Identification of the Microbiome Associated with Prognosis in Patients with Chronic Liver Disease.
Kenta YamamotoTakashi HondaYosuke InukaiShinya YokoyamaTakanori ItoNorihiro ImaiYoji IshizuMasanao NakamuraHiroki KawashimaPublished in: Microorganisms (2024)
We investigated the prognostic role of the gut microbiome and clinical factors in chronic liver disease (hepatitis, cirrhosis, and hepatocellular carcinoma [HCC]). Utilizing data from 227 patients whose stool samples were collected over the prior 3 years and a Cox proportional hazards model, we integrated clinical attributes and microbiome composition based on 16S ribosomal RNA sequencing. HCC was the primary cause of mortality, with the Barcelona Clinic Liver Cancer staging system-derived B/C significantly increasing the mortality risk (hazard ratio [HR] = 8.060; 95% confidence interval [CI]: 3.6509-17.793; p < 0.001). Cholesterol levels < 140 mg/dL were associated with higher mortality rates (HR = 4.411; 95% CI: 2.0151-9.6555; p < 0.001). Incertae sedis from Ruminococcaceae showed a protective effect, reducing mortality risk (HR = 0.289; 95% CI: 0.1282 to 0.6538; p = 0.002), whereas increased Veillonella presence was associated with a higher risk (HR = 2.733; 95% CI: 1.1922-6.2664; p = 0.017). The potential of specific bacterial taxa as independent prognostic factors suggests that integrating microbiome data could improve the prognosis and treatment of chronic liver disease. These microbiome-derived markers have prognostic significance independently and in conjunction with clinical factors, suggesting their utility in improving a patient's prognosis.
Keyphrases
- prognostic factors
- cardiovascular events
- end stage renal disease
- electronic health record
- primary care
- ejection fraction
- single cell
- big data
- newly diagnosed
- risk factors
- lymph node
- chronic kidney disease
- cardiovascular disease
- coronary artery disease
- case report
- high resolution
- peritoneal dialysis
- single molecule
- artificial intelligence
- replacement therapy
- atomic force microscopy