1,446 research outputs found

    A generalized least-squares framework for rare-variant analysis in family data.

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    Rare variants may, in part, explain some of the hereditability missing in current genome-wide association studies. Many gene-based rare-variant analysis approaches proposed in recent years are aimed at population-based samples, although analysis strategies for family-based samples are clearly warranted since the family-based design has the potential to enhance our ability to enrich for rare causal variants. We have recently developed the generalized least squares, sequence kernel association test, or GLS-SKAT, approach for the rare-variant analyses in family samples, in which the kinship matrix that was computed from the high dimension genetic data was used to decorrelate the family structure. We then applied the SKAT-O approach for gene-/region-based inference in the decorrelated data. In this study, we applied this GLS-SKAT method to the systolic blood pressure data in the simulated family sample distributed by the Genetic Analysis Workshop 18. We compared the GLS-SKAT approach to the rare-variant analysis approach implemented in family-based association test-v1 and demonstrated that the GLS-SKAT approach provides superior power and good control of type I error rate

    Identifying association under a previous linkage peak on chromosome 16 for body mass index using cross-sectional and longitudinal data of the Framingham Heart Study

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    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

    Application of Bayesian classification with singular value decomposition method in genome-wide association studies

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    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

    Insulin clearance and the incidence of type 2 diabetes in Hispanics and African Americans: the IRAS Family Study.

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    ObjectiveWe aimed to identify factors that are independently associated with the metabolic clearance rate of insulin (MCRI) and to examine the association of MCRI with incident type 2 diabetes in nondiabetic Hispanics and African Americans.Research design and methodsWe investigated 1,116 participants in the Insulin Resistance Atherosclerosis Study (IRAS) Family Study with baseline examinations from 2000 to 2002 and follow-up examinations from 2005 to 2006. Insulin sensitivity (S(I)), acute insulin response (AIR), and MCRI were determined at baseline from frequently sampled intravenous glucose tolerance tests. MCRI was calculated as the ratio of the insulin dose over the incremental area under the curve of insulin. Incident diabetes was defined as fasting glucose ≥126 mg/dL or antidiabetic medication use by self-report.ResultsWe observed that S(I) and HDL cholesterol were independent positive correlates of MCRI, whereas fasting insulin, fasting glucose, subcutaneous adipose tissue, visceral adipose tissue, and AIR were independent negative correlates (all P < 0.05) at baseline. After 5 years of follow-up, 71 (6.4%) participants developed type 2 diabetes. Lower MCRI was associated with a higher risk of incident diabetes after adjusting for demographics, lifestyle factors, HDL cholesterol, indexes of obesity and adiposity, and insulin secretion (odds ratio 2.01 [95% CI 1.30-3.10], P = 0.0064, per one-SD decrease in loge-transformed MCRI).ConclusionsOur data showed that lower MCRI predicts the incidence of type 2 diabetes

    Heritability patterns in hand osteoarthritis: the role of osteophytes

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    Abstract 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 (h 2 = 0.63, P = 0.00004), the first carpometacarpal joint (h 2 = 0.38, P = 0.01), the distal interphalangeal joints (h 2 = 0.36, P = 0.02), and the proximal interphalangeal joints (h 2 = 0.30, P = 0.03) with osteophytes. The number and severity of joints with osteophyte involvement was heritable overall (h 2 = 0.38, P = 0.008 for number and h 2 = 0.35, P = 0.01 for severity) and for all interphalangeal joints (h 2 = 0.42, P = 0.004 and h 2 = 0.33, P = 0.02). The severity of carpometacarpal joint involvement was also heritable (h 2 = 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

    Genome-Wide Association Study Identifies Loci for Liver Enzyme Concentrations in Mexican Americans: The GUARDIAN Consortium.

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    ObjectivePopulations of Mexican American ancestry are at an increased risk for nonalcoholic fatty liver disease. The objective of this study was to determine whether loci in known and novel genes were associated with variation in aspartate aminotransferase (AST) (n = 3,644), alanine aminotransferase (ALT) (n = 3,595), and gamma-glutamyl transferase (GGT) (n = 1,577) levels by conducting the first genome-wide association study (GWAS) of liver enzymes, which commonly measure liver function, in individuals of Mexican American ancestry.MethodsLevels of AST, ALT, and GGT were determined by enzymatic colorimetric assays. A multi-cohort GWAS of individuals of Mexican American ancestry was performed. Single-nucleotide polymorphisms (SNP) were tested for association with liver outcomes by multivariable linear regression using an additive genetic model. Association analyses were conducted separately in each cohort, followed by a nonparametric meta-analysis.ResultsIn the PNPLA3 gene, rs4823173 (P = 3.44 × 10-10 ), rs2896019 (P = 7.29 × 10-9 ), and rs2281135 (P = 8.73 × 10-9 ) were significantly associated with AST levels. Although not genome-wide significant, these same SNPs were the top hits for ALT (P = 7.12 × 10-8 , P = 1.98 × 10-7 , and P = 1.81 × 10-7 , respectively). The strong correlation (r2  = 1.0) for these SNPs indicated a single hit in the PNPLA3 gene. No genome-wide significant associations were found for GGT.ConclusionsPNPLA3, a locus previously identified with ALT, AST, and nonalcoholic fatty liver disease in European and Japanese GWAS, is also associated with liver enzymes in populations of Mexican American ancestry

    Metabolic Syndrome Derived from Principal Component Analysis and Incident Cardiovascular Events: The Multi Ethnic Study of Atherosclerosis (MESA) and Health, Aging, and Body Composition (Health ABC).

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    Background. The NCEP metabolic syndrome (MetS) is a combination of dichotomized interrelated risk factors from predominantly Caucasian populations. We propose a continuous MetS score based on principal component analysis (PCA) of the same risk factors in a multiethnic cohort and compare prediction of incident CVD events with NCEP MetS definition. Additionally, we replicated these analyses in the Health, Aging, and Body composition (Health ABC) study cohort. Methods and Results. We performed PCA of the MetS elements (waist circumference, HDL, TG, fasting blood glucose, SBP, and DBP) in 2610 Caucasian Americans, 801 Chinese Americans, 1875 African Americans, and 1494 Hispanic Americans in the multiethnic study of atherosclerosis (MESA) cohort. We selected the first principal component as a continuous MetS score (MetS-PC). Cox proportional hazards models were used to examine the association between MetS-PC and 5.5 years of CVD events (n = 377) adjusting for age, gender, race, smoking and LDL-C, overall and by ethnicity. To facilitate comparison of MetS-PC with the binary NCEP definition, a MetS-PC cut point was chosen to yield the same 37% prevalence of MetS as the NCEP definition (37%) in the MESA cohort. Hazard ratio (HR) for CVD events were estimated using the NCEP and Mets-PC-derived binary definitions. In Cox proportional models, the HR (95% CI) for CVD events for 1-SD (standard deviation) of MetS-PC was 1.71 (1.54-1.90) (P < 0.0001) overall after adjusting for potential confounders, and for each ethnicity, HRs were: Caucasian, 1.64 (1.39-1.94), Chinese, 1.39 (1.06-1.83), African, 1.67 (1.37-2.02), and Hispanic, 2.10 (1.66-2.65). Finally, when binary definitions were compared, HR for CVD events was 2.34 (1.91-2.87) for MetS-PC versus 1.79 (1.46-2.20) for NCEP MetS. In the Health ABC cohort, in a fully adjusted model, MetS-PC per 1-SD (Health ABC) remained associated with CVD events (HR = 1.21, 95%CI 1.12-1.32) overall, and for each ethnicity, Caucasian (HR = 1.24, 95%CI 1.12-1.39) and African Americans (HR = 1.16, 95%CI 1.01-1.32). Finally, when using a binary definition of MetS-PC (cut point 0.505) designed to match the NCEP definition in terms of prevalence in the Health ABC cohort (35%), the fully adjusted HR for CVD events was 1.39, 95%CI 1.17-1.64 compared with 1.46, 95%CI 1.23-1.72 using the NCEP definition. Conclusion. MetS-PC is a continuous measure of metabolic syndrome and was a better predictor of CVD events overall and in individual ethnicities. Additionally, a binary MetS-PC definition was better than the NCEP MetS definition in predicting incident CVD events in the MESA cohort, but this superiority was not evident in the Health ABC cohort
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