TY - JOUR
T1 - Genotype patterns at PICALM, CR1, BIN1, CLU, and APOE genes are associated with episodic memory
AU - Barral, S.
AU - Bird, T.
AU - Goate, A.
AU - Farlow, M. R.
AU - Diaz-Arrastia, R.
AU - Bennett, D. A.
AU - Graff-Radford, N.
AU - Boeve, B. F.
AU - Sweet, R. A.
AU - Stern, Y.
AU - Wilson, R. S.
AU - Foroud, T.
AU - Ott, J.
AU - Mayeux, R.
N1 - Funding Information:
Supported by NIH and NIA grants U24AG26396, U24AG021886, R01AG17917, P50AG8702, P30AG10161, P30AG013846, P30AG028377, P30AG010133, P50AG05134, P50AG016574, P50AG05138, P30AG013854, P30AG08017, P50AG016582, P50AG016570, P30AG028383, P30AG010124, P50AG005133, R01AG027224, P50AG05142, P30AG012300, P50AG05136, and P50AG05681 and NSFC grant 30730057 from the Chinese Government to J. Ott. Genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the NIH to The Johns Hopkins University (contract HHSN268200782096C) . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript, but did review the manuscript before submission.
Funding Information:
Dr. Barral receives research support from Alzheimer Disease Genetic Consortium. Dr. Bird receives research support from Athena Diagnostics, Inc. Dr. Goate serves as consultant for AstraZeneca; serves as an expert testimony for Howrey & Associates; receives research support from AstraZeneca, Genetech, Pfizer, and NIA; and holds patent royalties from Taconic (Tau mutation patent). Dr. Farlow serves as a board member for Medivation, Merck, and INC Res/Toyama; serves as a consultant for Accera, Astellas, Baxter, Bristol Meyers Squibb, GE Healthcare, Novartis, Pfizer, Prana, and sanofi-aventis; serves as an expert testimony for Pfizer; receives research support from Danone Research, Elan Pharma, Eli Lilly, Novartis, Genetech, OctaPharma, Pfizer, sanofi-aventis, Sonexa Therapeutics, Eisai, and NIA; holds a patent from Elan and patent royalties from UpToDate; and holds stock options from QR Pharm and MedAvante. Dr. Diaz-Arrastia receives research support from NIH. Dr. Bennett receives research support from NIH. Dr. Graff-Radford serves as board member of The Neurologist; serves as a consultant for Codman; and receives research support from Medivation, Janssen, Allon, Forest, and NIA. Dr. Boeve receives research support from Cephalon Inc., Allon Pharmaceuticals, Mangurian Foundation, Alzheimer Association, and NIH; receives royalties as a co-editor of Behavioral Neurology of Dementia; and receives support for development of educational presentations from the American Academy of Neurology. Dr. Sweet receives research support from NIH. Dr. Stern serves as consultant for Allergan Inc., Cephalon Inc., Elan Corporation, Eisai Inc., Pfizer, Ortho-McNeil Neurologics, Merck Serono, GlaxoSmithKline, Eli Lilly, Janssen, and NIH. Dr. Wilson receives research support from a grant from Rush University Medical Center. Dr. Foroud receives research support from NIH. Dr. Ott receives research support from Natural Science Foundation of China. Dr. Mayeux receives research support from NIH. Go to Neurology.org for full disclosures.
PY - 2012/5/8
Y1 - 2012/5/8
N2 - Objective: Several genome-wide association studies (GWAS) have associated variants in lateonset Alzheimer disease (LOAD) susceptibility genes; however, these single nucleotide polymorphisms (SNPs) have very modest effects, suggesting that single SNP approaches may be inadequate to identify genetic risks. An alternative approach is the use of multilocus genotype patterns (MLGPs) that combine SNPs at different susceptibility genes. Methods: Using data from 1,365 subjects in the National Institute on Aging Late-Onset Alzheimer's Disease Family Study, we conducted a family-based association study in which we tabulated MLGPs for SNPs at CR1, BIN1, CLU, PICALM, and APOE. We used generalized estimating equations to model episodic memory as the dependent endophenotype of LOAD and the MLGPs as predictors while adjusting for sex, age, and education. Results: Several genotype patterns influenced episodic memory performance. A pattern that included PICALM and CLU was the strongest genotypic profile for lower memory performance (β = -0.32, SE = 0.19, p = 0.021). The effect was stronger after addition of APOE (p = 0.016). Two additional patterns involving PICALM, CR1, and APOE and another pattern involving PICALM, BIN1, and APOE were also associated with significantly poorer memory performance (==-0.44, SE = 0.09, p = 0.009 and β = -0.29, SE = 0.07, p = 0.012) even after exclusion of patients with LOAD. We also identified genotype pattern involving variants in PICALM, CLU, and APOE as a predictor of better memory performance (β = 0.26, SE = 0.10, p = 0.010). Conclusions: MLGPs provide an alternative analytical approach to predict an individual's genetic risk for episodic memory performance, a surrogate indicator of LOAD. Identifying genotypic patterns contributing to the decline of an individual's cognitive performance may be a critical step along the road to preclinical detection of Alzheimer disease.
AB - Objective: Several genome-wide association studies (GWAS) have associated variants in lateonset Alzheimer disease (LOAD) susceptibility genes; however, these single nucleotide polymorphisms (SNPs) have very modest effects, suggesting that single SNP approaches may be inadequate to identify genetic risks. An alternative approach is the use of multilocus genotype patterns (MLGPs) that combine SNPs at different susceptibility genes. Methods: Using data from 1,365 subjects in the National Institute on Aging Late-Onset Alzheimer's Disease Family Study, we conducted a family-based association study in which we tabulated MLGPs for SNPs at CR1, BIN1, CLU, PICALM, and APOE. We used generalized estimating equations to model episodic memory as the dependent endophenotype of LOAD and the MLGPs as predictors while adjusting for sex, age, and education. Results: Several genotype patterns influenced episodic memory performance. A pattern that included PICALM and CLU was the strongest genotypic profile for lower memory performance (β = -0.32, SE = 0.19, p = 0.021). The effect was stronger after addition of APOE (p = 0.016). Two additional patterns involving PICALM, CR1, and APOE and another pattern involving PICALM, BIN1, and APOE were also associated with significantly poorer memory performance (==-0.44, SE = 0.09, p = 0.009 and β = -0.29, SE = 0.07, p = 0.012) even after exclusion of patients with LOAD. We also identified genotype pattern involving variants in PICALM, CLU, and APOE as a predictor of better memory performance (β = 0.26, SE = 0.10, p = 0.010). Conclusions: MLGPs provide an alternative analytical approach to predict an individual's genetic risk for episodic memory performance, a surrogate indicator of LOAD. Identifying genotypic patterns contributing to the decline of an individual's cognitive performance may be a critical step along the road to preclinical detection of Alzheimer disease.
UR - http://www.scopus.com/inward/record.url?scp=84863616992&partnerID=8YFLogxK
U2 - 10.1212/WNL.0b013e3182553c48
DO - 10.1212/WNL.0b013e3182553c48
M3 - Article
AN - SCOPUS:84863616992
SN - 0028-3878
VL - 78
SP - 1464
EP - 1471
JO - Neurology
JF - Neurology
IS - 19
ER -