| Title: | Tools for evaluating bias in ADRD research |
| Lead Institution: | University of California, San Francisco |
| Principal investigator: | Professor M. Maria Glymour |
Application 78748
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About
Critical social exposures and potentially modifiable risk factors for Alzheimer's disease and dementia occur across the lifespan, prior to the diagnosis of these conditions. For example, Alzheimer's disease and dementia is associated with social identities such as gender, education and income (and other socioeconomic factors), race, and ethnicity. In addition, a number of potentially modifiable behavioral or physiologic characteristics are associated with increased risk of Alzheimer's disease and dementia. However, various biases make it difficult to accurately assess the effects genetic, social, and modifiable risk factors. The ultimate goal of our research is to pinpoint how and when we can intervene to prevent or delay the onset of Alzheimer's disease and dementia. However, a socially and biologically informed approach that incorporates the effects of potential biases will be required to accomplish this. We propose rigorously evaluating the effects of genetic, lifecourse social, and modifiable risk factors using a diverse set of epidemiologic methods and approaches to evaluate, quantify, and correct for potential biases. This three-year study will improve the validity of lifecourse research cohorts and provide more valid and public health relevant estimates of the effects of genetic, social and potentially modifiable determinants of Alzheimer's disease and dementia. The tools will be useful to other Alzheimer's disease and dementia researchers. UKBiobank provides an incomparable source of data because of its size, the detailed characterization of the cohort, and the heterogeneity of participants compared to the other cohorts we plan to leverage.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 7863 | Discordance in chromosomal and self-reported sex in the UK Biobank: Implications for transgender- and intersex-inclusive data collection | Sarah F. Ackley (+5) | 2023 | Proceedings of the National Academy of Sciences of the United States of America |
| 8989 | Genetic risk score for Alzheimer's disease predicts brain volume differences in mid and late life in UK biobank participants | Peter T. Buto (+9) | 2024 | Alzheimer's & Dementia |
Enabling scientific discoveries that improve human health