Neurobiological commonalities and distinctions among 3 major psychiatric disorders: a graph theoretical analysis of the structural connectome

Abstract

Background: White matter network alterations have increasingly been implicated in major depressive disorder, bipolar disorder and schizophrenia. The aim of this study was to identify shared and distinct white matter network alterations among the 3 disorders. Methods: We used analysis of covariance, with age and gender as covariates, to investigate white matter network alterations in 123 patients with schizophrenia, 123 with bipolar disorder, 124 with major depressive disorder and 209 healthy controls. Results: We found significant group differences in global network efficiency (F = 3.386, p = 0.018), nodal efficiency (F = 8.015, p < 0.001 corrected for false discovery rate [FDR]) and nodal degree (F = 5.971, p FDR < 0.001) in the left middle occipital gyrus, as well as nodal efficiency (F = 6.930, p FDR < 0.001) and nodal degree (F = 5.884, p FDR < 0.001) in the left postcentral gyrus. We found no significant alterations in patients with major depressive disorder. Post hoc analyses revealed that compared with healthy controls, patients in the schizophrenia and bipolar disorder groups showed decreased global network efficiency, nodal efficiency and nodal degree in the left middle occipital gyrus. Furthermore, patients in the schizophrenia group showed decreased nodal efficiency and nodal degree in the left postcentral gyrus compared with healthy controls. Limitations: Our findings could have been confounded in part by treatment differences. Conclusion: Our findings implicate graded white matter network alterations across the 3 disorders, enhancing our understanding of shared and distinct pathophysiological mechanisms across diagnoses and providing vital insights into neuroimaging-based methods for diagnosis and research. to Fei Wang). The authors thank Dr.

Psychiatric symptoms and syndromes transcending diagnostic boundaries in Indian multiplex families: The cohort of ADBS study

“…This approach is further validated by large-scale, cross-disorder genetic studies, that show a significant genetic overlap between multiple psychiatric disorders 3, 20-23 . Such overlaps have also been found in terms of brain markers in recent transdiagnostic studies 8, 24 . The presence of overlaps does not necessarily mean an absence of specific factors, though attempts to identify these have had equivocal success 17 .…”

“…Transdiagnostic research is yielding novel insights into role of the neuronal markers 8, 10, 12, 20, 24, 63 , molecular 7, 64, 65 , genetic 3, 5, 7, 22, 34, 54, 55 as well as psychosocial factors 13, 66 . Pleiotropic genetic loci associated with multiple psychiatric conditions are being identified 67 .…”

Psychiatric symptoms and syndromes transcending diagnostic boundaries in Indian multiplex families: The cohort of ADBS study

“…This approach is further validated by largescale, cross-disorder genetic studies, that show a significant genetic overlap between multiple psychiatric disorders 3,[20][21][22][23] . Such overlaps have also been found in terms of brain markers in recent transdiagnostic studies 8,24 . The presence of overlaps does not necessarily mean an absence of specific factors, though attempts to identify these have had equivocal success 17 .…”

“…A better understanding of the basic mechanisms of pathobiology that contribute to these syndromes is essential for improved interventions 1 . Recent findings, using diverse strategies ranging from epidemiology, and descriptive psychopathology, to pathophysiology and genetics, suggest that the diagnostic categories (of the various syndromes) may not be distinct and that transdiagnostic studies are thus necessary for brain-based disorders [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] . The transition in research from traditional categorical approaches to brain-based dimensional approaches has been proposed by the Research Domain Criteria (RDoC) project following suggestions by the National Institute of Mental Health 18,19 .…”

Altered Topological Properties of Grey Matter Structural Covariance Networks in Complete Thoracic Spinal Cord Injury Patients: A Graph Theoretical Network Analysis

“…The topological properties of SCNs including global and regional covariance parameters could be explored accordingly [ 22 ]. The graph theoretical network analysis of SCNs has been widely used in neurodegenerative diseases (e.g., Parkinson disease [ 23 , 24 ] and Alzheimer disease [ 25 ]) and psychological diseases (e.g., obsessive-compulsive disorder [ 26 , 27 ], schizophrenia [ 28 ] and major depression [ 29 ]). The brain morphometric and topological properties in these diseases were found rearranged, providing a fundamental for further improvement of clinical diagnose and specific treatments.…”