Metabolic crosstalk between skeletal muscle cells and liver through IRF4-FSTL1 in nonalcoholic steatohepatitis

Inter-organ crosstalk has gained more and more attention recently. However, the mechanisms under this remain incompletely understood. Here, we revealed an endocrine pathway regulated by skeletal muscle IRF4 that manipulates liver pathology. We studied that skeletal muscle specifically deleted IRF4 (F4MKO) mice showed ameliorated liver steatosis, inflammation and fibrosis, without changes in body weight on NASH diet. Proteomics analysis of serum suggested that follistatin-like protein 1 (FSTL1), as a myokine, might linked the communication between skeletal muscle and liver. Dual luciferase assays showed that IRF4 can transcriptionally regulated FSTL1 and reconstitution of FSTL1 expression in skeletal muscle of F4MKO mice, using adeno-associated virus, was sufficient to restore the liver pathology. Furthermore, we performed co-culture experiments to verify different receptors contribute to FSTL1's function in different cell types of liver. Finally, we found serum FSTL1 level was positively correlated with NASH progression in human, whereas the mRNA level of Fstl1 and its receptors were downregulated in liver biopsy from NASH patients. These data reveal a signaling pathway from skeletal muscle to liver via IRF4-FSTL1-receptors in the pathogenesis of NASH and implicate useful targets for the management of NASH. Overall design: Three liver tissue samples of each group for RNA sequencing were collected. Total RNA was isolated using the Trizol method according to manufacturer's instructions. RNA quality was measured using the Agilent 2100 Bioanalyzer (RNA 6000 Nano Kit; Agilent Technologies, Santa Clara, CA, USA). cDNA libraries for each sample were constructed as reported previously Libraries were sequenced on BGIseq500 platform (BGI-Shenzhen, China), using 150 bp paired-end reads aimed at 30 million reads per sample.The raw sequencing data was filtered with trim-galore (v0.6.7) by removing reads containing sequencing adapter and reads with low-quality base. The clean reads were mapped to the reference genome (mm10) using Hisat2 (2.2.1). Quantification of gene expression was calculated using FeatureCounts (v2.0.1), converted to transcripts per million (TPM) using the R software. We conducted a differential gene expression analysis comparing F4MKO versus control and overexpression of FSTL1 in F4MKO (F4MKO+FSTL1) versus F4MKO. Subsequently, differential expression analysis between groups was conducted using the DESeq2(1.3.40) with adjust P value < 0.05 and |FC|>1.5. We used the obtained log2FC to perform a gene-set enrichment analysis to detect pathways and biological processes enriched with profiling genes.