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Predicting Postoperative Liver Dysfunction Based on Blood Derived MicroRNA Signatures

ABSTRACT: Treatment options and reliable predictive marker to determine patients at risk to develop postoperative LD and to define the optimal time point of liver resection are limited. Accordingly, there is an urgent need for an easily assessable preoperative test to predict postoperative liver function recovery, specifically as current markers are often expensive, time consuming and sometimes invasive. Emerging evidence suggests that microRNA (miRNA) signatures represent potent diagnostic, prognostic and treatment response biomarkers for several diseases. Using next-generation sequencing as an unbiased systematic approach 554 miRNAs were detected in preoperative plasma of 21 patients suffering from postoperative LD after liver resection and 27 matched controls. Subsequently, we identified a miRNA signature - consisting of miRNAs 151a-5p, 192-5p and 122-5p - that highly correlated with patients developing postoperative LD after liver resection. The predictive potential for postoperative LD was subsequently confirmed using real-time PCR in an independent validation cohort of 98 patients. Ultimately, a regression model of the two miRNA ratios 151a-5p to 192-5p and 122-5p to 151a-5p was found to reliably predict postoperative LD, severe morbidity, prolonged intensive care unit and hospital stay and even mortality prior to surgery with a remarkable accuracy, thereby outperforming established markers of postoperative LD. Ultimately, we documented that miRNA ratios closely followed liver function recovery after partial hepatectomy. Conclusion: Given the clinical relevance of predicting potentially fatal postoperative clinical outcome after liver resection, our data demonstrate the clinical utility of a novel miRNA-based biomarker to support the selection of patients undergoing partial hepatectomy. The dynamical changes during liver function recovery indicate a possible role in tailoring the optimal time point of surgery to each individual patient. Thereby, our data might help to tailor surgical strategies to the specific risk profile of individual patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE123605 | GEO | 2019/06/30

REPOSITORIES: GEO

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Project description:Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p<0.05). Due to the limited sample size these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identifies 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.

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Predicting Postoperative Liver Dysfunction Based on Blood Derived MicroRNA Signatures

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