Molecular, Functional, and Structural Imaging of Major Depressive Disorder

Zhang, Kai; Zhu, Yi; Zhu, Yuankai; Wu, Shuang; Líu, Hao; Zhang, Wei; Xu, Caiyun; Zhang, Hong; Hayashi, Takuya; Tian, Mei

doi:10.1007/s12264-016-0030-0

Cited by 68 publications

(41 citation statements)

References 132 publications

(152 reference statements)

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“…Confirming earlier reports, we did not find differences in speed of neurocognitive performance in any of the domains (Daban et al, 2012). The specificity in differences in cognitive functioning across the three mood disorder subgroups demonstrates the heterogeneity of mood disorders that has been shown in other domains including biological markers (Glaus et al, 2014; Thase, 2014), structural and functional neuroimaging (Zhang et al, 2016), and treatment response (Karyotaki et al, 2016). …”

Section: Discussionmentioning

confidence: 87%

Neurocognitive performance as an endophenotype for mood disorder subgroups

Merikangas

Cui

Calkins

et al. 2017

Journal of Affective Disorders

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Background There is growing evidence that neurocognitive function may be an endophenotype for mood disorders. The goal of this study is to examine the specificity and familiality of neurocognitive functioning across the full range of mood disorder subgroups, including Bipolar I (BP-I), Bipolar II (BP-II), Major Depressive Disorders (MDD), and controls in a community-based family study. Methods A total of 310 participants from 137 families with mood spectrum disorders (n=151) and controls (n=159) completed the University of Pennsylvania’s Computerized Neurocognitive Battery (CNB) that assessed the accuracy and speed of task performance across five domains. Mixed effects regression models tested association and familiality. Results Compared to those without mood disorders, participants with BP-I had increased accuracy in complex cognition, while participants with MDD were more accurate in emotion recognition. There was also a significant familial association for accuracy of complex cognition. Mood disorder subgroups did not differ in performance speed in any of the domains. Limitations The small number of BP-I cases, and family size limited statistical power of these analyses, and the cross-sectional assessment of neurocognitive function precluded our ability to determine whether performance precedes or post dates onset of disorder. Conclusions This is one of the few community-based family studies of potential neurocognitive endophenotypes that includes the full range of mood disorder subgroups. There were few differences in neurocognitive function except enhanced accuracy in specific domains among those with BP-I and MDD. The differential findings across specific mood disorder subgroups substantiate their heterogeneity in other biologic and endophenotypic domains.

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Section: Discussionmentioning

confidence: 87%

Neurocognitive performance as an endophenotype for mood disorder subgroups

Merikangas

Cui

Calkins

et al. 2017

Journal of Affective Disorders

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“…Major depression affects the structure, connectivity, and biochemistry of several, especially frontal brain areas implicated in cognitive control, emotion regulation, and memory processing [94]. Several studies have robustly shown evidence of grey matter reduction in the ACC [95][96][97].…”

Section: Depressive Spectrum: Subclinical To Clinicalmentioning

confidence: 99%

Brain Structure and Subclinical Symptoms: A Dimensional Perspective of Psychopathology in the Depression and Anxiety Spectrum

2019

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Human psychopathology is the result of complex and subtle neurobiological alterations. Categorial DSM or ICD diagnoses do not allow a biologically founded and differentiated description of these diverse processes across a spectrum or continuum, emphasising the need for a scientific and clinical paradigm shift towards a dimensional psychiatric nosology. The subclinical part of the spectrum is, however, of special interest for early detection of mental disorders. We review the current evidence of brain structural correlates (grey matter volume, cortical thickness, and gyrification) in non-clinical (psychiatrically healthy) subjects with minor depressive and anxiety symptoms. We identified 16 studies in the depressive spectrum and 20 studies in the anxiety spectrum. These studies show effects associated with subclinical symptoms in the hippocampus, anterior cingulate cortex, and anterior insula similar to major depression and changes in amygdala similar to anxiety disorders. Precuneus and temporal areas as parts of the default mode network were affected specifically in the subclinical studies. We derive several methodical considerations crucial to investigations of brain structural correlates of minor psycho(patho)logical symptoms in healthy participants. And we discuss neurobiological overlaps with findings in patients as well as distinct findings, e.g. in areas involved in the default mode network. These results might lead to more insight into the early pathogenesis of clinical significant depression or anxiety and need to be enhanced by multi-centre and longitudinal studies.

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“…Furthermore, several genetic variants that influence brain structure have been identified 10,11 . Subcortical brain volume and WM microstructure abnormalities in corticostriatal and limbic networks have also been shown to distinguish individuals with SCZ, BD and MDD from controls in several studies, albeit with some inconsistencies [12][13][14][15][16][17] . Differences between patients and controls in global measures of WM microstructure, diffusion tensor imaging (DTI) biomarkers fractional anisotropy (FA) and mean diffusivity (MD), have been more consistently reported in these disorders [18][19][20][21][22][23] , and could suggest wide-spread WM integrity reductions.…”

Section: Introductionmentioning

confidence: 99%

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank

Reus

Shen

Gibson

et al. 2016

Preprint

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Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks.Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with major psychiatric disorders is unknown.We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data compromised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). Our, findings however, indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. In the current study, we found little or no evidence for genetic overlap between major psychiatric disorders and structural brain measures. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders.not peer-reviewed)

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Molecular, Functional, and Structural Imaging of Major Depressive Disorder

Cited by 68 publications

References 132 publications

Neurocognitive performance as an endophenotype for mood disorder subgroups

Neurocognitive performance as an endophenotype for mood disorder subgroups

Brain Structure and Subclinical Symptoms: A Dimensional Perspective of Psychopathology in the Depression and Anxiety Spectrum

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank

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