Metabolic phenotyping of patients with advanced chronic liver disease for better characterization of cirrhosis regression.

BACKGROUND & AIMS: Regression of cirrhosis has been observed in patients with viral and non-viral etiologies of liver disease in whom the underlying cause of liver injury was effectively suppressed. However, the understanding of the factors contributing to reversibility of fibrosis and cirrhosis is limited. Our aims were to assess clinical factors, perform genotyping of known variants, and comprehensive metabolic phenotyping to characterize the regression of fibrosis in patients with compensated advanced chronic liver disease (cACLD). METHODS: In a case-control pilot study of 81 patients with cACLD, we compared individuals exhibiting histological or clinical evidence of cACLD regression ("regressors"; n = 44) with those showing no improvement ("non-regressors"; n = 37) after a minimum of 24 months of successful treatment of the cause of liver disease. Data were validated using an external validation cohort (n = 30). RESULTS: Regardless of the cause of cACLD, the presence of obesity (odds ratio [OR] 0.267 95% CI 0.072-0.882; p = 0.049), high liver stiffness (OR 0.960, 95% CI 0.925-0.995; p = 0.032), and carriage of GCKR variant rs1260326 (OR 0.148, 95% CI 0.030-0.773; p = 0.019) are associated with a reduced likelihood of fibrosis regression in a subgroup of 60 patients with ACLD genotyped for known genetic variants. Using liver tissue transcriptomics, we identified metabolic pathways differentiating regressors from non-regressors, with top pathways associated with lipid metabolism - especially fatty acids, bile acids, phospholipids, triacylglycerides (biosynthesis), and the carnitine shuttle. In the entire discovery cohort, we further measured metabolites within the defined pathways, which led to the identification of 33 circulating markers differentiating regressors from non-regressors after etiological therapy. The validation cohort confirmed 14 of the differentially expressed markers. CONCLUSIONS: We identified and validated a group of lipid biomarkers associated with regression of fibrosis that could be used as non-invasive biomarkers for detecting regression of fibrosis in cACLD. IMPACT AND IMPLICATIONS: Regression of cirrhosis/advanced chronic liver disease (ACLD) after removal of the underlying cause of liver injury has been observed in human cirrhosis. However, detailed characterization of ACLD regression remains an unmet need. In this study, we provide a comprehensive phenotyping of individuals likely to experience ACLD regression. While obesity, carriage of GCKR variant rs1260326 and high liver stiffness were associated with lower likelihood of regression of ACLD, a signature of circulating lipid metabolites enabled differentiation of regressors from non-regressors after effective etiologic therapy. The lipid signature we discovered and externally validated could be used as non-invasive biomarker to detect regression of fibrosis in patients with compensated ACLD.

Metabolomics by UHPLC-MS: benefits provided by complementary use of Q-TOF and QQQ for pathway profiling.

INTRODUCTION: Non-targeted metabolic profiling using high-resolution mass spectrometry (HRMS) is a standard approach for pathway identification despite technical limitations. OBJECTIVES: To assess the performance of combining targeted quadrupole (QQQ) analysis with HRMS for in-depth pathway profiling. METHODS: Serum of exercising patients with type 1 diabetes (T1D) was profiled using targeted and non-targeted assays. RESULTS: Non-targeted analysis yielded a broad unbiased metabolic profile, targeted analysis increased coverage of purine metabolism (twofold) and TCA cycle (three metabolites). CONCLUSION: Our screening strategy combined the benefits of the unbiased full-scan HRMS acquisition with the deeper insight into specific pathways by large-scale QQQ analysis.

Transcriptomics-driven metabolic pathway analysis reveals similar alterations in lipid metabolism in mouse MASH model and human.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent chronic liver disease worldwide, and can rapidly progress to metabolic dysfunction-associated steatohepatitis (MASH). Accurate preclinical models and methodologies are needed to understand underlying metabolic mechanisms and develop treatment strategies. Through meta-analysis of currently proposed mouse models, we hypothesized that a diet- and chemical-induced MASH model closely resembles the observed lipid metabolism alterations in humans. METHODS: We developed transcriptomics-driven metabolic pathway analysis (TDMPA), a method to aid in the evaluation of metabolic resemblance. TDMPA uses genome-scale metabolic models to calculate enzymatic reaction perturbations from gene expression data. We performed TDMPA to score and compare metabolic pathway alterations in MASH mouse models to human MASH signatures. We used an already-established WD+CCl4-induced MASH model and performed functional assays and lipidomics to confirm TDMPA findings. RESULTS: Both human MASH and mouse models exhibit numerous altered metabolic pathways, including triglyceride biosynthesis, fatty acid beta-oxidation, bile acid biosynthesis, cholesterol metabolism, and oxidative phosphorylation. We confirm a significant reduction in mitochondrial functions and bioenergetics, as well as in acylcarnitines for the mouse model. We identify a wide range of lipid species within the most perturbed pathways predicted by TDMPA. Triglycerides, phospholipids, and bile acids are increased significantly in mouse MASH liver, confirming our initial observations. CONCLUSIONS: We introduce TDMPA, a methodology for evaluating metabolic pathway alterations in metabolic disorders. By comparing metabolic signatures that typify human MASH, we show a good metabolic resemblance of the WD+CCl4 mouse model. Our presented approach provides a valuable tool for defining metabolic space to aid experimental design for assessing metabolism.

Steatotic liver disease, in which fat accumulates in the liver, is one of the most prevalent liver diseases worldwide and it is important to develop relevant animal models to help us understand its mechanisms. We aimed to assess the suitability of animal models for studying steatotic liver disease in humans. We developed an approach that evaluates how genes affect the metabolism or the chemical reactions and processes that occur in the body. We used it to compare a mouse model of the disease with human observations. Our results showed that there are significant changes in fat and energy metabolism in the mouse model. These observations match with changes observed in humans, suggesting it is a good model for studying human disease. Our findings could advance our understanding of the disease as well as help define strategies for its treatment.

Specific GAG ratios in the diagnosis of mucopolysaccharidoses.

Mucopolysaccharidoses (MPS) screening is tedious and still performed by analysis of total glycosaminoglycans (GAG) using 1,9-dimethylmethylene blue (DMB) photometric assay, although false positive and negative tests have been reported. Analysis of differentiated GAGs have been pursued classically by gel electrophoresis or more recently by quantitative LC-MS assays. Secondary elevations of GAGs have been reported in urinary tract infections (UTI). In this manuscript, we describe the diagnostic accuracy of urinary GAG measurements by LC-MS for MPS typing in 68 untreated MPS and mucolipidosis (ML) patients, 183 controls and 153 UTI samples. We report age-dependent reference values and cut-offs for chondroitin sulfate (CS), dermatan sulfate (DS), heparan sulfate (HS) and keratan sulfate (KS) and specific GAG ratios. The use of HS/DS ratio in combination to GAG concentrations normalized to creatinine improves the diagnostic accuracy in MPS type I, II, VI and VII. In total 15 samples classified to the wrong MPS type could be correctly assigned using HS/DS ratio. Increased KS/HS ratio in addition to increased KS improves discrimination of MPS type IV by excluding false positives. Some samples of UTI patients showed elevation of specific GAGs, mainly CS, KS and KS/HS ratio and could be misclassified as MPS type IV. Finally, DMB photometric assay performed in MPS and ML samples reveal four false negative tests (sensitivity of 94%). In conclusion, specific GAG ratios in complement to quantitative GAG values obtained by LC-MS enhance discrimination of MPS types. Exclusion of patients with UTI improve diagnostic accuracy in MPS IV but not in other types.

Effects of Freezing and Thawing Procedures on Selected Clinical Chemistry Parameters in Plasma.

Introduction: Measurements from frozen sample collections are important key indicators in clinical studies. It is a prime concern of biobanks and laboratories to minimize preanalytical bias and variance through standardization. In this study, we aimed at assessing the effects of different freezing and thawing conditions on the reproducibility of medical routine parameters from frozen samples. Materials and Methods: In total, 12 pooled samples were generated from leftover lithium heparinized plasma samples from clinical routine testing. Aliquots of the pools were frozen using three freezing methods (in carton box at -80°C, flash freezing in liquid nitrogen, and controlled-rate freezing [CRF]) and stored at -80°C. After 3 days, samples were thawed using two methods (30 minutes at room temperature or water bath at 25°C for 3 minutes). Ten clinical chemistry laboratory parameters were measured before (baseline) and after freeze-thaw treatment: total calcium, potassium, sodium, alanine aminotransferase, lactate dehydrogenase (LDH), lipase, uric acid, albumin, c-reactive protein (CRP), and total protein. We evaluated the influence of the different preanalytical treatments on the test results and compared each condition with nonfrozen baseline measurements. Results: We found no significant differences between freezing methods for all tested parameters. Only LDH was significantly affected by thawing with fast-rate thawing being closer to baseline than slow-rate thawing. Potassium, LDH, lipase, uric acid, albumin, and CRP values were significantly changed after freezing and thawing compared with unfrozen samples. The least prominent changes compared with unfrozen baseline measurements were obtained when a CRF protocol of the local biobank and fast thawing was applied. However, the observed changes between baseline and frozen samples were smaller than the measurement uncertainty for 9 of the 10 parameters. Discussion: Changes introduced through freezing-thawing were small and not of clinical importance. A slight statistically based preference toward results from slow CRF and fast thawing of plasma being closest to unfrozen samples could be supported.