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Leung PBM, Liu Z, Zhong Y, Tubbs JD, Di Forti M, Murray RM, So HC, Sham PC, Lui SSY. Bidirectional two-sample Mendelian randomization study of differential white blood cell counts and schizophrenia. Brain Behav Immun 2024; 118:22-30. [PMID: 38355025 DOI: 10.1016/j.bbi.2024.02.015] [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: 07/24/2023] [Revised: 01/15/2024] [Accepted: 02/08/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND Schizophrenia and white blood cell counts (WBC) are both complex and polygenic traits. Previous evidence suggests that increased WBC are associated with higher all-cause mortality, and other studies have found elevated WBC in first-episode psychosis and chronic schizophrenia. However, these observational findings may be confounded by antipsychotic exposures and their effects on WBC. Mendelian randomization (MR) is a useful method for examining the directions of genetically-predicted relationships between schizophrenia and WBC. METHODS We performed a two-sample MR using summary statistics from genome-wide association studies (GWAS) conducted by the Psychiatric Genomics Consortium Schizophrenia Workgroup (N = 130,644) and the Blood Cell Consortium (N = 563,946). The MR methods included inverse variance weighted (IVW), MR Egger, weighted median, MR-PRESSO, contamination mixture, and a novel approach called mixture model reciprocal causal inference (MRCI). False discovery rate was employed to correct for multiple testing. RESULTS Multiple MR methods supported bidirectional genetically-predicted relationships between lymphocyte count and schizophrenia: IVW (b = 0.026; FDR p-value = 0.008), MR Egger (b = 0.026; FDR p-value = 0.008), weighted median (b = 0.013; FDR p-value = 0.049), and MR-PRESSO (b = 0.014; FDR p-value = 0.010) in the forward direction, and IVW (OR = 1.100; FDR p-value = 0.021), MR Egger (OR = 1.231; FDR p-value < 0.001), weighted median (OR = 1.136; FDR p-value = 0.006) and MRCI (OR = 1.260; FDR p-value = 0.026) in the reverse direction. MR Egger (OR = 1.171; FDR p-value < 0.001) and MRCI (OR = 1.154; FDR p-value = 0.026) both suggested genetically-predicted eosinophil count is associated with schizophrenia, but MR Egger (b = 0.060; FDR p-value = 0.010) and contamination mixture (b = -0.013; FDR p-value = 0.045) gave ambiguous results on whether genetically predicted liability to schizophrenia would be associated with eosinophil count. MR Egger (b = 0.044; FDR p-value = 0.010) and MR-PRESSO (b = 0.009; FDR p-value = 0.045) supported genetically predicted liability to schizophrenia is associated with elevated monocyte count, and the opposite direction was also indicated by MR Egger (OR = 1.231; FDR p-value = 0.045). Lastly, unidirectional genetic liability from schizophrenia to neutrophil count were proposed by MR-PRESSO (b = 0.011; FDR p-value = 0.028) and contamination mixture (b = 0.011; FDR p-value = 0.045) method. CONCLUSION This MR study utilised multiple MR methods to obtain results suggesting bidirectional genetic genetically-predicted relationships for elevated lymphocyte counts and schizophrenia risk. In addition, moderate evidence also showed bidirectional genetically-predicted relationships between schizophrenia and monocyte counts, and unidirectional effect from genetic liability for eosinophil count to schizophrenia and from genetic liability for schizophrenia to neutrophil count. The influence of schizophrenia to eosinophil count is less certain. Our findings support the role of WBC in schizophrenia and concur with the hypothesis of neuroinflammation in schizophrenia.
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Affiliation(s)
- Perry B M Leung
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Zipeng Liu
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Guangzhou Women and Children's Medical Center, Guangdong Provincial Clinical Research Centre for Child Health, Guangzhou, China
| | - Yuanxin Zhong
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Justin D Tubbs
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Marta Di Forti
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Hon-Cheong So
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region; Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region.
| | - Pak C Sham
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region.
| | - Simon S Y Lui
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
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Llorca-Bofí V, Madero S, Amoretti S, Cuesta MJ, Moreno C, González-Pinto A, Bergé D, Rodriguez-Jimenez R, Roldán A, García-León MÁ, Ibáñez A, Usall J, Contreras F, Mezquida G, García-Rizo C, Berrocoso E, Bernardo M, Bioque M. Inflammatory blood cells and ratios at remission for psychosis relapse prediction: A three-year follow-up of a cohort of first episodes of schizophrenia. Schizophr Res 2024; 267:24-31. [PMID: 38513331 DOI: 10.1016/j.schres.2024.03.011] [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: 03/15/2023] [Revised: 02/19/2024] [Accepted: 03/14/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND The clinical course following a first episode of schizophrenia (FES) is often characterized by recurrent relapses, resulting in unfavorable clinical and functional outcomes. Inflammatory dysregulation has been implicated in relapse risk; however, the predictive value of inflammatory blood cells in clinically remitted patients after a FES has not been previously explored. METHODS In this study, we closely monitored 111 patients in remission after a FES until relapse or a three-year follow-up endpoint. The participants were recruited from the multicenter 2EPS Project. Data on inflammatory blood cells and ratios were collected at baseline and at the time of relapse or after three years of follow-up. RESULTS Monocyte counts (OR = 1.91; 95 % CI = 1.07-3.18; p = 0.009) and basophil counts (OR = 1.09; 95 % CI = 1.01-1.12; p = 0.005) at baseline were associated with an increased risk of relapse, while the platelet-lymphocyte ratio (OR = 0.98; 95 % CI = 0.97-0.99; p = 0.019) was identified as a protective factor. However, after adjusting for cannabis and tobacco use during the follow-up, only monocyte counts (OR = 1.73; 95 % CI = 1.03-2.29; p = 0.027) and basophil counts (OR = 1.08; 95 % CI = 1.01-1.14; p = 0.008) remained statistically significant. ROC curve analysis indicated that the optimal cut-off values for discriminating relapsers were 0.52 × 10^9/L (AUC: 0.66) for monocytes and 0.025 × 10^9/L (AUC: 0.75) for basophils. When considering baseline inflammatory levels, no significant differences were observed in the inflammatory biomarkers at the endpoint between relapsers and non-relapsers. CONCLUSION This study provides evidence that higher monocyte and basophil counts measured at remission after a FES are associated with an increased risk of relapse during a three-year follow-up period.
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Affiliation(s)
- Vicent Llorca-Bofí
- Department of Medicine, University of Barcelona, Barcelona, Spain; Department of Psychiatry, Santa Maria University Hospital Lleida, Lleida, Spain; Institut de Recerca Biomèdica de Lleida (IRBLleida), Lleida, Spain
| | - Santiago Madero
- Department of Medicine, University of Barcelona, Barcelona, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain.
| | - Silvia Amoretti
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute, Hospital Clínic of Barcelona, Spain; Bipolar and Depressive Disorder Unit, Neuroscience Institute, Hospital Clínic de Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) Instituto de Salud Carlos III, Spain; Group of Psychiatry, Mental Health and Addictions, Psychiatric Genetics Unit, Vall d'Hebron Research Institute (VHIR), Spain; University of Barcelona, Spain.
| | - Manuel J Cuesta
- Department of Psychiatry, Hospital Universitario de Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.
| | - Carmen Moreno
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain.
| | - Ana González-Pinto
- Bioaraba, Alava University Hospital, UPV/EHU, Vitoria, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain.
| | - Dani Bergé
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Hospital del Mar Medical Research Institute, Universitat Pompeu Fabra, Barcelona, Spain.
| | - Roberto Rodriguez-Jimenez
- Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, Spain; CIBERSAM (Biomedical Research Networking Centre in Mental Health), Spain; Universidad Complutense de Madrid (UCM), Madrid, Spain
| | - Alexandra Roldán
- Department of Psychiatry, Hospital de la Santa Creu i Sant Pau, IIB-SANT PAU, Barcelona, Spain; CIBERSAM, ISCIII, Spain.
| | - María Ángeles García-León
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.
| | - Angela Ibáñez
- Department of Psychiatry, Hospital Universitario Ramón y Cajal, IRYCIS, Universidad de Alcalá, Madrid, Spain; Centro de Investigación Biomédica en red en salud Mental (CIBERSAM), ISCIII, Madrid, Spain
| | - Judith Usall
- Research Institute Sant Joan de Déu, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Barcelona, Spain.
| | - Fernando Contreras
- Psychiatric Service, Bellvitge Universitari Hospital, IDIBELL, CIBERSAM, Spain.
| | - Gisela Mezquida
- University of Barcelona, Spain; Barcelona Clinic Schizophrenia Unit, Hospital Clínic of Barcelona, Neuroscience Institute, Spain; Institut d'Investigacions Biomèdiques, August Pi i Sunyer, Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Instituto de Salud Carlos III, Spain.
| | - Clemente García-Rizo
- Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain.
| | - Esther Berrocoso
- Neuropsychopharmacology and Psychobiology Research Group, Department of Neuroscience, University of Cádiz, Cádiz, Spain; Instituto de Investigación e Innovación Biomédica de Cádiz, INiBICA, Hospital Universitario Puerta del Mar, Cádiz, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
| | - Miquel Bernardo
- Barcelona Clinic Schizophrenia Unit, Hospital Clinic, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), CIBERSAM, ISCIII, Barcelona, Spain.
| | - Miquel Bioque
- Department of Medicine, University of Barcelona, Barcelona, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en red en salud Mental (CIBERSAM), Instituto de Salud Carlos III (ISCIII), Spain.
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