👤 Geneviève Tavernier

Patients with non-infectious systemic inflammation may suffer from one of many diseases, including hyperinflammation (HI), autoinflammatory disorders (AID), and systemic autoimmune disease (AI). Despite their clinical overlap, the pathophysiology and patient management differ between these disorders. We aimed to investigate blood biomarkers able to discriminate between patient groups. We included 44 patients with active clinical and/or genetic systemic inflammatory disease (9 HI, 27 AID, 8 systemic AI) and 16 healthy controls. We quantified 55 serum proteins and combined multiple machine learning algorithms to identify five proteins (CCL26, CXCL10, ICAM-1, IL-27, and SAA) that maximally separated patient groups. High ICAM-1 was associated with HI. AID was characterized by an increase in SAA and decrease in CXCL10 levels. A trend for higher CXCL10 and statistically lower SAA was observed in patients with systemic AI. Principal component analysis and unsupervised hierarchical clustering confirmed separation of disease groups. Logistic regression modelling revealed a high statistical significance for HI (P = 0.001), AID, and systemic AI (P < 0.0001). Predictive accuracy was excellent for systemic AI (AUC 0.94) and AID (0.91) and good for HI (0.81). Further research is needed to validate findings in a larger prospective cohort. Results will contribute to a better understanding of the pathophysiology of systemic inflammatory disorders and can improve diagnosis and patient management. Show less

Impaired glucose metabolism is observed in obesity and type 2 diabetes. Glucose controls gene expression through the transcription factor ChREBP in liver and adipose tissues. Mlxipl encodes 2 isoforms: ChREBPα, the full-length form (translocation into the nucleus is under the control of glucose), and ChREBPβ, a constitutively nuclear shorter form. ChREBPβ gene expression in white adipose tissue is strongly associated with insulin sensitivity. Here, we investigated the consequences of ChREBPβ deficiency on insulin action and energy balance. ChREBPβ-deficient male and female C57BL6/J and FVB/N mice were produced using CRISPR/Cas9-mediated gene editing. Unlike global ChREBP deficiency, lack of ChREBPβ showed modest effects on gene expression in adipose tissues and the liver, with variations chiefly observed in brown adipose tissue. In mice fed chow and 2 types of high-fat diets, lack of ChREBPβ had moderate effects on body composition and insulin sensitivity. At thermoneutrality, ChREBPβ deficiency did not prevent the whitening of brown adipose tissue previously reported in total ChREBP-KO mice. These findings revealed that ChREBPβ is dispensable for metabolic adaptations to nutritional and thermic challenges. Show less

Impaired adipose tissue insulin signalling is a critical feature of insulin resistance. Here we identify a pathway linking the lipolytic enzyme hormone-sensitive lipase (HSL) to insulin action via the glucose-responsive transcription factor ChREBP and its target, the fatty acid elongase ELOVL6. Genetic inhibition of HSL in human adipocytes and mouse adipose tissue results in enhanced insulin sensitivity and induction of ELOVL6. ELOVL6 promotes an increase in phospholipid oleic acid, which modifies plasma membrane fluidity and enhances insulin signalling. HSL deficiency-mediated effects are suppressed by gene silencing of ChREBP and ELOVL6. Mechanistically, physical interaction between HSL, independent of lipase activity, and the isoform activated by glucose metabolism ChREBPα impairs ChREBPα translocation into the nucleus and induction of ChREBPβ, the isoform with high transcriptional activity that is strongly associated with whole-body insulin sensitivity. Targeting the HSL-ChREBP interaction may allow therapeutic strategies for the restoration of insulin sensitivity. Show less