# Connecting late-life depression and cognition with statistical physics based connectomics and sparse Frechet regression

> **NIH NIH RF1** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2021 · $1,261,160

## Abstract

Recently, several lines of evidence have supported that synaptic dysfunction represents one of
the earliest brain changes in Alzheimer’s disease (AD), leading to hyper-excitation in neuronal
circuits. However, network changes related to age, sex and other risk factors such as the
apolipoprotein E (APOE) ε4 allele tend to overlap with disease neuropathology, increasing the
difficulty of separating disease-specific alterations from those related to normal aging
trajectories in males and females (women comprise two thirds of all persons diagnosed with AD
dementia, while female ε4 allele carriers are four times more likely to develop AD than men).
Further compounding the challenges is the potential for psychiatric conditions to influence these
relationships. Specifically, late life depression (LLD) has been proposed as a significant
contributor to accelerated cognitive decline and progression to dementia. While it remains
unclear which neurobiological aspects of LLD represent pathognomonic features, versus co-
occurring aspects of AD, determining their impact on functional outcomes is a significant
opportunity to disentangle the relationship between depression and neurodegenerative
processes in late life.
 We will use multi-modal connectomics to analyze excitation-inhibition balance (E-I balance)
in the well-characterized ADNI and ADNI-D samples to elucidate the relationship between late-
life depression and neurodegeneration. Our pipeline will be based on a novel resting-state
structural connectomics (rs-SC) approach that yields a hyperexcitation indicator (HI).
Previously, in a group of cognitively normal APOE-ε4 carriers and age/gender matched non-
carriers we demonstrated a sex-by-age-by-genotype interaction, with significant hyperexcitation
with increasing age only observable in women, but not in men. In particular, results supported
that hyperexcitation in female carriers began to exhibit at age 50 in the default mode network
(DMN). Further, the degree of hyperexcitation was shown to be related to compensatory
recruitment of neuronal resources during a spatial learning memory task (virtual Morris water
maze task). Motivated by this pilot study, we will examine the links between mood (late-life
depression) and subsequent cognitive decline and development of dementia in the context of
synaptic dysfunction.

## Key facts

- **NIH application ID:** 10190424
- **Project number:** 1RF1MH125928-01
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO
- **Principal Investigator:** Alex Leow
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,261,160
- **Award type:** 1
- **Project period:** 2021-04-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10190424

## Citation

> US National Institutes of Health, RePORTER application 10190424, Connecting late-life depression and cognition with statistical physics based connectomics and sparse Frechet regression (1RF1MH125928-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10190424. Licensed CC0.

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