Salivary microbiome and serum metabolomics add to clinical biomarkers to predict 6-month hospitalizations in a multicenter cirrhosis outpatient cohort

医学 微生物群 队列 肝硬化 代谢组学 中心(范畴论) 队列研究 门诊部 肠道微生物群 内科学 生物信息学 生物 结晶学 化学
作者
Jasmohan S. Bajaj,K. Rajender Reddy,Puneeta Tandon,Jennifer C. Lai,Jacqueline G. O’Leary,Florence Wong,Guadalupe García–Tsao,Hugo E. Vargas,Patrick S. Kamath,Scott W. Biggins,Phillip Vutien,Jawaid Shaw,Ana Teresa Limon Miro,Chinmay Bera,Joseph McGinley,Masoumeh Sikaroodi,Brian J. Bush,Leroy R. Thacker,Patrick M. Gillevet
出处
期刊:Hepatology [Lippincott Williams & Wilkins]
卷期号:83 (6): 1483-1494 被引量:4
标识
DOI:10.1097/hep.0000000000001462
摘要

BACKGROUND AND AIMS: Prognosticating outcomes such as hospitalizations in outpatients with cirrhosis is challenging, especially with changing etiologies and demographics. This study aims to determine the impact of multi-omic strategies on outcome prediction. APPROACH AND RESULTS: NACSELD3 enrolls outpatients with cirrhosis with controlled/eradicated etiologies from 10 centers and follows them systematically. At baseline, clinical/demographic and cirrhosis details were recorded and saliva and serum samples were collected for microbiome and metabolome analysis, respectively. Multi-omic bioinformatic studies to determine the interaction of microbiota and metabolites with the clinical prediction of 6-month hospitalizations were performed. Five hundred sixty-five patients (60.2 y, 68% men, 35% alcohol, 33% metabolic dysfunction-associated steatohepatitis, 21%, eradicated HCV with MELD 3.0 12) were enrolled. One hundred sixty-three (29%) required 6-month hospitalizations; most (75%) were liver-related. Those hospitalized had worse cirrhosis severity and comorbidity indices but similar demographics and oral health variables. Salivary microbiome alpha-diversity was lower (1.96±0.48 vs. 2.09±0.45, p =0.018) with greater pathobionts ( Streptococcus , Treponema, Enterococcaceae) and lower commensal genhospitalized/noera ( Veillonella, Prevotella, Haemophilus , Lachnospiraceae spp) at baseline. Serum metabolomics showed significant separation at baseline between hospitalized/non-hospitalized patients using supervised analyses with microbial-origin (phenyllactate, secondary bile acids, indoles), choline moieties, and polyamine/GABA (3-ureidopropionate/spermidine) metabolites being most prominent. Area under the curve using random forest for clinical, microbial, and metabolomic variables was higher than that of these individually. Latent factor analysis showed clinical variables (MELD 3.0, hemoglobin, and albumin) with the greatest impact, followed by salivary microbiota and then serum microbiome for hospitalization prediction. CONCLUSIONS: In a multicenter North American outpatient cirrhosis cohort with controlled etiologies, serum metabolomics and salivary microbiome add to clinical variables to prognosticate 6-month hospitalization.
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