Biomedical subjects

Pradeep Natarajan

Publications and source records attributed to Pradeep Natarajan.

At least 19 recordsLinked to original sources

PubMed2026

Comparison of Performance of Publicly Available Polygenic Risk Scores to Predict Clinically Actionable Coronary Artery Calcium Scores: The BioHEART-CT Cohort.

AIM: Coronary artery disease (CAD) remains the leading cause of morbidity and mortality globally. Polygenic Risk Scores (PRS) have been trained against major adverse cardiovascular outcomes (MACE) in large cohorts. Few studies have examined the effectiveness of these CAD MACE PRS tools in detecting individuals with subclinical coronary calcification. An association would provide an opportunity for clinical translation and targeting of CT imaging to new patients at risk for subclinical disease. METHODS: An analysis of 53 publicly available CAD PRS tools was completed in participants of the BioHEART-CT Discovery 1000 cohort presenting for clinically referred CT coronary angiography (CCTA). Associations between PRS and two binary CACS outcomes reflecting clinically significant coronary calcification were assessed: a) Absolute CACS (CACS ≥100 Agatston units [AU]; and b) Percentile CACS (CACS ≥75th age-/sex-adjusted percentile). Models were adjusted for genetic principal components, modifiable cardiovascular risk factors, and age/sex (in Absolute CACS). A subgroup analysis was performed using Framingham Risk Score (FRS) at baseline. RESULTS: Among 803 BioHEART-CT Discovery 1000 participants, 487 (60.6%) had any detectable coronary calcium. Most PRS tools demonstrated significant association with CACS outcomes, particularly evident when PRS was modelled as a continuous predictor. For Percentile CACS, 94.3% of PRS tools were significantly associated after full adjustment (median OR per PRS SD 1.41 (IQR 1.23-1.60). Quintile-based analysis revealed that individuals in the Top Quintile PRS had up to 7.99-fold increased odds of Percentile CACS ≥75th compared to those in the Bottom Quintile. Analysis by FRS group revealed positive performance, especially in individuals of Low FRS wherein incorporating a PRS increased pre-test probability from 14% to 26%. CONCLUSION: Whilst most CAD PRS tools have been developed against clinical events, we show their ability to predict clinically relevant coronary calcification. Utility appears strongest in individuals traditionally considered lower risk, presenting an opportunity for clinical translation for improved diagnosis in the primary prevention setting, with the potential to triage individuals into a CACS screening pathway.

coronary artery disease↗

PubMed2026

Machine learning-driven spleen imaging and genomics uncover a splenic connection to coronary artery disease.

Despite advances in managing traditional risk factors, coronary artery disease (CAD) remains the leading cause of mortality. Circulating hematopoietic cells influence risk for CAD separately from traditional risk factors, but the role of a key regulating organ, the spleen, is unknown. The understudied spleen is a representation of the hematopoietic system optimally suited for unbiased radiologic investigations toward mechanistic insights. Here, we leveraged deep learning to extract 107 splenic radiomic features from abdominal magnetic resonance imaging (MRI) scans of 42,059 UK Biobank participants and of 2745 Mass General Brigham Biobank (MGBB) participants. Of these, 10 features from UK Biobank were associated with CAD. Genome-wide association analysis of CAD-associated features identified 219 loci, including 9p21. Variants at 9p21, the strongest yet mechanistically elusive CAD locus, were associated with splenic features such as run-length nonuniformity, reflecting heterogeneity of continuous texture regions. Research MRI findings were consistent internally, but external clinical validation highlighted challenges in translating analyses of abdominal MRI scans to routine clinical practice because of variability in imaging protocols and greater clinical heterogeneity among patients. Our study, combining deep learning with genomics, presents a framework to uncover potential splenic involvement in CAD and emphasizes translational gaps between research and clinical radiomics.

Humans↗

PubMed2026

REPLY: Heterogeneous Value of a Multicondition Cardiovascular PRS Panel.

Explore the source record for details and available documents.

Letter↗

PubMed2026

Genetic evidence supports the combined targeting of lipoprotein(a) and LDL cholesterol to reduce coronary artery disease risk.

Distinct genetic mechanisms govern how lipoprotein(a) (Lp(a)) and low-density lipoprotein cholesterol (LDL-C) promote atherosclerosis. It remains unclear whether targeting both provides additive cardiovascular benefits. Here we use coding loss-of-function variants in LPA and PCSK9 and genetic scores associated with Lp(a) and LDL-C levels to evaluate the effects of lowering Lp(a) and LDL-C on coronary artery disease (CAD) risk. Among 408,039 individuals from the UK Biobank, LPA or PCSK9 loss-of-function carriers have lower CAD risk than noncarriers (odds ratio (OR) 0.91 and 0.81). Carriers of both variants have even lower CAD risk (OR 0.73). Genetic lowering of Lp(a) and LDL-C showed a stronger reduction of CAD risk (OR 0.70) than either trait individually (OR 0.85 and 0.81) in the two-factor genetic score analysis. Among statin users, Lp(a) reduction was linearly associated with CAD risk. A phenome-wide association study revealed that combined therapy was associated with cardiometabolic benefits without adverse effects. The additive benefits were replicated in 65,171 individuals from the Mass General Brigham Biobank.

Humans↗

PubMed2026

Mechanism of age-related accumulation of mtDNA mutations in human blood.

Accumulation of mutant mitochondrial DNA (mtDNA) heteroplasmy is among the strongest signatures of ageing1. Here we investigated the underlying mechanism by calling mtDNA sequence, mtDNA abundance and mtDNA heteroplasmic variants in human blood using whole-genome sequences from approximately 750,000 individuals. We observed that mtDNA single-nucleotide variants (mtSNVs) accumulate sharply at age 60 years, occur at low levels of heteroplasmy, exhibit little evidence of positive selection and are likely to be predominantly neutral. The mutational spectrum of mtSNVs does not reflect oxidative lesions, as is commonly invoked, but is more consistent with mtDNA replication errors. To understand why mtSNVs become detectable with age, we performed a genome-wide association study for heteroplasmic mtSNV burden, identifying germline variants near TERT, TCL1A and SMC4, all of which have been linked to clonal haematopoiesis (CH)2. Rare-variant analysis also showed that high mtSNV burden is associated with mutations in numerous CH driver genes. These genetic associations persisted even after exclusion of individuals with known CH driver mutations. Our results support a model in which 'cryptic' mtDNA mutations initially arise randomly as replication errors but are undetectable in bulk. They then become apparent only through age-related expansion of cellular clones in blood. We propose that the high copy number and mutation rate of mtDNA make it a sensitive blood-based marker of somatic mosaicism due to CH. Our work mechanistically unifies three prominent signatures of ageing: common germline variants in TERT, CH and observed accrual of mtDNA mutations.

Humans↗

PubMed2026

The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration.

Rare coding variants can have large effects on disease risk and provide direct routes from human genetics to disease mechanisms and therapeutic targets, but their discovery is constrained by sample size, particularly for low-prevalence diseases. Here we establish the Biobank Rare Variant Analysis (BRaVa) consortium, a global rare variant association resource that integrates sequencing and linked health-record data from ten biobanks and cohorts comprising over 1.2 million individuals across diverse ancestries. We performed gene-based meta-analyses of rare coding variation across 33 clinical endpoints and 11 quantitative traits. Aggregating evidence across biobanks and ancestries identified 514 gene-trait associations, including 31 not previously reported in prior studies or curated association resources following systematic literature review. Notably, 36.1% of gene-level associations were undetectable in any individual biobank, and 91 emerged only through cross-ancestry meta-analysis, demonstrating that federated integration enables discovery beyond the reach of single cohorts. Similar gains were observed at the variant level, where 25.0% of phenotype-locus associations were detectable only through meta-analysis. Effect size estimates were correlated across ancestries with concordant directions of effect, supporting the generalizability of rare variant associations. The identified signals implicate pathways involved in transcriptional and epigenetic regulation, metabolism, vascular and epithelial biology, and immune function, highlighting rare coding variation as an engine for biological discovery across medical record phenotypes. For example, damaging variation in ANKRD12 implicates inflammatory transcriptional dysregulation in asthma and chronic obstructive pulmonary disease, and ultra-rare predicted loss-of-function variants in NAA15 link protein acetylation processes to type 2 diabetes risk. BRaVa establishes a scalable framework and freely available community resource for rare variant meta-analysis across global biobanks. Public release of gene- and variant-level association summary statistics provides a reference map of rare coding variant associations to support disease gene discovery, biological interpretation, and therapeutic target prioritization as sequencing-linked health-record resources continue to expand.

Journal Article↗

PubMed2026

GWAS Meta-analysis Identifies Novel Associated Loci and Points to Causal Tissues in Central Serous Chorioretinopathy.

OBJECTIVE: To define CSC genetic architecture and identify implicated ocular tissues, cell types, genes, and circulating proteins. DATA SOURCES: Genome-wide data were assembled from FinnGen, All of Us, Mass General Brigham Biobank, Million Veteran Program, and a Dutch chronic CSC cohort. Serum protein quantitative trait loci, human single-cell ocular atlases, and UK Biobank macular optical coherence tomography (OCT) imaging were used for downstream analyses. STUDY SELECTION: Five European-ancestry cohorts with genome-wide data and cohort-specific CSC case-control definitions were included, comprising 2,584 cases and 1,044,455 controls. Variants present in at least 2 cohorts were meta-analyzed. DATA EXTRACTION AND SYNTHESIS: Cohort-level GWASs were adjusted for age, age squared, sex, genotyping array or batch, and 10 genetic principal components, then combined using fixed-effects inverse-variance meta-analysis. Post-GWAS analyses included gene prioritization, colocalization, Mendelian randomization, single-cell disease-relevance scoring, and testing of a CSC genetic risk score in UK Biobank OCT images. MAIN OUTCOMES AND MEASURES: Genome-wide significant CSC loci, effector genes and proteins, tissue and cell-type enrichment, and CSC-relevant OCT abnormalities. RESULTS: Across 11,068,938 variants, 10 loci reached genome-wide significance (P < 5 × 10-8), including 3 novel loci near TGFB1, LINC00551, and LOC105375630 and 7 replicated loci near CFH, CD46, NOTCH4, PREX1, PTPRB, GATA5, and TNFRSF10A. Integrative analyses prioritized 10 candidate effector genes. Colocalization and Mendelian randomization implicated circulating TNFRSF10A, TGFB1, and CASP10 levels. Single-cell analyses localized genetic risk to sclera (P = 2.0 × 10-4) and vascular endothelial cells (P = 4.0 × 10-4), with fibroblast enrichment. In UK Biobank, OCT abnormalities were more frequent in the top vs bottom 1% of CSC genetic risk (18 of 109 [16.5%] vs 8 of 134 [6.0%]; odds ratio, 4.05; 95% CI, 1.65-10.87; P = .002). CONCLUSIONS AND RELEVANCE: In this GWAS meta-analysis, CSC susceptibility localized predominantly to scleral and vascular biology rather than primary retinal pigment epithelial dysfunction. These findings support CSC as a sclerovascular disorder and nominate complement regulation, endothelial signaling, and extracellular matrix pathways for future study.

Journal Article↗

PubMed2026

Development and Validation of a Clinical Polygenic Risk Report in U.S.-Based Health Systems for 8 Cardiovascular Conditions.

BACKGROUND: Polygenic risk scores (PRS) stratify inherited cardiovascular risk, but their path to clinical implementation remains unclear. OBJECTIVES: We aimed to develop and validate integrated PRS for 8 cardiovascular conditions and outline a framework for their clinical reporting. METHODS: We analyzed genotype and clinical data from 245,394 All of Us Research Program participants. Publicly available PRS for 8 traits-coronary artery disease, atrial fibrillation, type 2 diabetes, venous thromboembolism (VTE), thoracic aortic aneurysm (TAA), extreme hypertension, severe hypercholesterolemia, and elevated lipoprotein(a)-were combined using PRSmix, an elastic-net approach. Integrated PRS were externally validated in 53,306 Mass General Brigham Biobank participants using logistic regression, adjusting for age, sex, and ancestry. RESULTS: Of 53,306 genotyped Mass General Brigham Biobank participants (55.6% women, mean age 53 ± 17 years), integrated PRS demonstrated robust discrimination and appropriate calibration across 8 cardiovascular traits. Comparing high genetic risk (top 10% of PRS distribution, or top 20% for rarer TAA and VTE) vs average risk (26th-75th percentiles, or 21st-80th percentiles for TAA and VTE) yielded ORs: coronary artery disease (3.7 [95% CI: 3.4-4.1]), type 2 diabetes (3.1 [95% CI: 2.8-3.3]), atrial fibrillation (3.0 [95% CI: 2.7-3.3]), VTE (1.9 [95% CI: 1.6-2.0]), TAA (1.7 [95% CI: 1.5-1.9]), hypertension (2.1 [95% CI: 1.8-2.3]), hypercholesterolemia (4.1 [95% CI: 3.7-4.5]), and lipoprotein(a) (41.0 [95% CI: 27.0-62.2]). Incorporating integrated PRS into clinical models improved risk classification, while prospective analyses confirmed significant associations with incident cardiovascular outcomes. CONCLUSIONS: Integrated PRS offer an implementable framework for genetic risk reporting, and are now available as a clinically orderable test. Broader prospective validation studies are needed to further establish clinical utility.

Humans↗

PubMed2026

Management and Consequences of Genotype-Positive Familial Hypercholesterolemia.

IMPORTANCE: Familial hypercholesterolemia (FH) is a common genetic condition that causes hypercholesterolemia and increased risk for premature atherosclerotic cardiovascular disease (ASCVD). The prevalence, management, and consequences of genetically confirmed FH across the US are poorly understood. OBJECTIVE: To identify genotype-positive FH in a national US cohort and describe its prevalence, consequences, and lipid-lowering management. DESIGN, SETTING, AND PARTICIPANTS: In the All of Us (AoU) cohort study, whole-genome sequencing and phenotypic data from US adult participants enrolled between May 2018 and July 2022 were analyzed to identify and study genotype-positive FH. Data were analyzed between May 2024 and May 2025. EXPOSURE: FH variants (pathogenic or likely pathogenic) in LDLR, APOB, and PCSK9 genes were manually classified with standard criteria. MAIN OUTCOMES AND MEASURES: The primary outcomes were demographic characteristics, lipid measurements, ASCVD, and prevalence of FH and noncarriers in AoU. Lipid management was then characterized among individuals with FH through lipid-lowering therapy (LLT) documentation and guideline-based low-density lipoprotein cholesterol (LDL-C) targets. RESULTS: A total of 245 388 participants were included, with mean (SD) age of 56.5 (16.9) years and 145 563 female participants (59.3%). Genotype-positive FH was identified in 865 participants (prevalence, 0.35%; 95% CI, 0.33%-0.38%; 1 in 287 participants). Among individuals with genotype-positive FH, 349 (40%) were prescribed statins, and 332 (38.4%) had LDL-C measured. Coronary artery disease, peripheral artery disease, and transient ischemic attack or stroke were significantly more common in genotype-positive FH carriers compared to noncarriers (coronary artery disease: odds ratio [OR], 2.91; 95% CI, 2.34-3.58; peripheral artery disease: OR, 1.51; 95% CI, 1.16-1.96; and transient ischemic attack or stroke: OR, 1.54; 95% CI, 1.11-2.09). Only 30.1% of participants positive for FH variants had LDL-C less than 100 mg/dL at their most recent result compared to 48.2% of noncarriers (P < .001). Of the total participants with ASCVD and LLT prescription, significantly fewer individuals with FH met the secondary prevention LDL-C target (<70 mg/dL; 19.33% vs 43.12%; P < .001) compared to noncarriers. CONCLUSIONS AND RELEVANCE: This cohort study finds a prevalence of genotype-positive FH in All of Us participants of 0.35% (95% CI, 0.33%-0.38%), with state-level variation. A minority of individuals with genotype-positive FH met guideline-recommended LDL-C targets and had increased rates of ASCVD.

Humans↗

PubMed2026

Precision Diagnosis in APOL1 Kidney Disease With the p.N264K M1 Protective Variant.

IMPORTANCE: The APOL1 M1 (p.N264K) variant protects against G2-associated APOL1 focal segmental glomerulosclerosis (FSGS) and chronic kidney disease (CKD). However, the utility of knowing an individual's M1 status in guiding kidney disease diagnosis and other clinical scenarios remains underexplored. OBJECTIVE: To test 2 hypotheses: (1) in patients with APOL1 high-risk (HR) genotype kidney disease with at least 1 G2 allele, M1 can distinguish APOL1 CKD from non-APOL1 CKD; (2) in people with APOL1 low-risk (LR) genotypes, M1 is independently associated with protection against FSGS and CKD. DESIGN, SETTING, AND PARTICIPANTS: Retrospective case-control study using data from 2 tertiary care hospitals (Columbia University Irving Medical Center and Mass General Brigham Biobank) and population-based data (the UK Biobank [UKB], Electronic Medical Records and Genomics [eMERGE-III], and All of Us [AoU]). Participants were individuals with a diagnosis of FSGS or steroid-resistant nephrotic syndrome (SRNS), individuals with CKD, and controls. EXPOSURES: Exposures included the M1 variant (p.N264K) obtained from exome or genome sequencing data, sex, and genetic ancestry. MAIN OUTCOME AND MEASURE: The main outcome was the presence or absence of kidney disease, defined as FSGS or non-FSGS CKD, compared with non-kidney disease controls. Association between the M1 variant and disease status was assessed using odds ratios (ORs). RESULTS: A total of 107 696 individuals (54 994 [51.1%] female; 8779 [8.2%] with African ancestry, 78 475 [72.9%] with European ancestry, and 16 129 [15.0%] with multiethnic ancestry), including 3460 with FSGS or SRNS, 24 382 with non-FSGS CKD kidney disease, and 79 854 controls were enrolled in the discovery cohort. In the APOL1-HR group (1413 participants), M1 was significantly inversely associated with FSGS or SRNS cases compared with controls without kidney disease (OR, 0.20; 95% CI, 0.04-0.63; P = 3.69 × 10-3). Among individuals with CKD with APOL1-HR genotypes, M1 was 4 times more frequent in those whose CKD was not due to FSGS or SRNS. Importantly, electronic health record and biopsy review identified an alternative, non-APOL1 cause for CKD in nearly all APOL1-HR-M1 cases. There was no association between individuals with APOL1-LR genotypes with M1 and protection against CKD or FSGS. CONCLUSIONS AND RELEVANCE: In this case-control study of 107 696 individuals, presence of an APOL1-HR genotype M1 was significantly associated with protection against kidney disease, suggesting that it may have a role as a genetic modifier. Patients with CKD with an APOL1-HR genotype and M1 should be evaluated for an alternative and potentially treatable cause of their CKD.

Humans↗

PubMed2026

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs.

MOTIVATION: Genome-wide association studies (GWAS) at biobank scale are computationally intensive, especially for admixed populations requiring robust statistical models. SAIGE is a widely used method for generalized linear mixed-model GWAS but is limited by its CPU-based implementation, making phenome-wide association studies impractical for many research groups. RESULTS: We developed SAIGE-GPU, a GPU-accelerated version of SAIGE that replaces CPU-intensive matrix operations with GPU-optimized kernels. The core innovation is distributing genetic relationship matrix calculations across GPUs and communication layers. Applied to 2068 phenotypes from 635 969 participants in the Million Veteran Program, including diverse and admixed populations, SAIGE-GPU achieved a 5-fold speedup in mixed model fitting on supercomputing infrastructure and cloud platforms. We further optimized the variant association testing step through multi-core and multi-trait parallelization. Deployed on Google Cloud Platform and Azure, the method provided substantial cost and time savings. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

Genome-Wide Association Study↗

PubMed2026

Polygenic Risk Based Detection and Treatment of Subclinical Coronary Atherosclerosis in the PROACT Clinical Trials.

BACKGROUND: Coronary artery disease (CAD) polygenic risk scores (PRS) may identify individuals at elevated genetic risk "flying under the radar" in contemporary practice. The aims of the PROACT (Polygenic Risk Based Detection and Treatment of Subclinical Coronary Atherosclerosis) trials are to prospectively identify these individuals, quantify subclinical coronary plaque, and slow its progression with pharmacologic interventions. OBJECTIVES: The aim of this study is to report interim feasibility and implementation findings from PROACT, a genotype-first, biobank-enabled trial, characterizing eligibility yield, callback engagement, and subclinical coronary atherosclerosis on coronary computed tomographic angiography among individuals with high CAD PRS. METHODS: Within a hospital-based biobank, adults 40 to 75 years of age with high CAD PRS, without cardiovascular disease, and not on lipid-lowering therapy were invited. The authors characterize 2,495 eligible individuals with high CAD PRS, report on the feasibility and early operational outcomes of a genotype-first callback strategy for a clinical trial in the first 1,314 invited, and describe plaque prevalence by age and sex in the first 204 participants using coronary computed tomographic angiography. RESULTS: Among 64,092 genotyped participants, 2,495 (3.9%) were eligible and had high CAD PRS despite low clinical risk (median 10-year pooled cohort equations risk for atherosclerotic cardiovascular disease 3%; Q1-Q3: 1%-8%). Recruitment showed high engagement: among 1,314 invited individuals, 283 (21.5%) opted in, and 204 (15.5%) completed baseline imaging. Compared with participants who did not opt in, those who opted in had higher specialty care engagement and lived closer to the study site. Analysis of the first 204 participants enrolled by January 31, 2025 (mean age 56.3 ± 8.5 years, 69% women), showed that despite the low clinical risk and favorable cardiovascular health (mean Life's Essential 8 score 73.3 ± 11.5 vs the U.S. average of ∼65), one-half the participants (102 of 204) had subclinical plaque. Subclinical plaque prevalence was 76.2% in men and 38.3% in women and was high across age groups. CONCLUSIONS: These exploratory findings highlight the feasibility of implementing genotype-first recruitment for prevention trials and reveal a large proportion of "silent" high-genetic risk individuals with subclinical plaque for whom pharmacotherapy could be beneficial but who remain undetected by standard clinical assessments. (Polygenic Risk Based Detection of Subclinical Coronary Atherosclerosis and Change in Cardiovascular Health [PROACT 1], NCT05819814; Polygenic Risk Based Detection of Subclinical Coronary Atherosclerosis and Intervention With Statin and Colchicine [PROACT 2], NCT05850091).

Adult↗

PubMed2026

Clonal Hematopoiesis and Incident Heart Failure.

IMPORTANCE: Clonal hematopoiesis of indeterminate potential (CHIP), the age-related clonal expansion of hematopoietic cells with acquired preleukemic variants, has been associated with cardiometabolic diseases, including heart failure (HF). However, prior studies have lacked power to examine less common CHIP driver variants and have not investigated potential mediators of the CHIP-HF association. OBJECTIVE: To test whether specific CHIP subtypes are associated with incident HF and determine the extent to which CHIP-associated comorbidities mediate this association. DESIGN, SETTING, AND PARTICIPANTS: This was a UK Biobank prospective population-based cohort study of community-dwelling adults in the UK, with enrollment from 2006 to 2010 and follow-up through 2020. Included were participants with whole-exome sequencing (WES) and without prevalent HF, hematologic malignancy, or other CHIP-associated comorbidities (coronary artery disease [CAD], atrial fibrillation [AF], type 2 diabetes [T2D], or chronic kidney disease [CKD]) at baseline. Study data were analyzed from April through October 2025. EXPOSURES: Presence of CHIP and gene-specific CHIP subtypes (DNMT3A, non-DNMT3A, TET2, ASXL1, JAK2, DNA damage repair genes, and spliceosome genes). Mediation analyses examined CHIP-associated comorbidities (CAD, AF, T2D, and CKD). MAIN OUTCOMES AND MEASURES: The primary outcome was incident HF. Cox regression tested associations of CHIP and CHIP subtypes with incident HF, adjusted for age, sex, race, and cardiovascular risk factors. RESULTS: Among 417 616 participants (mean [SD] age, 56.1 [8.1] years; 234 868 female [56.2%]), 7183 (1.7%) developed incident HF over a median (IQR) of 11.1 (10.4-11.8) years of follow-up. CHIP was associated with HF risk (adjusted hazard ratio [aHR], 1.27; 95% CI, 1.15-1.40; P < .001), driven by non-DNMT3A subtypes (aHR, 1.52; 95% CI, 1.33-1.75; P < .001), including associations with TET2, ASXL1, JAK2, and spliceosome CHIP. DNMT3A CHIP was more modestly associated with HF (aHR, 1.15; 95% CI, 1.00-1.31; P = .04). In mediation analyses, development of CAD, AF, T2D, and/or CKD collectively accounted for 28.2% of the association (95% CI, 11.6%-45.4%; P = .001) between non-DNMT3A CHIP and HF. CONCLUSIONS AND RELEVANCE: Results of this cohort study suggest that CHIP, especially non-DNMT3A CHIP, was associated with incident HF. Other CHIP-associated comorbidities explained only a minority of the association between non-DNMT3A CHIP and HF. These findings suggest that CHIP is an HF risk factor and potential therapeutic target.

Adult↗

PubMed2025

Contributions of Common, Rare, and Somatic Genetic Variants to Incidence of Atrial Fibrillation.

IMPORTANCE: Atrial fibrillation (AF) has a complex genetic architecture involving common, rare, and somatic variants. The association between these components requires further investigation. OBJECTIVE: To examine the individual and combined contributions of polygenic, monogenic, and somatic genetic variants to AF incidence, and develop an integrated genomic model (IGM-AF) for improved risk prediction. DESIGN, SETTING, AND PARTICIPANTS: This cohort study used whole-genome sequence data from participants of the UK Biobank, with follow-up for AF events through hospital records, death registries, and self-report. The UK Biobank recruited participants aged 40 to 69 years in the UK between 2006 and 2010. Study data were analyzed from August 2022 to November 2024. EXPOSURES: IGM-AF comprising an AF polygenic risk score (PRS), a composite rare variant gene set (AFgeneset), and somatic variants associated with clonal hematopoiesis of indeterminate potential (CHIP). Clinical AF risk was estimated using the Cohorts for Heart and Aging Research in Genomic Epidemiology AF (CHARGE-AF) score. MAIN OUTCOMES AND MEASURES: The primary outcome was hazard ratios (HRs) for 5-year incident AF attributable to PRS, AFgeneset, CHIP, and their interactions. The predictive performance of IGM-AF and its components was quantified using HRs, C statistics, and reclassification indices. RESULTS: A total of 416 085 individuals (mean [SD] age, 56.6 [8.0] years; 224 642 female [54.0%]) with 30 797 AF cases were included. The PRS (HR per 1 SD, 1.65; 95% CI, 1.63-1.67; P < 1 × 10-8), AFgeneset (HR, 1.63; 95% CI, 1.52-1.75; P = 1.46 × 10-42), and CHIP (HR, 1.26; 95% CI, 1.15-1.38; P = 1.41 × 10-6) were associated with incident AF. The 5-year cumulative incidence of AF was at least 2-fold among individuals having all 3 genetic drivers (common, rare, and somatic drivers) compared with those with only 1 driver. Integration of IGM-AF with a clinical risk model (CHARGE-AF) showed higher predictive performance (C statistic, 0.80; 95% CI, 0.80-0.80) compared with IGM-AF and CHARGE-AF alone. The classification of the at-risk population for AF was improved when IGM-AF was added to CHARGE-AF (net reclassification index, 0.08; 95% CI, 0.07-0.09). CONCLUSIONS AND RELEVANCE: Results of this cohort study demonstrated the complementary value of common, rare, and somatic variants in shaping genomic AF risk. Leveraging comprehensive genetic information may enhance screening and preventive interventions for AF.

Humans↗

PubMed2025

Clonal Hematopoiesis and Risk of New-Onset Myocarditis and Pericarditis.

IMPORTANCE: Clonal hematopoiesis of indeterminate potential (CHIP) is the age-related clonal expansion of hematopoietic stem cells with leukemia-associated mutations. Certain CHIP mutations promote atherosclerosis and heart failure through immune-related pathways. OBJECTIVE: To test whether CHIP is associated with the development of myocarditis and pericarditis. DESIGN, SETTING, AND PARTICIPANTS: This observational population-based cohort study used data from the UK Biobank. Enrollment occurred between 2006 and 2010. Participants with whole-exome sequencing, no prevalent cardiovascular disease or hematological malignancy, and complete covariate data were included. Follow-up occurred for a median of 13.6 (IQR, 12.8-14.2) years. Analyses were conducted from November 2024 to July 2025. EXPOSURES: Any CHIP (variant allele frequency [VAF] ≥2%) and large CHIP (VAF ≥10%) constituted coprimary study exposures. Secondary analyses considered DNMT3A and TET2 CHIP as separate exposures. MAIN OUTCOMES AND MEASURES: The primary outcome was a composite of incident myocarditis and pericarditis. Cox regression tested associations of CHIP with myocarditis and pericarditis, adjusting for age, sex, race and ancestry, and cardiovascular risk factors. Secondary analyses considered myocarditis and pericarditis as separate outcomes. Additional analyses compared associations of CHIP with myocarditis and pericarditis with those with other cardiovascular diseases, and tested the bidirectional associations between CHIP and noncardiac immune-mediated inflammatory diseases. RESULTS: Among 335 426 participants (mean age, 56.1 years; 185 429 female [55.3%] and 149 997 male [44.7%]), 11 057 had any CHIP (3.3%), 7271 had large CHIP (2.2%), and 382 developed myocarditis or pericarditis (0.11%). Any and large CHIP were associated with multivariable-adjusted hazard ratios of 1.75 (95% CI, 1.14-2.68; P = .01) and 2.07 (95% CI, 1.28-3.33; P = .003), respectively, for the primary composite outcome of incident myocarditis and pericarditis. Increased risks were observed for DNMT3A and TET2 CHIP, with hazard ratios of 2.22 (95% CI, 1.17-4.21; P = .01) for DNMT3A with pericarditis and 3.65 (95% CI, 1.16-11.49; P = .03) for TET2 with myocarditis. CHIP associated with myocarditis and pericarditis more strongly than with other cardiovascular diseases (eg, coronary artery disease and heart failure). Any CHIP was also associated with 1.27-fold risk (95% CI, 1.16-1.39; P < .001) of developing noncardiac immune-mediated inflammatory diseases, without evidence for reverse causation. CONCLUSIONS AND RELEVANCE: In this study, CHIP was a strong risk factor for myocarditis and pericarditis among middle-aged adults. Targeting CHIP and its downstream pathways may represent a strategy for preventing or treating pericarditis and myocarditis.

Adult↗

PubMed2025

Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals.

BACKGROUND: Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability. RESULTS: Here, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246 K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) program. We identify numerous rare coding and non-coding gene associations related to LDL-C, with replication across 86 K participants in All of Us. Our findings are based on single-variant analyses, rare coding and non-coding variant aggregation tests, and sliding window approaches. Through this comprehensive analysis, we identify 704 novel single-variant associations, 25 novel rare coding variant aggregates, 28 novel rare non-coding variant aggregates, and one novel sliding window aggregate. CONCLUSIONS: This study provides a meta-analysis framework for large-scale whole genome sequence association analyses from diverse population groups, yielding novel rare non-coding variant associations.

Humans↗

PubMed2025

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging.

BACKGROUND: Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid plaque phenotyping in patients with advanced atherosclerosis, its application in population-based settings of asymptomatic individuals remains unexplored. METHODS: We developed a YOLOv8-based model for plaque detection using carotid ultrasound images from 19,499 participants of the population-based UK Biobank (UKB) and fine-tuned it for external validation in the BiDirect study (N = 2,105). Cox regression was used to estimate the impact of plaque presence and count on major cardiovascular events. To explore the genetic architecture of carotid atherosclerosis, we conducted a genome-wide association study (GWAS) meta-analysis of the UKB and CHARGE cohorts. Mendelian randomization (MR) assessed the effect of genetic predisposition to vascular risk factors on carotid atherosclerosis. RESULTS: Our model demonstrated high performance with accuracy, sensitivity, and specificity exceeding 85%, enabling identification of carotid plaques in 45% of the UKB population (aged 47-83 years). In the external BiDirect cohort, a fine-tuned model achieved 86% accuracy, 78% sensitivity, and 90% specificity. Plaque presence and count were associated with risk of major adverse cardiovascular events (MACE) over a follow-up of up to seven years, improving risk reclassification beyond the Pooled Cohort Equations. A GWAS meta-analysis of carotid plaques uncovered two novel genomic loci, with downstream analyses implicating targets of investigational drugs in advanced clinical development. Observational and MR analyses showed associations between smoking, LDL cholesterol, hypertension, and odds of carotid atherosclerosis. CONCLUSIONS: Our model offers a scalable solution for early carotid plaque detection, potentially enabling automated screening in asymptomatic individuals and improving plaque phenotyping in population-based cohorts. This approach could advance large-scale atherosclerosis research.

atherosclerosis↗

PubMed2025

Colchicine and Longitudinal Dynamics of Clonal Hematopoiesis: An Exploratory Substudy of the LoDoCo2 Trial.

BACKGROUND: Clonal hematopoiesis (CH) is an aging-related hematologic condition associated with increased risk for cardiovascular events. Larger CH clones associate more strongly with cardiovascular risk. Preclinical data indicate that inflammatory signaling drives expansion of CH clones and CH-associated cardiovascular disease. However, the effect of anti-inflammatory therapies on CH clonal dynamics in humans is unclear. OBJECTIVES: The goal of this study was to test the association of randomization to colchicine vs placebo with CH growth in participants with chronic coronary artery disease. It also assessed the association of colchicine use with change in inflammatory biomarkers over time according to CH status. METHODS: In this exploratory substudy of the LoDoCo2 (Low-Dose Colchicine 2) trial, high-coverage targeted sequencing was used to detect CH driver mutations and to quantify variant allele frequency at 4 timepoints: baseline, after a 30-day open-label colchicine run-in phase (0.5 mg daily), 1 year postrandomization to colchicine or placebo, and at end of study (median follow-up of 25.0 months). Clonal dynamics were assessed by using a generalized linear mixed model. High-sensitivity C-reactive protein and interleukin-6 were additionally measured at baseline, randomization, and 1 year postrandomization. RESULTS: In total, 854 participants contributed 2,047 observations across 4 timepoints, including before and after the prerandomization colchicine run-in period. Randomization to placebo was associated with a 14.9% annual increase in CH clone size (βtime = 0.14; 95% CI: 0.08 to 0.21) vs a nonsignificant 6.3% increase with colchicine (βtime on colchicine: 0.06; 95% CI: -0.01 to 0.14), although this difference between treatment arms was not statistically significant (Pinteraction = 0.13). Compared with placebo, colchicine was associated with attenuated clonal growth in TET2 CH (βtime on colchicine: 0.09 [95% CI: -0.04 to 0.22]; βtime placebo: 0.27 [95% CI: 0.16 to 0.37]; Pinteraction= 0.04). Among individuals with non-DNMT3A CH, interleukin-6 levels increased to a lesser extent in those receiving colchicine vs placebo over 1 year (30.0% vs 98.1% increase, respectively; Pinteraction = 0.01). CONCLUSIONS: In this exploratory analysis, treatment with low-dose colchicine was associated with attenuated clonal expansion in TET2 CH. These findings suggest the potential for colchicine to curb the proliferative advantage of key CH driver mutations and to mitigate their associated risk of cardiovascular disease. Further validation in prospective studies is warranted.

Humans↗