Genetic predictors of participation in optional components of UK Biobank.
Genetic predictors of participation in optional components of UK Biobank.
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DOI：
10.1038/s41467-021-21073-y
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发表时间：
2021-02-09
影响因子：
16.6
通讯作者：
Tilling K
中科院分区：
文献类型：
--
作者：
Tyrrell J;Zheng J;Beaumont R;Hinton K;Richardson TG;Wood AR;Davey Smith G;Frayling TM;Tilling K
像英国生物银行这样的大型研究越来越多地用于GWAS和孟德尔随机化（MR）研究。然而，选择进入和退出研究可能会使遗传和表型关联产生偏倚。我们在451,306名英国生物银行参与者中研究了影响四个可选组件参与的遗传因素。我们使用GWAS来识别与参与相关的遗传变异，使用MR来估计表型对参与的影响，使用遗传相关性来比较不同研究中的参与偏倚。32个变异与参与其中一个可选成分相关（P < 6 × 10−9），包括与智力和阿尔茨海默病相关的基因座。遗传相关性表明，参与偏倚在所有研究中都很常见。核磁共振显示，受教育时间越长、月经初潮年龄越大、身材越高，参与的几率越大，而肥胖、血脂异常、神经质、阿尔茨海默氏症和精神分裂症的比例越高，参与的几率就越低。我们的效应估计可以用于敏感性分析，以解释遗传或非遗传分析中的选择性参与偏差。大型生物库研究通常用于GWAS，但可能受到影响参与和退出的因素的影响。在这里，作者表明，一些影响参与的因素可能有潜在的遗传成分。
Large studies such as UK Biobank are increasingly used for GWAS and Mendelian randomization (MR) studies. However, selection into and dropout from studies may bias genetic and phenotypic associations. We examine genetic factors affecting participation in four optional components in up to 451,306 UK Biobank participants. We used GWAS to identify genetic variants associated with participation, MR to estimate effects of phenotypes on participation, and genetic correlations to compare participation bias across different studies. 32 variants were associated with participation in one of the optional components (P < 6 × 10−9), including loci with links to intelligence and Alzheimer’s disease. Genetic correlations demonstrated that participation bias was common across studies. MR showed that longer educational duration, older menarche and taller stature increased participation, whilst higher levels of adiposity, dyslipidaemia, neuroticism, Alzheimer’s and schizophrenia reduced participation. Our effect estimates can be used for sensitivity analysis to account for selective participation biases in genetic or non-genetic analyses. Large BioBank studies are commonly used in GWAS, but may be biased by factors affecting participation and dropout. Here the authors show that some of the factors affecting participation may have underlying genetic components.
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影响因子：
64.8
作者：
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
通讯作者：
Marchini J
基因发现和多基因预测，从基因组全基因组协会的教育程度研究中，有110万个人。
影响因子：
30.8
作者：
Lee JJ;Wedow R;Okbay A;Kong E;Maghzian O;Zacher M;Nguyen-Viet TA;Bowers P;Sidorenko J;Karlsson Linnér R;Fontana MA;Kundu T;Lee C;Li H;Li R;Royer R;Timshel PN;Walters RK;Willoughby EA;Yengo L;23andMe Research Team;COGENT (Cognitive Genomics Consortium);Social Science Genetic Association Consortium;Alver M;Bao Y;Clark DW;Day FR;Furlotte NA;Joshi PK;Kemper KE;Kleinman A;Langenberg C;Mägi R;Trampush JW;Verma SS;Wu Y;Lam M;Zhao JH;Zheng Z;Boardman JD;Campbell H;Freese J;Harris KM;Hayward C;Herd P;Kumari M;Lencz T;Luan J;Malhotra AK;Metspalu A;Milani L;Ong KK;Perry JRB;Porteous DJ;Ritchie MD;Smart MC;Smith BH;Tung JY;Wareham NJ;Wilson JF;Beauchamp JP;Conley DC;Esko T;Lehrer SF;Magnusson PKE;Oskarsson S;Pers TH;Robinson MR;Thom K;Watson C;Chabris CF;Meyer MN;Laibson DI;Yang J;Johannesson M;Koellinger PD;Turley P;Visscher PM;Benjamin DJ;Cesarini D
通讯作者：
Cesarini D
影响因子：
5
作者：
Fry A;Littlejohns TJ;Sudlow C;Doherty N;Adamska L;Sprosen T;Collins R;Allen NE
通讯作者：
Allen NE
影响因子：
2.1
作者：
Bowden J;Davey Smith G;Haycock PC;Burgess S
通讯作者：
Burgess S
影响因子：
7.7
作者：
Domingue, Benjamin W.;Belsky, Daniel W.;Boardman, Jason D.
通讯作者：
Boardman, Jason D.