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Segura AG, Prohens L, Julià L, Amoretti S, RIbero M, Pino-Camacho L, Cano-Escalera G, Mane A, Rodriguez-Jimenez R, Roldan A, Sarró S, Ibañez A, Usall J, Lobo A, Garcia-Rizo C, Cuesta MJ, Parellada M, González-Pinto A, Berrocoso E, Bernardo M, Mas S, Rodríguez N, Perez-Ramos A, Salmeron S, González-Peñas J, Gurriarán X, Farré A, Pousa E, Zorrilla I, Mar-Barrutia L, Trabsa A, Martinez L, Sánchez-Cabezudo Á, Jiménez-López E, Pomarol-Clotet E, Salvador R, Butjosa A, Elena RA, Moreno-Izco L, Torres AMS, Saiz J, León-Quismondo L, Rivero O, González-Blanco L, De-la-Cámara C. Methylation profile scores of environmental exposures and risk of relapse after a first episode of schizophrenia. Eur Neuropsychopharmacol 2025; 94:4-15. [PMID: 39956014 DOI: 10.1016/j.euroneuro.2025.02.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2024] [Revised: 02/03/2025] [Accepted: 02/06/2025] [Indexed: 02/18/2025]
Abstract
Both genetic and environmental factors have been found to play a significant role in psychosis relapse, either independently or through their synergistic interaction. Recently, DNA methylation (DNAm) has been proposed through the calculation of methylation profile scores (MPS). The aim of the present study is to evaluate the association of MPS as a surrogate marker of the biological impact of early stressful life events (including stressful intrauterine conditions and obstetric complications, childhood adversity and toxic habits), with the risk of schizophrenia (SCZ) relapse. 91 participants from a cohort of first-episode schizophrenia (FES) patients with less than five years of evolution were classified as non-relapse (patients who had not experienced a relapse after 3 years of enrollment) or relapse (patients who relapsed during the 3-year follow-up). As inclusion criteria, patients fulfilled Andreasen's criteria of symptomatic remission. Genome-wide DNA methylation (DNAm) was profiled and fourteen MPS reflecting environmental exposure were constructed including both early stressful life events (including stressful intrauterine conditions and delivery issues, childhood adversity) and toxic habits. Increased levels of MPS reflecting gestational diabetes (p = 0.009), hypertensive disorders during pregnancy (p = 0.004), pre-eclampsia (p = 0.049), early preterm birth (p = 0.030), childhood adversity abuse (p = 0.021) and all childhood adversity (p = 0.030) were significantly associated with an increased risk of relapse. Our study suggests that changes in specific methylation patterns may represent one of the biological mechanisms linking early stressful life events to an increased risk of relapse.
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Affiliation(s)
- Alex-González Segura
- Bipolar and Depressive Disorders Unit, Hospital Clínic de Barcelona, Barcelona, Spain, Fundació Clínic-Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Llucia Prohens
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain, Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
| | - Laura Julià
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain, Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
| | - Silvia Amoretti
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain, Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain; Barcelona Clínic Schizophrenia Unit, Hospital Clínic de Barcelona, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Barcelona, Spain; Group of Psychiatry, Mental Health and Addictions, Valld'Hebron Research Institute (VHIR), Vall d'Hebron Research Institute (VHIR), Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Maria RIbero
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Psychiatry, Hospital Universitario de Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Laura Pino-Camacho
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Guillermo Cano-Escalera
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; BIOARABA, Department Psychiatry, Hospital Universitario de Alava, UPV/EHU, Vitoria, Spain
| | - Anna Mane
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Hospital del Mar Medicar Research Institute (IMIM), Barcelona, Spain
| | - Roberto Rodriguez-Jimenez
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Universidad Complutense de Madrid (UCM), Spain; Department of Psychiatry, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, Spain
| | - Alexandra Roldan
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
| | - Salvador Sarró
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
| | - Angela Ibañez
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Psychiatry, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Universidad de Alcalá, Madrid, Spain
| | - Judith Usall
- Institut de Recerca Sant Joan de Déu, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
| | - Antonio Lobo
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine and Psychiatry, Universidad de Zaragoza, Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain
| | - Clemente Garcia-Rizo
- Barcelona Clínic Schizophrenia Unit, Hospital Clínic de Barcelona, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Manuel Jesus Cuesta
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Psychiatry, Hospital Universitario de Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Mara Parellada
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Ana González-Pinto
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; BIOARABA, Department Psychiatry, Hospital Universitario de Alava, UPV/EHU, Vitoria, Spain
| | - Esther Berrocoso
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; 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
| | - Miquel Bernardo
- Barcelona Clínic Schizophrenia Unit, Hospital Clínic de Barcelona, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
| | - Sergi Mas
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain, Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
| | - Natalia Rodríguez
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain, Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Anaid Perez-Ramos
- Barcelona Clínic Schizophrenia Unit, Hospital Clínic de Barcelona, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Barcelona, Spain
| | - Sergi Salmeron
- Barcelona Clínic Schizophrenia Unit, Hospital Clínic de Barcelona, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Barcelona, Spain
| | - Javier González-Peñas
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Xaquín Gurriarán
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Adriana Farré
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
| | - Esther Pousa
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
| | - Iñaki Zorrilla
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; BIOARABA, Department Psychiatry, Hospital Universitario de Alava, UPV/EHU, Vitoria, Spain
| | - Lorea Mar-Barrutia
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; BIOARABA, Department Psychiatry, Hospital Universitario de Alava, UPV/EHU, Vitoria, Spain
| | - Amira Trabsa
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Hospital del Mar Medicar Research Institute (IMIM), Barcelona, Spain
| | - Laura Martinez
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Hospital del Mar Medicar Research Institute (IMIM), Barcelona, Spain
| | - Ángeles Sánchez-Cabezudo
- Department of Psychiatry, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, Spain
| | - Estela Jiménez-López
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Health and Social Research Center, Universidad de Castilla-La Mancha, Cuenca, Spain
| | - Edith Pomarol-Clotet
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
| | - Raymond Salvador
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
| | - Anna Butjosa
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Institut de Recerca Sant Joan de Déu, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
| | - Rubio-Abadal Elena
- Institut de Recerca Sant Joan de Déu, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
| | - Lucía Moreno-Izco
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Psychiatry, Hospital Universitario de Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Ana M Sánchez Torres
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Psychiatry, Hospital Universitario de Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Jeronimo Saiz
- Department of Psychiatry, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Universidad de Alcalá, Madrid, Spain
| | - Leticia León-Quismondo
- Department of Psychiatry, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Universidad de Alcalá, Madrid, Spain
| | - Olga Rivero
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; INCLIVA Biomedical Research Institute, Fundación Investigación Hospital Clínico de Valencia, Valencia, Spain
| | - Leticia González-Blanco
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Psychiatry, University of Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Instituto de Neurociencias del Principado de Asturias (INEUROPA), Mental Health Services of the Principality of Asturias (SESPA), Oviedo, Spain
| | - Concepción De-la-Cámara
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine and Psychiatry, Universidad de Zaragoza, Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain; Hospital Clínico Universitario and Instituto de Investigación Sanitaria (IIS) Aragón, Zaragoza
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Bouter DC, Ravensbergen SJ, de Neve-Enthoven NGM, Ercan S, Bakker B, de Jong MH, Hoogendijk WJG, Grootendorst-van Mil NH. Combining the Risk: The Poly-Environmental Risk Score and Psychotic Symptoms in Adolescents. Schizophr Bull 2025:sbaf046. [PMID: 40227146 DOI: 10.1093/schbul/sbaf046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/15/2025]
Abstract
BACKGROUND AND HYPOTHESIS Psychotic symptoms are common in adolescents and predictive of psychiatric disorders. Numerous risk factors have been shown to precede psychiatric disorders. However, investigating individual risk factors does not account for the cumulative effect these risk factors may have. Therefore, we combined well-researched environmental risk factors for psychotic disorder in a composite measure: the poly-environmental risk score (PERS). STUDY DESIGN Risk factors were assessed in a cohort of 801 adolescents (aged 15) at risk for psychopathology. Binarized risk factors included winter birth, low gestational age, low birth weight, ethnic minority status, urban living environment, cannabis use, victim of bullying, emotional abuse, physical abuse, sexual abuse, high paternal age, parental severe mental illness, parental divorce, and parental death. The PERS was weighted with the log odds derived from recent meta-analyses. At age 18, self-reported psychotic experiences (PE) and clinician-rated psychotic symptoms (PS) were assessed. This updated PERS was compared to previous PERS models, which included fewer risk factors and different weightings. STUDY RESULTS The PERS was associated with PE and PS. Specifically, a PERS between 3 and 4, and PERS > 4 corresponded with a 2.2- and 5.2-fold increase in the odds of psychotic symptoms in late adolescence. The updated 14-item PERS performed better compared to previous compositions of the PERS. CONCLUSIONS A composite score of childhood and adolescent risk factors measured at age 15 was associated with psychotic symptoms at age 18. Future research should consider the cumulative effect of risk factors when examining the determinants of psychopathology.
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Affiliation(s)
- Diandra C Bouter
- Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Susan J Ravensbergen
- Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Nita G M de Neve-Enthoven
- Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Sibel Ercan
- Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Benno Bakker
- Epidemiological and Social Psychiatric Research Institute (ESPRi), Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
- Parnassia Psychiatric Institute, 3009 AM, Rotterdam, The Netherlands
| | - Mark H de Jong
- Epidemiological and Social Psychiatric Research Institute (ESPRi), Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
- Yulius Mental Health, 3300 BA, Dordrecht, The Netherlands
| | - Witte J G Hoogendijk
- Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Nina H Grootendorst-van Mil
- Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
- Epidemiological and Social Psychiatric Research Institute (ESPRi), Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
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Petit P, Vuillerme N. Global research trends on the human exposome: a bibliometric analysis (2005-2024). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2025; 32:7808-7833. [PMID: 40056347 PMCID: PMC11953191 DOI: 10.1007/s11356-025-36197-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/24/2025] [Indexed: 03/10/2025]
Abstract
Exposome represents one of the most pressing issues in the environmental science research field. However, a comprehensive summary of worldwide human exposome research is lacking. We aimed to explore the bibliometric characteristics of scientific publications on the human exposome. A bibliometric analysis of human exposome publications from 2005 to December 2024 was conducted using the Web of Science in accordance with PRISMA guidelines. Trends/hotspots were investigated with keyword frequency, co-occurrence, and thematic map. Sex disparities in terms of publications and citations were examined. From 2005 to 2024, 931 publications were published in 363 journals and written by 4529 authors from 72 countries. The number of publications tripled during the last 5 years. Publications written by females (51% as first authors and 34% as last authors) were cited fewer times (13,674) than publications written by males (22,361). Human exposome studies mainly focused on air pollution, metabolomics, chemicals (e.g., per- and polyfluoroalkyl substances (PFAS), endocrine-disrupting chemicals, pesticides), early-life exposure, biomarkers, microbiome, omics, cancer, and reproductive disorders. Social and built environment factors, occupational exposure, multi-exposure, digital exposure (e.g., screen use), climate change, and late-life exposure received less attention. Our results uncovered high-impact countries, institutions, journals, references, authors, and key human exposome research trends/hotspots. The use of digital exposome technologies (e.g., sensors, and wearables) and data science (e.g., artificial intelligence) has blossomed to overcome challenges and could provide valuable knowledge toward precision prevention. Exposome risk scores represent a promising research avenue.
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Affiliation(s)
- Pascal Petit
- AGEIS, Université Grenoble Alpes, 38000, Grenoble, France.
- Laboratoire AGEIS, Université Grenoble Alpes, Bureau 315, Bâtiment Jean Roget, UFR de Médecine, Domaine de La Merci, 38706, La Tronche Cedex, France.
| | - Nicolas Vuillerme
- AGEIS, Université Grenoble Alpes, 38000, Grenoble, France
- Institut Universitaire de France, Paris, France
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Chen Y, Yuan Q, Dimitrov L, Risk B, Ku B, Huels A. Interaction between Neighborhood Exposome and Genetic Risk in Child Psychotic-like Experiences. RESEARCH SQUARE 2025:rs.3.rs-5830171. [PMID: 40034438 PMCID: PMC11875302 DOI: 10.21203/rs.3.rs-5830171/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/05/2025]
Abstract
Persistent distressing psychotic-like experiences (PLE) among children may be driven by genetics and neighborhood environmental exposures. However, the gene-environment interaction to persistent distressing PLE is unknown. The study included 6,449 participants from the Adolescent Brain and Cognitive Development Study. Genetic risk was measured by a multi-ancestry schizophrenia polygenic risk score (SCZ-PRS). Multi-dimensional neighborhood-level exposures were used to form a neighborhood exposome (NE) score. SCZ-PRS was not statistically significantly associated with odds of persistent distressing PLE (OR = 1.04, 95% CI: 0.97, 1.13, P = 0.280), whereas NE score was (OR = 1.15, 95% CI: 1.05, 1.26, P = 0.003). The association between NE score and persistent distressing PLE was statistically significantly attenuated as SCZ-PRS increased (OR for interaction = 0.92, 95% CI: 0.86, 1.00, P = 0.039). The findings indicate that persistent distressing PLE may be driven by detrimental neighborhood exposures, particularly among children with low genetic risks.
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Affiliation(s)
- Yinxian Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Qingyue Yuan
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Lina Dimitrov
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Benjamin Risk
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Benson Ku
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Anke Huels
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
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Arias-Magnasco A, Lin BD, Pries LK, Guloksuz S. Mapping the exposome of mental health: exposome-wide association study of mental health outcomes among UK Biobank participants. Psychol Med 2025; 55:e16. [PMID: 39917825 PMCID: PMC11968124 DOI: 10.1017/s0033291724003015] [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: 09/15/2024] [Revised: 10/28/2024] [Accepted: 10/30/2024] [Indexed: 04/05/2025]
Abstract
BACKGROUND Dissecting the exposome linked to mental health outcomes can help identify potentially modifiable targets to improve mental well-being. However, the multiplicity of exposures and the complexity of mental health phenotypes pose a challenge that requires data-driven approaches. METHODS Guided by our previous systematic approach, we conducted hypothesis-free exposome-wide analyses to identify factors associated with 7 psychiatric diagnostic domains and 19 symptom dimensions in 157,298 participants from the UK Biobank Mental Health Survey. After quality control, 294 environmental, lifestyle, behavioral, and economic variables were included. An Exposome-Wide Association Study was conducted per outcome in two equally split datasets. Variables associated with each outcome were then tested in a multivariable model. RESULTS Across all diagnostic domains and symptom dimensions, the top three exposures were childhood adversities and traumatic events. Cannabis use was associated with common psychiatric disorders (depressive, anxiety, psychotic, and bipolar manic disorders), with ORs ranging from 1.10 to 1.79 in the multivariable models. Additionally, differential associations were identified between specific outcomes-such as neurodevelopmental disorders, eating disorders, and self-harm behaviors-and exposures, including early life experiences (being adopted), lifestyle (time spent using computers), and dietary habits (vegetarian diet). CONCLUSIONS This comprehensive mapping of the exposome revealed that several factors, particularly in the domains of those previously well-studied were shared across mental health phenotypes, providing further support for transdiagnostic pathoetiology. Our findings also showed that distinct relations might exist. Continued exposome research through multimodal mechanistic studies guided by the transdiagnostic mental health framework is required to better inform public health policies.
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Affiliation(s)
- Angelo Arias-Magnasco
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Bochao Danae Lin
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Lotta-Katrin Pries
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
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Wang Z, Drouard G, Whipp AM, Heinonen-Guzejev M, Bolte G, Kaprio J. Association between trajectories of the neighborhood social exposome and mental health in late adolescence: A FinnTwin12 cohort study. J Affect Disord 2024; 358:70-78. [PMID: 38697223 DOI: 10.1016/j.jad.2024.04.096] [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: 10/18/2023] [Revised: 04/14/2024] [Accepted: 04/21/2024] [Indexed: 05/04/2024]
Abstract
BACKGROUND Adolescent mental health problems impose a significant burden. Exploring evolving social environments could enhance comprehension of their impact on mental health. We aimed to depict the trajectories of the neighborhood social exposome from middle to late adolescence and assess the intricate relationship between them and late adolescent mental health. METHODS Participants (n = 3965) from the FinnTwin12 cohort with completed questionnaires at age 17 were used. Nine mental health measures were assessed. The social exposome comprised 28 neighborhood social indicators. Trajectories of these indicators from ages 12 to 17 were summarized via latent growth curve modeling into growth factors, including baseline intercept. Mixture effects of all growth factors were assessed through quantile-based g-computation. Repeated generalized linear regressions identified significant growth factors. Sex stratification was performed. RESULTS The linear-quadratic model was the most optimal trajectory model. No mixture effect was detected. Regression models showed some growth factors saliently linked to the p-factor, internalizing problems, anxiety, hyperactivity, and aggression. The majority of them were baseline intercepts. Quadratic growth factors about mother tongues correlated with anxiety among sex-combined participants and males. The linear growth factor in the proportion of households of couples without children was associated with internalizing problems in females. LIMITATIONS We were limited to including only neighborhood-level social exposures, and the multilevel contextual exposome situation interfered with our assessment. CONCLUSIONS Trajectories of the social neighborhood exposome modestly influenced late adolescent mental health. Tackling root causes of social inequalities through targeted programs for living conditions could improve adolescent mental health.
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Affiliation(s)
- Zhiyang Wang
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Gabin Drouard
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Alyce M Whipp
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | | | - Gabriele Bolte
- Department of Social Epidemiology, Institute of Public Health and Nursing Research, University of Bremen, Bremen, Germany
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Department of Public Health, Clinicum, University of Helsinki, Helsinki, Finland.
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7
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Guo J, Garshick E, Si F, Tang Z, Lian X, Wang Y, Li J, Koutrakis P. Environmental Toxicant Exposure and Depressive Symptoms. JAMA Netw Open 2024; 7:e2420259. [PMID: 38958973 PMCID: PMC11222999 DOI: 10.1001/jamanetworkopen.2024.20259] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 05/03/2024] [Indexed: 07/04/2024] Open
Abstract
Importance Recognizing associations between exposure to common environmental toxicants and mental disorders such as depression is crucial for guiding targeted mechanism research and the initiation of disease prevention efforts. Objectives To comprehensively screen and assess the associations between potential environmental toxicants and depressive symptoms and to assess whether systemic inflammation serves as a mediator. Design, Setting, and Participants A total of 3427 participants from the 2013-2014 and 2015-2016 waves of the National Health and Nutrition Examination and Survey who had information on blood or urine concentrations of environmental toxicants and depression scores assessed by the 9-item Patient Health Questionnaire (PHQ-9) were included. Statistical analysis was performed from July 1, 2023, to January 31, 2024. Exposures Sixty-two toxicants in 10 categories included acrylamide, arsenic, ethylene oxide, formaldehyde, iodine, metals, nicotine metabolites, polycyclic aromatic hydrocarbons, volatile organic compound (VOC) metabolites; and perchlorate, nitrate, and thiocyanate. Main Outcomes and Measures An exposome-wide association study and the deletion-substitution-addition algorithm were used to assess associations with depression scores (PHQ-9 ≥5) adjusted for other important covariates. A mediation analysis framework was used to evaluate the mediating role of systemic inflammation assessed by the peripheral white blood cell count. Results Among the 3427 adults included, 1735 (50.6%) were women, 2683 (78.3%) were younger than 65 years, and 744 (21.7%) were 65 years or older, with 839 (24.5%) having depressive symptoms. In terms of race and ethnicity, 570 participants (16.6%) were Mexican American, 679 (19.8%) were non-Hispanic Black, and 1314 (38.3%) were non-Hispanic White. We identified associations between 27 chemical compounds or metals in 6 of 10 categories of environmental toxicants and the prevalence of depressive symptoms, including the VOC metabolites N-acetyl-S-(2-hydroxy-3-butenyl)-l-cysteine (odds ratio [OR], 1.74 [95% CI, 1.38, 2.18]) and total nicotine equivalent-2 (OR, 1.42 [95% CI, 1.26-1.59]). Men and younger individuals appear more vulnerable to environmental toxicants than women and older individuals. Peripheral white blood cell count mediated 5% to 19% of the associations. Conclusions and Relevance In this representative cross-sectional study of adults with environmental toxicant exposures, 6 categories of environmental toxicants were associated with depressive symptoms with mediation by systemic inflammation. This research provides insight into selecting environmental targets for mechanistic research into the causes of depression and facilitating efforts to reduce environmental exposures.
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Affiliation(s)
- Jianhui Guo
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Eric Garshick
- Pulmonary, Allergy, Sleep, and Critical Care Medicine Section, Medical Service, Veterans Affairs Boston Healthcare System and Harvard Medical School, Boston, Massachusetts
| | - Feifei Si
- Peking University Sixth Hospital Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Ziqi Tang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Xinyao Lian
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Yaqi Wang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Jing Li
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Petros Koutrakis
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
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8
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Cuesta MJ, García de Jalón E, Sánchez-Torres AM, Gil-Berrozpe GJ, Aranguren L, Gutierrez G, Corrales A, Zarzuela A, Ibañez B, Peralta V. Additive effects of a family history of schizophrenia spectrum disorders and an environmental risk score for the outcome of patients with non-affective first-episode psychosis. Psychol Med 2024; 54:2435-2443. [PMID: 38505954 DOI: 10.1017/s0033291724000576] [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] [Indexed: 03/21/2024]
Abstract
BACKGROUND First-episode psychotic disorders comprise a heterogeneous phenotype with a complex etiology involving numerous common small-effect genetic variations and a wide range of environmental exposures. We examined whether a family of schizophrenia spectrum disorder (FH-Sz) interacts with an environmental risk score (ERS-Sz) regarding the outcome of patients with non-affective first episode psychosis (NAFEP). METHODS We included 288 patients with NAFEP who were evaluated after discharge from an intensive 2-year program. We evaluated three outcome measures: symptomatic remission, psychosocial functioning, and personal recovery. We analyzed the main and joint associations of a FH-Sz and the ERS-Sz on the outcomes by using the relative excess risk due to interaction (RERI) approach. RESULTS A FH-Sz showed a significant association with poor symptomatic remission and psychosocial functioning outcomes, although there was no significant interaction between a FH-Sz and the ERS-Sz on these outcomes. The ERS-Sz did not show a significant association with poor symptomatic remission and psychosocial functioning outcomes, even though the magnitude of the interaction between ERS-Sz and FH-Sz with the later outcome was moderate (RERI = 6.89, 95% confidence interval -16.03 to 29.81). There was no association between a FH-Sz and the ERS-Sz and personal recovery. CONCLUSIONS Our results provide further empirical support regarding the contribution of FH-Sz to poor symptomatic remission and poor psychosocial functioning outcomes in patients with NAFEP.
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Affiliation(s)
- Manuel J Cuesta
- Department of Psychiatry, Hospital Universitario de Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Elena García de Jalón
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud - Osasunbidea, Pamplona, Spain
| | - Ana M Sánchez-Torres
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Departament of Health Sciences, Universidad Pública de Navarra (UPNA), Pamplona, Spain
| | - Gustavo J Gil-Berrozpe
- Department of Psychiatry, Hospital Universitario de Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Lidia Aranguren
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud - Osasunbidea, Pamplona, Spain
| | - Gerardo Gutierrez
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud - Osasunbidea, Pamplona, Spain
| | - Asier Corrales
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud - Osasunbidea, Pamplona, Spain
| | - Amalia Zarzuela
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud - Osasunbidea, Pamplona, Spain
| | - Berta Ibañez
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Methodology Unit, Navarrabiomed - HUN - UPNA, RICAPPS, Pamplona, Spain
| | - Víctor Peralta
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud - Osasunbidea, Pamplona, Spain
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9
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Pagliaccio D, Tran KT, Visoki E, DiDomenico GE, Auerbach RP, Barzilay R. Probing the digital exposome: associations of social media use patterns with youth mental health. NPP - DIGITAL PSYCHIATRY AND NEUROSCIENCE 2024; 2:5. [PMID: 39464493 PMCID: PMC11504934 DOI: 10.1038/s44277-024-00006-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/07/2024] [Accepted: 03/22/2024] [Indexed: 10/29/2024]
Abstract
Recently, the U.S. Surgeon General issued an advisory highlighting the lack of knowledge about the safety of ubiquitous social media use on adolescent mental health. For many youths, social media use can become excessive and can contribute to frequent exposure to adverse peer interactions (e.g., cyberbullying, and hate speech). Nonetheless, social media use is complex, and although there are clear challenges, it also can create critical new avenues for connection, particularly among marginalized youth. In the current project, we leverage a large nationally diverse sample of adolescents from the Adolescent Brain Cognitive Development (ABCD) Study assessed between 2019-2020 (N = 10,147, M age = 12.0, 48% assigned female at birth, 20% Black, 20% Hispanic) to test the associations between specific facets of adolescent social media use (e.g., type of apps used, time spent, addictive patterns of use) and overall mental health. Specifically, a data-driven exposome-wide association was applied to generate digital exposomic risk scores that aggregate the cumulative burden of digital risk exposure. This included general usage, cyberbullying, having secret accounts, problematic/addictive use behavior, and other factors. In validation models, digital exposomic risk explained substantial variance in general child-reported psychopathology, and a history of suicide attempt, over and above sociodemographics, non-social screentime, and non-digital adversity (e.g., abuse, poverty). Furthermore, differences in digital exposomic scores also shed insight into mental health disparities, among youth of color and sexual and gender minority youth. Our work using a data-driven approach supports the notion that digital exposures, in particular social media use, contribute to the mental health burden of US adolescents.
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Affiliation(s)
- David Pagliaccio
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Kate T. Tran
- Lifespan Brain Institute of the Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Children’s Hospital of Philadelphia, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Philadelphia, PA, USA
| | - Elina Visoki
- Lifespan Brain Institute of the Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Children’s Hospital of Philadelphia, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Philadelphia, PA, USA
| | - Grace E. DiDomenico
- Lifespan Brain Institute of the Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Children’s Hospital of Philadelphia, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Philadelphia, PA, USA
| | - Randy P. Auerbach
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Ran Barzilay
- Lifespan Brain Institute of the Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Children’s Hospital of Philadelphia, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Philadelphia, PA, USA
- University of Pennsylvania Perelman School of Medicine, Department of Psychiatry, Philadelphia, PA, USA
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10
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Keller AS, Moore TM, Luo A, Visoki E, Gataviņš MM, Shetty A, Cui Z, Fan Y, Feczko E, Houghton A, Li H, Mackey AP, Miranda-Dominguez O, Pines A, Shinohara RT, Sun KY, Fair DA, Satterthwaite TD, Barzilay R. A general exposome factor explains individual differences in functional brain network topography and cognition in youth. Dev Cogn Neurosci 2024; 66:101370. [PMID: 38583301 PMCID: PMC11004064 DOI: 10.1016/j.dcn.2024.101370] [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: 01/16/2024] [Revised: 03/19/2024] [Accepted: 03/26/2024] [Indexed: 04/09/2024] Open
Abstract
Childhood environments are critical in shaping cognitive neurodevelopment. With the increasing availability of large-scale neuroimaging datasets with deep phenotyping of childhood environments, we can now build upon prior studies that have considered relationships between one or a handful of environmental and neuroimaging features at a time. Here, we characterize the combined effects of hundreds of inter-connected and co-occurring features of a child's environment ("exposome") and investigate associations with each child's unique, multidimensional pattern of functional brain network organization ("functional topography") and cognition. We apply data-driven computational models to measure the exposome and define personalized functional brain networks in pre-registered analyses. Across matched discovery (n=5139, 48.5% female) and replication (n=5137, 47.1% female) samples from the Adolescent Brain Cognitive Development study, the exposome was associated with current (ages 9-10) and future (ages 11-12) cognition. Changes in the exposome were also associated with changes in cognition after accounting for baseline scores. Cross-validated ridge regressions revealed that the exposome is reflected in functional topography and can predict performance across cognitive domains. Importantly, a single measure capturing a child's exposome could more accurately and parsimoniously predict cognition than a wealth of personalized neuroimaging data, highlighting the importance of children's complex, multidimensional environments in cognitive neurodevelopment.
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Affiliation(s)
- Arielle S Keller
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Tyler M Moore
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Audrey Luo
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Elina Visoki
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Mārtiņš M Gataviņš
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alisha Shetty
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Yong Fan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Audrey Houghton
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Hongming Li
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Adam Pines
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Kevin Y Sun
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Ran Barzilay
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
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11
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Cuesta MJ, Gil-Berrozpe GJ, Sánchez-Torres AM, Moreno-Izco L, García de Jalón E, Peralta V. 20-Year trajectories of six psychopathological dimensions in patients with first-episode psychosis: Could they be predicted? Psychiatry Res 2024; 331:115614. [PMID: 38039651 DOI: 10.1016/j.psychres.2023.115614] [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: 08/01/2023] [Revised: 11/14/2023] [Accepted: 11/17/2023] [Indexed: 12/03/2023]
Abstract
Patients with first-episode psychoses (FEP) exhibit heterogeneity in clinical manifestations and outcomes. This study investigated the long-term trajectories of six key psychopathological dimensions (reality-distortion, negative, disorganization, catatonia, mania and depression) in patients diagnosed with FEP. A total of 243 patients were followed up for 20 years and the trajectories of the dimensions were analysed using growth mixture modelling. These dimensions showed varied course patterns, ranging from two to five trajectories. Additionally, the study examined the predictive value of different factors in differentiating between the long-term trajectories. The exposome risk score showed that familial load, distal and intermediate risk factors, acute psychosocial stressors and acute onset were significant predictors for differentiating between long-term psychopathological trajectories. In contrast, polygenic risk score, duration of untreated psychosis and duration of untreated illness demonstrated little or no predictive value. The findings highlight the importance of conducting a multidimensional assessment not only at FEP but also during follow-up to customize the effectiveness of interventions. Furthermore, the results emphasize the relevance of assessing premorbid predictors from the onset of illness. This may enable the identification of FEP patients at high-risk of poor long-term outcomes who would benefit from targeted prevention programs on specific psychopathological dimensions.
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Affiliation(s)
- Manuel J Cuesta
- Department of Psychiatry, Complejo Hospitalario de Navarra (Pamplona, Spain); Navarra Institute for Health Research (IdiSNA) (Pamplona, Spain).
| | - Gustavo J Gil-Berrozpe
- Department of Psychiatry, Complejo Hospitalario de Navarra (Pamplona, Spain); Navarra Institute for Health Research (IdiSNA) (Pamplona, Spain)
| | - Ana M Sánchez-Torres
- Navarra Institute for Health Research (IdiSNA) (Pamplona, Spain); Departament of Health Sciences, Universidad Pública de Navarra (UPNA), Pamplona, Spain
| | - Lucía Moreno-Izco
- Department of Psychiatry, Complejo Hospitalario de Navarra (Pamplona, Spain); Navarra Institute for Health Research (IdiSNA) (Pamplona, Spain)
| | - Elena García de Jalón
- Navarra Institute for Health Research (IdiSNA) (Pamplona, Spain); Mental Health Department, Servicio Navarro de Salud - Osasunbidea (Pamplona, Spain)
| | - Victor Peralta
- Navarra Institute for Health Research (IdiSNA) (Pamplona, Spain); Mental Health Department, Servicio Navarro de Salud - Osasunbidea (Pamplona, Spain)
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12
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Hoffman KW, Tran KT, Moore TM, Gataviņš MM, Visoki E, DiDomenico GE, Schultz LM, Almasy L, Hayes MR, Daskalakis NP, Barzilay R. Allostatic load in early adolescence: gene / environment contributions and relevance for mental health. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.27.23297674. [PMID: 37961462 PMCID: PMC10635214 DOI: 10.1101/2023.10.27.23297674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background Allostatic load is the cumulative "wear and tear" on the body due to chronic adversity. We aimed to test poly-environmental (exposomic) and polygenic contributions to allostatic load and their combined contribution to early adolescent mental health. Methods We analyzed data on N = 5,035 diverse youth (mean age 12) from the Adolescent Brain Cognitive Development Study (ABCD). Using dimensionality reduction method, we calculated and overall allostatic load score (AL) using body mass index [BMI], waist circumference, blood pressure, blood glycemia, blood cholesterol, and salivary DHEA. Childhood exposomic risk was quantified using multi-level environmental exposures before age 11. Genetic risk was quantified using polygenic risk scores (PRS) for metabolic system susceptibility (type 2 diabetes [T2D]) and stress-related psychiatric disease (major depressive disorder [MDD]). We used linear mixed effects models to test main, additive, and interactive effects of exposomic and polygenic risk (independent variables) on AL (dependent variable). Mediation models tested the mediating role of AL on the pathway from exposomic and polygenic risk to youth mental health. Models adjusted for demographics and genetic principal components. Results We observed disparities in AL with non-Hispanic White youth having significantly lower AL compared to Hispanic and Non-Hispanic Black youth. In the diverse sample, childhood exposomic burden was associated with AL in adolescence (beta=0.25, 95%CI 0.22-0.29, P<.001). In European ancestry participants (n=2,928), polygenic risk of both T2D and depression was associated with AL (T2D-PRS beta=0.11, 95%CI 0.07-0.14, P<.001; MDD-PRS beta=0.05, 95%CI 0.02-0.09, P=.003). Both polygenic scores showed significant interaction with exposomic risk such that, with greater polygenic risk, the association between exposome and AL was stronger. AL partly mediated the pathway to youth mental health from exposomic risk and from MDD-PRS, and fully mediated the pathway from T2D-PRS. Conclusions AL can be quantified in youth using anthropometric and biological measures and is mapped to exposomic and polygenic risk. Main and interactive environmental and genetic effects support a diathesis-stress model. Findings suggest that both environmental and genetic risk be considered when modeling stress-related health conditions.
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Affiliation(s)
- Kevin W. Hoffman
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, US
| | - Kate T. Tran
- Lifespan Brain Institute of Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, US
| | - Tyler M. Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Lifespan Brain Institute of Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, US
| | - Mārtiņš M. Gataviņš
- Lifespan Brain Institute of Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, US
| | - Elina Visoki
- Lifespan Brain Institute of Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, US
| | - Grace E. DiDomenico
- Lifespan Brain Institute of Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, US
| | - Laura M. Schultz
- Lifespan Brain Institute of Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, US
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, US
| | - Laura Almasy
- Lifespan Brain Institute of Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, US
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, US
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
| | - Matthew R. Hayes
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
| | - Nikolaos P. Daskalakis
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ran Barzilay
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, US
- Lifespan Brain Institute of Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, US
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13
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Simpson-Kent IL, Gataviņš MM, Tooley UA, Boroshok AL, McDermott CL, Park AT, Delgado Reyes L, Bathelt J, Tisdall MD, Mackey AP. Multilayer network associations between the exposome and childhood brain development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.23.563611. [PMID: 37961103 PMCID: PMC10634748 DOI: 10.1101/2023.10.23.563611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Growing up in a high poverty neighborhood is associated with elevated risk for academic challenges and health problems. Here, we take a data-driven approach to exploring how measures of children's environments relate to the development of their brain structure and function in a community sample of children between the ages of 4 and 10 years. We constructed exposomes including measures of family socioeconomic status, children's exposure to adversity, and geocoded measures of neighborhood socioeconomic status, crime, and environmental toxins. We connected the exposome to two structural measures (cortical thickness and surface area, n = 170) and two functional measures (participation coefficient and clustering coefficient, n = 130). We found dense connections within exposome and brain layers and sparse connections between exposome and brain layers. Lower family income was associated with thinner visual cortex, consistent with the theory that accelerated development is detectable in early-developing regions. Greater neighborhood incidence of high blood lead levels was associated with greater segregation of the default mode network, consistent with evidence that toxins are deposited into the brain along the midline. Our study demonstrates the utility of multilayer network analysis to bridge environmental and neural explanatory levels to better understand the complexity of child development.
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Affiliation(s)
- Ivan L. Simpson-Kent
- Institute of Psychology, Developmental and Educational Psychology Unit, Leiden University, Leiden, the Netherlands
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Mārtiņš M. Gataviņš
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ursula A. Tooley
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Washington University in St. Louis, USA
- Department of Neurology, Washington University in St. Louis, USA
| | - Austin L. Boroshok
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Anne T. Park
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Joe Bathelt
- Department of Psychology, Royal Holloway, University of London, Egham, Surrey, United Kingdom
| | - M. Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Allyson P. Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
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14
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O’Hare K, Watkeys O, Whitten T, Dean K, Laurens KR, Tzoumakis S, Harris F, Carr VJ, Green MJ. Cumulative Environmental Risk in Early Life: Associations With Schizotypy in Childhood. Schizophr Bull 2023; 49:244-254. [PMID: 36302227 PMCID: PMC10016419 DOI: 10.1093/schbul/sbac160] [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] [Indexed: 11/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Psychotic disorders are associated with a growing number of recognized environmental exposures. Cumulative exposure to multiple environmental risk factors in childhood may contribute to the development of different patterns of schizotypy evident in early life. Hypotheses were that distinct profiles of schizotypy would have differential associations with a cumulative score of environmental risk factors. STUDY DESIGN We prospectively examined the relationship between 19 environmental exposures (which had demonstrated replicated associations with psychosis) measured from the prenatal period through to age 11 years, and 3 profiles of schizotypy in children (mean age = 11.9 years, n = 20 599) that have been established in population data from the New South Wales-Child Development Study. Multinomial logistic regression was used to examine associations between membership in each of 3 schizotypy profiles (true schizotypy, introverted schizotypy, and affective schizotypy) and exposure to a range of 19 environmental risk factors for psychosis (both individually and summed as a cumulative environmental risk score [ERS]), relative to children showing no risk. RESULTS Almost all environmental factors were associated with at least 1 schizotypy profile. The cumulative ERS was most strongly associated with the true schizotypy profile (OR = 1.61, 95% CI = 1.52-1.70), followed by the affective (OR = 1.33, 95% CI = 1.28-1.38), and introverted (OR = 1.32, 95% CI = 1.28-1.37) schizotypy profiles. CONCLUSIONS Consistent with the cumulative risk hypothesis, results indicate that an increased number of risk exposures is associated with an increased likelihood of membership in the 3 schizotypy profiles identified in middle childhood, relative to children with no schizotypy profile.
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Affiliation(s)
- Kirstie O’Hare
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Oliver Watkeys
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
| | - Tyson Whitten
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- School of Social Sciences, University of Adelaide, South Australia, Australia
| | - Kimberlie Dean
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Justice Health and Forensic Mental Health Network, Sydney, New South Wales, Australia
| | - Kristin R Laurens
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Queensland University of Technology (QUT), School of Psychology and Counselling, Brisbane, Australia
| | - Stacy Tzoumakis
- School of Criminology and Criminal Justice, Griffith University, Southport, Australia
- Griffith Criminology Institute, Griffith University, Southport, Australia
| | - Felicity Harris
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Vaughan J Carr
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
- Department of Psychiatry, Monash University, Melbourne, Australia
| | - Melissa J Green
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
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15
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Gómez-Carrillo A, Paquin V, Dumas G, Kirmayer LJ. Restoring the missing person to personalized medicine and precision psychiatry. Front Neurosci 2023; 17:1041433. [PMID: 36845417 PMCID: PMC9947537 DOI: 10.3389/fnins.2023.1041433] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Accepted: 01/09/2023] [Indexed: 02/11/2023] Open
Abstract
Precision psychiatry has emerged as part of the shift to personalized medicine and builds on frameworks such as the U.S. National Institute of Mental Health Research Domain Criteria (RDoC), multilevel biological "omics" data and, most recently, computational psychiatry. The shift is prompted by the realization that a one-size-fits all approach is inadequate to guide clinical care because people differ in ways that are not captured by broad diagnostic categories. One of the first steps in developing this personalized approach to treatment was the use of genetic markers to guide pharmacotherapeutics based on predictions of pharmacological response or non-response, and the potential risk of adverse drug reactions. Advances in technology have made a greater degree of specificity or precision potentially more attainable. To date, however, the search for precision has largely focused on biological parameters. Psychiatric disorders involve multi-level dynamics that require measures of phenomenological, psychological, behavioral, social structural, and cultural dimensions. This points to the need to develop more fine-grained analyses of experience, self-construal, illness narratives, interpersonal interactional dynamics, and social contexts and determinants of health. In this paper, we review the limitations of precision psychiatry arguing that it cannot reach its goal if it does not include core elements of the processes that give rise to psychopathological states, which include the agency and experience of the person. Drawing from contemporary systems biology, social epidemiology, developmental psychology, and cognitive science, we propose a cultural-ecosocial approach to integrating precision psychiatry with person-centered care.
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Affiliation(s)
- Ana Gómez-Carrillo
- Culture, Mind, and Brain Program, Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, QC, Canada
- Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
| | - Vincent Paquin
- Culture, Mind, and Brain Program, Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Guillaume Dumas
- Culture, Mind, and Brain Program, Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, QC, Canada
- Precision Psychiatry and Social Physiology Laboratory at the CHU Sainte-Justine Research Center, Université de Montréal, Montreal, QC, Canada
- Mila-Quebec Artificial Intelligence Institute, Montreal, QC, Canada
| | - Laurence J Kirmayer
- Culture, Mind, and Brain Program, Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, QC, Canada
- Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
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16
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Bel-Bahar TS, Khan AA, Shaik RB, Parvaz MA. A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment. Front Hum Neurosci 2022; 16:995534. [PMID: 36325430 PMCID: PMC9619053 DOI: 10.3389/fnhum.2022.995534] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 09/20/2022] [Indexed: 11/24/2022] Open
Abstract
Substance use disorders (SUDs) constitute a growing global health crisis, yet many limitations and challenges exist in SUD treatment research, including the lack of objective brain-based markers for tracking treatment outcomes. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity, and although much is known about EEG activity in acute and chronic substance use, knowledge regarding EEG in relation to abstinence and treatment outcomes is sparse. We performed a scoping review of longitudinal and pre-post treatment EEG studies that explored putative changes in brain function associated with abstinence and/or treatment in individuals with SUD. Following PRISMA guidelines, we identified studies published between January 2000 and March 2022 from online databases. Search keywords included EEG, addictive substances (e.g., alcohol, cocaine, methamphetamine), and treatment related terms (e.g., abstinence, relapse). Selected studies used EEG at least at one time point as a predictor of abstinence or other treatment-related outcomes; or examined pre- vs. post-SUD intervention (brain stimulation, pharmacological, behavioral) EEG effects. Studies were also rated on the risk of bias and quality using validated instruments. Forty-four studies met the inclusion criteria. More consistent findings included lower oddball P3 and higher resting beta at baseline predicting negative outcomes, and abstinence-mediated longitudinal decrease in cue-elicited P3 amplitude and resting beta power. Other findings included abstinence or treatment-related changes in late positive potential (LPP) and N2 amplitudes, as well as in delta and theta power. Existing studies were heterogeneous and limited in terms of specific substances of interest, brief times for follow-ups, and inconsistent or sparse results. Encouragingly, in this limited but maturing literature, many studies demonstrated partial associations of EEG markers with abstinence, treatment outcomes, or pre-post treatment-effects. Studies were generally of good quality in terms of risk of bias. More EEG studies are warranted to better understand abstinence- or treatment-mediated neural changes or to predict SUD treatment outcomes. Future research can benefit from prospective large-sample cohorts and the use of standardized methods such as task batteries. EEG markers elucidating the temporal dynamics of changes in brain function related to abstinence and/or treatment may enable evidence-based planning for more effective and targeted treatments, potentially pre-empting relapse or minimizing negative lifespan effects of SUD.
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Affiliation(s)
- Tarik S. Bel-Bahar
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Anam A. Khan
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Riaz B. Shaik
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Muhammad A. Parvaz
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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17
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Moore TM, Visoki E, Argabright ST, Didomenico GE, Sotelo I, Wortzel JD, Naeem A, Gur RC, Gur RE, Warrier V, Guloksuz S, Barzilay R. Modeling environment through a general exposome factor in two independent adolescent cohorts. EXPOSOME 2022; 2:osac010. [PMID: 36606125 PMCID: PMC9798749 DOI: 10.1093/exposome/osac010] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 11/15/2022] [Accepted: 12/05/2022] [Indexed: 12/15/2022]
Abstract
Exposures to perinatal, familial, social, and physical environmental stimuli can have substantial effects on human development. We aimed to generate a single measure that capture's the complex network structure of the environment (ie, exposome) using multi-level data (participant's report, parent report, and geocoded measures) of environmental exposures (primarily from the psychosocial environment) in two independent adolescent cohorts: The Adolescent Brain Cognitive Development Study (ABCD Study, N = 11 235; mean age, 10.9 years; 47.7% females) and an age- and sex-matched sample from the Philadelphia Neurodevelopmental Cohort (PNC, N = 4993). We conducted a series of data-driven iterative factor analyses and bifactor modeling in the ABCD Study, reducing dimensionality from 348 variables tapping to environment to six orthogonal exposome subfactors and a general (adverse) exposome factor. The general exposome factor was associated with overall psychopathology (B = 0.28, 95% CI, 0.26-0.3) and key health-related outcomes: obesity (odds ratio [OR] , 1.4; 95% CI, 1.3-1.5) and advanced pubertal development (OR, 1.3; 95% CI, 1.2-1.5). A similar approach in PNC reduced dimensionality of environment from 29 variables to 4 exposome subfactors and a general exposome factor. PNC analyses yielded consistent associations of the general exposome factor with psychopathology (B = 0.15; 95% CI, 0.13-0.17), obesity (OR, 1.4; 95% CI, 1.3-1.6), and advanced pubertal development (OR, 1.3; 95% CI, 1-1.6). In both cohorts, inclusion of exposome factors greatly increased variance explained in overall psychopathology compared with models relying solely on demographics and parental education (from <4% to >38% in ABCD; from <4% to >18.5% in PNC). Findings suggest that a general exposome factor capturing multi-level environmental exposures can be derived and can consistently explain variance in youth's mental and general health.
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Affiliation(s)
- Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Elina Visoki
- Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Stirling T Argabright
- Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Grace E Didomenico
- Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Ingrid Sotelo
- Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Jeremy D Wortzel
- Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Areebah Naeem
- Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA
| | - Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Sinan Guloksuz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Ran Barzilay
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Lifespan Brain Institute of the Children's Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, PA, USA.,Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia (CHOP), Philadelphia, PA, USA
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