Research reportCortical abnormalities and association with symptom dimensions across the depressive spectrum
Introduction
Biomarkers based on neuroimaging techniques noninvasively visualize brain abnormalities implicated in major depressive disorder (MDD) and are well-suited to guide the development of novel treatments, assess treatment response, and tailor treatment approaches to biological subtypes of depression (Lener and Iosifescu, 2015, Niciu et al., 2014). Structural MRI methods using cortical parcellation and morphometic analysis have allowed for the examination of subtle morphometric brain changes (eg., cortical thickness and surface area) (Tu et al., 2012, Qiu et al., 2014, Han et al., 2014). Through the application of FreeSurfer (Fischl, 2012), voxel-based morphometry (VBM), and voxel-based analysis (VBA) have allowed for the detection of subtle structural abnormalities in MDD within prefrontal, temporal, and limbic areas compared to healthy volunteers (Lorenzetti et al., 2009, Kempton et al., 2011, Bora et al., 2012, Du et al., 2012, Lai, 2013, Sacher et al., 2012).
Given the importance of early identification of individuals at risk for depression, studies have sought to identify whether specific brain structural abnormalities can be seen prior to onset of illness. Cross-sectional studies of unaffected first-degree relatives of patients with MDD have shown volumetric reductions in the hippocampus (Foland-Ross et al., 2015) and increases in the amygdala (Romanczuk-Seiferth et al., 2014) compared to non-depressed cohorts without familial risk. In a longitudinal study of 86 adolescents, emergence of depression was associated with attenuated growth of the hippocampus during early to mid-adolescence, suggesting that brain volumetric changes in individuals at high risk for depression occur prior to the onset of depression (Whittle et al., 2014). In a large study of a large sample of unmedicated depressed adult patients (N=103), number of depressive episodes was associated with volumetric reduction in the dentate gyrus and medial prefrontal cortex (Treadway et al., 2015). And, in a study of a large sample of healthy volunteers (N=102), male but not female subjects with subclinical symptoms of depression (measured by the Beck Depression Inventory), showed volumetric reductions in limbic areas (Spalletta et al., 2014). Taken together, this suggests that structural abnormalities in prefrontal cortical and limbic areas, associated with symptoms of depression, may serve as a biomarker of risk for the development of MDD (Treadway et al., 2015).
Moreover, although many structural neuroimaging studies of MDD have examined associations between structural brain abnormalities and clinical variables (eg., age at illness onset, duration of illness, number of episodes, length of remission, effect of medication, and severity of the current depressive episode) (Lorenzetti et al., 2009, Bora et al., 2012, Du et al., 2012, Lai, 2013, Grieve et al., 2013), few have examined specific symptom or behavioral dimensions of depressive illness (Chuang et al., 2014, Machino et al., 2014, Pizzagalli et al., 2004, Joffe et al., 2009). In prior studies, prominent anhedonia in patients with MDD has been associated with a significant reduction in overall gray matter density by age compared to MDD patients without anhedonia and a healthy control group (Pizzagalli et al., 2004). Negative symptoms (eg., blunted affect, alogia, and social withdrawal) have been associated with a significant reduction in gray matter volume in the cerebellum (Chuang et al., 2014). Rumination, the non-productive compulsive attention to internal mental distress (Treynor et al., 2003), has been associated with increased gray matter volume in the right superior temporal gyrus in patients who have failed two or more trials of antidepressants (ie., treatment-resistant depression) (Machino et al., 2014). In MDD patients with high levels of neuroticism, trait depression, and chronic stress, the effect of hippocampal volume reduction was mediated by BDNF 66Met carrier status (Joffe et al., 2009). If replicated, this may provide genetic links between stress-related brain morphometric changes and risk of onset or recurrence of depression.
Based on the National Institute of Mental Health (NIMH) Research Domain Criteria (R-DoC) initiative (Insel et al., 2010), the categorization of symptoms into domains or dimensions (eg., emotion regulation, cognitive processing systems, memory processing, and perception) has been proposed to investigate underlying neural circuits and systems emerging from a wide array of research techniques (eg., neuroimaging, genetics, electrophysiology, etc.). From this framework, links could be examined between structural and functional brain abnormalities, pathophysiologic mechanisms, risk of illness, and likelihood of treatment response. For example, fMRI studies measuring neural activity in response to the induction of rumination have shown hyperactivity in the subgenual anterior cingulate cortex (sgACC) and dorso-medial prefrontal cortex (dmPFC) (Kross et al., 2009, Lemogne et al., 2009, Yoshimura et al., 2010), and hypoactivity in the dorsomedial thalamus and ventral striatum (Grimm et al., 2009). In a meta-analysis of fMRI studies examining neural activation correlates of antidepressant treatment response, increased neural activity in the rostral anterior cingulate cortex (rACC) predicted an antidepressant response across 23 studies using different treatment interventions (Pizzagalli, 2011). In a recently fMRI study from our group, patients with treatment-resistant depression, in contrast to a healthy comparison group, showed reduced neural responses to positive faces in the right caudate, which appeared to increase in association with an antidepressant response to ketamine within a similar region of the right caudate (Murrough et al., 2015). Yet, in the clinical setting, the diagnosis of MDD is based on the coexistence of discrete symptoms taken from the Diagnostic and Statistical Manual of Mental Disorders (i.e. DSM) (Association American Psychiatric, 2013). Therefore, in order to implement neuroimaging biomarkers of depression as part of diagnostic algorithm in the clinical setting, a rapid and valid method of detecting patients at high risk for depression is necessary.
In order to examine structural imaging biomarkers of depression, we performed an MRI study on 57 MDD patients and 29 healthy control subjects (HC) at 3T and investigated whether differences in cortical regions found in patients with MDD were linked to symptom domains of MDD, measured by the visual analog scale (VAS), across the depressive spectrum. The VAS is a well-validated scale apt in discriminating illness severity (Folstein and Luria, 1973, Killgore, 1999) that can be rapidly self-administered.
Section snippets
Overall approach
We were interested in examining whether regionally specific structural differences found in MDD are (1) specific to individual symptoms of depression, and (2) are also found in non-depressed individuals who exhibit sub-clinical depressive symptoms. Our analytic approach consisted of a data-driven whole-brain cortical morphometric analysis comparing cortical volume (CV), surface area (SA), and cortical thickness (CT) in patients with MDD and HC. Extracted regions showing significant differences
Participants
Institutional Review Board (IRB) approval for this study was obtained. Fifty-seven MDD patients and 29 healthy volunteers were recruited and screened through the Mood and Anxiety Disorders Program (MAP) at Mount Sinai. All MDD patients who met current criteria for a major depressive episode, as assessed with the Structured Clinical Interview for DSM-IV—Patient Edition (FIrst et al., 1995), were free of concurrent antidepressant medication for at least 1 week before imaging and had current
Demographics and clinical characteristics
The MDD and HC groups had no significant differences in age, gender, race, handedness, or level of education. As expected, the HC group demonstrated significantly lower MADRS and VAS scores than the MDD group (Table 1).
Whole-brain analysis
Table 2 summarizes significant differences in cortical morphometry (CV, CT, and SA). Compared to HC, MDD patients had reduced CV in the pars triangularis (within a section commonly known as the ventrolateral prefrontal cortex, VLPFC), the entorhinal cortex, the parahippocampal
Conclusion
In the current study, specific morphometric reductions found in patients with MDD correlate with specific behavioral dimensions of depression across a clinical spectrum. Our main findings were that cortical volume is reduced within the VLPFC and that this reduction correlates with discrete behavioral dimensions in the depressive spectrum as measured by VAS. While previous studies have investigated the relationship between structural neuroimaging abnormalities and symptom domains of depression (
Conflicts of interest
There are no conflicts of interest to declare for all authors related to this current study. In the past 3 years, Dr. Murrough has served on advisory boards for Janssen Research and Development and Genentech, has provided consultation services for ProPhase, LLC and Impel Neuropharma and has received research support from Janssen and Avanir Pharmaceuticals; he is named on a patent pending for neuropeptide Y as a treatment for mood and anxiety disorders, on a patent pending for the combination of
Contributors
Drs. Marc Lener and James Murrough conceived the idea, and designed and executed the study. Mr. Wong and Dr. Lener conducted the brain cortical analysis and Dr. Kundu conducted the multiple comparisons correction in consultation with Drs. Balchandani, Tang, and Murrough who reviewed the manuscript, suggested further analyses and interpreted the results along with other authors. Ms. DeWilde provided database support. All authors took part in going through the manuscript carefully.
Role of funding source
This work was supported by the National Institute of Mental Health of the National Institutes of Health under Award number K23MH094707 (Career Development Award to JWM). Support was also provided by the Iris & Junming Le Foundation (Award to Dr. Murrough), by the Brain and Behavior Research Foundation (NARSAD grant to Dr. Murrough) and by grant UL1TR000067 from the NIH National Center for Advancing Translational Sciences to Mount Sinai. The content is solely the responsibility of the authors
Acknowledgments
We thank Drs. Dan Iosifescu M.D., Katherine Collins Ph.D., and Brian Iacoviello Ph.D. and the clinical staff at the Mood and Anxiety Disorders Program for their assistance in diagnostic and psychopathological assessments. We thank Dr. Cheuk Tang and the Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai. We thank Dr. Dennis Charney M.D. for helpful advice. Funding agencies did not have any further role in the analysis and reporting
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2021, Psychiatry Research - NeuroimagingCitation Excerpt :The latter finding, which aligns with literature reporting smaller DLPFC volume across clinical disorders, suggests associations between RNT and DLPFC volume may depend upon RNT severity. Similarly, we observed the same pattern of divergent results between RNT severity and VLPFC volume (Lener et al., 2016; Qiao et al., 2013) – a region closely coupled with the DLPFC. Taken together the results are consistent with findings from the cognitive literature, which suggest that while pathological levels of negative cognitive processes are associated with maladaptive outcomes, moderate levels (in some circumstances) may beneficial (e.g. Eysenck et al., 2007).
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2021, Journal of the American Academy of Child and Adolescent PsychiatryCitation Excerpt :The phenomenological experience of anxiety includes the inability to halt irrelevant cognitions, but the translation to cortical thickness effects requires additional clinical data on cognitive processing to assess this possibility. Of note, this is 1 of only a few studies that examine whole-brain associations between anxiety or mood symptoms and gray matter metrics in youths, as the vast majority of studies have focused on a priori−defined regions of interest,7,20,21,23,26,30,31 despite existing evidence of widespread, systemic effects of symptoms on cortical morphology.18,22,27,28,32 Our own examination of regionally specific effects largely corroborated this prior work.