# Genetic architecture of age of onset of amyloid positivity: Integrating imaging and genetic tools to identify novel drivers of disease

> **NIH NIH K76** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2024 · $1

## Abstract

ABSTRACT.
 Alzheimer's disease (AD) involves a long prodromal stage where β-amyloid (Aβ) plaques accumulate
before clinical symptom onset. Yet, the molecular factors that underlie the striking heterogeneity in the onset,
accumulation, and response to AD neuropathology are poorly understood. Advances in imaging genetics offer
an opportunity to move the field towards precision interventions by deconvolving the clinical heterogeneity by
using sensitive imaging biomarkers and genetics to nominate novel targets for intervention.
 Genome-wide association studies (GWAS) have identified 70+ genetic loci linked to AD, shedding light
on disease mechanisms. However, traditional case/control designs are limited by clinical misdiagnosis. My
prior work has leveraged imaging-derived traits as a more precise phenotype closer to disease biology in
genetic studies. Recent advances in artificial intelligence (AI), computational imaging analysis, and
harmonization allow us to extract quantitative features from images that humans cannot see at a scale that can
facilitate well-powered GWAS with more precise traits.
 We will leverage one such advanced modeling algorithm to estimate the age of Aβ+ onset from
16,000+ harmonized Aβ positron emission tomography (PET) from the AD Sequencing Project-Phenotype
Harmonization Consortium (Contact-PI: Dr. Timothy Hohman--primary mentor). Characterizing the genetic
architecture of Aβ+ onset can provide insight into the AD cascade of our research participants decades before
they joined our studies. Our initial work has shown that the age of Aβ+ onset varies significantly (40 to over 90
years) but is a heritable trait. Beyond APOE, in a subset of the cohort we propose here, we have found that
genes involved in Aβ clearance pathways seem to influence age of Aβ+ onset. Additionally, biological sex
appears to play a significant role.
 In this proposal, I will expand upon this preliminary work to characterize the association of established
AD-risk loci with age of Aβ+ onset, identify novel genetic drivers of age of Aβ+ onset leveraging state-of-the-art
genome-wide approaches, and identify sex-specific genetic drivers of age of Aβ+. We will use cutting-edge
methods that allow for inclusion of admixed individuals (rather than traditional exclusionary approaches) and
that account for sex as a biological variable. I will receive training from world experts in AI and advanced
analyses of large-scale image datasets, cutting-edge genomic analyses, the neurobiology of aging and clinical
geriatrics, and important career development skills for a successful physician-scientist career.
 This K76 research proposal – along with the parallel detailed training plan that expands upon my
expertise in genetics and radiology– uniquely position me as a leader and expert at the intersection of imaging
and genetics to lead the way in developing more precise treatment strategies in AD and related dementias.

## Key facts

- **NIH application ID:** 10973433
- **Project number:** 1K76AG088554-01
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Mary Ellen Irene Koran
- **Activity code:** K76 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1
- **Award type:** 1
- **Project period:** 2024-08-23 → 2024-08-24

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10973433

## Citation

> US National Institutes of Health, RePORTER application 10973433, Genetic architecture of age of onset of amyloid positivity: Integrating imaging and genetic tools to identify novel drivers of disease (1K76AG088554-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10973433. Licensed CC0.

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