We sought to identify novel biomarkers and related mechanisms that might shape the immune infiltration in IDD, thereby providing novel perspective for IDD diagnosis and therapies. Gene expression data sets GSE124272 (for initial analysis) and GSE56081 (for validation analysis) involving samples from IDD patients and healthy controls were retrieved from the Gene Expression Omnibus (GEO) database. Immune genes associated with IDD were identified by GSEA; module genes that exhibited coordinated expression patterns and the strongest positive or negative correlation with IDD were identified by WGCNA. The intersection between immune genes and module genes was used for LASSO variable selection, whereby we obtained pivotal genes that were highly representative of IDD. We then correlated (Pearson correlation) the expression of pivotal genes with immune cell proportion inferred by CIBERSORT algorithm, and revealed the potential immune-regulatory roles of pivotal genes on the pathogenesis of IDD. We discovered several immune-associated pathways in which IDD-associated immune genes were highly clustered, and identified two gene modules that might promote or inhibit the pathogenesis of IDD. These candidate genes were further narrowed down to 8 pivotal genes, namely, MSH2, LY96, ADAM8, HEBP2, ANXA3, RAB24, ZBTB16 and PIK3CD, among which ANXA3, MSH2, ZBTB16, LY96, PIK3CD, ZBTB16, and ADAM8 were revealed to be correlated with the proportion of CD8 T cells and resting memory CD4 T cells. This work identified 8 pivotal genes that might be involved in the pathogenesis of IDD through triggering various immune-associated pathways and altering the composition of immune and myeloid cells in IDD patients, which provides novel perspectives on IDD diagnosis and treatment.