Integrative single-cell RNA sequencing and metabolomics decipher the imbalanced lipid-metabolism in maladaptive immune responses during sepsis

BackgroundTo identify differentially expressed lipid metabolism-related genes (DE-LMRGs) responsible for immune dysfunction in sepsis.MethodsThe lipid metabolism-related hub genes were screened using machine learning algorithms, and the immune cell infiltration of these hub genes were assessed by CIBERSORT and Single-sample GSEA. Next, the immune function of these hub genes at the single-cell level were validated by comparing multiregional immune landscapes between septic patients (SP) and healthy control (HC). Then, the support vector machine-recursive feature elimination (SVM-RFE) algorithm was conducted to compare the significantly altered metabolites critical to hub genes between SP and HC. Furthermore, the role of the key hub gene was verified in sepsis rats and LPS-induced cardiomyocytes, respectively.ResultsA total of 508 DE-LMRGs were identified between SP and HC, and 5 hub genes relevant to lipid metabolism (MAPK14, EPHX2, BMX, FCER1A, and PAFAH2) were screened. Then, we found an immunosuppressive microenvironment in sepsis. The role of hub genes in immune cells was further confirmed by the single-cell RNA landscape. Moreover, significantly altered metabolites were mainly enriched in lipid metabolism-related signaling pathways and were associated with MAPK14. Finally, inhibiting MAPK14 decreased the levels of inflammatory cytokines and improved the survival and myocardial injury of sepsis.ConclusionThe lipid metabolism-related hub genes may have great potential in prognosis prediction and precise treatment for sepsis patients

Association between osteoprotegerin gene T950C polymorphism and osteoporosis risk in the Chinese population: Evidence via meta-analysis

<div><p>Osteoporosis has been reported to be at least partially developed in response to functional polymorphisms of the osteoprotegerin (OPG). However, conflicting results have been found. This meta-analysis aimed to provide an assessment of the relationship between the risk for developing osteoporosis and OPG T950C polymorphism in the Chinese population. Studies to be analyzed were identified with the literature search in PubMed, Embase, Web of Science, the Cochrane Library, and the Chinese National Knowledge Infrastructure during May 2017. Seven case-control studies that included a total of 1850 osteoporosis cases and 3074 controls were assessed in this meta-analysis. Overall, no significant associations could be detected between OPG T950C polymorphism and osteoporosis when all included studies were pooled into this meta-analysis. In a subgroup analyses, OPG T950C polymorphism was significantly associated with the osteoporosis risk in South China (CC+TC vs. TT: OR = 1.34, 95% CI = 1.17–1.54; CC vs. TC+TT: OR = 0.79, 95% CI = 0.69–0.95) and for studies that included postmenopausal osteoporosis (CC vs. TC+TT: OR = 0.78, 95% CI = 0.64–0.94) or hospital-based controls (CC vs. TC+TT: OR = 0.81, 95% CI = 0.68–0.96). In conclusion, the results of this meta-analysis suggest that OPG T950C polymorphism might be associated with an increased osteoporosis risk in the Chinese population.</p></div

Association of the OPG T950C polymorphism on the propensity to develop osteoporosis.

<p>Association of the OPG T950C polymorphism on the propensity to develop osteoporosis.</p