Abstract
Multiple myeloma ranks as the second most common hematopoietic malignancy in terms of both incidence and mortality. Prognostic stratification is critical for optimizing therapeutic strategies, as certain genetic alterations can significantly influence disease progression and treatment response. The meta-analysis analyzed data from 3421 multiple myeloma patients and 14,720 controls. PubMed, Web of Science, and Scopus were used as databases. Associations between the SNPs and multiple myeloma were calculated as a measure of pooled odds ratios (ORs) and 95% confidence intervals. Statistical analysis was performed using Review Manager (RevMan). DNAH11 rs4487645 A/C genotype (OR = 1.35; 95% CI: 1.24-1.46; p < 0.00001; I(2) = 0%), ULK4 rs1052501 G/G genotype (OR = 1.21; 95% CI: 0.98-1.50; p = 0.08; I(2) = 64%), ULK4 rs1052501 A/G genotype (OR = 1.23; 95% CI: 1.13-1.34; p < 0.00001; I(2) = 0%), DTNB rs6746082 A/A genotype (OR = 1.10; 95% CI: 1.01-1.20; p = 0.03; I(2) = 45%), and VDR rs1544410 A/G genotype (OR = 1.87; 95% CI: 1.04-3.36; p = 0.04; I(2) = 0%) increased multiple myeloma risk. Our study concludes that DNAH11, ULK4, DTNB, and VDR may serve as predictive biomarkers for MM risk.