Study Design: A case-control study of risk alleles for degenerative disc disease (DDD) using magnetic resonance (MR) imaging for phenotyping.Objective: We aim to provide the first statistically adequately powered study of the relationship between the presence of common risk alleles and occurrence of DDD in Eastern US population.Summary Of Background Data: Many genetic predisposing factors have been identified in elevating the risk of DDD, including common variants in VDR, COL1A1, AGC1, COL9A2/3 genes.Methods: We utilized the Mass General Brigham (MGB) Biobank in which subjects' Medical Record is linked with genotyped data from single-nucleotide polymorphism (SNP) arrays. Subjects with lumbosacral spine MR imaging studies were used to construct the Cases cohort; the Biobank's Controls cohort was used as the Control cohort. Odds ratios (OR) and False-discovery-rate (FDR) q values from multiple-hypotheses-testing corrections were used to assess the likelihood of DDD given occurrence of the listed DDD risk alleles.Results: Four-hundred-fourteen subjects (mean age = 64, range = 27 to 94) were Cases and 925 Controls (mean age = 46, range = 21-61). A systematic search has identified 25 SNPs in 18 genes in the SNP arrays. At univariate level, rs1544410 in VDR was significantly associated with DDD for male subjects (odds ratio [OR] = 0.594, P = 0.011). After adjustment for all significant variants and demographics, three predictor variables had a significant association with the outcome, age (OR = 1.130, q < 0.0001), rs143383 (OR = 1.951, q = 0.056), and rs3737821 (OR = 2.701, q = 0.069). A novel variant-to-variant correlation rs143383:rs763110 had a significant adjusted OR = 7.933, q = 0.070).Conclusion: In this large-scale study of common variants' correlation with the presence of DDD in the Northeast United States, we have found a novel and significant variant-to-variant interaction to be associated with the risk of developing DDD, corroborating and necessitating the inclusion of gene-gene interactions in predictive risk model development for DDD.Level of Evidence: 4. [ABSTRACT FROM AUTHOR]