Multi-region brain transcriptomes uncover two subtypes of aging individuals with differences in Alzheimer risk and the impact of APOEε4
7 affiliations
- 1Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA
- 2Department of Neurology, College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- 3Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- 4The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- 5Rush Alzheimer Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
- 6Broad Institute, Cambridge, MA 02142, USA
- 7Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA
Abstract
The heterogeneity of the older population suggests the existence of subsets of individuals which share certain brain molecular features and respond differently to risk factors for Alzheimer’s disease, but this population structure remains poorly defined. Here, we performed an unsupervised clustering of individuals with multi-region brain transcriptomes to assess whether a broader approach, simultaneously considering data from multiple regions involved in cognition would uncover such subsets. We implemented a canonical correlation-based analysis in a Discovery cohort of 459 participants from two longitudinal studies of cognitive aging that have RNA sequence profiles in three brain regions. 690 additional participants that have data in only one or two of these regions were used in the Replication effort. These clustering analyses identified two meta-clusters, MC-1 and MC-2. The two sets of participants differ primarily in their trajectories of cognitive decline, with MC-2 having a delay of 3 years to the median age of incident dementia. This is due, in part, to a greater impact of tau pathology on neuronal chromatin architecture and to broader brain changes including greater loss of white matter integrity in MC-1. Further evidence of biological differences includes a significantly larger impact of APOEε4 risk on cognitive decline in MC-1. These findings suggest that our proposed population structure captures an aspect of the more distributed molecular state of the aging brain that either enhances the effect of risk factors in MC-1 or of protective effects in MC-2. These observations may inform the design of therapeutic development efforts and of trials as both become increasingly more targeted molecularly. One Sentence Summary: There are two types of aging brains, with one being more vulnerable to APOEε4 and subsequent neuronal dysfunction and cognitive loss.
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BibTeX
@article{lee2026multiregion,
title = {{Multi-region brain transcriptomes uncover two subtypes of aging individuals with differences in Alzheimer risk and the impact of APOEε4}},
author = {Annie Lee and Yiyi Ma and Lei Yu and Robert J. Dawe and Cristin Aubin and Konstantinos Arfanakis and Richard P Mayeux and David A. A Bennett and Hans‐Ulrich Klein and Philip L. De Jager},
journal = {iScience},
year = {2026},
month = aug,
doi = {10.1016/j.isci.2026.117038},
url = {https://doi.org/10.1016/j.isci.2026.117038},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Multi-region brain transcriptomes uncover two subtypes of aging individuals with differences in Alzheimer risk and the impact of APOEε4
AU - Annie Lee
AU - Yiyi Ma
AU - Lei Yu
AU - Robert J. Dawe
AU - Cristin Aubin
AU - Konstantinos Arfanakis
AU - Richard P Mayeux
AU - David A. A Bennett
AU - Hans‐Ulrich Klein
AU - Philip L. De Jager
PY - 2026
DA - 2026/08/01
JO - iScience
DO - 10.1016/j.isci.2026.117038
UR - https://doi.org/10.1016/j.isci.2026.117038
AB - The heterogeneity of the older population suggests the existence of subsets of individuals which share certain brain molecular features and respond differently to risk factors for Alzheimer’s disease, but this population structure remains poorly defined. Here, we performed an unsupervised clustering of individuals with multi-region brain transcriptomes to assess whether a broader approach, simultaneously considering data from multiple regions involved in cognition would uncover such subsets. We implemented a canonical correlation-based analysis in a Discovery cohort of 459 participants from two longitudinal studies of cognitive aging that have RNA sequence profiles in three brain regions. 690 additional participants that have data in only one or two of these regions were used in the Replication effort. These clustering analyses identified two meta-clusters, MC-1 and MC-2. The two sets of participants differ primarily in their trajectories of cognitive decline, with MC-2 having a delay of 3 years to the median age of incident dementia. This is due, in part, to a greater impact of tau pathology on neuronal chromatin architecture and to broader brain changes including greater loss of white matter integrity in MC-1. Further evidence of biological differences includes a significantly larger impact of APOEε4 risk on cognitive decline in MC-1. These findings suggest that our proposed population structure captures an aspect of the more distributed molecular state of the aging brain that either enhances the effect of risk factors in MC-1 or of protective effects in MC-2. These observations may inform the design of therapeutic development efforts and of trials as both become increasingly more targeted molecularly. One Sentence Summary: There are two types of aging brains, with one being more vulnerable to APOEε4 and subsequent neuronal dysfunction and cognitive loss.
SN - 2589-0042
ER -