AI Article Synopsis
- The study investigates the relationship between Alzheimer's disease and other medical conditions like diabetes and heart disease in older adults.
- It uses genetic data from African American participants to find links between certain genetic variants and the co-occurrence of Alzheimer's and other conditions.
- The research highlights the discovery of both known and novel genetic variants connected to Alzheimer's and its comorbidities, suggesting a new approach to analyzing shared genetic factors for different diseases.
Article Abstract
Background: Alzheimer's disease and related dementias (ADRD) frequently co-occur with comorbidities such as diabetes and cardiovascular diseases in elderly populations.
Objective: Utilize a life-course approach to identify genetic variants that are associated with the co-occurrence of ADRD and another comorbid condition.
Methods: Research data from African American participants of the Indianapolis-Ibadan Dementia Project (IIDP) linked with electronic medical record (EMR) data and genome-wide association study (GWAS) data were utilized. The age of onset for ADRD was obtained from longitudinal follow-up of the IIDP study. Age of onset for comorbid conditions was obtained from EMR. The analysis included 1177 African Americans, among whom 174 were diagnosed with ADRD. A semi-parametric marginal bivariate survival model was used to examine the influence of single nucleotide polymorphisms (SNPs) on dual time-to-event outcomes while adjusting for sex, years of education, and the first principal component of GWAS data.
Results: Targeted analysis of 20 SNPs that were reported to be associated with ADRD revealed that six were significantly associated with dual-disease outcomes, specifically congestive heart failure and cancer. In addition, eight novel SNPs were identified for associations with both ADRD and a comorbid condition.
Conclusions: Using a bivariate survival model approach, we identified genetic variants associated not only with ADRD, but also with comorbid conditions. Our utilization of dual-disease models represents a novel analytic strategy for uncovering shared genetic variants for multiple disease phenotypes.
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| http://dx.doi.org/10.1177/13872877241289054 | DOI Listing |
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