Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI.

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.

A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids.

Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups.

An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis.

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D.

DNA methylation age is associated with an altered hemostatic profile in a multiethnic meta-analysis.

Many hemostatic factors are associated with age and age-related diseases; however, much remains unknown about the biological mechanisms linking aging and hemostatic factors. DNA methylation is a novel means by which to assess epigenetic aging, which is a measure of age and the aging processes as determined by altered epigenetic states. We used a meta-analysis approach to examine the association between measures of epigenetic aging and hemostatic factors, as well as a clotting time measure. For fibrinogen, we performed European and African ancestry-specific meta-analyses which were then combined via a random effects meta-analysis. For all other measures we could not estimate ancestry-specific effects and used a single fixed effects meta-analysis. We found that 1-year higher extrinsic epigenetic age as compared with chronological age was associated with higher fibrinogen (0.004 g/L/y; 95% confidence interval, 0.001-0.007; P = .01) and plasminogen activator inhibitor 1 (PAI-1; 0.13 U/mL/y; 95% confidence interval, 0.07-0.20; P = 6.6 × 10-5) concentrations, as well as lower activated partial thromboplastin time, a measure of clotting time. We replicated PAI-1 associations using an independent cohort. To further elucidate potential functional mechanisms, we associated epigenetic aging with expression levels of the PAI-1 protein encoding gene (SERPINE1) and the 3 fibrinogen subunit-encoding genes (FGA, FGG, and FGB) in both peripheral blood and aorta intima-media samples. We observed associations between accelerated epigenetic aging and transcription of FGG in both tissues. Collectively, our results indicate that accelerated epigenetic aging is associated with a procoagulation hemostatic profile, and that epigenetic aging may regulate hemostasis in part via gene transcription.

Testing cross-phenotype effects of rare variants in longitudinal studies of complex traits.

Many gene mapping studies of complex traits have identified genes or variants that influence multiple phenotypes. With the advent of next-generation sequencing technology, there has been substantial interest in identifying rare variants in genes that possess cross-phenotype effects. In the presence of such effects, modeling both the phenotypes and rare variants collectively using multivariate models can achieve higher statistical power compared to univariate methods that either model each phenotype separately or perform separate tests for each variant. Several studies collect phenotypic data over time and using such longitudinal data can further increase the power to detect genetic associations. Although rare-variant approaches exist for testing cross-phenotype effects at a single time point, there is no analogous method for performing such analyses using longitudinal outcomes. In order to fill this important gap, we propose an extension of Gene Association with Multiple Traits (GAMuT) test, a method for cross-phenotype analysis of rare variants using a framework based on the distance covariance. The approach allows for both binary and continuous phenotypes and can also adjust for covariates. Our simple adjustment to the GAMuT test allows it to handle longitudinal data and to gain power by exploiting temporal correlation. The approach is computationally efficient and applicable on a genome-wide scale due to the use of a closed-form test whose significance can be evaluated analytically. We use simulated data to demonstrate that our method has favorable power over competing approaches and also apply our approach to exome chip data from the Genetic Epidemiology Network of Arteriopathy.

Meta-analysis of epigenome-wide association studies of cognitive abilities.

Cognitive functions are important correlates of health outcomes across the life-course. Individual differences in cognitive functions are partly heritable. Epigenetic modifications, such as DNA methylation, are susceptible to both genetic and environmental factors and may provide insights into individual differences in cognitive functions. Epigenome-wide meta-analyses for blood-based DNA methylation levels at ~420,000 CpG sites were performed for seven measures of cognitive functioning using data from 11 cohorts. CpGs that passed a Bonferroni correction, adjusting for the number of CpGs and cognitive tests, were assessed for: longitudinal change; being under genetic control (methylation QTLs); and associations with brain health (structural MRI), brain methylation and Alzheimer's disease pathology. Across the seven measures of cognitive functioning (meta-analysis n range: 2557-6809), there were epigenome-wide significant (P < 1.7 × 10-8) associations for global cognitive function (cg21450381, P = 1.6 × 10-8), and phonemic verbal fluency (cg12507869, P = 2.5 × 10-9). The CpGs are located in an intergenic region on chromosome 12 and the INPP5A gene on chromosome 10, respectively. Both probes have moderate correlations (~0.4) with brain methylation in Brodmann area 20 (ventral temporal cortex). Neither probe showed evidence of longitudinal change in late-life or associations with white matter brain MRI measures in one cohort with these data. A methylation QTL analysis suggested that rs113565688 was a cis methylation QTL for cg12507869 (P = 5 × 10-5 and 4 × 10-13 in two lookup cohorts). We demonstrate a link between blood-based DNA methylation and measures of phonemic verbal fluency and global cognitive ability. Further research is warranted to understand the mechanisms linking genomic regulatory changes with cognitive function to health and disease.

DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation.

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p < 1.6 × 10-3). The replicated methylation sites are heritable (h2 > 30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

Modeling the Causal Role of DNA Methylation in the Association Between Cigarette Smoking and Inflammation in African Americans: A 2-Step Epigenetic Mendelian Randomization Study.

The association between cigarette smoking and inflammation is well known. However, the biological mechanisms behind the association are not fully understood, particularly the role of DNA methylation, which is known to be affected by smoking. Using 2-step epigenetic Mendelian randomization, we investigated the role of DNA methylation in the association between cigarette smoking and inflammation. In 822 African Americans from the Genetic Epidemiology Network of Arteriopathy, phase 2 (Jackson, Mississippi; 2000-2005), study population, we examined the association of cigarette smoking with DNA methylation using single nucleotide polymorphisms identified in previous genome-wide association studies of cigarette smoking. We then investigated the association of DNA methylation with levels of inflammatory markers using cis-methylation quantitative trait loci single nucleotide polymorphisms. We found that current smoking status was associated with the DNA methylation levels (M values) of cg03636183 in the coagulation factor II (thrombin) receptor-like 3 gene (F2RL3) (M = -0.64, 95% confidence interval (CI): -0.84, -0.45) and of cg19859270 in the G protein-coupled receptor 15 gene (GPR15) (M = -0.21, 95% CI: -0.27, -0.15). The DNA methylation levels of cg03636183 in F2RL3 were associated with interleukin-18 concentration (-0.11 pg/mL, 95% CI: -0.19, -0.04). These combined negative effects suggest that cigarette smoking increases interleukin-18 levels through the decrease in DNA methylation levels of cg03636183 in F2RL3.

Gene expression signature of Gleason score is associated with prostate cancer outcomes in a radical prostatectomy cohort.

Prostate cancer (PCa) is a leading cause of cancer-related mortality worldwide. Gleason score (GS) is one of the best predictors of PCa aggressiveness, but additional tumor biomarkers may improve its prognostic accuracy. We developed a gene expression signature of GS to enhance the prediction of PCa outcomes. Elastic net was used to construct a gene expression signature by contrasting GS 8-10 vs. ≤6 tumors in The Cancer Genome Atlas (TCGA) dataset. The constructed signature was then evaluated for its ability to predict recurrence and metastatic-lethal (ML) progression in a Fred Hutchinson (FH) patient cohort (N=408; NRecurrence=109; NMLprogression=27). The expression signature included transcripts representing 49 genes. In the FH cohort, a 25% increase in the signature was associated with a hazard ratio (HR) of 1.51 (P=2.7×10-5) for recurrence. The signature's area under the curve (AUC) for predicting recurrence and ML progression was 0.68 and 0.76, respectively. Compared to a model with age at diagnosis, pathological stage and GS, the gene expression signature improved the AUC for recurrence (3%) and ML progression (6%). Higher levels of the signature were associated with increased expression of genes in cell cycle-related pathways and decreased expression of genes in androgen response, estrogen response, oxidative phosphorylation, and apoptosis. This gene expression signature based on GS may improve the prediction of recurrence as well as ML progression in PCa patients after radical prostatectomy.

SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function.

Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium (nStage1: 111,666; nStage2: 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea (PPM1J, EDEM3, ACP1, SPEG, EYA4, CYP1A1, and ATXN2L; PStage1<3.7×10-7), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 (P=5.4×10-8 by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2-knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation.

DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases.

BACKGROUND: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation. RESULTS: We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10-7) in the discovery panel of European ancestry and replicated (P < 2.29 × 10-4) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10-5), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10-3), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10-5). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants. CONCLUSION: We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.

Multiethnic Exome-Wide Association Study of Subclinical Atherosclerosis.

BACKGROUND: The burden of subclinical atherosclerosis in asymptomatic individuals is heritable and associated with elevated risk of developing clinical coronary heart disease. We sought to identify genetic variants in protein-coding regions associated with subclinical atherosclerosis and the risk of subsequent coronary heart disease. METHODS AND RESULTS: We studied a total of 25 109 European ancestry and African ancestry participants with coronary artery calcification (CAC) measured by cardiac computed tomography and 52 869 participants with common carotid intima-media thickness measured by ultrasonography within the CHARGE Consortium (Cohorts for Heart and Aging Research in Genomic Epidemiology). Participants were genotyped for 247 870 DNA sequence variants (231 539 in exons) across the genome. A meta-analysis of exome-wide association studies was performed across cohorts for CAC and carotid intima-media thickness. APOB p.Arg3527Gln was associated with 4-fold excess CAC (P=3×10-10). The APOE ε2 allele (p.Arg176Cys) was associated with both 22.3% reduced CAC (P=1×10-12) and 1.4% reduced carotid intima-media thickness (P=4×10-14) in carriers compared with noncarriers. In secondary analyses conditioning on low-density lipoprotein cholesterol concentration, the ε2 protective association with CAC, although attenuated, remained strongly significant. Additionally, the presence of ε2 was associated with reduced risk for coronary heart disease (odds ratio 0.77; P=1×10-11). CONCLUSIONS: Exome-wide association meta-analysis demonstrates that protein-coding variants in APOB and APOE associate with subclinical atherosclerosis. APOE ε2 represents the first significant association for multiple subclinical atherosclerosis traits across multiple ethnicities, as well as clinical coronary heart disease.

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants.

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy.

A statistical approach for rare-variant association testing in affected sibships.

Sequencing and exome-chip technologies have motivated development of novel statistical tests to identify rare genetic variation that influences complex diseases. Although many rare-variant association tests exist for case-control or cross-sectional studies, far fewer methods exist for testing association in families. This is unfortunate, because cosegregation of rare variation and disease status in families can amplify association signals for rare variants. Many researchers have begun sequencing (or genotyping via exome chips) familial samples that were either recently collected or previously collected for linkage studies. Because many linkage studies of complex diseases sampled affected sibships, we propose a strategy for association testing of rare variants for use in this study design. The logic behind our approach is that rare susceptibility variants should be found more often on regions shared identical by descent by affected sibling pairs than on regions not shared identical by descent. We propose both burden and variance-component tests of rare variation that are applicable to affected sibships of arbitrary size and that do not require genotype information from unaffected siblings or independent controls. Our approaches are robust to population stratification and produce analytic p values, thereby enabling our approach to scale easily to genome-wide studies of rare variation. We illustrate our methods by using simulated data and exome chip data from sibships ascertained for hypertension collected as part of the Genetic Epidemiology Network of Arteriopathy (GENOA) study.

Effect modification by vitamin D receptor genetic polymorphisms in the association between cumulative lead exposure and pulse pressure: a longitudinal study.

BACKGROUND: Although the association between lead and cardiovascular disease is well established, potential mechanisms are still poorly understood. Calcium metabolism plays a role in lead toxicity and thus, vitamin D receptor (VDR) polymorphisms have been suggested to modulate the association between lead and health outcomes. We investigated effect modification by VDR genetic polymorphisms in the association between cumulative lead exposure and pulse pressure, a marker of arterial stiffness. METHODS: We examined 727 participants (3,100 observations from follow-ups from 1991 to 2011) from the Normative Aging Study (NAS), a longitudinal study of aging. Tibia and patella bone lead levels were measured using K-x-ray fluorescence. Four single nucleotide polymorphisms (SNPs) in the VDR gene, Bsm1, Taq1, Apa1, and Fok1, were genotyped. Linear mixed effects models with random intercepts were implemented to take into account repeated measurements. RESULTS: Adjusting for potential confounders, pulse pressure was 2.5 mmHg (95% CI: 0.4-4.7) and 1.9 mmHg (95% CI: 0.1-3.8) greater per interquartile range (IQR) increase in tibia lead (15 µg/g) and patella lead (20 µg/g), respectively, in those with at least one minor frequency allele in Bsm1 compared with those with major frequency allele homozygotes. The observed interaction effect between bone lead and the Bsm1 genotype persists over time during the follow-up. Similar results were observed in effect modification by Taq1. CONCLUSIONS: This study suggests that subjects with the minor frequency alleles of VDR Bsm1 or Taq1 may be more susceptible to cumulative lead exposure-related elevated pulse pressure.

Characterization of European ancestry nonalcoholic fatty liver disease-associated variants in individuals of African and Hispanic descent.

UNLABELLED: Nonalcoholic fatty liver disease (NAFLD) is an obesity-related condition affecting over 50% of individuals in some populations and is expected to become the number one cause of liver disease worldwide by 2020. Common, robustly associated genetic variants in/near five genes were identified for hepatic steatosis, a quantifiable component of NAFLD, in European ancestry individuals. Here we tested whether these variants were associated with hepatic steatosis in African- and/or Hispanic-Americans and fine-mapped the observed association signals. We measured hepatic steatosis using computed tomography in five African American (n = 3,124) and one Hispanic American (n = 849) cohorts. All analyses controlled for variation in age, age(2) , gender, alcoholic drinks, and population substructure. Heritability of hepatic steatosis was estimated in three cohorts. Variants in/near PNPLA3, NCAN, LYPLAL1, GCKR, and PPP1R3B were tested for association with hepatic steatosis using a regression framework in each cohort and meta-analyzed. Fine-mapping across African American cohorts was conducted using meta-analysis. African- and Hispanic-American cohorts were 33.9/37.5% male, with average age of 58.6/42.6 years and body mass index of 31.8/28.9 kg/m(2) , respectively. Hepatic steatosis was 0.20-0.34 heritable in African- and Hispanic-American families (P < 0.02 in each cohort). Variants in or near PNPLA3, NCAN, GCKR, PPP1R3B in African Americans and PNPLA3 and PPP1R3B in Hispanic Americans were significantly associated with hepatic steatosis; however, allele frequency and effect size varied across ancestries. Fine-mapping in African Americans highlighted missense variants at PNPLA3 and GCKR and redefined the association region at LYPLAL1. CONCLUSION: Multiple genetic variants are associated with hepatic steatosis across ancestries. This explains a substantial proportion of the genetic predisposition in African- and Hispanic-Americans. Missense variants in PNPLA3 and GCKR are likely functional across multiple ancestries.

SNP set association analysis for familial data.

Genome-wide association studies (GWAS) are a popular approach for identifying common genetic variants and epistatic effects associated with a disease phenotype. The traditional statistical analysis of such GWAS attempts to assess the association between each individual single-nucleotide polymorphism (SNP) and the observed phenotype. Recently, kernel machine-based tests for association between a SNP set (e.g., SNPs in a gene) and the disease phenotype have been proposed as a useful alternative to the traditional individual-SNP approach, and allow for flexible modeling of the potentially complicated joint SNP effects in a SNP set while adjusting for covariates. We extend the kernel machine framework to accommodate related subjects from multiple independent families, and provide a score-based variance component test for assessing the association of a given SNP set with a continuous phenotype, while adjusting for additional covariates and accounting for within-family correlation. We illustrate the proposed method using simulation studies and an application to genetic data from the Genetic Epidemiology Network of Arteriopathy (GENOA) study.

Association of the vitamin D metabolism gene CYP24A1 with coronary artery calcification.

OBJECTIVE: 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 comprising 697 Amish subjects, and SNPs nominally associated with CAC quantity (4 SNPs in CYP24A1, P=0.008 to 0.00003) were then tested for association with CAC quantity in 2 independent cohorts of subjects of white European ancestry (Genetic Epidemiology Network of Arteriopathy study [n=916] and the Penn Coronary Artery Calcification sample [n=2061]). One of the 4 SNPs, rs2762939, was associated with CAC quantity in both the Genetic Epidemiology Network of Arteriopathy (P=0.007) and Penn Coronary Artery Calcification (P=0.01) studies. In all 3 populations, the rs2762939 C allele was associated with lower CAC quantity. Metaanalysis for the association of this SNP with CAC quantity across all 3 studies yielded a P value of 2.9×10(-6). CONCLUSIONS: A common SNP in the CYP24A1 gene was associated with CAC quantity in 3 independent populations. This result suggests a role for vitamin D metabolism in the development of CAC quantity.

Quantitative proteomic analysis of ribosomal protein L35b mutant of Saccharomyces cerevisiae.

Recent studies have revealed that in higher eukaryotes, several ribosomal proteins are involved in some pathological events or developmental defects, indicating that ribosomal proteins perform unconventional functions other than protein biosynthesis. To obtain an insight into the novel roles of ribosomal proteins, we aimed to analyze the changes in proteome expression in ribosomal protein mutants by using Saccharomyces cerevisiae as a model system. We introduced the rpl35bDelta mutation into the 4159 green fluorescent protein (GFP)-tagged yeast strains by using the synthetic genetic array (SGA) method, and performed quantitative proteomic analysis by using a multilabel microplate reader and flow cytometer. We identified 22 upregulated and 20 downregulated proteins in the rpl35bDelta mutant. These proteins were primarily classified into the Gene Ontology (GO) categories of cellular biosynthetic process, translation, protein or nucleotide metabolic process, cell wall organization and biogenesis, and hyperosmotic response. We also investigated the correlation between the mRNA and protein levels of the identified proteins. Our results show that a ribosomal protein mutation can lead to perturbation in the expression of several proteins, including some other ribosomal proteins. Furthermore, our approach of combining a library of GFP-tagged yeast strains and the SGA method provides an effective and highly sensitive method for dynamic analysis of the effects of various mutations on proteome expression.