# Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning

**Authors:** Luigi Lorenzini, Mario Tranfa, Leonard Pieperhoff, Federico Masserini, Mara ten Kate, Lyduine E. Collij, Giuseppe Pontillo, Emma S. Luckett, Alle Meije Wink, Henk JMM Mutsaerts, Tiago Gil Oliveira, Daniele Altomare, Mercè Boada, Anouk den Braber, Cindy Birck, Christopher Buckley, Gill Farrar, Wiesje van der Flier, Giovanni B. Frisoni, Rossella Gismondi, Juan Domingo Gispert, Bernard J. Hanseeuw, Frank Jessen, Marta Marquié, Anja Mett, Craig Ritchie, Gemma Salvadó, Michael Schöll, Mahnaz Shekari, Andrew W. Stephens, Betty M. Tijms, David Vállez García, Rik Vandenberghe, Pieter Jelle Visser, Luca Roccatagliata, Neil P. Oxtoby, Matteo Pardini, Frederik Barkhof

PMC · DOI: 10.1002/alz.70762 · 2025-10-14

## TL;DR

This study identifies two stable brain subtypes in cognitively unimpaired individuals, showing different patterns of cortical thinning and clinical decline linked to Alzheimer's disease.

## Contribution

The study introduces stable MRI-based subtypes of cortical thickness in preclinical Alzheimer's disease, linked to distinct network and transcriptomic mechanisms.

## Key findings

- Two stable subtypes—limbic-predominant and hippocampal-sparing—were identified in cognitively unimpaired individuals.
- Each subtype shows distinct clinical decline patterns and longitudinal cortical thinning linked to specific brain networks and gene expression.
- Subtype assignments remain stable over time, suggesting potential for clinical trial stratification and early prognosis.

## Abstract

The emergence, stability, and contributing factors of Alzheimer's disease (AD) gray matter subtypes remain unclear.

We analyzed data from 1323 individuals without a diagnosis of dementia (CDR < 1) with T1w‐MRI and amyloid‐PET, including 622 with longitudinal data (3.66 ± 1.78 years). Cortical thickness subtypes were identified using a non‐negative matrix factorization (NMF) clustering algorithm. We examined clinical and demographic differences, subtype stability, and longitudinal thinning patterns using brain network models and imaging‐transcriptomic analysis. Replication was performed with an alternative clustering approach and a validation cohort.

Two stable subtypes emerged: limbic‐predominant and hippocampal‐sparing. Limbic‐predominant participants were older, had higher amyloid burden, and faster memory decline, while hippocampal‐sparing individuals showed greater attention and executive function decline. Distinct thinning patterns were linked to specific network properties and gene expression profiles.

These MRI‐based subtypes reflect underlying pathophysiological mechanisms and may aid in prognostication and clinical trial stratification.

Two gray matter thickness subtypes can already be identified in preclinical stages, exhibiting distinct clinical characteristics and progression patterns.Individual subtype assignment remains stable over time.Longitudinal cortical thinning patterns follow distinct network‐ and transcriptomic‐based mechanisms within each subtype.

Two gray matter thickness subtypes can already be identified in preclinical stages, exhibiting distinct clinical characteristics and progression patterns.

Individual subtype assignment remains stable over time.

Longitudinal cortical thinning patterns follow distinct network‐ and transcriptomic‐based mechanisms within each subtype.

## Linked entities

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

## Full-text entities

- **Diseases:** amyloid (MESH:C000718787), memory decline (MESH:D060825), attention and executive function decline (MESH:D001289), dementia (MESH:D003704), AD (MESH:D000544)

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12519513/full.md

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Source: https://tomesphere.com/paper/PMC12519513