E3S Web of Conferences (Jan 2024)

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

  • Amukti Danang Prasetyaning,
  • Wazni Annisa Rizqita,
  • Irham Lalu Muhammad,
  • Sulistyani Nanik,
  • Ma’ruf Muhammad,
  • Adikusuma Wirawan,
  • Sarasmita Made Ary,
  • Khairi Sabiah,
  • Purwanto Barkah Djaka,
  • Suyatmi Suyatmi,
  • Siswanto Lalu Muhammad Harmain,
  • Chong Rockie

DOI
https://doi.org/10.1051/e3sconf/202450101021
Journal volume & issue
Vol. 501
p. 01021

Abstract

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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.