Determinants of mosaic chromosomal alteration fitness.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.

Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood.

Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European American (EA) ancestry group compared to those of Hispanic American (HA), African American (AA), and East Asian (EAS) ancestry. Further, we identified two genes ( CFHR1 and LRP6 ) that harbor multiple rare, putatively deleterious variants associated with mLOY susceptibility, show that subsets of human hematopoietic stem cells are enriched for activity of mLOY susceptibility variants, and that certain alleles on chromosome Y are more likely to be lost than others.

Transcriptional Variabilities in Human hiPSC-derived Cardiomyocytes: All Genes Are Not Equal and Their Robustness May Foretell Donor's Disease Susceptibility.

Human induced pluripotent stem cells (hiPSCs) are frequently used to study disease-associated variations. We characterized transcriptional variability from a hiPSC-derived cardiomyocyte (hiPSC-CM) study of left ventricular hypertrophy (LVH) using donor samples from the HyperGEN study. Multiple hiPSC-CM differentiations over reprogramming events (iPSC generation) across 7 donors were used to assess variabilities from reprogramming, differentiation, and donor LVH status. Variability arising from pathological alterations was assessed using a cardiac stimulant applied to the hiPSC-CMs to trigger hypertrophic responses. We found that for most genes (73.3%~85.5%), technical variability was smaller than biological variability. Further, we identified and characterized lists of "noise" genes showing greater technical variability and "signal" genes showing greater biological variability. Together, they support a "genetic robustness" hypothesis of disease-modeling whereby cellular response to relevant stimuli in hiPSC-derived somatic cells from diseased donors tends to show more transcriptional variability. Our findings suggest that hiPSC-CMs can provide a valid model for cardiac hypertrophy and distinguish between technical and disease-relevant transcriptional changes.

Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association.

A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform health care delivery. The American Heart Association supports the creation of tools and services that would further the science and practice of precision medicine by enabling more precise approaches to cardiovascular and stroke research, prevention, and care of individuals and populations. Nevertheless, several challenges exist, and few artificial intelligence tools have been shown to improve cardiovascular and stroke care sufficiently to be widely adopted. This scientific statement outlines the current state of the art on the use of artificial intelligence algorithms and data science in the diagnosis, classification, and treatment of cardiovascular disease. It also sets out to advance this mission, focusing on how digital tools and, in particular, artificial intelligence may provide clinical and mechanistic insights, address bias in clinical studies, and facilitate education and implementation science to improve cardiovascular and stroke outcomes. Last, a key objective of this scientific statement is to further the field by identifying best practices, gaps, and challenges for interested stakeholders.

The American Heart Association at 100: A Century of Scientific Progress and the Future of Cardiovascular Science: A Presidential Advisory From the American Heart Association.

In 1924, the founders of the American Heart Association (AHA) envisioned an international society focused on the heart and aimed at facilitating research, disseminating information, increasing public awareness, and developing public health policy related to heart disease. This presidential advisory provides a comprehensive review of the past century of cardiovascular and stroke science, with a focus on the AHA's contributions, as well as informed speculation about the future of cardiovascular science into the next century of the organization's history. The AHA is a leader in fundamental, translational, clinical, and population science, and it promotes the concept of the "learning health system," in which a continuous cycle of evidence-based practice leads to practice-based evidence, permitting an iterative refinement in clinical evidence and care. This advisory presents the AHA's journey over the past century from instituting professional membership to establishing extraordinary research funding programs; translating evidence to practice through clinical practice guidelines; affecting systems of care through quality programs, certification, and implementation; leading important advocacy efforts at the federal, state and local levels; and building global coalitions around cardiovascular and stroke science and public health. Recognizing an exciting potential future for science and medicine, the advisory offers a vision for even greater impact for the AHA's second century in its continued mission to be a relentless force for longer, healthier lives.

Factors associated with frequency of fruit and vegetable consumption among selected sub-Saharan African populations: evidence from the Cardiovascular H3Africa Innovation Resource Project.

BACKGROUND: Frequent fruit and vegetable consumption is considered a promising dietary behaviour that protects health. However, most existing studies about the factors associated with this phenomenon among Africans are based on single-country reports, apart from one meta-regression combining smaller studies. This study harmonized large datasets and assessed factors associated with the frequency of fruit and vegetable consumption in this population. METHODS: Individual-level data on sociodemographics, lifestyle and diet from 20 443 participants across five African countries (Burkina Faso, Ghana, Kenya, South Africa and Nigeria), from the Stroke Investigative Research and Educational Network (SIREN) and Africa Wits-INDEPTH partnership for Genomic Research (AWI-Gen) studies, were harmonized. Total frequency of fruit and vegetable consumption (in portions/week) was classified as 'low' (≤6), 'moderate' (7-14) and 'high' (≥15). Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) of factors associated with the total frequency of fruit and vegetable consumption (using 'low' consumption as the reference) were estimated using multinomial regression models. RESULTS: Mean age of participants was 54.3 ± 11.8 years, 10 641 (52.1%) were female, and the median (interquartile range) frequency of total fruit and vegetable consumption was 10.0 (4.0, 21.0) portions/week. Participants with a family history of cardiovascular disease [moderate (aOR, 0.92; 95% CI, 0.85, 1.00) and high (aOR, 0.85; 95% CI, 0.78, 0.92)], current smokers [moderate (aOR, 0.83; 95% CI, 0.74, 0.94) and high (aOR, 0.78; 95% CI, 0.69, 0.88)], current alcohol users [moderate (aOR, 0.92; 95% CI, 0.85, 1.00) and high (aOR, 0.82; 95% CI, 0.76, 0.89)] and physically inactive participants [moderate (aOR, 0.85; 95% CI, 0.75, 0.96) and high (aOR, 0.80; 95% CI, 0.70, 0.90)] were less likely to consume fruits and vegetables frequently. CONCLUSION: Africans with lifestyle risk factors for cardiovascular disease were less likely to consume fruit and vegetables frequently.

Clinical and neuroimaging factors associated with 30-day fatality among indigenous West Africans with spontaneous intracerebral hemorrhage.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is associated with a high case fatality rate in resource-limited settings. The independent predictors of poor outcome after ICH in sub-Saharan Africa remains to be characterized in large epidemiological studies. We aimed to determine factors associated with 30-day fatality among West African patients with ICH. METHODS: The Stroke Investigative Research and Educational Network (SIREN) study is a multicentre, case-control study conducted at 15 sites in Nigeria and Ghana. Adults aged ≥18 years with spontaneous ICH confirmed with neuroimaging. Demographic, cardiovascular risk factors, clinical features and neuroimaging markers of severity were assessed. The independent risk factors for 30-day mortality were determined using a multivariate logistic regression analysis with an adjusted odds ratio (OR) and 95% confidence interval (CI). RESULTS: Among 964 patients with ICH, 590 (61.2%) were males with a mean age (SD) of 54.3(13.6) years and a case fatality of 34.3%. Factors associated with 30-day mortality among ICH patients include: Elevated mean National Institute of Health Stroke Scale(mNIHSS);(OR 1.06; 95% CI 1.02-1.11), aspiration pneumonitis; (OR 7.17; 95% CI 2.82-18.24), ICH volume > 30mls; OR 2.68; 95% CI 1.02-7.00)) low consumption of leafy vegetables (OR 0.36; 95% CI 0.15-0.85). CONCLUSION: This study identified risk and protective factors associated with 30-day mortality among West Africans with spontaneous ICH. These factors should be further investigated in other populations in Africa to enable the development of ICH mortality predictions models among indigenous Africans.

A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies.

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of NIPSNAP3A and an intergenic region on chromosome 1.

Metabolite profiles and DNA methylation in metabolic syndrome: a two-sample, bidirectional Mendelian randomization.

Introduction: Metabolic syndrome (MetS) increases the risk of cardiovascular disease and death. Previous '-omics' studies have identified dysregulated serum metabolites and aberrant DNA methylation in the setting of MetS. However, the relationship between the metabolome and epigenome have not been elucidated. In this study, we identified serum metabolites associated with MetS and DNA methylation, and we conducted bidirectional Mendelian randomization (MR) to assess causal relationships between metabolites and methylation. Methods: We leveraged metabolomic and genomic data from a national United States cohort of older adults (REGARDS), as well as metabolomic, epigenomic, and genomic data from a family-based study of hypertension (HyperGEN). We conducted metabolite profiling for MetS in REGARDS using weighted logistic regression models and validated them in HyperGEN. Validated metabolites were selected for methylation studies which fit linear mixed models between metabolites and six CpG sites previously linked to MetS. Statistically significant metabolite-CpG pairs were selected for two-sample, bidirectional MR. Results: Forward MR indicated that glucose and serine metabolites were causal on CpG methylation near CPT1A [B(SE): -0.003 (0.002), p = 0.028 and B(SE): 0.029 (0.011), p = 0.030, respectively] and that serine metabolites were causal on ABCG1 [B(SE): -0.008(0.003), p = 0.006] and SREBF1 [B(SE): -0.009(0.004), p = 0.018] methylation, which suggested a protective effect of serine. Reverse MR showed a bidirectional relationship between cg06500161 (ABCG1) and serine [B(SE): -1.534 (0.668), p = 0.023]. Discussion: The metabolome may contribute to the relationship between MetS and epigenetic modifications.

Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.

Determinants of mosaic chromosomal alteration fitness.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well-understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our estimates of mCA fitness were correlated (R 2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using a theoretical probability distribution. Individuals with lymphoid-associated mCAs had a significantly higher white blood cell count and faster clonal expansion rate. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified TCL1A , NRIP1 , and TERT locus variants as modulators of mCA clonal expansion rate.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study.

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

Association of potato consumption with calcified atherosclerotic plaques in the coronary arteries: The NHLBI Family Heart Study.

BACKGROUND AND AIMS: While the association of potato consumption with risk factors for coronary artery disease has been inconsistent, no data are available in the literature on the influence of potato consumption on subclinical disease. Thus, we sought to examine whether baked/mashed potato consumption is associated with calcified atherosclerotic plaques in the coronary arteries. METHODS AND RESULTS: In a cross-sectional design, we studied 2208 participants of the NHLBI Family Heart Study. These subjects were selected based on their elevated cardiovascular disease risk compared to the general population. Potato consumption was assessed by a semi-quantitative food frequency questionnaire. We defined prevalent CAC using an Agatston score of at least 100 and fitted generalized estimating equations to calculate prevalence odds ratios of CAC. Mean age at initial clinic visit was 58.2 years and 55% were female. Median consumption of potatoes was 2-4/week. There was no statistically significant association between frequency of potato consumption and prevalent CAC: odds ratios (95% CI) for CAC were 1.0 (reference), 0.85 (0.56-1.30), 0.85 (0.58-1.26), and 0.95 (0.60-1.53) among subjects reporting potato consumption of <1/week, 1/week, 2-4/week, and 5+/week, respectively (p for linear trend 0.83), adjusting for age, sex, BMI, smoking, exercise, diabetes, hypertension, total calories, prevalent coronary heart disease, income, education, and daily red meat intake. CONCLUSIONS: We found no significant association between baked/mashed potato consumption and CAC in older adults. STUDY REGISTRATION NUMBER: NCT00005136. Study registration date: 5/25/2000.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study.

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.

Determinants of First-Ever Stroke Severity in West Africans: Evidence From the SIREN Study.

Background Baseline stroke severity is probably partly responsible for poor stroke outcomes in sub-Saharan Africa. However, there is a paucity of information on determinants of stroke severity among indigenous Africans. We sought to identify the factors associated with stroke severity among West Africans in the SIREN (Stroke Investigative Research and Educational Networks) study. Methods and Results Stroke was diagnosed clinically and confirmed with brain neuroimaging. Severe stroke was defined as a Stroke Levity Scale score of ≤5. A multivariate logistic regression model was constructed to identify factors associated with stroke severity at 95% CI and a nominal cutoff of 5% type 1 error. A total of 3660 stroke cases were included. Overall, 50.7%% had severe stroke, including 47.6% of all ischemic strokes and 56.1% of intracerebral hemorrhage. Factors independently associated with severe stroke were meat consumption (adjusted odds ratio [aOR], 1.97 [95% CI, 1.43-2.73]), low vegetable consumption (aOR, 2.45 [95% CI, 1.93-3.12]), and lesion volume, with an aOR of 1.67 (95% CI, 1.03-2.72) for lesion volume of 10 to 30 cm3 and aOR of 3.88 (95% CI, 1.93-7.81) for lesion volume >30 cm3. Severe ischemic stroke was independently associated with total anterior circulation infarction (aOR, 3.1 [95% CI, 1.5-6.9]), posterior circulation infarction (aOR, 2.2 [95% CI, 1.1-4.2]), and partial anterior circulation infarction (aOR, 2.0 [95% CI, 1.2-3.3]) compared with lacunar stroke. Increasing age (aOR, 2.6 [95% CI, 1.3-5.2]) and lesion volume >30 cm3 (aOR, 6.2 [95% CI, 2.0-19.3]) were independently associated with severe intracerebral hemorrhage. Conclusions Severe stroke is common among indigenous West Africans, where modifiable dietary factors are independently associated with it. These factors could be targeted to reduce the burden of severe stroke.

Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups.

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.

The genetic determinants of recurrent somatic mutations in 43,693 blood genomes.

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

The impact of alcoholic drinks and dietary factors on epigenetic markers associated with triglyceride levels.

Background: Many epigenetic loci have been associated with plasma triglyceride (TG) levels, but epigenetic connections between those loci and dietary exposures are largely unknown. This study aimed to characterize the epigenetic links between diet, lifestyle, and TG. Methods: We first conducted an epigenome-wide association study (EWAS) for TG in the Framingham Heart Study Offspring population (FHS, n = 2,264). We then examined relationships between dietary and lifestyle-related variables, collected four times in 13 years, and differential DNA methylation sites (DMSs) associated with the last TG measures. Third, we conducted a mediation analysis to evaluate the causal relationships between diet-related variables and TG. Finally, we replicated three steps to validate identified DMSs associated with alcohol and carbohydrate intake in the Genetics of Lipid-Lowering Drugs and Diet Network (GOLDN) study (n = 993). Results: In the FHS, the EWAS revealed 28 TG-associated DMSs at 19 gene regions. We identified 102 unique associations between these DMSs and one or more dietary and lifestyle-related variables. Alcohol and carbohydrate intake showed the most significant and consistent associations with 11 TG-associated DMSs. Mediation analyses demonstrated that alcohol and carbohydrate intake independently affect TG via DMSs as mediators. Higher alcohol intake was associated with lower methylation at seven DMSs and higher TG. In contrast, increased carbohydrate intake was associated with higher DNA methylation at two DMSs (CPT1A and SLC7A11) and lower TG. Validation in the GOLDN further supports the findings. Conclusion: Our findings imply that TG-associated DMSs reflect dietary intakes, particularly alcoholic drinks, which could affect the current cardiometabolic risk via epigenetic changes. This study illustrates a new method to map epigenetic signatures of environmental factors for disease risk. Identification of epigenetic markers of dietary intake can provide insight into an individual's risk of cardiovascular disease and support the application of precision nutrition. Clinical Trial Registration: www.ClinicalTrials.gov, the Framingham Heart Study (FHS), NCT00005121; the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), NCT01023750.

Structural variation across 138,134 samples in the TOPMed consortium.

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hematologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.

Structural variation across 138,134 samples in the TOPMed consortium.

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hemotologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.