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Li Q, Coulson Theodorsen M, Konvalinka I, Eskelund K, Karstoft KI, Bo Andersen S, Andersen TS. Resting-state EEG functional connectivity predicts post-traumatic stress disorder subtypes in veterans. J Neural Eng 2022; 19. [PMID: 36250685 DOI: 10.1088/1741-2552/ac9aaf] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/13/2022] [Indexed: 01/11/2023]
Abstract
Objective. Post-traumatic stress disorder (PTSD) is highly heterogeneous, and identification of quantifiable biomarkers that could pave the way for targeted treatment remains a challenge. Most previous electroencephalography (EEG) studies on PTSD have been limited to specific handpicked features, and their findings have been highly variable and inconsistent. Therefore, to disentangle the role of promising EEG biomarkers, we developed a machine learning framework to investigate a wide range of commonly used EEG biomarkers in order to identify which features or combinations of features are capable of characterizing PTSD and potential subtypes.Approach. We recorded 5 min of eyes-closed and 5 min of eyes-open resting-state EEG from 202 combat-exposed veterans (53% with probable PTSD and 47% combat-exposed controls). Multiple spectral, temporal, and connectivity features were computed and logistic regression, random forest, and support vector machines with feature selection methods were employed to classify PTSD. To obtain robust results, we performed repeated two-layer cross-validation to test on an entirely unseen test set.Main results. Our classifiers obtained a balanced test accuracy of up to 62.9% for predicting PTSD patients. In addition, we identified two subtypes within PTSD: one where EEG patterns were similar to those of the combat-exposed controls, and another that were characterized by increased global functional connectivity. Our classifier obtained a balanced test accuracy of 79.4% when classifying this PTSD subtype from controls, a clear improvement compared to predicting the whole PTSD group. Interestingly, alpha connectivity in the dorsal and ventral attention network was particularly important for the prediction, and these connections were positively correlated with arousal symptom scores, a central symptom cluster of PTSD.Significance. Taken together, the novel framework presented here demonstrates how unsupervised subtyping can delineate heterogeneity and improve machine learning prediction of PTSD, and may pave the way for better identification of quantifiable biomarkers.
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Affiliation(s)
- Qianliang Li
- Section for Cognitive Systems, DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Maya Coulson Theodorsen
- Section for Cognitive Systems, DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark.,Department of Military Psychology, Danish Veteran Centre, Danish Defence, Copenhagen, Denmark.,Research and Knowledge Centre, Danish Veteran Centre, Danish Defence, Ringsted, Denmark
| | - Ivana Konvalinka
- Section for Cognitive Systems, DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Kasper Eskelund
- Department of Military Psychology, Danish Veteran Centre, Danish Defence, Copenhagen, Denmark.,Research and Knowledge Centre, Danish Veteran Centre, Danish Defence, Ringsted, Denmark
| | - Karen-Inge Karstoft
- Research and Knowledge Centre, Danish Veteran Centre, Danish Defence, Ringsted, Denmark.,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Søren Bo Andersen
- Research and Knowledge Centre, Danish Veteran Centre, Danish Defence, Ringsted, Denmark
| | - Tobias S Andersen
- Section for Cognitive Systems, DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark
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Wang J, Gao F, Cui S, Yang S, Gao F, Wang X, Zhu G. Utility of 7,8-dihydroxyflavone in preventing astrocytic and synaptic deficits in the hippocampus elicited by PTSD. Pharmacol Res 2022; 176:106079. [PMID: 35026406 DOI: 10.1016/j.phrs.2022.106079] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/07/2022] [Accepted: 01/08/2022] [Indexed: 02/07/2023]
Abstract
Astrocytic functions and brain-derived neurotrophic factor (BDNF)-tyrosine kinase receptor B (TrkB) signaling pathways are impaired in stress-related neuropsychiatric diseases. Previous studies have reported neuroprotective effects of 7,8-dihydroxyflavone (7,8-DHF), a TrkB activator. Here, we investigated the molecular mechanisms underlying pathogenesis of post-traumatic stress disorder (PTSD) using a modified single-prolonged stress (SPS&S) model and the potential beneficial effects of 7,8-DHF. SPS&S reduced the hippocampal expression of glial fibrillary acidic protein (GFAP), a marker of astrocytes, and induced morphological changes in astrocytes. From the perspective of synaptic function, the SPS&S model displayed reduced expression of BDNF, p-TrkB, postsynaptic density protein 95 (PSD95), AMPA receptor subunit GluR1 (GluA1), NMDA receptor subunit N2A/N2B ratio, calpain-1, phosphorylated protein kinase B (Akt) and phosphorylated mammalian target of rapamycin (mTOR) and conversely, higher phosphatase and tension homolog (PTEN) expression in the hippocampus. Acute or continuous intraperitoneal administration of 7,8-DHF (5 mg/kg) after SPS&S procedures prevented SPS&S-induced fear memory generalization and anxiety-like behaviors as well as abnormalities of hippocampal oscillations. Most importantly, 7,8-DHF attenuated SPS&S-induced abnormal BDNF-TrkB signaling and calpain-1-dependent cascade of synaptic deficits. Furthermore, treatment with a TrkB inhibitor completely blocked while an mTOR inhibitor partially blocked the effects of 7,8-DHF on behavioral changes of SPS&S model mice. Our collective findings suggest that 7,8-DHF effectively alleviates PTSD-like symptoms, including fear generalization and anxiety-like behavior, potentially by preventing astrocytic and synaptic deficits in the hippocampus through targeting of TrkB.
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Affiliation(s)
- Juan Wang
- Key Laboratory of Xin'an Medicine, the Ministry of Education, Anhui University of Chinese Medicine, China
| | - Feng Gao
- Key Laboratory of Xin'an Medicine, the Ministry of Education, Anhui University of Chinese Medicine, China
| | - Shuai Cui
- Key Laboratory of Xin'an Medicine, the Ministry of Education, Anhui University of Chinese Medicine, China
| | - Shaojie Yang
- Key Laboratory of Xin'an Medicine, the Ministry of Education, Anhui University of Chinese Medicine, China
| | - Fang Gao
- Key Laboratory of Xin'an Medicine, the Ministry of Education, Anhui University of Chinese Medicine, China
| | - Xuncui Wang
- Key Laboratory of Xin'an Medicine, the Ministry of Education, Anhui University of Chinese Medicine, China
| | - Guoqi Zhu
- Key Laboratory of Xin'an Medicine, the Ministry of Education, Anhui University of Chinese Medicine, China; Key Laboratory of Molecular Biology (Brain diseases), Anhui University of Chinese Medicine, Hefei, Anhui 230038, China.
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