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. ,   Social Science Genetic Association Consortium, Kweon Hyeokmoon , Koellinger Philipp D. , Benjamin Daniel J. , Turley Patrick ,   Within Family Consortium, 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 , 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 , 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 , Pedersen Nancy L. , Porteous David J. , Silventoinen Karri , Southey Melissa C. , Stoltenberg Camilla , Tucker-Drob Elliot M. , Wright Margaret J. , 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. , 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 , Koellinger Philipp D. , Kaprio Jaakko , Medland Sarah E. , Walters Robin G. , Benjamin Daniel J. , Turley Patrick , Evans David M. , Davey Smith George , Hayward Caroline , Brumpton Ben , Hemani Gibran , Davies Neil M. 
Published: May 2022

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.