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

Cognitive Function Is Associated with the Genetically Determined Efficiency of DNA Repair Mechanisms

Several modifiable risk factors for neurodegeneration and dementia have been identified, although individuals vary in their vulnerability despite a similar risk of exposure. This difference in vulnerability could be explained at least in part by the variability in DNA repair mechanisms' efficiency between individuals. Therefore, the aim of this study was to test associations between documented, prevalent genetic variation (single nucleotide polymorphism, SNP) in DNA repair genes, cognitive function, and brain structure. Community-living participants (n = 488,159; 56.54 years (8.09); 54.2% female) taking part in the UK Biobank study and for whom cognitive and genetic measures were available were included. SNPs in base excision repair (BER) genes of the bifunctional DNA glycosylases OGG1 (rs1052133, rs104893751), NEIL1 (rs7402844, rs5745906), NEIL2 (rs6601606), NEIL3 (rs10013040, rs13112390, rs13112358, rs1395479), MUTYH (rs34612342, rs200165598), NTHL1 (rs150766139, rs2516739) were considered. Cognitive measures included fluid intelligence, the symbol-digit matching task, visual matching, and trail-making. Hierarchical regression and latent class analyses were used to test the associations between SNPs and cognitive measures. Associations between SNPs and brain measures were also tested in a subset of 39,060 participants. Statistically significant associations with cognition were detected for 12 out of the 13 SNPs analyzed. The strongest effects amounted to a 1-6% difference in cognitive function detected for NEIL1 (rs7402844), NEIL2 (rs6601606), and NTHL1 (rs2516739). Associations varied by age and sex, with stronger effects detected in middle-aged women. Weaker associations with brain measures were also detected. Variability in some BER genes is associated with cognitive function and brain structure and may explain variability in the risk for neurodegeneration and dementia.

Evaluation of Utilizing the Distinct Genes as Predictive Biomarkers in Late-Onset Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disease that is characterized by a devastating decline in cognitive activities among all types of dementia, and it severely affects the quality of life. Late-onset AD (LOAD) occurs after the age of 65 years and develops sporadically. Although aging comes first along the main risk factors underlying LOAD, disease-causing susceptibility genes have been associated with disease pathogenesis. In our study, we included the genes PARP1 , POLB , HTRA2 , SLC1A2 , HS1BP3 , and DRD3 to be investigated in LOAD patients based on their expression levels. Within this framework, we aimed to determine the possible functions of these genes in the pathophysiology of the disease. We investigated whether the utilization of these genes as biomarkers in the early diagnosis of LOAD may help the treatment scheme to be applied in the clinic. We involved 50 individuals in the study and collected peripheral blood samples from the patients and control groups for molecular genetic analysis. Subsequently, RNA was extracted from the peripheral blood samples, and expression analyzes were performed using qualitative reverse transcription polymerase chain reaction. The results obtained were evaluated by using proper statistical methods. Our results demonstrated that there was no difference between patient and control groups in terms of HTRA2 , DRD3 , HS1BP3 , and POLB genes. The expression levels of the SLC1A2 and PARP1 genes were significantly lower in the patient group compared with the control group. In conclusion, we presume that the PARP1 and SLC1A2 genes can be utilized as molecular biomarkers for LOAD.