Multivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validation

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dc.contributor.authorSzefer, Elena
dc.contributor.authorLu, Donghuan
dc.contributor.authorNathoo, Farouk
dc.contributor.authorBeg, Mirza Faisal
dc.contributor.authorGraham, Jinko
dc.date.accessioned2019-06-11T16:22:10Z
dc.date.available2019-06-11T16:22:10Z
dc.date.copyright2017en_US
dc.date.issued2017
dc.description.abstractUsing publicly-available data from the Alzheimer’s Disease Neuroimaging Initiative, we investigate the joint association between single-nucleotide polymorphisms (SNPs) in previously established linkage regions for Alzheimer’s disease (AD) and rates of decline in brain structure. In an initial, discovery stage of analysis, we applied a weighted RV test to assess the association between 75,845 SNPs in the Alzgene linkage regions and rates of change in structural MRI measurements for 56 brain regions affected by AD, in 632 subjects. After confirming association, we selected refined lists of 1694 and 22 SNPs via a bootstrap-enhanced sparse canonical correlation analysis. In a final, validation stage, we confirmed association between the refined list of 1694 SNPs and the imaging phenotypes in an independent data set. Genes corresponding to priority SNPs having the highest contribution in the validation data have previously been implicated or hypothesized to be implicated in AD, including GCLC, IDE, and STAMBP1andFAS. Though the effect sizes of the 1694 SNPs in the priority set are likely small, further investigation within this set may advance understanding of the missing heritability in AD. Our analysis addresses challenges in current imaging-genetics studies such as biased sampling designs and high-dimensional data with low association signal.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipData collection and sharing was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This work is based on Elena Szefer's MSc thesis supervised by J Graham and was supported in part by the Natural Sciences and Engineering Research Council of Canada. The authors would like to thank Ellen Wijsman for helpful discussions about APOE and population stratification and Wayne Wang for assistance with the genomic quality control of the ADNI-2 validation data. The authors are grateful to the anonymous reviewers for constructive comments which greatly improved the manuscript.en_US
dc.identifier.citationSzefer, E.; Lu, D.; Nathoo, F.; Beg, M. F.; & Graham, J. (2017). Multivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validation. Statistical Applications in Genetics and Molecular Biology, 16(5-6), 367-386. DOI: 10.1515/sagmb-2016-0077en_US
dc.identifier.urihttps://doi.org/10.1515/sagmb-2016-0077
dc.identifier.urihttp://hdl.handle.net/1828/10919
dc.language.isoenen_US
dc.publisherStatistical Applications in Genetics and Molecular Biologyen_US
dc.subjectmultivariate analysis
dc.subjectlinkage regions
dc.subjectimaging genetics
dc.subjectendophenotypes
dc.subjectinverse probability weighting
dc.subjectvariable importance probabilities
dc.subject.departmentDepartment of Mathematics and Statistics
dc.titleMultivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validationen_US
dc.typeArticleen_US

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