# Understanding ethno-racial differences in AT(N)-defined heterogeneity profiles

> **NIH NIH K01** · WASHINGTON UNIVERSITY · 2024 · $126,675

## Abstract

PROJECT ABSTRACT
Alzheimer disease (AD) is a highly heterogeneous disorder which varies in presentation within and across
diverse communities and backgrounds. Neuroanatomically, heterogeneity is observed in the topographical
patterns of amyloid (A), tau (T), and neurodegeneration (N) markers used to stage AD. For example, patterns
of tau accumulation and brain atrophy are highly correlated and have been subtyped by advanced multivariate
and machine learning methods into those involving typical AD regions (e.g., medial-temporal, lateral
temporoparietal), hippocampal-sparing, limbic-predominant regions or minimal atrophy, while amyloid
accumulation can be subtyped into frontal, parietal, and occipital regions. Notably, spatial subtypes are
associated with distinct cognitive, genetic (e.g., APOE e4 genotype), and fluid biomarker profiles, thus
suggesting that clinical heterogeneity may in part stem from neuroanatomical heterogeneity. Although
neuroanatomical heterogeneity in AD has important implications for cognitive and functional outcomes as well
as patient-specific treatments, there is a large gap in the literature regarding AD biomarker topographical
patterns in ethno-racial groups. Similarly, it is largely unknown to what extent structural and social
determinants of health (SSDOH) affect heterogeneity. The present study fills a critical gap in the literature by
including under-represented minorities and relevant SSDOH factors in the investigation of heterogeneity in
AT(N) imaging markers.
Using data from the racially and ethnically diverse Health and Aging Brain Study –
Health Disparities (HABS-HD), this study will
A) determine AD heterogeneity profiles (i.e., spatial subtypes and
magnitude) for A, T, and N neuroimaging markers (i.e., magnetic resonance imaging [MRI], amyloid and tau
positron emission tomography [PET]) using a machine learning approach; B) assess within and between group
differences in heterogeneity profiles across Mexican-Americans, Blacks, and non-Hispanic Whites (NHW); and
C) assess overall effects of SSDOH (e.g., area deprivation index, acculturation, education etc.) on A, T, and N
heterogeneity profiles within and between ethno-racial groups. Biomarker cut-points and group-level
composites used to classify individuals in research and clinical settings are often informed through the
identification of AD-specific or AD-vulnerable brain regions. However, the identified AD-sensitive regions and
associated cut-points are typically derived from one group (i.e., NHWs) and applied to all. Characterizing
heterogeneity in AT(N) imaging markers using a diverse and representative sample is therefore crucial to
informing whether AD-sensitive regions are similar across individuals and thus whether current cut-points are
appropriate.

## Key facts

- **NIH application ID:** 10899650
- **Project number:** 5K01AG083115-02
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Karin Meeker
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $126,675
- **Award type:** 5
- **Project period:** 2023-08-15 → 2024-08-02

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10899650

## Citation

> US National Institutes of Health, RePORTER application 10899650, Understanding ethno-racial differences in AT(N)-defined heterogeneity profiles (5K01AG083115-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10899650. Licensed CC0.

---

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