# Plasma proteomic signatures of physical activity and Alzheimer's disease and related dementias > **NIH NIH K99** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $102,873 ## Abstract PROJECT SUMMARY/ABSTRACT Physical activity (PA) has been listed as a promising intervention to delay or prevent Alzheimer’s disease (AD) and related dementias (ADRD), however most studies used self-reported PA. Our preliminary data show that, among older women, higher amounts of accelerometer-measured moderate to vigorous intensity PA and steps/day are associated with lower risk of rigorously adjudicated incident mild cognitive impairment (MCI) and ADRD. However, the molecular mechanisms through which PA influences ADRD risk are unclear. The plasma proteome is a promising target for identifying the molecular mechanisms of PA because proteins regulate biological processes, capture disease mechanisms, and may identify intervention targets. Machine learning (ML) methods have been applied to derive PA proteomic signatures, proteomic aging clocks, and ADRD proteomic clocks. However, few studies have systematically applied and compared ML methods to derive PA proteomic signatures. The objective of this research is to enhance our understanding of PA, proteomics, and how they relate to ADRD. I propose leveraging an NIA-funded study (RF1AG079149) that will use the SOMAscan platform to measure ~7,000 clinically relevant plasma proteins and plasma AD biomarkers in a case cohort of 2,836 (n=1,336 incident MCI/ADRD cases) women in the richly phenotyped and racially/ethnically diverse Women’s Health Initiative (WHI) Memory Study (WHIMS) from samples collected in 1995-1998 (n=2,836) and 14-18 years later in 2012-2013 (n=1,000; 500 incident MCI/ADRD cases) and the WHI Objective Physical Activity and Cardiovascular Health (OPACH; R01HL105065) study which collected accelerometry in 2012-2014 among 6,489 women, including the 1,000 WHIMS women in RF1AG079149. WHIMS contains longitudinal annual cognitive assessments and rigorously adjudicated MCI/dementia over 27 years of follow-up. In the R00 phase, I propose obtaining plasma biomarkers of AD pathology from 600 Black and Hispanic/Latina OPACH women. Study results will be replicated in the Atherosclerosis Risk in Communities study to extend findings to men and women. Our Aims are: (1a) Apply and compare ML methods to derive PA proteomic signatures, (1b) Examine the overlap of PA proteomic signatures, proteomic aging clocks, and ADRD proteomic clocks, (1c) Relate PA proteomic signatures with MCI/ADRD and cognitive functioning, (2) Determine the role of PA-associated plasma proteins in our observed PA-MCI/ADRD associations, and (3) Determine the associations of PA (self-reported and accelerometer-measured) and PA- associated plasma proteins with plasma AD biomarkers among Black, Hispanic/Latina, and White women. This research will advance understanding of the molecular mechanisms linking PA, aging, and ADRD. The addition of plasma AD biomarker data to OPACH will have an enduring impact by enabling broader studies of accelerometry and AD pathology in relation to aging-related phenotypes. ## Key facts - **NIH application ID:** 10914261 - **Project number:** 5K99AG082863-02 - **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO - **Principal Investigator:** Steve Nguyen - **Activity code:** K99 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $102,873 - **Award type:** 5 - **Project period:** 2023-09-01 → 2025-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10914261 ## Citation > US National Institutes of Health, RePORTER application 10914261, Plasma proteomic signatures of physical activity and Alzheimer's disease and related dementias (5K99AG082863-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10914261. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*