Abstract
Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose ℓ 1 -norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the ℓ1 -norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce the estimation bias in regression tasks. But using them in SCCA remains largely unexplored. In this paper, we design a unified non-convex SCCA model, based on seven non-convex functions, for unbiased estimation and stable feature selection simultaneously. We also propose an efficient optimization algorithm. The proposed method obtains both higher correlation coefficients and better canonical loading patterns. Specifically, these SCCA methods with non-convex penalties discover a strong association between the APOE e4 rs429358 SNP and the hippocampus region of the brain. They both are Alzheimer's disease related biomarkers, indicating the potential and power of the non-convex methods in brain imaging genetics.
| Original language | English (US) |
|---|---|
| Article number | 14052 |
| Journal | Scientific reports |
| Volume | 7 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 1 2017 |
Funding
Data collection and sharing for this project was funded by the Alzheimer\u2019s 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 the following: AbbVie, Alzheimer\u2019s Association; Alzheimer\u2019s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; 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\u2019s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. L. Du was supported by the National Natural Science Foundation of China (61602384); the Natural Science Basic Research Plan in Shaanxi Province of China (2017JQ6001); the China Postdoctoral Science Foundation (2017M613202); and the Fundamental Research Funds for the Central Universities (3102016OQD0065) at Northwestern Polytechnical University. This work was also supported by the National Institutes of Health R01 EB022574, R01 LM011360, U01 AG024904, P30 AG10133, R01 AG19771, UL1 TR001108, R01 AG 042437, R01 AG046171, R01 AG040770; the Department of Defense W81XWH-14-2-0151, W81XWH-13-1-0259, W81XWH-12-2-0012; the National Collegiate Athletic Association 14132004 at Indiana University.
ASJC Scopus subject areas
- General