This study explores the suitability of Raman spectroscopy as a bioanalytical tool, when coupled with ultra-filtration and multivariate analysis, to detect imbalances in both high molecular weight and low molecular weight fractions of the same samples of human patient serum, in the native liquid form.

Obese patients who often present metabolic dysfunction-associated fatty liver disease (MAFLD) are at risk of severe presentation of coronavirus disease 2019 (COVID-19). These patients are more likely to be hospitalized and receive antiviral agents and other drugs required to treat acute respiratory distress syndrome and systemic inflammation, combat bacterial and fungal superinfections and reverse multi-organ failure. Among these pharmaceuticals, antiretrovirals such as lopinavir/ritonavir and remdesivir, antibiotics and antifungal agents can induce drug-induced liver injury (DILI), whose mechanisms are not always understood. In the present article, we hypothesize that obese COVID-19 patients with MAFLD might be at higher risk for DILI than non-infected healthy individuals or MAFLD patients. These patients present several concomitant factors, which individually can favour DILI: polypharmacy, systemic inflammation at risk of cytokine storm, fatty liver and sometimes nonalcoholic steatohepatitis (NASH) as well as insulin resistance and other diseases linked to obesity. Hence, in obese COVID-19 patients, some drugs might cause more severe (and/or more frequent) DILI, while others might trigger the transition of fatty liver to NASH, or worsen pre-existing steatosis, necroinflammation and fibrosis. We also present the main mechanisms whereby drugs can be more hepatotoxic in MAFLD including impaired activity of xenobiotic-metabolizing enzymes, mitochondrial dysfunction, altered lipid homeostasis and oxidative stress. Although comprehensive investigations are needed to confirm our hypothesis, we believe that the current epidemic of obesity and related metabolic diseases has extensively contributed to increase the number of cases of DILI in COVID-19 patients, which may have participated in presentation severity and death.

In amyotrophic lateral sclerosis (ALS), motor neuron degeneration is associated with systemic metabolic impairment. However, the evolution of metabolism alteration is partially unknown and its link with disease progression has never been described. For the first time, we ran a study focused on (1) the evolution of metabolism disturbance during disease progression through omics approaches and (2) the relation between metabolome profile and clinical evolution. SOD1-G93A (mSOD1) transgenic mice (n = 11) and wild-type (WT) littermates (n = 17) were studied during 20 weeks. Metabolomic profile of muscle and cerebral cortex was analysed at week 20, and plasma samples were assessed at four time points over 20 weeks. The relevant metabolic pathways highlighted by metabolomic analysis were explored by a targeted transcriptomic approach in mice. Plasma metabolomics were also performed in 24 ALS patients and 24 gender- and age-matched controls. Metabolomic analysis of muscle and cerebral cortex enabled an excellent discrimination between mSOD1 and WT mice (p < 0.001). These alterations included especially tryptophan, arginine, and proline metabolism pathways (including polyamines) as also revealed by transcriptomic analysis and findings in ALS patients. Multivariate models performed to explain clinical findings in ALS mice, and patients were excellent (p < 0.01) and highlighted three main metabolic pathways: arginine and proline, tryptophan, and branched amino acid metabolism. This work is the first longitudinal study that evaluates metabolism alteration in ALS, including the analysis of different tissues and using a combination of omics methods. We particularly identified arginine and proline metabolism. This pathway is also associated with disease progression and may open new perspectives of therapeutic targets.

Changes in protein concentrations within human blood are used as an indicator for nutritional state, hydration and underlying illnesses. They are often measured at regular clinical appointments and the current analytical process can result in long waiting times for results and the need for return patient visits. Attenuated total reflectance -Fourier transform infrared (ATR-FTIR) spectroscopy has the ability to detect minor molecular differences, qualitatively and quantitatively, in biofluid samples, without extensive sample preparation. ATR-FTIR can return an analytical measurement almost instantaneously and therefore could be deemed as an ideal technique for monitoring molecular alterations in blood within the clinic.To determine the suitability of using ATR-FTIR spectroscopy to enable protein quantification in a clinical setting, pooled human serum samples spiked with varying concentrations of human serum albumin (HSA) and immunoglobulin G (IgG) were analysed, before analysing patient clinical samples. Using a validated partial least squares method, the spiked samples (IgG) produced a linearity as high as 0.998 and a RMSEV of 0.49 ± 0.05 mg mL -1 , with the patient samples producing R 2 values of 0.992 and a corresponding RMSEV of 0.66 ± 0.05 mg mL -1 . This claim was validated using two blind testing models, leave one patient out cross validation and k-fold cross validation, achieving optimum linearity and RMSEV values of 0.934 and 1.99 ± 0.79 mg mL -1 , respectively. This demonstrates that ATR-FTIR is able to quantify protein within clinically relevant complex matrices and concentrations, such as serum samples, rapidly and with simple sample preparation. The ability to provide a quantification step, along with rapid disease classification, from a spectroscopic signature will aid clinical translation of vibrational spectroscopy to assist with problems currently faced with patient diagnostic pathways.

Metabolism is involved in both pharmacology and toxicology of most xenobiotics including drugs. Yet, visualization tools facilitating metabolism exploration are still underused, despite the availibility of pertinent bioinformatics solutions. Since molecular networking appears as a suitable tool to explore structurally related molecules, we aimed to investigate its interest in in vitro metabolism exploration. Quetiapine, a widely prescribed antipsychotic drug, undergoes well-described extensive metabolism, and is therefore an ideal candidate for such a proof of concept. Quetiapine was incubated in metabolically competent human liver cell models (HepaRG) for different times (0 h, 3 h, 8 h, 24 h) with or without cytochrom P450 (CYP) inhibitor (ketoconazole as CYP3A4/5 inhibitor and quinidine as CYP2D6 inhibitor), in order to study its metabolism kinetic and pathways. HepaRG culture supernatants were analyzed on an ultra-high performance liquid chromatography coupled with tandem mass spectrometry (LC-HRMS/MS). Molecular networking approach on LC-HRMS/MS data allowed to quickly visualize the quetiapine metabolism kinetics and determine the major metabolic pathways (CYP3A4/5 and/or CYP2D6) involved in metabolite formation. In addition, two unknown putative metabolites have been detected. In vitro metabolite findings were confirmed in blood sample from a patient treated with quetiapine. This is the first report using LC-HRMS/MS untargeted screening and molecular networking to explore in vitro drug metabolism. Our data provide new evidences of the interest of molecular networking in drug metabolism exploration and allow our in vitro model consistency assessment.

In amyotrophic lateral sclerosis (ALS), motor neuron degeneration occurs simultaneously with systemic metabolic impairment and neuroinflammation. Playing an important role in the regulation of both phenomena, interleukin (IL)-6, a major cytokine of the inflammatory response has been proposed as a target for management of ALS. Although a pilot clinical trial provided promising results in humans, another recent preclinical study showed that knocking out the IL-6 gene in mice carrying ALS did not improve clinical outcome. In this study, we aimed to determine the relevance of the IL-6 pathway blockade in a mouse model of ALS by using a pharmacological antagonist of IL-6, a murine surrogate of tocilizumab, namely MR16-1. We analyzed the immunological and metabolic effects of IL-6 blockade by cytokine measurement, blood cell immunophenotyping, targeted metabolomics, and transcriptomics. A deleterious clinical effect of MR16-1 was revealed, with a speeding up of weight loss (p = 0.0041) and decreasing body weight (p < 0.05). A significant increase in regulatory T-cell count (p = 0.0268) and a decrease in C-X-C ligand-1 concentrations in plasma (p = 0.0479) were observed. Metabolomic and transcriptomic analyses revealed that MR16-1 mainly affected branchedchain amino acid, lipid, arginine, and proline metabolism. IL-6 blockade negatively affected body weight, despite a moderated anti-inflammatory effect. Metabolic effects of IL-6 were mild compared with metabolic disturbances observed in ALS, but a modification of lipid metabolism by

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