A Mendelian randomization study on causal effects of leisure sedentary behaviour on the risk of rheumatoid arthritis.

BACKGROUND: The causal inference between leisure sedentary behaviour (LSB) and rheumatoid arthritis (RA) is still controversial because of potential residual confounding and reverse causality. METHODS: The present study used publicly available large-scale genome-wide association studies (GWAS) of LSB (television watching, computer use, and driving) and RA to perform a two-sample Mendelian randomization (MR) study to evaluate the causal effect of LSB on the risk of RA. We detected significant causal associations using the multiplicative random effects-inverse variance weighted (MRE-IVW) method, the maximum likelihood, robust adjusted profile scores, the weighted median, MR-Egger regression, and several complementary sensitivity analyses. Risk factor analysis was also conducted to further investigate potential mediators linking causal inference. RESULTS: Increased genetic liability to leisure television watching was significantly associated with a higher risk of RA (MRE-IVW method; OR = 2.46, 95% CI 1.77-3.41; p = 8.35 × 10-8 ). MR estimates indicated that prolonged leisure computer use was causally associated with a lower risk of RA (MRE-IVW method; OR = 0.23, 95% CI 0.12-0.46; p = 2.19 × 10-5 ). However, we found no evidence for a causal effect of leisure driving on the risk of RA (MRE-IVW method; OR = 0.59, 95% CI 0.10-3.41; p = 0.557). No pleiotropy was detected by the sensitivity analysis. CONCLUSIONS: This study supports a causal association between prolonged leisure television watching and an increased risk of RA. Additionally, prolonged computer use might be a protective factor for RA.

The functions and prognostic values of chemokine and chemokine receptors in gastric cancer.

Chemokine and chemokine receptors (CCRs) play a significant role in tumor infiltration of immune cells, tumor angiogenesis and distant metastasis. In this study, we explored the importance of CCRs in gastric cancer (GC) by analyzing the datasets from TCGA database. First, we analyzed the characteristics of the CCRs mutations. Then, we screened the differentially expressed CCRs and performed GO functional annotation and KEGG pathway analyses to explore their potential biological functions. Using multivariate Cox regression analyses, we constructed a prediction model based on four-CCRs (CCL15, CCL21, CCR3 and ACKR3) signature, and we found that the risk score of the model was an independent prognostic factor of GC. Next, a nomogram was constructed to assess the prognosis of GC patients. GSEA indicated that the high-risk group was significantly enriched in immune response and immune system process. Moreover, GSVA was employed to investigate the up- and down-regulated signaling pathways in the high- and low-risk groups. The correlation between risk score and immune-cell infiltration indicated that the four-CCRs signature might play a pivotal role in GC immune microenvironment. In conclusion, we revealed the potential molecular mechanisms of CCRs in GC and constructed a prediction model which might guide personalized treatment and prognosis for GC patients.