# Hemodynamic Biomarkers of Healthy and Diseased Aging

> **NIH NIH K25** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $140,212

## Abstract

Project Summary
This K25 proposal is for a five-year mentored training program to enable Dr. Ariana Anderson from UCLA to
transition from a statistician to an independent investigator, with an active research plan in identifying
functional biomarkers of cognitive decline and aging. Dr. Anderson's proposal includes a comprehensive
training program involving formal training in calibrated fMRI, fMRI data collection, neuropsychological
assessments, volunteering, directed readings, coursework, mentoring, conferences, and career development,
which are designed to complement and complete the applicant's previous training in mathematics and
statistics. The proposed research addresses an important issue that affects nearly all fMRI studies; the
modeled blood-flow response to neuronal stimuli is assumed to be constant across ages, genotypes and
diseases, even though we know that this assumption is categorically false. This lowers the statistical power of
fMRI studies, increases necessary sample sizes, and introduces bias into fMRI studies of disease and aging.
Moreover, a poor understanding of hemodynamic change with age in healthy patients makes identifying
biomarkers of unhealthy aging difficult. We will use cerebral blood flow measurements (ASL), hypercapnic and
hemodynamic changes, along with genetic risk factors, as biomarkers to predict future cognitive decline. The
relationship between the hemodynamic response, cognitive decline, aging and disease will be unraveled
through the following three aims. Aim 1.) Create age-corrected hemodynamic response functions, after
adjusting for cardiac and respiratory artifacts recorded during scan-time, so that future age studies can use
age-corrected models of blood flow. We will estimate this in subjects with and without genetic risk for
Alzheimer's disease. Age-corrected hemodynamic response functions will reduce bias and increase statistical
power (increase the sensitivity, and/or reduce the required sample sizes). Aim 2.) Evaluate whether age-
abnormal hemodynamics predict abnormal cognitive ability. Modeling normal hemodynamics will allow us to
identify abnormal hemodynamics, creating biomarkers for specific diseases such as vascular dementia. Aim 3.)
Create a new HRF model to account for age-related CBF changes, using calibrated fMRI. Abnormal
hemodynamics may better predict which patients are more likely to experience cognitive decline, leading to
earlier treatment.

## Key facts

- **NIH application ID:** 9925162
- **Project number:** 5K25AG051782-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Ariana Anderson
- **Activity code:** K25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $140,212
- **Award type:** 5
- **Project period:** 2016-08-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9925162

## Citation

> US National Institutes of Health, RePORTER application 9925162, Hemodynamic Biomarkers of Healthy and Diseased Aging (5K25AG051782-05). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/9925162. Licensed CC0.

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