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Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Authors :
Howe, Laurence J.
Nivard, Michel G.
Morris, Tim T.
Hansen, Ailin F.
Rasheed, Humaira
Cho, Yoonsu
Chittoor, Geetha
Ahlskog, Rafael
Lind, Penelope A.
Palviainen, Teemu
van der Zee, Matthijs D.
Cheesman, Rosa
Mangino, Massimo
Wang, Yunzhang
Li, Shuai
Klaric, Lucija
Ratliff, Scott M.
Bielak, Lawrence F.
Nygaard, Marianne
Giannelis, Alexandros
Willoughby, Emily A.
Reynolds, Chandra A.
Balbona, Jared V.
Andreassen, Ole A.
Ask, Helga
Baras, Aris
Bauer, Christopher R.
Boomsma, Dorret I.
Campbell, Archie
Campbell, Harry
Chen, Zhengming
Christofidou, Paraskevi
Corfield, Elizabeth
Dahm, Christina C.
Dokuru, Deepika R.
Evans, Luke M.
de Geus, Eco J. C.
Giddaluru, Sudheer
Gordon, Scott D.
Harden, K. Paige
Hill, W. David
Hughes, Amanda
Kerr, Shona M.
Kim, Yongkang
Kweon, Hyeokmoon
Latvala, Antti
Lawlor, Deborah A.
Li, Liming
Lin, Kuang
Magnus, Per
Magnusson, Patrik K. E.
Mallard, Travis T.
Martikainen, Pekka
Mills, Melinda C.
Njølstad, Pål Rasmus
Overton, John D.
Pedersen, Nancy L.
Porteous, David J.
Reid, Jeffrey
Silventoinen, Karri
Southey, Melissa C.
Stoltenberg, Camilla
Tucker-Drob, Elliot M.
Wright, Margaret J.
Koellinger, Philipp D.
Benjamin, Daniel J.
Turley, Patrick
Hewitt, John K.
Keller, Matthew C.
Stallings, Michael C.
Lee, James J.
Christensen, Kaare
Kardia, Sharon L. R.
Peyser, Patricia A.
Smith, Jennifer A.
Wilson, James F.
Hopper, John L.
Hägg, Sara
Spector, Tim D.
Pingault, Jean-Baptiste
Plomin, Robert
Havdahl, Alexandra
Bartels, Meike
Martin, Nicholas G.
Oskarsson, Sven
Justice, Anne E.
Millwood, Iona Y.
Hveem, Kristian
Naess, Øyvind
Willer, Cristen J.
Åsvold, Bjørn Olav
Kaprio, Jaakko
Medland, Sarah E.
Walters, Robin G.
Evans, David M.
Smith, George Davey
Hayward, Caroline
Brumpton, Ben
Hemani, Gibran
Davies, Neil M.
Davey Smith, George
Institute for Molecular Medicine Finland
Genetic Epidemiology
Institute of Criminology and Legal Policy
Population Research Unit (PRU)
Demography
Sociology
Helsinki Inequality Initiative (INEQ)
Center for Population, Health and Society
Biological Psychology
APH - Mental Health
APH - Methodology
AMS - Sports
AMS - Ageing & Vitality
APH - Personalized Medicine
Economics
Amsterdam Neuroscience - Complex Trait Genetics
Sociology [until 2010]
Source :
Nature genetics, vol 54, iss 5, Nature Genetics, Nature genetics, 54(5), 581-592. Nature Publishing Group, 2022, ' Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects ', Nature Genetics, vol. 54, no. 5, pp. 581-592 . https://doi.org/10.1038/s41588-022-01062-7, Howe, L J, Nivard, M G, Morris, T T, Hansen, A F, Rasheed, H, van der Zee, M D, Boomsma, D I, de Geus, E J C, Kweon, H, Koellinger, P D, Bartels, M, Davey Smith, G, Hayward, C, Brumpton, B, Hemani, G, Davies, N M & Social Science Genetic Association Consortium 2022, ' Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects ', Nature genetics, vol. 54, no. 5, pp. 581-592 . https://doi.org/10.1038/s41588-022-01062-7, Howe, L J, Nivard, M G, Morris, T T, Hansen, A F, Rasheed, H, Cho, Y, Chittoor, G, Ahlskog, R, Lind, P A, Palviainen, T, van der Zee, M D, Cheesman, R, Mangino, M, Wang, Y, Li, S, Klaric, L, Ratliff, S M, Bielak, L F, Nygaard, M, Giannelis, A, Willoughby, E A, Reynolds, C A, Balbona, J V, Andreassen, O A, Ask, H, Baras, A, Bauer, C R, Boomsma, D I, Campbell, A, Campbell, H, Chen, Z, Christofidou, P, Corfield, E, Dahm, C C, Dokuru, D R, Evans, L M, de Geus, E J C, Giddaluru, S, Gordon, S D, Harden, K P, Hill, W D, Hughes, A, Kerr, S M, Kim, Y, Kweon, H, Latvala, A, Lawlor, D A, Li, L, Lin, K, Christensen, K, Social Science Genetic Association Consortium & Within Family Consortium (Christina Dahm; member) 2022, ' Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects ', Nature Genetics, vol. 54, no. 5, pp. 581-592 . https://doi.org/10.1038/s41588-022-01062-7
Publication Year :
2022
Publisher :
Nature Portfolio, 2022.

Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects. Within-sibship genome-wide association analyses using data from 178,076 siblings illustrate differences between population-based and within-sibship GWAS estimates for phenotypes influenced by demographic and indirect genetic effects.

Details

ISSN :
10614036
Database :
OpenAIRE
Journal :
Nature genetics, vol 54, iss 5, Nature Genetics, Nature genetics, 54(5), 581-592. Nature Publishing Group, 2022, ' Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects ', Nature Genetics, vol. 54, no. 5, pp. 581-592 . https://doi.org/10.1038/s41588-022-01062-7, Howe, L J, Nivard, M G, Morris, T T, Hansen, A F, Rasheed, H, van der Zee, M D, Boomsma, D I, de Geus, E J C, Kweon, H, Koellinger, P D, Bartels, M, Davey Smith, G, Hayward, C, Brumpton, B, Hemani, G, Davies, N M & Social Science Genetic Association Consortium 2022, ' Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects ', Nature genetics, vol. 54, no. 5, pp. 581-592 . https://doi.org/10.1038/s41588-022-01062-7, Howe, L J, Nivard, M G, Morris, T T, Hansen, A F, Rasheed, H, Cho, Y, Chittoor, G, Ahlskog, R, Lind, P A, Palviainen, T, van der Zee, M D, Cheesman, R, Mangino, M, Wang, Y, Li, S, Klaric, L, Ratliff, S M, Bielak, L F, Nygaard, M, Giannelis, A, Willoughby, E A, Reynolds, C A, Balbona, J V, Andreassen, O A, Ask, H, Baras, A, Bauer, C R, Boomsma, D I, Campbell, A, Campbell, H, Chen, Z, Christofidou, P, Corfield, E, Dahm, C C, Dokuru, D R, Evans, L M, de Geus, E J C, Giddaluru, S, Gordon, S D, Harden, K P, Hill, W D, Hughes, A, Kerr, S M, Kim, Y, Kweon, H, Latvala, A, Lawlor, D A, Li, L, Lin, K, Christensen, K, Social Science Genetic Association Consortium & Within Family Consortium (Christina Dahm; member) 2022, ' Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects ', Nature Genetics, vol. 54, no. 5, pp. 581-592 . https://doi.org/10.1038/s41588-022-01062-7
Accession number :
edsair.doi.dedup.....c79333b5ded2e2eaeb727a1345dda5ae