ORIGINAL RESEARCH ARTICLE published: 06 August 2012 doi: 10.3389/fnins.2012.00115 Discovery and replication of gene inﬂuences on brain structure using LASSO regression Omid Kohannim1, Derrek P. Hibar 1, Jason L. Stein1, Neda Jahanshad 1, Xue Hua1, Priya Rajagopalan1, Arthur W. Toga1, Clifford R. Jack Jr.2, Michael W. Weiner 3,4,5,6, Greig I. de Zubicaray 7, Katie L. McMahon8, Narelle K. Hansell 9, Nicholas G. Martin9, Margaret J. Wright 9, Paul M. Thompson1* and The Alzheimer’s Disease Neuroimaging Initiative† 1 Imaging Genetics Center at the Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA, USA 2 Mayo Clinic, Rochester, MN, USA 3 Department of Radiology, UC San Francisco, San Francisco, CA, USA 4 Department of Medicine, UC San Francisco, San Francisco, CA, USA 5 Department of Psychiatry, UC San Francisco, San Francisco, CA, USA 6 Department of Veterans Affairs Medical Center, San Francisco, CA, USA 7 School of Psychology, University of Queensland, Brisbane, QLD, Australia 8 Center for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia 9 Queensland Institute of Medical Research, Brisbane, QLD, Australia Edited by: Leonard C. Schalkwyk, King’s College London, UK Reviewed by: Matthew Davies, King’s College London, UK Andre Marquand, King’s College London, UK *Correspondence: Paul M. Thompson, Imaging Genetics Center at the Laboratory of Neuro Imaging, Department of Neurology, University of California Los Angeles, School of Medicine, Neuroscience Research Building 225E, 635 Charles Young Drive, Los Angeles, CA 90095-1769, USA. e-mail: thompson@loni.ucla.edu †Data used in preparing this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (www.loni.ucla.edu/ADNI). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. For a complete listing of ADNI investigators, please see: http://adni. loni.ucla.edu/wp-content/uploads/ how_to_apply/ADNI_Manuscript_ Citations.pdf 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 neu- roimaging 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 neu- ropsychiatric 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. Keywords: neuroimaging, MRI, imaging genetics, GWAS, LASSO, MACROD2 INTRODUCTION Genome-wide association studies (GWAS) offer a powerful approach to discover genes that affect individual risk for devel- oping neurological and psychiatric disorders. Several high- density GWAS studies of Alzheimer’s disease (AD), in par- ticular (e.g., Grupe et al., 2006), have identiﬁed genes that consistently affect AD risk across multiple populations and ethnic groups, with varying degrees of aggregated evidence. Among others, these include highly replicated risk genes such as ApoE,1 CLU,2 PICALM,3 and CR14 (Corder et al., 1993; Harold et al., 2009; Lambert et al., 2009), as well as others supported by moderate evidence GAB2,5 1Apolipoprotein E 2Clusterin 3Phosphatidylinositol binding clathrin assembly protein 4Complement component (3b/4b) receptor 1 5GRB2-associated binding protein 2 www.frontiersin.org August 2012 | Volume 6 | Article 115 | 1