Many GWAS have identified novel loci associated with common diseases, but have focused only on main effects of individual genetic variants rather than interactions with environmental factors (GxE). Identification of GxE interactions is particularly important for coronary heart disease (CHD), a major preventable source of morbidity and mortality with strong non-genetic risk factors. Atherosclerosis is the major cause of CHD, and coronary artery calcification (CAC) is directly correlated with quantity of coronary atherosclerotic plaque. In the current study, we tested for genetic variants influencing extent of CAC via interaction with smoking (GxS), by conducting a GxS discovery GWAS in Genetic Epidemiology Network of Arteriopathy (GENOA) sibships (N = 915 European Americans) followed by replication in Framingham Heart Study (FHS) sibships (N = 1025 European Americans). Generalized estimating equations accounted for the correlation within sibships in strata-specific groups of smokers and nonsmokers, as well as GxS interaction. Primary analysis found SNPs that showed suggestive associations (p≤10−5) in GENOA GWAS, but these index SNPs did not replicate in FHS. However, secondary analysis was able to replicate candidate gene regions in FHS using other SNPs (+/−250 kb of GENOA index SNP). In smoker and nonsmoker groups, replicated genes included TCF7L2 (p = 6.0×10−5) and WWOX (p = 4.5×10−6); and TNFRSF8 (p = 7.8×10−5), respectively. For GxS interactions, replicated genes included TBC1D4 (p = 6.9×10−5) and ADAMTS9 (P = 7.1×10−5). Interestingly, these genes are involved in inflammatory pathways mediated by the NF-κB axis. Since smoking is known to induce chronic and systemic inflammation, association of these genes likely reflects roles in CAC development via inflammatory pathways. Furthermore, the NF-κB axis regulates bone remodeling, a key physiological process in CAC development. In conclusion, GxS GWAS has yielded evidence for novel loci that are associated with CAC via interaction with smoking, providing promising new targets for future population-based and functional studies of CAC development.
A more thorough understanding of the differences in DNA methylation (DNAm) profiles in populations may hold promise for identifying molecular mechanisms through which genetic and environmental factors jointly contribute to human diseases. Inflammation is a key molecular mechanism underlying several chronic diseases including cardiovascular disease, and it affects DNAm profile on both global and locus-specific levels. To understand the impact of inflammation on the DNAm of the human genome, we investigated DNAm profiles of peripheral blood leukocytes from 966 African American participants in the Genetic Epidemiology Network of Arteriopathy (GENOA) study. By testing the association of DNAm sites on CpG islands of over 14,000 genes with C-reactive protein (CRP), an inflammatory biomarker of cardiovascular disease, we identified 257 DNAm sites in 240 genes significantly associated with serum levels of CRP adjusted for age, sex, body mass index and smoking status, and corrected for multiple testing. Of the significantly associated DNAm sites, 80.5% were hypomethylated with higher CRP levels. The most significant Gene Ontology terms enriched in the genes associated with the CRP levels were immune system process, immune response, defense response, response to stimulus, and response to stress, which are all linked to the functions of leukocytes. While the CRP-associated DNAm may be cell-type specific, understanding the DNAm association with CRP in peripheral blood leukocytes of multi-ethnic populations can assist in unveiling the molecular mechanism of how the process of inflammation affects the risks of developing common disease through epigenetic modifications.
Obesity is a highly heritable trait and a growing public health problem. African Americans are a genetically diverse, yet understudied population with a high prevalence of obesity (body mass index (BMI) greater than 30 kg/m2). Recent studies based upon single nucleotide polymorphisms (SNPs) have identified genetic markers associated with obesity. However, a large proportion of the heritability of obesity remains unexplained. Copy number variation (CNV) has been cited as a possible source of missing heritability in common diseases such as obesity. We conducted a CNV genome-wide association study of BMI in two African American cohorts from GENOA and HyperGEN. We performed independent and identical association analyses in each study, then combined the results in a meta-analysis. We identified three CNVs associated with BMI, obesity, and other obesity-related traits after adjusting for multiple testing. These CNVs overlap the PARK2, GYPA and SGCZ genes. Our results suggest that CNV may play a role in the etiology of obesity in African Americans.
Obesity; CNVs; Meta-analysis; BMI; African Americans
Background and method
We investigated whether chronic kidney disease detected by increased serum creatinine (SCr) or urine albumin-to-creatinine ratio (UACR) may reflect arteriosclerosis involving the kidneys. The sample consisted of 1585 members of sibships (804 non-Hispanic whites and 781 non-Hispanic blacks) in which at least two siblings had primary hypertension. We first evaluated the correlations of increased SCr and UACR with the presence of cerebral small vessel arteriosclerosis, which was determined by increased subcortical white matter hyperintensity (WMH) volume on brain magnetic resonance imaging; and with peripheral large vessel arteriosclerosis, which was determined by decreased ankle-brachial index (ABI). After age adjustment, increased SCr and UACR correlated with increased WMH volume (0.54 and 0.52, respectively) and with decreased ABI (0.50 and 0.54, respectively; all P < 0.001). We then used logistic regression to evaluate the dependency of each measure of disease on conventional risk factors for arteriosclerosis to assess whether the risk factors’ effects were proportional across different measures of disease.
Age, race, sex, hypertension, diabetes, total cholesterol, and smoking made similar overall contributions to the prediction of each measure of disease, as judged by the model C-statistics, which varied in a narrow range from 0.84 to 0.85 (all P < 0.001). However, the relative contributions that the modifiable risk factors, including hypertension, diabetes, total cholesterol, and smoking made to prediction of increased SCr and UACR were disproportionate to their relative contributions to prediction of decreased ABI (P < 0.0001).
The findings support the view that chronic kidney disease detected by increased SCr or UACR primarily reflects small vessel arteriosclerosis involving the kidneys.
albuminuria; ankle-brachial blood pressure index; arteriosclerosis; blood pressure; glomerular filtration rate; hypertension; subcortical white matter hyperintensity
Coronary artery calcification (CAC) detected by computed tomography is a non-invasive measure of coronary atherosclerosis, that underlies most cases of myocardial infarction (MI). We aimed to identify common genetic variants associated with CAC and further investigate their associations with MI.
Methods and Results
Computed tomography was used to assess quantity of CAC. A meta-analysis of genome-wide association studies for CAC was carried out in 9,961 men and women from five independent community-based cohorts, with replication in three additional independent cohorts (n=6,032). We examined the top single nucleotide polymorphisms (SNPs) associated with CAC quantity for association with MI in multiple large genome-wide association studies of MI. Genome-wide significant associations with CAC for SNPs on chromosome 9p21 near CDKN2A and CDKN2B (top SNP: rs1333049, P=7.58×10−19) and 6p24 (top SNP: rs9349379, within the PHACTR1 gene, P=2.65×10−11) replicated for CAC and for MI. Additionally, there is evidence for concordance of SNP associations with both CAC and with MI at a number of other loci, including 3q22 (MRAS gene), 13q34 (COL4A1/COL4A2 genes), and 1p13 (SORT1 gene).
SNPs in the 9p21 and PHACTR1 gene loci were strongly associated with CAC and MI, and there are suggestive associations with both CAC and MI of SNPs in additional loci. Multiple genetic loci are associated with development of both underlying coronary atherosclerosis and clinical events.
cardiac computed tomography; coronary artery calcification; coronary atherosclerosis; genome-wide association studies; myocardial infarction
Estimated glomerular filtration rate (eGFR) is a powerful predictor of mortality in diabetic patients with limited proteinuria data. In this study, we tested whether concomitant proteinuria increases the risk of mortality among patients with type 2 diabetes.
Participants included 6523 patients > 30 years with type 2 diabetes who were enrolled in a management program of a medical center before 2007. Renal function was assessed by eGFR according to the Modification of Diet in Renal Disease Study equation for Chinese. Proteinuria was assessed by urine dipstick.
A total of 573 patients (8.8%) died over a median follow-up time of 4.91 years (ranging from 0.01 year to 6.42 years). The adjusted expanded cardiovascular disease (CVD)-related mortality rates among patients with proteinuria were more than three folds higher for those with an eGFR of 60 mL/min/1.73 m2 or less compared with those with an eGFR of 90 mL/min/1.73 m2 or greater [hazard ratio, HR, 3.15 (95% confidence interval, CI, 2.0–5.1)]. The magnitude of adjusted HR was smaller in patients without proteinuria [1.98 (95% CI, 1.1–3.7)]. An eGFR of 60 mL/min/1.73 m2 to 89 mL/min/1.73 m2 significantly affected all-cause mortality and mortality from expanded CVD-related causes only in patients with proteinuria. Similarly, proteinuria affected all outcomes only in patients with an eGFR of <60 mL/min/1.73 m2.
The risks of all-cause mortality, as well as expanded and non-expanded mortality from CVD-related causes associated with proteinuria or an eGFR of 90 mL/min/1.73 m2 or greater are independently increased. Therefore, the use of proteinuria measurements with eGFR increases the precision of risk stratification for mortality.
Renal function; Mortality; Type 2 diabetes
Our goal was to evaluate the influence of quality control (QC) decisions using two genotype calling algorithms, CRLMM and Birdseed, designed for the Affymetrix SNP Array 6.0.
Various QC options were tried using the two algorithms and comparisons were made on subject and call rate and on association results using two data sets.
For Birdseed, we recommend using the contrast QC instead of QC call rate for sample QC. For CRLMM, we recommend using the signal-to-noise rate ≥4 for sample QC and a posterior probability of 90% for genotype accuracy. For both algorithms, we recommend calling the genotype separately for each plate, and dropping SNPs with a lower call rate (<95%) before evaluating samples with lower call rates. To investigate whether the genotype calls from the two algorithms impacted the genome-wide association results, we performed association analysis using data from the GENOA cohort; we observed that the number of significant SNPs were similar using either CRLMM or Birdseed.
Using our suggested workflow both algorithms performed similarly; however, fewer samples were removed and CRLMM took half the time to run our 854 study samples (4.2 h) compared to Birdseed (8.4 h).
Genotype call; Birdseed; CRLMM; Quality control decisions; Association
To determine the relationship between genetic polymorphisms and environmental factors (skin color) on blood pressure among African American women.
A descriptive study, consisting of 137 African American women from a Midwestern, metropolitan area was conducted. Blood pressure was measured using a digital blood pressure monitor. Self-reporting methods were utilized to obtain information on skin color. Buccal swab saliva samples were obtained for genotyping.
Of the four single nucleotide polymorphisms (SNPs) on the sodium bicarbonate co-transporter gene (SLC4A5) examined in this study, only one SNP (rs10177833) and skin color interaction was found to be associated with systolic blood pressure. The additive effect of rs10177833 on systolic blood pressure is statistically different between women with dark skin color and women with medium skin color (P=.0153). No SNP and skin color interaction was found to be associated with blood pressure readings in other SNPs tested (rs8179526, rs6726450 and rs6731545).
These findings of genetic and skin color relatedness to blood pressure is important when considering appropriate diagnostic and treatment plans for African American women with hypertension. African American women with darker skin color may require further assessment for risk factors such as discrimination related stress when being seen by health professionals for hypertension. (Ethn Dis. 2012;22(2):155-161)
Blood Pressure; Genetic; African American; Skin Color
Admixture mapping based on recently admixed populations is a powerful method to detect disease variants with substantial allele frequency differences in ancestral populations. We performed admixture mapping analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP), followed by trait-marker association analysis, in 6303 unrelated African-American participants of the Candidate Gene Association Resource (CARe) consortium. We identified five genomic regions (P< 0.001) harboring genetic variants contributing to inter-individual BP variation. In follow-up association analyses, correcting for all tests performed in this study, three loci were significantly associated with SBP and one significantly associated with DBP (P< 10−5). Further analyses suggested that six independent single-nucleotide polymorphisms (SNPs) contributed to the phenotypic variation observed in the admixture mapping analysis. These six SNPs were examined for replication in multiple, large, independent studies of African-Americans [Women's Health Initiative (WHI), Maywood, Genetic Epidemiology Network of Arteriopathy (GENOA) and Howard University Family Study (HUFS)] as well as one native African sample (Nigerian study), with a total replication sample size of 11 882. Meta-analysis of the replication set identified a novel variant (rs7726475) on chromosome 5 between the SUB1 and NPR3 genes, as being associated with SBP and DBP (P< 0.0015 for both); in meta-analyses combining the CARe samples with the replication data, we observed P-values of 4.45 × 10−7 for SBP and 7.52 × 10−7 for DBP for rs7726475 that were significant after accounting for all the tests performed. Our study highlights that admixture mapping analysis can help identify genetic variants missed by genome-wide association studies because of drastically reduced number of tests in the whole genome.
Obesity and genetic variation in aromatase and type 1 17-β hydroxysteroid dehydrogenase (HSD) could influence the E2 trajectory of decline during the menopause transition.
Design and participants
E2 trajectories during the menopause transition (phenotype) were identified using 5934 data points acquired annually from 681 women in Study of Women’s Health across the Nation (SWAN), a multiethnic study of the mid-life. E2 trajectories were related to CYP19 and type I 17-βHSD single-nucleotide polymorphisms (SNPs) and obesity.
logE2 trajectories began to decline precipitously 2 years before the final menstrual period (FMP). The trajectory of the logE2 decline varied with genotypes and obesity. logE2 rates of decline were greater in nonobese women than in obese women, P < 0.05. Women with the CYP19rs936306 CT variant had logE2 rate of decline that was 54% as rapid as the rate of decline of women with the TT variant, P < 0.05. logE2 rate of decline in women with the CYP19rs749292 GG variant was two-thirds the rate of logE2 decline in women with the AG variant, P < 0.05. logRates of E2 decline with 17-βHSD SNPs (rs2830, rs592389, and rs615942) varied according to genotype within obesity groups. Within each obesity group, logE2 rate of decline was greater in heterozygous variants and much less in homozygotes (P < 0.05). Obese women with selected CYP19 and 17-β HSD gene variants had remarkably different E2 trajectories around the FMP, resulting in different postmenopausal E2 levels. The rate of the E2 decline and the subsequent postmenopausal E2 levels may be relevant to oestrogen-sensitive chronic diseases including cancers.
Objectives. SLC2A9 gene variants associate with serum uric acid in white populations, but little is known about African American populations. Since SLC2A9 is a transporter, gene variants may be expected to associate more closely with the fractional excretion of urate, a measure of renal tubular transport, than with serum uric acid, which is influenced by production and extrarenal clearance.
Methods. Genotypes of single nucleotide polymorphisms (SNPs) distributed across the SLC2A9 gene were obtained in the Genetic Epidemiology Network of Arteriopathy cohorts. The associations of SNPs with serum uric acid, fractional excretion of urate and urine urate-to-creatinine ratio were assessed with adjustments for age, sex, diuretic use, BMI, homocysteine and triglycerides.
Results. We identified SLC2A9 gene variants that were associated with serum uric acid in 1155 African American subjects (53 SNPs) and 1132 white subjects (63 SNPs). The most statistically significant SNPs in African American subjects (rs13113918) and white subjects (rs11723439) were in the latter half of the gene and explained 2.7 and 2.8% of the variation in serum uric acid, respectively. After adjustment for this SNP in African Americans, 0.9% of the variation in serum uric acid was explained by an SNP (rs1568318) in the first half of the gene. Unexpectedly, SLC2A9 gene variants had stronger associations with serum uric acid than with fractional excretion of urate.
Conclusions. These findings support two different loci by which SLC2A9 variants affect uric acid levels in African Americans and suggest SLC2A9 variants affect serum uric acid level via renal and extrarenal clearance.
Uric acid; Fractional excretion of urate; SLC2A9; Race; Genetic epidemiology
Left ventricular (LV) mass and related phenotypes are heritable, important predictors of cardiovascular disease, particularly in hypertensive individuals.
Identify genetic predictors of echocardiographic phenotypes in hypertensive families.
Methods & Results
A multi-stage genome-wide association study (GWAS) was conducted in hypertensive-ascertained African American families (HyperGEN, Stage I; GENOA, Stage II); findings were replicated in HyperGEN Caucasian families (Stage III). Echocardiograms were collected using a common protocol, and participants were genotyped with the Affymetrix Genome-Wide Human SNP 6.0 Array. In Stages I and II, 1258 and 989 African Americans, and Stage III 1316 Caucasians, were analyzed using mixed models adjusted for ancestry. Phenotypes included LV mass, LV internal dimension (LVID), wall thicknesses (posterior (PWT) and intraventricular septum (IVST)), and relative wall thickness (RWT). In Stage I, 5 single nucleotide polymorphisms (SNP) had P≤10−6. In Stage II, one SNP (rs1436109; NCAM1 intron 1) replicated with the same phenotype (PWT, P=0.025) in addition to RWT (P=0.032). In Stage III, rs1436109 was associated with RWT (P=5.47×10−4) and LVID (P=1.86×10−4). Fisher’s combined P-value for all stages was RWT=3.80×10−9, PWT=3.12×10−7, IVST=8.69×10−7, LV mass=2.52×10−3, and LVID=4.80×10−4.
This GWAS conducted in hypertensive families identified a variant in NCAM1 associated with LV wall thickness and RWT. NCAM is upregulated during the remodeling period of hypertrophy to heart failure in Dahl salt-sensitive rats. Our initial screening in hypertensive African-Americans may have provided the context for this novel locus.
GWAS; NCAM1; hypertrophy; genomics
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.
The Vitamin D endocrine system is essential for calcium homeostasis, and low levels of vitamin D metabolites have been associated with cardiovascular disease risk. We hypothesized that DNA sequence variation in genes regulating vitamin D metabolism and signaling pathways might influence variation in coronary artery calcification (CAC).
Methods and Results
We genotyped single nucleotide polymorphisms (SNPs) in GC, CYP27B1, CYP24A1, and VDR and tested their association with CAC quantity, as measured by electron beam computed tomography. Initial association studies were carried out in a discovery sample comprised of 697 Amish subjects and SNPs nominally associated with CAC quantity (4 SNPs in CYP24A1, P = 0.008-0.00003) were then tested for association with CAC quantity in two independent cohorts of subjects of European Caucasian ancestry (Genetic Epidemiology Network of Arteriopathy (GENOA) Study (n = 916) and The Penn Coronary Artery Calcification (PennCAC) sample (n = 2,061)). One of the four SNPs, rs2762939, was associated with CAC quantity in both GENOA (P = 0.007) and PennCAC (P = 0.01). In all three populations the rs2762939 C allele was associated with lower CAC quantity. Meta-analysis for the association of this SNP with CAC quantity across all three studies yielded a P value of 2.9 × 10-6.
A common SNP in the CYP24A1 gene was associated with CAC quantity in three independent populations. This result suggests a role for vitamin D metabolism in the development of CAC quantity.
Using the exome sequencing data from 697 unrelated individuals and their simulated disease phenotypes from Genetic Analysis Workshop 17, we develop and apply a gene-based method to identify the relationship between a gene with multiple rare genetic variants and a phenotype. The method is based on the Mantel test, which assesses the correlation between two distance matrices using a permutation procedure. Using up to 100,000 permutations to estimate the statistical significance in 200 replicate data sets, we found that the method had 5.1% type I error at an α level of 0.05 and had various power to detect genes with simulated genetic associations. FLT1 and KDR had the most significant correlations with Q1 and were replicated 170 and 24 times, respectively, in 200 simulated data sets using a Bonferroni corrected p-value of 0.05 as a threshold. These results suggest that the distance correlation method can be used to identify genotype-phenotype association when multiple rare genetic variants in a gene are involved.
Epistasis (i.e. gene–gene interaction) has long been recognized as an important mechanism underlying the complexity of the genetic architecture of human traits. Definitions of epistasis range from the purely molecular to the traditional statistical measures of interaction. The statistical detection of epistasis usually does not map onto or easily relate to the biological interactions between genetic variations through their combined influence on gene expression or through their interactions at the gene product (i.e. protein) or DNA level. Recently, greater high-dimensional data on protein–protein interaction (PPI) and gene expression profiles have been collected that enumerates sets of biological interactions. To better align statistical and molecular models of epistasis, we present an example of how to incorporate the PPI information into the statistical analysis of interactions between copy number variations (CNVs). Among the 23 640 pairs of known human PPIs and the 1141 common CNVs detected among HapMap samples, we identified 37 pairs of CNVs overlapping with both genes of a PPI pair. Two CNV pairs provided sufficient genotype variation to search for epistatic effects on gene expression. Using 47 294 probe-specific gene expression levels as the outcomes, five epistatic effects were identified with P-value less than 10−6. We found a CNV–CNV interaction significantly associated with gene expression of TP53TG3 (P-value of 2 × 10−20). The proteins associated with the CNV pair also bind TP53 which regulates the transcription of TP53TG3. This study demonstrates that using PPI data can assist in targeting statistical hypothesis testing to biological plausible epistatic interaction that reflects molecular mechanisms.
The aim of this study was to evaluate the effect of MetS on arterial stiffness in a longitudinal study.
Brachial-ankle pulse wave velocity (baPWV), a measurement interpreted as arterial stiffness, was measured in 1518 community-dwelling persons at baseline and re-examined within a mean follow-up period of 3 years. Multivariate linear regression with generalized estimating equations (GEE) were used to examine the longitudinal relationship between MetS and its individual components and baPWV, while multivariate logistic regression with GEE was used to examine the longitudinal relationship between MetS and its individual components and the high risk group with arterial stiffness.
Subjects with MetS showed significantly greater baPWV at the end point than those without MetS, after adjusting for age, gender, education, hypertension medication and mean arterial pressure (MAP). MetS was associated with the top quartile of baPWV (the high-risk group of arterial stiffness, adjusted odds ratio [95% confidence interval] 1.52 [1.21-1.90]), and a significant linear trend of risk for the number of components of MetS was found (p for trend < 0.05). In further considering the individual MetS component, elevated blood pressure and fasting glucose significantly predicted a high risk of arterial stiffness (adjusted OR [95% CI] 3.72 [2.81-4.93] and 1.35 [1.08-1.68], respectively).
MetS affects the subject's progression to arterial stiffness. Arterial stiffness increased as the number of MetS components increased. Management of MetS is important for preventing the progression to advanced arterial stiffness.
metabolic syndrome; pulse wave velocity; arterial stiffness
Chronic kidney disease (CKD) is an increasing global public health concern, particularly among populations of African ancestry. We performed an interrogation of known renal loci, genome-wide association (GWA), and IBC candidate-gene SNP association analyses in African Americans from the CARe Renal Consortium. In up to 8,110 participants, we performed meta-analyses of GWA and IBC array data for estimated glomerular filtration rate (eGFR), CKD (eGFR <60 mL/min/1.73 m2), urinary albumin-to-creatinine ratio (UACR), and microalbuminuria (UACR >30 mg/g) and interrogated the 250 kb flanking region around 24 SNPs previously identified in European Ancestry renal GWAS analyses. Findings were replicated in up to 4,358 African Americans. To assess function, individually identified genes were knocked down in zebrafish embryos by morpholino antisense oligonucleotides. Expression of kidney-specific genes was assessed by in situ hybridization, and glomerular filtration was evaluated by dextran clearance. Overall, 23 of 24 previously identified SNPs had direction-consistent associations with eGFR in African Americans, 2 of which achieved nominal significance (UMOD, PIP5K1B). Interrogation of the flanking regions uncovered 24 new index SNPs in African Americans, 12 of which were replicated (UMOD, ANXA9, GCKR, TFDP2, DAB2, VEGFA, ATXN2, GATM, SLC22A2, TMEM60, SLC6A13, and BCAS3). In addition, we identified 3 suggestive loci at DOK6 (p-value = 5.3×10−7) and FNDC1 (p-value = 3.0×10−7) for UACR, and KCNQ1 with eGFR (p = 3.6×10−6). Morpholino knockdown of kcnq1 in the zebrafish resulted in abnormal kidney development and filtration capacity. We identified several SNPs in association with eGFR in African Ancestry individuals, as well as 3 suggestive loci for UACR and eGFR. Functional genetic studies support a role for kcnq1 in glomerular development in zebrafish.
Chronic kidney disease (CKD) is an increasing global public health problem and disproportionately affects populations of African ancestry. Many studies have shown that genetic variants are associated with the development of CKD; however, similar studies are lacking in African ancestry populations. The CARe consortium consists of more than 8,000 individuals of African ancestry; genome-wide association analysis for renal-related phenotypes was conducted. In cross-ethnicity analyses, we found that 23 of 24 previously identified SNPs in European ancestry populations have the same effect direction in our samples of African ancestry. We also identified 3 suggestive genetic variants associated with measurement of kidney function. We then tested these genes in zebrafish knockdown models and demonstrated that kcnq1 is involved in kidney development in zebrafish. These results highlight the similarity of genetic variants across ethnicities and show that cross-species modeling in zebrafish is feasible for genes associated with chronic human disease.
Epidemiological studies of DNA methylation (DNAm) profiles may hold substantial promise for identifying mechanisms through which genetic and environmental factors jointly contribute to disease risk. Different cell types are likely to have different DNAm patterns. We investigate the DNAm differences between two types of biospecimens available in many genetic epidemiology studies. We compared DNAm patterns in two different DNA samples from each of 34 participants in the Genetic Epidemiology Network of Arteriopathy study (20 Caucasians and 14 African-Americans). One was extracted from peripheral blood cells (PBC) and the other from transformed B-lymphocytes (TBL). The genome-wide DNAm profiles were compared at over 27,000 genome-wide methylation sites. We found that 26 out of the 34 participants had correlation coefficients higher than 0.9 between methylation profiles of PBC and TBL. Although a high correlation was observed in the DNAm profile between PBC and TBL, we also observed variation across samples from different DNA resources and donors. Using principal component analysis of the DNAm profiles, the two sources of the DNA samples could be accurately predicted. We also identified 3,723 autosomal DNAm sites that had significantly different methylation statuses in PBC compared to TBL (Bonferroni corrected p value <0.05). Both PBC and TBL provide a rich resource for understanding the DNAm profiles in humans participating in epidemiologic studies. While the majority of DNAm findings in PBC and TBL may be consistent, caution must be used when interpreting results because of the possibility of cell type-specific methylation modification.
Copy number data are routinely being extracted from genome-wide association study chips using a variety of software. We empirically evaluated and compared four freely-available software packages designed for Affymetrix SNP chips to estimate copy number: Affymetrix Power Tools (APT), Aroma.Affymetrix, PennCNV and CRLMM. Our evaluation used 1,418 GENOA samples that were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0. We compared bias and variance in the locus-level copy number data, the concordance amongst regions of copy number gains/deletions and the false-positive rate amongst deleted segments.
APT had median locus-level copy numbers closest to a value of two, whereas PennCNV and Aroma.Affymetrix had the smallest variability associated with the median copy number. Of those evaluated, only PennCNV provides copy number specific quality-control metrics and identified 136 poor CNV samples. Regions of copy number variation (CNV) were detected using the hidden Markov models provided within PennCNV and CRLMM/VanillaIce. PennCNV detected more CNVs than CRLMM/VanillaIce; the median number of CNVs detected per sample was 39 and 30, respectively. PennCNV detected most of the regions that CRLMM/VanillaIce did as well as additional CNV regions. The median concordance between PennCNV and CRLMM/VanillaIce was 47.9% for duplications and 51.5% for deletions. The estimated false-positive rate associated with deletions was similar for PennCNV and CRLMM/VanillaIce.
If the objective is to perform statistical tests on the locus-level copy number data, our empirical results suggest that PennCNV or Aroma.Affymetrix is optimal. If the objective is to perform statistical tests on the summarized segmented data then PennCNV would be preferred over CRLMM/VanillaIce. Specifically, PennCNV allows the analyst to estimate locus-level copy number, perform segmentation and evaluate CNV-specific quality-control metrics within a single software package. PennCNV has relatively small bias, small variability and detects more regions while maintaining a similar estimated false-positive rate as CRLMM/VanillaIce. More generally, we advocate that software developers need to provide guidance with respect to evaluating and choosing optimal settings in order to obtain optimal results for an individual dataset. Until such guidance exists, we recommend trying multiple algorithms, evaluating concordance/discordance and subsequently consider the union of regions for downstream association tests.
The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10−8) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10−8). The top IBC association for SBP was rs2012318 (P= 6.4 × 10−6) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10−6) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.
BMI represents an internal metabolic and physiological environment that plays a key role in development of high blood pressure (BP) for many Americans. African–American women have a higher prevalence of high BP and being overweight than men or other ethnic groups. This study examines the genetic–environmental interaction effects of single nucleotide polymorphisms and BMI on BP among African–American women using 1418 African–American women and men from the Genetic Epidemiology Network of Arteriopathy study. A total of 403 tests of single nucleotide polymorphism–BMI interaction were conducted using methods of internal replication, cross-validation, and false discovery rate. One single nucleotide polymorphism (located in the ATP6B1 gene, rs2266917) passed adjustments for multiple testing and had a significant independent main effect (P = 0.0018) on diastolic BP among African–American women. A significant sex-specific interaction effect was found between MMP3_rs679620 and BMI in African–American women (P = 0.0009). MMP3_rs679620 (A–G polymorphism) encodes a Lys-Glu nonsynonymous variant at the 45th amino acid of metallopeptidase 3 and indicates a putative functional modification of metallopeptidase 3. These findings were not identified in African–American men. MMP3_rs679620 appears to have a protective effect on diastolic BP in women with high BMI. Surprisingly, MMP3_rs679620 had the opposite effect on women with low BMI, resulting in higher diastolic BP.
African–American; blood pressure; BMI; MMP3_rs679620; women
African American women have the highest prevalence of hypertension and obesity of any group in the United States. African American girls have the highest incidence of obesity of any groups of children in the nation, and diagnoses of hypertension have been rising among this group. Because both genetic heredity and body mass index (BMI) are important risk factors for hypertension, this study examined the gene-BMI interaction for hypertension across the lifespan in two generations of African American women. Participants comprised of 868 African American women in the parent cohort and 322 in the offspring cohort from the Hypertension Genetic Epidemiology Network (HyperGEN) study, part of the Family Blood Pressure Program (FBPP). A total of 115 single-nucleotide polymorphisms (SNPs) were evaluated among the parent cohort and 491 among the offspring cohort for tests of SNP-BMI interaction using methods of false discovery rate (FDR; <.20) and examination of minor allele frequency (MAF; >.05) and Hardy-Weinberg equilibrium (>.10). One SNP (located in the CAPN 13 gene, rs1879282) passed adjustments for the multiple testing mentioned above and had a significant (p < .01) gene-BMI interaction on both systolic blood pressure (SBP) and diastolic blood pressure (DBP) among African American female offspring. The rs1879282 SNP is located on chromosome 2 on the calpain (CAPN) 13 gene, which is part of a family of cytosolic calcium-activated proteases involved in apoptosis, cell division, modulation of integrin–cytoskeletal interactions, and synaptic plasticity. This SNP was not available for testing in the African American parent cohort.
blood pressure; body mass index; genetic; women; African American
Left ventricular mass (LVM) is a strong, independent predictor of heart disease incidence and mortality. LVM is a complex, quantitative trait with genetic and environmental risk factors. This research characterizes the genetic architecture of LVM in an African-American population by examining the main and interactive effects of individual candidate gene single nucleotide polymorphisms (SNPs) and conventional risk factors for increased LVM.
We used least-squares linear regression to investigate 1,878 SNPs from 234 candidate genes for SNP main effects, SNP-risk factor interactions, or SNP-SNP interactions associated with LVM in 1,328 African-Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We reduced the probability of false positive results by implementing three analytic criteria: 1) the false discovery rate, 2) cross-validation, and 3) testing for internal replication of results.
We identified 409 SNP-SNP interactions passing all three criteria, while no SNP main effects or SNP-risk factor interactions passed all three. A multivariable model including four SNP-SNP interactions explained 11.3% of the variation in LVM in the full GENOA sample and 5.6% of LVM variation in independent test sets.
The results of this research underscore that context dependent effects, specifically SNP-SNP interactions, may dominate genetic contributions to variation in complex traits such as LVM.
Previous studies indicate that the endothelin system is involved in hypertension, heart failure, atherosclerosis, chronic kidney disease, and diabetes. To explore the potential genetic effects of copy number variations (CNV) on the endothelin system which underlie these diseases, we studied the association of genome-wide CNVs with gene expression levels of seven genes involved in the endothelin system using independent HapMap subjects including 90 Asians (45 Han Chinese and 45 Japanese), 60 Caucasians, and 60 Africans.
Methods and Results
For each subject, the genome-wide variations were measured using the Affymetrix® 6.0 chip that includes measurements of 906,000 single nucleotide polymorphisms and 946,000 CNV probes. The gene expression profiles of the transformed B-lymphocytes were measured for the same subjects. Among the 210 subjects, we identified 1,529 CNV regions on 22 autosomes. By testing the association between CNVs and the gene expression levels in each racial group using linear regression, we identified four statistically significant CNV associations in all three groups (alpha=0.05). The strongest association was between a 66 kbp CNV region located on chromosome 6 and endothelin-1 (EDN1) expression. The effects of the CNV-EDN1 association in the three racial groups were in the same direction and explained 7%–14% of the variation in EDN1 expression.
Although the biological function of the chromosome 6 CNV is unclear, the significant and consistent association found in three racial groups suggests that CNVs may contribute to variation in underlying risks of common disease through their effects on key molecular signaling pathways.
hypertension; heart failure; atherosclerosis; endothelin system