Suppression of insulin-induced gene 1 (INSIG1) function promotes hepatic lipid remodelling and restrains NASH progression

Abstract

Objective Non-alcoholic fatty liver disease (NAFLD) is a silent pandemic associated with obesity and the metabolic syndrome, and also increases cardiovascular- and cirrhosis-related morbidity and mortality. A complete understanding of adaptive compensatory metabolic programmes that modulate non-alcoholic steatohepatitis (NASH) progression is lacking. Methods and results Transcriptomic analysis of liver biopsies in patients with NASH revealed that NASH progression is associated with rewiring of metabolic pathways, including upregulation of de novo lipid/cholesterol synthesis and fatty acid remodelling. The modulation of these metabolic programmes was achieved by activating sterol regulatory element-binding protein (SREBP) transcriptional networks; however, it is still debated whether, in the context of NASH, activation of SREBPs acts as a pathogenic driver of lipotoxicity, or rather promotes the biosynthesis of protective lipids that buffer excessive lipid accumulation, preventing inflammation and fibrosis. To elucidate the pathophysiological role of SCAP/SREBP in NASH and wound-healing response, we used an Insig1 deficient (with hyper-efficient SREBPs) murine model challenged with a NASH-inducing diet. Despite enhanced lipid and cholesterol biosynthesis, Insig1 KO mice had similar systemic metabolism and insulin sensitivity to Het/WT littermates. Moreover, activating SREBPs resulted in remodelling the lipidome, decreased hepatocellular damage, and improved wound-healing responses. Conclusions Our study provides actionable knowledge about the pathways and mechanisms involved in NAFLD pathogenesis, which may prove useful for developing new therapeutic strategies. Our results also suggest that the SCAP/SREBP/INSIG1 trio governs transcriptional programmes aimed at protecting the liver from lipotoxic insults in NASH.

A network-based approach reveals the dysregulated transcriptional regulation in non-alcoholic fatty liver disease

“…To validate whether modules related to significant transcriptomics and metabolic changes in patients with NAFLD can truly reflect the perturbations in a disease-specific manner, we analyzed GCNs generated using liver-biopsy transcriptomics data sets from two independent NAFLD cohorts with 75 and 58 samples, respectively ( Azzu et al., 2021 ; Hoang et al., 2019 ). To avoid repeated IDs, we assigned cohort 1 to the studied NAFLD cohort, and 2 and 3 for NAFLD cohorts for validation in the downstream analysis.…”

“…For instance, INSIG , a key player in the insulin signaling pathway is included in the disease-associated modules among all three cohorts. A recent study has reported that INSIG is a central regulator in a negative feedback loop ensuring the balance of lipid desaturation and cholesterol composition and loss of INSIG1 improves liver damage and would healing NASH progression ( Azzu et al., 2021 ). In addition, GCK , which is a kinase specific to glucose, is involved in the module of cohort 2, and it is significantly upregulated in the NAFLD patients compared with the normal subjects ( Data S2 ).…”

“…NAFLD cohorts. hepatic RNA-seq (raw fastq files) of NAFLD cohort 1 ( Govaere et al., 2020 ) and cohort 2 ( Hoang et al., 2019 ) were retrieved from European Nucleotide Archive (ENA) database ( https://www.ebi.ac.uk/ena/ ) ( Amid et al., 2020 ) under accession numbers SRP217231 (215 biopsy-proven NAFLD patients) and SRP197353 (78 biopsy-proven NAFLD patients), respectively; Hepatic RNA-seq of NAFLD cohort 3 ( Azzu et al., 2021 ) with 58 biopsy-proven NAFLD patients were retrieved from the ArrayExpress data repository ( Parkinson et al., 2005 ) under accession number E-MTAB-9815 . Principle component analysis (PCA) was used to detect outlier samples ( Figure S1 ) and three outlier samples in NAFLD cohort 2 were removed based on this analysis.…”

“…Moreover, the heterogeneity of clinical manifestations among NAFLD patients acts as an essential impediment for the discovery of critical pathogenic drivers, requiring in-depth systematic analysis consequently ( Alonso et al., 2017 ). Recently, several liver-biopsy proved transcriptomics data from large patients’ cohorts had been conducted ( Azzu et al., 2021 ; Govaere et al., 2020 ; Hoang et al., 2019 ), and these datasets may be used to provide significant functional insights based on network analysis that cannot be derived from individual gene-level analysis.…”

SREBP1-induced fatty acid synthesis depletes macrophages antioxidant defences to promote their alternative activation

“…Sections were dried overnight at 37°C, dewaxed with xylene and 100% ethanol, and washed in running water for a minimum of 4 minutes. The sections were stained with standard haematoxylin and eosin (H&E) as previously described 62 .…”