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      Disparities in allele frequencies and population differentiation for 101 disease-associated single nucleotide polymorphisms between Puerto Ricans and non-Hispanic whites

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          Abstract

          Background

          Variations in gene allele frequencies can contribute to differences in the prevalence of some common complex diseases among populations. Natural selection modulates the balance in allele frequencies across populations. Population differentiation (F ST) can evidence environmental selection pressures. Such genetic information is limited in Puerto Ricans, the second largest Hispanic ethnic group in the US, and a group with high prevalence of chronic disease. We determined allele frequencies and population differentiation for 101 single nucleotide polymorphisms (SNPs) in 30 genes involved in major metabolic and disease-relevant pathways in Puerto Ricans (n = 969, ages 45–75 years) and compared them to similarly aged non-Hispanic whites (NHW) (n = 597).

          Results

          Minor allele frequency (MAF) distributions for 45.5% of the SNPs assessed in Puerto Ricans were significantly different from those of NHW. Puerto Ricans carried risk alleles in higher frequency and protective alleles in lower frequency than NHW. Patterns of population differentiation showed that Puerto Ricans had SNPs with exceptional F ST values in intronic, non-synonymous and promoter regions. NHW had exceptional F ST values in intronic and promoter region SNPs only.

          Conclusion

          These observations may serve to explain and broaden studies on the impact of gene polymorphisms on chronic diseases affecting Puerto Ricans.

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          Most cited references67

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          Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease.

          Association studies offer a potentially powerful approach to identify genetic variants that influence susceptibility to common disease, but are plagued by the impression that they are not consistently reproducible. In principle, the inconsistency may be due to false positive studies, false negative studies or true variability in association among different populations. The critical question is whether false positives overwhelmingly explain the inconsistency. We analyzed 301 published studies covering 25 different reported associations. There was a large excess of studies replicating the first positive reports, inconsistent with the hypothesis of no true positive associations (P < 10(-14)). This excess of replications could not be reasonably explained by publication bias and was concentrated among 11 of the 25 associations. For 8 of these 11 associations, pooled analysis of follow-up studies yielded statistically significant replication of the first report, with modest estimated genetic effects. Thus, a sizable fraction (but under half) of reported associations have strong evidence of replication; for these, false negative, underpowered studies probably contribute to inconsistent replication. We conclude that there are probably many common variants in the human genome with modest but real effects on common disease risk, and that studies using large samples will convincingly identify such variants.
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            The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes.

            Genetic association studies are viewed as problematic and plagued by irreproducibility. Many associations have been reported for type 2 diabetes, but none have been confirmed in multiple samples and with comprehensive controls. We evaluated 16 published genetic associations to type 2 diabetes and related sub-phenotypes using a family-based design to control for population stratification, and replication samples to increase power. We were able to confirm only one association, that of the common Pro12Ala polymorphism in peroxisome proliferator-activated receptor-gamma(PPARgamma) with type 2 diabetes. By analysing over 3,000 individuals, we found a modest (1.25-fold) but significant (P=0.002) increase in diabetes risk associated with the more common proline allele (85% frequency). Moreover, our results resolve a controversy about common variation in PPARgamma. An initial study found a threefold effect, but four of five subsequent publications failed to confirm the association. All six studies are consistent with the odds ratio we describe. The data implicate inherited variation in PPARgamma in the pathogenesis of type 2 diabetes. Because the risk allele occurs at such high frequency, its modest effect translates into a large population attributable risk-influencing as much as 25% of type 2 diabetes in the general population.
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              A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity.

              The peroxisome proliferator-activated receptor-gamma (PPARgamma) is a transcription factor that has a pivotal role in adipocyte differentiation and expression of adipocyte-specific genes. The PPARgamma1 and gamma2 isoforms result from alternative splicing and have ligand-dependent and -independent activation domains. PPARgamma2 has an additional 28 amino acids at its amino terminus that renders its ligand-independent activation domain 5-10-fold more effective than that of PPARgamma1. Insulin stimulates the ligand-independent activation of PPARgamma1 and gamma2 (ref. 5), however, obesity and nutritional factors only influence the expression of PPARgamma2 in human adipocytes. Here, we report that a relatively common Pro12Ala substitution in PPARgamma2 is associated with lower body mass index (BMI; P=0.027; 0.015) and improved insulin sensitivity among middle-aged and elderly Finns. A significant odds ratio (4.35, P=0.028) for the association of the Pro/Pro genotype with type 2 diabetes was observed among Japanese Americans. The PPARgamma2 Ala allele showed decreased binding affinity to the cognate promoter element and reduced ability to transactivate responsive promoters. These findings suggest that the PPARgamma2 Pro12Ala variant may contribute to the observed variability in BMI and insulin sensitivity in the general population.
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                Author and article information

                Journal
                BMC Genet
                BMC Genetics
                BioMed Central
                1471-2156
                2009
                14 August 2009
                : 10
                : 45
                Affiliations
                [1 ]Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
                [2 ]Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
                [3 ]Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
                [4 ]Genome Biology and Cell Circuits Program, Broad Institute, Cambridge, MA, USA
                [5 ]Department of Epidemiology, University of Alabama, Birmingham, Birmingham, AL, USA
                [6 ]Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
                Article
                1471-2156-10-45
                10.1186/1471-2156-10-45
                2734553
                19682384
                cabb93a1-7346-4cb6-b884-63da2f593045
                Copyright © 2009 Mattei et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 2 January 2009
                : 14 August 2009
                Categories
                Research Article

                Genetics
                Genetics

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