Aberrant Development of Cross-Frequency Multiplex Functional Connectome in First-Episode, Drug-Naive Major Depressive Disorder and Schizophrenia

Introduction: Both major depressive disorder (MDD) and schizophrenia (SCH) are characterized by neurodevelopmental abnormalities; however, transdiagnostic and diagnosis-specific patterns of such abnormalities have rarely been examined, particularly in large-scale functional brain networks via advanced multilayer network models. Methods: Here, we collected resting-state functional magnetic resonance imaging data from 45 MDD patients, 64 SCH patients, and 48 healthy controls (HCs; 13–45 years old), and we constructed functional networks in different frequency intervals. The frequency-dependent networks were then fused by multiplex network models, followed by graph-based topological analyses. Results: We found that functional networks of the patients showed common neurodevelopmental abnormalities in the right ventromedial parietooccipital sulcus (opposite correlations with age to HCs), whereas functional networks of the MDD patients exhibited specific alterations in the left superior parietal lobule and right precentral gyrus with respect to cross-frequency interactions. These findings were quite different from those from brain networks within each frequency interval, which revealed SCH-specific neurodevelopmental abnormalities in the right superior temporal gyrus (opposite correlations with age to the other two groups) in 0.027–0.073 Hz, and SCH-specific alterations in the left superior temporal gyrus and bilateral insula in 0.073–0.198 Hz. Finally, multivariate analysis of age prediction revealed that the subcortical network lost prediction ability in both patient groups, whereas the visual network exhibited additional prediction ability in the MDD patients. Discussion and Conclusion: Altogether, these findings demonstrate transdiagnostic and diagnosis-specific neurodevelopmental abnormalities and alterations in large-scale functional brain networks between MDD and SCH, which have important implications for understanding shared and unique neural mechanisms underlying the diseases. Recent methodological advances in network neuroscience allow integrating connectivity information from different scales or aspects through multilayer network models. Utilizing such models, we found common and specific neurodevelopmental abnormalities in multiband functional brain networks between major depressive disorder (MDD) and schizophrenia (SCH), and the abnormalities cannot be uncovered by individually analyzing brain networks within each frequency interval. These findings have important implications for understanding shared and unique neural mechanisms underlying MDD and SCH and highlight the necessity of integrating connectivity information from different frequency intervals to search for new biomarkers of the diseases.