title: Towards compendia of negative genetic association studies: an example for Alzheimer disease.
abstract: Most genetic sequence variants that contribute to variability in complex human traits will have small effects that are not readily detectable with population samples typically used in genetic association studies. A potentially valuable tool in the gene discovery process is meta-analysis of the accumulated published data, but in order to be valid these require a sample of studies representative of the true genetic effect and thus hypothetically should include some positive and an abundance of negative reports. A survey of the literature on association studies for Alzheimer disease (AD) from January 2004-April 2005, identified 138 studies, 86 of which reported positive findings other than for apolipoprotein E (APOE), strongly indicative of publication bias. We report here an analysis of 62 genetic markers, tested for association with AD risk as well as for possible effects upon quantitative indices of AD severity (mini-mental state examination scores, age-at-onset, and cerebrospinal fluid (CSF) beta-amyloid (Abeta) and CSF tau proteins). Within this set, only modest signals were present that, with the exception of APOE are easily lost when corrections for multiple hypotheses are applied. In isolation, results are thus broadly negative. Genes studied encompass both novel candidates as well as several recently claimed to be associated with AD (e.g. urokinase plasminogen activator (PLAU) and acetyl-coenzyme A acetyltransferase 1 (ACAT1)). By reporting these data we hope to encourage the publication of gene compendia to guide further studies and aid future meta-analyses aimed at resolving the involvement of genes in complex human traits.
authors.affiliation: Center for Genomics and Bioinformatics, Karolinska Institute, Berzeliusvag 35, 171 77 Stockholm, Sweden.
authors.forename: Mia E-L
authors.initials: ME
authors.lastname: Blomqvist
authors.forename: Chandra
authors.initials: C
authors.lastname: Reynolds
authors.forename: Hagit
authors.initials: H
authors.lastname: Katzov
authors.forename: Lars
authors.initials: L
authors.lastname: Feuk
authors.forename: Niels
authors.initials: N
authors.lastname: Andreasen
authors.forename: Nenad
authors.initials: N
authors.lastname: Bogdanovic
authors.forename: Kaj
authors.initials: K
authors.lastname: Blennow
authors.forename: Anthony J
authors.initials: AJ
authors.lastname: Brookes
authors.forename: Jonathan A
authors.initials: JA
authors.lastname: Prince
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000134:cerebrospinal fluid / Q000235:genetics*; D016229:Amyloid beta-Peptides / Q000134:cerebrospinal fluid; D000704:Analysis of Variance; D001057:Apolipoproteins E / Q000235:genetics; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005838:Genotype; D006801:Humans; D008297:Male; D008875:Middle Aged; D010446:Peptide Fragments / Q000134:cerebrospinal fluid; D007703:Peptidyl-Dipeptidase A / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D012307:Risk Factors; D016875:tau Proteins / Q000134:cerebrospinal fluid
chemical_list: D016229:Amyloid beta-Peptides; D001057:Apolipoproteins E; D010446:Peptide Fragments; C075222:amyloid beta-protein (1-42); D016875:tau Proteins; D007703:Peptidyl-Dipeptidase A