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Deng Z, Liu L, Liu W, Liu R, Ma T, Xin Y, Xie Y, Zhang Y, Zhou Y, Tang Y. Alterations in the fecal microbiota of methamphetamine users with bad sleep quality during abstinence. BMC Psychiatry 2024; 24:324. [PMID: 38664669 PMCID: PMC11046801 DOI: 10.1186/s12888-024-05773-5] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Methamphetamine (MA) abuse has resulted in a plethora of social issues. Sleep disturbance is a prominent issue about MA addiction, which serve as a risk factor for relapse, and the gut microbiota could play an important role in the pathophysiological mechanisms of sleep disturbances. Therefore, improving sleep quality can be beneficial for treating methamphetamine addiction, and interventions addressing the gut microbiota may represent a promising approach. METHOD We recruited 70 MA users to investigate the associations between sleep quality and fecal microbiota by the Pittsburgh Sleep Quality Index (PSQI), which was divided into MA-GS (PSQI score < 7, MA users with good sleep quality, n = 49) and MA-BS group (PSQI score ≥ 7, MA users with bad sleep quality, n = 21). In addition, we compared the gut microbiota between the MA-GS and healthy control (HC, n = 38) groups. 16S rRNA sequencing was applied to identify the gut bacteria. RESULT The study revealed that the relative abundances of the Thermoanaerobacterales at the order level differed between the MA-GS and MA-BS groups. Additionally, a positive correlation was found between the relative abundance of the genus Sutterella and daytime dysfunction. Furthermore, comparisons between MA users and HCs revealed differences in beta diversity and relative abundances of various bacterial taxa. CONCLUSION In conclusion, the study investigated alterations in the gut microbiota among MA users. Furthermore, we demonstrated that the genus Sutterella changes may be associated with daytime dysfunction, suggesting that the genus Sutterella may be a biomarker for bad sleep quality in MA users.
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Affiliation(s)
- Zijing Deng
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Linzi Liu
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Wen Liu
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Ruina Liu
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shanxi, PR China
| | - Tao Ma
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Yide Xin
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Yu Xie
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Yifan Zhang
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Yifang Zhou
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Yanqing Tang
- Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, PR China.
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Zeng Q, Tang Y, Zhou HT, Li N, Liu WY, Chen SL, Li S, Lu NN, Fang H, Wang SL, Liu YP, Song YW, Li YX, Jin J. [Role of neoadjuvant rectal score in prognosis and adjuvant chemotherapy decision-making in locally advanced rectal cancer following neoadjuvant short-course radiotherapy and consolidation chemotherapy]. Zhonghua Zhong Liu Za Zhi 2024; 46:335-343. [PMID: 38644269 DOI: 10.3760/cma.j.cn112152-20231024-00216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Objectives: To assess the prognostic impact of the neoadjuvant rectal (NAR) score following neoadjuvant short-course radiotherapy and consolidation chemotherapy in locally advanced rectal cancer (LARC), as well as its value in guiding decisions for adjuvant chemotherapy. Methods: Between August 2015 and August 2018, patients were eligible from the STELLAR phase III trial (NCT02533271) who received short-course radiotherapy plus consolidation chemotherapy and for whom the NAR score could be calculated. Based on the NAR score, patients were categorized into low (<8), intermediate (8-16), and high (>16) groups. The Kaplan-Meier method, log rank tests, and multivariate Cox proportional hazard regression models were used to evaluate the impact of the NAR score on disease-free survival (DFS). Results: Out of the 232 patients, 24.1%, 48.7%, and 27.2% had low (56 cases), intermediate (113 cases), and high NAR scores (63 cases), respectively. The median follow-up period was 37 months, with 3-year DFS rates of 87.3%, 68.3%, and 53.4% (P<0.001) for the low, intermediate, and high NAR score groups. Multivariate analysis demonstrated that the NAR score (intermediate NAR score: HR, 3.10, 95% CI, 1.30-7.37, P=0.011; high NAR scores: HR=5.44, 95% CI, 2.26-13.09, P<0.001), resection status (HR, 3.00, 95% CI, 1.64-5.52, P<0.001), and adjuvant chemotherapy (HR, 3.25, 95% CI, 2.01-5.27, P<0.001) were independent prognostic factors for DFS. In patients with R0 resection, the 3-year DFS rates were 97.8% and 78.0% for those with low and intermediate NAR scores who received adjuvant chemotherapy, significantly higher than the 43.2% and 50.6% for those who did not (P<0.001, P=0.002). There was no significant difference in the 3-year DFS rate (54.2% vs 53.3%, P=0.214) among high NAR score patients, regardless of adjuvant chemotherapy. Conclusions: The NAR score is a robust prognostic indicator in LARC following neoadjuvant short-course radiotherapy and consolidation chemotherapy, with potential implications for subsequent decisions regarding adjuvant chemotherapy. These findings warrant further validation in studies with larger sample sizes.
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Affiliation(s)
- Q Zeng
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - H T Zhou
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - W Y Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S L Chen
- Department of Radiation Oncology, Fujian Medical University Union Hospital, Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors (Fujian Medical University), Clinical Research Center for Radiology and Radiotherapy of Fujian Province (Digestive, Hematological and Breast Malignancies), Fuzhou 350001, China
| | - S Li
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - N N Lu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S L Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y P Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y W Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y X Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
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Chen Y, Ye X, Zhong Y, Kang X, Tang Y, Zhu H, Pang C, Ning S, Liang S, Zhang F, Li C, Li J, Gu C, Cheng Y, Kuang Z, Qiu J, Jin J, Luo H, Fu M, Hui HX, Li L, Ruan D, Liu P, Chen X, Sun L, Ai S, Gao X. SP6 controls human cytotrophoblast fate decisions and trophoblast stem cell establishment by targeting MSX2 regulatory elements. Dev Cell 2024:S1534-5807(24)00193-X. [PMID: 38582082 DOI: 10.1016/j.devcel.2024.03.025] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 12/14/2023] [Accepted: 03/12/2024] [Indexed: 04/08/2024]
Abstract
The commitment and differentiation of human placental progenitor cytotrophoblast (CT) cells are crucial for a successful pregnancy, but the underlying mechanism remains poorly understood. Here, we identified the transcription factor (TF), specificity protein 6 (SP6), as a human species-specific trophoblast lineage TF expressed in human placental CT cells. Using pluripotent stem cells as a model, we demonstrated that SP6 controls CT generation and the establishment of trophoblast stem cells (TSCs) and identified msh homeobox 2 (MSX2) as the downstream effector in these events. Mechanistically, we showed that SP6 interacts with histone acetyltransferase P300 to alter the landscape of H3K27ac at targeted regulatory elements, thereby favoring transcriptional activation and facilitating CT cell fate decisions and TSC maintenance. Our results established SP6 as a regulator of the human trophoblast lineage and implied its role in placental development and the pathogenies of placental diseases.
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Affiliation(s)
- Yanglin Chen
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Xianhua Ye
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Yulong Zhong
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Xiangjin Kang
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, China
| | - Yanqing Tang
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Haoyun Zhu
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Changmiao Pang
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Shaoqiang Ning
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Shiqing Liang
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Feifan Zhang
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Chao Li
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Jie Li
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Chengtao Gu
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Yuanxiong Cheng
- Department of Respiratory and Critical Care Medicine, The Third Affiliated Hospital, Southern Medical University, Guangzhou 510630, Guangdong, China
| | - Zhanpeng Kuang
- Department of Pediatrics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jingyang Qiu
- Department of Cell Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Jin Jin
- Department of Gynaecology and Obstetrics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Haisi Luo
- Department of Gynaecology and Obstetrics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Mingyu Fu
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Hannah Xiaoyan Hui
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong 999077, China
| | - Lei Li
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, China; Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510515, China
| | - Degong Ruan
- School of Biomedical Sciences, Stem Cell, and Regenerative Medicine Consortium, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China
| | - Pentao Liu
- School of Biomedical Sciences, Stem Cell, and Regenerative Medicine Consortium, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China
| | - Xi Chen
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Liangzhong Sun
- Department of Pediatrics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Shanshan Ai
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
| | - Xuefei Gao
- Guangdong Provincial Key Laboratory of Bone and Joint Degenerative Diseases, Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; Department of Respiratory and Critical Care Medicine, The Third Affiliated Hospital, Southern Medical University, Guangzhou 510630, Guangdong, China; Department of Pediatrics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
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Liu W, Jiang X, Deng Z, Xie Y, Guo Y, Wu Y, Sun Q, Kong L, Wu F, Tang Y. Functional and structural alterations in different durations of untreated illness in the frontal and parietal lobe in major depressive disorder. Eur Arch Psychiatry Clin Neurosci 2024; 274:629-642. [PMID: 37542558 PMCID: PMC10995069 DOI: 10.1007/s00406-023-01625-7] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 05/22/2023] [Indexed: 08/07/2023]
Abstract
Major depressive disorder (MDD) is one of the most disabling illnesses that profoundly restricts psychosocial functions and impairs quality of life. However, the treatment rate of MDD is surprisingly low because the availability and acceptability of appropriate treatments are limited. Therefore, identifying whether and how treatment delay affects the brain and the initial time point of the alterations is imperative, but these changes have not been thoroughly explored. We investigated the functional and structural alterations of MDD for different durations of untreated illness (DUI) using regional homogeneity (ReHo) and voxel-based morphometry (VBM) with a sample of 125 treatment-naïve MDD patients and 100 healthy controls (HCs). The MDD patients were subgrouped based on the DUI, namely, DUI ≤ 1 M, 1 < DUI ≤ 6 M, 6 < DUI ≤ 12 M, and 12 < DUI ≤ 48 M. Subgroup comparison (MDD with different DUIs) was applied to compare ReHo and grey matter volume (GMV) extracted from clusters of regions with significant differences (the pooled MDD patients relative to HCs). Correlations and mediation effects were analysed to estimate the relationships between the functional and structural neuroimaging changes and clinical characteristics. MDD patients exhibited decreased ReHo in the left postcentral gyrus and precentral gyrus and reduced GMV in the left middle frontal gyrus and superior frontal gyrus relative to HCs. The initial functional abnormalities were detected after being untreated for 1 month, whereas this duration was 3 months for GMV reduction. Nevertheless, a transient increase in ReHo was observed after being untreated for 3 months. No significant differences were discovered between HCs and MDD patients with a DUI less than 1 month or among MDD patients with different DUIs in either ReHo or GMV. Longer DUI was related to reduced ReHo with GMV as mediator in MDD patients. We identified disassociated functional and anatomical alterations in treatment-naïve MDD patients at different time points in distinct brain regions at the early stage of the disease. Additionally, we also discovered that GMV mediated the relationship between a longer DUI and diminished ReHo in MDD patients, disclosing the latent deleterious and neuro-progressive implications of DUI on both the structure and function of the brain and indicating the necessity of early treatment of MDD.
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Affiliation(s)
- Wen Liu
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Xiaowei Jiang
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
- Department of Radiology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Zijing Deng
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Yu Xie
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Yingrui Guo
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Yifan Wu
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Qikun Sun
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Lingtao Kong
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Feng Wu
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China.
- Department of Gerontology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China.
- Department of Psychiatry and Geriatric Medicine, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, People's Republic of China.
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Chen JL, Tang Y, Qin DL, Li ZL, Tang ZH, Quan ZW. [Prediction of prognosis of patients with radical resection of intrahepatic cholangiocarcinoma based on single cell omics]. Zhonghua Wai Ke Za Zhi 2024; 62:316-323. [PMID: 38432673 DOI: 10.3760/cma.j.cn112139-20231215-00276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
Objectives: To analyze the survival benefit of intrahepatic cholangiocarcinoma (ICC) radical resection based on single cell omics. Methods: This is a retrospective case-series study. ICC single-cell sequencing was integrated from four data sets in the Gene Expression Omnibus Database, with a total of 46 patients undergoing radical resection, to explore the characteristics of the microenvironment. Microarray data of 100 ICC cases was analyzed in the EMBI database with survival data. The infiltration abundance of each epithelial cell cluster was calculated in each microarray data sample using the ssGSEA algorithm. The key epithelial cell cluster associated with poor patient outcomes was explored. The clinical value of key marker genes in this subgroup was studied. Prognostic marker genes were selected using the univariate and multivariate Cox proportional hazards(CoxPH) model. The The CoxPH model was constructed by the target genes and a nomogram was drawn. Kaplan-Meier survival analysis was used to verify the relationship between score and prognosis of patients. The predictive power of the model was evaluated by receiver operating characteristic(ROC) curves, calibration curves, and decision curve analysis (DCA). Results: Epithelial cell clusters infiltrated almost exclusively in tumor tissue. The MT2A+ epithelial cell subset was associated with a poorer prognosis for patients with a high invasion abundance and patients characterized by infiltration of this group were defined as antioxidant. After screening marker genes in this cluster using a univariate and multivariate CoxPH model, the following genes were found to be independent prognostic factors: FILPIL, NFKBIA, PEG10, SERPINB5. The CoxPH model was constructed using the four gene expression levels, and the survival rate of patients in the high-risk group was significantly lower than those in the low-risk group (all P<0.05). The constructed nomogram had good discrimination and validity. The ROC curve showed that the predicted area under the curve was 0.779, 0.844 and 0.845 at 1, 3 and 5 years, respectively. Compared to clinical indicators, the model had better predictive power using the calibration curve and the DCA test. Conclusions: The MT2A+ epithelial cell group may be associated with the prognosis of patients with ICC, and the concept of ICC tissue typing of antioxidant and non-antioxidant types is proposed. The type of antioxidant may predict the poor prognosis of the patients, and postoperative adjuvant therapy and other means could be considered to improve the survival of the patients.
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Affiliation(s)
- J L Chen
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092,China
| | - Y Tang
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092,China
| | - D L Qin
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092,China
| | - Z L Li
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092,China
| | - Z H Tang
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092,China
| | - Z W Quan
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092,China
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Qin DL, Chen JL, Tang Y, Li ZL, Tang ZH, Quan ZW. [New advances in the diagnosis and treatment of intrahepatic cholangiocarcinoma]. Zhonghua Wai Ke Za Zhi 2024; 62:331-337. [PMID: 38432675 DOI: 10.3760/cma.j.cn112139-20231215-00274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
Intrahepatic cholangiocarcinoma (ICC) is a type of primary liver cancer, which has shown an increasing trend in incidence and mortality in recent years, with a poor prognosis. The clinical diagnosis and treatment of ICC currently face the challenges of low detection rate, high mortality rate, poor treatment outcome, and urgently need more in-depth research to promote the improvement of clinical diagnosis and treatment level. In recent years, ICC diagnosis and treatment related research has made new progress in many aspects, and the knowledge about these new clinical diagnosis and treatment advances should be updated in a timely manner. This article reviewed the latest research results in recent years, summarized some new views on ICC typing, prevention and diagnosis staging that have been proposed recently, as well as the new progress made in surgical treatment and systemic treatment, and briefly discussed the potential of ICC individualized precision treatment and the occurrence of rare complications caused by combined treatment.
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Affiliation(s)
- D L Qin
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - J L Chen
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Y Tang
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Z L Li
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Z H Tang
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Z W Quan
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
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Jia P, Tang Y, Niu L, Qiu L. Clinical and radiographic outcomes of a combined surgery approach to treat peri-implantitis. Int J Oral Maxillofac Surg 2024; 53:333-342. [PMID: 38154998 DOI: 10.1016/j.ijom.2023.11.013] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 11/17/2023] [Accepted: 11/22/2023] [Indexed: 12/30/2023]
Abstract
Peri-implant infra-bony defects are difficult to treat, and data on the management of peri-implantitis are lacking. The aim of this study was to evaluate the effect of a combined surgical approach to manage peri-implantitis: implantoplasty with xenogeneic bone grafting and a concentrated growth factor membrane. Two independent examiners analysed the medical records and radiographs taken before surgery and at the last follow-up. Data were analysed at the implant level; some patient-level data (age, sex, smoking habit) were also considered. Linear regression analysis with generalized estimating equations (GEE) was used to explore the effect of variables of interest (including marginal bone level (MBL)) on implantitis treatment success and resolution rates. The effect of the prosthesis type on postoperative clinical and radiographic parameters was also explored by GEE, with adjustment for age, sex, tooth site, location, follow-up duration, and implant length (model IV including all). Thirty patients with 72 implants were investigated. The implant survival rate was 100% over a mean observation period of 3.3 years (range 2-11 years). The treatment success rate (bone loss <0.5 mm, no bleeding on probing (BOP), no suppuration, probing depth (PD) < 5 mm) was higher in females than males (50% vs 19.0%; P = 0.008). At the last postoperative follow-up, the MBL (1.51 ± 1.07 vs 4.01 ± 1.13 mm), PD (3.61 ± 0.84 vs 6.54 ± 1.01 mm), and BOP (23.38 ± 23.18% vs 79.17 ± 15.51%) were significantly reduced when compared to pre-surgery values (all P < 0.001). Furthermore, a significantly higher PD reduction (β = -1.10 mm, 95% confidence interval -1.97 to -0.23 mm, P = 0.014) was observed for implants with a single crown than a full-arch prosthesis (GEE model IV). Preliminary clinical and radiographic data indicate that implantoplasty in combination with surgery could be an effective treatment option for peri-implantitis.
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Affiliation(s)
- P Jia
- Fourth Division, Peking University School and Hospital of Stomatology, China; National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, China; Research Center of Engineering and Technology for Digital Dentistry of the Ministry of Health, China; Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - Y Tang
- Fourth Division, Peking University School and Hospital of Stomatology, China; National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, China; Research Center of Engineering and Technology for Digital Dentistry of the Ministry of Health, China; Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - L Niu
- Fourth Division, Peking University School and Hospital of Stomatology, China; National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, China; Research Center of Engineering and Technology for Digital Dentistry of the Ministry of Health, China; Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - L Qiu
- Fourth Division, Peking University School and Hospital of Stomatology, China; National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, China; Research Center of Engineering and Technology for Digital Dentistry of the Ministry of Health, China; Beijing Key Laboratory of Digital Stomatology, Beijing, China.
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Xing Y, Qin Q, Wang ZB, Wang DY, Li SY, Sun YW, Jin HM, Wu GS, Cai LJ, Wang XY, Tang Y. [Observation of the consistency between intellectualized and manual-based cognitive assessment tools in the outpatient clinic]. Zhonghua Yi Xue Za Zhi 2024; 104:600-607. [PMID: 38264825 DOI: 10.3760/cma.j.cn112137-20231129-01234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
Objective: The intellectualized versions of the Montreal Cognitive Assessment Scale (MoCA) and the Mini-mental State Examination (MMSE) (i-MoCA/i-MMSE) were developed. The validity of this system was evaluated in a clinical sample through comparing with the manual-based assessments. Methods: A total of 88 patients [aged (66.82±11.37) years, 30 males and 58 females] were enrolled in the outpatient clinic of Xuanwu Hospital of Capital Medical University with complaints of cognitive decline, from February to October 2023. All participants completed manual-based and intellectualized assessments in a randomized order, with an interval of 2 weeks to control for the practice effect. The reliability of the intellectualized version of assessments was evaluated based on the manual-based version using the Concordance correlation coefficient (CCC). The difference between the intellectualized and the manual-based assessments was tested by the Repeated ANCOVA with demographic information controlled. The accuracy of evaluation of the i-MoCA and i-MMSE was analyzed by the Receiver Operating Characteristic (ROC) analysis. Results: High concordance was observed between the intellectualized version and the manual-based assessments (CCCMoCA=0.87, CCCMMSE=0.83). Controlling for basic demographic information, there was no significant difference in the scores of the intellectualized version and the manual-based assessments (all P>0.05). The accuracy of i-MoCA in screening patients with cognitive impairment was 94.3% (sensitivity=94.6%, specificity=78.1%), while the accuracy of i-MMSE in screening patients with cognitive impairment was 94.9% (sensitivity=94.9%, specificity=77.6%). In addition, the majority of subdomains measured by the cognitive assessments exhibited high consistency across the intellectualized the manual-based versions (CCCMoCA=0.32-0.78; CCCMMSE=0.54-0.79). Conclusion: Both the i-MoCA and i-MMSE showed high consistency and diagnostic accuracy with the manual-based versions in terms of overall cognitive function and subdomains.
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Affiliation(s)
- Y Xing
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Q Qin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Z B Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - D Y Wang
- Beijing Wise Spirit Technology Limited, Beijing 100192, China
| | - S Y Li
- Beijing Wise Spirit Technology Limited, Beijing 100192, China
| | - Y W Sun
- Beijing Wise Spirit Technology Limited, Beijing 100192, China
| | - H M Jin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - G S Wu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - L J Cai
- Beijing Wise Spirit Technology Limited, Beijing 100192, China
| | - X Y Wang
- Beijing Wise Spirit Technology Limited, Beijing 100192, China
| | - Y Tang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
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9
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Liu W, Liu L, Deng Z, Liu R, Ma T, Xin Y, Xie Y, Zhou Y, Tang Y. Associations between impulsivity and fecal microbiota in individuals abstaining from methamphetamine. CNS Neurosci Ther 2024; 30:e14580. [PMID: 38421126 PMCID: PMC10851322 DOI: 10.1111/cns.14580] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 12/13/2023] [Accepted: 12/15/2023] [Indexed: 03/02/2024] Open
Abstract
INTRODUCTION Methamphetamine (MA) abuse is a major public problem, and impulsivity is both a prominent risk factor and a consequence of addiction. Hence, clarifying the biological mechanism of impulsivity may facilitate the understanding of addiction to MA. The microbiota-gut-brain axis was suggested to underlie a biological mechanism of impulsivity induced by MA. METHODS We therefore recruited 62 MA addicts and 50 healthy controls (HCs) to investigate the alterations in impulsivity and fecal microbiota and the associations between them in the MA group. Thereafter, 25 MA abusers who abstained from MA for less than 3 months were followed up for 2 months to investigate the relationship between impulsivity and microbiota as abstinence became longer. 16S rRNA sequencing was conducted for microbiota identification. RESULTS Elevated impulsivity and dysbiosis characterized by an increase in opportunistic pathogens and a decrease in probiotics were identified in MA abusers, and both the increased impulsivity and disrupted microbiota tended to recover after longer abstinence from MA. Impulsivity was related to microbiota, and the effect of MA abuse on impulsivity was mediated by microbiota. CONCLUSION Our findings potentially highlighted the importance of abstention and implicated the significant role of the microbiota-gut-brain axis in the interrelationship between microbiota and behaviors, as well as the potential of microbiota as a target for intervention of impulsivity.
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Affiliation(s)
- Wen Liu
- Department of PsychiatryThe First Hospital of China Medical UniversityShenyangLiaoningPR China
| | - Linzi Liu
- Department of PsychiatryThe First Hospital of China Medical UniversityShenyangLiaoningPR China
| | - Zijing Deng
- Department of PsychiatryThe First Hospital of China Medical UniversityShenyangLiaoningPR China
| | - Ruina Liu
- Department of PsychiatryThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anShanxiPR China
| | - Tao Ma
- Department of PsychiatryThe First Hospital of China Medical UniversityShenyangLiaoningPR China
| | - Yide Xin
- Department of PsychiatryThe First Hospital of China Medical UniversityShenyangLiaoningPR China
| | - Yu Xie
- Department of PsychiatryThe First Hospital of China Medical UniversityShenyangLiaoningPR China
| | - Yifang Zhou
- Department of PsychiatryThe First Hospital of China Medical UniversityShenyangLiaoningPR China
| | - Yanqing Tang
- Department of PsychiatryShengjing Hospital of China Medical UniversityShenyangLiaoningPR China
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Zheng J, Womer FY, Tang L, Guo H, Zhang X, Tang Y, Wang F. Integrative omics analysis reveals epigenomic and transcriptomic signatures underlying brain structural deficits in major depressive disorder. Transl Psychiatry 2024; 14:17. [PMID: 38195555 PMCID: PMC10776753 DOI: 10.1038/s41398-023-02724-8] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/11/2023] [Accepted: 12/19/2023] [Indexed: 01/11/2024] Open
Abstract
Several lines of evidence support the involvement of transcriptomic and epigenetic mechanisms in the brain structural deficits of major depressive disorder (MDD) separately. However, research in these two areas has remained isolated. In this study, we proposed an integrative strategy that combined neuroimaging, brain-wide gene expression, and peripheral DNA methylation data to investigate the genetic basis of gray matter abnormalities in MDD. The MRI T1-weighted images and Illumina 850 K DNA methylation microarrays were obtained from 269 patients and 416 healthy controls, and brain-wide transcriptomic data were collected from Allen Human Brain Atlas. The between-group differences in gray matter volume (GMV) and differentially methylated CpG positions (DMPs) were examined. The genes with their expression patterns spatially related to GMV changes and genes with DMPs were overlapped and selected. Using principal component regression, the associations between DMPs in overlapped genes and GMV across individual patients were investigated, and the region-specific correlations between methylation status and gene expression were examined. We found significant associations between the decreased GMV and DMPs methylation status in the anterior cingulate cortex, inferior frontal cortex, and fusiform face cortex regions. These DMPs genes were primarily enriched in the neurodevelopmental and synaptic transmission process. There was a significant negative correlation between DNA methylation and gene expression in genes associated with GMV changes of the frontal cortex in MDD. Our findings suggest that GMV abnormalities in MDD may have a transcriptomic and epigenetic basis. This imaging-transcriptomic-epigenetic integrative analysis provides spatial and biological links between cortical morphological deficits and peripheral epigenetic signatures in MDD.
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Affiliation(s)
- Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Fay Y Womer
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lili Tang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Huiling Guo
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China.
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China.
- Department of Gerontology, The First Hospital of China Medical University, Shenyang, China.
- Shengjing Hospital of China Medical University, Shenyang, China.
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China.
- Department of Mental Health, School of Public Health, Nanjing Medical University, Nanjing, China.
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11
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Jiang X, Cao B, Li C, Jia L, Jing Y, Cai W, Zhao W, Sun Q, Wu F, Kong L, Tang Y. Identifying misdiagnosed bipolar disorder using support vector machine: feature selection based on fMRI of follow-up confirmed affective disorders. Transl Psychiatry 2024; 14:9. [PMID: 38191549 PMCID: PMC10774279 DOI: 10.1038/s41398-023-02703-z] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 11/27/2023] [Accepted: 12/05/2023] [Indexed: 01/10/2024] Open
Abstract
Nearly a quarter of bipolar disorder (BD) patients were misdiagnosed as major depressive disorder (MDD) patients, which cannot be corrected until mania/hypomania develops. It is important to recognize these obstacles so that the appropriate treatment can be initiated. Thus, we sought to distinguish patients with BD from MDD, especially to identify misdiagnosed BD before mania/hypomania, and further explore potential trait features that allow accurate differential diagnosis independent of state matters. Functional magnetic resonance imaging scans were performed at baseline on 92 MDD patients and 48 BD patients. The MDD patients were then followed up for more than two years. After follow-up, 23 patients transformed into BD (tBD), and 69 patients whose diagnoses remained unchanged were eligible for unipolar depression (UD). A support vector machine classifier was trained on the amygdala-based functional connectivity (FC) of 48 BD and 50 UD patients using a novel region-based feature selection. Then, the classifier was tested on the dataset, encompassing tBD and the remaining UD. It performed well for known BD and UD and can also distinguish tBD from UD with an accuracy of 81%, sensitivity of 82.6%, specificity of 79%, and AUC of 74.6%, respectively. Feature selection results revealed that ten regions within the cortico-limbic neural circuit contributed most to classification. Furthermore, in the FC comparisons among diseases, BD and tBD shared almost overlapped FC patterns in the cortico-limbic neural circuit, and both of them presented pronounced differences in most regions within the circuit compared with UD. The FC values of the most discriminating brain regions had no prominent correlations with the severity of depression, anxiety, and mania/hypomania (FDR correction). It suggests that BD possesses some trait features in the cortico-limbic neural circuit, rendering it dichotomized by the classifier based on known-diagnosis data.
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Affiliation(s)
- Xiaowei Jiang
- Brain Function Research Section, Department of Radiology, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, T6G 2B7, Canada
| | - Chao Li
- Brain Function Research Section, Department of Radiology, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Linna Jia
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Yi Jing
- Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, Liaoning, 110167, PR China
| | - Wei Cai
- Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, Liaoning, 110167, PR China
| | - Wenhui Zhao
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Qikun Sun
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Feng Wu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Lingtao Kong
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China.
- Department of Geriatric Medicine, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China.
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12
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Chen Y, Zhao P, Pan C, Chang M, Zhang X, Duan J, Wei Y, Tang Y, Wang F. State- and trait-related dysfunctions in bipolar disorder across different mood states: a graph theory study. J Psychiatry Neurosci 2024; 49:E11-E22. [PMID: 38238036 PMCID: PMC10803102 DOI: 10.1503/jpn.230069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/10/2023] [Accepted: 09/14/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND The interplay between state- and trait-related disruptions in structural networks remains unclear in bipolar disorder (BD), but graph theory can offer insights into global and local network changes. We sought to use diffusion-tensor imaging (DTI) and graph theory approaches to analyze structural topological properties across distinct mood states and identify high-risk individuals by examining state- and trait-related impairments in BD. METHODS We studied changes in white matter network among patients with BD and healthy controls, exploring relationships with clinical variables. Secondary analysis involved comparing patients with BD with unaffected people at high genetic risk for BD. RESULTS We included 152 patients with BD, including 52 with depressive BD (DBD), 64 with euthymic BD (EBD) and 36 with manic BD (MBD); we also included 75 healthy controls. Secondary analyses involved 27 unaffected people at high genetic risk for BD. Patients with DBD and MBD exhibited significantly lower global efficiencies than those with EBD and healthy controls, with patients with DBD showing the lowest global efficiencies. In addition, patients with DBD displayed impaired local efficiency and normalized clustering coefficient (γ). At a global level, γ correlated negatively with depression and anxiety. Compared with healthy controls, and across mood states, patients with BD showed abnormal shortest path lengths in the frontolimbic circuit, a trend mirrored among those at high genetic risk for BD. LIMITATIONS Considerations include medication effects, absence of recorded BD episode counts and the cross-sectional nature of the study. CONCLUSION Mood-specific whole-brain network metrics could serve as potential biomarkers in BD for transitions between mood states. Moreover, these findings contribute to evidence of trait-related frontolimbic circuit irregularities, shedding light on underlying pathophysiological mechanisms in BD.
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Affiliation(s)
- Yifan Chen
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
| | - Pengfei Zhao
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
| | - Chunyu Pan
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
| | - Miao Chang
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
| | - Xizhe Zhang
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
| | - Jia Duan
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
| | - Yange Wei
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
| | - Yanqing Tang
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
| | - Fei Wang
- From the Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chen, Wang); the Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China (Chen, Zhao, Pan, Duan, Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China (Chen, Zhao, Duan, Wei, Wang); the Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China (Zhang); the School of Computer Science and Engineering, Northeastern University, Shenyang, China (Pan); and the Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China (Tang)
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Sun X, Sun J, Lu X, Dong Q, Zhang L, Wang W, Liu J, Ma Q, Wang X, Wei D, Chen Y, Liu B, Huang CC, Zheng Y, Wu Y, Chen T, Cheng Y, Xu X, Gong Q, Si T, Qiu S, Lin CP, Cheng J, Tang Y, Wang F, Qiu J, Xie P, Li L, He Y, Xia M. Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome. Biol Psychiatry 2023; 94:936-947. [PMID: 37295543 DOI: 10.1016/j.biopsych.2023.05.021] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/15/2023] [Accepted: 05/29/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND Major depressive disorder (MDD) is a highly heterogeneous disorder that typically emerges in adolescence and can occur throughout adulthood. Studies aimed at quantitatively uncovering the heterogeneity of individual functional connectome abnormalities in MDD and identifying reproducibly distinct neurophysiological MDD subtypes across the lifespan, which could provide promising insights for precise diagnosis and treatment prediction, are still lacking. METHODS Leveraging resting-state functional magnetic resonance imaging data from 1148 patients with MDD and 1079 healthy control participants (ages 11-93), we conducted the largest multisite analysis to date for neurophysiological MDD subtyping. First, we characterized typical lifespan trajectories of functional connectivity strength based on the normative model and quantitatively mapped the heterogeneous individual deviations among patients with MDD. Then, we identified neurobiological MDD subtypes using an unsupervised clustering algorithm and evaluated intersite reproducibility. Finally, we validated the subtype differences in baseline clinical variables and longitudinal treatment predictive capacity. RESULTS Our findings indicated great intersubject heterogeneity in the spatial distribution and severity of functional connectome deviations among patients with MDD, which inspired the identification of 2 reproducible neurophysiological subtypes. Subtype 1 showed severe deviations, with positive deviations in the default mode, limbic, and subcortical areas and negative deviations in the sensorimotor and attention areas. Subtype 2 showed a moderate but converse deviation pattern. More importantly, subtype differences were observed in depressive item scores and the predictive ability of baseline deviations for antidepressant treatment outcomes. CONCLUSIONS These findings shed light on our understanding of different neurobiological mechanisms underlying the clinical heterogeneity of MDD and are essential for developing personalized treatments for this disorder.
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Affiliation(s)
- Xiaoyi Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; School of Systems Science, Beijing Normal University, Beijing, China
| | - Jinrong Sun
- Department of Psychiatry and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China; Affiliated WuTaiShan Hospital of Medical College of Yangzhou University, Yangzhou Mental Health Centre, Yangzhou, China
| | - Xiaowen Lu
- Department of Psychiatry and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China; Affiliated Wuhan Mental Health Center, Huazhong University of Science and Technology, Wuhan, China
| | - Qiangli Dong
- Department of Psychiatry and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China; Department of Psychiatry, Lanzhou University Second Hospital, Lanzhou, China
| | - Liang Zhang
- Department of Psychiatry and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China; Mental Health Education and Counseling Center, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Wenxu Wang
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Jin Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qing Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Xiaoqin Wang
- Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Dongtao Wei
- Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Bangshan Liu
- Department of Psychiatry and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yankun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Taolin Chen
- Huaxi Magnetic Resonance Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Qiyong Gong
- Huaxi Magnetic Resonance Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Peng Xie
- Chongqing Key Laboratory of Neurobiology, Chongqing, China; Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lingjiang Li
- Department of Psychiatry and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
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Hao M, Qin Y, Li Y, Tang Y, Ma Z, Tan J, Jin L, Wang F, Gong X. Metabolome subtyping reveals multi-omics characteristics and biological heterogeneity in major psychiatric disorders. Psychiatry Res 2023; 330:115605. [PMID: 38006718 DOI: 10.1016/j.psychres.2023.115605] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 11/02/2023] [Accepted: 11/10/2023] [Indexed: 11/27/2023]
Abstract
Growing evidence suggests that major psychiatric disorders (MPDs) share common etiologies and pathological processes. However, the diagnosis is currently based on descriptive symptoms, which ignores the underlying pathogenesis and hinders the development of clinical treatments. This highlights the urgency of characterizing molecular biomarkers and establishing objective diagnoses of MPDs. Here, we collected untargeted metabolomics, proteomics and DNA methylation data of 327 patients with MPDs, 131 individuals with genetic high risk and 146 healthy controls to explore the multi-omics characteristics of MPDs. First, differential metabolites (DMs) were identified and we classified MPD patients into 3 subtypes based on DMs. The subtypes showed distinct metabolomics, proteomics and DNA methylation signatures. Specifically, one subtype showed dysregulation of complement and coagulation proteins, while the DNA methylation showed abnormalities in chemical synapses and autophagy. Integrative analysis in metabolic pathways identified the important roles of the citrate cycle, sphingolipid metabolism and amino acid metabolism. Finally, we constructed prediction models based on the metabolites and proteomics that successfully captured the risks of MPD patients. Our study established molecular subtypes of MPDs and elucidated their biological heterogeneity through a multi-omics investigation. These results facilitate the understanding of pathological mechanisms and promote the diagnosis and prevention of MPDs.
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Affiliation(s)
- Meng Hao
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan Zhangjiang Institute, Obstetrics and Gynecology Hospital, Human Phenome Institute, Fudan University, China
| | - Yue Qin
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan Zhangjiang Institute, Obstetrics and Gynecology Hospital, Human Phenome Institute, Fudan University, China
| | - Yi Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan Zhangjiang Institute, Obstetrics and Gynecology Hospital, Human Phenome Institute, Fudan University, China; International Human Phenome Institutes, Shanghai, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Zehan Ma
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Jingze Tan
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan Zhangjiang Institute, Obstetrics and Gynecology Hospital, Human Phenome Institute, Fudan University, China; International Human Phenome Institutes, Shanghai, China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China.
| | - Xiaohong Gong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China.
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15
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Gu ZJ, Song QJ, Gu WQ, Zhang GP, Su Y, Tang Y, Wang MF, Guo Y, Wu WM, Chen J. New approaches in the diagnosis and prognosis of gestational diabetes mellitus. Eur Rev Med Pharmacol Sci 2023; 27:10583-10594. [PMID: 37975383 DOI: 10.26355/eurrev_202311_34338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Gestational diabetes mellitus (GDM) is the most common pregnancy metabolic disorder in which a person with no history of hyperglycemia exhibits any degree of impaired glucose tolerance during gestation. GDM can be resolved on its own after birth, but mothers with GDM are more at risk for future problems, such as type 2 diabetes, obesity, and cardiovascular disease. In addition, GDM can cause macrosomia in infants and obesity or even the risk of diabetes in childhood. Standard diagnostic tests for GDM are the oral glucose tolerance test (OGTT) and glucose challenge test (GCT), which is a mandatory test at 28-28 weeks of pregnancy in most countries. Disorders in various molecular mechanisms, such as hepatocyte growth factor (HGF), mechanistic target of rapamycin (mTOR), and nuclear factor-kappaB (NF-κB) signaling pathways are involved in GDM. Therefore, a better understanding of these mechanisms can help find new therapeutic and diagnostic strategies accordingly. In this review, we first deal with molecular mechanisms involved in GDM occurrence and then summarized the studies that hired this knowledge for early diagnosis and prognosis of GDM. Finally, we present the latest achievements in the diagnosis of GDM based on exosomes, microRNAs, glycosylated hemoglobin, and inflammatory factors detection in maternal circulation.
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Affiliation(s)
- Z-J Gu
- Department of Obstetrics and Gynaecology, Taicang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Taicang, China.
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16
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Liu W, Jiang X, Xin Y, Deng Z, Xie Y, Zhou Y, Wu Y, Sun Q, Kong L, Wu F, Tang Y. Sex effects on differentiating patients with major depressive disorder from bipolar disorder in depressive state: A fMRI study with follow-up. J Affect Disord 2023; 340:396-404. [PMID: 37572701 DOI: 10.1016/j.jad.2023.08.041] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 08/04/2023] [Accepted: 08/07/2023] [Indexed: 08/14/2023]
Abstract
BACKGROUND Bipolar disorder (BD) is difficult to discriminate from major depressive disorder (MDD) before the appearance of mania or hypomania. This study was designed to identify whether patients with MDD and those who converted to BD are distinguishable using dynamic amplitude low-frequency fluctuations (dALFF) and describe the sex effects on the identification of the two disorders. METHODS We compared the dALFF values of 35 BD patients who converted from MDD during the 2-year follow-up, 99 MDD patients, and 130 healthy controls (HCs) using two-way ANOVA. Pearson's correlation was used to compare dALFF in dysfunctional brain regions and clinical characteristics. RESULTS A main effect of diagnosis was discovered in the frontal and occipital gyrus. For the main effect of sex, both the left middle occipital gyrus and the medial part of the superior frontal gyrus had higher dALFF values in males compared to females. An interaction of sex and diagnosis effect was observed in the right precentral gyrus. Male MDD patients exhibited a higher dALFF value than male BD patients. Additionally, we discovered a higher dALFF value in females than in males in BD patients. WCST scores were positively associated with dALFF values in the frontal and occipital gyrus in MDD patients. Meanwhile, dALFF values in the occipital gyrus positively correlated with WCST in female MDD patients only. LIMITATION Most of the participants were on medication and the sample size was small. CONCLUSIONS Our study is the first to find the non-neglectable role of sex effects in differentiating BD and MDD at an early stage.
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Affiliation(s)
- Wen Liu
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China; Department of Psychiatry, The First Hospital of China Medical University Shenyang 110001, Liaoning, PR China
| | - Xiaowei Jiang
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China; Department of Radiology, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China
| | - Yide Xin
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China
| | - Zijing Deng
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China; Department of Psychiatry, The First Hospital of China Medical University Shenyang 110001, Liaoning, PR China
| | - Yu Xie
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China
| | - Yifang Zhou
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China; Department of Psychiatry, The First Hospital of China Medical University Shenyang 110001, Liaoning, PR China
| | - Yifan Wu
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China; Department of Psychiatry, The First Hospital of China Medical University Shenyang 110001, Liaoning, PR China
| | - Qikun Sun
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China
| | - Lingtao Kong
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China; Department of Psychiatry, The First Hospital of China Medical University Shenyang 110001, Liaoning, PR China
| | - Feng Wu
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China; Department of Psychiatry, The First Hospital of China Medical University Shenyang 110001, Liaoning, PR China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University Shenyang 110001, Liaoning, PR China; Department of Gerontology, The First Hospital of China Medical University, Shenyang 110001, Liaoning, PR China.
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17
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Bettridge JM, Snow LC, Tang Y, Petrovska L, Lawes J, Smith RP. Using SNP addresses for Salmonella Typhimurium DT104 in routine veterinary outbreak detection. Epidemiol Infect 2023; 151:e187. [PMID: 37876041 PMCID: PMC10644063 DOI: 10.1017/s0950268823001723] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 09/12/2023] [Accepted: 09/17/2023] [Indexed: 10/26/2023] Open
Abstract
SNP addresses are a pathogen typing method based on whole-genome sequences (WGSs), assigning groups at seven different levels of genetic similarity. Public health surveillance uses it for several gastro-intestinal infections; this work trialled its use in veterinary surveillance for salmonella outbreak detection. Comparisons were made between temporal and spatio-temporal cluster detection models that either defined cases by their SNP address or by phage type, using historical data sets. Clusters of SNP incidents were effectively detected by both methods, but spatio-temporal models consistently detected these clusters earlier than the corresponding temporal models. Unlike phage type, SNP addresses appeared spatially and temporally limited, which facilitated the differentiation of novel, stable, or expanding clusters in spatio-temporal models. Furthermore, these models flagged spatio-temporal clusters containing only two to three cases at first detection, compared with a median of seven cases in phage-type models. The large number of SNP addresses will require automated methods to implement these detection models routinely. Further work is required to explore how temporal changes and different host species may impact the sensitivity and specificity of cluster detection. In conclusion, given validation with more sequencing data, SNP addresses are likely to be a valuable addition to early warning systems in veterinary surveillance.
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Affiliation(s)
- J. M. Bettridge
- Department of Epidemiological Sciences, Animal and Plant Health Agency, Weybridge, UK
- Natural Resources Institute, University of Greenwich, Chatham, UK
| | - L. C. Snow
- Department of Epidemiological Sciences, Animal and Plant Health Agency, Weybridge, UK
| | - Y. Tang
- Department of Bacteriology, Animal and Plant Health Agency, Weybridge, UK
| | - L. Petrovska
- Department of Bacteriology, Animal and Plant Health Agency, Weybridge, UK
| | - J. Lawes
- Department of Epidemiological Sciences, Animal and Plant Health Agency, Weybridge, UK
| | - R. P. Smith
- Department of Epidemiological Sciences, Animal and Plant Health Agency, Weybridge, UK
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18
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Tang Y, Ma X, Zhao SH. [Research status and progress of cardiovascular magnetic resonance molecular imaging]. Zhonghua Xin Xue Guan Bing Za Zhi 2023; 51:1090-1097. [PMID: 37859364 DOI: 10.3760/cma.j.cn112148-20230807-00057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Affiliation(s)
- Y Tang
- Department of Magnetic Resonance Imaging, Fuwai Hospital, National Center for Cardiovascular Diseases of China, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - X Ma
- Department of Magnetic Resonance Imaging, Fuwai Hospital, National Center for Cardiovascular Diseases of China, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - S H Zhao
- Department of Magnetic Resonance Imaging, Fuwai Hospital, National Center for Cardiovascular Diseases of China, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
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Yin MY, Wang Y, Tang Y, Han QH. [Human amniotic membrane plug for recurrent retinal detachment associated with pathologic myopic macular hole]. Zhonghua Yan Ke Za Zhi 2023; 59:846-849. [PMID: 37805418 DOI: 10.3760/cma.j.cn112142-20221211-00631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/09/2023]
Abstract
A 60-year-old woman presented with a history of "pathological myopia combined with macular hole retinal detachment, " for which she underwent vitrectomy, internal limiting membrane tamponade, and silicone oil filling surgery one year ago. Seven months ago, the silicone oil was removed. She now returned to seek medical attention as her visual acuity has declined by 10 diopters. Examination revealed a recurrence of macular hole retinal detachment. The patient was treated with combined amniotic membrane tamponade and silicone oil filling. During the surgery, the frozen amniotic membrane was cut into 2 mm × 2 mm and placed under the macular hole retina after silicone oil filling. Within 6 months after the surgery, her retina repositioned well, the macular hole closed, and her visual function improved from hand motion to 0.05. No severe complications were observed. Therefore, this surgical approach provides a new perspective for treating recurrent pathological myopia combined with macular hole retinal detachment.
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Affiliation(s)
- M Y Yin
- Tianjin Eye Hospital, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, Tianjin Eye Institute, Tianjin Key Laboratory of Ophthalmology and Visual Science, Tianjin 300020, China
| | - Y Wang
- Tianjin Eye Hospital, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, Tianjin Eye Institute, Tianjin Key Laboratory of Ophthalmology and Visual Science, Tianjin 300020, China
| | - Y Tang
- Tianjin Eye Hospital, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, Tianjin Eye Institute, Tianjin Key Laboratory of Ophthalmology and Visual Science, Tianjin 300020, China
| | - Q H Han
- Tianjin Eye Hospital, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, Tianjin Eye Institute, Tianjin Key Laboratory of Ophthalmology and Visual Science, Tianjin 300020, China
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Mi Y, Xue Z, Qu S, Yin Y, Huang J, Kou R, Wang X, Luo S, Li W, Tang Y. The economic burden of coronary heart disease in mainland China. Public Health 2023; 224:140-151. [PMID: 37797560 DOI: 10.1016/j.puhe.2023.08.034] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 07/06/2023] [Accepted: 08/25/2023] [Indexed: 10/07/2023]
Abstract
OBJECTIVES The aim of this study was to systematically evaluate the current economic burden of coronary heart disease (CHD) in mainland China and provide a reference for the formulation of policies to reduce the economic burden of CHD. STUDY DESIGN A systematic literature review was conducted of empirical studies on the economic burden of CHD over the past 20 years. METHODS PubMed, Web of Science, Embase, China Knowledge Resource Integrated Database and the WANFANG database were comprehensively searched for relevant articles published between 1 January 2000 and 22 December 2021. Content analysis was used to extract the data, and Stata 17.0 software was used for analysis. The median values were used to describe trends. RESULTS A total of 35 studies were included in this review. The annual median per-capita hospitalisation expense and the average expense per hospitalisation were $3544.40 ($891.64-$18,371.46) and $5407.34 ($1139.93-$8277.55), respectively. The median ratio on medical consumables expenses, drug expenses, medical examination expenses and treatment expenses were 41.59% (12.40%-63.73%), 26.90% (7.30%-60.00%), 9.45% (1.65%-33.40%) and 10.10% (2.36%-66.00%), respectively. The median per-capita hospitalisation expense in the eastern, central and western regions were $9374.45 ($2056.13-$18,371.46), $4751.5 ($2951.95-$8768.93) and $3251.25 ($891.64-$13,986.38), respectively. The median average expense per hospitalisation in the eastern and central regions were $6177.15 ($1679.15-$8277.55) and $1285.49 ($1239.93-$2197.36), respectively. The median average length of stay in the eastern, central and western regions were 9.3 days, 15.2 days and 16.1 days, respectively. CONCLUSIONS The economic burden of CHD is more severe in mainland China than in developed countries, especially in terms of the direct economic burden. In terms of the types of direct medical expenses, a proportion of medical examination expenses, treatment expenses and drug expenses were lowest in the eastern region, but medical consumables expenses were the highest in this region. This study provides guidance for the formulation of policies to reduce the economic burden of CHD in mainland China.
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Affiliation(s)
- Y Mi
- School of Public Health, Weifang Medical University, Weifang, PR China
| | - Z Xue
- School of Public Health, Weifang Medical University, Weifang, PR China
| | - S Qu
- School of Public Health, Weifang Medical University, Weifang, PR China
| | - Y Yin
- Qingdao Stomatological Hospital, Qingdao, PR China
| | - J Huang
- School of Public Health, Weifang Medical University, Weifang, PR China
| | - R Kou
- School of Public Health, Weifang Medical University, Weifang, PR China
| | - X Wang
- Personnel Department, Weifang Medical University, Weifang, PR China
| | - S Luo
- School of Management, Weifang Medical University, Weifang, PR China
| | - W Li
- School of Public Health, Weifang Medical University, Weifang, PR China.
| | - Y Tang
- School of Public Health, Weifang Medical University, Weifang, PR China.
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Zeng Q, Tang Y, Jin J. Prognostic Role and Time Varying Failure Hazard of Neoadjuvant Rectal (NAR) Scores in the Stellar Randomized Phase 3 Trial. Int J Radiat Oncol Biol Phys 2023; 117:S105. [PMID: 37784277 DOI: 10.1016/j.ijrobp.2023.06.063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) This study examined the prognostic role of the neoadjuvant rectal (NAR) score on disease-free survival (DFS) in the STELLAR phase III trial and assessed time-varying failure hazard. MATERIALS/METHODS The study included patients from the STELLAR trial who underwent total mesorecta excision and had calculable NAR scores. Chi-square tests were used to analyze the distribution of demographic information, treatment information, and NAR scores. Kaplan-Meier and Cox regression analyses assessed DFS, while smoothed hazard plots evaluated hazard variations. RESULTS Of 461 patients, 231 received total neoadjuvant therapy (TNT) and 229 received concurrent chemoradiotherapy (CRT). With a median follow-up of 37 months, 3-year DFS rates for low, intermediate, and high NAR scores were 86.2%, 72.671.8%, and 53.153.6%, respectively (P <0.001). In the TNT group, rates for the corresponding NAR score groups were 87.3%, 67.6%, and 52.4% while in the CRT group, rates were 84.7%, 76.0%, and 53.4% (both P <0.001). Multivariate analysis showed NAR scores as independent prognostic factors for DFS (intermediate vs. low, hazard ratio (HR) = 2.452.55, 95% confidence interval (CI): 1.347 - 4.4675, P <0.003; high vs. low, HR = 4.2668, 95% CI: 2.5133 - 8.727.79, P <0.001). The DFS hazardrisk rates for different NAR score groups initially increased and then decreased, peaking in the second year with rates of 5.04.6%, 11.62%, and 21.52% for low, intermediate, and high NAR scores, respectively. After the fourth year, the high NAR score still had a higher failure hazardrisk (12.5%), while the intermediate and low NAR score had a lower relapse hazardrisk (<3%). CONCLUSION The NAR score was a strong prognostic factor for DFS in the STELLAR trial, irrespective of TNT or CRT modalities. Hazard variations at different NAR score levels offer insights for personalized monitoring and warrant further investigation in clinical trials using NAR scores as endpoints. (NCT02533271).
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Affiliation(s)
- Q Zeng
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Wang SJ, Tang Y, Jing H, Fang H, Zhai Y, Chen S, Sun G, Hu C, Wang SL. Methodological and Reporting Quality of Non-Inferiority or Equivalence Designs: A Systematic Review of Trial Characteristics, Design Consideration and Interpretation in Breast Cancer Radiotherapy Trials. Int J Radiat Oncol Biol Phys 2023; 117:e212. [PMID: 37784879 DOI: 10.1016/j.ijrobp.2023.06.1102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To investigate the methodological and reporting quality of non-inferiority (NI)/equivalence trials of breast cancer radiotherapy and to provide suggestions for future NI/equivalence trials. MATERIALS/METHODS Prospective phase III randomized controlled trials (RCTs) comparing different radiation modalities in patients with breast cancer and designed or interpreted as NI/equivalence were identified in PubMed, EMBASE and Cochrane library. Two reviewers independently extracted data on trial characteristics, statistical design assumptions and analysis considerations, primary end point results and conclusions. The relationship between the number of published trials and the year of publication was assessed by simple linear regression. Trials with pre-specified NI margins as absolute risk differences were reevaluated using margins as relative risk differences. RESULTS A total of 1490 records were screened and 41 articles published between January 1, 2001 and May 9, 2022 were selected for full text review. A total of 21 trials were included (18 designed as NI and 3 as equivalence). Publication of these trials increased over time (p = 0.023). Trial interventions included dose fractionation (n = 10), partial/whole breast irradiation (n = 8) and tumor bed boost (n = 3). Eleven (52.4%) trials clearly described the non-efficacy benefits. The primary endpoints included 5-year local recurrence (LR) (n = 11), 5-year locoregional recurrence (n = 3), acute/late toxicities (n = 5), 2-year LR and cosmetic outcome (n = 1), and 10-year LR (n = 1). Only seven (33.3%) trials provided justification of the margins. The absolute and relative risk margins were both mentioned in nine (42.9%) trials' methods and reported in six (28.6%) trials' results. The analyzed populations were intention-to-treat (ITT) in 10, both ITT and per-protocol in 9 trials. Seventeen (81%) trials reported confidence interval (CI), with twelve reporting CI that agreed with the type I error used in sample size calculation, but only eight (38.1%) reported p value for NI/equivalence test. Fifteen (71.4%) trials concluded NI/equivalence. Five (23.8%) trials had misleading conclusions (four for not mentioning small sample size insufficient to confirm NI/equivalence and one for inconsistent with the published results). Thirteen (61.9%) trials reported that the protocol's initial accrual target was not met, with ten (47.6%) owing to overestimation of event rates. For trials that met NI only based on absolute margin, three of eight (37.5%) trials were classified as inconclusive with the assumed relative margins. CONCLUSION The use of NI/equivalence trials of breast cancer radiotherapy has dramatically increased recently, but there is substantial room for improvement in the methodological and reporting quality of NI/equivalence trials.
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Affiliation(s)
- S J Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- GCP center/Clinical research center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Zhai
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - G Sun
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - C Hu
- Division of Quantitative Sciences, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD
| | - S L Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Song Y, Kong J, Li N, Liu X, Li X, Zhu L, Wang Y, Fang H, Jing H, Tang Y, Li Y, Wang XH, Zhang J, Wang S. Comparison of Supraclavicular Surgery plus Radiotherapy vs. Radiotherapy Alone in Breast Cancer Patients with Synchronous Ipsilateral Supraclavicular Lymph Node Metastasis: A Multicenter Retrospective Study. Int J Radiat Oncol Biol Phys 2023; 117:e208. [PMID: 37784870 DOI: 10.1016/j.ijrobp.2023.06.1094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To evaluate and compare the outcomes of supraclavicular lymph node dissection (SLND) plus radiotherapy (RT) and RT alone for patients with synchronous ipsilateral supraclavicular lymph node metastasis (sISLM). MATERIALS/METHODS In all, 293 patients with sISLM across three centers were included. Of these, 85 (29.0%) received SLND plus RT and 208 (71.0%) received RT alone. All patients received preoperative systemic therapy followed by mastectomy or lumpectomy and axillary dissection. Supraclavicular recurrence-free survival (SCRFS), locoregional recurrence-free survival (LRRFS), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS) were evaluated by using the Kaplan-Meier method and multivariate Cox models. Multiple imputation was used for missing data. RESULTS The median follow-up duration of the RT and SLND+RT groups were 53.7 and 63.5 months, respectively. For the RT and SLND+RT groups, the 5-year SCRFS rates were 91.7% vs. 85.5% (P = 0.522), LRRFS rates were 79.1% vs. 73.1% (P = 0.412), DMFS rates were 60.4 vs. 58.8% (P = 0.708), DFS rates were 57.6% vs. 49.7% (P = 0.291), and OS rates were 71.9% vs. 62.2% (P = 0.272), respectively. There was no significant effect on any outcome when comparing SLND+RT versus RT alone in the multivariate analysis. Based on four risk factors of DFS, patients were classified into three risk groups: the intermediate- and high-risk groups had significantly lower survival outcomes than the low-risk group. SLND+RT did not improve outcomes of any risk group compared with RT alone. CONCLUSION Patients with sISLM may not benefit from SLND. Distant metastasis remained the major failure pattern, especially for intermediate- and high-risk groups with sISLM may not benefit from SLND. Distant metastasis remained the major failure pattern, especially for intermediate- and high-risk groups.
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Affiliation(s)
- Y Song
- Department of Radiation Oncology, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Kong
- The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - N Li
- Department of Radiochemotherapy, Tangshan People's Hospital., Tangshan, Hebei, China
| | - X Liu
- Department of Radiation Oncology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - X Li
- Department of Radiation Oncology, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - L Zhu
- Department of Radiation Oncology, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Y Wang
- Department of Radiochemotherapy, Tangshan People's Hospital., Tangshan, Hebei, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- GCP center/Clinical research center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X H Wang
- Department of Radiochemotherapy, People's Hospital of Tangshan City, Tangshan, China
| | - J Zhang
- Department of Radiation Oncology, Forth Hospital of Hebei Medical University, Shijiazhuang, China
| | - S Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Chen SY, Tang Y, Jing H, Fang H, Song YW, Liu YP, Jin J, Lu NN, Qi S, Chen B, Tang Y, Li YX, Wang SL. Early Cardiotoxicity in Patients Receiving Hypofractionated Radiotherapy after Breast Conserving Surgery: Analysis of a Prospective Study. Int J Radiat Oncol Biol Phys 2023; 117:e169. [PMID: 37784775 DOI: 10.1016/j.ijrobp.2023.06.1008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To evaluate the early cardiotoxicity of hypofractionated radiotherapy (HFRT) in patients with left-sided breast cancer after breast-conserving surgery, and to investigate the correlation between cardiotoxicity and cardiac dose. MATERIALS/METHODS A total of 103 women from 2017 to 2018 who received left-sided whole-breast with or without regional nodal irradiation either using deep inspiration breath-hold (DIBH) or free-breathing (FB) technique were prospectively enrolled. N-terminal pro-B-type natriuretic peptide (NT-proBNP), electrocardiogram, and radionuclide myocardial perfusion imaging were conducted before and after HFRT. Logistic regression analyses were performed to determine the association of cancer treatment, cardiac dose, and cardiovascular risk factors with cardiotoxic effects. RESULTS The mean dose (Dmean) of the heart, left anterior descending coronary artery (LAD), left ventricular (LV), and right ventricular (RV) in all patients was 403 cGy, 1685 cGy, 627 cGy, and 444 cGy, respectively. In comparison to FB, DIBH significantly reduced cardiac dose (heart Dmean 250 cGy vs. 570 cGy, LAD Dmean 1250 cGy vs. 2170 cGy, LV Dmean 420 cGy vs. 850 cGy, RV Dmean 260 cGy vs. 650 cGy; all p<0.001). With a median follow-up of 49 months (range, 2-65 months), no patients had clinical cardiac abnormalities or cardiac-related symptoms, but 42 (41%) patients had subclinical cardiac events. Among them, 41 were electrocardiogram changes, and one had LV ejection fraction decreased by 10% compared with the baseline level. Twenty-five (60%) recovered during follow-up, of which 17 (40%) experienced subclinical changes only once. The mean value of NT-proBNP did not change significantly before and after HFRT. In univariate analyses, DIBH technique significantly decreased the risk of subclinical cardiac events compared with FB (OR 0.31, 95% CI 0.14-0.71; p = 0.006); however, higher mean doses of heart and LV, anthracycline-based chemotherapy, obesity, and hypertension were associated with increased risk of subclinical cardiac events (all p<0.05). CONCLUSION Early subclinical cardiac damage after HFRT in left-sided breast cancer is dose-related, and mostly manageable and reversible without medical intervention.
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Affiliation(s)
- S Y Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- GCP center/Clinical research center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y W Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y P Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N N Lu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Qi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - B Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y X Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S L Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Gao LR, Qin S, Wei R, Tian Y, Xia W, Song YW, Wang S, Fang H, Yu T, Jing H, Liu Y, Tang Y, Qi S, Chen B, Li YX, Lu NN. Adaptive Ultra-Hypofractionated Whole-Pelvic Radiotherapy in High-Risk and Very High-Risk Prostate Cancer on 1.5-1.5 MR Linac: The Estimated Delivered Dose and Early Toxicity Results. Int J Radiat Oncol Biol Phys 2023; 117:e384. [PMID: 37785297 DOI: 10.1016/j.ijrobp.2023.06.2500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To study the feasibility and safety for patients with high-risk (HR) and very high-risk (VHR) prostate cancer treated with adaptive ultra-hypofractionated whole-pelvic radiotherapy (UHF-WPRT) on 1.5 magnetic resonance (MR)-Linac. MATERIALS/METHODS Sevenpatients with clinical stage T3a-4N0-1M0-1c consecutively treated with UHF-WPRT on a 1.5-T MR-Linac were recruited prospectively in a phase II trial (NCT05183074, ChiCTR2000033382). A 36.25 Gy dose in five fractions was delivered every other day with a boost of 40 Gy to the whole prostate, as well as 25 Gy to whole pelvic nodal area with a concomitant boost of 35 Gy to metastatic regional nodes. To estimate the delivered dose, we collected data by 3D-MR for the following stages: pre-MR, position verification-MR (PV-MR) in the Adapt-To-Shape (ATS) workflow, and 3D-MR during the beam-on phase (Bn-MR) and at the end of RT (post-MR). The target and organ-at-risk contours in the PV-MR, Bn-MR, and post-MR stages were projected from the pre-MR data by deformable image registration and manually adapted by the physician, followed by dose recalculation for the ATS plan. The cumulative acute genitourinary (GU) and gastrointestinal (GI) toxicities were evaluated as per NCI-CTCAE 5.0 criteria. The primary endpoints were acute ≥grade 3 genitourinary (GU) and gastrointestinal (GI) toxicities during the first 3 months. RESULTS Overall, 133 MR scans were collected (35 pre-MR, 35 PV-MR, 31 Bn-MR and 32 post-MR scans). With a median on-couch time of 61 minutes, the mean prostate and pelvic planning target volume (PTV)-V95% of all scans was 96.98 ± 3.06% and 96.44 ± 2.85%, respectively. The corresponding mean prostate clinical target volume (CTV)-V100% was 99.89 ± 0.32%, 98.71 ± 1.90%, 97.77 ± 2.89%, and 98.56 ± 1.72%, and the mean pelvic CTV-V100% was 97.57% ± 3.70%, 96.54 ± 3.80%, 95.43 ± 4.31%, and 94.39 ± 4.47% on pre-MR, PV-MR, Bn-MR and post-MR scans, respectively. For the 4 patients with positive nodes, the mean V100% of metastatic regional nodes was 99.89 ± 0.81%. The median V29 Gy change in the rectal wall was -1% (-18%-20%). The V29 Gy of the rectal wall increased by >15% was observed in one scan. A slight increase in the high dose of bladder wall was noted due to gradual bladder growth during the workflow. With median follow-up time of 7.3 (4.6-12.2) months, all patients were followed-up for more than 3 months. No patient was observed with acute CTCAE grade 2 or more severe GU or GI toxicities (0%). CONCLUSION UHF-RT to prostate and pelvic with ATS workflow is well tolerated by patients with HR and VHR prostate cancer, with only mild GU and GI toxicities. The 3D-MR-based dosimetry analysis demonstrated clinically acceptable estimated dose coverage of target volumes during the beam-on period.
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Affiliation(s)
- L R Gao
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Qin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - R Wei
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tian
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing, China
| | - W Xia
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y W Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - T Yu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Qi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - B Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y X Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N N Lu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Feng M, Tang Y, Fan M, Li L, Wang S, Yin Q, Ai H, Zhao S, Yin Y, Liu D, Ren Y, Li J, Li F, Lang J. Low-Dose Fractionated Radiotherapy Combined with Neoadjuvant Chemotherapy for T3-4 Nasopharyngeal Carcinoma Patients: The Preliminary Results of a Phase II Randomized Controlled Trial. Int J Radiat Oncol Biol Phys 2023; 117:e580-e581. [PMID: 37785764 DOI: 10.1016/j.ijrobp.2023.06.1921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Over 70% of NPC patients were local advanced NPC (LANPC). The 5-year local recurrence-free survival rate is only 70% in T3-4 patients. Neoadjuvant chemotherapy (NACT) followed with concurrent chemoradiotherapy (CCRT) was recommended for LANPC patients. Low-dose fractionated radiotherapy (LDFRT), which is <100cGy, induces enhanced cell killing by the hyper-radiation sensitivity phenomenon and potentiates effects of chemotherapy. The synergy of LDFRT and NACT has not been used in the clinical practice and few studies focused on it. A single arm study found the ORR of primary site was improved to 90% for head and neck squamous carcinoma patients treated with LDFRT and NACT. Our previous study found the ORR of lymph nodes was higher in LDFRT group for high-risk LANPC patients. However, another study showed there was no significant difference between LDFRT and control group for LANPC patients. So, we aimed to investigate the potential efficacy of this novel neoadjuvant therapy for T3-4 NPC patients. MATERIALS/METHODS A total of 60 pathological confirmed T3-4 (UICC/AJCC8th) NPC patients were prospectively enrolled in our study. They were randomly assigned to two groups. For the LDFRT group, the patients received 3 cycles of NACT (docetaxel 75mg/m2 D1, cisplatin 80mg/m2 D1) with LDFRT, and followed with CCRT. LDFRT was delivered as 50cGy per fraction twice a day to primary site on D1,2 for each cycle of NACT. The patients in the control group only received NACT and followed with CCRT. All the patients underwent IGRT. RECIST criteria and CTCAE 5.0 was used to evaluate the ORR and toxicity at post-NACT and the completion of CCRT. RESULTS From February 2022 to December 2022, 60 T3-4 NPC patients were included, and 30 patients for each group. For the primary site, the median volume reduction rate and the ORR after NACT was significantly improved in LDFRT group (69.27% vs 40.10%, p<0.001;93.33% vs 73.33%, p = 0.038). For the median volume reduction rate of primary site and lymph node, it was also obviously improved in LDFRT group (86.59% vs 55.43%, p<0.001). Though there was a tendency of ORR improvement in LDFRT group, but no significant difference (96.67% vs 83.33%, p = 0.195). After the completion of CCRT, the median volume reduction rate of primary site had an increased tendency in LDFRT group (96.16% vs 88.3%, p = 0.065), but the ORR had no statistical significance (LDFRT group: CR 45.8%, PR 54.2%; control group: CR 37.5%, PR 62.5%). For the toxicity, the incidence of grade 3-4 adverse events had no difference between two groups (p = 0.786). No grade 5 adverse events occurred. CONCLUSION LDFRT combined with NACT could obviously improve the median volume reduction rate and ORR of primary tumor for T3-4 NPC patients, and the toxicity was similar and tolerable. This novel treatment could be a promising strategy to improve treatment response and needed to be confirmed further.
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Affiliation(s)
- M Feng
- Sichuan Cancer Hospital, Chengdu, China; Department of Oncology, The Third People's Hospital of Sichuan Province, Chengdu, China
| | - Y Tang
- Sichuan Cancer Hospital, Chengdu, China
| | - M Fan
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - L Li
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - S Wang
- APHP, Hopitaux Universitaires Henri Mondor. Service d'Oncologie-Radiothérapie, Créteil, France
| | - Q Yin
- The Third People's Hospital of Sichuan Province, Chengdu, China
| | - H Ai
- Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
| | - S Zhao
- Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
| | - Y Yin
- Sichuan Institute of Brain Science and Brain-like Intelligence, Chengdu, China
| | - D Liu
- Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
| | - Y Ren
- Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
| | - J Li
- Sichuan Cancer Hospital & Institute, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - F Li
- sichuan cancer hospital and institution, Chengdu, China
| | - J Lang
- Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
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Feng M, Zhao S, Fan M, Li L, Wang S, Ai H, Tang Y, Yin Y, Ren Y, Li J, Li F, Lang J. Long-Term Survival Outcome for Metastatic Nasopharyngeal Carcinoma Patients Receiving Radiation to Primary and Metastatic Sites with Palliative Chemotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e581. [PMID: 37785765 DOI: 10.1016/j.ijrobp.2023.06.1922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) A total of 6% - 8% of NPC patients were initial diagnosed as distant metastatic disease. The median overall survival (OS) is only 10-15 months with palliative chemotherapy for these patients. A phase III study showed that palliative chemotherapy combined with radical radiotherapy to primary site could be a newly effective treatment method for metastatic NPC. Another phase 2, RCT found that the patients who had the solid tumors with 1-5 metastases received standard palliative care plus stereotactic body radiation therapy (SABR), and the 5-year OS were improved to 42.3%. Nevertheless, there was few studies focus on the radiation to both primary site and metastatic lesions. Therefore, we aimed to investigate the potential clinical benefits for initial diagnosed metastatic NPC patients with radiation to both primary site and distant metastatic lesions plus palliative chemotherapy. MATERIALS/METHODS Metastatic NPC patients treated with radiation to both primary site and distant metastatic lesions plus palliative chemotherapy were retrospectively collected in our hospital from May 2008 to May 2022. For treatment group, all patients underwent IGRT according to ICRU reports 50 and 62. The prescribed dose for primary site: GTVT: ≥66Gy, GTVn: ≥66Gy, CTV1: 60-66Gy, CTV2 54-60Gy, CTVln 50-54Gy. And the prescribed dose for distant metastatic lesions was more than 30Gy. For the control group, the patients treated with palliative chemotherapy were selected by propensity score matching from our hospital. The regimen for palliative chemotherapy was cisplatin-based chemotherapy every three weeks (100mg/m2 D1) for both groups. Kaplan-Meier method was used to analyze the OS. Cox regression model was used for multivariate analysis. RESULTS A total of 54 metastatic NPC patients with radiation to both primary site and distant metastatic lesions were retrospectively included in the treatment group, and another 54 patients were selected as the control group. The median follow-up time was 52 months. In the treatment group, the median age was 52 years (37-82), male (68%), female (32%), the main metastatic sites were bone (36 cases, 66%), lung (18 cases, 33%) and liver (10 cases, 18%). There were 23 oligometastasis cases and 31 cases. 3-year and 5-year OS in the treatment group were both dramatically improved than control group (63.2% vs 50.6%, p<0.05; 49.6% vs 38.9%, p<0.05). Multivariate analysis showed that T stage, liver metastatic lesion and oligometastases were the independent prognostic factors for them. CONCLUSION Palliative chemotherapy combined with radiation to primary sites and distant metastatic lesions might improve the OS for initial diagnosed distant metastatic NPC patients. More prospective clinical trials were needed to confirm it further.
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Affiliation(s)
- M Feng
- Sichuan Cancer Hospital, Chengdu, China; Department of Oncology, The Third People's Hospital of Sichuan Province, Chengdu, China
| | - S Zhao
- Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
| | - M Fan
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - L Li
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - S Wang
- University of Nebraska Medical Center, Omaha, NE
| | - H Ai
- Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
| | - Y Tang
- Sichuan Cancer Hospital, Chengdu, China
| | - Y Yin
- Sichuan Institute of Brain Science and Brain-like Intelligence, Chengdu, China
| | - Y Ren
- Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
| | - J Li
- Sichuan Cancer Hospital & Institute, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - F Li
- Department of Radiation Oncology, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - J Lang
- Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China
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Zhang W, Tang Y, Chen W, Gao Y, Wang W, Liu S, Wei L, Cai Y, Zhu Y, Cheng G, Zhang H, Wang X, Zhu S, Wang J, Li G, Yang J, Zhang K, Li N, Li Y, Jin J. Cost-Effectiveness of Short-Course Radiotherapy Based Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer in China. Int J Radiat Oncol Biol Phys 2023; 117:e356-e357. [PMID: 37785230 DOI: 10.1016/j.ijrobp.2023.06.2439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The phase III STELLAR (NCT02533271) trial demonstrated that four cycles of chemotherapy after short-course radiotherapy (SCRT-TNT) were not inferior to the standard care of long-course concurrent radiotherapy (LCRT) in patients with locally advanced rectal cancer (LARC). This study assessed the cost-effectiveness of SCRT-TNT versus LCRT in locally advanced rectal cancer in China on the basis of the STELLAR trial. MATERIALS/METHODS A Markov model was used to synthesize the healthcare costs and benefits of LARC patients based on results from the STELLAR trial. The model assumes that LARC who meet the inclusion criteria of the STELLAR trial experience four possible states: No Evidence of Disease (NED), locally recurrence, distant metastases, or any death from rectal cancer or other unrelated causes, where local recurrence continues to be classified as resectable and unresectable. The transition status period is 3 month, and 5 years is used to calculate direct medical costs and health benefits. The probabilities of states transition after SCRT-TNT or LCRT were derived from the results of the STELLAR trial and previous published article (Table.1). Costs were evaluated from the Chinese payer's perspective reported in early 2022 US dollars (US$1 = 6.78 Chinese Yuan). Sensitivity analyses were performed for key variables. Cost-effectiveness was evaluated using the incremental cost-effectiveness ratio and net monetary benefits. Effectiveness was defined as quality-adjusted life-years (QALYs). Willingness-to-pay (WTP) threshold was set at $43500/QALY. Data were collected from October 3, 2020, to September 20, 2021, and analyzed from November 15, 2020, to October 25, 2021. RESULTS During the 5-year horizon, for the base case scenario, SCRT-TNT incurred a lower total cost and higher QALYs compared with LCCRT. The total cost was $65767 and QALYs were 1.77 for SCRT-TNT; for LCCRT, the total cost was $72802 and QALYs were 1.64. This resulted in an ICER of -$ 55470.69 per QALY. Therefore, SCRT-TNT was a cost-saving and dominating treatment strategy compared with LCRT. Sensitivity analysis showed that ICERs were most sensitive to the parameters of distant metastases risk after treatment. CONCLUSION SCRT-TNT in locally advanced rectal cancer can be a cost-effective alternative to LCRT in China, and should be considered in appropriately selected patients.
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Affiliation(s)
- W Zhang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Y Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - W Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Gao
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - W Wang
- Guizhou Provincial Cancer Hospital, GUIZHOU, China
| | - S Liu
- Jilin Provincial Cancer Hospital, Changchun, China
| | - L Wei
- Department of Radiation Oncology, First Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Y Cai
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Zhu
- Zhejiang Cancer Hospital, Hangzhou, China
| | - G Cheng
- Department of Radiation Oncology, China-Japan Union Hospital of Jilin University, Changchun 130033, China
| | - H Zhang
- Department of Radiation and Medical Oncology, Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China, Wuhan, China
| | - X Wang
- Department of Radiation Oncology/Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - S Zhu
- Hunan Cancer Hospital, Changsha, Hunan province, China
| | - J Wang
- Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - G Li
- Department of Radiation Oncology, National Geriatrics Center, Beijing Hospital of the Ministry of Health, Beijing, China
| | - J Yang
- Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - K Zhang
- Qinghai Red Cross Hospital, XINING, China
| | - N Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China; Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, Beijing, China
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Zhao X, Fang H, Jing H, Zhang N, Zhang J, Jin J, Zhong Q, Yang WF, Zhong Y, Dong L, Tie J, Wu HF, Wang XH, Lu Y, Hou X, Zhao L, Qi S, Song Y, Liu Y, Tang Y, Lu N, Chen B, Tang Y, Li Y, Wang S. Lymphocyte Count Kinetics and the Effect of Different Radiotherapy Techniques on Radiation-Induced Lymphopenia in Patients with Breast Cancer Receiving Hypofractionated Postmastectomy Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e216-e217. [PMID: 37784888 DOI: 10.1016/j.ijrobp.2023.06.1112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Radiation-induced lymphopenia (RIL) is associated with poor prognosis in solid tumors. This study aimed to describe the lymphocyte kinetics in patients with breast cancer receiving hypofractionated postmastectomy radiotherapy (RT) and to investigate the association of different RT techniques with RIL. MATERIALS/METHODS We assessed 607 patients who received hypofractionated postmastectomy RT for breast cancer in our prospective clinical database from 8 hospitals. All patients received irradiation to the chest wall and supraclavicular fossa. RT techniques included integrated RT with the photon-based intensity modulated techniques to irradiate all target volumes (integrated RT) and a hybrid approach combining photon irradiation to supraclavicular nodes and electron irradiation to the chest wall (hybrid RT). Peripheral lymphocyte counts (PLC) were tested prior to RT (baseline), weekly during RT, at 1, 2 weeks, 3, 6 months after RT, and then every 6 months. Grade 3+ RIL was defined as PLC nadir during RT of <0.5 ×103/ml. Mean PLC was compared by the t test. Univariate, multivariate, and propensity score matching (PSM) analyses were used to evaluate the effect of different RT techniques on grade 3+ RIL. RESULTS During RT, 121 (19.9%) of patients had grade 3+ RIL. The PLC started to recover at 1 week and reached baseline levels 1 year after RT. A greater proportion of the patients treated with the integrated RT (90/269, 33.5%) developed grade 3+ PLC compared with those receiving hybrid RT (31/338, 9.2%, P < 0.001). After conducting PSM, multivariate analyses showed lower baseline PLC (HR = 0.15, P<0.001) and RT technique (the integrated RT vs. hybrid RT, HR = 4.76, P<0.001) were independent risk factors for grade 3+ RIL. The PLC in patients receiving the integrated RT after RT were higher than that in those receiving hybrid RT (p<0.05). CONCLUSION RT technique affect the risk of and recovery from RIL, which may impact survival. Choosing appropriate RT technique to minimize RIL might be considered to benefit their outcomes.
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Affiliation(s)
- X Zhao
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N Zhang
- Department of Radiation Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China
| | - J Zhang
- Department of Radiation Oncology, Forth Hospital of Hebei Medical University, Shijiazhuang, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Q Zhong
- Department of Radiation Oncology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - W F Yang
- Department of Radiation Oncology, Affiliated Taizhou hospital of Wenzhou Medical University, Taizhou, China
| | - Y Zhong
- Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - L Dong
- Department of Radiation Oncology, The First Hospital, Jilin University, Changchun, China
| | - J Tie
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - H F Wu
- Department of Radiation Oncology, Jilin Cancer Hospital, Changchun, China
| | - X H Wang
- Department of Radiochemotherapy, People's Hospital of Tangshan City, Tangshan, China
| | - Y Lu
- Department of Radiation Oncology, Cancer Hospital of Henan Province, Zhengzhou, Henan, China
| | - X Hou
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of medical Sciences & Peking Union Medical College, Beijing, China
| | - L Zhao
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - S Qi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N Lu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - B Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- GCP center/Clinical research center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Li
- Department of Radiation Oncology, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Fang H, Hou YR, Huang HY, Wu DW, Jia SP, Tang Y, Li N. [International comparison and assessment of the quality of drug clinical trial implementation in China based on scientific regulatory system]. Zhonghua Zhong Liu Za Zhi 2023; 45:1-7. [PMID: 37749051 DOI: 10.3760/cma.j.cn112152-20230805-00060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
With the rapid development of clinical research and the continuous enhancement of innovation capability in China, the quality of clinical research under China's scientific regulatory system has drawn widespread attention. This study evaluated the quality results of China's drug clinical trials implementation, compared the scientific regulatory systems of clinical research quality between China and the United States, analyzed real-world clinical application on the approval of new anti-tumor drugs through clinical trials, in order to analyze China's status and level of clinical trial implementation quality in the international industry, and explore the advantages and value of China's clinical research scientific regulation by collecting clinical trial data inspections disclosed by regulatory agencies in both China and the United States, as well as verifying information on the approval of new anti-tumor drugs.
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Affiliation(s)
- H Fang
- Department of Clinical Trial Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y R Hou
- Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, China
| | - H Y Huang
- Department of Clinical Trial Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - D W Wu
- Department of Clinical Trial Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S P Jia
- Department of Clinical Trial Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y Tang
- Department of Clinical Trial Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N Li
- Department of Clinical Trial Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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31
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Sun L, Zhao T, Liang X, Xia M, Li Q, Liao X, Gong G, Wang Q, Pang C, Yu Q, Bi Y, Chen P, Chen R, Chen Y, Chen T, Cheng J, Cheng Y, Cui Z, Dai Z, Deng Y, Ding Y, Dong Q, Duan D, Gao JH, Gong Q, Han Y, Han Z, Huang CC, Huang R, Huo R, Li L, Lin CP, Lin Q, Liu B, Liu C, Liu N, Liu Y, Liu Y, Lu J, Ma L, Men W, Qin S, Qiu J, Qiu S, Si T, Tan S, Tang Y, Tao S, Wang D, Wang F, Wang J, Wang P, Wang X, Wang Y, Wei D, Wu Y, Xie P, Xu X, Xu Y, Xu Z, Yang L, Yuan H, Zeng Z, Zhang H, Zhang X, Zhao G, Zheng Y, Zhong S, He Y. Functional connectome through the human life span. bioRxiv 2023:2023.09.12.557193. [PMID: 37745373 PMCID: PMC10515818 DOI: 10.1101/2023.09.12.557193] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The functional connectome of the human brain represents the fundamental network architecture of functional interdependence in brain activity, but its normative growth trajectory across the life course remains unknown. Here, we aggregate the largest, quality-controlled multimodal neuroimaging dataset from 119 global sites, including 33,809 task-free fMRI and structural MRI scans from 32,328 individuals ranging in age from 32 postmenstrual weeks to 80 years. Lifespan growth charts of the connectome are quantified at the whole cortex, system, and regional levels using generalized additive models for location, scale, and shape. We report critical inflection points in the non-linear growth trajectories of the whole-brain functional connectome, particularly peaking in the fourth decade of life. Having established the first fine-grained, lifespan-spanning suite of system-level brain atlases, we generate person-specific parcellation maps and further show distinct maturation timelines for functional segregation within different subsystems. We identify a spatiotemporal gradient axis that governs the life-course growth of regional connectivity, transitioning from primary sensory cortices to higher-order association regions. Using the connectome-based normative model, we demonstrate substantial individual heterogeneities at the network level in patients with autism spectrum disorder and patients with major depressive disorder. Our findings shed light on the life-course evolution of the functional connectome and serve as a normative reference for quantifying individual variation in patients with neurological and psychiatric disorders.
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Affiliation(s)
- Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Qian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chenxuan Pang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qian Yu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yanchao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Pindong Chen
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Rui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Taolin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Zhengjia Dai
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yao Deng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuyin Ding
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Zaizhu Han
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chu-Chung Huang
- Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Ruiwang Huang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ran Huo
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Lingjiang Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, China
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei
- Department of Education and Research, Taipei City Hospital, Taipei
| | - Qixiang Lin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Bangshan Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, China
| | - Chao Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ningyu Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Ying Liu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Yong Liu
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Jing Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Leilei Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Ji’nan, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jiali Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, China
| | - Xiaoqin Wang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dongtao Wei
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Yankun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Peng Xie
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiufeng Xu
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Liyuan Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Zilong Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Haibo Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xi Zhang
- Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Gai Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Suyu Zhong
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
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Liu L, Deng Z, Liu W, Liu R, Ma T, Zhou Y, Wang E, Tang Y. The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets. Front Cell Infect Microbiol 2023; 13:1257073. [PMID: 37790913 PMCID: PMC10543748 DOI: 10.3389/fcimb.2023.1257073] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 08/29/2023] [Indexed: 10/05/2023] Open
Abstract
Background Methamphetamine use disorder (MUD) poses a considerable public health threat, and its identification remains challenging due to the subjective nature of the current diagnostic system that relies on self-reported symptoms. Recent studies have suggested that MUD patients may have gut dysbiosis and that gut microbes may be involved in the pathological process of MUD. We aimed to examine gut dysbiosis among MUD patients and generate a machine-learning model utilizing gut microbiota features to facilitate the identification of MUD patients. Method Fecal samples from 78 MUD patients and 50 sex- and age-matched healthy controls (HCs) were analyzed by 16S rDNA sequencing to identify gut microbial characteristics that could help differentiate MUD patients from HCs. Based on these microbial features, we developed a machine learning model to help identify MUD patients. We also used public data to verify the model; these data were downloaded from a published study conducted in Wuhan, China (with 16 MUD patients and 14 HCs). Furthermore, we explored the gut microbial features of MUD patients within the first three months of withdrawal to identify the withdrawal period of MUD patients based on microbial features. Results MUD patients exhibited significant gut dysbiosis, including decreased richness and evenness and changes in the abundance of certain microbes, such as Proteobacteria and Firmicutes. Based on the gut microbiota features of MUD patients, we developed a machine learning model that demonstrated exceptional performance with an AUROC of 0.906 for identifying MUD patients. Additionally, when tested using an external and cross-regional dataset, the model achieved an AUROC of 0.830. Moreover, MUD patients within the first three months of withdrawal exhibited specific gut microbiota features, such as the significant enrichment of Actinobacteria. The machine learning model had an AUROC of 0.930 for identifying the withdrawal period of MUD patients. Conclusion In conclusion, the gut microbiota is a promising biomarker for identifying MUD and thus represents a potential approach to improving the identification of MUD patients. Future longitudinal studies are needed to validate these findings.
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Affiliation(s)
- Linzi Liu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Zijing Deng
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Wen Liu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Ruina Liu
- Department of Psychiatry, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Tao Ma
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Yifang Zhou
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Enhui Wang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Yanqing Tang
- Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
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Zeng K, Zeng Y, Zhan H, Zhan Z, Wang L, Xie Y, Tang Y, Li C, Chen Y, Li S, Liu M, Chen X, Liang L, Deng F, Song Y, Zhou A. SEC61G assists EGFR-amplified glioblastoma to evade immune elimination. Proc Natl Acad Sci U S A 2023; 120:e2303400120. [PMID: 37523556 PMCID: PMC10410745 DOI: 10.1073/pnas.2303400120] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 07/06/2023] [Indexed: 08/02/2023] Open
Abstract
Amplification of chromosome 7p11 (7p11) is the most common alteration in primary glioblastoma (GBM), resulting in gains of epidermal growth factor receptor (EGFR) copy number in 50 to 60% of GBM tumors. However, treatment strategies targeting EGFR have thus far failed in clinical trials, and the underlying mechanism remains largely unclear. We here demonstrate that EGFR amplification at the 7p11 locus frequently encompasses its neighboring genes and identifies SEC61G as a critical regulator facilitating GBM immune evasion and tumor growth. We found that SEC61G is always coamplified with EGFR and is highly expressed in GBM. As an essential subunit of the SEC61 translocon complex, SEC61G promotes translocation of newly translated immune checkpoint ligands (ICLs, including PD-L1, PVR, and PD-L2) into the endoplasmic reticulum and promotes their glycosylation, stabilization, and membrane presentation. Depletion of SEC61G promotes the infiltration and cytolytic activity of CD8+ T cells and thus inhibits GBM occurrence. Further, SEC61G inhibition augments the therapeutic efficiency of EGFR tyrosine kinase inhibitors in mice. Our study demonstrates a critical role of SEC61G in GBM immune evasion, which provides a compelling rationale for combination therapy of EGFR-amplified GBMs.
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Affiliation(s)
- Kunlin Zeng
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Yu Zeng
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Hongchao Zhan
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Ziling Zhan
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Li Wang
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Yuxin Xie
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Yanqing Tang
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Cuiying Li
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Yanwen Chen
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Shangbiao Li
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
- Department of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou510285, China
| | - Ming Liu
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Xiaoxia Chen
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Li Liang
- Guangdong Province Key Laboratory of Molecular Tumor Pathology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Fan Deng
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
| | - Ye Song
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou510515, China
| | - Aidong Zhou
- Department of Cell Biology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
- Department of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou510285, China
- Guangdong Province Key Laboratory of Molecular Tumor Pathology, School of Basic Medical Science, Southern Medical University, Guangzhou510515, China
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Wang Y, Zhang H, Liu L, Li Z, Zhou Y, Wei J, Xu Y, Zhou Y, Tang Y. Cognitive function and cardiovascular health in the elderly: network analysis based on hypertension, diabetes, cerebrovascular disease, and coronary heart disease. Front Aging Neurosci 2023; 15:1229559. [PMID: 37600511 PMCID: PMC10436622 DOI: 10.3389/fnagi.2023.1229559] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 07/21/2023] [Indexed: 08/22/2023] Open
Abstract
Introduction Cognitive decline in the elderly population is a growing concern, and vascular factors, such as hypertension, diabetes, cerebrovascular disease, and coronary heart disease, have been associated with cognitive impairments. This study aims to provide deeper insights into the structure of cognitive function networks under these different vascular factors and explore their potential associations with specific cognitive domains. Methods Cognitive function was assessed using a modified Chinese version of the mini-mental state examination (MMSE) scale, and intensity centrality and side weights were estimated by network modeling. The network structure of cognitive function was compared across subgroups by including vascular factors as subgroup variables while controlling for comorbidities and confounders. Results The results revealed that cerebrovascular disease and coronary heart disease had a more significant impact on cognitive function. Cerebrovascular disease was associated with weaker centrality in memory and spatial orientation, and a sparser cognitive network structure. Coronary heart disease was associated with weaker centrality in memory, repetition, executive function, recall, attention, and calculation, as well as a sparser cognitive network structure. The NCT analyses further highlighted significant differences between the cerebrovascular disease and coronary heart disease groups compared to controls in terms of overall network structure and connection strength. Conclusion Our findings suggest that specific cognitive domains may be more vulnerable to impairments in patients with cerebrovascular disease and coronary heart disease. These insights could be used to improve the accuracy and sensitivity of cognitive screening in these patient populations, inform personalized cognitive intervention strategies, and provide a better understanding of the potential mechanisms underlying cognitive decline in patients with vascular diseases.
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Affiliation(s)
- Yucheng Wang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
- School of Public Health, China Medical University, Shenyang, China
| | - Huanrui Zhang
- Department of Geriatrics, The First Hospital of China Medical University, Shenyang, China
| | - Linzi Liu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Zijia Li
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Yang Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, Beijing, China
- School of Basic Medicine of Peking Union Medical College, Beijing, China
| | - Jiayan Wei
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Yixiao Xu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Yifang Zhou
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
- Department of Geriatrics, The First Hospital of China Medical University, Shenyang, China
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Long Y, Wu Q, Yang Y, Cai J, Xiao J, Liu Z, Xu Y, Chen Y, Huang M, Zhang R, Xu X, Hu J, Liu Z, Liu F, Zheng Y, Meng H, Wang Z, Tang Y, Song X, Chen Y, Wang X, Liu T, Wu X, Fang M, Wan C, Zhao J, Wu R. Early non-response as a predictor of later non-response to antipsychotics in schizophrenia: a randomized trial. BMC Med 2023; 21:263. [PMID: 37468932 DOI: 10.1186/s12916-023-02968-7] [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] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 06/30/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND It remains a challenge to predict the long-term response to antipsychotics in patients with schizophrenia who do not respond at an early stage. This study aimed to investigate the optimal predictive cut-off value for early non-response that would better predict later non-response to antipsychotics in patients with schizophrenia. METHODS This multicenter, 8-week, open-label, randomized trial was conducted at 19 psychiatric centers throughout China. All enrolled participants were assigned to olanzapine, risperidone, amisulpride, or aripiprazole monotherapy for 8 weeks. The positive and negative syndrome scale (PANSS) was evaluated at baseline, week 2, week 4, and week 8. The main outcome was the prediction of nonresponse. Nonresponse is defined as a < 20% reduction in the total scores of PANSS from baseline to endpoint. Severity ratings of mild, moderate, and severe illness corresponded to baseline PANSS total scores of 58, 75, and 95, respectively. RESULTS At week 2, a reduction of < 5% in the PANSS total score showed the highest total accuracy in the severe and mild schizophrenia patients (total accuracy, 75.0% and 80.8%, respectively), and patients who were treated with the risperidone and amisulpride groups (total accuracy, 82.4%, and 78.2%, respectively). A 10% decrease exhibited the best overall accuracy in the moderate schizophrenia patients (total accuracy, 84.0%), olanzapine (total accuracy, 79.2%), and aripiprazole group (total accuracy, 77.4%). At week 4, the best predictive cut-off value was < 20%, regardless of the antipsychotic or severity of illness (total accuracy ranging from 89.8 to 92.1%). CONCLUSIONS Symptom reduction at week 2 has acceptable discrimination in predicting later non-response to antipsychotics in schizophrenia, and a more accurate predictive cut-off value should be determined according to the medication regimen and baseline illness severity. The response to treatment during the next 2 weeks after week 2 could be further assessed to determine whether there is a need to change antipsychotic medication during the first four weeks. TRIAL REGISTRATION This study was registered on Clinicaltrials.gov (NCT03451734).
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Affiliation(s)
- Yujun Long
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 139# Renmin Middle RD, Changsha, 410011, Hunan, China
| | - Qiongqiong Wu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 139# Renmin Middle RD, Changsha, 410011, Hunan, China
| | - Ye Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 139# Renmin Middle RD, Changsha, 410011, Hunan, China
| | - Jingda Cai
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 139# Renmin Middle RD, Changsha, 410011, Hunan, China
| | - Jingmei Xiao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 139# Renmin Middle RD, Changsha, 410011, Hunan, China
| | - Zhaoqian Liu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yifeng Xu
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Manli Huang
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Ruiguo Zhang
- Department of Psychiatry, Xijing Hospital, Air Force Military Medical University, Xi'an, Shaanxi, China
| | - Xijia Xu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, Jiangsu, China
| | - Jian Hu
- Department of Psychiatry, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Zhifen Liu
- Department of Psychiatry, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Fang Liu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Yingjun Zheng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Huaqing Meng
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhimin Wang
- The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Yanqing Tang
- Department of Psychiatry, the First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Xueqin Song
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yunchun Chen
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xueyi Wang
- Department of Psychiatry, First Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Tiebang Liu
- Department of Psychiatry, Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | - Xiaoli Wu
- Department of Psychiatry, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | | | - Chunling Wan
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Jingping Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 139# Renmin Middle RD, Changsha, 410011, Hunan, China
| | - Renrong Wu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 139# Renmin Middle RD, Changsha, 410011, Hunan, China.
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Lin Z, Tang Y, Chen Z, Li S, Xu X, Hou X, Chen Z, Wen J, Zeng W, Meng X, Fan H. Soluble CD80 oral delivery by recombinant Lactococcus suppresses tumor growth by enhancing antitumor immunity. Bioeng Transl Med 2023; 8:e10533. [PMID: 37476068 PMCID: PMC10354755 DOI: 10.1002/btm2.10533] [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] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 04/04/2023] [Accepted: 04/12/2023] [Indexed: 07/22/2023] Open
Abstract
CD80 is an important co-stimulatory molecule that participates in the immune response. Soluble CD80 can induce T cell activation and overcome PDL1-mediated immune suppression. In this study, we aimed to construct recombinant Lactococcus lactis for oral delivery of the soluble CD80 (hsCD80) protein or the fusion protein containing the cholera toxin B subunit (CTB) and hsCD80 (CTB-hsCD80) under the control of the nisin-inducible expression system. The recombinant L. lactis expressed and secreted hsCD80 or CTB-hsCD80 fusion proteins after induction by nisin in vitro and in the enteric cavity. Additionally, the CTB-hsCD80 fusion protein showed uptake by intestinal epithelial cells, was cleaved by the furin protease, and was released as free hsCD80 protein into the blood circulation. Orally administered hsCD80 and CTB-hsCD80 containing L. lactis increased the proportion of activated T cells in the spleen and intestinal epithelium, inhibited tumor growth, and prolonged the survival of tumor-bearing mice. The hsCD80-containing L. lactis showed greater therapeutic effects on primary colonic adenoma in APCmin/- mice and completely suppressed tumor growth. Further, recombinant CTB-hsCD80 in L. lactis was more efficient than hsCD80-containing bacteria in inhibiting the growth of xenografted colon cancer and melanoma cells. hsCD80 engineered probiotics may serve as a promising new approach for antitumor immunotherapy, especially for colorectal cancer.
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Affiliation(s)
- Ziqing Lin
- Department of Cell Biology, School of Basic MedicineSouthern Medical UniversityGuangzhouChina
- Guangzhou Virotech Phamaceutical Co., LtdGuangzhouChina
| | - Yanqing Tang
- Department of Cell Biology, School of Basic MedicineSouthern Medical UniversityGuangzhouChina
| | - Zerong Chen
- Department of Cell Biology, School of Basic MedicineSouthern Medical UniversityGuangzhouChina
- Department of Urology, Nanfang HospitalSouthern Medical UniversityGuangzhouChina
| | - Simin Li
- Department of Cell Biology, School of Basic MedicineSouthern Medical UniversityGuangzhouChina
| | - Xueyan Xu
- Department of Cell Biology, School of Basic MedicineSouthern Medical UniversityGuangzhouChina
- Department of Dermatology, Dermatology Hospital of Southern Medical UniversitySouthern Medical UniversityGuangzhouChina
| | - Xufeng Hou
- Department of Cell Biology, School of Basic MedicineSouthern Medical UniversityGuangzhouChina
| | - Zhenhui Chen
- Department of Microbiology, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public HealthSouthern Medical UniversityGuangzhouChina
| | - Junjie Wen
- Guangzhou Weisengene Biological Technology Co., Ltd.GuangzhouChina
| | - Weisen Zeng
- Department of Cell Biology, School of Basic MedicineSouthern Medical UniversityGuangzhouChina
| | - Xiaojing Meng
- Department of Occupational Health and Occupational Medicine, School of Public HealthSouthern Medical UniversityGuangzhouGuangdongChina
| | - Hongying Fan
- Department of Microbiology, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public HealthSouthern Medical UniversityGuangzhouChina
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Wei Y, Womer FY, Sun K, Zhu Y, Sun D, Duan J, Zhang R, Wei S, Jiang X, Zhang Y, Tang Y, Zhang X, Wang F. Applying dimensional psychopathology: transdiagnostic prediction of executive cognition using brain connectivity and inflammatory biomarkers. Psychol Med 2023; 53:3557-3567. [PMID: 35536000 DOI: 10.1017/s0033291722000174] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND The association between executive dysfunction, brain dysconnectivity, and inflammation is a prominent feature across major psychiatric disorders (MPDs), schizophrenia, bipolar disorder, and major depressive disorder. A dimensional approach is warranted to delineate their mechanistic interplay across MPDs. METHODS This single site study included a total of 1543 participants (1058 patients and 485 controls). In total, 1169 participants underwent diffusion tensor and resting-state functional magnetic resonance imaging (745 patients and 379 controls completed the Wisconsin Card Sorting Test). Fractional anisotropy (FA) and regional homogeneity (ReHo) assessed structural and functional connectivity, respectively. Pro-inflammatory cytokine levels [interleukin (IL)-1β, IL-6, and tumor necrosis factor-α] were obtained in 325 participants using blood samples collected with 24 h of scanning. Group differences were determined for main measures, and correlation and mediation analyses and machine learning prediction modeling were performed. RESULTS Executive deficits were associated with decreased FA, increased ReHo, and elevated IL-1β and IL-6 levels across MPDs, compared to controls. FA and ReHo alterations in fronto-limbic-striatal regions contributed to executive deficits. IL-1β mediated the association between FA and cognition, and IL-6 mediated the relationship between ReHo and cognition. Executive cognition was better predicted by both brain connectivity and cytokine measures than either one alone for FA-IL-1β and ReHo-IL-6. CONCLUSIONS Transdiagnostic associations among brain connectivity, inflammation, and executive cognition exist across MPDs, implicating common neurobiological substrates and mechanisms for executive deficits in MPDs. Further, inflammation-related brain dysconnectivity within fronto-limbic-striatal regions may represent a transdiagnostic dimension underlying executive dysfunction that could be leveraged to advance treatment.
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Affiliation(s)
- Yange Wei
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
| | - Fay Y Womer
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63130, USA
| | - Kaijin Sun
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yue Zhu
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
| | - Dandan Sun
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
| | - Jia Duan
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
| | - Ran Zhang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
| | - Shengnan Wei
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
| | - Xiaowei Jiang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
| | - Yanbo Zhang
- Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, T6G 2B7, Canada
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 210001, China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China
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Zhang C, Huang L, Tang Y, Wang P, Chen Y, Zhang L, Shen H, Yu Y, Tian X, Wang Y. [Identification and verification of α-11 giardin-interacting protein]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2023; 35:155-162. [PMID: 37253564 DOI: 10.16250/j.32.1374.2022288] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To identify and verify the interacting protein of α-11 giardin, so as provide the experimental evidence for studies on the α-11 giardin function. METHODS The yeast two-hybrid cDNA library of the Giardia lambia C2 strain and the bait plasmid of α-11 giardin were constructed. All proteins interacting with α-11 giardin were screened using the yeast two-hybrid system. α-11 giardin and all screened potential interacting protein genes were constructed into pBiFc-Vc-155 and pBiFc-Vn-173 plasmids, and co-transfected into the breast cancer cell line MDA-MB-231. The interactions between α-11 giardin and interacting proteins were verified using bimolecular fluorescence complementation (BiFC). RESULTS The yeast two-hybrid G. lambia cDNA library which was quantified at 2.715 × 107 colony-forming units (CFU) and the bait plasmid containing α-11 giardin gene without an autoactivation activity were constructed. Following two-round positive screening with the yeast two-hybrid system, two potential proteins interacting with α-11 giardin were screened, including eukaryotic translation initiation factor 5A (EIF5A), calmodulin-dependent protein kinase (CAMKL) and nicotinamide adenine dinucleotide phosphate-specific glutamate dehydrogenase (NADP-GDH), hypothetical protein 1 (GL50803_95880), hypothetical protein 2 (GL50803_87261) and a protein from Giardia canis virus. The α-11 giardin and EIF5A genes were transfected into the pBiFc-Vc-155 and pBiFc-Vn-173 plasmids using BiFC, and the recombinant plasmids pBiFc-Vc-155-α-11 and pBiFc-Vn-173-EIF5A were co-tranfected into MDA-MB-231 cells, which displayed green fluorescence under a microscope, indicating the interaction between α-11 giardin and EIF5A protein in cells. CONCLUSIONS The yeast two-hybrid cDNA library of the G. lambia C2 strain has been successfully constructed, and six potential protein interacting with α-11 giardin have been identified, including EIF5A that interacts with α-11 giardin in cells.
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Affiliation(s)
- C Zhang
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
| | - L Huang
- Hongci Hospital of Tangshan City, Hebei Province, China
| | - Y Tang
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
| | - P Wang
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
| | - Y Chen
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
| | - L Zhang
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
| | - H Shen
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
| | - Y Yu
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
| | - X Tian
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
| | - Y Wang
- College of Life Sciences, North China University of Technology, Tangshan, Hebei 063000, China
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Wang L, Ma Q, Sun X, Xu Z, Zhang J, Liao X, Wang X, Wei D, Chen Y, Liu B, Huang CC, Zheng Y, Wu Y, Chen T, Cheng Y, Xu X, Gong Q, Si T, Qiu S, Lin CP, Cheng J, Tang Y, Wang F, Qiu J, Xie P, Li L, He Y, Xia M, Zhang Y, Li L, Cheng J, Gong Q, Li L, Lin CP, Qiu J, Qiu S, Si T, Tang Y, Wang F, Xie P, Xu X, Xia M. Frequency-resolved connectome alterations in major depressive disorder: A multisite resting fMRI study. J Affect Disord 2023; 328:47-57. [PMID: 36781144 DOI: 10.1016/j.jad.2023.01.104] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 01/24/2023] [Accepted: 01/27/2023] [Indexed: 02/13/2023]
Abstract
BACKGROUND Functional connectome studies have revealed widespread connectivity alterations in major depressive disorder (MDD). However, the low frequency bandpass filtering (0.01-0.08 Hz or 0.01-0.1 Hz) in most studies have impeded our understanding on whether and how these alterations are affected by frequency of interest. METHODS Here, we performed frequency-resolved (0.01-0.06 Hz, 0.06-0.16 Hz and 0.16-0.24 Hz) connectome analyses using a large-sample resting-state functional MRI dataset of 1002 MDD patients and 924 healthy controls from seven independent centers. RESULTS We reported significant frequency-dependent connectome alterations in MDD in left inferior parietal, inferior temporal, precentral, and fusiform cortices and bilateral precuneus. These frequency-dependent connectome alterations are mainly derived by abnormalities of medium- and long-distance connections and are brain network-dependent. Moreover, the connectome alteration of left precuneus in high frequency band (0.16-0.24 Hz) is significantly associated with illness duration. LIMITATIONS Multisite harmonization model only removed linear site effects. Neurobiological underpinning of alterations in higher frequency (0.16-0.24 Hz) should be further examined by combining fMRI data with respiration, heartbeat and blood flow recordings in future studies. CONCLUSIONS These results highlight the frequency-dependency of connectome alterations in MDD and the benefit of examining connectome alteration in MDD under a wider frequency band.
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Affiliation(s)
- Lei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qing Ma
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Xiaoyi Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; School of Systems Science, Beijing Normal University, Beijing, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jiaying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Xiaoqin Wang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Dongtao Wei
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Bangshan Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yankun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Taolin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ching-Po Lin
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK; Institute of Neuroscience, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Peng Xie
- Chongqing Key Laboratory of Neurobiology, Chongqing, China; Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lingjiang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | | | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
| | - Yihe Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
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Guo Y, Jiang X, Jia L, Zhu Y, Han X, Wu Y, Liu W, Zhao W, Zhu H, Wang D, Tu Z, Zhou Y, Sun Q, Kong L, Wu F, Tang Y. Altered gray matter volumes and plasma IL-6 level in major depressive disorder patients with suicidal ideation. Neuroimage Clin 2023; 38:103403. [PMID: 37079937 PMCID: PMC10148078 DOI: 10.1016/j.nicl.2023.103403] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 04/07/2023] [Accepted: 04/08/2023] [Indexed: 04/22/2023]
Abstract
BACKGROUNDS Suicidal ideation (SI) is one of the most serious consequences of major depressive disorder (MDD). Understanding the unique mechanism of MDD with SI (MDD + S) is crucial for treatment development. While abundant research has studied MDD, past studies have not reached a consensus on the mechanism of MDD + S. The study aimed to investigate the abnormalities of the gray matter volumes (GMVs) and plasma IL-6 level in MDD + S to further reveal the mechanism of MDD + S. METHODS We tested the plasma IL-6 level using Luminex multifactor assays and collected the Structural Magnetic Resonance Imaging (SMRI) data from 34 healthy controls (HCs), 36 MDD patients without SI (MDD - S) and 34 MDD + S patients. We performed a partial correlation between the GMVs of the brain regions with significant differences and plasma IL-6 level with age, sex, medication, scores of HAMD-17 and HAMA as the covariates. RESULTS Compared with HCs and MDD - S, MDD + S had significantly decreased GMVs in the left cerebellum Crus I/II and significantly increased plasma IL-6 level; compared with HCs, both the MDD + S and MDD - S had significantly decreased GMVs in right precentral and postcentral gyri. No significant correlation was found between the GMVs and the plasma IL-6 level in the MDD + S and MDD - S, respectively. While the GMVs of the right precentral and postcentral gyri negatively correlated with the level of IL-6 in the whole MDD (r = -0.28, P = 0.03). The GMVs of the left cerebellum Crus I/II (r = -0.47, P = 0.02), and the right precentral and postcentral gyri (r = -0.42, P = 0.04) negatively correlated with the level of IL-6 in HCs. CONCLUSION The altered GMVs and the plasma IL-6 level may provide a scientific basis to understand the pathophysiological mechanisms of MDD + S.
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Affiliation(s)
- Yingrui Guo
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Xiaowei Jiang
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China; Department of Radiology, The First Hospital of China Medical University, Shenyang, China
| | - Linna Jia
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Yue Zhu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Xinyu Han
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Yifan Wu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Wen Liu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Wenhui Zhao
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Huaqian Zhu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Dahai Wang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Zhaoyuan Tu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Yifang Zhou
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Qikun Sun
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Lingtao Kong
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Feng Wu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China; Department of Geriatric Medicine, The First Hospital of China Medical University, Shenyang, China.
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Tang Y, Zhang L, Ye D, Zhao A, Liu Y, Zhang M. Causal relationship between Type 1 diabetes and osteoporosis and fracture occurrence: a two-sample Mendelian randomization analysis. Osteoporos Int 2023; 34:1111-1117. [PMID: 37012460 DOI: 10.1007/s00198-023-06734-6] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 03/21/2023] [Indexed: 04/05/2023]
Abstract
We used two-sample Mendelian Randomization to reveal causal estimates of type 1 diabetes and bone. Type 1 diabetes was found to be a risk factor for bone metabolic health, although there was no clear evidence to support a genetic association between type 1 diabetes and osteoporosis and fracture risk. INTRODUCTION Based on the random assignment of gametes at conception, Mendelian randomization (MR) analysis simulates randomized controlled trials in an observational setting. Therefore, we used MR to assess the association causality of type 1 diabetes (T1D) with fractures and osteoporosis. METHODS From a genome-wide association meta-analysis, independent single nucleotide polymorphisms closely associated with T1D were selected as instrumental variables. Data on fracture and osteoporosis were obtained from the FinnGen Consortium. We performed a two-sample MR analysis, using inverse-variance weighted (IVW) as the primary analysis method, to assess possible causal associations between T1D and bone risk. The results were verified by MR-Egger regression and median weighted method (WME). MR-PRESSO and MR-Egger intercepts were used to evaluate the horizontal pleiotropy of instrumental variables, and the Q-test and "leave-one-out" methods were used to test the heterogeneity of MR results. RESULTS IVW (OR=1.040, 95% CI=0.974-1.109, P=0.238), MR-Egger regression (OR=1.077, 95% CI=0.921-1.260, P=0.372) and WME (OR=1.021, 95% CI=0.935-1.114, P=0.643) all showed that there was no causal relationship between T1D and osteoporosis, but the direction was consistent. The indicative significance of IVW results in T1D and forearm fractures (OR=1.062, 95% CI=1.010-1.117, P=0.020), but the results are not robust enough. There was no causal effect in femur, lumbar and pelvis, or shoulder and upper arm fractures. CONCLUSIONS After MR analysis, although T1D may be a risk factor for bone health, we do not have sufficient evidence to support a causal effect of T1D on osteoporosis and fractures at a genetically predicted level. More cases need to be included for analysis.
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Affiliation(s)
- Y Tang
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - L Zhang
- General Practice Ward/International Medical Center Ward, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China
| | - D Ye
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - A Zhao
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Y Liu
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - M Zhang
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China.
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Li Z, Wang Y, Wang Z, Kong L, Liu L, Li L, Tang Y. Estradiol and raloxifene as adjunctive treatment for women with schizophrenia: A meta-analysis of randomized, double-blind, placebo-controlled trials. Acta Psychiatr Scand 2023; 147:360-372. [PMID: 36585771 DOI: 10.1111/acps.13530] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [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: 07/19/2022] [Revised: 12/13/2022] [Accepted: 12/26/2022] [Indexed: 01/01/2023]
Abstract
OBJECTIVES We conducted a comprehensive meta-analysis of all available trials to evaluate the efficacy and safety of estrogen and selective estrogen receptor modulators as adjunctive treatment for women with schizophrenia. METHODS Multiple databases were searched from the inception until March 2022. Only randomized, double-blind, placebo-controlled studies (randomized controlled trials) were included. Mean differences (MDs) and their 95% confidence intervals (CIs) were calculated using random effects models. RESULTS The meta-analysis included six estradiol versus placebo studies (n = 724) and seven raloxifene versus placebo studies (n = 419), covering a total of 1143 patients. Adjunctive estradiol outperformed the placebo in terms of the Positive and Negative Syndrome Scale (PANSS) total score (MD = -7.29; 95% CI = -10.67 to -3.91; I2 = 59.1%; p < 0.001; k = 9; N = 858), positive symptom score (MD = -1.54; 95% CI = -3.04 to -0.72; I2 = 45.8%; p < 0.001; k = 7; N = 624), negative symptom score (MD = -1.9; 95% CI = -1.77 to -0.34; I2 = 37.6%; p < 0.05; k = 14; N = 1042), and general psychopathology score (MD = -4.27; 95% CI = -7.14 to -1.41; I2 = 76.3%; p < 0.005; k = 7; N = 624). Adjunctive raloxifene outperformed the placebo in terms of the PANSS total score (MD = -6.83; 95% CI = -11.69 to -1.97; I2 = 67.8%; p = 0.006; k = 8; N = 432) and general psychopathology score (MD = -3.82; 95% CI = -6.36 to -1.28; I2 = 65.3%; p < 0.005; k = 8; N = 432). CONCLUSIONS Our meta-analysis showed that estradiol and raloxifene are effective and safe adjunctive treatments that improve schizophrenia symptoms in women. Moreover, the effects of estradiol and raloxifene differed in terms of timing and dosage. Both are promising adjunctive treatments that merit further study.
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Affiliation(s)
- Zijia Li
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, People's Republic of China
| | - Yucheng Wang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, People's Republic of China
- School of Public Health, China Medical University, Shenyang, People's Republic of China
| | - Zhe Wang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, People's Republic of China
| | - Lingtao Kong
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, People's Republic of China
| | - Linzi Liu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, People's Republic of China
| | - Liu Li
- Shenyang Women's and Children's Hospital, Shenyang, People's Republic of China
| | - Yanqing Tang
- Department of Psychiatry and Geriatrics, The First Hospital of China Medical University, Shenyang, People's Republic of China
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Wei X, Dong S, Su Z, Tang L, Zhao P, Pan C, Wang F, Tang Y, Zhang W, Zhang X. NetMoST: A network-based machine learning approach for subtyping schizophrenia using polygenic SNP allele biomarkers. ArXiv 2023:arXiv:2302.00104v2. [PMID: 36776814 PMCID: PMC9915719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
Subtyping neuropsychiatric disorders like schizophrenia is essential for improving the diagnosis and treatment of complex diseases. Subtyping schizophrenia is challenging because it is polygenic and genetically heterogeneous, rendering the standard symptom-based diagnosis often unreliable and unrepeatable. We developed a novel network-based machine-learning approach, netMoST, to subtyping psychiatric disorders. NetMoST identifies polygenic risk SNP-allele modules from genome-wide genotyping data as polygenic haplotype biomarkers (PHBs) for disease subtyping. We applied netMoST to subtype a cohort of schizophrenia subjects into three distinct biotypes with differentiable genetic, neuroimaging and functional characteristics. The PHBs of the first biotype (36.9% of all patients) were related to neurodevelopment and cognition, the PHBs of the second biotype (28.4%) were enriched for neuroimmune functions, and the PHBs of the third biotype (34.7%) were associated with the transport of calcium ions and neurotransmitters. Neuroimaging patterns provided additional support to the new biotypes, with unique regional homogeneity (ReHo) patterns observed in the brains of each biotype compared with healthy controls. Our findings demonstrated netMoST's capability for uncovering novel biotypes of complex diseases such as schizophrenia. The results also showed the power of exploring polygenic allelic patterns that transcend the conventional GWAS approaches.
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Affiliation(s)
- Xinru Wei
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 210001, China
| | - Shuai Dong
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 210001, China
| | - Zhao Su
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 210001, China
| | - Lili Tang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Pengfei Zhao
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Chunyu Pan
- School of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
- Department of Gerontology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Weixiong Zhang
- Department of Health Technology and Informatics, Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 210001, China
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Duan J, Gong X, Womer FY, Sun K, Tang L, Liu J, Zheng J, Zhu Y, Tang Y, Zhang X, Wang F. Neurodevelopmental trajectories, polygenic risk, and lipometabolism in vulnerability and resilience to schizophrenia. BMC Psychiatry 2023; 23:153. [PMID: 36894907 PMCID: PMC9999573 DOI: 10.1186/s12888-023-04597-z] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 02/07/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND Schizophrenia (SZ) arises from a complex interplay involving genetic and molecular factors. Early intervention of SZ hinges upon understanding its vulnerability and resiliency factors in study of SZ and genetic high risk for SZ (GHR). METHODS Herein, using integrative and multimodal strategies, we first performed a longitudinal study of neural function as measured by amplitude of low frequency function (ALFF) in 21 SZ, 26 GHR, and 39 healthy controls to characterize neurodevelopmental trajectories of SZ and GHR. Then, we examined the relationship between polygenic risk score for SZ (SZ-PRS), lipid metabolism, and ALFF in 78 SZ, and 75 GHR in cross-sectional design to understand its genetic and molecular substrates. RESULTS Across time, SZ and GHR diverge in ALFF alterations of the left medial orbital frontal cortex (MOF). At baseline, both SZ and GHR had increased left MOF ALFF compared to HC (P < 0.05). At follow-up, increased ALFF persisted in SZ, yet normalized in GHR. Further, membrane genes and lipid species for cell membranes predicted left MOF ALFF in SZ; whereas in GHR, fatty acids best predicted and were negatively correlated (r = -0.302, P < 0.05) with left MOF. CONCLUSIONS Our findings implicate divergence in ALFF alteration in left MOF between SZ and GHR with disease progression, reflecting vulnerability and resiliency to SZ. They also indicate different influences of membrane genes and lipid metabolism on left MOF ALFF in SZ and GHR, which have important implications for understanding mechanisms underlying vulnerability and resiliency in SZ and contribute to translational efforts for early intervention.
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Affiliation(s)
- Jia Duan
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Xiaohong Gong
- State Key Laboratory of Genetic Engineering and Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai, China
| | - Fay Y Womer
- Dept of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kaijin Sun
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China
| | - Lili Tang
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Juan Liu
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Junjie Zheng
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China
| | - Yue Zhu
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Yanqing Tang
- Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China.
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.
| | - Fei Wang
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China. .,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China.
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Li M, Wu F, Cao Y, Jiang X, Kong L, Tang Y. Abnormal white matter integrity in Papez circuit in first-episode medication-naive adults with anxious depression: A combined voxel-based analysis and region of interest study. J Affect Disord 2023; 324:489-495. [PMID: 36610591 DOI: 10.1016/j.jad.2022.12.149] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 12/25/2022] [Accepted: 12/31/2022] [Indexed: 01/06/2023]
Abstract
BACKGROUND Anxious depression is one of the subtypes of major depressive disorder (MDD), usually defined as "patients with MDD and high levels of anxiety symptoms". Compared to non-anxious MDD (naMDD), patients with anxious MDD (aMDD) have more severe depressive symptoms and suicidal ideation, worse treatment outcomes and remission rates, and poorer prognosis. Current research suggests that the Papez circuit is an important brain structure closely related to emotion, memory, and cognition. This study applied DTI to explore the altered white matter integrity in Papez circuit of patients with aMDD. METHODS DTI data were acquired from 30 medication-naive outpatients with naMDD and 55 with aMDD and 88 demographically similar healthy control (HC) subjects. Voxel-based analysis (VBM) and region of interest (ROI) analysis were conducted to explore the significant difference of fractional anisotropy (FA) values among 3 groups. Pearson's correlations were performed to analyze the correlation between FA values and the score of HAMA-14 and HAMD-17. RESULTS We found that aMDD patients had significantly higher FA values in left fornix (belong to Papez circuit) and left posterior thalamic radiation and right anterior corona radiata (belong to limbic-thalamo-cortical circuitry) compared with HC. And there was variability in the white matter integrity in right posterior thalamic radiation (belong to limbic-thalamo-cortical circuitry) and left fornix (belong to Papez circuit) between aMDD and naMDD patients. LIMITATIONS The cross-sectional study and the population vary between aMDD group and naMDD group are limitations. CONCLUSIONS Abnormal white matter integrity in Papez circuit and Limbic-Thalamo-Cortical circuitry may play an important role in the neuropathology of aMDD and might help to identify aMDD.
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Affiliation(s)
- Mengxue Li
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
| | - Feng Wu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
| | - Yang Cao
- Shenyang Mental Health Center, Shenyang 110168, Liaoning, China
| | - Xiaowei Jiang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
| | - Lingtao Kong
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China.
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
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Tang Y, Liu C, Wu YH, Pei F, Gu YC. [Micro-CT analysis of tooth development of C57BL/6 mice strain]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 58:238-243. [PMID: 36854424 DOI: 10.3760/cma.j.cn112144-20220802-00433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
Objective: To investigate the normal process of tooth development of C57BL/6 mouse strain by using micro-CT for better understanding about the tooth development of the human being and other species. Methods: A total of 54 C57BL/6 mice were used at postnatal day 1 (P1), P3, P7, P10, P14, P21, P28, P42 and P56 (n=6 for each age group). After euthanasia, the skulls and alveolar bones (with molars) were isolated and scanned by micro-CT scanner. After three dimensional reconstruction, the developmental status of the crown and root(s) for each tooth type was examined in different views. Results: The tooth development of mice from birth to mature (P56) could be divided into three stages. The first stage was from P1 to P14, in which the crowns of all the first, second and third molars had formed, while the roots had not fully developed yet. The second stage was from ablactation (P21) to P28, in which all the roots of the molars had reached their normal length, and the apical foramens had closed. Due to the mastication and occlusal abrasion, the incisors exhibited sharp cutting edges at the buccal enamel layer, and the corresponding molars formed a pit-to-fossa articulated relationship. The third stage was from P42 to P56, in which the root canal differentiation occurred, and 1-2 canal configuration was formed in several flat roots. The development of molar roots had completed and the apexes were enlarged due to the deposition of cementum around. Conclusions: In the process of mouse tooth development, the mineralization of the cusps, followed by crown formation and roots elongation, was precisely regulated in a spatial-temporal pattern. The incisors and the molars exhibited different modes of development.
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Affiliation(s)
- Y Tang
- Central Laboratory, Suzhou Ninth People's Hospital, Soochow University, Suzhou 215200, China
| | - C Liu
- Central Laboratory, Suzhou Ninth People's Hospital, Soochow University, Suzhou 215200, China
| | - Y H Wu
- Department of Stomatology, The Affiliated Hospital of Nantong University, Nantong 226001, China
| | - F Pei
- Department of Stomatology, The Affiliated Hospital of Nantong University, Nantong 226001, China
| | - Y C Gu
- Central Laboratory, Suzhou Ninth People's Hospital, Soochow University, Suzhou 215200, China
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47
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Chen JL, Yu XP, Tang Y, Chen C, Qiu YH, Wu H, Song TQ, He Y, Mao XH, Zhai WL, Cheng ZJ, Li JD, Geng ZM, Tang ZH, Quan ZW. [Survival analysis of patients with intrahepatic cholangiocarcinoma treated with adjuvant chemotherapy after radical resection based on CoxPH model and deep learning algorithm]. Zhonghua Wai Ke Za Zhi 2023; 61:313-320. [PMID: 36822588 DOI: 10.3760/cma.j.cn112139-20230105-00007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Objective: To establish a predictive model for survival benefit of patients with intrahepatic cholangiocarcinoma (ICC) who received adjuvant chemotherapy after radical resection. Methods: The clinical and pathological data of 249 patients with ICC who underwent radical resection and adjuvant chemotherapy at 8 hospitals in China from January 2010 to December 2018 were retrospectively collected. There were 121 males and 128 females,with 88 cases>60 years old and 161 cases≤60 years old. Feature selection was performed by univariate and multivariate Cox regression analysis. Overall survival time and survival status were used as outcome indicators,then target clinical features were selected. Patients were stratified into high-risk group and low-risk group,survival differences between the two groups were analyzed. Using the selected clinical features, the traditional CoxPH model and deep learning DeepSurv survival prediction model were constructed, and the performance of the models were evaluated according to concordance index(C-index). Results: Portal vein invasion, carcinoembryonic antigen>5 μg/L,abnormal lymphocyte count, low grade tumor pathological differentiation and positive lymph nodes>0 were independent adverse prognostic factors for overall survival in 249 patients with adjuvant chemotherapy after radical resection (all P<0.05). The survival benefit of adjuvant chemotherapy in the high-risk group was significantly lower than that in the low-risk group (P<0.05). Using the above five features, the traditional CoxPH model and the deep learning DeepSurv survival prediction model were constructed. The C-index values of the training set were 0.687 and 0.770, and the C-index values of the test set were 0.606 and 0.763,respectively. Conclusion: Compared with the traditional Cox model, the DeepSurv model can more accurately predict the survival probability of patients with ICC undergoing adjuvant chemotherapy at a certain time point, and more accurately judge the survival benefit of adjuvant chemotherapy.
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Affiliation(s)
- J L Chen
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
| | - X P Yu
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
| | - Y Tang
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
| | - C Chen
- Department of Hepatobiliary Surgery,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China
| | - Y H Qiu
- Department of Biliary Surgery, the Third Affiliated Hospital of Naval Medical University,Shanghai 200433,China
| | - H Wu
- Department of Liver Transplantation,West China Hospital,Sichuan University,Chengdu 610041,China
| | - T Q Song
- Department of Hepatobiliary Oncology,Tianjin Medical University Cancer Hospital,Tianjin 300060,China
| | - Y He
- Department of Hepatobiliary Surgery,the Southwest Hospital of Army Medical University,Chongqing 400038,China
| | - X H Mao
- Department of Hepatobiliary Surgery,Hunan Provincial People's Hospital,Changsha 410005,China
| | - W L Zhai
- Department of Hepatobiliary and Pancreas Liver Transplantation Surgery,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China
| | - Z J Cheng
- Department of Hepatobiliary and Pancreatic Surgery,Zhongda Hospital,Southeast University,Nanjing 210009,China
| | - J D Li
- Department of Hepatobiliary Surgery,Affiliated Hospital of North Sichuan Medical College,Nanchong 637000,China
| | - Z M Geng
- Department of Hepatobiliary Surgery,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China
| | - Z H Tang
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
| | - Z W Quan
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
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Zhong SJ, Gao JJ, Tang P, Liu YP, Wang SL, Fang H, Qiu JP, Song YW, Chen B, Qi SN, Tang Y, Lu NN, Jing H, Zhai YR, Zhou AP, Bi XG, Ma JH, Li CL, Zhang Y, Shou JZ, Xing NZ, Li YX. [The efficacy of radiotherapy based combined therapy for unresectable locally invasive bladder cancer and its associated factors analysis]. Zhonghua Zhong Liu Za Zhi 2023; 45:175-181. [PMID: 36781240 DOI: 10.3760/cma.j.cn112152-20220714-00490] [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] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
Objective: Retrospective analysis of the efficacy and influencing factors of bladder preservation integrated therapy for unresectable invasive bladder cancer confined to the pelvis was done, also including the bladder function preservation and adverse effects analysis. Methods: Sixty-nine patients with unresectable locally invasive bladder cancer who received radiotherapy-based combination therapy from March 1999 to December 2021 at our hospital were selected. Among them, 42 patients received concurrent chemoradiotherapy, 32 underwent neoadjuvant chemotherapyand 43 with transurethral resection of bladder tumors (TURBT) prior to radiotherapy. The late adverse effect of radiotherapy, preservation of bladder function, replase and metastasis and survival were followed-up. Cox proportional hazards models were applied for the multifactorial analysis. Results: The median age was 69 years. There were 63 cases (91.3%) of uroepithelial carcinoma, 64 of stage Ⅲ and 4 of stage Ⅳ. The median duration of follow-up was 76 months. There were 7 grade 2 late genito urinary toxicities, 2 grade 2 gastrointestinal toxicities, no grade 3 or higher adverse events occurred. All patients maintained normal bladder function, except for 8 cases who lost bladder function due to uncontrolled tumor in the bladder. Seventeen cases recurred locally. There were 11 cases in the concurrent chemoradiotherapy group with a local recurrence rate of 26.2% (11/42) and 6 cases in the non-concurrent chemoradiotherapy group with a local recurrence rate of 22.2% (6/27), and the difference in local recurrence rate between the two groups was not statistically significant (P=0.709). There were 23 cases of distant metastasis (including 2 cases of local recurrence with distant metastasis), including 10 cases in the concurrent chemoradiotherapy group with a distant metastasis rate of 23.8% (10/42) and 13 cases in the non-concurrent chemoradiotherapy group with a distant metastasis rate of 48.1% (13/27), and the distant metastasis rate in the non-concurrent chemoradiotherapy group was higher than that in the concurrent chemoradiotherapy group (P=0.036). The median 5-year overall survival (OS) time was 59 months and the OS rate was 47.8%. The 5-year progression-free survival (PFS) time was 20 months and the PFS rate was 34.4%. The 5-year OS rates of concurrent and non-concurrent chemoradiotherapy group were 62.9% and 27.6% (P<0.001), and 5-year PFS rates were 45.4% and 20.0%, respectively (P=0.022). The 5-year OS rates of with or without neoadjuvant chemotherapy were 78.4% and 30.1% (P=0.002), and the 5-year PFS rates were 49.1% and 25.1% (P=0.087), respectively. The 5-year OS rates with or without TURBT before radiotherapy were 45.5% and 51.9% (P=0.233) and the 5-year PFS rates were 30.8% and 39.9% (P=0.198), respectively. Multivariate Cox regression analysis results showed that the clinical stage (HR=0.422, 95% CI: 0.205-0.869) was independent prognostic factor for PFS of invasive bladder cancer. The multivariate analysis showed that clinical stages (HR=0.278, 95% CI: 0.114-0.678), concurrent chemoradiotherapy (HR=0.391, 95% CI: 0.165-0.930), neoadjuvant chemotherapy (HR=0.188, 95% CI: 0.058-0.611), and recurrences (HR=10.855, 95% CI: 3.655-32.638) were independent prognostic factors for OS of invasive bladder cancer. Conclusion: Unresectable localized invasive bladder cancer can achieve satisfactory long-term outcomes with bladder-preserving combination therapy based on radiotherapy, most patients can retain normal bladder function with acceptable late adverse effects and improved survival particularly evident in patients with early, concurrent chemoradiotherapy and neoadjuvant chemotherapy.
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Affiliation(s)
- S J Zhong
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J J Gao
- The First Department of Oncology, the People's Hospital of Jimo of Qingdao of Shandong, Qingdao 266200, China
| | - P Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y P Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S L Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J P Qiu
- Department of Radiation Oncology, the First Hospital of China Medical University, Shenyang 110001, China
| | - Y W Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - B Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S N Qi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N N Lu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y R Zhai
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - A P Zhou
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - X G Bi
- Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J H Ma
- Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - C L Li
- Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y Zhang
- Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J Z Shou
- Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N Z Xing
- Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y X Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Yu XP, Chen JL, Tang Y, Chen C, Qiu YH, Wu H, Song TQ, He Y, Mao XH, Zhai WL, Cheng ZJ, Liang X, Li JD, Sun CD, Ma K, Lin RX, Geng ZM, Tang ZH, Quan ZW. [A nomogram for preoperative prediction of lymph node metastasis in patients with intrahepatic cholangiocarcinoma based on inflammation-related markers]. Zhonghua Wai Ke Za Zhi 2023; 61:321-329. [PMID: 36822589 DOI: 10.3760/cma.j.cn112139-20230106-00009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Objectives: To construct a nomogram for prediction of intrahepatic cholangiocarcinoma (ICC) lymph node metastasis based on inflammation-related markers,and to conduct its clinical verification. Methods: Clinical and pathological data of 858 ICC patients who underwent radical resection were retrospectively collected at 10 domestic tertiary hospitals in China from January 2010 to December 2018. Among the 508 patients who underwent lymph node dissection,207 cases had complete variable clinical data for constructing the nomogram,including 84 males,123 females,109 patients≥60 years old,98 patients<60 years old and 69 patients were pathologically diagnosed with positive lymph nodes after surgery. Receiver operating characteristic curve was drawn to calculate the accuracy of preoperative imaging examinations to determine lymph node status,and the difference in overall survival time was compared by Log-rank test. Partial regression squares and statistically significant preoperative variables were screened by backward stepwise regression analysis. R software was applied to construct a nomogram,clinical decision curve and clinical influence curve,and Bootstrap method was used for internal verification. Moreover,retrospectively collecting clinical information of 107 ICC patients with intraoperative lymph node dissection admitted to 9 tertiary hospitals in China from January 2019 to June 2021 was for external verification to verify the accuracy of the nomogram. 80 patients with complete clinical data but without lymph node dissection were divided into lymph node metastasis high-risk group and low-risk group according to the score of the nomogram among the 858 patients. Log-rank test was used to compare the overall survival of patients with or without lymph node metastasis diagnosed by pathology. Results: The area under the curve of preoperative imaging examinations for lymph node status assessment of 440 patients was 0.615,with a false negative rate of 62.8% (113/180) and a false positive rate of 14.2% (37/260). The median survival time of 207 patients used to construct a nomogram with positive or negative postoperative pathological lymph node metastases was 18.5 months and 27.1 months,respectively (P<0.05). Five variables related to lymph node metastasis were screened out by backward stepwise regression analysis,which were combined calculi,neutrophil/lymphocyte ratio,albumin,liver capsule invasion and systemic immune inflammation index,according to which a nomogram was constructed with concordance index(C-index) of 0.737 (95%CI: 0.667 to 0.806). The C-index of external verification was 0.674 (95%CI:0.569 to 0.779). The calibration prediction curve was in good agreement with the reference curve. The results of the clinical decision curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.32,the maximum net benefit could be obtained by 0.11,and the cost/benefit ratio was 1∶2. The results of clinical influence curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.6,the probability of correctly predicting lymph node metastasis could reach more than 90%. There was no significant difference in overall survival time between patients with high/low risk of lymph node metastasis assessed by the nomogram and those with pathologically confirmed lymph node metastasis or without lymph node metastasis (Log-rank test:P=0.082 and 0.510,respectively). Conclusion: The prediction accuracy of preoperative nomogram for ICC lymph node metastasis based on inflammation-related markers is satisfactory,which can be used as a supplementary method for preoperative diagnosis of lymph node metastasis and is helpful for clinicians to make personalized decision of lymph node dissection for patients with ICC.
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Affiliation(s)
- X P Yu
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
| | - J L Chen
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
| | - Y Tang
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
| | - C Chen
- Department of Hepatobiliary Surgery,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China
| | - Y H Qiu
- Department of Biliary Surgery, the Third Affiliated Hospital of to Naval Medical University,Shanghai 200433,China
| | - H Wu
- Department of Liver Surgery,West China Hospital of Sichuan University,Chengdu 610041,China
| | - T Q Song
- Department of Hepatobiliary Oncology,Tianjin Medical University Cancer Hospital,Tianjin 300060,China
| | - Y He
- Department of Hepatobiliary Surgery,the Southwest Hospital of Army Medical University,Chongqing 400038,China
| | - X H Mao
- Department of Hepatobiliary Surgery,Hunan Provincial People's Hospital,Changsha 410005,China
| | - W L Zhai
- Department of Hepatobiliary Pancreas and Liver Transplantation Surgery,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China
| | - Z J Cheng
- Department of Hepatobiliary and Pancreatic Surgery,Zhongda Hospital, Southeast University,Nanjing 210009,China
| | - X Liang
- Department of Hepatobiliary and Pancreatic Surgery,Sir Run Run Shaw Hospital Affiliated to Zhejiang University School of Medicine,Hangzhou 310020,China
| | - J D Li
- Department of Hepatobiliary Surgery,Affiliated Hospital of North Sichuan Medical College,Nanchong 637000,China
| | - C D Sun
- Department of Hepatobiliary and Pancreatic Surgery,the Affiliated Hospital of Qingdao University,Qingdao 266003,China
| | - K Ma
- Department of Hepatobiliary and Pancreatic Surgery,the Affiliated Hospital of Qingdao University,Qingdao 266003,China
| | - R X Lin
- Department of Hepatobiliary and Pancreatic Surgery,the Second Norman Bethune Hospital of Jilin University,Changchun 130041,China
| | - Z M Geng
- Department of Hepatobiliary Surgery,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China
| | - Z H Tang
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
| | - Z W Quan
- Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China
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50
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Tang ZH, Tang Y, Yu XP, Chen JL, Quan ZW. [Exploring the significance of chemotherapy in the perioperative application of biliary tract carcinomas]. Zhonghua Wai Ke Za Zhi 2023; 61:277-282. [PMID: 36822583 DOI: 10.3760/cma.j.cn112139-20230109-00013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Biliary tract cancer is extremely malignant with a poor prognosis. At the moment, the only curative method available is radical resection. Targeted and immunotherapy are currently advancing quickly, but chemotherapy still holds a key role in the perioperative management of biliary cancer. Perioperative chemotherapy aims to decrease tumor volume before surgery so that patients can have their tumors surgically removed or have a higher radical resection rate. It also aims to remove any tumor cells that remain after surgery and prevent the growth of new tumors. Chemotherapy-based combination treatment techniques have been increasingly investigated in recent years to improve perioperative care and patient survival. From the standpoint of chemotherapy regimens and clinical trial success in the perioperative phase of radical surgery, the value of chemotherapy in the perioperative period of biliary tract cancer were explored in this paper.
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Affiliation(s)
- Z H Tang
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Y Tang
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - X P Yu
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - J L Chen
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Z W Quan
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
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