Kei Hang K. Chan

Shared Molecular Pathways and Gene Networks for Cardiovascular Disease and Type 2 Diabetes in Women across Diverse Ethnicities

Background—Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Methods and Results—Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women’s Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene–gene or protein–protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Conclusions—Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D.

Shared Molecular Pathways and Gene Networks for Cardiovascular Disease and Type 2 Diabetes Mellitus in Women Across Diverse Ethnicities

Background—Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Methods and Results—Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women’s Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene–gene or protein–protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Conclusions—Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D.

Common Genetic Variants in Peroxisome Proliferator-Activated Receptor-γ (PPARG) and Type 2 Diabetes Risk Among Women's Health Initiative Postmenopausal Women

CONTEXT Peroxisome proliferator-activated receptor-γ (PPARG) plays a pivotal role in adipogenesis and glucose homeostasis. OBJECTIVE We investigated whether PPARG gene variants were associated with type 2 diabetes (T2D) risk in the multiethnic Womens Health Initiative (WHI). RESEARCH DESIGN AND METHODS We assessed PPARG single-nucleotide polymorphisms (SNPs) in a case-control study nested in the prospective WHI observational study (WHI-OS) (1543 T2D cases and 2170 matched controls). After identifying 24 tagSNPs, we used multivariable logistic regression models and haplotype-based analyses to estimate these tagSNP-T2D associations. Single-SNP analyses were also conducted in another study of 5642 African American and Hispanic American women in the WHI SNP Health Association Resource (WHI-SHARe). RESULTS We found a borderline significant association between the Pro12Ala (rs1801282) variant and T2D risk in WHI-OS [odds ratio (OR) 0.51, 95% confidence interval (CI) 0.31-0.83, P = .01, combined group, additive model; P = .04, Hispanic American] and WHI-SHARe (OR 0.25, 95% CI 0.08-0.77, P = .02, Hispanic American) participants. In promoter region, rs6809631, rs9817428, rs10510411, rs12629293, and rs12636454 were also associated with T2D risk (range ORs 0.68-0.78, 95% CIs 0.52-0.91 to 0.60-1.00, P ≤ .05) in WHI-OS, in which rs9817428 was replicated in then WHI-SHARe Hispanic American group (P = .04). CONCLUSIONS The association between PPARG Pro12Ala SNP and increased T2D susceptibility was confirmed, with Pro12 as risk allele. Additional significant loci included 5 PPARG promoter variants.

Rare Loss-of-Function Variants in NPC1 Predispose to Human Obesity

Some Shanghai Clinical Center f a role of Niemann-Pick type C1 (NPC1) for obesity traits. However, whether the loss-of-function mutations in NPC1 cause adiposity in humans remains unknown. We recruited 25 probands with rare autosomal-recessive Niemann-Pick type C (NP-C) disease and their parents in assessment of the effect of heterozygous NPC1 mutations on adiposity. We found that male NPC1+/− carriers had a significantly higher BMI than matched control subjects or the whole population-based control subjects. Consistently, male NPC1+/− mice had increased fat storage while eating a high-fat diet. We further conducted an in-depth assessment of rare variants in the NPC1 gene in young, severely obese subjects and lean control subjects and identified 17 rare nonsynonymous/frameshift variants in NPC1 (minor allele frequency <1%) that were significantly associated with an increased risk of obesity (3.40% vs. 0.73%, respectively, in obese patients and control subjects, P = 0.0008, odds ratio = 4.8, 95% CI 1.7–13.2), indicating that rare NPC1 variants were enriched in young, morbidly obese Chinese subjects. Importantly, participants carrying rare variants with severely damaged cholesterol-transporting ability had more fat accumulation than those with mild/no damage rare variants. In summary, rare loss-of-function NPC1 mutations were identified as being associated with human adiposity with a high penetrance, providing potential therapeutic interventions for obesity in addition to the role of NPC1 in the familial NP-C disease.

Genetic Variations in Magnesium-Related Ion Channels May Affect Diabetes Risk among African American and Hispanic American Women

BACKGROUND Prospective studies consistently link low magnesium intake to higher type 2 diabetes (T2D) risk. OBJECTIVE We examined the association of common genetic variants [single nucleotide polymorphisms (SNPs)] in genes related to magnesium homeostasis with T2D risk and potential interactions with magnesium intake. METHODS Using the Womens Health Initiative-SNP Health Association Resource (WHI-SHARe) study, we identified 17 magnesium-related ion channel genes (583 SNPs) and examined their associations with T2D risk in 7287 African-American (AA; n = 1949 T2D cases) and 3285 Hispanic-American (HA; n = 611 T2D cases) postmenopausal women. We performed both single- and multiple-locus haplotype analyses. RESULTS Among AA women, carriers of each additional copy of SNP rs6584273 in cyclin mediator 1 (CNNM1) had 16% lower T2D risk [OR: 0.84; false discovery rate (FDR)-adjusted P = 0.02]. Among HA women, several variants were significantly associated with T2D risk, including rs10861279 in solute carrier family 41 (anion exchanger), member 2 (SLC41A2) (OR: 0.54; FDR-adjusted P = 0.04), rs7174119 in nonimprinted in Prader-Willi/Angelman syndrome 1 (NIPA1) (OR: 1.27; FDR-adjusted P = 0.04), and 2 SNPs in mitochondrial RNA splicing 2 (MRS2) (rs7738943: OR = 1.55, FDR-adjusted P = 0.01; rs1056285: OR = 1.48, FDR-adjusted P = 0.02). Even with the most conservative Bonferroni adjustment, two 2-SNP-haplotypes in SLC41A2 and MRS2 region were significantly associated with T2D risk (rs12582312-rs10861279: P = 0.0006; rs1056285-rs7738943: P = 0.002). Among women with magnesium intake in the lowest 30% (AA: ≤0.164 g/d; HA: ≤0.185 g/d), 4 SNP signals were strengthened [rs11590362 in claudin 19 (CLDN19), rs823154 in SLC41A1, rs5929706 and rs5930817 in membra; HA: ≥0.313 g/d), rs6584273 in CNNM1 (OR: 0.71; FDR-adjusted P = 0.04) and rs1800467 in potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) (OR: 2.50; FDR-adjusted P = 0.01) were significantly associated with T2D risk. CONCLUSIONS Our findings suggest important associations between genetic variations in magnesium-related ion channel genes and T2D risk in AA and HA women that vary by amount of magnesium intake.

Common genetic variants in fatty acid-binding protein-4 (FABP4) and clinical diabetes risk in the Women's Health Initiative Observational Study.

Adipocypte fatty acid–binding protein‐4 (FABP4/adipocyte P2) may play a central role in energy metabolism and inflammation. In animal models, defects of the aP2 gene (aP2−/−) partially protected against the development of obesity‐related insulin resistance, dyslipidemia, and atherosclerosis. However, it is unclear whether common genetic variation in FABP4 gene contributes to risk of type 2 diabetes (T2D) or diabetes‐related metabolic traits in humans. We comprehensively assess the genetic associations of variants in the FABP4 gene with T2D risk and diabetes‐associated biomarkers in a prospective study of 1,529 cases and 2,147 controls among postmenopausal women aged 50–79 years who enrolled in the Womens Health Initiative Observational Study (WHI‐OS). We selected and genotyped a total of 11 haplotype‐tagging single‐nucleotide polymorphisms (tSNPs) spanning 41.3 kb across FABP4 in all samples. None of the SNPs and their derived haplotypes showed significant association with T2D risk. There were no significant associations between SNPs and plasma levels of inflammatory and endothelial biomarkers, including C‐reactive protein, tumor necrosis factor (TNF), interleukin‐6 (IL‐6), E‐selectin, and intercellular adhesion molecule (ICAM‐1). Among African‐American women, several SNPs were significantly associated with lower levels of vascular cell adhesion molecule‐1 (VCAM‐1), especially among those with incident T2D. On average, plasma levels of VCAM‐1 were significantly lower among carriers of each minor allele at rs1486004(C/T; −1.08 ng/ml, P = 0.01), rs7017115(A/G; −1.07 ng/ml, P = 0.02), and rs2290201(C/T; −1.12 ng/ml, P = 0.002) as compared with the homozygotes of the common allele, respectively. After adjusting for multiple testing, carriers of the rs2290201 minor allele remained significantly associated with decreasing levels of plasma VCAM‐1 in these women (P = 0.02). In conclusion, our finding from a multiethnic cohort of postmenopausal women did not support the notion that common genetic variants in the FABP4 gene may trigger increased risk of T2D. The observed significant association between reduced VCAM‐1 levels and FABP4 genotypes in African‐American women warrant further confirmation.

Shared genetic regulatory networks for cardiovascular disease and type 2 diabetes in multiple populations of diverse ethnicities in the United States

Cardiovascular diseases (CVD) and type 2 diabetes (T2D) are closely interrelated complex diseases likely sharing overlapping pathogenesis driven by aberrant activities in gene networks. However, the molecular circuitries underlying the pathogenic commonalities remain poorly understood. We sought to identify the shared gene networks and their key intervening drivers for both CVD and T2D by conducting a comprehensive integrative analysis driven by five multi-ethnic genome-wide association studies (GWAS) for CVD and T2D, expression quantitative trait loci (eQTLs), ENCODE, and tissue-specific gene network models (both co-expression and graphical models) from CVD and T2D relevant tissues. We identified pathways regulating the metabolism of lipids, glucose, and branched-chain amino acids, along with those governing oxidation, extracellular matrix, immune response, and neuronal system as shared pathogenic processes for both diseases. Further, we uncovered 15 key drivers including HMGCR, CAV1, IGF1 and PCOLCE, whose network neighbors collectively account for approximately 35% of known GWAS hits for CVD and 22% for T2D. Finally, we cross-validated the regulatory role of the top key drivers using in vitro siRNA knockdown, in vivo gene knockout, and two Hybrid Mouse Diversity Panels each comprised of >100 strains. Findings from this in-depth assessment of genetic and functional data from multiple human cohorts provide strong support that common sets of tissue-specific molecular networks drive the pathogenesis of both CVD and T2D across ethnicities and help prioritize new therapeutic avenues for both CVD and T2D.

Leveraging Multi-ethnic Evidence for Mapping Complex Traits in Minority Populations: An Empirical Bayes Approach.

Elucidating the genetic basis of complex traits and diseases in non-European populations is particularly challenging because US minority populations have been under-represented in genetic association studies. We developed an empirical Bayes approach named XPEB (cross-population empirical Bayes), designed to improve the power for mapping complex-trait-associated loci in a minority population by exploiting information from genome-wide association studies (GWASs) from another ethnic population. Taking as input summary statistics from two GWASs-a target GWAS from an ethnic minority population of primary interest and an auxiliary base GWAS (such as a larger GWAS in Europeans)-our XPEB approach reprioritizes SNPs in the target population to compute local false-discovery rates. We demonstrated, through simulations, that whenever the base GWAS harbors relevant information, XPEB gains efficiency. Moreover, XPEB has the ability to discard irrelevant auxiliary information, providing a safeguard against inflated false-discovery rates due to genetic heterogeneity between populations. Applied to a blood-lipids study in African Americans, XPEB more than quadrupled the discoveries from the conventional approach, which used a target GWAS alone, bringing the number of significant loci from 14 to 65. Thus, XPEB offers a flexible framework for mapping complex traits in minority populations.

Common Variations in the Genes Encoding C-Reactive Protein, Tumor Necrosis Factor-α, and Interleukin-6, and the Risk of Clinical Diabetes in the Women's Health Initiative Observational Study

BACKGROUND Circulating concentrations of high-sensitivity C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) have been associated with an increased risk of diabetes. METHODS To examine the roles of genetic variation in the genes encoding CRP, TNF- α, and IL-6 in the development of diabetes, we conducted a prospective case-control study nested within the Womens Health Initiative Observational Study. We followed 82 069 postmenopausal women (50-79 years of age) with no history of diabetes for incident diabetes for a mean follow-up of 5.5 years. We identified 1584 cases and matched them with 2198 controls with respect to age, ethnicity, clinical center, time of blood draw, and length of follow-up. We genotyped 13 haplotype-tagging single-nucleotide polymorphisms (tSNPs) across 2.3 kb of the CRP (C-reactive protein, pentraxin-related) gene, 16 tSNPs across 2.8 kb of the TNF (tumor necrosis factor) gene, and 14 tSNPs across 4.8 kb of the IL6 [interleukin 6 (interferon, beta 2)] gene. Plasma concentrations of TNF-α receptor 2 (TNF-α-R2) and IL-6 were measured. RESULTS After adjusting for matching factors, confounding variables, and multiple comparisons, we found 8 variants in the TNF gene to be associated with plasma TNF-α-R2 concentrations in white women (q < 0.05). After adjusting for multiple comparisons (q > 0.05), we found no association of any IL6 gene variant with plasma IL-6 concentration, nor did we find any significant associations between any SNPs among these 3 genes and diabetes risk (q > 0.05). CONCLUSIONS We found modest associations between TNF variants and circulating concentrations of TNF-α-R2. Common variants of the CRP, TNF, and IL6 genes were not significantly associated with risk of clinical diabetes in postmenopausal women.

Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data

Since most analysis software for genome‐wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even datasets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent‐of‐origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper, we reexamine the computational bottlenecks and implement ultra‐fast pedigree‐based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (six CPU cores at 2.67 GHz), analyzing a univariate HDL (high‐density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1,388 individuals in 124 pedigrees) takes less than 2 min and 1.5 GB of memory. Complete multivariate QTL analysis of the three time‐points of the longitudinal HDL multivariate trait takes less than 5 min and 1.5 GB of memory. The algorithm is implemented as the Ped‐GWAS Analysis (Option 29) in the Mendel statistical genetics package, which is freely available for Macintosh, Linux, and Windows platforms from http://genetics.ucla.edu/software/mendel.