Background Parkinson’s disease (PD) is associated with enteric nervous system dysfunction and gut microbiota dysbiosis. Short-chain fatty acids (SCFAs), derived from gut microbiota, are supposed to anticipate PD pathogenesis via the pathway of spinal cord and vagal nerve or the circulatory system. However, the serum concentration of SCFAs in PD patients is poorly known. This study aims to investigate the exact level of SCFAs in PD patients and its correlation with Parkinson’s symptoms. Methods 50 PD patients and 50 healthy controls were recruited, and their demographic and clinical characteristics were collected. The serum concentration of SCFAs was detected using a gas chromatography-mass spectrometer. SCFAs were compared between PD and control groups. The correlation between serum SCFAs and Parkinson’s symptoms and the potential effects of medications on the serum SCFAs was analyzed. Results Serum propionic acid, butyric acid and caproic acid were lower, while heptanoic acid was higher in PD patients than in control subjects. However, only the serum level of propionic acid was correlated with Unified Parkinson’s Disease Rating Scale (UPDRs) part III score (R = -0.365, P = 0.009), Mini-mental State Examination (MMSE) score (R = -0.416, P = 0.003), and Hamilton Depression Scale (HAMD) score (R = 0.306, P = 0.03). There was no correlation between other serum SCFAs and motor complications. The use of trihexyphenidyl or tizanidine increased the serum concentration of propionic acid. Conclusions Serum SCFAs are altered in PD patients, and the decrease of serum propionic acid level is correlated with motor symptoms, cognitive ability and non-depressed state. Thus, the gut microbial-derived SCFAs potentially affect Parkinson’s symptoms through the blood circulation. Propionic acid supplementation might ameliorate motor and non-motor symptoms of PD patients, although clinical trials are needed to test this hypothesis.

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Background: This study aims to find immune-related hub gene as potential novel biomarker for KIRC. Methods: We constructed a KIRC immune prognostic signature. The receiver operating characteristic (ROC) curves, survival curves, univariate and multivariate Cox regression analysis were utilized to validate the signature. Immunohistochemical staining was used to detect the expression of TRME1 in renal clear cell carcinoma tissues. The clinical characteristics, the status of the tumor microenvironment, and immune infiltration were analyzed through the ESTIMATE and CIBERSORT algorithms for the hub gene, while the Gene Set Enrichment Analysis and PPI analysis were performed to predict the function of the hub gene. Results: In Immunohistochemical staining, we found that the expression of TREM1 was significantly upregulated with increasing tumor grade in renal clear cell carcinoma, and elevated TREM1 expression was associated with poor prognosis.The CIBERSORT and ESTIMATE algorithms revealed that TREM1 was correlated with the infiltration of 12 types of immune cells. Therefore, it was determined that TREM1 was involved in numerous classical pathways in the immune response via GSEA analysis. Conclusions: The results suggest that TREM1 may act as an implicit novel prognostic biomarker in KIRC that could be utilized to facilitate immunotherapeutic strategy.

Background The tumor immune microenvironment plays a crucial role in the efficacy of various therapeutics. However, their correlation is not yet completely understood in Clear cell renal cell carcinoma (ccRCC). This study aimed to investigate the potential of TREM-1 as a potential novel biomarker for ccRCC. Methods We constructed a ccRCC immune prognostic signature. The clinical characteristics, the status of the tumor microenvironment, and immune infiltration were analyzed through the ESTIMATE and CIBERSORT algorithms for the hub gene, while the Gene Set Enrichment Analysis and PPI analysis were performed to predict the function of the hub gene. Immunohistochemical staining was used to detect the expression of TREM-1 in renal clear cell carcinoma tissues. Results The CIBERSORT and ESTIMATE algorithms revealed that TREM-1 was correlated with the infiltration of 12 types of immune cells. Therefore, it was determined that TREM-1 was involved in numerous classical pathways in the immune response via GSEA analysis. In Immunohistochemical staining, we found that the expression of TREM-1 was significantly upregulated with increasing tumor grade in renal clear cell carcinoma, and elevated TREM-1 expression was associated with poor prognosis. Conclusions The results suggest that TREM-1 may act as an implicit novel prognostic biomarker in ccRCC that could be utilized to facilitate immunotherapeutic strategy.