Abstract
Alzheimer's disease (AD) is a degenerative illness that accounts for the common type of dementia among adults over the age of 65. Despite extensive studies on the pathogenesis of the disease, early diagnosis of AD is still debatable. In this research, we performed bioinformatics approaches on the AD-related E-MTAB 6094 dataset to uncover new potential biomarkers for AD diagnosis. To achieve this, we performed in-depth in silico assays, including differentially expressed genes analysis, weighted gene co-expression network analyses, module-trait association analyses, gene ontology and pathway enrichment analyses, and hub genes network analyses. Finally, the expression of the identified candidate genes was evaluated in AD patients PBMC samples by qRT-PCR. Through computational analyses, we found that RN7SK LncRNA and its co-expressed genes of TNF, TNFAIP3, CCLT3, and FLT3 are from key genes in AD development that are associated with inflammatory responses. Our experimental validation revealed that RN7SK LncRNA and TNF were substantially up-regulated in AD samples (P = 0.006 and P = 0.023, respectively). Whereas, TNFAIP3 expression was significantly decreased (P = 0.016). However, the expression of CCL3 and FLT3 did not differ significantly between two groups (P = 0.396 and P = 0.521, respectively). In conclusion, in this study a novel LncRNA associated with AD pathogenesis were identified, which may provide new diagnostic biomarker for AD.
Keywords:
Alzheimer’s disease; Bioinformatics; Biomarker; LncRNA; PBMC; RN7SK.