GSE63042
An integrated transcriptome and expressed variant analysis of sepsis survival and death
Background: Sepsis, a leading cause of morbidity and mortality, is not a homogeneous disease but rather a syndrome encompassing many heterogeneous pathophysiologies. Patient factors including genetics predispose to poor outcomes, though current clinical characterizations fail to identify those at greatest risk of progression and mortality. Results: The Community Acquired Pneumonia and Sepsis Outcome Diagnostic study enrolled 1,152 subjects with suspected sepsis. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS) or sepsis (infection with SIRS), including 78 sepsis survivors and 28 sepsis nonsurvivors, who had previously undergone plasma proteomic and metabolomic profiling. The expression of 338 genes differed between subjects with SIRS and those with sepsis, primarily reflective of immune activation in sepsis. The expression of 1,238 genes differed with sepsis outcome: Nonsurvivors had lower expression of many immune function-related genes. Functional genetic variants associated with sepsis mortality were sought based on a common disease – rare variant hypothesis. VPS9D1, whose expression was increased in sepsis survivors, had a higher burden of missense variants in sepsis survivors, and these were associated with altered expression of 3,799 genes, primarily reflecting Golgi and endosome biology. Conclusions: Host response in sepsis survivors – activation of immune response-related genes – was muted in sepsis nonsurvivors. The association of sepsis survival with robust immune response and presence of missense variants in VPS9D1 warrants replication and further functional studies. Overall design: We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS, n=23) or sepsis (infection with SIRS), including 78 sepsis survivors and 28 sepsis nonsurvivors, who had previously undergone plasma proteomic and metabolomic profiling.