A correction to: Bonnie R Joubert, Ethan M Lange, Nora Franceschini, Victor Mwapasa, Kari E North, Steven R Meshnick andthe NIAID Center for HIV/AIDS Vaccine Immunology. A whole genome association study of mother-to-child transmission of HIV in Malawi. Genome Medicine 2010, 2:17.
A multi-ethnic study demonstrates that the extrapolation of genetic disease risk models from European populations to other ethnicities is compromised more strongly by genetic structure than by environmental or global genetic background in differential genetic risk associations across ethnicities.
The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.
The number of known associations between human diseases and common genetic variants has grown dramatically in the past decade, most being identified in large-scale genetic studies of people of Western European origin. But because the frequencies of genetic variants can differ substantially between continental populations, it's important to assess how well these associations can be extended to populations with different continental ancestry. Are the correlations between genetic variants, disease endpoints, and risk factors consistent enough for genetic risk models to be reliably applied across different ancestries? Here we describe a systematic analysis of disease outcome and risk-factor–associated variants (tagSNPs) identified in European populations, in which we test whether the effect size of a tagSNP is consistent across six populations with significant non-European ancestry. We demonstrate that although nearly all such tagSNPs have effects in the same direction across all ancestries (i.e., variants associated with higher risk in Europeans will also be associated with higher risk in other populations), roughly a quarter of the variants tested have significantly different magnitude of effect (usually lower) in at least one non-European population. We therefore advise caution in the use of tagSNP-based genetic disease risk models in populations that have a different genetic ancestry from the population in which original associations were first made. We then show that this differential strength of association can be attributed to population-dependent variations in the correlation between tagSNPs and the variant that actually determines risk—the so-called functional variant. Risk models based on functional variants are therefore likely to be more robust than tagSNP-based models.
Genome-wide association studies of obesity measures have identified associations with single nucleotide polymorphisms (SNPs). However, no large-scale evaluation of gene-environment interactions has been performed. We conducted a search of gene-environment (G×E) interactions in post-menopausal African-American and Hispanic women from the Women’s Health Initiative SNP Health Association Resource GWAS study. Single SNP linear regression on body mass index (BMI) and waist-to-hip circumference ratio (WHR) adjusted for multidimensional-scaling-derived axes of ancestry and age was run in race-stratified data with 871,512 SNPs available from African-Americans (N=8,203) and 786,776 SNPs from Hispanics (N=3,484). Tests of G×E interaction at all SNPs for recreational physical activity (met-hrs/wk), dietary energy intake (kcal/day), alcohol intake (categorical), cigarette smoking years, and cigarette smoking (ever vs. never) were run in African-Americans and Hispanics adjusted for ancestry and age at interview, followed by meta-analysis of G×E interaction terms. The strongest evidence for concordant G×E interactions in African-Americans and Hispanics was for smoking and marker rs10133840 (Q statistic P=0.70, beta=−0.01, P=3.81×10−7) with BMI as the outcome. The strongest evidence for G×E interaction within a cohort was in African-Americans with WHR as outcome for dietary energy intake and rs9557704 (SNP×kcal =−0.04, P=2.17×10−7). No results exceeded the Bonferroni–corrected statistical significance threshold.
BMI; WHR; genetic epidemiology; disparity; obesity; GWAS
Diabetes has been associated with increased risk of breast cancer in a number of epidemiologic studies, but its effects on survival among women diagnosed with breast cancer have been examined less frequently. Importantly, prior investigations have rarely considered the influence of factors associated with diabetes such as obesity, age at diabetes diagnosis, duration of diabetes, or diabetes treatments.
We evaluated the effect of self-reported diabetes on breast cancer incidence and mortality in the Long Island Breast Cancer Study Project, which includes 1,447 breast cancer cases and 1,453 controls. Follow-up data for all-cause (n = 395) and 5-year breast cancer-specific mortality (n = 104) through December 2005 were determined for case women from the National Death Index. Adjusted logistic regression and Cox proportional hazards models were used to estimate odds ratios (OR) and hazards ratios (HR), respectively.
Postmenopausal women with diabetes were at increased risk of developing breast cancer [OR = 1.35; 95 % confidence interval (CI) = 0.99–1.85], as were those who were not of white race regardless of menopausal status [OR = 3.89; 95 % CI = 1.66–9.11]. Among case women, diabetes was associated with a modestly increased risk of death from all causes [HR = 1.65; 95 % CI = 1.18–2.29], an association that was stronger in women who were obese at breast cancer diagnosis [HR = 2.49; 94 % CI = 1.58–3.93]. In analyses restricted to diabetics, there was no statistically significant effect of duration of diabetes or type of treatment on breast cancer incidence or mortality.
Our findings suggest that diabetes may increase incidence of breast cancer in older women and non-whites, and mortality due to all causes.
Breast cancer; Diabetes; Survival
We evaluated whether the addition of carotid intima media thickness and plaque (CIMT-P), and, a single nucleotide polymorphism on chromosome 9p21 (9p21) together improve coronary heart disease (CHD) risk prediction in the ARIC study.
Ten year CHD risk was estimated using the ARIC coronary risk score (ACRS) alone and in combination with CIMT-P and 9p21 individually and together in White participants (n=9338). Area under the receiver operating characteristic curve (AUC), model calibration, net reclassification index (NRI), integrated discrimination index (IDI) and number of individuals reclassified were estimated.
The AUC of the ACRS, ACRS+9p21, ACRS+CIMT-P and ACRS+CIMT-P+9p21 models were 0.748, 0.751, 0.763 and 0.766 respectively. The percentage of individuals reclassified, model calibration, NRI and IDI improved when CIMT-P and 9p21 were added to the ACRS only model (see manuscript).
Addition of 9p21 allele information to CIMT-P minimally improves CHD risk prediction in whites in the ARIC study.
Carotid intima media thickness; Plaque; 9p21; Risk prediction; Coronary heart disease
Several genome-wide studies have identified loci associated with reproductive traits, such as ages of menarche and menopause, in women of European ancestry. In this study, we investigated the relevance of these loci in minority US Hispanic women. We utilized data from 3468 women who were genotyped as a part of the Women's Health Initiative SNP Health Association Resource. We replicated associations of eight loci (LRP18, LIN28B, CENPW, INHBA, TMEM38B, ZNF483, NFAT5 and OLFM2) with age at menarche, and of two loci (MCM8 and BRSK1/TMEM150B) with age at menopause. The MCM8 locus was also associated with early menopause risk. Three loci (CENPW, MCM8 and BRSK1/TMEM150B) were associated with the length of reproductive lifespan. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in minority US Hispanic women.
Chronic periodontitis (CP) is a common oral disease that confers substantial systemic inflammatory and microbial burden and is a major cause of tooth loss. Here, we present the results of a genome-wide association study of CP that was carried out in a cohort of 4504 European Americans (EA) participating in the Atherosclerosis Risk in Communities (ARIC) Study (mean age—62 years, moderate CP—43% and severe CP—17%). We detected no genome-wide significant association signals for CP; however, we found suggestive evidence of association (P < 5 × 10−6) for six loci, including NIN, NPY, WNT5A for severe CP and NCR2, EMR1, 10p15 for moderate CP. Three of these loci had concordant effect size and direction in an independent sample of 656 adult EA participants of the Health, Aging, and Body Composition (Health ABC) Study. Meta-analysis pooled estimates were severe CP (n = 958 versus health: n = 1909)—NPY, rs2521634 [G]: odds ratio [OR = 1.49 (95% confidence interval (CI = 1.28–1.73, P = 3.5 × 10−7))]; moderate CP (n = 2293)—NCR2, rs7762544 [G]: OR = 1.40 (95% CI = 1.24–1.59, P = 7.5 × 10−8), EMR1, rs3826782 [A]: OR = 2.01 (95% CI = 1.52–2.65, P = 8.2 × 10−7). Canonical pathway analysis indicated significant enrichment of nervous system signaling, cellular immune response and cytokine signaling pathways. A significant interaction of NUAK1 (rs11112872, interaction P = 2.9 × 10−9) with smoking in ARIC was not replicated in Health ABC, although estimates of heritable variance in severe CP explained by all single nucleotide polymorphisms increased from 18 to 52% with the inclusion of a genome-wide interaction term with smoking. These genome-wide association results provide information on multiple candidate regions and pathways for interrogation in future genetic studies of CP.
Background: Arsenic (III) methyltransferase (AS3MT) has been related to urine arsenic metabolites in association studies. Other genes might also play roles in arsenic metabolism and excretion.
Objective: We evaluated genetic determinants of urine arsenic metabolites in American Indian adults from the Strong Heart Study (SHS).
Methods: We evaluated heritability of urine arsenic metabolites [percent inorganic arsenic (%iAs), percent monomethylarsonate (%MMA), and percent dimethylarsinate (%DMA)] in 2,907 SHS participants with urine arsenic measurements and at least one relative within the cohort. We conducted a preliminary linkage analysis in a subset of 487 participants with available genotypes on approximately 400 short tandem repeat markers using a general pedigree variance component approach for localizing quantitative trait loci (QTL).
Results: The medians (interquartile ranges) for %iAs, %MMA, and %DMA were 7.7% (5.4–10.7%), 13.6% (10.5–17.1%), and 78.4% (72.5–83.1%), respectively. The estimated heritability was 53% for %iAs, 50% for %MMA, and 59% for %DMA. After adjustment for sex, age, smoking, body mass index, alcohol consumption, region, and total urine arsenic concentrations, LOD [logarithm (to the base of 10) of the odds] scores indicated suggestive evidence for genetic linkage with QTLs influencing urine arsenic metabolites on chromosomes 5 (LOD = 2.03 for %iAs), 9 (LOD = 2.05 for %iAs and 2.10 for %MMA), and 11 (LOD = 1.94 for %iAs). A peak for %DMA on chromosome 10 within 2 Mb of AS3MT had an LOD of 1.80.
Conclusions: This population-based family study in American Indian communities supports a genetic contribution to variation in the distribution of arsenic metabolites in urine and, potentially, the involvement of genes other than AS3MT.
American Indians; arsenic metabolism; arsenic species; determinants; heritability; linkage scan; Strong Heart Study
Genetic imputation has become standard practice in modern genetic studies. However, several important issues have not been adequately addressed including the utility of study-specific reference, performance in admixed populations, and quality for less common (minor allele frequency [MAF] 0.005–0.05) and rare (MAF < 0.005) variants. These issues only recently became addressable with genome-wide association studies (GWAS) follow-up studies using dense genotyping or sequencing in large samples of non-European individuals. In this work, we constructed a study-specific reference panel of 3,924 haplotypes using African Americans in the Women’s Health Initiative (WHI) genotyped on both the Metabochip and the Affymetrix 6.0 GWAS platform. We used this reference panel to impute into 6,459 WHI SNP Health Association Resource (SHARe) study subjects with only GWAS genotypes. Our analysis confirmed the imputation quality metric Rsq (estimated r2, specific to each SNP) as an effective post-imputation filter. We recommend different Rsq thresholds for different MAF categories such that the average (across SNPs) Rsq is above the desired dosage r2 (squared Pearson correlation between imputed and experimental genotypes).With a desired dosage r2 of 80%, 99.9% (97.5%, 83.6%, 52.0%, 20.5%) of SNPs with MAF > 0.05 (0.03–0.05, 0.01–0.03, 0.005–0.01, and 0.001–0.005) passed the post-imputation filter. The average dosage r2 for these SNPs is 94.7%, 92.1%, 89.0%, 83.1%, and 79.7%, respectively. These results suggest that for African Americans imputation of Metabochip SNPs from GWAS data, including low frequency SNPs with MAF 0.005–0.05, is feasible and worthwhile for power increase in downstream association analysis provided a sizable reference panel is available.
genotype imputation; Metabochip; internal reference; African Americans; rare variants
Genetic variants in intron 1 of the fat mass– and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI–associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646–kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3×10−6) had not been highlighted in previous studies. While rs56137030was correlated at r2>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.
Genetic variants within the fat mass– and obesity-associated (FTO) gene are associated with increased risk of obesity. To better understand which specific genetic variant(s) in this genetic region is associated with obesity risk, we attempt to genotype or impute all known genetic variants in the region and test for association with body mass index as a measurement of obesity in over 20,000 African Americans. We identified 29 potential candidate variants, of which one variant (rs1421085) is a particularly interesting candidate for future functional follow-up studies. Our example shows the powerful approach of studying a large African American population, substantially reducing the number of possible functional variants compared with European descent populations.
Although smoking behavior is known to affect body mass index (BMI), the potential for smoking to influence genetic associations with BMI is largely unexplored.
As part of the ‘Population Architecture using Genomics and Epidemiology (PAGE)’ Consortium, we investigated interaction between genetic risk factors associated with BMI and smoking for 10 single nucleotide polymorphisms (SNPs) previously identified in genome-wide association studies. We included 6 studies with a total of 56,466 subjects (16,750 African Americans (AA) and 39,716 European Americans (EA)). We assessed effect modification by testing an interaction term for each SNP and smoking (current vs. former/never) in the linear regression and by stratified analyses.
We did not observe strong evidence for interactions and only observed two interactions with p-values <0.1: for rs6548238/TMEM18, the risk allele (C) was associated with BMI only among AA females who were former/never smokers (β = 0.018, p = 0.002), vs. current smokers (β = 0.001, p = 0.95, pinteraction = 0.10). For rs9939609/FTO, the A allele was more strongly associated with BMI among current smoker EA females (β = 0.017, p = 3.5x10-5), vs. former/never smokers (β = 0.006, p = 0.05, pinteraction = 0.08).
These analyses provide limited evidence that smoking status may modify genetic effects of previously identified genetic risk factors for BMI. Larger studies are needed to follow up our results.
Clinical Trial Registration
Obesity; Body mass index; Genome-wide association study; Genetic risk factor; Smoking interactions; Genetic epidemiology
Age, family history, and body mass index (BMI) influence the prevalence of hypertension, but very little is known about the interplay of these factors in Chinese populations. The authors examined this issue in Chinese adults (n = 4104) in the People’s Republic of China Study. In young adults (24–39 years), the prevalence of hypertension/1000 persons (95% confidence interval [CI]) at the referent BMI was greater among subjects with a parental history of hypertension (35; 15–54) compared with those without (7; 3–11). Among middle-aged (40–71 years) adults, the prevalence of hypertension was similar regardless of parental history; however, the effect of BMI was modified by parental history status. For example, at BMI = 25 kg/m2, the prevalence difference/1000 persons was 375 (95% CI = 245–506) and 97 (95% CI = 51–144) among subjects with and without a parental history, respectively. These large differences call for further investigation of the genetic and environmental factors that could be driving this interaction.
Asian; blood pressure; body mass index; Chinese; family history
The independence assumption for a case-only analysis of statistical interaction, i. e. that genetic (G) and environmental exposures (E) are not associated in the source population, is often checked in surrogate populations. Few studies have examined G-E association in empirical data, particularly in controls from population-based studies, the type of controls expected to provide the most valid surrogate estimates of G-E association. We used controls from two population-based case-control studies to evaluate G-E independence for 43 selected genetic polymorphisms and smoking behavior. The odds ratio (ORz) was used to estimate G-E association and, therefore, the magnitude of bias introduced into the case-only odds ratio (COR). Odds ratios of moderate magnitude [mmORz], defined as ORz≤0.7 or ORz≥1.4, were found at least one of the six smoking measures (ever, former, current, cig/day, years smoked, pack-years) for 45% and 59% of the SNPs examined in the control groups of two independently conducted North Carolina studies, respectively. Consequently, case-only estimates of G-E interaction in the context of a multiplicative benchmark would be biased for these SNPs and smoking measures. MmORzs were found more often for smoking amount than smoking status. We recommend that a stand-alone case-only study should only be conducted when G-E independence can be verified for each polymorphism and exposure metric with population-specific data. Our results suggest that ORz is specific to each underlying population rather than an estimate of a ‘universal’ ORz for that SNP and smoking measure. Further, misspecification of smoking is likely to introduce bias into the COR.
Case-only; controls; gene-environment interaction; genetic polymorphisms; smoking
Single nucleotide polymorphisms (SNPs) in alcohol metabolism genes are associated with squamous cell carcinoma of the head and neck (SCCHN), and may influence cancer risk in conjunction with alcohol. Genetic variation in the oxidative stress pathway may impact the carcinogenic effect of reactive oxygen species produced by ethanol metabolism. We hypothesized that alcohol interacts with these pathways to affect SCCHN incidence.
Interview and genotyping data for 64 SNPs were obtained from 2552 European- and African-American subjects (1227 cases, 1325 controls) from the Carolina Head and Neck Cancer Epidemiology study, a population-based case-control study of SCCHN conducted in North Carolina from 2002–2006. We estimated odds ratios and 95% confidence intervals for SNPs and haplotypes, adjusting for age, sex, race, and duration of cigarette smoking. P-values were adjusted for multiple testing using Bonferroni correction.
Two SNPs were associated with SCCHN risk: ADH1B rs1229984 A allele (OR=0.7, 95%CI=0.6–0.9) and ALDH2 rs2238151 C allele (OR=1.2, 95%CI=1.1–1.4). Three were associated with sub-site tumors: ADH1B rs17028834 C allele (larynx, OR=1.5, 95%CI=1.1–2.0), SOD2 rs4342445 A allele (oral cavity, OR=1.3, 95%CI=1.1–1.6), and SOD2 rs5746134 T allele (hypopharynx, OR=2.1, 95%CI=1.2–3.7). Four SNPs in alcohol metabolism genes interacted additively with alcohol consumption: ALDH2 rs2238151, ADH1B rs1159918, ADH7 rs1154460, and CYP2E1 rs2249695. No alcohol interactions were found for oxidative stress SNPs.
Conclusions and Impact
Previously unreported associations of SNPs in ALDH2, CYP2E1, GPX2, SOD1, and SOD2 with SCCHN and sub-site tumors provide evidence that alterations in alcohol and oxidative stress pathways influence SCCHN carcinogenesis, and warrant further investigation.
Head and Neck Neoplasms; Head and Neck Neoplasms/epidemiology; Gene-environment interaction; Alcohol Drinking/metabolism; Oxidative Stress
Adiponectin is an adipose-secreted protein with influence on several physiologic pathways including those related to insulin sensitivity, inflammation, and atherogenesis. Adiponectin levels are highly heritable and several single nucleotide polymorphisms (SNPs) in adiponectin-related genes (ADIPOQ, ADIPOR1, ADIPOR2) have been examined in relation to circulating adiponectin levels and obesity phenotypes, but despite differences in adiponectin levels and obesity prevalence by race, few studies have included black participants. Using cross-sectional interview data and blood samples collected from 990 black and 977 white women enrolled in the Southern Community Cohort Study from 2002 to 2006, we examined 25 SNPs in ADIPOQ, 19 in ADIPOR1, and 27 in ADIPOR2 in relation to serum adiponectin levels and body mass index (BMI) using race-stratified linear regression models adjusted for age and percentage African ancestry. SNP rs17366568 in ADIPOQ was significantly associated with serum adiponectin levels in white women only (adjusted mean adiponectin levels = 15.9 for G/G genotype, 13.7 for A/G, and 9.3 for A/A, p=0.00036). No other SNPs were associated with adiponectin or BMI among blacks or whites. Because adiponectin levels as well as obesity are highly heritable and vary by race but associations with polymorphisms in the ADIPOQ, ADIPOR1, and ADIPOR2 genes have been few in this and other studies, future work including large populations from diverse racial groups is needed to detect additional genetic variants that influence adiponectin and BMI.
Adiponectin; obesity; genetics; African Americans
Polymorphisms in several distinct genomic regions, including the F7 gene, were recently associated with factor VII (FVII) levels in European Americans (EAs). The genetic determinants of FVII in African Americans (AAs) are unknown. We used a 50 000 single nucleotide polymorphism (SNP) gene-centric array having dense coverage of over 2 000 candidate genes for cardiovascular disease (CVD) pathways in a community-based sample of 16 324 EA and 3898 AA participants from the Candidate Gene Association Resource (CARe) consortium. Our aim was the discovery of new genomic loci and more detailed characterization of existing loci associated with FVII levels. In EAs, we identified three new loci associated with FVII, of which APOA5 on chromosome 11q23 and HNF4A on chromosome 20q12–13 were replicated in a sample of 4289 participants from the Whitehall II study. We confirmed four previously reported FVII-associated loci (GCKR, MS4A6A, F7 and PROCR) in CARe EA samples. In AAs, the F7 and PROCR regions were significantly associated with FVII. Several of the FVII-associated regions are known to be associated with lipids and other cardiovascular-related traits. At the F7 locus, there was evidence of at least five independently associated SNPs in EAs and three independent signals in AAs. Though the variance in FVII explained by the existing loci is substantial (20% in EA and 10% in AA), larger sample sizes and investigation of lower frequency variants may be required to identify additional FVII-associated loci in EAs and AAs and further clarify the relationship between FVII and other CVD risk factors.
Background and Aims
Epidemiologic studies have suggested beneficial effects of flavonoids on cardiovascular disease. Cocoa and particularly dark chocolate are rich in flavonoids and recent studies have demonstrated blood pressure lowering effects of dark chocolate. However, limited data are available on the association of chocolate consumption and the risk of coronary heart disease (CHD). We sought to examine the association between chocolate consumption and prevalent CHD.
We studied in a cross-sectional design 4,970 participants aged 25 to 93 years who participated in the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study. Chocolate intake was assessed through a semi-quantitative food frequency questionnaire. We used generalized estimating equations to estimate adjusted odds ratios.
Compared to subjects who did not report any chocolate intake, odds ratios (95% CI) for CHD were 1.01 (0.76-1.37), 0.74 (0.56-0.98), and 0.43 (0.28-0.67) for subjects consuming 1-3 times/month, 1-4 times/week, and 5+ times/week, respectively (p for trend <0.0001) adjusting for age, sex, family CHD risk group, energy intake, education, non-chocolate candy intake, linolenic acid intake, smoking, alcohol intake, exercise, and fruit and vegetables. Consumption of non-chocolate candy was associated with a 49% higher prevalence of CHD comparing 5+/week vs. 0/week [OR=1.49 (0.96-2.32)].
These data suggest that consumption of chocolate is inversely related with prevalent CHD in a general population.
epidemiology; carbohydrate; nutrition; cardiovascular disease
The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS.
RESEARCH DESIGN AND METHODS
Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected.
Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure.
Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.
Physical inactivity accentuates the association of variants in the FTO locus with obesity-related traits but evidence is largely lacking in non-European populations.
Here we tested the hypothesis that physical activity (PA) modifies the association of the FTO single-nucleotide polymorphism (SNP) rs9939609 on adiposity traits in 2,656 African Americans (AA) (1,626 women and 1,030 men) and 9,867 European Americans (EA) (5,286 women and 4,581 men) aged 45-66 years in the Atherosclerosis Risk in Communities (ARIC) study. Individuals in the lowest quintile of the sport activity index of the Baecke questionnaire were categorized as low PA. Baseline BMI, waist circumference (WC), and skinfold measures were dependent variables in regression models testing the additive effect of the SNP, low PA, and their interaction, adjusting for age, alcohol use, cigarette use, educational attainment, and percent European ancestry in AA adults, stratified by sex and race/ethnicity.
rs9939609 was associated with adiposity in all groups other than AA women. The SNPxPA interaction was significant in AA men (p≤0.002 for all traits) and EA men (p≤0.04 for all traits). For each additional copy of the A (risk) allele, WC in AA men was higher in those with low PA (βlowPA : 5.1 cm, 95% C.I. 2.6-7.5) than high PA (βhighPA: 0.7 cm, 95% C.I. −0.4 – 1.9); p (interaction) = 0.002). The interaction effect was not observed in EA or AA women.
FTO SNP x PA interactions on adiposity were observed for AA as well as EA men. Differences by sex require further examination.
Genetics; genotype; FTO; obesity; adiposity; BMI; physical activity; exercise; African-American; interaction; environment
Background and Aims
While a diet rich in anti-oxidant has been favorably associated with coronary disease and hypertension, limited data have evaluated the influence of such diet on subclinical disease. Thus, we sought to examine whether chocolate consumption is associated with calcified atherosclerotic plaque in the coronary arteries (CAC).
In a cross-sectional design, we studied 2,217 participants of the NHLBI Family Heart Study. Chocolate consumption was assessed by a semi-quantitative food-frequency questionnaire and CAC was measured by cardiac CT. We defined prevalent CAC using an Agatston score of at least 100 and fitted generalized estimating equations to calculate prevalence odds ratios of CAC.
There was an inverse association between frequency of chocolate consumption and prevalent CAC. Odds ratios (95% CI) for CAC were 1.0 (reference), 0.94 (0.66-1.35), 0.78 (0.53-1.13), and 0.68 (0.48-0.97) for chocolate consumption of 0, 1-3 times per month, once per week, and 2+ times per week, respectively (p for trend 0.022), adjusting for age, sex, energy intake, waist-hip ratio, education, smoking, alcohol consumption, ratio of total-to-HDL-cholesterol, non-chocolate candy, and diabetes mellitus. Controlling for additional confounders did not alter the findings. Exclusion of subjects with coronary heart disease or diabetes mellitus did not materially change the odds ratio estimates but did modestly decrease the overall significance (p = 0.07).
These data suggest that chocolate consumption might be inversely associated with prevalent CAC.
Chocolate; diet; epidemiology; coronary calcium; subclinical disease
Adiponectin is a promising biomarker linking obesity and disease risk; however, limited data are available regarding adiponectin in black women among whom obesity is highly prevalent.
A cross-sectional analysis was conducted to assess racial differences and correlates of serum adiponectin measured in 996 black and 996 white women enrolled in the Southern Community Cohort Study through Community Health Centers in twelve southeastern states from 2002–2006.
Blacks had significantly lower adiponectin levels than whites (median 10.9 versus 14.9 ug/ml, Wilcoxon p<0.0001). Among blacks, adiponectin was lower among overweight and obese women compared to healthy weight women but showed no clear decreasing trend with increasing severity of obesity; adjusted geometric means (95% confidence interval) were 15.0 (13.8–16.4), 11.5 (10.6–12.5), 9.7 (9.0–10.6), 11.4 (10.3–12.6), and 10.9 (9.5–12.6) ug/ml for body mass index [BMI] categories of 18.5–24.9, 25–29.9, 30–34.9, 35–39.9, and 40–45 (p for trend<0.0001). In contrast, among whites there was a monotonic reduction in adiponectin over increasing BMI (adjusted geometric means = 19.9 (18.3–21.7), 15.1 (13.9–16.4), 14.3 (13.2–15.5), 12.5 (11.2–13.9), and 11.0 (9.7–12.5) ug/ml, p for trend<0.0001). BMI, age, HDL-cholesterol, and hypertension were important correlates of adiponectin in both groups.
Among women, racial differences exist in both the magnitude and form of the adiponectin-BMI association.
Adiponectin; obesity; African Americans
Identification and characterization of the genetic variants underlying type 2 diabetes susceptibility can provide important understanding of the etiology and pathogenesis of type 2 diabetes. We previously identified strong evidence of linkage for type 2 diabetes on chromosome 22 among 3,383 Hypertension Genetic Epidemiology Network (HyperGEN) participants from 1,124 families. The checkpoint 2 (CHEK2) gene, an important mediator of cellular responses to DNA damage, is located 0.22 Mb from this linkage peak. In this study, we tested the hypothesis that the CHEK2 gene contains one or more polymorphic variants that are associated with type 2 diabetes in HyperGEN individuals. In addition, we replicated our findings in two other Family Blood Pressure Program (FBPP) populations and in the population-based Atherosclerosis Risk in Communities (ARIC) study. We genotyped 1,584 African-American and 1,531 white HyperGEN participants, 1,843 African-American and 1,569 white GENOA participants, 871 African-American and 1,009 white GenNet participants, and 4,266 African-American and 11,478 white ARIC participants for four single nucleotide polymorphisms (SNPs) in CHEK2. Using additive models, we evaluated the association of CHEK2 SNPs with type 2 diabetes in participants within each study population stratified by race, and in a meta-analysis, adjusting for age, age2, sex, sex-by-age interaction, study center, and relatedness. One CHEK2 variant, rs4035540, was associated with an increased risk of type 2 diabetes in HyperGEN participants, two replication samples, and in the meta-analysis. These results may suggest a new pathway in the pathogenesis of type 2 diabetes that involves pancreatic beta-cell damage and apoptosis.
CHEK2 gene; CHEK2 SNPs; Type 2 diabetes; Family Blood Pressure Program; Atherosclerosis Risk in Communities Study
When the case-only study design is used to estimate statistical interaction between genetic (G) and environmental (E) exposures, G and E must be independent in the underlying population, or the case-only estimate of interaction (COR) will be biased. Few studies have examined the occurrence of G-E association in published control group data.
To examine the assumption of G-E independence in empirical data, we conducted a systematic review and meta-analysis of G-E associations in controls for frequently investigated DNA repair genes (XRCC1 Arg399Gln, Arg194Trp, or Arg280His, XPD Lys751Gln, and Asp312Asn, and XRCC3 Thr241Met) and smoking (ever/never smoking, current/not current smoker, smoking duration, smoking intensity and pack-years).
Across the 55 included studies, SNP-smoking associations in controls (ORz) were not reliably at the null value of 1.0 for any SNP-smoking combinations. Two G-E combinations were too heterogeneous for summary estimates: XRCC1 399 and ever-never smoking (N=21), and XPD 751 and pack-years (N=12). ORz ranges for these combinations were: [ORz (95% confidence interval (CI)] 0.7 (0.4, 1.2) – 1.9 (1.2, 2.8) and 0.8 (0.5, 1.3) – 2.3 (0.8, 6.1), respectively). Estimates for studies considered homogeneous (Cochran’s Q p-value <0.10) varied 2- to 5-fold. No study characteristics were identified that could explain heterogeneity.
We recommend the independence assumption be evaluated in the population underlying any potential case-only study, rather than in a proxy control group(s) or pooled controls.
These results suggest that G-E association in controls may be population-specific. Increased access to control data would improve evaluation of the independence assumption.
case-only; gene-environment interaction; DNA repair genes; smoking; controls
To determine whether genetic variants associated with diabetes and obesity predict gestational weight gain.
960 participants in the Pregnancy, Infection and Nutrition cohorts were genotyped for 27 single-nucleotide polymorphisms (SNPs) associated with diabetes and obesity.
Among white and black women (n=960), KCNQ1 risk allele carriage was directly associated with weight gain (p < 0.01). In Bayesian hierarchical models among white women (N=628), we found posterior odds ratios > 3 for inclusion of TCF2 and THADA SNPs in our models. Among black women (n=332), we found associations between risk allele carriage and weight gain for the THADA and INSIG2 SNPs. In Bayesian variable selection models, we found an interaction between the TSPAN8 risk allele and pre-gravid obesity, with lower weight gain among obese risk allele carriers.
We found evidence that diabetes and obesity risk alleles interact with maternal pre-gravid BMI to predict gestational weight gain.
diabetes; gestational weight gain; genetics; obesity; single nucleotide polymorphisms
Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.
The metabolic syndrome represents a clustering of metabolic phenotypes (e.g. elevated blood pressure, cholesterol levels, and plasma glucose, as well as abdominal obesity) and is associated with an increased risk of atherosclerosis and type 2 diabetes. Although multiple genes influencing the specific metabolic syndrome components have been reported, few studies have evaluated the genetic underpinnings of the syndrome as a whole. Here, we describe an approach to evaluate multiple clustered traits, which allows us to test whether common genetic variants influence the co-occurrence of one or more metabolic phenotypes. By examining approximately 20,000 European American and 6,200 African American participants from five studies, we show that three regions on chromosomes 12, 19, and 20 are associated with multiple metabolic phenotypes. These genetic variants are highly intriguing candidates that may increase our understanding of the biologic basis of the clustering of metabolic phenotypes and help identify targets for early intervention.