CoChat
Sign Up
Cited by 29Treatment of Major DepressionNeural and Behavioral Psychology StudiesNeurotransmitter Receptor Influence on Behavior

Increased Cortical Thickness in Patients With Major Depressive Disorder Following Antidepressant Treatment

Open access
Nemati, Samaneh, Abdallah, Chadi G.·2020·Chronic Stress
DOI 10.1177/2470547019899962PMC PMC6959134
Open this paper in CoChat — free account

Abstract

Background: Considering the slow-acting properties of traditional antidepressants, an important challenge in the field is the identification of early treatment response biomarkers. Reduced cortical thickness has been reported in neuroimaging studies of depression. However, little is known whether antidepressants reverse this abnormality. In this brief report, we investigated early cortical thickness changes following treatment with sertraline compared to placebo. Methods: Participants (n = 215) with major depressive disorder were randomized to a selective serotonin reuptake inhibitor, sertraline, or to placebo. Structural magnetic resonance imaging scans were acquired at baseline and one week following treatment. Response was defined as at least 50% improvement in Hamilton rating scale for depression score at week 8. In a vertex-wise approach, we examined the effects of treatment, response, and treatment × response. Results: Following correction for multiple comparisons, we found a significant effect of treatment, with widespread increase in cortical thickness following sertraline compared to placebo. Clusters with increased thickness were found in the left medial prefrontal cortex, right medial and lateral prefrontal cortex, and within the right parieto-temporal lobes. There were no sertraline-induced cortical thinning, and no significant response effects or treatment × response interactions. Conclusion: Our findings suggest that cortical thickness abnormalities may be responsive to antidepressant treatment. However, a relationship between these early cortical changes and later treatment response was not demonstrated. Future studies would be needed to investigate whether those early effects are maintained at eight weeks and are associated with enhanced response.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1177/2470547019899962

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • In imaging studies of traditional antidepressant treatment response, increased cortical thickness and cerebral blood flow in the PFC correlate with efficacy.

    “In imaging studies of traditional antidepressant treatment response, increased cortical thickness and cerebral blood flow in the PFC correlate with efficacy (108–112).”

    From Psychedelics and Other Psychoplastogens for Treating Mental Illness. (2021) · cites this paper as [112]

    The Discussion (page unavailable) reports increased thickness in a prefrontal region after sertraline treatment and describes another study linking increased anterior cingulate thickness to treatment response. But this paper says its own early thickness changes did not predict later response. It does not report that increased prefrontal cerebral blood flow correlates with efficacy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 39

  1. [1]Kessler RC Berglund P Demler O Jin R Merikangas KR Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005; 62: 593–602. 15939837
  2. [2]Caspi A Sugden K Moffitt TE et al Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science. 2003; 301: 386– 389. 12869766
  3. [4]McGrath CL Kelley ME Holtzheimer PE et al Toward a neuroimaging treatment selection biomarker for major depressive disorder. JAMA Psychiatry. 2013; 70: 821– 829. 23760393 PMC4413467
  4. [5]Abdallah CG Sanacora G Duman RS Krystal JH. Ketamine and rapid-acting antidepressants: a window into a new neurobiology for mood disorder therapeutics. Annu Rev Med. 2015; 66: 509– 523. 25341010 PMC4428310
  5. [8]van Eijndhoven P van Wingen G Katzenbauer M et al Paralimbic cortical thickness in first-episode depression: evidence for trait-related differences in mood regulation. Am J Psychiatry. 2013; 170: 1477–14 86. 23929204
  6. [9]Järnum H Eskildsen SF Steffensen EG et al Longitudinal MRI study of cortical thickness, perfusion, and metabolite levels in major depressive disorder. Acta Psychiatr Scand. 2011; 124: 435– 446. 21923809
  7. [10]Na K-S Chang HS Won E et al Association between glucocorticoid receptor methylation and hippocampal subfields in major depressive disorder. PLoS One. 2014; 9: e85425. 24465557 PMC3897456
  8. [11]Li M Metzger CD Li W et al Dissociation of glutamate and cortical thickness is restricted to regions subserving trait but not state markers in major depressive disorder. J Affect Disord. 2014; 169: 91– 100. 25173431
  9. [12]Tu P-C Chen L-F Hsieh J-C Bai Y-M Li C-T Su T-P. Regional cortical thinning in patients with major depressive disorder: a surface-based morphometry study. Psychiatry Res. 2012; 202: 206– 213. 22521631
  10. [13]Lener MS Kundu P Wong E et al Cortical abnormalities and association with symptom dimensions across the depressive spectrum. J Affect Disord. 2016; 190: 529– 536. 26571102 PMC4764252
  11. [14]Papmeyer M Giles S Sussmann JE et al Cortical thickness in individuals at high familial risk of mood disorders as they develop major depressive disorder. Biol Psychiatry. 2015; 78: 58– 66. 25534753
  12. [15]Meier TB Drevets WC Wurfel BE et al Relationship between neurotoxic kynurenine metabolites and reductions in right medial prefrontal cortical thickness in major depressive disorder. Brain Behav Immun. 2016; 53: 39– 48. 26546831 PMC4783304
  13. [16]Won E Choi S Kang J Lee M-S Ham B-J. Regional cortical thinning of the orbitofrontal cortex in medication-naïve female patients with major depressive disorder is not associated with MAOA-uVNTR polymorphism. Ann Gen Psychiatry. 2016; 15: 26. 27752275 PMC5062832
  14. [17]Qiu L Lui S Kuang W et al Regional increases of cortical thickness in untreated, first-episode major depressive disorder. Translat Psychiatry. 2014; 4: e378. PMC4012282 24713859
  15. [18]Reynolds S Carrey N Jaworska N Langevin LM Yang X-R MacMaster FP. Cortical thickness in youth with major depressive disorder. BMC Psychiatry. 2014; 14: 83. 24645731 PMC3994552
  16. [19]Han K-M Choi S Jung J et al Cortical thickness, cortical and subcortical volume, and white matter integrity in patients with their first episode of major depression. J Affect Disord. 2014; 155: 42– 48. 24210630
  17. [20]Koolschijn PCM van Haren NE Schnack HG Janssen J Pol HEH Kahn RS. Cortical thickness and voxel-based morphometry in depressed elderly. Eur Neuropsychopharmacol. 2010; 20: 398– 404. 20227249
  18. [22]Sartorius A Demirakca T Böhringer A et al Electroconvulsive therapy increases temporal gray matter volume and cortical thickness. Eur Neuropsychopharmacol. 2016; 26: 506– 517. 26792445
  19. [23]Trivedi MH McGrath PJ Fava M et al Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): rationale and design. J Psychiatr Res. 2016; 78: 11– 23. 27038550 PMC6100771
  20. [24]Greenberg T Chase HW Almeida JR et al Moderation of the relationship between reward expectancy and prediction error-related ventral striatal reactivity by anhedonia in unmedicated major depressive disorder: findings from the EMBARC study. Am J Psychiatry. 2015; 172: 881– 891. 26183698 PMC4858169
  21. [25]Glasser MF Sotiropoulos SN Wilson JA et al The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage. 2013; 80: 105– 124. 23668970 PMC3720813
  22. [26]Abdallah CG Dutta A Averill CL et al Ketamine, but not the NMDAR antagonist lanicemine, increases prefrontal global connectivity in depressed patients. Chronic Stress (Thousand Oaks). 2018; 2: 2470547018796102. PMC6154502 30263977
  23. [28]Saricicek Aydogan A Oztekin E Esen ME et al Cortical thickening in remitters compared to non‐remitters with major depressive disorder following 8‐week antidepressant treatment. Acta Psychiatr Scand. 2019; 140: 217– 226. 31250445
  24. [29]Bush G Luu P Posner MI. Cognitive and emotional influences in anterior cingulate cortex. Trends Cogn Sci. 2000; 4: 215– 222. 10827444
  25. [30]Li R Ma Z Yu J He Y Li J. Altered local activity and functional connectivity of the anterior cingulate cortex in elderly individuals with subthreshold depression. Psychiatry Res. 2014; 222: 29– 36. 24656767
  26. [31]Brooks JO III Foland-Ross LC Thompson PM Altshuler LL. Preliminary evidence of within-subject changes in gray matter density associated with remission of bipolar depression. Psychiatry Res. 2011; 193: 53– 55. 21561743 PMC3986411
  27. [32]Oertel-Knöchel V Reuter J Reinke B et al Association between age of disease-onset, cognitive performance and cortical thickness in bipolar disorders. J Affect Disord. 2015; 174: 627– 635. 25577157
  28. [33]Dannlowski U Ohrmann P Konrad C et al Reduced amygdala–prefrontal coupling in major depression: association with MAOA genotype and illness severity. Int J Neuropsychopharmacol. 2009; 12: 11– 22. 18544183
  29. [34]Oda K Okubo Y Ishida R et al Regional cerebral blood flow in depressed patients with white matter magnetic resonance hyperintensity. Biol Psychiatry. 2003; 53: 150– 156. 12547471
  30. [35]Lawrence NS Williams AM Surguladze S et al Subcortical and ventral prefrontal cortical neural responses to facial expressions distinguish patients with bipolar disorder and major depression. Biol Psychiatry. 2004; 55: 578– 587. 15013826
  31. [36]Van Tol M-J Li M Metzger C et al Local cortical thinning links to resting-state disconnectivity in major depressive disorder. Psychol Med. 2014; 44: 2053– 2065. 24176247
  32. [37]Cotter D Mackay D Chana G Beasley C Landau S Everall IP. Reduced neuronal size and glial cell density in area 9 of the dorsolateral prefrontal cortex in subjects with major depressive disorder. Cereb Cortex. 2002; 12: 386– 394. 11884354
  33. [38]Rajkowska G Miguel-Hidalgo JJ Wei J et al Morphometric evidence for neuronal and glial prefrontal cell pathology in major depression. Biol Psychiatry. 1999; 45: 1085– 1098. 10331101
  34. [39]Li BJ Friston K Mody M Wang HN Lu HB Hu DW. A brain network model for depression: from symptom understanding to disease intervention. CNS Neurosci Therapeut. 2018; 24: 1004– 1019. PMC6490158 29931740
  35. [40]Abdallah CG Averill LA Collins KA et al Ketamine treatment and global brain connectivity in major depression. Neuropsychopharmacology. 2017; 42: 1210– 1219. 27604566 PMC5437875
  36. [41]Alexopoulos GS Hoptman MJ Kanellopoulos D Murphy CF Lim KO Gunning FM. Functional connectivity in the cognitive control network and the default mode network in late-life depression. J Affect Disord. 2012; 139: 56– 65. 22425432 PMC3340472
  37. [42]Greicius MD Flores BH Menon V et al Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry. 2007; 62: 429– 437. 17210143 PMC2001244
  38. [43]Berman MG Misic B Buschkuehl M et al Does resting-state connectivity reflect depressive rumination? A tale of two analyses. Neuroimage. 2014; 103: 267– 279. 25264228
  39. [44]Hecht D. Depression and the hyperactive right-hemisphere. Neurosci Res. 2010; 68: 77– 87. 20603163

Cited by

Sorted by citations

Authors
Nemati, S., & Abdallah, C. G.
Affiliations
United States Department of Veterans Affairs (US)
Corresponding author
Abdallah, Chadi G.
ORCID
Venue
Chronic Stress
Publisher
SAGE Publications
Published
2020-01
Volume
4
ISSN
2470-5470 (ISSN-L)
DOI
10.1177/2470547019899962
PMC
PMC6959134
OpenAlex
W2999247284
Cited by
29
References
5
Citations by year
2026: 3 · 2025: 5 · 2024: 6 · 2023: 4 · 2022: 6 · 2021: 2 · 2020: 3
FWCI
2.25
Type
journal article
Language
en
Open access
Licence
Locations
  • Chronic Stress (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Institute of Mental Health (K23MH101498)
  • VA National Center for PTSD
Topics
  • Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
Keywords
major depressive disorder, cortical thickness, sertraline, antidepressant response, selective serotonin reuptake inhibitors, treatment response biomarkers, medial prefrontal cortex, cortical thinning, structural neuroimaging

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review