Systemic inflammatory response syndrome, infection, and outcome in intracerebral hemorrhage

Boehme, Amelia K; Comeau, Mary E.; Langefeld, Carl D.; Lord, Aaron; Moomaw, Charles J.; Osborne, Jennifer; James, Michael L.; Martini, Sharyl; Testai, Fernando D.; Woo, Daniel; Elkind, Mitchell S.V.

doi:10.1212/nxi.0000000000000428

Cited by 24 publications

(36 citation statements)

References 41 publications

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“…From the GSE24265 dataset, after comparing the gene expression data obtained from ICH tissue with that obtained from the contralateral brain tissues, we obtained 67 DEGs. GO analysis indicated that the main functional annotation results were consistent with those obtained by previous reports, i.e., a significant increase in inflammatory response promotes ICH-induced brain injury, which may be one of the main factors contributing to the poor prognosis in patients with ICH (Boehme et al 2018;Fu et al 2018). The immune response can antagonize the inflammatory response, induced after an episode of cerebral hemorrhage, to reduce the secondary damage to brain tissue, and thereby improve the recovery of nerve function (Klebe et al 2015;Lu et al 2014).…”

Section: Discussionsupporting

confidence: 87%

Peer Review #1 of "Identification of hub genes and small-molecule compounds related to intracerebral hemorrhage with bioinformatics analysis (v0.2)"

2019

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Background.Because of the complex mechanisms of injury, conventional surgical treatment and early blood pressure control does not significantly reduce mortality or improve patient prognosis in cases of intracerebral hemorrhage (ICH). We aimed to identify the hub genes associated with intracerebral hemorrhage, to act as therapeutic targets, and to identify potential small-molecule compounds for treating ICH. Methods. The GSE24265 dataset, consisting of data from 4 perihematomal brain tissues and 7 contralateral brain tissues, was downloaded from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs) in ICH, with a fold change (FC) value of (|log2FC|) > 2 and a P-value of < 0.05 set as cutoffs. The functional annotation of DEGs was performed using Gene Ontology (GO) resources, and the cell signaling pathway analysis of DEGs was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG), with a P-value of < 0.05 set as the cutoff. We constructed a protein-protein interaction (PPI) network to clarify the interrelationships between the different DEGs and to select the hub genes with significant interactions. Next, the DEGs were analyzed using the CMap tool to identify small-molecule compounds with potential therapeutic effects. Finally, we verified the expression levels of the hub genes by RT-qPCR on the rat ICH model. Result. A total of 59 up-regulated genes and 8 down-regulated genes associated with ICH were identified. The biological functions of DEGs associated with ICH are mainly involved in the inflammatory response, chemokine activity, and immune response. The KEGG analysis identified several pathways significantly associated with ICH, including but not limited to HIF-1, TNF, toll-like receptor, cytokinecytokine receptor interaction, and chemokine molecules. A PPI network consisting of 57 nodes and 373 edges was constructed using STRING, and 10 hub genes were identified with Cytoscape software. These hub genes are closely related to secondary brain injury induced by ICH. RT-qPCR results showed that the expression of ten hub genes was significantly increased in the rat model of ICH. In addition, a CMap analysis of three small-molecule compounds revealed their therapeutic potential. Conclusion. In this study we obtained ten hub genes, such as IL6, TLR2, CXCL1, TIMP1, PLAUR, SERPINE1, SELE, CCL4, CCL20, and CD163, which play an important role in the pathology of ICH. At the same time, the ten hub genes obtained through PPI network analysis were verified in the rat model of ICH. In addition, we obtained three small molecule compounds that will have therapeutic effects on ICH, including Hecogenin, Lidocaine, and NU-1025.

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Section: Discussionsupporting

confidence: 87%

Peer Review #1 of "Identification of hub genes and small-molecule compounds related to intracerebral hemorrhage with bioinformatics analysis (v0.2)"

2019

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“…vs 6, IQR[3][4][5][6][7][8][9][10][11][12]; p < 0.01; Glasgow Coma Scale score: 11, IQR[3][4][5][6][7][8][9][10][11][12][13][14] vs 15, IQR [13-15]; p < 0.01) and less favorable ICH characteristics (ICH volume: 18.3 cm 3 , IQR [4.6-47.2] vs 7.4 cm 3 , IQR [2.4-18.6]; p < 0.01; IVH: 57.6%, n = 98/170 vs 24.8%, n = 79/ 319; p < 0.01; hematoma enlargement: 12.7%, n = 15/118 vs 4.3%, n = 11/258; p < 0.01). Unadjusted outcomes comparing SIRS vs controls (at hospital discharge: mRS score 5, IQR [4-6] vs 3, IQR [2-5]; at 3 months: mRS score 5, IQR [3-6] vs 3, IQR [2-4]; at 12 months: mRS score 6, IQR [3-6] vs 3, IQR [1-5]; all p < 0.01) were all significantly in disfavor of patients with SIRS.…”

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confidence: 99%

“…In ICH, approximately 20% of patients develop SIRS during hospital stay, 2 and a correlation between SIRS and stroke severity has been suggested. 4 Recent stroke research has focused on systemic and local inflammatory responses as novel therapeutic target (NCT03338998), 3,5 yet the association of SIRS with functional long-term outcomes after ICH remains undetermined. The present study aimed at investigating associations of SIRS with long-term functional outcome and contributing factors after ICH.…”

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confidence: 99%

Systemic inflammatory response syndrome and long-term outcome after intracerebral hemorrhage

Hagen

Sembill

Sprügel

et al. 2019

Neurol Neuroimmunol Neuroinflamm

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ObjectiveTo investigate whether the systemic inflammatory response syndrome (SIRS) without infection as surrogate of a systemic immune response is associated with poor long-term functional outcome in patients with spontaneous intracerebral hemorrhage (ICH).MethodsWe analyzed consecutive patients with spontaneous ICH from our prospective cohort study (2018–2015). SIRS was defined according to standard criteria: i.e., 2 or more of the following parameters during hospitalization: body temperature <36°C or >38°C, respiratory rate >20 per minute, heart rate >90 per minute, or white blood cell count <4,000/μL or >12,000/μL in the absence of infection. The primary outcome consisted of the modified Rankin Scale (mRS) at 3 and 12 months investigated by adjusted ordinal shift analyses. Bias and confounding were addressed by propensity score matching and multivariable regression models.ResultsOf 780 patients with ICH, 21.8% (n = 170) developed SIRS during hospitalization. Patients with SIRS showed more severe ICH compared with those without; i.e., larger ICH volumes (18.3 cm3, interquartile range [IQR 4.6–47.2 cm3] vs 7.4 cm3, IQR [2.4–18.6 cm3]; p < 0.01), increased intraventricular hemorrhage (57.6%, n = 98/170 vs 24.8%, n = 79/319; p < 0.01), and poorer neurologic admission status (NIH Stroke Scale score 16, IQR [7–30] vs 6, IQR [3–12]; p < 0.01). ICH severity-adjusted analyses revealed an independent association of SIRS with poorer functional outcome after 3 (OR 1.80, 95% CI [1.08–3.00]; p = 0.025) and 12 months (OR 1.76, 95% CI [1.04–2.96]; p = 0.034). Increased ICH volumes on follow-up imaging (OR 1.38, 95% CI [1.01–1.89]; p = 0.05) and previous liver dysfunction (OR 3.01, 95% CI [1.03–10.19]; p = 0.04) were associated with SIRS.ConclusionsIn patients with ICH, we identified SIRS to be predictive of poorer long-term functional outcome over the entire range of mRS estimates. Clinically relevant associations with SIRS were documented for previous liver dysfunction and hematoma enlargement.

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“…Zhao et al found that p38MAPK was activated at 24 h in an animal model of ICH, and the use of an inhibitor could recede the inflammatory injury after ICH (Zhou et al 2014 ). Boehme AK et al showed systemic inflammatory response syndrome (SIRS) on admission was associated with an ICH score on admission and infection after ICH infection (Boehme et al 2018 ). Together, MAPK/ERK and p38MAPK could represent potential therapeutic targets to prevent neurological deficits after ICH.…”

Section: Discussionmentioning

confidence: 99%

Biomarker and Drug Target Discovery Using Quantitative Proteomics Post-Intracerebral Hemorrhage Stroke in the Rat Brain

et al. 2018

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The pathological mechanisms of acute intracerebral hemorrhage (ICH) remain unknown and unverified. In the present study, we used quantitative proteomics to elucidate the pathological mechanisms and to identify novel biomarker and therapeutic target candidates via tissue proteome in a rat model of acute ICH. Rats were experimentally induced with ICH (n = 6) or Sham (n = 6), and their brain tissue was obtained by 24 h. The TMT-LC–MS/MS-based proteomics approach was used to quantify the differential proteomes across brain tissue, and the results were further analyzed by ingenuity pathway analysis to explore canonical pathways and the relationship involved in the uploaded data. Upon quantification, we found that 96 secreted proteins that were identified in the ICH 24-h group were significantly different those in the control group (P < 0.05); among these proteins, 57 increased and 39 decreased in abundance. Bioinformatic analyses of differentially expressed proteins demonstrated that the protein localization and ERK1 and ERK2 cascade were the top two biological processes with the highest concentrations of differentially proteins. The top protein-protein action network with high confidence levels of protein was the albumin and ERK signaling pathways. Albumin, ERK, and p-ERK were assessed in brain tissue by western blot analysis, and higher expression levels of albumin and p-ERK were observed in the ICH group. Our proteomic results highlight important change in the biological processes of ERK1 and ERK2 cascade, which are possible targets for future interventions of ICH. To our knowledge, this study provides in-depth analysis of ICH in brain tissue, and we propose 96 new biomarker candidates for ICH, including albumin and ERK.Electronic supplementary materialThe online version of this article (10.1007/s12031-018-1206-z) contains supplementary material, which is available to authorized users.

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Systemic inflammatory response syndrome, infection, and outcome in intracerebral hemorrhage

Cited by 24 publications

References 41 publications

Peer Review #1 of "Identification of hub genes and small-molecule compounds related to intracerebral hemorrhage with bioinformatics analysis (v0.2)"

Peer Review #1 of "Identification of hub genes and small-molecule compounds related to intracerebral hemorrhage with bioinformatics analysis (v0.2)"

Systemic inflammatory response syndrome and long-term outcome after intracerebral hemorrhage

Biomarker and Drug Target Discovery Using Quantitative Proteomics Post-Intracerebral Hemorrhage Stroke in the Rat Brain

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