One for all and all for One: Improving replication of genetic studies through network diffusion

Daniel Lancour; Adam Naj; Richard Mayeux; Jonathan L Haines; Margaret A Pericak-Vance; Gerard D Schellenberg; Mark Crovella; Lindsay A Farrer; Simon Kasif

doi:10.1371/journal.pgen.1007306

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One for all and all for One: Improving replication of genetic studies through network diffusion

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One for all and all for One: Improving replication of genetic studies through network diffusion

Daniel Lancour, Adam Naj, Richard Mayeux, Jonathan L Haines, Margaret A Pericak-Vance, Gerard D Schellenberg, Mark Crovella, Lindsay A Farrer and Simon Kasif

PLoS genetics, Vol.14(4), pp.e1007306-e1007306

2018-04

DOI: https://doi.org/10.1371/journal.pgen.1007306

PMCID: PMC5933817

PMID: 29684019

Appears in UM Open Access Research Published in PloS

Abstract

Genome-Wide Association Study

Reproducibility of Results

Datasets as Topic

Humans

Risk Factors

Alzheimer Disease - metabolism

Support Vector Machine

Alzheimer Disease - genetics

Protein Interaction Maps

Improving accuracy in genetic studies would greatly accelerate understanding the genetic basis of complex diseases. One approach to achieve such an improvement for risk variants identified by the genome wide association study (GWAS) approach is to incorporate previously known biology when screening variants across the genome. We developed a simple approach for improving the prioritization of candidate disease genes that incorporates a network diffusion of scores from known disease genes using a protein network and a novel integration with GWAS risk scores, and tested this approach on a large Alzheimer disease (AD) GWAS dataset. Using a statistical bootstrap approach, we cross-validated the method and for the first time showed that a network approach improves the expected replication rates in GWAS studies. Several novel AD genes were predicted including CR2, SHARPIN, and PTPN2. Our re-prioritized results are enriched for established known AD-associated biological pathways including inflammation, immune response, and metabolism, whereas standard non-prioritized results were not. Our findings support a strategy of considering network information when investigating genetic risk factors.

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Collaboration types: Domestic collaboration
Citation topics: 1 Clinical & Life Sciences; 1.52 Neurodegenerative Diseases; 1.52.57 Alzheimer's Disease
Web Of Science research areas: Genetics & Heredity
ESI research areas: Molecular Biology & Genetics

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Title: One for all and all for One: Improving replication of genetic studies through network diffusion
Creators: Daniel Lancour - Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts, United States of America
Adam Naj - Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
Richard Mayeux - Department of Neurology and Sergievsky Center, Columbia University, New York, New York, United States of America
Jonathan L Haines - Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
Margaret A Pericak-Vance - Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida, United States of America
Gerard D Schellenberg - Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
Mark Crovella - Department of Computer Science, Boston University, Boston, Massachusetts, United States of America
Lindsay A Farrer - Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, United States of America
Simon Kasif - Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
Publication Details: PLoS genetics, Vol.14(4), pp.e1007306-e1007306
Publisher: United States
Grant note: R01 AG30146 / NIH HHS P30 AG028377 / NIA NIH HHS P50 NS039764 / NINDS NIH HHS R01 AG17917 / NIH HHS P50 AG005144 / NIA NIH HHS R01 AG027944 / NIA NIH HHS R01 AG030146 / NIA NIH HHS R01 AG031581 / NIH HHS P50 MH060451 / NIMH NIH HHS P50 AG005142 / NIH HHS P30 AG028377 / NIH HHS P01 AG03991 / NIH HHS AG07562 / NIH HHS P50 AG008702 / NIA NIH HHS P50 AG023501 / NIA NIH HHS R37 AG015473 / NIA NIH HHS P01 AG010491 / NIA NIH HHS AG05128 / NIH HHS P50 AG005681 / NIA NIH HHS P30 AG008017 / NIA NIH HHS R01 AG031581 / NIA NIH HHS P50 AG023501 / NIH HHS P30 AG028383 / NIH HHS R01 AG019085 / NIA NIH HHS 1RC2AG036502 / NIH HHS P01 AG002219 / NIH HHS R01 AG030653 / NIA NIH HHS R01 AG041797 / NIA NIH HHS R01 AG021547 / NIA NIH HHS P50 AG016573 / NIA NIH HHS P01 AG019724 / NIA NIH HHS P50 AG008702 / NIH HHS R01 MH080295 / NIMH NIH HHS AG019757 / NIH HHS P30 AG013854 / NIH HHS P50 AG005134 / NIA NIH HHS U24-AG041689-01 / NIH HHS U01 AG032984 / NIH HHS P50 AG016574 / NIH HHS P50 AG005128 / NIA NIH HHS Wellcome Trust RF1 AG057519 / NIA NIH HHS R01 AG048927 / NIA NIH HHS AG030653 / NIH HHS AG025688 / NIH HHS R01 CA129769 / NCI NIH HHS R01 AG035137 / NIA NIH HHS P50 AG005134 / NIH HHS AG021547 / NIH HHS T32 GM100842 / NIGMS NIH HHS U24 AG21886 / NIH HHS R01 AG027944 / NIH HHS P30 AG019610 / NIH HHS P30 AG010161 / NIH HHS R01 MH080295 / NIH HHS P30 AG010129 / NIA NIH HHS R01 AG019085 / NIH HHS R01 AG020688 / NIA NIH HHS R01 AG022374 / NIA NIH HHS P30 AG008017 / NIH HHS R01 AG026916 / NIA NIH HHS P50 AG005142 / NIA NIH HHS RC2 AG036528 / NIH HHS UO1 HG004610 / NIH HHS R01 NS059873 / NINDS NIH HHS P30 AG010124 / NIA NIH HHS U24 AG026395 / NIA NIH HHS U01 AG016976 / NIA NIH HHS P30 AG10133 / NIH HHS U24 AG021886 / NIA NIH HHS R01 AG017917 / NIA NIH HHS P50 AG016573 / NIH HHS UO1 AG006781 / NIH HHS P30 AG008051 / NIA NIH HHS U01 AG032984 / NIA NIH HHS R01 AG15819 / NIH HHS P50 AG016574 / NIA NIH HHS U01 AG006781 / NIA NIH HHS P50 AG008671 / NIA NIH HHS AG041718 / NIH HHS R01 AG019757 / NIA NIH HHS 5R01AG012101 / NIH HHS RC2 AG036528 / NIA NIH HHS R37 AG015473 / NIH HHS R01 AG041232 / NIA NIH HHS R01 AG041718 / NIA NIH HHS P50 AG005131 / NIA NIH HHS P50 AG005133 / NIH HHS R01 NS059873 / NIH HHS P30 AG019610 / NIA NIH HHS P01 AG002219 / NIA NIH HHS UL1 TR001445 / NCATS NIH HHS P50 AG005136 / NIA NIH HHS U01 AG024904 / NIA NIH HHS R01 AG025259 / NIH HHS P30 AG013846 / NIH HHS U24 AG026395 / NIH HHS R01 AG026916 / NIH HHS P01 AG019724 / NIH HHS P50 AG016582 / NIH HHS P50 AG005138 / NIH HHS UO1 HG006375 / NIH HHS P30 AG08051 / NIH HHS U01 HG006375 / NHGRI NIH HHS P50 AG005146 / NIA NIH HHS P30 AG010124 / NIH HHS P50 AG016582 / NIA NIH HHS P01 AG026276 / NIA NIH HHS R01AG041797 / NIH HHS R01 CA129769 / NIH HHS R01 AG020688 / NIH HHS P50 AG016570 / NIA NIH HHS U01 HG004610 / NHGRI NIH HHS R01AG33193 / NIH HHS P50 AG033514 / NIA NIH HHS P30 AG010129 / NIH HHS 1R01AG035137 / NIH HHS P50 AG005681 / NIH HHS U01 AG016976 / NIH HHS P30 AG010161 / NIA NIH HHS U01 AG10483 / NIH HHS P30 AG013854 / NIA NIH HHS R01 AG012101 / NIA NIH HHS U24 AG041689 / NIA NIH HHS AG027944 / NIH HHS R01 AG017173 / NIA NIH HHS AG05144 / NIH HHS R01 AG015819 / NIA NIH HHS P50 AG005146 / NIH HHS R01 AG033193 / NIA NIH HHS P50 AG008671 / NIH HHS 5R01AG022374 / NIH HHS AG02365 / NIH HHS P30 AG012300 / NIH HHS U01 AG010483 / NIA NIH HHS P30 AG028383 / NIA NIH HHS P30 AG012300 / NIA NIH HHS P30 AG010133 / NIA NIH HHS P50 AG005133 / NIA NIH HHS R01 AG013616 / NIA NIH HHS R01 AG048927 / NIH HHS P50 AG025688 / NIA NIH HHS P01 AG003991 / NIA NIH HHS P50 AG005131 / NIH HHS 5R01AG013616 / NIH HHS R01 AG017173 / NIH HHS P30 AG013846 / NIA NIH HHS R01 AG025259 / NIA NIH HHS P50 AG005138 / NIA NIH HHS UL1 RR029893 / NIH HHS P50 AG005136 / NIH HHS UL1 RR029893 / NCRR NIH HHS AG010491 / NIH HHS P50 AG033514 / NIH HHS P50 AG016570 / NIH HHS RC2 AG036502 / NIA NIH HHS
Academic Unit: Miller School of Medicine; John P. Hussman Institute for Human Genomics; UMMG Dept of Human Genetics (Dr. John T. Macdonald Foundation)
Language: English
Resource Type: Journal article
PMID: 29684019
PMCID: PMC5933817
Record Identifier: 991031576400302976