# Modeling Alzheimer’s disease: Bayesian copula graphical model from demographic, cognitive, and neuroimaging data

**Authors:** Lucas Vogels, Reza Mohammadi, Marit Schoonhoven, Ş Ilker Birbil, Martin Dyrba

PMC · DOI: 10.1177/13872877251337944 · Journal of Alzheimer's Disease · 2025-05-04

## TL;DR

This study uses a Bayesian statistical model to uncover how factors like brain volume and amyloid-beta levels relate to cognitive decline in Alzheimer's disease.

## Contribution

The novel application of Bayesian Gaussian copula graphical models to Alzheimer’s disease data, capturing conditional dependencies across diverse variables.

## Key findings

- Aging reduces cognition through hippocampal and PCC volume loss and amyloid-beta accumulation.
- Being a woman is positively correlated with cognition, but this is dampened by brain volume loss and amyloid-beta in women.
- Brain-region specific glucose uptake has limited direct relation to cognition, but hippocampal and PCC volumes are significant.

## Abstract

The early detection of Alzheimer’s disease (AD) requires an understanding of the relationships between a wide range of features. Conditional independencies and partial correlations are suitable measures for these relationships, because they can identify the effects of confounding and mediating variables.

To estimate conditional dependencies and partial correlations between relevant features in AD using a Bayesian approach to Gaussian copula graphical models (GCGMs). This approach has two key advantages. First, it includes binary, discrete, and continuous variables. Second, it quantifies the uncertainty of the estimates. Despite these advantages, Bayesian GCGMs have not been applied to AD research yet.

We design a GCGM to find the conditional dependencies and partial correlations among brain-region specific gray matter volume and glucose uptake, amyloid-beta levels, demographic information, and cognitive test scores. We applied our model to 
1022
 participants, including healthy and cognitively impaired, across different stages of AD.

We found that aging reduces cognition through three indirect pathways: hippocampal volume loss, posterior cingulate cortex (PCC) volume loss, and amyloid-beta accumulation. We found a positive partial correlation between being woman and cognition, but also discovered four indirect pathways that dampen this association in women: lower hippocampal volume, lower PCC volume, more amyloid-beta accumulation, and less education. We found limited relations between brain-region specific glucose uptake and cognition, but discovered that the hippocampus and PCC volumes are related to cognition.

This study shows that the use of GCGMs offers valuable insights into AD pathogenesis.

## Linked entities

- **Diseases:** Alzheimer’s disease (MONDO:0004975)

## Full-text entities

- **Genes:** APP (amyloid beta precursor protein) [NCBI Gene 351] {aka AAA, ABETA, ABPP, AD1, APPI, CTFgamma}
- **Diseases:** AD (MESH:D000544)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12583651/full.md

## References

61 references — full list in the complete paper: https://tomesphere.com/paper/PMC12583651/full.md

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Source: https://tomesphere.com/paper/PMC12583651