Multi-ancestry polygenic risk scores for venous thromboembolism.

Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality, with large disparities in incidence rates between Black and White Americans. Polygenic risk scores (PRSs) limited to variants discovered in genome-wide association studies in European-ancestry samples can identify European-ancestry individuals at high risk of VTE. However, there is limited evidence on whether high-dimensional PRS constructed using more sophisticated methods and more diverse training data can enhance the predictive ability and their utility across diverse populations. We developed PRSs for VTE using summary statistics from the International Network against Venous Thrombosis (INVENT) consortium genome-wide association studies meta-analyses of European- (71 771 cases and 1 059 740 controls) and African-ancestry samples (7482 cases and 129 975 controls). We used LDpred2 and PRS-CSx to construct ancestry-specific and multi-ancestry PRSs and evaluated their performance in an independent European- (6781 cases and 103 016 controls) and African-ancestry sample (1385 cases and 12 569 controls). Multi-ancestry PRSs with weights tuned in European-ancestry samples slightly outperformed ancestry-specific PRSs in European-ancestry test samples (e.g. the area under the receiver operating curve [AUC] was 0.609 for PRS-CSx_combinedEUR and 0.608 for PRS-CSxEUR [P = 0.00029]). Multi-ancestry PRSs with weights tuned in African-ancestry samples also outperformed ancestry-specific PRSs in African-ancestry test samples (PRS-CSxAFR: AUC = 0.58, PRS-CSx_combined AFR: AUC = 0.59), although this difference was not statistically significant (P = 0.34). The highest fifth percentile of the best-performing PRS was associated with 1.9-fold and 1.68-fold increased risk for VTE among European- and African-ancestry subjects, respectively, relative to those in the middle stratum. These findings suggest that the multi-ancestry PRS might be used to improve performance across diverse populations to identify individuals at highest risk for VTE.

Genome-wide analysis to assess if heavy alcohol consumption modifies the association between SNPs and pancreatic cancer risk.

BACKGROUND: Pancreatic cancer is a leading cause of cancer-related death globally. Risk factors for pancreatic cancer include common genetic variants and potentially heavy alcohol consumption. We assessed if genetic variants modify the association between heavy alcohol consumption and pancreatic cancer risk. METHODS: We conducted a genome-wide interaction analysis of single nucleotide polymorphisms (SNP) by heavy alcohol consumption (more than 3 drinks per day) for pancreatic cancer in European ancestry populations from genome-wide association studies (GWAS). Our analysis included 3,707 cases and 4,167 controls from case-control studies and 1,098 cases and 1,162 controls from cohort studies. Fixed effect meta-analyses were conducted. RESULTS: A potential novel region of association on 10p11.22, lead SNP rs7898449 (Pinteraction = 5.1 x 10-8 in the meta-analysis, Pinteraction = 2.1x10-9 in the case-control studies, Pinteraction = 0.91 cohort studies) was identified. A SNP correlated with this lead SNP is an eQTL for the NRP1 gene. Of the 17 genomic regions with genome-wide significant evidence of association with pancreatic cancer in prior studies, we observed suggestive evidence that heavy alcohol consumption modified the association for one SNP near LINC00673, rs11655237 on 17q25.1 (Pinteraction = 0.004). CONCLUSIONS: We identified a novel genomic region that may be associated with pancreatic cancer risk in conjunction with heavy alcohol consumption located near an eQTL for the NRP1, a protein that plays an important role in the development and progression of pancreatic cancer Impact: This work can provide insight into the etiology of pancreatic cancer particularly in heavy drinkers.

Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate.

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium.

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38 465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program (with varying sample size by trait, where the minimum sample size was n = 737 for MMP-1). We identified 22 distinct single-variant associations across 6 traits-E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin-that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

The Women's Health Initiative Randomized Trials and Clinical Practice: A Review.

Importance: Approximately 55 million people in the US and approximately 1.1 billion people worldwide are postmenopausal women. To inform clinical practice about the health effects of menopausal hormone therapy, calcium plus vitamin D supplementation, and a low-fat dietary pattern, the Women's Health Initiative (WHI) enrolled 161 808 postmenopausal US women (N = 68 132 in the clinical trials) aged 50 to 79 years at baseline from 1993 to 1998, and followed them up for up to 20 years. Observations: The WHI clinical trial results do not support hormone therapy with oral conjugated equine estrogens plus medroxyprogesterone acetate for postmenopausal women or conjugated equine estrogens alone for those with prior hysterectomy to prevent cardiovascular disease, dementia, or other chronic diseases. However, hormone therapy is effective for treating moderate to severe vasomotor and other menopausal symptoms. These benefits of hormone therapy in early menopause, combined with lower rates of adverse effects of hormone therapy in early compared with later menopause, support initiation of hormone therapy before age 60 years for women without contraindications to hormone therapy who have bothersome menopausal symptoms. The WHI results do not support routinely recommending calcium plus vitamin D supplementation for fracture prevention in all postmenopausal women. However, calcium and vitamin D are appropriate for women who do not meet national guidelines for recommended intakes of these nutrients through diet. A low-fat dietary pattern with increased fruit, vegetable, and grain consumption did not prevent the primary outcomes of breast or colorectal cancer but was associated with lower rates of the secondary outcome of breast cancer mortality during long-term follow-up. Conclusions and Relevance: For postmenopausal women, the WHI randomized clinical trials do not support menopausal hormone therapy to prevent cardiovascular disease or other chronic diseases. Menopausal hormone therapy is appropriate to treat bothersome vasomotor symptoms among women in early menopause, without contraindications, who are interested in taking hormone therapy. The WHI evidence does not support routine supplementation with calcium plus vitamin D for menopausal women to prevent fractures or a low-fat diet with increased fruits, vegetables, and grains to prevent breast or colorectal cancer. A potential role of a low-fat dietary pattern in reducing breast cancer mortality, a secondary outcome, warrants further study.

Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes.

Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.

Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations.

Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p < 1.2E-7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.

MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups.

Polygenic risk scores (PRSs) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in summary statistics from genome-wide association studies (GWASs) across multiple ancestry groups via Bayesian hierarchical modeling and ensemble learning. In our simulation studies and data analyses across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. For example, MUSSEL has an average gain in prediction R2 across 11 continuous traits of 40.2% and 49.3% compared to PRS-CSx and CT-SLEB, respectively, in the African ancestry population. The best-performing method, however, varies by GWAS sample size, target ancestry, trait architecture, and linkage disequilibrium reference samples; thus, ultimately a combination of methods may be needed to generate the most robust PRSs across diverse populations.

MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric.

Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.

Heart Failure Risk Among African-American Women With an ICAM1 Missense Variant.

BACKGROUND: A common genetic variant of ICAM1 among African-American individuals (rs5491; p.K56M) is associated with heart failure (HF) hospitalization, but whether this risk is specific to heart failure with preserved ejection fraction (HFpEF) remains unclear. Older women are at high risk for HFpEF, and the relationship between rs5491 and HFpEF across the age spectrum is unknown. OBJECTIVES: This study assessed risk of HF and its subtypes conferred by ICAM1 p.K56M (rs5491). METHODS: Associations of rs5491 with risk of HF and its subtypes were estimated among African American individuals in WHI (Women's Health Initiative). The study evaluated whether the association between rs5491 and HF hospitalizations was modified by baseline age. Subsequently, African-American women in WHI and MESA (Multi-Ethnic Study of Atherosclerosis) were pooled and analyses were repeated. RESULTS: Among 8,401 women in WHI, the minor allele frequency of rs5491 was 20.7%, and 731 HF hospitalizations occurred over 19.2 years. The rs5491 variant was not associated with HF or its subtypes across WHI. Interaction analyses suggested that age as a continuous variable modified the association of rs5491 with HFpEF hospitalization (interaction P = 0.04). Upon categorizing women into age decades, rs5491 conferred increased risk of HFpEF among women ≥70 years (HR per additional rs5491 allele: 1.82 [95% CI: 1.25-2.65]; P = 0.002) but was not associated with HFpEF risk among women <70 years. Pooling African-American women in WHI (n = 8,401) and MESA (n = 856) demonstrated that the effect modification by age on the association of rs5491 with HFpEF became more significant (interaction P = 0.009), with consistent HFpEF risk effect estimates among women ≥70 years. CONCLUSIONS: ICAM1 p.K56M (rs5491) is associated with HFpEF among African-American women ≥70 years.

Targeted Proteomics Reveals Functional Targets for Early Diabetes Susceptibility in Young Adults.

BACKGROUND: The circulating proteome may encode early pathways of diabetes susceptibility in young adults for surveillance and intervention. Here, we define proteomic correlates of tissue phenotypes and diabetes in young adults. METHODS: We used penalized models and principal components analysis to generate parsimonious proteomic signatures of diabetes susceptibility based on phenotypes and on diabetes diagnosis across 184 proteins in >2000 young adults in the CARDIA (Coronary Artery Risk Development in Young Adults study; mean age, 32 years; 44% women; 43% Black; mean body mass index, 25.6±4.9 kg/m2), with validation against diabetes in >1800 individuals in the FHS (Framingham Heart Study) and WHI (Women's Health Initiative). RESULTS: In 184 proteins in >2000 young adults in CARDIA, we identified 2 proteotypes of diabetes susceptibility-a proinflammatory fat proteotype (visceral fat, liver fat, inflammatory biomarkers) and a muscularity proteotype (muscle mass), linked to diabetes in CARDIA and WHI/FHS. These proteotypes specified broad mechanisms of early diabetes pathogenesis, including transorgan communication, hepatic and skeletal muscle stress responses, vascular inflammation and hemostasis, fibrosis, and renal injury. Using human adipose tissue single cell/nuclear RNA-seq, we demonstrate expression at transcriptional level for implicated proteins across adipocytes and nonadipocyte cell types (eg, fibroadipogenic precursors, immune and vascular cells). Using functional assays in human adipose tissue, we demonstrate the association of expression of genes encoding these implicated proteins with adipose tissue metabolism, inflammation, and insulin resistance. CONCLUSIONS: A multifaceted discovery effort uniting proteomics, underlying clinical susceptibility phenotypes, and tissue expression patterns may uncover potentially novel functional biomarkers of early diabetes susceptibility in young adults for future mechanistic evaluation.

Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI.

Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.

Prevalence of frequent premature ventricular contractions and nonsustained ventricular tachycardia in older women screened for atrial fibrillation in the Women's Health Initiative.

BACKGROUND: Frequent premature ventricular contractions (PVCs) and nonsustained ventricular tachycardia (NSVT) have been associated with cardiovascular disease and mortality. Their prevalence, especially in ambulatory populations, is understudied and limited by few female participants and the use of short-duration (24- to 48-hour) monitoring. OBJECTIVE: The objective of this study was to report the prevalence of frequent PVCs and NSVT in a community-based population of women likely to undergo electrocardiogram (ECG) screening by sequential patch monitoring. METHODS: Participants from the Women's Health Initiative Strong and Healthy (WHISH) trial with no history of atrial fibrillation (AF) but 5-year predicted risk of incident AF ≥5% by CHARGE-AF score were randomly selected to undergo screening with 7-day ECG patch monitors at baseline, 6 months, and 12 months. Recordings were reviewed for PVCs and NSVT (>5 beats); data were analyzed with multivariate regression models. RESULTS: There were 1067 participants who underwent ECG screening at baseline, 866 at 6 months, and 777 at 12 months. Frequent PVCs were found on at least 1 patch from 4.3% of participants, and 1 or more episodes of NSVT were found in 12 (1.1%) women. PVC frequency directly correlated with CHARGE-AF score and NSVT on any patch. Detection of frequent PVCs increased with sequential monitoring. CONCLUSION: In postmenopausal women at high risk for AF, frequent PVCs were relatively common (4.3%) and correlated with higher CHARGE-AF score. As strategies for AF screening continue to evolve, particularly in those individuals at high risk of AF, the prevalence of incidental ventricular arrhythmias is an important benchmark to guide clinical decision-making.

Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas.

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.

Multi-ancestry polygenic risk scores for venous thromboembolism.

Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality, with large disparities in incidence rates between Black and White Americans. Polygenic risk scores (PRSs) limited to variants discovered in genome-wide association studies in European-ancestry samples can identify European-ancestry individuals at high risk of VTE. However, there is limited evidence on whether high-dimensional PRS constructed using more sophisticated methods and more diverse training data can enhance the predictive ability and their utility across diverse populations. We developed PRSs for VTE using summary statistics from the International Network against Venous Thrombosis (INVENT) consortium GWAS meta-analyses of European- (71,771 cases and 1,059,740 controls) and African-ancestry samples (7,482 cases and 129,975 controls). We used LDpred2 and PRSCSx to construct ancestry-specific and multi-ancestry PRSs and evaluated their performance in an independent European- (6,261 cases and 88,238 controls) and African-ancestry sample (1,385 cases and 12,569 controls). Multi-ancestry PRSs with weights tuned in European- and African-ancestry samples, respectively, outperformed ancestry-specific PRSs in European- (PRSCSXEUR: AUC=0.61 (0.60, 0.61), PRSCSX_combinedEUR: AUC=0.61 (0.60, 0.62)) and African-ancestry test samples (PRSCSXAFR: AUC=0.58 (0.57, 0.6), PRSCSX_combined AFR: AUC=0.59 (0.57, 0.60)). The highest fifth percentile of the best-performing PRS was associated with 1.9-fold and 1.68-fold increased risk for VTE among European- and African-ancestry subjects, respectively, relative to those in the middle stratum. These findings suggest that the multi-ancestry PRS may be used to identify individuals at highest risk for VTE and provide guidance for the most effective treatment strategy across diverse populations.

Radon Exposure, Clonal Hematopoiesis, and Stroke Susceptibility in the Women's Health Initiative.

BACKGROUND AND OBJECTIVES: Studies suggest that clonal hematopoiesis of indeterminate potential (CHIP) may increase risk of hematologic malignancy and cardiovascular disease, including stroke. However, few studies have investigated plausible environmental risk factors for CHIP such as radon, despite the climate-related increases in and documented infrequency of testing for this common indoor air pollutant.The purpose of this study was to estimate the risk of CHIP related to radon, an established environmental mutagen. METHODS: We linked geocoded addresses of 10,799 Women's Health Initiative Trans-Omics for Precision Medicine (WHI TOPMed) participants to US Environmental Protection Agency-predicted, county-level, indoor average screening radon concentrations, categorized as follows: Zone 1 (>4 pCi/L), Zone 2 (2-4 pCi/L), and Zone 3 (<2 pCi/L). We defined CHIP as the presence of one or more leukemogenic driver mutations with variant allele frequency >0.02. We identified prevalent and incident ischemic and hemorrhagic strokes; subtyped ischemic stroke using Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria; and then estimated radon-related risk of CHIP as an odds ratio (OR) and 95% CI using multivariable-adjusted, design-weighted logistic regression stratified by age, race/ethnicity, smoking status, and stroke type/subtype. RESULTS: The percentages of participants with CHIP in Zones 1, 2, and 3 were 9.0%, 8.4%, and 7.7%, respectively (ptrend = 0.06). Among participants with ischemic stroke, Zones 2 and 1 were associated with higher estimated risks of CHIP relative to Zone 3: 1.39 (1.15-1.68) and 1.46 (1.15-1.87), but not among participants with hemorrhagic stroke: 0.98 (0.68-1.40) and 1.03 (0.70-1.52), or without stroke: 1.04 (0.74-1.46) and 0.95 (0.63-1.42), respectively (pinteraction = 0.03). Corresponding estimates were particularly high among TOAST-subtyped cardioembolism: 1.78 (1.30-2.47) and 1.88 (1.31-2.72), or other ischemic etiologies: 1.37 (1.06-1.78) and 1.50 (1.11-2.04), but not small vessel occlusion: 1.05 (0.74-1.49) and 1.00 (0.68-1.47), respectively (pinteraction = 0.10). Observed patterns of association among strata were insensitive to attrition weighting, ancestry adjustment, prevalent stroke exclusion, separate analysis of DNMT3A driver mutations, and substitution with 3 alternative estimates of radon exposure. DISCUSSION: The robust elevation of radon-related risk of CHIP among postmenopausal women who develop incident cardioembolic stroke is consistent with a potential role of somatic genomic mutation in this societally burdensome form of cerebrovascular disease, although the mechanism has yet to be confirmed.

Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure.

BACKGROUND: The Dietary Approaches to Stop Hypertension (DASH) diet score lowers blood pressure (BP). We examined interactions between genotype and the DASH diet score in relation to systolic BP. METHODS: We analyzed up to 9 420 585 single nucleotide polymorphisms in up to 127 282 individuals of 6 population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (n=35 660) and UK Biobank (n=91 622) and performed European population-specific and cross-population meta-analyses. RESULTS: We identified 3 loci in European-specific analyses and an additional 4 loci in cross-population analyses at Pinteraction<5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency, 0.03) and the DASH diet score (Pinteraction=4e-8; P for heterogeneity, 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (Pinteraction=9.4e-7) and 0.20±0.06 mm Hg (Pinteraction=0.001) in Cohorts for Heart and Aging Research in Genomic Epidemiology and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P=4e-273) and cis-DNA methylation quantitative trait loci variants (P=1e-300). Although the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by single nucleotide polymorphisms potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSIONS: We demonstrated gene-DASH diet score interaction effects on systolic BP in several loci. Studies with larger diverse populations are needed to validate our findings.

Clonal Hematopoiesis and Incident Heart Failure With Preserved Ejection Fraction.

Importance: Clonal hematopoiesis of indeterminate potential (CHIP), the age-related clonal expansion of hematopoietic stem cells with leukemogenic acquired genetic variants, is associated with incident heart failure (HF). Objective: To evaluate the associations of CHIP and key gene-specific CHIP subtypes with incident HF with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF). Design, Setting, and Participants: This population-based cohort study included participants from 2 racially diverse prospective cohort studies with uniform HF subtype adjudication: the Jackson Heart Study (JHS) and Women's Health Initiative (WHI). JHS participants were enrolled during 2000 to 2004 and followed up through 2016. WHI participants were enrolled during 1993 to 1998 and followed up through 2022. Participants who underwent whole-genome sequencing, lacked prevalent HF at baseline, and were followed up for HF adjudication were included. Follow-up occurred over a median (IQR) of 12.0 (11.0-12.0) years in the JHS and 15.3 (9.0-22.0) years in the WHI. Statistical analysis was performed from June to December 2023. Exposures: Any CHIP and the most common gene-specific CHIP subtypes (DNMT3A and TET2 CHIP). Main Outcomes and Measures: First incident hospitalized HF events were adjudicated from hospital records and classified as HFpEF (left ventricular ejection fraction ≥50%) or HFrEF (ejection fraction <50%). Results: A total of 8090 participants were included; 2927 from the JHS (median [IQR] age, 56 [46-65] years; 1846 [63.1%] female; 2927 [100.0%] Black or African American) and 5163 from the WHI (median [IQR] age, 67 [62-72] years; 5163 [100.0%] female; 29 [0.6%] American Indian or Alaska Native, 37 [0.7%] Asian or Pacific Islander, 1383 [26.8%] Black or African American, 293 [5.7%] Hispanic or Latinx, 3407 [66.0%] non-Hispanic White, and 14 [0.3%] with other race and ethnicity). The multivariable-adjusted hazard ratio (HR) for composite CHIP and HFpEF was 1.28 (95% CI, 0.93-1.76; P = .13), and for CHIP and HFrEF it was 0.79 (95% CI, 0.49-1.25; P = .31). TET2 CHIP was associated with HFpEF in both cohorts (meta-analyzed HR, 2.35 [95% CI, 1.34 to 4.11]; P = .003) independent of cardiovascular risk factors and coronary artery disease. Analyses stratified by C-reactive protein (CRP) in the WHI found an increased risk of incident HFpEF in individuals with CHIP and CRP greater than or equal to 2 mg/L (HR, 1.94 [95% CI, 1.20-3.15]; P = .007), but not in those with CHIP and CRP less than 2 mg/L or those with CRP greater than or equal to 2 mg/L without CHIP, when compared with participants without CHIP and CRP less than 2 mg/L. Conclusions and Relevance: In this cohort study, TET2 CHIP was an independent risk factor associated with incident HFpEF. This finding may have implications for the prevention and management of HFpEF, including development of targeted therapies.

Individual and Neighborhood-level Socioeconomic Status and Somatic Mutations Associated With Increased Risk of Cardiovascular Disease and Mortality: A Cross-Sectional Analysis in the Women's Health Initiative.

BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP), the expansion of leukemogenic mutations in white blood cells, has been associated with increased risk of atherosclerotic cardiovascular diseases, cancer, and mortality. OBJECTIVE: We examined the relationship between individual- and neighborhood-level socioeconomic status (SES) and CHIP and evaluated effect modification by interpersonal and intrapersonal resources. METHODS: The study population included 10,799 postmenopausal women from the Women's Health Initiative without hematologic malignancy or antineoplastic medication use. Individual- and neighborhood (Census tract)-level SES were assessed across several domains including education, income, and occupation, and a neighborhood-level SES summary z-score, which captures multiple dimensions of SES, was generated. Interpersonal and intrapersonal resources were self-reports. CHIP was ascertained based on a prespecified list of leukemogenic driver mutations. Weighted logistic regression models adjusted for covariates were used to estimate risk of CHIP as an odds ratio (OR) and 95% confidence interval (95% CI). RESULTS: The interval-scale neighborhood-level SES summary z-score was associated with a 3% increased risk of CHIP: OR (95% CI) = 1.03 (1.00-1.05), p = .038. Optimism significantly modified that estimate, such that among women with low/medium and high levels of optimism, the corresponding ORs (95% CIs) were 1.03 (1.02-1.04) and 0.95 (0.94-0.96), pInteraction < .001. CONCLUSIONS: Our findings suggest that reduced risk of somatic mutation may represent a biological pathway by which optimism protects contextually advantaged but at-risk women against age-related chronic disease and highlight potential benefits of long-term, positive psychological interventions.