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.
Highlights
Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits
To investigate the characteristics of the suspected misreporting individuals, we examined the phenotypes of 18 common diseases in the UK Biobank (UKB) and used disease count as an indicator of disease burden for each participant (Methods; Table 1 and Supplementary Data 1)
Our results showed that disease ascertainment was likely to be the main cause of the misreports and longitudinal changes (MLC) biases, which can be largely corrected for using additional information and coarse longitudinal data
Summary
Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. In epidemiological or genetic studies, phenotypic data of behavioural and lifestyle traits are often collected from selfreported questionnaires, which are subject to misreports (i.e., selfreport biases), especially for questions related to smoking, drinking, and drug use[15,16,17,18] These phenotypes are subject to change during lifetime[19,20,21,22], for instance in response to disease diagnosis, but data to track such longitudinal variations are rarely available. We elaborate on why some of the previous studies might suffer from MLC biases
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