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Zhang X, Grove J, Gu Y, Buus CK, Nielsen LK, Neufeld SAS, Koko M, Malawsky DS, Wade E, Verhoef E, Gui A, Hegemann L, Geschwind DH, Wray NR, Havdahl A, Ronald A, Pourcain BS, Robinson EB, Bourgeron T, Baron-Cohen S, Børglum AD, Martin HC, Warrier V. An axis of genetic heterogeneity in autism is indexed by age at diagnosis and is associated with varying developmental and mental health profiles. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.31.24311279. [PMID: 39132493 PMCID: PMC11312648 DOI: 10.1101/2024.07.31.24311279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
There is growing recognition that earliest signs of autism need not clearly manifest in the first three years of life. To what extent is this variation in developmental trajectories associated with age at autism diagnosis? Does the genetic profile of autism vary with age at autism diagnosis? Using longitudinal data from four birth cohorts, we demonstrate that two different trajectories of socio-emotional behaviours are associated with age at diagnosis. We further demonstrate that the age at autism diagnosis is partly heritable (h 2 SNP = 0.12, s.e.m = 0.01), and is associated with two moderately correlated (r g = 0.38, s.e.m = 0.07) autism polygenic factors. One of these factors is associated with earlier diagnosis of autism, lower social and communication abilities in early childhood. The second factor is associated with later autism diagnosis, increased socio-emotional difficulties in adolescence, and has moderate to high positive genetic correlations with Attention-Deficit/Hyperactivity Disorder, mental health conditions, and trauma. Overall, our research identifies an axis of heterogeneity in autism, indexed by age at diagnosis, which partly explains heterogeneity in autism and the profiles of co-occurring neurodevelopmental and mental health profiles. Our findings have important implications for how we conceptualise autism and provide one model to explain some of the diversity within autism.
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Martini MI, Butwicka A, Du Rietz E, Kanina A, Rosenqvist MA, Larsson H, Lichtenstein P, Taylor MJ. Age effects on autism heritability and etiological stability of autistic traits. J Child Psychol Psychiatry 2024. [PMID: 38239074 DOI: 10.1111/jcpp.13949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/19/2023] [Indexed: 02/20/2024]
Abstract
BACKGROUND Autism and autistic traits onset in childhood but persist into adulthood. Little is known about how genetic and environmental factors influence autism and autistic traits into adulthood. We aimed to determine age effects on the heritability of clinically diagnosed autism and the etiological stability of autistic traits from childhood to adulthood using twin methods. METHODS From 23,849 twin pairs in the Swedish Twin Register born between 1959 and 2010, we identified 485 individuals (1.01%, 31.5% female) with a clinical autism diagnosis. We estimated and compared the relative contribution of genetic, shared, and nonshared environmental influences to autism in childhood and adulthood. We further used multivariate twin analysis with four measurement points among 1,348 twin pairs in the longitudinal Twin Study of Child and Adolescent Development to assess the phenotypic and etiological stability of autistic traits - measured with three scales from the Child Behavior Checklist - from childhood to adulthood. RESULTS Autism heritability was comparable from childhood, (96% [95% CI, 76-99%]) to adulthood (87% [67-96%]). Autistic traits were moderately stable (phenotypic correlation = 0.35-0.61) from childhood to adulthood, and their heritability varied between 52 and 71%. We observed stable as well as newly emerging genetic influences on autistic traits from ages 8-9 to 19-20, and unique nonshared environmental influences at each age. CONCLUSIONS Genetic factors are important for autism and autistic traits in adulthood and separate genetic studies in adults are warranted.
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Affiliation(s)
- Miriam I Martini
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Agnieszka Butwicka
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Division of Mental Health Services, R&D Department, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland
| | - Ebba Du Rietz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Aleksandra Kanina
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mina A Rosenqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mark J Taylor
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Pender R, Fearon P, St Pourcain B, Heron J, Mandy W. Developmental trajectories of autistic social traits in the general population. Psychol Med 2023; 53:814-822. [PMID: 34154678 DOI: 10.1017/s0033291721002166] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Autistic people show diverse trajectories of autistic traits over time, a phenomenon labelled 'chronogeneity'. For example, some show a decrease in symptoms, whilst others experience an intensification of difficulties. Autism spectrum disorder (ASD) is a dimensional condition, representing one end of a trait continuum that extends throughout the population. To date, no studies have investigated chronogeneity across the full range of autistic traits. We investigated the nature and clinical significance of autism trait chronogeneity in a large, general population sample. METHODS Autistic social/communication traits (ASTs) were measured in the Avon Longitudinal Study of Parents and Children using the Social and Communication Disorders Checklist (SCDC) at ages 7, 10, 13 and 16 (N = 9744). We used Growth Mixture Modelling (GMM) to identify groups defined by their AST trajectories. Measures of ASD diagnosis, sex, IQ and mental health (internalising and externalising) were used to investigate external validity of the derived trajectory groups. RESULTS The selected GMM model identified four AST trajectory groups: (i) Persistent High (2.3% of sample), (ii) Persistent Low (83.5%), (iii) Increasing (7.3%) and (iv) Decreasing (6.9%) trajectories. The Increasing group, in which females were a slight majority (53.2%), showed dramatic increases in SCDC scores during adolescence, accompanied by escalating internalising and externalising difficulties. Two-thirds (63.6%) of the Decreasing group were male. CONCLUSIONS Clinicians should note that for some young people autism-trait-like social difficulties first emerge during adolescence accompanied by problems with mood, anxiety, conduct and attention. A converse, majority-male group shows decreasing social difficulties during adolescence.
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Affiliation(s)
- Richard Pender
- University College London, Division of Psychiatry, Maple House, 149 Tottenham Court Road, London W1T 7BN, UK
| | - Pasco Fearon
- University College London, Research Department of Clinical, Educational and Health Psychology, 1-19 Torrington Place, London WC1E 7HB, UK
| | - Beate St Pourcain
- Max Planck Institute for Psycholinguistics, Wundtlaan 1, 6525 XD Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, The Netherlands
- MRC Integrative Epidemiology Unit, University of Bristol, UK
| | - Jon Heron
- Bristol Medical School, University of Bristol, Population Health Sciences, Oakfield House, Clifton BS8 2BN, UK
| | - Will Mandy
- University College London, Research Department of Clinical, Educational and Health Psychology, 1-19 Torrington Place, London WC1E 7HB, UK
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Long J, Lu F, Yang S, Zhang Q, Chen X, Pang Y, Wang M, He B, Liu H, Duan X, Chen H, Ye S, Chen H. Different functional connectivity optimal frequency in autism compared with healthy controls and the relationship with social communication deficits: Evidence from gene expression and behavior symptom analyses. Hum Brain Mapp 2022; 44:258-268. [PMID: 35822559 PMCID: PMC9783427 DOI: 10.1002/hbm.26011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 06/15/2022] [Accepted: 06/27/2022] [Indexed: 02/05/2023] Open
Abstract
Studies have reported that different brain regions/connections possess distinct frequency properties, which are related to brain function. Previous studies have proposed altered brain activity frequency and frequency-specific functional connectivity (FC) patterns in autism spectrum disorder (ASD), implying the varied dominant frequency of FC in ASD. However, the difference of the dominant frequency of FC between ASD and healthy controls (HCs) remains unclear. In the present study, the dominant frequency of FC was measured by FC optimal frequency, which was defined as the intermediate of the frequency bin at which the FC strength could reach the maximum. A multivariate pattern analysis was conducted to determine whether the FC optimal frequency in ASD differs from that in HCs. Partial least squares regression (PLSR) and enrichment analyses were conducted to determine the relationship between the FC optimal frequency difference of ASD/HCs and cortical gene expression. PLSR analyses were also performed to explore the relationship between FC optimal frequency and the clinical symptoms of ASD. Results showed a significant difference of FC optimal frequency between ASD and HCs. Some genes whose cortical expression patterns are related to the FC optimal frequency difference of ASD/HCs were enriched for social communication problems. Meanwhile, the FC optimal frequency in ASD was significantly related to social communication symptoms. These results may help us understand the neuro-mechanism of the social communication deficits in ASD.
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Affiliation(s)
- Jinjin Long
- School of MedicineGuizhou UniversityGuiyangChina,Guiyang Hospital of StomatologyGuiyangChina
| | - Fengmei Lu
- Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | | | | | - Xue Chen
- School of MedicineGuizhou UniversityGuiyangChina
| | - Yajing Pang
- School of Electrical EngineeringZhengzhou UniversityZhengzhouChina
| | - Min Wang
- Bioinformatics and BioMedical Bigdata Mining Laboratory, School of Big HealthGuizhou Medical UniversityChina
| | - Bifang He
- School of MedicineGuizhou UniversityGuiyangChina
| | - Heng Liu
- Department of Radiology, Affiliated Hospital of Zunyi Medical UniversityMedical Imaging Center of Guizhou ProvinceZunyiChina
| | - Xujun Duan
- Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Huafu Chen
- Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Shaobing Ye
- The People's Hospital of Kaizhou DistrictChongqingChina
| | - Heng Chen
- School of MedicineGuizhou UniversityGuiyangChina,Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
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Akingbuwa WA, Hammerschlag AR, Bartels M, Middeldorp CM. Systematic Review: Molecular Studies of Common Genetic Variation in Child and Adolescent Psychiatric Disorders. J Am Acad Child Adolesc Psychiatry 2022; 61:227-242. [PMID: 33932494 DOI: 10.1016/j.jaac.2021.03.020] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 03/08/2021] [Accepted: 03/19/2021] [Indexed: 12/13/2022]
Abstract
OBJECTIVE A systematic review of studies using molecular genetics and statistical approaches to investigate the role of common genetic variation in the development, persistence, and comorbidity of childhood psychiatric traits was conducted. METHOD A literature review was performed using the PubMed database, following PRISMA guidelines. There were 131 studies meeting inclusion criteria, having investigated at least one type of childhood-onset or childhood-measured psychiatric disorder or trait with the aim of identifying trait-associated common genetic variants, estimating the contribution of single nucleotide polymorphisms (SNPs) to the amount of variance explained (SNP-based heritability), investigating genetic overlap between psychiatric traits, or investigating whether the stability in traits or the association with adult traits is explained by genetic factors. RESULTS The first robustly associated genetic variants have started to be identified for childhood psychiatric traits. There were substantial contributions of common genetic variants to many traits, with variation in single nucleotide polymorphism heritability estimates depending on age and raters. Moreover, genetic variants also appeared to explain comorbidity as well as stability across a range of psychiatric traits in childhood and across the life span. CONCLUSION Common genetic variation plays a substantial role in childhood psychiatric traits. Increased sample sizes will lead to increased power to identify genetic variants and to understand genetic architecture, which will ultimately be beneficial to targeted and prevention strategies. This can be achieved by harmonizing phenotype measurements, as is already proposed by large international consortia and by including the collection of genetic material in every study.
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Affiliation(s)
- Wonuola A Akingbuwa
- Ms. Akingbuwa, Dr. Hammerschlag, and Profs. Bartels and Middeldorp are with Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Ms. Akingbuwa, Dr. Hammerschlag, and Prof. Bartels are also with Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, The Netherlands.
| | - Anke R Hammerschlag
- Ms. Akingbuwa, Dr. Hammerschlag, and Profs. Bartels and Middeldorp are with Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Ms. Akingbuwa, Dr. Hammerschlag, and Prof. Bartels are also with Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, The Netherlands; Dr. Hammerschlag and Prof. Middeldorp are also with the Child Health Research Centre, the University of Queensland, Brisbane, Queensland, Australia
| | - Meike Bartels
- Ms. Akingbuwa, Dr. Hammerschlag, and Profs. Bartels and Middeldorp are with Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Ms. Akingbuwa, Dr. Hammerschlag, and Prof. Bartels are also with Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Christel M Middeldorp
- Ms. Akingbuwa, Dr. Hammerschlag, and Profs. Bartels and Middeldorp are with Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Dr. Hammerschlag and Prof. Middeldorp are also with the Child Health Research Centre, the University of Queensland, Brisbane, Queensland, Australia; Prof. Middeldorp is also with the Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Services, Brisbane, Queensland, Australia
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Havdahl A, Niarchou M, Starnawska A, Uddin M, van der Merwe C, Warrier V. Genetic contributions to autism spectrum disorder. Psychol Med 2021; 51:2260-2273. [PMID: 33634770 PMCID: PMC8477228 DOI: 10.1017/s0033291721000192] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 01/14/2021] [Accepted: 01/18/2021] [Indexed: 12/12/2022]
Abstract
Autism spectrum disorder (autism) is a heterogeneous group of neurodevelopmental conditions characterized by early childhood-onset impairments in communication and social interaction alongside restricted and repetitive behaviors and interests. This review summarizes recent developments in human genetics research in autism, complemented by epigenetic and transcriptomic findings. The clinical heterogeneity of autism is mirrored by a complex genetic architecture involving several types of common and rare variants, ranging from point mutations to large copy number variants, and either inherited or spontaneous (de novo). More than 100 risk genes have been implicated by rare, often de novo, potentially damaging mutations in highly constrained genes. These account for substantial individual risk but a small proportion of the population risk. In contrast, most of the genetic risk is attributable to common inherited variants acting en masse, each individually with small effects. Studies have identified a handful of robustly associated common variants. Different risk genes converge on the same mechanisms, such as gene regulation and synaptic connectivity. These mechanisms are also implicated by genes that are epigenetically and transcriptionally dysregulated in autism. Major challenges to understanding the biological mechanisms include substantial phenotypic heterogeneity, large locus heterogeneity, variable penetrance, and widespread pleiotropy. Considerable increases in sample sizes are needed to better understand the hundreds or thousands of common and rare genetic variants involved. Future research should integrate common and rare variant research, multi-omics data including genomics, epigenomics, and transcriptomics, and refined phenotype assessment with multidimensional and longitudinal measures.
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Affiliation(s)
- A. Havdahl
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Department of Psychology, PROMENTA Research Center, University of Oslo, Oslo, Norway
| | - M. Niarchou
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, TN, USA
| | - A. Starnawska
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Department of Biomedicine, Aarhus University, Denmark
- Center for Genomics for Personalized Medicine, CGPM, and Center for Integrative Sequencing, iSEQ, Aarhus, Denmark
| | - M. Uddin
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - C. van der Merwe
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, MA, USA
| | - V. Warrier
- Department of Psychiatry, Autism Research Centre, University of Cambridge, UK
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Johnson CN, Ramphal B, Koe E, Raudales A, Goldsmith J, Margolis AE. Cognitive correlates of autism spectrum disorder symptoms. Autism Res 2021; 14:2405-2411. [PMID: 34269525 DOI: 10.1002/aur.2577] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 05/14/2021] [Accepted: 06/14/2021] [Indexed: 01/12/2023]
Abstract
Due to the diverse behavioral presentation of autism spectrum disorder (ASD), identifying ASD subtypes using patterns of cognitive abilities has become an important point of research. Some previous studies on cognitive profiles in ASD suggest that the discrepancy between verbal intelligence quotient (VIQ) and performance IQ (PIQ) is associated with ASD symptoms, while others have pointed to VIQ as the critical predictor. Given that VIQ is a component of the VIQ-PIQ discrepancy, it was unclear which was most driving these associations. This study tested whether VIQ, PIQ, or the VIQ-PIQ discrepancy was most associated with ASD symptoms in children and adults with ASD (N = 527). Using data from the Autism Brain Imaging Data Exchange (ABIDE), we tested the independent contribution of each IQ index and their discrepancy to ASD symptom severity using multiple linear regressions predicting ASD symptoms. VIQ was most associated with lower symptom severity as measured by the Autism Diagnostic Observation Schedule (ADOS) total score, and when VIQ was included in models predicting ASD symptoms, associations with PIQ and IQ discrepancy were not significant. An association between VIQ and ASD communication symptoms drove the association with ASD symptom severity. These results suggest that associations between ASD communication symptoms and IQ discrepancy or PIQ reported in prior studies likely resulted from variance shared with VIQ. Subtyping ASD on the basis of VIQ should be a point of future research, as it may allow for the development of more personalized approaches to intervention. LAY SUMMARY: Previous research on links between autism severity and verbal and nonverbal intelligence has produced mixed results. Our study examined whether verbal intelligence, nonverbal intelligence, or the discrepancy between the two was most related to autism symptoms. We found that higher verbal intelligence was most associated with less severe autism communication symptoms. Given the relevance of verbal intelligence in predicting autism symptom severity, subtyping autism on the basis of verbal intelligence could lead to more personalized treatments.
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Affiliation(s)
- Camille N Johnson
- New York State Psychiatric Institute and Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Bruce Ramphal
- New York State Psychiatric Institute and Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Emily Koe
- New York State Psychiatric Institute and Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Amarelis Raudales
- New York State Psychiatric Institute and Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Jeff Goldsmith
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Amy E Margolis
- New York State Psychiatric Institute and Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
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Zhao B, Shan Y, Yang Y, Yu Z, Li T, Wang X, Luo T, Zhu Z, Sullivan P, Zhao H, Li Y, Zhu H. Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits. Nat Commun 2021; 12:2878. [PMID: 34001886 PMCID: PMC8128893 DOI: 10.1038/s41467-021-23130-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 04/16/2021] [Indexed: 02/03/2023] Open
Abstract
Structural variations of the human brain are heritable and highly polygenic traits, with hundreds of associated genes identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) can both prioritize these GWAS findings and also identify additional gene-trait associations. Here we perform cross-tissue TWAS analysis of 211 structural neuroimaging and discover 278 associated genes exceeding Bonferroni significance threshold of 1.04 × 10-8. The TWAS-significant genes for brain structures have been linked to a wide range of complex traits in different domains. Through TWAS gene-based polygenic risk scores (PRS) prediction, we find that TWAS PRS gains substantial power in association analysis compared to conventional variant-based GWAS PRS, and up to 6.97% of phenotypic variance (p-value = 7.56 × 10-31) can be explained in independent testing data sets. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.
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Affiliation(s)
- Bingxin Zhao
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Shan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zhaolong Yu
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tianyou Luo
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ziliang Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Patrick Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Hongyu Zhao
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Biostatistics, Yale University, New Haven, CT, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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Nayar K, Sealock JM, Maltman N, Bush L, Cook EH, Davis LK, Losh M. Elevated Polygenic Burden for Autism Spectrum Disorder Is Associated With the Broad Autism Phenotype in Mothers of Individuals With Autism Spectrum Disorder. Biol Psychiatry 2021; 89:476-485. [PMID: 33229037 PMCID: PMC7901138 DOI: 10.1016/j.biopsych.2020.08.029] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 08/15/2020] [Accepted: 08/31/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder that encompasses a complex and heterogeneous set of traits. Subclinical traits that mirror the core features of ASD, referred to as the broad autism phenotype (BAP), have been documented repeatedly in unaffected relatives and are believed to reflect underlying genetic liability to ASD. The BAP may help inform the etiology of ASD by allowing the stratification of families into more phenotypically and etiologically homogeneous subgroups. This study explores polygenic scores related to the BAP. METHODS Phenotypic and genotypic information were obtained from 2614 trios from the Simons Simplex Collection. Polygenic scores of ASD (ASD-PGSs) were generated across the sample to determine the shared genetic overlap between the BAP and ASD. Maternal and paternal ASD-PGSs were explored in relation to BAP traits and their child's ASD symptomatology. RESULTS Maternal pragmatic language was related to child's social communicative atypicalities. In fathers, rigid personality was related to increased repetitive behaviors in children. Maternal (but not paternal) ASD-PGSs were related to the pragmatic language and rigid BAP domains. CONCLUSIONS Associations emerged between parent and child phenotypes, with more associations emerging in mothers than in fathers. ASD-PGS associations emerged with BAP in mothers only, highlighting the potential for a female protective factor, and implicating the polygenic etiology of ASD-related phenotypes in the BAP.
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Affiliation(s)
| | | | | | | | | | | | - Molly Losh
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois.
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10
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Operationalizing Social Communication in Autism and Related Neurodevelopmental Research: a Scoping Review Over 20 Years. CURRENT DEVELOPMENTAL DISORDERS REPORTS 2021. [DOI: 10.1007/s40474-021-00224-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Bai T, Zhang L, Xie X, Xiao G, Huang W, Li D, Zu M, Wei L, Zuo X, J I GJ, Hu P, Zhu C, Qiu B, Tian Y, Wang K. Common variant of CNTNAP2 gene modulate the social performances and functional connectivity of posterior right temporoparietal junction. Soc Cogn Affect Neurosci 2020; 14:1297-1305. [PMID: 31993662 PMCID: PMC7137726 DOI: 10.1093/scan/nsaa008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 11/20/2019] [Accepted: 01/08/2020] [Indexed: 11/14/2022] Open
Abstract
Social deficits are features of autism and highly heritable traits. A common variant in autism-related CNTNAP2 gene, rs2710102, has been linked with social performance, but the neural substrates are largely unknown. We investigated variations in social performance and functional connectivity (static and dynamic) in the subregions of right temporoparietal junction (RTPJ), a key node of brain social network, using resting-state magnetic resonance imaging (n = 399) by genotype at rs2710102 in healthy volunteers. Social performance was evaluated using the social domain of the Autism-Spectrum Quotient (AQ-social; n = 641) and fixation time on eye areas during an eye-tracking task (n = 32). According to previous evidence that the A-allele is the risk allele for social dysfunction, we classified participants into GG and A-allele carriers (AA/AG) groups. The A-allele carriers showed poor social performance (high AQ-social and short fixation time on eye areas) compared with the GG carriers. In the A-allele carriers, decreased stationary functional connectivity between the orbitofrontal cortex and posterior RTPJ (pRTPJ), and decreased dynamic functional connectivity (dFC) between the medial prefrontal cortex (mPFC) and pRTPJ were observed. The fixation time at eye areas positively were correlated with the pRTPJ-mPFC dFC. These findings provided insight for genetic effect on social behavior and its potential neural substrate.
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Affiliation(s)
- Tongjian Bai
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China
| | - Long Zhang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China
| | - Xiaohui Xie
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Guixian Xiao
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Wanling Huang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Dandan Li
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China
| | - Meidan Zu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Lin Wei
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, Hefei 230022, China
| | - Xianbo Zuo
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, Hefei 230022, China
| | - Gong-Jun J I
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei 238001, China
| | - Panpan Hu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, Hefei 230022, China
| | - Chunyan Zhu
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, Hefei 230022, China.,Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei 238001, China
| | - Bensheng Qiu
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, Hefei 230022, China.,Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, Hefei 230022, China
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, Hefei 230022, China.,Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei 238001, China
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12
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Warrier V, Toro R, Won H, Leblond CS, Cliquet F, Delorme R, De Witte W, Bralten J, Chakrabarti B, Børglum AD, Grove J, Poelmans G, Hinds DA, Bourgeron T, Baron-Cohen S. Social and non-social autism symptoms and trait domains are genetically dissociable. Commun Biol 2019; 2:328. [PMID: 31508503 PMCID: PMC6722082 DOI: 10.1038/s42003-019-0558-4] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 07/19/2019] [Indexed: 02/06/2023] Open
Abstract
The core diagnostic criteria for autism comprise two symptom domains - social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, though this hypothesis has not yet been tested using molecular genetics. We test this using a genome-wide association study (N = 51,564) of a non-social trait related to autism, systemising, defined as the drive to analyse and build systems. We demonstrate that systemising is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemising. Supporting this, polygenic scores for systemising are significantly and positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism.
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Affiliation(s)
- Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Hyejung Won
- Department of Genetics and Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599 USA
| | - Claire S. Leblond
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Freddy Cliquet
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Richard Delorme
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
- Child and Adolescent Psychiatry Department, Robert Debré Hospital, Paris, France
| | - Ward De Witte
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Bhismadev Chakrabarti
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
- Centre for Autism, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK
| | - Anders D. Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Geert Poelmans
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
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13
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Massrali A, Brunel H, Hannon E, Wong C, Baron-Cohen S, Warrier V. Integrated genetic and methylomic analyses identify shared biology between autism and autistic traits. Mol Autism 2019; 10:31. [PMID: 31346403 PMCID: PMC6637466 DOI: 10.1186/s13229-019-0279-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 05/29/2019] [Indexed: 02/07/2023] Open
Abstract
Previous studies have identified differences in DNA methylation in autistic individuals compared to neurotypical individuals. Yet, it is unclear if this extends to autistic traits-subclinical manifestation of autism features in the general population. Here, we investigate the association between DNA methylation at birth (cord blood), and scores on the Social and Communication Disorders Checklist (SCDC), a measure of autistic traits, in 701 8-year-olds, by conducting a methylome-wide association study (MWAS). We did not identify significant CpGs associated with SCDC. The most significant CpG site was cg14379490, on chromosome 9 (MWAS beta = - 1.78 ± 0.35, p value = 5.34 × 10 -7 ). Using methylation data for autism in peripheral tissues, we did not identify a significant concordance in effect direction of CpGs with p value < 10-4 in the SCDC MWAS (binomial sign test, p value > 0.5). In contrast, using methylation data for autism from post-mortem brain tissues, we identify a significant concordance in effect direction of CpGs with a p value < 10-4 in the SCDC MWAS (binomial sign test, p value = 0.004). Supporting this, we observe an enrichment for genes that are dysregulated in the post-mortem autism brain (one-sided Wilcoxon rank-sum test, p value = 6.22 × 10-5). Finally, integrating genome-wide association study (GWAS) data for autism (n = 46,350) with mQTL maps from cord-blood (n = 771), we demonstrate that mQTLs of CpGs associated with SCDC scores at p value thresholds of 0.01 and 0.005 are significantly shifted toward lower p values in the GWAS for autism (p < 5 × 10-3). We provide additional support for this using a GWAS of SCDC, and demonstrate a lack of enrichment in a GWAS of Alzheimer's disease. Our results highlight the shared cross-tissue methylation architecture of autism and autistic traits, and demonstrate that mQTLs associated with differences in DNA methylation associated with childhood autistic traits are enriched for common genetic variants associated with autism and autistic traits.
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Affiliation(s)
- Aicha Massrali
- Autism Research Centre, University of Cambridge, Cambridge, UK
| | - Helena Brunel
- Autism Research Centre, University of Cambridge, Cambridge, UK
| | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, RILD Building, Level 4, Barrack Rd, Exeter, UK
| | - Chloe Wong
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, London, UK
| | - iPSYCH-MINERvA Epigenetics Group
- Autism Research Centre, University of Cambridge, Cambridge, UK
- University of Exeter Medical School, University of Exeter, RILD Building, Level 4, Barrack Rd, Exeter, UK
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, London, UK
- Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, UK
| | - Simon Baron-Cohen
- Autism Research Centre, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, UK
| | - Varun Warrier
- Autism Research Centre, University of Cambridge, Cambridge, UK
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14
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Navigating the social world: The role of social competence, peer victimisation and friendship quality in the development of social anxiety in childhood. J Anxiety Disord 2018; 60:1-10. [PMID: 30268999 PMCID: PMC6269163 DOI: 10.1016/j.janxdis.2018.09.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 05/24/2018] [Accepted: 09/11/2018] [Indexed: 01/04/2023]
Abstract
Social and communication (SC) difficulties predict increased social anxiety (SA) symptoms in childhood. Peer victimisation and friendship quality are commonly associated with both SC difficulties and SA. Based on this, we tested for a cascade effect of early SC difficulties, peer victimisation and friendship quality on SA in late childhood, using a population-based sample of 8028 children from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Parent-reported data were collected on SC difficulties at age 7 and SA at age 7, 10 and 13. Child-reported data on peer victimisation and friendship quality were collected at age 8. Our results revealed that SC difficulties predict increased negative friendship qualities and peer victimisation. Relational victimisation predicted increased SA symptoms at 13 years old. Neither overt nor relational victimisation mediated the developmental relationship between SC difficulties and SA. Furthermore, friendship quality did not moderate the developmental relationship between SC difficulties and SA. In addition, no sex differences were observed. The evidence demonstrates that peer victimisation and friendship quality do not explain why some children with SC difficulties go on to develop SA. Future research clarifying the complex etiological pathways contributing towards the development of SA in childhood and adolescence is warranted.
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15
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Mandy W, Pellicano L, St Pourcain B, Skuse D, Heron J. The development of autistic social traits across childhood and adolescence in males and females. J Child Psychol Psychiatry 2018; 59:1143-1151. [PMID: 29672866 DOI: 10.1111/jcpp.12913] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/28/2018] [Indexed: 12/18/2022]
Abstract
BACKGROUND Autism is a dimensional condition, representing the extreme end of a continuum of social competence that extends throughout the general population. Currently, little is known about how autistic social traits (ASTs), measured across the full spectrum of severity, develop during childhood and adolescence, including whether there are developmental differences between boys and girls. Therefore, we sought to chart the trajectories of ASTs in the general population across childhood and adolescence, with a focus on gender differences. METHODS Participants were 9,744 males (n = 4,784) and females (n = 4,960) from ALSPAC, a UK birth cohort study. ASTs were assessed when participants were aged 7, 10, 13 and 16 years, using the parent-report Social Communication Disorders Checklist. Data were modelled using latent growth curve analysis. RESULTS Developmental trajectories of males and females were nonlinear, showing a decline from 7 to 10 years, followed by an increase between 10 and 16 years. At 7 years, males had higher levels of ASTs than females (mean raw score difference = 0.88, 95% CI [.72, 1.04]), and were more likely (odds ratio [OR] = 1.99; 95% CI, 1.82, 2.16) to score in the clinical range on the SCDC. By 16 years this gender difference had disappeared: males and females had, on average, similar levels of ASTs (mean difference = 0.00, 95% CI [-0.19, 0.19]) and were equally likely to score in the SCDC's clinical range (OR = 0.91, 95% CI, 0.73, 1.10). This was the result of an increase in females' ASTs between 10 and 16 years. CONCLUSIONS There are gender-specific trajectories of autistic social impairment, with females more likely than males to experience an escalation of ASTs during early- and midadolescence. It remains to be discovered whether the observed female adolescent increase in ASTs represents the genuine late onset of social difficulties or earlier, subtle, pre-existing difficulties becoming more obvious.
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Affiliation(s)
- William Mandy
- Research Department of Clinical, Educational and Health Psychology, UCL, London, UK
| | - Liz Pellicano
- Department of Educational Studies, Macquarie University, Sydney, NSW, Australia
| | - Beate St Pourcain
- Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | | | - Jon Heron
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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16
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Fluharty ME, Heron J, Munafò MR. Longitudinal associations of social cognition and substance use in childhood and early adolescence: findings from the Avon Longitudinal Study of Parents and Children. Eur Child Adolesc Psychiatry 2018; 27:739-752. [PMID: 29058116 PMCID: PMC5973965 DOI: 10.1007/s00787-017-1068-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2017] [Accepted: 10/12/2017] [Indexed: 01/06/2023]
Abstract
Substance use is associated with impaired social cognition. Experimental studies have shown that acute intoxication of alcohol, tobacco, and cannabis decreases the performance in non-verbal, social communication and theory of mind tasks. However, in epidemiological studies the temporal direction of this association has gone relatively unstudied. We investigated both directions of association within an adolescent birth cohort: the association of social cognition with subsequent substance use, and the association of early substance use with subsequent social cognition. We used data from the Avon Longitudinal Study of Parents and Children, a UK birth cohort. Logistic regression indicated that poor childhood non-verbal communication was associated with decreased odds of adolescent alcohol (OR 0.70, 95% 0.54-0.91), tobacco (OR 0.62, 95% CI 0.47-0.83), and cannabis use (OR 0.62, 95% CI 0.46-0.83). Early adolescent substance use was associated with increased odds of poor social communication (alcohol: OR 1.46, 95% CI 0.99-2.14; tobacco: OR 1.95, 95% CI 1.33-2.86) and poor social reciprocity (alcohol: OR 1.57, 95% CI 1.18-2.09; tobacco: OR 1.92, 95% CI 1.43-2.58; cannabis: OR 1.54, 95% CI 1.16-2.05). Overall, the relationship between social cognition and substance use was different in each temporal direction. Poor non-verbal communication in childhood appeared protective against later substance use, while adolescent substance use was associated with decreased social cognitive performance.
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Affiliation(s)
- Meg E Fluharty
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK.
- School of Experimental Psychology, UK Centre for Tobacco and Alcohol Studies, University of Bristol, Bristol, UK.
- School of Experimental Psychology, University of Bristol, 12a Priory Road, Bristol, BS8 1TU, UK.
| | - Jon Heron
- School of Community and Social Medicine, University of Bristol, Bristol, UK
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- School of Experimental Psychology, UK Centre for Tobacco and Alcohol Studies, University of Bristol, Bristol, UK
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17
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Bralten J, van Hulzen KJ, Martens MB, Galesloot TE, Arias Vasquez A, Kiemeney LA, Buitelaar JK, Muntjewerff JW, Franke B, Poelmans G. Autism spectrum disorders and autistic traits share genetics and biology. Mol Psychiatry 2018; 23:1205-1212. [PMID: 28507316 PMCID: PMC5984081 DOI: 10.1038/mp.2017.98] [Citation(s) in RCA: 106] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Revised: 02/06/2017] [Accepted: 03/16/2017] [Indexed: 02/06/2023]
Abstract
Autism spectrum disorders (ASDs) and autistic traits in the general population may share genetic susceptibility factors. In this study, we investigated such potential overlap based on common genetic variants. We developed and validated a self-report questionnaire of autistic traits in adults. We then conducted genome-wide association studies (GWASs) of six trait scores derived from the questionnaire through exploratory factor analysis in 1981 adults from the general population. Using the results from the Psychiatric Genomics Consortium GWAS of ASDs, we observed genetic sharing between ASDs and the autistic traits 'childhood behavior', 'rigidity' and 'attention to detail'. Gene-set analysis subsequently identified 'rigidity' to be significantly associated with a network of ASD gene-encoded proteins that regulates neurite outgrowth. Gene-wide association with the well-established ASD gene MET reached significance. Taken together, our findings provide evidence for an overlapping genetic and biological etiology underlying ASDs and autistic population traits, which suggests that genetic studies in the general population may yield novel ASD genes.
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Affiliation(s)
- J Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - K J van Hulzen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - M B Martens
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - T E Galesloot
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - A Arias Vasquez
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - L A Kiemeney
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - J K Buitelaar
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - J W Muntjewerff
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - B Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - G Poelmans
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Molecular Animal Physiology, Donders Institute for Brain, Cognition and Behaviour, Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University, Nijmegen, The Netherlands
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18
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St Pourcain B, Eaves LJ, Ring SM, Fisher SE, Medland S, Evans DM, Davey Smith G. Developmental Changes Within the Genetic Architecture of Social Communication Behavior: A Multivariate Study of Genetic Variance in Unrelated Individuals. Biol Psychiatry 2018; 83:598-606. [PMID: 29100628 PMCID: PMC5855319 DOI: 10.1016/j.biopsych.2017.09.020] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Revised: 08/01/2017] [Accepted: 09/17/2017] [Indexed: 12/04/2022]
Abstract
BACKGROUND Recent analyses of trait-disorder overlap suggest that psychiatric dimensions may relate to distinct sets of genes that exert maximum influence during different periods of development. This includes analyses of social communication difficulties that share, depending on their developmental stage, stronger genetic links with either autism spectrum disorder or schizophrenia. We developed a multivariate analysis framework in unrelated individuals to model directly the developmental profile of genetic influences contributing to complex traits, such as social communication difficulties, during an approximately 10-year period spanning childhood and adolescence. METHODS Longitudinally assessed quantitative social communication problems (N ≤ 5551) were studied in participants from a United Kingdom birth cohort (Avon Longitudinal Study of Parents and Children; age range, 8-17 years). Using standardized measures, genetic architectures were investigated with novel multivariate genetic-relationship-matrix structural equation models incorporating whole-genome genotyping information. Analogous to twin research, genetic-relationship-matrix structural equation models included Cholesky decomposition, common pathway, and independent pathway models. RESULTS A two-factor Cholesky decomposition model described the data best. One genetic factor was common to Social Communication Disorder Checklist measures across development; the other accounted for independent variation at 11 years and later, consistent with distinct developmental profiles in trait-disorder overlap. Importantly, genetic factors operating at 8 years explained only approximately 50% of genetic variation at 17 years. CONCLUSIONS Using latent factor models, we identified developmental changes in the genetic architecture of social communication difficulties that enhance the understanding of autism spectrum disorder- and schizophrenia-related dimensions. More generally, genetic-relationship-matrix structural equation models present a framework for modeling shared genetic etiologies between phenotypes and can provide prior information with respect to patterns and continuity of trait-disorder overlap.
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Affiliation(s)
- Beate St Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, The Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
| | - Lindon J Eaves
- Department of Human and Molecular Genetics, Institute for Psychiatric and Behavioral Genetics, Commonwealth University School of Medicine, Richmond, Virginia
| | - Susan M Ring
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, The Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Sarah Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Queensland, Australia
| | - David M Evans
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; University of Queensland Diamantina Institute, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
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19
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St Pourcain B, Robinson EB, Anttila V, Sullivan BB, Maller J, Golding J, Skuse D, Ring S, Evans DM, Zammit S, Fisher SE, Neale BM, Anney RJL, Ripke S, Hollegaard MV, Werge T, Ronald A, Grove J, Hougaard DM, Børglum AD, Mortensen PB, Daly MJ, Davey Smith G. ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties. Mol Psychiatry 2018; 23:263-270. [PMID: 28044064 PMCID: PMC5382976 DOI: 10.1038/mp.2016.198] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Revised: 06/10/2016] [Accepted: 08/01/2016] [Indexed: 01/21/2023]
Abstract
Difficulties in social communication are part of the phenotypic overlap between autism spectrum disorders (ASD) and schizophrenia. Both conditions follow, however, distinct developmental patterns. Symptoms of ASD typically occur during early childhood, whereas most symptoms characteristic of schizophrenia do not appear before early adulthood. We investigated whether overlap in common genetic influences between these clinical conditions and impairments in social communication depends on the developmental stage of the assessed trait. Social communication difficulties were measured in typically-developing youth (Avon Longitudinal Study of Parents and Children, N⩽5553, longitudinal assessments at 8, 11, 14 and 17 years) using the Social Communication Disorder Checklist. Data on clinical ASD (PGC-ASD: 5305 cases, 5305 pseudo-controls; iPSYCH-ASD: 7783 cases, 11 359 controls) and schizophrenia (PGC-SCZ2: 34 241 cases, 45 604 controls, 1235 trios) were either obtained through the Psychiatric Genomics Consortium (PGC) or the Danish iPSYCH project. Overlap in genetic influences between ASD and social communication difficulties during development decreased with age, both in the PGC-ASD and the iPSYCH-ASD sample. Genetic overlap between schizophrenia and social communication difficulties, by contrast, persisted across age, as observed within two independent PGC-SCZ2 subsamples, and showed an increase in magnitude for traits assessed during later adolescence. ASD- and schizophrenia-related polygenic effects were unrelated to each other and changes in trait-disorder links reflect the heterogeneity of genetic factors influencing social communication difficulties during childhood versus later adolescence. Thus, both clinical ASD and schizophrenia share some genetic influences with impairments in social communication, but reveal distinct developmental profiles in their genetic links, consistent with the onset of clinical symptoms.
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Affiliation(s)
- B St Pourcain
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - E B Robinson
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research and Medical and the Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - V Anttila
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research and Medical and the Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - B B Sullivan
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research and Medical and the Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - J Maller
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - J Golding
- Centre for Child and Adolescent Health, University of Bristol, Bristol, UK
| | - D Skuse
- Behavioural and Brain Sciences, Institute of Child Health, University College London, London, UK
| | - S Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - D M Evans
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD, Australia
| | - S Zammit
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - S E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - B M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research and Medical and the Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - R J L Anney
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - S Ripke
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research and Medical and the Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - M V Hollegaard
- Statens Serum Institut, Department of Congenital Disorders, Copenhagen, Denmark
| | - T Werge
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, Copenhagen, Denmark
- Institute of Clinical Sciences, Faculty of Medicine and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - iPSYCH-SSI-Broad Autism Group
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research and Medical and the Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Centre for Child and Adolescent Health, University of Bristol, Bristol, UK
- Behavioural and Brain Sciences, Institute of Child Health, University College London, London, UK
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD, Australia
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
- Statens Serum Institut, Department of Congenital Disorders, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, Copenhagen, Denmark
- Institute of Clinical Sciences, Faculty of Medicine and Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Psychological Sciences, Birkbeck, University of London, London, UK
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
| | - A Ronald
- Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - J Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - D M Hougaard
- Statens Serum Institut, Department of Congenital Disorders, Copenhagen, Denmark
| | - A D Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
| | - P B Mortensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
| | - M J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research and Medical and the Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - G Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
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20
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Topal Z, Demir Samurcu N, Taskiran S, Tufan AE, Semerci B. Social communication disorder: a narrative review on current insights. Neuropsychiatr Dis Treat 2018; 14:2039-2046. [PMID: 30147317 PMCID: PMC6095123 DOI: 10.2147/ndt.s121124] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Social communication disorder (SCD) is a novel diagnosis listed under the rubric of communication disorders within the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) and it is reported to be characterized by impairment in use of verbal and nonverbal communication for social aims. This review attempts to summarize the current understanding of the SCD concept along with its evolution and presents data from previous studies conducted. Suggestions for further research are also delineated. As listed in DSM-5, the criteria for this novel diagnosis are vague, display elevated comorbidity with other neurodevelopmental disorders and other childhood psychopathologies, and show partial overlap with autistic spectrum disorders both in terms of genetics and family histories. Data on cross-cultural presentations and temporal stability are also limited. The social communication model proposed by Catani and Bambini may help integrate the neurobiological findings pertaining to SCD. Valid and reliable assessment methods need to be developed for SCD. This may involve either development of novel instruments capturing the DSM-5 criteria or application of statistical methods such as item response theory to existing instruments. The relationships between broad autism phenotype, pragmatic language impairment, nonverbal learning disorder, learning disorders, autistic spectrum disorders, and SCD should be evaluated with further studies.
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Affiliation(s)
- Zehra Topal
- Department of Child and Adolescent Psychiatry, Hakkari State Hospital, Hakkari, Turkey
| | - Nuran Demir Samurcu
- Department of Child and Adolescent Psychiatry, Izzet Baysal Hospital for Maternity and Pediatric Disorder, Bolu, Turkey
| | - Sarper Taskiran
- Department of Psychiatry, Koc University Medical Faculty, Istanbul, Turkey
| | - Ali Evren Tufan
- Department of Child and Adolescent Psychiatry, Abant Izzet Baysal University Medical Faculty, Bolu, Turkey,
| | - Bengi Semerci
- Department of Psychology, Bengi Semerci Institute, Hasan Kalyoncu University, Istanbul, Turkey
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21
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Sokolova E, Oerlemans AM, Rommelse NN, Groot P, Hartman CA, Glennon JC, Claassen T, Heskes T, Buitelaar JK. A Causal and Mediation Analysis of the Comorbidity Between Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD). J Autism Dev Disord 2017; 47:1595-1604. [PMID: 28255761 PMCID: PMC5432632 DOI: 10.1007/s10803-017-3083-7] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Autism spectrum disorder (ASD) and Attention-deficit/hyperactivity disorder (ADHD) are often comorbid. The purpose of this study is to explore the relationships between ASD and ADHD symptoms by applying causal modeling. We used a large phenotypic data set of 417 children with ASD and/or ADHD, 562 affected and unaffected siblings, and 414 controls, to infer a structural equation model using a causal discovery algorithm. Three distinct pathways between ASD and ADHD were identified: (1) from impulsivity to difficulties with understanding social information, (2) from hyperactivity to stereotypic, repetitive behavior, (3) a pairwise pathway between inattention, difficulties with understanding social information, and verbal IQ. These findings may inform future studies on understanding the pathophysiological mechanisms behind the overlap between ASD and ADHD.
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Affiliation(s)
- Elena Sokolova
- Radboud University, Postbus 9010, 6500, Nijmegen, The Netherlands.
- Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands.
| | - Anoek M Oerlemans
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Nanda N Rommelse
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Perry Groot
- Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jeffrey C Glennon
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom Claassen
- Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands
| | - Tom Heskes
- Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
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22
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Coleman JR, Lester KJ, Keers R, Munafò MR, Breen G, Eley TC. Genome-wide association study of facial emotion recognition in children and association with polygenic risk for mental health disorders. Am J Med Genet B Neuropsychiatr Genet 2017; 174:701-711. [PMID: 28608620 PMCID: PMC5638097 DOI: 10.1002/ajmg.b.32558] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Accepted: 05/12/2017] [Indexed: 11/12/2022]
Abstract
Emotion recognition is disrupted in many mental health disorders, which may reflect shared genetic aetiology between this trait and these disorders. We explored genetic influences on emotion recognition and the relationship between these influences and mental health phenotypes. Eight-year-old participants (n = 4,097) from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed the Diagnostic Analysis of Non-Verbal Accuracy (DANVA) faces test. Genome-wide genotype data was available from the Illumina HumanHap550 Quad microarray. Genome-wide association studies were performed to assess associations with recognition of individual emotions and emotion in general. Exploratory polygenic risk scoring was performed using published genomic data for schizophrenia, bipolar disorder, depression, autism spectrum disorder, anorexia, and anxiety disorders. No individual genetic variants were identified at conventional levels of significance in any analysis although several loci were associated at a level suggestive of significance. SNP-chip heritability analyses did not identify a heritable component of variance for any phenotype. Polygenic scores were not associated with any phenotype. The effect sizes of variants influencing emotion recognition are likely to be small. Previous studies of emotion identification have yielded non-zero estimates of SNP-heritability. This discrepancy is likely due to differences in the measurement and analysis of the phenotype.
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Affiliation(s)
- Jonathan R.I. Coleman
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, MRC SocialGenetic and Developmental Psychiatry (SGDP) CentreLondonUK,National Institute for Health Research Biomedical Research CentreSouth London and Maudsley National Health Service TrustLondonUK
| | | | - Robert Keers
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, MRC SocialGenetic and Developmental Psychiatry (SGDP) CentreLondonUK,School of Biological and Chemical SciencesQueen Mary University of LondonLondonUK
| | - Marcus R. Munafò
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK,UK Centre for Tobacco and Alcohol Studies, School of Experimental PsychologyUniversity of BristolBristolUK
| | - Gerome Breen
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, MRC SocialGenetic and Developmental Psychiatry (SGDP) CentreLondonUK,National Institute for Health Research Biomedical Research CentreSouth London and Maudsley National Health Service TrustLondonUK
| | - Thalia C. Eley
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, MRC SocialGenetic and Developmental Psychiatry (SGDP) CentreLondonUK,National Institute for Health Research Biomedical Research CentreSouth London and Maudsley National Health Service TrustLondonUK
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23
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Sun J, Duan G, Li N, Guo S, Zhang Y, Ying Y, Zhang M, Wang Q, Liu JY, Zhang X. SCN11A variants may influence postoperative pain sensitivity after gynecological surgery in Chinese Han female patients. Medicine (Baltimore) 2017; 96:e8149. [PMID: 28953656 PMCID: PMC5626299 DOI: 10.1097/md.0000000000008149] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Nav1.9, encoded by sodium voltage-gated channel alpha subunit 11 (SCN11A), is one of the main sodium channels involved in pain transmission. Dysfunction of Nav1.9 alters pain sensitivity, resulting in insensitivity to pain or familial episodic pain. Our purpose was to explore the effects of SCN11A single-nucleotide polymorphisms (SNPs) on postoperative pain sensitivity in Chinese Han female patients after gynecological surgery.Here, we combined the methods of tag SNPs and candidate SNPs. The associations between eleven SCN11A SNPs and basic pain sensitivity in female healthy volunteers were analyzed using the Plink software. The SNPs associated with basic pain sensitivity were termed positive SCN11A SNPs. The effect of these positive SNPs on postoperative pain sensitivity was explored in patients undergoing elective gynecological laparoscopic surgery and receiving postoperative patient-controlled analgesia (PCA). We assessed pain intensity using the numeric pain rating scale (NRS) and recorded PCA consumption.Our results suggested that 5 SNPs (rs33985936, rs13080116, rs11720988, rs11709492, and rs11720013) in 11 tag and candidate SNPs were associated with basic pain sensitivity (P < .05). No evident association was found between the 5 positive SNPs and NRS (P > .05). However, among these positive SNPs, the minor alleles of rs33985936 and rs13080116 were significantly associated with increased PCA consumption (P < .01).To our knowledge, this is the first study to report that SCN11A SNPs affect postoperative pain sensitivity in Chinese Han women after gynecological surgery. The SNP rs33985936 and rs13080116 may serve as novel predictors for postoperative pain.
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Affiliation(s)
- Jiaoli Sun
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
| | - Guangyou Duan
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
- Department of Anesthesiology, Xinqiao Hospital, Third Military Medical University, Chongqing
| | - Ningbo Li
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
| | - Shanna Guo
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
| | - Yuhao Zhang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
- Department of Anesthesiology, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai
| | - Ying Ying
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
| | - Mi Zhang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
| | - Qingli Wang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
- Department of Anesthesiology, Wuhan General Hospital of Guangzhou Military
| | - Jing Yu Liu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology and Center for Human Genome Research, Huazhong University of Science and Technology, Wuhan, China
| | - Xianwei Zhang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
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24
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Cabana-Domínguez J, Roncero C, Pineda-Cirera L, Palma-Álvarez RF, Ros-Cucurull E, Grau-López L, Esojo A, Casas M, Arenas C, Ramos-Quiroga JA, Ribasés M, Fernàndez-Castillo N, Cormand B. Association of the PLCB1 gene with drug dependence. Sci Rep 2017; 7:10110. [PMID: 28860459 PMCID: PMC5579249 DOI: 10.1038/s41598-017-10207-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Accepted: 08/04/2017] [Indexed: 12/27/2022] Open
Abstract
Genetic factors involved in the susceptibility to drug addiction still remain largely unknown. MiRNAs seem to play key roles in the drug-induced plasticity of the brain that likely drives the emergence of addiction. In this work we explored the role of miRNAs in drug addiction. With this aim, we selected 62 SNPs located in the 3'UTR of target genes that are predicted to alter the binding of miRNA molecules and performed a case-control association study in a Spanish sample of 735 cases (mainly cocaine-dependent subjects with multiple drug dependencies) and 739 controls. We found an association between rs1047383 in the PLCB1 gene and drug dependence that was replicated in an independent sample (663 cases and 667 controls). Then we selected 9 miRNAs predicted to bind the rs1047383 region, but none of them showed any effect on PLCB1 expression. We also assessed two miRNAs binding a region that contains a SNP in linkage disequilibrium with rs1047383, but although one of them, hsa-miR-582, was found to downregulate PLCB1, no differences were observed between alleles. Finally, we explored the possibility that PLCB1 expression is altered by cocaine and we observed a significant upregulation of the gene in the nucleus accumbens of cocaine abusers and in human dopaminergic-like neurons after cocaine treatment. Our results, together with previous studies, suggest that PLCB1 participates in the susceptibility to drug dependence.
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Affiliation(s)
- Judit Cabana-Domínguez
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain
- Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain
| | - Carlos Roncero
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
- Addiction and Dual Diagnosis Unit Vall Hebron, Psychiatric Services, Hospital Universitari Vall d'Hebron-ASPB, Barcelona, Catalonia, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain
| | - Laura Pineda-Cirera
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain
- Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain
| | - R Felipe Palma-Álvarez
- Addiction and Dual Diagnosis Unit Vall Hebron, Psychiatric Services, Hospital Universitari Vall d'Hebron-ASPB, Barcelona, Catalonia, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain
| | - Elena Ros-Cucurull
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
- Addiction and Dual Diagnosis Unit Vall Hebron, Psychiatric Services, Hospital Universitari Vall d'Hebron-ASPB, Barcelona, Catalonia, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain
| | - Lara Grau-López
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
- Addiction and Dual Diagnosis Unit Vall Hebron, Psychiatric Services, Hospital Universitari Vall d'Hebron-ASPB, Barcelona, Catalonia, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain
| | - Abderaman Esojo
- Addiction and Dual Diagnosis Unit Vall Hebron, Psychiatric Services, Hospital Universitari Vall d'Hebron-ASPB, Barcelona, Catalonia, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain
| | - Miquel Casas
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain
| | - Concepció Arenas
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Josep Antoni Ramos-Quiroga
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
| | - Marta Ribasés
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
| | - Noèlia Fernàndez-Castillo
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain.
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain.
- Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain.
| | - Bru Cormand
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain.
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain.
- Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain.
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25
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Boudellioua I, Mahamad Razali RB, Kulmanov M, Hashish Y, Bajic VB, Goncalves-Serra E, Schoenmakers N, Gkoutos GV, Schofield PN, Hoehndorf R. Semantic prioritization of novel causative genomic variants. PLoS Comput Biol 2017; 13:e1005500. [PMID: 28414800 PMCID: PMC5411092 DOI: 10.1371/journal.pcbi.1005500] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 05/01/2017] [Accepted: 04/04/2017] [Indexed: 12/14/2022] Open
Abstract
Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants. We address the problem of how to distinguish which of the many thousands of DNA sequence variants carried by an individual with a rare disease is responsible for the disease phenotypes. This can help clinicians arrive at a diagnosis, but also can be instrumental in improving our understanding of the pathobiology of the disease. Many methods are currently available to help with the problem of determining causative variant, using information about evolutionary conservation and prediction of the functional consequences of the sequence variant. We have developed a novel algorithm (PVP) which augments existing strategies by using the similarity of the patients phenotype to known phenotype-genotype data in human and model organism databases to further rank potential candidate genes. In a retrospective study, we apply PVP to the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism, and find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.
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Affiliation(s)
- Imane Boudellioua
- King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia
| | - Rozaimi B. Mahamad Razali
- King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia
| | - Maxat Kulmanov
- King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia
| | - Yasmeen Hashish
- King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia
| | - Vladimir B. Bajic
- King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia
| | - Eva Goncalves-Serra
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - Nadia Schoenmakers
- University of Cambridge Metabolic Research Laboratories, Wellcome Trust—Medical Research Council, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, United Kingdom
| | - Georgios V. Gkoutos
- College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom
- Institute of Translational Medicine, University Hospitals Birmingham, NHS Foundation Trust, Birmingham, United Kingdom
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
- * E-mail: (GVG); (PNS); (RH)
| | - Paul N. Schofield
- Department of Physiology, Development & Neuroscience, University of Cambridge, Cambridge, United Kingdom
- * E-mail: (GVG); (PNS); (RH)
| | - Robert Hoehndorf
- King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia
- * E-mail: (GVG); (PNS); (RH)
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26
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Stergiakouli E, Davey Smith G, Martin J, Skuse DH, Viechtbauer W, Ring SM, Ronald A, Evans DE, Fisher SE, Thapar A, St Pourcain B. Shared genetic influences between dimensional ASD and ADHD symptoms during child and adolescent development. Mol Autism 2017; 8:18. [PMID: 28392908 PMCID: PMC5379648 DOI: 10.1186/s13229-017-0131-2] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 03/14/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Shared genetic influences between attention-deficit/hyperactivity disorder (ADHD) symptoms and autism spectrum disorder (ASD) symptoms have been reported. Cross-trait genetic relationships are, however, subject to dynamic changes during development. We investigated the continuity of genetic overlap between ASD and ADHD symptoms in a general population sample during childhood and adolescence. We also studied uni- and cross-dimensional trait-disorder links with respect to genetic ADHD and ASD risk. METHODS Social-communication difficulties (N ≤ 5551, Social and Communication Disorders Checklist, SCDC) and combined hyperactive-impulsive/inattentive ADHD symptoms (N ≤ 5678, Strengths and Difficulties Questionnaire, SDQ-ADHD) were repeatedly measured in a UK birth cohort (ALSPAC, age 7 to 17 years). Genome-wide summary statistics on clinical ASD (5305 cases; 5305 pseudo-controls) and ADHD (4163 cases; 12,040 controls/pseudo-controls) were available from the Psychiatric Genomics Consortium. Genetic trait variances and genetic overlap between phenotypes were estimated using genome-wide data. RESULTS In the general population, genetic influences for SCDC and SDQ-ADHD scores were shared throughout development. Genetic correlations across traits reached a similar strength and magnitude (cross-trait rg ≤ 1, pmin = 3 × 10-4) as those between repeated measures of the same trait (within-trait rg ≤ 0.94, pmin = 7 × 10-4). Shared genetic influences between traits, especially during later adolescence, may implicate variants in K-RAS signalling upregulated genes (p-meta = 6.4 × 10-4). Uni-dimensionally, each population-based trait mapped to the expected behavioural continuum: risk-increasing alleles for clinical ADHD were persistently associated with SDQ-ADHD scores throughout development (marginal regression R2 = 0.084%). An age-specific genetic overlap between clinical ASD and social-communication difficulties during childhood was also shown, as per previous reports. Cross-dimensionally, however, neither SCDC nor SDQ-ADHD scores were linked to genetic risk for disorder. CONCLUSIONS In the general population, genetic aetiologies between social-communication difficulties and ADHD symptoms are shared throughout child and adolescent development and may implicate similar biological pathways that co-vary during development. Within both the ASD and the ADHD dimension, population-based traits are also linked to clinical disorder, although much larger clinical discovery samples are required to reliably detect cross-dimensional trait-disorder relationships.
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Affiliation(s)
- Evie Stergiakouli
- MRC Integrative Epidemiology Unit (MRC IEU), University of Bristol, Bristol, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (MRC IEU), University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Joanna Martin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - David H. Skuse
- Institute of Child Health, University College London, London, UK
| | - Wolfgang Viechtbauer
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Susan M. Ring
- MRC Integrative Epidemiology Unit (MRC IEU), University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Angelica Ronald
- Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - David E. Evans
- MRC Integrative Epidemiology Unit (MRC IEU), University of Bristol, Bristol, UK
- University of Queensland Diamantina Institute, Translational Research Institute, University of Queensland, Brisbane, Australia
| | - Simon E. Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Anita Thapar
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Beate St Pourcain
- MRC Integrative Epidemiology Unit (MRC IEU), University of Bristol, Bristol, UK
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
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Pickard H, Rijsdijk F, Happé F, Mandy W. Are Social and Communication Difficulties a Risk Factor for the Development of Social Anxiety? J Am Acad Child Adolesc Psychiatry 2017; 56:344-351.e3. [PMID: 28335879 PMCID: PMC5376399 DOI: 10.1016/j.jaac.2017.01.007] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Revised: 12/22/2016] [Accepted: 01/25/2017] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Social anxiety (SA) is a common condition associated with social and communication (SC) difficulties in typically developing young people, as well as those with autism spectrum disorder (ASD). Whether SC difficulties place children at risk for developing SA is unclear. Using a longitudinal design, the present study aimed to disentangle the relationship between SA symptoms and SC difficulties using a population-based sample of 9,491 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). METHOD Parent-reported data on SC difficulties and SA symptoms were collected at ages 7, 10, and 13 years. A cross-lagged panel model was used to investigate the longitudinal stability and directional relationship between latent SC difficulties and SA constructs over time. RESULTS More SC difficulties were associated with greater SA symptoms at all ages. Earlier SC difficulties predicted a small but significant amount of variance in later SA symptoms. The reverse relationship from SA to SC difficulties was not observed. The relationship from SC difficulties to SA was strongest from age 7 to 10 years. No sex differences were observed. CONCLUSION The evidence suggests that SC difficulties may be an important risk factor for the development of SA. These findings suggest the potential usefulness of incorporating social skills training alongside effective interventions to prevent or alleviate symptoms of SA in childhood.
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Affiliation(s)
- Hannah Pickard
- Medical Research Council (MRC) Social, Genetic, and Developmental Psychiatry (SGDP) Centre, King's College London, UK.
| | - Fruhling Rijsdijk
- Medical Research Council (MRC) Social, Genetic, and Developmental Psychiatry (SGDP) Centre, King's College London, UK
| | - Francesca Happé
- Medical Research Council (MRC) Social, Genetic, and Developmental Psychiatry (SGDP) Centre, King's College London, UK
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28
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Wangler MF, Hu Y, Shulman JM. Drosophila and genome-wide association studies: a review and resource for the functional dissection of human complex traits. Dis Model Mech 2017; 10:77-88. [PMID: 28151408 PMCID: PMC5312009 DOI: 10.1242/dmm.027680] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Human genome-wide association studies (GWAS) have successfully identified thousands of susceptibility loci for common diseases with complex genetic etiologies. Although the susceptibility variants identified by GWAS usually have only modest effects on individual disease risk, they contribute to a substantial burden of trait variation in the overall population. GWAS also offer valuable clues to disease mechanisms that have long proven to be elusive. These insights could lead the way to breakthrough treatments; however, several challenges hinder progress, making innovative approaches to accelerate the follow-up of results from GWAS an urgent priority. Here, we discuss the largely untapped potential of the fruit fly, Drosophila melanogaster, for functional investigation of findings from human GWAS. We highlight selected examples where strong genomic conservation with humans along with the rapid and powerful genetic tools available for flies have already facilitated fine mapping of association signals, elucidated gene mechanisms, and revealed novel disease-relevant biology. We emphasize current research opportunities in this rapidly advancing field, and present bioinformatic analyses that systematically explore the applicability of Drosophila for interrogation of susceptibility signals implicated in more than 1000 human traits, based on all GWAS completed to date. Thus, our discussion is targeted at both human geneticists seeking innovative strategies for experimental validation of findings from GWAS, as well as the Drosophila research community, by whom ongoing investigations of the implicated genes will powerfully inform our understanding of human disease.
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Affiliation(s)
- Michael F Wangler
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX 77030, USA
- Program in Developmental Biology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yanhui Hu
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Joshua M Shulman
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX 77030, USA
- Program in Developmental Biology, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
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29
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Pappa I, St Pourcain B, Benke K, Cavadino A, Hakulinen C, Nivard MG, Nolte IM, Tiesler CMT, Bakermans-Kranenburg MJ, Davies GE, Evans DM, Geoffroy MC, Grallert H, Groen-Blokhuis MM, Hudziak JJ, Kemp JP, Keltikangas-Järvinen L, McMahon G, Mileva-Seitz VR, Motazedi E, Power C, Raitakari OT, Ring SM, Rivadeneira F, Rodriguez A, Scheet PA, Seppälä I, Snieder H, Standl M, Thiering E, Timpson NJ, Veenstra R, Velders FP, Whitehouse AJO, Smith GD, Heinrich J, Hypponen E, Lehtimäki T, Middeldorp CM, Oldehinkel AJ, Pennell CE, Boomsma DI, Tiemeier H. A genome-wide approach to children's aggressive behavior: The EAGLE consortium. Am J Med Genet B Neuropsychiatr Genet 2016; 171:562-72. [PMID: 26087016 DOI: 10.1002/ajmg.b.32333] [Citation(s) in RCA: 104] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 05/28/2015] [Indexed: 12/23/2022]
Abstract
Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of aggressive behavior in children. We analyzed data from nine population-based studies and assessed aggressive behavior using well-validated parent-reported questionnaires. This is the largest sample exploring children's aggressive behavior to date (N = 18,988), with measures in two developmental stages (N = 15,668 early childhood and N = 16,311 middle childhood/early adolescence). First, we estimated the additive genetic variance of children's aggressive behavior based on genome-wide SNP information, using genome-wide complex trait analysis (GCTA). Second, genetic associations within each study were assessed using a quasi-Poisson regression approach, capturing the highly right-skewed distribution of aggressive behavior. Third, we performed meta-analyses of genome-wide associations for both the total age-mixed sample and the two developmental stages. Finally, we performed a gene-based test using the summary statistics of the total sample. GCTA quantified variance tagged by common SNPs (10-54%). The meta-analysis of the total sample identified one region in chromosome 2 (2p12) at near genome-wide significance (top SNP rs11126630, P = 5.30 × 10(-8) ). The separate meta-analyses of the two developmental stages revealed suggestive evidence of association at the same locus. The gene-based analysis indicated association of variation within AVPR1A with aggressive behavior. We conclude that common variants at 2p12 show suggestive evidence for association with childhood aggression. Replication of these initial findings is needed, and further studies should clarify its biological meaning. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Irene Pappa
- School of Pedagogical and Educational Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Beate St Pourcain
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- School of Oral and Dental Sciences, University of Bristol, Bristol, United Kingdom
- School of Experimental Psychology, University of Bristol, Bristol, United Kingdom
| | - Kelly Benke
- Johns Hopkins Bloomberg School of Public Health, Mental Health Department, Baltimore, Maryland
| | - Alana Cavadino
- Population, Policy and Practice, UCL Institute of Child Health, University College London, London, United Kingdom
- Centre for Environmental and Preventive Medicine, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Christian Hakulinen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Michel G Nivard
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam (NCA), Amsterdam, The Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Carla M T Tiesler
- Institute of Epidemiology I, Helmholtz Zentrum Munich, German Research Centre for Environmental Health, Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children's Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | | | - Gareth E Davies
- Avera Institute for Human Genetics, Sioux Falls, South Dakota
| | - David M Evans
- University of Queensland Diamantina Institute, Translational Research Institute, Woolloongabba, Brisbane, Australia
| | - Marie-Claude Geoffroy
- Population, Policy and Practice, UCL Institute of Child Health, University College London, London, United Kingdom
- McGill Group for Suicide Studies, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum Munich, German Research Centre for Environmental Health, Neuherberg, Germany
| | - Maria M Groen-Blokhuis
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
- EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - James J Hudziak
- Vermont Center for Children, Youth, and Families, Department of Psychiatry, University of Vermont, College of Medicine, Vermont
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center-Sophia Children's Hospital, The Netherlands
| | - John P Kemp
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- University of Queensland Diamantina Institute, Translational Research Institute, Woolloongabba, Brisbane, Australia
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | | | - George McMahon
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- University of Queensland Diamantina Institute, Translational Research Institute, Woolloongabba, Brisbane, Australia
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Viara R Mileva-Seitz
- School of Pedagogical and Educational Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Ehsan Motazedi
- Department of Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Christine Power
- Population, Policy and Practice, UCL Institute of Child Health, University College London, London, United Kingdom
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Susan M Ring
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus University Medical Center-Sophia Children's Hospital, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center-Sophia Children's Hospital, The Netherlands
| | - Alina Rodriguez
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Paul A Scheet
- Department of Epidemiology, University of Texas/MD Anderson Cancer Center, Houston, Texas
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Marie Standl
- Institute of Epidemiology I, Helmholtz Zentrum Munich, German Research Centre for Environmental Health, Neuherberg, Germany
| | - Elisabeth Thiering
- Institute of Epidemiology I, Helmholtz Zentrum Munich, German Research Centre for Environmental Health, Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children's Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Nicholas J Timpson
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - René Veenstra
- Department of Sociology, University of Groningen, Groningen, The Netherlands
| | - Fleur P Velders
- Generation R Study Group, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Joachim Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum Munich, German Research Centre for Environmental Health, Neuherberg, Germany
| | - Elina Hypponen
- School of Pedagogical and Educational Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
- School of Population Health and Sansom Institute, University of South Australia, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland
| | - Christel M Middeldorp
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam (NCA), Amsterdam, The Netherlands
- Department of child and adolescent psychiatry, GGZ in Geest/VU University Medical Center, Amsterdam, The Netherlands
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Craig E Pennell
- School of Women's and Infants' Health, University of Western Australia, Perth, Australia
| | - Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Henning Tiemeier
- Generation R Study Group, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center-Sophia Children's Hospital, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center-Sophia Children's Hospital, Rotterdam, The Netherlands
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30
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Robinson EB, St. Pourcain B, Anttila V, Kosmicki JA, Bulik-Sullivan B, Grove J, Maller J, Samocha KE, Sanders SJ, Ripke S, Martin J, Hollegaard MV, Werge T, Hougaard DM, Neale BM, Evans DM, Skuse D, Mortensen PB, Børglum AD, Ronald A, Smith GD, Daly MJ. Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nat Genet 2016; 48:552-5. [PMID: 26998691 PMCID: PMC4986048 DOI: 10.1038/ng.3529] [Citation(s) in RCA: 262] [Impact Index Per Article: 32.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2015] [Accepted: 02/22/2016] [Indexed: 12/13/2022]
Abstract
Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of this risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortium and population-based resources (total n > 38,000), we find genome-wide genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both LD score correlation and de novo variant analysis, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in diagnosis with an ASD or other neuropsychiatric disorder. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.
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Affiliation(s)
- Elise B. Robinson
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
| | - Beate St. Pourcain
- The Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen The Netherlands
| | - Verneri Anttila
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
| | - Jack A. Kosmicki
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Brendan Bulik-Sullivan
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
| | - Jakob Grove
- Department of Biomedicine, University of Aarhus, Aarhus, DK
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Julian Maller
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
| | - Kaitlin E. Samocha
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Program in Genetics and Genomics, Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02114, USA
| | - Stephan J. Sanders
- Department of Psychiatry, University of California San Francisco, San Francisco, California 94143, USA
| | - Stephan Ripke
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Department of Psychiatry and Psychotherapy, Charité, Campus Mitte, 10117 Berlin, Germany
| | - Joanna Martin
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
| | - Mads V. Hollegaard
- Statens Serum Institut, Department of Congenital Disorders, DK-2300 Copenhagen, Denmark
| | - Thomas Werge
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, and Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - David M. Hougaard
- Statens Serum Institut, Department of Congenital Disorders, DK-2300 Copenhagen, Denmark
| | | | - Benjamin M. Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Department of Psychiatry, Harvard Medical School, Boston MA 02114, USA
| | - David M. Evans
- The Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Diamantina Institute, Translational Research Institute, University of Queensland, Brisbane, Australia
| | - David Skuse
- Behavioural Sciences Unit, Institute of Child Health, University College London, Gower Street, London WC1E 6BT, UK
| | - Preben Bo Mortensen
- Department of Biomedicine, University of Aarhus, Aarhus, DK
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- National Centre for Register-based Research, University of Aarhus, Aarhus, DK
| | - Anders D. Børglum
- Department of Biomedicine, University of Aarhus, Aarhus, DK
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
| | - Angelica Ronald
- Department of Psychological Sciences, Centre for Brain and Cognitive Development, Birkbeck, University of London, London WC1E 7HX, UK
| | - George Davey Smith
- The Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge MA 02142, USA
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31
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Schoonjans AS, Meuwissen M, Reyniers E, Kooy F, Ceulemans B. PLCB1 epileptic encephalopathies; Review and expansion of the phenotypic spectrum. Eur J Paediatr Neurol 2016; 20:474-9. [PMID: 26818157 DOI: 10.1016/j.ejpn.2016.01.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2015] [Revised: 01/05/2016] [Accepted: 01/05/2016] [Indexed: 01/14/2023]
Abstract
BACKGROUND Biallelic loss-of-function mutations of phospholipase C-β1 (PLCB1) have been described in three children with an early onset epileptic encephalopathy (EE). In two of them a homozygous deletion of the promotor and first three coding exons was found. The third patient had an almost identical heterozygous deletion in combination with a heterozygous splice site variant. All patients had intractable epilepsy and a severe developmental delay. METHODS AND RESULTS We present the case of a boy with an infantile EE starting at the age of four months with a fever induced status epilepticus, modified hypsarrhythmia and developmental regression. The epilepsy was reasonably controlled with corticoids and valproate whereupon generalized tonic-clonic seizures appeared only each 3-4 months. However, only a slow developmental progress was seen hereafter, resulting in a severe intellectual disability with absent speech, motor delay and autistic features. We identified a novel homozygous partial deletion of PLCB1, affecting exons 7-9. CONCLUSIONS This report emphasizes the role of PLCB1 haploinsufficiency in severe EE. We demonstrate a phenotypic variability in patients with a PLCB1-associated EE. In addition, our findings underscore the importance of microarray analysis in all patients with an EE of unknown etiology.
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Affiliation(s)
- An-Sofie Schoonjans
- Department of Neurology-Pediatric Neurology, University and University Hospital Antwerp, Antwerp, Belgium.
| | - Marije Meuwissen
- Department of Medical Genetics, University and University Hospital Antwerp, Antwerp, Belgium
| | - Edwin Reyniers
- Department of Medical Genetics, University and University Hospital Antwerp, Antwerp, Belgium
| | - Frank Kooy
- Department of Medical Genetics, University and University Hospital Antwerp, Antwerp, Belgium
| | - Berten Ceulemans
- Department of Neurology-Pediatric Neurology, University and University Hospital Antwerp, Antwerp, Belgium
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32
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Evans PD, Mueller KL, Gamazon ER, Cox NJ, Tomblin JB. A genome-wide sib-pair scan for quantitative language traits reveals linkage to chromosomes 10 and 13. GENES BRAIN AND BEHAVIOR 2016; 14:387-97. [PMID: 25997078 DOI: 10.1111/gbb.12223] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 05/06/2015] [Accepted: 05/06/2015] [Indexed: 02/03/2023]
Abstract
Although there is considerable evidence that individual differences in language development are highly heritable, there have been few genome-wide scans to locate genes associated with the trait. Previous analyses of language impairment have yielded replicable evidence for linkage to regions on chromosomes 16q, 19q, 13q (within lab) and at 13q (between labs). Here we report the first linkage study to screen the continuum of language ability, from normal to disordered, as found in the general population. 383 children from 147 sib-ships (214 sib-pairs) were genotyped on the Illumina(®) Linkage IVb Marker Panel using three composite language-related phenotypes and a measure of phonological memory (PM). Two regions (10q23.33; 13q33.3) yielded genome-wide significant peaks for linkage with PM. A peak suggestive of linkage was also found at 17q12 for the overall language composite. This study presents two novel genetic loci for the study of language development and disorders, but fails to replicate findings by previous groups. Possible reasons for this are discussed.
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Affiliation(s)
- P D Evans
- Department of Medicine, The University of Chicago, IL, USA
| | - K L Mueller
- Murdoch Childrens Research Institute, Melbourne, Australia.,Department of Communication Sciences and Disorders, The University of Iowa, IA, USA
| | - E R Gamazon
- Department of Medicine, The University of Chicago, IL, USA.,Present address: Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - N J Cox
- Department of Medicine, The University of Chicago, IL, USA.,Department of Communication Sciences and Disorders, The University of Iowa, IA, USA.,Present address: Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - J B Tomblin
- Department of Communication Sciences and Disorders, The University of Iowa, IA, USA
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A Genetically Informed Cross-Lagged Analysis of Autistic-Like Traits and Affective Problems in Early Childhood. JOURNAL OF ABNORMAL CHILD PSYCHOLOGY 2015; 44:937-47. [PMID: 26456961 DOI: 10.1007/s10802-015-0088-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
A genetically informed cross-lagged model was applied to twin data to explore etiological links between autistic-like traits and affective problems in early childhood. The sample comprised 310 same-sex twin pairs (143 monozygotic and 167 dizygotic; 53 % male). Autistic-like traits and affective problems were assessed at ages 2 and 3 using parent ratings. Both constructs were related within and across age (r = 0.30-0.53) and showed moderate stability (r = 0.45-0.54). Autistic-like traits and affective problems showed genetic and environmental influences at both ages. Whereas at age 2, the covariance between autistic-like traits and affective problems was entirely due to environmental influences (shared and nonshared), at age 3, genetic factors also contributed to the covariance between constructs. The stability paths, but not the cross-lagged paths, were significant, indicating that there is stability in both autistic-like traits and affective problems but they do not mutually influence each other across age. Stability effects were due to genetic, shared, and nonshared environmental influences. Substantial novel genetic and nonshared environmental influences emerge at age 3 and suggest change in the etiology of these constructs over time. During early childhood, autistic-like traits tend to occur alongside affective problems and partly overlapping genetic and environmental influences explain this association.
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Abstract
Language is a defining characteristic of the human species, but its foundations remain mysterious. Heritable disorders offer a gateway into biological underpinnings, as illustrated by the discovery that FOXP2 disruptions cause a rare form of speech and language impairment. The genetic architecture underlying language-related disorders is complex, and although some progress has been made, it has proved challenging to pinpoint additional relevant genes with confidence. Next-generation sequencing and genome-wide association studies are revolutionizing understanding of the genetic bases of other neurodevelopmental disorders, like autism and schizophrenia, and providing fundamental insights into the molecular networks crucial for typical brain development. We discuss how a similar genomic perspective, brought to the investigation of language-related phenotypes, promises to yield equally informative discoveries. Moreover, we outline how follow-up studies of genetic findings using cellular systems and animal models can help to elucidate the biological mechanisms involved in the development of brain circuits supporting language.
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Affiliation(s)
- Sarah A Graham
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, The Netherlands;
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, The Netherlands; .,Donders Institute for Brain, Cognition and Behavior, Radboud University, 6525 EN Nijmegen, The Netherlands;
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Galfalvy H, Haghighi F, Hodgkinson C, Goldman D, Oquendo MA, Burke A, Huang YY, Giegling I, Rujescu D, Bureau A, Turecki G, Mann JJ. A genome-wide association study of suicidal behavior. Am J Med Genet B Neuropsychiatr Genet 2015; 168:557-63. [PMID: 26079190 DOI: 10.1002/ajmg.b.32330] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2014] [Accepted: 05/22/2015] [Indexed: 01/28/2023]
Abstract
Genome wide array studies have reported limited success in identifying genetic markers conferring risk for suicidal behavior (SB). This may be attributable to study designs with primary outcome other than SB. We performed a GWAS on suicides and cases with a history of nonfatal suicide attempts compared with psychiatric controls and healthy volunteers. A consortium of USA, Canadian and German teams assembled two groups of cases (suicide attempters and suicides, N = 577) and non-attempter psychiatric and healthy controls (N = 1,233). Logistic regression was used to test genotype-suicidal behavior association. The test was repeated separating suicide attempt and completed suicide as outcomes. No SNP reached genome-wide significance, but several SNPs within STK3, ADAMTS14, PSME2, and TBX20 genes reached P < 1 × 10(-5) . The top SNPs for the suicide attempt analysis included two from DPP10, one from CTNNA3 and one from STK32B. In the suicide analysis we found seven SNPs from the TBX20 gene in the top hits. Pathway analysis identified the following pathways: "Cellular Assembly and Organization," "Nervous System Development and Function," "Cell Death and Survival," "Immunological Disease," "Infectious Disease," and "Inflammatory Response." The top genes in the SB analysis did not overlap with those in the ideation analysis. No genome wide significant results suggest that susceptibility to SB has genetic risk factors with smaller effect sizes. The strongest candidate genes, ADAMTS14, and PSME2 (both linked to inflammatory response), STK3 (neuronal cell death), and TBX20 (brainstem motor neuron development), have not been previously reported in association with suicide and warrant further study.
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Affiliation(s)
- Hanga Galfalvy
- Department of Psychiatry, Columbia University, New York City, New York
- Department of Biostatistics, Columbia University, New York City, New York
| | - Fatemeh Haghighi
- Department of Psychiatry, Columbia University, New York City, New York
| | - Colin Hodgkinson
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
| | - David Goldman
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
| | - Maria A Oquendo
- Department of Psychiatry, Columbia University, New York City, New York
| | - Ainsley Burke
- Department of Psychiatry, Columbia University, New York City, New York
| | - Yung-Yu Huang
- Department of Psychiatry, Columbia University, New York City, New York
| | - Ina Giegling
- Psychiatric Clinic, Martin-Luther-Universität Halle-Wittenberg, Munich, Germany
| | - Dan Rujescu
- Psychiatric Clinic, Martin-Luther-Universität Halle-Wittenberg, Munich, Germany
| | - Alexandre Bureau
- Centre de recherche de l'Institut universitaire en santé mentale de Québec and Département de médecine sociale et préventive, Université Laval, Quebec City, Canada
| | - Gustavo Turecki
- Department of Psychiatry, McGill University, Montreal, Canada
| | - J John Mann
- Department of Psychiatry, Columbia University, New York City, New York
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Decreased expression of mGluR5 within the dorsolateral prefrontal cortex in autism and increased microglial number in mGluR5 knockout mice: Pathophysiological and neurobehavioral implications. Brain Behav Immun 2015; 49:197-205. [PMID: 26052099 DOI: 10.1016/j.bbi.2015.05.009] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Revised: 05/16/2015] [Accepted: 05/28/2015] [Indexed: 12/29/2022] Open
Abstract
Metabotropic glutamate receptor 5 (mGluR5) and microglial abnormalities have been implicated in autism spectrum disorder (ASD). However, controversy exists as to whether the receptor is down or upregulated in functioning in ASD. In addition, whilst activation of mGluR5 has been shown to attenuate microglial activation, its role in maintaining microglial homeostasis during development has not been investigated. We utilised published microarray data from the dorsolateral prefrontal cortex (DLPFC) of control (n=30) and ASD (n=27) individuals to carry out regression analysis to assess gene expression of mGluR5 downstream signalling elements. We then conducted a post-mortem brain stereological investigation of the DLPFC, to estimate the proportion of mGluR5-positive neurons and glia. Finally, we carried out stereological investigation into numbers of microglia in mGluR5 knockout mice, relative to wildtype littermates, together with assessment of changes in microglial somal size, as an indicator of activation status. We found that gene expression of mGluR5 was significantly decreased in ASD versus controls (p=0.018) as well as downstream elements SHANK3 (p=0.005) and PLCB1 (p=0.009) but that the pro-inflammatory marker NOS2 was increased (p=0.047). Intensity of staining of mGluR5-positive neurons was also significantly decreased in ASD versus controls (p=0.016). Microglial density was significantly increased in mGluR5 knockout animals versus wildtype controls (p=0.011). Our findings provide evidence for decreased expression of mGluR5 and its signalling components representing a key pathophysiological hallmark in ASD with implications for the regulation of microglial number and activation during development. This is important in the context of microglia being considered to play key roles in synaptic pruning during development, with preservation of appropriate connectivity relevant for normal brain functioning.
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Pappa I, Fedko IO, Mileva-Seitz VR, Hottenga JJ, Bakermans-Kranenburg MJ, Bartels M, van Beijsterveldt CEM, Jaddoe VWV, Middeldorp CM, Rippe RCA, Rivadeneira F, Tiemeier H, Verhulst FC, van IJzendoorn MH, Boomsma DI. Single Nucleotide Polymorphism Heritability of Behavior Problems in Childhood: Genome-Wide Complex Trait Analysis. J Am Acad Child Adolesc Psychiatry 2015; 54:737-44. [PMID: 26299295 DOI: 10.1016/j.jaac.2015.06.004] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Revised: 05/04/2015] [Accepted: 06/16/2015] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Genetic factors contribute to individual differences in behavior problems. In children, genome-wide association studies (GWAS) have yielded the first suggestive results when aiming to identify genetic variants that explain heritability, but the proportion of genetic variance that can be attributed to common single nucleotide polymorphisms (SNPs) remains to be determined, as only a few studies have estimated SNP heritability, with diverging results. METHOD Genomic-relationship-matrix restricted maximum likelihood (GREML) as implemented in the software Genome-Wide Complex Trait Analysis (GCTA) was used to estimate SNP heritability (SNP h(2)) for multiple phenotypes within 4 broad domains of children's behavioral problems (attention-deficit/hyperactivity symptoms, internalizing, externalizing, and pervasive developmental problems) and cognitive function. We combined phenotype and genotype data from 2 independent, population-based Dutch cohorts, yielding a total number of 1,495 to 3,175 of 3-, 7-, and 9-year-old children. RESULTS Significant SNP heritability estimates were found for attention-deficit/hyperactivity symptoms (SNP h(2) = 0.37-0.71), externalizing problems (SNP h(2) = 0.44), and total problems (SNP h(2) = 0.18), rated by mother or teacher. Sensitivity analyses with exclusion of extreme cases and quantile normalization of the phenotype data decreased SNP h(2) as expected under genetic inheritance, but they remained statistically significant for most phenotypes. CONCLUSION We provide evidence of the influence of common SNPs on child behavior problems in an ethnically homogenous sample. These results support the continuation of large GWAS collaborative efforts to unravel the genetic basis of complex child behaviors.
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Affiliation(s)
- Irene Pappa
- School of Pedagogical and Educational Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands and the Generation R Study Group, Erasmus Medical Center
| | | | - Viara R Mileva-Seitz
- Generation R Study Group, Erasmus Medical Center; Centre for Child and Family Studies
| | - Jouke-Jan Hottenga
- VU University Amsterdam; EMGO(+) Institute for Health and Care Research, VU University Medical Center, Amsterdam
| | | | - Meike Bartels
- VU University Amsterdam; EMGO(+) Institute for Health and Care Research, VU University Medical Center, Amsterdam; Neuroscience Campus Amsterdam
| | | | - Vincent W V Jaddoe
- Generation R Study Group, Erasmus Medical Center; Erasmus Medical Center
| | | | | | | | - Henning Tiemeier
- Generation R Study Group, Erasmus Medical Center; Erasmus Medical Center; Erasmus Medical Center-Sophia Children's Hospital, Rotterdam
| | - Frank C Verhulst
- Generation R Study Group, Erasmus Medical Center; Erasmus Medical Center-Sophia Children's Hospital, Rotterdam
| | - Marinus H van IJzendoorn
- School of Pedagogical and Educational Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands and the Generation R Study Group, Erasmus Medical Center; Centre for Child and Family Studies, Leiden University, Leiden, The Netherlands.
| | - Dorret I Boomsma
- VU University Amsterdam; EMGO(+) Institute for Health and Care Research, VU University Medical Center, Amsterdam; Neuroscience Campus Amsterdam
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Colvert E, Tick B, McEwen F, Stewart C, Curran SR, Woodhouse E, Gillan N, Hallett V, Lietz S, Garnett T, Ronald A, Plomin R, Rijsdijk F, Happé F, Bolton P. Heritability of Autism Spectrum Disorder in a UK Population-Based Twin Sample. JAMA Psychiatry 2015; 72:415-23. [PMID: 25738232 PMCID: PMC4724890 DOI: 10.1001/jamapsychiatry.2014.3028] [Citation(s) in RCA: 269] [Impact Index Per Article: 29.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
IMPORTANCE Most evidence to date highlights the importance of genetic influences on the liability to autism and related traits. However, most of these findings are derived from clinically ascertained samples, possibly missing individuals with subtler manifestations, and obtained estimates may not be representative of the population. OBJECTIVES To establish the relative contributions of genetic and environmental factors in liability to autism spectrum disorder (ASD) and a broader autism phenotype in a large population-based twin sample and to ascertain the genetic/environmental relationship between dimensional trait measures and categorical diagnostic constructs of ASD. DESIGN, SETTING, AND PARTICIPANTS We used data from the population-based cohort Twins Early Development Study, which included all twin pairs born in England and Wales from January 1, 1994, through December 31, 1996. We performed joint continuous-ordinal liability threshold model fitting using the full information maximum likelihood method to estimate genetic and environmental parameters of covariance. Twin pairs underwent the following assessments: the Childhood Autism Spectrum Test (CAST) (6423 pairs; mean age, 7.9 years), the Development and Well-being Assessment (DAWBA) (359 pairs; mean age, 10.3 years), the Autism Diagnostic Observation Schedule (ADOS) (203 pairs; mean age, 13.2 years), the Autism Diagnostic Interview-Revised (ADI-R) (205 pairs; mean age, 13.2 years), and a best-estimate diagnosis (207 pairs). MAIN OUTCOMES AND MEASURES Participants underwent screening using a population-based measure of autistic traits (CAST assessment), structured diagnostic assessments (DAWBA, ADI-R, and ADOS), and a best-estimate diagnosis. RESULTS On all ASD measures, correlations among monozygotic twins (range, 0.77-0.99) were significantly higher than those for dizygotic twins (range, 0.22-0.65), giving heritability estimates of 56% to 95%. The covariance of CAST and ASD diagnostic status (DAWBA, ADOS and best-estimate diagnosis) was largely explained by additive genetic factors (76%-95%). For the ADI-R only, shared environmental influences were significant (30% [95% CI, 8%-47%]) but smaller than genetic influences (56% [95% CI, 37%-82%]). CONCLUSIONS AND RELEVANCE The liability to ASD and a more broadly defined high-level autism trait phenotype in this large population-based twin sample derives primarily from additive genetic and, to a lesser extent, nonshared environmental effects. The largely consistent results across different diagnostic tools suggest that the results are generalizable across multiple measures and assessment methods. Genetic factors underpinning individual differences in autismlike traits show considerable overlap with genetic influences on diagnosed ASD.
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Affiliation(s)
- Emma Colvert
- MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Beata Tick
- MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Fiona McEwen
- MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England2Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, K
| | - Catherine Stewart
- South London and Maudsley NHS (National Health Service) Foundation Trust, Maudsley Hospital, London, England4Department of Psychology, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Sarah R. Curran
- Department of Psychology, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England5Brighton and Sussex Medical School, University of Sussex, East Sussex, England6Sussex Partnership NHS Foundation Trust, Trust Headquart
| | - Emma Woodhouse
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Nicola Gillan
- South London and Maudsley NHS (National Health Service) Foundation Trust, Maudsley Hospital, London, England
| | - Victoria Hallett
- Department of Psychology, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Stephanie Lietz
- Research Department of Clinical, Educational and Health Psychology, University College London, London, England
| | - Tracy Garnett
- South London and Maudsley NHS (National Health Service) Foundation Trust, Maudsley Hospital, London, England
| | - Angelica Ronald
- MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England9Department of Psychological Sciences, University of London, London, England
| | - Robert Plomin
- MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Frühling Rijsdijk
- MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Francesca Happé
- MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Patrick Bolton
- MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England2Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, K
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Stergiakouli E, Martin J, Hamshere ML, Langley K, Evans DM, St Pourcain B, Timpson NJ, Owen MJ, O'Donovan M, Thapar A, Davey Smith G. Shared genetic influences between attention-deficit/hyperactivity disorder (ADHD) traits in children and clinical ADHD. J Am Acad Child Adolesc Psychiatry 2015; 54:322-7. [PMID: 25791149 PMCID: PMC4382052 DOI: 10.1016/j.jaac.2015.01.010] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2014] [Revised: 12/12/2014] [Accepted: 01/26/2015] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Twin studies and genome-wide complex trait analysis (GCTA) are not in agreement regarding heritability estimates for behavioral traits in children from the general population. This has sparked a debate on the possible difference in genetic architecture between behavioral traits and psychiatric disorders. In this study, we test whether polygenic risk scores associated with variation in attention-deficit/hyperactivity disorder (ADHD) trait levels in children from the general population predict ADHD diagnostic status and severity in an independent clinical sample. METHOD Single nucleotide polymorphisms (SNPs) with p < .5 from a genome-wide association study of ADHD traits in 4,546 children (mean age, 7 years 7 months) from the Avon Longitudinal Study of Parents and Children (ALSPAC; general population sample) were selected to calculate polygenic risk scores in 508 children with an ADHD diagnosis (independent clinical sample) and 5,081 control participants. Polygenic scores were tested for association with case-control status and severity of disorder in the clinical sample. RESULTS Increased polygenic score for ADHD traits predicted ADHD case-control status (odds ratio = 1.17 [95% CI = 1.08-1.28], p = .0003), higher ADHD symptom severity (β = 0.29 [95% CI = 0.04-0.54], p = 0.02), and symptom domain severity in the clinical sample. CONCLUSION This study highlights the relevance of additive genetic variance in ADHD, and provides evidence that shared genetic factors contribute to both behavioral traits in the general population and psychiatric disorders at least in the case of ADHD.
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Affiliation(s)
- Evie Stergiakouli
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK.
| | - Joanna Martin
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Marian L. Hamshere
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Kate Langley
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK,School of Psychology, College of Biomedical and Life Sciences, Cardiff University
| | - David M. Evans
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK,University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Beate St Pourcain
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK,School of Oral and Dental Sciences, University of Bristol, and the School of Experimental Psychology, University of Bristol
| | - Nicholas J. Timpson
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Michael J. Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Michael O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Anita Thapar
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - George Davey Smith
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
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Insights into the genetic foundations of human communication. Neuropsychol Rev 2015; 25:3-26. [PMID: 25597031 DOI: 10.1007/s11065-014-9277-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2014] [Accepted: 12/22/2014] [Indexed: 12/19/2022]
Abstract
The human capacity to acquire sophisticated language is unmatched in the animal kingdom. Despite the discontinuity in communicative abilities between humans and other primates, language is built on ancient genetic foundations, which are being illuminated by comparative genomics. The genetic architecture of the language faculty is also being uncovered by research into neurodevelopmental disorders that disrupt the normally effortless process of language acquisition. In this article, we discuss the strategies that researchers are using to reveal genetic factors contributing to communicative abilities, and review progress in identifying the relevant genes and genetic variants. The first gene directly implicated in a speech and language disorder was FOXP2. Using this gene as a case study, we illustrate how evidence from genetics, molecular cell biology, animal models and human neuroimaging has converged to build a picture of the role of FOXP2 in neurodevelopment, providing a framework for future endeavors to bridge the gaps between genes, brains and behavior.
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St Pourcain B, Haworth CMA, Davis OSP, Wang K, Timpson NJ, Evans DM, Kemp JP, Ronald A, Price T, Meaburn E, Ring SM, Golding J, Hakonarson H, Plomin R, Davey Smith G. Heritability and genome-wide analyses of problematic peer relationships during childhood and adolescence. Hum Genet 2014; 134:539-51. [PMID: 25515860 PMCID: PMC4424375 DOI: 10.1007/s00439-014-1514-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2014] [Accepted: 11/09/2014] [Indexed: 01/09/2023]
Abstract
Peer behaviour plays an important role in the development of social adjustment, though little is known about its genetic architecture. We conducted a twin study combined with a genome-wide complex trait analysis (GCTA) and a genome-wide screen to characterise genetic influences on problematic peer behaviour during childhood and adolescence. This included a series of longitudinal measures (parent-reported Strengths-and-Difficulties Questionnaire) from a UK population-based birth-cohort (ALSPAC, 4-17 years), and a UK twin sample (TEDS, 4-11 years). Longitudinal twin analysis (TEDS; N ≤ 7,366 twin pairs) showed that peer problems in childhood are heritable (4-11 years, 0.60 < twin-h(2) ≤ 0.71) but genetically heterogeneous from age to age (4-11 years, twin-r(g) = 0.30). GCTA (ALSPAC: N ≤ 5,608, TEDS: N ≤ 2,691) provided furthermore little support for the contribution of measured common genetic variants during childhood (4-12 years, 0.02 < GCTA-h(2)(Meta) ≤ 0.11) though these influences become stronger in adolescence (13-17 years, 0.14 < GCTA-h (2)(ALSPAC) ≤ 0.27). A subsequent cross-sectional genome-wide screen in ALSPAC (N ≤ 6,000) focussed on peer problems with the highest GCTA-heritability (10, 13 and 17 years, 0.0002 < GCTA-P ≤ 0.03). Single variant signals (P ≤ 10(-5)) were followed up in TEDS (N ≤ 2835, 9 and 11 years) and, in search for autism quantitative trait loci, explored within two autism samples (AGRE: N Pedigrees = 793; ACC: N Cases = 1,453/N Controls = 7,070). There was, however, no evidence for association in TEDS and little evidence for an overlap with the autistic continuum. In summary, our findings suggest that problematic peer relationships are heritable but genetically complex and heterogeneous from age to age, with an increase in common measurable genetic variation during adolescence.
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Affiliation(s)
- Beate St Pourcain
- MRC Integrative Epidemiology Unit (MRC IEU), University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK,
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Swineford LB, Thurm A, Baird G, Wetherby AM, Swedo S. Social (pragmatic) communication disorder: a research review of this new DSM-5 diagnostic category. J Neurodev Disord 2014; 6:41. [PMID: 25484991 PMCID: PMC4258293 DOI: 10.1186/1866-1955-6-41] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2013] [Accepted: 09/13/2014] [Indexed: 11/10/2022] Open
Abstract
Social (pragmatic) communication disorder (SCD) is a new diagnostic category in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5). The purpose of this review is to describe and synthesize the relevant literature from language and autism spectrum disorder (ASD) research relating to pragmatic language impairment and other previously used terms that relate to SCD. The long-standing debate regarding how social communication/pragmatic impairments overlap and/or differ from language impairments, ASD, and other neurodevelopmental disorders is examined. The possible impact of the addition of SCD diagnostic category and directions for future research are also discussed.
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Affiliation(s)
- Lauren B Swineford
- />Pediatrics and Developmental Neuroscience Branch, National Institute of Mental Health, 10 Center Drive MSC 1255, Building 10, Room 1C250, Bethesda, MD 20892-1255 USA
| | - Audrey Thurm
- />Pediatrics and Developmental Neuroscience Branch, National Institute of Mental Health, 10 Center Drive MSC 1255, Building 10, Room 1C250, Bethesda, MD 20892-1255 USA
| | - Gillian Baird
- />Guy’s and St Thomas’ NHS Foundation Trust, King’s Health Partners Paediatric Neurosciences St Thomas Hospital, London, SE1 5HE UK
| | - Amy M Wetherby
- />Department of Clinical Science, Florida State University, 1940 North Monroe Street, Suite 72, Tallahassee, FL 32303 USA
| | - Susan Swedo
- />Pediatrics and Developmental Neuroscience Branch, National Institute of Mental Health, 10 Center Drive MSC 1255, Building 10, Room 1C250, Bethesda, MD 20892-1255 USA
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Namjou B, Marsolo K, Caroll RJ, Denny JC, Ritchie MD, Verma SS, Lingren T, Porollo A, Cobb BL, Perry C, Kottyan LC, Rothenberg ME, Thompson SD, Holm IA, Kohane IS, Harley JB. Phenome-wide association study (PheWAS) in EMR-linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5-IL13 to Eosinophilic Esophagitis. Front Genet 2014; 5:401. [PMID: 25477900 PMCID: PMC4235428 DOI: 10.3389/fgene.2014.00401] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2014] [Accepted: 10/31/2014] [Indexed: 02/06/2023] Open
Abstract
Objective: We report the first pediatric specific Phenome-Wide Association Study (PheWAS) using electronic medical records (EMRs). Given the early success of PheWAS in adult populations, we investigated the feasibility of this approach in pediatric cohorts in which associations between a previously known genetic variant and a wide range of clinical or physiological traits were evaluated. Although computationally intensive, this approach has potential to reveal disease mechanistic relationships between a variant and a network of phenotypes. Method: Data on 5049 samples of European ancestry were obtained from the EMRs of two large academic centers in five different genotyped cohorts. Recently, these samples have undergone whole genome imputation. After standard quality controls, removing missing data and outliers based on principal components analyses (PCA), 4268 samples were used for the PheWAS study. We scanned for associations between 2476 single-nucleotide polymorphisms (SNP) with available genotyping data from previously published GWAS studies and 539 EMR-derived phenotypes. The false discovery rate was calculated and, for any new PheWAS findings, a permutation approach (with up to 1,000,000 trials) was implemented. Results: This PheWAS found a variety of common variants (MAF > 10%) with prior GWAS associations in our pediatric cohorts including Juvenile Rheumatoid Arthritis (JRA), Asthma, Autism and Pervasive Developmental Disorder (PDD) and Type 1 Diabetes with a false discovery rate < 0.05 and power of study above 80%. In addition, several new PheWAS findings were identified including a cluster of association near the NDFIP1 gene for mental retardation (best SNP rs10057309, p = 4.33 × 10−7, OR = 1.70, 95%CI = 1.38 − 2.09); association near PLCL1 gene for developmental delays and speech disorder [best SNP rs1595825, p = 1.13 × 10−8, OR = 0.65(0.57 − 0.76)]; a cluster of associations in the IL5-IL13 region with Eosinophilic Esophagitis (EoE) [best at rs12653750, p = 3.03 × 10−9, OR = 1.73 95%CI = (1.44 − 2.07)], previously implicated in asthma, allergy, and eosinophilia; and association of variants in GCKR and JAZF1 with allergic rhinitis in our pediatric cohorts [best SNP rs780093, p = 2.18 × 10−5, OR = 1.39, 95%CI = (1.19 − 1.61)], previously demonstrated in metabolic disease and diabetes in adults. Conclusion: The PheWAS approach with re-mapping ICD-9 structured codes for our European-origin pediatric cohorts, as with the previous adult studies, finds many previously reported associations as well as presents the discovery of associations with potentially important clinical implications.
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Affiliation(s)
- Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; College of Medicine, University of Cincinnati Cincinnati, OH, USA
| | - Keith Marsolo
- College of Medicine, University of Cincinnati Cincinnati, OH, USA ; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA
| | - Robert J Caroll
- Department of Biomedical Informatics, Vanderbilt University School of Medicine Nashville, TN, USA
| | - Joshua C Denny
- Department of Biomedical Informatics, Vanderbilt University School of Medicine Nashville, TN, USA ; Department of Medicine, Vanderbilt University School of Medicine Nashville, TN, USA
| | - Marylyn D Ritchie
- Center for Systems Genomics, The Pennsylvania State University Philadelphia, PA, USA
| | - Shefali S Verma
- Center for Systems Genomics, The Pennsylvania State University Philadelphia, PA, USA
| | - Todd Lingren
- College of Medicine, University of Cincinnati Cincinnati, OH, USA ; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA
| | - Aleksey Porollo
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; College of Medicine, University of Cincinnati Cincinnati, OH, USA ; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA
| | - Beth L Cobb
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA
| | - Cassandra Perry
- Division of Genetics and Genomics, Boston Children's Hospital Boston, MA, USA
| | - Leah C Kottyan
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; College of Medicine, University of Cincinnati Cincinnati, OH, USA ; Division of Allergy and Immunology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA
| | - Marc E Rothenberg
- Division of Allergy and Immunology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA
| | - Susan D Thompson
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; College of Medicine, University of Cincinnati Cincinnati, OH, USA
| | - Ingrid A Holm
- Division of Genetics and Genomics, Department of Pediatrics, The Manton Center for Orphan Disease Research, Harvard Medical School, Boston Children's Hospital Boston, MA, USA
| | - Isaac S Kohane
- Children's Hospital Informatics Program, Center for Biomedical Informatics, Harvard Medical School Boston, MA, USA
| | - John B Harley
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; College of Medicine, University of Cincinnati Cincinnati, OH, USA ; U.S. Department of Veterans Affairs Medical Center Cincinnati, OH, USA
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Abstract
In recent years, considerable progress has been made in understanding the genomic basis of autism spectrum disorder (ASD). Hundreds of variants have been proposed as predisposing to ASD, and the challenge now is to validate candidates and to understand how gene networks interact to produce ASD phenotypes. Genome-wide association and second-generation sequencing studies in particular have provided important indications about how to understand ASD on a molecular level, and we are beginning to see these experimental approaches translate into novel treatments and diagnostic tests. We review key studies in the field over the past five years and discuss some of the remaining technological and methodological challenges that remain.
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