A gene-based clustering approach reveals QSOX1/IL1RAP as promising biomarkers for the severity of non-alcoholic fatty liver disease

Abstract

Background and AimsNon-alcoholic fatty liver disease (NAFLD) is a progressive liver disease that ranges from simple steatosis to inflammation, fibrosis, and cirrhosis. To address the unmet need for new NAFLD biomarkers, we aimed to identify candidate biomarkers using publicly available RNA sequencing (RNA-seq) and proteomics data. MethodsAn approach involving unsupervised gene clustering was performed using homogeneously processed and integrated RNA-seq data of 625 liver specimens to screen for NAFLD biomarkers, in combination with public proteomics data from healthy controls and NAFLD patients. Additionally, we validated the results in the NAFLD and healthy cohorts using enzyme-linked immunosorbent assay (ELISA) of plasma and immunohistochemical staining (IHC) of liver samples. ResultsWe generated a database (https://dreamapp.biomed.au.dk/NAFLD/) for exploring gene expression changes along NAFLD progression to facilitate the identification of genes and pathways involved in the diseases progression. Through cross-analysis of the gene and protein clusters, we identified 38 genes as potential biomarkers for NAFLD severity. Up-regulation of Quiescin sulfhydryl oxidase 1 (QSOX1) and down-regulation of Interleukin-1 receptor accessory protein (IL1RAP) were associated with increasing NAFLD severity in RNA-seq and proteomics data. Particularly, the QSOX1/IL1RAP ratio in plasma demonstrated effectiveness in diagnosing NAFLD, with an area under the receiver operating characteristic (AUROC) of up to 0.95 as quantified by proteomics profiling, and an AUROC of 0.82 with ELISA. ConclusionsWe discovered a significant association between the levels of QSOX1 and IL1RAP and NAFLD severity. Furthermore, the QSOX1/IL1RAP ratio shows promise as a non-invasive biomarker for diagnosing NAFLD and assessing its severity. Lay SummaryThis study aimed to find non-invasive biomarkers for non-alcoholic fatty liver disease (NAFLD). Researchers utilized a new gene clustering method to analyze RNA-seq data from 625 liver samples. The identified biomarkers were further validated using plasma proteomics profiling, enzyme-linked immunosorbent assay (ELISA), and liver immunohistochemical staining (IHC) in three separate groups of healthy controls and NAFLD patients. The study revealed that the levels of QSOX1 were elevated while IL1RAP levels were reduced with increasing severity of NAFLD. Importantly, the ratio of QSOX1 to IL1RAP expression in plasma showed promise as a non-invasive diagnostic tool for assessing the severity of NAFLD, eliminating the reliance on liver biopsy. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/23293038v4_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@7941eeorg.highwire.dtl.DTLVardef@d7a8eborg.highwire.dtl.DTLVardef@930ae5org.highwire.dtl.DTLVardef@1b042bb_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIRNA-seq data from 625 liver specimens comprising healthy controls and NAFLD patients with increasing severity were utilized for screening NAFLD biomarkers. C_LIO_LIAn unsupervised method for clustering genes based on the similarity of gene expression trajectory across all samples enhanced the discovery of novel effective non-invasive NAFLD biomarkers. C_LIO_LIQSOX1, IL1RAP, and especially the QSOX1/IL1RAP ratio, were found to be associated with NAFLD severity. C_LIO_LIThe high sensitivity of the QSOX1/IL1RAP ratio in predicting NAFLD severity was validated with plasma proteomics quantification (AUROC = 0.95) and ELISA (AUROC = 0.82) in two independent patient cohorts. C_LI