Publications by year
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.
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
Bailey S, Green H, Merriel S, Oram R, Thirlwell C, Ruth K, Tyrrell J, Weedon M (In Press). Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis: a cohort study in the UK Biobank. British Journal of Cancer
Karageorgiou V, Casanova F, O'Loughlin J, Green H, McKinley TJ, Bowden J, Tyrrell J
(In Press). Body Mass Index and Inflammation in Depression and Treatment-Resistant Depression: a Mendelian Randomization Study.
Body Mass Index and Inflammation in Depression and Treatment-Resistant Depression: a Mendelian Randomization Study
. Introduction: Major depressive disorder (MDD) has a significant impact on global burden of disease. Complications in clinical management can occur when response to pharmacological modalities is considered inadequate and symptoms persist (treatment-resistant depression (TRD)). We aim to investigate inflammation, proxied by C-reactive protein (CRP) levels, and body mass index (BMI) as putative causal risk factors for depression and subsequent treatment resistance, leveraging genetic
information to avoid confounding via Mendelian Randomization (MR).
Methods: We used the European UK Biobank subcohort (n = 451, 025), the mental health questionnaire (MHQ) and clinical records. For treatment resistance, a previously curated phenotype based on GP records and prescription data was employed. We applied univariable and multivariable MR models to genetically predict the exposures and assess their causal contribution to a range of depression outcomes. We used weak and pleiotropy, robust estimation techniques within univariable, multivariable and mediation MR models in order to address
our research question with maximum rigour. In addition, we developed a novel statistical procedure to apply pleiotropy robust multivariable MR to one sample data and employed an unfamiliar bootstrap procedure to accurately quantify estimate uncertainty in mediation analysis which outperforms
Results: in univariable MR models, genetically predicted BMI was positively associated with depression outcomes, including MDD and TRD, with a larger magnitude in women and with age acting
as a moderator of the effect of BMI on PHQ9 (p = 0.011). Multivariable MR analyses suggested an independent causal effect of BMI on TRD not through CRP. Our mediation analyses suggested
that the effect of CRP on PHQ9 was partly mediated by BMI. Individuals with TRD (n = 2, 199) observationally had higher CRP and BMI compared with individuals with MDD alone and healthy
controls. A positive causal association was noted for both the exposures, but in multivariable analyses only BMI retained statistical significance at the 5% level.
Discussion: Our work supportst the assertion BMI exerts a causal effect on a range of clinical and questionnaire-based depression phenotypes, with the effect being stronger in women and in younger individuals. We show that this effect is independent of inflammation proxied by CRP levels as the effects of CRP do not persist when jointly estimated with BMI. This is consistent with previous evidence suggesting that overweight contributed to depression even in the absence of any metabolic consequences. It appears that BMI exerts an effect on TRD that persists when we account for BMI influencing MDD.
Hagenaars SP, Gillett AC, Casanova F, Young KG, Green H, Lewis CM, Tyrrell J
(In Press). The impact of depression diagnosis on diabetes and lifetime hyperglycaemia.
The impact of depression diagnosis on diabetes and lifetime hyperglycaemia
AbstractAimsThe aim of this study was to evaluate longitudinal associations between the mean and variability of HbA1c levels in individuals with type 2 diabetes (T2D) and major depressive disorder (MDD).MethodsIndividuals with T2D from the UK Biobank with linked primary care records were analysed. An HbA1c measurement within +/- 6-months of T2D diagnosis was taken as baseline, with subsequent HbA1c measurements used as the outcome in generalised least squares regression to evaluate longitudinal associations with a three-level MDD diagnosis variable (MDD controls, pre-T2D MDD cases and post-T2D MDD cases).ResultsUsing 7,968 T2D individuals, we show that MDD has utility in explaining mean HbA1c levels (p=6.53E-08). This is attributable to MDD diagnosis interacting with baseline T2D medication (p=3.36E-04) and baseline HbA1c (p=2.66E-05), but not with time-when all else is equal, the temporal trend in expected HbA1c did not differ by MDD diagnosis. However, joint consideration with baseline T2D medication showed that each additional medication prescribed was associated with a +4 mmol/mol (2.5%) increase in expected HbA1c across follow up for post-T2D MDD cases, relative to pre-T2D MDD cases and MDD controls. Furthermore, variability in HbA1c increased across time for post-T2D MDD cases but decreased for MDD controls and pre-T2D MDD cases.ConclusionsThese findings suggest closer monitoring of individuals with both T2D and MDD is essential to improve their diabetic control, particularly for those who develop MDD after T2D diagnosis.Novelty statementWhat is already known?Comorbid T2D and MDD is associated with poorer diabetic control and worse prognosis.What this study has found?We demonstrate a strong complex relationship between MDD and diabetic control, influenced by diabetic medication and baseline HbA1c levels. We showed that individuals who develop MDD after their T2D diagnosis have greater variability in HbA1c levels over time.What are the implications of the study?This study shows the importance of closer monitoring of HbA1c in individuals with both T2D and MDD, particularly those who develop MDD after diabetes, to improve diabetic control and reduce complications associated comorbid T2D and MDD. Abstract
Green HD, Young KG, Jones AG, Weedon MN, Dennis JM
(In Press). Using joint models to adjust for informative drop-out when modelling a longitudinal biomarker: an application to type 2 diabetes disease progression.
Using joint models to adjust for informative drop-out when modelling a longitudinal biomarker: an application to type 2 diabetes disease progression
AbstractLinear mixed effects models are frequently used in biomedical statistics to model the trajectory of a repeatedly measured longitudinal variable, such as a biomarker, over time. However, population-level estimates may be biased by censoring bias resulting from exit criteria that depend on the variable in question. A joint longitudinal-survival model, in which the exit criteria and longitudinal variable are modelled simultaneously, may address this bias. Using blood glucose progression (change in HbA1c) in type 2 diabetes patients on metformin monotherapy as an example, we study the potential benefit of using joint models to model trajectory of a biomarker in observational data. 7,712 patients with type 2 diabetes initiating metformin monotherapy were identified in UK Biobank’s general practice (GP) linked records. Genetic information was extracted from UK Biobank, and prescription records, baseline clinical features and biomarkers, and longitudinal HbA1c measures were extracted from GP records. Exit criteria for follow-up for a patient was defined as progression to an additional glucose-lowering drug (which is more likely in patient with higher HbA1c). Estimates of HbA1c trajectory over time were compared using linear mixed effect model approaches (which do not account for censoring bias) and joint models. In the primary analysis, a 0.19 mmol/mol per year higher (p = 0.01) HbA1c gradient was estimated using the joint model compared to the linear mixed effects model. This difference between models was attenuated (0.13 mmol/mol per year higher, p=0.43) when baseline clinical features and biomarkers were included as additional covariates.Censoring bias should be carefully considered when modelling trajectories of repeatedly measured longitudinal variables in observational data. Joint longitudinal-survival models are a useful approach to identify and potentially correct for censoring bias when estimating population-level trajectories.Author SummaryModelling biomarkers that change over time in real world data is a challenging statistical problem due to many potential sources of bias. For example, when studying a chronic disease using a biomarker or other measurement that represents disease severity, medication intended to affect that measurement has a profound effect on how it will change over time. One common way to control for this is to study a cohort on the same treatment strategy. That way, results are not influenced by treatment change. If a patient progresses to stronger medication, then future data is no longer used. However, this approach introduces its own bias. Patients whose condition progress particularly quickly are more likely to change treatment more rapidly (and therefore be removed from further analysis, or ‘censored’), so the cohort is biased towards those whose condition progresses slower. In this paper we apply a technique called joint longitudinal-survival modelling which can adjust for this censoring bias and produce less biased estimates of progression rates. We use HbA1c (a widely used measure of glucose control) in type 2 diabetes as an example, however our methods are theoretically applicable to a range of problems across medicine in which a biomarker or feature is repeatedly measured in an individual. Abstract
Green HD, Merriel SWD, Oram RA, Ruth KS, Tyrrell J, Jones SE, Thirlwell C, Weedon MN, Bailey SER
(2023). Response to: Genetic risk scores may compound rather than solve the issue of prostate cancer overdiagnosis (BJC-LT3342090). Br J Cancer
(4), 487-488. Author URL
Green H, Merriel SWD, Oram R, Ruth K, Tyrrell J, Jones S, Thirlwell C, Gillings M, Weedon M, Bailey SER, et al
(2022). Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis: a cohort study in the UK Biobank.
Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis: a cohort study in the UK Biobank
Objectives to assess how accurately a genetic risk score (GRS) can identify incident prostate cancer in men seeing their general practitioner with lower urinary tract symptoms. Design Cohort study. Setting UK Biobank data linked to primary care records. Participants Men registered with the UK Biobank, eligible for the primary care data linkage, with a record showing that they consulted their general practitioner with lower urinary tract symptoms (LUTS) that could indicate possible undiagnosed prostate cancer. Main outcome measures a diagnosis of prostate cancer within two years of the patient’s first consultation with their general practitioner for LUTS. Results a GRS is associated with prostate cancer in men with symptoms (OR=2.54 [2.16 to 2.99] p=5e-29). An integrated risk model including age and GRS applied to symptomatic men predicted prostate cancer with an AUC of 0.768 (0.739 to 0.796). Men aged 40 years and under in the bottom four GRS quintiles, aged 50 years and under in the bottom two GRS quintiles, and aged 50 to 60 years in the bottom GRS quintile had a two-year prostate cancer incidence below 1%, despite the presence of symptoms. The negative predictive value of the combined model exceeded 99%. Conclusions This study is the first to apply a genetic risk score in a clinical setting to improve the triage of men with symptoms of prostate cancer. It demonstrates the added benefit of incorporating an estimate of genetic risk of prostate cancer into the clinical assessment of symptomatic men in primary care. Assessment of prostate cancer risk in men with LUTS is currently based on presenting clinical features alone. Men with the lowest genetic risk of developing prostate cancer could safely avoid invasive investigation, with adequate safety netting, whilst those identified with the greatest risk could be fast-tracked for further investigation. Abstract
Oram R, Loginovic P, Ferrat L, Green H, Weedon M, Tyrrell J, Petzold A, Braithwaite T (2022). Applying a genetic risk score model to enhance prediction of future Multiple Sclerosis diagnosis at first presentation with optic neuritis: a cohort study in the UK Biobank.
Tyrrell J, Gillett A, Casanova F, Young K, Green H, Lewis C, Hagenaars S (2022). The impact of depression. diagnosis on diabetes and lifetime hyperglycaemia. World Congress of Psychiatric Genetic (WCPG). 13th - 17th Sep 2022.
Hagenaars S, Casanova F, Gillett A, Green H, Lewis C, Tyrrell J
(2021). ASSESSING THE IMPACT OF DEPRESSION DIAGNOSIS ON DIABETES AND LIFETIME HYPERGLYCAEMIA. 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).
Nice R, Chanchlani N, Kennedy NA, Green HD, Lin S, Gordon C, Chee D, Hamilton B, Bewshea C, Goodhand J, et al
(2021). POSITIVITY THRESHOLDS OF TOTAL INFLIXIMAB AND ADALIMUMAB ANTI-DRUG ANTIBODY ASSAYS AND IMPACT IN CLINICAL PRACTICE. Author URL
Nice R, Chanchlani N, Green H, Bewshea C, Ahmad T, Goodhand JR, McDonald TJ, Perry MH, Kennedy NA
(2021). Validating the positivity thresholds of drug-tolerant anti-infliximab and anti-adalimumab antibody assays. Aliment Pharmacol Ther
Validating the positivity thresholds of drug-tolerant anti-infliximab and anti-adalimumab antibody assays.
BACKGROUND: When used proactively, drug-tolerant anti-tumour necrosis factor (TNF) antibody assays provide early opportunity to suppress immunogenicity. AIM: to validate positivity thresholds of IDKmonitor drug-tolerant anti-infliximab and -adalimumab antibody assays. METHODS: We applied positivity thresholds, defined by testing sera from 498 anti-TNF naive healthy adults, from the Exeter Ten Thousand study to data from our therapeutic drug monitoring (TDM) service and Personalised Anti-TNF Therapy in Crohn's disease (PANTS) cohort to explore associations with drug level and treatment outcomes. RESULTS: the 80% one-sided lower confidence interval of the 99th centile concentration for anti-infliximab and -adalimumab antibodies were lower than the manufacturers threshold of 10 arbitrary units (AU)/mL; 9 and 6 AU/mL, respectively. Using these new thresholds in the TDM cohort, more adalimumab- than infliximab- (11.2% [814/7272] vs 3.1% [390/12 683] P Abstract
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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
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
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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
Genetic evidence that higher central adiposity causes gastro-oesophageal reflux disease: a Mendelian randomization study
. 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.
. 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.
. 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.
. 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.
Hamilton B, Green H, Heerasing N, Hendy P, Moore L, Chanchlani N, Walker G, Bewshea C, Kennedy NA, Ahmad T, et al
(2020). Incidence and prevalence of inflammatory bowel disease in Devon, UK. Frontline Gastroenterology
Incidence and prevalence of inflammatory bowel disease in Devon, UK
Background and aimsWe sought to define temporal changes in prevalence of inflammatory bowel disease (IBD) in East Devon, UK, in order to facilitate service planning over the next 5 years.MethodsMultiple primary and secondary care databases were used to identify and verify cases. Point prevalence and incidence of IBD were reported in April 2017 and from 2008 to 2016, respectively. Future prevalence and healthcare activity requirements were estimated by linear regression.ResultsPrevalence of ulcerative colitis (UC), Crohn’s disease (CD) and inflammatory bowel disease unclassified (IBDU) were 479.72, 265.94 and 35.34 per 100 000 persons, respectively. In 2016, the incidence rates of UC, CD and IBDU were 15.4, 10.7 and 1.4 per 100 000 persons per year, respectively. There were no significant changes in the incidence of CD (p=0.49, R=0.26) or UC (p=0.80, R=0.10). IBD prevalence has increased by 39.9% (95% CI 28.2 to 53.7) in the last 10 years without differences in the rate of change between UC and CD. Overall, 27% of patients were managed in primary care, a quarter of whom were eligible but not receiving endoscopic surveillance. Outpatient clinics, MRI and biologic use, but not helpline calls, admissions, or surgeries increased over and above the change in IBD prevalence.ConclusionsWe report one of the highest prevalence and incidence rates of IBD from Northern Europe. Overall, IBD incidence is static, but prevalence is increasing. We estimate that 1% of our population will live with IBD between 2025 and 2030. Abstract
Nice R, Chanchlani N, Green H, Bewshea C, Kennedy N, Ahmad T, Goodhand J, McDonald T, Perry M (2020). OP21 Positivity thresholds of total infliximab and adalimumab anti-drug antibody assay: the prevalence of clearing and transient anti-drug antibodies in a national therapeutic drug monitoring service. Journal of Crohn's and Colitis, 14(Supplement_1), s018-s019.
Walker GJ, Lin S, Chanchlani N, Thomas A, Hendy P, Heerasing N, Moore L, Green HD, Chee D, Bewshea C, et al (2020). Quality improvement project identifies factors associated with delay in IBD diagnosis. Alimentary Pharmacology & Therapeutics, 52(3), 471-480.
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
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
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Green H, Beaumont R, Jones S, Yaghootkar H, Wood A, Goodhand J, Kennedy N, Ahmad T, Frayling T, Weedon M, et al
(2019). MODIFIABLE RISK FACTORS FOR GASTRO-OESOPHAGAL REFLUX DISEASE: a MENDELIAN RANDOMISATION STUDY. Author URL
Walker G, Lin S, Thomas A, Chanchlani N, Moore L, Hendy P, Heerasing N, Green H, Mole S, Bewshea C, et al
(2019). PROSPECTIVE COHORT TO IDENTIFY FACTORS ASSOCIATED WITH DIAGNOSTIC DELAY IN PATIENTS WITH INFLAMMATORY BOWEL DISEASE. Author URL
Bewshea CM, Ahmad T, Kennedy N, Goodhand J, McDonald T, Green H (2019). Predictors of anti-TNF treatment failure in anti-TNF-naive patients with active luminal Crohn's disease: a prospective, multicentre, cohort study. Lancet Gastroenterology and Hepatology
Walker G, Lin S, Chanchlani N, Thomas A, Moore L, Hendy P, Heerasing N, Green H, Bewshea C, Goodhand J, et al
(2019). Prospective cohort to identify factors associated with a delay in diagnosis in patients with inflammatory bowel disease. Author URL
Green H, Hamilton B, Walker G, Goodhand J, Kennedy N, Ahmad T, Weedon M
(2018). GWAS OF MICROSCOPIC COLITIS IN THE UK BIOBANK CONFIRMS ASSOCIATION WITHIN THE HLA REGION. Author URL
Green HD, Thomas G, Terry JR
(2017). Signal reconstruction of pulmonary vein recordings using a phenomenological mathematical model: Application to pulmonary vein isolation therapy. Frontiers in Physiology
Signal reconstruction of pulmonary vein recordings using a phenomenological mathematical model: Application to pulmonary vein isolation therapy
Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is commonly initiated by ectopic beats originating from a small myocardial sleeve extending over the pulmonary veins. Pulmonary vein isolation therapy attempts to isolate the pulmonary veins from the left atrium by ablating tissue, commonly by using radiofrequency ablation. During this procedure, the cardiologist records electrical activity using a lasso catheter, and the activation pattern recorded is used as a guide toward which regions to ablate. However, poor contact between electrode and tissue can lead to important regions of electrical activity not being recorded in clinic. We reproduce these signals through the use of a phenomenological model of the cardiac action potential on a cylinder, which we fit to post-AF atrial cells, and model the bipolar electrodes of the lasso catheter by an approximation of the surface potential. The resulting activation pattern is validated by direct comparison with those of clinical recordings. A potential application of the model is to reconstruct the missing electrical activity, minimizing the impact of the information loss on the clinical procedure, and we present results to demonstrate this. Abstract