Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans
Year: 2015
Type: review
Abstract: INTRODUCTION: Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. METHODS: Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated. RESULTS: ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD. DISCUSSION: Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.
Source: Alzheimer s & Dementia
Authors: Andrew J. Saykin, Li Shen, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Vijay K. Ramanan, Tatiana M. Foroud, Kelley M. Faber, Nadeem Sarwar, Leanne M. Munsie, Xiaolan Hu, Holly D. Soares, Steven G. Potkin, Paul M. Thompson, John S.K. Kauwe, Rima Kaddurah‐Daouk, Robert C. Green, Arthur W. Toga, Michael W. Weiner, Alzheimer's Disease Neuroimaging Initiative
Institutions: Indiana University Indianapolis, Indiana University School of Medicine, Indiana University – Purdue University Indianapolis, Eisai (United Kingdom), Eli Lilly (United States), Bristol-Myers Squibb (United States), University of California, Irvine, University of Southern California, Brigham Young University, Duke University, Brigham and Women's Hospital, Harvard University, San Francisco VA Medical Center, University of California, San Francisco, Alzheimer’s Disease Neuroimaging Initiative
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,200
Funders: National Science Foundation, U.S. Department of Defense, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Biogen, University of Southern California, F. Hoffmann-La Roche, Medpace, Meso Scale Diagnostics, Synarc, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Eisai, Servier, IXICO, National Institutes of Health, Genentech, University of California, San Diego, Canadian Institutes of Health Research, National Institute on Aging, National Institute of Biomedical Imaging and Bioengineering, U.S. National Library of Medicine, National Center for Advancing Translational Sciences
Awards: G1012222616, G104586243, Indiana Alzheimer Disease Center, Bioinformatics Strategies for Multidimensional Brain Imaging Genetics, G1554142629, G1593117279, Pleiotropic and Interaction Effects on Alzheimer's disease Risk and Progression, G1650819308, G1654311910, III: Small: Collaborative Research: A Large-Scale Data Mining Framework for Genome-Wide Mapping of Multi-Modal Phenotypic Biomarkers and Outcome Prediction, Alzheimer's Disease Neuroimaging Initiative, G2100670906, G2189010064, G2340207221, G2409989180, G2423387114, G2522063444, Indiana Clinical and Translational Sciences Institute, G2835601961, G29951154, G3131374986, G3216574877, G3553156159, Integration of Bio-, Medical, and Imaging Informatics for Complex Diseases, G3710456697, G3752451908, G3779651404, G3870774570, G3908963977, G3966393351, Integration of Bio-, Medical, and Imaging Informatics for Complex Diseases, G4119534169, G43180419, G4475667458, G4501223628, THE NCAA-DOD GRAND ALLIANCE: CONCUSSION ASSESSMENT, RESEARCH, AND EDUCATION (CARE) CONSORTIUM, Alzheimer's disease risk analyzed using population imaging genomics, G4800177743, G5207404921, G5209990037, G528601746, G5365730499, EFFECTS OF TRAUMATIC BRAIN INJURY (TBI) AND POST TRAUMATIC STRESS DISORDER (PTSD) ON ALZHEIMER'S DISEASE (AD) IN VETERANS USING IMAGING AND BIOMARKERS IN THE AD NEUROIMAGING INITIATIVE (ADNI)", G5654639750, G5740349702, G5850682332, G613619302, G6173816828, G6210868510, G6371410416, G6412110892, G6425121803, G6447063303, G6719828067, G6792506723, G6899163935, G6948409098, G7268282379, G7298697282, Memory Circuitry in MCI and Early Alzheimerâs Disease Prodrome: Molecular Drivers, G764699806, Amyloid Imaging, VMCI, and Analysis for ADNI, G7799614282, G781725486, G8107776361, G8228018387, Laboratory of Neuro Imaging Resource (LONIR), G8281378126, G8301434335, G839208290, G8636843673, G8852128998, G8895907669, G8897063270, G8957659042, G9000039018, G9000122335, National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD)
OpenAlex ID: W1901948746