Clinical Interest of Serum Alpha-2 Macroglobulin, Apolipoprotein A1, and Haptoglobin in Patients with Non-Alcoholic Fatty Liver Disease, with and without Type 2 Diabetes, before or during COVID-19

Exploring the Correlation Between Vitamin D Levels and Serological Markers in Liver Diseases: Insights from a Cross-Sectional Study

BACKGROUND/AIM

This study investigated the correlation between vitamin D levels and serological markers of liver diseases in two groups of patients: the control group (CG) and the study group (SG).

MATERIALS AND METHODS

The study analyzed data on vitamin D levels categorized as insufficient, sufficient, and optimal, along with serological markers, such as alpha2-macroglobulin, haptoglobin, apolipoprotein A1, bilirubin total, gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), glucose, total cholesterol, and triglycerides.

RESULTS

The results indicate significant differences in vitamin D levels between the two groups, particularly in SG, where vitamin D levels varied according to its status and correlated with serological markers. Marker levels, including alpha2-macroglobulin, glucose, and total cholesterol, were notably higher in SG compared to CG, suggesting a potential association with non-alcoholic fatty liver disease (NAFLD). Further analysis using Pearson correlation revealed a strong, inverse relationship between vitamin D levels and FibroTest, NashTest, alpha2-globulin, and glucose. Additionally, increasing FibroTest and NashTest stages, as well as levels of alpha2-macroglobulin and glucose, were associated with lower vitamin D levels in SG.

CONCLUSION

These findings under-score the complex interplay between vitamin D and serological markers in NAFLD, highlighting the potential significance of vitamin D levels in disease progression. Further research is warranted to elucidate the mechanisms underlying this relationship and its clinical implications.

Association of apolipoprotein A1 levels with lumbar bone mineral density and β-CTX in osteoporotic fracture individuals: a cross-sectional investigation

Background

The relationship between the levels of high-density lipoprotein (HDL) and bone mineral density (BMD) is controversial. Furthermore, the specific role of apolipoprotein A1 (APOA1), a primary HDL component, in regulating BMD remains unclear. This study aimed to elucidate the correlation between APOA1 levels and lumbar BMD in patients with osteoporotic fracture (OPF) for novel insights into potential therapeutic strategies against osteoporosis.

Methods

This study included 587 OPF patients enrolled at the Kunshan Hospital, Affiliated with Jiangsu University between January 2017 and July 2022. The patient's serum APOA1 levels were determined, followed by the assessment of lumbar BMD and C-terminal telopeptide of type I collagen (β-CTX) as outcome variables. The association of APOA1 levels with lumbar BMD and β-CTX was assessed via Generalized Estimating Equations (GEE) and spline smoothing plot analyses. A generalized additive model (GAM) helped ascertain non-linear correlations. Moreover, a subgroup analysis was also conducted to validate the result's stability.

Results

It was observed that APOA1 levels were positively correlated with lumbar BMD (β = 0.07, 95% CI: 0.02 to 0.11, p = 0.0045), indicating that increased APOA1 levels were linked with enhanced lumbar BMD. Furthermore, APOA1 levels were negatively related to β-CTX (β = -0.19, 95% CI: -0.29 to -0.09, p = 0.0003), suggesting APOA1 might reduce osteolysis. In addition, these findings were robustly supported by subgroup and threshold effect analyses.

Conclusion

This study indicated that increased APOA1 levels were correlated with enhanced lumbar BMD and decreased osteolysis in OPF patients. Therefore, APOA1 may inhibit osteoclast activity to prevent further deterioration in osteoporotic patients. However, further research I warranted to validate these conclusions and elucidate the underlying physiologies.

Multiomics Picture of Obesity in Young Adults

Obesity is a socially significant disease that is characterized by a disproportionate accumulation of fat. It is also associated with chronic inflammation, cancer, diabetes, and other comorbidities. Investigating biomarkers and pathological processes linked to obesity is especially vital for young individuals, given their increased potential for lifestyle modifications. By comparing the genetic, proteomic, and metabolomic profiles of individuals categorized as underweight, normal, overweight, and obese, we aimed to determine which omics layer most accurately reflects the phenotypic changes in an organism that result from obesity. We profiled blood plasma samples by employing three omics methodologies. The untargeted GC×GC-MS metabolomics approach identified 313 metabolites. To augment the metabolomic dataset, we integrated a label-free HPLC-MS/MS proteomics method, leading to the identification of 708 proteins. The genomic layer encompassed the genotyping of 647,250 SNPs. Utilizing omics data, we trained sparse Partial Least Squares models to predict body mass index. Molecular features exhibiting frequently non-zero coefficients were selected as potential biomarkers, and we further explored enriched biological pathways. Proteomics was the most effective in single-omics analyses, with a median absolute error (MAE) of 5.44 ± 0.31 kg/m2, incorporating an average of 24 proteins per model. Metabolomics showed slightly lower performance (MAE = 6.06 ± 0.33 kg/m2), followed by genomics (MAE = 6.20 ± 0.34 kg/m2). As expected, multiomic models demonstrated better accuracy, particularly the combination of proteomics and metabolomics (MAE = 4.77 ± 0.33 kg/m2), while including genomics data did not enhance the results. This manuscript is the first multiomics study of obesity in a gender-balanced cohort of young adults profiled by genomic, proteomic, and metabolomic methods. The comprehensive approach provides novel insights into the molecular mechanisms of obesity, opening avenues for more targeted interventions.

Global epidemiology of type 2 diabetes in patients with NAFLD or MAFLD: a systematic review and meta-analysis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) and metabolic-associated fatty liver disease (MAFLD) shares common pathophysiological mechanisms with type 2 diabetes, making them significant risk factors for type 2 diabetes. The present study aimed to assess the epidemiological feature of type 2 diabetes in patients with NAFLD or MAFLD at global levels.

METHODS

Published studies were searched for terms that included type 2 diabetes, and NAFLD or MAFLD using PubMed, EMBASE, MEDLINE, and Web of Science databases from their inception to December 2022. The pooled global and regional prevalence and incidence density of type 2 diabetes in patients with NAFLD or MAFLD were evaluated using random-effects meta-analysis. Potential sources of heterogeneity were investigated using stratified meta-analysis and meta-regression.

RESULTS

A total of 395 studies (6,878,568 participants with NAFLD; 1,172,637 participants with MAFLD) from 40 countries or areas were included in the meta-analysis. The pooled prevalence of type 2 diabetes among NAFLD or MAFLD patients was 28.3% (95% confidence interval 25.2-31.6%) and 26.2% (23.9-28.6%) globally. The incidence density of type 2 diabetes in NAFLD or MAFLD patients was 24.6 per 1000-person year (20.7 to 29.2) and 26.9 per 1000-person year (7.3 to 44.4), respectively.

CONCLUSIONS

The present study describes the global prevalence and incidence of type 2 diabetes in patients with NAFLD or MAFLD. The study findings serve as a valuable resource to assess the global clinical and economic impact of type 2 diabetes in patients with NAFLD or MAFLD.

[Establishment and validation of a predictive nomogram for liver fibrosis in patients with Wilson disease and abnormal lipid metabolism]

OBJECTIVE

To establish and validate predictive nomogram for liver fibrosis in patients with Wilson disease (WD) showing abnormal lipid metabolism.

METHODS

We retrospectively collected the clinical data of 500 patients with WD showing abnormalities in lipid metabolism, who were treated in the Department of Encephalopathy of the First Affiliated Hospital of Anhui University of Chinese Medicine from December, 2018 to December, 2021 and divided into modeling group and validation group. The independent risk factors of liver fibrosis in these patients were screened using LASSO regression and multivariate logistic regression analysis for establishment of the predictive nomogram. The area under the curve (AUC), calibration curve and decision curve of the receiver-operating characteristic curve (ROC) were used for internal and external verification of the nomogram in the modeling and validation group and evaluating the differentiation, calibration and clinical practicability of the model.

RESULTS

Triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (Apo-B) were independent risk factors for the development of liver fibrosis in patients with WD and abnormal lipid metabolism (P < 0.05). The predictive nomogram showed good discrimination, calibration and clinical utility in both the modeling and validation groups.

CONCLUSION

The established predictive nomogram in this study has a high accuracy for early identification and risk prediction of liver fibrosis in patients with WD having abnormal lipid metabolism.

Diabetes: A Multifaceted Disorder

Diabetes is a chronic disease associated with increased morbidity and mortality from cardiovascular diseases cancer, chronic obstructive pulmonary disease, and kidney or liver disease [...].