首页 » 文章 » 文章详细信息
Evidence-Based Complementary and Alternative Medicine Volume 2020 ,2020-02-18
Brain Functional Differences in Drug-Naive Major Depression with Anxiety Patients of Different Traditional Chinese Medicine Syndrome Patterns: A Resting-State fMRI Study
Research Article
Yi Du 1 Jingjie Zhao 1 Yongzhi Wang 1 Yu Han 2 Ligang Deng 3 Hongxiao Jia 4 Yuan Zhou 5 , 6 Joyce Su 7 Li Li 1
Show affiliations
DOI:10.1155/2020/7504917
Received 2019-07-18, accepted for publication 2020-01-16, Published 2020-02-18
PDF
摘要

Major depressive disorder (MDD), especially combined with anxiety, has a high incidence and low detection rate in China. Literature has shown that patients under major depression with anxiety (MDA) are more likely to nominate a somatic, rather than psychological, symptom as their presenting complaint. In the theory of Traditional Chinese Medicine (TCM), clinical symptoms of MDD patients are mainly categorized into two different syndrome patterns: Deficiency and Excess. We intend to use resting-state functional magnetic resonance imaging (rs-fMRI) to investigate their brain functional differences and hopefully to find their brain function mechanism. For our research, 42 drug-naive MDA patients were divided into two groups (21 for Deficiency and 21 for Excess), with an additional 19 unaffected participants in the normal control (NC) group. We took Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Scale (HAMA), and brain fMRI scan for each group and analyzed the data. We first used Degree Centrality (DC) to map the functional differences in brain regions, utilized these regions as seed points, and used a seed-based functional connectivity (FC) analysis to identify the specific functional connection between groups. The Deficiency group was found to have higher HAMD scores, HAMA scores, and HAMD somatic factor than the Excess group. In the DC analysis, significant decreases were found in the right precuneus of both the Deficiency and Excess groups compared to the NC group. In the FC analysis, the right precuneus showed significant decreased network connectivity with the bilateral cuneus, as well as the right lingual gyrus in the Deficiency group when compared to the NC group and the Excess group. Through our research, it was found that precuneus dysfunction may have a relationship with MDA and Deficiency patients have more severe physical and emotional symptoms, and we realized that a larger sample size and multiple brain mode observations were needed in further research.

授权许可

Copyright © 2020 Yi Du et al. 2020
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

通讯作者

Li Li.Department of Traditional Chinese Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China, ccmu.edu.cn.lili@ccmu.edu.cn

推荐引用方式

Yi Du,Jingjie Zhao,Yongzhi Wang,Yu Han,Ligang Deng,Hongxiao Jia,Yuan Zhou,Joyce Su,Li Li. Brain Functional Differences in Drug-Naive Major Depression with Anxiety Patients of Different Traditional Chinese Medicine Syndrome Patterns: A Resting-State fMRI Study. Evidence-Based Complementary and Alternative Medicine ,Vol.2020(2020)

您觉得这篇文章对您有帮助吗?
分享和收藏
0

是否收藏?

参考文献
[1] X.-N. Zuo, R. Ehmke, M. Mennes. (2012). Network centrality in the human functional connectome. Cerebral Cortex.22(8):1862-1875. DOI: 10.1038/515180a.
[2] X. Cao, Z. Liu, C. Xu. (2012). Disrupted resting-state functional connectivity of the hippocampus in medication-naïve patients with major depressive disorder. Journal of Affective Disorders.141(2-3):194-203. DOI: 10.1038/515180a.
[3] D Li, X. Huang, Q. Wu. (2010). Brain functions in major depressive disorder: a resting-state functional magnetic resonance imaging study. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi.27:16-19. DOI: 10.1038/515180a.
[4] S. L. Sommerfeldt, K. R. Cullen, G. Han. (2016). Executive attention impairment in adolescents with major depressive disorder. Journal of Clinical Child and Adolescent Psychology.45(1):69-83. DOI: 10.1038/515180a.
[5] M. Goto, O. Abe, H. Yamasue, T. Gomi. et al.(2016). Head motion and correction methods in resting-state functional MRI. Magnetic Resonance in Medical Sciences.15(2):178-186. DOI: 10.1038/515180a.
[6] J. Brakowski, S. Spinelli, N. Dörig. (2017). Resting state brain network function in major depression–depression symptomatology, antidepressant treatment effects, future research. Journal of Psychiatric Research.92:147-159. DOI: 10.1038/515180a.
[7] R. L. Buckner, J. Sepulcre, T. Talukdar. (2009). Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer’s disease. Journal of Neuroscience.29(6):1860-1873. DOI: 10.1038/515180a.
[8] A. Dutta, S. McKie, J. F. W. Deakin. (2014). Resting state networks in major depressive disorder. Psychiatry Research: Neuroimaging.224(3):139-151. DOI: 10.1038/515180a.
[9] Z. Yao, L. Wang, Q. Lu, H. Liu. et al.(2009). Regional homogeneity in depression and its relationship with separate depressive symptom clusters: a resting-state fMRI study. Journal of Affective Disorders.115(3):430-438. DOI: 10.1038/515180a.
[10] L.-L. Zeng, S. Hhen, H. Shen. (2012). Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. Brain.135(5):1498-1507. DOI: 10.1038/515180a.
[11] C. Yu, J. Lyu, Y. Chen. (2015). Epidemiology of major depressive episodes among Chinese adults aged 30-79 years: data from the China kadoorie biobank. Zhonghua Liu Xing Bing Xue Za Zhi.36(1):52-56. DOI: 10.1038/515180a.
[12] D. Peng, E. B. Liddle, S. J. Iwabuchi. (2015). Dissociated large-scale functional connectivity networks of the precuneus in medication-naïve first-episode depression. Psychiatry Research: Neuroimaging.232(3):250-256. DOI: 10.1038/515180a.
[13] I. M. Veer, C. Beckmann, M. J. van Tol. (2010). Whole brain resting-state analysis reveals decreased functional connectivity in major depression. Frontiers in Systems Neuroscience.4. DOI: 10.1038/515180a.
[14] C.-H. Lai, Y.-T. Wu. (2013). Decreased regional homogeneity in lingual gyrus, increased regional homogeneity in cuneus and correlations with panic symptom severity of first-episode, medication-naïve and late-onset panic disorder patients. Psychiatry Research: Neuroimaging.211(2):127-131. DOI: 10.1038/515180a.
[15] D. S. F. Yu, D. T. F. Lee. (2012). Do medically unexplained somatic symptoms predict depression in older Chinese?. International Journal of Geriatric Psychiatry.27(2):119-126. DOI: 10.1038/515180a.
[16] D. D. Price. (2000). Psychological and neural mechanisms of the affective dimension of pain. Science.288:1769-1772. DOI: 10.1038/515180a.
[17] G. Parker, Y.-C. Cheah, K. Roy. (2001). Do the Chinese somatize depression? A cross-cultural study. Social Psychiatry and Psychiatric Epidemiology.36(6):287-293. DOI: 10.1038/515180a.
[18] D. A. Gusnard, E. Akbudak, G. L. Shulman, M. E. Raichle. et al.(2001). Medial prefrontal cortex and self-referential mental activity: relation to a default mode of brain function. Proceedings of the National Academy of Sciences.98(7):4259-4264. DOI: 10.1038/515180a.
[19] J. Bogousslavsky, J. Miklossy, J. P. Deruaz, G. Assal. et al.(1987). Lingual and fusiform gyri in visual processing: a clinico-pathologic study of superior altitudinal hemianopia. Journal of Neurology, Neurosurgery & Psychiatry.50(5):607-614. DOI: 10.1038/515180a.
[20] Q.-Z. Wu, D.-M. Li, W.-H. Kuang. (2011). Abnormal regional spontaneous neural activity in treatment-refractory depression revealed by resting-state fMRI. Human Brain Mapping.32(8):1290-1299. DOI: 10.1038/515180a.
[21] C. G. Yan, R. C. Craddock, Y. He. (2013). Addressing head motion dependencies for small-world topologies in functional connectomics. Frontiers in Human Neuroscience.7:910. DOI: 10.1038/515180a.
[22] L. Xu, Yu Chen, M. Wang, X. Zhou. et al.(2017). Clinical syndrome differentiation of depression. Journal of Hubei University of Traditional Chinese Medicine.19:37-40. DOI: 10.1038/515180a.
[23] L. Wang, D. Wenji, Y. Su. (2012). Amplitude of low-frequency oscillations in first-episode, treatment-naive patients with major depressive disorder: a resting-state functional MRI study. PLoS. One..7(10). DOI: 10.1038/515180a.
[24] C. Andreescu, M. Wu, M. A. Butters, J. Figurski. et al.(2011). The default mode network in late-life anxious depression. The American Journal of Geriatric Psychiatry.19(11):980-983. DOI: 10.1038/515180a.
[25] M. F. Mason, M. I. Norton, J. D. Van Horn, D. M. Wegner. et al.(2007). Wandering minds: the default network and stimulus-independent thought. Science.315(5810):393-395. DOI: 10.1038/515180a.
[26] C.-H. Liu, X. Ma, L.-P. Song. (2015). Alteration of spontaneous neuronal activity within the salience network in partially remitted depression. Brain Research.1599:93-102. DOI: 10.1038/515180a.
[27] N. L. Nixon, P. F. Liddle, E. Nixon, G. Worwood. et al.(2014). Biological vulnerability to depression: linked structural and functional brain network findings. British Journal of Psychiatry.204(4):283-289. DOI: 10.1038/515180a.
[28] G. Li, G. Guo, S. Chen, H. Wang. et al.(2016). Classification and analysis of TCM syndromes of depression based on literature. Chinese Journal of Traditional Chinese Medicine.34:876-879. DOI: 10.1038/515180a.
[29] C. Lemogne, H. Mayberg, L. Bergouignan. (2010). Self-referential processing and the prefrontal cortex over the course of depression: a pilot study. Journal of Affective Disorders.124(1-2):196-201. DOI: 10.1038/515180a.
[30] F. Liu, W. Guo, L. Liu. (2013). Abnormal amplitude low-frequency oscillations in medication-naive, first-episode patients with major depressive disorder: a resting-state fMRI study. Journal of Affective Disorders.146(3):401-406. DOI: 10.1038/515180a.
[31] K. Vassilopoulou, M. Papathanasiou, I. Michopoulos. (2013). A magnetic resonance imaging study of hippocampal, amygdala and subgenual prefrontal cortex volumes in major depression subtypes: melancholic versus psychotic depression. Journal of Affective Disorders.146(2):197-204. DOI: 10.1038/515180a.
[32] D. P. Goldberg, H.-U. Wittchen, P. Zimmermann, H. Pfister. et al.(2014). Anxious and non-anxious forms of major depression: familial, personality and symptom characteristics. Psychological Medicine.44(6):1223-1234. DOI: 10.1038/515180a.
[33] A. Etkin, A. F. Schatzberg. (2011). Common abnormalities and disorder-specific compensation during implicit regulation of emotional processing in generalized anxiety and major depressive disorders. American Journal of Psychiatry.168(9):968-978. DOI: 10.1038/515180a.
[34] M. Y. Zhang. (2011). Depression is a common disease. Chinese Journal of Psychiatry.44:46. DOI: 10.1038/515180a.
[35] C. E. Waugh, J. P. Hamilton, M. C. Chen, J. Joormann. et al.(2012). Neural temporal dynamics of stress in comorbid major depressive disorder and social anxiety disorder. Biology of Mood & Anxiety Disorders.2(1). DOI: 10.1038/515180a.
[36] P. Fransson, G. Marrelec. (2008). The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: evidence from a partial correlation network analysis. Neuroimage.42(3):1178-1184. DOI: 10.1038/515180a.
[37] Y. Wu, X. Wang. (2012). Chinese Medicine Internal Medicine. DOI: 10.1038/515180a.
[38] A. V. Utevsky, D. V. Smith, S. A. Huettel. (2014). Precuneus is a functional core of the default-mode network. The Journal of Neuroscience.34(3):932-940. DOI: 10.1038/515180a.
[39] R. Jones, J. Bhattacharya. (2014). A role for the precuneus in thought-action fusion: evidence from participants with significant obsessive-compulsive symptoms. NeuroImage: Clinical.4:112-121. DOI: 10.1038/515180a.
[40] Medinati, Z. Tao. (2012). Physical characteristics of depression in outpatient of general hospital. Chinese Practical Medicine.7:88-89. DOI: 10.1038/515180a.
[41] C.-G. Yan, B. Cheung, C. Kelly. (2013). A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. NeuroImage.76:183-201. DOI: 10.1038/515180a.
[42] M. B. First, R. L. Spitzer, G. Miriam, J. B. W. Williams. et al.(1997). Structured Clinical Interview for DSM-IV axis I Disorders: SCID-I: Clinical Version: Administration Booklet. DOI: 10.1038/515180a.
[43] Y. Ma, Z. Chen, W. Jin. (2011). Preliminary observation on the treatment of depression by integrated traditional Chinese and western medicine. Clinical Study of Traditional Chinese Medicine.1:6-7. DOI: 10.1038/515180a.
[44] C. Zhu, Li Xia. (2014). Quzhao. Guipi decoction for depression of deficiency of heart and spleen. Jilin Traditional Chinese Medicine.34:695-699. DOI: 10.1038/515180a.
[45] M. Zhang. (2007). Guidelines for the prevention and treatment of dementia in the elderly. DOI: 10.1038/515180a.
[46] M. F. Folstein, S. E. Folstein, P. R. McHugh. (1975). Mini-mental state. Journal of Psychiatric Research.12(3):189-198. DOI: 10.1038/515180a.
[47] H. Macpherson, B. Elliot, A. Hopton, H. Lansdown. et al.(2013). Acupuncture for depression: patterns of diagnosis and treatment within a randomised controlled trial. Evidence-based Complementary and Alternative Medicine.2013:286048-9. DOI: 10.1038/515180a.
[48] R. Saveanu, A. Etkin, A.-M. Duchemin. (2015). The international study to predict optimized treatment in depression (iSPOT-D): outcomes from the acute phase of antidepressant treatment. Journal of Psychiatric Research.61:1-12. DOI: 10.1038/515180a.
[49] S. J. Ferri, G. Hajcak. (2016). Emotion regulation and amygdala-precuneus connectivity: focusing on attentional deployment. Cognitive, Affective, & Behavioral Neuroscience.16:1-12. DOI: 10.1038/515180a.
[50] J. B. W. Williams. (1988). A structured interview guide for the Hamilton Depression Rating Scale. Archives of General Psychiatry.45(8):742-747. DOI: 10.1038/515180a.
[51] Y. Chen, Z. Liu, J. Zhang. (2017). Precuneus degeneration in nondemented elderly individuals with APOE ɛ4: evidence from structural and functional MRI analyses. Human Brain Mapping.38(1):271-282. DOI: 10.1038/515180a.
[52] E. P. T. Bruner, X. Chen. (2017). Evidence for expansion of the precuneus in human evolution. Brain Structure and Function.222(2):1-8. DOI: 10.1038/515180a.
[53] C. Li, W. F. Jinqiu, J. Wu. (2006). Investigation on the relationship between common emotional symptoms and TCM classification of depressive patients in Shenyang. China Clinical Rehabilitation.47:42-45. DOI: 10.1038/515180a.
[54] D. Z. Song, X. Y. Long, S.-F. Li. (2011). REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS One.6. DOI: 10.1038/515180a.
[55] M. E. Raichle. (2015). The brain’s default mode network. Annual Review of Neuroscience.38(1):433-447. DOI: 10.1038/515180a.
[56] C. Chen, Z. Chen, S. Hu, H. Zhang. et al.(2003). Factor analysis of Hamilton depression scale of TCM syndrome of depression. Journal of Hunan College of Traditional Chinese Medicine.04:32-34. DOI: 10.1038/515180a.
[57] H. Han, J. Park. (2018). Using SPM 12’s second-level bayesian inference procedure for fMRI analysis: practical guidelines for end users. Frontiers in Neuroinformatics.12(1). DOI: 10.1038/515180a.
[58] K. S. R. Kroenke, R. L. Spitzer, J. B. W. Williams. (2001). The PHQ-9. Journal of General Internal Medicine.16(9):606-613. DOI: 10.1038/515180a.
[59] K. Smith. (2014). Mental health: a world of depression. Nature.515(7526):181. DOI: 10.1038/515180a.
[60] W. Maier, R. Buller, M. Philipp, I. Heuser. et al.(1988). The Hamilton Anxiety Scale: reliability, validity and sensitivity to change in anxiety and depressive disorders. Journal of Affective Disorders.14(1):61-68. DOI: 10.1038/515180a.
[61] M. Cabanis, M. Pyka, S. Mehl. (2013). The precuneus and the insula in self-attributional processes. Cognitive, Affective, & Behavioral Neuroscience.13(2):330-345. DOI: 10.1038/515180a.
[62] M. Worboys. (2013). The Hamilton Rating Scale for Depression: the making of a “gold standard” and the unmaking of a chronic illness, 1960-1980. Chronic Illness.9(3):202-219. DOI: 10.1038/515180a.
[63] M.-J. Van Tol, M. Li, C. D. Metzger. (2014). Local cortical thinning links to resting-state disconnectivity in major depressive disorder. Psychological Medicine.44(10):2053-2065. DOI: 10.1038/515180a.
[64] C. Yuan, H. Zhu, Z. Ren. (2017). Precuneus-related regional and network functional deficits in social anxiety disorder: a resting-state functional MRI study. Comprehensive Psychiatry.82:22-29. DOI: 10.1038/515180a.
[65] Z. Y. Yan. (2010). DPARSF: a MATLAB toolbox for ‘‘pipeline’’ data analysis of resting-state fMRI. Frontiers in System Neuroscience.4(13). DOI: 10.1038/515180a.
[66] M. Uchimura, T. Nakano, Y. Morito, H. Ando. et al.(2015). Automatic representation of a visual stimulus relative to a background in the right precuneus. European Journal of Neuroscience.42(1):1651-1659. DOI: 10.1038/515180a.
[67] A. E. Cavanna. (2007). The precuneus and consciousness. CNS Spectrums.12(7):545-552. DOI: 10.1038/515180a.
[68] X. Cui, W. Guo, Y. Wang. (2017). Aberrant default mode network homogeneity in patients with first-episode treatment-naive melancholic depression. International Journal of Psychophysiology.112:46-51. DOI: 10.1038/515180a.
[69] A. E. Cavanna, M. R. Trimble. (2006). The precuneus: a review of its functional anatomy and behavioural correlates. Brain.129(3):564-583. DOI: 10.1038/515180a.
[70] R. Esposito, F. Cieri, P. Chiacchiaretta. (2018). Modifications in resting state functional anticorrelation between default mode network and dorsal attention network: comparison among young adults, healthy elders and mild cognitive impairment patients. Brain Imaging and Behavior.12(1):127-141. DOI: 10.1038/515180a.
[71] M. Freton, C. Lemogne, L. Bergouignan, P. Delaveau. et al.(2014). The eye of the self: precuneus volume and visual perspective during autobiographical memory retrieval. Brain Structure and Function.219(3):959-968. DOI: 10.1038/515180a.
文献评价指标
浏览 61次
下载全文 2次
评分次数 0次
用户评分 0.0分
分享 0次