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Hu X, Cheng B, Tang Y, Long T, Huang Y, Li P, Song Y, Song X, Li K, Yin Y, Chen X. Gray matter volume and corresponding covariance connectivity are biomarkers for major depressive disorder. Brain Res 2024; 1837:148986. [PMID: 38714227 DOI: 10.1016/j.brainres.2024.148986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 04/06/2024] [Accepted: 05/04/2024] [Indexed: 05/09/2024]
Abstract
The major depressive disorder (MDD) is a common and severe mental disorder. To identify a reliable biomarker for MDD is important for early diagnosis and prevention. Given easy access and high reproducibility, the structural magnetic resonance imaging (sMRI) is an ideal method to identify the biomarker for depression. In this study, sMRI data of first episode, treatment-naïve 66 MDD patients and 54 sex-, age-, and education-matched healthy controls (HC) were used to identify the differences in gray matter volume (GMV), group-level, individual-level covariance connections. Finally, the abnormal GMV and individual covariance connections were applied to classify MDD from HC. MDD patients showed higher GMV in middle occipital gyrus (MOG) and precuneus (PCun), and higher structural covariance connections between MOG and PCun. In addition, the Allen Human Brain Atlas (AHBA) was applied and revealed the genetic basis for the changes of gray matter volume. Importantly, we reported that GMV in MOG, PCun and structural covariance connectivity between MOG and PCun are able to discriminate MDD from HC. Our results revealed structural underpinnings for MDD, which may contribute towards early discriminating for depression.
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Affiliation(s)
- Xiao Hu
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, China
| | - Bochao Cheng
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yuying Tang
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Tong Long
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yan Huang
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Pei Li
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yu Song
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Xiyang Song
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Kun Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yijie Yin
- School of Sociality and Psychology, Southwest Minzu University, Chengdu 610041, China
| | - Xijian Chen
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China.
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Guo W, Guo Y, Song S, Huang X, Zhang Y, Zhang A, Meng F, Chang M, Wang Z. Causal effect of the age at first birth with depression: a mendelian randomization study. BMC Med Genomics 2024; 17:192. [PMID: 39049090 PMCID: PMC11270952 DOI: 10.1186/s12920-024-01966-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 07/17/2024] [Indexed: 07/27/2024] Open
Abstract
BACKGROUND This study aimed to explore the causal relationship between age at first birth (AFB) and depression. METHODS Using the univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) methods to examine the potential correlation between age at first birth (AFB) and major depressive disorder and postpartum depression. A public database was used to obtain the genome-wide association studies (GWAS) summary data. We put inverse-variance-weighted (IVW) as the primary method in Mendelian randomization (MR) analysis and used sensitivity analysis to confirm the robustness of our result. RESULTS We found a significant causal association between AFB and major depressive disorder by using the IVW algorithm (odd ratio [OR] 0.826; 95% confidence interval [CI] 0.793 - 0.861; P = 4.51 × 10- 20). MR-Egger, weighted median, simple mode and weighted mode method concluded the same result (P < 0.05). During the sensitivity analysis, the heterogeneity test (Q-value = 55.061, df = 48, P = 2.81 × 10- 01, I2 = 12.82%) and the leave-one-out plot analysis confirmed the stability of the results. The outcomes of the pleiotropy test (MR-Egger intercept = 8.932 × 10- 3. SE = 6.909 × 10- 3. P = 2.02 × 10- 01) and MR_PRESSO global test (P = 2.03 × 10- 01) indicated there is no pleiotropy. CONCLUSION There is solid evidence that a higher age at first birth is associated with a lower risk of major depressive disorder.
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Affiliation(s)
- Wanshu Guo
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, 150000, China
- Center for Bioinformatics, Northeast Agricultural University, Harbin, 150000, China
| | - Yuanyuan Guo
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, 150000, China
- Center for Bioinformatics, Northeast Agricultural University, Harbin, 150000, China
| | - Shaokang Song
- Yebio Bioengineering Co., Ltd of Qingdao, Qingdao, 266000, China
| | - Xuankai Huang
- Da Bei Nong Food Group , Breeding Center , Harbin, 150000, Heilongjiang, China
- Branch of Animal Husbandry and Veterinary, Heilongjiang Academy of Agricultural Sciences, No. 2, Heyi St, Longsha District, Qiqihaer, 161005, China
| | - Yu Zhang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, 150000, China
- Center for Bioinformatics, Northeast Agricultural University, Harbin, 150000, China
| | - Aizhen Zhang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, 150000, China
- Center for Bioinformatics, Northeast Agricultural University, Harbin, 150000, China
| | - Fangrong Meng
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, 150000, China
- Center for Bioinformatics, Northeast Agricultural University, Harbin, 150000, China
| | - Minghang Chang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, 150000, China
- Center for Bioinformatics, Northeast Agricultural University, Harbin, 150000, China
| | - Zhipeng Wang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, 150000, China.
- Center for Bioinformatics, Northeast Agricultural University, Harbin, 150000, China.
- Da Bei Nong Food Group , Breeding Center , Harbin, 150000, Heilongjiang, China.
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Mao X, Huang W, Xue Q, Zhang X. Prognostic impact and immunotherapeutic implications of NETosis-related prognostic model in clear cell renal cell carcinoma. J Cancer Res Clin Oncol 2024; 150:278. [PMID: 38801430 PMCID: PMC11129999 DOI: 10.1007/s00432-024-05761-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 04/23/2024] [Indexed: 05/29/2024]
Abstract
BACKGROUND The ramifications of necroptosis on the prognostication of clear cell renal cell carcinoma (ccRCC) remain inadequately expounded. METHODS A prognostic model delineating the facets of necroptosis in ccRCC was constructed, employing a compendium of algorithms. External validation was effectuated using the E-MTAB-1980 dataset. The exploration of immune infiltration scores was undertaken through the exploitation of multiple algorithms. Single-cell RNA sequencing data were procured from the GSE171306 dataset. Real-time quantitative PCR (RT-qPCR) was engaged to scrutinize the differential expression of SLC25A37 across cancer and paracancer tissues, as well as diverse cell lines. Assessments of proliferative and metastatic alterations in 769-P and 786-O cells were accomplished through Cell Counting Kit-8 (CCK8) and wound healing assays. RESULTS The necroptosis-related signature (NRS) emerges as a discerning metric, delineating patients' immune attributes, tumor mutation burden, immunotherapy response, and drug susceptibility. Single-cell RNA sequencing analysis unveils the marked enrichment of SLC25A37 in tumor cells. Concurrently, RT-qPCR discloses the overexpression of SLC25A37 in both ccRCC tissues and cell lines. SLC25A37 knockdown mitigates the proliferative and metastatic propensities of 769-P and 786-O cells, as evidenced by CCK8 and wound healing assays. CONCLUSION The NRS assumes a pivotal role in ascertaining the prognosis, tumor mutation burden, immunotherapy response, drug susceptibility, and immune cell infiltration features of ccRCC patients. SLC25A37 emerges as a putative player in immunosuppressive microenvironments, thereby providing a prospective avenue for the design of innovative immunotherapeutic targets for ccRCC.
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Affiliation(s)
- Xingjun Mao
- Department of Urology, Baoying People's Hospital, Xincheng Road, Baoying, Yangzhou, 225800, Jiangsu, China
| | - Wen Huang
- Department of Good Clinical Practice Office, Nanjing First Hospital, Nanjing Medical University, ChangLe Road 68, Qinhuai District, Nanjing, Jiangsu, China
| | - Qing Xue
- Department of Urology, Baoying People's Hospital, Xincheng Road, Baoying, Yangzhou, 225800, Jiangsu, China.
| | - Xiaolei Zhang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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Han S, DiBlasi E, Monson ET, Shabalin A, Ferris E, Chen D, Fraser A, Yu Z, Staley M, Callor WB, Christensen ED, Crockett DK, Li QS, Willour V, Bakian AV, Keeshin B, Docherty AR, Eilbeck K, Coon H. Whole-genome sequencing analysis of suicide deaths integrating brain-regulatory eQTLs data to identify risk loci and genes. Mol Psychiatry 2023; 28:3909-3919. [PMID: 37794117 PMCID: PMC10730410 DOI: 10.1038/s41380-023-02282-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 09/14/2023] [Accepted: 09/20/2023] [Indexed: 10/06/2023]
Abstract
Recent large-scale genome-wide association studies (GWAS) have started to identify potential genetic risk loci associated with risk of suicide; however, a large portion of suicide-associated genetic factors affecting gene expression remain elusive. Dysregulated gene expression, not assessed by GWAS, may play a significant role in increasing the risk of suicide death. We performed the first comprehensive genomic association analysis prioritizing brain expression quantitative trait loci (eQTLs) within regulatory regions in suicide deaths from the Utah Suicide Genetic Risk Study (USGRS). 440,324 brain-regulatory eQTLs were obtained by integrating brain eQTLs, histone modification ChIP-seq, ATAC-seq, DNase-seq, and Hi-C results from publicly available data. Subsequent genomic analyses were conducted in whole-genome sequencing (WGS) data from 986 suicide deaths of non-Finnish European (NFE) ancestry and 415 ancestrally matched controls. Additional independent USGRS suicide deaths with genotyping array data (n = 4657) and controls from the Genome Aggregation Database were explored for WGS result replication. One significant eQTL locus, rs926308 (p = 3.24e-06), was identified. The rs926308-T is associated with lower expression of RFPL3S, a gene important for neocortex development and implicated in arousal. Gene-based analyses performed using Sherlock Bayesian statistical integrative analysis also detected 20 genes with expression changes that may contribute to suicide risk. From analyzing publicly available transcriptomic data, ten of these genes have previous evidence of differential expression in suicide death or in psychiatric disorders that may be associated with suicide, including schizophrenia and autism (ZNF501, ZNF502, CNN3, IGF1R, KLHL36, NBL1, PDCD6IP, SNX19, BCAP29, and ARSA). Electronic health records (EHR) data was further merged to evaluate if there were clinically relevant subsets of suicide deaths associated with genetic variants. In summary, our study identified one risk locus and ten genes associated with suicide risk via gene expression, providing new insight into possible genetic and molecular mechanisms leading to suicide.
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Affiliation(s)
- Seonggyun Han
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
| | - Emily DiBlasi
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Eric T Monson
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Andrey Shabalin
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Elliott Ferris
- Department of Neurobiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Danli Chen
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Alison Fraser
- Pedigree & Population Resource, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Zhe Yu
- Pedigree & Population Resource, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Michael Staley
- Office of the Medical Examiner, Utah Department of Health and Human Services, Salt Lake City, UT, USA
| | - W Brandon Callor
- Office of the Medical Examiner, Utah Department of Health and Human Services, Salt Lake City, UT, USA
| | - Erik D Christensen
- Office of the Medical Examiner, Utah Department of Health and Human Services, Salt Lake City, UT, USA
| | - David K Crockett
- Clinical Analytics, Intermountain Health, Salt Lake City, UT, USA
| | - Qingqin S Li
- Neuroscience Therapeutic Area, Janssen Research & Development, LLC, Titusville, NJ, USA
| | - Virginia Willour
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Amanda V Bakian
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Brooks Keeshin
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Pediatrics, University of Utah, Salt Lake City, UT, USA
| | - Anna R Docherty
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Karen Eilbeck
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Hilary Coon
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
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Luan T, Yang X, Kuang G, Wang T, He J, Liu Z, Gong X, Wan J, Li K. Identification and Analysis of Neutrophil Extracellular Trap-Related Genes in Osteoarthritis by Bioinformatics and Experimental Verification. J Inflamm Res 2023; 16:3837-3852. [PMID: 37671131 PMCID: PMC10476866 DOI: 10.2147/jir.s414452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 08/11/2023] [Indexed: 09/07/2023] Open
Abstract
Background Osteoarthritis (OA) is a common joint disease with long-term pain and dysfunction that negatively affects the quality of life of patients. Neutrophil extracellular traps (NETs), consisting of DNA, proteins and cytoplasm, are released by neutrophils and play an important role in a variety of diseases. However, the relationship between OA and NETs is unclear. Methods In our study, we used bioinformatics to explore the relationship between OA and NETs and the potential biological markers. GSE55235, GSE55457, GSE117999 and GSE98918 were downloaded from the Gene Expression Omnibus (GEO) database for subsequent analysis.After differential analysis of OA expression matrices, intersection with NET-related genes (NRGs) was taken to identify Differentially expressed NRGs (DE-NRGs) in OA processes. Evaluation of immune cell infiltration by ssGSEA and CIBERSORT algorithm. The GSVA method was used to analyze the activity changes of Neutrophils pathway, Neutrophil degranulation and Neutrophil granule constituents pathway. Results Based on RandomForest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) learning algorithms, five core genes (CRISPLD2, IL1B, SLC25A37, MMP9, and TLR7) were identified to construct an OA-related nomogram model for predicting OA progression. ROC curve results for these genes validated the nomogram's reliability. Correlation analysis, functional enrichment, and drug predictions were performed for the core genes. TLR7 emerged as a key focus due to its high importance ranking in RF and SVM-RFE analyses. Gene Set Enrichment Analysis (GSEA) revealed a strong association between TLR7 and the Neutrophil extracellular trap pathway. Expression of core genes was demonstrated in mice OA models and human OA samples. TLR7 expression in ATDC5 cell line was significantly higher than control after TNFα induction, along with increased IL6 and MMP13. Conclusion TLR7 may be related to NETs and affects OA.
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Affiliation(s)
- Tiankuo Luan
- Department of Anatomy, Chongqing Medical University, Chongqing, People’s Republic of China
| | - Xian Yang
- Department of Pharmacology, Chongqing Medical University, Chongqing, People’s Republic of China
| | - Ge Kuang
- Department of Anatomy, Chongqing Medical University, Chongqing, People’s Republic of China
| | - Ting Wang
- Department of Orthopedics, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
| | - Jiaming He
- Department of Anatomy, Chongqing Medical University, Chongqing, People’s Republic of China
| | - Zhibo Liu
- Department of Orthopedics, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
| | - Xia Gong
- Department of Anatomy, Chongqing Medical University, Chongqing, People’s Republic of China
| | - Jingyuan Wan
- Department of Pharmacology, Chongqing Medical University, Chongqing, People’s Republic of China
| | - Ke Li
- Department of Orthopedics, the First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
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Pasquadibisceglie A, Bonaccorsi di Patti MC, Musci G, Polticelli F. Membrane Transporters Involved in Iron Trafficking: Physiological and Pathological Aspects. Biomolecules 2023; 13:1172. [PMID: 37627237 PMCID: PMC10452680 DOI: 10.3390/biom13081172] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/27/2023] Open
Abstract
Iron is an essential transition metal for its involvement in several crucial biological functions, the most notable being oxygen storage and transport. Due to its high reactivity and potential toxicity, intracellular and extracellular iron levels must be tightly regulated. This is achieved through transport systems that mediate cellular uptake and efflux both at the level of the plasma membrane and on the membranes of lysosomes, endosomes and mitochondria. Among these transport systems, the key players are ferroportin, the only known transporter mediating iron efflux from cells; DMT1, ZIP8 and ZIP14, which on the contrary, mediate iron influx into the cytoplasm, acting on the plasma membrane and on the membranes of lysosomes and endosomes; and mitoferrin, involved in iron transport into the mitochondria for heme synthesis and Fe-S cluster assembly. The focus of this review is to provide an updated view of the physiological role of these membrane proteins and of the pathologies that arise from defects of these transport systems.
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Affiliation(s)
| | | | - Giovanni Musci
- Department of Biosciences and Territory, University of Molise, 86090 Pesche, Italy;
| | - Fabio Polticelli
- Department of Sciences, University Roma Tre, 00146 Rome, Italy;
- National Institute of Nuclear Physics, Roma Tre Section, 00146 Rome, Italy
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Lin J, Yang H, Zhang Y, Cao Z, Li D, Sun L, Zhang X, Wang Y. Association of time spent in outdoor light and genetic risk with the incidence of depression. Transl Psychiatry 2023; 13:40. [PMID: 36737433 PMCID: PMC9898270 DOI: 10.1038/s41398-023-02338-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 01/24/2023] [Accepted: 01/26/2023] [Indexed: 02/05/2023] Open
Abstract
Depression is the consequence of both environment and genes working together. Genetic factors increase depression risk, but it is unclear whether this association can be offset by time spent in outdoor light. The study was undertaken to investigate the optimal time spent in outdoor light for lowering the risk of depression and the joint association of time spent in outdoor light and depression genetic risk. In UK Biobank, 380,976 depression-free individuals were included in this study. Polygenic risk score (PRS) was categorized into three groups in terms of tertiles. Time spent in outdoor light on a typical day in summer or winter originated from the questionnaire survey. Depression was defined as hospital admission. The potential dose-response relationship between time spent in outdoor light and depression risk was shown by a restricted cubic spline. Data were analyzed using Cox regressions and Laplace regression. After the median follow-up of 12.6 years, 13,636 individuals suffered from depression in the end. A nonlinear (J-shaped relationship) trend was observed between time spent in outdoor light and depression risk. On average, 1.5 h/day of outdoor light was related to the minimum risk of depression. Individuals below and above this optimal time both had elevated depression risk (below, HR = 1.09, 95% CI: 1.02-1.16; above, HR = 1.13, 95% CI: 1.07-1.20), and the time to incident depression were both shortened by 0.46 years (50th percentile differences [PD] = -0.46, 95% CI: -0.78, -0.14) and 0.63 years (50th PD = -0.63, 95% CI: -0.90, -0.35) years, respectively. In a comparison of individuals with the lowest tertile of PRS and average 1.5 h/day outdoor light, the HRs and 95% CIs of depression were 1.36 (1.21-1.53) and 1.43 (1.29-1.58) in those with the highest tertile of PRS and below/above this reference value, respectively. Significant multiplicative interactions were observed between intermediate genetic risks and longer time spent in outdoor light. We found that an average of 1.5 h/day spent in outdoor light was associated with a lower depression risk whatever the degree of depression genetic predisposition. Moderate time spent in outdoor light may contribute to a decreased depression risk even among people with a higher genetic risk of depression.
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Affiliation(s)
- Jing Lin
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Yuan Zhang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Zhi Cao
- School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Dun Li
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Li Sun
- School of Nursing, Tianjin Medical University, Tianjin, China
| | - Xinyu Zhang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, Tianjin, China.
- School of Integrative Medicine, Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
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C/EBPβ Regulates TFAM Expression, Mitochondrial Function and Autophagy in Cellular Models of Parkinson's Disease. Int J Mol Sci 2023; 24:ijms24021459. [PMID: 36674978 PMCID: PMC9865173 DOI: 10.3390/ijms24021459] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/30/2022] [Accepted: 01/09/2023] [Indexed: 01/14/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder that results from the degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc). Since there are only symptomatic treatments available, new cellular and molecular targets involved in the onset and progression of this disease are needed to develop effective treatments. CCAAT/Enhancer Binding Protein β (C/EBPβ) transcription factor levels are altered in patients with a variety of neurodegenerative diseases, suggesting that it may be a good therapeutic target for the treatment of PD. A list of genes involved in PD that can be regulated by C/EBPβ was generated by the combination of genetic and in silico data, the mitochondrial transcription factor A (TFAM) being among them. In this paper, we observed that C/EBPβ overexpression increased TFAM promoter activity. However, downregulation of C/EBPβ in different PD/neuroinflammation cellular models produced an increase in TFAM levels, together with other mitochondrial markers. This led us to propose an accumulation of non-functional mitochondria possibly due to the alteration of their autophagic degradation in the absence of C/EBPβ. Then, we concluded that C/EBPβ is not only involved in harmful processes occurring in PD, such as inflammation, but is also implicated in mitochondrial function and autophagy in PD-like conditions.
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Mitoferrin, Cellular and Mitochondrial Iron Homeostasis. Cells 2022; 11:cells11213464. [PMID: 36359860 PMCID: PMC9658796 DOI: 10.3390/cells11213464] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/28/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
Abstract
Iron is essential for many cellular processes, but cellular iron homeostasis must be maintained to ensure the balance of cellular signaling processes and prevent disease. Iron transport in and out of the cell and cellular organelles is crucial in this regard. The transport of iron into the mitochondria is particularly important, as heme and the majority of iron-sulfur clusters are synthesized in this organelle. Iron is also required for the production of mitochondrial complexes that contain these iron-sulfur clusters and heme. As the principal iron importers in the mitochondria of human cells, the mitoferrins have emerged as critical regulators of cytosolic and mitochondrial iron homeostasis. Here, we review the discovery and structure of the mitoferrins, as well as the significance of these proteins in maintaining cytosolic and mitochondrial iron homeostasis for the prevention of cancer and many other diseases.
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Crist RC, Vickers-Smith R, Kember RL, Rentsch CT, Xu H, Edelman EJ, Hartwell EE, Kampman KM, Kranzler HR. Analysis of genetic and clinical factors associated with buprenorphine response. Drug Alcohol Depend 2021; 227:109013. [PMID: 34488071 PMCID: PMC9328121 DOI: 10.1016/j.drugalcdep.2021.109013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 08/12/2021] [Accepted: 08/15/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND Buprenorphine, approved for treating opioid use disorder (OUD), is not equally efficacious for all patients. Candidate gene studies have shown limited success in identifying genetic moderators of buprenorphine treatment response. METHODS We studied 1616 European-ancestry individuals enrolled in the Million Veteran Program, of whom 1609 had an ICD-9/10 code consistent with OUD, a 180-day buprenorphine treatment exposure, and genome-wide genotype data. We conducted a genome-wide association study (GWAS) of buprenorphine treatment response [defined as having no opioid-positive urine drug screens (UDS) following the first prescription]. We also examined correlates of buprenorphine treatment response in multivariable analyses. RESULTS Although no variants reached genome-wide significance, 6 loci were nominally significant (p < 1 × 10-5), four of which were located near previously characterized genes: rs756770 (ADAMTSL2), rs11782370 (SLC25A37), rs7205113 (CRISPLD2), and rs13169373 (LINC01947). A higher maximum daily buprenorphine dosage (aOR = 0.98; 95 %CI: 0.97, 0.995), greater number of UDS (aOR = 0.97; 95 %CI: 0.96, 0.99), and history of hepatitis C (HCV) infection (aOR = 0.71; 95 %CI: 0.57, 0.88) were associated with a reduced odds of buprenorphine response. Older age (aOR: 1.01; 95 %CI: 1.000, 1.02) was associated with increased odds of buprenorphine response. CONCLUSIONS This study had limited statistical power to detect genetic variants associated with a complex human phenotype like buprenorphine treatment response. Meta-analysis of multiple data sets is needed to ensure adequate statistical power for a GWAS of buprenorphine treatment response. The most robust phenotypic predictor of buprenorphine treatment response was intravenous drug use, a proxy for which was HCV infection.
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Affiliation(s)
- Richard C. Crist
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104,Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
| | - Rachel Vickers-Smith
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104,Department of Epidemiology, University of Kentucky College of Public Health, Lexington, KY 40536,Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington, KY 40536
| | - Rachel L. Kember
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104,Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
| | - Christopher T. Rentsch
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, 06516,Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - Heng Xu
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
| | | | - Emily E. Hartwell
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104,Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
| | - Kyle M. Kampman
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104,Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
| | - Henry R. Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104,Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104,Corresponding Author: Henry R. Kranzler, M.D., Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, 3535 Market St., Suite 500, Philadelphia, PA 19104, Phone: 215-746-1943,
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11
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Shalimova A, Babasieva V, Chubarev VN, Tarasov VV, Schiöth HB, Mwinyi J. Therapy response prediction in major depressive disorder: current and novel genomic markers influencing pharmacokinetics and pharmacodynamics. Pharmacogenomics 2021; 22:485-503. [PMID: 34018822 DOI: 10.2217/pgs-2020-0157] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Major depressive disorder is connected with high rates of functional disability and mortality. About a third of the patients are at risk of therapy failure. Several pharmacogenetic markers especially located in CYP450 genes such as CYP2D6 or CYP2C19 are of relevance for therapy outcome prediction in major depressive disorder but a further optimization of predictive tools is warranted. The article summarizes the current knowledge on pharmacogenetic variants, therapy effects and side effects of important antidepressive therapeutics, and sheds light on new methodological approaches for therapy response estimation based on genetic markers with relevance for pharmacokinetics, pharmacodynamics and disease pathology identified in genome-wide association study analyses, highlighting polygenic risk score analysis as a tool for further optimization of individualized therapy outcome prediction.
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Affiliation(s)
- Alena Shalimova
- Department of Neuroscience, Functional Pharmacology, University of Uppsala, Uppsala, 751 24, Sweden.,Department of Pharmacology, Institute of Pharmacy, I. M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Viktoria Babasieva
- Department of Neuroscience, Functional Pharmacology, University of Uppsala, Uppsala, 751 24, Sweden.,Department of Pharmacology, Institute of Pharmacy, I. M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Vladimir N Chubarev
- Department of Pharmacology, Institute of Pharmacy, I. M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Vadim V Tarasov
- Department of Pharmacology, Institute of Pharmacy, I. M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia.,Institute of Translational Medicine & Biotechnology, I. M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Helgi B Schiöth
- Department of Neuroscience, Functional Pharmacology, University of Uppsala, Uppsala, 751 24, Sweden.,Institute of Translational Medicine & Biotechnology, I. M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Jessica Mwinyi
- Department of Neuroscience, Functional Pharmacology, University of Uppsala, Uppsala, 751 24, Sweden
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12
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Li X, Su X, Liu J, Li H, Li M, Li W, Luo XJ. Transcriptome-wide association study identifies new susceptibility genes and pathways for depression. Transl Psychiatry 2021; 11:306. [PMID: 34021117 PMCID: PMC8140098 DOI: 10.1038/s41398-021-01411-w] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Revised: 04/22/2021] [Accepted: 04/30/2021] [Indexed: 12/11/2022] Open
Abstract
Depression is the most prevalent mental disorder with substantial morbidity and mortality. Although genome-wide association studies (GWASs) have identified multiple risk variants for depression, due to the complicated gene regulatory mechanisms and complexity of linkage disequilibrium (LD), the biological mechanisms by which the risk variants exert their effects on depression remain largely unknown. Here, we perform a transcriptome-wide association study (TWAS) of depression by integrating GWAS summary statistics from 807,553 individuals (246,363 depression cases and 561,190 controls) and summary-level gene-expression data (from the dorsolateral prefrontal cortex (DLPFC) of 1003 individuals). We identified 53 transcriptome-wide significant (TWS) risk genes for depression, of which 23 genes were not implicated in risk loci of the original GWAS. Seven out of 53 risk genes (B3GALTL, FADS1, TCTEX1D1, XPNPEP3, ZMAT2, ZNF501 and ZNF502) showed TWS associations with depression in two independent brain expression quantitative loci (eQTL) datasets, suggesting that these genes may represent promising candidates. We further conducted conditional analyses and identified the potential risk genes that driven the TWAS association signal in each locus. Finally, pathway enrichment analysis revealed biologically pathways relevant to depression. Our study identified new depression risk genes whose expression dysregulation may play a role in depression. More importantly, we translated the GWAS associations into risk genes and relevant pathways. Further mechanistic study and functional characterization of the TWS depression risk genes will facilitate the diagnostics and therapeutics for depression.
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Affiliation(s)
- Xiaoyan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, 230601, Hefei, Anhui, China
| | - Xi Su
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, China
| | - Jiewei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
| | - Huijuan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
| | - Wenqiang Li
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China.
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, China.
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China.
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, 650204, Kunming, China.
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13
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Integrative genomics analysis identifies five promising genes implicated in insomnia risk based on multiple omics datasets. Biosci Rep 2021; 40:226183. [PMID: 32830860 PMCID: PMC7468094 DOI: 10.1042/bsr20201084] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 08/15/2020] [Accepted: 08/21/2020] [Indexed: 12/27/2022] Open
Abstract
In recent decades, many genome-wide association studies on insomnia have reported numerous genes harboring multiple risk variants. Nevertheless, the molecular functions of these risk variants conveying risk to insomnia are still ill-studied. In the present study, we integrated GWAS summary statistics (N=386,533) with two independent brain expression quantitative trait loci (eQTL) datasets (N=329) to determine whether expression-associated SNPs convey risk to insomnia. Furthermore, we applied numerous bioinformatics analyses to highlight promising genes associated with insomnia risk. By using Sherlock integrative analysis, we detected 449 significant insomnia-associated genes in the discovery stage. These identified genes were significantly overrepresented in six biological pathways including Huntington’s disease (P=5.58 × 10−5), Alzheimer’s disease (P=5.58 × 10−5), Parkinson’s disease (P=6.34 × 10−5), spliceosome (P=1.17 × 10−4), oxidative phosphorylation (P=1.09 × 10−4), and wnt signaling pathways (P=2.07 × 10−4). Further, five of these identified genes were replicated in an independent brain eQTL dataset. Through a PPI network analysis, we found that there existed highly functional interactions among these five identified genes. Three genes of LDHA (P=0.044), DALRD3 (P=5.0 × 10−5), and HEBP2 (P=0.032) showed significantly lower expression level in brain tissues of insomnic patients than that in controls. In addition, the expression levels of these five genes showed prominently dynamic changes across different time points between behavioral states of sleep and sleep deprivation in mice brain cortex. Together, the evidence of the present study strongly suggested that these five identified genes may represent candidate genes and contributed risk to the etiology of insomnia.
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14
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Zhong Y, Chen L, Li J, Yao Y, Liu Q, Niu K, Ma Y, Xu Y. Integration of summary data from GWAS and eQTL studies identified novel risk genes for coronary artery disease. Medicine (Baltimore) 2021; 100:e24769. [PMID: 33725943 PMCID: PMC7982177 DOI: 10.1097/md.0000000000024769] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 01/23/2021] [Indexed: 01/05/2023] Open
Abstract
Several genetic loci have been reported to be significantly associated with coronary artery disease (CAD) by multiple genome-wide association studies (GWAS). Nevertheless, the biological and functional effects of these genetic variants on CAD remain largely equivocal. In the current study, we performed an integrative genomics analysis by integrating large-scale GWAS data (N = 459,534) and 2 independent expression quantitative trait loci (eQTL) datasets (N = 1890) to determine whether CAD-associated risk single nucleotide polymorphisms (SNPs) exert regulatory effects on gene expression. By using Sherlock Bayesian, MAGMA gene-based, multidimensional scaling (MDS), functional enrichment, and in silico permutation analyses for independent technical and biological replications, we highlighted 4 susceptible genes (CHCHD1, TUBG1, LY6G6C, and MRPS17) associated with CAD risk. Based on the protein-protein interaction (PPI) network analysis, these 4 genes were found to interact with each other. We detected a remarkably altered co-expression pattern among these 4 genes between CAD patients and controls. In addition, 3 genes of CHCHD1 (P = .0013), TUBG1 (P = .004), and LY6G6C (P = .038) showed significantly different expressions between CAD patients and controls. Together, we provide evidence to support that these identified genes such as CHCHD1 and TUBG1 are indicative factors of CAD.
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Affiliation(s)
- Yigang Zhong
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine
| | | | - Jingjing Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Yinghao Yao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Qiang Liu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Kaimeng Niu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Yunlong Ma
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Yizhou Xu
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine
- Zhejiang Chinese Medical University
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15
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Li S, Li X, Liu J, Huo Y, Li L, Wang J, Luo XJ. Functional variants fine-mapping and gene function characterization provide insights into the role of ZNF323 in schizophrenia pathogenesis. Am J Med Genet B Neuropsychiatr Genet 2021; 186:28-39. [PMID: 33522098 DOI: 10.1002/ajmg.b.32835] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 01/03/2021] [Accepted: 01/09/2021] [Indexed: 12/22/2022]
Abstract
Schizophrenia is a severe mental disease characterized with positive symptoms, negative symptoms, and cognitive impairments. Although recent genome-wide association studies (GWASs) have identified over 145 risk loci for schizophrenia, pinpointing the causal variants and genes at the reported loci and elucidating their roles in schizophrenia remain major challenges. Here we identify a functional single-nucleotide polymorphism (SNP; rs213237) in ZNF323 promoter by using functional fine-mapping. We found that allelic differences at rs213237 affected the ZNF323 promoter activity significantly. Consistently, expression quantitative trait loci (eQTL) analysis showed that rs213237 was significantly associated with ZNF323 expression in diverse human brain tissues, suggesting that rs213237 may contribute to schizophrenia risk through regulating ZNF323 expression. Interestingly, we found that ZNF323 protein was localized in the nucleus and knockdown of ZNF323 in macaque neural stem cells (mNSCs) significantly impaired proliferation and survival of mNSCs. We further showed that stable knockdown of ZNF323 in SH-SY5Y cells resulted in significant decrease of the tyrosine hydroxylase (TH) protein expression. Finally, transcriptome analysis revealed that ZNF323 may regulate pivotal schizophrenia risk genes (including VIPR2 and NPY) and schizophrenia-associated pathways (including PI3K-AKT and NOTCH signaling pathways), suggesting that ZNF323 may be a major regulator of schizophrenia risk genes. Our study reveals how a genetic variant in ZNF323 promoter contributes to schizophrenia risk through regulating ZNF323 expression. More importantly, our findings demonstrate that ZNF323 may have a pivotal role in schizophrenia pathogenesis through regulating schizophrenia risk genes and schizophrenia-associated biological processes (including neurodevelopment, PI3K-AKT, and NOTCH signaling pathways).
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Affiliation(s)
- Shiwu Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Xiaoyan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Jiewei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yongxia Huo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Long Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Junyang Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
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16
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Dong Z, Ma Y, Zhou H, Shi L, Ye G, Yang L, Liu P, Zhou L. Integrated genomics analysis highlights important SNPs and genes implicated in moderate-to-severe asthma based on GWAS and eQTL datasets. BMC Pulm Med 2020; 20:270. [PMID: 33066754 PMCID: PMC7568423 DOI: 10.1186/s12890-020-01303-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 09/27/2020] [Indexed: 02/06/2023] Open
Abstract
Background Severe asthma is a chronic disease contributing to disproportionate disease morbidity and mortality. From the year of 2007, many genome-wide association studies (GWAS) have documented a large number of asthma-associated genetic variants and related genes. Nevertheless, the molecular mechanism of these identified variants involved in asthma or severe asthma risk remains largely unknown. Methods In the current study, we systematically integrated 3 independent expression quantitative trait loci (eQTL) data (N = 1977) and a large-scale GWAS summary data of moderate-to-severe asthma (N = 30,810) by using the Sherlock Bayesian analysis to identify whether expression-related variants contribute risk to severe asthma. Furthermore, we performed various bioinformatics analyses, including pathway enrichment analysis, PPI network enrichment analysis, in silico permutation analysis, DEG analysis and co-expression analysis, to prioritize important genes associated with severe asthma. Results In the discovery stage, we identified 1129 significant genes associated with moderate-to-severe asthma by using the Sherlock Bayesian analysis. Two hundred twenty-eight genes were prominently replicated by using MAGMA gene-based analysis. These 228 replicated genes were enriched in 17 biological pathways including antigen processing and presentation (Corrected P = 4.30 × 10− 6), type I diabetes mellitus (Corrected P = 7.09 × 10− 5), and asthma (Corrected P = 1.72 × 10− 3). With the use of a series of bioinformatics analyses, we highlighted 11 important genes such as GNGT2, TLR6, and TTC19 as authentic risk genes associated with moderate-to-severe/severe asthma. With respect to GNGT2, there were 3 eSNPs of rs17637472 (PeQTL = 2.98 × 10− 8 and PGWAS = 3.40 × 10− 8), rs11265180 (PeQTL = 6.0 × 10− 6 and PGWAS = 1.99 × 10− 3), and rs1867087 (PeQTL = 1.0 × 10− 4 and PGWAS = 1.84 × 10− 5) identified. In addition, GNGT2 is significantly expressed in severe asthma compared with mild-moderate asthma (P = 0.045), and Gngt2 shows significantly distinct expression patterns between vehicle and various glucocorticoids (Anova P = 1.55 × 10− 6). Conclusions Our current study provides multiple lines of evidence to support that these 11 identified genes as important candidates implicated in the pathogenesis of severe asthma.
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Affiliation(s)
- Zhouzhou Dong
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Yunlong Ma
- Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Hua Zhou
- Department of Respiratory Disease, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, P.R. China
| | - Linhui Shi
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Gongjie Ye
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Lei Yang
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Panpan Liu
- Critical Care Unit, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China
| | - Li Zhou
- Department of Immunology and Rheumatology, Ningbo Medical Center Lihuili Hospital, Taipei Medical University Ningbo Medical Center, Ningbo, Zhejiang, 315100, P.R. China.
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17
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Ma X, Wang P, Xu G, Yu F, Ma Y. Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma. BMC Med Genomics 2020; 13:123. [PMID: 32867763 PMCID: PMC7457797 DOI: 10.1186/s12920-020-00768-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 08/17/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Childhood-onset asthma is highly affected by genetic components. In recent years, many genome-wide association studies (GWAS) have reported a large group of genetic variants and susceptible genes associated with asthma-related phenotypes including childhood-onset asthma. However, the regulatory mechanisms of these genetic variants for childhood-onset asthma susceptibility remain largely unknown. METHODS In the current investigation, we conducted a two-stage designed Sherlock-based integrative genomics analysis to explore the cis- and/or trans-regulatory effects of genome-wide SNPs on gene expression as well as childhood-onset asthma risk through incorporating a large-scale GWAS data (N = 314,633) and two independent expression quantitative trait loci (eQTL) datasets (N = 1890). Furthermore, we applied various bioinformatics analyses, including MAGMA gene-based analysis, pathway enrichment analysis, drug/disease-based enrichment analysis, computer-based permutation analysis, PPI network analysis, gene co-expression analysis and differential gene expression analysis, to prioritize susceptible genes associated with childhood-onset asthma. RESULTS Based on comprehensive genomics analyses, we found 31 genes with multiple eSNPs to be convincing candidates for childhood-onset asthma risk; such as, PSMB9 (cis-rs4148882 and cis-rs2071534) and TAP2 (cis-rs9267798, cis-rs4148882, cis-rs241456, and trans-10,447,456). These 31 genes were functionally interacted with each other in our PPI network analysis. Our pathway enrichment analysis showed that numerous KEGG pathways including antigen processing and presentation, type I diabetes mellitus, and asthma were significantly enriched to involve in childhood-onset asthma risk. The co-expression patterns among 31 genes were remarkably altered according to asthma status, and 25 of 31 genes (25/31 = 80.65%) showed significantly or suggestively differential expression between asthma group and control group. CONCLUSIONS We provide strong evidence to highlight 31 candidate genes for childhood-onset asthma risk, and offer a new insight into the genetic pathogenesis of childhood-onset asthma.
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Affiliation(s)
- Xiuqing Ma
- Department of Pulmonary & Critical Care Medicine, Chinese PLA General Hospital, Beijing, 100853 China
| | - Peilan Wang
- Outpatient Department, Chinese PLA General Hospital, Beijing, 100853 China
| | - Guobing Xu
- Department of Cardiovascular Medicine, Zhongxiang People’s Hospital, Zhongxiang, 431900 Hubei Province China
| | - Fang Yu
- Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100853 China
| | - Yunlong Ma
- Institute of Biomedical Big Data, School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027 P. R. China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China
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18
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Integrative genomics analysis of eQTL and GWAS summary data identifies PPP1CB as a novel bone mineral density risk genes. Biosci Rep 2020; 40:222598. [PMID: 32266926 PMCID: PMC7178214 DOI: 10.1042/bsr20193185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 03/03/2020] [Accepted: 04/03/2020] [Indexed: 11/17/2022] Open
Abstract
In recent years, multiple genome-wide association studies (GWAS) have identified numerous susceptibility variants and risk genes that demonstrate significant associations with bone mineral density (BMD). However, exploring how these genetic variants contribute risk to BMD remains a major challenge. We systematically integrated two independent expression quantitative trait loci (eQTL) data (N = 1890) and GWAS summary statistical data of BMD (N = 142,487) using Sherlock integrative analysis to reveal whether expression-associated variants confer risk to BMD. By using Sherlock integrative analysis and MAGMA gene-based analysis, we found there existed 36 promising genes, for example, PPP1CB, XBP1, and FDFT1, whose expression alterations may contribute susceptibility to BMD. Through a protein-protein interaction (PPI) network analysis, we further prioritized the PPP1CB as a hub gene that has interactions with predicted genes and BMD-associated genes. Two eSNPs of rs9309664 (PeQTL = 1.42 × 10-17 and PGWAS = 1.40 × 10-11) and rs7475 (PeQTL = 2.10 × 10-6 and PGWAS = 1.70 × 10-7) in PPP1CB were identified to be significantly associated with BMD risk. Consistently, differential gene expression analysis found that the PPP1CB gene showed significantly higher expression in low BMD samples than that in high BMD samples based on two independent expression datasets (P = 0.0026 and P = 0.043, respectively). Together, we provide a convergent line of evidence to support that the PPP1CB gene involves in the etiology of osteoporosis.
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19
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Liu L, Gu H, Hou F, Xie X, Li X, Zhu B, Zhang J, Wei WH, Song R. Dyslexia associated functional variants in Europeans are not associated with dyslexia in Chinese. Am J Med Genet B Neuropsychiatr Genet 2019; 180:488-495. [PMID: 31264768 DOI: 10.1002/ajmg.b.32750] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 04/30/2019] [Accepted: 06/14/2019] [Indexed: 01/09/2023]
Abstract
Genome-wide association studies (GWAS) of developmental dyslexia (DD) often used European samples and identified only a handful associations with moderate or weak effects. This study aims to identify DD functional variants by integrating the GWAS associations with tissue-specific functional data and test the variants in a Chinese DD study cohort named READ. We colocalized associations from nine DD related GWAS with expression quantitative trait loci (eQTL) derived from brain tissues and identified two eSNPs rs349045 and rs201605. Both eSNPs had supportive evidence of chromatin interactions observed in human hippocampus tissues and their respective target genes ZNF45 and DNAH9 both had lower expression in brain tissues in schizophrenia patients than controls. In contrast, an eSNP rs4234898 previously identified based on eQTL from the lymphoblastic cell lines of dyslexic children had no chromatin interaction with its target gene SLC2A3 in hippocampus tissues and SLC2A3 expressed higher in the schizophrenia patients than controls. We genotyped the three eSNPs in the READ cohort of 372 cases and 354 controls and discovered only weak associations in rs201605 and rs4234898 with three DD symptoms (p < .05). The lack of associations could be due to low power in READ but could also implicate different etiology of DD in Chinese.
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Affiliation(s)
- Lingfei Liu
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huaiting Gu
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fang Hou
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xinyan Xie
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xin Li
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bing Zhu
- Hangzhou Center for Disease Control and Prevention, Hangzhou, China
| | - Jiajia Zhang
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina
| | - Wen-Hua Wei
- Department of Women's and Children's Health, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | - Ranran Song
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Nedic Erjavec G, Svob Strac D, Tudor L, Konjevod M, Sagud M, Pivac N. Genetic Markers in Psychiatry. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1192:53-93. [PMID: 31705490 DOI: 10.1007/978-981-32-9721-0_4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Psychiatric disorders such as addiction (substance use and addictive disorders), depression, eating disorders, schizophrenia, and post-traumatic stress disorder (PTSD) are severe, complex, multifactorial mental disorders that carry a high social impact, enormous public health costs, and various comorbidities as well as premature morbidity. Their neurobiological foundation is still not clear. Therefore, it is difficult to uncover new set of genes and possible genetic markers of these disorders since the understanding of the molecular imbalance leading to these disorders is not complete. The integrative approach is needed which will combine genomics and epigenomics; evaluate epigenetic influence on genes and their influence on neuropeptides, neurotransmitters, and hormones; examine gene × gene and gene × environment interplay; and identify abnormalities contributing to development of these disorders. Therefore, novel genetic approaches based on systems biology focused on improvement of the identification of the biological underpinnings might offer genetic markers of addiction, depression, eating disorders, schizophrenia, and PTSD. These markers might be used for early prediction, detection of the risk to develop these disorders, novel subtypes of the diseases and tailored, personalized approach to therapy.
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Affiliation(s)
- Gordana Nedic Erjavec
- Division of Molecular Medicine, Rudjer Boskovic Institute, Bijenicka 54, HR-10000, Zagreb, Croatia
| | - Dubravka Svob Strac
- Division of Molecular Medicine, Rudjer Boskovic Institute, Bijenicka 54, HR-10000, Zagreb, Croatia
| | - Lucija Tudor
- Division of Molecular Medicine, Rudjer Boskovic Institute, Bijenicka 54, HR-10000, Zagreb, Croatia
| | - Marcela Konjevod
- Division of Molecular Medicine, Rudjer Boskovic Institute, Bijenicka 54, HR-10000, Zagreb, Croatia
| | - Marina Sagud
- School of Medicine, University of Zagreb, Salata 2, HR-10000, Zagreb, Croatia
- Department of Psychiatry, University Hospital Centre Zagreb, Kispaticeva 12, HR-10000, Zagreb, Croatia
| | - Nela Pivac
- Division of Molecular Medicine, Rudjer Boskovic Institute, Bijenicka 54, HR-10000, Zagreb, Croatia.
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Gonda X, Petschner P, Eszlari N, Baksa D, Edes A, Antal P, Juhasz G, Bagdy G. Genetic variants in major depressive disorder: From pathophysiology to therapy. Pharmacol Ther 2018; 194:22-43. [PMID: 30189291 DOI: 10.1016/j.pharmthera.2018.09.002] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
In spite of promising preclinical results there is a decreasing number of new registered medications in major depression. The main reason behind this fact is the lack of confirmation in clinical studies for the assumed, and in animals confirmed, therapeutic results. This suggests low predictive value of animal studies for central nervous system disorders. One solution for identifying new possible targets is the application of genetics and genomics, which may pinpoint new targets based on the effect of genetic variants in humans. The present review summarizes such research focusing on depression and its therapy. The inconsistency between most genetic studies in depression suggests, first of all, a significant role of environmental stress. Furthermore, effect of individual genes and polymorphisms is weak, therefore gene x gene interactions or complete biochemical pathways should be analyzed. Even genes encoding target proteins of currently used antidepressants remain non-significant in genome-wide case control investigations suggesting no main effect in depression, but rather an interaction with stress. The few significant genes in GWASs are related to neurogenesis, neuronal synapse, cell contact and DNA transcription and as being nonspecific for depression are difficult to harvest pharmacologically. Most candidate genes in replicable gene x environment interactions, on the other hand, are connected to the regulation of stress and the HPA axis and thus could serve as drug targets for depression subgroups characterized by stress-sensitivity and anxiety while other risk polymorphisms such as those related to prominent cognitive symptoms in depression may help to identify additional subgroups and their distinct treatment. Until these new targets find their way into therapy, the optimization of current medications can be approached by pharmacogenomics, where metabolizing enzyme polymorphisms remain prominent determinants of therapeutic success.
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Affiliation(s)
- Xenia Gonda
- Department of Psychiatry and Psychotherapy, Kutvolgyi Clinical Centre, Semmelweis University, Budapest, Hungary; NAP-2-SE New Antidepressant Target Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary; MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary.
| | - Peter Petschner
- MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary; Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary
| | - Nora Eszlari
- NAP-2-SE New Antidepressant Target Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary; Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary
| | - Daniel Baksa
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary; SE-NAP 2 Genetic Brain Imaging Migraine Research Group, Hungarian Academy of Sciences, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary
| | - Andrea Edes
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary; SE-NAP 2 Genetic Brain Imaging Migraine Research Group, Hungarian Academy of Sciences, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary
| | - Peter Antal
- Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary
| | - Gabriella Juhasz
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary; SE-NAP 2 Genetic Brain Imaging Migraine Research Group, Hungarian Academy of Sciences, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary; Neuroscience and Psychiatry Unit, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Gyorgy Bagdy
- NAP-2-SE New Antidepressant Target Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary; MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary; Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary.
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Iniesta R, Hodgson K, Stahl D, Malki K, Maier W, Rietschel M, Mors O, Hauser J, Henigsberg N, Dernovsek MZ, Souery D, Dobson R, Aitchison KJ, Farmer A, McGuffin P, Lewis CM, Uher R. Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables. Sci Rep 2018; 8:5530. [PMID: 29615645 PMCID: PMC5882876 DOI: 10.1038/s41598-018-23584-z] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 03/13/2018] [Indexed: 12/19/2022] Open
Abstract
Individuals with depression differ substantially in their response to treatment with antidepressants. Specific predictors explain only a small proportion of these differences. To meaningfully predict who will respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables. Using statistical learning on common genetic variants and clinical information in a training sample of 280 individuals randomly allocated to 12-week treatment with antidepressants escitalopram or nortriptyline, we derived models to predict remission with each antidepressant drug. We tested the reproducibility of each prediction in a validation set of 150 participants not used in model derivation. An elastic net logistic model based on eleven genetic and six clinical variables predicted remission with escitalopram in the validation dataset with area under the curve 0.77 (95%CI; 0.66-0.88; p = 0.004), explaining approximately 30% of variance in who achieves remission. A model derived from 20 genetic variables predicted remission with nortriptyline in the validation dataset with an area under the curve 0.77 (95%CI; 0.65-0.90; p < 0.001), explaining approximately 36% of variance in who achieves remission. The predictive models were antidepressant drug-specific. Validated drug-specific predictions suggest that a relatively small number of genetic and clinical variables can help select treatment between escitalopram and nortriptyline.
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Affiliation(s)
- Raquel Iniesta
- Biostatistics and Health Informatics Department. Institute of Psychiatry, Psychology and Neuroscience, Kings College London. 16 De Crespigny Park, London, SE5 8AF, UK
| | - Karen Hodgson
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Daniel Stahl
- Biostatistics and Health Informatics Department. Institute of Psychiatry, Psychology and Neuroscience, Kings College London. 16 De Crespigny Park, London, SE5 8AF, UK
| | - Karim Malki
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Wolfgang Maier
- Department of Psychiatry, University of Bonn, Regina-Pacis-Weg 3, 53113, Bonn, Germany
| | - Marcella Rietschel
- Central Institute of Mental Health, Division of Genetic Epidemiology in Psychiatry, Square J5, 68159, Mannheim, Germany
| | - Ole Mors
- Research Department P, Aarhus University Hospital, Norrebrogade 44, DK-8000, Aarhus C Risskov, Denmark
| | - Joanna Hauser
- Laboratory of Psychiatric Genetics, Department of Psychiatry, Poznan University of Medical Sciences, Collegium Maius, Fredry 10, 61-701, Poznań, Poland
| | - Neven Henigsberg
- Croatian Institute for Brain Research, Medical School, University of Zagreb, 10 000, Zagreb, Salata 3, Croatia
| | - Mojca Zvezdana Dernovsek
- Vzgojni zavod Planina, Planina 211, 6232 Planina, Slovenina and Universitiy of Ljubljana, Medical Faculty, Vrazov trg 2, 1000, Ljubljana, Slovenia
| | - Daniel Souery
- Laboratoire de Psychologie Médicale, Université Libre de Bruxelles and Psy Pluriel - Centre Européen de Psychologie Médicale, Av Jack Pastur 47a, 1180, Uccle, Belgium
| | - Richard Dobson
- Biostatistics and Health Informatics Department. Institute of Psychiatry, Psychology and Neuroscience, Kings College London. 16 De Crespigny Park, London, SE5 8AF, UK
| | - Katherine J Aitchison
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
- Department of Psychiatry and Medical Genetics, University of Alberta, 116 St and 85 Ave, Edmonton, AB T6G 2R3, Canada
| | - Anne Farmer
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Peter McGuffin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Rudolf Uher
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK.
- Dalhousie University Department of Psychiatry, 5909 Veterans' Memorial Lane, Halifax, B3H 2E2, Nova Scotia, Canada.
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Shadrina M, Bondarenko EA, Slominsky PA. Genetics Factors in Major Depression Disease. Front Psychiatry 2018; 9:334. [PMID: 30083112 PMCID: PMC6065213 DOI: 10.3389/fpsyt.2018.00334] [Citation(s) in RCA: 136] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 07/02/2018] [Indexed: 12/22/2022] Open
Abstract
Depressive disorders (DDs) are one of the most widespread forms of psychiatric pathology. According to the World Health Organization, about 350 million people in the world are affected by this condition. Family and twin studies have demonstrated that the contribution of genetic factors to the risk of the onset of DDs is quite large. Various methodological approaches (analysis of candidate genes, genome-wide association analysis, genome-wide sequencing) have been used, and a large number of the associations between genes and different clinical DD variants and DD subphenotypes have been published. However, in most cases, these associations have not been confirmed in replication studies, and only a small number of genes have been proven to be associated with DD development risk. To ascertain the role of genetic factors in DD pathogenesis, further investigations of the relevant conditions are required. Special consideration should be given to the polygenic characteristics noted in whole-genome studies of the heritability of the disorder without a pronounced effect of the major gene. These observations accentuate the relevance of the analysis of gene-interaction roles in DD development and progression. It is important that association studies of the inherited variants of the genome should be supported by analysis of dynamic changes during DD progression. Epigenetic changes that cause modifications of a gene's functional state without changing its coding sequence are of primary interest. However, the opportunities for studying changes in the epigenome, transcriptome, and proteome during DD are limited by the nature of the disease and the need for brain tissue analysis, which is possible only postmortem. Therefore, any association studies between DD pathogenesis and epigenetic factors must be supplemented through the use of different animal models of depression. A threefold approach comprising the combination of gene association studies, assessment of the epigenetic state in DD patients, and analysis of different "omic" changes in animal depression models will make it possible to evaluate the contribution of genetic, epigenetic, and environmental factors to the development of different forms of depression and to help develop ways to decrease the risk of depression and improve the treatment of DD.
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Affiliation(s)
- Maria Shadrina
- Laboratory of Molecular Genetics of Hereditary Diseases, Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Elena A Bondarenko
- Laboratory of Molecular Genetics of Hereditary Diseases, Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Petr A Slominsky
- Laboratory of Molecular Genetics of Hereditary Diseases, Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia
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