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.

Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis.

BACKGROUND: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. METHODS: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. RESULTS: Using a Bonferroni-corrected significance threshold of P<1.6×10-4, we identified 3 genes (ATP1B1, ARVCF, and LIPG) associated with CAC and 2 genes (ABCG8 and EIF2B2) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both ATP1B1 and ARVCF also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis. CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.

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.

Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification.

Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.

Carriers of rare damaging CCR2 genetic variants are at lower risk of atherosclerotic disease.

Background: The CCL2/CCR2 axis governs monocyte trafficking and recruitment to atherosclerotic lesions. Human genetic analyses and population-based studies support an association between circulating CCL2 levels and atherosclerosis. Still, it remains unknown whether pharmacological targeting of CCR2, the main CCL2 receptor, would provide protection against human atherosclerotic disease. Methods: In whole-exome sequencing data from 454,775 UK Biobank participants (40-69 years), we identified predicted loss-of-function (LoF) or damaging missense (REVEL score >0.5) variants within the CCR2 gene. We prioritized variants associated with lower monocyte count (p<0.05) and tested associations with vascular risk factors and risk of atherosclerotic disease over a mean follow-up of 14 years. The results were replicated in a pooled cohort of three independent datasets (TOPMed, deCODE and Penn Medicine BioBank; total n=441,445) and the effect of the most frequent damaging variant was experimentally validated. Results: A total of 45 predicted LoF or damaging missense variants were identified in the CCR2 gene, 4 of which were also significantly associated with lower monocyte count, but not with other white blood cell counts. Heterozygous carriers of these variants were at a lower risk of a combined atherosclerosis outcome, showed a lower burden of atherosclerosis across four vascular beds, and were at a lower lifetime risk of coronary artery disease and myocardial infarction. There was no evidence of association with vascular risk factors including LDL-cholesterol, blood pressure, glycemic status, or C-reactive protein. Using a cAMP assay, we found that cells transfected with the most frequent CCR2 damaging variant (3:46358273:T:A, M249K, 547 carriers, frequency: 0.14%) show a decrease in signaling in response to CCL2. The associations of the M249K variant with myocardial infarction were consistent across cohorts (ORUKB: 0.62 95%CI: 0.39-0.96; ORexternal: 0.64 95%CI: 0.34-1.19; ORpooled: 0.64 95%CI: 0.450.90). In a phenome-wide association study, we found no evidence for higher risk of common infections or mortality among carriers of damaging CCR2 variants. Conclusions: Heterozygous carriers of damaging CCR2 variants have a lower burden of atherosclerosis and lower lifetime risk of myocardial infarction. In conjunction with previous evidence from experimental and epidemiological studies, our findings highlight the translational potential of CCR2-targeting as an atheroprotective approach.

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.

Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.

Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification.

Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC (ARSE and MMP16), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease.

Whole genome sequence analysis of blood lipid levels in >66,000 individuals.

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

Association of Vascular Properties With the Brain White Matter Hyperintensity in Middle-Aged Population.

Background The periventricular white matter is more sensitive to the systemic hemodynamic alterations than the deep white matter because of differences in its vascular structure and systemic circulation relationship. We hypothesize that periventricular white matter hyperintensity (PVWMH) volume shows greater association than deep white matter hyperintensity (DWMH) volume with vascular properties (VPs) reflecting arterial stiffness and cardiovascular remodeling, indicators of the systemic circulation. Methods and Results A total of 426 participants (age, 59.0±6.1 years; 57.5% women; and 39.7% Black race) in the Genetic Study of Atherosclerosis Risk who were aged ≥50 years and had brain magnetic resonance imaging were studied. VPs included pulse pressure, hypertensive response to exercise, diastolic brachial artery diameter, diastolic common carotid artery diameter, common carotid artery distensibility coefficient, and left ventricular function. The relative associations of VPs with PVWMH and DWMH as multiple measures within the same individual were determined using multilevel linear models. We also determined if age modified the differences in VPs associations with PVWMH and DWMH. Our findings indicated that, within the same subject, PVWMH volume had greater association than DWMH volume with pulse pressure (P=0.002), hypertensive response to exercise (P=0.04), diastolic brachial artery diameter (P=0.012), and diastolic common carotid artery diameter (P=0.04), independent of age and cardiovascular risk factors. The differences of PVWMH versus DWMH associations with VPs did not differ at any age threshold. Conclusions We show, for the first time, that PVWMH has greater association than DWMH, independent of age, with vascular measurements of arterial stiffness and cardiovascular remodeling suggesting that changes in the systemic circulation affect the PVWMH and DWMH differently.

Association of Coronary Artery Atherosclerosis With Brain White Matter Hyperintensity.

Background and Purpose: We aim to determine, in healthy high-risk adults, the association between subclinical coronary artery disease and white matter hyperintensity (WMH) volume and location, independent of atherosclerotic risk factors. Methods: Seven hundred eighty-two asymptomatic first-degree relatives of index cases with early-onset coronary artery disease (<60 years old) from GeneSTAR (Genetic Study of Atherosclerosis Risk) with contemporaneous coronary computed tomography angiography and brain magnetic resonance imaging were analyzed. Multilevel mixed-effects linear regression models, accounting for family structure, evaluated the association of total WMH volume and 3 regions (deep WMH, periventricular WMH [PVWMH], or borderzone [cuff]) with markers of coronary artery disease. Separate models were created for total WMH, deep WMH, PVWMH, and cuff volumes, each, as dependent variables, across coronary computed tomography angiography variables, adjusted for covariates. Results: Mean age was 51 years ±10, with 58% women and 39% African American people. Participants with any coronary plaque had 52% larger WMH volumes than those without plaque (95% CI, 0.24­0.59). Per 1% greater coronary plaque volume, total WMH volumes were 0.07% larger (95% CI, 0.04­0.10). Every 1% higher total coronary plaque volume was associated with 5.03% larger deep WMH volume (95% CI, 4.67­5.38), 5.10% PVWMH larger volume (95% CI, 4.72­5.48), and 2.74% larger cuff volume (95% CI, 2.38­3.09) with differences in this association when comparing deep WMH to PVWMH (P interaction, 0.001) or cuff (P interaction, <0.001), respectively. Conclusions: In healthy, high-risk individuals, the presence and volume of coronary artery plaque are associated with larger WMH volumes, appearing the strongest for PVWMH. These findings in high-risk families suggest a disease relationship in 2 different vascular beds, beyond traditional risk factors, possibly due to genetic predisposition.

White Matter Injury Is Associated with Reduced Manual Dexterity and Elevated Serum Ceramides in Subjects with Cerebral Small Vessel Disease.

INTRODUCTION: We have demonstrated that asymptomatic cerebral small vessel disease (cSVD) measured by white matter hyperintensity volume is associated with reduced manipulative manual dexterity on the Grooved Peg Board Test (GPBT) in middle-aged healthy individuals with a family history of early coronary artery disease. In this current study, we aim to identify the association of subcortical white matter microstructural impairment measured by diffusion tensor imaging, manual dexterity measured by GPBT and circulating serums ceramide, another marker for white matter injury. We hypothesize that lower regional fractional anisotropy (rFA) is associated with worse performance on GPBT and elevated serum ceramides in the same study population. METHODS: rFA of 48 regions representing the subcortical white matters were analyzed in GeneSTAR participants in addition to serum ceramides and GPBT scores. Unadjusted univariable analyses with Bonferroni correction for multiple comparisons were completed using Spearman correlation for testing the associations between ceramides, rFA of subcortical white matter, and GPBT performance. Subsequently, sensitivity analyses were performed after excluding the participants that had any physical limitation that may influence their performance on GPBT. Finally, in the adjusted analysis using generalized estimating equation, linear regression models were performed for the areas that met significance threshold in the unadjusted analyses. RESULTS: 112 subjects (age [49 ± 11], 51% female, 39.3% African American) were included. Adjusted analyses for the significant correlations that met the Bonferroni correction threshold in the unadjusted univariable analyses identified significant negative associations between rFA of the right fornix (RF) and log-GPBT score (ß = -0.497, p = 0.037). In addition, rFA of RF negatively correlated with log serum ceramide levels (C18: ß = -0.03, p = 0.003, C20: ß = -0.0002, p = 0.004) and rFA of left genu of corpus callosum negatively correlated with log C18 level (ß = -0.0103, p = 0.027). CONCLUSIONS: These results demonstrate that subcortical microstructural white matter disruption is associated with elevated serum ceramides and reduced manual dexterity in a population with cSVD. These findings suggest that injury to white matter tracts undermines neural networks, with functional consequences in a middle-aged population with cardiovascular risk factors.

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

BACKGROUND: Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. METHODS AND RESULTS: Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. CONCLUSION: This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.

Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities.

BACKGROUND AND PURPOSE: Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. METHODS: Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. RESULTS: In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. CONCLUSIONS: Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.

Allelic Heterogeneity at the CRP Locus Identified by Whole-Genome Sequencing in Multi-ancestry Cohorts.

Whole-genome sequencing (WGS) can improve assessment of low-frequency and rare variants, particularly in non-European populations that have been underrepresented in existing genomic studies. The genetic determinants of C-reactive protein (CRP), a biomarker of chronic inflammation, have been extensively studied, with existing genome-wide association studies (GWASs) conducted in >200,000 individuals of European ancestry. In order to discover novel loci associated with CRP levels, we examined a multi-ancestry population (n = 23,279) with WGS (∼38× coverage) from the Trans-Omics for Precision Medicine (TOPMed) program. We found evidence for eight distinct associations at the CRP locus, including two variants that have not been identified previously (rs11265259 and rs181704186), both of which are non-coding and more common in individuals of African ancestry (∼10% and ∼1% minor allele frequency, respectively, and rare or monomorphic in 1000 Genomes populations of East Asian, South Asian, and European ancestry). We show that the minor (G) allele of rs181704186 is associated with lower CRP levels and decreased transcriptional activity and protein binding in vitro, providing a plausible molecular mechanism for this African ancestry-specific signal. The individuals homozygous for rs181704186-G have a mean CRP level of 0.23 mg/L, in contrast to individuals heterozygous for rs181704186 with mean CRP of 2.97 mg/L and major allele homozygotes with mean CRP of 4.11 mg/L. This study demonstrates the utility of WGS in multi-ethnic populations to drive discovery of complex trait associations of large effect and to identify functional alleles in noncoding regulatory regions.

The relationship of family history and risk of type 2 diabetes differs by ancestry.

AIM: Type 2 diabetes (T2DM) in a first-degree relative is a risk factor for incident diabetes. Americans of African ancestry (AA) have higher rates of T2DM than Americans of European ancestry (EA). Thus, we aimed to determine whether the presence, number and kinship of affected relatives are associated with race-specific T2DM incidence in a prospective study of participants from the Genetic Study of Atherosclerosis Risk (GeneSTAR), who underwent baseline screening including a detailed family history. METHODS: Nondiabetic healthy siblings (n=1405) of patients with early-onset coronary artery disease (18-59 years) were enrolled (861 EA and 544 AA) and followed for incident T2DM (mean 14±6 years). RESULTS: Baseline age was 46.2±7.3 years and 56% were female. T2DM occurred in 12.3% of EA and 19.1% of AA. Among EA, 32.6% had ≥1 affected first-degree relatives versus 53.1% in AA, P<0.0001. In fully adjusted Cox proportional hazard analyses, any family history was related to incident T2DM in EA (HR=2.53, 95% CI: 1.58-4.06) but not in AA (HR=1.01, 0.67-1.53). The number of affected relatives conferred incremental risk of T2DM in EA with HR=1.82 (1.08-3.06), 4.83 (2.15-10.85) and 8.46 (3.09-23.91) for 1, 2, and ≥3 affected, respectively. In AA only ≥3 affected increased risk (HR=2.45, 1.44-4.19). Specific kinship patterns were associated with incident T2DM in EA but not in AA. CONCLUSIONS: The presence of any first-degree relative with T2DM does not discriminate risk in AA given the high race-specific prevalence of diabetes. Accounting for the number of affected relatives may more appropriately estimate risk for incident diabetes in both races.

Diabetes and Platelet Response to Low-Dose Aspirin.

Context: Previous studies have suggested less cardioprotective benefit of aspirin in adults with diabetes, raising concerns about "aspirin resistance" and potentially reduced effectiveness for prevention of cardiovascular disease (CVD). Objective: To examine differences in platelet response to aspirin by diabetes status. Design, Setting, Participants: We examined platelet response before and after aspirin (81 mg/day for 14 days) in 2113 adults (175 with diabetes, 1,938 without diabetes), in the Genetic Study of Aspirin Responsiveness cohort, who had family history of early-onset CVD. Main Outcome Measures: In vivo platelet activation (urinary thromboxane B2), in vitro platelet aggregation to agonists (arachidonic acid, adenosine diphosphate, collagen), and platelet function analyzer-100 closure time. Results: Although adults with diabetes had higher in vivo platelet activation before aspirin, the reduction in in vivo platelet activation after aspirin was similar in those with vs without diabetes. Likewise, the reduction in multiple in vitro platelet measures was similar after aspirin by diabetes status. In regression analyses adjusted for age, sex, race, BMI, smoking, platelet counts, and fibrinogen levels, in vivo platelet activation remained higher in adults with vs without diabetes after aspirin (P = 0.04), but this difference was attenuated after additional adjustment for preaspirin levels (P = 0.10). No differences by diabetes status were noted for any of the in vitro platelet measures after aspirin in fully adjusted models that also accounted for preaspirin levels. Conclusions: In vitro platelet response to aspirin does not differ by diabetes status, suggesting no intrinsic differences in platelet response to aspirin. Instead, factors extrinsic to platelet function should be investigated to give further insights into aspirin use for primary prevention in diabetes.

Epicardial Fat Distribution Assessed with Cardiac CT in Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy.

Purpose To compare epicardial fat in patients with arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) with that in healthy subjects. Materials and Methods In this retrospective study, cardiac CT scans in 44 patients with ARVD/C (mean age, 39 years ± 12; 23 men) were compared with those in 45 control group participants between January 2008 and July 2015. Volumes of intrathoracic adipose tissue, mediastinal adipose tissue (MAT), and total epicardial adipose tissue (EAT) were quantified. EAT was subdivided into three regions-right ventricular (RV) EAT, left ventricular (LV) EAT, and peri-atrial EAT (atrial EAT)-and normalized to MAT for all regions. Logistic regression and receiver operating characteristic analysis were performed to evaluate the association between epicardial fat with the diagnosis of ARVD/C. Results Total EAT volume was higher in patients with ARVD/C than in healthy control group participants (median, 98 mL vs 76 mL, respectively; P = .04). Regionally, LV and RV EAT volumes were higher in patients with ARVD/C than in control group participants, most notably when indexed to MAT (median LV EAT index: 0.49 vs 0.15, respectively; median RV EAT index: 0.91 vs 0.52; P ˂ .0005 for both). The optimal cutoff for diagnosis of ARVD/C was an LV EAT index of 0.24, with a sensitivity and specificity of 91% and 71%, respectively. Atrial EAT volume and total intrathoracic adipose tissue volume were not different between groups. RV diameter showed a positive correlation with total EAT index and LV EAT index (r = 0.21, P = .05 and r = 0.33, P = .002, respectively). Conclusion Higher amounts of right ventricular and left ventricular epicardial fat are found in hearts with arrhythmogenic right ventricular dysplasia/cardiomyopathy, particularly adjacent to the left ventricle, which correlates with disease severity and helps differentiate patients from healthy subjects. © RSNA, 2018 Online supplemental material is available for this article.