PuSH - Publikationsserver des Helmholtz Zentrums München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Keller, M.F.* ; Saad, M.* ; Bras, J.* ; Bettella, F.* ; Nicolaou, N.* ; Simon-Sanchez, J.* ; Mittag, F.* ; Buchel, F.* ; Sharma, M.* ; Gibbs, J.R.* ; Schulte, C.* ; Moskvina, V.* ; Dürr, A.* ; Holmans, P.* ; Kilarski, L.L.* ; Guerreiro, R.* ; Hernandez, D.G.* ; Brice, A.* ; Ylikotila, P.* ; Stefansson, H.* ; Majamaa, K.* ; Morris, H.R.* ; Williams, N.* ; Gasser, T.* ; Heutink, P.* ; Wood, N.W.* ; Hardy, J.* ; Martinez, M.* ; Singleton, A.B.* ; Nalls, M.A.* ; International Parkinson's Disease Genomics Consortium (IPDGC) (Illig, T. ; Lichtner, P.) ; Wellcome Trust Case Control Consortium 2 (WTCCC2) (*)

Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease.

Hum. Mol. Genet. 21, 4996-5009 (2012)
Verlagsversion Volltext DOI PMC
Closed
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
7.692
1.710
74
144
Tags
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern

Zusatzinfos bearbeiten
Eigene Tags bearbeiten
Privat
Eigene Anmerkung bearbeiten
Privat
Auf Publikationslisten für
Homepage nicht anzeigen
Als besondere Publikation
markieren
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Sprache englisch
Veröffentlichungsjahr 2012
HGF-Berichtsjahr 2013
ISSN (print) / ISBN 0964-6906
e-ISSN 1460-2083
Zeitschrift Human Molecular Genetics
Quellenangaben Band: 21, Heft: 22, Seiten: 4996-5009 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Begutachtungsstatus Peer reviewed
Institut(e) Research Unit Molecular Epidemiology (AME)
Institute of Human Genetics (IHG)
POF Topic(s) 30501 - Systemic Analysis of Genetic and Environmental Factors that Impact Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-504200-001
G-500700-001
PubMed ID 22892372
DOI 10.1093/hmg/dds335
Scopus ID 84868134823
Erfassungsdatum 2013-08-05
[➜Korrektur melden]