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Baltira C, Aronica E, Elmquist WF, Langer O, Löscher W, Sarkaria JN, Wesseling P, de Gooijer MC, van Tellingen O. The impact of ATP-binding cassette transporters in the diseased brain: Context matters. Cell Rep Med 2024; 5:101609. [PMID: 38897176 PMCID: PMC11228798 DOI: 10.1016/j.xcrm.2024.101609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 02/20/2024] [Accepted: 05/16/2024] [Indexed: 06/21/2024]
Abstract
ATP-binding cassette (ABC) transporters facilitate the movement of diverse molecules across cellular membranes, including those within the CNS. While most extensively studied in microvascular endothelial cells forming the blood-brain barrier (BBB), other CNS cell types also express these transporters. Importantly, disruptions in the CNS microenvironment during disease can alter transporter expression and function. Through this comprehensive review, we explore the modulation of ABC transporters in various brain pathologies and the context-dependent consequences of these changes. For instance, downregulation of ABCB1 may exacerbate amyloid beta plaque deposition in Alzheimer's disease and facilitate neurotoxic compound entry in Parkinson's disease. Upregulation may worsen neuroinflammation by aiding chemokine-mediated CD8 T cell influx into multiple sclerosis lesions. Overall, ABC transporters at the BBB hinder drug entry, presenting challenges for effective pharmacotherapy. Understanding the context-dependent changes in ABC transporter expression and function is crucial for elucidating the etiology and developing treatments for brain diseases.
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Affiliation(s)
- Chrysiida Baltira
- Division of Pharmacology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Eleonora Aronica
- Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Neuroscience, Department of (Neuro)Pathology, Amsterdam, the Netherlands; Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, the Netherlands
| | - William F Elmquist
- Brain Barriers Research Center, Department of Pharmaceutics, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Oliver Langer
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Löscher
- Translational Neuropharmacology Lab, NIFE, Department of Experimental Otology of the ENT Clinics, Hannover Medical School, Hannover, Germany; Center for Systems Neuroscience, Hannover, Germany
| | - Jann N Sarkaria
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Pieter Wesseling
- Department of Pathology, Amsterdam University Medical Centers, Amsterdam, the Netherlands; Laboratory for Childhood Cancer Pathology, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Mark C de Gooijer
- Division of Pharmacology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Faculty of Biology, Medicine and Health, University of Manchester; The Christie NHS Foundation Trust, Manchester, UK.
| | - Olaf van Tellingen
- Division of Pharmacology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Mouse Cancer Clinic, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
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2
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Gueltzow M, Lahtinen H, Bijlsma MJ, Myrskylä M, Martikainen P. Genetic propensity to depression and the role of partnership status. Soc Sci Med 2024; 351:116992. [PMID: 38772210 DOI: 10.1016/j.socscimed.2024.116992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 05/23/2024]
Abstract
Social relationships and genetic propensity are known to affect depression risk, but their joint effects are poorly understood. This study examined the association of a polygenic index for depression with time to antidepressant (AD) purchasing and the moderating role of partnership status. We analysed data from 30,192 Finnish individuals who participated in the FINRISK and Health 2000 and 2011 surveys and had register and medication data available. We measured genetic risk with a polygenic index (PGI) for depression. Depression was assessed through antidepressant purchases. We estimated an accelerated failure time model with partnership status as time-varying and different sets of confounder adjustments. The predicted cumulative hazard of antidepressant purchasing varied across PGI and partnership status. At follow-up year 10, being widowed was associated with the largest cumulative hazard of 0.34 (95%CI: 0.28-0.39) in the 80th and 0.20 (95%CI: 0.17-0.23) in the 20th PGI percentile, followed by divorced, single, married and cohabiting. Cohabiting was associated with a cumulative hazard of 0.19 (95%CI: 0.16-0.23) in the 80th and 0.11 (95%CI: 0.1-0.13) in the 20th PGI percentile. We found no evidence for an interaction between the PGI and partnership status. Results were robust to different model specifications, gender stratification, and the choice of PGI. Although antidepressant purchasing correlated with both PGI and partnership status, we found no evidence that partnership status could partially offset or amplify the association between the PGI for depression and antidepressant purchasing incidence.
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Affiliation(s)
- Maria Gueltzow
- Max Planck Institute for Demographic Research, Rostock, Germany; Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland.
| | - Hannu Lahtinen
- Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland; Helsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland
| | - Maarten J Bijlsma
- Max Planck Institute for Demographic Research, Rostock, Germany; Unit PharmacoTherapy, -Epidemiology, and -Economics (PTEE), Groningen Research Institute of Pharmacy, University of Groningen, the Netherlands
| | - Mikko Myrskylä
- Max Planck Institute for Demographic Research, Rostock, Germany; Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland; Helsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland
| | - Pekka Martikainen
- Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland; Helsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland
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Morris E, McGrail K, Cressman S, Stewart SE, Austin J. Assessing the impact of psychiatric genetic counseling on psychiatric hospitalizations. Clin Genet 2024; 105:630-638. [PMID: 38342854 DOI: 10.1111/cge.14493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/18/2024] [Accepted: 01/21/2024] [Indexed: 02/13/2024]
Abstract
Psychiatric genetic counseling (pGC) can improve patient empowerment and self-efficacy. We explored the relationship between pGC and psychiatric hospitalizations, for which no prior data exist. Using Population Data BC (a provincial dataset), we tested two hypotheses: (1) among patients (>18 years) with psychiatric conditions who received pGC between May 2010 and Dec 2016 (N = 387), compared with the year pre-pGC, in the year post-pGC there would be fewer (a) individuals hospitalized and (b) total hospital admissions; and (2) using a matched cohort design, compared with controls (N = 363, matched 1:4 for sex, diagnosis, time since diagnosis, region, and age, and assigned a pseudo pGC index date), the pGC cohort (N = 91) would have (a) more individuals whose number of hospitalizations decreased and (b) fewer hospitalizations post-pGC/pseudo-index. We also explored total days in hospital. Within the pGC cohort, there were fewer hospitalizations post-pGC than pre- pGC (p = 0.011, OR = 1.69), and total days in hospital decreased (1085 to 669). However, when compared to matched controls, the post-pGC/pseudo index change in hospitalizations among pGC cases was not statistically significant, even after controlling for the higher number of hospitalizations prior. pGC may lead to fewer psychiatric hospitalizations and cost savings; further studies exploring this are warranted.
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Affiliation(s)
- Emily Morris
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Kimberlyn McGrail
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Sonya Cressman
- University of British Columbia Digital Emergency Medicine, Vancouver, British Columbia, Canada
- Centre for Clinical Epidemiology and Evaluation, Simon Fraser University, Burnaby, British Columbia, Canada
| | - S Evelyn Stewart
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jehannine Austin
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
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Dong Z, Jiang W, Li H, DeWan AT, Zhao H. LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information. Brief Bioinform 2024; 25:bbae335. [PMID: 38980374 PMCID: PMC11232466 DOI: 10.1093/bib/bbae335] [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: 04/08/2024] [Revised: 06/05/2024] [Accepted: 06/26/2024] [Indexed: 07/10/2024] Open
Abstract
Gene-environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we review state-of-art methods for estimating the proportion of phenotypic variance explained by genome-wide GE interactions and introduce a novel statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by ~23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307 259 unrelated European-Ancestry subjects and 966 766 variants, across 217 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 34 significant E-Y pairs while LDSC-based method only identified 23 significant E-Y pairs with 22 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits.
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Affiliation(s)
- Zihan Dong
- Department of Biostatistics, Yale School of Public Health, 60 College Street, New Haven, CT 06510, United States
- Center for Perinatal, Pediatric and Environmental Epidemiology, 60 College Street, Yale School of Public Health, New Haven, CT 06510, United States
| | - Wei Jiang
- Department of Biostatistics, Yale School of Public Health, 60 College Street, New Haven, CT 06510, United States
| | - Hongyu Li
- Department of Biostatistics, Yale School of Public Health, 60 College Street, New Haven, CT 06510, United States
| | - Andrew T DeWan
- Center for Perinatal, Pediatric and Environmental Epidemiology, 60 College Street, Yale School of Public Health, New Haven, CT 06510, United States
- Department of Chronic Disease Epidemiology, Yale School of Public Health, 60 College Street, New Haven, CT 06510, United States
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, 60 College Street, New Haven, CT 06510, United States
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Tabesh S, Zia-Tohidi A, Firoozi M, Farahani H. Decomposing the variance in early maladaptive schemas: the major role of one general factor, the minor role of domains, and their differential relations to facial emotion recognition. Front Psychol 2024; 15:1342480. [PMID: 38813563 PMCID: PMC11134781 DOI: 10.3389/fpsyg.2024.1342480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 04/25/2024] [Indexed: 05/31/2024] Open
Abstract
Introduction Despite the growing interest in the early maladaptive schemas, the progress in understanding their impacts is decelerated by a lack of clear understanding of their structure. Different composite scores are calculated without a solid ground or a clarified meaning. Here we explain that the schema variance can be theoretically decomposed into three components: schema-specific, domain-specific due to the unmet core needs, and the common variance we call general susceptibility; each can differentially correlate with other substantive variables. Using this framework, we empirically examine the structure of schemas and their relationships to facial emotion recognition, a crucial ability that can widely affect our social interactions. Methods A sample of adults completed an emotion recognition task and the Young Schema Questionnaire. Using different factor models, the specific and shared variance across schemas was analyzed. Then, the relation of these variance components to facial emotion recognition was explored. Results A general factor explained 27%, 40%, and 64% of the total variance in items, schemas, and domains, respectively. Partialling out the common variance, there was little domain-specific variance remained. Regarding facial emotion recognition, they were not correlated with specific schemas; however, the general susceptibility factor was correlated with anger recognition. Discussion The variance decomposition approach to schemas, which uses the bifactor model, may offer a clearer way to explore the impacts of schemas. While domain scores are widely used, their reliability, validity, and meaning are questionable. The generic factor, which is consistently extractable from empirical data, requires further attention.
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Affiliation(s)
- Sajedeh Tabesh
- Department of Psychology, Faculty of Psychology and Educational Sciences, University of Tehran, Tehran, Iran
| | - Ali Zia-Tohidi
- Department of Psychology, Faculty of Psychology and Educational Sciences, University of Tehran, Tehran, Iran
| | - Manijeh Firoozi
- Department of Psychology, Faculty of Psychology and Educational Sciences, University of Tehran, Tehran, Iran
| | - Hojjatollah Farahani
- Department of Psychology, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran
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Chen P, Sun S, Yang Y, Huang A, Zhang H, Wang M. Cumulative Genetic Scores Interact with Maternal and Paternal Parenting in Predicting Parent-Adolescent Cohesion and Conflict. J Youth Adolesc 2024; 53:1171-1185. [PMID: 38308791 DOI: 10.1007/s10964-024-01947-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 01/16/2024] [Indexed: 02/05/2024]
Abstract
Previous research concerning the interplay between genetics and parenting in the development of the parent-child relationship during adolescence has been extremely scarce, predominantly adopting single-gene designs. This limited body of work has largely overlooked the distinct effects of maternal and paternal roles, as well as potential gender differences. Additionally, existing gene-by-environment (G × E) studies have mainly concentrated on adverse environmental factors and associated negative outcomes, somewhat neglecting positive environments and outcomes. The present study examined the interactions of cumulative genetic scores (CGS, dopamine receptor D2 TaqIA and oxytocin receptor gene rs53576 polymorphisms) with both positive and negative parenting on parent-adolescent cohesion and conflict. Furthermore, this study aimed to ascertain with which gene-environment model the potential G × E interactions would align. A total of 745 Chinese Han adolescents (Mage = 13.36 ± 0.96 years; 46.8% girls) from grades 7 to 9 participated in this study. Results revealed a significant effect of CGS and negative maternal parenting on mother-adolescent conflict among males, consistent with the weak differential susceptibility model. As CGS increased, the effects of negative maternal parenting on mother-son conflict were magnified. These findings have implications for the timing and focus of interventions aimed at improving parent-adolescent relationships.
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Affiliation(s)
- Pian Chen
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Shan Sun
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Yang Yang
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Aodi Huang
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Hongmei Zhang
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Meiping Wang
- Department of Psychology, Shandong Normal University, Jinan, China.
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Stanca A, Carella MC, Basile P, Forleo C, Ciccone MM, Guaricci AI. Cardiomyopathies and Psychiatric Disorders: An Overview and General Clinical Recommendations. Cardiol Rev 2024:00045415-990000000-00245. [PMID: 38602404 DOI: 10.1097/crd.0000000000000693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/12/2024]
Abstract
The association between cardiomyopathies (CMPs) and psychiatric disorders is a complex and bidirectional phenomenon that involves multiple mechanisms and factors. CMPs may raise the risk of psychiatric disorders due to the psychological stress, physical limitations, social isolation, or poor prognosis associated with the underlying disease. Psychiatric disorders, on the other hand, can increase the possibility of developing or worsening CMPs due to the behavioral, neuroendocrine, inflammatory, or pharmacological effects of mental illness or its treatment. Moreover, some common genetic or environmental factors may have a relevant influence on both conditions. With this comprehensive review, we sought to provide an overview of the current evidence on the strict and intriguing interconnection between CMPs and psychiatric disorders, focusing on the epidemiology, pathophysiology, clinical implications, and management strategies.
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Affiliation(s)
- Alessandro Stanca
- From the University Cardiology Unit, Interdisciplinary Department of Medicine (DIM), "Aldo Moro" University School of Medicine, AOUC Polyclinic of Bari, Bari, Italy
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Ponce-Valencia A, Jiménez-Rodríguez D, Hernández Morante JJ, Martínez Cortés C, Pérez-Sánchez H, Echevarría Pérez P. An Interpretable Machine Learning Approach to Predict Sensory Processing Sensitivity Trait in Nursing Students. Eur J Investig Health Psychol Educ 2024; 14:913-928. [PMID: 38667814 PMCID: PMC11049261 DOI: 10.3390/ejihpe14040059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 03/22/2024] [Accepted: 03/31/2024] [Indexed: 04/28/2024] Open
Abstract
Sensory processing sensitivity (SPS) is a personality trait that makes certain individuals excessively sensitive to stimuli. People carrying this trait are defined as Highly Sensitive People (HSP). The SPS trait is notably prevalent among nursing students and nurse staff. Although there are HSP diagnostic tools, there is little information about early detection. Therefore, the aim of this work was to develop a prediction model to identify HSP and provide an individualized nursing assessment. A total of 672 nursing students completed all the evaluations. In addition to the HSP diagnosis, emotional intelligence, communication skills, and conflict styles were evaluated. An interpretable machine learning model was trained to predict the SPS trait. We observed a 33% prevalence of HSP, which was higher in women and people with previous health training. HSP were characterized by greater emotional repair (p = 0.033), empathy (p = 0.030), respect (p = 0.038), and global communication skills (p = 0.036). Overall, sex and emotional intelligence dimensions are important to detect this trait, although personal characteristics should be considered. The present individualized prediction model could help to predict the presence of the SPS trait in nursing students, which may be useful in conducting intervention strategies to avoid the negative consequences and reinforce the positive ones of this trait.
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Affiliation(s)
- Alicia Ponce-Valencia
- Faculty of Nursing, Universidad Católica de Murcia, Campus de Guadalupe, 30107 Murcia, Spain; (A.P.-V.); (P.E.P.)
| | - Diana Jiménez-Rodríguez
- Faculty of Health Sciences, Universidad de Almería, Carretera Sacramento s/n, 04120 Almería, Spain;
| | - Juan José Hernández Morante
- Faculty of Nursing, Universidad Católica de Murcia, Campus de Guadalupe, 30107 Murcia, Spain; (A.P.-V.); (P.E.P.)
| | - Carlos Martínez Cortés
- Structural Bioinformatics and High-Performance Computing (BIO-HPC) Research Group, Universidad Católica de Murcia, Campus de Guadalupe, 30107 Murcia, Spain; (C.M.C.); (H.P.-S.)
| | - Horacio Pérez-Sánchez
- Structural Bioinformatics and High-Performance Computing (BIO-HPC) Research Group, Universidad Católica de Murcia, Campus de Guadalupe, 30107 Murcia, Spain; (C.M.C.); (H.P.-S.)
| | - Paloma Echevarría Pérez
- Faculty of Nursing, Universidad Católica de Murcia, Campus de Guadalupe, 30107 Murcia, Spain; (A.P.-V.); (P.E.P.)
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Schmitt O, Finnegan E, Trevarthen A, Wongsaengchan C, Paul ES, Mendl M, Fureix C. Exploring the similarities between risk factors triggering depression in humans and elevated in-cage "inactive but awake" behavior in laboratory mice. Front Vet Sci 2024; 11:1348928. [PMID: 38605924 PMCID: PMC11008528 DOI: 10.3389/fvets.2024.1348928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Accepted: 02/29/2024] [Indexed: 04/13/2024] Open
Abstract
Introduction Depression is a human mental disorder that can also be inferred in non-human animals. This study explored whether time spent inactive but awake ("IBA") in the home-cage in mice was further triggered by risk factors similar to those increasing vulnerability to depression in humans (early life stress, genetic predispositions, adulthood stress). Methods Eighteen DBA/2 J and 18 C57BL/6 J females were tested, of which half underwent as pups a daily maternal separation on post-natal days 2-14 (early-life stress "ELS") (other half left undisturbed). To assess the effect of the procedure, the time the dams from which the 18 subjects were born spent active in the nest (proxy for maternal behavior) was recorded on post-natal days 2, 6, 10 and 14 for 1 h before separation and following reunion (matched times for controls), using live instantaneous scan sampling (total: 96 scans/dam). For each ELS condition, about half of the pups were housed post-weaning (i.e., from 27 days old on average) in either barren (triggering IBA and depression-like symptoms) or larger, highly enriched cages (n = 4-5 per group). Time mice spent IBA post-weaning was observed blind to ELS treatment using live instantaneous scan sampling in two daily 90-min blocks, two days/week, for 6 weeks (total: 192 scans/mouse). Data were analyzed in R using generalized linear mixed models. Results The dams were significantly more active in the nest over time (p = 0.016), however with no significant difference between strains (p = 0.18), ELS conditions (p = 0.20) and before/after separation (p = 0.83). As predicted, post-weaning barren cages triggered significantly more time spent IBA in mice than enriched cages (p < 0.0001). However, neither ELS (p = 0.4) nor strain (p = 0.84) significantly influenced time mice spent IBA, with no significant interaction with environmental condition (ELS × environment: p = 0.2861; strain × environment: p = 0.5713). Discussion Our results therefore only partly support the hypothesis that greater time spent IBA in mice is triggered by risk factors for human depression. We discuss possible explanations for this and further research directions.
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Affiliation(s)
| | | | | | | | | | | | - Carole Fureix
- Bristol Veterinary School, University of Bristol, Bristol, United Kingdom
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10
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Casazza W, Inkster AM, Del Gobbo GF, Yuan V, Delahaye F, Marsit C, Park YP, Robinson WP, Mostafavi S, Dennis JK. Sex-dependent placental methylation quantitative trait loci provide insight into the prenatal origins of childhood onset traits and conditions. iScience 2024; 27:109047. [PMID: 38357671 PMCID: PMC10865402 DOI: 10.1016/j.isci.2024.109047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 06/19/2023] [Accepted: 01/23/2024] [Indexed: 02/16/2024] Open
Abstract
Molecular quantitative trait loci (QTLs) allow us to understand the biology captured in genome-wide association studies (GWASs). The placenta regulates fetal development and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explain variation in genetic risk for childhood onset traits, and that effects differ by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with mQTL and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions that typically affect gene expression in prenatal tissues. All mQTL were also enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.
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Affiliation(s)
- William Casazza
- Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital, Vancouver, BC, Canada
- Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
| | - Amy M. Inkster
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Giulia F. Del Gobbo
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- Children’s Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Victor Yuan
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | | | - Carmen Marsit
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Yongjin P. Park
- Department of Statistics, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Wendy P. Robinson
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Sara Mostafavi
- Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital, Vancouver, BC, Canada
- Paul Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - Jessica K. Dennis
- Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital, Vancouver, BC, Canada
- Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
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Rakotobe M, Fjerdingstad N, Ruiz-Reig N, Lamonerie T, D'Autréaux F. Central role of the habenulo-interpeduncular system in the neurodevelopmental basis of susceptibility and resilience to anxiety in mice. Neurobiol Dis 2024; 191:106392. [PMID: 38145853 DOI: 10.1016/j.nbd.2023.106392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/20/2023] [Accepted: 12/21/2023] [Indexed: 12/27/2023] Open
Abstract
Having experienced stress during sensitive periods of brain development strongly influences how individuals cope with later stress. Some are prone to develop anxiety or depression, while others appear resilient. The as-yet-unknown mechanisms underlying these differences may lie in how genes and environmental stress interact to shape the circuits that control emotions. Here, we investigated the role of the habenulo-interpeduncular system (HIPS), a critical node in reward circuits, in early stress-induced anxiety in mice. We found that habenular and IPN components characterized by the expression of Otx2 are synaptically connected and particularly sensitive to chronic stress (CS) during the peripubertal period. Stress-induced peripubertal activation of this HIPS subcircuit elicits both HIPS hypersensitivity to later stress and susceptibility to develop anxiety. We also show that HIPS silencing through conditional Otx2 knockout counteracts these effects of stress. Together, these results demonstrate that a genetic factor, Otx2, and stress interact during the peripubertal period to shape the stress sensitivity of the HIPS, which is shown to be a key modulator of susceptibility or resilience to develop anxiety.
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Affiliation(s)
- Malalaniaina Rakotobe
- Université Côte d'Azur, CNRS, Inserm, iBV, Institut de Biologie Valrose, 06108 Nice, France
| | - Niels Fjerdingstad
- Université Côte d'Azur, CNRS, Inserm, iBV, Institut de Biologie Valrose, 06108 Nice, France
| | - Nuria Ruiz-Reig
- Université Côte d'Azur, CNRS, Inserm, iBV, Institut de Biologie Valrose, 06108 Nice, France
| | - Thomas Lamonerie
- Université Côte d'Azur, CNRS, Inserm, iBV, Institut de Biologie Valrose, 06108 Nice, France.
| | - Fabien D'Autréaux
- Université Côte d'Azur, CNRS, Inserm, iBV, Institut de Biologie Valrose, 06108 Nice, France. Fabien.D'
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12
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Pan C, Cheng B, Qin X, Cheng S, Liu L, Yang X, Meng P, Zhang N, He D, Cai Q, Wei W, Hui J, Wen Y, Jia Y, Liu H, Zhang F. Enhanced polygenic risk score incorporating gene-environment interaction suggests the association of major depressive disorder with cardiac and lung function. Brief Bioinform 2024; 25:bbae070. [PMID: 38436562 DOI: 10.1093/bib/bbae070] [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: 10/19/2023] [Revised: 01/18/2024] [Accepted: 02/02/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND Depression has been linked to an increased risk of cardiovascular and respiratory diseases; however, its impact on cardiac and lung function remains unclear, especially when accounting for potential gene-environment interactions. METHODS We developed a novel polygenic and gene-environment interaction risk score (PGIRS) integrating the major genetic effect and gene-environment interaction effect of depression-associated loci. The single nucleotide polymorphisms (SNPs) demonstrating major genetic effect or environmental interaction effect were obtained from genome-wide SNP association and SNP-environment interaction analyses of depression. We then calculated the depression PGIRS for non-depressed individuals, using smoking and alcohol consumption as environmental factors. Using linear regression analysis, we assessed the associations of PGIRS and conventional polygenic risk score (PRS) with lung function (N = 42 886) and cardiac function (N = 1791) in the subjects with or without exposing to smoking and alcohol drinking. RESULTS We detected significant associations of depression PGIRS with cardiac and lung function, contrary to conventional depression PRS. Among smokers, forced vital capacity exhibited a negative association with PGIRS (β = -0.037, FDR = 1.00 × 10-8), contrasting with no significant association with PRS (β = -0.002, FDR = 0.943). In drinkers, we observed a positive association between cardiac index with PGIRS (β = 0.088, FDR = 0.010), whereas no such association was found with PRS (β = 0.040, FDR = 0.265). Notably, in individuals who both smoked and drank, forced expiratory volume in 1-second demonstrated a negative association with PGIRS (β = -0.042, FDR = 6.30 × 10-9), but not with PRS (β = -0.003, FDR = 0.857). CONCLUSIONS Our findings underscore the profound impact of depression on cardiac and lung function, highlighting the enhanced efficacy of considering gene-environment interactions in PRS-based studies.
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Affiliation(s)
- Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Xiaoyue Qin
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Na Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Dan He
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Qingqing Cai
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Wenming Wei
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Jingni Hui
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Huan Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
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Rea-Sandin G, Del Toro J, Wilson S. The Heritability of Psychopathology Symptoms in Early Adolescence: Moderation by Family Cultural Values in the ABCD Study. Behav Genet 2024; 54:119-136. [PMID: 37702839 PMCID: PMC10833244 DOI: 10.1007/s10519-023-10154-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 09/04/2023] [Indexed: 09/14/2023]
Abstract
Family cultural values that emphasize support, loyalty, and obligation to the family are associated with lower psychopathology in Hispanic/Latino/a youth, but there is a need to understand the implications of family cultural values for youth development in racially/ethnically heterogeneous samples. This study examined phenotypic associations between parent- and youth-reported family cultural values in late childhood on youth internalizing and externalizing symptoms in early adolescence, and whether family cultural values moderated genetic and environmental influences on psychopathology symptoms. The sample comprised 10,335 children (Mage=12.89 years; 47.9% female; 20.3% Hispanic/Latino/a, 15.0% Black, 2.1% Asian, 10.5% other) and their parents from the Adolescent Brain Cognitive Development (ABCD) Study, and biometric models were conducted in the twin subsample (n = 1,042 twin pairs; 43.3% monozygotic). Parents and youth reported on their family cultural values using the Mexican American Cultural Values Scale at youth age 11-12, and parents reported on youth internalizing and externalizing symptoms using the Child Behavior Checklist at youth ages 11-12 and 12-13. Greater parent- and youth-reported family cultural values predicted fewer youth internalizing and externalizing symptoms. Biometric models indicated that higher parent-reported family cultural values increased the nonshared environmental influences on externalizing symptoms whereas youth-reported family cultural values decreased the nonshared environmental influences on internalizing symptoms. This study highlights the need for behavior genetic research to consider a diverse range of cultural contexts to better understand the etiology of youth psychopathology.
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Affiliation(s)
- Gianna Rea-Sandin
- Department of Psychology, , University of Minnesota, Minneapolis, MN, USA.
| | - Juan Del Toro
- Department of Psychology, , University of Minnesota, Minneapolis, MN, USA
| | - Sylia Wilson
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
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14
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Monteil A, Guérineau NC, Gil-Nagel A, Parra-Diaz P, Lory P, Senatore A. New insights into the physiology and pathophysiology of the atypical sodium leak channel NALCN. Physiol Rev 2024; 104:399-472. [PMID: 37615954 DOI: 10.1152/physrev.00014.2022] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/13/2023] [Accepted: 08/15/2023] [Indexed: 08/25/2023] Open
Abstract
Cell excitability and its modulation by hormones and neurotransmitters involve the concerted action of a large repertoire of membrane proteins, especially ion channels. Unique complements of coexpressed ion channels are exquisitely balanced against each other in different excitable cell types, establishing distinct electrical properties that are tailored for diverse physiological contributions, and dysfunction of any component may induce a disease state. A crucial parameter controlling cell excitability is the resting membrane potential (RMP) set by extra- and intracellular concentrations of ions, mainly Na+, K+, and Cl-, and their passive permeation across the cell membrane through leak ion channels. Indeed, dysregulation of RMP causes significant effects on cellular excitability. This review describes the molecular and physiological properties of the Na+ leak channel NALCN, which associates with its accessory subunits UNC-79, UNC-80, and NLF-1/FAM155 to conduct depolarizing background Na+ currents in various excitable cell types, especially neurons. Studies of animal models clearly demonstrate that NALCN contributes to fundamental physiological processes in the nervous system including the control of respiratory rhythm, circadian rhythm, sleep, and locomotor behavior. Furthermore, dysfunction of NALCN and its subunits is associated with severe pathological states in humans. The critical involvement of NALCN in physiology is now well established, but its study has been hampered by the lack of specific drugs that can block or agonize NALCN currents in vitro and in vivo. Molecular tools and animal models are now available to accelerate our understanding of how NALCN contributes to key physiological functions and the development of novel therapies for NALCN channelopathies.
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Affiliation(s)
- Arnaud Monteil
- Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France
- LabEx "Ion Channel Science and Therapeutics," Montpellier, France
- Department of Physiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Nathalie C Guérineau
- Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France
- LabEx "Ion Channel Science and Therapeutics," Montpellier, France
| | - Antonio Gil-Nagel
- Department of Neurology, Epilepsy Program, Hospital Ruber Internacional, Madrid, Spain
| | - Paloma Parra-Diaz
- Department of Neurology, Epilepsy Program, Hospital Ruber Internacional, Madrid, Spain
| | - Philippe Lory
- Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France
- LabEx "Ion Channel Science and Therapeutics," Montpellier, France
| | - Adriano Senatore
- Department of Biology, University of Toronto Mississauga, Mississauga, Ontario, Canada
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15
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Hannigan LJ, Lund IO, Dahl Askelund A, Ystrom E, Corfield EC, Ask H, Havdahl A. Genotype-environment interplay in associations between maternal drinking and offspring emotional and behavioral problems. Psychol Med 2024; 54:203-214. [PMID: 37929303 DOI: 10.1017/s0033291723003057] [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] [Indexed: 11/07/2023]
Abstract
BACKGROUND While maternal at-risk drinking is associated with children's emotional and behavioral problems, there is a paucity of research that properly accounts for genetic confounding and gene-environment interplay. Therefore, it remains uncertain what mechanisms underlie these associations. We assess the moderation of associations between maternal at-risk drinking and childhood emotional and behavioral problems by common genetic variants linked to environmental sensitivity (genotype-by-environment [G × E] interaction) while accounting for shared genetic risk between mothers and offspring (GE correlation). METHODS We use data from 109 727 children born to 90 873 mothers enrolled in the Norwegian Mother, Father, and Child Cohort Study. Women self-reported alcohol consumption and reported emotional and behavioral problems when children were 1.5/3/5 years old. We included child polygenic scores (PGSs) for traits linked to environmental sensitivity as moderators. RESULTS Associations between maternal drinking and child emotional (β1 = 0.04 [95% confidence interval (CI) 0.03-0.05]) and behavioral (β1 = 0.07 [0.06-0.08]) outcomes attenuated after controlling for measured confounders and were almost zero when we accounted for unmeasured confounding (emotional: β1 = 0.01 [0.00-0.02]; behavioral: β1 = 0.01 [0.00-0.02]). We observed no moderation of these adjusted exposure effects by any of the PGS. CONCLUSIONS The lack of strong evidence for G × E interaction may indicate that the mechanism is not implicated in this kind of intergenerational association. It may also reflect insufficient power or the relatively benign nature of the exposure in this sample.
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Affiliation(s)
- Laurie John Hannigan
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Ingunn Olea Lund
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Adrian Dahl Askelund
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Eivind Ystrom
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway
- School of Pharmacy, University of Oslo, Oslo, Norway
| | - Elizabeth C Corfield
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Helga Ask
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway
| | - Alexandra Havdahl
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway
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Mboweni EN, Mphasha MH, Skaal L. Exploring Mental Health Awareness: A Study on Knowledge and Perceptions of Mental Health Disorders among Residents of Matsafeni Village, Mbombela, Mpumalanga Province. Healthcare (Basel) 2023; 12:85. [PMID: 38200990 PMCID: PMC10779020 DOI: 10.3390/healthcare12010085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 12/20/2023] [Accepted: 12/28/2023] [Indexed: 01/12/2024] Open
Abstract
The global rise in mental health disorders has significant social, economic, and physical impacts. Despite advancements in support, cultural beliefs attributing mental illnesses to spiritual causes persist, fostering discrimination and stigmatization. The study aims to explore the understanding and perceptions of mental health in Matsafeni Village, acknowledging the complexity of mental health issues. A qualitative method and a descriptive exploratory design were employed, enabling the researcher to describe, examine, and explore the knowledge and perceptions regarding mental health. Data collection was conducted through unstructured, open-ended interviews, with 15 participants selected through convenience sampling. The data were analyzed through thematic analysis. Measures of rigor were ensured through credibility, transferability, confirmability, and dependability. Participants demonstrated knowledge of mental health disorders, recognizing disruptions in thought patterns and diverse symptoms. They highlighted key signs and behaviors, emphasizing the need for spotting indicators such as untidiness. Perceptions of the causes of mental illness varied, including witchcraft and genetics. Participants unanimously advocated for seeking help from traditional healers, medical facilities, and therapies. Community members shared their views of mental health, covering their understanding, recognition of signs, personal interactions, and observations of behaviors in individuals with mental health conditions. Reported symptoms align with existing research, emphasizing the complexity of managing safety concerns in severe mental illnesses. The study highlights the need for community education to reduce stigma, considering cultural factors in mental health perceptions. Recommendations include early interventions, enhanced mental health services, and collaboration between western and traditional approaches for a holistic and culturally sensitive approach to mental health.
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Affiliation(s)
| | | | - Linda Skaal
- Department of Public Health, Sefako Makgatho University, Ga-Rankuwa 0204, South Africa;
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Pan C, Liu L, Cheng S, Yang X, Meng P, Zhang N, He D, Chen Y, Li C, Zhang H, Zhang J, Zhang Z, Cheng B, Wen Y, Jia Y, Liu H, Zhang F. A multidimensional social risk atlas of depression and anxiety: An observational and genome-wide environmental interaction study. J Glob Health 2023; 13:04146. [PMID: 38063329 PMCID: PMC10704948 DOI: 10.7189/jogh.13.04146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023] Open
Abstract
Background Mental disorders are largely socially determined, yet the combined impact of multidimensional social factors on the two most common mental disorders, depression and anxiety, remains unclear. Methods We constructed a polysocial risk score (PsRS), a multidimensional social risk indicator including components from three domains: socioeconomic status, neighborhood and living environment and psychosocial factors. Supported by the UK Biobank cohort, we randomly divided 110 332 participants into the discovery cohort (60%; n = 66 200) and the replication cohort (40%; n = 44 134). We tested the associations between 13 single social factors with Patient Health Questionnaire (PHQ) score, Generalized Anxiety Disorder Scale (GAD) score and self-reported depression and anxiety. The significant social factors were used to calculate PsRS for each mental disorder by considering weights from the multivariable linear model. Generalized linear models were applied to explore the association between PsRS and depression and anxiety. Genome-wide environmental interaction study (GWEIS) was further performed to test the effect of interactions between PsRS and SNPs on the risk of mental phenotypes. Results In the discovery cohort, PsRS was positively associated with PHQ score (β = 0.37; 95% CI = 0.35-0.38), GAD score (β = 0.27; 95% CI = 0.25-0.28), risk of self-reported depression (OR = 1.29; 95% CI = 1.28-1.31) and anxiety (OR = 1.19; 95% CI = 1.19-1.23). Similar results were observed in the replication cohort. Emotional stress, lack of social support and low household income were significantly associated with the development of depression and anxiety. GWEIS identified multiple candidate loci for PHQ score, such as rs149137169 (ST18) (Pdiscovery = 1.08 × 10-8, Preplication = 3.25 × 10-6) and rs3759812 (MYO9A) (Pdiscovery = 3.87 × 10-9, Preplication = 6.21 × 10-5). Additionally, seven loci were detected for GAD score, such as rs114006170 (TMPRSS11D) (Pdiscovery = 1.14 × 10-9, Preplication = 7.36 × 10-5) and rs77927903 (PIP4K2A) (Pdiscovery = 2.40 × 10-9, Preplication = 0.002). Conclusions Our findings reveal the positive effects of multidimensional social factors on the risk of depression and anxiety. It is important to address key social disadvantage in mental health promotion and treatment.
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Serpico D. A Wolf in Sheep's Clothing: Idealisations and the aims of polygenic scores. STUDIES IN HISTORY AND PHILOSOPHY OF SCIENCE 2023; 102:72-83. [PMID: 37907020 DOI: 10.1016/j.shpsa.2023.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 07/13/2023] [Accepted: 10/07/2023] [Indexed: 11/02/2023]
Abstract
Research in pharmacogenomics and precision medicine has recently introduced the concept of Polygenic Scores (PGSs), namely, indexes that aggregate the effects that many genetic variants are predicted to have on individual disease risk. The popularity of PGSs is increasing rapidly, but surprisingly little attention has been paid to the idealisations they make about phenotypic development. Indeed, PGSs rely on quantitative genetics models and methods, which involve considerable theoretical assumptions that have been questioned on various grounds. This comes with epistemological and ethical concerns about the use of PGSs in clinical decision-making. In this paper, I investigate to what extent idealisations in genetics models can impact the data gathering and clinical interpretation of genomics findings, particularly the calculation and predictive accuracy of PGSs. Although idealisations are considered ineliminable components of scientific models, they may be legitimate or not depending on the epistemic aims of a model. I thus analyse how various idealisations have been introduced in classical models and progressively readapted throughout the history of genetic theorising. Notably, this process involved important changes in the epistemic purpose of such idealisations, which raises the question of whether they are legitimate in the context of contemporary genomics.
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Affiliation(s)
- Davide Serpico
- Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122, Trento, Italy; Interdisciplinary Centre for Ethics & Institute of Philosophy, Jagiellonian University, Grodzka 52, 31-044 Kraków, Poland.
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Peter HL, Giglberger M, Streit F, Frank J, Kreuzpointner L, Rietschel M, Kudielka BM, Wüst S. Association of polygenic scores for depression and neuroticism with perceived stress in daily life during a long-lasting stress period. GENES, BRAIN, AND BEHAVIOR 2023; 22:e12872. [PMID: 37876358 PMCID: PMC10733580 DOI: 10.1111/gbb.12872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 07/31/2023] [Accepted: 10/06/2023] [Indexed: 10/26/2023]
Abstract
Genetic factors contribute significantly to interindividual differences in the susceptibility to stress-related disorders. As stress can also be conceptualized as environmental exposure, controlled gene-environment interaction (GxE) studies with an in-depth phenotyping may help to unravel mechanisms underlying the interplay between genetic factors and stress. In a prospective-longitudinal quasi-experimental study, we investigated whether polygenic scores (PGS) for depression (DEP-PGS) and neuroticism (NEU-PGS), respectively, were associated with responses to chronic stress in daily life. We examined law students (n = 432) over 13 months. Participants in the stress group experienced a long-lasting stress phase, namely the preparation for the first state examination for law students. The control group consisted of law students without particular stress exposure. In the present manuscript, we analyzed perceived stress levels assessed at high frequency and in an ecologically valid manner by ambulatory assessments as well as depression symptoms and two parameters of the cortisol awakening response. The latter was only assessed in a subsample (n = 196). No associations between the DEP-PGS and stress-related variables were found. However, for the NEU-PGS we found a significant GxE effect. Only in individuals experiencing academic stress a higher PGS for neuroticism predicted stronger increases of perceived stress levels until the exam. At baseline, a higher NEU-PGS was associated with higher perceived stress levels in both groups. Despite the small sample size, we provide preliminary evidence that the genetic disposition for neuroticism is associated with stress level increases in daily life during a long-lasting stress period.
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Affiliation(s)
- Hannah L. Peter
- Institute of PsychologyUniversity of RegensburgRegensburgGermany
| | | | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental HealthUniversity of MannheimMannheimGermany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental HealthUniversity of MannheimMannheimGermany
| | | | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental HealthUniversity of MannheimMannheimGermany
| | | | - Stefan Wüst
- Institute of PsychologyUniversity of RegensburgRegensburgGermany
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de Las Fuentes L, Schwander KL, Brown MR, Bentley AR, Winkler TW, Sung YJ, Munroe PB, Miller CL, Aschard H, Aslibekyan S, Bartz TM, Bielak LF, Chai JF, Cheng CY, Dorajoo R, Feitosa MF, Guo X, Hartwig FP, Horimoto A, Kolčić I, Lim E, Liu Y, Manning AK, Marten J, Musani SK, Noordam R, Padmanabhan S, Rankinen T, Richard MA, Ridker PM, Smith AV, Vojinovic D, Zonderman AB, Alver M, Boissel M, Christensen K, Freedman BI, Gao C, Giulianini F, Harris SE, He M, Hsu FC, Kühnel B, Laguzzi F, Li X, Lyytikäinen LP, Nolte IM, Poveda A, Rauramaa R, Riaz M, Robino A, Sofer T, Takeuchi F, Tayo BO, van der Most PJ, Verweij N, Ware EB, Weiss S, Wen W, Yanek LR, Zhan Y, Amin N, Arking DE, Ballantyne C, Boerwinkle E, Brody JA, Broeckel U, Campbell A, Canouil M, Chai X, Chen YDI, Chen X, Chitrala KN, Concas MP, de Faire U, de Mutsert R, de Silva HJ, de Vries PS, Do A, Faul JD, Fisher V, Floyd JS, Forrester T, Friedlander Y, Girotto G, Gu CC, Hallmans G, Heikkinen S, Heng CK, Homuth G, Hunt S, Ikram MA, Jacobs DR, Kavousi M, Khor CC, Kilpeläinen TO, Koh WP, Komulainen P, Langefeld CD, Liang J, Liu K, Liu J, Lohman K, Mägi R, Manichaikul AW, McKenzie CA, Meitinger T, Milaneschi Y, Nauck M, Nelson CP, O'Connell JR, Palmer ND, Pereira AC, Perls T, Peters A, Polašek O, Raitakari OT, Rice K, Rice TK, Rich SS, Sabanayagam C, Schreiner PJ, Shu XO, Sidney S, Sims M, Smith JA, Starr JM, Strauch K, Tai ES, Taylor KD, Tsai MY, Uitterlinden AG, van Heemst D, Waldenberger M, Wang YX, Wei WB, Wilson G, Xuan D, Yao J, Yu C, Yuan JM, Zhao W, Becker DM, Bonnefond A, Bowden DW, Cooper RS, Deary IJ, Divers J, Esko T, Franks PW, Froguel P, Gieger C, Jonas JB, Kato N, Lakka TA, Leander K, Lehtimäki T, Magnusson PKE, North KE, Ntalla I, Penninx B, Samani NJ, Snieder H, Spedicati B, van der Harst P, Völzke H, Wagenknecht LE, Weir DR, Wojczynski MK, Wu T, Zheng W, Zhu X, Bouchard C, Chasman DI, Evans MK, Fox ER, Gudnason V, Hayward C, Horta BL, Kardia SLR, Krieger JE, Mook-Kanamori DO, Peyser PA, Province MM, Psaty BM, Rudan I, Sim X, Smith BH, van Dam RM, van Duijn CM, Wong TY, Arnett DK, Rao DC, Gauderman J, Liu CT, Morrison AC, Rotter JI, Fornage M. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci. Front Genet 2023; 14:1235337. [PMID: 38028628 PMCID: PMC10651736 DOI: 10.3389/fgene.2023.1235337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 09/27/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: "Some College" (yes/no, for any education beyond high school) and "Graduated College" (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10-8) and suggestive (p < 1 × 10-6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.
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Affiliation(s)
- Lisa de Las Fuentes
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Karen L Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Yun Ju Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Patricia B Munroe
- Clinical Pharmacology, Queen Mary University of London, London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, United Kingdom
| | - Clint L Miller
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
- Biochemistry and Molecular Genetics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, United States
| | - Hugo Aschard
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, United States
- Département de Génomes et Génétique, Institut Pasteur de Lille, Université de Lille, Lille, France
| | - Stella Aslibekyan
- School of Public Health, Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Traci M Bartz
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Ching-Yu Cheng
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Medical School, Duke-National University of Singapore, Singapore, Singapore
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Fernando P Hartwig
- Postgraduate Programme in Epidemiology, Faculty of Medicine, Federal University of Pelotas, Pelotas, RS, Brazil
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Andrea Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil
| | - Ivana Kolčić
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Elise Lim
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Yongmei Liu
- Division of Cardiology, Department of Medicine, Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, United States
| | - Alisa K Manning
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Solomon K Musani
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Melissa A Richard
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Albert V Smith
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
- Icelandic Heart Association, Kopavogur, Iceland
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
- National Institutes of Health, Baltimore, MD, United States
| | - Maris Alver
- Estonian Genome Center, Insititute of Genomics, University of Tartu, Tartu, Estonia
| | - Mathilde Boissel
- European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
| | - Kaare Christensen
- Unit of Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Barry I Freedman
- Nephrology Division, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States
| | - Sarah E Harris
- Department of Psychology, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fang-Chi Hsu
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Federica Laguzzi
- Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Xiaoyin Li
- Department of Population and Quantitative Health Sciences, Cleveland, OH, United States
- Department of Mathematics and Statistics, St. Cloud State University, St. Cloud, MN, United States
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, University of Tampere, Tampere, Finland
- Finnish Cardiovascular Research Center, University of Tampere, Tampere, Finland
| | - Ilja M Nolte
- Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Alaitz Poveda
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Muhammad Riaz
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Antonietta Robino
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - Tamar Sofer
- Biostatistics, Department of Medicine, Brigham and Women's Hospital, Harvard University, Boston, MA, United States
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Bamidele O Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, United States
| | - Peter J van der Most
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Erin B Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald and University of Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research, Greifswald, Germany
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Yiqiang Zhan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Dan E Arking
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Christie Ballantyne
- Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX, United States
- Houston Methodist Debakey Heart and Vascular Center, Houston, TX, United States
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, United States
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States
| | - Ulrich Broeckel
- Section on Genomic Pediatrics, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Mickaël Canouil
- European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
| | - Xiaoran Chai
- Data Science Unit, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Yii-Der Ida Chen
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Xu Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kumaraswamy Naidu Chitrala
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
| | - Maria Pina Concas
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - Ulf de Faire
- Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Ahn Do
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| | - Virginia Fisher
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - James S Floyd
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States
| | - Terrence Forrester
- Tropical Medicine Research Institute, University of the West Indies, Mona, Jamaica
| | - Yechiel Friedlander
- Braun School of Public Health, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Giorgia Girotto
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - C Charles Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Göran Hallmans
- Section for Nutritional Research, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Sami Heikkinen
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald and University of Greifswald, Greifswald, Germany
| | - Steven Hunt
- Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States
- Department of Genetic Medicine, Weill Cornell Medicine in Qatar, Doha, Qatar
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Environmental Medicine and Public Health, The Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | | | - Carl D Langefeld
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Jingjing Liang
- Department of Population and Quantitative Health Sciences, Cleveland, OH, United States
| | - Kiang Liu
- Epidemiology, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Kurt Lohman
- Division of Cardiology, Department of Medicine, Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, United States
| | - Reedik Mägi
- Estonian Genome Center, Insititute of Genomics, University of Tartu, Tartu, Estonia
| | - Ani W Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
| | - Colin A McKenzie
- Tropical Medicine Research Institute, University of the West Indies, Mona, Jamaica
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, Munich, Germany
| | | | - Matthias Nauck
- German Center for Cardiovascular Research, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, United States
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Alexandre C Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil
| | - Thomas Perls
- Geriatrics Section, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research, Neuherberg, Germany
| | - Ozren Polašek
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Treva K Rice
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
| | - Charumathi Sabanayagam
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Medical School, Duke-National University of Singapore, Singapore, Singapore
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Stephen Sidney
- Division of Research, Kaiser Permanente of Northern California, Oakland, CA, United States
| | - Mario Sims
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, United Kingdom
| | - Konstantin Strauch
- German Research Center for Environmental Health, Helmholtz Zentrum München, Institute of Genetic Epidemiology, Neuherberg, Germany
- Institute of Medical Informatics Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Kent D Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, Minneapolis, MN, United States
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Diana van Heemst
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Ya-Xing Wang
- Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
| | - Wen-Bin Wei
- Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
| | - Gregory Wilson
- Jackson Heart Study Graduate Training Center, School of Public, Jackson State University, Jackson, MS, United States
| | - Deng Xuan
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Jie Yao
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Caizheng Yu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian-Min Yuan
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
- Division of Cancer Control and Population Sciences, University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center, Pittsburgh, PA, United States
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Diane M Becker
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Amélie Bonnefond
- European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Richard S Cooper
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, United States
| | - Ian J Deary
- Department of Psychology, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
| | - Jasmin Divers
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Tõnu Esko
- Estonian Genome Center, Insititute of Genomics, University of Tartu, Tartu, Estonia
- Broad Institute, Massachusetts Institute of Technology and Harvard University, Boston, MA, United States
| | - Paul W Franks
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, United States
| | - Philippe Froguel
- European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Jost B Jonas
- Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
- Department of Ophthalmology, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany
- Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Timo A Lakka
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Karin Leander
- Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Terho Lehtimäki
- Department of Clinical Chemistry, University of Tampere, Tampere, Finland
- Finnish Cardiovascular Research Center, University of Tampere, Tampere, Finland
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Ioanna Ntalla
- Clinical Pharmacology, Queen Mary University of London, London, United Kingdom
- Celgene, Bristol Myers Squibb, Mississauga, ON, Canada
| | | | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Harold Snieder
- Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Pim van der Harst
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Henry Völzke
- German Center for Cardiovascular Research, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Lynne E Wagenknecht
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Tangchun Wu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Cleveland, OH, United States
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
- National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
| | - Ervin R Fox
- Division of Cardiology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Bernardo L Horta
- Postgraduate Programme in Epidemiology, Faculty of Medicine, Federal University of Pelotas, Pelotas, RS, Brazil
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jose Eduardo Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Michael M Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States
- Department of Epidemiology, University of Washington, Seattle, WA, United States
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, United States
| | - Igor Rudan
- Centre for Global Health, The Usher Institute, The University of Edinburgh, Edinburgh, United Kingdom
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Tien Yin Wong
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Medical School, Duke-National University of Singapore, Singapore, Singapore
| | - Donna K Arnett
- College of Public Health, Dean's Office, University of Kentucky, Lexington, KY, United States
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - James Gauderman
- Division of Biostatistics, Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, United States
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21
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Jiang M, Yan W, Li X, Zhao L, Lu T, Zhang D, Li J, Wang L. Calcium Homeostasis and Psychiatric Disorders: A Mendelian Randomization Study. Nutrients 2023; 15:4051. [PMID: 37764834 PMCID: PMC10535008 DOI: 10.3390/nu15184051] [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: 08/28/2023] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Observational studies have investigated the impact of calcium homeostasis on psychiatric disorders; however, the causality of associations is yet to be established. Bidirectional Mendelian randomization (MR) analysis of calcium homeostasis hormones was conducted on nine psychiatric disorders. Calcium, serum 25-hydroxyvitamin D levels (25OHD), parathyroid hormone, and fibroblast growth factor 23 are the major calcium homeostasis hormones. The causality was evaluated by the inverse variance weighted method (IVW) and the MR Steiger test, while Cochran's Q test, the MR-Egger intercept test, funnel plot, and the leave-one-out method were used for sensitivity analyses. Bonferroni correction was used to determine the causative association features (p < 6.94 × 10-4). Schizophrenia (SCZ) was significantly associated with decreased 25OHD concentrations with an estimated effect of -0.0164 (Prandom-effect IVW = 2.39 × 10-7). In the Multivariable MR (MVMR) analysis adjusting for potentially confounding traits including body mass index, obesity, mineral supplements (calcium, fish oil, and vitamin D) and outdoor time (winter and summer), the relationship between SCZ and 25OHD remained. The genetically predicted autism spectrum disorder and bipolar disorder were also nominally associated with decreased 25OHD. This study provided evidence for a causal effect of psychiatric disorders on calcium homeostasis. The clinical monitoring of 25OHD levels in patients with psychiatric disorders is beneficial.
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Affiliation(s)
- Miaomiao Jiang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health, Peking University Sixth Hospital, Peking University Institute of Mental Health, Peking University, Beijing 100191, China
| | - Weiheng Yan
- Children's Hospital Capital Institute of Pediatrics, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100020, China
| | - Xianjing Li
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health, Peking University Sixth Hospital, Peking University Institute of Mental Health, Peking University, Beijing 100191, China
| | - Liyang Zhao
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health, Peking University Sixth Hospital, Peking University Institute of Mental Health, Peking University, Beijing 100191, China
| | - Tianlan Lu
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health, Peking University Sixth Hospital, Peking University Institute of Mental Health, Peking University, Beijing 100191, China
| | - Dai Zhang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health, Peking University Sixth Hospital, Peking University Institute of Mental Health, Peking University, Beijing 100191, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, Institute for Brain Research and Rehabilitation (IBRR), South China Normal University, Guangzhou 510631, China
| | - Jun Li
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health, Peking University Sixth Hospital, Peking University Institute of Mental Health, Peking University, Beijing 100191, China
| | - Lifang Wang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health, Peking University Sixth Hospital, Peking University Institute of Mental Health, Peking University, Beijing 100191, China
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22
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Bjornson KJ, Vanderplow AM, Yang Y, Anderson DR, Kermath BA, Cahill ME. Stress-mediated dysregulation of the Rap1 small GTPase impairs hippocampal structure and function. iScience 2023; 26:107566. [PMID: 37664580 PMCID: PMC10470260 DOI: 10.1016/j.isci.2023.107566] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 05/15/2023] [Accepted: 08/02/2023] [Indexed: 09/05/2023] Open
Abstract
The effects of repeated stress on cognitive impairment are thought to be mediated, at least in part, by reductions in the stability of dendritic spines in brain regions critical for proper learning and memory, including the hippocampus. Small GTPases are particularly potent regulators of dendritic spine formation, stability, and morphology in hippocampal neurons. Through the use of small GTPase protein profiling in mice, we identify increased levels of synaptic Rap1 in the hippocampal CA3 region in response to escalating, intermittent stress. We then demonstrate that increased Rap1 in the CA3 is sufficient in and of itself to produce stress-relevant dendritic spine and cognitive phenotypes. Further, using super-resolution imaging, we investigate how the pattern of Rap1 trafficking to synapses likely underlies its effects on the stability of select dendritic spine subtypes. These findings illuminate the involvement of aberrant Rap1 regulation in the hippocampus in contributing to the psychobiological effects of stress.
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Affiliation(s)
- Kathryn J. Bjornson
- Department of Comparative Biosciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Amanda M. Vanderplow
- Department of Comparative Biosciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Yezi Yang
- Department of Comparative Biosciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Danielle R. Anderson
- Department of Comparative Biosciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Bailey A. Kermath
- Department of Comparative Biosciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Michael E. Cahill
- Department of Comparative Biosciences, University of Wisconsin-Madison, Madison, WI 53706, USA
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23
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Deng S, Xie R, Kong A, Luo Y, Li J, Chen M, Wang X, Gong H, Wang L, Fan X, Pan Q, Li D. Early-life stress contributes to depression-like behaviors in a two-hit mouse model. Behav Brain Res 2023; 452:114563. [PMID: 37406776 DOI: 10.1016/j.bbr.2023.114563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 06/23/2023] [Accepted: 07/01/2023] [Indexed: 07/07/2023]
Abstract
BACKGROUND Depression is a common psychological disorder with pathogenesis involving genetic and environmental interactions. Early life stress can adversely affect physical and emotional development and dramatically increase the risk for the development of depression and anxiety disorders. METHODS To examine potential early life stress driving risk for anxiety and depression, we used a two-hit developmental stress model,injecting poly(I: C) into neonatal mice on P2-P6 followed by peripubertal unpredictable stress in adolescence. RESULTS Our study shows that early-life and adolescent stress leads to anxiety and depression-related behavioral phenotypes in male mice. Early-life stress exacerbated depression-like behavior in mice following peripubertal unpredictable stress. We confirmed that early life stress might be involved in the decreased neuronal activity in the medial prefrontal cortex (mPFC) and might be involved in shaping behavioral phenotypes of animals. We found that increased microglia and neuroinflammation in the mPFC of two-hit mice and early life stress further boost microglia activation and inflammatory factors in the mPFC region of mice following adolescent stress. LIMITATIONS The specific neural circuits and mechanisms by which microglia regulate depression-like behaviors require further investigation. CONCLUSIONS Our findings provide a novel insight into developmental risk factors and biological mechanisms in depression and anxiety disorders.
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Affiliation(s)
- Shilong Deng
- Department of Physiology, School of Basic Medical Sciences, Southwest Medical University, Luzhou 646000, China; Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China
| | - Ruxin Xie
- Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China
| | - Anqi Kong
- Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China
| | - Yi Luo
- Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China
| | - Jianghui Li
- Department of Physiology, School of Basic Medical Sciences, Southwest Medical University, Luzhou 646000, China
| | - Mei Chen
- Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China
| | - Xiaqing Wang
- Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China
| | - Hong Gong
- Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China
| | - Lian Wang
- Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China
| | - Xiaotang Fan
- Department of Military Cognitive Psychology, School of Psychology, Third Military Medical University, Chongqing 400038, China.
| | - Qiangwen Pan
- Department of Physiology, School of Basic Medical Sciences, Southwest Medical University, Luzhou 646000, China.
| | - Dabing Li
- Department of Physiology, School of Basic Medical Sciences, Southwest Medical University, Luzhou 646000, China.
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24
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Morrill K, Chen F, Karlsson E. Comparative neurogenetics of dog behavior complements efforts towards human neuropsychiatric genetics. Hum Genet 2023; 142:1231-1246. [PMID: 37578529 DOI: 10.1007/s00439-023-02580-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 06/02/2023] [Indexed: 08/15/2023]
Abstract
Domestic dogs display a wide array of heritable behaviors that have intermediate genetic complexity thanks to a long history of human-influenced selection. Comparative genetics in dogs could address the scarcity of non-human neurogenetic systems relevant to human neuropsychiatric disorders, which are characterized by mental, emotional, and behavioral symptoms and involve vastly complex genetic and non-genetic risk factors. Our review describes the diverse behavioral "phenome" of domestic dogs, past and ongoing sources of behavioral selection, and the state of canine behavioral genetics. We highlight two naturally disordered behavioral domains that illustrate how dogs may prove useful as a comparative, forward neurogenetic system: canine age-related cognitive dysfunction, which can be examined more rapidly given the attenuated lifespan of dogs, and compulsive disorders, which may have genetic roots in purpose-bred behaviors. Growing community science initiatives aimed at the companion dog population will be well suited to investigating such complex behavioral phenotypes and offer a comparative resource that parallels human genomic initiatives in scale and dimensionality.
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Affiliation(s)
- Kathleen Morrill
- Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
- Vertebrate Genome Biology, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Morningside Graduate School of Biomedical Sciences UMass Chan Medical School, Worcester, MA, USA.
| | - Frances Chen
- Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Vertebrate Genome Biology, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Elinor Karlsson
- Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Vertebrate Genome Biology, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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25
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Handley ED, Russotti J, Ross AJ, Toth SL, Cicchetti D. A person-centered data analytic approach to dopaminergic polygenic moderation of child maltreatment exposure. Dev Psychobiol 2023; 65:e22403. [PMID: 37338249 PMCID: PMC10287038 DOI: 10.1002/dev.22403] [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: 10/11/2022] [Revised: 04/27/2023] [Accepted: 05/03/2023] [Indexed: 06/21/2023]
Abstract
The present study illustrates the utility of latent class analysis, a person-centered data analytic approach, as an innovative method for identifying naturally occurring patterns of polygenic risk, specifically within the dopaminergic system. Moreover, this study tests whether latent classes of polygenic variation moderate the effect of child maltreatment exposure on internalizing symptoms among African ancestry youth. African ancestry youth were selected for this study because youth of color are overrepresented in the child welfare system and because African ancestry individuals are significantly underrepresented in genomics research. Results identified three latent classes of dopaminergic gene variation. Class 1 was marked predominately by homozygous minor alleles, Class 2 was characterized by homozygous major and heterozygous presentations, and Class 3 was marked by heterozygous alleles on the DAT-1 single-nucleotide polymorphisms (SNPs) and a combination of homozygous major and minor alleles on the other SNPs. Results indicated that a greater number of maltreatment subtypes experienced were associated with higher internalizing symptoms only for children with the latent polygenic Class 2 pattern. This latent class was distinctly characterized by more homozygous major or heterozygous allelic presentations along all three DAT-1 SNPs. This significant latent polygenic class by environment interaction was replicated in an independent replication sample. Together, findings suggest that African ancestry children with a pattern of dopaminergic variation characterized by this specific combination of polygenic variation are more vulnerable to developing internalizing symptoms following maltreatment exposure, relative to their peers with other dopamine-related polygenic patterns.
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Affiliation(s)
| | | | | | | | - Dante Cicchetti
- Mt. Hope Family Center, University of Rochester
- University of Minnesota
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26
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Abdulkadir M, Tischfield JA, Heiman GA, Hoekstra PJ, Dietrich A. Polygenic and environmental determinants of tics in the Avon Longitudinal Study of Parents and Children. Am J Med Genet B Neuropsychiatr Genet 2023; 192:73-84. [PMID: 36479979 PMCID: PMC10247895 DOI: 10.1002/ajmg.b.32924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 11/14/2022] [Accepted: 11/22/2022] [Indexed: 12/13/2022]
Abstract
Tourette syndrome (TS) is caused by multiple genetic and environmental factors. Yet, little is known about the interplay of these factors in the occurrence of tics. We investigated whether polygenic risk score (PRS) of TS and pregnancy-related factors together enhance the explained variance of tic occurrence in the Avon Longitudinal Study of Parents and Children (Ncases = 612; Ncontrols = 4,201; 50% male; mean age 13.8 years). We included a cumulative adverse pregnancy risk score, maternal anxiety and depression, and maternal smoking and alcohol use during pregnancy. We investigated possible joint effects of genetic and pregnancy-related risk factors using a multivariable approach, and explored mediation effects between the pregnancy-related risk factors in explaining tic presence. The PRS and the cumulative adverse pregnancy risk score, maternal anxiety, or maternal depression explained significantly more variance of tic presence compared to models including only the PRS. Furthermore, we found that the cumulative adverse pregnancy risk score mediated the association between several pregnancy-related factors (maternal anxiety, depression, and smoking) and tics. The combination of a PRS and pregnancy-related risk factors explained more variance of tics in a general population cohort compared to studying these factors in isolation.
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Affiliation(s)
- Mohamed Abdulkadir
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, The Netherlands
- Rutgers, the State University of New Jersey, Department of Genetics and the Human Genetics Institute of New Jersey, Piscataway, NJ, USA
| | - Jay A. Tischfield
- Rutgers, the State University of New Jersey, Department of Genetics and the Human Genetics Institute of New Jersey, Piscataway, NJ, USA
| | - Gary A. Heiman
- Rutgers, the State University of New Jersey, Department of Genetics and the Human Genetics Institute of New Jersey, Piscataway, NJ, USA
| | - Pieter J. Hoekstra
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, The Netherlands
| | - Andrea Dietrich
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, The Netherlands
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27
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Segura AG, Mezquida G, Martínez-Pinteño A, Gassó P, Rodriguez N, Moreno-Izco L, Amoretti S, Bioque M, Lobo A, González-Pinto A, García-Alcon A, Roldán-Bejarano A, Vieta E, de la Serna E, Toll A, Cuesta MJ, Mas S, Bernardo M. Link between cognitive polygenic risk scores and clinical progression after a first-psychotic episode. Psychol Med 2023; 53:4634-4647. [PMID: 35678455 PMCID: PMC10388335 DOI: 10.1017/s0033291722001544] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 05/05/2022] [Accepted: 05/09/2022] [Indexed: 11/05/2022]
Abstract
BACKGROUND Clinical intervention in early stages of psychotic disorders is crucial for the prevention of severe symptomatology trajectories and poor outcomes. Genetic variability is studied as a promising modulator of prognosis, thus novel approaches considering the polygenic nature of these complex phenotypes are required to unravel the mechanisms underlying the early progression of the disorder. METHODS The sample comprised of 233 first-episode psychosis (FEP) subjects with clinical and cognitive data assessed periodically for a 2-year period and 150 matched controls. Polygenic risk scores (PRSs) for schizophrenia, bipolar disorder, depression, education attainment and cognitive performance were used to assess the genetic risk of FEP and to characterize their association with premorbid, baseline and progression of clinical and cognitive status. RESULTS Schizophrenia, bipolar disorder and cognitive performance PRSs were associated with an increased risk of FEP [false discovery rate (FDR) ⩽ 0.027]. In FEP patients, increased cognitive PRSs were found for FEP patients with more cognitive reserve (FDR ⩽ 0.037). PRSs reflecting a genetic liability for improved cognition were associated with a better course of symptoms, functionality and working memory (FDR ⩽ 0.039). Moreover, the PRS of depression was associated with a worse trajectory of the executive function and the general cognitive status (FDR ⩽ 0.001). CONCLUSIONS Our study provides novel evidence of the polygenic bases of psychosis and its clinical manifestation in its first stage. The consistent effect of cognitive PRSs on the early clinical progression suggests that the mechanisms underlying the psychotic episode and its severity could be partially independent.
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Affiliation(s)
- Alex G. Segura
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Gisela Mezquida
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
| | - Albert Martínez-Pinteño
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Patricia Gassó
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
| | - Natalia Rodriguez
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Lucía Moreno-Izco
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Silvia Amoretti
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Group of Psychiatry, Mental Health and Addictions, Psychiatric Genetics Unit, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Miquel Bioque
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Antonio Lobo
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain
- Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain
| | - Ana González-Pinto
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Hospital Universitario de Alava, Vitoria-Gasteiz, Spain
- Instituto de Investigación Sanitaria Bioaraba, Vitoria-Gasteiz, Spain
- University of the Basque Country, Vizcaya, Spain
| | - Alicia García-Alcon
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
| | - Alexandra Roldán-Bejarano
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Psychiatry Department, Institut d'Investigació Biomèdica-SantPau (IIB-SANTPAU), Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Eduard Vieta
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Elena de la Serna
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
- Department of Child and Adolescent Psychiatry and Psychology, Clínic Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Alba Toll
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institute of Neuropsychiatry and Addiction, Parc de Salut Mar, Barcelona, Spain
- Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Manuel J. Cuesta
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Sergi Mas
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
| | - Miquel Bernardo
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - PEPs Group
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
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Dash GF, Karalunas SL, Kenyon EA, Carter EK, Mooney MA, Nigg JT, Feldstein Ewing SW. Gene-by-Environment Interaction Effects of Social Adversity on Externalizing Behavior in ABCD Youth. Behav Genet 2023; 53:219-231. [PMID: 36795263 PMCID: PMC9933005 DOI: 10.1007/s10519-023-10136-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 02/01/2023] [Indexed: 02/17/2023]
Abstract
This study tested whether multiple domains of social adversity, including neighborhood opportunity/deprivation and life stress, moderate genetic (A), common environmental (C), and unique environmental (E) influences on externalizing behaviors in 760 same-sex twin pairs (332 monozygotic; 428 dizygotic) ages 10-11 from the ABCD Study. Proportion of C influences on externalizing behavior increased at higher neighborhood adversity (lower overall opportunity). A decreased and C and E increased at lower levels of educational opportunity. A increased at lower health-environment and social-economic opportunity levels. For life stress, A decreased and E increased with number of experienced events. Results for educational opportunity and stressful life experiences suggest a bioecological gene-environment interaction pattern such that environmental influences predominate at higher levels of adversity, whereas limited access to healthcare, housing, and employment stability may potentiate genetic liability for externalizing behavior via a diathesis-stress mechanism. More detailed operationalization of social adversity in gene-environment interaction studies is needed.
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Affiliation(s)
- Genevieve F Dash
- Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, 320 S. 6th St. Columbia, 65211, Columbia, MO, USA.
| | - Sarah L Karalunas
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
| | - Emily A Kenyon
- Department of Psychology, University of Rhode Island, Kingston, RI, USA
| | - Emily K Carter
- Department of Psychology, University of Rhode Island, Kingston, RI, USA
| | - Michael A Mooney
- Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Joel T Nigg
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Sarah W Feldstein Ewing
- Department of Psychology, University of Rhode Island, Kingston, RI, USA
- MPI ABCD - Oregon Health & Science University (OHSU) Site, Portland, USA
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29
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Edwards AC, Ohlsson H, Lannoy S, Stephenson M, Crump C, Sundquist J, Kendler KS, Sundquist K. Exposure to alcohol outlets and risk of suicidal behavior in a Swedish cohort of young adults. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2023; 47:930-939. [PMID: 37526582 PMCID: PMC10916709 DOI: 10.1111/acer.15051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/15/2023] [Accepted: 03/01/2023] [Indexed: 08/02/2023]
Abstract
BACKGROUND Greater alcohol accessibility, for example in the form of a high density of alcohol outlets or low alcohol taxation rates, may be associated with increased risk of suicidal behavior. However, most studies have been conducted at the aggregate level, and some have not accounted for potential confounders such as socioeconomic position or neighborhood quality. METHODS In a Swedish cohort of young adults aged 18 to 25, we used logistic regressions to evaluate whether living in a neighborhood that included bars, nightclubs, and/or government alcohol outlets was associated with risk of suicide attempt (SA) or suicide death (SD) during four separate 2-year observation periods. Neighborhoods were defined using pre-established nationwide designations. We conducted combined-sex and sex-stratified analyses, and included as covariates indicators of socioeconomic position, neighborhood deprivation, and aggregate genetic liability to suicidal behavior. RESULTS Risk of SA was increased in some subsamples of individuals living in a neighborhood with a bar or government alcohol outlet (odds ratios [ORs] = 1.05 to 1.15). Risk of SD was also higher among certain subsamples living in a neighborhood with a government outlet (ORs = 1.47 to 1.56), but lower for those living near a bar (ORs = 0.89 to 0.91). Significant results were driven by, but not exclusive to, the male subsample. Individuals with higher aggregate genetic risk for SA were more sensitive to the effects of a neighborhood government alcohol outlet, pooled across observation periods, in analyses of the sexes combined (relative excess risk due to interaction [RERI] = 0.05; 95% confidence intervals [CI] 0.01; 0.09) and in the male subsample (RERI = 0.06; 95% CI 0.001; 0.12). CONCLUSIONS Although effect sizes are small, living in a neighborhood with bars and/or government alcohol outlets may increase suicidal behavior among young adults. Individuals with higher genetic liability for SA are slightly more susceptible to these exposures.
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Affiliation(s)
- Alexis C. Edwards
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Henrik Ohlsson
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Séverine Lannoy
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Mallory Stephenson
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
- Integrative Life Sciences, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Casey Crump
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jan Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Kenneth S. Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
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30
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Peedicayil J. Genome-Environment Interactions and Psychiatric Disorders. Biomedicines 2023; 11:biomedicines11041209. [PMID: 37189827 DOI: 10.3390/biomedicines11041209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 04/08/2023] [Accepted: 04/17/2023] [Indexed: 05/17/2023] Open
Abstract
Environmental factors are known to interact with the genome by altering epigenetic mechanisms regulating gene expression and contributing to the pathogenesis of psychiatric disorders. This article is a narrative review of how the major environmental factors contribute to the pathogenesis of common psychiatric disorders such as schizophrenia, bipolar disorder, major depressive disorder, and anxiety disorder this way. The cited articles were published between 1 January 2000 and 31 December 2022 and were obtained from PubMed and Google Scholar. The search terms used were as follows: gene or genetic; genome; environment; mental or psychiatric disorder; epigenetic; and interaction. The following environmental factors were found to act epigenetically on the genome to influence the pathogenesis of psychiatric disorders: social determinants of mental health, maternal prenatal psychological stress, poverty, migration, urban dwelling, pregnancy and birth complications, alcohol and substance abuse, microbiota, and prenatal and postnatal infections. The article also discusses the ways by which factors such as drugs, psychotherapy, electroconvulsive therapy, and physical exercise act epigenetically to alleviate the symptoms of psychiatric disorders in affected patients. These data will be useful information for clinical psychiatrists and those researching the pathogenesis and treatment of psychiatric disorders.
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Affiliation(s)
- Jacob Peedicayil
- Department of Pharmacology & Clinical Pharmacology, Christian Medical College, Vellore 632 002, India
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31
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Pacella R, Nation A, Mathews B, Scott JG, Higgins DJ, Haslam DM, Dunne MP, Finkelhor D, Meinck F, Erskine HE, Thomas HJ, Malacova E, Lawrence DM, Monks C. Child maltreatment and health service use: findings of the Australian Child Maltreatment Study. Med J Aust 2023; 218 Suppl 6:S40-S46. [PMID: 37004185 PMCID: PMC10952869 DOI: 10.5694/mja2.51892] [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: 08/23/2022] [Revised: 01/16/2023] [Accepted: 01/23/2023] [Indexed: 04/03/2023]
Abstract
OBJECTIVES To examine associations between child maltreatment and health service use, both overall, by type and by the number of types of maltreatment reported. DESIGN, SETTING Cross-sectional, retrospective survey using the Juvenile Victimization Questionnaire-R2: Adapted Version (Australian Child Maltreatment Study); computer-assisted mobile telephone interviews using random digit dialling, Australia, 9 April - 11 October 2021. PARTICIPANTS Australians aged 16 years or more. The target sample size was 8500 respondents: 3500 people aged 16-24 years and 1000 respondents each from the five age groups (25-34, 35-44, 45-54, 55-64, 65 years or more). MAIN OUTCOME MEASURES Self-reported health service use during the past twelve months: hospital admissions, length of stay, and reasons for admission; and numbers of consultations with health care professionals, overall and by type. Associations between maltreatment and health service use are reported as odds ratios adjusted for age group, gender, socio-economic status, financial hardship (childhood and current), and geographic remoteness. RESULTS A total of 8503 participants completed the survey. Respondents who had experienced child maltreatment were significantly more likely than those who had not to report a hospital admission during the preceding twelve months (adjusted odds ratio [aOR], 1.39; 95% confidence interval [CI], 1.16-1.66), particularly admission with a mental disorder (aOR, 2.4; 95% CI, 1.03-5.6). The likelihood of six or more visits to general practitioners (aOR, 2.37; 95% CI, 1.87-3.02) or of a consultation with a mental health nurse (aOR, 2.67; 95% CI, 1.75-4.06), psychologist (aOR, 2.40; 95% CI, 2.00-2.88), or psychiatrist (aOR, 3.02; 95% CI, 2.25-4.04) were each higher for people who reported maltreatment during childhood. People who reported three or more maltreatment types were generally most likely to report greater health service use. CONCLUSIONS Child maltreatment has a major impact on health service use. Early, targeted interventions are vital, not only for supporting children directly, but also for their longer term wellbeing and reducing their health system use throughout life.
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Affiliation(s)
- Rosana Pacella
- Institute for Lifecourse DevelopmentUniversity of GreenwichLondonUnited Kingdom
| | - Alexandra Nation
- Institute for Lifecourse DevelopmentUniversity of GreenwichLondonUnited Kingdom
| | - Ben Mathews
- Queensland University of TechnologyBrisbaneQLD
- Bloomberg School of Public HealthJohns Hopkins UniversityBaltimoreMDUnited States of America
| | - James G Scott
- Child Health Research Centrethe University of QueenslandBrisbaneQLD
- QIMR Berghofer Medical Research InstituteBrisbaneQLD
| | - Daryl J Higgins
- Institute of Child Protection Studies, Australian Catholic UniversityMelbourneVIC
| | - Divna M Haslam
- Queensland University of TechnologyBrisbaneQLD
- The University of QueenslandBrisbaneQLD
| | - Michael P Dunne
- Queensland University of TechnologyBrisbaneQLD
- Institute for Community Health ResearchHue UniversityHue CityVietnam
| | - David Finkelhor
- Crimes against Children Research CenterUniversity of New HampshireDurhamNHUnited States of America
| | - Franziska Meinck
- University of EdinburghEdinburghUnited Kingdom
- North‐West UniversityPotchefstroomSouth Africa
| | - Holly E Erskine
- The University of QueenslandBrisbaneQLD
- Queensland Centre for Mental Health ResearchBrisbaneQLD
| | - Hannah J Thomas
- QIMR Berghofer Medical Research InstituteBrisbaneQLD
- Queensland Centre for Mental Health ResearchBrisbaneQLD
| | - Eva Malacova
- QIMR Berghofer Medical Research InstituteBrisbaneQLD
| | | | - Claire Monks
- Institute for Lifecourse DevelopmentUniversity of GreenwichLondonUnited Kingdom
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Xie T, Schweren LJS, Larsson H, Li L, Du Rietz E, Haavik J, Grimstvedt Kvalvik L, Solberg BS, Klungsøyr K, Snieder H, Hartman CA. Do Poor Diet and Lifestyle Behaviors Modify the Genetic Susceptibility to Impulsivity in the General Population? Nutrients 2023; 15:nu15071625. [PMID: 37049467 PMCID: PMC10096670 DOI: 10.3390/nu15071625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/19/2023] [Accepted: 03/23/2023] [Indexed: 03/30/2023] Open
Abstract
The present study investigated whether an unhealthy diet and other lifestyle behaviors may modify the genetic susceptibility to impulsivity. A total of 33,047 participants (mean age = 42.1 years, 59.8% females) from the Dutch Lifelines cohort were included. Each diet index and other lifestyle behaviors were tested for their interactions on the effect on the attention-deficit/hyperactivity disorder (ADHD) polygenic risk score (PRS) on impulsivity using a linear regression model with adjustment for covariates. The ADHD PRS was significantly associated with impulsivity (B = 0.03 (95% CI: 0.02, 0.04); p = 2.61 × 10−9). A poorer diet, a higher intake of energy, and a higher intake of fat were all associated with higher impulsivity, and a high intake of energy amplified the effect of ADHD PRS on impulsivity (e.g., for the interaction term of ADHD PRS and highest tertile on intake of energy, B = 0.038 (95% CI: 0.014, 0.062); p = 0.002. The other lifestyle factors, namely short and long sleep duration, current and past smoking, higher alcohol intake, and more time spent on moderate-to-vigorous physical activity were associated with higher impulsivity, but no interaction effect was observed. In conclusion, we found that a high intake of energy exacerbated the genetic susceptibility to impulsivity. Our study helps to improve our understanding of the role of diet and genetic factors on impulsivity.
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Affiliation(s)
- Tian Xie
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, The Netherlands
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, The Netherlands
- Correspondence:
| | - Lizanne J. S. Schweren
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, The Netherlands
| | - Henrik Larsson
- School of Medical Sciences, Örebro University, 70172 Örebro, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17165 Stockholm, Sweden
| | - Lin Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17165 Stockholm, Sweden
| | - Ebba Du Rietz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17165 Stockholm, Sweden
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, 5020 Bergen, Norway
- Bergen Center for Brain Plasticity, Division of Psychiatry, Haukeland University Hospital, 5012 Bergen, Norway
| | - Liv Grimstvedt Kvalvik
- Department of Global Public Health and Primary Care, University of Bergen, 5020 Bergen, Norway
| | - Berit Skretting Solberg
- Department of Biomedicine, University of Bergen, 5020 Bergen, Norway
- Child- and Adolescent Psychiatric Outpatient Unit, Hospital Betanien, 5143 Bergen, Norway
| | - Kari Klungsøyr
- Department of Global Public Health and Primary Care, University of Bergen, 5020 Bergen, Norway
- Division of Mental and Physical Health, Norwegian Institute of Public Health, 5015 Bergen, Norway
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, The Netherlands
| | - Catharina A. Hartman
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, The Netherlands
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A comparison of stress reactivity between BTBR and C57BL/6J mice: an impact of early-life stress. Exp Brain Res 2023; 241:687-698. [PMID: 36670311 DOI: 10.1007/s00221-022-06541-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 12/28/2022] [Indexed: 01/21/2023]
Abstract
Early-life stress (ELS) is associated with hypothalamic-pituitary-adrenal (HPA) axis dysregulation and can increase the risk of psychiatric disorders later in life. The aim of this study was to investigate the influence of ELS on baseline HPA axis functioning and on the response to additional stress in adolescent male mice of strains C57BL/6J and BTBR. As a model of ELS, prolonged separation of pups from their mothers (for 3 h once a day: maternal separation [MS]) was implemented. To evaluate HPA axis activity, we assessed serum corticosterone levels and mRNA expression of corticotropin-releasing hormone (Crh) in the hypothalamus, of steroidogenesis genes in adrenal glands, and of an immediate early gene (c-Fos) in both tissues at baseline and immediately after 1 h of restraint stress. HPA axis activity at baseline did not depend on the history of ELS in mice of both strains. After the exposure to the acute restraint stress, C57BL/6J-MS mice showed less pronounced upregulation of Crh and of corticosterone concentration as compared to the control, indicating a decrease in stress reactivity. By contrast, BTBR-MS mice showed stronger upregulation of c-Fos in the hypothalamus and adrenal glands as compared to controls, thus pointing to greater activation of these organs in response to the acute restraint stress. In addition, we noted that BTBR mice are more stress reactive (than C57BL/6J mice) because they exhibited greater upregulation of corticosterone, c-Fos, and Cyp11a1 in response to the acute restraint stress. Taken together, these results indicate strain-specific and situation-dependent effects of ELS on HPA axis functioning and on c-Fos expression.
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Iob E, Ajnakina O, Steptoe A. The interactive association of adverse childhood experiences and polygenic susceptibility with depressive symptoms and chronic inflammation in older adults: a prospective cohort study. Psychol Med 2023; 53:1426-1436. [PMID: 37010219 DOI: 10.1017/s0033291721003007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Adverse childhood experiences (ACEs) and genetic liability are important risk factors for depression and inflammation. However, little is known about the gene-environment (G × E) mechanisms underlying their aetiology. For the first time, we tested the independent and interactive associations of ACEs and polygenic scores of major depressive disorder (MDD-PGS) and C-reactive protein (CRP-PGS) with longitudinal trajectories of depression and chronic inflammation in older adults. METHODS Data were drawn from the English longitudinal study of ageing (N~3400). Retrospective information on ACEs was collected in wave3 (2006/07). We calculated a cumulative risk score of ACEs and also assessed distinct dimensions separately. Depressive symptoms were ascertained on eight occasions, from wave1 (2002/03) to wave8 (2016/17). CRP was measured in wave2 (2004/05), wave4 (2008/09), and wave6 (2012/13). The associations of the risk factors with group-based depressive-symptom trajectories and repeated exposure to high CRP (i.e. ⩾3 mg/L) were tested using multinomial and ordinal logistic regression. RESULTS All types of ACEs were independently associated with high depressive-symptom trajectories (OR 1.44, 95% CI 1.30-1.60) and inflammation (OR 1.08, 95% CI 1.07-1.09). The risk of high depressive-symptom trajectories (OR 1.47, 95% CI 1.28-1.70) and inflammation (OR 1.03, 95% CI 1.01-1.04) was also higher for participants with higher MDD-PGS. G×E analyses revealed that the associations between ACEs and depressive symptoms were larger among participants with higher MDD-PGS (OR 1.13, 95% CI 1.04-1.23). ACEs were also more strongly related to inflammation in participants with higher CRP-PGS (OR 1.02, 95% CI 1.01-1.03). CONCLUSIONS ACEs and polygenic susceptibility were independently and interactively associated with elevated depressive symptoms and chronic inflammation, highlighting the clinical importance of assessing both ACEs and genetic risk factors to design more targeted interventions.
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Affiliation(s)
- Eleonora Iob
- Research Department of Behavioural Science and Health, Institute of Epidemiology and Healthcare, University College London, London, UK
| | - Olesya Ajnakina
- Research Department of Behavioural Science and Health, Institute of Epidemiology and Healthcare, University College London, London, UK
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Andrew Steptoe
- Research Department of Behavioural Science and Health, Institute of Epidemiology and Healthcare, University College London, London, UK
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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: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [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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Savaglio M, Yap MB, O'Donnell R, Skouteris H. Targeted community-based programmes for children's mental health: A systematic review and meta-analysis of the Australian literature. Aust N Z J Psychiatry 2023; 57:197-212. [PMID: 36113092 DOI: 10.1177/00048674221124506] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
OBJECTIVE No synthesis of the Australian evidence regarding targeted prevention and early intervention for mental health concerns among young children exists. This review aimed to (1) describe the types of targeted community-based mental health programmes evaluated in Australia to support children aged 1-9 years exhibiting internalising and/or externalising symptoms and (2) examine their impact on children's internalising and externalising symptoms and disorder diagnosis. METHOD A systematic review and meta-analysis was conducted (PROSPERO: CRD42021255257). Four databases (PsycINFO, PsycArticles, MEDLINE and CINAHL) were searched for Australian studies published in the past 10 years that quantitatively evaluated the impact of a targeted programme on children's mental health. The National Institute of Health Quality Assessment Tools were used to evaluate the study quality. RESULTS Forty-two studies were included; the majority (67%) were medium quality. The mean sample size was 142 (SD = 170), children's average age was 5.78 years (SD = 2.44) and 58% were male. Aboriginal and Torres Strait Islander children were underrepresented. Studies evaluated 16 programmes that targeted (1) externalising symptoms (n = 20 studies, n = 6 programmes), (2) internalising symptoms (n = 14 studies, n = 7 programmes) or (3) both, termed transdiagnostic programmes (n = 8 studies, n = 3 programmes). Externalising programmes achieved a significant moderate mean reduction in externalising behaviours (standardised mean differences = -0.56), internalising programmes yielded a small mean improvement in anxiety symptoms (standardised mean differences = -0.25) and 57% reduced odds of anxiety disorder diagnosis. Evidence supporting transdiagnostic programmes was inconclusive. CONCLUSION Parenting-focused programmes targeting young children's internalising or externalising behaviours have the largest local evidence base supporting their effectiveness. Limitations include a lack of engagement with fathers, triangulation of outcomes, homogeneity and implementation reporting. Greater implementation and evaluation of community-driven integrated and systemic approaches that identify, engage and support Australia's most disadvantaged cohorts of young children and their families are needed.
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Affiliation(s)
- Melissa Savaglio
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Marie Bh Yap
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia.,Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Renee O'Donnell
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Helen Skouteris
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.,Warwick Business School, University of Warwick, Coventry, UK
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Hou Y, Shang M, Yu X, Gu Y, Li H, Lu M, Jiang M, Zhen H, Zhu B, Tao F. Joint effects of recent stressful life events and adverse childhood experiences on perinatal comorbid anxiety and depression. BMC Pregnancy Childbirth 2023; 23:41. [PMID: 36653742 PMCID: PMC9847044 DOI: 10.1186/s12884-023-05375-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 01/11/2023] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Stressful life events (SLEs) and adverse childhood experiences (ACEs) have been reported to be associated with perinatal depression (PND) or perinatal anxiety (PNA) alone; however, in most cases, majority of PND and PNA coexist and could lead to more serious health consequences. The independent effect of recent SLEs and their joint effects with ACEs on perinatal comorbid anxiety and depression (CAD) remain inadequately explored. METHODS Based on a longitudinal study, 1082 participants receiving prenatal care in Ma'anshan, China were included. Women were recruited in the first trimester (T1: ≤14+ 6 weeks) and followed up at 15 ~ 27 weeks (T2), 28 ~ 40 weeks (T3), and postpartum (T4). Depression and anxiety status were assessed at all time points, while recent SLEs and ACEs were measured at T1. Logistic regression was conducted to examine the associations of SLEs with the risks of CAD at different time points, as well as their joint effects with ACEs on CAD. RESULTS Approximately 38.5% of women experienced at least one SLE, which was significantly associated with higher risks of CAD at all time points (p < 0.05). As the number of SLEs increased, the risk of CAD increased (p for trend < 0.05). Specific types of SLEs were associated with CAD in different periods, while only interpersonal events were consistently associated with risks of CAD throughout the whole perinatal period. The joint effects of SLEs with ACEs on CAD were identified throughout the perinatal period, with the highest observed in the first trimester (aOR = 7.47, 95% CI: 3.73-14.95; p for trend < 0.001). CONCLUSION Our study demonstrated independent associations of recent SLEs and their joint effects with ACEs with risks of perinatal CAD. SLEs combined with ACEs should be recognized as a major risk factor for perinatal CAD and managed at the earliest time to prevent and control CAD.
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Affiliation(s)
- Yanyan Hou
- grid.186775.a0000 0000 9490 772XDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Mengqing Shang
- grid.186775.a0000 0000 9490 772XDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Xiayan Yu
- grid.186775.a0000 0000 9490 772XDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Yue Gu
- grid.186775.a0000 0000 9490 772XDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Haiyan Li
- grid.186775.a0000 0000 9490 772XDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Mengjuan Lu
- grid.186775.a0000 0000 9490 772XDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Minmin Jiang
- grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XDepartment of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Hualong Zhen
- grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XDepartment of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Beibei Zhu
- grid.186775.a0000 0000 9490 772XDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China
| | - Fangbiao Tao
- grid.186775.a0000 0000 9490 772XDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, No 81 Meishan Road, 230032 Hefei, Anhui China ,grid.186775.a0000 0000 9490 772XAnhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, 230032 Hefei, Anhui China ,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, 230032 Hefei, Anhui China
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Alonso L, Peeva P, Stasko S, Bader M, Alenina N, Winter Y, Rivalan M. Constitutive depletion of brain serotonin differentially affects rats' social and cognitive abilities. iScience 2023; 26:105998. [PMID: 36798444 PMCID: PMC9926123 DOI: 10.1016/j.isci.2023.105998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 09/30/2022] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
Central serotonin appears a promising transdiagnostic marker of psychiatric disorders and a modulator of some of their key behavioral symptoms. In adult male Tph2 -/- rats, constitutively lacking central serotonin, we tested individual's cognitive, social and non-social abilities and characterized group's social organization under classical and ethological testing conditions. Using unsupervised machine learning, we identified the functions most dependent on serotonin. Although serotonin depletion did not affect cognitive performances in classical testing, in the home-cage it induced compulsive aggression and sexual behavior, hyperactive and hypervigilant stereotyped behavior, reduced self-care and exacerbated corticosterone levels. This profile recalled symptoms of impulse control and anxiety disorders. Serotonin appeared essential for behavioral adaptation to dynamic social environments. Our animal model challenges the essential role of serotonin in decision-making, flexibility, impulsivity, and risk-taking. These findings highlight the importance of studying everyday life functions within the dynamic social living environment to model complexity in animal models.
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Affiliation(s)
- Lucille Alonso
- Humboldt-Universität zu Berlin, Berlin, Germany,Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Polina Peeva
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | | | - Michael Bader
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany,Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Natalia Alenina
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany,Corresponding author
| | - York Winter
- Humboldt-Universität zu Berlin, Berlin, Germany,Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Marion Rivalan
- Humboldt-Universität zu Berlin, Berlin, Germany,Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany,Corresponding author
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Muacevic A, Adler JR, Qureshi D, Saeed H, Nkemjika S. Poorly Managed Stressors Contributing to an Affective Disorder in a High-Performance Athlete: A Case Report. Cureus 2023; 15:e33507. [PMID: 36756010 PMCID: PMC9904424 DOI: 10.7759/cureus.33507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/08/2023] [Indexed: 01/09/2023] Open
Abstract
Recently, there has been an increase in awareness about mental illness, especially among professional athletes. This has brought to focus the important roles that sports psychiatrists and other allied health professionals play in professional sports. It has also exposed the limitations of sports psychiatry, especially the shortage of sports psychiatrists. Professional athletes are subjected to multiple stressors during their careers, resulting in significant mental health outcomes. If not adequately addressed, stress can cause performance slumps and poorer outcomes, which in turn exacerbates stress in a vicious cycle. We present the case of a former male athlete with multiple physical, somatic, and psychosocial stressors that predisposed him to develop mental illness. This case highlights the potential consequences of a lack of early recognition and management of physical and psychosocial stressors in athletes, which can contribute to psychological illness and potentially lead to adverse medical outcomes such as repeat hospitalization and homelessness.
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40
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Prevalence of Common Alleles of Some Stress Resilience Genes among Adolescents Born in Different Periods Relative to the Socioeconomic Crisis of the 1990s in Russia. Curr Issues Mol Biol 2022; 45:51-65. [PMID: 36661490 PMCID: PMC9857244 DOI: 10.3390/cimb45010004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/13/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022] Open
Abstract
Social stress is common among people and is considered one of the causes of the declining birth rate. Predisposition to stress and stress-induced disorders is largely determined genetically. We hypothesized that due to differences in stress resistance, carriers of different genetic variants of genes associated with stress resilience and stress-induced diseases may have dissimilar numbers of offspring under conditions of long-term social stress. To test this hypothesis, a comparative analysis of frequencies of seven common polymorphic regions [exon 3 variable number of tandem repeats (VNTR) of the DRD4 gene, rs4680 of COMT, STin2 VNTR and the 5-HTTLPR (rs774676466) insertion/deletion polymorphism of SLC6A4, rs4570625 of TPH2, rs6265 of BDNF, and rs258747 of NR3C1] was performed on standardized groups of randomly selected adolescents born before, during, and after severe socioeconomic deprivation (the crisis of the 1990s in Russia). There were significant differences in frequencies of "long" alleles of the DRD4 gene (p = 0.020, χ2 = 5.492) and rs4680 (p = 0.022, χ2 = 5.289) in the "crisis" group as compared to the combined "noncrisis" population. It is possible that the dopaminergic system had an impact on the successful adaptation of a person to social stress.
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Tonini E, Watkeys O, Quidé Y, Whitford TJ, Cairns MJ, Green MJ. Polygenic risk for schizophrenia as a moderator of associations between childhood trauma and schizotypy. Prog Neuropsychopharmacol Biol Psychiatry 2022; 119:110612. [PMID: 35961623 DOI: 10.1016/j.pnpbp.2022.110612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 08/01/2022] [Accepted: 08/06/2022] [Indexed: 10/15/2022]
Abstract
Recent evidence shows that genetic and environmental risk factors for psychotic disorders are associated with higher levels of schizotypy (or psychosis proneness) in the general population. However, little is known about how these risk factors interact. We specifically examined whether genetic loading for schizophrenia moderates the association between childhood trauma severity and schizotypy. Schizotypy was measured using the Schizotypal Personality Questionnaire (SPQ), and childhood trauma severity was measured with the Childhood Trauma Questionnaire (CTQ) among a total of 168 participants (comprising 51 healthy individuals, 56 diagnosed with schizophrenia, and 61 with bipolar disorder). Polygenic risk scores (PRS) for schizophrenia were calculated for all participants and examined as a potential moderator of associations between total scores on the CTQ and schizotypy total scores and dimensions (i.e., cognitive-perceptual, interpersonal, disorganised). Multiple linear regression models revealed associations between childhood trauma and all dimensions of schizotypy, but no associations between PRS and schizotypy. A significant interaction between PRS and childhood trauma was evident for the interpersonal and disorganised dimensions of schizotypy, as well as the total score, reflecting positive associations between childhood trauma severity and these two schizotypal dimensions, only for individuals with low or average PRS for schizophrenia. This suggests that trauma may be able to increase risk for psychosis independently of any genetic vulnerability. The present findings are consistent with the idea of several risk pathways for the development of psychotic disorders.
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Affiliation(s)
- Emiliana Tonini
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales (UNSW), Kensington, NSW, Australia; Neuroscience Research Australia (NeuRA), Randwick, NSW, Australia
| | - Oliver Watkeys
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales (UNSW), Kensington, NSW, Australia; Neuroscience Research Australia (NeuRA), Randwick, NSW, Australia
| | - Yann Quidé
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales (UNSW), Kensington, NSW, Australia; Neuroscience Research Australia (NeuRA), Randwick, NSW, Australia; School of Psychology, University of New South Wales (UNSW), Kensington, NSW, Australia
| | - Thomas J Whitford
- School of Psychology, University of New South Wales (UNSW), Kensington, NSW, Australia
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Melissa J Green
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales (UNSW), Kensington, NSW, Australia; Neuroscience Research Australia (NeuRA), Randwick, NSW, Australia.
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42
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Dong Q, Zhou L, Wang W, Wei X, Pluess M, Ma X. Development and Validation of the Chinese Version of the Highly Sensitive Child Scale: Understanding environmental sensitivity and depressive symptoms in adolescents. Front Psychiatry 2022; 13:999150. [PMID: 36545039 PMCID: PMC9760681 DOI: 10.3389/fpsyt.2022.999150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022] Open
Abstract
Background Environmental sensitivity (ES) is considered a significant personality factor in the development and maintenance of depressive symptoms in adolescents. However, a clear instrument that can capture ES in Chinese adolescents is lacking. The current study aimed to investigate the psychometric properties of a Chinese version of the Highly Sensitive Child (HSC) Scale for assessing adolescent ES, and explore the potential moderation effect of ES on relationships between maternal behaviors and adolescent depressive symptoms. Methods In total, 2,166 students from four middle and high schools and 105 depressed adolescents completed measurements of environmental sensitivity, maternal behaviors, depressive emotions, sleep duration, and academic performance. Results First, exploratory factor and confirmatory factor analyses indicated that the HSC scale had a good model fit with the bifactor construct, total scale reliability was adequate-good, and measurement invariances across genders and different samples were supported. Furthermore, the results confirmed that the relationship between maternal behaviors and adolescent depressive symptoms had small effects. Compared to low environmentally sensitive adolescents, high environmentally sensitive adolescents exhibited less depressive emotions and better academic performance in the context of high-quality maternal behaviors. Low-quality maternal behaviors significantly predicted increased depressive emotions and worse academic performance in adolescents when environmental sensitivity was high. Moreover, on the contrary, maternal behaviors did not influence depressive emotions and academic performance in adolescents who were less sensitive to their environment. The relationship between maternal behaviors and adolescent depressive symptoms is influenced by different levels of environmental sensitivity. Conclusion Our findings support the HSC scale as a comprehensive and psychometrically robust tool to measure ES in Chinese adolescents. In addition, the present study clarifies the moderating role of environmental sensitivity underlying the relationship between maternal behaviors and adolescent depressive symptoms. It is important to consider the role of ES in prevention and intervention strategies targeting adolescent depressive symptoms.
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Affiliation(s)
- Qian Dong
- Department of Psychiatry, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Lina Zhou
- Department of Psychiatry, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Wei Wang
- Department of Psychiatry, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Xin Wei
- Xi’an No.3 Middle School, Xi’an, Shaanxi, China
| | - Michael Pluess
- Department of Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom
- Centre for Economic Performance, London School of Economics, London, United Kingdom
| | - Xiancang Ma
- Department of Psychiatry, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
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Dick DM. The Promise and Peril of Genetics. CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE 2022; 31:480-485. [PMID: 36591341 PMCID: PMC9802013 DOI: 10.1177/09637214221112041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Human genetics is advancing at an unprecedented pace. Improvements in genotyping technology and rapidly falling costs have accelerated gene discovery. We can now comprehensively scan the genome, testing variation across millions of genetic markers, to identify specific variants associated with any outcome of interest. Large consortia consisting of hundreds of scientists are analyzing data from hundreds of thousands to millions of individuals. Multivariate methods now enable us to identify genes involved in underlying processes, to complement studies focused on specific disorders or traits. There has been an exponential increase in use of direct-to-consumer genetic feedback platforms. These advances are poised to have a widespread effect on medicine and society. However, with such rapid progress will come ethical, social, and legal challenges. Among those challenges is the need for increased efforts to enhance public understanding of the ways genes contribute to complex behavioral outcomes, and for increased diversity in the field of genetics to ensure that all people benefit from advances. Psychologists can play an important role in addressing the inevitable questions that will arise as genetics increasingly becomes mainstream.
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Affiliation(s)
- Danielle M. Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Rutgers University
- Rutgers Addiction Research Center, Rutgers University
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Genetic associations with resilience to potentially traumatic events and vantage sensitivity to social support. Arch Psychiatr Nurs 2022; 40:147-157. [PMID: 36064238 DOI: 10.1016/j.apnu.2022.07.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 05/30/2022] [Accepted: 07/03/2022] [Indexed: 11/21/2022]
Abstract
INTRODUCTION Stress responses and mental health outcomes greatly vary when individuals are exposed to potentially traumatic events (PTEs). The Differential Susceptibility Model (DSM) (Pluess, 2015) suggests individual differences in stress responses are influenced by gene-environment interactions, with genes conferring reactivity. While individuals can be resilient (or vulnerable) to PTEs, they can also have vantage sensitivity (or resistance) to social support. This study examined whether selected genotypes moderated the effect of PTEs and social support on mental health. METHODS This cross-sectional candidate gene study included 450 college students (M age = 20.4, 79.3 % women) who provided buccal cells for genotyping and completed measures of psychosocial variables. DNA was genotyped for 12 genetic variants. RESULTS Hierarchical regression revealed that the Mental Health Inventory (MHI) was associated with the Trauma History Questionnaire (THQ), rs1800795 in IL-6, and THQ × rs1800795 [R2 = 0.10, F(3, 418) = 15.68, p < .01]. The MHI was associated with the Social Support Survey (SSS), rs4680 in COMT, and SSS × rs4680 [R2 = 0.24, F(3, 429) = 44.19, p < .01]. Only THQ and SSS survived multiple testing corrections. DISCUSSION Findings partially support the DSM that the G/G genotype of rs1800795 in IL-6 is associated with resilience to PTEs, and the Met/Met genotype of rs4680 in COMT is associated with vantage sensitivity to social support. Limitations include cross-sectional design, limited PTE measurement, small convenience sample, and noncorrection for multiple significance test. Clinicians need to view resilience holistically and understand resilience is associated with psychosocial and genetic factors.
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Genetic and psychosocial stressors have independent effects on the level of subclinical psychosis: findings from the multinational EU-GEI study. Epidemiol Psychiatr Sci 2022; 31:e68. [PMID: 36165168 PMCID: PMC9533114 DOI: 10.1017/s2045796022000464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
AIMS Gene x environment (G×E) interactions, i.e. genetic modulation of the sensitivity to environmental factors and/or environmental control of the gene expression, have not been reliably established regarding aetiology of psychotic disorders. Moreover, recent studies have shown associations between the polygenic risk scores for schizophrenia (PRS-SZ) and some risk factors of psychotic disorders, challenging the traditional gene v. environment dichotomy. In the present article, we studied the role of GxE interaction between psychosocial stressors (childhood trauma, stressful life-events, self-reported discrimination experiences and low social capital) and the PRS-SZ on subclinical psychosis in a population-based sample. METHODS Data were drawn from the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study, in which subjects without psychotic disorders were included in six countries. The sample was restricted to European descendant subjects (n = 706). Subclinical dimensions of psychosis (positive, negative, and depressive) were measured by the Community Assessment of Psychic Experiences (CAPE) scale. Associations between the PRS-SZ and the psychosocial stressors were tested. For each dimension, the interactions between genes and environment were assessed using linear models and comparing explained variances of 'Genetic' models (solely fitted with PRS-SZ), 'Environmental' models (solely fitted with each environmental stressor), 'Independent' models (with PRS-SZ and each environmental factor), and 'Interaction' models (Independent models plus an interaction term between the PRS-SZ and each environmental factor). Likelihood ration tests (LRT) compared the fit of the different models. RESULTS There were no genes-environment associations. PRS-SZ was associated with positive dimensions (β = 0.092, R2 = 7.50%), and most psychosocial stressors were associated with all three subclinical psychotic dimensions (except social capital and positive dimension). Concerning the positive dimension, Independent models fitted better than Environmental and Genetic models. No significant GxE interaction was observed for any dimension. CONCLUSIONS This study in subjects without psychotic disorders suggests that (i) the aetiological continuum hypothesis could concern particularly the positive dimension of subclinical psychosis, (ii) genetic and environmental factors have independent effects on the level of this positive dimension, (iii) and that interactions between genetic and individual environmental factors could not be identified in this sample.
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Zhang H, Khan A, Rzhetsky A. Gene-environment interactions explain a substantial portion of variability of common neuropsychiatric disorders. Cell Rep Med 2022; 3:100736. [PMID: 36070757 PMCID: PMC9512674 DOI: 10.1016/j.xcrm.2022.100736] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 11/28/2021] [Accepted: 08/12/2022] [Indexed: 11/30/2022]
Abstract
In complex diseases, the phenotypic variability can be explained by genetic variation (G), environmental stimuli (E), and interaction of genetic and environmental factors (G-by-E effects), among which the contribution G-by-E remains largely unknown. In this study, we focus on ten major neuropsychiatric disorders using data for 138,383 United States families with 404,475 unique individuals. We show that, while gene-environment interactions account for only a small portion of the total phenotypic variance for a subset of disorders (depression, adjustment disorder, substance abuse), they explain a rather large portion of the phenotypic variation of the remaining disorders: over 20% for migraine and close to or over 30% for anxiety/phobic disorder, attention-deficit/hyperactivity disorder, recurrent headaches, sleep disorders, and post-traumatic stress disorder. In this study, we have incorporated—in the same analysis—clinical data, family pedigrees, the spatial distribution of individuals, their socioeconomic and demographic confounders, and a collection of environmental measurements. G-by-E interactions contribute to the etiology of neuropsychiatric disorders Environmental quality is associated with the risk of neuropsychiatric disorders Geographic locations explain a part of variability of neuropsychiatric disorders Identifying specific G-by-E interactions might be the future of personalized medicine
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Affiliation(s)
- Hanxin Zhang
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA; Department of Medicine, Institute of Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Atif Khan
- Department of Medicine, Institute of Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Andrey Rzhetsky
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA; Department of Medicine, Institute of Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA; Department of Human Genetics and Committee on Quantitative Methods in Social, Behavioral, and Health Sciences, The University of Chicago, Chicago, IL 60637, USA.
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Anxiolytic Effect of Carvedilol in Chronic Unpredictable Stress Model. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:6906722. [PMID: 36035219 PMCID: PMC9417788 DOI: 10.1155/2022/6906722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 07/13/2022] [Accepted: 07/25/2022] [Indexed: 11/18/2022]
Abstract
Anxiety disorders are the most prevalent psychiatric disorders being also a comorbid state of other diseases. We aimed to evaluate the anxiolytic-like effects of carvedilol (CVD), a drug used to treat high blood pressure and heart failure with potent antioxidant effects, in animals exposed to chronic unpredictable stress (CUS). To do this, female Swiss mice were exposed to different stressors for 21 days. Between days 15 and 21, the animals received oral CVD (5 or 10 mg/kg) or the antidepressant desvenlafaxine (DVS 10 mg/kg). On the 22nd day, behavioral tests were conducted to evaluate locomotor activity (open field) and anxiety-like alterations (elevated plus-maze—EPM and hole board—HB tests). After behavioral determinations, the animals were euthanized, and the adrenal gland, blood and brain areas, prefrontal cortex (PFC), and hippocampus were removed for biochemical analysis. CUS reduced the crossings while increased rearing and grooming, an effect reversed by both doses of CVD and DVS. CUS decreased the number of entries and permanence time in the open arms of the EPM, while all treatments reversed this effect. CUS reduced the number of head dips in the HB, an effect reversed by CVD. The CUS reduced weight gain, while only CVD5 reversed this effect. A reduction in the cortical layer size of the adrenal gland was observed in stressed animals, which CVD reversed. Increased myeloperoxidase activity (MPO) and interferon-γ (IFN-γ), as well as reduction of interleukin-4 (IL-4) induced by CUS, were reversed by CVD. DVS and CVD increased IL-6 in both brain areas. In the hippocampus, DVS caused an increase in IFN-γ. Our data show that CVD presents an anxiolytic effect partially associated with immune-inflammatory mechanism regulation.
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Langley K, Martin J, Thapar A. Genetics of Attention-Deficit Hyperactivity Disorder. Curr Top Behav Neurosci 2022; 57:243-268. [PMID: 35538303 DOI: 10.1007/7854_2022_338] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Attention-Deficit Hyperactivity Disorder (ADHD) has long been recognized as being a highly heritable condition and our understanding of the genetic contributions to ADHD has grown over the past few decades. This chapter will discuss the studies that have examined its heritability and the efforts to identify specific genetic risk-variants at the molecular genetic level. We outline the various techniques that have been used to characterize genetic contributions to ADHD, describing what we have learnt so far, what there is still to learn and the methodologies that can be used to further our knowledge. In doing so we will discuss research into rare and common genetic variants, polygenic risk scores, and gene-environment interplay, while also describing what genetic studies have revealed about the biological processes involved in ADHD and what they have taught us about the overlap between ADHD and other psychiatric and somatic disorders. Finally, we will discuss the strengths and limitations of the current methodologies and clinical implications of genetic research to date.
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Affiliation(s)
- Kate Langley
- School of Psychology, Cardiff University, Cardiff, UK. .,MRC Centre for Psychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.
| | - Joanna Martin
- MRC Centre for Psychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.,Division of Psychological Medicine, School of Medicine, Cardiff University, Cardiff, UK.,Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
| | - Anita Thapar
- MRC Centre for Psychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.,Division of Psychological Medicine, School of Medicine, Cardiff University, Cardiff, UK.,Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
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49
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Kanarik M, Grimm O, Mota NR, Reif A, Harro J. ADHD co-morbidities: A review of implication of gene × environment effects with dopamine-related genes. Neurosci Biobehav Rev 2022; 139:104757. [PMID: 35777579 DOI: 10.1016/j.neubiorev.2022.104757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 06/25/2022] [Accepted: 06/26/2022] [Indexed: 02/07/2023]
Abstract
ADHD is a major burden in adulthood, where co-morbid conditions such as depression, substance use disorder and obesity often dominate the clinical picture. ADHD has substantial shared heritability with other mental disorders, contributing to comorbidity. However, environmental risk factors exist but their interaction with genetic makeup, especially in relation to comorbid disorders, remains elusive. This review for the first time summarizes present knowledge on gene x environment (GxE) interactions regarding the dopamine system. Hitherto, mainly candidate (GxE) studies were performed, focusing on the genes DRD4, DAT1 and MAOA. Some evidence suggest that the variable number tandem repeats in DRD4 and MAOA may mediate GxE interactions in ADHD generally, and comorbid conditions specifically. Nevertheless, even for these genes, common variants are bound to suggest risk only in the context of gender and specific environments. For other polymorphisms, evidence is contradictory and less convincing. Particularly lacking are longitudinal studies testing the interaction of well-defined environmental with polygenic risk scores reflecting the dopamine system in its entirety.
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Affiliation(s)
- Margus Kanarik
- Chair of Neuropsychopharmacology, Institute of Chemistry, University of Tartu, Ravila 14A Chemicum, 50411 Tartu, Estonia
| | - Oliver Grimm
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - Nina Roth Mota
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - Jaanus Harro
- Chair of Neuropsychopharmacology, Institute of Chemistry, University of Tartu, Ravila 14A Chemicum, 50411 Tartu, Estonia; Psychiatry Clinic, North Estonia Medical Centre, Paldiski Road 52, 10614 Tallinn, Estonia.
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50
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Ortega MA, Fraile-Martínez Ó, García-Montero C, Alvarez-Mon MA, Lahera G, Monserrat J, Llavero-Valero M, Mora F, Rodríguez-Jiménez R, Fernandez-Rojo S, Quintero J, Alvarez De Mon M. Nutrition, Epigenetics, and Major Depressive Disorder: Understanding the Connection. Front Nutr 2022; 9:867150. [PMID: 35662945 PMCID: PMC9158469 DOI: 10.3389/fnut.2022.867150] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 04/19/2022] [Indexed: 12/12/2022] Open
Abstract
Major depressive disorder (MDD) is a complex, multifactorial disorder of rising prevalence and incidence worldwide. Nearly, 280 million of people suffer from this leading cause of disability in the world. Moreover, patients with this condition are frequently co-affected by essential nutrient deficiency. The typical scene with stress and hustle in developed countries tends to be accompanied by eating disorders implying overnutrition from high-carbohydrates and high-fat diets with low micronutrients intake. In fact, currently, coronavirus disease 2019 (COVID-19) pandemic has drawn more attention to this underdiagnosed condition, besides the importance of the nutritional status in shaping immunomodulation, in which minerals, vitamins, or omega 3 polyunsaturated fatty acids (ω-3 PUFA) play an important role. The awareness of nutritional assessment is greater and greater in the patients with depression since antidepressant treatments have such a significant probability of failing. As diet is considered a crucial environmental factor, underlying epigenetic mechanisms that experience an adaptation or consequence on their signaling and expression mechanisms are reviewed. In this study, we included metabolic changes derived from an impairment in cellular processes due to lacking some essential nutrients in diet and therefore in the organism. Finally, aspects related to nutritional interventions and recommendations are also addressed.
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Affiliation(s)
- Miguel A. Ortega
- Department of Medicine and Medical Specialities, University of Alcala, Alcalá de Henares, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
- Cancer Registry and Pathology Department, Hospital Universitario Principe de Asturias, Alcalá de Henares, Spain
- *Correspondence: Miguel A. Ortega
| | - Óscar Fraile-Martínez
- Department of Medicine and Medical Specialities, University of Alcala, Alcalá de Henares, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
| | - Cielo García-Montero
- Department of Medicine and Medical Specialities, University of Alcala, Alcalá de Henares, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
| | - Miguel Angel Alvarez-Mon
- Department of Medicine and Medical Specialities, University of Alcala, Alcalá de Henares, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
| | - Guillermo Lahera
- Department of Medicine and Medical Specialities, University of Alcala, Alcalá de Henares, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
- Psychiatry Service, Center for Biomedical Research in the Mental Health Network, University Hospital Príncipe de Asturias, Alcalá de Henares, Spain
| | - Jorge Monserrat
- Department of Medicine and Medical Specialities, University of Alcala, Alcalá de Henares, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
| | - Maria Llavero-Valero
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
| | - Fernando Mora
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
- Department of Legal Medicine and Psychiatry, Complutense University, Madrid, Spain
| | - Roberto Rodríguez-Jiménez
- Department of Legal Medicine and Psychiatry, Complutense University, Madrid, Spain
- Institute for Health Research 12 de Octubre Hospital, (Imas 12)/CIBERSAM (Biomedical Research Networking Centre in Mental Health), Madrid, Spain
| | - Sonia Fernandez-Rojo
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
- Department of Legal Medicine and Psychiatry, Complutense University, Madrid, Spain
| | - Javier Quintero
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
- Department of Legal Medicine and Psychiatry, Complutense University, Madrid, Spain
| | - Melchor Alvarez De Mon
- Department of Medicine and Medical Specialities, University of Alcala, Alcalá de Henares, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
- Immune System Diseases-Rheumatology, Oncology Service an Internal Medicine, University Hospital Príncipe de Asturias, (CIBEREHD), Alcalá de Henares, Spain
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