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Yashin AI, Wu D, Arbeev K, et al. Interplay between stress-related genes may influence Alzheimer's disease development: The results of genetic interaction analyses of human data. Mech Ageing Dev. 2021;196:111477doi: 10.1016/j.mad.2021.111477.
Yashin, A. I., Wu, D., Arbeev, K., Bagley, O., Akushevich, I., Duan, M., Yashkin, A., & Ukraintseva, S. (2021). Interplay between stress-related genes may influence Alzheimer's disease development: The results of genetic interaction analyses of human data. Mechanisms of ageing and development, 196111477. https://doi.org/10.1016/j.mad.2021.111477
Yashin, Anatoliy I, et al. "Interplay between stress-related genes may influence Alzheimer's disease development: The results of genetic interaction analyses of human data." Mechanisms of ageing and development vol. 196 (2021): 111477. doi: https://doi.org/10.1016/j.mad.2021.111477
Yashin AI, Wu D, Arbeev K, Bagley O, Akushevich I, Duan M, Yashkin A, Ukraintseva S. Interplay between stress-related genes may influence Alzheimer's disease development: The results of genetic interaction analyses of human data. Mech Ageing Dev. 2021 Jun;196:111477. doi: 10.1016/j.mad.2021.111477. Epub 2021 Mar 30. PMID: 33798591; PMCID: PMC8173104.
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Mech Ageing Dev. 2021 Jun;196:111477. doi: 10.1016/j.mad.2021.111477. Epub 2021 Mar 30.

Interplay between stress-related genes may influence Alzheimer's disease development: The results of genetic interaction analyses of human data.

Mechanisms of ageing and development

Anatoliy I Yashin, Deqing Wu, Konstantin Arbeev, Olivia Bagley, Igor Akushevich, Matt Duan, Arseniy Yashkin, Svetlana Ukraintseva

Affiliations

  1. Biodemography of Aging Research Unit, Duke University SSRI, USA. Electronic address: [email protected].
  2. Biodemography of Aging Research Unit, Duke University SSRI, USA.

PMID: 33798591 PMCID: PMC8173104 DOI: 10.1016/j.mad.2021.111477

Abstract

Emerging evidence from experimental and clinical research suggests that stress-related genes may play key roles in AD development. The fact that genome-wide association studies were not able to detect a contribution of such genes to AD indicates the possibility that these genes may influence AD non-linearly, through interactions of their products. In this paper, we selected two stress-related genes (GCN2/EIF2AK4 and APP) based on recent findings from experimental studies which suggest that the interplay between these genes might influence AD in humans. To test this hypothesis, we evaluated the effects of interactions between SNPs in these two genes on AD occurrence, using the Health and Retirement Study data on white indidividuals. We found several interacting SNP-pairs whose associations with AD remained statistically significant after correction for multiple testing. These findings emphasize the importance of nonlinear mechanisms of polygenic AD regulation that cannot be detected in traditional association studies. To estimate collective effects of multiple interacting SNP-pairs on AD, we constructed a new composite index, called Interaction Polygenic Risk Score, and showed that its association with AD is highly statistically significant. These results open a new avenue in the analyses of mechanisms of complex multigenic AD regulation.

Copyright © 2021. Published by Elsevier B.V.

Keywords: APP gene; Alzheimer’s disease; Epistasis; GCN2/EIF2AK4 gene; Genetic interactions; Integrated stress response; Multifactorial traits; Polygenic effects; Polygenic risk score

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