Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease

Lesley Jones(Cardiff University), Peter Holmans(Medical Research Council), Marian L. Hamshere(Cardiff University), Denise Harold(Cardiff University), Valentina Moskvina(Medical Research Council), Dobril Ivanov(Cardiff University), Andrew Pocklington(Cardiff University), Richard Abraham(Cardiff University), Paul Hollingworth(Cardiff University), Rebecca Sims(Cardiff University), Amy Gerrish(Cardiff University), Jaspreet Singh Pahwa(Cardiff University), Nicola Jones(Medical Research Council), Alexandra Stretton(Cardiff University), Angharad R. Morgan(Medical Research Council), Simon Lovestone(NIHR Biomedical Research Centre at The Royal Marsden and the ICR), John Powell(King's College London), Petroula Proitsi(King's College London), Michelle K. Lupton(King's College London), Carol Brayne(University of Cambridge), David C. Rubinsztein(University of Cambridge), Michael Gill(Trinity College Dublin), Brian Lawlor(Trinity College Dublin), Aoibhinn Lynch(Trinity College Dublin), Kevin Morgan(University of Nottingham), Kristelle Brown(University of Nottingham), Peter Passmore(Queen's University Belfast), David Craig(Queen's University Belfast), Bernadette McGuinness(Queen's University Belfast), Stephen Todd(Queen's University Belfast), Clive Holmes(University of Southampton), David Mann(Greater Manchester STEM Centre), A. David Smith(University of Oxford), Seth Love(Frenchay Hospital), Patrick G. Kehoe(University of Bristol), Simon Mead(MRC Prion Unit), Nick C. Fox(UK Dementia Research Institute), Martin N. Rossor(UK Dementia Research Institute), John Collinge(University College London), Wolfgang Maier(University of Bonn), Frank Jessen(University of Bonn), Britta Schürmann(University of Bonn), Hendrik van den Bussche(Universität Hamburg), Isabella Heuser(Universität Hamburg), Oliver Peters(University Medical Center Hamburg-Eppendorf), Johannes Kornhuber(Friedrich-Alexander-Universität Erlangen-Nürnberg), Jens Wiltfang, Martin Dichgans(LMU Klinikum), Lutz Frölich(University Hospital Heidelberg), Harald Hampel(Trinity College Dublin), Michael Hüll(University of Freiburg), Dan Rujescu(Ludwig-Maximilians-Universität München), Alison Goate(Washington University in St. Louis), John Kauwe(Brigham Young University), Carlos Cruchaga(Washington University in St. Louis), Petra Nowotny(Washington University in St. Louis), John C. Morris(Washington University in St. Louis), Kevin H. Mayo(Washington University in St. Louis), Gill Livingston(Mental Health Research UK), Nicholas Bass(University College London), Hugh Gurling(Mental Health Research UK), Andrew McQuillin(University College London), Rhian Gwilliam(Wellcome Sanger Institute), Panos Deloukas(Wellcome Sanger Institute), Ammar Al‐Chalabi(King's College London), Christopher E. Shaw(King's College London), Andrew B. Singleton(National Institute on Aging), Rita Guerreiro(National Institutes of Health), Thomas W. Mühleisen(Life & Brain (Germany)), Markus M. Nöthen(University of Bonn), Susanne Moebus(University of Duisburg-Essen), Karl‐Heinz Jöckel(University of Duisburg-Essen), Norman Klopp(Helmholtz Zentrum München), H.‐Erich Wichmann(LMU Klinikum), E. Rüther(University of Göttingen), Minerva M. Carrasquillo(Mayo Clinic in Florida), V. Shane Pankratz(Mayo Clinic), Steven G. Younkin(Jacksonville College), John Hardy, Michael O’Donovan(Medical Research Council), Michael J. Owen(Cardiff University), Julie Williams(Cardiff University)
PLoS ONE
November 15, 2010
Cited by 612Open Access
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Abstract

BACKGROUND: Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. METHODOLOGY: We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. PRINCIPAL FINDINGS: We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. SIGNIFICANCE: Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches.


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