Development of non-invasive method for assessment of hepatic steatosis

Association Between Liver Fibrosis Score and Diabetic Kidney Disease: A Retrospective Cross-Sectional Study of Hospitalized Patients

OBJECTIVES

To investigate the association between liver fibrosis score and diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM).

METHODS

A total of 897 hospitalized patients with T2DM were included in this study. Each patient completed DKD screening. Logistic regression analysis was used to assess the predictive value of non-alcoholic fatty liver disease fibrosis score (NAFLD-FS) and fibrosis-4 (FIB-4) for the occurrence of DKD and risk for DKD progression, respectively.

RESULTS

The prevalence of DKD and risk for its progression significantly increased with increasing NAFLD-FS risk category. DKD prevalence also increased with increasing FIB-4 risk category. Multivariate logistic regression analysis showed that the "high-risk" NAFLD-FS had a significantly higher risk of DKD (odds ratio [OR]: 1.89, 95% confidence interval [CI]: 1.16-3.08) and risk for DKD progression (OR: 2.88, 95% CI: 1.23-6.78), and the "intermediate-risk" FIB-4 had a significantly higher risk of DKD (OR: 1.41, 95% CI: 1.00-1.98). Subgroup analysis showed that the association between NAFLD-FS and FIB-4 and DKD was significant in the female subgroup, whereas the association between the "high-risk" NAFLD-FS and risk for DKD progression was significant in the male subgroup.

CONCLUSIONS

NAFLD-FS and FIB-4 are strongly associated with DKD and risk for DKD progression in patients with T2DM. Additionally, sexual dimorphism exists in this association.

A pilot study optimizing metabolomic and lipidomic acquisition in serum for biomarker discovery in nonalcoholic fatty liver disease

Background

The worldwide prevalence of non-alcoholic fatty liver disease (NAFLD) has stimulated work to identify biomarkers and develop effective treatments. Metabolomics is an emerging tool that has been widely applied to discover biomarkers and simultaneously uncover pathological mechanisms. Here, we aim to optimize metabolomic acquisition with the goal of obtaining a systemic metabolic profile to unravel the potential link between dysregulated metabolism and NAFLD.

Methods

We analyzed serum samples collected from healthy subjects (n = 8) and NAFLD patients (n = 8) via an integrative analytical workflow using two orthogonal separation modes with T3 and amide columns and two ionization polarity modes on a UPLC-ESI-Q/TOF. Data dependent acquisition was employed for data acquisition. Differentially expressed metabolites and lipids were identified by comparing the collected metabolic and lipidomic profiles between the healthy subjects and NAFLD patients.

Results

The integrative LC-MS/MS analytical workflow employed here features an improved coverage of metabolites and lipids, which leads to the identification of 20 potential biomarkers of NAFLD, including lipids, acylcarnitines, and organic acids.

Conclusions

This pilot study has identified potential biomarkers for NAFLD and revealed corresponding dysregulated metabolic pathways related to NAFLD's occurrence and progression, establishing a molecular basis for NAFLD diagnosis and therapeutic intervention.