Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes

Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals...

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Published inNature communications Vol. 12; no. 1; pp. 20211 - 11
Main Authors Xue, Angli, Jiang, Longda, Zhu, Zhihong, Wray, Naomi R., Visscher, Peter M., Zeng, Jian, Yang, Jian
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 12.01.2021
Nature Publishing Group
Nature Portfolio
Subjects
45
45/43
631/208/205
631/208/457
631/208/480
692/499
Alcohol
Alcohol Drinking - genetics
Alcohols
Behavior
Bias
Biobanks
Biological Specimen Banks
Body Mass Index
Disease
Genetic diversity
Genetic variance
Genome-wide association studies
Genome-Wide Association Study
Genomes
Humanities and Social Sciences
Humans
Mendelian Randomization Analysis
multidisciplinary
Quantitative Trait, Heritable
Science
Science (multidisciplinary)
United Kingdom
United Kingdom
United Kingdom > UK
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Abstract Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank ( n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data. Conflicting reports have found disease to sometimes be positively and sometimes negatively correlated with alcohol consumption. Here, the authors show that misreporting and reduction of alcohol consumption is associated with disease, leading to misleading associations between alcohol and disease.
AbstractList Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank ( n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data. Conflicting reports have found disease to sometimes be positively and sometimes negatively correlated with alcohol consumption. Here, the authors show that misreporting and reduction of alcohol consumption is associated with disease, leading to misleading associations between alcohol and disease.
Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.
Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.
Conflicting reports have found disease to sometimes be positively and sometimes negatively correlated with alcohol consumption. Here, the authors show that misreporting and reduction of alcohol consumption is associated with disease, leading to misleading associations between alcohol and disease.
Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank ( n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.
Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.Conflicting reports have found disease to sometimes be positively and sometimes negatively correlated with alcohol consumption. Here, the authors show that misreporting and reduction of alcohol consumption is associated with disease, leading to misleading associations between alcohol and disease.
ArticleNumber 20211
Author Zeng, Jian
Yang, Jian
Zhu, Zhihong
Visscher, Peter M.
Xue, Angli
Wray, Naomi R.
Jiang, Longda
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  organization: Institute for Molecular Bioscience, The University of Queensland, School of Life Sciences, Westlake University, Westlake Laboratory of Life Sciences and Biomedicine
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Snippet Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are...
Conflicting reports have found disease to sometimes be positively and sometimes negatively correlated with alcohol consumption. Here, the authors show that...
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StartPage 20211
SubjectTerms 45
45/43
631/208/205
631/208/457
631/208/480
692/499
Alcohol
Alcohol Drinking - genetics
Alcohols
Behavior
Bias
Biobanks
Biological Specimen Banks
Body Mass Index
Disease
Genetic diversity
Genetic variance
Genome-wide association studies
Genome-Wide Association Study
Genomes
Humanities and Social Sciences
Humans
Mendelian Randomization Analysis
multidisciplinary
Quantitative Trait, Heritable
Science
Science (multidisciplinary)
United Kingdom
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Title Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes
URI https://link.springer.com/article/10.1038/s41467-020-20237-6
https://www.ncbi.nlm.nih.gov/pubmed/33436567
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https://www.proquest.com/docview/2477496682
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Volume 12
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