# Deep Phenotypic Characterization of Prodromal Dementia with Lewy Bodies

> **NIH NIH R56** · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · 2022 · $3,171,435

## Abstract

Approximately 1.4 million people in the United States have Lewy body dementia, which includes both dementia with
Lewy bodies (DLB) and Parkinson's disease (PD) dementia (PDD). Patients with DLB experience cognitive decline
similar to Alzheimer's disease (AD), motor changes seen in PD5, behavioral and psychotic features associated with
DSM5 Axis I psychiatric disorders, and constitutional and autonomic features that are often missed as early warning
signs. Importantly, recent efforts have described prodromal DLB subtypes according to presenting symptoms (e.g.,
cognition, motor, sleep, behavior). Both AD and PD have benefited from large longitudinal studies that have
advanced research, but few have DLB as a focus. Unfortunately, the diagnosis of DLB and its prodromal states can
be difficult, with patients seeing more than 3 physicians and experiencing an 18-month delay to diagnosis. While the
DLB consensus criteria have excellent specificity, until recently there has been no standardized way to assess signs
and symptoms to improve sensitivity. We have led recent efforts to improve diagnosis with the Lewy Body Composite
Risk Score (LBCRS) and the DLB-Module (DLB-MOD) for the NIA-funded Alzheimer Disease Research Center
Program. These advances hastened the ability to (a) characterize DLB, (b) discriminate DLB from cognitively normal
controls and AD, and (c) discriminate mild cognitive impairment (MCI) due to DLB from MCI due to AD. This
application will test the HYPOTHESIS that DLB-MCI has unique neuropsychological, neuroanatomic, and
neurophysiologic signatures distinct from MCI due to AD or vascular dementia (VCID). We further posit that
combining state-of-the-science plasma biomarkers (e.g., amyloid, tau, synuclein) improves detection and permits
antemortem characterization of co-morbid pathology and how pathology may drive transition to DLB and rates of
progression. We will leverage existing longitudinal cohorts (n=850) of healthy brain aging, MCI, AD, and VCID that
use identical data collection platforms to provide robust comparison groups at no cost to this application. Our
SPECIFIC AIMS are: (1) Recruit and deep phenotype a DLB-MCI cohort (n=300) systematically characterizing
and validating clinical-cognitive-sleep-behavioral-autonomic features, MRI, DAT, qEEG, plasma and genetic DLB
biomarkers; (2) Refine phenotypic presentations of prodromal DLB and their associated biomarker signatures to
formally test the recently published clinical criteria and leverage archival data from the PI's existing cohorts using
identical data platforms to differentiate DLB-MCI as a distinct clinical entity; and (3) Model clinical-cognitive
features, genetic, imaging, qEEG, and plasma biomarkers to predict transition and characterize progression to DLB
based on biological variables (e.g., sex, ApoE), comorbid pathologies (e.g., amyloid, tau), and symptom
presentations (e.g., fluctuations, hallucinations). DLB is the second most common cause of neurodegenerative
de...

## Key facts

- **NIH application ID:** 10670501
- **Project number:** 1R56AG074889-01A1
- **Recipient organization:** UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
- **Principal Investigator:** James E Galvin
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $3,171,435
- **Award type:** 1
- **Project period:** 2022-09-30 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10670501

## Citation

> US National Institutes of Health, RePORTER application 10670501, Deep Phenotypic Characterization of Prodromal Dementia with Lewy Bodies (1R56AG074889-01A1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10670501. Licensed CC0.

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