TY - JOUR
T1 - Genetic analysis of quantitative phenotypes in AD and MCI
T2 - Imaging, cognition and biomarkers
AU - Shen, Li
AU - Thompson, Paul M.
AU - Potkin, Steven G.
AU - Bertram, Lars
AU - Farrer, Lindsay A.
AU - Foroud, Tatiana M.
AU - Green, Robert C.
AU - Hu, Xiaolan
AU - Huentelman, Matthew J.
AU - Kim, Sungeun
AU - Kauwe, John S.K.
AU - Li, Qingqin
AU - Liu, Enchi
AU - Macciardi, Fabio
AU - Moore, Jason H.
AU - Munsie, Leanne
AU - Nho, Kwangsik
AU - Ramanan, Vijay K.
AU - Risacher, Shannon L.
AU - Stone, David J.
AU - Swaminathan, Shanker
AU - Toga, Arthur W.
AU - Weiner, Michael W.
AU - Saykin, Andrew J.
N1 - Funding Information:
This work was also supported, in part, by National Institutes of Health (NIH) R01 LM011360 and National Science Foundation (NSF) IIS-1117335 (Dr. Shen), by National Institutes of Health (NIH) R01s AG040060, MH097268, NS080655, and HD050735 and P41 EB015922 (Dr. Thompson), by National Institutes of Health (NIH) U01 AG024904, AG036535, U24RR025736, and U24 RR21992 (Dr. Potkin), by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF) grant number #16SV5538, the Cure Alzheimer’s Fund, and the Fidelity Biosciences Research Initiative (Dr. Bertram), by National Institutes of Health (NIH) U24 AG021886, National Cell Repository for Alzheimer’s Disease (Dr. Foroud), by National Institutes of Health (NIH) R01 HG002213, K24 AG027841 and the Alzheimer’s Association (Dr. Green), by National Institutes of Health (NIH) R01 AG042611, the Alzheimer’s Association (MNIRG-11-205368), the Charleston Conference on Alzheimer’s disease Young Investigator Award and the Brigham Young University Gerontology Program (Dr. Kauwe), by National Institutes of Health (NIH) R01 LM009012 and R01 LM010098 (Dr. Moore), by National Institutes of Health (NIH) K99 LM011384 (Dr. Nho), by Alzheimer’s Disease Neuroimaging Initiative (Grant # U01 AG024904) and the Laboratory of Neuro Imaging Resource (LONIR) (Grant # 9 P41EB015922-15) at UCLA (Dr. Toga), by National Institutes of Health (NIH) U01AG024904, RC2 AG036535, R01 AG19771, P30 AG10133, at Indiana University School of Medicine (Dr. Saykin).
PY - 2014/6
Y1 - 2014/6
N2 - The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI), formally established in 2009, aims to provide resources and facilitate research related to genetic predictors of multidimensional Alzheimer's disease (AD)-related phenotypes. Here, we provide a systematic review of genetic studies published between 2009 and 2012 where either ADNI APOE genotype or genome-wide association study (GWAS) data were used. We review and synthesize ADNI genetic associations with disease status or quantitative disease endophenotypes including structural and functional neuroimaging, fluid biomarker assays, and cognitive performance. We also discuss the diverse analytical strategies used in these studies, including univariate and multivariate analysis, meta-analysis, pathway analysis, and interaction and network analysis. Finally, we perform pathway and network enrichment analyses of these ADNI genetic associations to highlight key mechanisms that may drive disease onset and trajectory. Major ADNI findings included all the top 10 AD genes and several of these (e.g., APOE, BIN1, CLU, CR1, and PICALM) were corroborated by ADNI imaging, fluid and cognitive phenotypes. ADNI imaging genetics studies discovered novel findings (e.g., FRMD6) that were later replicated on different data sets. Several other genes (e.g., APOC1, FTO, GRIN2B, MAGI2, and TOMM40) were associated with multiple ADNI phenotypes, warranting further investigation on other data sets. The broad availability and wide scope of ADNI genetic and phenotypic data has advanced our understanding of the genetic basis of AD and has nominated novel targets for future studies employing next-generation sequencing and convergent multi-omics approaches, and for clinical drug and biomarker development.
AB - The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI), formally established in 2009, aims to provide resources and facilitate research related to genetic predictors of multidimensional Alzheimer's disease (AD)-related phenotypes. Here, we provide a systematic review of genetic studies published between 2009 and 2012 where either ADNI APOE genotype or genome-wide association study (GWAS) data were used. We review and synthesize ADNI genetic associations with disease status or quantitative disease endophenotypes including structural and functional neuroimaging, fluid biomarker assays, and cognitive performance. We also discuss the diverse analytical strategies used in these studies, including univariate and multivariate analysis, meta-analysis, pathway analysis, and interaction and network analysis. Finally, we perform pathway and network enrichment analyses of these ADNI genetic associations to highlight key mechanisms that may drive disease onset and trajectory. Major ADNI findings included all the top 10 AD genes and several of these (e.g., APOE, BIN1, CLU, CR1, and PICALM) were corroborated by ADNI imaging, fluid and cognitive phenotypes. ADNI imaging genetics studies discovered novel findings (e.g., FRMD6) that were later replicated on different data sets. Several other genes (e.g., APOC1, FTO, GRIN2B, MAGI2, and TOMM40) were associated with multiple ADNI phenotypes, warranting further investigation on other data sets. The broad availability and wide scope of ADNI genetic and phenotypic data has advanced our understanding of the genetic basis of AD and has nominated novel targets for future studies employing next-generation sequencing and convergent multi-omics approaches, and for clinical drug and biomarker development.
KW - Alzheimer's disease
KW - Biomarker
KW - Cognition
KW - Genetic association study
KW - Neuroimaging
KW - Quantitative traits
UR - https://www.scopus.com/pages/publications/84899809381
U2 - 10.1007/s11682-013-9262-z
DO - 10.1007/s11682-013-9262-z
M3 - Article
C2 - 24092460
AN - SCOPUS:84899809381
SN - 1931-7557
VL - 8
SP - 183
EP - 207
JO - Brain Imaging and Behavior
JF - Brain Imaging and Behavior
IS - 2
ER -