miR‑148 family members are putative biomarkers for sepsis

Dong, Lei; Li, Hongwei; Zhang, Shunli; Yang, Guanzheng

doi:10.3892/mmr.2019.10174

Cited by 9 publications

(10 citation statements)

References 35 publications

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“…Zboromyrska et al [ 18 ] studied multiplex real-time polymerase chain reaction, the Magicplex TM Sepsis test, the specificity of which was up to 95%, while the sensitivity was only 29%. Dong et al [ 19 ] found that members of the miR-148 family (miR-148A/B and miR-152) were candidate biomarkers for sepsis by studying the Gene Expression Omnibus dataset GSE12624, but further study is required to evaluate the diagnostic performance. Guo et al [ 20 ] found that the AUC value of miR-495 in the diagnosis of sepsis was 0.915 when the cutoff value was 0.655, the sensitivity was 89.5%, and the specificity was 83.0%.…”

Section: Discussionmentioning

confidence: 99%

Role of international normalized ratio in nonpulmonary sepsis screening: An observational study

Zhang¹,

Du²,

Cheng³

et al. 2021

WJCC

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BACKGROUND Currently, there is a lack of sepsis screening tools that can be widely used worldwide. Pulmonary sepsis can be of sufficient concern to physicians due to their noticeable symptoms, which usually rely less on screening tools. AIM To investigate the efficiency of the international normalized ratio (INR) for the early rapid recognition of adult nonpulmonary infectious sepsis. METHODS This is a prospective observational study. A total of 108 sepsis patients and 106 nonsepsis patients were enrolled according to relevant inclusion and exclusion criteria. Commonly used clinical indicators, such as white blood cell, neutrophil count, lymphocyte count, neutrophil-lymphocyte count ratio (NLCR), platelets (PLT), prothrombin time, INR, activated partial thromboplastin time, and quick Sequential “Sepsis-related” Organ Failure Assessment (qSOFA) scores were recorded within 24 h after admission. The diagnostic performances of these clinical indicators were analyzed and compared through multivariate logistic regression analysis, Spearman correlation, and receiver operating characteristic curve analysis. RESULTS The INR value of the sepsis group was significantly higher than that of the nonsepsis group. INR has superior diagnostic efficacy for sepsis, with an area under the curve value of 0.918, when those preexisting diseases which significantly affect coagulation function were excluded. The diagnostic efficacy of the INR was more significant than that of NLCR, PLT, and qSOFA ( P < 0.05). Moreover, INR levels of 1.17, 1.20, and 1.22 could be used to categorize the relative risk of nonpulmonary infections sepsis into three categories: low, medium and high risk, respectively. CONCLUSION The INR is a promising and easily available biomarker for diagnosis, and it can be used as one of the indicators for early screening of adult nonpulmonary infectious sepsis. When its value is higher than the optimal cutoff value (1.22), high vigilance is required for adult nonpulmonary infectious sepsis.

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Section: Discussionmentioning

confidence: 99%

Role of international normalized ratio in nonpulmonary sepsis screening: An observational study

Zhang¹,

Du²,

Cheng³

et al. 2021

WJCC

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“…WGCNA has also been used to analyze correlation patterns in sepsis. These research efforts focused on inflammatory cells in vitro ( 21 ), long non-coding RNA ( 22 ), transcription factors and miRNA ( 23 ) based on samples with or without sepsis, but did not distinguish between patients with positive outcomes from those with negative outcomes. A recent study identified two transcription factors, CEBPB and ETV6, associated with mortality outcome via WGCNA ( 24 ).…”

Section: Introductionmentioning

confidence: 99%

SDF4 Is a Prognostic Factor for 28-Days Mortality in Patients With Sepsis via Negatively Regulating ER Stress

Zhu

Wang

et al. 2021

Front. Immunol.

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Sepsis is a heterogeneous syndrome induced by infection and results in high mortality. Even though more than 100 biomarkers for sepsis prognosis were evaluated, prediction of patient outcomes in sepsis continues to be driven by clinical signs because of unsatisfactory specificity and sensitivity of these biomarkers. This study aimed to elucidate the key candidate genes involved in sepsis response and explore their downstream effects based on weighted gene co-expression network analysis (WGCNA). The dataset GSE63042 with sepsis outcome information was obtained from the Gene Expression Omnibus (GEO) database and then consensus WGCNA was conducted. We identified the hub gene SDF4 (stromal cell derived factor 4) from the M6 module, which was significantly associated with mortality. Subsequently, two datasets (GSE54514 and E-MTAB-4421) and cohort validation (n=89) were performed. Logistic regression analysis was used to build a prediction model and the combined score resulting in a satisfactory prognosis value (area under the ROC curve=0.908). The model was subsequently tested by another sepsis cohort (n=70, ROC= 0.925). We next demonstrated that endoplasmic reticulum (ER) stress tended to be more severe in patients PBMCs with negative outcomes compared to those with positive outcomes and SDF4 was related to this phenomenon. In addition, our results indicated that adenovirus-mediated Sdf4 overexpression attenuated ER stress in cecal ligation and puncture (CLP) mice lung. In summary, our study indicates that incorporation of SDF4 can improve clinical parameters predictive value for the prognosis of sepsis, and decreased expression levels of SDF4 contributes to excessive ER stress, which is associated with worsened outcomes, whereas overexpression of SDF4 attenuated such activation.

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“…Rather than relating thousands of genes to a clinical trait, WGCNA focuses on the relationship between a few modules and the trait ( Zhang & Horvath, 2005 ; Horvath et al, 2006 ). Recently, WGCNA has been used to explore co-expression patterns in cancer, ischaemic stroke and sepsis ( Dong et al, 2019 ; Niemira et al, 2019 ; Wang et al, 2020 ; Zhang et al, 2020 ). Thus, in this study, we characterized the proteomic profile in patients with sepsis and identified protein co-expression modules by using WGCNA that could be used in the diagnosis of sepsis.…”

Section: Introductionmentioning

confidence: 99%

Serum proteomics reveals disorder of lipoprotein metabolism in sepsis

Liang

Chen

et al. 2021

Life Sci. Alliance

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Sepsis is defined as an organ dysfunction syndrome and it has high mortality worldwide. This study analysed the proteome of serum from patients with sepsis to characterize the pathological mechanism and pathways involved in sepsis. A total of 59 patients with sepsis were enrolled for quantitative proteomic analysis. Weighted gene co-expression network analysis (WGCNA) was performed to construct a co-expression network specific to sepsis. Key regulatory modules that were detected were highly correlated with sepsis patients and related to multiple functional groups, including plasma lipoprotein particle remodeling, inflammatory response, and wound healing. Complement activation was significantly associated with sepsis-associated encephalopathy. Triglyceride/cholesterol homeostasis was found to be related to sepsis-associated acute kidney injury. Twelve hub proteins were identified, which might be predictive biomarkers of sepsis. External validation of the hub proteins showed their significantly differential expression in sepsis patients. This study identified that plasma lipoprotein processes played a crucial role in sepsis patients, that complement activation contributed to sepsis-associated encephalopathy, and that triglyceride/cholesterol homeostasis was associated with sepsis-associated acute kidney injury.

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miR‑148 family members are putative biomarkers for sepsis

Cited by 9 publications

References 35 publications

Role of international normalized ratio in nonpulmonary sepsis screening: An observational study

Role of international normalized ratio in nonpulmonary sepsis screening: An observational study

SDF4 Is a Prognostic Factor for 28-Days Mortality in Patients With Sepsis via Negatively Regulating ER Stress

Serum proteomics reveals disorder of lipoprotein metabolism in sepsis

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