSH-lowering T allele of the FSHB promoter polymorphism (rs10835638; c.-211G>T) for associations with 29, mainly female, reproductive phenotypes in up to 63 350 women and 56 608 men. We conducted a GWAS in 9534 individuals to identify genetic variants associated with length of menstrual cycle. MAIN RESULTS AND THE ROLE OF CHANCE: the FSH-lowering T allele of the FSHB promoter polymorphism (rs10835638; MAF 0.16) was associated with longer menstrual cycles [0.16 SD (c. 1 day) per minor allele; 95% confidence interval (CI) 0.12-0.20; P = 6 × 10(-16)], later age at menopause (0.13 years per minor allele; 95% CI 0.04-0.22; P = 5.7 × 10(-3)), greater female nulliparity [odds ratio (OR) = 1.06; 95% CI 1.02-1.11; P = 4.8 × 10(-3)] and lower risk of endometriosis (OR = 0.79; 95% CI 0.69-0.90; P = 4.1 × 10(-4)). The FSH-lowering T allele was not associated with other female reproductive illnesses or conditions in our study and we did not replicate associations with male infertility or PCOS. In the GWAS for menstrual cycle length, only variants near the FSHB gene reached genome-wide significance (P < 5 × 10(-9)). LIMITATIONS, REASONS FOR CAUTION: the data included might be affected by recall bias. Cycle length was not available for 25% of women still cycling (1% did not answer, 6% did not know and for 18% cycle length was recorded as 'irregular'). Women with a cycle length recorded were aged over 40 and were approaching menopause; however, we did not find evidence that this affected the results. Many of the groups with illnesses had relatively small sample sizes and so the study may have been under-powered to detect an effect. WIDER IMPLICATIONS OF THE FINDINGS: We found a strong novel association between a genetic variant that lowers FSH levels and longer menstrual cycles, at a locus previously robustly associated with age at menopause. The variant was also associated with nulliparity and endometriosis risk. These findings should now be verified in a second independent group of patients. We conclude that lifetime differences in circulating levels of FSH between individuals can influence menstrual cycle length and a range of reproductive outcomes, including menopause timing, infertility, endometriosis and PCOS. STUDY FUNDING/COMPETING INTERESTS: None. TRIAL REGISTRATION NUMBER: Not applicable.
Abstract.
Author URL.
Jones SE, Tyrrell J, Wood AR, Beaumont RN, Ruth KS, Tuke MA, Yaghootkar H, Hu Y, Teder-Laving M, Hayward C, et al (2016). Genome-wide association analyses in 128,266 individuals identifies new morningness and sleep duration loci. PLoS Genetics
Horikoshi M, Beaumont RN, Day FR, Warrington NM, Kooijman MN, Fernandez-Tajes J, Feenstra B, van Zuydam NR, Gaulton KJ, Grarup N, et al (2016). Genome-wide associations for birth weight and correlations with adult disease.
Nature,
538(7624), 248-252.
Abstract:
Genome-wide associations for birth weight and correlations with adult disease.
Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P
Abstract.
Author URL.
Kilpeläinen TO, Carli JFM, Skowronski AA, Sun Q, Kriebel J, Feitosa MF, Hedman ÅK, Drong AW, Hayes JE, Zhao J, et al (2016). Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.
Nat Commun,
7Abstract:
Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.
Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P
Abstract.
Author URL.
Frayling TM, Tyrrell J, Jones SE, Beaumont R, Astley CM, Lovell R, Yaghootkar H, Tuke M, Ruth KS, Freathy RM, et al (2016). Height, body mass index, and socioeconomic status: mendelian randomisation study in UK Biobank. British Medical Journal
Pilling LC, Atkins JL, Bowman K, Jones SE, Tyrrell J, Beaumont RN, Ruth KS, Tuke MA, Yaghootkar H, Wood AR, et al (2016). Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants.
Aging (Albany NY),
8(3), 547-560.
Abstract:
Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants.
Variation in human lifespan is 20 to 30% heritable in twins but few genetic variants have been identified. We undertook a Genome Wide Association Study (GWAS) using age at death of parents of middle-aged UK Biobank participants of European decent (n=75,244 with father's and/or mother's data, excluding early deaths). Genetic risk scores for 19 phenotypes (n=777 proven variants) were also tested. In GWAS, a nicotine receptor locus(CHRNA3, previously associated with increased smoking and lung cancer) was associated with fathers' survival. Less common variants requiring further confirmation were also identified. Offspring of longer lived parents had more protective alleles for coronary artery disease, systolic blood pressure, body mass index, cholesterol and triglyceride levels, type-1 diabetes, inflammatory bowel disease and Alzheimer's disease. In candidate analyses, variants in the TOMM40/APOE locus were associated with longevity, but FOXO variants were not. Associations between extreme longevity (mother >=98 years, fathers >=95 years, n=1,339) and disease alleles were similar, with an additional association with HDL cholesterol (p=5.7x10-3). These results support a multiple protective factors model influencing lifespan and longevity (top 1% survival) in humans, with prominent roles for cardiovascular-related pathways. Several of these genetically influenced risks, including blood pressure and tobacco exposure, are potentially modifiable.
Abstract.
Author URL.
Almeida M, Blondell L, Peralta JM, Kent JW, Jun G, Teslovich TM, Fuchsberger C, Wood AR, Manning AK, Frayling TM, et al (2016). Independent test assessment using the extreme value distribution theory.
BMC Proc,
10(Suppl 7), 245-249.
Abstract:
Independent test assessment using the extreme value distribution theory.
The new generation of whole genome sequencing platforms offers great possibilities and challenges for dissecting the genetic basis of complex traits. With a very high number of sequence variants, a naïve multiple hypothesis threshold correction hinders the identification of reliable associations by the overreduction of statistical power. In this report, we examine 2 alternative approaches to improve the statistical power of a whole genome association study to detect reliable genetic associations. The approaches were tested using the Genetic Analysis Workshop 19 (GAW19) whole genome sequencing data. The first tested method estimates the real number of effective independent tests actually being performed in whole genome association project by the use of an extreme value distribution and a set of phenotype simulations. Given the familiar nature of the GAW19 data and the finite number of pedigree founders in the sample, the number of correlations between genotypes is greater than in a set of unrelated samples. Using our procedure, we estimate that the effective number represents only 15 % of the total number of independent tests performed. However, even using this corrected significance threshold, no genome-wide significant association could be detected for systolic and diastolic blood pressure traits. The second approach implements a biological relevance-driven hypothesis tested by exploiting prior computational predictions on the effect of nonsynonymous genetic variants detected in a whole genome sequencing association study. This guided testing approach was able to identify 2 promising single-nucleotide polymorphisms (SNPs), 1 for each trait, targeting biologically relevant genes that could help shed light on the genesis of the human hypertension. The first gene, PFH14, associated with systolic blood pressure, interacts directly with genes involved in calcium-channel formation and the second gene, MAP4, encodes a microtubule-associated protein and had already been detected by previous genome-wide association study experiments conducted in an Asian population. Our results highlight the necessity of the development of alternative approached to improve the efficiency on the detection of reasonable candidate associations in whole genome sequencing studies.
Abstract.
Author URL.
Blangero J, Teslovich TM, Sim X, Almeida MA, Jun G, Dyer TD, Johnson M, Peralta JM, Manning A, Wood AR, et al (2016). Omics-squared: human genomic, transcriptomic and phenotypic data for genetic analysis workshop 19.
BMC Proc,
10(Suppl 7), 71-77.
Abstract:
Omics-squared: human genomic, transcriptomic and phenotypic data for genetic analysis workshop 19.
BACKGROUND: the Genetic Analysis Workshops (GAW) are a forum for development, testing, and comparison of statistical genetic methods and software. Each contribution to the workshop includes an application to a specified data set. Here we describe the data distributed for GAW19, which focused on analysis of human genomic and transcriptomic data. METHODS: GAW19 data were donated by the T2D-GENES Consortium and the San Antonio Family Heart Study and included whole genome and exome sequences for odd-numbered autosomes, measures of gene expression, systolic and diastolic blood pressures, and related covariates in two Mexican American samples. These two samples were a collection of 20 large families with whole genome sequence and transcriptomic data and a set of 1943 unrelated individuals with exome sequence. For each sample, simulated phenotypes were constructed based on the real sequence data. 'Functional' genes and variants for the simulations were chosen based on observed correlations between gene expression and blood pressure. The simulations focused primarily on additive genetic models but also included a genotype-by-medication interaction. A total of 245 genes were designated as 'functional' in the simulations with a few genes of large effect and most genes explaining
Abstract.
Author URL.
Fuchsberger C, Flannick J, Teslovich TM, Mahajan A, Agarwala V, Gaulton KJ, Ma C, Fontanillas P, Moutsianas L, McCarthy DJ, et al (2016). The genetic architecture of type 2 diabetes.
Nature,
536(7614), 41-47.
Abstract:
The genetic architecture of type 2 diabetes.
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
Abstract.
Author URL.
Wood AR, Tyrrell J, Beaumont R, Jones SE, Tuke MA, Ruth KS, GIANT consortium, Yaghootkar H, Freathy RM, Murray A, et al (2016). Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively.
Diabetologia,
59(6), 1214-1221.
Abstract:
Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively.
AIMS/HYPOTHESIS: Genome-wide association (GWA) studies have identified hundreds of common genetic variants associated with obesity and type 2 diabetes. These studies have usually focused on additive association tests. Identifying deviations from additivity may provide new biological insights and explain some of the missing heritability for these diseases. METHODS: We performed a GWA study using a dominance deviation model for BMI, obesity (29,925 cases) and type 2 diabetes (4,040 cases) in 120,286 individuals of British ancestry from the UK Biobank study. We also investigated whether single nucleotide polymorphisms previously shown to be associated with these traits showed any enrichment for departures from additivity. RESULTS: Known obesity-associated variants in FTO showed strong evidence of deviation from additivity (p DOMDEV = 3 × 10(-5)) through a recessive effect of the allele associated with higher BMI. The average BMI of individuals carrying zero, one or two BMI-raising alleles was 27.27 (95% CI 27.22, 27.31) kg/m(2), 27.54 (95% CI 27.50, 27.58) kg/m(2) and 28.07 (95% CI 28.00, 28.14) kg/m(2), respectively. A similar effect was observed in 105,643 individuals from the GIANT Consortium (p DOMDEV = 0.003; meta-analysis p DOMDEV = 1 × 10(-7)). For type 2 diabetes, we detected a recessive effect (p DOMDEV = 5 × 10(-4)) at CDKAL1. Relative to homozygous non-risk allele carriers, homozygous risk allele carriers had an OR of 1.48 (95% CI 1.32, 1.65), while the heterozygous group had an OR of 1.06 (95% CI 0.99, 1.14), a result consistent with that of a previous study. We did not identify any novel associations at genome-wide significance. CONCLUSIONS/INTERPRETATION: Although we found no evidence of widespread non-additive genetic effects contributing to obesity and type 2 diabetes risk, we did find robust examples of recessive effects at the FTO and CDKAL1 loci. ACCESS TO RESEARCH MATERIALS: Summary statistics are available at www.t2diabetesgenes.org and by request (a.r.wood@exeter.ac.uk). All underlying data are available on application from the UK Biobank.
Abstract.
Author URL.
Yaghootkar H, Stancáková A, Freathy RM, Vangipurapu J, Weedon MN, Xie W, Wood AR, Ferrannini E, Mari A, Ring SM, et al (2015). Association analysis of 29,956 individuals confirms that a low-frequency variant at CCND2 halves the risk of type 2 diabetes by enhancing insulin secretion.
Diabetes,
64(6), 2279-2285.
Abstract:
Association analysis of 29,956 individuals confirms that a low-frequency variant at CCND2 halves the risk of type 2 diabetes by enhancing insulin secretion.
A recent study identified a low-frequency variant at CCND2 associated with lower risk of type 2 diabetes, enhanced insulin response to a glucose challenge, higher height, and, paradoxically, higher BMI. We aimed to replicate the strength and effect size of these associations in independent samples and to assess the underlying mechanism. We genotyped the variant in 29,956 individuals and tested its association with type 2 diabetes and related traits. The low-frequency allele was associated with a lower risk of type 2 diabetes (OR 0.53; P = 2 × 10(-13); 6,647 case vs. 12,645 control subjects), higher disposition index (β = 0.07 log10; P = 2 × 10(-11); n = 13,028), and higher Matsuda index of insulin sensitivity (β = 0.02 log10; P = 5 × 10(-3); n = 13,118) but not fasting proinsulin (β = 0.01 log10; P = 0.5; n = 6,985). The low frequency allele was associated with higher adult height (β = 1.38 cm; P = 6 × 10(-9); n = 13,927), but the association of the variant with BMI (β = 0.36 kg/m(2); P = 0.02; n = 24,807), estimated in four population-based samples, was less than in the original publication where the effect estimate was biased by analyzing case subjects with type 2 diabetes and control subjects without diabetes separately. Our study establishes that a low-frequency allele in CCND2 halves the risk of type 2 diabetes primarily through enhanced insulin secretion.
Abstract.
Author URL.
Pers TH, Karjalainen JM, Chan Y, Westra H-J, Wood AR, Yang J, Lui JC, Vedantam S, Gustafsson S, Esko T, et al (2015). Biological interpretation of genome-wide association studies using predicted gene functions.
Nat Commun,
6Abstract:
Biological interpretation of genome-wide association studies using predicted gene functions.
The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.
Abstract.
Author URL.
Westra H-J, Arends D, Esko T, Peters MJ, Schurmann C, Schramm K, Kettunen J, Yaghootkar H, Fairfax BP, Andiappan AK, et al (2015). Cell Specific eQTL Analysis without Sorting Cells.
PLoS Genet,
11(5).
Abstract:
Cell Specific eQTL Analysis without Sorting Cells.
The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.
Abstract.
Author URL.
Joshi PK, Esko T, Mattsson H, Eklund N, Gandin I, Nutile T, Jackson AU, Schurmann C, Smith AV, Zhang W, et al (2015). Directional dominance on stature and cognition in diverse human populations.
Nature,
523(7561), 459-462.
Abstract:
Directional dominance on stature and cognition in diverse human populations.
Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
Abstract.
Author URL.
Gaulton KJ, Ferreira T, Lee Y, Raimondo A, Mägi R, Reschen ME, Mahajan A, Locke A, Rayner NW, Robertson N, et al (2015). Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.
Nature Genetics,
47(12), 1415-1425.
Abstract:
Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci
We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
Abstract.
Gaulton KJ, Ferreira T, Lee Y, Raimondo A, Mägi R, Reschen ME, Mahajan A, Locke A, Rayner NW, Robertson N, et al (2015). Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.
Nat Genet,
47(12), 1415-1425.
Abstract:
Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.
We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
Abstract.
Author URL.
Reppe S, Wang Y, Thompson WK, McEvoy LK, Schork AJ, Zuber V, LeBlanc M, Bettella F, Mills IG, Desikan RS, et al (2015). Genetic sharing with cardiovascular disease risk factors and diabetes reveals novel bone mineral density loci.
PLoS ONE,
10(12).
Abstract:
Genetic sharing with cardiovascular disease risk factors and diabetes reveals novel bone mineral density loci
Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity.
Abstract.
Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, Powell C, Vedantam S, Buchkovich ML, Yang J, et al (2015). Genetic studies of body mass index yield new insights for obesity biology.
Nature,
518(7538), 197-206.
Abstract:
Genetic studies of body mass index yield new insights for obesity biology.
Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
Abstract.
Author URL.
Thrift AP, Gong J, Peters U, Chang-Claude J, Rudolph A, Slattery ML, Chan AT, Esko T, Wood AR, Yang J, et al (2015). Mendelian randomization study of height and risk of colorectal cancer.
Int J Epidemiol,
44(2), 662-672.
Abstract:
Mendelian randomization study of height and risk of colorectal cancer.
BACKGROUND: for men and women, taller height is associated with increased risk of all cancers combined. For colorectal cancer (CRC), it is unclear whether the differential association of height by sex is real or is due to confounding or bias inherent in observational studies. We performed a Mendelian randomization study to examine the association between height and CRC risk. METHODS: to minimize confounding and bias, we derived a weighted genetic risk score predicting height (using 696 genetic variants associated with height) in 10,226 CRC cases and 10,286 controls. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for associations between height, genetically predicted height and CRC. RESULTS: Using conventional methods, increased height (per 10-cm increment) was associated with increased CRC risk (OR = 1.08, 95% CI = 1.02-1.15). In sex-specific analyses, height was associated with CRC risk for women (OR = 1.15, 95% CI = 1.05-1.26), but not men (OR = 0.98, 95% CI = 0.92-1.05). Consistent with these results, carrying greater numbers of (weighted) height-increasing alleles (per 1-unit increase) was associated with higher CRC risk for women and men combined (OR = 1.07, 95% CI = 1.01-1.14) and for women (OR = 1.09, 95% CI = . 01-1.19). There was weaker evidence of an association for men (OR = 1.05, 95% CI = 0.96-1.15). CONCLUSION: We provide evidence for a causal association between height and CRC for women. The CRC-height association for men remains unclear and warrants further investigation in other large studies.
Abstract.
Author URL.
Shungin D, Winkler TW, Croteau-Chonka DC, Ferreira T, Locke AE, Mägi R, Strawbridge RJ, Pers TH, Fischer K, Justice AE, et al (2015). New genetic loci link adipose and insulin biology to body fat distribution.
Nature,
518(7538), 187-196.
Abstract:
New genetic loci link adipose and insulin biology to body fat distribution.
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P
Abstract.
Author URL.
Robinson MR, Hemani G, Medina-Gomez C, Mezzavilla M, Esko T, Shakhbazov K, Powell JE, Vinkhuyzen A, Berndt SI, Gustafsson S, et al (2015). Population genetic differentiation of height and body mass index across Europe.
Nature GeneticsAbstract:
Population genetic differentiation of height and body mass index across Europe
Across-nation differences in the mean values for complex traits are common, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10-8; BMI, P < 5.95 × 10-4), and we find an among-population genetic correlation for tall and slender individuals (r = −0.80, 95% CI = −0.95, −0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).
Abstract.
Robinson MR, Hemani G, Medina-Gomez C, Mezzavilla M, Esko T, Shakhbazov K, Powell JE, Vinkhuyzen A, Berndt SI, Gustafsson S, et al (2015). Population genetic differentiation of height and body mass index across Europe.
Nature Genetics,
47(11), 1357-1361.
Abstract:
Population genetic differentiation of height and body mass index across Europe
Across-nation differences in the mean values for complex traits are common, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10 -8; BMI, P < 5.95 × 10 -4), and we find an among-population genetic correlation for tall and slender individuals (r = -0.80, 95% CI = -0.95, -0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).
Abstract.
Locke JM, Hysenaj G, Wood AR, Weedon MN, Harries LW (2015). Targeted allelic expression profiling in human islets identifies cis-regulatory effects for multiple variants identified by type 2 diabetes genome-wide association studies.
Diabetes,
64(4), 1484-1491.
Abstract:
Targeted allelic expression profiling in human islets identifies cis-regulatory effects for multiple variants identified by type 2 diabetes genome-wide association studies.
Genome-wide association studies (GWAS) have identified variation at >65 genomic loci associated with susceptibility to type 2 diabetes, but little progress has been made in elucidating the molecular mechanisms behind most of these associations. Using samples heterozygous for transcribed single nucleotide polymorphisms (SNPs), allelic expression profiling is a powerful technique for identifying cis-regulatory variants controlling gene expression. In this study, exonic SNPs, suitable for measuring mature mRNA levels and in high linkage disequilibrium with 65 lead type 2 diabetes GWAS SNPs, were identified and allelic expression determined by real-time PCR using RNA and DNA isolated from islets of 36 white nondiabetic donors. A significant allelic expression imbalance (AEI) was identified for 7/14 (50%) genes tested (ANPEP, CAMK2B, HMG20A, KCNJ11, NOTCH2, SLC30A8, and WFS1), with significant AEI confirmed for five of these genes using other linked exonic SNPs. Lastly, results of a targeted islet expression quantitative trait loci experiment support the AEI findings for ANPEP, further implicating ANPEP as the causative gene at its locus. The results of this study support the hypothesis that changes to cis-regulation of gene expression are involved in a large proportion of SNP associations with type 2 diabetes susceptibility.
Abstract.
Author URL.
Wood AR, Tuke MA, Nalls M, Hernandez D, Gibbs JR, Lin H, Xu CS, Li Q, Shen J, Jun G, et al (2015). Whole-genome sequencing to understand the genetic architecture of common gene expression and biomarker phenotypes.
Hum Mol Genet,
24(5), 1504-1512.
Abstract:
Whole-genome sequencing to understand the genetic architecture of common gene expression and biomarker phenotypes.
Initial results from sequencing studies suggest that there are relatively few low-frequency (
Abstract.
Author URL.
Wood AR, Tuke MA, Nalls MA, Hernandez DG, Bandinelli S, Singleton AB, Melzer D, Ferrucci L, Frayling TM, Weedon MN, et al (2014). Another explanation for apparent epistasis.
Nature,
514(7520), E3-E5.
Author URL.
Almasy L, Dyer TD, Peralta JM, Jun G, Wood AR, Fuchsberger C, Almeida MA, Kent JW, Fowler S, Blackwell TW, et al (2014). Data for Genetic Analysis Workshop 18: human whole genome sequence, blood pressure, and simulated phenotypes in extended pedigrees.
BMC Proc,
8(Suppl 1).
Abstract:
Data for Genetic Analysis Workshop 18: human whole genome sequence, blood pressure, and simulated phenotypes in extended pedigrees.
Genetic Analysis Workshop 18 (GAW18) focused on identification of genes and functional variants that influence complex phenotypes in human sequence data. Data for the workshop were donated by the T2D-GENES Consortium and included whole genome sequences for odd-numbered autosomes in 464 key individuals selected from 20 Mexican American families, a dense set of single-nucleotide polymorphisms in 959 individuals in these families, and longitudinal data on systolic and diastolic blood pressure measured at 1-4 examinations over a period of 20 years. Simulated phenotypes were generated based on the real sequence data and pedigree structures. In the design of the simulation model, gene expression measures from the San Antonio Family Heart Study (not distributed as part of the GAW18 data) were used to identify genes whose mRNA levels were correlated with blood pressure. Observed variants within these genes were designated as functional in the GAW18 simulation if they were nonsynonymous and predicted to have deleterious effects on protein function or if they were noncoding and associated with mRNA levels. Two simulated longitudinal phenotypes were modeled to have the same trait distributions as the real systolic and diastolic blood pressure data, with effects of age, sex, and medication use, including a genotype-medication interaction. For each phenotype, more than 1000 sequence variants in more than 200 genes present on the odd-numbered autosomes individually explained less than 0.01-2.78% of phenotypic variance. Cumulatively, variants in the most influential gene explained 7.79% of trait variance. An additional simulated phenotype, Q1, was designed to be correlated among family members but to not be associated with any sequence variants. Two hundred replicates of the phenotypes were simulated, with each including data for 849 individuals.
Abstract.
Author URL.
Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, Chu AY, Estrada K, Luan J, Kutalik Z, et al (2014). Defining the role of common variation in the genomic and biological architecture of adult human height.
Nature Genetics,
46(11), 1173-1186.
Abstract:
Defining the role of common variation in the genomic and biological architecture of adult human height
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated 1/42,000, 1/43,700 and 1/49,500 SNPs explained 1/421%, 1/424% and 1/429% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/I 2-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
Abstract.
Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, Chu AY, Estrada K, Luan J, Kutalik Z, et al (2014). Defining the role of common variation in the genomic and biological architecture of adult human height.
Nat Genet,
46(11), 1173-1186.
Abstract:
Defining the role of common variation in the genomic and biological architecture of adult human height.
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
Abstract.
Author URL.
Mahajan A, Go MJ, Zhang W, Below JE, Gaulton KJ, Ferreira T, Horikoshi M, Johnson AD, Ng MCY, Prokopenko I, et al (2014). Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.
NATURE GENETICS,
46(3), 234-+.
Author URL.
Winkler TW, Day FR, Croteau-Chonka DC, Wood AR, Locke AE, Mägi R, Ferreira T, Fall T, Graff M, Justice AE, et al (2014). Quality control and conduct of genome-wide association meta-analyses.
Nat Protoc,
9(5), 1192-1212.
Abstract:
Quality control and conduct of genome-wide association meta-analyses.
Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.
Abstract.
Author URL.
Majithia AR, Flannick J, Shahinian P, Guo M, Bray MA, Fontanillas P, Gabriel SB, Manning AK, Hartl C, Agarwala V, et al (2014). Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes.
Proceedings of the National Academy of Sciences of the United States of America,
111(36), 13127-13132.
Abstract:
Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes
Peroxisome proliferator-activated receptor gamma (PPARG) is a master transcriptional regulator of adipocyte differentiation and a canonical target of antidiabetic thiazolidinedione medications. In rare families, loss-of-function (LOF) mutations in PPARG are known to cosegregate with lipodystrophy and insulin resistance; in the general population, the common P12A variant is associated with a decreased risk of type 2 diabetes (T2D). Whether and how rare variants in PPARG and defects in adipocyte differentiation influence risk of T2D in the general population remains undetermined. By sequencing PPARG in 19,752 T2D cases and controls drawn from multiple studies and ethnic groups, we identified 49 previously unidentified, nonsynonymous PPARG variants (MAF < 0.5%). Considered in aggregate (with or without computational prediction of functional consequence), these rare variants showed no association with T2D (OR = 1.35; P = 0.17). The function of the 49 variants was experimentally tested in a novel high-throughput human adipocyte differentiation assay, and nine were found to have reduced activity in the assay. Carrying any of these nine LOF variants was associated with a substantial increase in risk of T2D (OR = 7.22; P = 0.005). The combination of large-scale DNA sequencing and functional testing in the laboratory reveals that approximately 1 in 1,000 individuals carries a variant in PPARG that reduces function in a human adipocyte differentiation assay and is associated with a substantial risk of T2D.
Abstract.
Vimaleswaran KS, Berry DJ, Lu C, Tikkanen E, Pilz S, Hiraki LT, Cooper JD, Dastani Z, Li R, Houston DK, et al (2013). Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts.
PLoS Medicine,
10(2).
Abstract:
Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts
Background: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. Methods and Findings: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10-27). The BMI allele score was associated both with BMI (p = 6.30×10-62) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10-57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). Conclusions: on the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency. Please see later in the article for the Editors' Summary. © 2013 Vimaleswaran et al.
Abstract.
Xie W, Wood AR, Lyssenko V, Weedon MN, Knowles JW, Alkayyali S, Assimes TL, Quertermous T, Abbasi F, Paananen J, et al (2013). Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes.
Diabetes,
62(6), 2141-2150.
Abstract:
Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes.
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.
Abstract.
Author URL.
Berndt SI, Gustafsson S, Mägi R, Ganna A, Wheeler E, Feitosa MF, Justice AE, Monda KL, Croteau-Chonka DC, Day FR, et al (2013). Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nature Genetics
Berndt SI, Gustafsson S, Mägi R, Ganna A, Wheeler E, Feitosa MF, Justice AE, Monda KL, Croteau-Chonka DC, Day FR, et al (2013). Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture.
Nature Genetics,
45(5), 501-512.
Abstract:
Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups. © 2013 Nature America, Inc. All rights reserved.
Abstract.
Wood AR, Perry JRB, Tanaka T, Hernandez DG, Zheng H-F, Melzer D, Gibbs JR, Nalls MA, Weedon MN, Spector TD, et al (2013). Imputation of variants from the 1000 Genomes Project modestly improves known associations and can identify low-frequency variant-phenotype associations undetected by HapMap based imputation.
PLoS One,
8(5).
Abstract:
Imputation of variants from the 1000 Genomes Project modestly improves known associations and can identify low-frequency variant-phenotype associations undetected by HapMap based imputation.
Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF
Abstract.
Author URL.
Randall JC, Winkler TW, Kutalik Z, Berndt SI, Jackson AU, Monda KL, Kilpeläinen TO, Esko T, Mägi R, Li S, et al (2013). Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits.
PLoS Genetics,
9(6).
Abstract:
Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR
Abstract.
Morrison FS, Locke JM, Wood AR, Tuke M, Pasko D, Murray A, Frayling T, Harries LW (2013). The splice site variant rs11078928 may be associated with a genotype-dependent alteration in expression of GSDMB transcripts.
BMC Genomics,
14Abstract:
The splice site variant rs11078928 may be associated with a genotype-dependent alteration in expression of GSDMB transcripts.
BACKGROUND: Many genetic variants have been associated with susceptibility to complex traits by genome wide association studies (GWAS), but for most, causal genes and mechanisms of action have yet to be elucidated. Using bioinformatics, we identified index and proxy variants associated with autoimmune disease susceptibility, with the potential to affect splicing of candidate genes. PCR and sequence analysis of whole blood RNA samples from population controls was then carried out for the 8 most promising variants to determine the effect of genetic variation on splicing of target genes. RESULTS: We identified 31 splice site SNPs with the potential to affect splicing, and prioritised 8 to determine the effect of genotype on candidate gene splicing. We identified that variants rs11078928 and rs2014886 were associated with altered splicing of the GSDMB and TSFM genes respectively. rs11078928, present in the asthma and autoimmune disease susceptibility locus on chromosome 17q12-21, was associated with the production of a novel Δ exon5-8 transcript of the GSDMB gene, and a separate decrease in the percentage of transcripts with inclusion of exon 6, whereas the multiple sclerosis susceptibility variant rs2014886, was associated with an alternative TFSM transcript encompassing a short cryptic exon within intron 2. CONCLUSIONS: Our findings demonstrate the utility of a bioinformatic approach in identification and prioritisation of genetic variants effecting splicing of their host genes, and suggest that rs11078928 and rs2014886 may affect the splicing of the GSDMB and TSFM genes respectively.
Abstract.
Author URL.
Coviello AD, Haring R, Wellons M, Vaidya D, Lehtimäki T, Keildson S, Lunetta KL, He C, Fornage M, Lagou V, et al (2012). A genome-wide association meta-analysis of circulating sex hormone-binding globulin reveals multiple loci implicated in sex steroid hormone regulation.
PLoS Genetics,
8(7).
Abstract:
A genome-wide association meta-analysis of circulating sex hormone-binding globulin reveals multiple loci implicated in sex steroid hormone regulation
Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×10-106), PRMT6 (rs17496332, 1p13.3, p = 1.4×10-11), GCKR (rs780093, 2p23.3, p = 2.2×10-16), ZBTB10 (rs440837, 8q21.13, p = 3.4×10-09), JMJD1C (rs7910927, 10q21.3, p = 6.1×10-35), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×10-08), NR2F2 (rs8023580, 15q26.2, p = 8.3×10-12), ZNF652 (rs2411984, 17q21.32, p = 3.5×10-14), TDGF3 (rs1573036, Xq22.3, p = 4.1×10-14), LHCGR (rs10454142, 2p16.3, p = 1.3×10-07), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×10-08), and UGT2B15 (rs293428, 4q13.2, p = 5.5×10-06). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×10-08, women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.
Abstract.
Murabito JM, White CC, Kavousi M, Sun YV, Feitosa MF, Nambi V, Lamina C, Schillert A, Coassin S, Bis JC, et al (2012). Association between chromosome 9p21 variants and the ankle-brachial index identified by a meta-analysis of 21 genome-wide association studies.
Circulation: Cardiovascular Genetics,
5(1), 100-112.
Abstract:
Association between chromosome 9p21 variants and the ankle-brachial index identified by a meta-analysis of 21 genome-wide association studies
Background-Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts. Methods and Results-Continuous ABI and PAD (ABI
Abstract.
Estrada K, Styrkarsdottir U, Evangelou E, Hsu YH, Duncan EL, Ntzani EE, Oei L, Albagha OME, Amin N, Kemp JP, et al (2012). Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.
Nature Genetics,
44(5), 491-501.
Abstract:
Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture
Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10 -8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10 -4, Bonferroni corrected), of which six reached P < 5 × 10 -8, including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility. © 2012 Nature America, Inc. All rights reserved.
Abstract.
Estrada K, Styrkarsdottir U, Evangelou E, Hsu Y-H, Duncan EL, Ntzani EE, Oei L, Albagha OME, Amin N, Kemp JP, et al (2012). Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nature Genetics
Morris AP, Ferreira T, Mahajan A, Prokopenko I, Kumar A, Lagou V, Lindgren CM, Rayner NW, Wiltshire S, Dimas AS, et al (2012). Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes.
Nature Genetics,
44(9), 981-990.
Abstract:
Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signaling and cell cycle regulation, in diabetes pathogenesis. © 2012 Nature America, Inc. All rights reserved.
Abstract.
Morris AP, Voight BF, Teslovich TM, Ferreira T, Segre AV, Steinthorsdottir V, Strawbridge RJ, Khan H, Grallert H, Mahajan A, et al (2012). Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes.
NATURE GENETICS,
44(9), 981-+.
Author URL.
Islam M, Jafar TH, Wood AR, De Silva NMG, Caulfield M, Chaturvedi N, Frayling TM (2012). Multiple genetic variants explain measurable variance in type 2 diabetes-related traits in Pakistanis. Diabetologia, 1-12.
Islam M, Jafar TH, Wood AR, De Silva NMG, Caulfield M, Chaturvedi N, Frayling TM (2012). Multiple genetic variants explain measurable variance in type 2 diabetes-related traits in Pakistanis.
DIABETOLOGIA,
55(8), 2193-2204.
Author URL.
Scott RA, Chu AY, Grarup N, Manning AK, Hivert M-F, Shungin D, Toenjes A, Yesupriya A, Barnes D, Bouatia-Naji N, et al (2012). No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels.
DIABETES,
61(5), 1291-1296.
Author URL.
Dastani Z, Hivert MF, Timpson NJ, Perry JRB, Yuan X, Scott RA, Henneman P, Heid IM, Kizer JR, Lyytikäinen LP, et al (2012). Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.
PLoS Genetics,
8(3).
Abstract:
Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals
Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8- 1.2 ×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p
Abstract.
Wood AR, Hernandez DG, Nalls MA, Yaghootkar H, Gibbs JR, Harries LW, Chong S, Moore M, Weedon MN, Guralnik JM, et al (2011). Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association.
Hum Mol Genet,
20(20), 4082-4092.
Abstract:
Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association.
The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.
Abstract.
Author URL.
Speliotes EK, Yerges-Armstrong LM, Wu J, Hernaez R, Kim LJ, Palmer CD, Gudnason V, Eiriksdottir G, Garcia ME, Launer LJ, et al (2011). Genome-Wide Association Analysis Identifies Variants Associated with Nonalcoholic Fatty Liver Disease That Have Distinct Effects on Metabolic Traits. PLoS Genetics, 7(3), e1001324-e1001324.
Harries LW, Hernandez D, Henley W, Wood AR, Holly AC, Bradley-Smith RM, Yaghootkar H, Dutta A, Murray A, Frayling TM, et al (2011). Human aging is characterized by focused changes in gene expression and deregulation of alternative splicing.
Aging Cell,
10(5), 868-878.
Abstract:
Human aging is characterized by focused changes in gene expression and deregulation of alternative splicing.
Aging is a major risk factor for chronic disease in the human population, but there are little human data on gene expression alterations that accompany the process. We examined human peripheral blood leukocyte in-vivo RNA in a large-scale transcriptomic microarray study (subjects aged 30-104 years). We tested associations between probe expression intensity and advancing age (adjusting for confounding factors), initially in a discovery set (n= 58), following-up findings in a replication set (n=240). We confirmed expression of key results by real-time PCR. of 16,571 expressed probes, only 295 (2%) were robustly associated with age. Just six probes were required for a highly efficient model for distinguishing between young and old (area under the curve in replication set; 95%). The focused nature of age-related gene expression may therefore provide potential biomarkers of aging. Similarly, only 7 of 1065 biological or metabolic pathways were age-associated, in gene set enrichment analysis, notably including the processing of messenger RNAs (mRNAs); [P
Abstract.
Author URL.
Nalls MA, Couper DJ, Tanaka T, van Rooij FJA, Chen M-H, Smith AV, Toniolo D, Zakai NA, Yang Q, Greinacher A, et al (2011). Multiple Loci Are Associated with White Blood Cell Phenotypes.
PLOS GENETICS,
7(6).
Author URL.
Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU, Allen HL, Lindgren CM, Luan J, Maegi R, et al (2010). Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index.
NATURE GENETICS,
42(11), 937-U53.
Author URL.
Lango Allen H, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F, Willer CJ, Jackson AU, Vedantam S, Raychaudhuri S, et al (2010). Hundreds of variants clustered in genomic loci and biological pathways affect human height.
Nature,
467(7317), 832-838.
Abstract:
Hundreds of variants clustered in genomic loci and biological pathways affect human height.
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P
Abstract.
Author URL.
Heid IM, Jackson AU, Randall JC, Winkler TW, Qi L, Steinthorsdottir V, Thorleifsson G, Zillikens MC, Speliotes EK, Maegi R, et al (2010). Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution.
NATURE GENETICS,
42(11), 949-U160.
Author URL.
ANDREW W, ANDREW NV (1948). Age changes in the deep cervical lymph nodes of 100 Wistar Institute rats.
Am J Anat,
82(1), 105-165.
Author URL.
