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Wu C, Jia L, Mu Q, Fang Z, Hamoudi HJAS, Huang M, Hu S, Zhang P, Xu Y, Lu S. Altered hippocampal subfield volumes in major depressive disorder with and without anhedonia. BMC Psychiatry 2023; 23:540. [PMID: 37491229 PMCID: PMC10369779 DOI: 10.1186/s12888-023-05001-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 07/04/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND Previous neuroimaging findings have demonstrated the association between anhedonia and the hippocampus. However, few studies have focused on the structural changes in the hippocampus in major depressive disorder (MDD) patients with anhedonia. Meanwhile, considering that multiple and functionally specialized subfields of the hippocampus have their own signatures, the present study aimed to investigate the volumetric alterations of the hippocampus as well as its subfields in MDD patients with and without anhedonia. METHODS A total of 113 subjects, including 30 MDD patients with anhedonia, 40 MDD patients without anhedonia, and 43 healthy controls (HCs), were recruited in the study. All participants underwent high-resolution brain magnetic resonance imaging (MRI) scans, and the automated hippocampal substructure module in FreeSurfer 6.0 was used to evaluate the volumes of hippocampal subfields. We compared the volumetric differences in hippocampal subfields among the three groups by analysis of variance (ANOVA, post hoc Bonferroni), and partial correlation was used to explore the association between hippocampal subregion volumes and clinical characteristics. RESULTS ANOVA showed significant volumetric differences in the hippocampal subfields among the three groups in the left hippocampus head, mainly in the cornu ammonis (CA) 1, granule cell layer of the dentate gyrus (GC-ML-DG), and molecular layer (ML). Compared with HCs, both groups of MDD patients showed significantly smaller volumes in the whole left hippocampus head. Interestingly, further exploration revealed that only MDD patients with anhedonia had significantly reduced volumes in the left CA1, GC-ML-DG and ML when compared with HCs. No significant difference was found in the volumes of the hippocampal subfields between MDD patients without anhedonia and HCs, either the two groups of MDD patients. However, no association between hippocampal subfield volumes and clinical characteristics was found in either the subset of patients with anhedonia or in the patient group as a whole. CONCLUSIONS These preliminary findings suggest that MDD patients with anhedonia exhibit unique atrophy of the hippocampus and that subfield abnormalities in the left CA1 and DG might be associated with anhedonia in MDD.
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Affiliation(s)
- Congchong Wu
- Department of Psychiatry, The First Affiliated Hospital, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Lili Jia
- Department of Psychiatry, The First Affiliated Hospital, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Department of Clinical Psychology, The Fifth Peoples' Hospital of Lin'an District, Hangzhou, Zhejiang, China
| | - Qingli Mu
- Department of Psychiatry, The First Affiliated Hospital, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zhe Fang
- Department of Psychiatry, The First Affiliated Hospital, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | | | - Manli Huang
- Department of Psychiatry, The First Affiliated Hospital, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Shaohua Hu
- Department of Psychiatry, The First Affiliated Hospital, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Peng Zhang
- Department of Psychiatry, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, 310003, Zhejiang, China.
| | - Yi Xu
- Department of Psychiatry, The First Affiliated Hospital, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China.
| | - Shaojia Lu
- Department of Psychiatry, The First Affiliated Hospital, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China.
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Tang A, Woldemariam S, Roger J, Sirota M. Translational Bioinformatics to Enable Precision Medicine for All: Elevating Equity across Molecular, Clinical, and Digital Realms. Yearb Med Inform 2022; 31:106-115. [PMID: 36463867 PMCID: PMC9719766 DOI: 10.1055/s-0042-1742513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022] Open
Abstract
OBJECTIVES Over the past few years, challenges from the pandemic have led to an explosion of data sharing and algorithmic development efforts in the areas of molecular measurements, clinical data, and digital health. We aim to characterize and describe recent advanced computational approaches in translational bioinformatics across these domains in the context of issues or progress related to equity and inclusion. METHODS We conducted a literature assessment of the trends and approaches in translational bioinformatics in the past few years. RESULTS We present a review of recent computational approaches across molecular, clinical, and digital realms. We discuss applications of phenotyping, disease subtype characterization, predictive modeling, biomarker discovery, and treatment selection. We consider these methods and applications through the lens of equity and inclusion in biomedicine. CONCLUSION Equity and inclusion should be incorporated at every step of translational bioinformatics projects, including project design, data collection, model creation, and clinical implementation. These considerations, coupled with the exciting breakthroughs in big data and machine learning, are pivotal to reach the goals of precision medicine for all.
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Affiliation(s)
- Alice Tang
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA
- Graduate Program in Bioengineering, UCSF, San Francisco, CA, USA
- School of Medicine, UCSF, San Francisco, CA, USA
| | - Sarah Woldemariam
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA
- School of Medicine, UCSF, San Francisco, CA, USA
| | - Jacquelyn Roger
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA
- Graduate Program in Biological and Medical Informatics, UCSF, San Francisco, CA, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA
- Department of Pediatrics, UCSF, San Francisco, CA, USA
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