DOI: 10.1111/acel.13938 ISSN:

Sex‐ and APOE‐specific genetic risk factors for late‐onset Alzheimer's disease: Evidence from gene–gene interaction of longevity‐related loci

Serena Dato, Francesco De Rango, Paolina Crocco, Stefano Pallotti, Michael E. Belloy, Yann Le Guen, Michael D. Greicius, Giuseppe Passarino, Giuseppina Rose, Valerio Napolioni
  • Cell Biology
  • Aging

Abstract

Advanced age is the largest risk factor for late‐onset Alzheimer's disease (LOAD), a disease in which susceptibility correlates to almost all hallmarks of aging. Shared genetic signatures between LOAD and longevity were frequently hypothesized, likely characterized by distinctive epistatic and pleiotropic interactions. Here, we applied a multidimensional reduction approach to detect gene–gene interactions affecting LOAD in a large dataset of genomic variants harbored by genes in the insulin/IGF1 signaling, DNA repair, and oxidative stress pathways, previously investigated in human longevity. The dataset was generated from a collection of publicly available Genome Wide Association Studies, comprising a total of 2,469 gene variants genotyped in 20,766 subjects of Northwestern European ancestry (11,038 LOAD cases and 9,728 controls). The stratified analysis according to APOE*4 status and sex corroborated evidence that pathways leading to longevity also contribute to LOAD. Among the significantly interacting genes, PTPN1, TXNRD1, and IGF1R were already found enriched in gene–gene interactions affecting survival to old age. Furthermore, interacting variants associated with LOAD in a sex‐ and APOE‐specific way. Indeed, while in APOE*4 female carriers we found several inter‐pathway interactions, no significant epistasis was found in APOE*4 negative females; conversely, in males, significant intra‐ and inter‐pathways epistasis emerged according to APOE*4 status. These findings suggest that interactions of risk factors may drive different trajectories of cognitive aging. Beyond helping to disentangle the genetic architecture of LOAD, such knowledge may improve precision in predicting the risk of dementia and enable effective sex‐ and APOE‐stratified preventive and therapeutic interventions for LOAD.

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