An AS-qPCR-based method for the detection of Alzheimer's disease-related SNPs

Alzheimer's disease (AD) is one of the most serious neurodegenerative diseases in the world and has a strong genetic predisposition. At present, there is still no effective method for the early diagnosis and prevention of AD. Accumulating evidence shows the association of several loci with AD risk, such as apolipoprotein E (APOE) and translocase of outer mitochondrial membrane 40 (TOMM40). However, for routine disease diagnosis in clinics, genotype detection methods based on gene sequencing technology are time-consuming and excessively costly. Thus, in this study, we developed a high-sensitivity, low-cost, and convenient single nucleotide polymorphism (SNP) detection assay method based on allele-specific quantitative polymerase chain reaction (AS-qPCR) technology, which can be used to determine the SNP genotype in APOE and TOMM40. A total of 40 patients were recruited from the outpatient department of the memory clinic of Dongzhimen Hospital, Beijing University of Chinese Medicine. The SNP detection assay method includes three steps. First, positive plasmids with different genotypes (TT/CC/TC) in APOE rs429358, rs7412, and TOMM40 rs11556505 were prepared. Second, 3′-T/3′-C primers were designed to amplify these positive plasmids for each SNP site. Finally, we calculated the log10 of the copy number ratio for each positive plasmid, and the genotype interpretation interval was established. Based on this method, we investigated whether the SNPs in 40 patients could be accurately calculated using AS-qPCR technology. The accuracy of SNP detection was verified by PCR-Pooling sequencing. The results showed that SNP genotypes assessed by AS-qPCR technology corresponded perfectly to the results obtained by conventional DNA sequencing. We have developed a genotype detection method for AD based on AS-qPCR, which can be performed easily, rapidly, accurately, and at low cost. The method will contribute to the early diagnosis of patients with late-onset Alzheimer's and the detection of large clinical samples in the future.