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Olanzapine (OLA), a widely used second-generation antipsychotic (SGA), causes weight gain and metabolic alterations when administered orally to patients. Recently, we demonstrated that, contrarily to the oral treatment which induces weight gain, OLA administered via intraperitoneal (i.p.) in male mice resulted in body weight loss. This protection was due to an increase in energy expenditure (EE) through a mechanism involving the modulation of hypothalamic AMPK activation by higher OLA levels reaching this brain region compared to those of the oral treatment. Since clinical studies have shown hepatic steatosis upon chronic treatment with OLA, herein we further investigated the role of the hypothalamus-liver interactome upon OLA administration in wild-type (WT) and protein tyrosine phosphatase 1B knockout (PTP1B–KO) mice, a preclinical model protected against metabolic syndrome. WT and PTP1B–KO male mice were fed an OLA-supplemented diet or treated via i.p. Mechanistically, we found that OLA i.p. treatment induces mild oxidative stress and inflammation in the hypothalamus in a JNK1-independent and dependent manner, respectively, without features of cell dead. Hypothalamic JNK activation up-regulated lipogenic gene expression in the liver though the vagus nerve. This effect concurred with an unexpected metabolic rewiring in the liver in which ATP depletion resulted in increased AMPK/ACC phosphorylation. This starvation-like signature prevented steatosis. By contrast, intrahepatic lipid accumulation was observed in WT mice treated orally with OLA; this effect being absent in PTP1B–KO mice. We also demonstrated an additional benefit of PTP1B inhibition against hypothalamic JNK activation, oxidative stress and inflammation induced by chronic OLA i.p. treatment, thereby preventing hepatic lipogenesis. The protection conferred by PTP1B deficiency against hepatic steatosis in the oral OLA treatment or against oxidative stress and neuroinflammation in the i.p. treatment stron

Minimally invasive prognostic markers of inflammation and dyslipidemia in individuals with a risk of psychosis, also called “at-risk mental state” (ARMS), or in the first episode of psychosis (FEP) are of utmost clinical importance to prevent cardiovascular disorders. We analyzed the plasma concentration of inflammation-linked glycoproteins (Glycs) and lipoprotein subclasses by proton nuclear magnetic resonance (1H NMR) in a single acquisition. Study participants were healthy controls (HCs, N = 67) and patients with ARMS (N = 58), FEP (N = 110), or early psychosis diagnosis with ≥2 episodes (critical period (CP), N = 53). Clinical biomarkers such as high-sensitivity C-reactive protein, interleukin 6, fibrinogen, insulin, and lipoproteins were also measured. Although all participants had normal lipoprotein profiles and no inflammation according to conventional biomarkers, a gradual increase in the Glyc 1H NMR levels was observed from HCs to CP patients; this increase was statistically significant for GlycA (CP vs HC). In parallel, a progressive and significant proatherogenic 1H NMR lipoprotein profile was also identified across stages of psychosis (ARMS and CP vs HC). These findings highlight the potential of using 1H NMR Glyc and lipoprotein profiling to identify blood changes in individuals with ARMS or FEP and pave the way for applications using this technology to monitor metabolic and cardiovascular risks in clinical psychiatry.

Cocoa constitutes one of the richest sources of dietary flavonoids with demonstrated anti-diabetic potential. However, the metabolic impact of cocoa intake in a diabetic context remains unexplored. In this study, metabolomics tools have been used to investigate the potential metabolic changes induced by cocoa in type 2 diabetes (T2D). To this end, male Zucker diabetic fatty rats were fed on standard (ZDF) or 10% cocoa-rich diet (ZDF-C) from week 10 to 20 of life. Cocoa supplementation clearly decreased serum glucose levels, improved glucose metabolism and produced significant changes in the urine metabolome of ZDF animals. Fourteen differential urinary metabolites were identified, with eight of them significantly modified by cocoa. An analysis of pathways revealed that butanoate metabolism and the synthesis and degradation of branched-chain amino acids and ketone bodies are involved in the beneficial impact of cocoa on diabetes. Moreover, correlation analysis indicated major associations between some of these urine metabolites (mainly valine, leucine, and isoleucine) and body weight, glycemia, insulin sensitivity, and glycated hemoglobin levels. Overall, this untargeted metabolomics approach provides a clear metabolic fingerprint associated to chronic cocoa intake that can be used as a marker for the improvement of glucose homeostasis in a diabetic context.

Mass spectrometry imaging (MSI) has become a widespread analytical technique to perform nonlabeled spatial molecular identification. The Achilles' heel of MSI is the annotation and identification of molecular species due to intrinsic limitations of the technique (lack of chromatographic separation and the difficulty to apply tandem MS). Successful strategies to perform annotation and identification combine extra analytical steps, like using orthogonal analytical techniques to identify compounds; with algorithms that integrate the spectral and spatial information. In this review, we discuss different experimental strategies and bioinformatics tools to annotate and identify compounds in MSI experiments. We target strategies and tools for small molecule applications, such as lipidomics and metabolomics. First, we explain how sample preparation and the acquisition process influences annotation and identification, from sample preservation to the use of orthogonal techniques. Then, we review twelve software tools for annotation and identification in MSI. Finally, we offer perspectives on two current needs of the MSI community: the adaptation of guidelines for communicating confidence levels in identifications; and the creation of a standard format to store and exchange annotations and identifications in MSI.

Cocoa constitutes one of the richest sources of dietary flavonoids with demonstrated anti-diabetic potential. However, the metabolic impact of cocoa intake in a diabetic context remains unexplored. In this study, metabolomics tools have been used to investigate the potential metabolic changes induced by cocoa in type 2 diabetes (T2D). To this end, male Zucker diabetic fatty rats were fed on standard (ZDF) or 10% cocoa-rich diet (ZDF-C) from week 10 to 20 of life. Cocoa supplementation clearly decreased serum glucose levels, improved glucose metabolism and produced significant changes in the urine metabolome of ZDF animals. Fourteen differential urinary metabolites were identified, with eight of them significantly modified by cocoa. An analysis of pathways revealed that butanoate metabolism and the synthesis and degradation of branched-chain amino acids and ketone bodies are involved in the beneficial impact of cocoa on diabetes. Moreover, correlation analysis indicated major associations between some of these urine metabolites (mainly valine, leucine, and isoleucine) and body weight, glycemia, insulin sensitivity, and glycated hemoglobin levels. Overall, this untargeted metabolomics approach provides a clear metabolic fingerprint associated to chronic cocoa intake that can be used as a marker for the improvement of glucose homeostasis in a diabetic context.