@article{4451ac61d3cd4994a6ed3bd44aea90fa,
title = "Multi-site meta-analysis of morphometry",
abstract = "Genome-wide association studies GWAS link full genome data to a handful of traits. However, in neuroimaging studies, there is an almost unlimited number of traits that can be extracted for full image-wide big data analyses. Large populations are needed to achieve the necessary power to detect statistically significant effects, emphasizing the need to pool data across multiple studies. Neuroimaging consortia, e.g., ENIGMA and CHARGE, are now analyzing MRI data from over 30,000 individuals. Distributed processing protocols extract harmonized features at each site, and pool together only the cohort statistics using meta analysis to avoid data sharing. To date, such MRI projects have focused on single measures such as hippocampal volume, yet voxelwise analyses e.g., tensor-based morphometry; TBM may help better localize statistical effects. This can lead to 1013 tests for GWAS and become underpowered. We developed an analytical framework for multi-site TBM by performing multi-channel registration to cohort-specific templates. Our results highlight the reliability of the method and the added power over alternative options while preserving single site specificity and opening the doors for well-powered image-wide genome-wide discoveries.",
keywords = "ENIGMA, imaging genetics, mass univariate, meta-analysis, multi-channel registration, multi-site, voxelwise",
author = "Neda Jahanshad and Joshua Faskowitz and Gennady Roshchupkin and Hibar, {Derrek P.} and Gutman, {Boris A.} and Tustison, {Nicholas J.} and Adams, {Hieab H.H.} and Niessen, {Wiro J.} and Vernooij, {Meike W.} and Ikram, {M. Arfan} and Zwiers, {Marcel P.} and Vasquez, {Alejandro Arias} and Barbara Franke and Kroll, {Jennifer L.} and Benson Mwangi and Soares, {Jair C.} and Alex Ing and Sylvane Desrivieres and Gunter Schumann and Hansell, {Narelle K.} and {De Zubicaray}, {Greig I.} and McMahon, {Katie L.} and Martin, {Nicholas G.} and Wright, {Margaret J.} and Thompson, {Paul M.}",
note = "Funding Information: Funding for the ENIGMA Center for Worldwide Medicine Imaging and Genomics is provided as part of the 2014 NIH Big Data to Knowledge (BD2K) Initiative under U54EB020403 (PI: Thompson) to support big data analytics, management, and distribution of programs. Additional support was provided by R01AG059874 (Jahanshad). ADNI: Data collection and sharing for this project was funded by the Alzheimer{\textquoteright}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 the following: Alzheimer{\textquoteright}s Association; Alzheimer{\textquoteright}s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; 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.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neuro-track Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. 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{\textquoteright}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. BIG: This work makes use of the BIG (Brain Imaging Genetics) database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers of the Donders Centre for Cognitive Neuro-imaging, the Human Genetics and Cognitive Neuroscience Departments of the Radboud University Medical Centre, and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative is supported by the participating departments and centres and by external grants, i.e., the Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL), the Hersenstichting Nederland, and the Netherlands Organisation for Scientific Research (NWO). The research leading to these results also received funding from the European Community{\textquoteleft}s Seventh Framework Programme (FP7/2007–2013) under grant agreements number 602450 (IMAGEMEND) and number 602805 (Aggressotype) and from the National Institutes of Health (NIH) Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centers of Excellence. B. Franke is supported by a personal Vici grant from NWO (grant number 016-130-669). QTIM: QTIM was funded by the Australian National Health and Medical Research Council (Project Grants No. 496682 and 1009064) and the US National Institute of Child Health and Human Development (R01HD050735). The authors are grateful to the twins for their generosity of time and willingness to participate in our study. They also thank the many research assistants, radiographers, and other staff at the QIMR Berghofer Medical Research Institute and the Centre for Advanced Imaging, University of Queensland. Rotterdam: The generation and management of GWAS genotype data for the Rotterdam Study are supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project nr. 050-060-810. The Rotterdam Study is funded by the Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture, and Science, the Ministry for Health, Welfare, and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. This research is supported by the Dutch Technology Foundation STW, which is part of the NWO, and which is partly funded by the Ministry of Economic Affairs. MAI is supported by ZonMW grant number 916.13.054. HHHA is supported by the Van Leersum Grant of the Royal Netherlands Academy of Arts and Sciences. Publisher Copyright: {\textcopyright} 2019 Georg Thieme Verlag. All rights reserved.",
year = "2019",
month = sep,
doi = "10.1109/TCBB.2019.2914905",
language = "English",
volume = "16",
pages = "1508--1514",
journal = "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
issn = "1545-5963",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "5",
}