Abstract
Background: Oxidative stress (OS) is closely associated with the occurrence and progression of breast cancer (BC). However, its role as a potential etiological factor or trigger remains unclear. This study aims to systematically investigate the potential causal effects and mechanisms of OS-related genes in BC by integrating multi-omics data. Methods: This study obtained summary data for blood methylation (mQTL), gene expression (eQTL), alternative splicing (sQTL), and protein abundance (pQTL) from their respective quantitative trait loci (QTL) studies. The genetic association data for breast cancer (BC) were primarily derived from the Breast Cancer Association Consortium (BCAC) and were validated using the UK Biobank (UKB) and FinnGen databases. SMR (Summary-data-based Mendelian Randomization) analysis was performed to evaluate the associations between the molecular characteristics of oxidative stress-related genes and BC. Subsequently, colocalization analysis was conducted to determine whether the identified signals share the same causal genetic variants. Whole-transcriptome association studies (TWAS), whole-proteome association studies (PWAS), and multi-marker analysis with genomic annotation (MAGMA) were used as sensitivity analyses. In addition, the significant genes were validated using multi-omics analysis of blood samples in an independent cohort from Weifang Traditional Chinese Medicine Hospital. Results: By integrating multi-omics data from mQTL, eQTL, sQTL, and pQTL analyses, we identified PARK7 as a key oxidative stress-related gene that showed significant associations with breast cancer (BC) at multiple levels. Elevated gene expression of PARK7 (pSMR = 5.79E-06, OR = 0.91) and protein levels (pSMR = 8.46E-06, OR = 0.83) were significantly associated with reduced BC risk. In the mQTL analysis, cg10385390 (pSMR = 2.03E-03, OR = 1.09) and cg11518359 (pSMR = 3.54E-03, OR = 0.88) were significantly associated with BC. In the sQTL analysis, PARK7 (chr1:7961793-7962763) (pSMR = 8.87E-06, OR = 1.03) and PARK7 (chr1:7961735-7962763) (pSMR = 9.38E-06, OR = 0.97) were significantly associated with BC. In the integrated mQTL-eQTL SMR analysis, cg10385390 (pSMR = 7.61E-15, OR = 0.47) and cg11518359 (pSMR = 4.56E-09, OR = 2.78) exhibited significant associations. In the integrated sQTL-pQTL SMR analysis, PARK7 (chr1:7961793-7962763) (pSMR = 4.62E-44, OR = 0.85) and PARK7 (chr1:7961735-7962763) (pSMR = 6.56E-42, OR = 1.19) both showed significant associations. These findings revealed the multidimensional molecular mechanisms by which PARK7 regulates breast cancer risk through the oxidative stress pathway. All findings were supported by colocalization analysis (PPH4 > 0.7). Validation in an independent population cohort indicated that plasma levels of PARK7 mRNA and protein in breast cancer patients were significantly lower than those in healthy controls, consistent with the aforementioned results. Conclusion: This study innovatively integrates multi-omics data to elucidate the complex associations between the PARK7 gene and breast cancer risk, providing new insights for precision prevention and targeted intervention of breast cancer.