Identifying pathogenic variants associated with Alzeimer by integrating genomic databases and bioinformatics approaches

¹ Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55166, Indonesia
² Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram 83127, Indonesia
³ Department of Clinical Pharmacy, College of Pharmacy, Taipei Medical University, Taipei 110, Taiwan
⁴ School of Nursing, College of Nursing, Taipei Medical University, Taipei 11031, Taiwan
⁵ Faculty of Medicine, Universitas Ahmad Dahlan, Yogyakarta 55191, Indonesia 7 PKU Muhammadiyah Bantul Hospital, Bantul, Yogyakarta 55711, Indonesia
⁶ Department of Histology, Faculty of Medicine, Universitas Sebelas Maret, Surakarta 57126, Indonesia
⁷ Research Center for Computing, Research Organization for Electronics and Informatics, National Research and Innovation Agency (BRIN), Cibinong Science Center, Cibinong 16911, Indonesia 10 Mataram Training Health Center, Indonesia Ministry of Health, Mataram 83237, Indonesia
⁸ Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA

^* Corresponding author: lalu.irham@pharm.uad.ac.id

Abstract

Alzheimer’s disease (AD) is a major neurodegenerative disorder, including neuroinflammation, oxidative stress, synaptic dysfunction, metabolic changes, cognitive impairment, and misfolding of tau protein and amyloid beta peptide (Aß). Several genes associated with Alzheimer’s disease (AD) have been discovered recently through genome-wide association studies (GWAS). However, the relationship between many loci and the likelihood of the occurrence of AD remains unexplained. In this study, we sought to identify variants of this pathogen on different continents using genome-based methodologies and bioinformatics. We found that the variant rs138799625, rs7412, rs61762319, and rs75932628 most likely to damage Alzheimer’s. In addition, these four variants appear to affect the expression of the atp8b4, APOE, MME and TREM2 genes in whole blood tissue. Our findings suggest that these genomic variants require further research for validation in functional studies and clinical trials in Alzheimer’s patients. We conclude that the integration of genome-based databases and bioinformatics can improve our understanding of disease susceptibility, including Alzheimer’s.