AbstractClinical classification is essential for estimating disease prevalence but is difficult, often requiring complex investigations. The widespread availability of population level genetic data makes novel genetic stratification techniques a highly attractive alternative. We propose a generalizable mathematical framework for determining disease prevalence within a cohort using genetic risk scores. We compare and evaluate methods based on the means of genetic risk scores’ distributions; the Earth Mover’s Distance between distributions; a linear combination of kernel density estimates of distributions; and an Excess method. We demonstrate the performance of genetic stratification to produce robust prevalence estimates. Specifically, we show that robust estimates of prevalence are still possible even with rarer diseases, smaller cohort sizes and less discriminative genetic risk scores, highlighting the general utility of these approaches. Genetic stratification techniques offer exciting new research tools, enabling unbiased insights into disease prevalence and clinical characteristics unhampered by clinical classification criteria.

. OBJECTIVE
. To determine whether presentation, progression, and genetic susceptibility of robustly defined adult-onset type 1 diabetes (T1D) are altered by diagnosis age.
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. RESEARCH DESIGN AND METHODS
. We compared the relationship between diagnosis age and presentation, C-peptide loss (annual change in urine C-peptide–creatinine ratio [UCPCR]), and genetic susceptibility (T1D genetic risk score [GRS]) in adults with confirmed T1D in the prospective StartRight study, 1,798 adults with new-onset diabetes. T1D was defined in two ways: two or more positive islet autoantibodies (of GAD antibody, IA-2 antigen, and ZnT8 autoantibody) irrespective of clinical diagnosis (n = 385) or one positive islet autoantibody and a clinical diagnosis of T1D (n = 180).
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.
. RESULTS
. In continuous analysis, age of diagnosis was not associated with C-peptide loss for either definition of T1D (P > 0.1), with mean (95% CI) annual C-peptide loss in those diagnosed before and after 35 years of age (median age of T1D defined by two or more positive autoantibodies): 39% (31–46) vs. 44% (38–50) with two or more positive islet autoantibodies and 43% (33–51) vs. 39% (31–46) with clinician diagnosis confirmed by one positive islet autoantibody (P > 0.1). Baseline C-peptide and T1D GRS were unaffected by age of diagnosis or T1D definition (P > 0.1). In T1D defined by two or more autoantibodies, presentation severity was similar in those diagnosed before and after 35 years of age: unintentional weight loss, 80% (95% CI 74–85) vs. 82% (76–87); ketoacidosis, 24% (18–30) vs. 19% (14–25); and presentation glucose, 21 mmol/L (19–22) vs. 21 mmol/L (20–22) (all P ≥ 0.1). Despite similar presentation, older adults were less likely to be diagnosed with T1D, insulin-treated, or admitted to hospital.
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.
. CONCLUSIONS
. When adult-onset T1D is robustly defined, the presentation characteristics, progression, and T1D genetic susceptibility are not altered by age of diagnosis.
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OBJECTIVE: to determine whether genetic risk for type 1 diabetes (T1D) differentiates the four Aβ subgroups of ketosis-prone diabetes (KPD), where A+ and A- define the presence or absence of islet autoantibodies and β+ and β- define the presence or absence of β-cell function. RESEARCH DESIGN AND METHODS: We compared T1D genetic risk scores (GRS) of patients with KPD across subgroups, race/ethnicity, β-cell function, and glycemia. RESULTS: Among 426 patients with KPD (54% Hispanic, 31% African American, 11% White), rank order of GRS was A+β- > A+β+ = A-β- > A-β+. GRS of A+β- KPD was lower than that of a T1D cohort, and GRS of A-β+ KPD was higher than that of a type 2 diabetes cohort. GRS was lowest among African American patients, with a similar distribution across KPD subgroups. CONCLUSIONS: T1D genetic risk delineates etiologic differences among KPD subgroups. Patients with A+β- KPD have the highest and those with A-β+ KPD the lowest GRS.

Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case-control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for 'test and treat' approaches to be used to tailor care for individuals with type 1 diabetes.

AIMS: Many individuals with type 1 diabetes retain residual β-cell function, with increased endogenous insulin secretion associated with reduced hyperglycaemia, hypoglycaemia and glycaemic variability. However, it is unknown when these improvements occur during the day. Dysglycaemia is common in overnight and postprandial periods and associated with diabetes complications. Therefore, this study aimed to determine the influence of residual β-cell function upon nocturnal and postprandial glycaemic control in established type 1 diabetes. METHODS: Under free-living conditions, 66 participants wore a blinded continuous glucose monitor (CGM), kept a food diary, and completed a stimulated urine C-peptide creatinine (UCPCR) test. Nocturnal, and postprandial CGM outcomes (participant means and discrete event analysis) were compared between UCPCR groups: undetectable (Cpepund ), low (Cpeplow : 0.001-0.19 nmol/mmol) and high (Cpephigh : ≥0.2 nmol/mmol). RESULTS: Greater β-cell function was associated with incremental improvements in glycaemia. Cpephigh spent significantly greater time in normoglycaemia than Cpepund overnight (76 ± 20% vs. 58 ± 20%, p = 0.005) and 0-300 mins postprandially (68 ± 22% vs. 51 ± 22%, p = 0.045), while also having reducing nocturnal variability (SD 1.12 ± 0.41 vs. 1.52 ± 0.43 mmol/L, p = 0.010). Analysis of individual events, controlling for diabetes duration, BMI, basal insulin, use of a continuous or flash glucose monitor and (for postprandial) meal type, carbohydrate and bolus insulin intake, replicated the group findings, additionally demonstrating Cpepund had increased hyperglycaemia versus Cpeplow overnight and increased postprandial hypoglycaemic events compared with Cpephigh. For all participants, breakfast had a significantly higher incremental area under the curve than lunch and dinner. CONCLUSIONS: Residual β-cell function is associated with improved nocturnal and postprandial glycaemic control. These data may be of clinical importance for identifying specific periods and individuals where further glycaemic management strategies would be beneficial.

C-peptide declines in type 1 diabetes, although many long-duration patients retain low, but detectable levels. Histological analyses confirm that β-cells can remain following type 1 diabetes onset. We explored the trends observed in C-peptide decline in the UK Genetic Resource Investigating Diabetes (UK GRID) cohort (N = 4,079), with β-cell loss in pancreas donors from the network for Pancreatic Organ donors with Diabetes (nPOD) biobank and the Exeter Archival Diabetes Biobank (EADB) (combined N = 235), stratified by recently reported age at diagnosis endotypes (<7, 7–12, ≥13 years) across increasing diabetes durations. The proportion of individuals with detectable C-peptide declined beyond the first year after diagnosis, but this was most marked in the youngest age group (<1-year duration: age <7 years: 18 of 20 [90%], 7–12 years: 107 of 110 [97%], ≥13 years: 58 of 61 [95%] vs. 1–5 years postdiagnosis: <7 years: 172 of 522 [33%], 7–12 years: 604 of 995 [61%], ≥13 years: 225 of 289 [78%]). A similar profile was observed in β-cell loss, with those diagnosed at younger ages experiencing more rapid loss of islets containing insulin-positive (insulin+) β-cells <1 year postdiagnosis: age <7 years: 23 of 26 (88%), 7–12 years: 32 of 33 (97%), ≥13 years: 22 of 25 (88%) vs. 1–5 years postdiagnosis: <7 years: 1 of 12 (8.3%), 7–12 years: 7 of 13 (54%), ≥13 years: 7 of 8 (88%). These data should be considered in the planning and interpretation of intervention trials designed to promote β-cell retention and function.

We aim to assess the long-term impact of acute kidney injury (AKI) on progression of diabetic kidney disease (DKD) and all-cause mortality and investigate determinants of AKI in Chinese patients with type 2 diabetes (T2D). A consecutive cohort of 9,096 Chinese patients with T2D from the Hong Kong Diabetes Register was followed for 12 years (mean ± SD age 57 ± 13.2 years; 46.9% men; median duration of diabetes 5 years). AKI was defined based on the Kidney Disease: Improving Global Outcomes (KDIGO) criteria using serum creatinine. Estimated glomerular filtration rate measurements were used to identify the first episode with chronic kidney disease (CKD) and end-stage renal disease (ESRD). Polygenic risk score (PRS) composed of 27 single nucleotide polymorphisms (SNPs) known to be associated with serum uric acid (SUA) in European populations was used to examine the role of SUA in pathogenesis of AKI, CKD, and ESRD. Validation was sought in an independent cohort including 6,007 patients (age 61.2 ± 10.9 years; 59.5% men; median duration of diabetes 10 years). Patients with AKI had a higher risk for developing incident CKD (hazard ratio 14.3 [95% CI 12.69-16.11]), for developing ESRD (12.1 [10.74-13.62]), and for all-cause death (7.99 [7.31-8.74]) compared with those without AKI. Incidence rate for ESRD among patients with no episodes of AKI and one, two, and three or more episodes of AKI was 7.1, 24.4, 32.4, and 37.3 per 1,000 person-years, respectively. Baseline SUA was a strong independent predictor for AKI. A PRS composed of 27 SUA-related SNPs was associated with AKI and CKD in both discovery and replication cohorts but not ESRD. Elevated SUA may increase the risk of DKD through increasing AKI. The identification of SUA as a modifiable risk factor and PRS as a nonmodifiable risk factor may facilitate the identification of individuals at high risk to prevent AKI and its long-term impact in T2D.

AIMS/HYPOTHESIS: a key unanswered question in type 1 diabetes is whether beta cells initiate their own destruction or are victims of an aberrant immune response (beta cell suicide or homicide?). To investigate this, we assessed islet autoantibodies in individuals with congenital beta cell defects causing neonatal diabetes mellitus (NDM). METHODS: We measured autoantibodies to GAD (GADA), islet antigen-2 (IA-2A) and zinc transporter 8 (ZnT8A) in 242 individuals with NDM (median age diagnosed 1.8 months [IQR 0.39-2.9 months]; median age collected 4.6 months [IQR 1.8-27.6 months]; median diabetes duration 2 months [IQR 0.6-23 months]), including 75 whose NDM resulted from severe beta cell endoplasmic reticulum (ER) stress. As a control cohort we also tested samples from 69 diabetes-free individuals (median age collected 9.9 months [IQR 9.0-48.6 months]) for autoantibodies. RESULTS: We found low prevalence of islet autoantibodies in individuals with monogenic NDM; 13/242 (5.4% [95% CI 2.9, 9.0%]) had detectable GADA, IA-2A and/or ZnT8A. This was similar to the proportion in the control participants who did not have diabetes (1/69 positive [1.4%, 95% CI 0.03, 7.8%], p=0.3). Importantly, monogenic individuals with beta cell ER stress had a similar rate of GADA/IA-2A/ZnT8A positivity to non-ER stress aetiologies (2.7% [95% CI 0.3, 9.3%] vs 6.6% [95% CI 3.3, 11.5%] p=0.4). We observed no association between islet autoimmunity and genetic risk, age at testing (including 30 individuals >10 years at testing) or diabetes duration (p>0.4 for all). CONCLUSIONS/INTERPRETATION: Our data support the hypothesis that beta cell stress/dysfunction alone does not lead to the production of islet autoantibodies, even in the context of high-risk HLA types. This suggests that additional factors are required to trigger an autoimmune response towards beta cells.

OBJECTIVE: Genetic risk scores (GRS) aid classification of diabetes type in White European adult populations. We aimed to assess the utility of GRS in the classification of diabetes type among racially/ethnically diverse youth in the U.S. RESEARCH DESIGN AND METHODS: We generated type 1 diabetes (T1D)- and type 2 diabetes (T2D)-specific GRS in 2,045 individuals from the SEARCH for Diabetes in Youth study. We assessed the distribution of genetic risk stratified by diabetes autoantibody positive or negative (DAA+/-) and insulin sensitivity (IS) or insulin resistance (IR) and self-reported race/ethnicity (White, Black, Hispanic, and other). RESULTS: T1D and T2D GRS were strong independent predictors of etiologic type. The T1D GRS was highest in the DAA+/IS group and lowest in the DAA-/IR group, with the inverse relationship observed with the T2D GRS. Discrimination was similar across all racial/ethnic groups but showed differences in score distribution. Clustering by combined genetic risk showed DAA+/IR and DAA-/IS individuals had a greater probability of T1D than T2D. In DAA- individuals, genetic probability of T1D identified individuals most likely to progress to absolute insulin deficiency. CONCLUSIONS: Diabetes type-specific GRS are consistent predictors of diabetes type across racial/ethnic groups in a U.S. youth cohort, but future work needs to account for differences in GRS distribution by ancestry. T1D and T2D GRS may have particular utility for classification of DAA- children.

The year 2021 marks the centennial of Banting and Best's landmark description of the discovery of insulin. This discovery and insulin's rapid clinical deployment effectively transformed type 1 diabetes from a fatal diagnosis into a medically manageable chronic condition. In this Review, we describe key accomplishments leading to and building on this momentous occasion in medical history, including advancements in our understanding of the role of insulin in diabetes pathophysiology, the molecular characterization of insulin and the clinical use of insulin. Achievements are also viewed through the lens of patients impacted by insulin therapy and the evolution of insulin pharmacokinetics and delivery over the past 100 years. Finally, we reflect on the future of insulin therapy and diabetes treatment, as well as challenges to be addressed moving forward, so that the full potential of this transformative discovery may be realized.

AIMS/HYPOTHESIS: Among white European children developing type 1 diabetes, the otherwise common HLA haplotype DR15-DQ6 is rare, and highly protective. Adult-onset type 1 diabetes is now known to represent more overall cases than childhood onset, but it is not known whether DR15-DQ6 is protective in older-adult-onset type 1 diabetes. We sought to quantify DR15-DQ6 protection against type 1 diabetes as age of onset increased. METHODS: in two independent cohorts we assessed the proportion of type 1 diabetes cases presenting through the first 50 years of life with DR15-DQ6, compared with population controls. In the After Diabetes Diagnosis Research Support System-2 (ADDRESS-2) cohort (n = 1458) clinician-diagnosed type 1 diabetes was confirmed by positivity for one or more islet-specific autoantibodies. In UK Biobank (n = 2502), we estimated type 1 diabetes incidence rates relative to baseline HLA risk for each HLA group using Poisson regression. Analyses were restricted to white Europeans and were performed in three groups according to age at type 1 diabetes onset: 0-18 years, 19-30 years and 31-50 years. RESULTS: DR15-DQ6 was protective against type 1 diabetes through to age 50 years (OR 

AbstractClinical classification is essential for estimating disease prevalence but is difficult, often requiring complex investigations. The widespread availability of population level genetic data makes novel genetic stratification techniques a highly attractive alternative. We propose a generalizable mathematical framework for determining disease prevalence within a cohort using genetic risk scores. We compare and evaluate methods based on the means of genetic risk scores’ distributions; the Earth Mover’s Distance between distributions; a linear combination of kernel density estimates of distributions; and an Excess method. We demonstrate the performance of genetic stratification to produce robust prevalence estimates. Specifically, we show that robust estimates of prevalence are still possible even with rarer diseases, smaller cohort sizes and less discriminative genetic risk scores, highlighting the general utility of these approaches. Genetic stratification techniques offer exciting new research tools, enabling unbiased insights into disease prevalence and clinical characteristics unhampered by clinical classification criteria.

Type 1 diabetes (T1D) has a multifactorial autoimmune etiology, involving environmental prompts and polygenic predisposition. We hypothesized that pancreata from individuals with and at risk for T1D would exhibit dysregulated expression of genes associated with monogenic forms of diabetes caused by nonredundant single-gene mutations. Using a "monogenetic transcriptomic strategy," we measured the expression of these genes in human T1D, autoantibody-positive (autoantibody+), and control pancreas tissues with real-time quantitative PCR in accordance with the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines. Gene and protein expression was visualized in situ with use of immunofluorescence, RNAscope, and confocal microscopy. Two dozen monogenic diabetes genes showed altered expression in human pancreata from individuals with T1D versus unaffected control subjects. Six of these genes also saw dysregulation in pancreata from autoantibody+ individuals at increased risk for T1D. As a subset of these genes are related to cellular stress responses, we measured integrated stress response (ISR) genes and identified 20 with altered expression in T1D pancreata, including three of the four eIF2α-dependent kinases. Equally intriguing, we observed significant repression of the three arms of the ISR in autoantibody+ pancreata. Collectively, these efforts suggest monogenic diabetes and ISR genes are dysregulated early in the T1D disease process and likely contribute to the disorder's pathogenesis.

Type 1 diabetes (T1D) is an autoimmune disease in which the insulin-producing β cells of the pancreas are destroyed by T lymphocytes. Recent studies have demonstrated that monitoring for pancreatic islet autoantibodies, combined with genetic risk assessment, can identify most children who will develop T1D when they still have sufficient β cell function to control glucose concentrations without the need for insulin. In addition, there has been recent success in secondary prevention using immunotherapy to delay the progression of preclinical disease, and primary prevention approaches to inhibiting the initiating autoimmune process have entered large-scale clinical trials. By changing the focus of T1D management from late diagnosis and insulin replacement to early diagnosis and β cell preservation, we can anticipate a future without the need for daily insulin injections for children with T1D.

OBJECTIVE: We assessed longitudinal patterns of maternal C-peptide concentration to examine the hypothesis of β-cell regeneration in pregnancy with type 1 diabetes. RESEARCH DESIGN AND METHODS: C-peptide was measured on maternal serum samples from 127 participants (12, 24, and 34 weeks) and cord blood during the Continuous Glucose Monitoring in Women with Type 1 Diabetes in Pregnancy Trial (CONCEPTT). C-peptide was measured using a highly sensitive direct and solid-phase competitive electrochemiluminescent immunoassay. RESULTS: Three discrete patterns of maternal C-peptide trajectory were identified: pattern 1, undetectable throughout pregnancy, n = 74 (58%; maternal C-peptide

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.

AbstractAimsMisclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have recently been developed that can aid classification, but they have not been validated using pancreatic pathology. We evaluated a clinical diagnostic model against histologically defined type 1 diabetes.MethodsWe classified cases from the Network for Pancreatic Organ donors with Diabetes (nPOD) biobank as type 1 (n = 111) or non‐type 1 (n = 42) diabetes using histopathology. Type 1 diabetes was defined by lobular loss of insulin‐containing islets along with multiple insulin‐deficient islets. We assessed the discriminative performance of previously described type 1 diabetes diagnostic models, based on clinical features (age at diagnosis, BMI) and biomarker data [autoantibodies, type 1 diabetes genetic risk score (T1D‐GRS)], and singular features for identifying type 1 diabetes by the area under the curve of the receiver operator characteristic (AUC‐ROC).ResultsDiagnostic models validated well against histologically defined type 1 diabetes. The model combining clinical features, islet autoantibodies and T1D‐GRS was strongly discriminative of type 1 diabetes, and performed better than clinical features alone (AUC‐ROC 0.97 vs. 0.95; P = 0.03). Histological classification of type 1 diabetes was concordant with serum C‐peptide [median < 17 pmol/l (limit of detection) vs. 1037 pmol/l in non‐type 1 diabetes; P < 0.0001].ConclusionsOur study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C‐peptide‐based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible.Parts of this study were presented in abstract form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19–22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6–8 March 2019.

Background: IgA nephropathy (IgAN) is the commonest glomerulonephritis worldwide. Its prevalence is difficult to estimate, as people with mild disease do not commonly receive a biopsy diagnosis. We aimed to generate an IgA nephropathy genetic risk score (IgAN-GRS) and estimate the proportion of people with hematuria who had IgAN in the UK Biobank (UKBB). Methods: We calculated an IgAN-GRS using 14 single-nucleotide polymorphisms (SNPs) drawn from the largest European Genome-Wide Association Study (GWAS) and validated the IgAN-GRS in 464 biopsy-proven IgAN European cases from the UK Glomerulonephritis DNA Bank (UKGDB) and in 379,767 Europeans in the UKBB. We used the mean of IgAN-GRS to calculate the proportion of potential IgAN in 14,181 with hematuria and other nonspecific renal phenotypes from 379,767 Europeans in the UKBB. Results: the IgAN-GRS was higher in the IgAN cohort (4.30; 95% confidence interval [95% CI: 4.23–4.38) than in controls (3.98; 3.97–3.98; P < 0.0001). The mean GRS in UKBB participants with hematuria (n = 12,858) was higher (4.04; 4.02–4.06) than UKBB controls (3.98; 3.97–3.98; P < 0.0001) and higher in those with hematuria, hypertension, and microalbuminuria (n = 1323) (4.07; 4.02–4.13) versus (3.98; 3.97–3.98; P = 0.0003). Using the difference in these means, we estimated that IgAN accounted for 19% of noncancer hematuria and 28% with hematuria, hypertension, and microalbuminuria in UKBB. Conclusions: We used an IgAN-GRS to estimate the prevalence of IgAN contributing to common phenotypes that are not always biopsied. The noninvasive use of polygenic risk in this setting may have further utility to identify likely etiology of nonspecific renal phenotypes in large population cohorts.

The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the "single disease" approach appears untenable, as does the notion of individualizing each single patient's care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.

Abstract
Background
There is much interest in the use of prognostic and diagnostic prediction models in all areas of clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been increasing at the expense of classic statistical models. Previous studies have compared performance between these two approaches but their findings are inconsistent and many have limitations. We aimed to compare the discrimination and calibration of seven models built using logistic regression and optimised machine learning algorithms in a clinical setting, where the number of potential predictors is often limited, and externally validate the models.

Methods
We trained models using logistic regression and six commonly used machine learning algorithms to predict if a patient diagnosed with diabetes has type 1 diabetes (versus type 2 diabetes). We used seven predictor variables (age, BMI, GADA islet-autoantibodies, sex, total cholesterol, HDL cholesterol and triglyceride) using a UK cohort of adult participants (aged 18–50 years) with clinically diagnosed diabetes recruited from primary and secondary care (n = 960, 14% with type 1 diabetes). Discrimination performance (ROC AUC), calibration and decision curve analysis of each approach was compared in a separate external validation dataset (n = 504, 21% with type 1 diabetes).

Results
Average performance obtained in internal validation was similar in all models (ROC AUC ≥ 0.94). In external validation, there were very modest reductions in discrimination with AUC ROC remaining ≥ 0.93 for all methods. Logistic regression had the numerically highest value in external validation (ROC AUC 0.95). Logistic regression had good performance in terms of calibration and decision curve analysis. Neural network and gradient boosting machine had the best calibration performance. Both logistic regression and support vector machine had good decision curve analysis for clinical useful threshold probabilities.

Conclusion
Logistic regression performed as well as optimised machine algorithms to classify patients with type 1 and type 2 diabetes. This study highlights the utility of comparing traditional regression modelling to machine learning, particularly when using a small number of well understood, strong predictor variables.

. OBJECTIVE
. To investigate the impact of residual β-cell function on continuous glucose monitoring (CGM) outcomes following acute exercise in people with type 1 diabetes (T1D).
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. RESEARCH DESIGN AND METHODS
. Thirty participants with T1D for ≥3 years were recruited. First, participants wore a blinded CGM unit for 7 days of free-living data capture. Second, a 3-h mixed-meal test assessed stimulated C-peptide and glucagon. Peak C-peptide was used to allocate participants into undetectable (Cpepund &amp;lt;3 pmol/L), low (Cpeplow 3–200 pmol/L), or high (Cpephigh &amp;gt;200 pmol/L) C-peptide groups. Finally, participants completed 45 min of incline treadmill walking at 60% VO2peak followed by a further 48-h CGM capture.
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.
. RESULTS
. CGM parameters were comparable across groups during the free-living observation week. In the 12- and 24-h postexercise periods (12 h and 24 h), the Cpephigh group had a significantly greater amount of time spent with glucose 3.9–10 mmol/L (12 h, 73.5 ± 27.6%; 24 h, 76.3 ± 19.2%) compared with Cpeplow (12 h, 43.6 ± 26.1%, P = 0.027; 24 h, 52.3 ± 25.0%, P = 0.067) or Cpepund (12 h, 40.6 ± 17.0%, P = 0.010; 24 h, 51.3 ± 22.3%, P = 0.041). Time spent in hyperglycemia (12 h and 24 h glucose &amp;gt;10 and &amp;gt;13.9 mmol/L, P &amp;lt; 0.05) and glycemic variability (12 h and 24 h SD, P &amp;lt; 0.01) were significantly lower in the Cpephigh group compared with Cpepund and Cpeplow. Change in CGM outcomes from pre-exercise to 24-h postexercise was divergent: Cpepund and Cpeplow experienced worsening (glucose 3.9–10 mmol/L: −9.1% and −16.2%, respectively), with Cpephigh experiencing improvement (+12.1%) (P = 0.017).
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.
. CONCLUSIONS
. Residual β-cell function may partially explain the interindividual variation in the acute glycemic benefits of exercise in individuals with T1D. Quantifying C-peptide could aid in providing personalized and targeted support for exercising patients.
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Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The ‘palette model’ and the ‘threshold hypothesis’ can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. [Figure not available: see fulltext.]

AbstractType 1 diabetes (T1D) is a significant problem in Indians and misclassification of T1D and type 2 diabetes (T2D) is a particular problem in young adults in this population due to the high prevalence of early onset T2D at lower BMI. We have previously shown a genetic risk score (GRS) can be used to discriminate T1D from T2D in Europeans. We aimed to test the ability of a T1D GRS to discriminate T1D from T2D and controls in Indians. We studied subjects from Pune, India of Indo-European ancestry; T1D (n = 262 clinically defined, 200 autoantibody positive), T2D (n = 345) and controls (n = 324). We used the 9 SNP T1D GRS generated in Europeans and assessed its ability to discriminate T1D from T2D and controls in Indians. We compared Indians with Europeans from the Wellcome Trust Case Control Consortium study; T1D (n = 1963), T2D (n = 1924) and controls (n = 2938). The T1D GRS was discriminative of T1D from T2D in Indians but slightly less than in Europeans (ROC AUC 0.84 v 0.87, p &lt; 0.0001). HLA SNPs contributed the majority of the discriminative power in Indians. A T1D GRS using SNPs defined in Europeans is discriminative of T1D from T2D and controls in Indians. As with Europeans, the T1D GRS may be useful for classifying diabetes in Indians.

Heat shock protein 90 (Hsp90) is a protein chaperone that is upregulated and released from pancreatic β cells under pro-inflammatory conditions. We hypothesized that serum Hsp90 may have utility as a biomarker of type 1 diabetes risk and exhibit elevations before the onset of clinically significant hyperglycemia. To this end, total levels of the alpha cytoplasmic isoform of Hsp90 were assayed in autoantibody-positive progressors to type 1 diabetes using banked serum samples from the TrialNet Pathway to Prevention Cohort that had been collected 12 months prior to diabetes onset, with comparison to age, sex, and BMI-category matched autoantibody-positive nonprogressors and healthy controls. Hsp90 levels were higher in autoantibody-positive progressors and nonprogressors ≤ 18 years of age compared to matched healthy controls. However, Hsp90 levels were not different between progressors and nonprogressors in any age group. Hsp90 was positively correlated with age in control subjects, but this correlation was absent in autoantibody positive individuals. In aggregate these data indicate that elevated Hsp90 levels are present in youth with β cell autoimmunity, but are not able to distinguish youth or adult type 1 diabetes progressors from nonprogressors in samples collected 12 months prior to diabetes development.

Histological analysis of donor pancreases coupled with measurement of serum C-peptide in clinical cohorts has challenged the idea that all beta cells are eventually destroyed in type 1 diabetes. These findings have raised a number of questions regarding how the remaining beta cells have escaped immune destruction, whether pools of 'sleeping' or dysfunctional beta cells could be rejuvenated and whether there is potential for new growth of beta cells. In this Review, we describe histological and in vivo evidence of persistent beta cells in type 1 diabetes and discuss the limitations of current methods to distinguish underlying beta cell mass in comparison with beta cell function. We highlight that evidence for new beta cell growth in humans many years from diagnosis is limited, and that this growth may be very minimal if at all present. We review recent contributions to the debate around beta cell abnormalities contributing to the pathogenesis of type 1 diabetes. We also discuss evidence for restoration of beta cell function, as opposed to mass, in recent-onset type 1 diabetes, but highlight the absence of data supporting functional recovery in the setting of long-duration diabetes. Finally, future areas of research are suggested to help resolve the source and phenotype of residual beta cells that persist in some, but not all, people with type 1 diabetes.

PURPOSE OF REVIEW: the genetic risk for type 1 diabetes has been studied for over half a century, with the strong genetic associations of type 1 diabetes forming critical evidence for the role of the immune system in pathogenesis. In this review, we discuss some of the original research leading to recent developments in type 1 diabetes genetics. RECENT FINDINGS: We examine the translation of polygenic scores for type 1 diabetes into tools for prediction and diagnosis of type 1 diabetes, in particular, when used in combination with other biomarkers and clinical features, such as age and islet-specific autoantibodies. Furthermore, we review the description of age associations with type 1 diabetes genetic risk, and the investigation of loci linked to type 2 diabetes in progression of type 1 diabetes. Finally, we consider current limitations, including the scarcity of data from racial and ethnic minorities, and future directions. SUMMARY: the development of polygenic risk scores has allowed the integration of type 1 diabetes genetics into diagnosis and prediction. Emerging information on the role of specific genes in subgroups of individuals with the disease, for example, early-onset, mild autoimmunity, and so forth, is facilitating our understanding of the heterogeneity of type 1 diabetes, with the ultimate goal of using genetic information in research and clinical practice.

AIMS: Most people with Type 1 diabetes have low levels of persistent endogenous insulin production. The Diabetes Control and Complications Trial showed that close to diagnosis preserved endogenous insulin was associated with lower HbA1c , hypoglycaemia and complication rates, when intensively treated. We aimed to assess the clinical impact of persistent C-peptide on rate of hypoglycaemia and HbA1c in those with long duration (> 5 years) Type 1 diabetes. METHODS: We conducted a cross-sectional case-control study of 221 people (median age 24 years) with Type 1 diabetes. We confirmed ongoing endogenous insulin secretion by measuring C-peptide after a mixed-meal tolerance test. We compared self-reported hypoglycaemia (n = 160), HbA1c , insulin dose and microvascular complications (n = 140) in those with preserved and low C-peptide. RESULTS: Stimulated median (IQR) C-peptide was 114 (43, 273) pmol/l and

. OBJECTIVE
. We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals.
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. RESEARCH DESIGN AND METHODS
. We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients’ relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2–51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial–Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables.
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. RESULTS
. Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06–1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS &amp;gt;0.295, 95% CI 1.47–3.51; P = 0.0002).
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. CONCLUSIONS
. The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.
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Prior studies identified HLA class-II and 57 additional loci as contributors to genetic susceptibility for type 1 diabetes (T1D). We hypothesized that race and/or ethnicity would be contextually important for evaluating genetic risk markers previously identified from Caucasian/European cohorts. We determined the capacity for a combined genetic risk score (GRS) to discriminate disease-risk subgroups in a racially and ethnically diverse cohort from the southeastern U.S. including 637 T1D patients, 46 at-risk relatives having two or more T1D-related autoantibodies (≥2AAb+), 790 first-degree relatives (≤1AAb+), 68 second-degree relatives (≤1 AAb+), and 405 controls. GRS was higher among Caucasian T1D and at-risk subjects versus ≤ 1AAb+ relatives or controls (P 

OBJECTIVES: Careful selection for clinical islet transplantation (CIT) is required because of limited organ supply and the risks for lifelong immunosuppression. However, the indications for this novel treatment may not be widely known, and selection criteria continue to evolve. We sought to describe the pattern of referrals to our centre and the most common factors determining eligibility for CIT. METHODS: We performed a retrospective chart review of all applications for CIT received at the University of Alberta between May 2009 and April 2012. Demographics and clinical data were abstracted along with the sources of referral. Application results and reasons for eligibility or ineligibility were determined. For ineligible subjects, the primary reason for ineligibility was noted. RESULTS: We received 246 applications (mean age 43; range, 13 to 78 years; 54% male) from across Canada. The majority (81%) were self-referrals, with the remainder coming from specialists (15%) or primary care physicians (4%). of the applicants, 19% were deemed eligible and were accepted for waitlisting. Acceptance rates were not different between physician referrals and self-referrals (25% vs. 18%; p=ns). The main reasons for ineligibility were no indication (39%); contraindications (metabolic, 21%; medical comorbidity, 17%; psychosocial, 8%) or personal factors (15%). CONCLUSIONS: Most referrals were received from people with diabetes, but acceptance rates were not significantly lower than for physician referrals. It will be important to increase awareness of severe hypoglycemia or glycemic lability as major indications for CIT among patients and physicians and to evaluate any impact this may have on the current acceptance rate of 19%.

Type 1 diabetes (T1D) is a chronic disease of high blood glucose caused by autoimmune destruction of pancreatic beta cells eventually resulting in severe insulin deficiency. T1D has a significant heritable risk. Genetic associations found are particularly strong in the HLA class II region but T1D is a polygenic disease associated with over 60 loci across the genome. Polygenic risk scores are one method of summing these genetic risk elements as a single continuous variable. This review discusses the clinical and research utility of genetic risk scores in T1D particularly in disease prediction and progression. We also explore creative uses of genetic risk scores in big data and the limitations of using a genetic risk score. The increase in publically available genetic data and rapid fall in costs of genotyping mean that a T1D genetic risk score (T1D GRS) is likely to prove useful for disease prediction, discrimination, investigation of unusual cohorts, and investigation of biology in large datasets where genetic data are available.

BACKGROUND: Type 1 diabetes is typically considered a disease of children and young adults. Genetic susceptibility to young-onset type 1 diabetes is well defined and does not predispose to type 2 diabetes. It is not known how frequently genetic susceptibility to type 1 diabetes leads to a diagnosis of diabetes after age 30 years. We aimed to investigate the frequency and phenotype of type 1 diabetes resulting from high genetic susceptibility in the first six decades of life. METHODS: in this cross-sectional analysis, we used a type 1 diabetes genetic risk score based on 29 common variants to identify individuals of white European descent in UK Biobank in the half of the population with high or low genetic susceptibility to type 1 diabetes. We used Kaplan-Meier analysis to evaluate the number of cases of diabetes in both groups in the first six decades of life. We genetically defined type 1 diabetes as the additional cases of diabetes that occurred in the high genetic susceptibility group compared with the low genetic susceptibility group. All remaining cases were defined as type 2 diabetes. We assessed the clinical characteristics of the groups with genetically defined type 1 or type 2 diabetes. FINDINGS: 13 250 (3·5%) of 379 511 white European individuals in UK Biobank had developed diabetes in the first six decades of life. 1286 more cases of diabetes were in the half of the population with high genetic susceptibility to type 1 diabetes than in the half of the population with low genetic susceptibility. These genetically defined cases of type 1 diabetes were distributed across all ages of diagnosis; 537 (42%) were in individuals diagnosed when aged 31-60 years, representing 4% (537/12 233) of all diabetes cases diagnosed after age 30 years. The clinical characteristics of the group diagnosed with type 1 diabetes when aged 31-60 years were similar to the clinical characteristics of the group diagnosed with type 1 diabetes when aged 30 years or younger. For individuals diagnosed with diabetes when aged 31-60 years, the clinical characteristics of type 1 diabetes differed from those of type 2 diabetes: they had a lower BMI (27·4 kg/m2 [95% CI 26·7-28·0] vs 32·4 kg/m2 [32·2-32·5]; p

BACKGROUND: Around 0.3% of newborns will develop autoimmunity to pancreatic beta cells in childhood and subsequently develop type 1 diabetes before adulthood. Primary prevention of type 1 diabetes will require early intervention in genetically at-risk infants. The objective of this study was to determine to what extent genetic scores (two previous genetic scores and a merged genetic score) can improve the prediction of type 1 diabetes. METHODS AND FINDINGS: the Environmental Determinants of Diabetes in the Young (TEDDY) study followed genetically at-risk children at 3- to 6-monthly intervals from birth for the development of islet autoantibodies and type 1 diabetes. Infants were enrolled between 1 September 2004 and 28 February 2010 and monitored until 31 May 2016. The risk (positive predictive value) for developing multiple islet autoantibodies (pre-symptomatic type 1 diabetes) and type 1 diabetes was determined in 4,543 children who had no first-degree relatives with type 1 diabetes and either a heterozygous HLA DR3 and DR4-DQ8 risk genotype or a homozygous DR4-DQ8 genotype, and in 3,498 of these children in whom genetic scores were calculated from 41 single nucleotide polymorphisms. In the children with the HLA risk genotypes, risk for developing multiple islet autoantibodies was 5.8% (95% CI 5.0%-6.6%) by age 6 years, and risk for diabetes by age 10 years was 3.7% (95% CI 3.0%-4.4%). Risk for developing multiple islet autoantibodies was 11.0% (95% CI 8.7%-13.3%) in children with a merged genetic score of >14.4 (upper quartile; n = 907) compared to 4.1% (95% CI 3.3%-4.9%, P < 0.001) in children with a genetic score of ≤14.4 (n = 2,591). Risk for developing diabetes by age 10 years was 7.6% (95% CI 5.3%-9.9%) in children with a merged score of >14.4 compared with 2.7% (95% CI 1.9%-3.6%) in children with a score of ≤14.4 (P < 0.001). of 173 children with multiple islet autoantibodies by age 6 years and 107 children with diabetes by age 10 years, 82 (sensitivity, 47.4%; 95% CI 40.1%-54.8%) and 52 (sensitivity, 48.6%, 95% CI 39.3%-60.0%), respectively, had a score >14.4. Scores were higher in European versus US children (P = 0.003). In children with a merged score of >14.4, risk for multiple islet autoantibodies was similar and consistently >10% in Europe and in the US; risk was greater in males than in females (P = 0.01). Limitations of the study include that the genetic scores were originally developed from case-control studies of clinical diabetes in individuals of mainly European decent. It is, therefore, possible that it may not be suitable to all populations. CONCLUSIONS: a type 1 diabetes genetic score identified infants without family history of type 1 diabetes who had a greater than 10% risk for pre-symptomatic type 1 diabetes, and a nearly 2-fold higher risk than children identified by high-risk HLA genotypes alone. This finding extends the possibilities for enrolling children into type 1 diabetes primary prevention trials.

AIMS/HYPOTHESIS: the aim of this study was to identify genetic variants associated with beta cell function in type 1 diabetes, as measured by serum C-peptide levels, through meta-genome-wide association studies (meta-GWAS). METHODS: We performed a meta-GWAS to combine the results from five studies in type 1 diabetes with cross-sectionally measured stimulated, fasting or random C-peptide levels, including 3479 European participants. The p values across studies were combined, taking into account sample size and direction of effect. We also performed separate meta-GWAS for stimulated (n = 1303), fasting (n = 2019) and random (n = 1497) C-peptide levels. RESULTS: in the meta-GWAS for stimulated/fasting/random C-peptide levels, a SNP on chromosome 1, rs559047 (Chr1:238753916, T>A, minor allele frequency [MAF] 0.24-0.26), was associated with C-peptide (p = 4.13 × 10-8), meeting the genome-wide significance threshold (p T, MAF 0.07-0.10, p = 8.43 × 10-8). In the stimulated C-peptide meta-GWAS, rs61211515 (Chr6:30100975, T/-, MAF 0.17-0.19) in the MHC region was associated with stimulated C-peptide (β [SE] = - 0.39 [0.07], p = 9.72 × 10-8). rs61211515 was also associated with the rate of stimulated C-peptide decline over time in a subset of individuals (n = 258) with annual repeated measures for up to 6 years (p = 0.02). In the meta-GWAS of random C-peptide, another MHC region, SNP rs3135002 (Chr6:32668439, C>A, MAF 0.02-0.06), was associated with C-peptide (p = 3.49 × 10-8). Conditional analyses suggested that the three identified variants in the MHC region were independent of each other. rs9260151 and rs3135002 have been associated with type 1 diabetes, whereas rs559047 and rs61211515 have not been associated with a risk of developing type 1 diabetes. CONCLUSIONS/INTERPRETATION: We identified a locus on chromosome 1 and multiple variants in the MHC region, at least some of which were distinct from type 1 diabetes risk loci, that were associated with C-peptide, suggesting partly non-overlapping mechanisms for the development and progression of type 1 diabetes. These associations need to be validated in independent populations. Further investigations could provide insights into mechanisms of beta cell loss and opportunities to preserve beta cell function.

Type 1 diabetes is a chronic autoimmune disease characterised by insulin deficiency and resultant hyperglycaemia. Knowledge of type 1 diabetes has rapidly increased over the past 25 years, resulting in a broad understanding about many aspects of the disease, including its genetics, epidemiology, immune and β-cell phenotypes, and disease burden. Interventions to preserve β cells have been tested, and several methods to improve clinical disease management have been assessed. However, wide gaps still exist in our understanding of type 1 diabetes and our ability to standardise clinical care and decrease disease-associated complications and burden. This Seminar gives an overview of the current understanding of the disease and potential future directions for research and care.

PURPOSE OF REVIEW: About 50% of the heritability of type 1 diabetes (T1D) is attributed to human leukocyte antigen (HLA) alleles and the remainder to several (close to 50) non-HLA loci. A current challenge in the field of the genetics of T1D is to apply the knowledge accumulated in the last 40 years towards differential diagnosis and risk assessment. RECENT FINDINGS: T1D genetic risk scores seek to combine the information from HLA and non-HLA alleles to improve the accuracy of diagnosis, prediction, and prognosis. Here, we describe genetic risk scores that have been developed and validated in various settings and populations. Several genetic scores have been proposed that merge disease risk information from multiple genetic factors to optimize the use of genetic information and ultimately improve prediction and diagnosis of T1D.

OBJECTIVE: with rising obesity, it is becoming increasingly difficult to distinguish between type 1 diabetes (T1D) and type 2 diabetes (T2D) in young adults. There has been substantial recent progress in identifying the contribution of common genetic variants to T1D and T2D. We aimed to determine whether a score generated from common genetic variants could be used to discriminate between T1D and T2D and also to predict severe insulin deficiency in young adults with diabetes. RESEARCH DESIGN AND METHODS: We developed genetic risk scores (GRSs) from published T1D- and T2D-associated variants. We first tested whether the scores could distinguish clinically defined T1D and T2D from the Wellcome Trust Case Control Consortium (WTCCC) (n = 3,887). We then assessed whether the T1D GRS correctly classified young adults (diagnosed at 20-40 years of age, the age-group with the most diagnostic difficulty in clinical practice; n = 223) who progressed to severe insulin deficiency 0.280 (>50th centile in those with T1D) is indicative of T1D (50% sensitivity, 95% specificity). A low T1D GRS (

BACKGROUND AND AIMS: Nephrotoxicity is a rare idiosyncratic reaction to 5-aminosalicylate (5-ASA) therapies. The aims of this study were to describe the clinical features of this complication and identify clinically useful genetic markers so that these drugs can be avoided or so that monitoring can be intensified in high-risk patients. METHODS: Inflammatory bowel disease patients were recruited from 89 sites around the world. Inclusion criteria included normal renal function prior to commencing 5-ASA, ≥50% rise in creatinine any time after starting 5-ASA, and physician opinion implicating 5-ASA strong enough to justify drug withdrawal. An adjudication panel identified definite and probable cases from structured case report forms. A genome-wide association study was then undertaken with these cases and 4109 disease controls. RESULTS: After adjudication, 151 cases of 5-ASA-induced nephrotoxicity were identified. Sixty-eight percent of cases were males, with nephrotoxicity occurring at a median age of 39.4 years (range 6-79 years). The median time for development of renal injury after commencing 5-ASA was 3.0 years (95% confidence interval [CI] 2.3-3.7). Only 30% of cases recovered completely after drug withdrawal, with 15 patients requiring permanent renal replacement therapy. A genome-wide association study identified a suggestive association in the HLA region (p = 1×10(-7)) with 5-ASA-induced nephrotoxicity. A sub-group analysis of patients who had a renal biopsy demonstrating interstitial nephritis (n = 55) significantly strengthened this association (p = 4×10(-9), odds ratio 3.1). CONCLUSIONS: This is the largest and most detailed study of 5-ASA-induced nephrotoxicity to date. It highlights the morbidity associated with this condition and identifies for the first time a significant genetic predisposition to drug-induced renal injury.

Maturity onset diabetes of the young (MODY) is a rare but increasingly recognized cause of diabetes in young people. It is a monogenic disorder that typically presents at

OBJECTIVE: Monogenic diabetes is rare but is an important diagnosis in pediatric diabetes clinics. These patients are often not identified as this relies on the recognition of key clinical features by an alert clinician. Biomarkers (islet autoantibodies and C-peptide) can assist in the exclusion of patients with type 1 diabetes and allow systematic testing that does not rely on clinical recognition. Our study aimed to establish the prevalence of monogenic diabetes in U.K. pediatric clinics using a systematic approach of biomarker screening and targeted genetic testing. RESEARCH DESIGN AND METHODS: We studied 808 patients (79.5% of the eligible population)

Distinguishing patients with monogenic diabetes from those with type 1 diabetes (T1D) is important for correct diagnosis, treatment, and selection of patients for gene discovery studies. We assessed whether a T1D genetic risk score (T1D-GRS) generated from T1D-associated common genetic variants provides a novel way to discriminate monogenic diabetes from T1D. The T1D-GRS was highly discriminative of proven maturity-onset diabetes of young (MODY) (n = 805) and T1D (n = 1,963) (receiver operating characteristic area under the curve 0.87). A T1D-GRS of &amp;gt;0.280 (&amp;gt;50th T1D centile) was indicative of T1D (94% specificity, 50% sensitivity). We then analyzed the T1D-GRS of 242 white European patients with neonatal diabetes (NDM) who had been tested for all known NDM genes. Monogenic NDM was confirmed in 90, 59, and 8% of patients with GRS &amp;lt;5th T1D centile, 50–75th T1D centile, and &amp;gt;75th T1D centile, respectively. Applying a GRS 50th T1D centile cutoff in 48 NDM patients with no known genetic cause identified those most likely to have a novel monogenic etiology by highlighting patients with probable early-onset T1D (GRS &amp;gt;50th T1D centile) who were diagnosed later and had less syndromic presentation but additional autoimmune features compared with those with proven monogenic NDM. The T1D-GRS is a novel tool to improve the use of biomarkers in the discrimination of monogenic diabetes from T1D.

OBJECTIVE: Maintenance of endogenous pancreatic β-cell function could be an important goal in the management of type 1 diabetes. However, the impact of stimulated C-peptide level on overall glycemic control is unknown. The relationship between C-peptide and parameters of glucose control was therefore characterized in a cohort with rapidly changing β-cell function following islet transplantation. RESEARCH DESIGN AND METHODS: Standardized mixed-meal tolerance test was undertaken in 12 consecutive islet recipients at 1-6-month intervals, with graft function determined by 90-min stimulated C-peptide. Continuous glucose monitoring was undertaken in the week preceding each assessment and the relationship between C-peptide and glucose control evaluated by mixed Poisson regression. RESULTS: Recipients completed 5 (1-14) [median (range)] clinical assessments over 18 (1-51) months posttransplant encompassing a wide range of stimulated C-peptide levels (7-2,622 pmol/L). Increasing β-cell function across predefined C-peptide groups was associated with reduced insulin dose, HbA1c, mean glucose (low [1,000 pmol/L] 7.5 mmol/L), and glucose SD (low, 4.4 vs. excellent, 1.4 mmol/L). Highly statistically significant continuous associations between stimulated C-peptide and mean interstitial glucose (lower by 2.5% [95% CI 1.5-3.5%] per 100 pmol/L higher C-peptide), glucose SD, time outside glucose target range, and measures of hyper-/hypoglycemia risk were confirmed. CONCLUSIONS: Repeated assessment of islet transplant recipients has enabled modeling of the relationship between endogenous β-cell function and measures of glycemic control providing quantitative estimates of likely impact of an acute change in β-cell function in individuals with type 1 diabetes.

OBJECTIVE: Small studies using ultrasensitive C-peptide assays suggest endogenous insulin secretion is frequently detectable in patients with long-standing type 1 diabetes (T1D), but these studies do not use representative samples. We aimed to use the stimulated urine C-peptide-to-creatinine ratio (UCPCR) to assess C-peptide levels in a large cross-sectional, population-based study of patients with T1D. RESEARCH DESIGN AND METHODS: We recruited 924 patients from primary and secondary care in two U.K. centers who had a clinical diagnosis of T1D, were under 30 years of age when they received a diagnosis, and had a diabetes duration of >5 years. The median age at diagnosis was 11 years (interquartile range 6-17 years), and the duration of diabetes was 19 years (11-27 years). All provided a home postmeal UCPCR, which was measured using a Roche electrochemiluminescence assay. RESULTS: Eighty percent of patients (740 of 924 patients) had detectable endogenous C-peptide levels (UCPCR >0.001 nmol/mmol). Most patients (52%, 483 of 924 patients) had historically very low undetectable levels (UCPCR 0.0013-0.03 nmol/mmol); 8% of patients (70 of 924 patients) had a UCPCR ≥0.2 nmol/mmol, equivalent to serum levels associated with reduced complications and hypoglycemia. Absolute UCPCR levels fell with duration of disease. Age at diagnosis and duration of disease were independent predictors of C-peptide level in multivariate modeling. CONCLUSIONS: This population-based study shows that the majority of long-duration T1D patients have detectable urine C-peptide levels. While the majority of patients are insulin microsecretors, some maintain clinically relevant endogenous insulin secretion for many years after the diagnosis of diabetes. Understanding this may lead to a better understanding of pathogenesis in T1D and open new possibilities for treatment.

OBJECTIVE: Islet graft function is defined by serum C-peptide in a standardized challenge test. We assessed whether urine C-peptide creatinine ratio (UCPCR) sent from home could provide a viable alternative. RESEARCH DESIGN AND METHODS: Seventeen islet recipients provided 90-min serum C-peptide (sCP90) and 120-min UCPCR (UCPCR120) samples during 68 interval posttransplant mixed-meal tolerance tests, also posting from home a 120-min postbreakfast UCPCR sample every 2 weeks. UCPCR was compared with a clinical score of islet function, derived from HbA1c and insulin dose. RESULTS: UCPCR120 and mean home postmeal UCPCR were strongly correlated with sCP90 (r(s) = 0.73, P < 0.001; and rs = 0.73, P < 0.01, respectively). Mean home UCPCR increased with clinical score (r(s) = 0.75; P < 0.001) and with graft function defined both by sCP90 >200 pmol/L and insulin independence. UCPCR cutoffs to detect insulin independence and poor graft function were sensitive and specific. CONCLUSIONS: Home UCPCR provides a valid measure of C-peptide production in islet transplant recipients.

BACKGROUND: Mutation specific effects in monogenic disorders are rare. We describe atypical Fanconi syndrome caused by a specific heterozygous mutation in HNF4A. Heterozygous HNF4A mutations cause a beta cell phenotype of neonatal hyperinsulinism with macrosomia and young onset diabetes. Autosomal dominant idiopathic Fanconi syndrome (a renal proximal tubulopathy) is described but no genetic cause has been defined. METHODS AND RESULTS: We report six patients heterozygous for the p.R76W HNF4A mutation who have Fanconi syndrome and nephrocalcinosis in addition to neonatal hyperinsulinism and macrosomia. All six displayed a novel phenotype of proximal tubulopathy, characterised by generalised aminoaciduria, low molecular weight proteinuria, glycosuria, hyperphosphaturia and hypouricaemia, and additional features not seen in Fanconi syndrome: nephrocalcinosis, renal impairment, hypercalciuria with relative hypocalcaemia, and hypermagnesaemia. This was mutation specific, with the renal phenotype not being seen in patients with other HNF4A mutations. In silico modelling shows the R76 residue is directly involved in DNA binding and the R76W mutation reduces DNA binding affinity. The target(s) selectively affected by altered DNA binding of R76W that results in Fanconi syndrome is not known. CONCLUSIONS: the HNF4A R76W mutation is an unusual example of a mutation specific phenotype, with autosomal dominant atypical Fanconi syndrome in addition to the established beta cell phenotype.

Aims/hypothesis: Classically, type 1 diabetes is thought to proceed to absolute insulin deficiency. Recently developed ultrasensitive assays capable of detecting C-peptide under 5 pmol/l now allow very low levels of C-peptide to be detected in patients with long-standing type 1 diabetes. It is not known whether this low-level endogenous insulin secretion responds to physiological stimuli. We aimed to assess how commonly low-level detectable C-peptide occurs in long-duration type 1 diabetes and whether it responds to a meal stimulus. Methods: We performed a mixed-meal tolerance test in 74 volunteers with long-duration (>5 years) type 1 diabetes, i.e. with age at diagnosis 16 (9-23) years (median [interquartile range]) and diabetes duration of 30 (19-41) years. We assessed fasting and stimulated serum C-peptide levels using an electrochemiluminescence assay (detection limit 3.3 pmol/l), and also the urinary C-peptide:creatinine ratio (UCPCR). Results: Post-stimulation serum C-peptide was detectable at very low levels (>3.3 pmol/l) in 54 of 74 (73%) patients. In all patients with detectable serum C-peptide, C-peptide either increased (n = 43, 80%) or stayed the same (n = 11) in response to a meal, with no indication of levels falling (p < 0.0001). With increasing disease duration, absolute C-peptide levels fell although the numbers with detectable C-peptide remained high (68%, i.e. 25 of 37 patients with >30 years duration). Similar results were obtained for UCPCR. Conclusions/interpretation: Most patients with long-duration type 1 diabetes continue to secrete very low levels of endogenous insulin, which increase after meals. This is consistent with the presence of a small number of still functional beta cells and implies that beta cells are either escaping immune attack or undergoing regeneration. © 2013 the Author(s).

DNA polymerase δ, whose catalytic subunit is encoded by POLD1, is responsible for lagging-strand DNA synthesis during DNA replication. It carries out this synthesis with high fidelity owing to its intrinsic 3'- to 5'-exonuclease activity, which confers proofreading ability. Missense mutations affecting the exonuclease domain of POLD1 have recently been shown to predispose to colorectal and endometrial cancers. Here we report a recurring heterozygous single-codon deletion in POLD1 affecting the polymerase active site that abolishes DNA polymerase activity but only mildly impairs 3'- to 5'-exonuclease activity. This mutation causes a distinct multisystem disorder that includes subcutaneous lipodystrophy, deafness, mandibular hypoplasia and hypogonadism in males. This discovery suggests that perturbing the function of the ubiquitously expressed POLD1 polymerase has unexpectedly tissue-specific effects in humans and argues for an important role for POLD1 function in adipose tissue homeostasis. © 2013 Nature America, Inc. All rights reserved.

DNA polymerase δ, whose catalytic subunit is encoded by POLD1, is responsible for lagging-strand DNA synthesis during DNA replication. It carries out this synthesis with high fidelity owing to its intrinsic 3'- to 5'-exonuclease activity, which confers proofreading ability. Missense mutations affecting the exonuclease domain of POLD1 have recently been shown to predispose to colorectal and endometrial cancers. Here we report a recurring heterozygous single-codon deletion in POLD1 affecting the polymerase active site that abolishes DNA polymerase activity but only mildly impairs 3'- to 5'-exonuclease activity. This mutation causes a distinct multisystem disorder that includes subcutaneous lipodystrophy, deafness, mandibular hypoplasia and hypogonadism in males. This discovery suggests that perturbing the function of the ubiquitously expressed POLD1 polymerase has unexpectedly tissue-specific effects in humans and argues for an important role for POLD1 function in adipose tissue homeostasis.

AIMS: Hepatocyte nuclear factor 1β (HNF1B) mutations cause a syndrome of renal cysts and diabetes, with whole gene deletions accounting for approximately 50% of cases. The severity of the renal phenotype is variable, from enlarged cystic kidneys incompatible with life to normal renal development and function. We investigated the prevalence of HNF1B deletions in patients with diabetes but no known renal disease. METHODS: We tested 461 patients with familial diabetes diagnosed before 45 years, including 258 probands who met clinical criteria for maturity-onset diabetes of the young (two generations affected and at least one family member diagnosed under 25 years). A fluorescent polymerase chain reaction assay was used to analyse two intragenic polymorphic HNF1B markers and identify heterozygous patients who therefore did not have whole gene deletions. Those patients homozygous for both markers were then tested for an HNF1B deletion using multiplex ligation-dependent probe amplification. RESULTS: Heterozygous HNF1B intragenic polymorphisms were identified in 337/461 subjects. Multiplex ligation-dependent probe amplification analysis showed an HNF1B gene deletion in three of the remaining 124 probands, all of whom met the criteria for maturity-onset diabetes of the young. Testing of their relatives identified three additional deletion carriers and ultrasound scanning showed renal developmental abnormalities in three of these six patients. CONCLUSIONS: We estimate that HNF1B mutations account for < 1% of cases of maturity-onset diabetes of the young. Although HNF1B mutations are a rare cause of diabetes in the absence of known renal disease, a genetic diagnosis of renal cysts and diabetes syndrome is important as it raises the possibility of subclinical renal disease and the 50% risk of renal cysts and diabetes syndrome in the patient's offspring.

OBJECTIVES: the current assessment of insulin resistance (IR) in epidemiology studies relies on the blood measurement of C-peptide or insulin. A urine C-peptide creatinine ratio (UCPCR) can be posted from home unaided. It is validated against serum measures of the insulin in people with diabetes. We tested whether UCPCR could be a surrogate measure of IR by examining the correlation of UCPCR with serum insulin, C-peptide and HOMA2 (Homeostasis Model Assessment 2)-IR in participants without diabetes and with chronic kidney disease (CKD). DESIGN: Observational study. SETTING: Single-centre clinical research facility. PARTICIPANTS: 37 healthy volunteers and 30 patients with CKD (glomerular filtration rate 15-60) were recruited. PRIMARY AND SECONDARY ENDPOINTS: Serum insulin, C-peptide and glucose at fasting (0), 30, 60, 90 and 120 min were measured during an oral glucose tolerance test (OGTT). Second-void fasting UCPCR and 120 min post-OGTT UCPCR were collected. HOMA2-IR was calculated using fasting insulin and glucose. The associations between UCPCR and serum measures were assessed using Spearman's correlations. RESULTS: in healthy volunteers, fasting second-void UCPCR strongly correlated with serum insulin (rs=0.69, p

AIMS: Serum C-peptide measurement can assist clinical management of diabetes, but practicalities of collection limit widespread use. Urine C-peptide creatinine ratio may be a non-invasive practical alternative. The stability of C-peptide in urine allows outpatient or community testing. We aimed to assess how urine C-peptide creatinine ratio compared with serum C-peptide measurement during a mixed-meal tolerance test in individuals with late-onset, insulin-treated diabetes. METHODS: We correlated the gold standard of a stimulated serum C-peptide in a mixed-meal tolerance test with fasting and stimulated (mixed-meal tolerance test, standard home meal and largest home meal) urine C-peptide creatinine ratio in 51 subjects with insulin-treated diabetes (diagnosis after age 30 years, median age 66 years, median age at diagnosis 54, 42 with Type 2 diabetes, estimated glomerular filtration rate > 60 ml min(-1) 1.73 m(-2) ). RESULTS: Ninety-minute mixed-meal tolerance test serum C-peptide is correlated with mixed-meal tolerance test-stimulated urine C-peptide creatinine ratio (r = 0.82), urine C-peptide creatinine ratio after a standard breakfast at home (r = 0.73) and urine C-peptide creatinine ratio after largest home meal (r = 0.71). A stimulated (largest home meal) urine C-peptide creatinine ratio cut-off of 0.3 nmol/mmol had a 100% sensitivity and 96% specificity (area under receiver operating characteristic curve = 0.99) in identifying subjects without clinically significant endogenous insulin secretion (mixed-meal tolerance test-stimulated C-peptide < 0.2 nmol/l). In detecting a proposed serum C-peptide threshold for insulin requirement (stimulated serum C-peptide < 0.6 nmol/l), a stimulated (largest home meal) urine C-peptide creatinine ratio cut-off of 0.6 nmol/mmol had a sensitivity and specificity of 92%. CONCLUSION: in patients with insulin-treated diabetes diagnosed after age 30 years, urine C-peptide creatinine ratio is well correlated with serum C-peptide and may provide a practical alternative measure to detect insulin deficiency for use in routine clinical practice.

OBJECTIVE: Congenital uterine abnormalities are common and may be associated with developmental renal abnormalities. Mutations of the hepatocyte nuclear factor-1β (HNF1B) gene are associated with renal and uterine abnormalities. We aimed to study the role of HNF1B mutations in a cohort with congenital uterine abnormalities. STUDY DESIGN: We tested 108 probands with uterine abnormalities for HNF1B mutations. We collected clinical information from patient records. RESULTS: Nine of 108 women (8%) had a mutation or deletion in the HNF1B gene. Abnormal HNF1B was found in 18% of the 50 probands who had both uterine and renal abnormalities but in none of the 58 women with isolated uterine abnormalities. CONCLUSION: Mutations of the HNF1B gene are found in women with both uterine and renal abnormalities but are rare in isolated uterine abnormalities. We suggest that HNF1B testing should be performed in patients with both renal and uterine abnormalities, but not in patients with isolated uterine abnormalities.

BACKGROUND: Hepatocyte nuclear factor-1beta (HNF-1beta) is a critical transcription factor in pancreatic and renal development. Our previous report identified HNF-1beta mutations in 23/160 patients with unexplained renal disease. The most common phenotype is renal cysts, which is frequently associated with early-onset diabetes in the renal cysts and diabetes (RCAD) syndrome. HNF-1beta gene deletions have recently been shown to cause renal malformations and early-onset diabetes. METHODS: We developed a multiplex ligation-dependent probe amplification (MLPA) assay for HNF-1beta gene dosage analysis and tested patients with unexplained renal disease in whom mutations had not been found by sequencing. RESULTS: Whole HNF-1beta gene deletions were detected in 15/133 probands. Renal cysts were present in 13/15, including three with glomerulocystic kidney disease and one with cystic renal dysplasia. Renal function ranged from normal to transplantation aged 3 years. Ten probands had diabetes (nine having RCAD). In addition, four had abnormal liver function tests, two showed pancreatic atrophy and 3/10 female probands had uterine malformations. Whole HNF-1beta gene deletions are a common cause of developmental renal disease, particularly renal cystic disease with or without diabetes. CONCLUSIONS: the phenotype associated with deletions or coding region/splicing mutations is very similar suggesting that haploinsufficiency is the underlying mechanism. Patients with features suggestive of the HNF-1beta clinical phenotype should be tested for mutations both by sequence and dosage analysis.

Objective. - Dizziness is a symptom of acute mountain sickness (AMS). This study tested whether immediate fall in systolic blood pressure (BP) on standing was more severe at altitude and whether this was associated with symptoms of dizziness. Methods. - Eighty-five lowlanders flew into La Paz, Bolivia (3650 m), and after 4 to 5 days of acclimatization ascended in 90 minutes to the Chacaltaya Laboratory (5200 m) by road. Blood pressure was measured on 5 occasions, 3 times at 5200 m and twice at sea level, before and after the expedition using a mercury sphygmomanometer. Both a supine and an erect (within 15 seconds of standing) BP measurement were recorded. Participants recorded whether they felt dizzy on standing. A mixed-effect model was used to test for a difference in the change in BP for time and altitude. Results. - the immediate fall in systolic BP observed on standing was significantly greater (P <. 001) on all 3 altitude study days (18.2, 23.4, and 20.7 mm Hg) than at sea level (12.2 and 12.4 mm Hg). There was no significant difference in the change in diastolic BP or change in mean arterial BP betv/een sea level and altitude. Conclusions. - the immediate drop in systolic BP observed on standing was greater at altitude. However, mean arterial pressure was maintained, and we found no association between the degree of immediate fall in BP and dizziness or AMS.

We investigated the association between seven polymorphisms in four candidate genes involved in vitamin D and androgen metabolism with early-onset prostate cancer (CaP) risk. The polymorphisms were genotyped in 288 UK males who were diagnosed with CaP at the age of 55 y or younger and up to 700 population-based controls. An additional 50 cases (not selected for age) and 76 controls were also genotyped. Short (< or =22 repeats) AR (CAG)(n) repeats were associated with a significantly reduced risk of early onset CaP (OR 0.68, 95% CI 0.50-0.91) compared with men with long (> 22) repeats. Men homozygous for the leucine variant of SRD5A2 p.89V > L were also found to be at a significantly increased risk of CaP compared with men who were homozygous for the valine allele (OR 1.84, 95% CI 1.15-2.98). No associations were found with the AR (GGC)(n), CYP17 Msp A1 I, VDR Taq I, SRD5A2 (TA)(n) and p.49A >T polymorphisms and CaP risk. These findings suggest that common polymorphisms in the AR and SRD5A2 genes may be associated with early-onset CaP in British men.

Studies of families with breast cancer have indicated that male carriers of BRCA2 mutations are at increased risk of prostate cancer, particularly at an early age. To evaluate the contribution of BRCA2 mutations to early-onset prostate cancer, we screened the complete coding sequence of BRCA2 for germline mutations, in 263 men with diagnoses of prostate cancer who were ≤55 years of age. Protein-truncating mutations were found in six men (2.3%; 95% confidence interval 0.8%-5.0%), and all of these mutations were clustered outside the ovarian-cancer cluster region. The relative risk of developing prostate cancer by age 56 years from a deleterious germline BRCA2 mutation was 23-fold. Four of the patients with mutations did not have a family history of breast or ovarian cancer. Twenty-two variants of uncertain significance were also identified. These results confirm that BRCA2 is a high-risk prostate-cancer-susceptibility gene and have potential implications for the management of early-onset prostate cancer, in both patients and their relatives.