Stellate cell expression of SPARC-related modular calcium-binding protein 2 is associated with human non-alcoholic fatty liver disease severity

Abstract

Background & aims: Histological assessment of liver biopsies is the gold standard for diagnosis of non-alcoholic steatohepatitis (NASH), the progressive form of non-alcoholic fatty liver disease (NAFLD), despite its well-established limitations. Therefore, non-invasive biomarkers that can offer an integrated view of the liver are needed to improve diagnosis and reduce sampling bias. Hepatic stellate cells (HSCs) are central in the development of hepatic fibrosis, a hallmark of NASH. Secreted HSC-specific proteins may, therefore, reflect disease state in the NASH liver and serve as non-invasive diagnostic biomarkers.

Methods: We performed RNA-sequencing on liver biopsies from a histologically characterised cohort of obese patients (n = 30, BMI >35 kg/m²) to identify and evaluate HSC-specific genes encoding secreted proteins. Bioinformatics was used to identify potential biomarkers and their expression at single-cell resolution. We validated our findings using single-molecule fluorescence in situ hybridisation (smFISH) and ELISA to detect mRNA in liver tissue and protein levels in plasma, respectively.

Results: Hepatic expression of SPARC-related modular calcium-binding protein 2 (SMOC2) was increased in NASH compared to no-NAFLD (p.adj <0.001). Single-cell RNA-sequencing data indicated that SMOC2 was primarily expressed by HSCs, which was validated using smFISH. Finally, plasma SMOC2 was elevated in NASH compared to no-NAFLD (p <0.001), with a predictive accuracy of AUROC 0.88.

Conclusions: Increased SMOC2 in plasma appears to reflect HSC activation, a key cellular event associated with NASH progression, and may serve as a non-invasive biomarker of NASH.

Impact and implications: Non-alcoholic fatty liver disease (NAFLD) and its progressive form, non-alcoholic steatohepatitis (NASH), are the most common forms of chronic liver diseases. Currently, liver biopsies are the gold standard for diagnosing NAFLD. Blood-based biomarkers to complement liver biopsies for diagnosis of NAFLD are required. We found that activated hepatic stellate cells, a cell type central to NAFLD pathogenesis, upregulate expression of the secreted protein SPARC-related modular calcium-binding protein 2 (SMOC2). SMOC2 was elevated in blood samples from patients with NASH and may hold promise as a blood-based biomarker for the diagnosis of NAFLD.

Keywords: AUROC, area under the receiver operating characteristic curve; ECM, extracellular matrix; HSC, hepatic stellate cells; LSM, liver stiffness measurement; MCP, matricellular protein; NAFL, non-alcoholic fatty liver; NAFLD; NAFLD, non-alcoholic fatty liver disease; NAS, NAFLD activity score; NASH; PCA, principal component analysis; SAF, steatosis, activity, and fibrosis; SE, sensitivity; SMOC2; SMOC2, SPARC-related modular calcium-binding protein 2; SP, specificity; SPARC, secreted protein acidic and cysteine-rich; VSMCs, vascular smooth muscle cells; WGCNA, weighted gene co-expression network analysis; aHSC, activated HSC; hepatic stellate cells; non-invasive biomarker; qHSC, quiescent HSC; smFISH, single-molecule fluorescence in situ hybridisation; transcriptomics.

Graphical abstract

Fig. 1

Hepatic transcriptome profiling and identification of fibrogenesis-related NASH signature transcripts. (A) Pearson correlation (r) between WGCNA identified module eigengenes and biometric, blood chemistry, and histopathologic grades. Size of dos are proportional to the Pearson correlation coefficient. (B) Enriched (p.adj. <0.05) and representative (p.adj. ≥0.05) GO-slim categories for each module. (C) Pearson correlation between NAS and hepatic expression of transcripts in Module XII in the 30 patients. Transcripts showing high correlation (n = 116, r ≥0.6, -log₁₀(p.adj.) ≤4) are shown in red. (D) Venn diagram showing overlap of transcripts highly correlating with NAS and the human secretome obtained from SignalP. (E) Hierarchical clustering of Z-scores of transcripts highly correlating with NAS and overlapping with the human secretome (n = 41). Transcripts found in the human secretome from SignalP are shown on left and NAFLD status of patients (n = 30) is shown as colors on top. (F) Expression of Module XII top 6 transcripts correlating with NAS and overlapping with the human secretome. Hepatic expression of Module XII top 6 transcripts is visualised as boxplots with dots representing biological replicates. Mann-Whitney U test was employed to test difference in distribution between groups with Holm-corrected p values. Significance levels are ∗p <0.05, ∗∗p <0.01, ∗∗∗p <0.001, and ∗∗∗∗ p ≤0.0001. GO, gene ontology; NAFLD, non-alcoholic fatty liver disease; NAS, NAFLD activity score; WGCNA, weighted gene co-expression network analysis.

Fig. 2

Identification of cell type-specific gene expression of Module XII secreted proteins. (A) UMAP of human scRNA-seq integrated datasets GSE136103, GSE158723, and GSE115469 (n = 75,632 cells). (B) Estimated abundance of cell types (n = 7, estimated abundance >0.01) from the patient cohort RNA-seq data (n = 30). Estimated abundance is normalised to total estimated abundance for each cell type. Results are represented as stacked barplots and show mean estimated abundance for no-NAFLD, NAFL, and NASH patients. (C) Estimated cell type abundance of aHSCs and Kupffer cells shown as proportions of all estimated cell types. Mann-Whitney U test was employed to test difference in distribution between groups with Holm-corrected p values. (D) Cell type-resolved expression of Module XII genes encoding secreted proteins (log₂FC > 2, expression >5%) shown by dotplot. (E) UMAP showing Leiden clustering of qHSCs, aHSCs, and VSMCs (n = 1,767 cells). Right panel shows the UMAP representation of the human scRNA-seq datasets and treatment groups within each dataset. (F) UMAP showing normalised log₂-expression of SMOC2 in qHSCs, aHSCs, and VSMCs. (G) Normalised log₂-expression of SMOC2 in the major hepatic cell types represented as violin plots. UMAP, uniform manifold approximation and projection; NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; HSCs, hepatic stellate cells; VSMCs, vascular smooth muscle cells.

Fig. 3

Single-cell resolution of SMOC2, RGS5, and LUM transcripts show SMOC2 expression by HSCs in human liver. Confocal images of human liver needle biopsies from severely obese patients histologically graded as NASH (n = 2-3) showing SMOC2 (orange) co-localised with RGS5 (magenta) and/or LUM (green) (A) and co-localised with FBLN2 and/or LUM (B). Scale bars; middle panels = 50 μm and lower panels = 10 μm. (C) Fraction of total cells/image being SMOC2⁺, SMOC2⁺RGS5⁺, SMOC2⁺LUM⁺, and SMOC2⁺RGS5⁺LUM⁺. (D) Fraction of total cells/image being SMOC2⁺, SMOC2⁺FBLN2⁺, SMOC2⁺LUM⁺, and SMOC2⁺LUM⁺FBLN2⁺. (E) Quantification of SMOC2 transcripts in SMOC2⁺, SMOC2⁺RGS5⁺, SMOC2⁺LUM⁺, and SMOC2⁺RGS5⁺LUM⁺ cells. (F) Quantification of SMOC2 transcripts in SMOC2⁺, SMOC2⁺FBLN2⁺, SMOC2⁺LUM⁺, and SMOC2⁺LUM⁺FBLN2⁺ cells. QuPath was employed to detect and quantify single-, double-, and triple-positive stained cells. Cells with ≥2 SMOC2 transcripts/cell were considered SMOC2-positive cells. Fractions of positive cells are shown as mean + SE (n = 6-12 images/biological replicate) and SMOC2 transcripts/cell are shown as boxplots (n = 6-12 images/biological replicate). Mann-Whitney U test with Holm-correction was employed to test difference between cell fractions. Poisson regression with robust standard errors and p value calculation was employed to test difference between estimated transcripts/cell. Significance levels are ∗p <0.05, ∗∗p <0.01, ∗∗∗p <0.001, and ∗∗∗∗ p ≤0.0001. HSCs, hepatic stellate cells; NASH, non-alcoholic steatohepatitis.

Fig. 4

Predictive modelling of histological grades by hepatic expression of SMOC2. (A-C) Association of SMOC2 expression with NAFLD progression in our patient cohort RNA-seq data (n = 30). (D-F) Association of SMOC2 expression and previously proposed biomarkers of NAFLD (TREM2, AKR1B10, MFAP4, and GDF15) with NAFLD progression in previously described RNA-seq data from a NAFLD multi-centre cohort (GSE135251, n = 206). Patients with NAFLD were categorised by (A and D) severe NAFLD (NAS ≥4), (B and E) fibrosis (Kleiner fibrosis grade ≥2), and (C and F) NASH (SAF >2). Performance of SMOC2 expression was evaluated using AUROC analysis. Sensitivity and specificity were determined from optimal cut-off points using the Youden index. SMOC2 expression in our patient cohort segmented into groups are visualised as boxplots with dots representing biological replicates. (G) Expression of SMOC2, TREM2, AKR1B10, MFAP4, and GDF15 in the multi-centre NAFLD cohort are visualised as mean differences between segmented groups with dots representing the mean difference and whiskers representing 95% CIs. Significance levels are ∗∗p <0.01 and ∗∗∗p <0.001 (Mann-Whitney U test). NAFLD, non-alcoholic fatty liver disease; NAS, NAFLD activity score; NASH, non-alcoholic steatohepatitis; SAF, steatosis, activity fibrosis; AUROC, area under the receiver operating characteristic curve; CIs, confidence intervals.

Fig. 5

Predictive modelling of histological grades by plasma SMOC2. (A) Plasma SMOC2 levels in patients with severe NAFLD (NAS ≥4, n = 19) and mild NAFLD (NAS <4, n = 16) (left panel) and predictive accuracy of severe NAFLD (right panel). (B) Plasma SMOC2 levels in patients with fibrosis (Kleiner fibrosis ≥2, n = 12) and mild fibrosis (Kleiner fibrosis <2, n = 23) (left panel) and predictive accuracy of fibrosis (right panel). (C) Plasma SMOC2 levels in patients with NASH (SAF > 2, n = 20) and no-NASH (SAF <2, n = 15) (left panel) and predictive accuracy of NASH (right panel). Plasma SMOC2 performance was evaluated using AUROCs. Sensitivity and specificity were determined from optimal cut-off points using the Youden index. Significance levels are ∗∗p <0.01 and ∗∗∗∗ p ≤0.0001 (Mann-Whitney U test). NAFLD, non-alcoholic fatty liver disease; NAS, NAFLD activity score; NASH, non-alcoholic steatohepatitis; SAF, steatosis, activity fibrosis; AUROC, area under the receiver operating characteristic curve.