Regional gene expression signatures are associated with sex-specific functional connectivity changes in depression

Aleksandr Talishinsky, Jonathan Downar (), Petra E. Vértes, Jakob Seidlitz, Katharine Dunlop, Charles J. Lynch, Heather Whalley, Andrew McIntosh, Fidel Vila-Rodriguez, Zafiris J. Daskalakis, Daniel M. Blumberger and Conor Liston ()
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Aleksandr Talishinsky: Weill Cornell Medicine
Jonathan Downar: University Health Network
Petra E. Vértes: University of Cambridge
Jakob Seidlitz: Children’s Hospital of Philadelphia
Katharine Dunlop: Weill Cornell Medicine
Charles J. Lynch: Weill Cornell Medicine
Heather Whalley: University of Edinburgh
Andrew McIntosh: University of Edinburgh
Fidel Vila-Rodriguez: University of British Columbia
Zafiris J. Daskalakis: University of California
Daniel M. Blumberger: University of Toronto
Conor Liston: Weill Cornell Medicine

Nature Communications, 2022, vol. 13, issue 1, 1-20

Abstract: Abstract The neural substrates of depression may differ in men and women, but the underlying mechanisms are incompletely understood. Here, we show that depression is associated with sex-specific patterns of abnormal functional connectivity in the default mode network and in five regions of interest with sexually dimorphic transcriptional effects. Regional differences in gene expression in two independent datasets explained the neuroanatomical distribution of abnormal connectivity. These gene sets varied by sex and were strongly enriched for genes implicated in depression, synapse function, immune signaling, and neurodevelopment. In an independent sample, we confirmed the prediction that individual differences in default mode network connectivity are explained by inferred brain expression levels for six depression-related genes, including PCDH8, a brain-specific protocadherin integral membrane protein implicated in activity-related synaptic reorganization. Together, our results delineate both shared and sex-specific changes in the organization of depression-related functional networks, with implications for biomarker development and fMRI-guided therapeutic neuromodulation.

Date: 2022
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DOI: 10.1038/s41467-022-32617-1

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