Abstract
Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
Original language | English |
---|---|
Pages (from-to) | 236-248 |
Number of pages | 13 |
Journal | American journal of human genetics |
Volume | 93 |
Issue number | 2 |
DOIs | |
State | Published - Aug 8 2013 |
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In: American journal of human genetics, Vol. 93, No. 2, 08.08.2013, p. 236-248.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Meta-analysis of gene-level associations for rare variants based on single-variant statistics
AU - Hu, Yi Juan
AU - Berndt, Sonja I.
AU - Gustafsson, Stefan
AU - Ganna, Andrea
AU - Ingelsson, Erik
AU - Hirschhorn, Joel
AU - North, Kari E.
AU - Lin, Dan Yu
AU - Berndt, Sonja I.
AU - Gustafsson, Stefan
AU - Mägi, Reedik
AU - Ganna, Andrea
AU - Wheeler, Eleanor
AU - Feitosa, Mary F.
AU - Justice, Anne E.
AU - Monda, Keri L.
AU - Croteau-Chonka, Damien C.
AU - Day, Felix R.
AU - Esko, To˜nu
AU - Fall, Tove
AU - Ferreira, Teresa
AU - Gentilini, Davide
AU - Jackson, Anne U.
AU - Luan, Jian’an
AU - Randall, Joshua C.
AU - Vedantam, Sailaja
AU - Willer, Cristen J.
AU - Winkler, Thomas W.
AU - Wood, Andrew R.
AU - Workalemahu, Tsegaselassie
AU - Hu, Yi Juan
AU - Lee, Sang Hong
AU - Liang, Liming
AU - Lin, Dan Yu
AU - Min, Josine L.
AU - Neale, Benjamin M.
AU - Thorleifsson, Gudmar
AU - Yang, Jian
AU - Albrecht, Eva
AU - Amin, Najaf
AU - Bragg-Gresham, Jennifer L.
AU - Cadby, Gemma
AU - Heijer, Martin den
AU - Eklund, Niina
AU - Fischer, Krista
AU - Goel, Anuj
AU - Hottenga, Jouke Jan
AU - Huffman, Jennifer E.
AU - Jarick, Ivonne
AU - Johansson, Asa
AU - Johnson, Toby
AU - Kanoni, Stavroula
AU - Kleber, Marcus E.
AU - König, Inke R.
AU - Kristiansson, Kati
AU - Kutalik, Zoltán
AU - Lamina, Claudia
AU - Lecoeur, Cecile
AU - Li, Guo
AU - Mangino, Massimo
AU - McArdle, Wendy L.
AU - Medina-Gomez, Carolina
AU - Müller-Nurasyid, Martina
AU - Ngwa, Julius S.
AU - Nolte, Ilja M.
AU - Paternoster, Lavinia
AU - Pechlivanis, Sonali
AU - Perola, Markus
AU - Peters, Marjolein J.
AU - Preuss, Michael
AU - Rose, Lynda M.
AU - Shi, Jianxin
AU - Shungin, Dmitry
AU - Smith, Albert Vernon
AU - Strawbridge, Rona J.
AU - Surakka, Ida
AU - Teumer, Alexander
AU - Trip, Mieke D.
AU - Tyrer, Jonathan
AU - Vliet-Ostaptchouk, Jana V.Van
AU - Vandenput, Liesbeth
AU - Waite, Lindsay L.
AU - Zhao, Jing Hua
AU - Absher, Devin
AU - Asselbergs, Folkert W.
AU - Atalay, Mustafa
AU - Attwood, Antony P.
AU - Balmforth, Anthony J.
AU - Basart, Hanneke
AU - Beilby, John
AU - Bonnycastle, Lori L.
AU - Brambilla, Paolo
AU - Bruinenberg, Marcel
AU - Campbell, Harry
AU - Chasman, Daniel I.
AU - Chines, Peter S.
AU - Connell, John M.
AU - Cookson, William
AU - Faire, Ulf de
AU - Vegt, Femmie de
AU - Dei, Mariano
AU - Dimitriou, Maria
AU - Edkins, Sarah
AU - Estrada, Karol
AU - Evans, David M.
AU - Farrall, Martin
AU - Ferrario, Marco M.
AU - Ferrières, Jean
AU - Franke, Lude
AU - Frau, Francesca
AU - Gejman, Pablo V.
AU - Grallert, Harald
AU - Grönberg, Henrik
AU - Gudnason, Vilmundur
AU - Hall, Alistair S.
AU - Hall, Per
AU - Hartikainen, Anna Liisa
AU - Hayward, Caroline
AU - Heard-Costa, Nancy L.
AU - Heath, Andrew C.
AU - Hebebrand, Johannes
AU - Homuth, Georg
AU - Hu, Frank B.
AU - Hunt, Sarah E.
AU - Hyppönen, Elina
AU - Iribarren, Carlos
AU - Jacobs, Kevin B.
AU - Jansson, John Olov
AU - Jula, Antti
AU - Kähönen, Mika
AU - Kathiresan, Sekar
AU - Kee, Frank
AU - Khaw, Kay Tee
AU - Kivimaki, Mika
AU - Koenig, Wolfgang
AU - Kraja, Aldi T.
AU - Kumari, Meena
AU - Kuulasmaa, Kari
AU - Kuusisto, Johanna
AU - Laitinen, Jaana H.
AU - Lakka, Timo A.
AU - Langenberg, Claudia
AU - Launer, Lenore J.
AU - Lind, Lars
AU - Lindström, Jaana
AU - Liu, Jianjun
AU - Liuzzi, Antonio
AU - Lokki, Marja Liisa
AU - Lorentzon, Mattias
AU - Magnusson, Pamela A.Madden
AU - Magnusson, P. A.M.
AU - Manunta, Paolo
AU - Marek, Diana
AU - März, Winfried
AU - Leach, Irene Mateo
AU - McKnight, Barbara
AU - Medland, Sarah E.
AU - Mihailov, Evelin
AU - Milani, Lili
AU - Montgomery, Grant W.
AU - Mooser, Vincent
AU - Mühleisen, Thomas W.
AU - Munroe, Patricia B.
AU - Musk, Arthur W.
AU - Narisu, Narisu
AU - Navis, Gerjan
AU - Nicholson, George
AU - Nohr, Ellen A.
AU - Ong, Ken K.
AU - Oostra, Ben A.
AU - Palmer, Colin N.A.
AU - Palotie, Aarno
AU - Peden, John F.
AU - Pedersen, Nancy
AU - Peters, Annette
AU - Polasek, Ozren
AU - Pouta, Anneli
AU - Pramstaller, Peter P.
AU - Prokopenko, Inga
AU - Pütter, Carolin
AU - Radhakrishnan, Aparna
AU - Raitakari, Olli
AU - Rendon, Augusto
AU - Rivadeneira, Fernando
AU - Rudan, Igor
AU - Saaristo, Timo E.
AU - Sambrook, Jennifer G.
AU - Sanders, Alan R.
AU - Sanna, Serena
AU - Saramies, Jouko
AU - Schipf, Sabine
AU - Schreiber, Stefan
AU - Schunkert, Heribert
AU - Shin, So Youn
AU - Signorini, Stefano
AU - Sinisalo, Juha
AU - Skrobek, Boris
AU - Soranzo, Nicole
AU - Stancáková, Alena
AU - Stark, Klaus
AU - Stephens, Jonathan C.
AU - Stirrups, Kathleen
AU - Stolk, Ronald P.
AU - Stumvoll, Michael
AU - Swift, Amy J.
AU - Theodoraki, Eirini V.
AU - Thorand, Barbara
AU - Tregouet, David Alexandre
AU - Tremoli, Elena
AU - Klauw, Melanie M.Van der
AU - Meurs, Joyce B.J.van
AU - Vermeulen, Sita H.
AU - Viikari, Jorma
AU - Virtamo, Jarmo
AU - Vitart, Veronique
AU - Waeber, Gérard
AU - Wang, Zhaoming
AU - Widén, Elisabeth
AU - Wild, Sarah H.
AU - Willemsen, Gonneke
AU - Winkelmann, Bernhard R.
AU - Witteman, Jacqueline C.M.
AU - Wolffenbuttel, Bruce H.R.
AU - Wong, Andrew
AU - Wright, Alan F.
AU - Zillikens, M. Carola
AU - Amouyel, Philippe
AU - Boehm, Bernhard O.
AU - Boerwinkle, Eric
AU - Boomsma, Dorret I.
AU - Caulfield, Mark J.
AU - Chanock, Stephen J.
AU - Cupples, L. Adrienne
AU - Cusi, Daniele
AU - Dedoussis, George V.
AU - Erdmann, Jeanette
AU - Eriksson, Johan G.
AU - Franks, Paul W.
AU - Froguel, Philippe
AU - Gieger, Christian
AU - Gyllensten, Ulf
AU - Hamsten, Anders
AU - Harris, Tamara B.
AU - Hengstenberg, Christian
AU - Hicks, Andrew A.
AU - Hingorani, Aroon
AU - Hinney, Anke
AU - Hofman, Albert
AU - Hovingh, Kees G.
AU - Hveem, Kristian
AU - Illig, Thomas
AU - Jarvelin, Marjo Riitta
AU - Jöckel, Karl Heinz
AU - Keinanen-Kiukaanniemi, Sirkka M.
AU - Kiemeney, Lambertus A.
AU - Kuh, Diana
AU - Laakso, Markku
AU - Lehtimäki, Terho
AU - Levinson, Douglas F.
AU - Martin, Nicholas G.
AU - Metspalu, Andres
AU - Morris, Andrew D.
AU - Nieminen, Markku S.
AU - Njølstad, Inger
AU - Ohlsson, Claes
AU - Oldehinkel, Albertine J.
AU - Ouwehand, Willem H.
AU - Palmer, Lyle J.
AU - Penninx, Brenda
AU - Power, Chris
AU - Province, Michael A.
AU - Psaty, Bruce M.
AU - Qi, Lu
AU - Rauramaa, Rainer
AU - Ridker, Paul M.
AU - Ripatti, Samuli
AU - Salomaa, Veikko
AU - Samani, Nilesh J.
AU - Snieder, Harold
AU - Sørensen, Thorkild I.A.
AU - Spector, Timothy D.
AU - Stefansson, Kari
AU - Tönjes, Anke
AU - Tuomilehto, Jaakko
AU - Uitterlinden, André G.
AU - Uusitupa, Matti
AU - Harst, Pim van der
AU - Vollenweider, Peter
AU - Wallaschofski, Henri
AU - Wareham, Nicholas J.
AU - Watkins, Hugh
AU - Wichmann, H. Erich
AU - Wilson, James F.
AU - Abecasis, Goncalo R.
AU - Assimes, Themistocles L.
AU - Barroso, Inês
AU - Boehnke, Michael
AU - Borecki, Ingrid B.
AU - Deloukas, Panos
AU - Fox, Caroline S.
AU - Frayling, Timothy
AU - Groop, Leif C.
AU - Haritunian, Talin
AU - Heid, Iris M.
AU - Hunter, David
AU - Kaplan, Robert C.
AU - Karpe,MiriamMoffatt, Fredrik
AU - Mohlke, Karen L.
AU - O’Connell, Jeffrey R.
AU - Pawitan, Yudi
AU - Schadt, Eric E.
AU - Schlessinger, David
AU - Steinthorsdottir, Valgerdur
AU - Strachan, David P.
AU - Thorsteinsdottir, Unnur
AU - Duijn, Cornelia M.van
AU - Visscher, Peter M.
AU - Blasio, Anna Maria Di
AU - Hirschhorn, Joel N.
AU - Lindgren, Cecilia M.
AU - Morris, Andrew P.
AU - Meyre, David
AU - Scherag, André
AU - McCarthy, Mark I.
AU - Speliotes, Elizabeth K.
AU - North, Kari E.
AU - Loos, Ruth J.F.
N1 - Funding Information: This research was supported by the National Institutes of Health awards R01CA082659 (D.-Y.L.), P01CA142538 (D.-Y.L.), and U01HG004803 (D.-Y.L., K.E.N.) and by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute (S.I.B.). ARIC is a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN26820110005C, HHSN26820110006C, HHSN26820110007C, HHSN26820110008C, HHSN26820110009C, HHSN268201100010C, HHSN268201100011C, HHSN268201100012C, and HHSN26800625226C) and grants R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contribution. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and the National Institutes of Health Roadmap for Medical Research.
PY - 2013/8/8
Y1 - 2013/8/8
N2 - Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
AB - Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
UR - http://www.scopus.com/inward/record.url?scp=84881660693&partnerID=8YFLogxK
U2 - 10.1016/j.ajhg.2013.06.011
DO - 10.1016/j.ajhg.2013.06.011
M3 - Article
C2 - 23891470
AN - SCOPUS:84881660693
SN - 0002-9297
VL - 93
SP - 236
EP - 248
JO - American journal of human genetics
JF - American journal of human genetics
IS - 2
ER -