This week sees publication of our new paper Identifying direct risk factors in UK Biobank via simultaneous Bayesian-frequentist model-averaged hypothesis testing using Doublethink in Proceedings of the National Academy of Sciences (PNAS). This work was joint with Nicolas Arning and Helen Fryer.
In this study we applied a novel approach called Doublehthink to implement an exposome-wide association study (ExWAS) of non-genetic risk factors that influence risk of COVID-19 hospitalization in UK Biobank (UKB). Inspired by Bayesian model averaging, our approach enhances power by testing both individual variables and arbitrary groups of variables.
We employed Doublethink to reveal exposome-wide significant signals across nine individual variables and seven groups of variables, notably factors like aging, dementia and prior infection overlooked by 85% of previous studies of the UK Biobank. We found significant direct effects among some commonly reported risk factors like age, sex, and obesity, but not others like cardiovascular disease. The effects of hypertension, depression, and diabetes appeared to be mediated via general comorbidity.
Biobank-scale epidemiology has transformed the study of common diseases, particularly through the discovery of genetic risk factors using genome-wide association studies (GWAS) methods. ExWAS applies similiar logic to pursue agnostic, data-driven discovery of non-genetic risk factors.
Doublethink offers an ExWAS method that can test thousands of variables in hundreds of thousands of UK Biobank participants. It controls both Bayesian (false discovery rate; FDR) and classical (familywise error rate; FWER) measures of false positives. Its Bayesian model-averaging approach enables an agnostic approach to variable selection, but it also addresses drawbacks of Bayesian methods like computational burden and reliance on prior assumptions for its false positive control.
Through its capacity to interpret biobank-scale data, our new Doublethink-based ExWAS approach paves the way for future systematic analyses of risk factors for infectious and chronic diseases in UK Biobank and beyond.
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