title: Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm.
abstract: BACKGROUND
  Imaging genetics is an emerging field that studies the influence of genetic variation on brain structure and function. The major task is to examine the association between genetic markers such as single-nucleotide polymorphisms (SNPs) and quantitative traits (QTs) extracted from neuroimaging data. The complexity of these datasets has presented critical bioinformatics challenges that require new enabling tools. Sparse canonical correlation analysis (SCCA) is a bi-multivariate technique used in imaging genetics to identify complex multi-SNP-multi-QT associations. However, most of the existing SCCA algorithms are designed using the soft thresholding method, which assumes that the input features are independent from one another. This assumption clearly does not hold for the imaging genetic data. In this article, we propose a new knowledge-guided SCCA algorithm (KG-SCCA) to overcome this limitation as well as improve learning results by incorporating valuable prior knowledge.
  
  
  RESULTS
  The proposed KG-SCCA method is able to model two types of prior knowledge: one as a group structure (e.g. linkage disequilibrium blocks among SNPs) and the other as a network structure (e.g. gene co-expression network among brain regions). The new model incorporates these prior structures by introducing new regularization terms to encourage weight similarity between grouped or connected features. A new algorithm is designed to solve the KG-SCCA model without imposing the independence constraint on the input features. We demonstrate the effectiveness of our algorithm with both synthetic and real data. For real data, using an Alzheimer's disease (AD) cohort, we examine the imaging genetic associations between all SNPs in the APOE gene (i.e. top AD gene) and amyloid deposition measures among cortical regions (i.e. a major AD hallmark). In comparison with a widely used SCCA implementation, our KG-SCCA algorithm produces not only improved cross-validation performances but also biologically meaningful results.
  
  
  BACKGROUND
  Software is freely available on request.
authors.affiliation: BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Jingwen
authors.initials: J
authors.lastname: Yan
authors.affiliation: BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Lei
authors.initials: L
authors.lastname: Du
authors.affiliation: BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Sungeun
authors.initials: S
authors.lastname: Kim
authors.affiliation: BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Shannon L
authors.initials: SL
authors.lastname: Risacher
authors.affiliation: BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Heng
authors.initials: H
authors.lastname: Huang
authors.affiliation: BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Jason H
authors.initials: JH
authors.lastname: Moore
authors.affiliation: BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Saykin
authors.affiliation: BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Li
authors.initials: L
authors.lastname: Shen
mesh_terms: D000465:Algorithms; D000544:Alzheimer Disease / Q000235:genetics; D000682:Amyloid / Q000032:analysis*; D001057:Apolipoproteins E / Q000235:genetics; D001921:Brain / Q000378:metabolism; D001923:Brain Chemistry; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D015810:Linkage Disequilibrium; D059906:Neuroimaging / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D012984:Software
chemical_list: D000682:Amyloid; D001057:Apolipoproteins E