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PubMed2026

Interactive exploration of biobank-scale ancestral recombination graphs with Lorax.

MOTIVATION: Ancestral Recombination Graphs (ARGs) provide a comprehensive representation of genetic ancestry and underpin analyses of natural selection, disease association, and population history. However, existing visualization tools are limited in scalability and interactivity, making ARGs difficult to explore at biobank scale. RESULTS: We introduce Lorax, a GPU-accelerated, web-native platform for real-time visualization of population-scale ARGs. Lorax integrates genomic position, coalescent time, local genealogy, and metadata, enabling interactive exploration of ancestry and variant inheritance in biobank-scale datasets. AVAILABILITY AND IMPLEMENTATION: Lorax is freely available as a live demo at https://lorax.ucsc.edu/ and as a Python package "lorax-arg" on PyPI. The source code and documentation are available on GitHub at https://github.com/pratikkatte/lorax.

Software↗

PubMed2026

Exome sequencing and large-scale analysis of electronic medical record-linked biobank data identify candidate deafness genes.

INTRODUCTION: Rapid advances in whole-exome sequencing (WES) have enabled large-scale detection of pathogenic variants. Although hundreds of genes are implicated in hearing loss, up to half of inherited cases remain unsolved, limiting eligibility for gene therapy trials that require genetic diagnosis. Biobanks and electronic medical records (EMRs) offer opportunities to integrate genomic and clinical data at scale and expand the spectrum of hearing loss genes. Despite clinical value, EMRs often lack key information such as inheritance patterns, posing challenges for accurate interpretation. METHODS: WES was performed on DNA samples from 1038 hearing-impaired patients enrolled in the Maccabi Research and Innovation Center Tipa Biobank. Clinical data were extracted from EMRs. Audiograms were available for all cases, although data on age of onset, family history and mode of inheritance were mostly unavailable. We applied a scalable bioinformatics analysis strategy for high-throughput annotation, filtering and prioritisation of WES variants across more than 1000 patients, designed to accommodate incomplete and heterogeneous clinical records. RESULTS: Using this approach, 15% of cases were solved or potentially solved through known or novel variants in established deafness genes. Homozygous variants in novel candidate genes were identified in 3% of cases. Functional characterisation was performed for promising candidate genes to validate their role in the ear. CONCLUSION: These findings demonstrate that WES can determine disease aetiology in large, genetically heterogeneous populations, even in the context of incomplete clinical data. This approach supports large-scale genetic screening and provides a framework for identifying patients who may benefit from emerging gene-based therapies.

Genetic Testing↗

PubMed2026

Genome-wide association study of asthma with high treatment burden and/or worse outcomes defined using electronic healthcare data in UK Biobank.

BACKGROUND: In ∼10% of asthma patients, symptoms remain uncontrolled despite maximal treatment, representing an unmet clinical need. The causal variants, genes and pathways underlying genetic risk factors have not been fully elucidated, and it is unclear whether there are unique genetic risk factors for this asthma subtype. METHODS: We used electronic healthcare records linked to UK Biobank to identify asthma patients with high treatment burden and/or worse outcomes. We performed a genome-wide association study (GWAS) with this case population and healthy controls. We sought replication for associated (p≤5×10-6) signals in four independent studies (12 152 cases and 32 316 controls). Replicated signals were fine-mapped and linked to genes and pathways. RESULTS: In total, 7681 participants met our case definition and showed enrichment for adult-onset asthma, female gender and higher body mass index compared to asthma individuals not meeting case criteria. GWAS with 7681 cases and 38 405 controls revealed 21 reproducible association signals that had previously been associated with asthma, but had a larger effect size in our study. Variant-to-gene mapping highlighted 85 candidate genes, five of which were considered high confidence (BACH2, D2HGDH, IL1RL1, RPS26, SMAD3). CONCLUSION: We present the first use of electronic healthcare records in UK Biobank to identify a subtype of asthma enriched for patients with high treatment burden and/or worse outcomes. Our findings support the role of known asthma genes, highlighting genetic risk variants with stronger effect in these groups of patients. The prioritised genes provide potential therapeutic opportunities for this difficult-to-treat patient population.

Journal Article↗

PubMed2026

Arrhythmia and cardiomyopathy risk in Taiwan with complementary biobank evidence on thyroid genetic susceptibility: an integrative population-based framework.

BACKGROUND: Arrhythmia-induced cardiomyopathy (AiCM) is a potentially reversible cause of ventricular dysfunction; however, only a subset of patients with arrhythmia develop cardiomyopathy. Emerging evidence suggests that endocrine factors, particularly thyroid dysfunction with genetic susceptibility, may contribute to inter-individual variability in arrhythmia-related myocardial outcomes. METHODS: We performed a dual-cohort population-based study using the National Health Insurance Research Database (NHIRD, 2000-2015) and the Taiwan Biobank (TWB). In NHIRD, we examined the association between newly diagnosed arrhythmia and incident cardiomyopathy using Cox proportional hazards models. In TWB, genome-wide data, thyroid-stimulating hormone (TSH), polygenic risk scores (PRSs), lifestyle factors, and metabolic comorbidities were analyzed using multivariable regression and interaction models to assess determinants of thyroid dysfunction. RESULTS: In the NHIRD cohort, arrhythmia was associated with a significantly increased risk of incident cardiomyopathy (adjusted hazard ratio (aHR): 2.49, 95% CI: 1.94-2.96), with atrial fibrillation showing the strongest association among arrhythmia subtypes. In the TWB cohort, a higher thyroid polygenic risk score was strongly associated with thyroid dysfunction (adjusted odds ratio (aOR): 6.64, 95% CI: 5.86-7.52). The association between genetic susceptibility and thyroid dysfunction was further modified by metabolic and lifestyle factors, including diabetes, hyperlipidemia, and dietary patterns. Genome-wide analysis identified multiple loci associated with thyroid-stimulating hormone regulation, consistent with a polygenic architecture of thyroid endocrine traits. CONCLUSION: Arrhythmia was associated with an increased risk of cardiomyopathy in a nationwide cohort, while thyroid genetic susceptibility was strongly associated with thyroid dysfunction in a biobank cohort and modified by metabolic and lifestyle factors. These findings provide complementary population-level evidence of parallel cardiovascular and endocrine-genetic associations. Because the two cohorts were not individually linked, causal inference cannot be established. The results support a systems-level framework of endocrine-cardiac interaction and suggest that integrated clinical and genetic risk assessment may help identify individuals who warrant closer monitoring.

arrhythmia↗

PubMed2026

Genetic Correlation Between Brain Imaging Phenotypes and Externalizing Behavior: A Large-Scale LDSC Analysis of UK Biobank IDPs.

Externalizing has been associated with differences in brain structure and function; however, it remains unclear whether these associations reflect shared common-variant genetic influences. Cross-trait linkage disequilibrium score regression was used to estimate genome-wide genetic correlations between externalizing genome-wide association study (GWAS) results and 3,935 brain imaging-derived phenotypes from the UK Biobank BIG40 resource. The imaging phenotypes covered structural magnetic resonance imaging (MRI), diffusion MRI, susceptibility-weighted imaging, resting-state functional MRI, and task-based functional MRI. Results were included in the primary analysis when the imaging phenotype had positive single-nucleotide polymorphism (SNP) heritability, a heritability Z statistic of at least 1.96, a mean GWAS chi-square statistic of at least 1.02, at least 200,000 regression SNPs, and a complete LDSC result without a fatal error. Technical imaging quality-control phenotypes were excluded from biological inference. Individual results were corrected using the Benjamini-Hochberg false discovery rate procedure. Aggregated Cauchy association tests (ACATs) were used to evaluate evidence across all imaging phenotypes and within predefined imaging categories. Statistical power, simultaneous confidence bounds, and alternative quality-control definitions were examined in sensitivity analyses. Of the 3,935 imaging phenotypes, 3,716 produced estimable genetic correlations, 2,980 met the primary LDSC quality-control criteria, and 2,967 were classified as biological imaging phenotypes. No individual phenotype survived false discovery rate correction. The smallest unadjusted P value was 0.0005, and the minimum adjusted q value was 0.486. The distribution of genetic correlations was centered near zero, with a median genetic correlation of 0.0014 and a median absolute genetic correlation of 0.0338. ACAT provided no evidence of an aggregate association across all biological imaging phenotypes (P = 0.302), and no predefined imaging category survived multiple-testing correction. The median minimum detectable genetic correlation at 80% power was 0.216. Bonferroni-adjusted simultaneous confidence intervals were fully contained within the interval [-0.30, 0.30] for 80.0% of phenotypes in the primary analysis and 88.0% under the stringent heritability quality-control definition. Broad and stringent sensitivity analyses produced the same overall conclusions. In this study, no statistically robust evidence of genome-wide genetic correlations between externalizing and individual UK Biobank brain imaging phenotypes was found. Nevertheless, small, localized, mixed-direction, or developmentally specific genetic effects remain possible.

Journal Article↗

PubMed2026

Large-Scale Plasma Proteomics Enhances Prediction of Liver-Related Events Among Individuals With Prediabetes and Type 2 Diabetes: A Prospective Cohort Study in the UK Biobank.

OBJECTIVE: To develop a protein risk score (ProRS) for predicting liver-related events (LREs) in patients with diabetes and compare its predictive performance with the Fibrosis-4 Index (FIB-4) and an established polygenic risk score. RESEARCH DESIGN AND METHODS: This prospective cohort study included 13 516 individuals with prediabetes and type 2 diabetes (T2D) from the UK Biobank. Cox proportional hazards models and LASSO regression were applied to identify proteins associated with incident LREs and construct the ProRS. Predictive performance was assessed using Harrell's C-index, time-dependent area under the receiver operating characteristic curve, net reclassification improvement and integrated discrimination improvement. RESULTS: Over a median follow-up of 13.5 years, 171 (1.3%) incident LREs occurred. We identified 877 proteins associated with LRE risk, primarily enriched in inflammatory signalling, extracellular matrix remodelling and complement/coagulation cascades. In the training set, we developed a 24-protein ProRS (C-index, 0.842; 95% CI 0.797-0.884) that stratified individuals into low-, medium- and high-risk groups, with 10-year cumulative incidences of LREs of 0.2%, 1.2% and 14.2%, respectively. Compared with the low-risk group, the hazard ratio for LREs was 57.1 (95% CI 31.9-102) in the high-risk group. In the internal validation set, the ProRS model (C-index, 0.876; 95% CI 0.827-0.920) accurately predicted both short- and long-term LREs and outperformed FIB-4 index (C-index, 0.733; 95% CI 0.657-0.807) and polygenic risk score (C-index, 0.636; 95% CI 0.564-0.706). CONCLUSIONS: The protein risk score demonstrated superior performance compared with the FIB-4 index and the polygenic risk score in predicting incident LREs among individuals with prediabetes and T2D. The score allows stratification of individuals according to liver-related risk, though external validation in multi-ethnic cohorts is warranted.

Humans↗

PubMed2025

Risk of Cardiovascular Disease Mortality in Patients With Diagnosed Cancer and Associated Genetic and Proteomic Mechanisms: A UK Biobank-Based Cohort Study.

BACKGROUND: Previous studies have identified a link between cancer and cardiovascular disease; however, the underlying genetic and proteomic mechanisms remain unclear. Therefore, this study aimed to investigate the association between cancer diagnosis and cardiovascular mortality and to explore the potential mechanisms involved. METHODS: A total of 379 944 participants without cardiovascular disease at baseline, including 65 047 individuals with cancer, were recruited from the UK Biobank database. The primary end point was cardiovascular death. Multivariate Cox regression was performed to evaluate the risk of cardiovascular death in populations with and without cancer. Genome-wide association studies, phenome-wide association studies, and proteomic analyses were applied to investigate the underlying genetic and proteomic mechanisms. RESULTS: Multivariate Cox regression analysis showed an increased risk of cardiovascular death in the group with cancer (hazard ratio, 1.50 [95% CI, 1.40-1.61]) after multivariable adjustment. Proteomic analysis confirmed a strong association between cancer and cardiovascular disease, primarily involving pathways related to complement and coagulation cascades, and various inflammatory processes. In contrast, genome-wide association studies and phenome-wide association studies revealed only a limited number of shared genetic variations between cancer and cardiovascular conditions, such as hypertension and cardiac dysrhythmias. CONCLUSIONS: Cardiovascular risk is increased in patients with cancer and may be related to altered expression of inflammation- and coagulation-related proteins. In clinical practice, it is recommended to emphasize the management of endocrine, kidney, and inflammation-related risk factors in the population with cancer.

Humans↗

PubMed2026

Dynamic Fusion of Genomics and Functional Network Connectivity in UK Biobank Reveals Schizophrenia-Related SNP Manifolds.

Many mental disorders show strong genetic influence. In parallel, dynamic functional network connectivity (dFNC) has shown high sensitivity to brain changes related to mental disorders. However, previous studies linking dFNC to genetics largely follow a paradigm to identify associations between one set of genetic factors and multiple sets of connectivity features from different dFNC states, ignoring the potential variability in genetic correlates across states. We propose a novel joint ICA (jICA)-based "dynamic fusion" framework to identify dynamically tuned genetic manifolds. A sliding window approach was utilized to estimate four dFNC states and compute subject-level state-average dFNC (sa-dFNC) features. The sa-dFNC features of each state were combined with schizophrenia risk single nucleotide polymorphisms (SNPs) within a jICA fusion framework, resulting in four parallel fusions in 32,861 individuals of the UK Biobank cohort. The extracted four sets of joint SNP-dFNC components were further validated for clinical relevance in a combined schizophrenia cohort of 820 individuals (348 patients). The similarity of SNP-dFNC components across four parallel fusions was evaluated as a measure of state variability. We observed a mixture of "state-invariant" and "state-variant" components for SNP and dFNC modalities. Particularly, the schizophrenia-related state-variant SNP components, or manifolds, complemented each other by capturing different SNPs involved in the same biological functions, revealing a partition of genomic risk particularly elicited by the dynamics of brain function. By augmenting the SNP factors to state-variant manifolds, this dynamic fusion framework promises additional insights into the underlying genetic risk of disease-related alterations in dynamic brain function.

Humans↗

PubMed2025

Extracting and calibrating evidence of variant pathogenicity from population biobank data.

Genomic medicine requires a robust evidence base of variant phenotypic impacts, which remains incomplete even in extensively studied genes with monogenic disease associations. Here, we evaluated the broad potential of using population cohort data to identify evidence that can be used in variant assessment. Across 41 genes related to 18 clinically actionable monogenic phenotypes, we calculated variant-level odds ratios of disease enrichment using data from 469,803 UK Biobank participants. We found significant differences in odds ratio values between ClinVar-labeled pathogenic and benign variants in 11 phenotypes, spanning both common and rare disorders. To facilitate clinical translation, we calibrated the strength of evidence provided by variant-level odds ratios to align with American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) interpretation guidelines (PS4 criterion) and found that odds ratios may reach "moderate," "strong," or "very strong" evidence, varying by phenotype and gene. Overall, we found that 2.6% (N = 12,350) of participants harbor a rare variant of uncertain significance (VUS) with at least moderate evidence of pathogenicity-an indication of potentially unrecognized disease risk. Finally, by incorporating computational and functional data alongside population-based odds ratios, we identified variants that met the criteria for clinical reclassification. Notably, using this approach, we identified that 12.4% of rare VUSs in LDLR seen in participants meet diagnostic criteria to be classified as likely pathogenic, demonstrating its potential to scale the reclassification of VUSs.

Humans↗

PubMed2025

Prevalence and determinants of profound vitamin D deficiency (25-hydroxyvitamin D <10 nmol/L) in the UK Biobank and potential implications for disease association studies.

BACKGROUND: 25-hydroxyvitamin D (25OHD) is the principal biomarker of vitamin D status. Values below the assay detection limit (<10 nmol/L) are often reported as missing. Thus the most severely deficient participants are excluded from research which can lead to inaccurate findings such as underestimated prevalence of deficiency, overlooked risk factors, and biased evaluation of disease associations. METHODS: In total 369,626 individuals from the UK Biobank cohort were included in this study. Data on 25OHD concentration and relevant demographic and lifestyle factors such as age, supplement intake, diet, and time spent outdoors were used in the analyses. Ambient UVB radiation was approximated for each participant. 25OHD was evaluated as a categorical outcome and we reintroduced participants with 25OHD values < 10 nmol/L (conventionally reported as missing values) back to the dataset. Adjusted regression models were used to investigate the determinants of profound (25OHD <10 nmol/L) and severe (10-25 nmol/L) vitamin D deficiency and to assess disease associations (with 25-50 nmol/L as the reference category). RESULTS: 1,784 (0.48 %) individuals were profoundly deficient and a further 47,226 (12.78 %) individuals were severely vitamin D deficient. The proportions of profoundly and severely deficient were highest among Asians, 9 % and 47 %, respectively. Ambient UVB radiation was the second strongest predictor: comparing the lowest vs. highest quartile, the risk of profound deficiency was 17-fold increased and that of severe deficiency 7.5-fold increased. Use of vitamin D supplements substantially reduced risk of profound (4.4-fold) and severe (2.5-fold) deficiency, as did fish intake (5- and 1.9-fold, respectively). Profound deficiency was more strongly associated with chronic illness, diabetes, and emphysema compared to severe deficiency. CONCLUSION: The prevalence of profound and severe vitamin D deficiency among Asian and Black ethnicities in the UK is high and requires targeted action. Solar radiation is potent in protecting against profound and severe vitamin D deficiency. Studies evaluating the relationship between vitamin D status and other health outcomes may be biased if profoundly deficient participants are excluded.

Humans↗

PubMed2024

Ribosomal DNA copy number variation associates with hematological profiles and renal function in the UK Biobank.

The phenotypic impact of genetic variation of repetitive features in the human genome is currently understudied. One such feature is the multi-copy 47S ribosomal DNA (rDNA) that codes for rRNA components of the ribosome. Here, we present an analysis of rDNA copy number (CN) variation in the UK Biobank (UKB). From the first release of UKB whole-genome sequencing (WGS) data, a discovery analysis in White British individuals reveals that rDNA CN associates with altered counts of specific blood cell subtypes, such as neutrophils, and with the estimated glomerular filtration rate, a marker of kidney function. Similar trends are observed in other ancestries. A range of analyses argue against reverse causality or common confounder effects, and all core results replicate in the second UKB WGS release. Our work demonstrates that rDNA CN is a genetic influence on trait variance in humans.

Humans↗

PubMed2024

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank.

The phenotypic impact of compound heterozygous (CH) variation has not been investigated at the population scale. We phased rare variants (MAF ∼0.001%) in the UK Biobank (UKBB) exome-sequencing data to characterize recessive effects in 175,587 individuals across 311 common diseases. A total of 6.5% of individuals carry putatively damaging CH variants, 90% of which are only identifiable upon phasing rare variants (MAF < 0.38%). We identify six recessive gene-trait associations (p < 1.68 × 10-7) after accounting for relatedness, polygenicity, nearby common variants, and rare variant burden. Of these, just one is discovered when considering homozygosity alone. Using longitudinal health records, we additionally identify and replicate a novel association between bi-allelic variation in ATP2C2 and an earlier age at onset of chronic obstructive pulmonary disease (COPD) (p < 3.58 × 10-8). Genetic phase contributes to disease risk for gene-trait pairs: ATP2C2-COPD (p = 0.000238), FLG-asthma (p = 0.00205), and USH2A-visual impairment (p = 0.0084). We demonstrate the power of phasing large-scale genetic cohorts to discover phenome-wide consequences of compound heterozygosity.

Humans↗

PubMed2026

Joint effects of childhood adversity and genetic risk for psychosis on psychopathology in the UK Biobank.

BACKGROUND: The individual effects of genetic factors and adverse childhood experiences (ACEs) on risk of psychosis, including schizophrenia (SCZ) and bipolar disorder (BIP), have been widely acknowledged, but their interaction effects on individual psychopathological symptoms remain unclear. METHODS: Based on data from 163,704 individuals in the UK Biobank, we investigated the joint effects of polygenic risk scores (PRSs) of SCZ and BIP and ACEs on psychopathology. ACEs status and 55 psychopathological symptoms from seven domains were measured retrospectively using an online mental health questionnaire in 2016. Recent genome-wide association studies for SCZ and BIP were combined with genotype data to generate PRSs. Logistic regression analyses were then conducted to explore univariate and joint main effects of PRSs and ACEs on psychopathological symptoms, as well as their additive and multiplicative interaction effects. RESULTS: The interaction mechanisms for PRSs and ACEs varied across symptom domains: additive interactions were observed on the depression (RERIBIP-ACEs = 0.20-0.25), anxiety (RERISCZ-ACEs = 0.20; RERIBIP-ACEs = 0.22-0.26), help-seeking (RERISCZ-ACEs = 0.24; RERIBIP-ACEs = 0.23), and cognition domains (RERISCZ-ACEs = -0.23 to -0.17), whereas multiplicative interactions were only detected on the psychotic (betaSCZ-ACEs = -0.543; betaBIP-ACEs = -0.181), mania (betaBIP-ACEs = -0.195), self-harm or suicide (betaSCZ-ACEs = -0.118), and cognitive domains (betaSCZ-ACEs = -0.204 to -0.157). CONCLUSIONS: The interplay mechanisms for genetic liability to SCZ and BIP and ACEs vary across symptom domains. This study reveals heterogeneity in gene-ACEs interaction mechanisms underlying psychosis and may provide personalized guidance for psychological care after ACEs.

Humans↗

PubMed2025

Clinical implications of bone marrow adiposity identified by phenome-wide association and Mendelian randomization in the UK Biobank.

Bone marrow adiposity changes in diverse diseases, but the full scope of these, and whether they are directly influenced by marrow adiposity, remains unknown. To address this, we previously measured the bone marrow fat fraction of the femoral head, total hip, femoral diaphysis, and spine of over 48,000 UK Biobank participants. Here, we first use these data for PheWAS to identify diseases associated with marrow adiposity at each site. This reveals associations with 47 incident diseases across 12 disease categories, including osteoporosis, fracture, type 2 diabetes, cardiovascular diseases, cancers, and other conditions that burden public health worldwide. Intriguingly, type 2 diabetes associates positively with spine bone marrow adiposity but negatively with marrow adiposity at femoral sites. We then establish PRSs based on bone-marrow-fat-fraction-associated SNPs and use PRS-PheWAS and Mendelian randomization to explore causal associations between marrow adiposity and disease. PRS-PheWAS reveals that genetic predisposition to increased marrow adiposity is positively associated with osteoporosis and fractures. Mendelian randomization further suggests that increased marrow adiposity at the diaphysis and total hip is causally associated with osteoporosis. Our findings substantially advance understanding of how marrow adiposity impacts human health and highlight its potential as a biomarker and/or therapeutic target for diverse human diseases.

Humans↗

PubMed2025

Newly identified single-nucleotide polymorphism associated with the transition from nonalcoholic fatty liver disease to liver fibrosis: results from a nested case-control study in the UK biobank.

BACKGROUND: Genetic factors may have a significant influence on the likelihood of liver fibrosis in individuals with nonalcoholic fatty liver disease (NAFLD). The present study was conducted to explore how single-nucleotide polymorphism (SNP) impacts the development of fibrosis in those suffering from NAFLD. MATERIALS AND METHODS: Utilizing the UK Biobank dataset, we conducted a nested case-control analysis among NAFLD participants, defining the case group as those with liver fibrosis and cirrhosis during follow-up. For our in vitro investigations, we employed the LX-2 human hepatic stellate cell line. Our procedures included cultivating these cells, employing SAMM50-rs2073080 plasmid techniques to enhance the expression of recently discovered SNPs, and conducting biochemical assays. To quantify gene expression, we used real-time PCR with fluorescence detection. RESULTS: The study analyzed data from 5467 participants (1094 cases and 4373 controls). Genome-wide association analysis identified nine significant loci, including the novel rs2073080 variant, strongly associated with NAFLD-associated hepatic fibrosis. In vitro TGF-β modeling revealed significant upregulation of α-SMA and COL1A1, confirming model effectiveness. Oxidative stress markers like elevated malondialdehyde (MDA) and reduced catalase (CAT) and superoxide dismutase (SOD) levels indicated liver damage in the TGF-β group. SAMM50-rs2073080 was upregulated in the NAFLD-associated fibrosis model. In vitro experiments on LX-2 cells showed that SAMM50-rs2073080 overexpression led to increased fibrosis, as indicated by higher cellular MDA levels and lower CAT and SOD levels, compared to the vector group. CONCLUSION: Our research highlights a significant association of SAMM50-rs2073080 with the progression of NAFLD to hepatic fibrosis, and the in vitro experiments further corroborated these findings.

Humans↗

PubMed2026

The presence or absence of standard modifiable cardiovascular risk factors in patients with myocardial infarction impacts long-term but not 30-day mortality: a UK Biobank prospective cohort study.

AIMS: Prior studies reported higher early mortality after acute myocardial infarction (MI) in patients without standard modifiable cardiovascular risk factors (SMuRFs), warranting further validation. We aimed to evaluate whether SMuRF-absence is associated with increased 30-day cardiovascular mortality following MI. METHODS AND RESULTS: We conducted a population-based cohort study using UK Biobank data (n = 487 177). Incident MI cases occurring between 2006 and 2022 were identified through linkage to hospital and death registries. Standard modifiable cardiovascular risk factors (diabetes, hypertension, hypercholesterolaemia, current smoker) were defined at baseline and continuously assessed until MI onset. Thirty-day mortality following MI was estimated using Cox proportional hazards models, adjusted for sociodemographic, clinical, and cardiogenomic variables, were used to estimate 30-day mortality risks. Logistic regression model was used to estimate mortality risk at 10 years post-MI. Among 15 463 patients experiencing an MI (1034 without SMuRFs), SMuRF-absence was not significantly associated with 30-day mortality (HR: 0.82, 95% CI: 0.65-1.04, P = 0.103). Propensity score-matched analyses supported these findings (HR: 0.95, 95% CI: 0.69-1.29, P = 0.729). Further analyses stratified by distinct time intervals (2006-2022) revealed no significant modification of this association by advancements in acute MI management. Interaction analyses indicated no significant effect modification by sex, age, socioeconomic status, or period of MI occurrence. However, extended analysis to 10 years revealed that SMuRF absence was significantly associated with lower long-term mortality (OR: 0.61, 95% CI: 0.49-0.75, P < 0.01). CONCLUSION: In this population-based cohort, SMuRF status significantly impacted long-term but not short-term mortality following MI, indicating early survival is predominantly driven by acute-phase factors rather than baseline cardiovascular risk profiles.

Humans↗

PubMed2026

Rapid derivation of cloning-competent cells from peripheral blood advances conservation biobanking.

Establishing viable cell lines from endangered species is essential for conservation, yet traditional fibroblast derivation from skin biopsies faces challenges including contamination risk and extended culture timelines. Here, we demonstrate that endothelial progenitor cells (EPCs) and pericytes isolated from peripheral blood represent robust alternatives to fibroblasts for biobanking. Compared to canid fibroblasts, canid blood-derived cells exhibit 2- to 3-fold faster doubling rates (15 to 20 h vs. ~35 h for fibroblasts) and reduced time to banked cell lines (1.5 to 2 wks vs. 3 to 4 wks for fibroblasts). Proteomic profiling of 32 canonical markers confirmed EPCs and pericytes represent distinct populations with lineage-specific molecular signatures. Optical genome mapping demonstrated equivalent genomic stability across cell types with no detectable structural variants or aneuploidies. Finally, interspecific somatic cell nuclear transfer (iSCNT) experiments confirmed both EPCs and pericytes generate viable canid embryos with efficiency meeting or exceeding fibroblasts. As a proof of concept for conservation cloning, iSCNT embryos made with gray wolf blood-derived cells had a 15% implantation rate following embryo transfer and resulted in six viable fetuses. These findings support integrating blood-derived cell banking into conservation programs, which enables opportunistic genetic preservation during standard management activities and expands options for genetic rescue through assisted reproductive technologies.

Animals↗

PubMed2024

Whole -genome survival analysis of 144 286 people from the UK Biobank identifies novel loci associated with blood pressure.

This study utilized UK Biobank data from 144 286 participants and employed whole-genome sequencing (WGS) data and time-to-event data over a 12-year follow-up period to identify susceptibility in genetic variants associated with hypertension. Following genotype quality control, 6 319 822 single nucleotide polymorphisms underwent analysis, revealing 31 significant variant-level associations. Among these, 29 were novel - 15 in Fibrillin-2 ( FBN2 ) and 4 in Junctophilin-2 ( JPH2 ). Mendelian randomization utilizing two identified variants (rs17677724 and rs1014754) suggested that a genetically induced decrease in heart FBN2 expression and an increase in adrenal gland JPH2 expression were causally linked to hypertension. Phenome-wide association (PheWAS) analysis using the FinnGen dataset confirmed positive associations of rs17677724 and rs1014754 with hypertension, assessed across 2727 traits in 377 277 individuals. Lastly, rs1014754 positively associated with kallistatin, whereas rs17677724 negatively associated with renin in the Fenland study, suggesting a counterregulatory response to high blood pressure. This study, employing WGS data, identified novel genetic loci and potential therapeutic targets for hypertension.

Humans↗