BACKGROUND:Evidence of the diverse genetic architecture of dilated cardiomyopathy (DCM) continues to emerge and requires reassessment of the clinical relevance of implicated disease genes. Building on the 2019-2020 Clinical Genome Resource evaluation, the DCM gene curation expert panel reconvened in 2024-2025 to conduct a reassessment of genes in DCM. METHODS:The Clinical Genome Resource semiquantitative clinical validity classification framework was applied with specifications to DCM to classify genes into categories on the basis of strength of published evidence for a DCM phenotype. Previously curated genes were reassessed, and newly reported gene-disease-mode of inheritance (MOI) relationships, termed "curations," were evaluated. RESULTS:Sixty-eight genes were evaluated, inclusive of 72 unique gene-disease-MOI relationships across 51 previously evaluated and 17 newly assessed genes. Thirty-five curations were classified as high evidence (16 Definitive, 10 Strong, 9 Moderate), increasing by 16 from the prior assessment. Nine newly assessed genes were classified as high evidence: BAG5, FLII, LMOD2, MYLK3, MYZAP, NRAP, PPA2, PPP1R13L, and RPL3L. Twelve genes (11 newly appraised) were rated as high evidence with an autosomal recessive (AR) MOI. Five reevaluated genes from 2019-2020 had clinically significant changes in classification. Except for JPH2, for which curation was modified to separate autosomal dominant and AR MOI curations, clinically significant changes involved upgrades from low- to high-evidence categories (PLEKHM2, PRDM16, TBX20, TNNI3K), demonstrating the robustness of the Clinical Genome Resource gene curation process over time. An additional 29 gene-disease-MOI curations were classified as Limited, including 6 newly evaluated genes and 1 new MOI for a previously evaluated gene, MYBPC3-AR; 4 were classified as No Known Disease Relationship, and remained Disputed. Four previously evaluated genes were curated for both AD and AR MOIs: JPH2 (AD-Strong, AR-Limited), LDB3 (AD-Limited, AR-Strong), MYBPC3 (AD-Limited, AR-Limited), and TNNI3 (AD- and AR- Strong). CONCLUSIONS:With substantial new evidence, the genetic architecture of DCM has rapidly expanded. This updated assessment of genes reported in DCM yielded 35 high-evidence curations, an increase from 19 only 5 years ago. The results of this evidence-based evaluation process inform clinical interpretation of genetic information in the care of DCM patients and families.

Background The Global Burden of Disease Study has provided key evidence to inform clinicians, researchers, and policy makers across common diseases, but no similar effort with a single-study design exists for hundreds of rare diseases. Consequently, for many rare conditions there is little population-level evidence, including prevalence and clinical vulnerability, resulting in an absence of evidence-based care that was prominent during the COVID-19 pandemic. We aimed to inform rare disease care by providing key descriptors from national data and explore the impact of rare diseases during the COVID-19 pandemic. Methods In this nationwide retrospective observational cohort study, we used the electronic health records (EHRs) of more than 58 million people in England, linking nine National Health Service datasets spanning health-care settings for people who were alive on Jan 23, 2020. Starting with all rare diseases listed in Orphanet (an extensive online resource for rare diseases), we quality assured and filtered down to analyse 331 conditions mapped to ICD-10 or Systemized Nomenclature of Medicine-Clinical Terms that were clinically validated in our dataset. For all 331 rare diseases, we calculated population prevalences, analysed patients' clinical and demographic details, and investigated mortality with SARS-CoV-2. We assessed COVID-19-related mortality by comparing cohorts of patients for each rare disease and rare disease category with controls matched for age group, sex, ethnicity, and vaccination status, at a ratio of two controls per individual with a rare disease. Findings Of 58 162 316 individuals, we identified 894 396 with at least one rare disease and assessed COVID-19-related mortality between Sept 1, 2020, and Nov 30, 2021. We calculated reproducible estimates, adjusted for age and sex, for all 331 rare diseases, including for 186 (562%) conditions without existing prevalence estimates in Orphanet. 49 rare diseases were significantly more frequent in female individuals than in male individuals, and 62 were significantly more frequent in male individuals than in female individuals; 47 were significantly more frequent in Asian or British Asian individuals than in White individuals; and 22 were significantly more frequent in Black or Black British individuals than in White individuals. 37 rare diseases were significantly more frequent in the White population compared with either the Black or Asian population. 7965 (09%) of 894 396 patients with a rare disease died from COVID-19, compared with 141 287 (02%) of 58 162 316 in the full study population. In fully vaccinated individuals, the risk of COVID-19-related mortality was significantly higher for eight rare diseases, with patients with bullous pemphigoid (hazard ratio 807, 95% CI 301-2162) being at highest risk. Interpretation Our study highlights that national-scale EHRs provide a unique resource to estimate detailed prevalence, clinical, and demographic data for rare diseases. Using COVID-19-related mortality analysis, we showed the power of large-scale EHRs in providing insights to inform public health decision making for these often neglected patient populations.

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment.

The genetic contributions to early onset heart failure (HF) are incompletely understood. Genetic testing in advanced HF patients undergoing heart transplantation (HTx) may yield clinical benefits, but data is limited. We performed deep-coverage whole genome sequencing (WGS) in 102 Swedish HTx recipients. Gene lists were compiled through a systematic literature review. Variants were prioritized for pathogenicity and classified manually. We also compared polygenic HF risk scores to a population-based cohort. We found a pathogenic (LP/P) variant in 34 individuals (34%). Testing yield was highest in hypertrophic (63% LP/P carriers), dilated (40%) and arrhythmogenic right ventricular (33%) cardiomyopathy and lower in ischemic cardiomyopathy (10%). A family history was more common in LP/P variant carriers than in non-carriers but was present in less than half of carriers (44% vs 13%, P < 0.001), whereas age was similar. Polygenic risk scores were similar in HTx recipients and the population cohort. In conclusion, we observed a high prevalence of pathogenic cardiomyopathy gene variants in individuals with early-onset advanced HF, which could not accurately be ruled out by family history and age. In contrast, we did not observe higher polygenic risk scores in early onset advanced HF cases than in the general population.

Introduction There is uncertainty about the effectiveness of oral fluid restriction in patients with acute heart failure treated with intravenous loop diuretics, due to a lack of high-quality evidence from randomised controlled trials (RCTs). RCTs of non-pharmacological therapies are challenging and costly to undertake in the acute setting using conventional approaches. We sought to investigate the feasibility of conducting a pragmatic RCT that was integrated into the electronic health record (EHR), in the setting of acute unplanned care. Our primary aim was to determine the feasibility of using an automated, interruptive alert to invite clinicians to enrol patients into an RCT of fluid restriction in patients presenting with fluid overload. Methods THIRST Alert was a single-centre parallel group, open-label, randomised controlled trial conducted to pilot a novel and efficient approach to trial conduct in a hospital setting. Patient screening, recruitment, randomisation, and outcome ascertainment were all conducted through the EHR and routine care processes. A proportionate model of verbal opt-out consent was used. Over a 6-month period, clinicians who prescribed more than one dose of intravenous furosemide within 48 hours of an unplanned patient admission were exposed to an alert which invited them to assess whether their patient was suitable for inclusion into the trial. Patients <18 and those admitted to the care of surgical or maternity teams were excluded. Enrolled patients underwent simple 1:1 randomisation by the EHR, and were allocated to either oral fluid restriction of 1L/ day or no oral fluid restriction. The co-primary outcome measures were the number of patients enrolled and the documented difference in oral fluid intake between the intervention and control group in the 48 hours after randomised allocation. The trial did not involve any additional investigator input or patient follow-up. Results Between 3 May 2023 and 1 November 2023, a total of 1,191 alerts were triggered. 23 of 141 eligible patients (16%) were enrolled on the trial by routine care clinicians (table 1). In 21 of 23 patients (91%), there was evidence of adherence to the randomised treatment allocation: a clinical order concordant with the randomised allocation was recorded in the health record in 12/12 patients allocated to fluid restriction arm and 9/11 patients allocated to no restriction (figure 1). For 19/23 (83%) of the patients enrolled in the study, heart failure was included in the hospital episode statistics for the admission. In the intention to treat (ITT) analysis, the documented oral intake of the restricted group was 1170 ml (930–1620 ml IQR) and 650 ml (75–1100 ml IQR) in the unrestricted group. The mean number of documented entries for the primary outcome measure of fluid intake was 6.6 for the restricted group and 4.9 for the unrestricted group. Conclusions To our knowledge, the THIRST Alert trial is one of the first pragmatic RCTs delivered entirely through the electronic health record system and without the direct intervention of a research team. Our study demonstrates the feasibility of conducting low-cost and efficient trials during the routine care process to generate evidence that can inform practice and improve patient outcomes. Paradoxically, we observed a higher documented fluid intake in the fluid restriction group which may indicate differences in measurement and documentation in patients with active treatments. Further studies are required to determine whether oral fluid restriction is an effective adjunct to diuretic treatment in this setting or if it is a low-value intervention that contributes to care complexity and patient thirst without clinical benefit. Trial registration: NCT05869656. Funded by NIHR UCLH Biomedical Research Centre. Conflict of Interest None

BACKGROUND AND AIMS:The role of gender in decision-making for oral anticoagulation in patients with atrial fibrillation (AF) remains controversial. METHODS:The population cohort study used electronic healthcare records of 16 587 749 patients from UK primary care (2005-2020). Primary (composite of all-cause mortality, ischaemic stroke, or arterial thromboembolism) and secondary outcomes were analysed using Cox hazard ratios (HR), adjusted for age, socioeconomic status, and comorbidities. RESULTS:78 852 patients were included with AF, aged 40-75 years, no prior stroke, and no prescription of oral anticoagulants. 28 590 (36.3%) were women, and 50 262 (63.7%) men. Median age was 65.7 years (interquartile range 58.5-70.9), with women being older and having other differences in comorbidities. During a total follow-up of 431 086 patient-years, women had a lower adjusted primary outcome rate with HR 0.89 vs. men (95% confidence interval [CI] 0.87-0.92; P < .001) and HR 0.87 after censoring for oral anticoagulation (95% CI 0.83-0.91; P < .001). This was driven by lower mortality in women (HR 0.86, 95% CI 0.83-0.89; P < .001). No difference was identified between women and men for the secondary outcomes of ischaemic stroke or arterial thromboembolism (adjusted HR 1.00, 95% CI 0.94-1.07; P = .87), any stroke or any thromboembolism (adjusted HR 1.02, 95% CI 0.96-1.07; P = .58), and incident vascular dementia (adjusted HR 1.13, 95% CI 0.97-1.32; P = .11). Clinical risk scores were only modest predictors of outcomes, with CHA2DS2-VA (ignoring gender) superior to CHA2DS2-VASc for primary outcomes in this population (receiver operating characteristic curve area 0.651 vs. 0.639; P < .001) and no interaction with gender (P = .45). CONCLUSIONS:Removal of gender from clinical risk scoring could simplify the approach to which patients with AF should be offered oral anticoagulation.

Dilated cardiomyopathy (DCM) is a heart muscle disease that represents an important cause of morbidity and mortality, yet causal mechanisms remain largely elusive. Here, we perform a large-scale genome-wide association study and multitrait analysis for DCM using 9,365 cases and 946,368 controls. We identify 70 genome-wide significant loci, which show broad replication in independent samples and map to 63 prioritized genes. Tissue, cell type and pathway enrichment analyses highlight the central role of the cardiomyocyte and contractile apparatus in DCM pathogenesis. Polygenic risk scores constructed from our genome-wide association study predict DCM across different ancestry groups, show differing contributions to DCM depending on rare pathogenic variant status and associate with systolic heart failure across various clinical settings. Mendelian randomization analyses reveal actionable potential causes of DCM, including higher bodyweight and higher systolic blood pressure. Our findings provide insights into the genetic architecture and mechanisms underlying DCM and myocardial function more broadly.

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and cardiac transplantation. We report a genome-wide association study and multi-trait analysis of DCM (14,256 cases) and three left ventricular traits (36,203 UK Biobank participants). We identified 80 genomic risk loci and prioritized 62 putative effector genes, including several with rare variant DCM associations (MAP3K7, NEDD4L and SSPN). Using single-nucleus transcriptomics, we identify cellular states, biological pathways, and intracellular communications that drive pathogenesis. We demonstrate that polygenic scores predict DCM in the general population and modify penetrance in carriers of rare DCM variants. Our findings may inform the design of genetic testing strategies that incorporate polygenic background. They also provide insights into the molecular etiology of DCM that may facilitate the development of targeted therapeutics.

Cardiac trabeculae form a network of muscular strands that line the inner surfaces of the heart. Their development depends on multiscale morphogenetic processes and, while highly conserved across vertebrate evolution, their role in the pathophysiology of the mature heart is not fully understood. Here we report variant associations across the allele frequency spectrum for trabecular morphology in 47,803 participants of the UK Biobank using fractal dimension analysis of cardiac imaging. We identified an association between trabeculation and rare variants in 56 genes that regulate myocardial contractility and ventricular development. Genome-wide association studies identified 68 loci in pathways that regulate sarcomeric function, differentiation of the conduction system and cell fate determination. We found that trabeculation-associated variants were modifiers of cardiomyopathy phenotypes with opposing effects in hypertrophic and dilated cardiomyopathy. Together, these data provide insights into mechanisms that regulate trabecular development and plasticity, and identify a potential role in modifying monogenic disease expression. The inner surface of the heart has a meshwork of muscles called trabeculae. McGurk et al. report the genetic regulation of these complex structures across common and rare variants, revealing pathways implicated in heart development and cell fate.

Atrial fibrillation (AF) remains the most common cardiac arrhythmia worldwide and is associated with significant morbidity and mortality. The European Society of Cardiology (ESC)/European Association for Cardio-Thoracic Surgery (EACTS) have recently released the 2024 guidelines for the management of AF. This review highlights 10 novel aspects of the ESC/EACTS 2024 Guidelines. The AF-CARE framework is introduced, a structural approach that aims to improve patient care and outcomes, comprising of four pillars: [C] Comorbidity and risk factor management, [A] Avoid stroke and thromboembolism, [R] Reduce symptoms by rate and rhythm control, and [E] Evaluation and dynamic reassessment. Additionally, graphical patient pathways are provided to enhance clinical application. A significant shift is the new emphasis on comorbidity and risk factor control to reduce AF recurrence and progression. Individualized assessment of risk is suggested to guide the initiation of oral anticoagulation to prevent thromboembolism. New guidance is provided for anticoagulation in patients with trigger-induced and device-detected sub-clinical AF, ischaemic stroke despite anticoagulation, and the indications for percutaneous/surgical left atrial appendage exclusion. AF ablation is a first-line rhythm control option for suitable patients with paroxysmal AF, and in specific patients, rhythm control can improve prognosis. The AF duration threshold for early cardioversion was reduced from 48 to 24 h, and a wait-and-see approach for spontaneous conversion is advised to promote patient safety. Lastly, strong emphasis is given to optimize the implementation of AF guidelines in daily practice using a patient-centred, multidisciplinary and shared-care approach, with the simultaneous launch of a patient version of the guideline.

Introduction Acute heart failure (HF) is a major cause of unplanned hospitalisation characterised by excess body water. A restriction in oral fluid intake is commonly imposed on patients as an adjunct to pharmacological therapy with loop diuretics, but there is a lack of evidence from traditional randomised controlled trials (RCTs) to support the safety and effectiveness of this intervention in the acute setting.This study aims to explore the feasibility of using computer alerts within the electronic health record (EHR) system to invite clinical care teams to enrol patients into a pragmatic RCT at the time of clinical decision-making. It will additionally assess the effectiveness of using an alert to help address the clinical research question of whether oral fluid restriction is a safe and effective adjunct to pharmacological therapy for patients admitted with fluid overload.Methods and analysis THIRST (Randomised Controlled Trial within the electronic Health record of an Interruptive alert displaying a fluid Restriction Suggestion in patients with the treatable Trait of congestion) Alert is a single-centre, parallel-group, open-label pragmatic RCT embedded in the EHR system that will be conducted as a feasibility study at an National Health Service (NHS) hospital in London. The clinical care team will be invited to enrol suitable patients in the study using a point-of-care alert with a target sample size of 50 patients. Enrolled patients will then be randomised to either restricted or unrestricted oral fluid intake. Two primary outcomes will be explored (1) the proportion of eligible patients enrolled in the study and (2) the mean difference in oral fluid intake between randomised groups. A series of secondary outcomes are specified to evaluate the effectiveness of the alert, adherence to the randomised treatment allocation and the quality of data generated from routine care, relevant to the outcomes of interest.Ethics and dissemination This study was approved by Riverside Research Ethics Committee (Ref: 22/LO/0889) and will be published on completion.Trial registration number NCT05869656.

Iron homoeostasis is tightly regulated, with hepcidin and soluble transferrin receptor (sTfR) playing significant roles. However, the genetic determinants of these traits and the biomedical consequences of iron homoeostasis variation are unclear. In a meta-analysis of 12 cohorts involving 91,675 participants, we found 43 genomic loci associated with either hepcidin or sTfR concentration, of which 15 previously unreported. Mapping to putative genes indicated involvement in iron-trait expression, erythropoiesis, immune response and cellular trafficking. Mendelian randomisation of 292 disease outcomes in 1,492,717 participants revealed associations of iron-related loci and iron status with selected health outcomes across multiple domains. These associations were largely driven by HFE, which was associated with the largest iron variation. Our findings enhance understanding of iron homoeostasis and its biomedical consequences, suggesting that lifelong exposure to higher iron levels is likely associated with lower risk of anaemia-related disorders and higher risk of genitourinary, musculoskeletal, infectious and neoplastic diseases.

Introduction: Ascending aortic diameter (AAoD) is commonly monitored to manage patients at risk of aortic dissection. Z-scores have also been proposed to identify at risk aortas, adjusting AAo for age, gender, and body surface area (BSA). Despite improved imaging and proven association of AAoD with age, sex and BSA, cutoff remains at 4.5 cm for monitoring and 5.5 cm for surgery in guidelines. However, studies like International Registry of Acute Aortic Dissection found that most aortic dissection had AAoD<5.5 cm. Aim: Identify AAoD in the UK Biobank population and compare current 4.5 cm cutoff with Z-scores to classify cases with dilated ascending aortas. Methods: Using cardiac magnetic resonance images of participants in the UK Biobank, we applied a pre-trained neural network to segment and quantify the AAoD. We also obtained demographics and clinical covariates for the participants with AAoD. Two common Z-scores were calculated using published equations including: (1) age, height, and sex (Z-HAS) and (2) age, BSA and sex (Z-BAS). We identified participants with AAoD>4.5 cm and compared them with Z>2 cutoff value that might require imaging follow-up for managing their dilated aortas. Results: AAoD diameter was calculated for 44,799 participants (22,983 females and 21,816 males). Common demographics in both groups are listed in the Table. Average AAoD was 3.15±0.32 cm in females and 3.44±0.35 cm in males. Diameter cutoff of 4.5 cm identified 15 females and 110 males with dilated aortas. On the other hand, Z-HAS classified 862 females and 674 males, while Z-BAS classified 583 females and 405 males (orange dots in the top and bottom panels of Figure, respectively) with higher aortic diameter that might require regular follow-up imaging. Conclusion: Z-Score might identify more people at dilated aortas as compared to the hard cutoff. Future work is needed to define whether Z scores are more sensitive means of identifying patients who might be at increased risk of aortic dissection.

BackgroundThe effects of α and ß adrenergic receptor modulation on the risk of developing heart failure (HF) remains uncertain due to a lack of randomized controlled trials. This study aimed to estimate the effects of α and ß adrenergic receptors modulation on the risk of HF and to provide proof of principle for genetic target validation studies in HF.MethodsGenetic variants within the cis regions encoding the adrenergic receptors α1A, α2B, ß1, and ß2 associated with blood pressure in a 757,601-participant genome-wide association study (GWAS) were selected as instruments to perform a drug target Mendelian randomization study. Effects of these variants on HF risk were derived from the HERMES GWAS (542,362 controls; 40,805 HF cases).ResultsLower α1A or ß1 activity was associated with reduced HF risk: odds ratio (OR) 0.83 (95% CI 0.74–0.93, P = 0.001) and 0.95 (95% CI 0.93–0.97, P = 8 × 10−6). Conversely, lower α2B activity was associated with increased HF risk: OR 1.09 (95% CI 1.05–1.12, P = 3 × 10−7). No evidence of an effect of lower ß2 activity on HF risk was found: OR 0.99 (95% CI 0.92–1.07, P = 0.95). Complementary analyses showed that these effects were consistent with those on left ventricular dimensions and acted independently of any potential effect on coronary artery disease.ConclusionsThis study provides genetic evidence that α1A or ß1 receptor inhibition will likely decrease HF risk, while lower α2B activity may increase this risk. Genetic variant analysis can assist with drug development for HF prevention.

Summary paragraph Heart failure (HF), a syndrome of symptomatic fluid overload due to cardiac dysfunction, is the most rapidly growing cardiovascular disorder. Despite recent advances, mortality and morbidity remain high and treatment innovation is challenged by limited understanding of aetiology in relation to disease subtypes. Here we harness the de-confounding properties of genetic variation to map causal biology underlying the HF phenotypic spectrum, to inform the development of more effective treatments. We report a genetic association analysis in 1.9 million ancestrally diverse individuals, including 153,174 cases of HF; 44,012 of non-ischaemic HF; 5,406 cases of non-ischaemic HF with reduced ejection fraction (HFrEF); and 3,841 cases of non-ischaemic HF with preserved ejection fraction (HFpEF). We identify 66 genetic susceptibility loci across HF subtypes, 37 of which have not previously been reported. We map the aetiologic contribution of risk factor traits and diseases as well as newly identified effector genes for HF, demonstrating differential risk factor effects on disease subtypes. Our findings highlight the importance of extra-cardiac tissues in HF, particularly the kidney and the vasculature in HFpEF. Pathways of cellular senescence and proteostasis are notably uncovered, including IGFBP7 as an effector gene for HFpEF. Using population approaches causally anchored in human genetics, we provide fundamental new insights into the aetiology of heart failure subtypes that may inform new approaches to prevention and treatment.

BACKGROUND:HFrEF is a heterogenous condition with high mortality. We used serial assessments of 4210 circulating proteins to identify distinct novel protein-based HFrEF subphenotypes and to investigate underlying dynamic biological mechanisms. Herewith we aimed to gain pathophysiological insights and fuel opportunities for personalised treatment. METHODS:In 382 patients, we performed trimonthly blood sampling during a median follow-up of 2.1 [IQR:1.1-2.6] years. We selected all baseline samples and two samples closest to the primary endpoint (PEP; composite of cardiovascular mortality, HF hospitalization, LVAD implantation, and heart transplantation) or censoring, and applied an aptamer-based multiplex proteomic approach. Using unsupervised machine learning methods, we derived clusters from 4210 repeatedly measured proteomic biomarkers. Sets of proteins that drove cluster allocation were analysed via an enrichment analysis. Differences in clinical characteristics and PEP occurrence were evaluated. FINDINGS:We identified four subphenotypes with different protein profiles, prognosis and clinical characteristics, including age (median [IQR] for subphenotypes 1-4, respectively:70 [64, 76], 68 [60, 79], 57 [47, 65], 59 [56, 66]years), EF (30 [26, 36], 26 [20, 38], 26 [22, 32], 33 [28, 37]%), and chronic renal failure (45%, 65%, 36%, 37%). Subphenotype allocation was driven by subsets of proteins associated with various biological functions, such as oxidative stress, inflammation and extracellular matrix organisation. Clinical characteristics of the subphenotypes were aligned with these associations. Subphenotypes 2 and 3 had the worst prognosis compared to subphenotype 1 (adjHR (95%CI):3.43 (1.76-6.69), and 2.88 (1.37-6.03), respectively). INTERPRETATION:Four circulating-protein based subphenotypes are present in HFrEF, which are driven by varying combinations of protein subsets, and have different clinical characteristics and prognosis. CLINICAL TRIAL REGISTRATION:ClinicalTrials.gov Identifier: NCT01851538https://clinicaltrials.gov/ct2/show/NCT01851538. FUNDING:EU/EFPIA IMI2JU BigData@Heart grant n°116074, Jaap Schouten Foundation and Noordwest Academie.

Objective Patient phenotype definitions based on terminologies are required for the computational use of electronic health records. Within UK primary care research databases, such definitions have typically been represented as flat lists of Read terms, but Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) (a widely employed international reference terminology) enables the use of relationships between concepts, which could facilitate the phenotyping process. We implemented SNOMED CT-based phenotyping approaches and investigated their performance in the CPRD Aurum primary care database. Materials and Methods We developed SNOMED CT phenotype definitions for 3 exemplar diseases: diabetes mellitus, asthma, and heart failure, using 3 methods: "primary" (primary concept and its descendants), "extended" (primary concept, descendants, and additional relations), and "value set" (based on text searches of term descriptions). We also derived SNOMED CT codelists in a semiautomated manner for 276 disease phenotypes used in a study of health across the lifecourse. Cohorts selected using each codelist were compared to "gold standard" manually curated Read codelists in a sample of 500 000 patients from CPRD Aurum. Results SNOMED CT codelists selected a similar set of patients to Read, with F1 scores exceeding 0.93, and age and sex distributions were similar. The "value set" and "extended" codelists had slightly greater recall but lower precision than "primary" codelists. We were able to represent 257 of the 276 phenotypes by a single concept hierarchy, and for 135 phenotypes, the F1 score was greater than 0.9. Conclusions SNOMED CT provides an efficient way to define disease phenotypes, resulting in similar patient populations to manually curated codelists.

Background: Individuals with South Asian ancestry have higher risk of heart disease than other groups in Western countries; however, most genetic research has focused on European-ancestry (EUR) individuals. It is unknown whether reported genetic loci and polygenic scores (PGSs) for cardiometabolic traits are transferable to South Asians, and whether PGSs have utility in clinical settings. Methods: Using data from 22,000 British Pakistani and Bangladeshi individuals with linked electronic health records from the Genes & Health cohort (G&H), we conducted genome-wide association studies (GWAS) and characterised the genetic architecture of coronary artery disease (CAD), body mass index (BMI), lipid biomarkers and blood pressure. We applied a new technique to assess the extent to which loci from GWAS in EUR samples were transferable. We tested how well existing findings from EUR studies performed in genetic risk prediction and Mendelian randomisation in G&H. Results: Trans-ancestry genetic correlations between G&H and EUR samples for the tested traits were not significantly lower than 1, except for BMI (rg=0.85, p=0.02). We found evidence for transferability for the vast majority of loci from EUR discovery studies that were sufficiently powered to replicate in G&H. PGSs showed variable transferability in G&H, with the relative accuracy compared to EUR (ratio of incremental r2/AUC) [≥]0.95 for HDL-C, triglycerides, and blood pressure, but lower for BMI (0.78) and CAD (0.42). We observed significant improvement in categorical net reclassification in G&H (NRI=3.9%; 95% CI 0.9-7.0) when adding a previously developed CAD PGS to clinical risk factors (QRISK3). We used transferable loci as genetic instruments in trans-ancestry Mendelian randomisation and found evidence of an increased CAD risk for higher LDL-C and BMI, and for lower HDL-C in G&H, consistent with our findings for EUR samples. Conclusions: The genetic loci for CAD and its risk factors are largely transferable from EUR studies to British Pakistanis and Bangladeshis, whereas the transferability of PGSs varies greatly between traits. Our analyses suggest clinical utility for addition of PGS to existing clinical risk prediction tools for this population.