Investigation of base excision repair gene variants in late-onset Alzheimer’s disease

OpenAlex İngilizce

Base excision repair (BER) defects and concomitant oxidative DNA damage accumulation play a role in the etiology and progression of late-onset Alzheimer's disease (LOAD). However, it is not known whether genetic variant(s) of specific BER genes contribute to reduced BER activity in LOAD patients and whether they are associated with risk, development and/or progression of LOAD. Therefore, we performed targeted next generation sequencing for three BER genes, uracil glycosylase (UNG), endonuclease VIII-like DNA glycosylase 1 (NEIL1) and polymerase β (POLβ) including promoter, exonic and intronic regions in peripheral blood samples and postmortem brain tissues (temporal cortex, TC and cerebellum, CE) from LOAD patients, high-pathology control and cognitively normal age-matched controls. In addition, the known LOAD risk factor, APOE was included in this study to test whether any BER gene variants associate with APOE variants, particularly APOE ε4. We show that UNG carry five significant variants (rs1610925, rs2268406, rs80001089, rs1018782 and rs1018783) in blood samples of Turkish LOAD patients compared to age-matched controls and one of them (UNG rs80001089) is also significant in TC from Brazilian LOAD patients (p<0.05). The significant variants present only in CE and TC from LOAD are UNG rs2569987 and POLβ rs1012381950, respectively. There is also significant epistatic relationship (p = 0.0410) between UNG rs80001089 and NEIL1 rs7182283 in TC from LOAD subjects. Our results suggest that significant BER gene variants may be associated with the risk of LOAD in non-APOE ε4 carriers. On the other hand, there are no significant UNG, NEIL1 and POLβ variants that could affect their protein level and function, suggesting that there may be other factors such as post-transcriptional or-translational modifications responsible for the reduced activities and protein levels of these genes in LOAD pathogenesis. Further studies with increased sample size are needed to confirm the relationship between BER variants and LOAD risk.