Channing Division of Network Medicine
Julian Hecker*, Dmitry Prokopenko, Matthew Moll, Sanghun Lee, Wonji Kim, Dandi Qiao, Kirsten Voorhie, Woori Kim Stijn Vansteelandt, Brian D. Hobbs, Michael H. Cho, Edwin K. Silverman, Sharon M. Lutz, Dawn L. DeMeo, Scott T. Weiss, Christoph Lange
Scott T. Weiss
The identification and understanding of gene-environment interactions can provide insights into the causal pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains challenging since statistical power is limited and gene-environment correlations can introduce false positive interaction findings.
We recently proposed RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing methodology for quantitative traits that tackles these challenges by jointly analyzing sets of genetic variants using sample splitting combined with screening approaches and robust test statistics.
We applied RITSS to lung function data (forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and FEV1/FVC) in the UK Biobank. RITSS identified highly significant interactions between previously reported genetic variants for lung function and sex. These interactions are characterized by small effects on the single variant level but follow a systematic structure that results in an aggregated joint effect. Specifically, we observed shared genetic factors between males and females with an identical effect direction but a larger magnitude in males. This phenomenon was recently introduced in the literature as amplification.
While recent biobank analyses were largely unsuccessful in identifying sex-specific genetic variants on the single variant level, the systematic structure of amplification identified by our RITSS approach could potentially point toward the underlying mechanisms of sex-differential effects.
Further, this new gene-environment interaction research direction of amplification opens the path to a variety of promising follow-up analyses to investigate the related genes, pathways, and consistency of sex-specific genetic architecture across different lung function traits.
The clinical manifestation of respiratory diseases and their symptoms present differently between males and females. Drug response and metabolization can also vary based on sex. By studying gene-by-sex interactions, we can develop targeted therapies and gain insight into disease pathobiology. Here, we focused on lung function measurements that underlie the diagnosis and disease progression of asthma and chronic obstructive pulmonary disease. Our analysis revealed genetic variants with systematic sex-differential effects on FEV1, FVC, and FEV1/FVC, which may highlight potential mechanisms underlying lung function development. Given the increased likelihood of drug approval for targets with human genetic evidence, our research could accelerate targeted therapeutics identification. Additionally, our findings can enhance sex-specific risk predictions, addressing the historical underrepresentation of females in clinical trials and studies.