Comprehensive Transcriptome Profiling of Peripheral Blood Mononuclear Cells from Patients with Sepsis

Abstract

Background: Sepsis, as a clinical emergency, usually causes multiorgan dysfunction and can lead to high mortality. Establishment of specific and sensitive biomarkers for early diagnosis is critical to identify patients who would benefit from targeted therapy. In this study, we investigated this syndrome by analyzing the transcriptome of peripheral blood mononuclear cells (PBMCs) from patients with sepsis and identified sepsis-specific biomarkers. Methods: In this study, a total of 87 patients with sepsis and 40 healthy controls from a prospective multicenter cohort were enrolled. Samples from 44 subjects (24 patients with sepsis and 20 healthy controls) were sequenced and the remaining patients were included in the validation group. Using high-throughput sequencing, a gene expression profile of PBMCs from patients with sepsis was generated to elucidate the pathophysiology of sepsis and identify sepsis-specific biomarkers. Results: Principal component analysis (PCA) and unsupervised hierarchical cluster analysis showed that patients with sepsis separated from healthy controls. A total of 1639 differentially expressed genes (DEGs) were identified (|log2 fold change|>2, adjusted P value <0.05) between these two groups, with 1278 (78.0%) upregulated and 361 (22.0%) downregulated in patients with sepsis. Gene Ontology (GO) analysis of the upregulated DEGs identified 194 GO terms that were clustered into 27 groups, and analysis of the downregulated DEGs identified 20 GO terms that were clustered into 4 groups. Four unique genes were identified that could be predictive of patients with sepsis. External validation of the four genes using quantitative real-time polymerase chain reaction (qRT-PCR) was consistent with the results of mRNA sequencing, revealing their potential in sepsis diagnosis. Conclusions: The transcriptome characteristics of PBMCs, which were significantly altered in sepsis patients, provide new insights into sepsis pathogenesis. The four identified gene expression changes differentiated patients with sepsis from healthy subjects, which could serve as a convenient tool contributing to sepsis diagnosis.

Beneficial Effects of O-GlcNAc Stimulation in a Young Rat Model of Sepsis: Beyond Modulation of Gene Expression

“…As previously described by Chen et al in a sepsis mouse model [ 25 ], we demonstrated that 3 h after injection, lipopolysaccharides promote inflammatory pathways in the hearts of young rats with the increase in genes involved in the regulation of NF-κB signaling. Reinforcing this observation, genes involved in the MAPK, mTOR, TLR2/MyD88 and JAK/STAT pathway are also up-regulated in the LPS group, as recently described in sepsis patients [ 26 ], confirming the pertinence of such approaches. JAK/STAT3 is a major pathway described as cardio-protective [ 27 , 28 ]; however, this pathway could also contribute to cardiac dysfunction [ 29 , 30 , 31 ], notably during septic shock [ 32 , 33 ].…”

Transcriptomics in the intensive care unit

“…Examples include the use of a single gene, IFI27, which has a high diagnostic ability to differentiate between viral and bacterial pneumonia, with analysis of transcriptomic response signatures in sepsis. [10][11][12] The second approach is to use open access databases to further integrate data-driven artificial intelligence techniques into unscripted analyses and apply this to early prediction, prognostication, and mortality risk. The third approach is to combine individual transcriptomics data to complement other patient specific information.…”

Plac8-ERK pathway modulation of monocyte function in sepsis

“…The complexity of sepsis arises from its heterogeneity, with diverse clinical manifestations ranging from systemic inflammatory response to severe septic shock and multiple organ dysfunction syndrome [ 6 , 7 ]. Dysregulation of immune responses plays a central role in the pathophysiology of sepsis, and peripheral blood mononuclear cells (PBMCs) play a key role in this process [ 8 – 10 ]. Cells, including monocytes, lymphocytes, and dendritic cells, play important roles in balancing pro-inflammatory and anti-inflammatory responses [ 11 , 12 ].…”