Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study
BackgroundMajor depressive disorder (MDD) is a prevalent health problem with complex pathophysiology that is not clearly understood. Prior work has implicated the hippocampus in MDD, but how hippocampal subfields influence or are affected by MDD requires further characterization with high-resolution...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1060770/full |
| _version_ | 1797934963579944960 |
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| author | Judy Alper Judy Alper Rui Feng Gaurav Verma Sarah Rutter Kuang-han Huang Long Xie Paul Yushkevich Yael Jacob Stephanie Brown Marin Kautz Molly Schneider Hung-Mo Lin Lazar Fleysher Bradley N. Delman Patrick R. Hof James W. Murrough James W. Murrough Priti Balchandani |
| author_facet | Judy Alper Judy Alper Rui Feng Gaurav Verma Sarah Rutter Kuang-han Huang Long Xie Paul Yushkevich Yael Jacob Stephanie Brown Marin Kautz Molly Schneider Hung-Mo Lin Lazar Fleysher Bradley N. Delman Patrick R. Hof James W. Murrough James W. Murrough Priti Balchandani |
| author_sort | Judy Alper |
| collection | DOAJ |
| description | BackgroundMajor depressive disorder (MDD) is a prevalent health problem with complex pathophysiology that is not clearly understood. Prior work has implicated the hippocampus in MDD, but how hippocampal subfields influence or are affected by MDD requires further characterization with high-resolution data. This will help ascertain the accuracy and reproducibility of previous subfield findings in depression as well as correlate subfield volumes with MDD symptom scores. The objective of this study was to assess volumetric differences in hippocampal subfields between MDD patients globally and healthy controls (HC) as well as between a subset of treatment-resistant depression (TRD) patients and HC using automatic segmentation of hippocampal subfields (ASHS) software and ultra-high field MRI.MethodsThirty-five MDD patients and 28 HC underwent imaging using 7-Tesla MRI. ASHS software was applied to the imaging data to perform automated hippocampal segmentation and provide volumetrics for analysis. An exploratory analysis was also performed on associations between symptom scores for diagnostic testing and hippocampal subfield volumes.ResultsCompared to HC, MDD and TRD patients showed reduced right-hemisphere CA2/3 subfield volume (p = 0.01, η2 = 0.31 and p = 0.3, η2 = 0.44, respectively). Additionally, negative associations were found between subfield volumes and life-stressor checklist scores, including left CA1 (p = 0.041, f2 = 0.419), left CA4/DG (p = 0.010, f2 = 0.584), right subiculum total (p = 0.038, f2 = 0.354), left hippocampus total (p = 0.015, f2 = 0.134), and right hippocampus total (p = 0.034, f2 = 0.110). Caution should be exercised in interpreting these results due to the small sample size and low power.ConclusionDetermining biomarkers for MDD and TRD pathophysiology through segmentation on high-resolution MRI data and understanding the effects of stress on these regions can enable better assessment of biological response to treatment selection and may elucidate the underlying mechanisms of depression. |
| first_indexed | 2024-04-10T18:07:08Z |
| format | Article |
| id | doaj.art-65b6c1b261c84fd182305861a1915720 |
| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-04-10T18:07:08Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj.art-65b6c1b261c84fd182305861a19157202023-02-02T12:32:27ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402023-02-011410.3389/fpsyt.2023.10607701060770Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla studyJudy Alper0Judy Alper1Rui Feng2Gaurav Verma3Sarah Rutter4Kuang-han Huang5Long Xie6Paul Yushkevich7Yael Jacob8Stephanie Brown9Marin Kautz10Molly Schneider11Hung-Mo Lin12Lazar Fleysher13Bradley N. Delman14Patrick R. Hof15James W. Murrough16James W. Murrough17Priti Balchandani18Department of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Biomedical Engineering, City College of New York, New York, NY, United StatesDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, United StatesDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, United StatesDepartment of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesPopulation Health Science and Policy Department, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesNash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesNash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesBackgroundMajor depressive disorder (MDD) is a prevalent health problem with complex pathophysiology that is not clearly understood. Prior work has implicated the hippocampus in MDD, but how hippocampal subfields influence or are affected by MDD requires further characterization with high-resolution data. This will help ascertain the accuracy and reproducibility of previous subfield findings in depression as well as correlate subfield volumes with MDD symptom scores. The objective of this study was to assess volumetric differences in hippocampal subfields between MDD patients globally and healthy controls (HC) as well as between a subset of treatment-resistant depression (TRD) patients and HC using automatic segmentation of hippocampal subfields (ASHS) software and ultra-high field MRI.MethodsThirty-five MDD patients and 28 HC underwent imaging using 7-Tesla MRI. ASHS software was applied to the imaging data to perform automated hippocampal segmentation and provide volumetrics for analysis. An exploratory analysis was also performed on associations between symptom scores for diagnostic testing and hippocampal subfield volumes.ResultsCompared to HC, MDD and TRD patients showed reduced right-hemisphere CA2/3 subfield volume (p = 0.01, η2 = 0.31 and p = 0.3, η2 = 0.44, respectively). Additionally, negative associations were found between subfield volumes and life-stressor checklist scores, including left CA1 (p = 0.041, f2 = 0.419), left CA4/DG (p = 0.010, f2 = 0.584), right subiculum total (p = 0.038, f2 = 0.354), left hippocampus total (p = 0.015, f2 = 0.134), and right hippocampus total (p = 0.034, f2 = 0.110). Caution should be exercised in interpreting these results due to the small sample size and low power.ConclusionDetermining biomarkers for MDD and TRD pathophysiology through segmentation on high-resolution MRI data and understanding the effects of stress on these regions can enable better assessment of biological response to treatment selection and may elucidate the underlying mechanisms of depression.https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1060770/fulldepressionhippocampusmagnetic resonance imagingstresssubfieldsultrahigh field MRI |
| spellingShingle | Judy Alper Judy Alper Rui Feng Gaurav Verma Sarah Rutter Kuang-han Huang Long Xie Paul Yushkevich Yael Jacob Stephanie Brown Marin Kautz Molly Schneider Hung-Mo Lin Lazar Fleysher Bradley N. Delman Patrick R. Hof James W. Murrough James W. Murrough Priti Balchandani Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study Frontiers in Psychiatry depression hippocampus magnetic resonance imaging stress subfields ultrahigh field MRI |
| title | Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study |
| title_full | Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study |
| title_fullStr | Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study |
| title_full_unstemmed | Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study |
| title_short | Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study |
| title_sort | stress related reduction of hippocampal subfield volumes in major depressive disorder a 7 tesla study |
| topic | depression hippocampus magnetic resonance imaging stress subfields ultrahigh field MRI |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1060770/full |
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