Year: 2012
Type: article
Study design: Observational Study
Abstract: We implemented least absolute shrinkage and selection operator (LASSO) regression to evaluate gene effects in genome-wide association studies (GWAS) of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sparse groups of SNPs in individual genes were selected by LASSO, which identifies efficient sets of variants influencing the data. These SNPs were considered jointly when assessing their association with neuroimaging measures. We discovered 22 genes that passed genome-wide significance for influencing temporal lobe volume. This was a substantially greater number of significant genes compared to those found with standard, univariate GWAS. These top genes are all expressed in the brain and include genes previously related to brain function or neuropsychiatric disorders such as MACROD2, SORCS2, GRIN2B, MAGI2, NPAS3, CLSTN2, GABRG3, NRXN3, PRKAG2, GAS7, RBFOX1, ADARB2, CHD4, and CDH13. The top genes we identified with this method also displayed significant and widespread post hoc effects on voxelwise, tensor-based morphometry (TBM) maps of the temporal lobes. The most significantly associated gene was an autism susceptibility gene known as MACROD2. We were able to successfully replicate the effect of the MACROD2 gene in an independent cohort of 564 young, Australian healthy adult twins and siblings scanned with MRI (mean age: 23.8 ± 2.2 SD years). Our approach powerfully complements univariate techniques in detecting influences of genes on the living brain.
Source: Frontiers in Neuroscience
Author: Omid Kohannim
Institution: University of California, Los Angeles
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,801
Funders: Foundation for the National Institutes of Health, Alzheimer's Association, Bristol-Myers Squibb, Alzheimer's Drug Discovery Foundation, Eli Lilly and Company, Pfizer, AstraZeneca, Merck, Novartis, F. Hoffmann-La Roche, Medpace, Synarc, Northern California Institute for Research and Education, Elan, Eisai, National Institutes of Health, U.S. Food and Drug Administration, Genentech, Johnson and Johnson, National Institute on Aging, National Institute of Mental Health, National Institute of General Medical Sciences, National Institute of Biomedical Imaging and Bioengineering, National Center for Research Resources, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G104586243, Assessment of Gene Effects on the Brain and Disease Risk through Machine Learning, UC Davis Alzheimer's Disease Core Center, Genetic influences on the brain: A twin imaging study, Algorithms to Map Disease &Genetic Effects on the Brain, Novel PDEs for Cortical Mapping and Analysis in Disease, UCLA Alzheimer's Disease Research Center, "MR Morphometrics and Cognitive Decline Rate in Large-Scale Aging Studies", Alzheimer's disease risk analyzed using population imaging genomics, Empowering Personalized Medicine: Integrating Imaging, Genetics, and Biomarkers, UCLA-Caltech Medical Scientist Training Program, Alzheimer's Disease Neuroimaging Initiative, Alzheimer's Disease Cooperative Study, Alzheimer's Disease Neuroimaging Initiative (ADNI4), National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD)
OpenAlex ID: W2117078302