Document Type

Article

Publication Date

4-10-2020

Publication Title

Journal of Neurology and Experimental Neuroscience

DOI

10.17756/jnen.2020-069

Abstract

Advancements in biomedical research have contributed to increasing the life expectancy of humans, but we now observe an increase in age-related diseases such as Alzheimer’s disease. Genome-Wide Association Studies (GWAS) and linkage studies have identified human genes associated with Alzheimer’s disease (referred to as AD genes). A previous study by Vahdati in 2017 has revealed the human AD genes and counterparts in model species [1]. Thus, we further investigate the co-morbidity genes and alleles. Using ontology analysis combined with cluster analysis, the study identified functional pathways enriched among the human AD genes, including 179 genes out of 695 human AD genes (26%) that were associated with one or more of the four neurological diseases including Amyotrophic lateral sclerosis, Multiple sclerosis, Parkinson’s disease, and Schizophrenia [1]. More importantly, the results indicate co-morbidities with Late-Onset Alzheimer’s Disease (LOAD) and other neurological conditions, implying the complexity of the phenotypes in the human AD. The co-morbidity genes may account for mixed symptoms for human AD as well as age-related risks of infections. Of them, the three genes are well conserved (Angiotensin I Converting Enzyme gene, ACE; Methylenetetrahydrofolate Reductase gene, MTHFR; and tumor necrosis factor gene, TNF). In this study, we confirmed the comorbidity of the three genes associated with AD. We further identified the comorbidity of two alleles in the MTHFR gene, C677T and A222V, significantly associated with Alzheimer’s disease. This study provides an example of evidencebased analysis that is cost-effective and may be an effective approach to develop cure-alls for multiple diseases.

Publisher's Statement

Originally published here: https://doi.org/10.17756/jnen.2020-069

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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