The identification of genes that are expressed differentially in the diseased versus healthy individual give relevant information regarding the pathology of the disease. The identification of DEGs can be a significant step in the field of clinical and pharmaceutical research. They can act as a potent biomarker, therapeutic target, or gene signature for the early diagnosis of the disease. Intellectual disability is a neurodevelopmental disorder that affects at the fetal stage. Timely diagnosis of the disease can help in preventing severe neurodevelopmental delay in the child. In the current study, meta-analysis approach was applied for the identification of the DEGs in patients of intellectual disability disorder. 6 intellectual disability datasets were retrieved from the GEO database of NCBI and were subjected to quality check, trimming, and alignment. Post-alignment, featureCounts was used to form a raw gene count file for differential analysis. The differentially expression genes were analyzed using the EdgeR statistical package of R Studio. The genes which had an FDR p-value less than 0.05 and log2foldchange greater than 0 were considered as the upregulated and significantly expressed genes. The study found MTRNR2L1, PAPSS2, L1CAM, IGLV1-47, IGLV3-19, and IGKV1-16 genes to be upregulated in the patient sample. These genes can thus play an important role in the progression of intellectual disability disorder that facilitates early diagnosis of the disease.