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Neuroimaging pattern interactions for suicide risk in depression captured by ensemble learning over
Ting Wang1, Junneng Shao1, Rui Yan2
1School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing 210096, China.
Summary
Neuroimaging biomarkers for suicide risk in major depression disorder are needed. This study used transcriptome-defined parcellations (TDP) and ensemble learning to identify brain patterns linked to suicide, suggesting glutamatergic and GABAergic dysfunction in the visual cortex.
Area of Science:
- Neuroscience
- Genetics
- Psychiatry
Background:
- Urgent need for reliable neuroimaging biomarkers for suicide in major depression disorder (MDD).
- Requirement for biomarkers interpretable through molecular tissue signatures.
- Development of an ensemble learning scheme over transcriptome-defined parcellations (TDP) to explore brain patterns.
Purpose of the Study:
- To develop and validate a novel neuroimaging approach for identifying suicide risk biomarkers in MDD.
- To explore homogeneously parcellated brain patterns and their interactions using transcriptome data.
- To quantify brain dysfunction related to suicide using resting-state functional abnormality (RSFA) scores.
Main Methods:
- Recruited 96 MDD patients without suicide attempt (SA), 86 with SA, and 102 healthy controls for resting-state fMRI.
- Generated spatially-continuous TDPs based on gene expression from the Allen Human Brain Atlas.
- Applied a three-layer ensemble learning scheme to integrate TDPs and quantify RSFA scores for suicide risk prediction.
Main Results:
- Ensemble learning over TDPs achieved higher suicide predictive accuracy (73.23 ± 1.07%) compared to regional analysis or null models.
- A specific parieto-occipital TDP (PO-TDP) pattern, quantified by RSFA score, was crucial for suicide risk prediction.
- Alterations in the PO-TDP were associated with transcriptional profiles of GRIN2A and GABRG2, with overrepresentation of glutamatergic and GABAergic synapses.
Conclusions:
- Glutamatergic and GABAergic dysfunction in the visual cortex, indicated by the PO-TDP pattern, is implicated in suicide risk.
- An inherent excitatory/inhibitory imbalance in these pathways may contribute to aberrant emotional processing and neurocognitive deficits.
- These findings suggest potential molecular targets and neuroimaging biomarkers for suicide prevention in MDD.
