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
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
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.
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.
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
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
We investigated the association of 14 polymorphisms in the endothelial nitric oxide synthase gene (NOS3) with ankle brachial index (ABI) in non-Hispanic white hypertensives belonging to hypertensive sibships. Subjects (n = 659, mean age 61±9 y, 54% women) underwent measurement of ABI using a standard protocol, and the lowest of 4 ABI values was used in the analyses. Non-synonymous SNPs with a minor allele frequency > 0.02 and tag SNPs selected based on a measure of linkage disequilibrium (r2) were genotyped. We reduced the chance of false positives by testing for replication, randomly selecting 1 hypertensive sib from each sibship to create Subset 1 (n = 330) and Subset 2 (n = 329). Multivariable linear regression models were used to assess the associations of single NOS3 polymorphisms and haplotypes with ABI after adjustment for covariates (age, sex, body mass index, smoking, total cholesterol, HDL cholesterol, and diabetes). Two specific SNPs in significant LD with each other (rs891512 and rs1808593) were significantly associated with ABI in both subsets. Based on a sliding window approach with a window size of 2, estimated haplotypes from 2 SNP pairs (rs2070744–rs3918226 & rs1808593–rs7830) were also significantly associated with ABI in both subsets. In conclusion, specific NOS3 SNPs and haplotypes were associated with inter-individual variation in ABI, a non-invasive marker of peripheral arterial disease, in replicate subsets of hypertensive subjects. These findings motivate further investigation of the role of NOS3 variants in determining susceptibility to peripheral arterial disease.
genetics; nitric oxide synthase; ankle-brachial index; peripheral arterial disease
In order to take into account the complex genomic distribution of SNP variations when identifying chromosomal regions with significant SNP effects, a single nucleotide polymorphism (SNP) association scan statistic was developed. To address the computational needs of genome wide association (GWA) studies, a fast Java application, which combines single-locus SNP tests and a scan statistic for identifying chromosomal regions with significant clusters of significant SNP effects, was developed and implemented. To illustrate this application, SNP associations were analyzed in a pharmacogenomic study of the blood pressure lowering effect of thiazide-diuretics (N=195) using the Affymetrix Human Mapping 100K Set. 55,335 tagSNPs (pair-wise linkage disequilibrium R2<0.5) were selected to reduce the frequency correlation between SNPs. A typical workstation can complete the whole genome scan including 10,000 permutation tests within 3 hours. The most significant regions locate on chromosome 3, 6, 13 and 16, two of which contain candidate genes that may be involved in the underlying drug response mechanism. The computational performance of ChromoScan-GWA and its scalability were tested with up to 1,000,000 SNPs and up to 4,000 subjects. Using 10,000 permutations, the computation time grew linearly in these datasets. This scan statistic application provides a robust statistical and computational foundation for identifying genomic regions associated with disease and provides a method to compare GWA results even across different platforms.
Scan Statistic; Genome Wide Association; Single Nucleotide Polymorphism; Distance Distribution; ChromoScan
As part of the Genetic Epidemiology Network of Arteriopathy study, hypertensive non-Hispanic White sibships were screened using 471 single nucleotide polymorphisms (SNPs) to identify genes influencing coronary artery calcification (CAC) measured by computed tomography. Individuals with detectable CAC and CAC quantity ≥70th age- and sex-specific percentile were classified as having a high CAC burden and compared to individuals with CAC quantity <70th percentile. Two sibs from each sibship were randomly chosen and divided into two data sets, each with 360 unrelated individuals. Within each data set, we applied two machine learning algorithms, Random Forests and RuleFit, to identify the best predictors of having high CAC burden among 17 risk factors and 471 SNPs. Using five-fold cross-validation, both methods had ~70% sensitivity and ~60% specificity. Prediction accuracies were significantly different from random predictions (P-value <0.001) based on 1,000 permutation tests. Predictability of using 287 tagSNPs was as good as using all 471 SNPs. For Random Forests, among the top 50 predictors, the same eight tagSNPs and 15 risk factors were found in both data sets while eight tagSNPs and 12 risk factors were found in both data sets for RuleFit. Replicable effects of two tagSNPs (in genes GPR35 and NOS3) and 12 risk factors (age, body mass index, sex, serum glucose, high-density lipoprotein cholesterol, systolic blood pressure, cholesterol, homocysteine, triglycerides, fibrinogen, Lp(a) and low-density lipoprotein particle size) were identified by both methods. This study illustrates how machine learning methods can be used in sibships to identify important, replicable predictors of subclinical coronary atherosclerosis.
machine learning; Random Forests; RuleFit; coronary artery calcification; sibship
To localize susceptibility genes for alterations in brain structure associated with risk of stroke and dementia. We conducted genomewide linkage analyses for magnetic resonance imaging (MRI) measures of brain atrophy, ventricular, and subcortical white matter hyperintensity (leukoaraiosis) in 689 non-Hispanic white (673 sibling pairs; median age, 61 years) and 544 non-Hispanic black participants (503 sibling pairs; median age, 64 years) from sibships with at least 2 members with essential hypertension.
Design, Setting, and Patients
We determined brain, ventricular, and leukoaraiosis volumes from axial fluid-attenuated inversion recovery MRI; we calculated brain atrophy as the difference between total intracranial and brain volumes. Microsatellite markers (n=451) distributed across the 22 autosomes were genotyped, and we used variance components methods to estimate heritability and assess evidence of genetic linkage for each MRI measure.
Main Outcome Measures
Brain atrophy ventricular volume, and leukoaraiosis determined from fluid-attenuated inversion recovery MRI.
In both races, the heritability of each MRI measure was statistically greater than 0 (P< .001), ranging in magnitude from 0.42 (for ventricular volume in blacks) to 0.69 (for brain atrophy in blacks). Based on multipoint logarithm of odds scores (MLS), the strongest evidence of genetic linkage was observed for brain atrophy on chromosomes 1 (MLS, 3.49 at 161 cM; P< .001) and 17 (MLS, 3.08 at 18 cM; P< .001) in whites; for ventricular volume on chromosome 12 (MLS, 3.67 at 49 cM; P< .001) in blacks and chromosome 10 (MLS, 2.47 at 110 cM; P < .001) in whites; and for leukoaraiosis on chromosome 11 (MLS, 2.21 at 118 cM; P < .001) in whites and chromosome 22 (MLS, 2.02 at 36 cM; P= .001) in blacks.
The MRI measures of structural brain injury are heritable in non-Hispanic black and white sibships ascertained through hypertensive sibling pairs. The susceptibility loci for brain atrophy, ventricular volume, and leukoaraiosis identified by linkage analyses differ among MRI measures and between races.
This paper examines three common explanations for human characteristics: genes, the environment, and choice. Based on data from a representative sample of White and Black Americans, respondents indicated how much they believed each factor influenced individual differences in athleticism, nurturance, drive, math ability, violence, intelligence, and sexual orientation. Results show that across traits: 1) Black respondents generally favor choice and reject genetic explanations, whereas White respondents indicate less causal consistency; 2) although a sizeable subset of respondents endorse just one factor, most report multiple factors as at least partly influential; and 3) among White respondents greater endorsement of genetic explanations is associated with less acceptance of choice and the environment, although among Black respondents a negative relationship holds only between genes and choice. The social relevance of these findings is discussed within the context of the attribution, essentialism and lay theory literature. The results underscore the need to consider more complex and nuanced issues than are implied by the simplistic, unidimensional character of the nature/nurture and determinism/free will debates — perennial controversies that have significance in the current genomic era.
attributions; nature/nurture; determinism/free will; genetic explanations
β-adrenergic receptor (βAR) blockade is standard therapy for cardiac failure and ischemia. G-protein coupled receptor kinases (GRKs) desensitize βAR, suggesting that genetic GRK variants might modify outcomes in these syndromes. Re-sequencing of GRK2 and GRK5 revealed a non-synonymous polymorphism of GRK5, common in African Americans (AA), substituting leucine (L) for glutamine (Q) at position 41. GRK5-L41 more effectively uncoupled isoproterenol-stimulated responses than GRK5-Q41 in transfected cells and transgenic mice, and like pharmacological βAR blockade, GRK5-L41 protected against experimental catecholamine-induced cardiomyopathy. Human association studies showed a pharmacogenomic interaction between GRK5-L41 and β-blocker treatment on mortality outcome in independent cohorts of AA cardiac failure (P=0.036) and ischemia (P=0.023). In 375 prospectively followed AA heart failure subjects, GRK5-L41 was protective against death/cardiac transplant (single allele: RR=0.28, 95% CI=0.12-0.66; two alleles: RR=0.08, 95% CI=0.04-0.19; P=0.004). The gain-of-function GRK5-L41 polymorphism facilitates βAR desensitization during catecholamine excess, imparting “genetic β-blockade” and improving survival in heart failure.
Evaluate the consistency of the contribution of interactions between
single nucleotide polymorphism (SNP) genotype effects to variation in
measures of lipid metabolism across ethnic strata within gender.
Methods and Results
We considered 80 SNPs within the apolipoprotein (APO)
A1/C3/A4/A5 gene cluster using an over-parameterized general
linear model to identify SNPs whose genotype effects combine non-additively
to influence plasma levels of high density lipoprotein cholesterol (HDL-C),
total cholesterol (TC) and triglycerides (TG) in a consistent manner across
ethnic strata. We analyzed population-based samples of unrelated 18 to 30
year old African-Americans (n = 1,858) and European-Americans (n
= 1,973) ascertained without regard to health at four field
centers (Birmingham, Ala.; Chicago, Ill.; Minneapolis, Minn. and Oakland,
Calif., USA) by the Coronary Artery Risk Development in Young Adults
(CARDIA) study. To identify which SNP genotype effects combine
non-additively we used a two-tier analysis strategy. We first required that
pairs of SNPs show statistically significant non-additivity in both ethnic
strata within a gender, where experiment-wise significance was evaluated
using a permutation test to determine the probability of observing the
number of tests significant in both ethnic strata by chance alone. Second,
we required no significant evidence of heterogeneity of the relationship
between the phenotype and the two SNP genotypes across ethnic strata and
across field centers within each ethnic group. From this strategy we
identified ten pairs of SNPs, involving thirteen SNPs, that displayed
statistically significant non-additivity of SNP genotype effects on TC. Only
one of these thirteen SNPs had statistically significant genotype effects
that were consistent across samples.
Our analyses suggest that ignoring the contribution of interactions
between SNP genotype effects when modeling multi-SNP genotype-phenotype
relationships may result in an underestimate of the contribution of genetic
variation to variation in quantitative cardiovascular disease (CVD) risk
Cholesterol; Interaction; Epistasis; APOA1/C3/A4/A5 gene cluster; Association studies
The objective of this study was to evaluate 1) whether non-coding single nucleotide polymorphisms (non-cSNP) in the apolipoprotein E gene (APOE) identified by resequencing studies contribute to statistically explaining dyslipidemia if variations in the two cSNPs in exon 4 that define the ɛ2, ɛ3, and ɛ4 alleles are ignored, and 2) whether the contribution of these additional SNPs persists when variations in the cSNPs are considered. We used an ecological, multiple-population, data-mining strategy to identify single-SNP and two-SNP genotypes that distinguish between high and low levels of plasma lipids in three training samples, European-Americans from Rochester, MN, African-Americans from Jackson, MS, and Europeans from North Karelia, Finland. We found that a pair of SNPs located in the 5' region define genotypes A560T832/A560T832, A560T832/A560G832, and A560T832/T560T832, which distinguish between high and low levels of HDL-cholesterol (HDL-C), triglycerides (TG), and/or total cholesterol (T-C). The A560T832/- genotypes predicted high TG and high T-C in both genders in a large independent test sample from Copenhagen, Denmark. Prediction of high T-C in the Danish females was dependent on genotypes defined by the cSNPs. Our study suggests that both regulatory and structural variations should be considered when evaluating the utility of APOE for predicting dyslipidemia in the population at large.
apolipoprotein E gene; pleiotropy; data mining; regulation; lipids
Serial Analysis of Gene Expression (SAGE) is becoming a widely
used gene expression profiling method for the study of development,
cancer and other human diseases. Investigators using SAGE rely heavily
on the quantitative aspect of this method for cataloging gene expression
and comparing multiple SAGE libraries. We have developed additional
computational and statistical tools to assess the quality and reproducibility
of a SAGE library. Using these methods, a critical variable in the
SAGE protocol was identified that has the potential to bias the
Tag distribution relative to the GC content of the 10 bp SAGE Tag
DNA sequence. We also detected this bias in a number of publicly
available SAGE libraries. It is important to note that the GC content bias
went undetected by quality control procedures in the current SAGE
protocol and was only identified with the use of these statistical
analyses on as few as 750 SAGE Tags. In addition to keeping any
solution of free DiTags on ice, an analysis of the GC content should
be performed before sequencing large numbers of SAGE Tags to be
confident that SAGE libraries are free from experimental bias.
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.
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.
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.
The increasing availability of personal genomic tests has led to discussions about the validity and utility of such tests and the balance of benefits and harms. A multidisciplinary workshop was convened by the National Institutes of Health and the Centers for Disease Control and Prevention to review the scientific foundation for using personal genomics in risk assessment and disease prevention and to develop recommendations for targeted research. The clinical validity and utility of personal genomics is a moving target with rapidly developing discoveries but little translation research to close the gap between discoveries and health impact. Workshop participants made recommendations in five domains: (1) developing and applying scientific standards for assessing personal genomic tests; (2) developing and applying a multidisciplinary research agenda, including observational studies and clinical trials to fill knowledge gaps in clinical validity and utility; (3) enhancing credible knowledge synthesis and information dissemination to clinicians and consumers; (4) linking scientific findings to evidence-based recommendations for use of personal genomics; and (5) assessing how the concept of personal utility can affect health benefits, costs, and risks by developing appropriate metrics for evaluation. To fulfill the promise of personal genomics, a rigorous multidisciplinary research agenda is needed.
behavioral sciences; epidemiologic methods; evidence-based medicine; genetics; genetic testing; genomics; medicine; public health