重型抑郁症患者脑网络性别差异的功能磁共振成像研究进展

张乾营; 康丽君; 刘忠纯

doi:10.12122/j.issn.1674-4500.2023.01.33

重型抑郁症患者脑网络性别差异的功能磁共振成像研究进展

doi: 10.12122/j.issn.1674-4500.2023.01.33

武汉大学人民医院精神卫生中心，湖北武汉 430060

基金项目:

国家重点研发计划 2018YFC1314600

国家自然科学基金 81771472

详细信息

作者简介:
张乾营，在读硕士研究生，E-mail: 836477654@qq.com

通讯作者:
刘忠纯，博士，教授，主任医师，博士生导师，E-mail: zcliu6@whu.edu.cn

计量
- 文章访问数: 240
- HTML全文浏览量: 204
- PDF下载量: 19
- 被引次数: 0
出版历程
- 收稿日期: 2022-09-20
- 网络出版日期: 2023-01-18
- 刊出日期: 2023-01-20

Advances in functional magnetic resonance imaging of gender differences in brain networks of patients with major depressive disorder

Mental Health Center of Renmin Hospital of Wuhan University, Wuhan 430060, China

Funds:

the National Key R&D Program of China 2018YFC1314600

National Natural Science Foundation of China 81771472

摘要

摘要: 重型抑郁症存在显著的性别差异已经得到广泛的研究证实。基于磁共振成像的脑网络分析方法已经在重型抑郁症性别差异的临床医学研究中被普遍用于疾病的神经机制和诊疗研究，已有许多临床研究成果能为临床疾病的病理探究和辅助诊断提供更好的依据。笔者通过归纳总结几种最常用脑网络研究方法，综合论述了基于磁共振成像在重型抑郁症性别差异的研究进展及应用前景。
- 重型抑郁症 /
- 性别差异 /
- 磁共振成像 /
- 脑网络
Abstract: The existence of significant gender differences in major depressive disorder has been extensively studied. Brain network analysis based on magnetic resonance imaging has been commonly used in clinical medical research on gender differences in major depressive disorder to investigate the neurological mechanisms of the disease and provide a better basis for clinical pathology and diagnosis. The author summarizes several of the most commonly used brain network research methods and discusses the progress and application prospects of MRI-based research on gender differences in major depressive disorder.
- major depressive disorder /
- sex factors /
- magnetic resonance imaging /
- brain network

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参考文献(61)

[1]	Eid RS, et al. Sex differences in depression: insights from clinical and preclinical studies[J]. Prog Neurobiol, 2019, 176: 86-102. doi: 10.1016/j.pneurobio.2019.01.006
[2]	Do D, et al. Pharmaceutical side effects and the sex differences in depression and distress[J]. Am J Prev Med, 2022, 63(2): 213-24. doi: 10.1016/j.amepre.2022.01.036
[3]	Seney ML, et al. Large-scale transcriptomics studies provide insight into sex differences in depression[J]. Biol Psychiatry, 2022, 91(1): 14-24. doi: 10.1016/j.biopsych.2020.12.025
[4]	Abitante G, et al. Trajectories of positive and negative affect across adolescence: maternal history of depression and adolescent sex as predictors[J]. J Affect Disord, 2022, 315: 96-104. doi: 10.1016/j.jad.2022.07.038
[5]	Kang HJ, Park Y, Yoo KH, et al. Sex differences in the genetic architecture of depression[J]. Sci Rep, 2020, 10: 9927. doi: 10.1038/s41598-020-66672-9
[6]	Ponton E, Turecki G, Nagy C. Sex differences in the behavioral, molecular, and structural effects of ketamine treatment in depression[J]. Int J Neuropsychopharmacol, 2021, 25(1): 75-84.
[7]	张格, 林岚, 吴水才. 基于脑网络的图卷积神经网络在脑疾病中的研究进展[J]. 医疗卫生装备, 2021, 42(8): 85-92. doi: 10.19745/j.1003-8868.2021174
[8]	廖立方, 王欧成, 刘勇. 机器学习结合fMRI在抑郁症诊断中的研究进展[J]. 磁共振成像, 2021, 12(5): 107-9, 117. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC202105026.htm
[9]	徐金勇, 朱勇, 汪增荣. 脑网络组学研究技术进展[J]. 解剖学杂志, 2017, 40(6): 739-42. doi: 10.3969/j.issn.1001-1633.2017.06.023
[10]	黄国权, 余永强, 王海宝. 抑郁症性别差异的神经影像学研究进展[J]. 国际医学放射学杂志, 2012, 35(4): 325-7. https://www.cnki.com.cn/Article/CJFDTOTAL-GWLC201204009.htm
[11]	Lu Q, Jiang HT, Liu HY, et al. Depression severity evaluation for female patients based on a functional MRI model[J]. J Magn Reson Imaging, 2010, 31(5): 1067-74. doi: 10.1002/jmri.22161
[12]	辛斐, 谢超, 王丽君, 等. 大尺度脑网络交互支持内外部指向认知的研究进展[J]. 中国生物医学工程学报, 2020, 39(6): 736-46. doi: 10.3969/j.issn.0258-8021.2020.06.011
[13]	Borgsted C, et al. Hippocampal volume changes in a pharmacological sex-hormone manipulation risk model for depression in women[J]. Horm Behav, 2022, 145: 105234. doi: 10.1016/j.yhbeh.2022.105234
[14]	Liu YJ, Chen YP, Liang XY, et al. Altered resting-state functional connectivity of multiple networks and disrupted correlation with executive function in major depressive disorder[J]. Front Neurol, 2020, 11: 272. doi: 10.3389/fneur.2020.00272
[15]	和梦鑫, 平亮亮, 许秀峰. 基于图论的复杂脑网络分析在精神疾病中的研究进展[J]. 昆明医科大学学报, 2019, 40(5): 129-34. doi: 10.3969/j.issn.1003-4706.2019.05.025
[16]	刘春洋, 梅兰, 邱丽华, 等. 重度抑郁症患者脑灰质体积性别差异的3D高分辨MRI研究[J]. 放射学实践, 2022, 37(4): 460-5. doi: 10.13609/j.cnki.1000-0313.2022.04.009
[17]	Lima S, et al. The underestimated sex: a review on female animal models of depression[J]. Neurosci Biobehav Rev, 2022, 133: 104498. doi: 10.1016/j.neubiorev.2021.12.021
[18]	Kundakovic M, et al. Sex hormone fluctuation and increased female risk for depression and anxiety disorders: from clinical evidence to molecular mechanisms[J]. Front Neuroendocrinol, 2022, 66: 101010. doi: 10.1016/j.yfrne.2022.101010
[19]	Cai SP, Wang XW, Yang F, et al. Differences in brain structural covariance network characteristics in children and adults with autism spectrum disorder[J]. Autism Res, 2021, 14(2): 265-75. doi: 10.1002/aur.2464
[20]	牟静平, 成财, 梅兰, 等. 抑郁症灰白质表面积性别差异研究[J]. 磁共振成像, 2021, 12(1): 21-6, 37. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC202101006.htm
[21]	Fish AM, et al. Sex-biased trajectories of amygdalo-hippocampal morphology change over human development[J]. NeuroImage, 2020, 204: 116122. doi: 10.1016/j.neuroimage.2019.116122
[22]	Hu XY, Zhang LQ, Liang KL, et al. Sex-specific alterations of cortical morphometry in treatment-naïve patients with major depressive disorder[J]. Neuropsychopharmacology, 2022, 47(11): 2002-9. doi: 10.1038/s41386-021-01252-7
[23]	Yang X, Peng ZG, Ma XJ, et al. Sex differences in the clinical characteristics and brain gray matter volume alterations in unmedicated patients with major depressive disorder[J]. Sci Rep, 2017, 7: 2515. doi: 10.1038/s41598-017-02828-4
[24]	梅兰, 胡心宇, 刁显明, 等. 抑郁症性别差异的静息态磁共振脑功能成像研究[J]. 中国医学影像学杂志, 2019, 27(11): 809-12, 814. doi: 10.3969/j.issn.1005-5185.2019.11.003
[25]	Eyolfson E, Carr T, Khan A, et al. Repetitive mild traumatic brain injuries in mice during adolescence cause sexually dimorphic behavioral deficits and neuroinflammatory dynamics[J]. J Neurotrauma, 2020, 37(24): 2718-32. doi: 10.1089/neu.2020.7195
[26]	Ho TC, Sisk LM, Kulla A, et al. Sex differences in myelin content of white matter tracts in adolescents with depression[J]. Neuropsychopharmacology, 2021, 46(13): 2295-303. doi: 10.1038/s41386-021-01078-3
[27]	Domain L, et al. Multimodal MRI cerebral correlates of verbal fluency switching and its impairment in women with depression[J]. Neuroimage Clin, 2022, 33: 102910. doi: 10.1016/j.nicl.2021.102910
[28]	Kliamovich D, et al. Sex-specific patterns of white matter microstructure are associated with emerging depression during adolescence[J]. Psychiatry Res Neuroimaging, 2021, 315: 111324. doi: 10.1016/j.pscychresns.2021.111324
[29]	Chan RF, Copeland WE, Zhao M, et al. A methylation study implicates the rewiring of brain neural circuits during puberty in the emergence of sex differences in depression symptoms[J]. J Child Psychol Psychiatry, 2022, 63(7): 802-9. doi: 10.1111/jcpp.13522
[30]	Gaspar R, Soares-Cunha C, Domingues AV, et al. The duration of stress determines sex specificities in the vulnerability to depression and in the morphologic remodeling of neurons and microglia[J]. Front Behav Neurosci, 2022, 16: 834821. doi: 10.3389/fnbeh.2022.834821
[31]	Dorfschmidt L, Bethlehem RA, Seidlitz J, et al. Sexually divergent development of depression-related brain networks during healthy human adolescence[J]. Sci Adv, 2022, 8(21): 7825. doi: 10.1126/sciadv.abm7825
[32]	Dai WP, Huang SY, Luo Y, et al. Sex-specific transcriptomic signatures in brain regions critical for neuropathic pain-induced depression[J]. Front Mol Neurosci, 2022, 15: 886916. doi: 10.3389/fnmol.2022.886916
[33]	King JA, et al. Structural neuroimaging of anorexia nervosa: future directions in the quest for mechanisms underlying dynamic alterations[J]. Biol Psychiatry, 2018, 83(3): 224-34. doi: 10.1016/j.biopsych.2017.08.011
[34]	Kim K, Kim SW, Myung W, et al. Reduced orbitofrontal-thalamic functional connectivity related to suicidal ideation in patients with major depressive disorder[J]. Sci Rep, 2017, 7: 15772. doi: 10.1038/s41598-017-15926-0
[35]	Lee K, Kim S, Jo JK. The relationships between abnormal serum lipid levels, depression, and suicidal ideation according to sex[J]. J Clin Med, 2022, 11(8): 2119. doi: 10.3390/jcm11082119
[36]	Gärtner M, Ghisu ME, Scheidegger M, et al. Aberrant working memory processing in major depression: evidence from multivoxel pattern classification[J]. Neuropsychopharmacology, 2018, 43(9): 1972-9. doi: 10.1038/s41386-018-0081-1
[37]	袁悦铭, 张力, 张治国. 基于静息态功能磁共振成像的动态功能连接分析及临床应用研究进展[J]. 磁共振成像, 2018, 9(8): 579-88. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC201808007.htm
[38]	Hilland E, Landrø N, Harmer C, et al. Within-network connectivity in the salience network after attention bias modification training in residual depression: report from a preregistered clinical trial[J]. Front hum neurosci, 2018, 12: 508.
[39]	Sendi MSE, Zendehrouh E, Sui J, et al. Abnormal dynamic functional network connectivity estimated from default mode network predicts symptom severity in major depressive disorder[J]. Brain Connect, 2021, 11(10): 838-49. doi: 10.1089/brain.2020.0748
[40]	Wang SP, Wen HW, Hu XP, et al. Transition and dynamic reconfiguration of whole- brain network in major depressive disorder[J]. Mol Neurobiol, 2020, 57(10): 4031-44. doi: 10.1007/s12035-020-01995-2
[41]	Jenkins LM, et al. Considering sex differences clarifies the effects of depression on facial emotion processing during fMRI[J]. J Affect Disord, 2018, 225: 129-36. doi: 10.1016/j.jad.2017.08.027
[42]	Kong QM, Qiao H, Liu CZ, et al. Aberrant intrinsic functional connectivity in thalamo-cortical networks in major depressive disorder[J]. CNS Neurosci Ther, 2018, 24(11): 1063-72. doi: 10.1111/cns.12831
[43]	Ironside M, Moser AD, Holsen LM, et al. Reductions in rostral anterior cingulate GABA are associated with stress circuitry in females with major depression: a multimodal imaging investigation[J]. Neuropsychopharmacology, 2021, 46(12): 2188-96. doi: 10.1038/s41386-021-01127-x
[44]	Shi YS, et al. Abnormal functional connectivity strength in firstepisode, drug- naïve adult patients with major depressive disorder[J]. Prog Neuro Psychopharmacol Biol Psychiatry, 2020, 97: 109759. doi: 10.1016/j.pnpbp.2019.109759
[45]	Scalabrini A, Vai B, Poletti S, et al. All Roads lead to the defaultmode network global source of DMN abnormalities in major depressive disorde[J]. Neuropsychopharmacology, 2020, 45(12): 2058-69. doi: 10.1038/s41386-020-0785-x
[46]	王豪杰, 陈炜, 覃艳华, 等. 双相障碍患者的多巴胺转运受体基因多态性和静息态功能磁共振成像与脑奖赏环路的相关性研究[J]. 中国全科医学, 2017, 20(12): 1439-43. doi: 10.3969/j.issn.1007-9572.2017.12.007
[47]	Liu XY, et al. Disrupted rich-club network organization and individualized identification of patients with major depressive disorder[J]. Prog Neuro Psychopharmacol Biol Psychiatry, 2021, 108: 110074. doi: 10.1016/j.pnpbp.2020.110074
[48]	Wang JJ, Wang Y, Huang HY, et al. Abnormal dynamic functional network connectivity in unmedicated bipolar and major depressive disorders based on the triple- network model[J]. Psychol Med, 2020, 50(3): 465-74. doi: 10.1017/S003329171900028X
[49]	Li JM, et al. Causal interactions between the default mode network and central executive network in patients with major depression[J]. Neuroscience, 2021, 475: 93-102. doi: 10.1016/j.neuroscience.2021.08.033
[50]	Yang H, Chen X, Chen ZB, et al. Disrupted intrinsic functional brain topology in patients with major depressive disorder[J]. Mol Psychiatry, 2021, 26(12): 7363-71. doi: 10.1038/s41380-021-01247-2
[51]	Korgaonkar MS, Goldstein-Piekarski AN, Fornito A, et al. Intrinsic connectomes are a predictive biomarker of remission in major depressive disorder[J]. Mol Psychiatry, 2020, 25(7): 1537-49. doi: 10.1038/s41380-019-0574-2
[52]	Zhu XL, Yuan FL, Zhou GF, et al. Cross-network interaction for diagnosis of major depressive disorder based on resting state functional connectivity[J]. Brain Imaging Behav, 2021, 15(3): 1279-89. doi: 10.1007/s11682-020-00326-2
[53]	Terpstra AR, Girard TA, Colella B, et al. Higher anxiety symptoms predict progressive hippocampal atrophy in the chronic stages of moderate to severe traumatic brain injury[J]. Neurorehabil Neural Repair, 2017, 31(12): 1063-71. doi: 10.1177/1545968317736817
[54]	He CC, Gong L, Yin YY, et al. Amygdala connectivity mediates the association between anxiety and depression in patients with major depressive disorder[J]. Brain Imaging Behav, 2019, 13(4): 1146-59. doi: 10.1007/s11682-018-9923-z
[55]	Dvorak J, Hilke M, Trettin M, et al. Aberrant brain network topology in fronto- limbic circuitry differentiates euthymic bipolar disorder from recurrent major depressive disorder[J]. Brain Behav, 2019, 9(6): e01257.
[56]	Du Y, Zhao JJ, Wang YZ, et al. Brain functional differences in drug-naive major depression with anxiety patients of different traditional Chinese medicine syndrome patterns: a resting-state fMRI study[J]. Evid Based Complementary Altern Med, 2020, 2020: 7504917.
[57]	Williams ES, Mazei- Robison M, Robison AJ. Sex differences in major depressive disorder (MDD) and preclinical animal models for the study of depression[J]. Cold Spring Harb Perspect Biol, 2022, 14(3): a039198. doi: 10.1101/cshperspect.a039198
[58]	Amgalan A, Maher AS, Imms P, et al. Functional connectome dynamics after mild traumatic brain injury according to age and sex[J]. Front Aging Neurosci, 2022, 14: 852990. doi: 10.3389/fnagi.2022.852990
[59]	Wu ZX, Peng Y, Selvaraj S, et al. Development of brain structural networks over age 8: a preliminary study based on diffusion weighted imaging[J]. Front Aging Neurosci, 2020, 12: 61. doi: 10.3389/fnagi.2020.00061
[60]	Li GS, Liu YJ, Zheng YT, et al. Large-scale dynamic causal modeling of major depressive disorder based on resting-state functional magnetic resonance imaging[J]. Hum Brain Mapp, 2020, 41(4): 865-81. doi: 10.1002/hbm.24845
[61]	Liu Y, et al. Abnormal interhemispheric homotopic functional connectivity is correlated with gastrointestinal symptoms in patients with major depressive disorder[J]. J Psychiatr Res, 2021, 144: 234-40. doi: 10.1016/j.jpsychires.2021.10.016