Identification of candidate diagnostic biomarkers and gene networks for moderate stages of Alzheimer's disease in fusiform gyrus exhibiting neurofibrillary tangles

Background Alzheimer's disease (AD) is a neurodegenerative disorder whose incidence grows with age and its development is gradual. However, if detected earlier there is much hope to prevent further exacerbation. In this study, NGS transcriptomics data from cases and controls with Braak scores of III-IV were investigated that all possessed neurofibrillary tangles (NFTs) in their fusiform gyrus. Objective The aim of this study was to discover the underlying mechanisms at gene level which could explain cognitive impairment by considering the presence of NFTs in both groups. Methods Differentially expressed genes (DEGs) were determined and ROC AUC were evaluated by leave-one-out cross-validation method on the diagnostic DEGs to detect candidate gene biomarkers. WGCNA was employed to identify co-expression modules with their trait association. Finally, in silico hybridization of lncRNAs from potential biomarkers with important AD-related microRNAs was carried out. Results Highly ranked potential diagnostic gene biomarkers revealed assessed AUC ranges of 80–90% in which RASGRF2-AS1 demonstrated the highest value. WGCNA demonstrated upregulated genes in favor of dephosphorylation of tau, proper proteostasis and vascular health in resilient controls whereas dysfunctional proteostasis, chronic protein misfolding, heightened cellular stress and tetrahydrobiopterin deficiency were attributed to cognitive impairment in AD patients. In silico analyses predicted some lncRNAs with a high possibility of acting as sponge for AD-related microRNAs. Conclusions This study discovered potential diagnostic gene biomarkers and transcriptional signatures that could explain the mechanisms of cognitive decline by considering the existence of NFTs, which could provide further insight for diagnosis and treatment of the disease.