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Background: Coronary artery calcified atherosclerotic plaque (CAC) predicts cardiovascular disease (CVD). Despite exposure to more severe conventional CVD risk factors, African Americans (AAs) are less likely to develop CAC, and when they do, have markedly lower levels than European Americans. Genetic factors likely contribute to the observed ethnic differences. To identify genes associated with CAC in AAs with type 2 diabetes (T2D), a genome-wide association study (GWAS) was performed using the Illumina 5 M chip in 691 African American-Diabetes Heart Study participants (AA-DHS), with replication in 205 Jackson Heart Study (JHS) participants with T2D. Genetic association tests were performed on the genotyped and 1000 Genomes-imputed markers separately for each study, and combined in a meta-analysis. Results: Single nucleotide polymorphisms (SNPs), rs11353135 (2q22.1), rs16879003 (6p22.3), rs5014012, rs58071836 and rs10244825 (all on chromosome 7), rs10918777 (9q31.2), rs13331874 (16p13.3) and rs4459623 (18q12.1) were associated with presence and/or quantity of CAC in the AA-DHS and JHS, with meta-analysis p-values =8.0 × 10-7. The strongest result in AA-DHS alone was rs6491315 in the 13q32.1 region (parameter estimate (SE) = -1.14 (0.20); p-value =9.1 ×10-9). This GWAS peak replicated a previously reported AA-DHS CAC admixture signal (rs7492028, LOD score 2.8). Conclusions: Genetic association between SNPs on chromosomes 2, 6, 7, 9, 16 and 18 and CAC were detected in AAs with T2D from AA-DHS and replicated in the JHS. These data support a role for genetic variation on these chromosomes as contributors to CAC in AAs with T2D, as well as to variation in CAC between populations of African and European ancestry. [ABSTRACT FROM AUTHOR]

Background: Despite ethnic disparities in lipid profiles, there are few genome-wide association studies investigating genetic variation of lipids in non-European ancestry populations. In this study, we present findings from genetic association analyses for total cholesterol, low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), and triglycerides in a large Hispanic/Latino cohort in the U.S., the Hispanic Community Health Study / Study of Latinos (HCHS/SOL). Methods: We estimated a heritability of approximately 20% for each lipid trait, similar to previous estimates in Europeans. To search for novel lipid loci, we performed conditional association analysis in which the statistical model was adjusted for previously reported SNPs associated with any of the four lipid traits. SNPs that remained genome-wide significant (P < 5 × 10-8) after conditioning on known loci were evaluated for replication. Results: We identified eight potentially novel lipid signals with minor allele frequencies <1%, none of which replicated. We tested previously reported SNP-trait associations for generalization to Hispanics/Latinos via a statistical framework. The generalization analysis revealed that approximately 50% of previously established lipid variants generalize to HCHS/SOL based on directional FDR r-value < 0.05. Some failures to generalize were due to lack of power. Conclusions: These results demonstrate that many loci associated with lipid levels are shared across populations. [ABSTRACT FROM AUTHOR]

Background: The presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample. Results: A fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy. Conclusions: The identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations. [ABSTRACT FROM AUTHOR]

Background: Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease among children, the etiology of which involves a strong genetic component, but much of the underlying genetic determinants still remain unknown. Our aim was to identify novel genetic variants that predispose to JIA. Methods: We performed a genome-wide association study (GWAS) and replication in a total of 1166 JIA cases and 9500 unrelated controls of European ancestry. Correlation of SNP genotype and gene expression was investigated. Then we conducted targeted resequencing of a candidate locus, among a subset of 480 cases and 480 controls. SUM test was performed to evaluate the association of the identified rare functional variants. Results: The CXCR4 locus on 2q22.1 was found to be significantly associated with JIA, peaking at SNP rs953387. However, this result is subjected to subpopulation stratification within the subjects of European ancestry. After adjusting for principal components, nominal significant association remained (p < 10-4). Because of its interesting known function in immune regulation, we carried out further analyses to assess its relationship with JIA. Expression of CXCR4 was correlated with CXCR4 rs953387 genotypes in lymphoblastoid cell lines (p = 0.014) and T-cells (p = 0.0054). In addition, rare non-synonymous and stop-gain sequence variants in CXCR4, putatively damaging for CXCR4 function, were significantly enriched in JIA cases (p = 0.015). Conclusion: Our results suggest the association of CXCR4 variants with JIA, implicating that this gene may be involved in the pathogenesis of autoimmune disease. However, because this locus is subjected to population stratification within the subjects of European ancestry, additional replication is still necessary for this locus to be considered a true risk locus for JIA. This cell-surface chemokine receptor has already been targeted in other diseases and may serve as a tractable therapeutic target for a specific subset of pediatric arthritis patients with additional replication and functional validation of the locus. [ABSTRACT FROM AUTHOR]

Background: Clinically distinct autoimmune phenotypes share genetic susceptibility factors. We investigated the prevalence of familial autoimmunity among subjects with juvenile idiopathic arthritis (JIA), childhood systemic lupus erythematosus (cSLE) and juvenile dermatomyositis (JDM) in the CARRA Registry, the largest multicenter observational Registry for pediatric rheumatic disease. Methods: Children with JIA, cSLE and JDM enrolled in the CARRA Registry between May 2010 and May 2012 were investigated for differences in proportion of subjects who had first-degree relatives (FDR) with autoimmunity. If a significant difference was detected, pairwise comparisons, adjusted for multiple comparisons, were made. Results: There were 4677 JIA, 639 cSLE and 440 JDM subjects. The proportion of subjects having FDR with any autoimmune disease in the JDM group (20.5%) was less compared to subjects with JIA (31.8%, p < 0.001) or SLE (31.9%; p < 0.001). Significantly greater proportion of JIA cases had FDR with inflammatory arthritis (13%) compared to cSLE (9.2%, p = 0.007) or JDM (4.3%, p <0.001). Significantly greater proportion of cSLE cases had FDR with SLE (11.1% vs. 1.7% for JIA and 1.1% for JDM p < 0.001) or type-I diabetes (7.4% for cSLE vs. 3.1% for JIA and 3.0% for JDM p < 0.001). Conclusion: Higher proportions of subjects with JIA and cSLE have FDR with autoimmunity compared to those of JDM. Relatives of cSLE cases had an increased prevalence of SLE, and relatives of JIA cases were enriched for inflammatory arthropathies demonstrating distinct patterns of familial autoimmunity among these phenotypes. [ABSTRACT FROM AUTHOR]

Background Type 2 diabetes mellitus (T2DM) is a major cardiovascular disease (CVD) risk factor. Identification of genetic risk factors for CVD is important to understand disease risk. Two recent genome-wide association study (GWAS) meta-analyses in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium detected CVD-associated loci. Methods Variants identified in CHARGE were tested for association with CVD phenotypes, including vascular calcification, and conventional CVD risk factors, in the Diabetes Heart Study (DHS) (n = 1208; >80% T2DM affected). This included 36 genotyped or imputed single nucleotide polymorphisms (SNPs) from DHS GWAS data. 28 coding SNPs from 14 top CHARGE genes were also identified from exome sequencing resources and genotyped, along with 209 coding variants from the Illumina HumanExome BeadChip genotype data in the DHS were also tested. Genetic risk scores (GRS) were calculated to evaluate the association of combinations of variants with CVD measures. Results After correction for multiple comparisons, none of the CHARGE SNPs were associated with vascular calcification (p < 0.0014). Multiple SNPs showed nominal significance with calcification, including rs599839 (PSRC1, p = 0.008), rs646776 (CELSR2, p = 0.01), and rs17398575 (PIK3CG, p = 0.009). Additional COL4A2 and CXCL12 SNPs were nominally associated with all-cause or CVD-cause mortality. Three SNPs were significantly or nominally associated with serum lipids: rs3135506 (Ser19Trp, APOA5) with triglycerides (TG) (p = 5x10-5), LDL (p = 0.00070), and nominally with high density lipoprotein (HDL) (p = 0.0054); rs651821 (5'UTR, APOA5) with increased TGs (p = 0.0008); rs13832449 (splice donor, APOC3) associated with decreased TGs (p = 0.0015). Rs45456595 (CDKN2A, Gly63Arg), rs5128 (APOC3, 3'UTR), and rs72650673 (SH2B3, Glu400Lys) were nominally associated with history of CVD, subclinical CVD, or CVD risk factors (p < 0.010). From the exome chip, rs3750103 (CHN2, His204Arg/His68Arg) with carotid intima-medial thickness (IMT) (p = 3.9X10-5), and rs61937878 (HAL, Val549Met) with infra-renal abdominal aorta CP (AACP) (p = 7.1X10-5). The unweighted GRS containing coronary artery calcified plaque (CAC) SNPs was nominally associated with history of prior CVD (p = 0.033; OR = 1.09). The weighted GRS containing SNPs was associated with CAC and myocardial infarction (MI) was associated with history of MI (p = 0.026; OR = 1.15). Conclusions Genetic risk factors for subclinical CVD in the general population (CHARGE) were modestly associated with T2DM-related risk factors and CVD outcomes in the DHS. [ABSTRACT FROM AUTHOR]

Background: Patients with type 2 diabetes (T2D) are at elevated risk for cardiovascular disease (CVD) events and mortality. Recent studies have assessed the impact of genetic variants affecting high-density lipoprotein cholesterol (HDL) concentrations on CVD risk in the general population. This study examined the utility of HDL-associated single nucleotide polymorphisms (SNPs) for CVD risk prediction in European Americans with T2D enrolled in the Diabetes Heart Study (DHS). Methods: Genetic risk scores (GRS) of HDL-associated SNPs were constructed and evaluated for potential associations with mortality and with coronary artery calcified atherosclerotic plaque (CAC), a measure of subclinical CVD strongly associated with CVD events and mortality. Two sets of SNPs were used to construct GRS; while all SNPs were selected primarily for their impacts on HDL, one set of SNPs had pleiotropic effects on other lipid parameters, while the other set lacked effects on low-density lipoprotein cholesterol (LDL) or triglyceride concentrations. Results: The GRS were specifically associated with HDL concentrations (4.90 × 10-7 < p < 0.02) in models adjusted for age, sex, and body mass index (BMI), but were not associated with LDL or triglycerides. Cox proportional hazards regression analysis suggested the HDL-associated GRS had no impact on risk of CVD-mortality (0.48 < p < 0.99) in models adjusted for other known CVD risk factors. However, associations between several of the GRS and CAC were observed (3.85 × 10-4 < p < 0.03) in models adjusted for other known CVD risk factors. Conclusions: The GRS analyzed in this study provide a tool for assessment of HDL-associated SNPs and their impact on CVD risk in T2D. The observed associations between several of the GRS and CAC suggest a potential role for HDL-associated SNPs on subclinical CVD risk in patients with T2D. [ABSTRACT FROM AUTHOR]

Background: Haptoglobin (HP) is an acute phase protein that binds to freely circulating hemoglobin. HP exists as two distinct forms, HP1 and HP2. The longer HP2 form has been associated with cardiovascular (CVD) events and mortality in individuals with type 2 diabetes (T2DM). Methods: This study examined the association of HP genotypes with subclinical CVD, T2DM risk, and associated risk factors in a T2DM-enriched sample. Haptoglobin genotypes were determined in 1208 European Americans (EA) from 473 Diabetes Heart Study (DHS) families via PCR. Three promoter SNPs (rs5467, rs5470, and rs5471) were also genotyped. Results: Analyses revealed association between HP2-2 duplication and increased carotid intima-media thickness (IMT; p = 0.001). No association between HP and measures of calcified arterial plaque were observed, but the HP polymorphism was associated with triglyceride concentrations (p = 0.005) and CVD mortality (p = 0.04). We found that the HP2-2 genotype was associated with increased T2DM risk with an odds ratio (OR) of 1.49 (95% CI 1.18-1.86, p = 6.59×10-4). Promoter SNPs were not associated with any traits. Conclusions: This study suggests association between the HP duplication and IMT, triglycerides, CVD mortality, and T2DM in an EA population enriched for T2DM. Lack of association with atherosclerotic calcified plaque likely reflect differences in the pathogenesis of these CVD phenotypes. HP variation may contribute to the heritable risk for CVD complications in T2DM. [ABSTRACT FROM AUTHOR]

Background: Monocyte chemoattractant protein-1 (MCP-1) plays important roles in kidney disease susceptibility and atherogenesis in experimental models. Relationships between serum MCP-1 concentration and early nephropathy and subclinical cardiovascular disease (CVD) were assessed in African Americans (AAs) with type 2diabetes (T2D). Methods: Serum MCP-1 concentration, urine albumin: creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), and atherosclerotic calcified plaque (CP) in the coronary and carotid arteries and infrarenal aorta were measured in 479 unrelated AAs with T2D. Generalized linear models were fitted to test for associations betweenMCP-1 and urine ACR, eGFR, and CP. Results: Participants were 57% female, with mean ± SD (median) age 55.6±9.5 (55.0) years, diabetes duration 10.3±8.2 (8.0) years, urine ACR 149.7±566.7 (14.0) mg/g, CKD-EPI eGFR 92.4±23.3 (92.0) ml/min/1.73m2, MCP-1262.9±239.1 (224.4) pg/ml, coronary artery CP 280.1±633.8 (13.5), carotid artery CP 47.1±132.9 (0), and aorta CP1616.0±2864.0 (319.0). Adjusting for age, sex, smoking, HbA1c, BMI, and LDL, serum MCP-1 was positively associated with albuminuria (parameter estimate 0.0021, P=0.04) and negatively associated with eGFR (parameter estimate?0.0003, P=0.001). MCP-1 remained associated with eGFR after adjustment for urine ACR. MCP-1 levels did not correlate with the extent of CP in any vascular bed, HbA1c or diabetes duration, but were positively associated with BMI. No interaction between BMI and MCP-1 was detected on nephropathy outcomes. Conclusions: Serum MCP-1 levels are associated with eGFR and albuminuria in AAs with T2D. MCP-1 was not associated with subclinical CVD in this population. Inflammation appears to play important roles in development and/or progression of kidney disease in AAs. [ABSTRACT FROM AUTHOR]

Background: DNA from buccal brush samples is being used for high-throughput analyses in a variety of applications, but the impact of sample type on genotyping success and downstream statistical analysis remains unclear. The objective of the current study was to determine laboratory predictors of genotyping failure among buccal DNA samples, and to evaluate the successfully genotyped results with respect to analytic quality control metrics. Sample and genotyping characteristics were compared between buccal and blood samples collected in the population-based Genetic and Environmental Risk Factors for Hemorrhagic Stroke (GERFHS) study (https:// gerfhs.phs.wfubmc.edu/public/index.cfm). Results: Seven-hundred eight (708) buccal and 142 blood DNA samples were analyzed for laboratory-based and analysis metrics. Overall genotyping failure rates were not statistically different between buccal (11.3%) and blood (7.0%, p = 0.18) samples; however, both the Contrast Quality Control (cQC) rate and the dynamic model (DM) call rates were lower among buccal DNA samples (p < 0.0001). The ratio of double-stranded to total DNA (ds/total ratio) in the buccal samples was the only laboratory characteristic predicting sample success (p < 0.0001). A threshold of at least 34% ds/total DNA provided specificity of 98.7% with a 90.5% negative predictive value for eliminating probable failures. After genotyping, median sample call rates (99.1% vs. 99.4%, p < 0.0001) and heterozygosity rates (25.6% vs. 25.7%, p = 0.006) were lower for buccal versus blood DNA samples, respectively, but absolute differences were small. Minor allele frequency differences from HapMap were smaller for buccal than blood samples, and both sample types demonstrated tight genotyping clusters, even for rare alleles. Conclusions: We identified a buccal sample characteristic, a ratio of ds/total DNA <34%, which distinguished buccal DNA samples likely to fail high-throughput genotyping. Applying this threshold, the quality of final genotyping resulting from buccal samples is somewhat lower, but compares favorably to blood. Caution is warranted if cases and controls have different sample types, but buccal samples provide comparable results to blood samples in large-scale genotyping analyses. [ABSTRACT FROM AUTHOR]

Background: A growing number of clinical and basic research studies have implicated immunological abnormalities as being associated with and potentially responsible for the cognitive and behavioral deficits seen in autism spectrum disorder (ASD) children. Here we test the hypothesis that immune-related gene loci are associated with ASD. Findings: We identified 2,012 genes of known immune-function via Ingenuity Pathway Analysis. Family-based tests of association were computed on the 22,904 single nucleotide polymorphisms (SNPs) from the 2,012 immunerelated genes on 1,510 trios available at the Autism Genetic Resource Exchange (AGRE) repository. Several SNPs in immune-related genes remained statistically significantly associated with ASD after adjusting for multiple comparisons. Specifically, we observed significant associations in the CD99 molecule-like 2 region (CD99L2, rs11796490, P = 4.01 × 10-06, OR = 0.68 (0.58-0.80)), in the jumonji AT rich interactive domain 2 (JARID2) gene (rs13193457, P = 2.71 × 10-06, OR = 0.61 (0.49-0.75)), and in the thyroid peroxidase gene (TPO) (rs1514687, P = 5.72 × 10-06, OR = 1.46 (1.24-1.72)). Conclusions: This study suggests that despite the lack of a general enrichment of SNPs in immune function genes in ASD children, several novel genes with known immune functions are associated with ASD. [ABSTRACT FROM AUTHOR]

Background: Arachidonic acid (AA) is a long-chain omega-6 polyunsaturated fatty acid (PUFA) synthesized from the precursor dihomo-gamma-linolenic acid (DGLA) that plays a vital role in immunity and inflammation. Variants in the Fatty Acid Desaturase (FADS) family of genes on chromosome 11q have been shown to play a role in PUFA metabolism in populations of European and Asian ancestry; no work has been done in populations of African ancestry to date. Results: In this study, we report that African Americans have significantly higher circulating levels of plasma AA (p = 1.35 × 10-48) and lower DGLA levels (p = 9.80 × 10-11) than European Americans. Tests for association in N = 329 individuals across 80 nucleotide polymorphisms (SNPs) in the Fatty Acid Desaturase (FADS) locus revealed significant association with AA, DGLA and the AA/DGLA ratio, a measure of enzymatic efficiency, in both racial groups (peak signal p = 2.85 × 10-16 in African Americans, 2.68 × 10-23 in European Americans). Ancestry-related differences were observed at an upstream marker previously associated with AA levels (rs174537), wherein, 79-82% of African Americans carry two copies of the G allele compared to only 42-45% of European Americans. Importantly, the allelic effect of the G allele, which is associated with enhanced conversion of DGLA to AA, on enzymatic efficiency was similar in both groups. Conclusions: We conclude that the impact of FADS genetic variants on PUFA metabolism, specifically AA levels, is likely more pronounced in African Americans due to the larger proportion of individuals carrying the genotype associated with increased FADS1 enzymatic conversion of DGLA to AA. [ABSTRACT FROM AUTHOR]

Background: Previously we performed a linkage scan of 638 African American affected sibling pairs (ASP) with type 2 diabetes (T2D) enriched for end-stage renal disease (ESRD). Ordered subset linkage analysis (OSA) revealed a linkage peak on chromosome 7p in the subset of families with earlier age of T2D diagnosis. Methods: We fine mapped this region by genotyping 11 additional polymorphic markers in the same ASP and investigated a total of 68 single nucleotide polymorphisms (SNPs) in functional candidate genes (GCK1, IL6, IGFBP1 and IGFBP3) for association with age of T2D diagnosis, age of ESRD diagnosis, duration of T2D to onset of ESRD, body mass index (BMI) in African American cases and T2D-ESRD in an African American case-control cohort. OSA of fine mapping markers supported linkage at 28 cM on 7p (near D7S3051) in early-onset T2D families (max. LOD = 3.61, P = 0.002). SNPs in candidate genes and 70 ancestry-informative markers (AIMs) were evaluated in 577 African American T2D-ESRD cases and 596 African American controls. Results: The most significant association was observed between ESRD age of diagnosis and SNP rs730497, located in intron 1 of the GCK1 gene (recessive T2D age-adjusted P = 0.0006). Nominal associations were observed with GCK1 SNPs and T2D age of diagnosis (BMI-adjusted P = 0.014 to 0.032). Also, one IGFBP1 and four IGFBP3 SNPs showed nominal genotypic association with T2D-ESRD (P = 0.002-0.049). After correcting for multiple tests, only rs730497 remanined significant. Conclusion: Variant rs730947 in the GCK1 gene appears to play a role in early ESRD onset in African Americans. [ABSTRACT FROM AUTHOR]

A standard multivariate principal components (PCs) method was utilized to identify clusters of variables that may be controlled by a common gene or genes (pleiotropy). Heritability estimates were obtained and linkage analyses performed on six individual traits (total cholesterol (Chol), high and low density lipoproteins, triglycerides (TG), body mass index (BMI), and systolic blood pressure (SBP)) and on each PC to compare our ability to identify major gene effects. Using the simulated data from Genetic Analysis Workshop 13 (Cohort 1 and 2 data for year 11), the quantitative traits were first adjusted for age, sex, and smoking (cigarettes per day). Adjusted variables were standardized and PCs calculated followed by orthogonal transformation (varimax rotation). Rotated PCs were then subjected to heritability and quantitative multipoint linkage analysis. The first three PCs explained 73% of the total phenotypic variance. Heritability estimates were above 0.60 for all three PCs. We performed linkage analyses on the PCs as well as the individual traits. The majority of pleiotropic and trait-specific genes were not identified. Standard PCs analysis methods did not facilitate the identification of pleiotropic genes affecting the six traits examined in the simulated data set. In addition, genes contributing 20% of the variance in traits with over 0.60 heritability estimates could not be identified in this simulated data set using traditional quantitative trait linkage analyses. Lack of identification of pleiotropic and trait-specific genes in some cases may reflect their low contribution to the traits/PCs examined or more importantly, characteristics of the sample group analyzed, and not simply a failure of the PC approach itself. [ABSTRACT FROM AUTHOR]

The Framingham Heart Study provides a unique source of longitudinal family data related to CVD risk factors. Age-stratified heritability estimates were obtained over three age groups (31-49 years, 50-60 years, and 61-79 years), reflecting the longitudinal nature of the data, for four quantitative traits. Age-adjusted heritability estimates were obtained at a single common time point for the same four quantitative traits. The importance of these groups is that they consist of the same individuals. The highest age-stratified heritability estimate (h² = 0.88 (± 0.06)) was for height in the model adjusting for gender over all three age groups. SBP gave the lowest heritability estimate (h² = 0.15 (± 0.11)) for the 70 age group in the model adjusting for gender, height, BMI, smoker, and drinker. BMI had slightly higher estimates (h² = 0.64 (± 0.11)) in the 40 age group than previously published. The highest age-adjusted heritability estimate (h² = 0.90 (± 0.06)) was for height in the model adjusting for gender. SBP gave the lowest heritability estimate (h² = 0.38 (± 0.09)) for unadjusted model. These results indicate that some common, complex traits may vary little in their genetic architecture over time and suggest that a common set of genes may be contributing to observed variation for these longitudinally collected phenotypes. [ABSTRACT FROM AUTHOR]

With the availability of longitudinal data, age-specific (stratified) or age-adjusted genetic analyses have the potential to localize different putative trait influencing loci. If age does not influence the locus-specific penetrance function within the range examined, age-stratified analyses will tend to yield comparable results for an individual trait. However, age-stratified results should vary across age strata when the locus-specific penetrance function is age dependent. In this paper, age-stratified and age-adjusted quantitative trait loci (QTL) linkage analyses were contrasted for height, weight, body mass index (BMI), and systolic blood pressure on a subset of the Framingham Heart Study. The strata comprised individuals with data present in each of three age groups: 31-49, 50-60, 61-79. Genome-wide QTL analyses were performed using SOLAR. Over all ages, a linkage signal for height was detected on chromosome 14q11.2 near marker GATA74E02A (LOD for ages 31-49 = 2.38, LOD for ages 50-60 = 1.84, LOD for ages 61-79 = 2.45). Evidence of linkage to BMI in the 31-49 age group was found on chromosome 3q22 (GATA3C02, LOD = 2.89, p = 0.0003) at the same location as the signal for weight (LOD = 3.10, p = 0.0002). Linkage was also supported on chromosome 1p22.1 for BMI (LOD = 2.21, p = 0.0014) and weight (LOD = 2.47, p = 0.0007) in the 31-49 age group. Our age-stratified results suggest that QTL that are expressed over long periods of time and affecting multiple, correlated traits may be identified using genome scan and variance-component methodology to help detect early and/or late gene expression. [ABSTRACT FROM AUTHOR]

More than 100 risk loci for rheumatoid arthritis (RA) have been identified in individuals of European and Asian descent, but the genetic basis for RA in African Americans is less well understood. We genotyped 610 African Americans with autoantibodypositive RA and 933 African American controls on the Immunochip (iChip) array. Using multivariable regression, we evaluated the association between iChip markers and the risk of RA and radiographic severity. The single nucleotide polymorphism (SNP) rs1964995 (odds ratio = 1.97, p = 1.28 × 10–15) near HLA-DRB1 was the most strongly associated risk SNP for RA susceptibility; SNPs in AFF3, TNFSF11 and TNFSF18 loci were suggestively associated (10–4 < p < 3.1 × 10–6). Trans-ethnic fine mapping of AFF3 identified a 90% credible set containing previously studied variants, including rs9653442, rs7608424 and rs6712515, as well as the novel candidate variant rs11681966; several of these likely influence AFF3 gene expression level. Variants in TNFRSF9, CTLA4, IL2RA, C5/TRAF1 and ETS1 – but no variants within the major histocompatibility complex – were associated with RA radiographic severity. Conditional regression and pairwise linkage disequilibrium (LD) analyses suggest that additional pathogenic variants may be found in ETS1 and IL2RA beyond those found in other ethnicities. In summary, we used the dense genotyping of the iChip array and the unique LD structure of African Americans to validate known risk loci for RA susceptibility and radiographic severity, and to better characterize the associations of AFF3, ETS1 and IL2RA. [ABSTRACT FROM AUTHOR]

Background: Fibrotic idiopathic interstitial pneumonias (fIIP) are a group of fatal lung diseases with largely unknown etiology and without definitive treatment other than lung transplant to prolong life. There is strong evidence for the importance of both rare and common genetic risk alleles in familial and sporadic disease. We have previously used genome-wide single nucleotide polymorphism data to identify 10 risk loci for fIIP. Here we extend that work to imputed genome-wide genotypes and conduct new RNA sequencing studies of lung tissue to identify and characterize new fIIP risk loci., Results: We performed genome-wide genotype imputation association analyses in 1616 non-Hispanic white (NHW) cases and 4683 NHW controls followed by validation and replication (878 cases, 2017 controls) genotyping and targeted gene expression in lung tissue. Following meta-analysis of the discovery and replication populations, we identified a novel fIIP locus in the HLA region of chromosome 6 (rs7887 P meta  = 3.7 × 10(-09)). Imputation of classic HLA alleles identified two in high linkage disequilibrium that are associated with fIIP (DRB1*15:01 P = 1.3 × 10(-7) and DQB1*06:02 P = 6.1 × 10(-8)). Targeted RNA-sequencing of the HLA locus identified 21 genes differentially expressed between fibrotic and control lung tissue (Q < 0.001), many of which are involved in immune and inflammatory response regulation. In addition, the putative risk alleles, DRB1*15:01 and DQB1*06:02, are associated with expression of the DQB1 gene among fIIP cases (Q < 1 × 10(-16))., Conclusions: We have identified a genome-wide significant association between the HLA region and fIIP. Two HLA alleles are associated with fIIP and affect expression of HLA genes in lung tissue, indicating that the potential genetic risk due to HLA alleles may involve gene regulation in addition to altered protein structure. These studies reveal the importance of the HLA region for risk of fIIP and a basis for the potential etiologic role of auto-immunity in fIIP.

Background: Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted., Results: We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs., Conclusion: This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.

Background: Individuals with 1st degree relatives harboring an intracranial aneurysm (IA) are at an increased risk of IA, suggesting genetic variation is an important risk factor., Methods: Families with multiple members having ruptured or unruptured IA were recruited and all available medical records and imaging data were reviewed to classify possible IA subjects as definite, probable or possible IA or not a case. A 6 K SNP genome screen was performed in 333 families, representing the largest linkage study of IA reported to date. A 'narrow' (n = 705 definite IA cases) and 'broad' (n = 866 definite or probable IA) disease definition were used in multipoint model-free linkage analysis and parametric linkage analysis, maximizing disease parameters. Ordered subset analysis (OSA) was used to detect gene x smoking interaction., Results: Model-free linkage analyses detected modest evidence of possible linkage (all LOD < 1.5). Parametric analyses yielded an unadjusted LOD score of 2.6 on chromosome 4q (162 cM) and 3.1 on chromosome 12p (50 cM). Significant evidence for a gene x smoking interaction was detected using both disease models on chromosome 7p (60 cM; p

In this paper, we applied the nonparametric linkage regression approach to the Caucasian genome scan data from the Collaborative Study on the Genetics of Alcoholism to search for regions of the genome that exhibit evidence for linkage to putative alcoholism-predisposing genes. The multipoint single-locus model identified four regions of the genome with LOD scores greater than one. These regions were on 7p near D7S1790 (LOD = 1.31), two regions on 7q near D7S1870 (LOD = 1.15) and D7S1799 (LOD = 1.13) and 21q near D21S1440 and D21S1446 (LOD = 1.78). Jointly modeling these loci provided stronger evidence for linkage in each of these regions (LOD = 1.58 on 7q11, LOD = 1.61 on 11q23, and LOD = 1.95 on 21q22). The evidence for linkage tended to increase among pedigrees with earlier mean age of onset at 8q23 (p = 0.0016), 14q21 (p = 0.0079), and 18p12 (p = 0.0021) and with later mean age of onset at 4q35 (p = 0.0067) and 9p22 (p = 0.0008).

This paper explores the decay of linkage disequilibrium (LD) on the autosomes and chromosome X. The extent of marker-marker LD is important for both linkage and association studies. The analysis of the Caucasian sample from the Collaborative Study on the Genetics of Alcoholism study revealed the expected negative relationship between the magnitude of the marker-marker LD and distance (cM), with the male and female subgroups exhibiting similar patterns of LD. The observed extent of LD in females was less across the pseudoautosomal markers relative to the heterosomal region of chromosome X. Marked differences in LD patterns were also observed between chromosomes X and the 22 autosomes in both males and females.