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Xu L, Zhang J, Yang H, Cao C, Fang R, Liu P, Luo S, Wang B, Zhang K, Wang L. Epistasis in neurotransmitter receptors linked to posttraumatic stress disorder and major depressive disorder comorbidity in traumatized Chinese. Front Psychiatry 2024; 15:1257911. [PMID: 38487579 PMCID: PMC10937445 DOI: 10.3389/fpsyt.2024.1257911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 02/14/2024] [Indexed: 03/17/2024] Open
Abstract
Background Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) comorbidity occurs through exposure to trauma with genetic susceptibility. Neuropeptide-Y (NPY) and dopamine are neurotransmitters associated with anxiety and stress-related psychiatry through receptors. We attempted to explore the genetic association between two neurotransmitter receptor systems and the PTSD-MDD comorbidity. Methods Four groups were identified using latent profile analysis (LPA) to examine the patterns of PTSD and MDD comorbidity among survivors exposed to earthquake-related trauma: low symptoms, predominantly depression, predominantly PTSD, and PTSD-MDD comorbidity. NPY2R (rs4425326), NPY5R (rs11724320), DRD2 (rs1079597), and DRD3 (rs6280) were genotyped from 1,140 Chinese participants exposed to earthquake-related trauma. Main, gene-environment interaction (G × E), and gene-gene interaction (G × G) effects for low symptoms, predominantly depression, and predominantly PTSD were tested using a multinomial logistic model with PTSD-MDD comorbidity as a reference. Results The results demonstrated that compared to PTSD-MDD comorbidity, epistasis (G × G) NPY2R-DRD2 (rs4425326 × rs1079597) affects low symptoms (β = -0.66, OR = 0.52 [95% CI: 0.32-0.84], p = 0.008, pperm = 0.008) and predominantly PTSD (β = -0.56, OR = 0.57 [95% CI: 0.34-0.97], p = 0.037, pperm = 0.039), while NPY2R-DRD3 (rs4425326 × rs6280) impacts low symptoms (β = 0.82, OR = 2.27 [95% CI: 1.26-4.10], p = 0.006, pperm = 0.005) and predominantly depression (β = 1.08, R = 2.95 [95% CI: 1.55-5.62], p = 0.001, pperm = 0.001). The two G × G effects are independent. Conclusion NPY and dopamine receptor genes are related to the genetic etiology of PTSD-MDD comorbidity, whose specific mechanisms can be studied at multiple levels.
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Affiliation(s)
- Ling Xu
- Laboratory for Traumatic Stress Studies and Center for Genetics and BioMedical Informatics Research, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Jingyi Zhang
- Laboratory for Traumatic Stress Studies and Center for Genetics and BioMedical Informatics Research, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Haibo Yang
- Academy of Psychology and Behavior, Tianjin Normal University, Tianjin, China
| | - Chengqi Cao
- Laboratory for Traumatic Stress Studies and Center for Genetics and BioMedical Informatics Research, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Ruojiao Fang
- Laboratory for Traumatic Stress Studies and Center for Genetics and BioMedical Informatics Research, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Ping Liu
- People’s Hospital of Deyang City, Deyang, Sichuan, China
| | - Shu Luo
- People’s Hospital of Deyang City, Deyang, Sichuan, China
| | - Binbin Wang
- Laboratory for Traumatic Stress Studies and Center for Genetics and BioMedical Informatics Research, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Kunlin Zhang
- Laboratory for Traumatic Stress Studies and Center for Genetics and BioMedical Informatics Research, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Li Wang
- Laboratory for Traumatic Stress Studies and Center for Genetics and BioMedical Informatics Research, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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Shen J, Su X, Pan M, Wang Z, Ke Y, Wang Q, Dong J, Duan S. Current insights into the oncogenic roles of lncRNA LINC00355. CANCER INNOVATION 2023; 2:448-462. [PMID: 38125763 PMCID: PMC10730005 DOI: 10.1002/cai2.91] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/29/2023] [Accepted: 07/26/2023] [Indexed: 12/23/2023]
Abstract
Long noncoding RNAs (lncRNAs) are a class of nonprotein-coding transcripts that are longer than 200 nucleotides. LINC00355 is a lncRNA located on chromosome 13q21.31 and is consistently upregulated in various cancers. It regulates the expression of downstream genes at both transcriptional and posttranscriptional levels, including eight microRNAs (miR-15a-5p, miR-34b-5p, miR-424-5p, miR-1225, miR-217-5p, miR-6777-3p, miR-195, and miR-466) and three protein-coding genes (ITGA2, RAD18, and UBE3C). LINC00355 plays a role in regulating various biological processes such as cell cycle progression, proliferation, apoptosis, epithelial-mesenchymal transition, invasion, and metastasis of cancer cells. It is involved in the regulation of the Wnt/β-catenin signaling pathway and p53 signaling pathway. Upregulation of LINC00355 has been identified as a high-risk factor in cancer patients and its increased expression is associated with poorer overall survival, recurrence-free survival, and disease-free survival. LINC00355 upregulation has been linked to several unfavorable clinical characteristics, including advanced tumor node metastasis and World Health Organization stages, reduced Karnofsky Performance Scale scores, increased tumor size, greater depth of invasion, and more extensive lymph node metastasis. LINC00355 induces chemotherapy resistance in cancer cells by regulating five downstream genes, namely HMGA2, ABCB1, ITGA2, WNT10B, and CCNE1 genes. In summary, LINC00355 is a potential oncogene with great potential as a diagnostic marker and therapeutic target for cancer.
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Affiliation(s)
- Jinze Shen
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Xinming Su
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Ming Pan
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Zehua Wang
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Yufei Ke
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Qurui Wang
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Jingyin Dong
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Shiwei Duan
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
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Guo LK, Su Y, Zhang YYN, Yu H, Lu Z, Li WQ, Yang YF, Xiao X, Yan H, Lu TL, Li J, Liao YD, Kang ZW, Wang LF, Li Y, Li M, Liu B, Huang HL, Lv LX, Yao Y, Tan YL, Breen G, Everall I, Wang HX, Huang Z, Zhang D, Yue WH. Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis. Mil Med Res 2023; 10:24. [PMID: 37269009 DOI: 10.1186/s40779-023-00459-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/05/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND Choosing the appropriate antipsychotic drug (APD) treatment for patients with schizophrenia (SCZ) can be challenging, as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers. Previous studies have indicated the association between treatment response and genetic and epigenetic factors, but no effective biomarkers have been identified. Hence, further research is imperative to enhance precision medicine in SCZ treatment. METHODS Participants with SCZ were recruited from two randomized trials. The discovery cohort was recruited from the CAPOC trial (n = 2307) involved 6 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, Quetiapine, Aripiprazole, Ziprasidone, and Haloperidol/Perphenazine (subsequently equally assigned to one or the other) groups. The external validation cohort was recruited from the CAPEC trial (n = 1379), which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, and Aripiprazole groups. Additionally, healthy controls (n = 275) from the local community were utilized as a genetic/epigenetic reference. The genetic and epigenetic (DNA methylation) risks of SCZ were assessed using the polygenic risk score (PRS) and polymethylation score, respectively. The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis, methylation quantitative trait loci, colocalization, and promoter-anchored chromatin interaction. Machine learning was used to develop a prediction model for treatment response, which was evaluated for accuracy and clinical benefit using the area under curve (AUC) for classification, R2 for regression, and decision curve analysis. RESULTS Six risk genes for SCZ (LINC01795, DDHD2, SBNO1, KCNG2, SEMA7A, and RUFY1) involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response. The developed and externally validated prediction model, which incorporated clinical information, PRS, genetic risk score (GRS), and proxy methylation level (proxyDNAm), demonstrated positive benefits for a wide range of patients receiving different APDs, regardless of sex [discovery cohort: AUC = 0.874 (95% CI 0.867-0.881), R2 = 0.478; external validation cohort: AUC = 0.851 (95% CI 0.841-0.861), R2 = 0.507]. CONCLUSIONS This study presents a promising precision medicine approach to evaluate treatment response, which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ. Trial registration Chinese Clinical Trial Registry ( https://www.chictr.org.cn/ ), 18. Aug 2009 retrospectively registered: CAPOC-ChiCTR-RNC-09000521 ( https://www.chictr.org.cn/showproj.aspx?proj=9014 ), CAPEC-ChiCTR-RNC-09000522 ( https://www.chictr.org.cn/showproj.aspx?proj=9013 ).
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Affiliation(s)
- Liang-Kun Guo
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yi Su
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China
| | - Yu-Ya-Nan Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Hao Yu
- Department of Psychiatry, Jining Medical University, Jining, 272067, Shandong, China
| | - Zhe Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Wen-Qiang Li
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Yong-Feng Yang
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Hao Yan
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Tian-Lan Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Jun Li
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yun-Dan Liao
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Zhe-Wei Kang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Li-Fang Wang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yue Li
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Hai-Liang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Lu-Xian Lv
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Yin Yao
- Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Yun-Long Tan
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China
| | - Gerome Breen
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Ian Everall
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Hong-Xing Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Zhuo Huang
- State Key Laboratory of Natural and Biomimetic Drugs, Key Laboratory for Neuroscience for Ministry of Education, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, 100191, China.
| | - Dai Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
| | - Wei-Hua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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Jiao S, Cao T, Cai H. Peripheral biomarkers of treatment-resistant schizophrenia: Genetic, inflammation and stress perspectives. Front Pharmacol 2022; 13:1005702. [PMID: 36313375 PMCID: PMC9597880 DOI: 10.3389/fphar.2022.1005702] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/26/2022] [Indexed: 11/16/2022] Open
Abstract
Treatment-resistant schizophrenia (TRS) often results in severe disability and functional impairment. Currently, the diagnosis of TRS is largely exclusionary and emphasizes the improvement of symptoms that may not be detected early and treated according to TRS guideline. As the gold standard, clozapine is the most prescribed selection for TRS. Therefore, how to predict TRS in advance is critical for forming subsequent treatment strategy especially clozapine is used during the early stage of TRS. Although mounting studies have identified certain clinical factors and neuroimaging characteristics associated with treatment response in schizophrenia, the predictors for TRS remain to be explored. Biomarkers, particularly for peripheral biomarkers, show great potential in predicting TRS in view of their predictive validity, noninvasiveness, ease of testing and low cost that would enable their widespread use. Recent evidence supports that the pathogenesis of TRS may be involved in abnormal neurotransmitter systems, inflammation and stress. Due to the heterogeneity of TRS and the lack of consensus in diagnostic criteria, it is difficult to compare extensive results among different studies. Based on the reported neurobiological mechanisms that may be associated with TRS, this paper narratively reviews the updates of peripheral biomarkers of TRS, from genetic and other related perspectives. Although current evidence regarding biomarkers in TRS remains fragmentary, when taken together, it can help to better understand the neurobiological interface of clinical phenotypes and psychiatric symptoms, which will enable individualized prediction and therapy for TRS in the long run.
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Affiliation(s)
- Shimeng Jiao
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacy, Central South University, Changsha, China
- International Research Center for Precision Medicine, Transformative Technology and Software Services, Changsha, Hunan, China
| | - Ting Cao
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacy, Central South University, Changsha, China
- International Research Center for Precision Medicine, Transformative Technology and Software Services, Changsha, Hunan, China
| | - Hualin Cai
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacy, Central South University, Changsha, China
- International Research Center for Precision Medicine, Transformative Technology and Software Services, Changsha, Hunan, China
- *Correspondence: Hualin Cai,
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