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Details

Autor(en) / Beteiligte
Titel
Imputation of sequence variants for identification of genetic risks for Parkinson's disease: a meta-analysis of genome-wide association studies
Ist Teil von
  • The Lancet (British edition), 2011-02, Vol.377 (9766), p.641-649
Ort / Verlag
Kidlington: Elsevier Ltd
Erscheinungsjahr
2011
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • Summary Background Genome-wide association studies (GWAS) for Parkinson's disease have linked two loci ( MAPT and SNCA ) to risk of Parkinson's disease. We aimed to identify novel risk loci for Parkinson's disease. Methods We did a meta-analysis of datasets from five Parkinson's disease GWAS from the USA and Europe to identify loci associated with Parkinson's disease (discovery phase). We then did replication analyses of significantly associated loci in an independent sample series. Estimates of population-attributable risk were calculated from estimates from the discovery and replication phases combined, and risk-profile estimates for loci identified in the discovery phase were calculated. Findings The discovery phase consisted of 5333 case and 12 019 control samples, with genotyped and imputed data at 7 689 524 SNPs. The replication phase consisted of 7053 case and 9007 control samples. We identified 11 loci that surpassed the threshold for genome-wide significance (p<5×10−8 ). Six were previously identified loci ( MAPT, SNCA, HLA-DRB5, BST1, GAK and LRRK2 ) and five were newly identified loci ( ACMSD, STK39, MCCC1/LAMP3, SYT11 , and CCDC62/HIP1R ). The combined population-attributable risk was 60·3% (95% CI 43·7–69·3). In the risk-profile analysis, the odds ratio in the highest quintile of disease risk was 2·51 (95% CI 2·23–2·83) compared with 1·00 in the lowest quintile of disease risk. Interpretation These data provide an insight into the genetics of Parkinson's disease and the molecular cause of the disease and could provide future targets for therapies. Funding Wellcome Trust, National Institute on Aging, and US Department of Defense.

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