Whole Exome Sequencing Study Identifies Novel Rare Risk Variants for Habitual Coffee Consumption Involved in Olfactory Receptor and Hyperphagia.

Habitual coffee consumption is an addictive behavior with unknown genetic variations and has raised public health issues about its potential health-related outcomes. We performed exome-wide association studies to identify rare risk variants contributing to habitual coffee consumption utilizing the newly released UK Biobank exome dataset (n = 200,643). A total of 34,761 qualifying variants were imported into SKAT to conduct gene-based burden and robust tests with minor allele frequency <0.01, adjusting the polygenic risk scores (PRS) of coffee intake to exclude the effect of common coffee-related polygenic risk. The gene-based burden and robust test of the exonic variants found seven exome-wide significant associations, such as OR2G2 (PSKAT = 1.88 × 10−9, PSKAT-Robust = 2.91 × 10−17), VEZT1 (PSKAT = 3.72 × 10−7, PSKAT-Robust = 1.41 × 10−7), and IRGC (PSKAT = 2.92 × 10−5, PSKAT-Robust = 1.07 × 10−7). These candidate genes were verified in the GWAS summary data of coffee intake, such as rs12737801 (p = 0.002) in OR2G2, and rs34439296 (p = 0.008) in IRGC. This study could help to extend genetic insights into the pathogenesis of coffee addiction, and may point to molecular mechanisms underlying health effects of habitual coffee consumption.

The associations between sleep behaviors, lifestyle factors, genetic risk and mental disorders: A cohort study of 402 290 UK Biobank participants.

BACKGROUND: Sleep behaviors were believed to be associated with mental disorders (MD). However, the underlying mechanism of such association relationship, especially the role of multiple lifestyle factors in it remains unclear. METHODS: A total of 402,290 participants from UK Biobank who don't have MD at baseline were included. They were divided into poor, intermediate and healthy sleep patterns according to the sleep score, which was calculated based on the data collecting from five sleep behaviors. Cox proportional hazard model was used to estimate the associations between sleep behaviors and MD. The associations were further estimated when taking lifestyle factors such as physical activity, coffee intake, tea intake and genetic susceptibility into account. RESULTS: Healthy sleep pattern was associated with lower risk of overall MD status (HR,0.41, 95%CI,0.39-0.43), depressive disorders (HR,0.34, 95%CI,0.31-0.37) and anxiety disorders (HR,0.46, 95%CI,0.41-0.79), compared with poor sleep pattern. And in each subgroup of physical activity, tea intake, coffee intake, age and genetic risk scores (GRS), healthy sleep pattern could partly offset the risk of diseases. CONCLUSIONS: Our study suggested healthy sleep behaviors could diminish the negative effect from genetic predisposition and lifestyle factors on the risk of MD, highlighting the benefit of healthy sleep pattern.