Meta-analysis of RNA-Seq data identifies potent biomarker for Intellectual Disability Disorder (IDD)

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.