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Craig D.W.,Translational Genomics Research Institute TGen | Goor R.M.,U.S. National Center for Biotechnology Information | Wang Z.,U.S. National Center for Biotechnology Information | Paschall J.,U.S. National Center for Biotechnology Information | And 4 more authors.
Nature Reviews Genetics | Year: 2011

Access to genetic data across studies is an important aspect of identifying new genetic associations through genome-wide association studies (GWASs). Meta-analysis across multiple GWASs with combined cohort sizes of tens of thousands of individuals often uncovers many more genome-wide associated loci than the original individual studies; this emphasizes the importance of tools and mechanisms for data sharing. However, even sharing summary-level data, such as allele frequencies, inherently carries some degree of privacy risk to study participants. Here we discuss mechanisms and resources for sharing data from GWASs, particularly focusing on approaches for assessing and quantifying the privacy risks to participants that result from the sharing of summary-level data. © 2011 Macmillan Publishers Limited. All rights reserved. Source


Kullo I.J.,Mayo Medical School | Ding K.,Mayo Medical School | Shameer K.,Mayo Medical School | McCarty C.A.,Center for Human Genetics | And 8 more authors.
American Journal of Human Genetics | Year: 2011

The erythrocyte sedimentation rate (ESR), a commonly performed test of the acute phase response, is the rate at which erythrocytes sediment in vitro in 1 hr. The molecular basis of erythrocyte sedimentation is unknown. To identify genetic variants associated with ESR, we carried out a genome-wide association study of 7607 patients in the Electronic Medical Records and Genomics (eMERGE) network. The discovery cohort consisted of 1979 individuals from the Mayo Clinic, and the replication cohort consisted of 5628 individuals from the remaining four eMERGE sites. A nonsynonymous SNP, rs6691117 (Val→IIe), in the complement receptor 1 gene (CR1) was associated with ESR (discovery cohort p = 7 × 10-12, replication cohort p = × 3 10 -14, combined cohort p = 9 × 10-24). We imputed 61 SNPs in CR1, and a ''possibly damaging'' SNP (rs2274567, His→Arg) in linkage disequilibrium (r2 = 0.74) with rs6691117 was also associated with ESR (discovery p = 5 × 10-11, replication p = 7 × 10-17, and combined cohort p = 2 × 10-25). The two nonsynonymous SNPs in CR1 are near the C3b/C4b binding site, suggesting a possible mechanism by which the variants may influence ESR. In conclusion, genetic variation in CR1, which encodes a protein that clears complement-tagged inflammatory particles from the circulation, influences interindividual variation in ESR, highlighting an association between the innate immunity pathway and erythrocyte interactions. © 2011 by The American Society of Human Genetics. All rights reserved. Source


Yang J.,Queensland Institute of Medical Research | Manolio T.A.,National Human Genome Research Institute NHGRI | Pasquale L.R.,Harvard University | Boerwinkle E.,University of Texas Health Science Center at Houston | And 21 more authors.
Nature Genetics | Year: 2011

We estimate and partition genetic variation for height, body mass index (BMI), von Willebrand factor and QT interval (QTi) using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimate that ̃45%, ̃17%, ̃25% and ̃21% of the variance in height, BMI, von Willebrand factor and QTi, respectively, can be explained by all autosomal SNPs and a further ̃0.5-1% can be explained by X chromosome SNPs. We show that the variance explained by each chromosome is proportional to its length, and that SNPs in or near genes explain more variation than SNPs between genes. We propose a new approach to estimate variation due to cryptic relatedness and population stratification. Our results provide further evidence that a substantial proportion of heritability is captured by common SNPs, that height, BMI and QTi are highly polygenic traits, and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein. © 2011 Nature America, Inc. All rights reserved. Source


Sims M.,University of Mississippi Medical Center | Diez-Roux A.V.,Drexel University | Gebreab S.Y.,National Human Genome Research Institute NHGRI | Brenner A.,University of Michigan | And 6 more authors.
Journal of Epidemiology and Community Health | Year: 2016

Background Using Jackson Heart Study data, we examined associations of multiple measures of perceived discrimination with health behaviours among African- Americans (AA). Methods The cross-sectional associations of everyday, lifetime and burden of discrimination with odds of smoking and mean differences in physical activity, dietary fat and sleep were examined among 4925 participants aged 35-84 years after adjustment for age and socioeconomic status (SES). Results Men reported slightly higher levels of everyday and lifetime discrimination than women and similar levels of burden of discrimination as women. After adjustment for age and SES, everyday discrimination was associated with more smoking and a greater percentage of dietary fat in men and women (OR for smoking: 1.13, 95% CI 1.00 to 1.28 and 1.19, 95% CI 1.05 to 1.34; mean difference in dietary fat: 0.37, p < 0.05 and 0.43, p < 0.01, in men and women, respectively). Everyday and lifetime discrimination were associated with fewer hours of sleep in men and women (mean difference for everyday discrimination: -0.08, p < 0.05 and -0.18, p < 0.001, respectively; and mean difference for lifetime discrimination: -0.08, p < 0.05 and -0.24, p < 0.001, respectively). Burden of discrimination was associated with more smoking and fewer hours of sleep in women only. Conclusions Higher levels of perceived discrimination were associated with select health behaviours among men and women. Health behaviours offer a potential mechanism through which perceived discrimination affects health in AA. Source


Ramos E.M.,National Human Genome Research Institute NHGRI | Din-Lovinescu C.,Touro College | Duncanson A.,Wellcome Trust Sanger Institute | Dunn M.,University of Cambridge | And 23 more authors.
American Journal of Medical Genetics, Part C: Seminars in Medical Genetics | Year: 2014

Genome-wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data. As the field of medicine begins to incorporate genome-scale analysis into clinical care, approaches need to be developed for collecting and characterizing data on the clinical implications of variants, developing consensus on their actionability, and making this information available for clinical use. The National Human Genome Research Institute (NHGRI) and the Wellcome Trust thus convened a workshop to consider the processes and resources needed to: (1) identify clinically valid genetic variants; (2) decide whether they are actionable and what the action should be; and (3) provide this information for clinical use. This commentary outlines the key discussion points and recommendations from the workshop. © 2014 Wiley Periodicals, Inc. Source

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