Relationship between adiposity and admixture in African-American and Hispanic-American women.

ObjectiveThe objective of this study was to investigate whether differences in admixture in African-American (AFA) and Hispanic-American (HA) adult women are associated with adiposity and adipose distribution.DesignThe proportion of European, sub-Saharan African and Amerindian admixture was estimated for AFA and HA women in the Women's Heath Initiative using 92 ancestry informative markers. Analyses assessed the relationship between admixture and adiposity indices.SubjectsThe subjects included 11 712 AFA and 5088 HA self-identified post-menopausal women.ResultsThere was a significant positive association between body mass index (BMI) and African admixture when BMI was considered as a continuous variable, and age, education, physical activity, parity, family income and smoking were included covariates (P<10(-4)). A dichotomous model (upper and lower BMI quartiles) showed that African admixture was associated with a high odds ratio (OR=3.27 (for 100% admixture compared with 0% admixture), 95% confidence interval 2.08-5.15). For HA, there was no association between BMI and admixture. In contrast, when waist-to-hip ratio (WHR) was used as a measure of adipose distribution, there was no significant association between WHR and admixture in AFA but there was a strong association in HA (P<10(-4); OR Amerindian admixture=5.93, confidence interval=3.52-9.97).ConclusionThese studies show that: (1) African admixture is associated with BMI in AFA women; (2) Amerindian admixture is associated with WHR but not BMI in HA women; and (3) it may be important to consider different measurements of adiposity and adipose distribution in different ethnic population groups

A Common Variant in CLDN14 is Associated with Primary Biliary Cirrhosis and Bone Mineral Density.

Primary biliary cirrhosis (PBC), a chronic autoimmune liver disease, has been associated with increased incidence of osteoporosis. Intriguingly, two PBC susceptibility loci identified through genome-wide association studies are also involved in bone mineral density (BMD). These observations led us to investigate the genetic variants shared between PBC and BMD. We evaluated 72 genome-wide significant BMD SNPs for association with PBC using two European GWAS data sets (n = 8392), with replication of significant findings in a Chinese cohort (685 cases, 1152 controls). Our analysis identified a novel variant in the intron of the CLDN14 gene (rs170183, Pfdr = 0.015) after multiple testing correction. The three associated variants were followed-up in the Chinese cohort; one SNP rs170183 demonstrated consistent evidence of association in diverse ethnic populations (Pcombined = 2.43 × 10(-5)). Notably, expression quantitative trait loci (eQTL) data revealed that rs170183 was correlated with a decline in CLDN14 expression in both lymphoblastoid cell lines and T cells (Padj = 0.003 and 0.016, respectively). In conclusion, our study identified a novel PBC susceptibility variant that has been shown to be strongly associated with BMD, highlighting the potential of pleiotropy to improve gene discovery

Localization of insulin-2 (Ins-2) and the obesity mutant tubby (tub) to distinct regions of mouse chromosome 7

A DNA mapping panel derived from an interspecific backcross was used to position the mouse insulin-2 locus (Ins-2) on Chromosome 7, near H19 (0/114 recombinants) and Th (1/114 recombinants). Ins-2 is part of a human-mouse conserved linkage group that includes Th, H19, and Igf-2. Analysis of segregation in the F2 generation from the cross C57BL/6J-tub/tub x CAST/Ei demonstrated that Ins-2 and the obesity mutant tubby (tub) are distinct loci, thus eliminating Ins-2 as a candidate gene for tub. These results also refine the estimated genetic distance between tub and Hbb to 2.4 [plus-or-minus sign] 1.4 cM. The predicted location for a human homolog of tubby is HSA 11p15.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29864/1/0000212.pd

Data for Genetic Analysis Workshop 16 Problem 1, Association Analysis of Rheumatoid Arthritis Data

For Genetic Analysis Workshop 16 Problem 1, we provided data for genome-wide association analysis of rheumatoid arthritis. Single-nucleotide polymorphism (SNP) genotype data were provided for 868 cases and 1194 controls that had been assayed using an Illumina 550 k platform. In addition, phenotypic data were provided from genotyping DRB1 alleles, which were classified according to the rheumatoid arthritis shared epitope, levels of anti-cyclic citrullinated peptide, and levels of rheumatoid factor IgM. Several questions could be addressed using the data, including analysis of genetic associations using single SNPs or haplotypes, as well as gene-gene and genetic analysis of SNPs for qualitative and quantitative factors

An ancestry informative marker set for determining continental origin: validation and extension using human genome diversity panels

<p>Abstract</p> <p>Background</p> <p>Case-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs that were designed as a tool for ascertaining the origins of subjects from Europe, Sub-Saharan Africa, Americas, and East Asia.</p> <p>Results</p> <p>In this study, genotypes from Human Genome Diversity Panel populations were used to further evaluate a 93 SNP AIM panel, a subset of the 128 AIMS set, for distinguishing continental origins. Using both model-based and relatively model-independent methods, we here confirm the ability of this AIM set to distinguish diverse population groups that were not previously evaluated. This study included multiple population groups from Oceana, South Asia, East Asia, Sub-Saharan Africa, North and South America, and Europe. In addition, the 93 AIM set provides population substructure information that can, for example, distinguish Arab and Ashkenazi from Northern European population groups and Pygmy from other Sub-Saharan African population groups.</p> <p>Conclusion</p> <p>These data provide additional support for using the 93 AIM set to efficiently identify continental subject groups for genetic studies, to identify study population outliers, and to control for admixture in association studies.</p

Analysis of East Asia Genetic Substructure Using Genome-Wide SNP Arrays

Accounting for population genetic substructure is important in reducing type 1 errors in genetic studies of complex disease. As efforts to understand complex genetic disease are expanded to different continental populations the understanding of genetic substructure within these continents will be useful in design and execution of association tests. In this study, population differentiation (Fst) and Principal Components Analyses (PCA) are examined using >200 K genotypes from multiple populations of East Asian ancestry. The population groups included those from the Human Genome Diversity Panel [Cambodian, Yi, Daur, Mongolian, Lahu, Dai, Hezhen, Miaozu, Naxi, Oroqen, She, Tu, Tujia, Naxi, Xibo, and Yakut], HapMap [ Han Chinese (CHB) and Japanese (JPT)], and East Asian or East Asian American subjects of Vietnamese, Korean, Filipino and Chinese ancestry. Paired Fst (Wei and Cockerham) showed close relationships between CHB and several large East Asian population groups (CHB/Korean, 0.0019; CHB/JPT, 00651; CHB/Vietnamese, 0.0065) with larger separation with Filipino (CHB/Filipino, 0.014). Low levels of differentiation were also observed between Dai and Vietnamese (0.0045) and between Vietnamese and Cambodian (0.0062). Similarly, small Fst's were observed among different presumed Han Chinese populations originating in different regions of mainland of China and Taiwan (Fst's <0.0025 with CHB). For PCA, the first two PC's showed a pattern of relationships that closely followed the geographic distribution of the different East Asian populations. PCA showed substructure both between different East Asian groups and within the Han Chinese population. These studies have also identified a subset of East Asian substructure ancestry informative markers (EASTASAIMS) that may be useful for future complex genetic disease association studies in reducing type 1 errors and in identifying homogeneous groups that may increase the power of such studies