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Mapping structural disconnection and transcriptomic signatures in Alzheimer's disease with MIND networks
Yongsheng Wu1, Hao Zhang2, Junyu Qu1
1Qilu Hospital of Shandong University, Department of Radiology, Jinan, Shandong 250012, China.
Brain Research Bulletin
|January 18, 2026
Summary
Alzheimer's disease (AD) involves brain network disconnection. The novel MIND approach maps these structural changes and their genetic links, outperforming previous methods in diagnosing AD.
Area of Science:
- Neuroscience
- Computational Biology
- Genomics
Background:
- Alzheimer's disease (AD) is increasingly viewed as a disconnection syndrome affecting brain networks.
- Vertex-level structural disconnection and its molecular underpinnings in AD are not well understood.
- Morphometric Inverse Divergence (MIND) offers a novel method for detailed mapping of structural disconnection and its transcriptomic correlates in AD.
Purpose of the Study:
- To map structural disconnection patterns in Alzheimer's disease using the MIND approach.
- To investigate the association between MIND alterations, cognitive performance, and AD biomarkers.
- To explore the transcriptomic basis of MIND connectome alterations in AD.
- To evaluate the diagnostic performance of MIND compared to Morphometric Similarity Networks (MSNs).
Main Methods:
- Applied MIND to two independent datasets (ADNI and Qilu) comprising AD and cognitively normal (CN) individuals.
- Correlated MIND network alterations with cognitive scores (MMSE) and biomarker data (CSF Aβ-42, FDG-PET SUVR).
- Linked the MIND connectome to spatial gene expression data using partial least squares regression and gene enrichment analysis.
- Developed a deep neural network (ResDNN) to compare diagnostic performance of MIND versus MSNs.
Main Results:
- Decreased MIND degree observed in frontal, occipital, and temporal lobes correlated positively with cognitive function and metabolic activity.
- Increased MIND degree found in medial temporal lobe regions correlated negatively with cognition and AD biomarkers.
- MIND alterations were associated with gene expression profiles related to synaptic function, neurotransmission, and metabolism.
- MIND demonstrated superior diagnostic accuracy (AUC=0.90/0.88) compared to MSNs in distinguishing AD from CN.
Conclusions:
- The MIND approach effectively maps structural disconnection patterns in Alzheimer's disease.
- These patterns are linked to specific transcriptomic signatures, enhancing understanding of AD as a disconnection syndrome.
- MIND shows significant promise as a sensitive tool for mechanistic and clinical investigations in AD.
Keywords:
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