Nomograms to predict normal aortic root diameter for body surface area (BSA) in broad ranges of age have been widely used, but are limited by lack of consideration of gender effects, jumps in upper limits of aortic diameter between age strata, and data from older teenagers. Sinuses of Valsalva diameter was measured by American Society of Echocardiography convention in normal-weight, non-hypertensive, non-diabetic individuals ≥15 years old without aortic valve disease from clinical or population-based samples. Analyses of covariance and linear regression with assessment of residuals identified determinants and developed predictive models for normal aortic root diameter. Among 1,207 apparently normal individuals ≥15 years old (54% female), aortic root diameter was 2.1 to 4.3 cm. Aortic root diameter was strongly related to BSA and height (both r=0.48), age (r=0.36) and male gender (+2.7 mm adjusted for BSA and age) (all p<0.001). Multivariable equations using age, gender, and either BSA or height predicted aortic diameter strongly (both R=0.674, p <0.001) with minimal relation of residuals to age or body size:
for BSA: 2.423+(age [yrs]*0.009) + (bsa [m2]*0.461) -(sex [1=M, 2=F]*.267) SEE = 0.261 cmfor height: 1.519+(age [yrs]*0.010) + (ht [cm]*.010)-(sex [1=M, 2=F]*.247) SEE = 0.215 cm.
In conclusion, aortic root diameter is larger in men and increases with body size and age. Regression models incorporating body size, age and gender are applicable to adolescents and adults without limitations of previous nomograms.
Aortic root; echocardiography; normal limits
To determine whether the 9p21 SNP association with coronary heart disease is modified by other classical or novel risk markers.
The 9p21 SNP (rs10757274) and multiple risk markers were measured in the Atherosclerosis Risk in Communities Study, and incident coronary disease events were ascertained. Effect modification (interaction) of the 9p21 SNP with risk markers was tested in Cox proportional hazard regression models.
The incidence rates of coronary heart disease per 1000 person-years were 14.4, 17.0, and 18.7 for AA, AG, and GG genotypes, yielding hazard ratios of 1.0, 1.20 (95% CI = 1.07-1.36), and 1.34 (95% CI = 1.16-1.53). There was no meaningful evidence of an interaction (all p-interaction > 0.04) between 9p21 SNP and any of 14 other risk markers for coronary heart disease. These included novel markers not previously explored for 9p21 interaction (e.g., cardiac troponin T and N-terminal pro-brain natriuretic peptide).
Our study extends evidence that the 9p21 SNP association with coronary heart disease is not modified by classical or novel risk markers. Our findings therefore rule out additional plausible pathways by which 9p21 might have increased coronary heart disease risk.
coronary disease; prospective study; 9p21 SNP
G protein-coupled receptor kinases (GRKs) are important regulatory proteins for many G protein-coupled receptors, but little is known about GRK4 pharmacogenetics. We hypothesized three nonsynonymous GRK4 SNPs, R65L (rs2960306), A142V (rs1024323) and A486V (rs1801058) would be associated with blood pressure response to atenolol, but not hydrochlorothiazide, and would be associated with long term cardiovascular outcomes (all cause, death, nonfatal myocardial infarction, nonfatal stroke) in participants treated with an atenolol-based versus verapamil-SR-based antihypertensive strategy. GRK4 SNPs were genotyped in 768 hypertensive participants from the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) trial. In Caucasians and African Americans, increasing copies of the variant 65L-142V haplotype were associated with significantly reduced atenolol-induced diastolic blood pressure lowering (−9.1 ± 6.8 vs −6.8 ± 7.1 vs −5.3 ± 6.4 mmHg in participants with 0, 1 and 2 copies of 65L-142V respectively; p=0.0088). 1460 participants with hypertension and coronary artery disease from the INternational VErapamil SR / Trandolapril STudy (INVEST) were genotyped and variant alleles of all three GRK4 SNPs were associated with increased risk for adverse cardiovascular outcomes in an additive fashion, with 486V homozygotes reaching statistical significance (Odds ratio 2.29 [1.48–3.55], p=0.0002). These effects on adverse cardiovascular outcomes were independent of antihypertensive treatment. These results suggest the presence of GRK4 variant alleles may be important determinants of blood pressure response to atenolol and risk for adverse cardiovascular events. The associations with GRK4 variant alleles were stronger in patients who were also ADRB1 389R-homozygotes, suggesting a potential interaction between these two genes.
hypertension; GRK4; atenolol; beta-blocker; outcomes; ADRB1; pharmacogenetics
Genetic variants in 296 genes in regions identified through admixture mapping of hypertension, BMI, and lipids were assessed for association with hypertension, blood pressure, BMI, and HDL-C.
This study identified coding SNPs identified from HapMap2 data that were located in genes on chromosomes 5, 6, 8, and 21, where ancestry association evidence for hypertension, BMI or HDL-C was identified in previous admixture mapping studies. Genotyping was performed in 1,733 unrelated African-Americans from the National Heart, Lung and Blood Institute’s (NHLBI) Family Blood Pressure Project, and gene-based association analyses were conducted for hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), BMI, and HDL-C. A gene score based on the number of minor alleles of each SNP in a gene was created and used for gene-based regression analyses, adjusting for age, age2, sex, local marker ancestry, and BMI, as applicable. An individual’s African ancestry estimated from 2,507 ancestry-informative markers was also adjusted for to eliminate any confounding due to population stratification.
CXADR (rs437470) on chromosome 21 was associated with SBP and DBP with or without adjusting for local ancestry (p < 0.0006). F2RL1 (rs631465) on chromosome 5 was associated with BMI (p = 0.0005). Local ancestry in these regions was associated with the respective traits as well.
This study suggests that CXADR and F2RL1 likely play important roles in blood pressure and obesity variation, respectively; and these findings are consistent with other studies, so replication and functional analyses are necessary.
Blood pressure; Obesity; African Americans; Genetic Association Studies
Background and Aims
Elevated alanine aminotransferase (ALT >40 IU/mL) is a marker of liver injury but provides little insight into etiology. We aimed to identify and stratify risk factors associated with elevated ALT in a randomly selected population with a high prevalence of elevated ALT (39%), obesity (49%) and diabetes (30%).
Two machine learning methods, the support vector machine (SVM) and Bayesian logistic regression (BLR), were used to capture risk factors in a community cohort of 1532 adults from the Cameron County Hispanic Cohort (CCHC). A total of 28 predictor variables were used in the prediction models. The recently identified genetic marker rs738409 on the PNPLA3 gene was genotyped using the Sequenom iPLEX assay.
The four major risk factors for elevated ALT were fasting plasma insulin level and insulin resistance, increased BMI and total body weight, plasma triglycerides and non-HDL cholesterol, and diastolic hypertension. In spite of the highly significant association of rs738409 in females, the role of rs738409 in the prediction model is minimal, compared to other epidemiological risk factors. Age and drug and alcohol consumption were not independent determinants of elevated ALT in this analysis.
The risk factors most strongly associated with elevated ALT in this population are components of the metabolic syndrome and point to nonalcoholic fatty liver disease (NAFLD). This population-based model identifies the likely cause of liver disease without the requirement of individual pathological diagnosis of liver diseases. Use of such a model can greatly contribute to a population-based approach to prevention of liver disease.
Alanine aminotransferase; Liver disease; Machine learning; NAFLD; PNPLA3 polymorphism; Public health
Based on studies with limited statistical power, lipoprotein(a) [Lp(a)] is not considered a risk factor for cardiovascular disease (CVD) in African Americans. We evaluated associations between Lp(a) and incident CVD events in African Americans and Caucasians in the Atherosclerosis Risk in Communities (ARIC) study.
Methods and Results
Plasma Lp(a) was measured in African Americans (n=3,467) and Caucasians (n=9,851). Hazards ratios (HRs) for incident CVD events (coronary heart disease [CHD] and ischemic strokes) were calculated. Lp(a) levels were higher with wider interindividual variation in African Americans (median [interquartile range]: 12.8 [7.1–21.7] mg/dl) than Caucasians (4.3 [1.7–9.5] mg/dl; p <0.0001). At 20 years of follow-up, 676 CVD events occurred in African Americans and 1,821 events occurred in Caucasians. Adjusted HRs (95% confidence interval [CI]) per race-specific 1-SD–greater log-transformed Lp(a) were 1.13 (1.04–1.23) for incident CVD, 1.11 (1.00–1.22) for incident CHD, and 1.21 (1.06–1.39) for ischemic strokes in African Americans. For Caucasians, the respective HRs (95% CIs) were 1.09 (1.04–1.15), 1.10 (1.05–1.16), and 1.07 (0.97–1.19). Quintile analyses showed that risk for incident CVD was graded but statistically significant only for the highest compared with the lowest quintile (HR [95%CI] 1.35 [1.06–1.74] for African Americans; HR 1.27 [1.10–1.47] for Caucasians). Similar results were obtained using Lp(a) cut-offs of ≤10 mg/dl, >10–≤20 mg/dl, >20–≤30 mg/dl, and >30 mg/dl.
Lp(a) levels were positively associated with CVD events. Associations were at least as strong, with a larger range of Lp(a) concentrations, in African Americans compared with Caucasians.
lipoproteins; cardiovascular diseases; risk factors; race/ethnicity; cardiovascular disease risk factors
Orthostatic hypotension (OH), an independent predictor of mortality and cardiovascular events, strongly correlates with hypertension. Recent genome-wide studies have identified new loci influencing blood pressure (BP) in populations, but their impact on OH remains unknown.
Methods and results
A total of 38 970 men and women of European ancestry from five population-based cohorts were included, of whom 2656 (6.8%) met the diagnostic criteria for OH (systolic/diastolic BP drop ≥20/10 mmHg within 3 min of standing). Thirty-one recently discovered BP-associated single nucleotide polymorphisms (SNPs) were examined using an additive genetic model and the major allele as referent. Relations between OH, orthostatic systolic BP response, and genetic variants were assessed by inverse variance-weighted meta-analysis. We found Bonferroni adjusted (P < 0.0016) significant evidence for association between OH and the EBF1 locus (rs11953630, per-minor-allele odds ratio, 95% confidence interval: 0.90, 0.85–0.96; P = 0.001), and nominal evidence (P < 0.05) for CYP17A1 (rs11191548: 0.85, 0.75–0.95; P = 0.005), and NPR3-C5orf23 (rs1173771: 0.92, 0.87–0.98; P= 0.009) loci. Among subjects not taking BP-lowering drugs, three SNPs within the NPPA/NPPB locus were nominally associated with increased risk of OH (rs17367504: 1.13, 1.02–1.24; P = 0.02, rs198358: 1.10, 1.01–1.20; P = 0.04, and rs5068: 1.22, 1.04–1.43; P = 0.01). Moreover, an ADM variant was nominally associated with continuous orthostatic systolic BP response in the adjusted model (P= 0.04).
The overall association between common gene variants in BP loci and OH was generally weak and the direction of effect inconsistent with resting BP findings. These results suggest that OH and resting BP share few genetic components.
Orthostatic hypotension; Genetics; Single nucleotide polymorphism; Steroid 17-alpha-hydroxylase; Natriuretic peptides; Adrenomedullin
Arsenic is a toxic metal with harmful effects on human health, particularly on cognitive function. Autism Spectrum Disorders (ASDs) are lifelong neurodevelopmental and behavioral disorders manifesting in infancy or early childhood. We used data from 130 children between 2-8 years (65 pairs of ASD cases with age- and sex-matched control), to compare the mean total blood arsenic concentrations in children with and without ASDs in Kingston, Jamaica. Based on univariable analysis, we observed a significant difference between ASD cases and controls (4.03μg/L for cases vs. 4.48μg/L for controls, P < 0.01). In the final multivariable General Linear Model (GLM), after controlling for car ownership, maternal age, parental education levels, source of drinking water, consumption of “yam, sweet potato, or dasheen”, “carrot or pumpkin”, “callaloo, broccoli, or pak choi”, cabbage, avocado, and the frequency of seafood consumption per week, we did not find a significant association between blood arsenic concentrations and ASD status (4.36μg/L for cases vs. 4.65μg/L for controls, P = 0.23). Likewise, in a separate final multivariable GLM, we found that source of drinking water, eating avocado, and eating “callaloo, broccoli, or pak choi” were significantly associated with higher blood arsenic concentrations (all three P < 0.05). Based on our findings, we recommend assessment of arsenic levels in water, fruits, and vegetables, as well as increased awareness among the Jamaican population regarding potential risks for various exposures to arsenic.
Arsenic; Autism Spectrum Disorders; Fruits; Vegetables; Drinking water; Cooking water; Seafood; Jamaica
Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77% were concordant, 0.14% had missing data, and 0.09% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip.
As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111× in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86% with a minor allele frequency less than 0.5%), previously unknown (82%), and population-specific (82%). On average, 2.3% of the 13,595 SNVs each person carried were predicted to affect protein function of ∼313 genes per genome, and ∼95.7% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.
Next generation exome sequencing (ES) and whole genome sequencing (WGS) are new powerful tools for discovering the gene(s) that underlie Mendelian disorders. To accelerate these discoveries, the National Institutes of Health has established three Centers for Mendelian Genomics (CMGs): the Center for Mendelian Genomics at the University of Washington; the Center for Mendelian Disorders at Yale University; and the Baylor-Johns Hopkins Center for Mendelian Genomics at Baylor College of Medicine and Johns Hopkins University. The CMGs will provide ES/WGS and extensive analysis expertise at no cost to collaborating investigators where the causal gene(s) for a Mendelian phenotype has yet to be uncovered. Over the next few years and in collaboration with the global human genetics community, the CMGs hope to facilitate the identification of the genes underlying a very large fraction of all Mendelian disorders see http://mendelian.org.
mendelian; exome sequencing; commentary
C-reactive protein (CRP) levels are associated with cardiovascular disease and systemic inflammation. We assessed whether CRP-associated loci were associated with serum CRP and retinal markers of microvascular disease, in Asian populations.
Genome-wide association analysis (GWAS) for serum CRP was performed in East-Asian Chinese (N = 2,434) and Malays (N = 2,542) and South-Asian Indians (N = 2,538) from Singapore. Leveraging on GWAS data, we assessed, in silico, association levels among the Singaporean datasets for 22 recently identified CRP-associated loci. At loci where directional inconsistencies were observed, quantification of inter-ethnic linkage disequilibrium (LD) difference was determined. Next, we assessed association for a variant at CRP and retinal vessel traits [central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE)] in a total of 24,132 subjects of East-Asian, South-Asian and European ancestry.
Serum CRP was associated with SNPs in/near APOE, CRP, HNF1A and LEPR (p-values ≤4.7×10−8) after meta-analysis of Singaporean populations. Using a candidate-SNP approach, we further replicated SNPs at 4 additional loci that had been recently identified to be associated with serum CRP (IL6R, GCKR, IL6 and IL1F10) (p-values ≤0.009), in the Singaporean datasets. SNPs from these 8 loci explained 4.05% of variance in serum CRP. Two SNPs (rs2847281 and rs6901250) were detected to be significant (p-value ≤0.036) but with opposite effect directions in the Singaporean populations as compared to original European studies. At these loci we did not detect significant inter-population LD differences. We further did not observe a significant association between CRP variant and CRVE or CRAE levels after meta-analysis of all Singaporean and European datasets (p-value >0.058).
Common variants associated with serum CRP, first detected in primarily European studies, are also associated with CRP levels in East-Asian and South-Asian populations. We did not find a causal link between CRP and retinal measures of microvascular disease.
High levels of cardiac troponin T measured by a highly sensitive assay (hs-cTnT) are strongly associated with incident coronary heart disease (CHD) and heart failure (HF). No large-scale genome-wide association study (GWAS) of hs-cTnT has been reported to date. We sought to identify novel genetic variants that are associated with hs-cTnT levels.
Methods and Results
We performed a GWAS in 9,491 European-Americans and 2,053 African-Americans free of CHD and HF from 2 prospective cohorts: the Atherosclerosis Risk in Communities Study (ARIC) and the Cardiovascular Health Study (CHS). GWASs were conducted in each study and race stratum. Fixed-effect meta-analyses combined the results of linear regression from 2 cohorts within each race stratum, and then across race strata to produce overall estimates and p-values. The meta-analysis identified a significant association at chromosome 8q13 (rs10091374, p = 9.06 × 10−9) near the nuclear receptor coactivator 2 (NCOA2) gene. Over-expression of NCOA2 can be detected in myoblasts An additional analysis using logistic regression and the clinically motivated 99th percentile cut-point detected a significant association at 1q32 (rs10091374, p = 9.06 × 10−8) in the gene TNNT2, which encodes the cardiac troponin T protein itself. The hs-cTnT-associated SNPs were not associated with CHD in a large case-control study, but rs12564445 was significantly associated with incident HF in ARIC European-Americans (HR = 1.16, p-value = 0.004).
We identified 2 loci, near NCOA2 and in the TNNT2 gene, at which variation was significantly associated with hs-cTnT levels. Further use of the new assay should enable replication of these results.
genetics; genome-wide association study; troponin
9p21.3 is among the most strongly replicated regions for cardiovascular disease (CVD). There are few reports of sequencing the associated 9p21.3 interval. We set out to sequence the 9p21.3 region followed by a comprehensive study of genetic associations with clinical and subclinical CVD and its risk factors, and with copy number variation and gene expression, in the Framingham Heart Study (FHS).
Methods and Results
We sequenced 281 individuals (n=94 with myocardial infarction, n=94 with high coronary artery calcium levels, and n=93controls free of elevated coronary artery calcium or myocardial infarction) followed by genotyping and association in >7,000 additional FHS individuals. We assessed genetic associations with clinical and subclinical CVD, risk factor phenotypes, and gene expression levels of protein-coding genes CDKN2A and CDKN2B as well as the non-coding gene ANRIL in freshly harvested leukocytes and platelets. Within this large sample we found strong associations of 9p21.3 variants with increased risk for myocardial infarction, higher coronary artery calcium levels, and larger abdominal aorta diameters, and no evidence for association with traditional CVD risk factors. No common protein-coding variation, variants in splice donor or acceptor sites, or CNV events were observed. By contrast, strong associations were observed between genetic variants and gene expression, particularly for a short isoform of ANRIL and for CDKN2B.
Our thorough genomic characterization of 9p21.3 suggests common variants likely account for observed disease associations, and provide further support for the hypothesis that complex regulatory variation affecting ANRIL and CDKN2B gene expression may contribute to increased risk for clinically apparent and subclinical coronary artery disease and aortic disease.
genetics; myocardial infarction; risk factors; atherosclerosis; calcium
Narrow arterioles in the retina have been shown to predict hypertension as well as other vascular diseases, likely through an increase in the peripheral resistance of the microcirculatory flow. In this study, we performed a genome-wide association study in 18,722 unrelated individuals of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium and the Blue Mountain Eye Study, to identify genetic determinants associated with variations in retinal arteriolar caliber. Retinal vascular calibers were measured on digitized retinal photographs using a standardized protocol. One variant (rs2194025 on chromosome 5q14 near the myocyte enhancer factor 2C MEF2C gene) was associated with retinal arteriolar caliber in the meta-analysis of the discovery cohorts at genome-wide significance of P-value <5×10−8. This variant was replicated in an additional 3,939 individuals of European ancestry from the Australian Twins Study and Multi-Ethnic Study of Atherosclerosis (rs2194025, P-value = 2.11×10−12 in combined meta-analysis of discovery and replication cohorts). In independent studies of modest sample sizes, no significant association was found between this variant and clinical outcomes including coronary artery disease, stroke, myocardial infarction or hypertension. In conclusion, we found one novel loci which underlie genetic variation in microvasculature which may be relevant to vascular disease. The relevance of these findings to clinical outcomes remains to be determined.
To identify genes influencing blood pressure response to an angiotensin II receptor blocker, single nucleotide polymorphisms identified by genome-wide association analysis of the response to candesartan were validated by opposite direction associations with the response to a thiazide diuretic, hydrochlorothiazide. 198 White and 193 African Americans with primary hypertension were sampled from opposite tertiles of the race-sex-specific distributions of age-adjusted diastolic blood pressure response to candesartan. 285 polymorphisms associated with the response to candesartan at p<10−4 in Whites. 273 of the 285 polymorphisms, which were available for analysis in a separate sample of 196 Whites, validated for opposite direction associations with the response to hydrochlorothiazide (Fisher’s X2 1-sided p=0.02). Among the 273 polymorphisms, those in the chromosome 11q21 region were the most significantly associated with response to candesartan in Whites (e.g., rs11020821 near FUT4, p=8.98×10−7), had the strongest opposite direction associations with response to hydrochlorothiazide (e.g., rs3758785 in GPR83, p=7.10×10−3), and had same direction associations with response to candesartan in the 193 African Americans (e.g., rs16924603 near FUT4, p=1.52×10−2). Also notable among the 273 polymorphisms was rs11649420 on chromosome 16 in the amiloride-sensitive sodium channel subunit SCNN1G involved in mediating renal sodium reabsorption and maintaining blood pressure when the renin-angiotensin system is inhibited by candesartan. These results support the utility of genomewide association analyses to identify novel genes predictive of opposite direction associations with blood pressure responses to inhibitors of the renin-angiotensin and renal sodium transport systems.
Hypertension; pharmacogenetics; diuretic; blood pressure; genome
Human diseases are caused by alleles that encompass the full range of variant types, from single-nucleotide changes to copy-number variants, and these variations span a broad frequency spectrum, from the very rare to the common. The picture emerging from analysis of whole-genome sequences, the 1000 Genomes Project pilot studies, and targeted genomic sequencing derived from very large sample sizes reveals an abundance of rare and private variants. One implication of this realization is that recent mutation may have a greater influence on disease susceptibility or protection than is conferred by variations that arose in distant ancestors.
Genome-wide association studies (GWAS) have not consistently detected replicable genetic risk factors for ischemic stroke, potentially due to etiological heterogeneity of this trait. We performed GWAS of ischemic stroke and a major ischemic stroke subtype (large artery atherosclerosis, LAA) using 1,162 ischemic stroke cases (including 421 LAA cases) and 1,244 population controls from Australia. Evidence for a genetic influence on ischemic stroke risk was detected, but this influence was higher and more significant for the LAA subtype. We identified a new LAA susceptibility locus on chromosome 6p21.1 (rs556621: odds ratio (OR) = 1.62, P = 3.9 × 10−8) and replicated this association in 1,715 LAA cases and 52,695 population controls from 10 independent population cohorts (meta-analysis replication OR = 1.15, P = 3.9 × 10−4; discovery and replication combined OR = 1.21, P = 4.7 × 10−8). This study identifies a genetic risk locus for LAA and shows how analyzing etiological subtypes may better identify genetic risk alleles for ischemic stroke.
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
To identify panels of genetic variants that predict treatment-related coronary heart disease (CHD) outcomes in hypertensive patients on one of four different classes of initial antihypertensive treatment. The goal was to identify subgroups of people based on their genetic profile who benefit most from a particular treatment.
Candidate genetic variants (n=78) were genotyped in 39,114 participants from GenHAT, ancillary to ALLHAT. ALLHAT randomized hypertensive participants (>=55 years) to one of four treatments (amlodipine, chlorthalidone, doxazosin, lisinopril). The primary outcome was fatal CHD or non-fatal MI (mean follow-up=4.9 years). A pharmacogenetic panel was derived within each of the four treatment groups. ROC curves estimated the discrimination rate between those with and without a CHD event, based on the addition of the genetic panel risk score.
For each treatment group, we identified a panel of genetic variants that collectively improved prediction of CHD to a small but statistically significant extent. Chlorthalidone (A): NOS3, rs3918226; SELE, rs5361; ICAM1, rs1799969; AGT, rs5051; GNAS, rs7121; ROC comparison p=.004; Amlodipine (B): MMP1, rs1799750; F5, rs6025; NPPA, rs5065; PDE4D, rs6450512; MMP9, rs2274756; ROC comparison p=.006; Lisinopril (C): AGT, rs5051; PON1, rs705379; MMP12, rs652438; F12, rs1801020; GP1BA, rs6065; PDE4D, rs27653; ROC comparison p=.01; Doxazosin (D): F2, rs1799963; PAI1, rs1799768; MMP7, rs11568818; AGT, rs5051; ACE, rs4343; MMP2, rs243865; ROC comparison p=.007. Each panel was tested for a pharmacogenetic effect; panels A, B and D showed such evidence (p=.009, .006, and .001 respectively), panel C did not (p=.09).
Because each panel was associated with CHD in a specific treatment group but not the others, this research provides evidence that it may be possible to use gene panel scores as a tool to better assess antihypertensive treatment choices to reduce CHD risk in hypertensive individuals.
pharmacogenetics; antihypertensive pharmacogenetics; CVD; gene panels
Gene–lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13–0.31], P = 1.63 × 10−6). All SNPs were associated with 2-h glucose (β = 0.06–0.12 mmol/allele, P ≤ 1.53 × 10−7), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene–lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.
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
Candidate gene association studies for peripheral artery disease (PAD), including subclinical disease assessed with the ankle-brachial index (ABI), have been limited by the modest number of genes examined. We conducted a two stage meta-analysis of ~50,000 SNPs across ~2100 candidate genes to identify genetic variants for ABI.
Methods and results
We studied subjects of European ancestry from 8 studies (n = 21,547, 55% women, mean age 44–73 years) and African American ancestry from 5 studies (n = 7267, 60% women, mean age 41–73 years) involved in the candidate gene association resource (CARe) consortium. In each ethnic group, additive genetic models were used (with each additional copy of the minor allele corresponding to the given beta) to test each SNP for association with continuous ABI (excluding ABI > 1.40) and PAD (defined as ABI < 0.90) using linear or logistic regression with adjustment for known PAD risk factors and population stratification. We then conducted a fixed-effects inverse-variance weighted meta-analyses considering a p < 2 × 10−6 to denote statistical significance.
In the European ancestry discovery meta-analyses, rs2171209 in SYTL3 (β = −0.007, p = 6.02 × 10−7) and rs290481 in TCF7L2 (β = −0.008, p = 7.01 × 10−7) were significantly associated with ABI. None of the SNP associations for PAD were significant, though a SNP in CYP2B6 (p = 4.99 × 10−5) was among the strongest associations. These 3 genes are linked to key PAD risk factors (lipoprotein(a), type 2 diabetes, and smoking behavior, respectively). We sought replication in 6 population-based and 3 clinical samples (n = 15,440) for rs290481 and rs2171209. However, in the replication stage (rs2171209, p = 0.75; rs290481, p = 0.19) and in the combined discovery and replication analysis the SNP–ABI associations were no longer significant (rs2171209, p = 1.14 × 10−3; rs290481, p = 8.88 × 10−5). In African Americans, none of the SNP associations for ABI or PAD achieved an experiment-wide level of significance.
Genetic determinants of ABI and PAD remain elusive. Follow-up of these preliminary findings may uncover important biology given the known gene-risk factor associations. New and more powerful approaches to PAD gene discovery are warranted.
Ankle brachial index; Peripheral artery disease; Genetics; Candidate gene array; Meta-analysis; Ethnicity
We propose a two-stage approach to analyze genome-wide association (GWA) data in order to identify a set of promising single-nucleotide polymorphisms (SNPs). In stage one, we select a list of top signals from single SNP analyses by controlling false discovery rate (FDR). In stage two, we use the least absolute shrinkage and selection operator (LASSO) regression to reduce false positives. The proposed approach was evaluated using simulated quantitative traits based on genome-wide SNP data on 8,861 Caucasian individuals from the Atherosclerosis Risk in Communities (ARIC) Study. Our first stage, targeted at controlling false negatives, yields better power than using Bonferroni corrected significance level. The LASSO regression reduces the number of significant SNPs in stage two: it reduces false positive SNPs and it reduces true positive SNPs also at simulated causal loci due to linkage disequilibrium. Interestingly, the LASSO regression preserves the power from stage one, i.e., the number of causal loci detected from the LASSO regression in stage two is almost the same as in stage one, while reducing false positives further. Real data on systolic blood pressure in the ARIC study was analyzed using our two-stage approach which identified two significant SNPs, one of which was reported to be genome-significant in a meta-analysis containing a much larger sample size. On the other hand, a single SNP association scan did not yield any significant results.
LASSO; FDR; multi-marker; association; power
We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD.
This study evaluates association of rare variants and autism spectrum disorders (ASD) in case and control samples sequenced by two centers. Before doing association analyses, we studied how to combine information across studies. We first harmonized the whole-exome sequence (WES) data, across centers, in terms of the distribution of rare variation. Key features included filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. After filtering, the vast majority of variants calls from seven samples sequenced at both centers matched. We also evaluated whether one should combine summary statistics from data from each center (meta-analysis) or combine data and analyze it together (mega-analysis). For many gene-based tests, we showed that mega-analysis yields more power. After quality control of data from 1,039 ASD cases and 870 controls and a range of analyses, no gene showed exome-wide evidence of significant association. Our results comport with recent results demonstrating that hundreds of genes affect risk for ASD; they suggest that rare risk variants are scattered across these many genes, and thus larger samples will be required to identify those genes.