Platelets as a Gauge of Liver Disease Kinetics?

A multitude of laboratory and clinical interferences influence the utility of platelet-based diagnostic indices, including immature platelet fraction, in longitudinal monitoring and prognostication of patients with chronic liver disease (CLD). The complex yet highly regulated molecular basis of platelet production and clearance kinetics becomes dysregulated in liver pathogenesis. These underlying molecular mechanisms, including premature platelet clearance and bone marrow suppression in parallel with the progressive (e.g., treatment-naïve) or regressive (e.g., on-treatment and off-treatment) disease courses, involved in CLDs, may further confound the changes in platelet-liver correlations over time. Platelet count and function are commonly and secondarily altered in vivo in CLDs. However, the precise characterization of platelet functions during cirrhosis, including in vitro platelet aggregation, has proven challenging due to interferences such as thrombocytopenia. A flow cytometric approach may help monitor the unstably rebalanced hyper- and hypoaggregable states in patients with cirrhosis at risk of hyperaggregable, prothrombotic, or bleeding events. Studies have attempted to stratify patients with cirrhosis by substages and prognosis through the use of novel indices such as the ratio of in vitro endogenous platelet aggregation to platelet count. This review attempts to highlight clinical and laboratory precautions in the context of platelet-assisted CLD monitoring.

Gut Microbial Signatures for Glycemic Responses of GLP-1 Receptor Agonists in Type 2 Diabetic Patients: A Pilot Study.

Backgrounds: Glucagon-like peptide-1 receptor agonist (GLP-1 RA) is probably one of more effective antidiabetic agents in treatment of type 2 diabetes mellitus (T2D). However, the heterogenicity in responses to GLP-1 RA may be potentially related to gut microbiota, although no human evidence has been published. This pilot study aims to identify microbial signatures associated with glycemic responses to GLP-1 RA. Materials and Methods: Microbial compositions of 52 patients with T2D receiving GLP-1 RA were determined by 16S rRNA amplicon sequencing. Bacterial biodiversity was compared between responders versus non-responders. Pearson's correlation and random forest tree algorithm were used to identify microbial features of glycemic responses in T2D patients and multivariable linear regression models were used to validate clinical relevance. Results: Beta diversity significantly differed between GLP-1 RA responders (n = 34) and non-responders (n = 18) (ADONIS, P = 0.004). The top 17 features associated with glycohemoglobin reduction had a 0.96 diagnostic ability, based on area under the ROC curve: Bacteroides dorei and Roseburia inulinivorans, the two microbes having immunomodulation effects, along with Lachnoclostridium sp. and Butyricicoccus sp., were positively correlated with glycemic reduction; Prevotella copri, the microbe related to insulin resistance, together with Ruminococcaceae sp., Bacteroidales sp., Eubacterium coprostanoligenes sp., Dialister succinatiphilus, Alistipes obesi, Mitsuokella spp., Butyricimonas virosa, Moryella sp., and Lactobacillus mucosae had negative correlation. Furthermore, Bacteroides dorei, Lachnoclostridium sp. and Mitsuokella multacida were significant after adjusting for baseline glycohemoglobin and C-peptide concentrations, two clinical confounders. Conclusions: Unique gut microbial signatures are associated with glycemic responses to GLP-RA treatment and reflect degrees of dysbiosis in T2D patients.