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.

The integrative analysis of DNA methylation and mRNA expression profiles confirmed the role of selenocompound metabolism pathway in Kashin-Beck disease.

Kashin-Beck disease (KBD) is an endemic chronic osteochondropathy. The etiology of KBD remains unknown. In this study, we conducted an integrative analysis of genome-wide DNA methylation and mRNA expression profiles between KBD and normal controls to identify novel candidate genes and pathways for KBD. Articular cartilage samples from 17 grade III KBD patients and 17 healthy controls were used in this study. DNA methylation profiling of knee cartilage and mRNA expression profile data were obtained from our previous studies. InCroMAP was performed to integrative analysis of genome-wide DNA methylation profiles and mRNA expression profiles. Gene ontology (GO) enrichment analysis was conducted by online DAVID 6.7. The quantitative real-time polymerase chain reaction (qPCR), Western blot, immunohistochemistry (IHC), and lentiviral vector transfection were used to validate one of the identified pathways. We identified 298 common genes (such as COL4A1, HOXA13, TNFAIP6 and TGFBI), 36 GO terms (including collagen function, skeletal system development, growth factor), and 32 KEGG pathways associated with KBD (including Selenocompound metabolism pathway, PI3K-Akt signaling pathway, and TGF-beta signaling pathway). Our results suggest the dysfunction of many genes and pathways implicated in the pathogenesis of KBD, most importantly, both the integrative analysis and in vitro study in KBD cartilage highlighted the importance of selenocompound metabolism pathway in the pathogenesis of KBD for the first time.

Evaluating the effect of birth weight on brain volumes and depression: An observational and genetic study using UK Biobank cohort.

BACKGROUND: Birth weight influences not only brain development, but also mental health outcomes, including depression, but the underlying mechanism is unclear. METHODS: The phenotypic data of 12,872-91,009 participants (59.18-63.38% women) from UK Biobank were included to test the associations between the birth weight, depression, and brain volumes through the linear and logistic regression models. As birth weight is highly heritable, the polygenic risk scores (PRSs) of birth weight were calculated from the UK Biobank cohort (154,539 participants, 56.90% women) to estimate the effect of birth weight-related genetic variation on the development of depression and brain volumes. Finally, the mediation analyses of step approach and mediation analysis were used to estimate the role of brain volumes in the association between birth weight and depression. All analyses were conducted sex stratified to assess sex-specific role in the associations. RESULT: We observed associations between birth weight and depression (odds ratio [OR] = 0.968, 95% confidence interval [CI] = 0.957-0.979, p = 2.29 × 10-6). Positive associations were observed between birth weight and brain volumes, such as gray matter (B = 0.131, p = 3.51 × 10-74) and white matter (B = 0.129, p = 1.67 × 10-74). Depression was also associated with brain volume, such as left thalamus (OR = 0.891, 95% CI = 0.850-0.933, p = 4.46 × 10-5) and right thalamus (OR = 0.884, 95% CI = 0.841-0.928, p = 2.67 × 10-5). Additionally, significant mediation effects of brain volume were found for the associations between birth weight and depression through steps approach and mediation analysis, such as gray matter (B = -0.220, p = 0.020) and right thalamus (B = -0.207, p = 0.014). CONCLUSIONS: Our results showed the associations among birth weight, depression, and brain volumes, and the mediation effect of brain volumes also provide evidence for the sex-specific of associations.

CGSEA: A Flexible Tool for Evaluating the Associations of Chemicals with Complex Diseases.

The etiology of many human complex diseases or traits involves interactions between chemicals and genes that regulate important physiological processes. It has been well documented that chemicals can contribute to disease development through affecting gene expression in vivo In this study, we developed a flexible tool CGSEA for scanning the candidate chemicals associated with complex diseases or traits. CGSEA only need genome-wide summary level data, such as transcriptome-wide association studies (TWAS) and mRNA expression profiles. CGSEA was applied to the GWAS summaries of attention deficiency/hyperactive disorder, (ADHD), autism spectrum disorder (ASD) and cervical cancer. CGSEA identified several significant chemicals, which have been demonstrated to be involved in the development or treatment of ADHD, ASD and cervical cancer. The CGSEA program and user manual are available at https://github.com/ChengSQXJTU/CGSEA.