Unraveling Genetic Variants and Risk Factors in Alzheimer's Disease

Objectives of the proposed research:
Our research aims to investigate the role of genetic variants in Alzheimer's Disease (AD). We seek to identify and understand genetic factors that may contribute differently to AD risk in males and females. We also aim to identify the genetic variants for a certain cohort of AD patients receiving drug treatment.

Study design:
We will utilize data from the Alzheimer's Disease Sequencing Project (ADSP) resource to perform rigorous genetic analyses. This includes genome-wide association studies (GWAS) to identify sex-specific and cohort-specific genetic variants associated with AD. We will also employ bioinformatics and functional genomics approaches to annotate and characterize these variants, exploring their potential impact on gene function and regulation.

Analysis plan:
We will collect the available genetic and phenotype data to perform association analyses (e.g., logistic regression) to identify genetic variants associated with AD within each sex/cohort. Multiple testing correction using appropriate methods (e.g., Bonferroni correction or false discovery rate control) will be performed. We will annotate identified genetic variants with functional information (e.g., functional impact on genes, pathways, regulatory elements). Enrichment analysis will be conducted to understand the biological processes affected by sex-specific or cohort-specific variants.

Planned collaboration at other institutions:
Name of collaborator: Adam Naj; Institution: University of Pennsylvania
This collaboration involves joint efforts to achieve shared goals, with specific objectives, tasks, and outcomes in mind. Such collaborations may involve the exchange of expertise, resources, or personnel to leverage collective strengths and achieve more impactful results than would be possible independently.

Our study aims to uncover if and how Alzheimer's Disease affects sex-specific and drug-treated sub-cohorts differently. We'll analyze genomics data to find specific genetic factors associated with the disease in each sub-cohort. Then, we'll explore how these factors work and their impact on Alzheimer's development. Our goal is to provide insights that could lead to more personalized approaches for Alzheimer's diagnosis and treatment, ultimately improving our understanding of this disease.