Screening of Human Circular RNAs as Biomarkers for Early Onset Detection of Alzheimer’s Disease

The identification of biomarkers for Alzheimer's disease using a systems biology approach based on lncRNA-circRNA-miRNA-mRNA ceRNA networks

In addition to being the most prevalent form of neurodegeneration among the elderly, AD is a devastating multifactorial disease. Currently, treatments address only its symptoms. Several clinical studies have shown that the disease begins to manifest decades before the first symptoms appear, indicating that studying early changes is crucial to improving early diagnosis and discovering novel treatments. Our study used bioinformatics and systems biology to identify biomarkers in AD that could be used for diagnosis and prognosis. The procedure was performed on data from the GEO database, and GO and KEGG enrichment analysis were performed. Then, we set up a network of interactions between proteins. Several miRNA prediction tools including miRDB, miRWalk, and TargetScan were used. The ceRNA network led to the identification of eight mRNAs, four circRNAs, seven miRNAs, and seven lncRNAs. Multiple mechanisms, including the cell cycle and DNA replication, have been linked to the promotion of AD development by the ceRNA network. By using the ceRNA network, it should be possible to extract prospective biomarkers and therapeutic targets for the treatment of AD. It is possible that the processes involved in DNA cell cycle and the replication of DNA contribute to the development of Alzheimer's disease.

Detection of APP gene recombinant in human blood plasma

The pathogenesis of Alzheimer's disease (AD) is believed to involve the accumulation of amyloid-β in the brain, which is produced by the sequential cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase. Recently, analysis of genomic DNA and mRNA from postmortem brain neurons has revealed intra-exonic recombinants of APP (gencDNA), which have been implicated in the accumulation of amyloid-β. In this study, we computationally analyzed publicly available sequence data (SRA) using probe sequences we constructed to screen APP gencDNAs. APP gencDNAs were detected in SRAs constructed from both genomic DNA and RNA obtained from the postmortem brain and in the SRA constructed from plasma cell-free mRNA (cf-mRNA). The SRA constructed from plasma cf-mRNA showed a significant difference in the number of APP gencDNA reads between SAD and NCI: the p-value from the Mann-Whitney U test was 5.14 × 10-6. The transcripts were also found in circulating nucleic acids (CNA) from our plasma samples with NGS analysis. These data indicate that transcripts of APP gencDNA can be detected in blood plasma and suggest the possibility of using them as blood biomarkers for Alzheimer's disease.