Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
33785739
TITLE
Model-based assessment of replicability for genome-wide association meta-analysis.
ABSTRACT
Genome-wide association meta-analysis (GWAMA) is an effective approach to enlarge sample sizes and empower the discovery of novel associations between genotype and phenotype. Independent replication has been used as a gold-standard for validating genetic associations. However, as current GWAMA often seeks to aggregate all available datasets, it becomes impossible to find a large enough independent dataset to replicate new discoveries. Here we introduce a method, MAMBA (Meta-Analysis Model-based Assessment of replicability), for assessing the "posterior-probability-of-replicability" for identified associations by leveraging the strength and consistency of association signals between contributing studies. We demonstrate using simulations that MAMBA is more powerful and robust than existing methods, and produces more accurate genetic effects estimates. We apply MAMBA to a large-scale meta-analysis of addiction phenotypes with 1.2 million individuals. In addition to accurately identifying replicable common variant associations, MAMBA also pinpoints novel replicable rare variant associations from imputation-based GWAMA and hence greatly expands the set of analyzable variants.
DATE PUBLISHED
2021 03 30
HISTORY
PUBSTATUS PUBSTATUSDATE
received 2019/12/17
accepted 2021/01/07
entrez 2021/03/31 06:11
pubmed 2021/04/01 06:00
medline 2021/04/20 06:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
McGuire D McGuire Daniel D Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
Jiang Y Jiang Yu Y Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
Liu M Liu Mengzhen M Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
Weissenkampen JD Weissenkampen J Dylan JD Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
Eckert S Eckert Scott S Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
Yang L Yang Lina L Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
Chen F Chen Fang F Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
GWAS and Sequencing Consortium of Alcohol and Nicotine Use (GSCAN)
Berg A Berg Arthur A Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
Vrieze S Vrieze Scott S Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
Jiang B Jiang Bibo B Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA. bjiang@phs.psu.edu.
Li Q Li Qunhua Q Department of Statistics, Penn State University, University Park, PA, USA. qunhua.li@psu.edu.
Liu DJ Liu Dajiang J DJ Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA. dajiang.liu@psu.edu.
INVESTIGATORS
LASTNAME FORENAME INITIALS AFFILIATION
Liu Mengzhen M
Jiang Yu Y
Wedow Robbee R
Li Yue Y
Brazel David M DM
Chen Fang F
Datta Gargi G
Davila-Velderrain Jose J
McGuire Daniel D
Tian Chao C
Zhan Xiaowei X
Choquet H Éléne
Docherty Anna R AR
Faul Jessica D JD
Foerster Johanna R JR
Fritsche Lars G LG
Gabrielsen Maiken Elvestad ME
Gordon Scott D SD
Haessler Jeffrey J
Hottenga Jouke-Jan JJ
Huang Hongyan H
Jang Seon-Kyeong SK
Jansen Philip R PR
Ling Yueh Y
Ma Gi Reedik R
Matoba Nana N
McMahon George G
Mulas Antonella A
Orru Valeria V
Palviainen Teemu T
Pandit Anita A
Reginsson Gunnar W GW
Skogholt Anne Heidi AH
Smith Jennifer A JA
Taylor Amy E AE
Turman Constance C
Willemsen Gonneke G
Young Hannah H
Young Kendra A KA
Zajac Gregory J M GJM
Zhao Wei W
Zhou Wei W
Bjornsdottir Gyda G
Boardman Jason D JD
Boehnke Michael M
Boomsma Dorret I DI
Chen Chu C
Cucca Francesco F
Davies Gareth E GE
Eaton Charles B CB
Ehringer Marissa A MA
Esko To Nu TN
Fiorillo Edoardo E
Gillespie Nathan A NA
Gudbjartsson Daniel F DF
Haller Toomas T
Harris Kathleen Mullan KM
Heath Andrew C AC
Hewitt John K JK
Hickie Ian B IB
Hokanson John E JE
Hopfer Christian J CJ
Hunter David J DJ
Iacono William G WG
Johnson Eric O EO
Kamatani Yoichiro Y
Kardia Sharon L R SLR
Keller Matthew C MC
Kellis Manolis M
Kooperberg Charles C
Kraft Peter P
Krauter Kenneth S KS
Laakso Markku M
Lind Penelope A PA
Loukola Anu A
Lutz Sharon M SM
Madden Pamela A F PAF
Martin Nicholas G NG
McGue Matt M
McQueen Matthew B MB
Medland Sarah E SE
Metspalu Andres A
Mohlke Karen L KL
Nielsen Jonas B JB
Okada Yukinori Y
Peters Ulrike U
Polderman Tinca J C TJC
Posthuma Danielle D
Reiner Alexander P AP
Rice John P JP
Rimm Eric E
Rose Richard J RJ
Runarsdottir Valgerdur V
Stallings Michael C MC
Stanˇca Kova Alena A
Stefansson Hreinn H
Thai Khanh K KK
Tindle Hilary A HA
Tyrfingsson Thorarinn T
Wall Tamara L TL
Weir David R DR
Weisner Constance C
Whitfield John B JB
Winsvold Bendik Slagsvold BS
Yin Jie J
Zuccolo Luisa L
Bierut Laura J LJ
Hveem Kristian K
Lee James J JJ
Munafo Marcus R MR
Saccone Nancy L NL
Willer Cristen J CJ
Cornelis Marilyn C MC
David Sean P SP
Hinds David D
Jorgenson Eric E
Kaprio Jaakko J
Stitzel Jerry A JA
Stefansson Kari K
Thorgeirsson Thorgeir E TE
Abecasis Goncalo G
Liu Dajiang J DJ
Vrieze Scott S
JOURNAL
VOLUME: 12
ISSUE: 1
TITLE: Nature communications
ISOABBREVIATION: Nat Commun
YEAR: 2021
MONTH: 03
DAY: 30
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Internet
ISSN: 2041-1723
ISSNTYPE: Electronic
MEDLINE JOURNAL
MEDLINETA: Nat Commun
COUNTRY: England
ISSNLINKING: 2041-1723
NLMUNIQUEID: 101528555
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
Research Support, N.I.H., Extramural
COMMENTS AND CORRECTIONS
GRANTS
GRANTID AGENCY COUNTRY
R21 DA040177 NIDA NIH HHS United States
R01 DA037904 NIDA NIH HHS United States
R01 GM126479 NIGMS NIH HHS United States
R56 HG011035 NHGRI NIH HHS United States
R01 HG008983 NHGRI NIH HHS United States
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Algorithms
Computational Biology methods
Genetic Association Studies methods
Genome-Wide Association Study methods
Genotype methods
Meta-Analysis as Topic methods
Models, Genetic methods
Phenotype methods
Polymorphism, Single Nucleotide methods
Reproducibility of Results methods
Sample Size methods
Software methods
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's