Biology subjects

Khera, A. V.

Publications and source records attributed to Khera, A. V..

12 recordsLinked to original sources

bioRxiv2025

The 9p21.3 Coronary Artery Disease Risk Locus Modulates Vascular Cell-State Transitions via Enhancer-Driven Regulation of MTAP

The 9p21.3 locus is the strongest genetic association with coronary artery disease (CAD), yet its causal mechanisms remain unresolved. We map the regulatory architecture of 9p21.3 in disease-relevant vascular cells, identifying 12 enhancers within the CAD risk haplotype that respond dynamically to inflammatory and metabolic stress in fibroblasts and smooth muscle cells. These activated states are enriched for CAD heritability, implicating stress-responsive vascular wall cells in disease pathophysiology. Dense CRISPRi tiling integrated with fine-mapping and genomic constraint across >500,000 individuals nominates MTAP as the effector gene, with rs1537371 as a likely causal variant. Perturbation and multi-modal analyses show that MTAP loss induces pro-fibrotic and angiogenic programs and sensitizes vascular cells to TGF-{beta}-driven pathological transitions. Our findings reveal a vascular-specific enhancer network through which noncoding variation at 9p21.3 modulates CAD risk via MTAP--a previously unrecognized regulator of vascular remodeling located 269 kb from the risk haplotype. HighlightsO_LI9p21.3 CAD risk locus harbors 12 functional enhancers active in vascular wall cell types C_LIO_LICAD heritability is enriched in stressed vascular fibroblasts and smooth muscle cells C_LIO_LIHigh-resolution CRISPRi-MAC-seq maps 9p21.3 enhancer-gene and SNP-gene interactions C_LIO_LIMTAP identified as a causal effector gene regulated by 9p21.3 fine-mapped and constrained variants C_LIO_LIMTAP modulates TGF-{beta}-driven pathological vascular cell transitions C_LI

genomics↗

bioRxiv2021

A single cell atlas of human and mouse white adipose tissue

White adipose tissue (WAT), once regarded as morphologically and functionally bland, is now recognized to be dynamic, plastic, heterogenous, and involved in a wide array of biological processes including energy homeostasis, glucose and lipid handling, blood pressure control, and host defense1. High fat feeding and other metabolic stressors cause dramatic changes in adipose morphology, physiology, and cellular composition1, and alterations in adiposity are associated with insulin resistance, dyslipidemia, and type 2 diabetes (T2D)2. Here, we provide detailed cellular atlases of human and murine subcutaneous and visceral white fat at single cell resolution across a range of body weight. We identify subpopulations of adipocytes, adipose stem and progenitor cells (ASPCs), vascular, and immune cells and demonstrate commonalities and differences across species and dietary conditions. We link specific cell types to increased risk of metabolic disease, and we provide an initial blueprint for a comprehensive set of interactions between individual cell types in the adipose niche in leanness and obesity. These data comprise an extensive resource for the exploration of genes, traits, and cell types in the function of WAT across species, depots, and nutritional conditions.

physiology↗

bioRxiv2020

South Asian patient population genetics reveal strong founder effects and high rates of homozygosity - new resources for precision medicine

Population-scale genetic studies can identify drug targets and allow disease risk to be predicted with resulting benefit for management of individual health risks and system-wide allocation of health care delivery resources. Although population-scale projects are underway in many parts of the world, genetic variation between population groups means that additional projects are warranted. South Asia has a population whose genetics is the least characterized of any of the worlds major populations. Here we describe GenomeAsia studies that characterize population structure in South Asia and that create tools for economical and accurate genotyping at population-scale. Prior work on population structure characterized isolated population groups, the relevance of which to large-scale studies of disease genetics is unclear. For our studies we used whole genome sequence information from 4,807 individuals recruited in the health care delivery systems of Pakistan, India and Bangladesh to ensure relevance to population-scale studies of disease genetics. We combined this with WGS data from 927 individuals from isolated South Asian population groups, and developed a custom SNP array (called SARGAM) that is optimized for future human genetic studies in South Asia. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of homozygosity that approach 100 times that seen in outbred populations. We describe founder effects that increase the power to associate functional variants with disease processes and that make South Asia a uniquely powerful place for population-scale genetic studies.

genomics↗

bioRxiv2020

Analysis of cardiac magnetic resonance imaging traits in 29,000 individuals reveals shared genetic basis with dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we conducted a genome-wide association study (GWAS) of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 29,041 UK Biobank participants. 26 novel loci were associated with cardiac structure and function. These loci were found near 17 genes previously shown to cause Mendelian cardiomyopathies. A polygenic score of left ventricular end systolic volume was associated with incident DCM in previously disease-free individuals (hazard ratio = 1.54 per one standard deviation increase in the polygenic score, P = 2.1x10-16). Even among carriers of truncating mutations in TTN, the polygenic score influenced the size and function of the heart. These results further implicate common genetic polymorphisms in DCM pathogenesis.

genomics↗

bioRxiv2019

Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases

Summary ParagraphCommon human diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome1-3. Polygenic scores (PGSs) aggregate these alleles into a metric which represents an individuals genetic predisposition to a specific disease. PGSs have shown promise for early risk prediction4-7, and there is potential to use PGSs to understand disease biology in parallel8. Here, we investigate the role plasma protein levels play in cardiometabolic disease risk in a cohort of 3,087 healthy individuals using PGSs. We found PGSs for coronary artery disease (CAD), type 2 diabetes (T2D), chronic kidney disease (CKD), and ischaemic stroke (IS) were associated with levels of 49 plasma proteins. These associations were polygenic in architecture, largely independent of cis protein QTLs, and robust to environmental variation. Over a median 7.7 years follow-up, 28 of these plasma proteins were associated with future myocardial infarction (MI) or T2D events, 16 of which were causal mediators between polygenic risk and incident disease. These protein mediators of polygenic disease risk included targets of approved therapies which may have repurposing potential. Our results demonstrate that PGSs can identify proteins with causal roles in disease, and may have utility in drug development.

genetics↗

bioRxiv2019

Heterozygous ATP-binding Cassette Transporter G5 Gene Deficiency and Risk of Coronary Artery Disease

BackgroundFamilial sitosterolemia is a rare, recessive Mendelian disorder characterized by hyperabsorption and decreased biliary excretion of dietary sterols. Affected individuals typically have complete genetic deficiency - homozygous loss-of-function (LoF) variants -- in the ATP-binding cassette transporter G5 (ABCG5) or G8 (ABCG8) genes, and have substantially elevated plasma sitosterol and low-density lipoprotein cholesterol (LDL-C) levels. The impact of partial genetic deficiency of ABCG5 or ABCG8, as occurs in heterozygous carriers of LoF variants, on LDL-C and risk of coronary artery disease (CAD) has remained uncertain.\n\nMethodsWe first recruited nine sitosterolemia families, identified causative LoF variants in ABCG5 or ABCG8, and evaluated the associations of these ABCG5 or ABCG8 LoF variants with plasma phytosterols and lipid levels. We next assessed for LoF variants in ABCG5 or ABCG8 in CAD cases (n=29,361) versus controls (n=357,326). We tested the association of rare LoF variants in ABCG5 or ABCG8 with blood lipids and risk for CAD. Rare LoF variants were defined as protein-truncating variants with minor allele frequency less than 0.1% in ABCG5 or ABCG8.\n\nResultsIn sitosterolemia families, seven pedigrees harbored causative LoF variants in ABCG5 and two pedigrees in ABCG8. Homozygous LoF variants in either ABCG5 or ABCG8 led to marked elevations in sitosterol and LDL-C. Of those sitosterolemia families, heterozygous carriers of ABCG5 LoF variants exhibited increased sitosterol and LDL-C levels compared to non-carriers. Within the large-scale CAD case-control cohorts, prevalence of rare LoF variants in ABCG5 and in ABCG8 were approximately 0.1% each. ABCG5 heterozygous LoF variant carriers had significantly elevated LDL-C levels (24.7 mg/dL; 95% confidence interval [CI] 14 to 35; P=1.1x10-6), and were at two-fold increased risk of CAD (odds ratio 2.06, 95% CI 1.27 to 3.35; P=0.004). By contrast, ABCG8 heterozygous LoF carrier status was not associated with increased LDL-C or risk of CAD.\n\nConclusionsAlthough familial sitosterolemia is traditionally considered as a recessive disorder, we observed that heterozygous carriers of a LoF variant in ABCG5 had significantly increased sitosterol and LDL-C levels and a two-fold increase in risk of CAD.

genetics↗

bioRxiv2019

Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores

BackgroundThe inherited susceptibility of common, complex diseases may be caused by rare, monogenic pathogenic variants or by the cumulative effect of numerous common, polygenic variants. As such, comprehensive genome interpretation could involve two distinct genetic testing technologies -- high coverage next generation sequencing for known genes to detect pathogenic variants and a genome-wide genotyping array followed by imputation to calculate genome-wide polygenic scores (GPSs). Here we assessed the feasibility and accuracy of using low coverage whole genome sequencing (lcWGS) as an alternative to genotyping arrays to calculate GPSs.\n\nMethodsFirst, we performed downsampling and imputation of WGS data from ten individuals to assess concordance with known genotypes. Second, we assessed the correlation between GPSs for three common diseases -- coronary artery disease (CAD), breast cancer (BC), and atrial fibrillation (AF) -- calculated using lcWGS and genotyping array in 184 samples. Third, we assessed concordance of lcWGS-based genotype calls and GPS calculation in 120 individuals with known genotypes, selected to reflect diverse ancestral backgrounds. Fourth, we assessed the relationship between GPSs calculated using lcWGS and disease phenotypes in 11,502 European individuals seeking genetic testing.\n\nResultsWe found imputation accuracy r2 values of greater than 0.90 for all ten samples -- including those of African and Ashkenazi Jewish ancestry -- with lcWGS data at 0.5X. GPSs calculated using both lcWGS and genotyping array followed by imputation in 184 individuals were highly correlated for each of the three common diseases (r2 = 0.93 - 0.97) with similar score distributions. Using lcWGS data from 120 individuals of diverse ancestral backgrounds, including South Asian, East Asian, and Hispanic individuals, we found similar results with respect to imputation accuracy and GPS correlations. Finally, we calculated GPSs for CAD, BC, and AF using lcWGS in 11,502 European individuals, confirming odds ratios per standard deviation increment in GPSs ranging 1.28 to 1.59, consistent with previous studies.\n\nConclusionsHere we show that lcWGS is an alternative approach to genotyping arrays for common genetic variant assessment and GPS calculation. lcWGS provides comparable imputation accuracy while also overcoming the ascertainment bias inherent to variant selection in genotyping array design.

genomics↗

bioRxiv2019

A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease

Analyzing 5770 all-cause cirrhosis cases and 572,850 controls from seven cohorts, we identify a missense variant in the Mitochondrial Amidoxime Reducing Component 1 gene (MARC1 p.A165T) that associates with protection from all-cause cirrhosis (OR 0.88, p=2.1*10-8). This same variant also associates with lower levels of hepatic fat on computed tomographic imaging and lower odds of physician-diagnosed fatty liver as well as lower blood levels of alanine transaminase (-0.012 SD, 1.4*10-8), alkaline phosphatase (-0.019 SD, 6.6*10-9), total cholesterol (-0.037 SD, p=1*10-18) and LDL cholesterol (-0.035 SD, p=7.3*10-16). Carriers of rare protein-truncating variants in MARC1 had lower liver enzyme levels, cholesterol levels, and reduced odds of liver disease (OR 0.19, p= 0.04) suggesting that deficiency of the MARC1 enzyme protects against cirrhosis.

genomics↗

bioRxiv2019

An open resource of structural variation for medical and population genetics

Structural variants (SVs) rearrange large segments of the genome and can have profound consequences for evolution and human diseases. As national biobanks, disease association studies, and clinical genetic testing grow increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) have become integral for interpreting genetic variation. To date, no large-scale reference maps of SVs exist from high-coverage sequencing comparable to those available for point mutations in protein-coding genes. Here, we constructed a reference atlas of SVs across 14,891 genomes from diverse global populations (54% non-European) as a component of gnomAD. We discovered a rich landscape of 433,371 distinct SVs, including 5,295 multi-breakpoint complex SVs across 11 mutational subclasses, and examples of localized chromosome shattering, as in chromothripsis. The average individual harbored 7,439 SVs, which accounted for 25-29% of all rare protein-truncating events per genome. We found strong correlations between constraint against damaging point mutations and rare SVs that both disrupt and duplicate protein-coding sequence, suggesting intolerance to reciprocal dosage alterations for a subset of tightly regulated genes. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than any effect on noncoding SVs. Finally, we benchmarked carrier rates for medically relevant SVs, finding very large ([≥]1Mb) rare SVs in 3.8% of genomes (~1:26 individuals) and clinically reportable incidental SVs in 0.18% of genomes (~1:556 individuals). These data have been integrated directly into the gnomAD browser (https://gnomad.broadinstitute.org) and will have broad utility for population genetics, disease association, and diagnostic screening.

genomics↗

bioRxiv2018

Genetic association of photoplethysmography-derived arterial stiffness index with blood pressure and coronary artery disease

BackgroundArterial stiffness index (ASI) is independently associated with blood pressure and coronary artery disease (CAD) in epidemiologic studies. However, it is unknown whether these associations represent causal relationships.\n\nObjectivesHere, we assess whether genetic predisposition to increased ASI is associated with elevated blood pressure and CAD risk.\n\nMethodsGenome-wide association analysis (GWAS) of finger photoplethysmography-derived ASI was performed in 131,686 participants from the UK Biobank. Across UK Biobank participants not in the ASI GWAS, a 6-variant ASI polygenic risk score was calculated. The ASI polygenic score was associated with systolic and diastolic blood pressures (SBP, DBP, N=208,897), and with incident CAD over 10 years follow-up (N=223,061; 7,534 cases). The lack of CAD association observed was replicated among 184,305 participants (60,810 cases) from the Coronary Artery Disease Genetics Consortium (CARDIOGRAMplusC4D).\n\nResultsWe replicated prior reports of the epidemiologic association of ASI with SBP (Beta 0.55mmHg, [95% CI, 0.45-0.65], P=5.77x10-24), DBP (Beta 1.05mmHg, [95% CI, 0.99-1.11], P=7.27x10-272), and incident CAD (HR 1.08 [95% CI, 1.04-1.11], P=1.5x10-6) in multivariable models. While each SD increase in genetic predisposition to elevated ASI was highly associated with SBP (Beta 4.63 mmHg [95% CI, 2.1-7.2]; P=3.37x10-4), and DBP (Beta 2.61 mmHg [95% CI, 1.2-4.0]; P=2.85x10-4), no association was observed with incident CAD in UK Biobank (HR 1.12 [95% CI, 0.55-2.3]; P=0.75), or with prevalent CAD in CARDIOGRAMplusC4D (OR 0.56 [95% CI, 0.26-1.24]; P=0.15).\n\nConclusionsA genetic predisposition to higher ASI was associated with elevated blood pressure but not with increased risk of developing CAD.\n\nCondensed AbstractArterial stiffness index (ASI) is proposed by some as a surrogate of blood pressure and coronary artery disease (CAD) risk based on epidemiologic analyses. We tested whether genetic predisposition to increased ASI is associated with elevated blood pressure and CAD risk to assess whether these represent causal relationships. We find that a genetic predisposition to higher ASI is associated with elevated systolic (Beta 4.63 mmHg [95% CI, 2.1-7.2]) and diastolic blood pressures (Beta 2.61 mmHg [95% CI, 1.2-4.0]) in the UK Biobank, but not associated with incident CAD in the UK Biobank (P=0.75) or with prevalent CAD in CARDIOGRAMplusC4D (P=0.15). These data support a causal relationship of ASI with blood pressure but do not support the notion that ASI is a suitable surrogate for CAD risk.

bioinformatics↗

bioRxiv2017

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals

Deep-coverage whole genome sequencing at the population level is now feasible and offers potential advantages for locus discovery, particularly in the analysis rare mutations in non-coding regions. Here, we performed whole genome sequencing in 16,324 participants from four ancestries at mean depth >29X and analyzed correlations of genotypes with four quantitative traits - plasma levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. We conducted a discovery analysis including common or rare variants in coding as well as non-coding regions and developed a framework to interpret genome sequence for dyslipidemia risk. Common variant association yielded loci previously described with the exception of a few variants not captured earlier by arrays or imputation. In coding sequence, rare variant association yielded known Mendelian dyslipidemia genes and, in non-coding sequence, we detected no rare variant association signals after application of four approaches to aggregate variants in non-coding regions. We developed a new, genome-wide polygenic score for LDL-C and observed that a high polygenic score conferred similar effect size to a monogenic mutation (~30 mg/dl higher LDL-C for each); however, among those with extremely high LDL-C, a high polygenic score was considerably more prevalent than a monogenic mutation (23% versus 2% of participants, respectively).

genomics↗

bioRxiv2017

Genome-wide polygenic score to identify a monogenic risk-equivalent for coronary disease

Identification of individuals at increased genetic risk for a complex disorder such as coronary disease can facilitate treatments or enhanced screening strategies. A rare monogenic mutation associated with increased cholesterol is present in ~1:250 carriers and confers an up to 4-fold increase in coronary risk when compared with non-carriers. Although individual common polymorphisms have modest predictive capacity, their cumulative impact can be aggregated into a polygenic score. Here, we develop a new, genome-wide polygenic score that aggregates information from 6.6 million common polymorphisms and show that this score can similarly identify individuals with a 4-fold increased risk for coronary disease. In >400,000 participants from UK Biobank, the score conforms to a normal distribution and those in the top 2.5% of the distribution are at 4-fold increased risk compared to the remaining 97.5%. Similar patterns are observed with genome-wide polygenic scores for two additional diseases - breast cancer and severe obesity.\n\nOne Sentence SummaryA genome-wide polygenic score identifies 2.5% of the population born with a 4-fold increased risk for coronary artery disease.

genomics↗