1. Serum Levels of Metabolites Produced by Intestinal Microbes and Lipid Moieties Independently Associated With Acute-on-Chronic Liver Failure and Death in Patients With Cirrhosis
- Author
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Bajaj, Jasmohan S, Reddy, K Rajender, O'Leary, Jacqueline G, Vargas, Hugo E, Lai, Jennifer C, Kamath, Patrick S, Tandon, Puneeta, Wong, Florence, Subramanian, Ram M, Thuluvath, Paul, Fagan, Andrew, White, Melanie B, Gavis, Edith A, Sehrawat, Tejasav, de la Rosa Rodriguez, Randolph, Thacker, Leroy R, Sikaroodi, Masoumeh, Garcia-Tsao, Guadalupe, and Gillevet, Patrick M
- Subjects
Medical Biochemistry and Metabolomics ,Biomedical and Clinical Sciences ,Clinical Sciences ,Liver Disease ,Clinical Research ,Digestive Diseases ,Chronic Liver Disease and Cirrhosis ,Oral and gastrointestinal ,Good Health and Well Being ,Acute-On-Chronic Liver Failure ,Adult ,Aged ,Bacteria ,Biomarkers ,Databases ,Factual ,Feces ,Female ,Gastrointestinal Microbiome ,Hospital Mortality ,Humans ,Lipidomics ,Lipids ,Liver Cirrhosis ,Male ,Metabolomics ,Middle Aged ,North America ,Patient Admission ,Predictive Value of Tests ,Prognosis ,Prospective Studies ,Risk Assessment ,Risk Factors ,Time Factors ,Tryptophan ,Estrone ,Sepsis ,Neurosciences ,Paediatrics and Reproductive Medicine ,Gastroenterology & Hepatology ,Clinical sciences ,Nutrition and dietetics - Abstract
Background & aimsInpatients with cirrhosis have high rates of acute-on-chronic failure (ACLF) development and high mortality within 30 days of admission to the hospital. Better biomarkers are needed to predict these outcomes. We performed metabolomic analyses of serum samples from patients with cirrhosis at multiple centers to determine whether metabolite profiles might identify patients at high risk for ACLF and death.MethodsWe performed metabolomic analyses, using liquid chromatography, of serum samples collected at time of admission to 12 North American tertiary hepatology centers from 602 patients in the North American Consortium for the Study of End-Stage Liver Disease sites from 2015 through 2017 (mean age, 56 years; 61% men; mean model for end-stage liver disease score, 19.5). We performed analysis of covariance, adjusted for model for end-stage liver disease at time of hospital admission, serum levels of albumin and sodium, and white blood cell count, to identify metabolites that differed between patients who did vs did not develop ACLF and patients who did vs did not die during hospitalization and within 30 days. We performed random forest analysis to identify specific metabolite(s) that were associated with outcomes and area under the curve (AUC) analyses to analyze them in context of clinical parameters. We analyzed microbiomes of stool samples collected from 133 patients collected at the same time and examined associations with serum metabolites.ResultsOf the 602 patients analyzed, 88 developed ACLF (15%), 43 died in the hospital (7%), and 72 died within 30 days (12%). Increased levels of compounds of microbial origin (aromatic compounds, secondary or sulfated bile acids, and benzoate) and estrogen metabolites, as well as decreased levels of phospholipids, were associated with development of ACLF, inpatient, and 30-day mortality and were also associated with fecal microbiomes. Random forest analysis and logistic regression showed that levels of specific microbially produced metabolites identified patients who developed ACLF with an AUC of 0.84 (95% confidence interval [CI] 0.78-0.88; P = .001), patients who died while in the hospital with an AUC of 0.81 (95% CI 0.74-0.85; P = .002), and patients who died within 30 days with an AUC of 0.77 (95% CI 0.73-0.81; P = .02). The metabolites were significantly additive to clinical parameters for predicting these outcomes. Metabolites associated with outcomes were also correlated with microbiomes of stool samples.ConclusionsIn an analysis of serum metabolites and fecal microbiomes of patients hospitalized with cirrhosis at multiple centers, we associated metabolites of microbial origin and lipid moieties with development of ACLF and death as an inpatient or within 30 days, after controlling for clinical features.
- Published
- 2020