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Objective Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease after Alzheimer's disease (AD) worldwide. The prevalence of small intestinal bacterial overgrowth (SIBO) in PD patients is high. We conducted this comprehensive systematic review and meta-analysis to determine the association between SIBO and PD. Methods A comprehensive literature search of the PubMed, Cochrane Library and EMBASE databases was performed to identify studies correlating SIBO with PD. Studies were screened, and relevant data were extracted and analysed. We calculated the pooled prevalence of SIBO in all individuals with PD and compared the prevalence of SIBO between the two groups to calculate an odds ratio (OR) and 95% confidence interval (CI). Egger’s test was performed to assess publication bias. Results Eleven studies with 973 participants met the inclusion criteria. The pooled prevalence of SIBO in patients with PD was 46% (95% CI 36–56). A random-effects model was applied given the heterogeneity (I2 = 83%) detected among the studies. Egger’s test indicated no publication bias (p = 0.0657). Subgroup analyses showed that the prevalence of SIBO was greater in studies including patients diagnosed using the lactulose hydrogen breath test (LBT) (51%, 95% CI 37–65) than in those including patients diagnosed using the glucose hydrogen breath test (GBT) (35%, 95% CI 20–50), and the prevalence of SIBO in PD was highest (55%, 95% CI 38–72) in patients diagnosed by the LBT and GBT. The prevalence of SIBO was 52% (95% CI 40–64) among patients from Western countries and 33% (95% CI 22–43) among patients from Eastern countries. The pooled OR of SIBO in PD patients compared with healthy controls was 5.22 (95% CI 3.33–8.19, p Conclusion In conclusion, our meta-analysis found a strong association between SIBO and PD with approximately half of PD patients testing positive for SIBO. These relationships significantly differed based on diagnostic test and geographic area.

Background Increasing evidence has shown that cytolytic activity (CYT) is a new immunotherapy biomarker that characterises the antitumour immune activity of cytotoxic T cells and macrophages. In this study, we established a prognostic model associated with CYT. Methods A prognostic model based on CYT-related genes was developed. Furthermore, aberrant expression of genes of the model in colon cancer (CC) was identified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays. Next, the correlation between the model and T-cell infiltration in the CC microenvironment was analysed. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm and subclass mapping were used to predict clinical responses to immune checkpoint inhibitors. Results In total, 280 of the 1418 genes were differentially expressed based on CYT. A prognostic model (including HOXC8 and MS4A2) was developed based on CYT-related genes. The model was validated using the testing set, the whole set and a Gene Expression Omnibus (GEO) cohort (GSE41258). Gene set enrichment analysis (GSEA) and other analyses showed that the levels of immune infiltration and antitumour immune activation in low-risk-score tumours were greater than those in high-risk-score tumours. CC patients with a low-risk-score showed more promise in the response to anti-immune checkpoint therapy. Conclusions Overall, our model may precisely predict the overall survival of CC and reflect the strength of antitumour immune activity in the CC microenvironment. Furthermore, the model may be a predictive factor for the response to immunotherapy.