Skip to navigation Skip to main content Skip to footer

Approved Research

Leveraging population-based human data to uncover mechanisms connecting Alzheimer's diseaseand common infections and facilitate vaccines repurposing for AD prevention

Principal Investigator: Professor Svetlana Ukraintseva
Approved Research ID: 82705
Approval date: August 9th 2022

Lay summary

Alzheimer's disease (AD) is a complex neurodegenerative disorder, with potentially many mechanisms and involved biological processes. Accumulating evidence suggests that infections may play an important role in AD development, however, exact mechanism is unclear. Recent studies linked various microorganisms to AD and related traits. This indicates a possibility that the culprit may be not a specific microbe (or not only it) but weakened immunity that may increase the brain's vulnerability to various infections and damaging factors, and through this contribute to AD. The goal of this study using the UK Biobank data is to significantly improve our understanding of the complex connections between infections and AD. To address this objective, we will evaluate associations of common adult infectious diseases (pneumonia, flu, shingles, mycoses, and other) with AD and related disorders and traits (e.g., brain volume, cognitive scores), taking into account genetic and other factors, such as exposures to air pollution, brain trauma, and medication, using the rich information available in the UK Biobank data. Results of these analyses will help clarify the role of  infectious diseases in AD and other complex disorders, and will facilitate development of personalized AD prevention in older adults.

This project aims to significantly improve our understanding of the relationships between AD and common infectious diseases, taking into account genetic and exposure factors, using data from several human studies, including UK Biobank (UKB). Specific Aims:

Aim 1. Evaluate associations between AD traits and adult infectious diseases, including pneumonia, flu, shingles, and mycoses.

Aim 2. Evaluate effects of candidate genes involved in AD and vulnerability to infections, and their interactions with infections, on AD traits. Aim 3. Compare effects of infections on risks of AD vs. other major diseases, such as cancer, to investigate potential trade-offs. The UKB data are essential for fulfilling these aims. Specifically, we will use genetic and other information available from UKB, including on AD/ADRD, hippocampal volume, exposures to air pollution and brain trauma, and disease history, to investigate associations between infections and AD traits, taking into account genetic background. Focus will be on genes involved in both AD and vulnerability to infections (e.g., NECTIN2, APOE) that may modify associations between infections and AD-traits. We will also explore relationships between COVID-19, vaccinations, and AD-related traits. Results of these analyses will help clarify the role of infections in AD, and aid personalized AD prevention.    

As requested, herewith we submit a Scope Extension for this application, to cover additional analyses on diet, protein intake, cancer, as well as other covariates and risk factors relevant to Alzheimer's disease (AD) and vulnerability to infections. Our research will continue to be conducted in accordance with the overall project objective (uncovering mechanisms connecting AD and common infections and vaccinations), with additional emphasis on a broader range of covariates and risk factors that may impact vulnerability to infections and AD, such as diet, comorbidities, treatments, and others. This will allow for more detailed analyses to be done for project Aims. In Aim 3, which has emphasis on investigating potential trade-offs between effects of infection-related factors on AD and other major diseases, we will evaluate associations of various factors that may influence responses to infections (such as diet, protein intake, sugar intake, supplements, medications, vaccinations, etc.) with AD traits, as well as with other diseases (cancer, CHD, stroke, diabetes, depression, etc.), comorbidities, and survival. We will also add such broader range of covariates and risk factors that may impact vulnerability to infections and AD to Aims 1 and 2 analyses, to investigate in more detail the associations between the infection-related factors and AD traits, taking into account genetic background. We have Tier 3 data approved for this project.