# NIH grant: Multi-Dimensional Sleep Health Predicts Alzheimer’s Markers (DREAM) (1K08AG090752-01A1) — retained record

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[original source ↗](https://reporter.nih.gov/project-details/1K08AG090752-01A1)

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NIH grant 1K08AG090752-01A1: Multi-Dimensional Sleep Health Predicts Alzheimer’s Markers (DREAM)
Institute: {'code': 'AG', 'abbreviation': 'NIA', 'name': 'National Institute on Aging', 'admin_org_id': '12500002', 'admin_funding_url': ''}. PI: Sonya Sarjit Kaur. Award: $141957.
Start: 2026-07-01T00:00:00.
PROJECT SUMMARY (ABSTRACT)

This project is a Mentored Clinical Scientist Career Development Award with both research and career-development training components. Dr. Kaur (PI) is a licensed clinical neuropsychologist with the overarching career goal to 1) apply cutting edge paradigms to the study of sleep and Alzheimer’s Disease 2) bridge the gap between computational modeling and clinical care by identifying model biases and working to reduce these in sleep/circadian health and Alzheimer’s Disease/ Alzheimer’s Disease related dementia (AD/ADRD)  and 3) Use the above skills to implement tailored interventions aimed at improving sleep and preventing AD/ADRD.
Training provided via this K08 project has been thoughtfully designed to help Dr. Kaur develop into an independent clinical scientist. The training framework includes mentorship, structured coursework, mentored research, and a superb team of excellent advisors that will fill vital gaps in her scientific education and guide his professional development. Training will cover the areas of sleep and circadian science, computational neuroscience and machine learning, Alzheimer’s Disease biomarkers and population health, and career development/leadership. 
Research Specific Aims proposed in this K08 project will leverage the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) to examine if multidimensional sleep health, a novel metric of sleep that encompasses multiple dimensions including regularity, timing, sleep disordered breathing and satisfaction will predict trajectory of cognitive change over time and levels of plasma biomarkers of Alzheimer’s disease. Dr. Kaur will also apply an established machine learning model of brain aging to this dataset and examine if multidimensional sleep health predicts accelerated brain aging in this vulnerable population. In the completion of this aim, she will learn valuable skills in applying machine learning algorithms to multiple population groups and examining biases in the models. In response to reviewer’s valuable feedback, Dr. Kaur has added additional post hoc analyses to all Research Specific Aims to identify a) most salient aspects of sleep health that predict cognitive change and levels of plasma biomarkers of AD, as well as patterns of atrophy associated with MSH. This will enhance Dr. Kaur’s hands on training in machine learning and artificial intelligence paradigms with high dimensional neuroimaging data. 
The training and research within this K08 will prepare Dr. Kaur to submit a NIH Research Project (R01) application that implements machine learning/artificial intelligence in the study of sleep and brain aging. As sleep behaviors are culturally bound and sleep physiology is highly modifiable, this proposed trajectory of K08 and R01 studies can help develop uncover novel patterns of sleep health, ultimately creating new tools to identify high risk groups for early intervention. This project is also in line with NIH priorities to develop solution focused approaches to population health.
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