Research paper
Intrinsic gray-matter connectivity of the brain in major depressive disorder

https://doi.org/10.1016/j.jad.2019.01.048Get rights and content

Highlights

Abstract

Background

Major depressive disorder (MDD) has been assumed to be associated with aberrant brain connectivity. However, research suggests that brain connectivity abnormalities should not be restricted to extrinsic white matter connectivity, but may also impact on intrinsic gray matter connectivity. Therefore, our study aimed to investigate the intrinsic gray-matter connectivity in MDD.

Methods

The participants were 16 first-episode, drug-naïve patients with MDD and 16 healthy controls matched on age and gender. All participants were scanned by 3.0T structural magnetic resonance imaging. Global and local intrinsic gray-matter connectivity were measured based on surface-based geodesic distances, including mean coritical separation distances (MSDs), perimeter function, and radius function.

Results

MDD patients had significantly lower MSDs in the left postcentral gyrus and higher MSDs in the left superior parietal cortex. Marginally significant correlation was observed between MSDs in the left postcentral gyrus and symptoms of depression. Compared with healthy controls, depressed subjects had abnormal local intrinsic gray-matter connectivity in the left postcentral gyrus, the left transverse temporal gyrus, the right lingual gyrus, the right lateral occipital cortex, and the right superior frontal gyrus. Furthermore, local intrinsic gray matter connections of these brain areas were associated with some symptoms of depression.

Limitations

The small sample size limited the interpretability of our potential conclusions.

Conclusion

Aberrant intrinsic gray-matter connectivity was observed in depressed subjects, indicating abnormal intrinsic wiring cost of brain architecture. This might help explain the aberrant topological properties of brain functional connectivity and provide insights into the vulnerability of MDD.

Introduction

Major depressive disorder (MDD) is the most common psychiatric disorder and is characterized by affective, thought, cognitive, and somatic symptoms (American Psychiatric Association [AMA], 2013), which have seriously disabling risks and disease burdens (Whiteford et al., 2013). Research has provided considerable evidence demonstrating that MDD is accompanied by anatomical and functional brain abnormalities in areas associated with emotional or cognitive processing (Gong and He, 2015, Shen et al., 2015, Zhang et al., 2016), including the prefrontal cortex (Shan et al., 2017), the hippocampus (Carballedo et al., 2013, Phillips et al., 2015), the anterior cingulate cortex (Sambataro et al., 2017), and the amygadala (Ambrosi et al., 2017). Moreover, numerous neuroimaging studies have found that depressed patients have abnormal topological features in gray matter networks, including the default mode network (Guo et al., 2018, Peng et al., 2015a, Demirtaş et al., 2016), the frontoparietal network (Demirtaş et al., 2016), and the limbic regions (Jaworska et al., 2016). However, the specific psychopathological mechanism of MDD still remains to be elucidated.

A considerable body of genetic-neuroimaging studies suggests that depressed patients with brain-derived neurotrophic factor (BDNF) Met allele have abnormal cortical volume, thickness and surface area (Cardoner et al., 2013, Gonul et al., 2010, Legge et al., 2015). This abnormal brain architecture may derive from genetic architecture variations via underlying molecular and cellular mechanisms (Ryan et al., 2016, Won and Ham, 2016), and is capable of mediating cytosketetal changes, such as cell adhesion, axonal outgrowth, dendritic maturation and synaptic connection (Park and Poo, 2013). For instance, BDNF could increase axon and dendrite growth within 4.5 μm of the site of BDNF secretion (Horch and Katz, 2002). Furthermore, intrinsic axon collaterals can form long-distance connections along the cortical surface in specific regions (Melchitzky et al., 2001). The whole brain is interconnected by different modular organization, from synaptic connections of coupled neurons to whole-brain structural networks linked by white-matter fiber tracts (Budd and Kisvarday, 2012, Lee et al., 2016). Structural connectivity may be modulated by cytoarchitecture and intrinsic connectivity within cortices (Opris, 2013, Opris and Casanova, 2014).

Considering the above findings, we hypothesized that abnormal brain structural connections in MDD may not be confined to extrinsic white-matter connectivity by global and regional white matter fiber tracts, but may also be modulated by abnormal intrinsic synaptic connections of coupled neurons. Intrinsic connections are an important focus because substantial evidence suggests that intrinsic neuronal interactions impose strong constraints on brain function (Lee et al., 2016, Park and Friston, 2013). For example, Lee et al. (2016) found that neurons with similar orientation preferentially formed larger synapses along the gray matter, which could improve the net effect of synaptic specificity. Given that brain structure and function alterations in MDD are associated with the severity of depressive symptoms (Drysdale et al., 2017, Schmaal et al., 2017), MDD could be associated with alterations in intrinsic cortical connections. However, the majority of neuroimaging studies in MDD have focused on extrinsic connectivity by tracing white matter fiber (Bergamino et al., 2017, Ugwu et al., 2014, Won et al., 2016). In contrast, measuring intrinsic cortico-cortical connectivity has received little attention perhaps because intrinsic cortico-cortical connections are difficult to measure in vivo by conventional measures of brain volume or thickness. However, given that physical or geometric distance is the only method of measuring the inter-neuronal distance (Avena-Koenigsberger et al., 2017), cortical separation distances can be used to investigate the intrinsic cortico-cortical connections. For instance, Ecker et al. (2013) used cortical separation distances to explore the intrinsic gray-matter connections in Autism.

Cortical separation distance is defined as the minimum length linking two vertices on the cortical surface, which is parallel with the intrinsic horizontal gray-matter connections. Wiring cost is defined as the cost of maintaining anatomical connections between neurons, and indicates the shortest distances of intrinsic gray-matter connections required to wire the cortex within the cortical sheet. Mean separation distances (MSDs), reflect the average cortical separation distances from a vertex to the rest of the surface, and are thought to reflect the intrinsic cortico-cortical connections and the intrinsic wiring cost on the global level (Griffin, 1994). Local intrinsic cortico-cortical connections can be assessed within a geodesic circle, including the radius of the circle and the perimeter of the circle. The radius of a geodesic circle indicates the intra-areal wiring cost, whereas the perimeter of a geodesic circle is a measure of inter-areal wiring cost (Ecker et al., 2013, Griffin, 1994).

In the present study, we aimed to investigate the intrinsic gray-matter connectivity of the brain in individuals with MDD and healthy controls by measuring cortical separation distances. Our study estimated both the global and local levels of cortical separation distances for each vertex, including the mean separation distances (MSDs), and radius and perimeter of a geodesic circle. Based on aberrant brain morphology in MDD, our study hypothesized that MDD patients would show significantly abnormal global and local cortical separation distances relative to healthy controls, and that these cortical surface-based geodesic distances would be associated with symptom severity as measured by the 24-item Hamilton Depression Scale (24-HAMD, Hamilton, 1967, Zhang, 1998).

Section snippets

Subjects

Sixteen first episode, drug-naïve MDD patients and sixteen gender- and age- matched healthy controls were included in this study. Unmedicated MDD patients were recruited from outpatient clinics at the Shanghai Mental Health Center and Huashan Hospital, China. Matched healthy controls were recruited from the community via advertisement. All participants were interviewed independently by two psychiatrists using the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental

Demographic characteristics

There were no significant differences between MDD subjects and healthy controls (HC) in age (34.43 ± 6.72 years vs. 33.75 ± 6.36 years, p > 0.05), gender distribution (male:female, 7:9 vs. 7:9, p > 0.05), and education level (15.63 ± 1.99 years vs. 15.81 ± 2.48 years, p > 0.05). Compared with healthy controls, depressed patients showed significantly higher scores on both the 24-item HAMD and HAMA (p < 0.0001) (Table 1).

Comparison between MDD and HC in MSDs

Both MDD and HC had considerable variations in MSDs across the cortical

Discussion

Previous studies have suggested that the human brain is an intricate anatomical neural network interconnected by intrinsic gray-matter connectivity and extrinsic white-matter connectivity (Avena-Koenigsberger et al., 2017, Sporns and Betzel, 2016). A substantial number of studies have focused on extrinsic white-matter connections using diffusion tensor imaging (DTI) measures (Bergamino et al., 2017, Liao et al., 2013, Ugwu et al., 2014). However, measuring intrinsic cortico-cortical

Conclusion

In conclusion, our study found that MDD patients had abnormally intrinsic gray matter connectivity both at the global level and the local level. These findings support the notion that MDD is associated with abnormal intrinsic gray matter connectivity, though the precise mechanism of this abnormal brain architecture remains elusive. Furthermore, intrinsic cortico-cortical connections were correlated with some depressed symptoms, indicating that symptoms of depression may derive from the

Declarations of interest

All authors claim that there are no conflicts of interest.

Funding statement

This work was supported by the National Natural Science Foundation of China [grant number: 81571327]; the Science and Technology Commission of Shanghai Municipality [grant number: 201640003]; Guiding Medical Project of Shanghai Science and Technology Committee [grant number: 16411965300]; and the National Key Research and Development Program [grant number: 2016YFC0906400].

There are none any relevant conflicts of interest in our study.

Author statement contributors

Study design and supervision: Daihui Peng, Ting Shen; Acquisition and collection of data: Huifeng Zhang, Meihui Qiu, Lei Ding; Analysis and interpretation of data: all authors; Drafting of the manuscript: Huifeng Zhang, Meihui Qiu, Lei Ding, Daihui Peng, Ting Shen; Critical revision of the manuscript: all authors; data processing technical support: David Mellor, Gang Li, Daihui Peng, Ting Shen.

All authors have seen and approved the final version of the manuscript being submitted. All authors

Acknowledgments

The authors appreciate all participants who made contributions to our study for their generous participation, and researchers who helped to process the data in Department of Radiology (University of North Carolina, Chapel Hill, NC, USA)

References (53)

  • E. Won et al.

    Imaging genetics studies on monoaminergic genes in major depressive disorder

    Prog. Neuro-psychopharmacol. Biol. Psychiatry

    (2016)
  • J. Zhang et al.

    Disrupted brain connectivity networks in drug-naive, first-episode major depressive disorder

    Biol. Psychiatry

    (2011)
  • E. Ambrosi et al.

    Insula and amygdala resting-state functional connectivity differentiate bipolar from unipolar depression

    Acta Psychiatr Scand

    (2017)
  • Diagnostic and Statistical Manual of Mental Disorders (DSM-5®)

    (2013)
  • A. Avena-Koenigsberger et al.

    Communication dynamics in complex brain networks

    Nat. Rev. Neurosci.

    (2017)
  • J.M. Budd et al.

    Communication and wiring in the cortical connectome

    Front Neuroanat.

    (2012)
  • E. Bullmore et al.

    The economy of brain network organization

    Nat. Rev. Neurosci.

    (2012)
  • D.P. Buxhoeveden et al.

    The minicolumn hypothesis in neuroscience

    Brain

    (2002)
  • A. Carballedo et al.

    Brain-derived neurotrophic factor Val66Met polymorphism and early life adversity affect hippocampal volume

    Am. J. Med. Genet. B Neuropsychiatr. Genet.

    (2013)
  • N. Cardoner et al.

    Val66met Bdnf genotypes in melancholic depression: effects on brain structure and treatment outcome

    Depress. Anxiety

    (2013)
  • D.B. Chklovskii

    Exact Solution For the Optimal Neuronal Layout Problem

    (2004)
  • M. Demirtaş et al.

    Dynamic functional connectivity reveals altered variability in functional connectivity among patients with major depressive disorder

    Hum. Brain Mapp.

    (2016)
  • A.T. Drysdale et al.

    Resting-state connectivity biomarkers define neurophysiological subtypes of depression

    Nat. Med.

    (2017)
  • C. Ecker et al.

    Intrinsic gray-matter connectivity of the brain in adults with autism spectrum disorder

    Proc. Natl. Acad. Sci. U S A

    (2013)
  • A.S. Gonul et al.

    Association of the brain-derived neurotrophic factor Val66Met polymorphism with hippocampus volumes in drug-free depressed patients

    World J. Biol. Psychiatry

    (2010)
  • M. Hamilton

    Development of a rating scale for primary depressive illness

    Br. J. Soc. Clin. Psychol.

    (1967)
  • Cited by (0)

    1

    Huifeng Zhang and Meihui Qiu are the joint first author.

    View full text