A Bayesian Approach for Analysis of Whole-Genome Bisulphite Sequencing Data Identifies Disease-Associated Changes in DNA Methylation

DNA methylation is a key epigenetic modification involved in gene regulation whose contribution to disease susceptibility remains to be fully understood. Here, we present a novel Bayesian smoothing approach (called ABBA) to detect differentially methylated regions (DMRs) from whole-genome bisulphite sequencing (WGBS). We also show how this approach can be leveraged to identify disease-associated changes in DNA methylation, suggesting mechanisms through which these alterations might affect disease. From a data modeling perspective, ABBA has the distinctive feature of automatically adapting to different correlation structures in CpG methylation levels across the genome whilst taking into account the distance between CpG sites as a covariate. Our simulation study shows that ABBA has greater power to detect DMRs than existing methods, providing an accurate identification of DMRs in the large majority of simulated cases. To empirically demonstrate the method's efficacy in generating biological hypotheses, we performed WGBS of primary macrophages derived from an experimental rat system of glomerulonephritis and used ABBA to identify >1,000 disease-associated DMRs. Investigation of these DMRs revealed differential DNA methylation localized to a 600bp region in the promoter of the Ifitm3 gene. This was confirmed by ChIP-seq and RNA-seq analyses, showing differential transcription factor binding at the Ifitm3 promoter by JunD (an established determinant of glomerulonephritis) and a consistent change in Ifitm3 expression. Our ABBA analysis allowed us to propose a new role for Ifitm3 in the pathogenesis of glomerulonephritis via a mechanism involving promoter hypermethylation that is associated with Ifitm3 repression in the rat strain susceptible to glomerulonephritis.This research was funded by Engineering and Physical Sciences Research Council Grant EP/K030760/1 (L.B.), The Alan Turing Institute under the EPSRC grant EP/N510129/1 (L.B., P.D.), Royal Society IE110977 (L.B., P.D.), European Union (European Social Fund - ESF), Greek national funds through the Operational Program "Education and Lifelong Learning'' of the National Strategic Reference Framework (NSRF), project ARISTEIA (P.D.), Duke-NUS Medical School and Singapore Ministry of Health (O.J.L.R., E.P.), a Medical Research Council Chain-Florey fellowship (T.O.), the Medical Research Council (MR/M004716/1 to J.B. and E.P.) and by Kidney Research UK - RP9/2013 (J.B.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Generalisability of Randomised Controlled Trials in Heart Failure with Reduced Ejection Fraction

BACKGROUND: Heart failure (HF) trials have stringent in- and ex- clusion criteria, but limited data exists regarding generalisability of trials. We compared patient characteristics and outcomes between patients with HF and reduced ejection fraction (HFrEF) in trials and observational registries. METHODS AND RESULTS: Individual patient data for 16922 patients from five randomised clinical trials and 46914 patients from two HF registries were included. The registry patients were categorised into trial-eligible and non-eligible groups using the most commonly used in- and ex-clusion criteria. A total of 26104 (56%) registry patients fulfilled the eligibility criteria. Unadjusted all-cause mortality rates at one year were lowest in the trial population (7%), followed by trial-eligible patients (12%) and trial-non-eligible registry patients (26%). After adjustment for age and sex, all-cause mortality rates were similar between trial participants and trial-eligible registry patients (standardised mortality ratio (SMR) 0.97; 95% confidence interval (CI) 0.92 -1.03) but cardiovascular mortality was higher in trial participants (SMR 1.19; 1.12 -1.27). After full case-mix adjustment, the SMR for cardiovascular mortality remained higher in the trials at 1.28 (1.20- 1.37) compared to RCT-eligible registry patients. CONCLUSION: In contemporary HF registries, over half of HFrEF patients would have been eligible for trial enrolment. Crude clinical event rates were lower in the trials, but, after adjustment for case-mix, trial participants had similar rates of survival as registries. Despite this, they had about 30% higher cardiovascular mortality rates. Age and sex were the main drivers of differences in clinical outcomes between HF trials and observational HF registries

Sex differences in the generalizability of randomized clinical trials in heart failure with reduced ejection fraction

Aims: In order to understand how sex differences impact the generalizability of randomized clinical trials (RCTs) in patients with heart failure (HF) and reduced ejection fraction (HFrEF), we sought to compare clinical characteristics and clinical outcomes between RCTs and HF observational registries stratified by sex. Methods and results: Data from two HF registries and five HFrEF RCTs were used to create three subpopulations: one RCT population (n = 16 917; 21.7% females), registry patients eligible for RCT inclusion (n = 26 104; 31.8% females), and registry patients ineligible for RCT inclusion (n = 20 810; 30.2% females). Clinical endpoints included all-cause mortality, cardiovascular mortality, and first HF hospitalization at 1 year. Males and females were equally eligible for trial enrolment (56.9% of females and 55.1% of males in the registries). One-year mortality rates were 5.6%, 14.0%, and 28.6% for females and 6.9%, 10.7%, and 24.6% for males in the RCT, RCT-eligible, and RCT-ineligible groups, respectively. After adjusting for 11 HF prognostic variables, RCT females showed higher survival compared to RCT-eligible females (standardized mortality ratio [SMR] 0.72; 95% confidence interval [CI] 0.62–0.83), while RCT males showed higher adjusted mortality rates compared to RCT-eligible males (SMR 1.16; 95% CI 1.09–1.24). Similar results were also found for cardiovascular mortality (SMR 0.89; 95% CI 0.76–1.03 for females, SMR 1.43; 95% CI 1.33–1.53 for males). Conclusion: Generalizability of HFrEF RCTs differed substantially between the sexes, with females having lower trial participation and female trial participants having lower mortality rates compared to similar females in the registries, while males had higher than expected cardiovascular mortality rates in RCTs compared to similar males in registries

Introducing PIONEER: a project to harness big data in prostate cancer research

Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. Launched by the Innovative Medicines Initiative 2 and part of the Big Data for Better Outcomes Programme (BD4BO), the overarching goal of PIONEER is to provide high-quality evidence on prostate cancer management by unlocking the potential of big data. The project has identified critical evidence gaps in prostate cancer care, via a detailed prioritization exercise including all key stakeholders. By standardizing and integrating existing high-quality and multidisciplinary data sources from patients with prostate cancer across different stages of the disease, the resulting big data will be assembled into a single innovative data platform for research. Based on a unique set of methodologies, PIONEER aims to advance the field of prostate cancer care with a particular focus on improving prostate-cancer-related outcomes, health system efficiency by streamlining patient management, and the quality of health and social care delivered to all men with prostate cancer and their families worldwide.Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. In this Perspectives article, the authors introduce the PIONEER project and describe its aims and plans for ultimately improving prostate cancer care through the use of big data

Diagnostic and prognostic factors in patients with prostate cancer : a systematic review protocol

Funding PIONEER is funded through the IMI2 Joint Undertaking and is listed under grant agreement No. 777492. IMI2 receives support from the European Union’s Horizon 2020 research and innovation programme and the European Federation of Pharmaceutical Industries and Associations (EFPIA).Peer reviewedPublisher PD

Generalizability of randomized controlled trials in heart failure with reduced ejection fraction

BACKGROUND: Heart failure (HF) trials have stringent inclusion and exclusion criteria, but limited data exist regarding generalizability of trials. We compared patient characteristics and outcomes between patients with HF and reduced ejection fraction (HFrEF) in trials and observational registries. METHODS AND RESULTS: Individual patient data for 16 922 patients from five randomized clinical trials and 46 914 patients from two HF registries were included. The registry patients were categorized into trial-eligible and non-eligible groups using the most commonly used inclusion and exclusion criteria. A total of 26 104 (56%) registry patients fulfilled the eligibility criteria. Unadjusted all-cause mortality rates at 1 year were lowest in the trial population (7%), followed by trial-eligible patients (12%) and trial-non-eligible registry patients (26%). After adjustment for age and sex, all-cause mortality rates were similar between trial participants and trial-eligible registry patients [standardized mortality ratio (SMR) 0.97; 95% confidence interval (CI) 0.92-1.03] but cardiovascular mortality was higher in trial participants (SMR 1.19; 1.12-1.27). After full case-mix adjustment, the SMR for cardiovascular mortality remained higher in the trials at 1.28 (1.20-1.37) compared to RCT-eligible registry patients. CONCLUSION: In contemporary HF registries, over half of HFrEF patients would have been eligible for trial enrolment. Crude clinical event rates were lower in the trials, but, after adjustment for case-mix, trial participants had similar rates of survival as registries. Despite this, they had about 30% higher cardiovascular mortality rates. Age and sex were the main drivers of differences in clinical outcomes between HF trials and observational HF registries

Updating and Integrating Core Outcome Sets for Localised, Locally Advanced, Metastatic, and Nonmetastatic Castration-resistant Prostate Cancer: An Update from the PIONEER Consortium

CONTEXT: Harmonisation of outcome reporting and definitions for clinical trials and routine patient records can enable health care systems to provide more efficient outcome-driven and patient-centred interventions. We report on the work of the PIONEER Consortium in this context for prostate cancer (PCa). OBJECTIVE: To update and integrate existing core outcome sets (COS) for PCa for the different stages of the disease, assess their applicability, and develop standardised definitions of prioritised outcomes. EVIDENCE ACQUISITION: We followed a four-stage process involving: (1) systematic reviews; (2) qualitative interviews; (3) expert group meetings to agree standardised terminologies; and (4) recommendations for the most appropriate definitions of clinician-reported outcomes. EVIDENCE SYNTHESIS: Following four systematic reviews, a multinational interview study, and expert group consensus meetings, we defined the most clinically suitable definitions for (1) COS for localised and locally advanced PCa and (2) COS for metastatic and nonmetastatic castration-resistant PCa. No new outcomes were identified in our COS for localised and locally advanced PCa. For our COS for metastatic and nonmetastatic castration-resistant PCa, nine new core outcomes were identified. CONCLUSIONS: These are the first COS for PCa for which the definitions of prioritised outcomes have been surveyed in a systematic, transparent, and replicable way. This is also the first time that outcome definitions across all prostate cancer COS have been agreed on by a multidisciplinary expert group and recommended for use in research and clinical practice. To limit heterogeneity across research, these COS should be recommended for future effectiveness trials, systematic reviews, guidelines and clinical practice of localised and metastatic PCa. PATIENT SUMMARY: Patient outcomes after treatment for prostate cancer (PCa) are difficult to compare because of variability. To allow better use of data from patients with PCa, the PIONEER Consortium has standardised and recommended outcomes (and their definitions) that should be collected as a minimum in all future studies

Machine learning-based steroid metabolome analysis reveals three distinct subtypes of polycystic ovary syndrome and implicates 11-oxygenated androgens as major drivers of metabolic risk

Introduction: Polycystic ovary syndrome affects 10% of women and comes with a 2-3fold increased risk of type 2 diabetes, hypertension, and fatty liver disease. Androgen excess, a cardinal feature of PCOS, has been implicated as a major contributor to metabolic risk. Adrenal-derived 11-oxygenated androgens represent an important component of PCOS-related androgen excess and are preferentially activated in adipose tissue. We aimed to identify PCOS sub-types with distinct androgen profiles and compare their cardiometabolic risk parameters. Methods: We cross-sectionally studied 488 treatment-naïve women with PCOS diagnosed according to Rotterdam criteria [median age 28 (IQR 24-32) years; BMI 27.5 (22.4-34.6) kg/m 2 ] prospectively recruited at eight centres in the UK & Ireland (n=208), Austria (n=242) and Brazil (n=38). All participants underwent a standardised assessment including clinical history, anthropometric measurements, fasting bloods and a 2-hour oral glucose tolerance test. We quantified 11 androgenic serum steroids, including classic and 11-oxygenated androgens, using a validated multi-steroid profiling tandem mass spectrometry assay. We measured serum insulin to calculate HOMA-IR and the Matsuda insulin sensitivity index (ISI). Steroid data were analysed by unsupervised k-means clustering, followed by statistical analysis of differences in clinical phenotype and metabolic parameters. Results: Machine learning analysis identified three stable subgroups of women with PCOS with minimal overlap and distinct steroid metabolomes: a cluster characterised by mainly gonadal-derived androgen excess (testosterone, dihydrotestosterone; GAE cluster; 21.5% of women), a cluster with predominantly adrenal-derived androgen excess (11-oxygenated androgens; AAE cluster; 21.7%), and a cluster with comparably mild androgen excess (MAE cluster; 56.8%). Age and BMI were similar between groups. As compared to GAE and MAE, the AAE cluster had the highest rates of hirsutism (76.4% vs 67.6% vs 59.9%) and female pattern hair loss (32.1% vs 14.3% vs 21.7%). The AAE cluster had significantly increased insulin resistance as indicated by higher values for fasting insulin, 120min insulin and HOMA-IR, and lower ISI than GAE and MAE clusters (all