Metabolic-Immune Crosstalk in Myocardial Infarction: RLF and SMCHD1 Identified as Causal Therapeutic Targets via Integrated Lactylation-MR Analysis

Juli Tang^1*Yunzeng Zou^2,3,4Xiaoxue Zhang²Wenhao Zhong²Jie Yuan^2*Lingyan Yuan^5*

• ¹Shanghai Normal University College of Life Sciences, Shanghai, China
• ²Zhongshan Hospital Fudan University, Shanghai, China
• ³Shanghai Municipal Institute for Cardiovascular Diseases, Shanghai, China
• ⁴Fudan University Institutes of Biomedical Sciences, Shanghai, China
• ⁵Shanghai Normal University, Shanghai, China

Background: The diagnosis of Myocardial Infarction (MI) requires the discovery of specific diagnostic biomarkers beyond high-sensitivity cardiac troponins. To identify causal MI-associated genes regulated by lactylation modification and elucidate their roles in metabolic-immune dysregulation. Methods: This multi-omics study combined bioinformatic analyses of human MI datasets (GSE60993/GSE61144/GSE66360) with experimental validation to investigate lactylation-related genes (LRGs). Differential expression analysis (limma, P<0.05, |log₂FC|>0.585) identified 571 Differentially Expressed Genes (DEGs), which intersected with 2,051 curated lactylation-related genes (LRGs) (PubMed/GeneCards) yielding 56 lactylation-associated DEGs. Mendelian randomization (MR) utilized genetic instruments (P<5×10⁻⁶) from Gene eQTL and three MI-GWAS cohorts (43,676 cases/128,199 controls), employing inverse-variance weighted (IVW) regression with sensitivity analyses (MR-Egger/weighted median). Functional enrichment (clusterProfiler) of the 56 DEGs examined GO/KEGG terms (FDR P<0.05), supplemented by Gene Set Variation Analysis (GSVA) of Rearranged L-myc fusion (RLF) and Structural Maintenance of Chromosomes Hinge Domain Containing 1 (SMCHD1) expression strata and CIBERSORT-based immune infiltration assessment. Experimental validation involved LAD ligation-induced MI modeling in C57BL/6 mice, with RLF/SMCHD1 expression quantified via qPCR and Western blot. Results: Integrated transcriptomic analysis of three GEO datasets (73 MI patients, 67 controls) identified 571 DEGs. Cross-referencing these DEGs with 2,051 LRGs yielded 56 Lactylationassociated DEGs. MR analysis using 42,699 instrumental SNPs established RLF (AUC=0.823) and SMCHD1 (AUC=0.809) as causal risk genes that were significantly elevated in MI patients. Functional enrichment implicated both genes in metabolic dysregulation (nucleotide metabolism, HIF-1/MAPK signaling) and necroptosis. Immune profiling revealed increased monocytes, neutrophils, and activated CD4+ T cells within MI tissues, all positively correlated with RLF and SMCHD1 expression. Conversely, reduced CD8+ T cell infiltration correlated negatively with RLF expression. Independent validation confirmed significant RLF upregulation in MI. Quantitative analyses revealed significant increases in RLF and SMCHD1 expression-at both transcriptional (mRNA) and translational (protein) levels-in MI-induced mice relative to sham controls.This study pioneers the integration of lactylation modification with MR analysis for MI, establishing RLF and SMCHD1 as causal diagnostic biomarkers. Their dual roles in promoting metabolic dysregulation and pro-inflammatory immune infiltration position them as promising therapeutic targets for MI intervention.