Systematic investigation of genetic contributions of sex chromosomes to Alzheimer's disease
- PI
- Wang, Qi
- DAR ID
- 11066
- Initial Approval Date
- January 10, 2025
- Current DAR Status
- Active
- PI Institution
- ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
- PI Institution Country
- United States
- PI Institution Type
- Non-Profit
Requested Datasets (1)
Research Use Statement
Sex chromosomes have long been excluded in genetic and genomic research of human diseases, partially due to the technical challenges of analyzing the data from large-scale molecular profiling methods, such as next-generation sequencing (NGS). Yet their contributions are significantly implicated in the sex dimorphism of Alzheimer’s disease (AD). In this project, the team will apply a sex-chromosome-completement aware alignment approach to re-align large amounts of NGS data from large clinical cohorts of AD, for systematically investigating the genetic contributions of sex chromosomes to AD. Variants will be called based on the realignments, and both X and Y chromosomes will be specifically investigated for the variants’ associations with the harmonized AD phenotypes from ADSP-PHC. The team will also consider the contributions of the homologous X-Y gene pairs to gene expression and perform gene network analysis to evaluate how the expressions affect sex differences in AD. The reprocessed data will be disseminated to the public for broad use to benefit the scientific community. Taken together, the work will lay the foundation for determining the genetic components of sex chromosomes to AD and pave the way for future in-depth study of these genomic features and their implication in sexual dimorphism in AD.
Non-Technical Summary
Alzheimer’s disease (AD) impacts millions of US populations, especially women, yet the molecular mechanism behind the sex differences remains poorly understood. This study aims to specifically study the genetic contributions of the sex chromosomes to the observed sex disparities in AD, which will build a benchmark of the molecular mechanism driving sex differences in AD and greatly facilitate untangling the genetic contributions from other factors in its etiology.
Reported Publications (1)
Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.
- Interpretable deep learning framework for understanding molecular changes in human brains with Alzheimer's disease: implications for microglia activation and sex differences. Trivedi MR, et al. npj aging. 2025. PMID: 40670382