Circulating adiponectin has been associated with both clinical and subclinical cardiovascular disease (CVD). Variants of the adiponectin gene (ADIPOQ) are associated with clinical CVD, but little is known about associations with subclinical CVD. We studied the association of 11 ADIPOQ SNPs with common and internal carotid intima media thickness (cIMT), presence of coronary artery calcification (CAC), and CAC scores (in those with CAC) in 2847 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Participants were Caucasian (n=712), African-American (n=712), Chinese (n=718), and Hispanic (n=705). All models were adjusted for age, sex, and field site, and stratified by race/ethnic group. African-Americans with genotypes AG/GG of rs2241767 had 36% greater (95% CI (16%, 59%), p=0.0001) CAC prevalence; they also had a larger common cIMT (p=0.0043). Also in African-Americans, genotypes AG/AA of rs1063537 were associated with a 35% (95% CI (14%, 59%), p=0.0005) greater CAC prevalence. Hispanics with the AA genotype of rs11711353 had a 37% (95% CI (14%, 66%), p=0.0011), greater CAC prevalence compared to those with the GG genotype. Additional adjustment for ancestry in African-American and Hispanic participants did not change the results. No single SNP was associated with subclinical CVD phenotypes in Chinese or Caucasian participants. There appears to be an association between ADIPOQ SNPs and subclinical CVD in African-American and Hispanics. Replication as well as assessment of other ADIPOQ SNPs appears warranted.

A recent large-scale meta-analysis of genome-wide studies has identified 95 loci, 59 of them novel, as statistically significant predictors of blood lipid traits; we tested whether the same loci explain the observed heterogeneity in response to lipid-lowering therapy with fenofibrate. Using data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, n = 861) we fit linear mixed models with the genetic markers as predictors and high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, total cholesterol, and triglyceride concentrations as outcomes. For all four traits, we analyzed both baseline levels and changes in response to treatment with fenofibrate. For the markers that were significantly associated with fenofibrate response, we fit additional models evaluating potential epistatic interactions. All models were adjusted for age, sex, and study center as fixed effects, and pedigree as a random effect. Statistically significant associations were observed between the rs964184 polymorphism near APOA1 (P-value≤0.0001) and fenofibrate response for HDL and triglycerides. The association was replicated in the Pharmacogenetics of Hypertriglyceridemia in Hispanics study (HyperTG, n = 267). Suggestive associations with fenofibrate response were observed for markers in or near PDE3A, MOSC1, FLJ36070, CETP, the APOE-APOC1-APOC4-APOC2, and CILP2. Finally, we present strong evidence for epistasis (P-value for interaction =  0.0006 in GOLDN, 0.05 in HyperTG) between rs10401969 near CILP2 and rs4420638 in the APOE-APOC1-APOC4-APOC2 cluster with total cholesterol response to fenofibrate. In conclusion, we present evidence linking several novel and biologically relevant genetic polymorphisms to lipid lowering drug response, as well as suggesting novel gene-gene interactions in fenofibrate pharmacogenetics.

We developed a multinomial ordinal probit model with singular value decomposition for testing a large number of single nucleotide polymorphisms SNPs simultaneously for association with multidisease status when sample size is much smaller than the number of SNPs. The validity and performance of the method was evaluated via simulation. We applied the method to our real study sample recruited through the Mexican-American Coronary Artery Disease study. We found 3 genes SORCS1, AMPD1, and PPARα to be associated with the development of both IGT and IFG, while 5 genes AMPD2, PRKAA2, C5, TCF7L2, and ITR with the IGT mechanism only and 6 genes CAPN10, IL4, NOS3, CD14, GCG, and SORT1 with the IFG mechanism only. These data suggest that IGT and IFG may indicate different physiological mechanism to prediabetes, via different genetic determinants.

Background

Diabetic nephropathy (DN) is a leading cause of mortality and morbidity in patients with type 1 and type 2 diabetes. The multicenter FIND consortium aims to identify genes for DN and its associated quantitative traits, e.g. the urine albumin:creatinine ratio (ACR). Herein, the results of whole-genome linkage analysis and a sparse association scan for ACR and a dichotomous DN phenotype are reported in diabetic individuals.

Methods

A genomewide scan comprising more than 5,500 autosomal single nucleotide polymorphism markers (average spacing of 0.6 cM) was performed on 1,235 nuclear and extended pedigrees (3,972 diabetic participants) ascertained for DN from African-American (AA), American-Indian (AI), European-American (EA) and Mexican-American (MA) populations.

Results

Strong evidence for linkage to DN was detected on chromosome 6p (p = 8.0 × 10−5, LOD = 3.09) in EA families as well as suggestive evidence for linkage to chromosome 7p in AI families. Regions on chromosomes 3p in AA, 7q in EA, 16q in AA and 22q in MA displayed suggestive evidence of linkage for urine ACR. The linkage peak on chromosome 22q overlaps the MYH9/APOL1 gene region, previously implicated in AA diabetic and nondiabetic nephropathies.

Conclusion

These results strengthen the evidence for previously identified genomic regions and implicate several novel loci potentially involved in the pathogenesis of DN.

Using ∼60,000 SNPs selected for minimal linkage disequilibrium, we perform population structure analysis of 1,374 unrelated Hispanic individuals from the Multi-Ethnic Study of Atherosclerosis (MESA), with self-identification corresponding to Central America (n = 93), Cuba (n = 50), the Dominican Republic (n = 203), Mexico (n = 708), Puerto Rico (n = 192), and South America (n = 111). By projection of principal components (PCs) of ancestry to samples from the HapMap phase III and the Human Genome Diversity Panel (HGDP), we show the first two PCs quantify the Caucasian, African, and Native American origins, while the third and fourth PCs bring out an axis that aligns with known South-to-North geographic location of HGDP Native American samples and further separates MESA Mexican versus Central/South American samples along the same axis. Using k-means clustering computed from the first four PCs, we define four subgroups of the MESA Hispanic cohort that show close agreement with self-identification, labeling the clusters as primarily Dominican/Cuban, Mexican, Central/South American, and Puerto Rican. To demonstrate our recommendations for genetic analysis in the MESA Hispanic cohort, we present pooled and stratified association analysis of triglycerides for selected SNPs in the LPL and TRIB1 gene regions, previously reported in GWAS of triglycerides in Caucasians but as yet unconfirmed in Hispanic populations. We report statistically significant evidence for genetic association in both genes, and we further demonstrate the importance of considering population substructure and genetic heterogeneity in genetic association studies performed in the United States Hispanic population.

Author Summary

Using genotype data from about 60,000 distinct genetic markers, we examined population structure in 1,374 unrelated Hispanic individuals from the Multi-Ethnic Study of Atherosclerosis (MESA), with self-identification corresponding to Central America (n = 93), Cuba (n = 50), the Dominican Republic (n = 203), Mexico (n = 708), Puerto Rico (n = 192), and South America (n = 111). By comparing genetic ancestry of MESA Hispanic participants to reference samples representing worldwide diversity, we show major differences in ancestry of MESA Hispanics reflecting their Caucasian, African, and Native American origins, with finer differences corresponding to North-South geographic origins that separate MESA Mexican versus Central/South American samples. Based on our analysis, we define four subgroups of the MESA Hispanic cohort that show close agreement with the following self-identified regions of origin: Dominican/Cuban, Mexican, Central/South American, and Puerto Rican. We examine association of triglycerides with selected genetic markers, and we further demonstrate the importance of considering differences in genetic ancestry (or factors associated with genetic ancestry) when performing genetic studies of the United States Hispanic population.

Objective

To evaluate association with polycystic ovary syndrome (PCOS) of 295 variants in 39 genes central to metabolic insulin signaling and glycogen synthase kinase-3β (GSK-3β) regulation, followed by replication efforts.

Design

Case-control association study, with discovery and replication cohorts.

Setting

Subjects were recruited from reproductive endocrinology clinics, controls were recruited from communities surrounding the University of Alabama at Birmingham and Erasmus Medical Center.

Patients

273 cases with PCOS and 173 controls in the discovery cohort; 526 cases and 3585 controls in the replication cohort. All subjects were Caucasian.

Interventions

Phenotypic and genotypic assessment.

Main Outcome Measures

295 SNPs, PCOS status.

Results

Several SNPs were associated with PCOS in the discovery cohort. Four insulin receptor (INSR) SNPs and three insulin receptor substrate 2 (IRS2) SNPs associated with PCOS (P<0.05) were genotyped in the replication cohort. One INSR SNP (rs2252673) replicated association with PCOS. The minor allele conferred increased odds of PCOS in both cohorts, independent of body mass index (BMI).

Conclusions

A pathway-based, tagging SNP approach allowed us to identify novel INSR SNPs associated with PCOS, one of which confirmed association in a large replication cohort.

Under lean conditions, the adipose-derived hormone leptin maintains energy balance in part through CNS-mediated increases in sympathetic outflow that enhance fat burning 1,2. Triggering of beta adrenergic receptors in adipocytes stimulates energy expenditure via cAMP-dependent increases in lipolysis and fatty acid oxidation 3. Although the underlying mechanism is unclear, catecholamine signaling in fat cells is thought to be disrupted in obesity 4, where it may contribute to the ectopic accumulation of lipid in liver and to the development of insulin resistance 5,6. Here we show that the cAMP responsive CREB coactivator CRTC3 promotes obesity by attenuating beta adrenergic receptor signaling in adipose; mice with a knockout of the CRTC3 gene have increased energy expenditure, are resistant to diet induced obesity, and are protected from the development of hepatic steatosis under high fat diet feeding conditions. CRTC3 was activated in response to catecholamine signals, when it reduced adenyl cyclase activity by upregulating the expression of RGS2 7–9, a metabolic syndrome susceptibility gene 10, which we show here is also a direct target of CREB and CRTC3. RGS2 expression was down-regulated in adipocytes from CRTC3−/− mice, leading to increases in insulin and catecholamine signaling that enhanced glucose and fatty acid oxidation. As a common human CRTC3 variant (Ser72Asn), with increased transcriptional activity, is associated with several anthropometric indices of adiposity in two distinct Mexican-American cohorts, our results suggest that adipocyte CRTC3 may play a role in the development of obesity in this population.

Genetic association studies usually involve a large number of single-nucleotide polymorphisms (SNPs) (k) and a relative small sample size (n), which produces the situation that k is much greater than n. Because conventional statistical approaches are unable to deal with multiple SNPs simultaneously when k is much greater than n, single-SNP association studies have been used to identify genes involved in a disease’s pathophysiology, which causes a multiple testing problem. To evaluate the contribution of multiple SNPs simultaneously to disease traits when k is much greater than n, we developed the Bayesian regression with singular value decomposition (BRSVD) method. The method reduces the dimension of the design matrix from k to n by applying singular value decomposition to the design matrix. We evaluated the model using a Markov chain Monte Carlo simulation with Gibbs sampler constructed from the posterior densities driven by conjugate prior densities. Permutation was incorporated to generate empirical p-values. We applied the BRSVD method to the sequence data provided by Genetic Analysis Workshop 17 and found that the BRSVD method is a practical method that can be used to analyze sequence data in comparison to the single-SNP association test and the penalized regression method.

The pathogenesis of polycystic ovary syndrome (PCOS) is poorly understood. PCOS-like phenotypes are produced by prenatal androgenization (PA) of female rhesus monkeys. We hypothesize that perturbation of the epigenome, through altered DNA methylation, is one of the mechanisms whereby PA reprograms monkeys to develop PCOS. Infant and adult visceral adipose tissues (VAT) harvested from 15 PA and 10 control monkeys were studied. Bisulfite treated samples were subjected to genome-wide CpG methylation analysis, designed to simultaneously measure methylation levels at 27,578 CpG sites. Analysis was carried out using Bayesian Classification with Singular Value Decomposition (BCSVD), testing all probes simultaneously in a single test. Stringent criteria were then applied to filter out invalid probes due to sequence dissimilarities between human probes and monkey DNA, and then mapped to the rhesus genome. This yielded differentially methylated loci between PA and control monkeys, 163 in infant VAT, and 325 in adult VAT (BCSVD P<0.05). Among these two sets of genes, we identified several significant pathways, including the antiproliferative role of TOB in T cell signaling and transforming growth factor-β (TGF-β) signaling. Our results suggest PA may modify DNA methylation patterns in both infant and adult VAT. This pilot study suggests that excess fetal androgen exposure in female nonhuman primates may predispose to PCOS via alteration of the epigenome, providing a novel avenue to understand PCOS in humans.

Background

Acute severe ulcerative colitis (UC) remains a significant clinical challenge and the ability to predict, at an early stage, those individuals at risk of colectomy for medically refractory UC (MR-UC) would be a major clinical advance. The aim of this study was to use a genome-wide association study (GWAS) in a well-characterized cohort of UC patients to identify genetic variation that contributes to MR-UC.

Methods

A GWAS comparing 324 MR-UC patients with 537 Non-MR-UC patients was analyzed using logistic regression and Cox proportional hazards methods. In addition, the MR-UC patients were compared with 2601 healthy controls.

Results

MR-UC was associated with more extensive disease (p= 2.7×10−6) and a positive family history of UC (p= 0.004). A risk score based on the combination of 46 SNPs associated with MR-UC explained 48% of the variance for colectomy risk in our cohort. Risk scores divided into quarters showed the risk of colectomy to be 0%, 17%, 74% and 100% in the four groups. Comparison of the MR-UC subjects with healthy controls confirmed the contribution of the major histocompatibility complex to severe UC (peak association: rs17207986, p= 1.4×10−16) and provided genome-wide suggestive association at the TNFSF15 (TL1A) locus (peak association: rs11554257, p= 1.4×10−6).

Conclusions

A SNP-based risk scoring system, identified here by GWAS analyses, may provide a useful adjunct to clinical parameters for predicting natural history in UC. Furthermore, discovery of genetic processes underlying disease severity may help to identify pathways for novel therapeutic intervention in severe UC.

Background & Aims

There is little data available from genome-wide association studies (GWAS) of liver histology in patients with non-alcoholic fatty liver disease (NAFLD). We conducted a pilot GWAS in patients with NAFLD, characterized by histology, who were enrolled in the NASH CRN Database Study.

Methods

We studied clinical, laboratory, and histological data from 236 non-Hispanic Caucasian women with NAFLD. We analyzed 324,623 single nucleotide polymorphisms (SNPs) from the 22 autosomal chromosomes. Multivariate-adjusted logistic regression analyses were conducted for binary outcomes and linear regression analysis was applied for quantitative traits. A P-value < 1×10−6 was considered to be significant.

Results

In multivariate models adjusted for age, body mass index, diabetes, waist:hip ratios, and levels of hemoglobin A1c, the NAFLD activity score was associated with the SNP rs2645424 on chromosome 8 in farnesyl diphosphate farnesyl transferase 1 (FDFT1) (P=6.8×10−7). The degree of fibrosis was associated with the SNP rs343062 on chromosome 7 (P=2.7×10−8). SNPs associated with lobular inflammation included SNP rs1227756 on chromosome 10 in COL13A1 (P=2.0×10−7), rs6591182 on chromosome 11 (P=8.6×10−7), and rs887304 on chromosome 12 in EFCAB4B (P=7.7×10−7). SNPs associated with serum levels of alanine aminotransferase included rs2499604 on chromosome 1 (P=2.2×10−6), rs6487679 on chromosome 12 in PZP (P=1.3×10−6), rs1421201 on chromosome 18 (P=1.0×10−5), and rs2710833 on chromosome 4 (P=6.3×10−7). There were no significant associations between genotypes and steatosis, ballooning degeneration, portal inflammation, or other features of NAFLD.

Conclusions

A GWAS significantly associated genetic variants with features of hepatic histology in patients with NAFLD. These findings should be validated in larger and more diverse cohorts.

Background

Fibrin fragment D-dimer is one of several peptides produced when cross-linked fibrin is degraded by plasmin, and is the most widely-used clinical marker of activated blood coagulation. To identity genetic loci influencing D-dimer levels, we performed the first large-scale, genome-wide association search.

Methods and Results

A genome-wide investigation of the genomic correlates of plasma D-dimer levels was conducted among 21,052 European-ancestry adults. Plasma levels of D-dimer were measured independently in each of 13 cohorts. Each study analyzed the association between ~2.6 million genotyped and imputed variants across the 22 autosomal chromosomes and natural-log transformed D-dimer levels using linear regression in additive genetic models adjusted for age and sex. Among all variants, 74 exceeded the genome-wide significance threshold and marked 3 regions. At 1p22, rs12029080 (p-value 6.4×10−52) was 46.0 kb upstream from F3, coagulation factor III (tissue factor). At 1q24, rs6687813 (p-value 2.4×10−14) was 79.7 kb downstream of F5, coagulation factor V. At 4q32, rs13109457 (p-value 2.9×10−18) was located between 2 fibrinogen genes: 10.4 kb downstream from FGG and 3.0 kb upstream from FGA. Variants were associated with a 0.099, 0.096, and 0.061 unit difference, respectively, in natural-log transformed D-dimer and together accounted for 1.8% of the total variance. When adjusted for non-synonymous substitutions in F5 and FGA loci known to be associated with D-dimer levels, there was no evidence of an additional association at either locus.

Conclusions

Three genes were associated with fibrin D-dimer levels, of which the F3 association was the strongest and has not been previously reported.

Family-based linkage analysis has been a powerful tool for identification of genes contributing to traits with monogenic patterns of inheritance. These approaches have been of limited utility in identification of genes underlying complex traits. In contrast, searches for common genetic variants associated with complex traits have been highly successful. It is now widely recognized that common variations frequently explain only part of the inter-individual variation in populations. ‘Rare’ genetic variants have been hypothesized to contribute significantly to phenotypic variation in the population. We have developed a combination of family-based linkage, whole-exome sequencing, direct sequencing and association methods to efficiently identify rare variants of large effect. Key to the successful application of the method was the recognition that only a few families in a sample contribute significantly to a linkage signal. Thus, a search for mutations can be targeted to a small number of families in a chromosome interval restricted to the linkage peak. This approach has been used to identify a rare (1.1%) G45R mutation in the gene encoding adiponectin, ADIPOQ. This variant explains a strong linkage signal (LOD > 8.0) and accounts for ∼17% of the variance in plasma adiponectin levels in a sample of 1240 Hispanic Americans and 63% of the variance in families carrying the mutation. Individuals carrying the G45R mutation have mean adiponectin levels that are 19% of non-carriers. We propose that rare variants may be a common explanation for linkage peaks observed in complex trait genetics. This approach is applicable to a wide range of family studies and has potential to be a discovery tool for identification of novel genes influencing complex traits.

Genetic variation in both innate and adaptive immune systems is associated with Crohn's disease (CD) susceptibility, but much of the heritability to CD remains unknown. We performed a genome-wide association study (GWAS) in 896 CD cases and 3204 healthy controls all of Caucasian origin as defined by multidimensional scaling. We found supportive evidence for 21 out of 40 CD loci identified in a recent CD GWAS meta-analysis, including two loci which had only nominally achieved replication (rs4807569, 19p13; rs991804, CCL2/CCL7). In addition, we identified associations with genes involved in tight junctions/epithelial integrity (ASHL, ARPC1A), innate immunity (EXOC2), dendritic cell biology [CADM1 (IGSF4)], macrophage development (MMD2), TGF-β signaling (MAP3K7IP1) and FUT2 (a physiological trait that regulates gastrointestinal mucosal expression of blood group A and B antigens) (rs602662, P = 3.4 × 10−5). Twenty percent of Caucasians are ‘non-secretors’ who do not express ABO antigens in saliva as a result of the FUT2 W134X allele. We demonstrated replication in an independent cohort of 1174 CD cases and 357 controls between the four primary FUT2 single nucleotide polymorphisms (SNPs) and CD (rs602662, combined P-value 4.90 × 10−8) and also association with FUT2 W143X (P = 2.6 × 10−5). Further evidence of the relevance of this locus to CD pathogenesis was demonstrated by the association of the original four SNPs and CD in the recently published CD GWAS meta-analysis (rs602662, P = 0.001). These findings strongly implicate this locus in CD susceptibility and highlight the role of the mucus layer in the development of CD.

Background/Aims

Some studies suggest that polymorphisms in angiotensin-converting enzyme (ACE), angiotensinogen (AGT), angiotensin II type I receptor (AGTR1) and angiotensin II type II receptor (AGTR2) genes may contribute to renal function variation.

Methods

Genotyping for single nucleotide polymorphisms (SNPs) in these candidate genes was performed in 2,847 participants from four racial/ethnic groups (African American, Chinese, White and Hispanic) without known cardiovascular disease in the Multi-Ethnic Study of Atherosclerosis. SNP and haplotype analyses were performed to determine associations between genotypes and cross-sectional renal function measurements, including urine albumin excretion (UAE) and estimated glomerular filtration rate (eGFR) using serum creatinine and cystatin C.

Results

Twenty-four ACE SNPs, 10 AGT SNPs, 15 AGTR1 SNPs and 6 AGTR2 SNPs were typed successfully. After adjusting for ancestry, age and gender, 3 SNPs (AGT M235T, AGT rs2148582 and AGTR1 rs2131127) showed associations with an empiric p value <0.05 with the same phenotype in multiple racial/ethnic groups, suggesting replication. The AGT M235T SNP has been shown previously to be associated with diabetic and hypertensive nephropathy. Conclusions: These data suggest that genetic polymorphisms in the renin-angiotensin system are associated with renal phenotypes in the general population, but that many associations differ across racial/ethnic groups.

Objectives

Although statins are efficacious for lowering LDL-cholesterol (LDLC), there is wide inter-individual variation in response. We tested the extent to which combined effects of common alleles of LDLR and HMGCR can contribute to this variability.

Methods and Results

Haplotypes in the LDLR 3′-untranslated region (3UTR) were tested for association with lipid-lowering response to simvastatin treatment in the Cholesterol and Pharmacogenetics (CAP) trial (335 African-Americans and 609European-Americans). LDLR haplotype 5 (L5)was associated with smaller simvastatin-induced reductions in LDLC, total cholesterol, non-HDL cholesterol, and apolipoprotein B (P=0.0002–0.03)in African-Americans, but not European-Americans. The combined presence of L5 and previously described HMGCR haplotypes in African-Americans was associated with significantly attenuated apoB reduction(−22.4±1.5% N=89) both compared to noncarriers (−30.6±1.5% N=78, P=0.0001) and to carriers of either individual haplotype (−28.2±1.1% N=158, P=0.001). We observed similar differences when measuring simvastatin-mediated induction of LDLR surface expression using lymphoblast cell lines (P=0.03).

Conclusions

We have identified a common LDLR 3UTR haplotype that is associated with attenuated lipid-lowering response to simvastatin treatment. Response was further reduced in individuals with both LDLR and previously described HMGCR haplotypes. Previously identified racial differences in statin efficacy were partially explained by increased prevalence of these combined haplotypes in African-Americans.

Serum concentrations of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with serum lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 × 10-8), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (e.g., CYP7A1, NPC1L1, and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and impact lipid traits in three non-European populations (East Asians, South Asians, and African Americans). Our results identify several novel loci associated with serum lipids that are also associated with CAD. Finally, we validated three of the novel genes—GALNT2, PPP1R3B, and TTC39B—with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Background:

Many different genetic and clinical factors have been identified as causes or contributors to atherosclerosis. We present a model of preclinical atherosclerosis based on genetic and clinical data that predicts the presence of coronary artery calcification in healthy Americans of European descent aged 45 to 84 in the Multi-Ethnic Study of Atherosclerosis (MESA).

Methods and Results:

We assessed 712 individuals for the presence or absence of coronary artery calcification, and their genotypes for 2882 single-nucleotide polymorphisms (SNPs). Using these SNPs and relevant clinical data, a Bayesian network that predicts the presence of coronary calcification was constructed. The model contains 13 SNPs (from genes AGTR1, ALOX15, INSR, PRKAB1, IL1R2, ESR2, KCNK1, FBLN5, PPARA, VEGFA, PON1, TDRD6, PLA2G7, and one ancestry informative marker) and 5 clinical variables (sex, age, weight, smoking, and diabetes) and achieves 85% predictive accuracy, as measured by area under the ROC curve (AUC). This is a significant (p < 0.001) improvement upon models using just the SNP data or using just the clinical variables.

Conclusions:

We present an investigation of joint genetic and clinical factors associated with atherosclerosis that shows predictive results for both cases, and enhanced performance for the combination.

Blood pressure (BP) is a major cardiovascular disease risk factor. To date, few variants associated with inter-individual BP variation have been identified. A genome-wide association study of systolic (SBP), diastolic BP (DBP), and hypertension in the CHARGE Consortium (n=29,136) identified 13 SNPs for SBP, 20 for DBP, and 10 for hypertension at p <4×10-7. The top 10 loci for SBP and DBP were incorporated into a risk score; mean BP and prevalence of hypertension increased in relation to number of risk alleles carried. When 10 CHARGE SNPs for each trait were meta-analyzed jointly with the Global BPgen Consortium (n=34,433), four CHARGE loci attained genome-wide significance (p<5×10-8) for SBP (ATP2B1, CYP17A1, PLEKHA7, SH2B3), six for DBP (ATP2B1, CACNB2, CSK/ULK3, SH2B3, TBX3/TBX5, ULK4), and one for hypertension (ATP2B1). Identifying novel BP genes advances our understanding of BP regulation and highlights potential drug targets for the prevention or treatment of hypertension.

DESPAIR (DESign for PAIRs) is a computer program useful for designing a two-stage linkage study using relative pairs for a dichotomous phenotype. It determines the optimal two-stage study design – i.e., for specified power and significance level, how many pairs of relatives should be studied, how many equally spaced markers should be used initially, and what criterion should be used to specify the markers around which further searching should be done at a second stage. The program will calculate either the number of relative pairs required for a given number of first-stage markers or the number of markers required for a given number of relative pairs. We highlight the use of the latest version of DESPAIR to decide to what extent additional fine mapping in a candidate region of interest can lead to an increase in power in a previous linkage study sample. We also discuss new features of the program, such as the mean difference test for affected and discordant relative pairs and estimation of full sibling pair equivalents to design a study when several types of relative pairs are available. DESPAIR is part of the S.A.G.E. program package and is freely available for use online.

Introduction

The objective of the present study was to assess heritability of clinical and radiographic features of hand osteoarthritis (OA) in affected patients and their siblings.

Methods

A convenience sample of patients with clinical and radiographic hand OA and their siblings were evaluated by examination and radiography. Radiographs were scored for hand OA features by radiographic atlas. The heritability of hand OA phenotypes was assessed for clinical and radiographic measures based on anatomic locations and radiographic characteristics. Phenotypic data were transformed to reduce non-normality, if necessary. A variance components approach was used to calculate heritability.

Results

One hundred and thirty-six probands with hand OA and their sibling(s) were enrolled. By anatomic location, the highest heritability was seen with involvement of the first interphalangeal joint (h2 = 0.63, P = 0.00004), the first carpometacarpal joint (h2 = 0.38, P = 0.01), the distal interphalangeal joints (h2 = 0.36, P = 0.02), and the proximal interphalangeal joints (h2 = 0.30, P = 0.03) with osteophytes. The number and severity of joints with osteophyte involvement was heritable overall (h2 = 0.38, P = 0.008 for number and h2 = 0.35, P = 0.01 for severity) and for all interphalangeal joints (h2 = 0.42, P = 0.004 and h2 = 0.33, P = 0.02). The severity of carpometacarpal joint involvement was also heritable (h2 = 0.53, P = 0.0006). Similar results were obtained when the analysis was limited to the Caucasian sample.

Conclusions

In a population with clinical and radiographic hand OA and their siblings, the presence of osteophytes was the most sensitive biomarker for hand OA heritability. Significant heritability was detected for anatomic phenotypes by joint location, severity of joint involvement with osteophytes as well as for overall number and degree of hand OA involvement. These findings are in agreement with the strong genetic predisposition for hand OA reported by others. The results support phenotyping based on severity of osteophytes and a joint-specific approach. More specific phenotypes may hold greater promise in the study of genetics in hand OA.

Objective

Diabetes and atherosclerosis may share common genetic determinants. A prior study in Hispanics found association of haplotypes in the diabetes gene calpain-10 (CAPN10) with carotid artery intima-media thickness (CIMT). This study sought to replicate this association in an independent cohort.

Methods

Four CAPN10 SNPs were genotyped and haplotypes determined in 487 Hispanic Americans from 143 families ascertained via an index case with hypertension. CIMT was measured from B-mode ultrasound, and glycemic traits quantified from euglycemic clamps. Association of SNPs and haplotypes with CIMT was determined.

Results

The minor alleles of SNP-56 and SNP-63 were associated with increased CIMT in dominant and additive models. The association of haplotype 1112 with increased CIMT was replicated. No associations with fasting insulin, insulin secretion, or insulin sensitivity were observed.

Conclusions

CAPN10 association with CIMT was replicated, further supporting its role as a common genetic determinant of diabetes and atherosclerosis in Hispanics.

To analyze multiple single-nucleotide polymorphisms simultaneously when the number of markers is much larger than the number of studied individuals, as is the situation we have in genome-wide association studies (GWAS), we developed the iterative Bayesian variable selection method and successfully applied it to the simulated rheumatoid arthritis data provided by the Genetic Analysis Workshop 15 (GAW15). One drawback for applying our iterative Bayesian variable selection method is the relatively long running time required for evaluation of GWAS data. To improve computing speed, we recently developed a Bayesian classification with singular value decomposition (BCSVD) method. We have applied the BCSVD method here to the rheumatoid arthritis data distributed by GAW16 Problem 1 and demonstrated that the BCSVD method works well for analyzing GWAS data.

We performed association analysis under a previous linkage peak on chromosome 16 with genome-wide single-nucleotide polymorphism (SNP) data to identify genetic variants underlying body mass index (BMI). Data from all subjects with baseline measures and a subgroup who had complete data at four selected time points from the Framingham Heart Study were analyzed. The cross-sectional measures include BMI at baseline for all subjects, as well as BMI at selected time points for the subgroup. The longitudinal measure is the within-subject mean of BMI for the subgroup at the four time points.

Association analysis was first performed using PLINK after dividing large pedigrees into nuclear families. We then followed up the identified regions by variance-components methods as implemented in SOLAR using the extended pedigrees.

The strongest evidence for associations were observed at 52.3 Mbp (PLINK p = 0.00002, QTLD p = 0.005), on the FTO gene, and at 48.1 Mbp (PLINK p = 0.002, QTLD p = 0.0006) on chromosome 16, which are directly under the previous identified linkage peak. This association was consistently observed for all samples at baseline, and for the subgroup at time point 2, 3, 4 and MEAN, both by PLINK and SOLAR. In addition, another SNP/region at 46.7 Mbp on same chromosome was found to be associated with several BMI measures in the subgroup. Fine-mapping with more markers provided further evidence for SNP association with BMI in the same region (at 52.4 Mbp, QTLD p = 0.0003).

These results suggest the existence of genes/DNA variations in these regions that contribute to BMI variation.

Genome-wide association studies usually involve several hundred thousand of single-nucleotide polymorphisms (SNPs). Conventional approaches face challenges when there are enormous number of SNPs but a relatively small number of samples and, in some cases, are not feasible. We introduce here an iterative Bayesian variable selection method that provides a unique tool for association studies with a large number of SNPs (p) but a relatively small sample size (n). We applied this method to the simulated case-control sample provided by the Genetic Analysis Workshop 15 and compared its performance with stepwise variable selection method. We demonstrated that the results of iterative Bayesian variable selection applied to when p » n are as comparable as those of stepwise variable selection implemented to when n » p. When n > p, the iterative Bayesian variable selection performs better than stepwise variable selection does.