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Sefik E, Duan K, Li Y, Sholar B, Evans L, Pincus J, Ammar Z, Murphy MM, Klaiman C, Saulnier CA, Pulver SL, Goldman-Yassen AE, Guo Y, Walker EF, Li L, Mulle JG, Shultz S. Structural deviations of the posterior fossa and the cerebellum and their cognitive links in a neurodevelopmental deletion syndrome. Mol Psychiatry 2024:10.1038/s41380-024-02584-8. [PMID: 38744992 DOI: 10.1038/s41380-024-02584-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 04/16/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024]
Abstract
High-impact genetic variants associated with neurodevelopmental disorders provide biologically-defined entry points for mechanistic investigation. The 3q29 deletion (3q29Del) is one such variant, conferring a 40-100-fold increased risk for schizophrenia, as well as high risk for autism and intellectual disability. However, the mechanisms leading to neurodevelopmental disability remain largely unknown. Here, we report the first in vivo quantitative neuroimaging study in individuals with 3q29Del (N = 24) and neurotypical controls (N = 1608) using structural MRI. Given prior radiology reports of posterior fossa abnormalities in 3q29Del, we focused our investigation on the cerebellum and its tissue-types and lobules. Additionally, we compared the prevalence of cystic/cyst-like malformations of the posterior fossa between 3q29Del and controls and examined the association between neuroanatomical findings and quantitative traits to probe gene-brain-behavior relationships. 3q29Del participants had smaller cerebellar cortex volumes than controls, before and after correction for intracranial volume (ICV). An anterior-posterior gradient emerged in finer grained lobule-based and voxel-wise analyses. 3q29Del participants also had larger cerebellar white matter volumes than controls following ICV-correction and displayed elevated rates of posterior fossa arachnoid cysts and mega cisterna magna findings independent of cerebellar volume. Cerebellar white matter and subregional gray matter volumes were associated with visual-perception and visual-motor integration skills as well as IQ, while cystic/cyst-like malformations yielded no behavioral link. In summary, we find that abnormal development of cerebellar structures may represent neuroimaging-based biomarkers of cognitive and sensorimotor function in 3q29Del, adding to the growing evidence identifying cerebellar pathology as an intersection point between syndromic and idiopathic forms of neurodevelopmental disabilities.
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Affiliation(s)
- Esra Sefik
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Kuaikuai Duan
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Yiheng Li
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Brittney Sholar
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Lindsey Evans
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Jordan Pincus
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Zeena Ammar
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Melissa M Murphy
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Cheryl Klaiman
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Celine A Saulnier
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Neurodevelopmental Assessment & Consulting Services, Atlanta, GA, USA
| | - Stormi L Pulver
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Adam E Goldman-Yassen
- Department of Radiology, Children's Healthcare of Atlanta, Atlanta, GA, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Ying Guo
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Longchuan Li
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Jennifer G Mulle
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA.
| | - Sarah Shultz
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA.
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Schmilovich Z, Bourque VR, Douard E, Huguet G, Poulain C, Ross JP, Alipour P, Castonguay CÉ, Younis N, Jean-Louis M, Saci Z, Pausova Z, Paus T, Schuman G, Porteous D, Davies G, Redmond P, Harris SE, Deary IJ, Whalley H, Hayward C, Dion PA, Jacquemont S, Rouleau GA. Copy-number variants and polygenic risk for intelligence confer risk for autism spectrum disorder irrespective of their effects on cognitive ability. Front Psychiatry 2024; 15:1369767. [PMID: 38751416 PMCID: PMC11094536 DOI: 10.3389/fpsyt.2024.1369767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 04/05/2024] [Indexed: 05/18/2024] Open
Abstract
Introduction Rare copy number variants (CNVs) and polygenic risk for intelligence (PRS-IQ) both confer susceptibility for autism spectrum disorder (ASD) but have opposing effects on cognitive ability. The field has struggled to disentangle the effects of these two classes of genomic variants on cognitive ability from their effects on ASD susceptibility, in part because previous studies did not include controls with cognitive measures. We aim to investigate the impact of these genomic variants on ASD risk while adjusting for their known effects on cognitive ability. Methods In a cohort of 8,426 subjects with ASD and 169,804 controls with cognitive assessments, we found that rare coding CNVs and PRS-IQ increased ASD risk, even after adjusting for their effects on cognitive ability. Results Bottom decile PRS-IQ and CNVs both decreased cognitive ability but had opposing effects on ASD risk. Models combining both classes of variants showed that the effects of rare CNVs and PRS-IQ on ASD risk and cognitive ability were largely additive, further suggesting that susceptibility for ASD is conferred independently from its effects on cognitive ability. Despite imparting mostly additive effects on ASD risk, rare CNVs and PRS-IQ showed opposing effects on core and associated features and developmental history among subjects with ASD. Discussion Our findings suggest that cognitive ability itself may not be the factor driving the underlying liability for ASD conferred by these two classes of genomic variants. In other words, ASD risk and cognitive ability may be two distinct manifestations of CNVs and PRS-IQ. This study also highlights the challenge of understanding how genetic risk for ASD maps onto its dimensional traits.
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Affiliation(s)
- Zoe Schmilovich
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
| | - Vincent-Raphaël Bourque
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Elise Douard
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Guillaume Huguet
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
| | - Cécile Poulain
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Jay P. Ross
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
| | - Paria Alipour
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
| | - Charles-Étienne Castonguay
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
| | - Nadine Younis
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Martineau Jean-Louis
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
| | - Zohra Saci
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Tomas Paus
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Departments of Psychiatry of Neuroscience, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Gunter Schuman
- Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - David Porteous
- Lothian Birth Cohorts Group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Gail Davies
- Lothian Birth Cohorts Group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Paul Redmond
- Lothian Birth Cohorts Group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Sarah E. Harris
- Lothian Birth Cohorts Group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Ian J. Deary
- Lothian Birth Cohorts Group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Heather Whalley
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Caroline Hayward
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Patrick A. Dion
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
| | - Sébastien Jacquemont
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Guy A. Rouleau
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
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Tustison NJ, Yassa MA, Rizvi B, Cook PA, Holbrook AJ, Sathishkumar MT, Tustison MG, Gee JC, Stone JR, Avants BB. ANTsX neuroimaging-derived structural phenotypes of UK Biobank. Sci Rep 2024; 14:8848. [PMID: 38632390 PMCID: PMC11024129 DOI: 10.1038/s41598-024-59440-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 04/10/2024] [Indexed: 04/19/2024] Open
Abstract
UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem. This includes previously established cortical and subcortical measurements defined, in part, based on the Desikan-Killiany-Tourville atlas. Also included are morphological measurements from two recent developments: medial temporal lobe parcellation of hippocampal and extra-hippocampal regions in addition to cerebellum parcellation and thickness based on the Schmahmann anatomical labeling. Through predictive modeling, we assess the clinical utility of these IDP measurements, individually and in combination, using commonly studied phenotypic correlates including age, fluid intelligence, numeric memory, and several other sociodemographic variables. The predictive accuracy of these IDP-based models, in terms of root-mean-squared-error or area-under-the-curve for continuous and categorical variables, respectively, provides comparative insights between software libraries as well as potential clinical interpretability. Results demonstrate varied performance between package-based IDP sets and their combination, emphasizing the need for careful consideration in their selection and utilization.
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Affiliation(s)
- Nicholas J Tustison
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA.
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA.
| | - Michael A Yassa
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Batool Rizvi
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Philip A Cook
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew J Holbrook
- Department of Biostatistics, University of California, Los Angeles, CA, USA
| | | | | | - James C Gee
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - James R Stone
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Brian B Avants
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
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Ren Z, Wesselius A, Stehouwer CDA, Brouwers MCGJ. Relationship between educational attainment and non-alcoholic fatty liver disease: A two-sample Mendelian randomization study. Dig Liver Dis 2024; 56:565-570. [PMID: 38104027 DOI: 10.1016/j.dld.2023.11.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/28/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Observational studies have identified an inverse association between education and non-alcoholic fatty liver disease (NAFLD). However, it is not possible to establish causality for this relationship. AIMS To gain more insight into the causal nature of the relationship between education and NAFLD. METHODS We performed two-sample Mendelian randomization (MR) analyses using summary-level, large-scale datasets to study the association of genetically predicted educational attainment (n = 1271 genetic instruments, obtained from 1,131,881 participants) with risk of NAFLD (i.e., liver fat [n = 32,858 participants] and electronic health record (EHR)-based NAFLD [n = 778,614 participants]). In sensitivity analyses, educational attainment was replaced by three education-related traits (i.e., genetically predicted cognition, math ability and highest math). RESULTS Inverse-variance weighted method showed a statistically significant association between genetically predicted educational attainment and liver fat (beta: -0.251, 95%CI: -0.305; -0.198) and EHR-based NAFLD (OR: 0.609, 95%CI: 0.547; 0.677). MR-Egger regression did not show statistically significant intercepts. Similar findings were obtained when other MR tests were used or when educational attainment was replaced by education-related traits. CONCLUSIONS This study suggests a causal, protective effect of higher education on NAFLD risk. Societal interventions targeted at people with low education are needed to alleviate the burden of NAFLD.
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Affiliation(s)
- Zhewen Ren
- Department of Internal Medicine, Division of Endocrinology and Metabolic Diseases, Maastricht University Medical Center, Maastricht, the Netherlands; Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands; NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
| | - Anke Wesselius
- NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands; Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
| | - Coen D A Stehouwer
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands; Department of Internal Medicine, Division of General Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Martijn C G J Brouwers
- Department of Internal Medicine, Division of Endocrinology and Metabolic Diseases, Maastricht University Medical Center, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands; CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands.
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Hur YM. Relationship between cognitive ability and emotional problems in the context of poverty: a Nigerian adolescent twin study. Eur Child Adolesc Psychiatry 2024; 33:1103-1111. [PMID: 37237243 DOI: 10.1007/s00787-023-02230-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 05/11/2023] [Indexed: 05/28/2023]
Abstract
Although previous studies have identified negative relationships between cognitive ability and emotional problems (EP), mechanism explaining these relationships remained unclear. This study evaluated two explanatory models using bivariate moderation model-fitting analysis in a twin design. The resilience model suggests that high cognitive ability decreases the risk of EP in adverse settings, and the scarring model suggests that EP symptoms lead to persistent cognitive deficits following onset. The Standard Progressive Matrices Plus (SPM) and EP scale were administered to a sample of 3,202 twins (mean age = 14.62 ± 1.74 years) attending public schools in Nigeria. The results of bivariate moderation model-fitting analyses only supported the resilience model. Moderation effects were not significant in the scarring model when genetic and environmental influences were incorporated. The best-fitting bivariate moderation model assuming the resilience model yielded a genetic correlation of - 0.57 (95% CI = - 0.40, - 0.84) with no significant environmental correlations. Moreover, the SPM moderated the environmental, not genetic, influences on EP, such that environmental influences were strong when protective factors were absent (low SPM) and weak when these were present (high SPM). These results indicate the need to develop targeted prevention and intervention strategies for EP in adolescents displaying low cognitive ability in deprived settings.
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Affiliation(s)
- Yoon-Mi Hur
- Kookmin Twin Research Institute, General College of Education, Kookmin University, Seoul, South Korea.
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Hunt AD, Procyshyn TL. Changing perspectives on autism: Overlapping contributions of evolutionary psychiatry and the neurodiversity movement. Autism Res 2024; 17:459-466. [PMID: 38233966 DOI: 10.1002/aur.3078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/02/2023] [Indexed: 01/19/2024]
Abstract
Perspectives on autism and psychiatric conditions are affected by a mix of scientific and social influences. Evolutionary psychiatry (EP) and the neurodiversity movement are emerging paradigms that reflect these distinct influences, with the former grounded in scientific theory and the latter driven by political and social principles. Despite their separate foundations, there is a significant overlap between EP and neurodiversity that has not been explored. Specifically, both paradigms reframe disorders as natural cognitive differences rather than disease; expand the concept of "normal" beyond that implied in modern psychiatry; focus on relative strengths; recognize that modern environments disadvantage certain individuals to cause functional impairment; emphasize cognitive variation being socially accommodated and integrated rather than treated or cured; and can help reduce stigmatization. However, in other ways, they are distinct and sometimes in conflict. EP emphasizes scientific explanation, defines "dysfunction" in objective terms, and differentiates heterogenous cases based on underlying causes (e.g. autism due to de novo genetic mutations). The neurodiversity movement emphasizes social action, removes barriers to inclusion, promotes inclusive language, and allows unrestricted identification as neurodivergent. By comparing and contrasting these two approaches, we find that EP can, to some extent, support the goals of neurodiversity. In particular, EP perspectives could be convincing to groups more responsive to scientific evidence and help achieve a middle ground between neurodiversity advocates and critics of the movement.
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Affiliation(s)
- Adam D Hunt
- Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland
| | - Tanya L Procyshyn
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
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Kullberg MJ, Van Schie CC, Allegrini AG, Ahmadzadeh Y, Wechsler DL, Elzinga BM, McAdams TA. Comparing findings from the random-intercept cross-lagged panel model and the monozygotic twin difference cross-lagged panel model: Maladaptive parenting and offspring emotional and behavioural problems. JCPP Adv 2024; 4:e12203. [PMID: 38486957 PMCID: PMC10933702 DOI: 10.1002/jcv2.12203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/02/2023] [Indexed: 03/17/2024] Open
Abstract
Background In this study we compare results obtained when applying the monozygotic twin difference cross-lagged panel model (MZD-CLPM) and a random intercept cross-lagged panel model (RI-CLPM) to the same data. Each of these models is designed to strengthen researchers' ability to draw causal inference from cross-lagged associations. We explore differences and similarities in how each model does this, and in the results each model produces. Specifically, we examine associations between maladaptive parenting and child emotional and behavioural problems in identical twins aged 9, 12 and 16. Method Child reports of 5698 identical twins from the Twins Early Development Study (TEDS) were analysed. We ran a regular CLPM to anchor our findings within the current literature, then applied the MZD-CLPM and the RI-CLPM. Results The RI-CLPM and MZD-CLPM each enable researchers to evaluate the direction of effects between correlated variables, after accounting for unmeasured sources of potential confounding. Our interpretation of these models therefore focusses primarily on the magnitude and significance of cross-lagged associations. In both the MZD-CLPM and the RI-CLPM behavioural problems at age 9 resulted in higher levels of maladaptive parenting at age 12. Other effects were not consistently significant across the two models, although the majority of estimates pointed in the same direction. Conclusion In light of the triangulated methods, differences in the results obtained using the MZD-CLPM and the RI-CLPM underline the importance of careful consideration of what sources of unmeasured confounding different models control for and that nuance is required when interpreting findings using such models. We provide an overview of what the CLPM, RI-CLPM and MZD-CLPM can and cannot control for in this respect and the conclusions that can be drawn from each model.
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Affiliation(s)
| | - Charlotte C. Van Schie
- Institute of Clinical PsychologyLeiden UniversityLeidenThe Netherlands
- Leiden Institute for Brain and Cognition (LIBC)Leiden University Medical CentreLeidenThe Netherlands
- School of Psychology and Illawarra Health and Medical Research InstituteUniversity of WollongongWollongongAustralia
| | - Andrea G. Allegrini
- Psychology and Language SciencesUniversity College LondonLondonUK
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
| | - Yasmin Ahmadzadeh
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
| | - Daniel L. Wechsler
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
| | - Bernet M. Elzinga
- Institute of Clinical PsychologyLeiden UniversityLeidenThe Netherlands
- Leiden Institute for Brain and Cognition (LIBC)Leiden University Medical CentreLeidenThe Netherlands
| | - Tom A. McAdams
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
- Promenta Research CentreUniversity of OsloOsloNorway
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Pergola G, Rampino A, Sportelli L, Borcuk CJ, Passiatore R, Di Carlo P, Marakhovskaia A, Fazio L, Amoroso N, Castro MN, Domenici E, Gennarelli M, Khlghatyan J, Kikidis GC, Lella A, Magri C, Monaco A, Papalino M, Parihar M, Popolizio T, Quarto T, Romano R, Torretta S, Valsecchi P, Zunuer H, Blasi G, Dukart J, Beaulieu JM, Bertolino A. A miR-137-Related Biological Pathway of Risk for Schizophrenia Is Associated With Human Brain Emotion Processing. Biol Psychiatry Cogn Neurosci Neuroimaging 2024; 9:356-366. [PMID: 38000716 DOI: 10.1016/j.bpsc.2023.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 11/04/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023]
Abstract
BACKGROUND miR-137 is a microRNA involved in brain development, regulating neurogenesis and neuronal maturation. Genome-wide association studies have implicated miR-137 in schizophrenia risk but do not explain its involvement in brain function and underlying biology. Polygenic risk for schizophrenia mediated by miR-137 targets is associated with working memory, although other evidence points to emotion processing. We characterized the functional brain correlates of miR-137 target genes associated with schizophrenia while disentangling previously reported associations of miR-137 targets with working memory and emotion processing. METHODS Using RNA sequencing data from postmortem prefrontal cortex (N = 522), we identified a coexpression gene set enriched for miR-137 targets and schizophrenia risk genes. We validated the relationship of this set to miR-137 in vitro by manipulating miR-137 expression in neuroblastoma cells. We translated this gene set into polygenic scores of coexpression prediction and associated them with functional magnetic resonance imaging activation in healthy volunteers (n1 = 214; n2 = 136; n3 = 2075; n4 = 1800) and with short-term treatment response in patients with schizophrenia (N = 427). RESULTS In 4652 human participants, we found that 1) schizophrenia risk genes were coexpressed in a biologically validated set enriched for miR-137 targets; 2) increased expression of miR-137 target risk genes was mediated by low prefrontal miR-137 expression; 3) alleles that predict greater gene set coexpression were associated with greater prefrontal activation during emotion processing in 3 independent healthy cohorts (n1, n2, n3) in interaction with age (n4); and 4) these alleles predicted less improvement in negative symptoms following antipsychotic treatment in patients with schizophrenia. CONCLUSIONS The functional translation of miR-137 target gene expression linked with schizophrenia involves the neural substrates of emotion processing.
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Affiliation(s)
- Giulio Pergola
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.
| | - Antonio Rampino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy.
| | - Leonardo Sportelli
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Christopher James Borcuk
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Roberta Passiatore
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Institute of Neuroscience and Medicine, Brain & Behaviour, Research Centre Jülich, Jülich, Germany
| | - Pasquale Di Carlo
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | | | - Leonardo Fazio
- Department of Medicine and Surgery, Libera Università Mediterranea Giuseppe Degennaro, Casamassima, Italy
| | - Nicola Amoroso
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy
| | - Mariana Nair Castro
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires, Argentina (MNC); Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Fleni-Consejo Nacional de Investigaciones Científicas y Técnicas Neurosciences Institute, Ciudad Autónoma de Buenos Aires, Argentina
| | - Enrico Domenici
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy; Fondazione The Microsoft Research University of Trento, Centre for Computational and Systems Biology, Rovereto, Italy
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy; Genetics Unit, Istituto di Ricovero e Cura a Carattere Sanitario Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Jivan Khlghatyan
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy; Department of Neuroscience, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Gianluca Christos Kikidis
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Annalisa Lella
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Chiara Magri
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires, Argentina (MNC); Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Fleni-Consejo Nacional de Investigaciones Científicas y Técnicas Neurosciences Institute, Ciudad Autónoma de Buenos Aires, Argentina; Università degli Studi di Bari Aldo Moro, Dipartimento Interateneo di Fisica M. Merlin, Bari, Italy
| | - Marco Papalino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Madhur Parihar
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Teresa Popolizio
- Istituto di Ricovero e Cura a Carattere Sanitario Istituto Centro San Giovanni di Dio Fatebenefratelli, Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Tiziana Quarto
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Department of Law, University of Foggia, Foggia, Italy
| | - Raffaella Romano
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Silvia Torretta
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Paolo Valsecchi
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy; Department of Mental Health and Addiction Services, Azienda Socio Sanitaria Territoriale Spedali Civili of Brescia, Brescia, Italy
| | - Hailiqiguli Zunuer
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour, Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
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Beydoun MA, Beydoun HA, Hu YH, Li Z, Wolf C, Meirelles O, Noren Hooten N, Launer LJ, Evans MK, Zonderman AB. Infection burden and its association with neurite orientation dispersion and density imaging markers in the UK Biobank. Brain Behav Immun 2024; 115:394-405. [PMID: 37858740 PMCID: PMC10873031 DOI: 10.1016/j.bbi.2023.10.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/15/2023] [Accepted: 10/14/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Infection burden (IB), although linked to neurodegeneration, including Alzheimer's Disease (AD), has not been examined against neurite orientation, dispersion, and density imaging (NODDI) measures. METHODS Among 38,803 UK Biobank adults (Age:40-70 years), we tested associations of total IB (IBtotal, 47.5 %) and hospital-treated IB (IBhosp, 9.7 %) with NODDI measures (5-15 years later), including volume fraction of Gaussian isotropic diffusion (ISOVF), intra-cellular volume fraction (ICVF) and orientation dispersion (OD) indices, using multiple linear regression models. RESULTS Total and hospital-treated infection burdens (IBtotal and IBhosp) were associated with increased ISOVF, indicating increased free-water component. IBtotal was positively associated with OD, indicating that at higher IBtotal there was greater fanning of neurites. This was more evident in the lower cardiovascular health group. IBhosp was associated with higher OD, and lower ICVF at higher AD polygenic risk. Together, these findings indicate that both total and hospital-treated infections have effects on NODDI outcomes in the direction of poor brain health. These effects were largely homogeneous across cardiovascular health and AD polygenic risk groups, with some effects shown to be stronger at poor cardiovascular health and/or higher AD risk. CONCLUSIONS Total and hospital-treated infections were associated with poorer white matter microstructure (higher ISOVF or OD or lower ICVF), with some heterogeneity across cardiovascular health and AD risk. Longitudinal studies with multiple repeats on neuroimaging markers in comparable samples are needed.
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Affiliation(s)
- May A Beydoun
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA.
| | - Hind A Beydoun
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA; Alexander T. Augusta Military Medical Center, Fort Belvoir, VA, USA
| | - Yi-Han Hu
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA
| | - Zhiguang Li
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA
| | - Claudia Wolf
- Department of Education and Psychology, Freie Universitat, Berlin, Germany; Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Osorio Meirelles
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA
| | - Nicole Noren Hooten
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD, USA
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10
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Schmilovich Z, Bourque VR, Douard E, Huguet G, Poulain C, Ross JP, Alipour P, Castonguay CÉ, Younis N, Jean-Louis M, Saci Z, Pausova Z, Paus T, Schuman G, Porteous D, Davies G, Redmond P, Harris SE, Deary IJ, Whalley H, Hayward C, Dion PA, Jacquemont S, Rouleau GA. Copy-number variants and polygenic risk for intelligence confer risk for autism spectrum disorder irrespective of their effects on cognitive ability. medRxiv 2023:2023.11.29.23299190. [PMID: 38076919 PMCID: PMC10705642 DOI: 10.1101/2023.11.29.23299190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Rare copy number variants (CNVs) and polygenic risk for intelligence (PRS-IQ) both confer risk for autism spectrum disorder (ASD) but have opposing effects on cognitive ability. The field has struggled to disentangle the effects of these two classes of genomic variants on cognitive ability from their effects on ASD risk, in part because previous studies did not include controls with cognitive measures. We aim to investigate the impact of these genomic variants on ASD risk while adjusting for their known effects on cognitive ability. In a cohort of 8,426 subjects with ASD and 169,804 controls with cognitive assessments, we found that rare coding CNVs and PRS-IQ increased ASD risk, even after adjusting for their effects on cognitive ability. Bottom decile PRS-IQ and CNVs both decreased cognitive ability but had opposing effects on ASD risk. Models combining both classes of variants showed that the effects of rare CNVs and PRS-IQ on ASD risk and cognitive ability were largely additive, further suggesting that risk for ASD is conferred independently from its effects on cognitive ability. Despite imparting mostly additive effects on ASD risk, rare CNVs and PRS-IQ showed opposing effects on core and associated features and developmental history among subjects with ASD. Our findings suggest that cognitive ability itself may not be the factor driving the underlying risk for ASD conferred by these two classes of genomic variants. In other words, ASD risk and cognitive ability may be two distinct manifestations of CNVs and PRS-IQ. This study also highlights the challenge of understanding how genetic risk for ASD maps onto its dimensional traits.
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Affiliation(s)
- Zoe Schmilovich
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
| | - Vincent-Raphaël Bourque
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Elise Douard
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Guillaume Huguet
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
| | - Cécile Poulain
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Jay P. Ross
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
| | - Paria Alipour
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
| | - Charles-Étienne Castonguay
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
| | - Nadine Younis
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Martineau Jean-Louis
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
| | - Zohra Saci
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Tomas Paus
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Departments of Psychiatry of Neuroscience, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Gunter Schuman
- Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - David Porteous
- Lothian Birth Cohorts group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Lothian Birth Cohorts group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Lothian Birth Cohorts group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK
| | - Sarah E. Harris
- Lothian Birth Cohorts group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK
| | - Ian J. Deary
- Lothian Birth Cohorts group, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK
| | - Heather Whalley
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, UK
| | - Patrick A. Dion
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, Canada
| | - Sébastien Jacquemont
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Guy A. Rouleau
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montréal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, Canada
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11
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Wang B, Irizar H, Thygesen JH, Zartaloudi E, Austin-Zimmerman I, Bhat A, Harju-Seppänen J, Pain O, Bass N, Gkofa V, Alizadeh BZ, van Amelsvoort T, Arranz MJ, Bender S, Cahn W, Stella Calafato M, Crespo-Facorro B, Di Forti M, Giegling I, de Haan L, Hall J, Hall MH, van Haren N, Iyegbe C, Kahn RS, Kravariti E, Lawrie SM, Lin K, Luykx JJ, Mata I, McDonald C, McIntosh AM, Murray RM, Picchioni M, Powell J, Prata DP, Rujescu D, Rutten BPF, Shaikh M, Simons CJP, Toulopoulou T, Weisbrod M, van Winkel R, Kuchenbaecker K, McQuillin A, Bramon E. Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis. Schizophr Bull 2023; 49:1625-1636. [PMID: 37582581 PMCID: PMC10686343 DOI: 10.1093/schbul/sbad088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
BACKGROUND AND HYPOTHESIS Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes. STUDY DESIGN We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score. STUDY RESULTS After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores. CONCLUSIONS Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.
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Affiliation(s)
- Baihan Wang
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Haritz Irizar
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Johan H Thygesen
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
| | - Eirini Zartaloudi
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Isabelle Austin-Zimmerman
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Anjali Bhat
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Jasmine Harju-Seppänen
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Oliver Pain
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Nick Bass
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Vasiliki Gkofa
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Behrooz Z Alizadeh
- University of Groningen, University Medical Center Groningen, University Center for Psychiatry, Rob Giel Research Center, Groningen, The Netherlands
- Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Maria J Arranz
- Fundació Docència i Recerca Mutua Terrassa, Terrassa, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Institut de Recerca Biomédica Sant Pau (IIB-Sant Pau), Barcelona, Spain
| | - Stephan Bender
- Department of Child and Adolescent Psychiatry, Psychosomatic Medicine and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Wiepke Cahn
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Altrecht, General Mental Health Care, Utrecht, The Netherlands
| | - Maria Stella Calafato
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Benedicto Crespo-Facorro
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Sevilla, Spain
- Department of Psychiatry, University Hospital Virgen del Rocio, School of Medicine, University of Sevilla–IBiS, Sevilla, Spain
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | | | - Ina Giegling
- Comprehensive Centers for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Lieuwe de Haan
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Arkin, Institute for Mental Health, Amsterdam, The Netherlands
| | - Jeremy Hall
- Neuroscience and Mental Health Innovation Institute, School of Medicine, Cardiff University, Hadyn Ellis Building, Mandy Road, Cardiff, UK
| | - Mei-Hua Hall
- Psychosis Neurobiology Laboratory, Harvard Medical School, McLean Hospital, Belmont, MA, USA
| | - Neeltje van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia’s Children Hospital, Rotterdam, The Netherlands
| | - Conrad Iyegbe
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - René S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eugenia Kravariti
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jurjen J Luykx
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ignacio Mata
- Fundacion Argibide, Pamplona, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
| | - Colm McDonald
- The Centre for Neuroimaging & Cognitive Genomics (NICOG) and NCBES Galway Neuroscience Centre, University of Galway, Galway, Ireland
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Robin M Murray
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | | | - Marco Picchioni
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- St Magnus Hospital, Surrey, UK
| | - John Powell
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Diana P Prata
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciencias da Universidade de Lisboa, Portugal
| | - Dan Rujescu
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Division of General Psychiatry, Medical University of Vienna, Austria
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Madiha Shaikh
- North East London Foundation Trust, London, UK
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Claudia J P Simons
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- GGzE Institute for Mental Health Care, Eindhoven, The Netherlands
| | - Timothea Toulopoulou
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Interdisciplinary Program in Neuroscience, Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Türkiye
- National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Türkiye
- Department of Psychology, Bilkent University, Ankara, Türkiye
- School of Medicine, Department of Psychiatry, National and Kapodistrian University of Athens, Athens, Greece
- Department of Psychiatry and Behavioral Health System, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Matthias Weisbrod
- Department of General Psychiatry, Center of Psychosocial Medicine, University of Heidelberg, Germany
- SRH Klinikum, Karlsbad-Langensteinbach, Germany
| | - Ruud van Winkel
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- KU Leuven, Department of Neuroscience, Research Group Psychiatry, Leuven, Belgium
| | - Karoline Kuchenbaecker
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- UCL Genetics Institute, Division of Biosciences, University College London, London, UK
| | - Andrew McQuillin
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Elvira Bramon
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
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12
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Sidorchuk A, Brander G, Pérez-Vigil A, Crowley JJ, Larsson H, Lichtenstein P, Mataix-Cols D, Nordsletten AE. One versus two biological parents with mental disorders: Relationship to educational attainment in the next generation. Psychol Med 2023; 53:7025-7041. [PMID: 36545765 PMCID: PMC10719631 DOI: 10.1017/s0033291722003506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 10/17/2022] [Accepted: 10/19/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Both maternal and, separately, paternal mental illness are associated with diminished academic attainment among children. However, the differential impacts of diagnostic type and degree of parental burden (e.g. one v. both parents affected) on these functional outcomes are unknown. METHODS Using the Swedish national patient (NPR) and multi-generation (MGR) registers, 2 226 451 children (1 290 157 parental pairs), born 1 January 1973-31 December 1997, were followed through 31 December 2013. Diagnostic status of all cohort members was defined for eleven psychiatric disorders, and families classed by exposure: (1) parents affected with any disorder, (2) parents affected with a disorder group (e.g. neuropsychiatric disorders), and (3) parents affected with a specific disorder (e.g. ADHD). Pairs were further defined as 'unaffected,' 'single-affected,', or 'dual-affected.' Among offspring, the study evaluated fulfillment of four academic milestones, from compulsory (primary) school through University (college). Sensitivity analyses considered the impact of child's own mental health, as well as parental education, on main effects. RESULTS Marked reductions in the odds of achievement were observed, emerging at the earliest levels of schooling for both single-affected [adjusted odds ratio (aOR), 0.50; 95% CI 0.49-0.51] and dual-affected (aOR 0.29, 95% CI 0.28-0.30) pairs and persisting thereafter [aOR range (single), 0.52-0.65; aOR range (dual), 0.30-0.40]. This pattern was repeated for analyses within diagnosis/diagnostic group. Main results were robust to adjustment for offspring mental health and parent education level. CONCLUSIONS Parental mental illness is associated with profound reductions in educational attainment in the subsequent generation, with children from dual-affected families at uniquely high risk.
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Affiliation(s)
- Anna Sidorchuk
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Gustaf Brander
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Medical Biochemistry and Microbiology, Uppsala Universitet, Uppsala, Sweden
| | - Ana Pérez-Vigil
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - James J. Crowley
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro Universitet, Örebro, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - David Mataix-Cols
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Ashley E. Nordsletten
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
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13
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Tustison NJ, Yassa MA, Rizvi B, Cook PA, Holbrook AJ, Sathishkumar MT, Tustison MG, Gee JC, Stone JR, Avants BB. ANTsX neuroimaging-derived structural phenotypes of UK Biobank. Res Sq 2023:rs.3.rs-3459157. [PMID: 37961236 PMCID: PMC10635385 DOI: 10.21203/rs.3.rs-3459157/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem. This includes previously established cortical and subcortical measurements defined, in part, based on the Desikan-Killiany-Tourville atlas. Also included are morphological measurements from two recent developments: medial temporal lobe parcellation of hippocampal and extra-hippocampal regions in addition to cerebellum parcellation and thickness based on the Schmahmann anatomical labeling. Through predictive modeling, we assess the clinical utility of these IDP measurements, individually and in combination, using commonly studied phenotypic correlates including age, fluid intelligence, numeric memory, and several other sociodemographic variables. The predictive accuracy of these IDP-based models, in terms of root-mean-squared-error or area-under-the-curve for continuous and categorical variables, respectively, provides comparative insights between software libraries as well as potential clinical interpretability. Results demonstrate varied performance between package-based IDP sets and their combination, emphasizing the need for careful consideration in their selection and utilization.
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Affiliation(s)
- Nicholas J. Tustison
- Department of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA
- Department of Neurobiology & Behavior, University of California, Irvine, CA
| | - Michael A. Yassa
- Department of Neurobiology & Behavior, University of California, Irvine, CA
| | - Batool Rizvi
- Department of Neurobiology & Behavior, University of California, Irvine, CA
| | - Philip A. Cook
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
| | | | | | | | - James C. Gee
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
| | - James R. Stone
- Department of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA
| | - Brian B. Avants
- Department of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA
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14
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Sideli L, Aas M, Quattrone D, La Barbera D, La Cascia C, Ferraro L, Alameda L, Velthorst E, Trotta G, Tripoli G, Schimmenti A, Fontana A, Gayer-Anderson C, Stilo S, Seminerio F, Sartorio C, Marrazzo G, Lasalvia A, Tosato S, Tarricone I, Berardi D, D'Andrea G, Arango C, Arrojo M, Bernardo M, Bobes J, Sanjuán J, Santos JL, Menezes PR, Del-Ben CM, Jongsma HE, Jones PB, Kirkbride JB, Llorca PM, Tortelli A, Pignon B, de Haan L, Selten JP, Van Os J, Rutten BP, Bentall R, Di Forti M, Murray RM, Morgan C, Fisher HL. The relationship between genetic liability, childhood maltreatment, and IQ: findings from the EU-GEI multicentric case-control study. Soc Psychiatry Psychiatr Epidemiol 2023; 58:1573-1580. [PMID: 37335320 PMCID: PMC10460355 DOI: 10.1007/s00127-023-02513-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 06/04/2023] [Indexed: 06/21/2023]
Abstract
This study investigated if the association between childhood maltreatment and cognition among psychosis patients and community controls was partially accounted for by genetic liability for psychosis. Patients with first-episode psychosis (N = 755) and unaffected controls (N = 1219) from the EU-GEI study were assessed for childhood maltreatment, intelligence quotient (IQ), family history of psychosis (FH), and polygenic risk score for schizophrenia (SZ-PRS). Controlling for FH and SZ-PRS did not attenuate the association between childhood maltreatment and IQ in cases or controls. Findings suggest that these expressions of genetic liability cannot account for the lower levels of cognition found among adults maltreated in childhood.
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Affiliation(s)
- Lucia Sideli
- Department of Human Science, LUMSA University, Piazza delle Vaschette, 101, 00193, Rome, Italy.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England.
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy.
| | - Monica Aas
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
- NORMENT Centre for Psychosis Research, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Behavioural Sciences, OsloMet, Oslo Metropolitan University, Oslo, Norway
| | - Diego Quattrone
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
| | - Daniele La Barbera
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Caterina La Cascia
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Laura Ferraro
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Luis Alameda
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Centro Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Seville, Spain
- Instituto de Biomedicina de Sevilla (IBIS), Hospital Universitario Virgen del Rocio, Departamento de Psiquiatria, Universidad de Sevilla, Seville, Spain
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Eva Velthorst
- Department of Research, Mental Health Service Organization 'GGZ Noord-Holland-Noord', Hoorn, The Netherlands
| | - Giulia Trotta
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
| | - Giada Tripoli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, Palermo, Italy
| | - Adriano Schimmenti
- Faculty of Human and Social Sciences, UKE - Kore University of Enna, Enna, Italy
| | - Andrea Fontana
- Department of Human Science, LUMSA University, Piazza delle Vaschette, 101, 00193, Rome, Italy
| | - Charlotte Gayer-Anderson
- Department of Health Services and Population Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Simona Stilo
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Department of Mental Health and Addiction Services, ASP Crotone, Crotone, Italy
| | - Fabio Seminerio
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Crocettarachele Sartorio
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Giovanna Marrazzo
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Antonio Lasalvia
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy
| | - Sarah Tosato
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy
| | - Ilaria Tarricone
- Department of Medical and Surgical Sciences, Alma Mater Studiorum - Bologna University, Bologna, Italy
| | - Domenico Berardi
- Department of Biomedical and NeuroMotor Sciences, Psychiatry Unit, Alma Mater Studiorum - Bologna University, Bologna, Italy
| | - Giuseppe D'Andrea
- Department of Biomedical and NeuroMotor Sciences, Psychiatry Unit, Alma Mater Studiorum - Bologna University, Bologna, Italy
| | - Celso Arango
- Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, ISGM, CIBERSAM, Madrid, Spain
| | - Manuel Arrojo
- Department of Psychiatry, Psychiatric Genetic Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago de Compostela, Santiago, Spain
| | - Miguel Bernardo
- Barcelona Clinic Schizophrenia Unit, Hospital Clinic, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Institut d'Investigacions Biomèdiques, August Pi I Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Julio Bobes
- Department of Medicine, Psychiatry Area, School of Medicine, Universidad de Oviedo, ISPA, INEUROPA, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Oviedo, Spain
| | - Julio Sanjuán
- Department of Psychiatry, School of Medicine, Universidad de Valencia, Centro de Investigación Biomédica en Red de Salud Mental, Valencia, Spain
| | - Jose Luis Santos
- Department of Psychiatry, Hospital "Virgen de La Luz", Cuenca, Spain
| | | | | | - Hannah E Jongsma
- PsyLife Group, Division of Psychiatry, University College London, London, England
- Department of Psychiatry, University of Cambridge, Cambridge, England
| | - Peter B Jones
- CAMEO Early Intervention Service, Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, England
- EA 7280 Npsydo, Université Clermont Auvergne, Clermont-Ferrand, France
| | - James B Kirkbride
- PsyLife Group, Division of Psychiatry, University College London, London, England
| | | | - Andrea Tortelli
- Establissement Public de Santé, Maison Blanche, Paris, France
| | - Baptiste Pignon
- AP-HP, Groupe Hospitalier "Mondor", Pôle de Psychiatrie, Créteil, France
- Institut National de la Santé et de la Recherche Médicale, U955, Créteil, France
- Fondation FondaMental, Créteil, France
| | - Lieuwe de Haan
- Early Psychosis Section, Department of Psychiatry, Amsterdam UMC, Amsterdam, The Netherlands
| | - Jean-Paul Selten
- Institute for Mental Health, GGZ Rivierduinen, Leiden, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jim Van Os
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department Psychiatry, Utrecht University Medical Centre, Utrecht, The Netherlands
| | - Bart P Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Richard Bentall
- Department of Psychology, University of Sheffield, Cathedral Court, 1 Vicar Lane, Sheffield, S1 2LT, UK
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
| | - Craig Morgan
- Department of Health Services and Population Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Helen L Fisher
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
- ESRC Centre for Society and Mental Health, King's College London, London, UK
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15
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Shi R, Xiang S, Jia T, Robbins TW, Kang J, Banaschewski T, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Orfanos DP, Paus T, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Lin X, Sahakian BJ, Feng J. Structural neurodevelopment at the individual level - a life-course investigation using ABCD, IMAGEN and UK Biobank data. medRxiv 2023:2023.09.20.23295841. [PMID: 37790416 PMCID: PMC10543061 DOI: 10.1101/2023.09.20.23295841] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages and the neurobiological basis underlying individual heterogeneity remains poorly understood. Using structural magnetic resonance imaging from the IMAGEN cohort (n=1,543), we show that adolescents can be clustered into three groups defined by distinct developmental patterns of whole-brain gray matter volume (GMV). Genetic and epigenetic determinants of group clustering and long-term impacts of neurodevelopment in mid-to-late adulthood were investigated using data from the ABCD, IMAGEN and UK Biobank cohorts. Group 1, characterized by continuously decreasing GMV, showed generally the best neurocognitive performances during adolescence. Compared to Group 1, Group 2 exhibited a slower rate of GMV decrease and worsened neurocognitive development, which was associated with epigenetic changes and greater environmental burden. Further, Group 3 showed increasing GMV and delayed neurocognitive development during adolescence due to a genetic variation, while these disadvantages were attenuated in mid-to-late adulthood. In summary, our study revealed novel clusters of adolescent structural neurodevelopment and suggested that genetically-predicted delayed neurodevelopment has limited long-term effects on mental well-being and socio-economic outcomes later in life. Our results could inform future research on policy interventions aimed at reducing the financial and emotional burden of mental illness.
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16
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Wootton O, Shadrin AA, Mohn C, Susser E, Ramesar R, Gur RC, Andreassen OA, Stein DJ, Dalvie S. Genome-wide association study in 404,302 individuals identifies 7 significant loci for reaction time variability. Mol Psychiatry 2023; 28:4011-4019. [PMID: 37864076 PMCID: PMC10730420 DOI: 10.1038/s41380-023-02292-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 09/26/2023] [Accepted: 10/03/2023] [Indexed: 10/22/2023]
Abstract
Reaction time variability (RTV), reflecting fluctuations in response time on cognitive tasks, has been proposed as an endophenotype for many neuropsychiatric disorders. There have been no large-scale genome-wide association studies (GWAS) of RTV and little is known about its genetic underpinnings. Here, we used data from the UK Biobank to conduct a GWAS of RTV in participants of white British ancestry (n = 404,302) as well as a trans-ancestry GWAS meta-analysis (n = 44,873) to assess replication. We found 161 genome-wide significant single nucleotide polymorphisms (SNPs) distributed across 7 genomic loci in our discovery GWAS. Functional annotation of the variants implicated genes involved in synaptic function and neural development. The SNP-based heritability (h2SNP) estimate for RTV was 3%. We investigated genetic correlations between RTV and selected neuropsychological traits using linkage disequilibrium score regression, and found significant correlations with several traits, including a positive correlation with mean reaction time and schizophrenia. Despite the high genetic correlation between RTV and mean reaction time, we demonstrate distinctions in the genetic underpinnings of these traits. Lastly, we assessed the predictive ability of a polygenic score (PGS) for RTV, calculated using PRSice and PRS-CS, and found that the RTV-PGS significantly predicted RTV in independent cohorts, but that the generalisability to other ancestry groups was poor. These results identify genetic underpinnings of RTV, and support the use of RTV as an endophenotype for neurological and psychiatric disorders.
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Affiliation(s)
- Olivia Wootton
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
| | - Alexey A Shadrin
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Christine Mohn
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ezra Susser
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Raj Ramesar
- UCT MRC Genomic and Precision Medicine Research Unit, Division of Human Genetics, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Ruben C Gur
- Brain Behavior Laboratories, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dan J Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- SAMRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa
| | - Shareefa Dalvie
- UCT MRC Genomic and Precision Medicine Research Unit, Division of Human Genetics, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa
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17
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Cano-Ramirez H, Diaz-Castro L, Hoffman KL. Analysis of Educational Attainment in a Mexican Psychiatric Patient Population with Bipolar or Psychotic Disorders. Brain Sci 2023; 13:881. [PMID: 37371361 DOI: 10.3390/brainsci13060881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/16/2023] [Accepted: 05/24/2023] [Indexed: 06/29/2023] Open
Abstract
Schizophrenia has been associated with premorbid poor educational performance and low educational attainment (EA). However, some studies have found positive associations between psychotic disorders and excellent scholastic performance. In the present study, we examined the association between EA and several clinical and nonclinical characteristics in psychiatric patients diagnosed with psychotic or bipolar disorders. Data were obtained from the files of 1132 patients who entered a major Mexico City psychiatric hospital during the years 2009-2010 for the treatment of psychotic symptoms and who were subsequently diagnosed with schizophrenia, bipolar, schizoaffective, or another psychotic disorder. Chi-squared tests, t-tests, and Cox regression analysis were applied to explore associations between EA and factors including gender, familial history of mental illness, premorbid personality characteristics, age of symptom onset, diagnosis, civil status, and current employment. Family history of mental illness decreased the hazard of having lower EA (B = -0.137, p = 0.025, ExpB = 0.872, 95% CI = 0.774-0.983), while a schizophrenia diagnosis independently increased it (B = 0.201, p = 0.004, ExpB = 1.223, 95% CI = 1.068-1.401). In male patients (but not in females), family history of mental illness was significantly associated with higher EA, while in female patients, premorbid schizoid-like personality characteristics were associated with lower EA. For both genders, lower EA was associated with having more children and being employed in manual labor, while higher EA was associated with professional employment. Conclusions: Compared with bipolar disorder, a schizophrenia diagnosis is associated with lower EA; however, familial history of mental illness and premorbid schizoid-like characteristics independently favor higher and lower EA in males and females, respectively. Since lower EA is generally associated with a lower economic status, special preventative attention should be given to students at high risk for schizophrenia, particularly those displaying a schizoid-like personality.
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Affiliation(s)
- Hugo Cano-Ramirez
- Center for Investigation in Reproduction, Autonomous University of Tlaxcala-CINVESTAV, Tlaxcala 90000, Mexico
| | - Lina Diaz-Castro
- Department of Epidemiological and Psychosocial Investigation, National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico City 14370, Mexico
| | - Kurt Leroy Hoffman
- Center for Investigation in Reproduction, Autonomous University of Tlaxcala-CINVESTAV, Tlaxcala 90000, Mexico
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18
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Chen CJ, Liao WY, Chattopadhyay A, Lu TP. Exploring the genetic correlation of cardiovascular diseases and mood disorders in the UK Biobank. Epidemiol Psychiatr Sci 2023; 32:e31. [PMID: 37161899 DOI: 10.1017/s2045796023000252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/11/2023] Open
Abstract
AIMS Cardiovascular diseases (CVDs) are the leading cause of deaths globally. Mortality and incidence of CVDs are significantly higher in people with mood disorders. About 81.1% of CVD patients were reported with comorbidities in 2019, where the second most common comorbidity was due to major depressive disorder (MDD). This study, therefore, aimed to evaluate the genetic correlation between CVDs and mood disorders by using data from the UK Biobank towards understanding the influence of genetic factors on the comorbidity due to CVDs and mood disorders. METHODS The UK Biobank database provides genetic and health information from half a million adults, aged 40-69 years, recruited between 2006 and 2010. A total of 117,925 participants and 6,128,294 variants were included for analysis after applying exclusion criteria and quality control steps. This study focused on two CVD phenotypes, two mood disorders and 12 cardiometabolic-related traits to conduct association studies. RESULTS The results indicated a significant positive genetic correlation between CVDs and overall mood disorders and MDD specifically, showing substantial genetic overlap. Genetic correlation between CVDs and bipolar disorder was not significant. Furthermore, significant genetic correlation between mood disorders and cardiometabolic traits was also reported. CONCLUSIONS The results of this study can be used to understand that CVDs and mood disorders share a great deal of genetic liability in individuals of European ancestry.
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Affiliation(s)
- Chi-Jen Chen
- Institute of Epidemiology and Preventive Medicine, Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Wan-Yu Liao
- Institute of Epidemiology and Preventive Medicine, Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Amrita Chattopadhyay
- Bioinformatics and Biostatistics Core, Center of Genomics and Precision Medicine, Center of Genomics and Precision Medicine, National Taiwan University, Taipei, Taiwan
| | - Tzu-Pin Lu
- Institute of Epidemiology and Preventive Medicine, Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
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19
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Toseeb U, Vincent J, Oginni OA, Asbury K, Newbury DF. The Development of Mental Health Difficulties in Young People With and Without Developmental Language Disorder: A Gene-Environment Interplay Study Using Polygenic Scores. J Speech Lang Hear Res 2023; 66:1639-1657. [PMID: 37040695 DOI: 10.1044/2023_jslhr-22-00664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
PURPOSE Young people with developmental language disorder (DLD) have poorer mental health than those without DLD. However, not all young people with DLD are equally affected; some have more mental health difficulties than others. What explains these differences remains unclear. METHOD Data from a community cohort study, the Avon Longitudinal Study of Parents and Children, were analyzed to investigate genetic and environmental influences on the development of mental health difficulties at five time points from childhood (7 years) to adolescence (16 years) in 6,387 young people (8.7% with DLD). Regression and latent class models were fitted to the data. RESULTS Polygenic scores (PGSs), indices of genetic risk, for common psychiatric disorders (major depressive disorder, anxiety disorder, and attention deficit hyperactivity disorder) predicted mental health difficulties in both groups (with and without DLD). The presence of DLD, in some instances, amplified mental health difficulties for those with high genetic risk for common psychiatric disorders. Subgroups of children with similar developmental trajectories of mental health difficulties were identified. Young people with DLD were more likely than those without DLD to follow mental health subgroups characterized by consistently high levels of difficulties during development. PGSs, socioeconomic status, and the early home environment distinguished subgroups with low mental health difficulties from those characterized by high levels of difficulties, but these effects did not differ based on DLD status. CONCLUSIONS These findings suggest that, for the most part, both genetic and environmental risk affect the development of mental health difficulties in a cumulative way for young people with DLD (and those without). Some analysis did, however, suggest that genetic risk for common psychiatric disorders might manifest more strongly in those with DLD compared with those without DLD. SUPPLEMENTAL MATERIAL https://doi.org/10.23641/asha.22351012.
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Affiliation(s)
- Umar Toseeb
- Department of Education, University of York, United Kingdom
| | - John Vincent
- Department of Education, University of York, United Kingdom
| | - Olakunle A Oginni
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, United Kingdom
- Department of Mental Health, Obafemi Awolowo University, Ile-Ife, Nigeria
| | - Kathryn Asbury
- Department of Education, University of York, United Kingdom
| | - Dianne F Newbury
- Department of Medical and Biological Sciences, Oxford Brookes University, United Kingdom
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20
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Gao L, Gaba A, Li P, Saxena R, Scheer FAJL, Akeju O, Rutter MK, Hu K. Heart rate response and recovery during exercise predict future delirium risk-A prospective cohort study in middle- to older-aged adults. J Sport Health Sci 2023; 12:312-323. [PMID: 34915199 DOI: 10.1016/j.jshs.2021.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/10/2021] [Accepted: 11/17/2021] [Indexed: 05/17/2023]
Abstract
BACKGROUND Delirium is a neurocognitive disorder characterized by an abrupt decline in attention, awareness, and cognition after surgical/illness-induced stressors on the brain. There is now an increasing focus on how cardiovascular health interacts with neurocognitive disorders given their overlapping risk factors and links to subsequent dementia and mortality. One common indicator for cardiovascular health is the heart rate response/recovery (HRR) to exercise, but how this relates to future delirium is unknown. METHODS Electrocardiogram data were examined in 38,740 middle- to older-aged UK Biobank participants (mean age = 58.1 years, range: 40-72 years; 47.3% males) who completed a standardized submaximal exercise stress test (15-s baseline, 6-min exercise, and 1-min recovery) and required hospitalization during follow-up. An HRR index was derived as the product of the heart rate (HR) responses during exercise (peak/resting HRs) and recovery (peak/recovery HRs) and categorized into low/average/high groups as the bottom quartile/middle 2 quartiles/top quartile, respectively. Associations between 3 HRR groups and new-onset delirium were investigated using Cox proportional hazards models and a 2-year landmark analysis to minimize reverse causation. Sociodemographic factors, lifestyle factors/physical activity, cardiovascular risk, comorbidities, cognition, and maximal workload achieved were included as covariates. RESULTS During a median follow-up period of 11 years, 348 participants (9/1000) newly developed delirium. Compared with the high HRR group (16/1000), the risk for delirium was almost doubled in those with low HRR (hazard ratio = 1.90, 95% confidence interval (95%CI): 1.30-2.79, p = 0.001) and average HRR (hazard ratio = 1.54, 95%CI: 1.07-2.22, p = 0.020)). Low HRR was equivalent to being 6 years older, a current smoker, or ≥3 additional cardiovascular disease risks. Results were robust in sensitivity analysis, but the risk appeared larger in those with better cognition and when only postoperative delirium was considered (n = 147; hazard ratio = 2.66, 95%CI: 1.46-4.85, p = 0.001). CONCLUSION HRR during submaximal exercise is associated with future risk for delirium. Given that HRR is potentially modifiable, it may prove useful for neurological risk stratification alongside traditional cardiovascular risk factors.
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Affiliation(s)
- Lei Gao
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; Medical Biodynamics Program, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA.
| | - Arlen Gaba
- Medical Biodynamics Program, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Peng Li
- Medical Biodynamics Program, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Richa Saxena
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PL, UK
| | - Frank A J L Scheer
- Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Oluwaseun Akeju
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Martin K Rutter
- Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PL, UK; Diabetes, Endocrinology and Metabolism Centre, Manchester University National Health Service Foundation Trust, Manchester M13 9WL, UK
| | - Kun Hu
- Medical Biodynamics Program, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
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21
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McCutcheon RA, Keefe RSE, McGuire PK. Cognitive impairment in schizophrenia: aetiology, pathophysiology, and treatment. Mol Psychiatry 2023; 28:1902-1918. [PMID: 36690793 PMCID: PMC10575791 DOI: 10.1038/s41380-023-01949-9] [Citation(s) in RCA: 50] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 01/03/2023] [Accepted: 01/06/2023] [Indexed: 01/25/2023]
Abstract
Cognitive deficits are a core feature of schizophrenia, account for much of the impaired functioning associated with the disorder and are not responsive to existing treatments. In this review, we first describe the clinical presentation and natural history of these deficits. We then consider aetiological factors, highlighting how a range of similar genetic and environmental factors are associated with both cognitive function and schizophrenia. We then review the pathophysiological mechanisms thought to underlie cognitive symptoms, including the role of dopamine, cholinergic signalling and the balance between GABAergic interneurons and glutamatergic pyramidal cells. Finally, we review the clinical management of cognitive impairments and candidate novel treatments.
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Affiliation(s)
- Robert A McCutcheon
- Department of Psychiatry, University of Oxford, Oxford, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
- Oxford health NHS Foundation Trust, Oxford health NHS Foundation Trust, Oxford, UK.
| | - Richard S E Keefe
- Departments of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Philip K McGuire
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford health NHS Foundation Trust, Oxford health NHS Foundation Trust, Oxford, UK
- NIHR Oxford Health Biomedical Research Centre, Oxford, UK
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22
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Zhang C, Li X, Zhao L, Guo W, Deng W, Wang Q, Hu X, Du X, Sham PC, Luo X, Li T. Brain transcriptome-wide association study implicates novel risk genes underlying schizophrenia risk. Psychol Med 2023:1-11. [PMID: 37092861 DOI: 10.1017/s0033291723000417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
BACKGROUND To identify risk genes whose expression are regulated by the reported risk variants and to explore the potential regulatory mechanism in schizophrenia (SCZ). METHODS We systematically integrated three independent brain expression quantitative traits (eQTLs) (CommonMind, GTEx, and BrainSeq Phase 2, a total of 1039 individuals) and GWAS data (56 418 cases and 78 818 controls), with the use of transcriptome-wide association study (TWAS). Diffusion magnetic resonance imaging was utilized to quantify the integrity of white matter bundles and determine whether polygenic risk of novel genes linked to brain structure was present in patients with first-episode antipsychotic SCZ. RESULTS TWAS showed that eight risk genes (CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, PCDHA8, THOC7, and TYW5) reached transcriptome-wide significance (TWS) level. These findings were confirmed by an independent integrative approach (i.e. Sherlock). We further conducted conditional analyses and identified the potential risk genes that driven the TWAS association signal in each locus. Gene expression analysis showed that several TWS genes (including CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, THOC7 and TYW5) were dysregulated in the dorsolateral prefrontal cortex of SCZ cases compared with controls. TWS genes were mainly expressed on the surface of glutamatergic neurons, GABAergic neurons, and microglia. Finally, SCZ cases had a substantially greater TWS genes-based polygenic risk (PRS) compared to controls, and we showed that fractional anisotropy of the cingulum-hippocampus mediates the influence of TWS genes PRS on SCZ. CONCLUSIONS Our findings identified novel SCZ risk genes and highlighted the importance of the TWS genes in frontal-limbic dysfunctions in SCZ, indicating possible therapeutic targets.
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Affiliation(s)
- Chengcheng Zhang
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiaojing Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wanjun Guo
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wei Deng
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xun Hu
- The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiangdong Du
- Suzhou Psychiatric Hospital, Soochow University's Affiliated Guangji Hospital, Suzhou, Jiangsu, China
| | - Pak Chung Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong SAR, China
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Xiongjian Luo
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Tao Li
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
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23
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Linli Z, Rolls ET, Zhao W, Kang J, Feng J, Guo S. Smoking is associated with lower brain volume and cognitive differences: A large population analysis based on the UK Biobank. Prog Neuropsychopharmacol Biol Psychiatry 2023; 123:110698. [PMID: 36528239 DOI: 10.1016/j.pnpbp.2022.110698] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 11/25/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
The evidence about the association of smoking with both brain structure and cognitive functions remains inconsistent. Using structural magnetic resonance imaging from the UK Biobank (n = 33,293), we examined the relationships between smoking status, dosage, and abstinence with total and 166 regional brain gray matter volumes (GMV). The relationships between the smoking parameters with cognitive function, and whether this relationship was mediated by brain structure, were then investigated. Smoking was associated with lower total and regional GMV, with the extent depending on the frequency of smoking and on whether smoking had ceased: active regular smokers had the lowest GMV (Cohen's d = -0.362), and former light smokers had a slightly smaller GMV (Cohen's d = -0.060). The smaller GMV in smokers was most evident in the thalamus. Higher lifetime exposure (i.e., pack-years) was associated with lower total GMV (β = -311.84, p = 8.35 × 10-36). In those who ceased smoking, the duration of abstinence was associated with a larger total GMV (β = 139.57, p = 2.36 × 10-08). It was further found that reduced cognitive function was associated with smoker parameters and that the associations were partially mediated by brain structure. This is the largest scale investigation we know of smoking and brain structure, and these results are likely to be robust. The findings are of associations between brain structure and smoking, and in the future, it will be important to assess whether brain structure influences smoking status, or whether smoking influences brain structure, or both.
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Affiliation(s)
- Zeqiang Linli
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, PR China; Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, PR China; School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, PR China.
| | - Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, UK; Department of Computer Science, University of Warwick, Coventry, UK
| | - Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, PR China; Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, PR China
| | - Jujiao Kang
- Centre for Computational Systems Biology, Fudan University, Shanghai, PR China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry, UK; Centre for Computational Systems Biology, Fudan University, Shanghai, PR China.
| | - Shuixia Guo
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, PR China; Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, PR China.
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24
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Peng Q, Wilhelmsen KC, Ehlers CL. Pleiotropic loci for cannabis use disorder severity in multi-ancestry high-risk populations. Mol Cell Neurosci 2023; 125:103852. [PMID: 37061172 DOI: 10.1016/j.mcn.2023.103852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 04/04/2023] [Accepted: 04/07/2023] [Indexed: 04/17/2023] Open
Abstract
Cannabis use disorder (CUD) is common and has in part a genetic basis. The risk factors underlying its development likely involve multiple genes that are polygenetic and interact with each other and the environment to ultimately lead to the disorder. Co-morbidity and genetic correlations have been identified between CUD and other disorders and traits in select populations primarily of European descent. If two or more traits, such as CUD and another disorder, are affected by the same genetic locus, they are said to be pleiotropic. The present study aimed to identify specific pleiotropic loci for the severity level of CUD in three high-risk population cohorts: American Indians (AI), Mexican Americans (MA), and European Americans (EA). Using a previously developed computational method based on a machine learning technique, we leveraged the entire GWAS catalog and identified 114, 119, and 165 potentially pleiotropic variants for CUD severity in AI, MA, and EA respectively. Ten pleiotropic loci were shared between the cohorts although the exact variants from each cohort differed. While majority of the pleiotropic genes were distinct in each cohort, they converged on numerous enriched biological pathways. The gene ontology terms associated with the pleiotropic genes were predominately related to synaptic functions and neurodevelopment. Notable pathways included Wnt/β-catenin signaling, lipoprotein assembly, response to UV radiation, and components of the complement system. The pleiotropic genes were the most significantly differentially expressed in frontal cortex and coronary artery, up-regulated in adipose tissue, and down-regulated in testis, prostate, and ovary. They were significantly up-regulated in most brain tissues but were down-regulated in the cerebellum and hypothalamus. Our study is the first to attempt a large-scale pleiotropy detection scan for CUD severity. Our findings suggest that the different population cohorts may have distinct genetic factors for CUD, however they share pleiotropic genes from underlying pathways related to Alzheimer's disease, neuroplasticity, immune response, and reproductive endocrine systems.
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Affiliation(s)
- Qian Peng
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA 92037, USA.
| | - Kirk C Wilhelmsen
- Department of Neurology, West Virginia University, Morgantown, WV 26506, USA
| | - Cindy L Ehlers
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA 92037, USA
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25
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Wright L, Davies NM, Bann D. The association between cognitive ability and body mass index: A sibling-comparison analysis in four longitudinal studies. PLoS Med 2023; 20:e1004207. [PMID: 37053134 PMCID: PMC10101525 DOI: 10.1371/journal.pmed.1004207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 02/21/2023] [Indexed: 04/14/2023] Open
Abstract
BACKGROUND Body mass index (BMI) and obesity rates have increased sharply since the 1980s. While multiple epidemiologic studies have found that higher adolescent cognitive ability is associated with lower adult BMI, residual and unobserved confounding due to family background may explain these associations. We used a sibling design to test this association accounting for confounding factors shared within households. METHODS AND FINDINGS We used data from four United States general youth population cohort studies: the National Longitudinal Study of Youth 1979 (NLSY-79), the NLSY-79 Children and Young Adult, the NLSY 1997 (NLSY-97), and the Wisconsin Longitudinal Study (WLS); a total of 12,250 siblings from 5,602 households followed from adolescence up to age 62. We used random effects within-between (REWB) and residualized quantile regression (RQR) models to compare between- and within-family estimates of the association between adolescent cognitive ability and adult BMI (20 to 64 years). In REWB models, moving from the 25th to 75th percentile of adolescent cognitive ability was associated with -0.95 kg/m2 (95% CI = -1.21, -0.69) lower BMI between families. Adjusting for family socioeconomic position reduced the association to -0.61 kg/m2 (-0.90, -0.33). However, within families, the association was just -0.06 kg/m2 (-0.35, 0.23). This pattern of results was found across multiple specifications, including analyses conducted in separate cohorts, models examining age-differences in association, and in RQR models examining the association across the distribution of BMI. Limitations include the possibility that within-family estimates are biased due to measurement error of the exposure, confounding via non-shared factors, and carryover effects. CONCLUSIONS The association between high adolescent cognitive ability and low adult BMI was substantially smaller in within-family compared with between-family analysis. The well-replicated associations between cognitive ability and subsequent BMI may largely reflect confounding by family background factors.
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Affiliation(s)
- Liam Wright
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, United Kingdom
| | - Neil M. Davies
- Division of Psychiatry, University College London, London, United Kingdom
- Department of Statistical Sciences, University College London, London, United Kingdom
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - David Bann
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, United Kingdom
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26
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Zheng J, Ni C, Zhang Y, Huang J, Hukportie DN, Liang B, Tang S. Association of regular glucosamine use with incident dementia: evidence from a longitudinal cohort and Mendelian randomization study. BMC Med 2023; 21:114. [PMID: 36978077 PMCID: PMC10052856 DOI: 10.1186/s12916-023-02816-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/06/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND Emerging data suggests the neuroprotective and anti-neuroinflammatory effects of glucosamine. We aimed to examine the association between regular glucosamine use and risk of incident dementia, including dementia subtypes. METHODS We conducted large-scale observational and two-sample Mendelian randomization (MR) analyses. Participants in UK Biobank having accessible data for dementia incidence and who did not have dementia at baseline were included in the prospective cohort. Through the Cox proportional hazard model, we examined the risks of incident all-cause dementia, Alzheimer's disease (AD), and vascular dementia among glucosamine users and non-users. To further test the causal association between glucosamine use and dementia, we conducted a 2-sample MR utilizing summary statistics from genome-wide association studies (GWAS). The GWAS data were obtained from observational cohort participants of mostly European ancestry. RESULTS During a median follow-up of 8.9 years, there were 2458 cases of all-cause dementia, 924 cases of AD, and 491 cases of vascular dementia. In multivariable analysis, the hazard ratios (HR) of glucosamine users for all-cause dementia, AD, and vascular dementia were 0.84 (95% CI 0.75-0.93), 0.83 (95% CI 0.71-0.98), and 0.74 (95% CI 0.58-0.95), respectively. The inverse associations between glucosamine use and AD appeared to be stronger among participants aged below 60 years than those aged above 60 years (p = 0.04 for interaction). The APOE genotype did not modify this association (p > 0.05 for interaction). Single-variable MR suggested a causal relationship between glucosamine use and lower dementia risk. Multivariable MR showed that taking glucosamine continued to protect against dementia after controlling for vitamin, chondroitin supplement use and osteoarthritis (all-cause dementia HR 0.88, 95% CI 0.81-0.95; AD HR 0.78, 95% CI 0.72-0.85; vascular dementia HR 0.73, 95% CI 0.57-0.94). Single and multivariable inverse variance weighted (MV-IVW) and MR-Egger sensitivity analyses produced similar results for these estimations. CONCLUSIONS The findings of this large-scale cohort and MR analysis provide evidence for potential causal associations between the glucosamine use and lower risk for dementia. These findings require further validation through randomized controlled trials.
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Affiliation(s)
- Jiazhen Zheng
- Bioscience and Biomedical Engineering Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China
| | - Can Ni
- Bioscience and Biomedical Engineering Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China
| | - Yingchai Zhang
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong, SAR, China
| | - Jinghan Huang
- Biomedical Genetics Section, School of Medicine, Boston University, Boston, USA
- Department of Chemical Pathology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Daniel Nyarko Hukportie
- Department of Epidemiology, School of Public Health, (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, China
| | - Buwen Liang
- Bioscience and Biomedical Engineering Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China
| | - Shaojun Tang
- Bioscience and Biomedical Engineering Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China.
- Division of Emerging Interdisciplinary Areas, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, SAR, China.
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27
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Supiyev A, Karlsson R, Wang Y, Koch E, Hägg S, Kauppi K. Independent role of Alzheimer's disease genetics and C-reactive protein on cognitive ability in aging. Neurobiol Aging 2023; 126:103-112. [PMID: 36965205 DOI: 10.1016/j.neurobiolaging.2023.02.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/31/2023] [Accepted: 02/15/2023] [Indexed: 02/23/2023]
Abstract
Apolipoprotein E (APOE) ε4, the strongest genetic risk factor for late onset Alzheimer's disease (LOAD), has been associated with cognitive decline independent from AD pathology, but the role for other LOAD risk genes in normal cognitive aging is less studied. We examined the effect of APOE ε4 and several different polygenic risk scores (PRS) for LOAD on cognitive level and decline in aging, using longitudinal data from the UK Biobank. While PRS-LOAD including all variants (except APOE) predicted cognitive level, APOE ε4 and PRS-LOAD based on 17 non-APOE gene variants with strong association to AD (p < 5e-8) predicted age-related decline in verbal numeric reasoning. The effect on decline were partly driven by 4 variants involved in the immune system. Those variants also predicted serum levels of the inflammatory marker C-reactive protein (CRP), but CRP did not mediate the effect on decline. Those findings suggest genetic variations in immune functions play a role in aspects of cognitive aging that may be independent of LOAD pathology as well as systemic inflammation measured by CRP.
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Affiliation(s)
- Adil Supiyev
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Elise Koch
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway; Department of Integrative Medical Biology, Umeå Universitet, Biologihuset, Umeå, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Karolina Kauppi
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden; Department of Integrative Medical Biology, Umeå Universitet, Biologihuset, Umeå, Sweden
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28
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Andreassen OA, Hindley GFL, Frei O, Smeland OB. New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications. World Psychiatry 2023; 22:4-24. [PMID: 36640404 PMCID: PMC9840515 DOI: 10.1002/wps.21034] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/07/2022] [Indexed: 01/15/2023] Open
Abstract
Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.
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Affiliation(s)
- Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Guy F L Hindley
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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29
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Dong L, Wang Y, Wang X, Luo T, Zhou Q, Zhao G, Li B, Xia L, Xia K, Li J. Interactions of genetic risks for autism and the broad autism phenotypes. Front Psychiatry 2023; 14:1110080. [PMID: 37102084 PMCID: PMC10123509 DOI: 10.3389/fpsyt.2023.1110080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/07/2023] [Indexed: 04/28/2023] Open
Abstract
Background Common polygenic risk and de novo variants (DNVs) capture a small proportion of autism spectrum disorder (ASD) liability, and ASD phenotypic heterogeneity remains difficult to explain. Integrating multiple genetic factors contribute to clarifying the risk and clinical presentation of ASD. Methods In our study, we investigated the individual and combined effects of polygenic risk, damaging DNVs (including those in ASD risk genes), and sex among 2,591 ASD simplex families in the Simons Simplex Collection. We also explored the interactions among these factors, along with the broad autism phenotypes of ASD probands and their unaffected siblings. Finally, we combined the effects of polygenic risk, damaging DNVs in ASD risk genes, and sex to explain the total liability of ASD phenotypic spectrum. Results Our findings revealed that both polygenic risk and damaging DNVs contribute to an increased risk for ASD, with females exhibiting higher genetic burdens than males. ASD probands that carry damaging DNVs in ASD risk genes showed reduced polygenic risk. The effects of polygenic risk and damaging DNVs on autism broad phenotypes were inconsistent; probands with higher polygenic risk exhibited improvement in some behaviors, such as adaptive/cognitive behaviors, while those with damaging DNVs exhibited more severe phenotypes. Siblings with higher polygenic risk and damaging DNVs tended to have higher scores on broader autism phenotypes. Females exhibited more severe cognitive and behavioral problems compared to males among both ASD probands and siblings. The combination of polygenic risk, damaging DNVs in ASD risk genes, and sex explained 1-4% of the total liability of adaptive/cognitive behavior measurements. Conclusion Our study revealed that the risk for ASD and the autism broad phenotypes likely arises from a combination of common polygenic risk, damaging DNVs (including those in ASD risk genes), and sex.
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Affiliation(s)
- Lijie Dong
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Yijing Wang
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Xiaomeng Wang
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Tengfei Luo
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Qiao Zhou
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Guihu Zhao
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Bin Li
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Lu Xia
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- *Correspondence: Lu Xia,
| | - Kun Xia
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Kun Xia,
| | - Jinchen Li
- Bioinformatics Center and National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Jinchen Li,
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Hatoum AS, Morrison CL, Mitchell EC, Lam M, Benca-Bachman CE, Reineberg AE, Palmer RHC, Evans LM, Keller MC, Friedman NP. Genome-wide Association Study Shows That Executive Functioning Is Influenced by GABAergic Processes and Is a Neurocognitive Genetic Correlate of Psychiatric Disorders. Biol Psychiatry 2023; 93:59-70. [PMID: 36150907 PMCID: PMC9722603 DOI: 10.1016/j.biopsych.2022.06.034] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 06/08/2022] [Accepted: 06/23/2022] [Indexed: 11/02/2022]
Abstract
BACKGROUND Deficits in executive functions (EFs), cognitive processes that control goal-directed behaviors, are associated with psychopathology and neurologic disorders. Little is known about the molecular bases of individual differences in EFs. Prior candidate gene studies have been underpowered in their search for dopaminergic processes involved in cognitive functioning, and existing genome-wide association studies of EFs used small sample sizes and/or focused on individual tasks that are imprecise measures of EFs. METHODS We conducted a genome-wide association study of a common EF (cEF) factor score based on multiple tasks in the UK Biobank (n = 427,037 individuals of European descent). RESULTS We found 129 independent genome-wide significant lead variants in 112 distinct loci. cEF was associated with fast synaptic transmission processes (synaptic, potassium channel, and GABA [gamma-aminobutyric acid] pathways) in gene-based analyses. cEF was genetically correlated with measures of intelligence (IQ) and cognitive processing speed, but cEF and IQ showed differential genetic associations with psychiatric disorders and educational attainment. CONCLUSIONS Results suggest that cEF is a genetically distinct cognitive construct that is particularly relevant to understanding the genetic variance in psychiatric disorders.
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Affiliation(s)
- Alexander S Hatoum
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado; Department of Psychiatry, University of Washington St. Louis Medical School, St. Louis, Missouri
| | - Claire L Morrison
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado.
| | - Evann C Mitchell
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
| | - Max Lam
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, New York; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Chelsie E Benca-Bachman
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, Atlanta, Georgia
| | - Andrew E Reineberg
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado
| | - Rohan H C Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, Atlanta, Georgia
| | - Luke M Evans
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, Colorado
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
| | - Naomi P Friedman
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
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Valli I, De la Serna E, Segura AG, Pariente JC, Calvet-Mirabent A, Borras R, Ilzarbe D, Moreno D, Martín-Martínez N, Baeza I, Rosa-Justicia M, Garcia-Rizo C, Díaz-Caneja CM, Crossley NA, Young AH, Vieta E, Mas S, Castro-Fornieles J, Sugranyes G. Genetic and Structural Brain Correlates of Cognitive Subtypes Across Youth at Family Risk for Schizophrenia and Bipolar Disorder. J Am Acad Child Adolesc Psychiatry 2023; 62:74-83. [PMID: 35710081 DOI: 10.1016/j.jaac.2022.05.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/21/2022] [Accepted: 06/06/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Cognitive impairment is an important feature of schizophrenia (SZ) and bipolar disorder (BP) with severity across the two disorders characterized by significant heterogeneity. Youth at family risk for SZ and BP were clustered based on cognitive function and examined in terms of the clinical, genetic, and brain imaging correlates of cluster membership. METHOD One hundred sixty participants, 32 offspring of patients with SZ, 59 offspring of patients with BP and 69 offspring of healthy control parents underwent clinical and cognitive assessments, genotyping and structural MRI. K-means clustering was used to group family risk participants based on cognitive measures. Clusters were compared in terms of cortical and subcortical brain measures as well as polygenic risk scores. RESULTS Participants were grouped in 3 clusters with intact, intermediate, and impaired cognitive performance. The intermediate and impaired clusters had lower total brain surface area compared with the intact cluster, with prominent localization in frontal and temporal cortices. No between-cluster differences were identified in cortical thickness and subcortical brain volumes. The impaired cluster also had poorer psychosocial functioning and worse PRS-COG compared with the other 2 clusters and with offspring of healthy control parents, while there was no significant between-cluster difference in terms of PRS-SZ and PRS-BP. PRS-COG predicted psychosocial functioning, yet this effect did not appear to be mediated by an effect of PRS-COG on brain area. CONCLUSION Stratification based on cognition may help to elucidate the biological underpinnings of cognitive heterogeneity across SZ and BP risk.
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Affiliation(s)
- Isabel Valli
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London.
| | - Elena De la Serna
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | | | - Jose C Pariente
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Roger Borras
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Daniel Ilzarbe
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | - Dolores Moreno
- Institute of Neuroscience, Hospital Clínic Barcelona, Spain; Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nuria Martín-Martínez
- Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Inmaculada Baeza
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Mireia Rosa-Justicia
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Clemente Garcia-Rizo
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nicolas A Crossley
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Allan H Young
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Kent, United Kingdom
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Sergi Mas
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; University of Barcelona, Spain
| | - Josefina Castro-Fornieles
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Gisela Sugranyes
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
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Williams CM, Peyre H, Ramus F. Brain volumes, thicknesses, and surface areas as mediators of genetic factors and childhood adversity on intelligence. Cereb Cortex 2022; 33:5885-5895. [PMID: 36533516 DOI: 10.1093/cercor/bhac468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 12/23/2022] Open
Abstract
Although genetic and environmental factors influence general intelligence (g-factor), few studies examined the neuroanatomical measures mediating environmental and genetic effects on intelligence. Here, we investigate the brain volumes, cortical mean thicknesses, and cortical surface areas mediating the effects of the g-factor polygenic score (gPGS) and childhood adversity on the g-factor in the UK Biobank. We first examined the global and regional brain measures that contribute to the g-factor. Most regions contributed to the g-factor through global brain size. Parieto-frontal integration theory (P-FIT) regions were not more associated with the g-factor than non-PFIT regions. After adjusting for global brain size and regional associations, only a few regions predicted intelligence and were included in the mediation analyses. We conducted mediation analyses on global measures, regional volumes, mean thicknesses, and surface areas, separately. Total brain volume mediated 7.04% of the gPGS' effect on the g-factor and 2.50% of childhood adversity's effect on the g-factor. In comparison, the fraction of the gPGS and childhood adversity's effects mediated by individual regional volumes, surfaces, and mean thicknesses was 10-15 times smaller. Therefore, genetic and environmental effects on intelligence may be mediated to a larger extent by other brain properties.
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Affiliation(s)
- Camille M Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 29 rue d'ulm, 75005, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 29 rue d'ulm, 75005, Paris, France
- INSERM UMR 1141, Paris Diderot University, 48 Bd Sérurier, 75019, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, 48 Bd Sérurier, 75019, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 29 rue d'ulm, 75005, Paris, France
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Rao S, Baranova A, Yao Y, Wang J, Zhang F. Genetic Relationships between Attention-Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, and Intelligence. Neuropsychobiology 2022; 81:484-496. [PMID: 35764056 DOI: 10.1159/000525411] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 05/12/2022] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) commonly co-occur; both traits exert an influence on intelligence scores. Genetic relationships between these three traits are far from being clear. METHODS The summary results of genome-wide association studies of ADHD (20,183 cases and 35,191 controls), ASD (18,381 cases and 27,969 controls), and intelligence (269,867 participants) were used for the analyses. Local genetic correlation analysis and polygenic overlap analysis were used to explore the shared genetic components between ADHD, ASD, and intelligence. Mendelian randomization (MR) analysis was used to examine the causal associations between ADHD, ASD, and intelligence. A cross-trait meta-analysis was performed to identify pleiotropic genetic variants across the three traits. RESULTS Our results showed that intelligence has a positive and negative genetic correlation with ASD and ADHD, respectively, including three hub genomic regions showing correlated genetic effects across the three traits. Polygenic overlap analysis indicated that all the risk variants contributing to ADHD are overlapped with half of those for intelligence, and the majority of the shared variants have opposite effect directions between them. The majority of risk variants (80%) of ASD are overlapped with almost all the risk variants of intelligence (97%). Notably, some ASD/intelligence overlapping variants displayed opposing effects on these two conditions. MR analysis showed that the genetic liability to higher intelligence was associated with an increased risk for ASD (OR = 1.12) and a decreased risk for ADHD (OR = 0.78). Cross-trait meta-analyses identified 170 pleiotropic genomic loci across the three traits, including 12 novel loci. Functional analyses of the novel genes support their potential involvement in neurodevelopment. CONCLUSION Our results suggest that ADHD is associated with inheriting a reduced set of low-intelligence alleles, whereas ASD results from incongruous effects from a mixture of high-intelligence and low-intelligence contributing alleles summed up with additional, ASD-specific risk variants not associated with intelligence.
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Affiliation(s)
- Shuquan Rao
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Ancha Baranova
- School of Systems Biology, George Mason University, Manassas, Virginia, USA.,Research Centre for Medical Genetics, Moscow, Russian Federation
| | - Yao Yao
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Jun Wang
- Department of Psychiatry, Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Fuquan Zhang
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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Wang M, Huang S. The collective effects of genetic variants and complex traits. J Hum Genet 2022; 68:255-262. [PMID: 36513763 DOI: 10.1038/s10038-022-01105-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 12/01/2022] [Accepted: 12/02/2022] [Indexed: 12/15/2022]
Abstract
Traditional approaches in studying the genetics of complex traits have focused on identifying specific genetic variants. However, the collective effects of variants have remained largely unexplored. Here, we evaluated whether traits could be influenced by the collective effects of variants across the entire protein coding-region of the genome or the entire genome. We studied the UK Biobank exome sequencing data of 167,246 individuals as well as the genome-wide SNP array data of 408,868 individuals. We calculated for each individual four different measures of genetic variation such as heterozygosity and number of variants and two different measures of the overall deleteriousness of all variants, and performed correlations with 17 representative traits that have been studied previously. Linear regression analysis was performed with adjustment for age, sex, and genetic principal components. The results showed a high correlation among the six different measures and an inverse association of two well-correlated traits (educational attainment and height) with the total number of all variants as well as the overall deleteriousness of all variants. We have also categorized the genes based on whether they are expressed in the brain and found that the association with educational attainment only held for the brain-expressed genes. No other traits examined showed a significant correlation with the brain-expressed genes. The study demonstrates that common traits could be studied by analyzing the overall genetic variation and suggests that educational attainment is inversely related to genetic variation.
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Affiliation(s)
- Mingrui Wang
- Center for Medical Genetics, Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, 110 Xiangya Road, Changsha, Hunan, 410078, PR China
| | - Shi Huang
- Center for Medical Genetics, Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, 110 Xiangya Road, Changsha, Hunan, 410078, PR China.
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Arathimos R, Fabbri C, Vassos E, Davis KAS, Pain O, Gillett A, Coleman JRI, Hanscombe K, Hagenaars S, Jermy B, Corbett A, Ballard C, Aarsland D, Creese B, Lewis CM. Latent subtypes of manic and/or irritable episode symptoms in two population-based cohorts. Br J Psychiatry 2022; 221:722-731. [PMID: 35049489 DOI: 10.1192/bjp.2021.184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
BACKGROUND Mood disorders are characterised by pronounced symptom heterogeneity, which presents a substantial challenge both to clinical practice and research. Identification of subgroups of individuals with homogeneous symptom profiles that cut across current diagnostic categories could provide insights in to the transdiagnostic relevance of individual symptoms, which current categorical diagnostic systems cannot impart. AIMS To identify groups of people with homogeneous clinical characteristics, using symptoms of manic and/or irritable mood, and explore differences between groups in diagnoses, functional outcomes and genetic liability. METHOD We used latent class analysis on eight binary self-reported symptoms of manic and irritable mood in the UK Biobank and PROTECT studies, to investigate how individuals formed latent subgroups. We tested associations between the latent classes and diagnoses of psychiatric disorders, sociodemographic characteristics and polygenic risk scores. RESULTS Five latent classes were derived in UK Biobank (N = 42 183) and were replicated in the independent PROTECT cohort (N = 4445), including 'minimally affected', 'inactive restless', active restless', 'focused creative' and 'extensively affected' individuals. These classes differed in disorder risk, polygenic risk score and functional outcomes. One class that experienced disruptive episodes of mostly irritable mood largely comprised cases of depression/anxiety, and a class of individuals with increased confidence/creativity reported comparatively lower disruptiveness and functional impairment. CONCLUSIONS Findings suggest that data-driven investigations of psychopathological symptoms that include sub-diagnostic threshold conditions can complement research of clinical diagnoses. Improved classification systems of psychopathology could investigate a weighted approach to symptoms, toward a more dimensional classification of mood disorders.
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Affiliation(s)
- Ryan Arathimos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; and NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, UK
| | - Chiara Fabbri
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; and Department of Biomedical and Neuromotor Sciences, University of Bologna, Italy
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; and NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, UK
| | - Katrina A S Davis
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, UK; and Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Oliver Pain
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; and NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, UK
| | - Alexandra Gillett
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Jonathan R I Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; and NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, UK
| | - Ken Hanscombe
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; and NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, UK
| | - Saskia Hagenaars
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Bradley Jermy
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; and NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, UK
| | - Anne Corbett
- Faculty of Medicine, Department of Medicine, Imperial College London, UK
| | - Clive Ballard
- Medical School, College of Medicine and Health, University of Exeter, UK
| | - Dag Aarsland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; and Centre for Age-Related Research, Stavanger University Hospital, Norway
| | - Byron Creese
- Medical School, College of Medicine and Health, University of Exeter, UK
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, UK; and Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King's College London, UK
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Savignac C, Villeneuve S, Badhwar A, Saltoun K, Shafighi K, Zajner C, Sharma V, Gagliano Taliun SA, Farhan S, Poirier J, Bzdok D. APOE alleles are associated with sex-specific structural differences in brain regions affected in Alzheimer's disease and related dementia. PLoS Biol 2022; 20:e3001863. [PMID: 36512526 PMCID: PMC9747055 DOI: 10.1371/journal.pbio.3001863] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 09/30/2022] [Indexed: 12/15/2022] Open
Abstract
Alzheimer's disease is marked by intracellular tau aggregates in the medial temporal lobe (MTL) and extracellular amyloid aggregates in the default network (DN). Here, we examined codependent structural variations between the MTL's most vulnerable structure, the hippocampus (HC), and the DN at subregion resolution in individuals with Alzheimer's disease and related dementia (ADRD). By leveraging the power of the approximately 40,000 participants of the UK Biobank cohort, we assessed impacts from the protective APOE ɛ2 and the deleterious APOE ɛ4 Alzheimer's disease alleles on these structural relationships. We demonstrate ɛ2 and ɛ4 genotype effects on the inter-individual expression of HC-DN co-variation structural patterns at the population level. Across these HC-DN signatures, recurrent deviations in the CA1, CA2/3, molecular layer, fornix's fimbria, and their cortical partners related to ADRD risk. Analyses of the rich phenotypic profiles in the UK Biobank cohort further revealed male-specific HC-DN associations with air pollution and female-specific associations with cardiovascular traits. We also showed that APOE ɛ2/2 interacts preferentially with HC-DN co-variation patterns in estimating social lifestyle in males and physical activity in females. Our structural, genetic, and phenotypic analyses in this large epidemiological cohort reinvigorate the often-neglected interplay between APOE ɛ2 dosage and sex and link APOE alleles to inter-individual brain structural differences indicative of ADRD familial risk.
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Affiliation(s)
- Chloé Savignac
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Sylvia Villeneuve
- Department of Neurology and Neurosurgery, Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- McConnell Brain Imaging Centre (BIC), MNI, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Centre for Studies in the Prevention of Alzheimer’s Disease, Douglas Mental Health Institute, McGill University, Montreal, Quebec, Canada
| | - AmanPreet Badhwar
- Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
- Centre de recherche de l’Institut universitaire de gériatrie de Montréal (CRIUGM), Montreal, Quebec, Canada
| | - Karin Saltoun
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Kimia Shafighi
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Chris Zajner
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Vaibhav Sharma
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Sarah A. Gagliano Taliun
- Department of Neurosciences & Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
- Montreal Heart Institute, Montréal, Quebec, Canada
| | - Sali Farhan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Judes Poirier
- Department of Neurology and Neurosurgery, Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Centre for Studies in the Prevention of Alzheimer’s Disease, Douglas Mental Health Institute, McGill University, Montreal, Quebec, Canada
| | - Danilo Bzdok
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- McConnell Brain Imaging Centre (BIC), MNI, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- School of Computer Science, McGill University, Montreal, Quebec, Canada
- Mila—Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada
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Beydoun MA, Weiss J, Banerjee S, Beydoun HA, Noren Hooten N, Evans MK, Zonderman AB. Race, polygenic risk and their association with incident dementia among older US adults. Brain Commun 2022; 4:fcac317. [PMID: 36569604 PMCID: PMC9772879 DOI: 10.1093/braincomms/fcac317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 09/26/2022] [Accepted: 11/29/2022] [Indexed: 12/02/2022] Open
Abstract
Dementia incidence increases steadily with age at rates that may vary across racial groups. This racial disparity may be attributable to polygenic risk, as well as lifestyle and behavioural factors. We examined whether Alzheimer's disease polygenic score and race predict Alzheimer's disease and other related dementia incidence differentially by sex and mediation through polygenic scores for other health and behavioural conditions. We used longitudinal data from the nationally representative Health and Retirement Study. We restricted participants to those with complete data on 31 polygenic scores, including Alzheimer's disease polygenic score (2006-2012). Among participants aged 55 years and older in 2008, we excluded those with any memory problems between 2006 and 2008 and included those with complete follow-up on incident Alzheimer's disease and all-cause dementia, between 2010 and 2018 (N = 9683), based on self- or proxy-diagnosis every 2 years (2010, 2012, 2014, 2016 and 2018). Cox proportional hazards and 4-way decomposition models were conducted. Analyses were also stratified by sex and by race. There were racial differences in all-cause dementia incidence (age and sex-adjusted model, per standard deviation: hazard ratio, HR = 1.34, 95% confidence interval, CI: 1.09-1.65, P = 0.007), partially driven by educational attainment and income. We also found independent associations of race (age and sex-adjusted model, African American versus White adults: HR = 2.07, 95% CI: 1.52-2.83, P < 0.001) and Alzheimer's disease polygenic score (age and sex-adjusted model, per SD: HR = 1.37, 95% CI: 1.00-1.87, P < 0.001) with Alzheimer's disease incidence, including sex differences whereby women had a stronger effect of Alzheimer's disease polygenic score on Alzheimer's disease incidence compared with men (P < 0.05 for sex by Alzheimer's disease polygenic score interaction) adjusting for race and other covariates. The total impact of Alzheimer's disease polygenic scores on Alzheimer's disease incidence was mostly direct, while the effect of race on all-cause dementia incidence was mediated through socio-economic, lifestyle and health-related factors. Finally, among the 30 polygenic scores we examined, the total effects on the pathway Alzheimer's disease polygenic score --> Other polygenic score --> Incident Alzheimer's or all-cause dementia, were statistically significant for all, driven primarily by the controlled direct effect (P< 0. 001). In conclusion, both race and Alzheimer's disease polygenic scores were associated independently with Alzheimer's disease and all-cause dementia incidence. Alzheimer's disease polygenic score was more strongly linked to incident Alzheimer's disease among women, while racial difference in all-cause dementia was explained by other factors including socio-economic status.
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Affiliation(s)
- May A Beydoun
- Correspondence to: May A. Beydoun, PhD NIH Biomedical Research Center National Institute on Aging, IRP 251 Bayview Blvd. Suite 100, Room #: 04B118, Baltimore, MD 21224, USA E-mail:
| | | | - Sri Banerjee
- College of Health Professions, School of Health Sciences, Walden University, Baltimore, MD 21202, USA
| | - Hind A Beydoun
- Department of Research Programs, Fort Belvoir Community Hospital, Fort Belvoir, VA 22060, USA
| | - Nicole Noren Hooten
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
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Murillo-García N, Barrio-Martínez S, Setién-Suero E, Soler J, Papiol S, Fatjó-Vilas M, Ayesa-Arriola R. Overlap between genetic variants associated with schizophrenia spectrum disorders and intelligence quotient: a systematic review. J Psychiatry Neurosci 2022; 47:E393-E408. [PMID: 36414327 PMCID: PMC9710545 DOI: 10.1503/jpn.220026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 06/27/2022] [Accepted: 09/06/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND To study whether there is genetic overlap underlying the risk for schizophrenia spectrum disorders (SSDs) and low intelligence quotient (IQ), we reviewed and summarized the evidence on genetic variants associated with both traits. METHODS We performed this review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and preregistered it in PROSPERO. We searched the Medline databases via PubMed, PsycInfo, Web of Science and Scopus. We included studies in adults with a diagnosis of SSD that explored genetic variants (single nucleotide polymorphisms [SNPs], copy number variants [CNVs], genomic insertions or genomic deletions), estimated IQ and studied the relationship between genetic variability and both traits (SSD and IQ). We synthesized the results and assessed risk of bias using the Quality of Genetic Association Studies (Q-Genie) tool. RESULTS Fifty-five studies met the inclusion criteria (45 case-control, 9 cross-sectional, 1 cohort), of which 55% reported significant associations for genetic variants involved in IQ and SSD. The SNPs more frequently explored through candidate gene studies were in COMT, DTNBP1, BDNF and TCF4. Through genome-wide association studies, 2 SNPs in CHD7 and GATAD2A were associated with IQ in patients with SSD. The studies on CNVs suggested significant associations between structural variants and low IQ in patients with SSD. LIMITATIONS Overall, primary studies used heterogeneous IQ measurement tools and had small samples. Grey literature was not screened. CONCLUSION Genetic overlap between SSD and IQ supports the neurodevelopmental hypothesis of schizophrenia. Most of the risk polymorphisms identified were in genes relevant to brain development, neural proliferation and differentiation, and synaptic plasticity.
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Affiliation(s)
| | | | | | | | | | | | - Rosa Ayesa-Arriola
- From the Research Unit in Mental Illness, Valdecilla Biomedical Research Institute, Santander, Cantabria, Spain (Murillo-García, Barrio-Martínez, Ayesa-Arriola); the Department of Molecular Biology, Faculty of Medicine, University of Cantabria, Santander, Cantabria, Spain (Murillo-García, Ayesa-Arriola); the Faculty of Psychology, University Complutense of Madrid, Madrid, Spain (Barrio-Martínez); the Department of Psychology, Faculty of Health Sciences, University of Deusto, Bilbao, Basque Country, Spain (Setién-Suero); the Biomedical Research Networking Center for Mental Health (CIBERSAM), Madrid, Madrid, Spain (Soler, Papiol, Fatjó-Vilas, Ayesa-Arriola); the Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain (Soler, Fatjó-Vilas); the Institut de Biomedicina de la Universitat de Barcelona, Universitat de Barcelona, Barcelona, Spain (Soler); the Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, Germany (Papiol); the Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany (Papiol); the FIDMAG Sisters Hospitallers Research Foundation, Sant Boi de Llobregat, Barcelona, Spain (Fatjó-Vilas)
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39
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Duński E, Pękowska A. Keeping the balance: Trade-offs between human brain evolution, autism, and schizophrenia. Front Genet 2022; 13:1009390. [DOI: 10.3389/fgene.2022.1009390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 10/12/2022] [Indexed: 11/22/2022] Open
Abstract
The unique qualities of the human brain are a product of a complex evolutionary process. Evolution, famously described by François Jacob as a “tinkerer,” builds upon existing genetic elements by modifying and repurposing them for new functions. Genetic changes in DNA may lead to the emergence of new genes or cause altered gene expression patterns. Both gene and regulatory element mutations may lead to new functions. Yet, this process may lead to side-effects. An evolutionary trade-off occurs when an otherwise beneficial change, which is important for evolutionary success and is under strong positive selection, concurrently results in a detrimental change in another trait. Pleiotropy occurs when a gene affects multiple traits. Antagonistic pleiotropy is a phenomenon whereby a genetic variant leads to an increase in fitness at one life-stage or in a specific environment, but simultaneously decreases fitness in another respect. Therefore, it is conceivable that the molecular underpinnings of evolution of highly complex traits, including brain size or cognitive ability, under certain conditions could result in deleterious effects, which would increase the susceptibility to psychiatric or neurodevelopmental diseases. Here, we discuss possible trade-offs and antagonistic pleiotropies between evolutionary change in a gene sequence, dosage or activity and the susceptibility of individuals to autism spectrum disorders and schizophrenia. We present current knowledge about genes and alterations in gene regulatory landscapes, which have likely played a role in establishing human-specific traits and have been implicated in those diseases.
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40
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Lahti J, Tuominen S, Yang Q, Pergola G, Ahmad S, Amin N, Armstrong NJ, Beiser A, Bey K, Bis JC, Boerwinkle E, Bressler J, Campbell A, Campbell H, Chen Q, Corley J, Cox SR, Davies G, De Jager PL, Derks EM, Faul JD, Fitzpatrick AL, Fohner AE, Ford I, Fornage M, Gerring Z, Grabe HJ, Grodstein F, Gudnason V, Simonsick E, Holliday EG, Joshi PK, Kajantie E, Kaprio J, Karell P, Kleineidam L, Knol MJ, Kochan NA, Kwok JB, Leber M, Lam M, Lee T, Li S, Loukola A, Luck T, Marioni RE, Mather KA, Medland S, Mirza SS, Nalls MA, Nho K, O'Donnell A, Oldmeadow C, Painter J, Pattie A, Reppermund S, Risacher SL, Rose RJ, Sadashivaiah V, Scholz M, Satizabal CL, Schofield PW, Schraut KE, Scott RJ, Simino J, Smith AV, Smith JA, Stott DJ, Surakka I, Teumer A, Thalamuthu A, Trompet S, Turner ST, van der Lee SJ, Villringer A, Völker U, Wilson RS, Wittfeld K, Vuoksimaa E, Xia R, Yaffe K, Yu L, Zare H, Zhao W, Ames D, Attia J, Bennett DA, Brodaty H, Chasman DI, Goldman AL, Hayward C, Ikram MA, Jukema JW, Kardia SLR, Lencz T, Loeffler M, Mattay VS, Palotie A, Psaty BM, Ramirez A, Ridker PM, Riedel-Heller SG, Sachdev PS, Saykin AJ, Scherer M, Schofield PR, Sidney S, Starr JM, Trollor J, Ulrich W, Wagner M, Weir DR, Wilson JF, Wright MJ, Weinberger DR, Debette S, Eriksson JG, Mosley TH, Launer LJ, van Duijn CM, Deary IJ, Seshadri S, Räikkönen K. Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning. Mol Psychiatry 2022; 27:4419-4431. [PMID: 35974141 PMCID: PMC9734053 DOI: 10.1038/s41380-022-01710-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 07/11/2022] [Accepted: 07/13/2022] [Indexed: 12/14/2022]
Abstract
Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.
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Affiliation(s)
- Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.
- Turku Institute of Advanced Studies, University of Turku, Turku, Finland.
| | - Samuli Tuominen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Giulio Pergola
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Murdoch University, Murdoch, WA, Australia
| | - Alexa Beiser
- Department of Biostatistics, Boston University, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Katharina Bey
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Janie Corley
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, New York, NY, USA
| | - Eske M Derks
- Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Annette L Fitzpatrick
- Department of Family Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Global Health, University of Washington, Seattle, WA, USA
| | - Alison E Fohner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Institute of Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Ian Ford
- Robertson Center for Biostatistics, University of Glasgow, Glasgow, UK
| | - Myriam Fornage
- McGovern Medical School, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Zachary Gerring
- Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases, Greifswald, Germany
| | - Francine Grodstein
- Channing Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Harvard School of Public Health, Boston, MA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Assocation, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Eleanor Simonsick
- Translational Gerontology Branch, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Elizabeth G Holliday
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Institute of Social and Preventive Medicine, University of Lausanne, Lausanne, Switzerland
| | - Eero Kajantie
- National Institute for Health and Welfare, Helsinki and Oulu, Oulu, Finland
- Hospital for Children and Adolescents, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Pauliina Karell
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases, Bonn, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Nicole A Kochan
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - John B Kwok
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Markus Leber
- Department of Psychiatry, University of Cologne, Cologne, Germany
| | - Max Lam
- Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | - Teresa Lee
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - Shuo Li
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Anu Loukola
- Helsinki Biobank, University of Helsinki Central Hospital, Helsinki, Finland
| | - Tobias Luck
- Department of Economic and Social Sciences & Institute of Social Medicine, Rehabilitation Sciences and Healthcare Research, University of Applied Sciences Nordhausen, Nordhausen, Germany
- University of Leipzig, Leipzig, Germany
- LIFE Leipzig Research Center for Civilization Diseases, Leipzig, Germany
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Karen A Mather
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Sunnybrook Health Sciences Centre, University of Toronto, Randwick, NSW, Australia
| | - Sarah Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Saira S Mirza
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adrienne O'Donnell
- Department of Biostatistics, Boston University, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Christopher Oldmeadow
- Clinical Research Design, IT and Statistical Support Unit, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Jodie Painter
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Alison Pattie
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Simone Reppermund
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Richard J Rose
- Department of Psychological & Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA
| | - Vijay Sadashivaiah
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Claudia L Satizabal
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Peter W Schofield
- Neuropsychiatry Service, Hunter New England Local Health District, Charlestown, NSW, Australia
| | - Katharina E Schraut
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, Royal Infirmary of Edinburgh, University of Edinburgh, Edinburgh, UK
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Jeannette Simino
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Albert V Smith
- Icelandic Heart Assocation, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
- Institute of Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, USA
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Stella Trompet
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Sven J van der Lee
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurology and Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Arno Villringer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Day Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, Department Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Robert S Wilson
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases, Greifswald, Germany
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Rui Xia
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kristine Yaffe
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Habil Zare
- Department of Cell Systems & Anatomy, The University of Texas Health Science Center, San Antonio, TX, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas, San Antonio, TX, USA
- University of Texas Health Sciences Center, Houston, NA, US
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - David Ames
- National Ageing Research Institute, Parkville, Melbourne, VIC, Australia
- University of Melbourne, Academic Unit for Psychiatry of Old Age, St George's Hospital, Melbourne, VIC, Australia
| | - John Attia
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia
- Clinical Research Design, IT and Statistical Support Unit, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Henry Brodaty
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Dementia Collaborative Research Centre, University of New South Wales, Sydney, NSW, Australia
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Aaron L Goldman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Todd Lencz
- Hofstra Northwell School of Medicine, Hempstead, NY, USA
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Venkata S Mattay
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Food and Drug Administration, Washington, DC, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology and Department of Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Heath Research Institute, Seattle, WA, USA
| | - Alfredo Ramirez
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
- Department of Psychiatry, University of Cologne, Cologne, Germany
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Martin Scherer
- Institute of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Peter R Schofield
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Randwick, NSW, Australia
| | - Stephen Sidney
- Kaiser Permanente Northern California, Division of Research, Oakland, CA, USA
| | - John M Starr
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Julian Trollor
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - William Ulrich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Michael Wagner
- German Center for Neurodegenerative Diseases, Bonn, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Stephanie Debette
- Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, University of Bordeaux, Bordeaux, France
- Bordeaux University Hospital (CHU Bordeaux), Department of Neurology, Bordeaux, France
| | - Johan G Eriksson
- Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Helsinki, Singapore
| | - Thomas H Mosley
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Public Health, Oxford University, Oxford, UK
| | - Ian J Deary
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
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41
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Mitchell BL, Hansell NK, McAloney K, Martin NG, Wright MJ, Renteria ME, Grasby KL. Polygenic influences associated with adolescent cognitive skills. Intelligence 2022. [DOI: 10.1016/j.intell.2022.101680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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42
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Antaki D, Guevara J, Maihofer AX, Klein M, Gujral M, Grove J, Carey CE, Hong O, Arranz MJ, Hervas A, Corsello C, Vaux KK, Muotri AR, Iakoucheva LM, Courchesne E, Pierce K, Gleeson JG, Robinson EB, Nievergelt CM, Sebat J. A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex. Nat Genet 2022; 54:1284-1292. [PMID: 35654974 PMCID: PMC9474668 DOI: 10.1038/s41588-022-01064-5] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 03/28/2022] [Indexed: 01/21/2023]
Abstract
The genetic etiology of autism spectrum disorder (ASD) is multifactorial, but how combinations of genetic factors determine risk is unclear. In a large family sample, we show that genetic loads of rare and polygenic risk are inversely correlated in cases and greater in females than in males, consistent with a liability threshold that differs by sex. De novo mutations (DNMs), rare inherited variants and polygenic scores were associated with various dimensions of symptom severity in children and parents. Parental age effects on risk for ASD in offspring were attributable to a combination of genetic mechanisms, including DNMs that accumulate in the paternal germline and inherited risk that influences behavior in parents. Genes implicated by rare variants were enriched in excitatory and inhibitory neurons compared with genes implicated by common variants. Our results suggest that a phenotypic spectrum of ASD is attributable to a spectrum of genetic factors that impact different neurodevelopmental processes.
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Affiliation(s)
- Danny Antaki
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - James Guevara
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Adam X Maihofer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Marieke Klein
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Madhusudan Gujral
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jakob Grove
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine and Center for Integrative Sequencing, iSEQ, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Caitlin E Carey
- Harvard T.H. Chan School of Public Health, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Oanh Hong
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Maria J Arranz
- Research Laboratory Unit, Fundacio Docencia i Recerca Mutua, Terrassa, Spain
| | - Amaia Hervas
- Child and Adolescent Mental Health Unit, Hospital Universitari Mútua de Terrassa, Barcelona, Spain
| | - Christina Corsello
- TEACCH Autism Program, University of North Carolina, Chapel Hill, NC, USA
| | | | - Alysson R Muotri
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics and Department of Cellular & Molecular Medicine, University of California San Diego, School of Medicine, Center for Academic Research and Training in Anthropogeny, Archealization Center, Kavli Institute for Brain and Mind, La Jolla, CA, USA
| | - Lilia M Iakoucheva
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Autism Center of Excellence, University of California San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Autism Center of Excellence, University of California San Diego, La Jolla, CA, USA
| | - Joseph G Gleeson
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Elise B Robinson
- Harvard T.H. Chan School of Public Health, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | | | - Jonathan Sebat
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA.
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
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43
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Greenwood TA. Genetic Influences on Cognitive Dysfunction in Schizophrenia. Curr Top Behav Neurosci 2022; 63:291-314. [PMID: 36029459 DOI: 10.1007/7854_2022_388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Schizophrenia is a severe and debilitating psychotic disorder that is highly heritable and relatively common in the population. The clinical heterogeneity associated with schizophrenia is substantial, with patients exhibiting a broad range of deficits and symptom severity. Large-scale genomic studies employing a case-control design have begun to provide some biological insight. However, this strategy combines individuals with clinically diverse symptoms and ignores the genetic risk that is carried by many clinically unaffected individuals. Consequently, the majority of the genetic architecture underlying schizophrenia remains unexplained, and the pathways by which the implicated variants contribute to the clinically observable signs and symptoms are still largely unknown. Parsing the complex, clinical phenotype of schizophrenia into biologically relevant components may have utility in research aimed at understanding the genetic basis of liability. Cognitive dysfunction is a hallmark symptom of schizophrenia that is associated with impaired quality of life and poor functional outcome. Here, we examine the value of quantitative measures of cognitive dysfunction to objectively target the underlying neurobiological pathways and identify genetic variants and gene networks contributing to schizophrenia risk. For a complex disorder, quantitative measures are also more efficient than diagnosis, allowing for the identification of associated genetic variants with fewer subjects. Such a strategy supplements traditional analyses of schizophrenia diagnosis, providing the necessary biological insight to help translate genetic findings into actionable treatment targets. Understanding the genetic basis of cognitive dysfunction in schizophrenia may thus facilitate the development of novel pharmacological and procognitive interventions to improve real-world functioning.
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Affiliation(s)
- Tiffany A Greenwood
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
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44
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Korologou-Linden R, Bhatta L, Brumpton BM, Howe LD, Millard LAC, Kolaric K, Ben-Shlomo Y, Williams DM, Smith GD, Anderson EL, Stergiakouli E, Davies NM. The causes and consequences of Alzheimer's disease: phenome-wide evidence from Mendelian randomization. Nat Commun 2022; 13:4726. [PMID: 35953482 PMCID: PMC9372151 DOI: 10.1038/s41467-022-32183-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 07/20/2022] [Indexed: 12/12/2022] Open
Abstract
Alzheimer's disease (AD) has no proven causal and modifiable risk factors, or effective interventions. We report a phenome-wide association study (PheWAS) of genetic liability for AD in 334,968 participants of the UK Biobank study, stratified by age. We also examined the effects of AD genetic liability on previously implicated risk factors. We replicated these analyses in the HUNT study. PheWAS hits and previously implicated risk factors were followed up in a Mendelian randomization (MR) framework to identify the causal effect of each risk factor on AD risk. A higher genetic liability for AD was associated with medical history and cognitive, lifestyle, physical and blood-based measures as early as 39 years of age. These effects were largely driven by the APOE gene. The follow-up MR analyses were primarily null, implying that most of these associations are likely to be a consequence of prodromal disease or selection bias, rather than the risk factor causing the disease.
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Affiliation(s)
- Roxanna Korologou-Linden
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - Laxmi Bhatta
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ben M Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
| | - Laura D Howe
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Louise A C Millard
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
- Intelligent Systems Laboratory, Department of Computer Science, University of Bristol, Bristol, UK
| | - Katarina Kolaric
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Yoav Ben-Shlomo
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Dylan M Williams
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Emma L Anderson
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Evie Stergiakouli
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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45
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Yang M, Cui Y, Xue M, Forster MT, Lang X, Xiu M, Li Z, Zhang X. Sexual dimorphism in the relationship between Forkhead-Box P2 and BMI with cognitive deficits in schizophrenia. Front Aging Neurosci 2022; 14:920352. [PMID: 35992594 PMCID: PMC9381810 DOI: 10.3389/fnagi.2022.920352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/06/2022] [Indexed: 11/13/2022] Open
Abstract
FOXP2, cognitive deficits, and schizophrenia are associated with neurodegenerative pathophyisiology. Mounting evidence suggests that body mass index (BMI) and FOXP2 may contribute to cognitive deficits in schizophrenia. However, the sex difference in the contribution of FOXP2 and BMI, as well as their potential interaction with cognitive deficits in schizophrenia, have not been investigated. A total of 867 schizophrenia patients and 402 controls were recruited. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The polymorphism rs10447760 of the FOXP2 gene was genotyped. Male schizophrenia patients had superior language performance compared to female patients (F = 17.83; pBonferroni < 0.0001). BMI was positively associated with language scores in male patients with schizophrenia (ß = 0.60, t = 3.30, p = 0.001), as well as in patients with schizophrenia who carried the FOXP2 rs10447760 CC genotype (ß = 0.53, t = 3.16, p = 0.002). Interestingly, this association was only found in male patients with schizophrenia who also carried the FOXP2 rs10447760 CC genotype (ß = 0.63, t = 3.44, p = 0.001). Our study reveals a sex difference in the language deficits of schizophrenia patients and shows sexual dimorphism in the contribution of FOXP2, BMI, and their interaction to cognitive deficits in patients with schizophrenia.
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Affiliation(s)
- Mi Yang
- The Fourth Hospital of Chengdu, Chengdu, China
| | - Ying Cui
- Qingdao Mental Health Center, Qingdao, China
| | - Mei Xue
- Qingdao Mental Health Center, Qingdao, China
| | - Mattew T. Forster
- Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Xiaoe Lang
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Meihong Xiu
- Beijing HuiLongGuan Hospital, Peking University, Beijing, China
- *Correspondence: Zezhi Li Meihong Xiu Xiangyang Zhang
| | - Zezhi Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- *Correspondence: Zezhi Li Meihong Xiu Xiangyang Zhang
| | - Xiangyang Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- *Correspondence: Zezhi Li Meihong Xiu Xiangyang Zhang
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46
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Gillespie NA, Gentry AE, Kirkpatrick RM, Reynolds CA, Mathur R, Kendler KS, Maes HH, Webb BT, Peterson RE. Determining the stability of genome-wide factors in BMI between ages 40 to 69 years. PLoS Genet 2022; 18:e1010303. [PMID: 35951648 PMCID: PMC9398001 DOI: 10.1371/journal.pgen.1010303] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 08/23/2022] [Accepted: 06/21/2022] [Indexed: 11/18/2022] Open
Abstract
Genome-wide association studies (GWAS) have successfully identified common variants associated with BMI. However, the stability of aggregate genetic variation influencing BMI from midlife and beyond is unknown. By analysing 165,717 men and 193,073 women from the UKBiobank, we performed BMI GWAS on six independent five-year age intervals between 40 and 72 years. We then applied genomic structural equation modeling to test competing hypotheses regarding the stability of genetic effects for BMI. LDSR genetic correlations between BMI assessed between ages 40 to 73 were all very high and ranged 0.89 to 1.00. Genomic structural equation modeling revealed that molecular genetic variance in BMI at each age interval could not be explained by the accumulation of any age-specific genetic influences or autoregressive processes. Instead, a common set of stable genetic influences appears to underpin genome-wide variation in BMI from middle to early old age in men and women alike.
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Affiliation(s)
- Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- QIMR Berghofer Medical Research Institute, Herston, Australia
| | - Amanda Elswick Gentry
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Robert M. Kirkpatrick
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, California, United States of America
| | - Ravi Mathur
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, North Carolina, United States of America
| | - Kenneth S. Kendler
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Hermine H. Maes
- Virginia Institute for Psychiatric and Behavior Genetics, Departments of Human and Molecular Genetics, Psychiatry, & Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Bradley T. Webb
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, North Carolina, United States of America
| | - Roseann E. Peterson
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
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47
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Kuo SS, Musket CW, Rupert PE, Almasy L, Gur RC, Prasad KM, Roalf DR, Gur RE, Nimgaonkar VL, Pogue-Geile MF. Age-dependent patterns of schizophrenia genetic risk affect cognition. Schizophr Res 2022; 246:39-48. [PMID: 35709646 DOI: 10.1016/j.schres.2022.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 03/15/2022] [Accepted: 05/15/2022] [Indexed: 11/15/2022]
Abstract
Cognition shares substantial genetic overlap with schizophrenia, yet it remains unclear whether such genetic effects become significant during developmental periods of elevated risk for schizophrenia, such as the peak age of onset. We introduce an investigative framework integrating epidemiological, developmental, and genetic approaches to determine whether genetic effects shared between schizophrenia and cognition are significant across periods of differing risk for schizophrenia onset, and whether these effects are shared with depression. 771 European-American participants, including 636 (ages 15-84 years) from families with at least two first-degree relatives with schizophrenia and 135 unrelated controls, were divided into three age-risk groups based on ages relative to epidemiological age of onset patterns for schizophrenia: Pre-Peak (before peak age-of-onset: 15 to 22 years), Post-Peak (after peak age-of-onset: 23-42 years), and Plateau (during plateau of age-of-onset: over 42 years). For general cognition and 11 specific cognitive traits, we estimated genetic correlations with schizophrenia and with depression within each age-risk group. Genetic effects shared between deficits in general cognition and schizophrenia were nonsignificant before peak age of onset, yet were high and significant after peak age of onset and during the plateau of onset. These age-dependent genetic effects were largely consistent across specific cognitive traits and not transdiagnostically shared with depression. Schizophrenia genetic effects appear to influence cognitive traits in an age-dependent manner, supporting late developmental and perhaps neurodegenerative models that hypothesize increased expression of schizophrenia risk genes during and after the peak age of risk. Our findings underscore the utility of cognitive traits for tracking schizophrenia genetic effects across the lifespan.
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Affiliation(s)
- Susan S Kuo
- Department of Psychology, University of Pittsburgh, United States of America; Stanley Center for Psychiatric Genetics, Broad Institute of MIT and Harvard, United States of America; Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, United States of America
| | - Christie W Musket
- Department of Psychology, University of Pittsburgh, United States of America
| | - Petra E Rupert
- Department of Psychology, University of Pittsburgh, United States of America
| | - Laura Almasy
- Department of Genetics, University of Pennsylvania, United States of America
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, United States of America
| | - Konasale M Prasad
- Department of Psychiatry, University of Pittsburgh, United States of America; Department of Bioengineering, University of Pittsburgh, United States of America; Veteran Affairs Pittsburgh Healthcare System, United States of America
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania, United States of America
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, United States of America
| | - Vishwajit L Nimgaonkar
- Department of Psychiatry, University of Pittsburgh, United States of America; Department of Human Genetics, University of Pittsburgh, United States of America
| | - Michael F Pogue-Geile
- Department of Psychology, University of Pittsburgh, United States of America; Department of Psychiatry, University of Pittsburgh, United States of America.
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48
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Valge M, Meitern R, Hõrak P. Sexually antagonistic selection on educational attainment and body size in Estonian children. Ann N Y Acad Sci 2022; 1516:271-285. [PMID: 35815461 DOI: 10.1111/nyas.14859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Natural selection is a key mechanism of evolution, which results from the differential reproduction of phenotypes. We describe fecundity selection at different parity transitions on 15 anthropometric traits and educational attainment in Estonian children sampled in the middle of 20th century. The direction of selection on educational attainment and bodily traits was sexually antagonistic, and it occurred via different parity transitions in boys and girls. Compared to boys with primary education, obtaining tertiary education was associated with 3.5 times and secondary education two times higher odds of becoming a father. Transition to motherhood was not related to educational attainment, while education above primary was associated with lower odds (OR = 0.5-0.7) to progression to parities above one and two. Selection on anthropometric traits occurred almost exclusively via childlessness in boys, while among the girls, most of the traits that were associated with becoming a mother were additionally associated with a transition from one child to higher parities. Male (but not female) fitness was thus primarily determined by traits related to mating success. Selection favored stronger and larger boys and smaller girls. Selection on girls favored some traits that associate with perceived femininity, while other feminine traits were selected against.
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Affiliation(s)
- Markus Valge
- Department of Zoology, University of Tartu, Tartu, Estonia
| | | | - Peeter Hõrak
- Department of Zoology, University of Tartu, Tartu, Estonia
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49
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Kell HJ, McCabe KO, Lubinski D, Benbow CP. Wrecked by Success? Not to Worry. Perspect Psychol Sci 2022; 17:1291-1321. [PMID: 35686876 DOI: 10.1177/17456916211055637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
We examined the wrecked-by-success hypothesis. Initially formalized by Sigmund Freud, this hypothesis has become pervasive throughout the humanities, popular press, and modern scientific literature. The hypothesis implies that truly outstanding occupational success often exacts a heavy toll on psychological, interpersonal, and physical well-being. Study 1 tested this hypothesis in three cohorts of 1,826 high-potential, intellectually gifted individuals. Participants with exceptionally successful careers were compared with those of their gender-equivalent intellectual peers with more typical careers on well-known measures of psychological well-being, flourishing, core self-evaluations, and medical maladies. Family relationships, comfort with aging, and life satisfaction were also assessed. Across all three cohorts, those deemed occupationally outstanding individuals were similar to or healthier than their intellectual peers across these metrics. Study 2 served as a constructive replication of Study 1 but used a different high-potential sample: 496 elite science/technology/engineering/mathematics (STEM) doctoral students identified in 1992 and longitudinally tracked for 25 years. Study 2 replicated the findings from Study 1 in all important respects. Both studies found that exceptionally successful careers were not associated with medical frailty, psychological maladjustment, and compromised interpersonal and family relationships; if anything, overall, people with exceptionally successful careers were medically and psychologically better off.
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Affiliation(s)
- Harrison J Kell
- Center for Education and Career Development, Educational Testing Service, Princeton, New Jersey
| | | | - David Lubinski
- Department of Psychology and Human Development, Vanderbilt University
| | - Camilla P Benbow
- Department of Psychology and Human Development, Vanderbilt University
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50
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Wigdor EM, Weiner DJ, Grove J, Fu JM, Thompson WK, Carey CE, Baya N, van der Merwe C, Walters RK, Satterstrom FK, Palmer DS, Rosengren A, Bybjerg-Grauholm J, Hougaard DM, Mortensen PB, Daly MJ, Talkowski ME, Sanders SJ, Bishop SL, Børglum AD, Robinson EB. The female protective effect against autism spectrum disorder. Cell Genom 2022; 2:100134. [PMID: 36778135 PMCID: PMC9903803 DOI: 10.1016/j.xgen.2022.100134] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 02/26/2022] [Accepted: 04/27/2022] [Indexed: 12/20/2022]
Abstract
Autism spectrum disorder (ASD) is diagnosed three to four times more frequently in males than in females. Genetic studies of rare variants support a female protective effect (FPE) against ASD. However, sex differences in common inherited genetic risk for ASD are less studied, particularly within families. Leveraging the Danish iPSYCH resource, we found siblings of female ASD cases (n = 1,707) had higher rates of ASD than siblings of male ASD cases (n = 6,270; p < 1.0 × 10-10). In the Simons Simplex and SPARK collections, mothers of ASD cases (n = 7,436) carried more polygenic risk for ASD than fathers of ASD cases (n = 5,926; 0.08 polygenic risk score [PRS] SD; p = 7.0 × 10-7). Further, male unaffected siblings under-inherited polygenic risk (n = 1,519; p = 0.03). Using both epidemiologic and genetic approaches, our findings strongly support an FPE against ASD's common inherited influences.
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Affiliation(s)
- Emilie M. Wigdor
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
| | - Daniel J. Weiner
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jakob Grove
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, 8000 Aarhus, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, 8000 Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
| | - Jack M. Fu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Caitlin E. Carey
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Nikolas Baya
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Celia van der Merwe
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Raymond K. Walters
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - F. Kyle Satterstrom
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Duncan S. Palmer
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Anders Rosengren
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
- Institute of Biological Psychiatry, MHC Sct Hans, Copenhagen University Hospital, 4000 Roskilde, Denmark
| | - Jonas Bybjerg-Grauholm
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, 2300 Copenhagen, Denmark
| | | | - David M. Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, 2300 Copenhagen, Denmark
| | - Preben Bo Mortensen
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, 8000 Aarhus, Denmark
- Institute of Biological Psychiatry, MHC Sct Hans, Copenhagen University Hospital, 4000 Roskilde, Denmark
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark
- Center for Integrated Register-based Research, Aarhus University, 8210 Aarhus, Denmark
| | - Mark J. Daly
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Finnish Institute for Molecular Medicine, University of Helsinki, 00290 Helsinki, Finland
| | - Michael E. Talkowski
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Stephan J. Sanders
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Somer L. Bishop
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Anders D. Børglum
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, 8000 Aarhus, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, 8000 Aarhus, Denmark
- Institute of Biological Psychiatry, MHC Sct Hans, Copenhagen University Hospital, 4000 Roskilde, Denmark
| | - Elise B. Robinson
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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