# Motor Profiles as Novel Biomarker for Alzheimer’s Disease

> **NIH NIH K01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2022 · $130,140

## Abstract

PROJECT SUMMARY / ABSTRACT
Established biomarkers for Alzheimer's disease (AD), such as amyloid beta measured with PET, are expensive
and invasive. Cost-efficient, quick, and easy-to-administer motor measures, such as grip strength and walking
speed, have shown to precede the cognitive symptoms of AD by several years. Relative to single measures,
combining ambulatory and strength measures boosts predictive value for AD. This suggests that a composite
motor profile score that weighs functions spanning the breadth of motor domains will have optimal predictive
power. Cognitive and motor brain regions that are known to degenerate early (e.g., the hippocampus and
fornix) and later in the AD disease process (e.g., the cerebellum, (pre)motor cortex, and corticospinal tract) are
candidates for the prediction of motor dysfunction in mild cognitive impairment (MCI) and AD. The objective of
this K01 proposal is two-fold: 1) to further develop the research skills of the applicant with a series of mentored
activities, and 2) to identify the behavioral and neural motor profiles of MCI and AD with the aim of developing
a robust and valid risk scoring algorithm. Our central hypothesis is that a motor behavioral composite score
and neural motor profile score distinguish individuals with MCI and AD from healthy control subjects, and are
related to established AD biomarkers (amyloid burden, hippocampal volume, and APOE e4 status). The project
has three specific aims: 1) Quantify behavioral and neural motor dysfunction in MCI and AD; 2) Identify
behavioral and neural motor composite scores as novel AD biomarkers; and 3) Replicate a motor composite
score as AD biomarker in a large independent sample from the Vietnam Era Twin Study of Aging.
 The training plan aims to establish expertise in areas that are crucial for the candidate to conduct the
proposed research and to become an independent investigator in the field of AD. The following training goals
have been identified in close collaboration with the mentoring team: a) establishing a clinical perspective and
the conceptual framework required to implement effective research in MCI and AD; b) develop expertise in
machine learning relevant to prediction modeling; c) gaining an in-depth understanding of neurological motor
signs and function in MCI and AD; and d) develop expertise on AD biomarkers and their perceived role in AD
etiology. The training will be closely supervised by clinical experts of AD (Dr. Duff), and leaders in the field of
neural motor dysfunction in aging (Dr. Rosano), AD biomarkers (Dr. Foster), MCI risk factors (Dr. Kremen), and
machine learning (Dr. Tasdizen). The candidate's optimal institutional environment further ensures the success
of the training and research plan that will provide data for an R01 application on the prediction of MCI to AD
transition from a motor profile composite score. The proposed research makes a significant contribution
towards the development of novel cost-efficient A...

## Key facts

- **NIH application ID:** 10479137
- **Project number:** 5K01AG073578-02
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Vincent Koppelmans
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $130,140
- **Award type:** 5
- **Project period:** 2021-09-05 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10479137

## Citation

> US National Institutes of Health, RePORTER application 10479137, Motor Profiles as Novel Biomarker for Alzheimer’s Disease (5K01AG073578-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10479137. Licensed CC0.

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