# Connectomic Biomarkers of Preclinical Alzheimer's Disease within Multi-Synaptic Pathways

> **NIH AG R01** · MASSACHUSETTS GENERAL HOSPITAL · 2026 · $584,403

## Abstract

The overall goal of the proposed research is to define the specific brain networks that are vulnerable or
resilient in aging and Alzheimer’s disease (AD), and subsequently derive new accurate, precise, and robust
connectomic imaging biomarkers for (especially preclinical) AD, which could improve diagnosis, disease staging,
prediction, assessment of progression, and therapeutic efficacy. Information flows in the human brain through a
complex set of structural and functional networks. The complete connectivity map among brain areas, i.e. the
connectome, can help to better understand the vulnerability and resilience of the brain architecture and function
to aging effects and debilitating neurodegenerative diseases, such as AD, and to discover diagnostically and
therapeutically important biomarkers. Focusing on brain regions, but not interregional connectivity, may have
hindered progress in understanding and treating disorders characterized as “disconnection syndromes”.
Diffusion-weighted MRI (dMRI) and resting-state functional MRI (rs-fMRI) are used to noninvasively quantify
structural and functional brain networks, respectively. Network-based analysis of the brain has proved promising
in revealing the basis of cognitive dysfunction in mild cognitive impairment (MCI) and AD, demonstrating changes
distinct from those with healthy aging. Development of treatments to prevent or delay the onset of AD would be
greatly facilitated by a noninvasive, sensitive, and specific diagnostic biomarker able to discriminate cognitively
normal people and MCI patients who will progress to AD from those who will age healthily.
Structural connectivity between two brain regions is often defined based on the dMRI tractography-derived
streamlines between them. The direct fiber bundle connecting two brain areas is expected to be the major signal
carrier between them; however, multi-synaptic neural pathways (those mediated through other regions) also
provide connectivity. The investigators prop

## Key facts

- **NIH application ID:** 11083643
- **Project number:** 5R01AG068261-03
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Iman  Aganj
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AG
- **Fiscal year:** 2026
- **Award amount:** $584,403
- **Award type:** 5
- **Project period:** 2020-09-15T00:00:00 → 2027-04-30T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11083643

## Citation

> US National Institutes of Health, RePORTER application 11083643, Connectomic Biomarkers of Preclinical Alzheimer's Disease within Multi-Synaptic Pathways (5R01AG068261-03). Retrieved via AI Analytics 2026-05-17 from https://api.ai-analytics.org/grant/nih/11083643. Licensed CC0.

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