Obesity Duration, Severity, and Distribution Trajectories and Cardiovascular Disease Risk in the Atherosclerosis Risk in Communities Study

BACKGROUND: Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. METHODS AND RESULTS: We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communities study (N=14 514; mean age=54 years; 55% female) to associate obesity subclasses (derived from body mass index, waist circumference, self-reported weight at age 25, tricep skinfold, and calf circumference across up to four triennial visits) with total mortality, incident CVD, and CVD risk factors. We identified four obesity subclasses, summarized by their body mass index and waist circumference slope as decline (4.1%), stable/slow decline (67.8%), moderate increase (24.6%), and rapid increase (3.6%) subclasses. Compared with participants in the stable/slow decline subclass, the decline subclass was associated with elevated mortality (hazard ratio [HR] 1.45, 95% CI 1.31, 1.60, P<0.0001) and with heart failure (HR 1.41, 95% CI 1.22, 1.63, P<0.0001), stroke (HR 1.53, 95% CI 1.22, 1.92, P=0.0002), and coronary heart disease (HR 1.36, 95% CI 1.14, 1.63, P=0.0008), adjusting for baseline body mass index and CVD risk factor profile. The moderate increase latent class was not associated with any significant differences in CVD risk as compared to the stable/slow decline latent class and was associated with a lower overall risk of mortality (HR 0.85, 95% CI 0.80, 0.90, P<0.0001), despite higher body mass index at baseline. The rapid increase latent class was associated with a higher risk of heart failure versus the stable/slow decline latent class (HR 1.34, 95% CI 1.10, 1.62, P=0.004). CONCLUSIONS: Consideration of heterogeneity and longitudinal changes in obesity measures is needed in clinical care for a more precision-oriented view of CVD risk

Comparison of Proteomic Assessment Methods in Multiple Cohort Studies

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155922/1/pmic13292_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155922/2/pmic13292.pd

Analyses of biomarker traits in diverse UK biobank participants identify associations missed by European-centric analysis strategies

Despite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, as well as variants rare in European populations, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n = 9354), East Asian (n = 2559), and South Asian (n = 9823) ancestry UK Biobank (UKBB) participants. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in a recent European ancestry-focused analysis of UKBB participants. We identify 7 novel signals in African ancestry and 2 novel signals in South Asian ancestry participants (p < 1.61E−10). Many of these signals are highly plausible, including a cis pQTL for the gene encoding gamma-glutamyl transferase and PIEZO1 and G6PD variants with impacts on HbA1c through likely erythrocytic mechanisms. This work illustrates the importance of using the genetic data we already have in diverse populations, with novel discoveries possible in even modest sample sizes

Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics

Background: Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results: We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion: This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. © 2020 The Author(s)

Association Between Whole Blood-Derived Mitochondrial Dna Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia)

Obesity Partially Mediates the Diabetogenic Effect of Lowering LDL Cholesterol

OBJECTIVE LDL cholesterol (LDLc)-lowering drugs modestly increase body weight and type 2 diabetes risk, but the extent to which the diabetogenic effect of lowering LDLc is mediated through increased BMI is unknown. RESEARCH DESIGN AND METHODS We conducted summary-level univariable and multivariable Mendelian randomization (MR) analyses in 921,908 participants to investigate the effect of lowering LDLc on type 2 diabetes risk and the proportion of this effect mediated through BMI. We used data from 92,532 participants from 14 observational studies to replicate findings in individual-level MR analyses. RESULTS A 1-SD decrease in genetically predicted LDLc was associated with increased type 2 diabetes odds (odds ratio [OR] 1.12 [95% CI 1.01, 1.24]) and BMI (b 5 0.07 SD units [95% CI 0.02, 0.12]) in univariable MR analyses. The multivariable MR analysis showed evidence of an indirect effect of lowering LDLc on type 2 diabetes through BMI (OR 1.04 [95% CI 1.01, 1.08]) with a proportion mediated of 38% of the total effect (P 5 0.03). Total and indirect effect estimates were similar across a number of sensitivity analyses. Individual-level MR analyses confirmed the indirect effect of lowering LDLc on type 2 diabetes through BMI with an estimated proportion mediated of 8% (P 5 0.04). CONCLUSIONS These findings suggest that the diabetogenic effect attributed to lowering LDLc is partially mediated through increased BMI. Our results could help advance understanding of adipose tissue and lipids in type 2 diabetes pathophysiology and inform strategies to reduce diabetes risk among individuals taking LDLc-lowering medications

Genome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation

Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses was used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 × 10(–15)) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 × 10(–8)) and mtDNA replication (p = 1.2 × 10(–7)). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell-related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 × 10(–4)). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00439-021-02394-w

Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (−0.88% in hemizygous males, −0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; −0.98% in hemizygous males, −0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis

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 CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC

Supplemental Association of Clonal Hematopoiesis With Incident Heart Failure

Background: Age-related clonal hematopoiesis of indeterminate potential (CHIP), defined as clonally expanded leukemogenic sequence variations (particularly in DNMT3A, TET2, ASXL1, and JAK2) in asymptomatic individuals, is associated with cardiovascular events, including recurrent heart failure (HF). Objectives: This study sought to evaluate whether CHIP is associated with incident HF. Methods: CHIP status was obtained from whole exome or genome sequencing of blood DNA in participants without prevalent HF or hematological malignancy from 5 cohorts. Cox proportional hazards models were performed within each cohort, adjusting for demographic and clinical risk factors, followed by fixed-effect meta-analyses. Large CHIP clones (defined as variant allele frequency >10%), HF with or without baseline coronary heart disease, and left ventricular ejection fraction were evaluated in secondary analyses. Results: Of 56,597 individuals (59% women, mean age 58 years at baseline), 3,406 (6%) had CHIP, and 4,694 developed HF (8.3%) over up to 20 years of follow-up. CHIP was prospectively associated with a 25% increased risk of HF in meta-analysis (hazard ratio: 1.25; 95% confidence interval: 1.13-1.38) with consistent associations across cohorts. ASXL1, TET2, and JAK2 sequence variations were each associated with an increased risk of HF, whereas DNMT3A sequence variations were not associated with HF. Secondary analyses suggested large CHIP was associated with a greater risk of HF (hazard ratio: 1.29; 95% confidence interval: 1.15-1.44), and the associations for CHIP on HF with and without prior coronary heart disease were homogenous. ASXL1 sequence variations were associated with reduced left ventricular ejection fraction. Conclusions: CHIP, particularly sequence variations in ASXL1, TET2, and JAK2, represents a new risk factor for HF