Infectious and many non-infectious diseases share common molecular mechanisms. Among them, oxidative stress and the subsequent inflammatory reaction are of particular note. Metabolic disorders induced by external agents, be they bacterial or viral pathogens, excessive calorie intake, poor-quality nutrients, or environmental factors produce an imbalance between the production of free radicals and endogenous antioxidant systems; the consequence being the oxidation of lipids, proteins, and nucleic acids. Oxidation and inflammation are closely related, and whether oxidative stress and inflammation represent the causes or consequences of cellular pathology, both produce metabolic alterations that influence the pathogenesis of the disease. In this review, we highlight two key molecules in the regulation of these processes: Paraoxonase-1 (PON1) and chemokine (C-C motif) ligand 2 (CCL2). PON1 is an enzyme bound to high-density lipoproteins. It breaks down lipid peroxides in lipoproteins and cells, participates in the protection conferred by HDL against different infectious agents, and is considered part of the innate immune system. With PON1 deficiency, CCL2 production increases, inducing migration and infiltration of immune cells in target tissues and disturbing normal metabolic function. This disruption involves pathways controlling cellular homeostasis as well as metabolically-driven chronic inflammatory states. Hence, an understanding of these relationships would help improve treatments and, as well, identify new therapeutic targets.

Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunately, accessing the liver is invasive, requires a multidisciplinary team and is too expensive to be conducted on large segments of the population. NAFLD starts quietly and can progress until liver damage is irreversible. Given this complex situation, the search for noninvasive alternatives is clinically important. A hallmark of NAFLD progression is the dysregulation in lipid metabolism. In this context, recent advances in the area of machine learning have increased the interest in evaluating whether multi-omics data analysis performed on peripheral blood can enhance human interpretation. In the present review, we show how the use of machine learning can identify sets of lipids as predictive biomarkers of NAFLD progression. This approach could potentially help clinicians to improve the diagnosis accuracy and predict the future risk of the disease. While NAFLD has no effective treatment yet, the key to slowing the progression of the disease may lie in predictive robust biomarkers. Hence, to detect this disease as soon as possible, the use of computational science can help us to make a more accurate and reliable diagnosis. We aimed to provide a general overview for all readers interested in implementing these methods.

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its more severe form steatohepatitis (MASH) contribute to rising morbidity and mortality rates. The storage of fat in humans is closely associated with these diseases' progression. Thus, adipose tissue metabolic homeostasis could be key in both the onset and progression of MASH. We conducted a case-control observational research using a systems biology-based approach to analyse liver, abdominal subcutaneous adipose tissue (SAT), omental visceral adipose tissue (VAT), and blood of n = 100 patients undergoing bariatric surgery (NCT05554224). MASH was diagnosed through histologic assessment. Whole-slide image analysis, lipidomics, proteomics, and transcriptomics were performed on tissue samples. Lipidomics and proteomics profiles were determined on plasma samples. Liver transcriptomics, proteomics, and lipidomics revealed interconnected pathways associated with inflammation, mitochondrial dysfunction, and lipotoxicity in MASH. Paired adipose tissue biopsies had larger adipocyte areas in both fat depots in MASH. Enrichment analyses of proteomics and lipidomics data confirmed the association of liver lesions with mitochondrial dysfunction in VAT. Plasma lipidomics identified candidates with high diagnostic accuracy (AUC = 0.919, 95% CI 0.840-0.979) for screening MASH. Mitochondrial dysfunction is also present in VAT in patients with obesity-associated MASH. This may cause a disruption in the metabolic equilibrium of lipid processing and storage, which impacts the liver and accelerates detrimental adaptative responses. The project leading to these results has received funding from 'la Caixa' Foundation (HR21-00430), and from the Instituto de Salud Carlos III (ISCIII) (PI21/00510) and co-funded by the European Union.

SARS-CoV-2 infection produces a response of the innate immune system causing oxidative stress and a strong inflammatory reaction termed ‘cytokine storm’ that is one of the leading causes of death. Paraoxonase-1 (PON1) protects against oxidative stress by hydrolyzing lipoperoxides. Alterations in PON1 activity have been associated with pro-inflammatory mediators such as the chemokine (C-C motif) ligand 2 (CCL2), and the glycoprotein galectin-3. We aimed to investigate the alterations in the circulating levels of PON1, CCL2, and galectin-3 in 126 patients with COVID-19 and their interactions with clinical variables and analytical parameters. A machine learning approach was used to identify predictive markers of the disease. For comparisons, we recruited 45 COVID-19 negative patients and 50 healthy individuals. Our approach identified a synergy between oxidative stress, inflammation, and fibrogenesis in positive patients that is not observed in negative patients. PON1 activity was the parameter with the greatest power to discriminate between patients who were either positive or negative for COVID-19, while their levels of CCL2 and galectin-3 were similar. We suggest that the measurement of serum PON1 activity may be a useful marker for the diagnosis of COVID-19.