Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects.
Creators: name: Howe, Laurence J
name: Nivard, Michel G
name: Morris, Tim T
name: Hansen, Ailin F
name: Rasheed, Humaira
name: Cho, Yoonsu
name: Chittoor, Geetha
name: Ahlskog, Rafael
name: Lind, Penelope A
name: Palviainen, Teemu
name: Van Der Zee, Matthijs D
name: Cheesman, Rosa
name: Mangino, Massimo
name: Wang, Yunzhang
name: Li, Shuai
name: Klaric, Lucija
name: Ratliff, Scott M
name: Bielak, Lawrence F
name: Nygaard, Marianne
name: Giannelis, Alexandros
name: Willoughby, Emily A
name: Reynolds, Chandra A
name: Balbona, Jared V
name: Andreassen, Ole A
name: Ask, Helga
name: Baras, Aris
name: Bauer, Christopher R
name: Boomsma, Dorret I
name: Campbell, Archie
name: Campbell, Harry
name: Chen, Zhengming
name: Christofidou, Paraskevi
name: Corfield, Elizabeth
name: Dahm, Christina C
name: Dokuru, Deepika R
name: Evans, Luke M
name: De Geus, Eco JC
name: Giddaluru, Sudheer
name: Gordon, Scott D
name: Harden, K Paige
name: Hill, W David
name: Hughes, Amanda
name: Kerr, Shona M
name: Kim, Yongkang
name: Kweon, Hyeokmoon
name: Latvala, Antti
name: Lawlor, Deborah A
name: Li, Liming
name: Lin, Kuang
name: Magnus, Per
name: Magnusson, Patrik KE
name: Mallard, Travis T
name: Martikainen, Pekka
name: Mills, Melinda C
name: Njølstad, Pål Rasmus
name: Overton, John D
name: Pedersen, Nancy L
name: Porteous, David J
name: Reid, Jeffrey
name: Silventoinen, Karri
name: Southey, Melissa C
name: Stoltenberg, Camilla
name: Tucker-Drob, Elliot M
name: Wright, Margaret J
name: Social Science Genetic Association Consortium
name: Within Family Consortium
name: Hewitt, John K
name: Keller, Matthew C
name: Stallings, Michael C
name: Lee, James J
name: Christensen, Kaare
name: Kardia, Sharon LR
name: Peyser, Patricia A
name: Smith, Jennifer A
name: Wilson, James F
name: Hopper, John L
name: Hägg, Sara
name: Spector, Tim D
name: Pingault, Jean-Baptiste
name: Plomin, Robert
name: Havdahl, Alexandra
name: Bartels, Meike
name: Martin, Nicholas G
name: Oskarsson, Sven
name: Justice, Anne E
name: Millwood, Iona Y
name: Hveem, Kristian
name: Naess, Øyvind
name: Willer, Cristen J
name: Åsvold, Bjørn Olav
name: Koellinger, Philipp D
name: Kaprio, Jaakko
name: Medland, Sarah E
name: Walters, Robin G
name: Benjamin, Daniel J
name: Turley, Patrick
name: Evans, David M
name: Davey Smith, George
name: Hayward, Caroline
name: Brumpton, Ben
name: Hemani, Gibran
name: Davies, Neil M
Publisher: name: Apollo - University of Cambridge Repository
Year: 2022
Subjects: Article
/631/208/457
/631/208/205/2138
article

description: Funder: Jacobs Foundation; doi: https://doi.org/10.13039/501100003986
description: 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.