# Preclinical markers of Alzheimer's disease using psycholinguistic semantic measures

> **NIH NIH R00** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $96,067

## Abstract

PROJECT ABSTRACT
The clinical diagnosis of Alzheimer's disease (AD) is based on the core criterion of memory impairment, but
biomarker-detectable pathophysiological changes start decades before clinical symptoms. This preclinical
phase, in which someone has the neuropathology of AD but does not yet show clinical symptoms, is crucial for
potential intervention and timely diagnosis for patient and caregiver. The preclinical phase is currently only
detectable with expensive or invasive biomarkers. Because current cognitive measures are not sensitive to the
preclinical phase of AD and have low specificity and large variation with regard to individuals' educational and
cultural exposure, there is a critical need to develop sensitive, low-cost, and high-access cognitive markers for
early detection in diverse older adults. The primary goal of this project is to investigate if novel psycholinguistic
metrics of existing cognitive test data can accurately identify people in the earliest stages of AD. The semantic
fluency task—naming as many animals in one minute—tests semantic memory, one of the first cognitive domains
to become impaired in AD. Traditionally, semantic fluency is scored by the total number of items. However, there
is a wealth of information at the item-level of this task, because words are organized in a semantic network that
becomes vulnerable during AD, specifically for words that are poorly connected and not often used. These traits
of words in the semantic network can be captured with novel psycholinguistic metrics, such as lexical frequency,
e.g., `dog' is a high-frequent word in our language, as opposed to `iguana.' Nine novel item-level psycholinguistic
metrics of semantic fluency have been selected to: investigate how AD imaging biomarkers in nondemented
adults relate to psycholinguistic measures (Aim 1, K99); estimate the temporality of semantic impairment across
the AD continuum (Aim 2, R00); and determine the sensitivity and specificity of psycholinguistic measures to
predict progression to clinical AD (Aim 3, R00). Since the relationship of demographics to psycholinguistic
metrics is not well understood, this project strives to deconstruct cultural and demographic effects on these
metrics in order to maximize their potential utility in early diagnosis among diverse older adults. The project will
employ advanced statistical analyses to investigate data from three large longitudinal cohorts with diverse
participants and semantic fluency data in English, Spanish, and Dutch. This K99/R00 proposal lays the
foundation for an independent research program focused on semantic processing in normal aging and across
the AD continuum. The proposed project will provide the applicant with 1) new training in computational
semantics and structural equation modeling, 2) experience with imaging biomarker data, and 3) a strong
foundation in cultural neuropsychology. These experiences will supplement the applicant's strong background
in Neurolinguis...

## Key facts

- **NIH application ID:** 11089730
- **Project number:** 3R00AG066934-05S2
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Jet M.J. Vonk
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $96,067
- **Award type:** 3
- **Project period:** 2022-06-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11089730

## Citation

> US National Institutes of Health, RePORTER application 11089730, Preclinical markers of Alzheimer's disease using psycholinguistic semantic measures (3R00AG066934-05S2). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11089730. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*