Mitochondrial dysfunction, lipids metabolism, and amino acid biosynthesis are key pathways for COVID-19 recovery

Biological sciences; Human metabolismCiències biològiques; Metabolisme humàCiencias biológicas; Metabolismo humanoThe metabolic alterations caused by SARS-CoV-2 infection reflect disease progression. To analyze molecules involved in these metabolic changes, a multiomics study was performed using plasma from 103 patients with different degrees of COVID-19 severity during the evolution of the infection. With the increased severity of COVID-19, changes in circulating proteomic, metabolomic, and lipidomic profiles increased. Notably, the group of severe and critical patients with high HRG and ChoE (20:3) and low alpha-ketoglutaric acid levels had a high chance of unfavorable disease evolution (AUC = 0.925). Consequently, patients with the worst prognosis presented alterations in the TCA cycle (mitochondrial dysfunction), lipid metabolism, amino acid biosynthesis, and coagulation. Our findings increase knowledge regarding how SARS-CoV-2 infection affects different metabolic pathways and help in understanding the future consequences of COVID-19 to identify potential therapeutic targets.This work has been developed in the framework of the COVIDOMICS’ project supported by Direcció General de Recerca i Innovació en Salut (DGRIS), Departament de Salut, Generalitat de Catalunya (PoC-6-17 and PoC1-5). The research was also supported by the Programa de Suport als Grups de Recerca AGAUR (2021SGR01404), the SPANISH AIDS Research Network [RD16/0025/0006]-ISCIII-FEDER (Spain) and the CIBER -Consorcio Centro de Investigación Biomédica en Red- (CB21/13/00020 and CB07/08/0012), Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea – NextGenerationEU. FV is supported by grants from the Programa de Intensificación de Investigadores (INT20/00031)-ISCIII and by “Premi a la Trajectòria Investigadora dels Hospitals de l’ICS 2018”. AR is supported by a grant from IISPV through the project “2019/IISPV/05” (Boosting Young Talent), by GeSIDA through the “III Premio para Jóvenes Investigadores 2019” and by the Instituto de Salud Carlos III (ISCIII) under grant agreement “CP19/00146” through the Miguel Servet Program. Finally, this study would not have been possible without the generous collaboration of all the patients and their families and medical and nursing staff who have taken part in the project. We particularly acknowledge the collaboration of the Departments of Preventive Medicine and Epidemiology, Internal Medicine, Critical Care, Emergency, Occupational Health, Laboratory Medicine and Molecular Biology, and BioBank-IISPV (B.0000853 + B.0000854) integrated into the Spanish National Biobanks Platform (PT20/00197), CERCA Program (Generalitat de Catalunya) and IISPV, for their collaboration

Alterations in Metabolome and Microbiome Associated with an Early Stress Stage in Male Wistar Rats: A Multi-Omics Approach

Stress disorders have dramatically increased in recent decades becoming the most prevalent psychiatric disorder in the United States and Europe. However, the diagnosis of stress disorders is currently based on symptom checklist and psychological questionnaires, thus making the identification of candidate biomarkers necessary to gain better insights into this pathology and its related metabolic alterations. Regarding the identification of potential biomarkers, omic profiling and metabolic footprint arise as promising approaches to recognize early biochemical changes in such disease and provide opportunities for the development of integrative candidate biomarkers. Here, we studied plasma and urine metabolites together with metagenomics in a 3 days Chronic Unpredictable Mild Stress (3d CUMS) animal approach that aims to focus on the early stress period of a well-established depression model. The multi-omics integration showed a profile composed by a signature of eight plasma metabolites, six urine metabolites and five microbes. Specifically, threonic acid, malic acid, alpha-ketoglutarate, succinic acid and cholesterol were proposed as key metabolites that could serve as key potential biomarkers in plasma metabolome of early stages of stress. Such findings targeted the threonic acid metabolism and the tricarboxylic acid (TCA) cycle as important pathways in early stress. Additionally, an increase in opportunistic microbes as virus of the Herpesvirales was observed in the microbiota as an effect of the primary stress stages. Our results provide an experimental biochemical characterization of the early stage of CUMS accompanied by a subsequent omic profiling and a metabolic footprinting that provide potential candidate biomarkers

Brain N-Glycosylation and Lipidomic Profile Changes Induced by a High-Fat Diet in Dyslipidemic Hamsters

The consumption of diets rich in saturated fats is known to be associated with higher mortality. The adoption of healthy habits, for instance adhering to a Mediterranean diet, has proved to exert a preventive effect towards cardiovascular diseases and dyslipidemia. Little is known about how a suboptimal diet can affect brain function, structure, and the mechanisms involved. The aims of this study were to examine how a high-fat diet can alter the brain N-glycan and lipid profile in male Golden Syrian hamsters and to evaluate the potential of a Mediterranean-like diet to reverse this situation. During twelve weeks, hamsters were fed a normal fat diet (CTRL group), a high-fat diet (HFD group), and a high-fat diet followed by a Mediterranean-like diet (MED group). Out of seventy-two identified N-glycans, fourteen were significant (p < 0.05) between HFD and CTRL groups, nine between MED and CTRL groups, and one between MED and HFD groups. Moreover, forty-nine lipids were altered between HFD and CTRL groups, seven between MED and CTRL groups, and five between MED and HFD groups. Our results suggest that brain N-glycan composition in high-fat diet-fed hamsters can produce events comparable to those found in some neurodegenerative diseases, and may promote brain ageing

Alterations in Metabolome and Microbiome Associated with an Early Stress Stage in Male Wistar Rats: A Multi-Omics Approach

Stress disorders have dramatically increased in recent decades becoming the most prevalent psychiatric disorder in the United States and Europe. However, the diagnosis of stress disorders is currently based on symptom checklist and psychological questionnaires, thus making the identification of candidate biomarkers necessary to gain better insights into this pathology and its related metabolic alterations. Regarding the identification of potential biomarkers, omic profiling and metabolic footprint arise as promising approaches to recognize early biochemical changes in such disease and provide opportunities for the development of integrative candidate biomarkers. Here, we studied plasma and urine metabolites together with metagenomics in a 3 days Chronic Unpredictable Mild Stress (3d CUMS) animal approach that aims to focus on the early stress period of a well-established depression model. The multi-omics integration showed a profile composed by a signature of eight plasma metabolites, six urine metabolites and five microbes. Specifically, threonic acid, malic acid, alpha-ketoglutarate, succinic acid and cholesterol were proposed as key metabolites that could serve as key potential biomarkers in plasma metabolome of early stages of stress. Such findings targeted the threonic acid metabolism and the tricarboxylic acid (TCA) cycle as important pathways in early stress. Additionally, an increase in opportunistic microbes as virus of the Herpesvirales was observed in the microbiota as an effect of the primary stress stages. Our results provide an experimental biochemical characterization of the early stage of CUMS accompanied by a subsequent omic profiling and a metabolic footprinting that provide potential candidate biomarkers

Developing a model to predict the early risk of hypertriglyceridemia based on inhibiting lipoprotein lipase (LPL): a translational study

Abstract Hypertriglyceridemia (HTG) is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). One of the multiple origins of HTG alteration is impaired lipoprotein lipase (LPL) activity, which is an emerging target for HTG treatment. We hypothesised that early, even mild, alterations in LPL activity might result in an identifiable metabolomic signature. The aim of the present study was to assess whether a metabolic signature of altered LPL activity in a preclinical model can be identified in humans. A preclinical LPL-dependent model of HTG was developed using a single intraperitoneal injection of poloxamer 407 (P407) in male Wistar rats. A rat metabolomics signature was identified, which led to a predictive model developed using machine learning techniques. The predictive model was applied to 140 humans classified according to clinical guidelines as (1) normal, less than 1.7 mmol/L; (2) risk of HTG, above 1.7 mmol/L. Injection of P407 in rats induced HTG by effectively inhibiting plasma LPL activity. Significantly responsive metabolites (i.e. specific triacylglycerols, diacylglycerols, phosphatidylcholines, cholesterol esters and lysophospholipids) were used to generate a predictive model. Healthy human volunteers with the impaired predictive LPL signature had statistically higher levels of TG, TC, LDL and APOB than those without the impaired LPL signature. The application of predictive metabolomic models based on mechanistic preclinical research may be considered as a strategy to stratify subjects with HTG of different origins. This approach may be of interest for precision medicine and nutritional approaches