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Yu X, Chen Y, Chen J, Fan Y, Lu H, Wu D, Xu Y. Shared genetic architecture between autoimmune disorders and B-cell acute lymphoblastic leukemia: insights from large-scale genome-wide cross-trait analysis. BMC Med 2024; 22:161. [PMID: 38616254 PMCID: PMC11017616 DOI: 10.1186/s12916-024-03385-0] [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: 01/08/2024] [Accepted: 04/08/2024] [Indexed: 04/16/2024] Open
Abstract
BACKGROUND To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved. METHODS Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations. RESULTS Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P < 5 × 10-8), 16 of which had strong evidence of colocalization. We demonstrated that several loci have been previously reported (e.g., 17q21) and discovered some novel loci (e.g., 10p12, 5p13). Further gene-level identified 194 unique pleiotropic genes, for example IKZF1, GATA3, IKZF3, GSDMB, and ORMDL3. Pathway analysis determined the key role of cellular response to cytokine stimulus, B cell activation, and JAK-STAT signaling pathways. SNP-level and gene-level tissue enrichment suggested that crucial role pleiotropic mechanisms involved in the spleen, whole blood, and EBV-transformed lymphocytes. Also, hyprcoloc and stratified LD score regression analyses revealed that B cells at different developmental stages may be involved in mechanisms shared between two different diseases. Finally, two-sample MR analysis determined causal effects of asthma and rheumatoid arthritis on B-ALL. CONCLUSIONS Our research proved shared genetic architecture between autoimmune disorders and B-ALL and shed light on the potential mechanism that might involve in.
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Affiliation(s)
- Xinghao Yu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Collaborative Innovation Center of Hematology, Institute of Blood and Marrow Transplantation, Soochow University, Suzhou, China
| | - Yiyin Chen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Collaborative Innovation Center of Hematology, Institute of Blood and Marrow Transplantation, Soochow University, Suzhou, China
| | - Jia Chen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yi Fan
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Huimin Lu
- Department of Outpatient and Emergency, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Depei Wu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.
- Collaborative Innovation Center of Hematology, Institute of Blood and Marrow Transplantation, Soochow University, Suzhou, China.
| | - Yang Xu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.
- Collaborative Innovation Center of Hematology, Institute of Blood and Marrow Transplantation, Soochow University, Suzhou, China.
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Dan YL, Yang YQ, Zhu DC, Bo L, Lei SF. Accelerated biological aging as a potential risk factor for rheumatoid arthritis. Int J Rheum Dis 2024; 27:e15156. [PMID: 38665050 DOI: 10.1111/1756-185x.15156] [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: 02/08/2024] [Revised: 03/15/2024] [Accepted: 04/05/2024] [Indexed: 05/31/2024]
Abstract
OBJECTS Previous studies have suggested a potential correlation between rheumatoid arthritis (RA) and biological aging, but the intricate connections and mechanisms remain elusive. METHODS In our study, we focused on two specific measures of biological age (PhenoAge and BioAge), which are derived from clinical biomarkers. The residuals of these measures, when compared to chronological age, are defined as biological age accelerations (BAAs). Utilizing the extensive UK Biobank dataset along with various genetic datasets, we conducted a thorough assessment of the relationship between BAAs and RA at both the individual and aggregate levels. RESULTS Our observational studies revealed positive correlations between the two BAAs and the risk of developing both RA and seropositive RA. Furthermore, the genetic risk score (GRS) for PhenoAgeAccel was associated with an increased risk of RA and seropositive RA. Linkage disequilibrium score regression (LDSC) analysis further supported these findings, revealing a positive genetic correlation between PhenoAgeAccel and RA. PLACO analysis identified 38 lead pleiotropic single nucleotide polymorphisms linked to 301 genes, providing valuable insights into the potential mechanisms connecting PhenoAgeAccel and RA. CONCLUSION In summary, our study has successfully revealed a positive correlation between accelerated biological aging, as measured by BAAs, and the susceptibility to RA.
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Affiliation(s)
- Yi-Lin Dan
- Collaborative Innovation Center for Bone and Immunology between Sihong Hospital and Soochow University, Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Soochow University, Suzhou, Jiangsu, China
| | - Yi-Qun Yang
- Collaborative Innovation Center for Bone and Immunology between Sihong Hospital and Soochow University, Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Soochow University, Suzhou, Jiangsu, China
| | - Dong-Cheng Zhu
- Department of Orthopedics, Collaborative Innovation Center for Bone and Immunology between Sihong Hospital and Soochow University, Suqian, Jiangsu, China
| | - Lin Bo
- Department of Rheumatology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Shu-Feng Lei
- Collaborative Innovation Center for Bone and Immunology between Sihong Hospital and Soochow University, Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Soochow University, Suzhou, Jiangsu, China
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Segura AG, Serna EDL, Sugranyes G, Baeza I, Valli I, Martínez-Serrano I, Díaz-Caneja CM, Andreu-Bernabeu Á, Moreno DM, Gassó P, Rodríguez N, Martínez-Pinteño A, Prohens L, Torrent C, García-Rizo C, Mas S, Castro-Fornieles J. Polygenic risk scores mediating functioning outcomes through cognitive and clinical features in youth at family risk and controls. Eur Neuropsychopharmacol 2024; 81:28-37. [PMID: 38310718 DOI: 10.1016/j.euroneuro.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 02/06/2024]
Abstract
Schizophrenia and bipolar disorder exhibit substantial clinical overlap, particularly in individuals at familial high risk, who frequently present sub-threshold symptoms before the onset of illness. Severe mental disorders are highly polygenic traits, but their impact on the stages preceding the manifestation of mental disorders remains relatively unexplored. Our study aimed to examine the influence of polygenic risk scores (PRS) on sub-clinical outcomes over a 2-year period in youth at familial high risk for schizophrenia and bipolar disorder and controls. The sample included 222 children and adolescents, comprising offspring of parents with schizophrenia (n = 38), bipolar disorder (n = 80), and community controls (n = 104). We calculated PRS for psychiatric disorders, neuroticism and cognition using the PRS-CS method. Linear mixed-effects models were employed to investigate the association between PRS and cognition, symptom severity and functioning. Mediation analyses were conducted to explore whether clinical features acted as intermediaries in the impact of PRS on functioning outcomes. SZoff exhibited elevated PRS for schizophrenia. In the entire sample, PRS for depression, neuroticism, and cognitive traits showed associations with sub-clinical features. The effect of PRS for neuroticism and general intelligence on functioning outcomes were mediated by cognition and symptoms severity, respectively. This study delves into the interplay among genetics, the emergence of sub-clinical symptoms and functioning outcomes, providing novel evidence on mechanisms underpinning the continuum from sub-threshold features to the onset of mental disorders. The findings underscore the interplay of genetics, cognition, and clinical features, providing insights for personalized early interventions.
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Affiliation(s)
- Alex G Segura
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Elena de la Serna
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Gisela Sugranyes
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Inmaculada Baeza
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Isabel Valli
- Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Irene Martínez-Serrano
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Álvaro Andreu-Bernabeu
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Dolores M Moreno
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Adolescent Inpatient Unit, Department of Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Psychiatry Department, Universidad Complutense de Madrid, Madrid, Spain
| | - Patricia Gassó
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Natalia Rodríguez
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Albert Martínez-Pinteño
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Llucia Prohens
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Carla Torrent
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Barcelona Bipolar Disorders Program, Clinical Institute of Neuroscience, Hospital Clinic, University of Barcelona, Fundació Clinic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Clemente García-Rizo
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Barcelona Clinic Schizophrenia Unit, Institute of Neuroscience, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Sergi Mas
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
| | - Josefina Castro-Fornieles
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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Zhang D, Li J, Lu T, Zhao F, Guo P, Li Z, Duan X, Li Y, Li S, Li J. Illuminating Shared Genetic Associations Between Oesophageal Carcinoma and Pulmonary Carcinoma Risk. J Cancer 2024; 15:2412-2423. [PMID: 38495498 PMCID: PMC10937272 DOI: 10.7150/jca.92899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 01/23/2024] [Indexed: 03/19/2024] Open
Abstract
Background: Lung cancer and oesophageal cancer are prevalent malignancies with rising incidence and mortality worldwide. While some environmental and behavioural risk factors for these cancers are established, the contribution of genetic factors to their pathogenesis remains incompletely defined. This study aimed to interrogate the intricate genetic relationship between lung cancer and oesophageal cancer and their potential comorbidity. Methods: We utilised linkage disequilibrium score regression (LDSC) to analyse the genetic correlation between oesophageal carcinoma and lung carcinoma. We then employed several approaches, including pleiotropic analysis under the composite null hypothesis (PLACO), multi-marker analysis of genomic annotation (MAGMA), cis-expression quantitative trait loci (eQTL) analysis, and a pan-cancer assessment to identify pleiotropic loci and genes. Finally, we performed bidirectional Mendelian randomisation (MR) to evaluate the causal relationship between these malignancies. Results: LDSC revealed a significant genetic correlation between oesophageal carcinoma and lung carcinoma. Further analysis identified shared gene loci including PGBD1, ZNF323, and WNK1 using PLACO. MAGMA identified enriched pathways and 9 pleiotropic genes including HIST1H1B, HIST1H4L, and HIST1H2BL. eQTL analysis integrating oesophageal, lung, and blood tissues revealed 26 shared genes including TERT, NKAPL, RAD52, BTN3A2, GABBR1, CLPTM1L, and TRIM27. A pan-cancer exploration of the identified genes was undertaken. MR analysis showed no evidence for a bidirectional causal relationship between oesophageal carcinoma and lung carcinoma. Conclusions: This study provides salient insights into the intricate genetic links between lung carcinoma and oesophageal carcinoma. Utilising multiple approaches for genetic correlation, locus and gene analysis, and causal assessment, we identify shared genetic susceptibilities and regulatory mechanisms. These findings reveal new leads and targets to further elucidate the genetic basis of lung and oesophageal carcinoma, aiding development of preventive and therapeutic strategies.
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Affiliation(s)
- Dengfeng Zhang
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jing Li
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Tianxing Lu
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Fangchao Zhao
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Pengfei Guo
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Zhirong Li
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Xiaoliang Duan
- Department of Thoracic Surgery, Hebei Chest Hospital, Shijiazhuang, China
| | - Yishuai Li
- Department of Thoracic Surgery, Hebei Chest Hospital, Shijiazhuang, China
| | - Shujun Li
- Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jianhang Li
- Department of Thoracic Surgery, Hebei Chest Hospital, Shijiazhuang, China
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Dai J, Chen K, Zhu Y, Xia L, Wang T, Yuan Z, Zeng P. Identifying risk loci for obsessive-compulsive disorder and shared genetic component with schizophrenia: A large-scale multi-trait association analysis with summary statistics. Prog Neuropsychopharmacol Biol Psychiatry 2024; 129:110906. [PMID: 38043635 DOI: 10.1016/j.pnpbp.2023.110906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 11/26/2023] [Accepted: 11/28/2023] [Indexed: 12/05/2023]
Abstract
Due to limited samples, no genetic loci have been identified for obsessive-compulsive disorder (OCD) in genome-wide association studies. Additionally, although co-morbidities between OCD and schizophrenia (SCZ) were observed, their common genetic etiology was not completely known. Here, we conducted a comprehensive investigation regarding the genetic architecture of OCD and the common genetic foundation shared by OCD and SCZ using summary statistics data (2688 cases and 7037 controls for OCD; 53,386 cases and 77,258 controls for SCZ). We discovered significant genetic correlation between OCD and SCZ (r̂g=0.296, P = 2.82 × 10-11). We then performed two multi-trait association analyses to detect OCD-associated loci and colocalization analysis to detect causal variants. Parallel gene-level analyses were also implemented. We identified 323 OCD-relevant variants located within 12 loci, with four loci shared the same causal variants between OCD and SCZ. Further, the gene-level analyses discovered 8 OCD-associated genes. Finally, multiple functional analyses at both SNP and gene levels showed that these genetic association signals had significant enrichments in the regions of left ventricle and anterior cingulate cortex, and suggested an important role of pathways involving regulation of telomere maintenance, histone phosphorylation, and GnRH secretion. Overall, this study identified new genetic loci for OCD and provided substantial evidence supporting common genetic foundation underlying OCD and SCZ. The findings advanced our understanding of genetic architecture and pathophysiology of OCD as well as shedding light on shared genetic etiology of the two disorders.
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Affiliation(s)
- Jing Dai
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Keying Chen
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Yiyang Zhu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Lei Xia
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Zhongshang Yuan
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Xuzhou Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Jiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
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Yuan J, Zhang J, Luo Q, Peng L. Effects of nonalcoholic fatty liver disease on sarcopenia: evidence from genetic methods. Sci Rep 2024; 14:2709. [PMID: 38302636 PMCID: PMC10834579 DOI: 10.1038/s41598-024-53112-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 01/28/2024] [Indexed: 02/03/2024] Open
Abstract
With the aging of the population, sarcopenia has become more common. Studies have shown a broad association between liver disease and sarcopenia. However, this link remains unclear. Our study explored the link between NAFLD and sarcopenia and predicting the pathogenesis. To begin, we investigated the causal relationship and genetic correlation between them using MR and LDSC. Second, each GWAS was annotated by MAGMA. The annotated genes were analyzed for pleiotropy using the PLACO approach. Finally, functional analysis was conducted on the identified pleiotropic genes. We observed a significant genetic correlation between NAFLD and sarcopenia. Subsequently, we conducted gene-level pleiotropy analysis using PLACO and identified a total of 153 genes with pleiotropic effects. Functional analysis revealed enrichment of these genes in various tissues, including pancreas, liver, heart, blood, brain, and muscle, with involvement in cellular regulation, intracellular function, and antigen response. Moreover, our MR analysis provided evidence of a causal relationship between NAFLD and sarcopenia. Our study has discovered the genetic and causal relationships between NAFLD and sarcopenia, providing further insights into their pathophysiological mechanisms. The identification of pleiotropic genes also offers potential targets for future drug therapies aimed at controlling or treating NAFLD and sarcopenia.
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Affiliation(s)
- Jiaqin Yuan
- Department of Orthopedics, The Second People's Hospital of Yibin, Sichuan, China
| | - Jinglin Zhang
- Department of Occupational Diseases, Yibin Center for Disease Control and Prevention, Sichuan, China
| | - Qiang Luo
- Department of Cardiology, Children's Hospital of Chongqing Medical University, Chongqing, China.
| | - Lipeng Peng
- Department of Orthopedics, The Second People's Hospital of Yibin, Sichuan, China.
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Zhai M, Zhang Y, Yan D, Wang Y, Li W, Sun J. Genetic Insights into the Association and Causality Between Blood Metabolites and Alzheimer's Disease. J Alzheimers Dis 2024; 98:885-896. [PMID: 38489174 DOI: 10.3233/jad-230985] [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] [Indexed: 03/17/2024]
Abstract
Background Alzheimer's disease (AD) is an increasing public health concern with the aging of the global population. Understanding the genetic correlation and potential causal relationships between blood metabolites and AD may provide important insights into the metabolic dysregulation underlying this neurodegenerative disorder. Objective The aim of this study was to investigate the causal relationship between blood metabolites and AD using Mendelian randomization (MR) analysis. Methods Association data were obtained from three large-scale genome-wide association studies of 486 blood metabolites (N = 7,824), AD (71,880 cases and 383,378 controls), early-onset AD (N = 303,760), and late-onset AD (N = 307,112). Causal associations between blood metabolites and AD were assessed using inverse variance weighting (IVW), MR-Egger, and weighted median methods. Bidirectional two-sample MR analysis was used to identify causal blood metabolites. MR-PRESSO, MR-Egger, and Cochran-Q were used to quantify instrumental variable heterogeneity and horizontal pleiotropy. Results Using MR and sensitivity analysis, we identified 40 blood metabolites with potential causal associations with AD. After applying false discovery rate (FDR) correction, two metabolites, gamma-glutamylphenylalanine (OR = 1.15, 95% CI: 1.06-1.24, p = 3.88×10-4, q = 0.09) and X-11317 (OR = 1.16, 95% CI: 1.08-1.26, p = 1.14×10-4, q = 0.05), retained significant associations with AD. Reverse MR analysis indicated no significant causal effect of AD on blood metabolites. No significant instrumental variable heterogeneity or horizontal pleiotropy was found. Conclusions This two-sample MR study provides compelling evidence for a potential causal relationship between blood metabolic dysregulation and susceptibility to AD. Further investigation of the biological relevance of the identified metabolites to AD and additional supporting evidence is warranted.
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Affiliation(s)
- Modi Zhai
- National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Yu Zhang
- Beidahuang Industry Group General Hospital, Harbin, China
| | - Dongxue Yan
- National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Yuzhen Wang
- National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Wenzhong Li
- National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Jie Sun
- National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
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Liu Z, Xu J, Tan J, Li X, Zhang F, Ouyang W, Wang S, Huang Y, Li S, Pan X. Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study. iScience 2023; 26:108150. [PMID: 37908310 PMCID: PMC10613921 DOI: 10.1016/j.isci.2023.108150] [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: 05/26/2023] [Revised: 08/13/2023] [Accepted: 10/02/2023] [Indexed: 11/02/2023] Open
Abstract
Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.
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Affiliation(s)
- Zeye Liu
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Jing Xu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China
| | - Jiangshan Tan
- Key Laboratory of Pulmonary Vascular Medicine, National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xiaofei Li
- Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Fengwen Zhang
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Wenbin Ouyang
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Shouzheng Wang
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Yuan Huang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Pediatric Cardiac Surgery Center, Fuwai Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China
| | - Shoujun Li
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Pediatric Cardiac Surgery Center, Fuwai Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China
| | - Xiangbin Pan
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
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9
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Lin S, Zhang H, Qi M, Cooper DN, Yang Y, Yang Y, Zhao H. Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization. Neuroimage 2023; 279:120325. [PMID: 37579999 DOI: 10.1016/j.neuroimage.2023.120325] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 07/09/2023] [Accepted: 08/11/2023] [Indexed: 08/16/2023] Open
Abstract
Observational studies consistently disclose brain imaging-derived phenotypes (IDPs) as critical markers for early diagnosis of both brain disorders and cardiovascular diseases. However, it remains unclear about the shared genetic landscape between brain IDPs and the risk of brain disorders and cardiovascular diseases, restricting the applications of potential diagnostic techniques through brain IDPs. Here, we reported genetic correlations and putative causal relationships between 921 brain IDPs, 20 brain disorders and six cardiovascular diseases by leveraging their large-scale genome-wide association study (GWAS) summary statistics. Applications of Mendelian randomization (MR) identified significant putative causal effects of multiple region-specific brain IDPs in relation to the increased risks for amyotrophic lateral sclerosis (ALS), major depressive disorder (MDD), autism spectrum disorder (ASD) and schizophrenia (SCZ). We also found brain IDPs specifically from temporal lobe as a putatively causal consequence of hypertension. The genome-wide colocalization analysis identified three genomic regions in which MDD, ASD and SCZ colocalized with the brain IDPs, and two novel SNPs to be associated with ASD, SCZ, and multiple brain IDPs. Furthermore, we identified a list of candidate genes involved in the shared genetics underlying pairs of brain IDPs and MDD, ASD, SCZ, ALS and hypertension. Our results provide novel insights into the genetic relationships between brain disorders and cardiovascular diseases and brain IDP, which may server as clues for using brain IDPs to predict risks of diseases.
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Affiliation(s)
- Siying Lin
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China; School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China
| | - Haoyang Zhang
- School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China
| | - Mengling Qi
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, United Kingdom
| | - Yuedong Yang
- School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China.
| | - Yuanhao Yang
- Mater Research Institute, The University of Queensland, Brisbane, QLD, Australia.
| | - Huiying Zhao
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China.
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10
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Soda T, Merner AR, Small BJ, Torgerson LN, Muñoz K, Austin J, Storch EA, Pereira S, Lázaro-Muñoz G. Child and adolescent psychiatrists' use, attitudes, and understanding of genetic testing and pharmacogenetics in clinical practice. Psychiatry Res 2023; 325:115246. [PMID: 37172398 PMCID: PMC10365566 DOI: 10.1016/j.psychres.2023.115246] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 05/02/2023] [Accepted: 05/05/2023] [Indexed: 05/15/2023]
Abstract
The purpose of this study was to report current practices and attitudes of child and adolescent psychiatrists (CAP) regarding diagnostic genetic and pharmacogenetic (PGx) testing. We surveyed 958 US-based practicing CAP. 54.9% of respondents indicated that they had ordered/referred for a genetic test in the past 12 months. 87% of respondents agreed that it is their role to discuss genetic information regarding psychiatric conditions with their patients; however, 45% rated their knowledge of genetic testing practice guidelines as poor/very poor. The most ordered test was PGx (32.2%), followed by chromosomal microarray (23.0%). 73.4% reported that PGx is at least slightly useful in child and adolescent psychiatry. Most (62.8%) were asked by a patient/family to order PGx in the past 12 months and 41.7% reported they would order PGx in response to a family request. Those who ordered a PGx test were more likely to have been asked by a patient/family and to work in private practice. 13.8% of respondents agreed/strongly agreed that a PGx test can predict the effectiveness of specific antidepressants. Some respondents also indicated they would make clinical changes based on PGx information even if a medication was currently effective and there were no side effects. Genetic testing has become routine clinical care in child and adolescent psychiatry. Despite this, many providers rate their associated knowledge as poor/very poor. Patient requests were associated with ordering practices and providers misinterpretation of PGx may be leading to unnecessary changes in clinical management. There is need for further education and support for clinicians.
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Affiliation(s)
- Takahiro Soda
- Department of Psychiatry, University of Florida, Gainesville, FL, United States of America; Center for Autism and Neurodevelopment, University of Florida, Gainesville, Florida, United States of America
| | - Amanda R Merner
- Center for Bioethics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Brent J Small
- School of Aging Studies, University of South Florida, Tampa, FL, United States of America
| | | | - Katrina Muñoz
- School of Medicine, Emory University, Atlanta, Georgia, United States of America
| | - Jehannine Austin
- Department of Psychiatry, University of British Columbia, Vancouver, Canada; Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Eric A Storch
- Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, Texas, United States of America
| | - Stacey Pereira
- Center for Medical Ethics & Health Policy at Baylor College of Medicine
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard Medical School, Boston, Massachusetts, United States of America; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
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11
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Lu H, Zhang S, Jiang Z, Zeng P. Leveraging trans-ethnic genetic risk scores to improve association power for complex traits in underrepresented populations. Brief Bioinform 2023:bbad232. [PMID: 37332016 DOI: 10.1093/bib/bbad232] [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: 12/29/2022] [Revised: 05/06/2023] [Accepted: 06/04/2023] [Indexed: 06/20/2023] Open
Abstract
Trans-ethnic genome-wide association studies have revealed that many loci identified in European populations can be reproducible in non-European populations, indicating widespread trans-ethnic genetic similarity. However, how to leverage such shared information more efficiently in association analysis is less investigated for traits in underrepresented populations. We here propose a statistical framework, trans-ethnic genetic risk score informed gene-based association mixed model (GAMM), by hierarchically modeling single-nucleotide polymorphism effects in the target population as a function of effects of the same trait in well-studied populations. GAMM powerfully integrates genetic similarity across distinct ancestral groups to enhance power in understudied populations, as confirmed by extensive simulations. We illustrate the usefulness of GAMM via the application to 13 blood cell traits (i.e. basophil count, eosinophil count, hematocrit, hemoglobin concentration, lymphocyte count, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, mean corpuscular volume, monocyte count, neutrophil count, platelet count, red blood cell count and total white blood cell count) in Africans of the UK Biobank (n = 3204) while utilizing genetic overlap shared in Europeans (n = 746 667) and East Asians (n = 162 255). We discovered multiple new associated genes, which had otherwise been missed by existing methods, and revealed that the trans-ethnic information indirectly contributed much to the phenotypic variance. Overall, GAMM represents a flexible and powerful statistical framework of association analysis for complex traits in underrepresented populations by integrating trans-ethnic genetic similarity across well-studied populations, and helps attenuate health inequities in current genetics research for people of minority populations.
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Affiliation(s)
- Haojie Lu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Zhou Jiang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China
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12
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Dai J, Xu Y, Wang T, Zeng P. Exploring the relationship between socioeconomic deprivation index and Alzheimer's disease using summary-level data: From genetic correlation to causality. Prog Neuropsychopharmacol Biol Psychiatry 2023; 123:110700. [PMID: 36566903 DOI: 10.1016/j.pnpbp.2022.110700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 11/04/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
Patients with Alzheimer's disease (AD) are markedly increasing as population aging and no disease-modifying therapies are currently available for AD. Previous studies suggested a broad link between socioeconomic status and a variety of disorders, including mental illness and cognitive abilities. However, the association between socioeconomic deprivation and AD has been unknown. We here employed Townsend deprivation index (TDI) to explore such relation and found a positive genetic correlation (r̂g=0.211, P = 8.00 × 10-4) between the two traits with summary statistics data (N = 455,258 for TDI and N = 455,815 for AD). Then, we performed pleiotropy analysis at both variant and gene levels using a powerful method called PLACO and detected 87 distinct pleiotropic genes. Functional analysis demonstrated these genes were significantly enriched in pancreas, liver, heart, blood, brain, and muscle tissues. Using Mendelian randomization methods, we further found that one genetically predicted standard deviation elevation in TDI could lead to approximately 18.5% (95% confidence intervals 1.6- 38.2%, P = 0.031) increase of AD risk, and that the identified causal association was robust against used MR approaches, horizontal pleiotropy, and instrumental selection. Overall, this study provides deep insight into common genetic components underlying TDI and AD, and further reveals causal connection between them. It is also helpful to develop a more suitable plan for ameliorating inequities, hardship, and disadvantage, with the hope of improving health outcomes among economically disadvantaged people.
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Affiliation(s)
- Jing Dai
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Yue Xu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
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13
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Genetic correlation and gene-based pleiotropy analysis for four major neurodegenerative diseases with summary statistics. Neurobiol Aging 2023; 124:117-128. [PMID: 36740554 DOI: 10.1016/j.neurobiolaging.2022.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 03/25/2022] [Accepted: 12/27/2022] [Indexed: 01/02/2023]
Abstract
Recent genome-wide association studies suggested shared genetic components between neurodegenerative diseases. However, pleiotropic association patterns among them remain poorly understood. We here analyzed 4 major neurodegenerative diseases including Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), and found suggestively positive genetic correlation. We next implemented a gene-centric pleiotropy analysis with a powerful method called PLACO and detected 280 pleiotropic associations (226 unique genes) with these diseases. Functional analyses demonstrated that these genes were enriched in the pancreas, liver, heart, blood, brain, and muscle tissues; and that 42 pleiotropic genes exhibited drug-gene interactions with 341 drugs. Using Mendelian randomization, we discovered that AD and PD can increase the risk of developing ALS, and that AD and ALS can also increase the risk of developing FTD, respectively. Overall, this study provides in-depth insights into shared genetic components and causal relationship among the 4 major neurodegenerative diseases, indicating genetic overlap and causality commonly drive their co-occurrence. It also has important implications on the etiology understanding, drug development and therapeutic targets for neurodegenerative diseases.
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14
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Xu H, Shao Z, Zhang S, Liu X, Zeng P. How can childhood maltreatment affect post-traumatic stress disorder in adult: Results from a composite null hypothesis perspective of mediation analysis. Front Psychiatry 2023; 14:1102811. [PMID: 36970281 PMCID: PMC10033829 DOI: 10.3389/fpsyt.2023.1102811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 02/20/2023] [Indexed: 03/11/2023] Open
Abstract
BackgroundA greatly growing body of literature has revealed the mediating role of DNA methylation in the influence path from childhood maltreatment to psychiatric disorders such as post-traumatic stress disorder (PTSD) in adult. However, the statistical method is challenging and powerful mediation analyses regarding this issue are lacking.MethodsTo study how the maltreatment in childhood alters long-lasting DNA methylation changes which further affect PTSD in adult, we here carried out a gene-based mediation analysis from a perspective of composite null hypothesis in the Grady Trauma Project (352 participants and 16,565 genes) with childhood maltreatment as exposure, multiple DNA methylation sites as mediators, and PTSD or its relevant scores as outcome. We effectively addressed the challenging issue of gene-based mediation analysis by taking its composite null hypothesis testing nature into consideration and fitting a weighted test statistic.ResultsWe discovered that childhood maltreatment could substantially affected PTSD or PTSD-related scores, and that childhood maltreatment was associated with DNA methylation which further had significant roles in PTSD and these scores. Furthermore, using the proposed mediation method, we identified multiple genes within which DNA methylation sites exhibited mediating roles in the influence path from childhood maltreatment to PTSD-relevant scores in adult, with 13 for Beck Depression Inventory and 6 for modified PTSD Symptom Scale, respectively.ConclusionOur results have the potential to confer meaningful insights into the biological mechanism for the impact of early adverse experience on adult diseases; and our proposed mediation methods can be applied to other similar analysis settings.
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Affiliation(s)
- Haibo Xu
- Center for Mental Health Education and Research, Xuzhou Medical University, Xuzhou, China
- School of Management, Xuzhou Medical University, Xuzhou, China
- *Correspondence: Haibo Xu,
| | - Zhonghe Shao
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Xin Liu
- Center for Mental Health Education and Research, Xuzhou Medical University, Xuzhou, China
- School of Management, Xuzhou Medical University, Xuzhou, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Ping Zeng,
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15
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Chen M, Li S, Zhu Z, Dai C, Hao X. Investigating the shared genetic architecture and causal relationship between pain and neuropsychiatric disorders. Hum Genet 2023; 142:431-443. [PMID: 36445456 DOI: 10.1007/s00439-022-02507-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 11/14/2022] [Indexed: 11/30/2022]
Abstract
Pain often occurs in parallel with neuropsychiatric disorders. However, the underlying mechanisms and potential causality have not been well studied. We collected the genome-wide association study (GWAS) summary statistics of 26 common pain and neuropsychiatric disorders with sample size ranging from 17,310 to 482,730 in European population. The genetic correlation between pair of pain and neuropsychiatric disorders, as well as the relevant cell types were investigated by linkage disequilibrium (LD) score regression analyses. Then, transcriptome-wide association study (TWAS) was applied to identify the potential shared genes by integrating the gene expression information and GWAS. In addition, Mendelian randomization (MR) analyses were conducted to infer the potential causality between pain and neuropsychiatric disorders. Among the 169 pairwise pain and neuropsychiatric disorders, 55 pairs showed positive correlations (median rg = 0.43) and 9 pairs showed negative correlations (median rg = -0.31). Using MR analyses, 26 likely causal associations were identified, including that neuroticism and insomnia were risk factors for most of short-term pain, and multisite chronic pain was risk factor for neuroticism, insomnia, major depressive disorder and attention deficit/hyperactivity disorder, and vice versa. The signals of pain and neuropsychiatric disorders tended to be enriched in the functional regions of cell types from central nervous system (CNS). A total of 19 genes shared in at least one pain and neuropsychiatric disorder pair were identified by TWAS, including AMT, NCOA6, and UNC45A, which involved in glycine degradation, insulin secretion, and cell proliferation, respectively. Our findings provided the evidence of shared genetic structure, causality and potential shared pathogenic mechanisms between pain and neuropsychiatric disorders, and enhanced our understanding of the comorbidities of pain and neuropsychiatric disorders.
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Affiliation(s)
- Mengya Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Si Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Ziwei Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Chengguqiu Dai
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Xingjie Hao
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
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16
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Soda T, Merner AR, Small BJ, Torgerson LN, Muñoz K, Austin J, Storch EA, Pereira S, Lázaro-Muñoz G. Child and Adolescent Psychiatrists' Use, Attitudes, and Understanding of Genetic Tests in Clinical Practice. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.24.23284953. [PMID: 36747629 PMCID: PMC9901070 DOI: 10.1101/2023.01.24.23284953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Objective To report current practices and attitudes of child and adolescent psychiatrists (CAP) regarding diagnostic genetic and pharmacogenetic (PGx) testing. Methods Survey of 958 US-based practicing CAP. Results 54.9% of respondents indicated that they had ordered/referred for a genetic test in the past 12 months. 87% of respondents agreed that it is their role to discuss genetic information regarding psychiatric conditions with their patients; however, 45% rated their knowledge of genetic testing practice guidelines as poor/very poor. The most ordered test was PGx (32.2%), followed by chromosomal microarray (23.0%). 73.4% reported that PGx is at least slightly useful in child and adolescent psychiatry. Most (62.8%) were asked by a patient/family to order PGx in the past 12 months and 41.7% reported they would order PGx in response to a family request. Those who ordered a PGx test were more likely to have been asked by a patient/family and to work in private practice. 13.8% of respondents agreed/strongly agreed that a PGx test can predict the effectiveness of specific antidepressants. Some respondents also indicated they would make clinical changes based on PGx information even if a medication was currently effective and there were no side effects. Conclusions Genetic testing has become routine clinical care in child and adolescent psychiatry. Despite this, many providers rate their associated knowledge as poor/very poor. Patient requests were associated with ordering practices and providers misinterpretation of PGx may be leading to unnecessary changes in clinical management. There is need for further education and support for clinicians.
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17
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Qiao J, Shao Z, Wu Y, Zeng P, Wang T. Detecting associated genes for complex traits shared across East Asian and European populations under the framework of composite null hypothesis testing. Lab Invest 2022; 20:424. [PMID: 36138484 PMCID: PMC9503281 DOI: 10.1186/s12967-022-03637-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 09/12/2022] [Indexed: 11/21/2022]
Abstract
Background Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking. Methods By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement. Results Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones. Conclusion Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03637-8.
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Affiliation(s)
- Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Zhonghe Shao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuxuan Wu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. .,Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. .,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. .,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. .,Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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18
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Depression and bipolar disorder subtypes differ in their genetic correlations with biological rhythms. Sci Rep 2022; 12:15740. [PMID: 36131119 PMCID: PMC9492698 DOI: 10.1038/s41598-022-19720-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 09/02/2022] [Indexed: 11/29/2022] Open
Abstract
Major Depression and Bipolar Disorder Type I (BIP-I) and Type II (BIP-II), are characterized by depressed, manic, and hypomanic episodes in which specific changes of physical activity, circadian rhythm, and sleep are observed. It is known that genetic factors contribute to variation in mood disorders and biological rhythms, but unclear to what extent there is an overlap between their underlying genetics. In the present study, data from genome-wide association studies were used to examine the genetic relationship between mood disorders and biological rhythms. We tested the genetic correlation of depression, BIP-I, and BIP-II with physical activity (overall physical activity, moderate activity, sedentary behaviour), circadian rhythm (relative amplitude), and sleep features (sleep duration, daytime sleepiness). Genetic correlations of depression, BIP-I, and BIP-II with biological rhythms were compared to discover commonalities and differences. A gene-based analysis tested for associations of single genes and common circadian genes with mood disorders. Depression was negatively correlated with overall physical activity and positively with sedentary behaviour, while BIP-I showed associations in the opposite direction. Depression and BIP-II had negative correlations with relative amplitude. All mood disorders were positively correlated with daytime sleepiness. Overall, we observed both genetic commonalities and differences across mood disorders in their relationships with biological rhythms: depression and BIP-I differed the most, while BIP-II was in an intermediate position. Gene-based analysis suggested potential targets for further investigation. The present results suggest shared genetic underpinnings for the clinically observed associations between mood disorders and biological rhythms. Research considering possible joint mechanisms may offer avenues for improving disease detection and treatment.
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19
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Shao Z, Wang T, Qiao J, Zhang Y, Huang S, Zeng P. A comprehensive comparison of multilocus association methods with summary statistics in genome-wide association studies. BMC Bioinformatics 2022; 23:359. [PMID: 36042399 PMCID: PMC9429742 DOI: 10.1186/s12859-022-04897-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 08/22/2022] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Multilocus analysis on a set of single nucleotide polymorphisms (SNPs) pre-assigned within a gene constitutes a valuable complement to single-marker analysis by aggregating data on complex traits in a biologically meaningful way. However, despite the existence of a wide variety of SNP-set methods, few comprehensive comparison studies have been previously performed to evaluate the effectiveness of these methods. RESULTS We herein sought to fill this knowledge gap by conducting a comprehensive empirical comparison for 22 commonly-used summary-statistics based SNP-set methods. We showed that only seven methods could effectively control the type I error, and that these well-calibrated approaches had varying power performance under the simulation scenarios. Overall, we confirmed that the burden test was generally underpowered and score-based variance component tests (e.g., sequence kernel association test) were much powerful under the polygenic genetic architecture in both common and rare variant association analyses. We further revealed that two linkage-disequilibrium-free P value combination methods (e.g., harmonic mean P value method and aggregated Cauchy association test) behaved very well under the sparse genetic architecture in simulations and real-data applications to common and rare variant association analyses as well as in expression quantitative trait loci weighted integrative analysis. We also assessed the scalability of these approaches by recording computational time and found that all these methods can be scalable to biobank-scale data although some might be relatively slow. CONCLUSION In conclusion, we hope that our findings can offer an important guidance on how to choose appropriate multilocus association analysis methods in post-GWAS era. All the SNP-set methods are implemented in the R package called MCA, which is freely available at https://github.com/biostatpzeng/ .
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Affiliation(s)
- Zhonghe Shao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuchen Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Shuiping Huang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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Renzaho AM, Hall BJ, Chen W. The mental health-migration interface among sub-Saharan African and Chinese populations. Curr Opin Psychol 2022; 47:101416. [DOI: 10.1016/j.copsyc.2022.101416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/15/2022] [Accepted: 06/28/2022] [Indexed: 11/03/2022]
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