title: Seemingly unrelated regression empowers detection of network failure in dementia.
abstract: Brain connectivity is progressively disrupted in Alzheimer's disease (AD). Here, we used a seemingly unrelated regression (SUR) model to enhance the power to identify structural connections related to cognitive scores. We simultaneously solved regression equations with different predictors and used correlated errors among the equations to boost power for associations with brain networks. Connectivity maps were computed to represent the brain's fiber networks from diffusion-weighted magnetic resonance imaging scans of 200 subjects from the Alzheimer's Disease Neuroimaging Initiative. We first identified a pattern of brain connections related to clinical decline using standard regressions powered by this large sample size. As AD studies with a large number of diffusion tensor imaging scans are rare, it is important to detect effects in smaller samples using simultaneous regression modeling like SUR. Diagnosis of mild cognitive impairment or AD is well known to be associated with ApoE genotype and educational level. In a subsample with no apparent associations using the general linear model, power was boosted with our SUR model-combining genotype, educational level, and clinical diagnosis.
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA; Department of Psychiatry, University of Southern California, Los Angeles, CA, USA.
authors.forename: Neda
authors.initials: N
authors.lastname: Jahanshad
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA.
authors.forename: Talia M
authors.initials: TM
authors.lastname: Nir
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA.
authors.forename: Arthur W
authors.initials: AW
authors.lastname: Toga
authors.affiliation: Department of Radiology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Clifford R
authors.initials: CR
authors.lastname: Jack
authors.affiliation: Department of Radiology, University of California San Francisco, CA, USA.
authors.forename: Matt A
authors.initials: MA
authors.lastname: Bernstein
authors.affiliation: Department of Radiology, University of California San Francisco, CA, USA; Department of Medicine, University of California San Francisco, CA, USA; Department of Psychiatry, University of California San Francisco, CA, USA; Department of Veterans Affairs Medical Center, San Francisco, CA, USA.
authors.forename: Michael W
authors.initials: MW
authors.lastname: Weiner
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA; Department of Neurology, University of Southern California, Los Angeles, CA, USA; Department of Psychiatry, University of Southern California, Los Angeles, CA, USA; Department of Radiology, University of Southern California, Los Angeles, CA, USA; Department of Engineering, University of Southern California, Los Angeles, CA, USA; Department of Pediatrics, University of Southern California, Los Angeles, CA, USA; Department of Ophthalmology, University of Southern California, Los Angeles, CA, USA. Electronic address: pthomp@usc.edu.
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology* / Q000523:psychology; D001921:Brain / Q000503:physiopathology*; D003071:Cognition; D060825:Cognitive Dysfunction / Q000175:diagnosis / Q000473:pathology / Q000503:physiopathology / Q000523:psychology; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D004522:Educational Status; D005260:Female; D005838:Genotype; D006801:Humans; D016014:Linear Models; D008297:Male; D009415:Nerve Net / Q000473:pathology* / Q000503:physiopathology*; D009431:Neural Conduction; D059906:Neuroimaging / Q000379:methods*
keywords: APOE4; Brain connectivity; HARDI tractography; Multivariate analysis; Neuroimaging genetics; Seemingly unrelated regression (SUR)