Computational biology and chemistry · 2026
Multi-omics and machine learning uncover the MX1-ISG15-STAT1 synergistic axis as the core interferon signature in systemic lupus erythematosus and identify herbal-derived multi-target therapeutic candidates.
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Cao Junjie, Chen Yanru, Huang Rong, Ma Lin
Аннотация
OBJECTIVE: To address unmet therapeutic needs and safety limitations of current systemic lupus erythematosus (SLE) treatments, this study aimed (i) to delineate the core interferon (IFN)-centric regulatory network and its key mechanisms in SLE and (ii) to identify and evaluate herbal-derived multi-target therapeutic candidates for SLE.
METHODS: Five GEO datasets were integrated into training and testing cohorts, subjected to a comprehensive pipeline including differential expression analysis, WGCNA, 113 machine learning model combinations (random forest optimal), Mendelian Randomization (MR), co-expression analysis, and molecular docking. SLE-related targets were predicted via multiple databases, with functional enrichment and molecular dynamics simulations performed.
RESULTS: Six core genes (IFI27, ISG15, MX1, TAP1, USP18, STAT1) were identified; MX1 and ISG15 synergistically upregulated STAT1 (interaction P = 0.003), with their concurrent high expression correlating with elevated SLEDAI scores. MR analysis provided supportive evidence for a potential causal association between MX1 and SLE (OR=1.70, 95% CI:1.16-2.50, P = 0.006). while naringenin, taxifolin, and deoxycholic acid showed excellent binding affinity to core targets (binding energy < -5 kcal/mol).
CONCLUSION: The MX1-ISG15-STAT1 axis is the core of SLE's IFN-centric network. Identified herbal-derived multi-target candidates provide novel insights for mechanism-based SLE therapeutics.
METHODS: Five GEO datasets were integrated into training and testing cohorts, subjected to a comprehensive pipeline including differential expression analysis, WGCNA, 113 machine learning model combinations (random forest optimal), Mendelian Randomization (MR), co-expression analysis, and molecular docking. SLE-related targets were predicted via multiple databases, with functional enrichment and molecular dynamics simulations performed.
RESULTS: Six core genes (IFI27, ISG15, MX1, TAP1, USP18, STAT1) were identified; MX1 and ISG15 synergistically upregulated STAT1 (interaction P = 0.003), with their concurrent high expression correlating with elevated SLEDAI scores. MR analysis provided supportive evidence for a potential causal association between MX1 and SLE (OR=1.70, 95% CI:1.16-2.50, P = 0.006). while naringenin, taxifolin, and deoxycholic acid showed excellent binding affinity to core targets (binding energy < -5 kcal/mol).
CONCLUSION: The MX1-ISG15-STAT1 axis is the core of SLE's IFN-centric network. Identified herbal-derived multi-target candidates provide novel insights for mechanism-based SLE therapeutics.