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CC BY 4.0 · Glob Med Genet 2022; 09(02): 110-117
DOI: 10.1055/s-0042-1743570
Original Article

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

Sercan Kenanoglu
1   Department of Medical Genetics, Faculty of Medicine, Erciyes University, Kayseri, Turkey
,
Nefise Kandemir
1   Department of Medical Genetics, Faculty of Medicine, Erciyes University, Kayseri, Turkey
2   Department of Medical Genetics, Diskapi Yildirim Beyazit Training and Research Hospital, Ankara, Turkey
,
Hilal Akalin
1   Department of Medical Genetics, Faculty of Medicine, Erciyes University, Kayseri, Turkey
,
Nuriye Gokce
1   Department of Medical Genetics, Faculty of Medicine, Erciyes University, Kayseri, Turkey
,
Mehmet F. Gol
3   Department of Neurology, Faculty of Medicine, Erciyes University, Kayseri, Turkey
,
Murat Gultekin
3   Department of Neurology, Faculty of Medicine, Erciyes University, Kayseri, Turkey
,
Emel Koseoglu
3   Department of Neurology, Faculty of Medicine, Erciyes University, Kayseri, Turkey
,
Meral Mirza
3   Department of Neurology, Faculty of Medicine, Erciyes University, Kayseri, Turkey
,
Munis Dundar
1   Department of Medical Genetics, Faculty of Medicine, Erciyes University, Kayseri, Turkey
› Institutsangaben
Funding This work was supported by a research grant at Erciyes University with project number: TYL-2016–6956.
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Abstract

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.

Keywords

PARP1 - POLB - HTRA2 - SLC1A2 - HS1BP3 - DRD3


Publikationsverlauf

Eingereicht: 21. Januar 2022

Angenommen: 26. Januar 2022

Artikel online veröffentlicht:
08. März 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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