A multi-dimensional bioinformatic dissection of the molecular mechanisms in high-BMI-associated colorectal cancer: identification and validation of EGLN1 as a key target.

BACKGROUND: Colorectal cancer (CRC) represents a major global health burden, and a high body mass index (BMI) has been established as an independent risk factor. Despite this clear epidemiological association, the complex molecular mechanisms driving CRC progression in the context of high BMI remain to be fully elucidated. This study aimed to systematically investigate the genetic association and potential molecular mechanisms between high BMI and CRC through a multi-dimensional bioinformatic integrative analysis and to identify key therapeutic targets. METHODS: This study integrated global burden of disease data, a two-sample Mendelian randomization (MR) analysis of BMI and CRC, and analyses of differentially expressed genes and weighted gene co-expression network analysis (WGCNA) in CRC. By intersecting gene sets, we identified key genes in BMI-associated CRC (KGs-BACC) and subsequently performed Gene Ontology/Kyoto Encyclopedia of Genes and Genomes enrichment analysis, protein-protein interaction (PPI) network construction, and prognostic survival analysis based on The Cancer Genome Atlas cohort. Causal candidate targets were further identified through expression quantitative trait locus (eQTL)-MR and protein quantitative trait locus (pQTL)-MR analyses and subjected to a phenome-wide association study (PheWAS). The underlying mechanisms of EGLN1 were explored using single-gene gene set enrichment analysis (GSEA), single-cell RNA sequencing analysis, and a gut microbiota MR-based mediation analysis. Finally, a potential target and its corresponding compound were validated through computational drug screening, molecular docking, and in vitro cellular experiments. RESULTS: The global disease burden of CRC attributable to high BMI increased significantly from 1990 to 2021, with the age-standardized rate in males showing a more rapid increase. MR analysis confirmed that high BMI is a risk factor for CRC [inverse variance weighted (IVW): OR = 1.105, 95% CI = 1.028-1.186, P = 0.006]. We identified 120 KGs-BACC, which were primarily enriched in lipid metabolism, the HIF-1 signaling pathway, and the PPAR signaling pathway. The PPI network revealed core hub genes such as KLF4 and MAPK3 . A four-gene prognostic model derived from the KGs-BACC ( ACADVL, TGFA, SMPD1, BSG ) demonstrated robust risk stratification and survival prediction capabilities. Through eQTL-MR and pQTL-MR, EGLN1 was identified as a core causal protective target in high-BMI-associated CRC (protein level OR = 0.832, 95% CI = 0.753-0.918, P < 0.01); its expression was downregulated in tumors, and PheWAS analysis revealed limited pleiotropy. GSEA indicated that low EGLN1 expression is associated with cell proliferation and metabolic reprogramming. Single-cell analysis showed that EGLN1 is predominantly enriched in T cells and intestinal epithelial cells. Gut microbiota mediation MR analysis found that the abundance of Halarcobacter mediated approximately 34.6% of the protective effect of EGLN1 on CRC. Computational screening and molecular docking identified the natural compound cianidanol as having the strongest binding affinity to EGLN1 (binding energy = -11.24 kcal/mol). In vitro experiments confirmed that cianidanol significantly inhibited the proliferation, migration, and invasion of HCT116 CRC cells and upregulated PHD2 protein expression. CONCLUSION: This study systematically reveals the critical protective role of EGLN1 in high BMI-associated CRC and underscores its value as a potential drug target. EGLN1 influences CRC pathogenesis by modulating multiple dimensions, including the hypoxia response, energy metabolism, the immune microenvironment, and the gut microbiota. The natural compound cianidanol, as a modulator of EGLN1 , demonstrated significant anti-tumor activity in vitro . These findings provide new insights into the molecular mechanisms linking obesity and CRC and establish a theoretical foundation for developing precision therapeutic strategies targeting EGLN1 .