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Gillespie NA, Couvy-Duchesne B, Neale MC, Hickie IB, Martin NG. The impact of genes and environment assessed longitudinally on psychological and somatic distress in twins from ages 15 to 35 years. Psychol Med 2025; 55:e17. [PMID: 39911006 PMCID: PMC11968121 DOI: 10.1017/s0033291724003222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 07/23/2024] [Accepted: 11/19/2024] [Indexed: 02/07/2025]
Abstract
BACKGROUND Genetically informative twin studies have consistently found that individual differences in anxiety and depression symptoms are stable and primarily attributable to time-invariant genetic influences, with non-shared environmental influences accounting for transient effects. METHODS We explored the etiology of psychological and somatic distress in 2279 Australian twins assessed up to six times between ages 12-35. We evaluated autoregressive, latent growth, dual-change, common, and independent pathway models to identify which, if any, best describes the observed longitudinal covariance and accounts for genetic and environmental influences over time. RESULTS An autoregression model best explained both psychological and somatic distress. Familial aggregation was entirely explained by additive genetic influences, which were largely stable from ages 12 to 35. However, small but significant age-dependent genetic influences were observed at ages 20-27 and 32-35 for psychological distress and at ages 16-19 and 24-27 for somatic distress. In contrast, environmental influences were predominantly transient and age-specific. CONCLUSIONS The longitudinal trajectory of psychological distress from ages 12 to 35 can thus be largely explained by forward transmission of a stable additive genetic influence, alongside smaller age-specific genetic innovations. This study addresses the limitation of previous research by exhaustively exploring alternative theoretical explanations for the observed patterns in distress symptoms over time, providing a more comprehensive understanding of the genetic and environmental factors influencing psychological and somatic distress across this age range.
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Affiliation(s)
- Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behaviour Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- QIMR Berghofer Medical Research Institute, Genetic Epidemiology Laboratory, Brisbane, Queensland, Australia
| | - Baptiste Couvy-Duchesne
- QIMR Berghofer Medical Research Institute, Genetic Epidemiology Laboratory, Brisbane, Queensland, Australia
- Sorbonne University, Paris Brain Institute – ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013, Paris, France
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behaviour Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Ian B. Hickie
- Brain and Mind Institute, University of Sydney, New South Wales, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Genetic Epidemiology Laboratory, Brisbane, Queensland, Australia
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2
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Luo M, Trindade Pons V, Thomas NS, Drake J, Su MH, Vladimirov V, van Loo HM, Gillespie NA. The Mechanisms Underlying the Intergenerational Transmission of Substance Use and Misuse: An Integrated Research Approach. Twin Res Hum Genet 2024:1-12. [PMID: 39710930 DOI: 10.1017/thg.2024.46] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2024]
Abstract
Substance use and substance use disorders run in families. While it has long been recognized that the etiology of substance use behaviors and disorders involves a combination of genetic and environmental factors, two key questions remain largely unanswered: (1) the intergenerational transmission through which these genetic predispositions are passed from parents to children, and (2) the molecular mechanisms linking genetic variants to substance use behaviors and disorders. This article aims to provide a comprehensive conceptual framework and methodological approach for investigating the intergenerational transmission of substance use behaviors and disorders, by integrating genetic nurture analysis, gene expression imputation, and weighted gene co-expression network analysis. We also additionally describe two longitudinal cohorts - the Brisbane Longitudinal Twin Study in Australia and the Lifelines Cohort Study in the Netherlands. By applying the methodological framework to these two unique datasets, our future research will explore the complex interplay between genetic factors, gene expression, and environmental influences on substance use behaviors and disorders across different life stages and populations.
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Affiliation(s)
- Mannan Luo
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Victória Trindade Pons
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Nathaniel S Thomas
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - John Drake
- Department of Psychiatry, College of Medicine, University of Arizona Phoenix, Phoenix, Arizona, USA
| | - Mei-Hsin Su
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Vladimir Vladimirov
- Department of Psychiatry, College of Medicine, University of Arizona Phoenix, Phoenix, Arizona, USA
- Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hanna M van Loo
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
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3
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Wilkinson J, Curry OS, Mitchell BL, Bates T. Modular morals: Mapping the organization of the moral brain. Brain Cogn 2024; 180:106201. [PMID: 39173228 DOI: 10.1016/j.bandc.2024.106201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 06/10/2024] [Accepted: 06/16/2024] [Indexed: 08/24/2024]
Abstract
Is morality the product of multiple domain-specific psychological mechanisms, or one domain-general mechanism? Previous research suggests that morality consists of a range of solutions to the problems of cooperation recurrent in human social life. This theory of 'morality as cooperation' suggests that there are (at least) seven specific moral domains: family values, group loyalty, reciprocity, heroism, deference, fairness and property rights. However, it is unclear how these types of morality are implemented at the neuroanatomical level. The possibilities are that morality is (1) the product of multiple distinct domain-specific adaptations for cooperation, (2) the product of a single domain-general adaptation which learns a range of moral rules, or (3) the product of some combination of domain-specific and domain-general adaptations. To distinguish between these possibilities, we first conducted an anatomical likelihood estimation meta-analysis of previous studies investigating the relationship between these seven moral domains and neuroanatomy. This meta-analysis provided evidence for a combination of specific and general adaptations. Next, we investigated the relationship between the seven types of morality - as measured by the Morality as Cooperation Questionnaire (Relevance) - and grey matter volume in a large neuroimaging (n = 607) sample. No associations between moral values and grey matter volume survived whole-brain exploratory testing. We conclude that whatever combination of mechanisms are responsible for morality, either they are not neuroanatomically localised, or else their localisation is not manifested in grey matter volume. Future research should employ phylogenetically informed a priori predictions, as well as alternative measures of morality and of brain function.
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Affiliation(s)
- James Wilkinson
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; School of Business and Economics, Maastricht University, Maastricht, the Netherlands.
| | - Oliver Scott Curry
- School of Anthropology and Museum Ethnography, University of Oxford, Oxford, United Kingdom
| | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Timothy Bates
- Centre for Cognitive Ageing and Cognitive Epidemiology Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, United Kingdom
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4
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Blose BA, Silverstein SM, Stuart KV, Keane PA, Khawaja AP, Wagner SK. Association between polygenic risk for schizophrenia and retinal morphology: A cross-sectional analysis of the United Kingdom Biobank. Psychiatry Res 2024; 339:116106. [PMID: 39079374 DOI: 10.1016/j.psychres.2024.116106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 07/17/2024] [Accepted: 07/24/2024] [Indexed: 08/15/2024]
Abstract
We examined the relationship between genetic risk for schizophrenia (SZ), using polygenic risk scores (PRSs), and retinal morphological alterations. Retinal structural and vascular indices derived from optical coherence tomography (OCT) and color fundus photography (CFP) and PRSs for SZ were analyzed in N = 35,024 individuals from the prospective cohort study, United Kingdom Biobank (UKB). Results indicated that macular ganglion cell-inner plexiform layer (mGC-IPL) thickness was significantly inversely related to PRS for SZ, and this relationship was strongest within higher PRS quintiles and independent of potential confounders and age. PRS, however, was unrelated to retinal vascular characteristics, with the exception of venular tortuosity, and other retinal structural indices (macular retinal nerve fiber layer [mRNFL], inner nuclear layer [INL], cup-to-disc ratio [CDR]). Additionally, the association between greater PRS and reduced mGC-IPL thickness was only significant for participants in the 40-49 and 50-59 age groups, not those in the 60-69 age group. These findings suggest that mGC-IPL thinning is associated with a genetic predisposition to SZ and may reflect neurodevelopmental and/or neurodegenerative processes inherent to SZ. Retinal microvasculature alterations, however, may be secondary consequences of SZ and do not appear to be associated with a genetic predisposition to SZ.
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Affiliation(s)
- Brittany A Blose
- Department of Psychology, University of Rochester, Rochester, NY, United States; Department of Psychiatry, University of Rochester Medical Center, Rochester, New York, United States
| | - Steven M Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, New York, United States; Department of Ophthalmology, University of Rochester Medical Center, Rochester, New York, United States; Department of Neuroscience, University of Rochester Medical Center, Rochester, New York, United States; Center for Visual Science, University of Rochester, Rochester, New York, United States.
| | - Kelsey V Stuart
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom; Institute of Ophthalmology, University College London, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Pearse A Keane
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom; Institute of Ophthalmology, University College London, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Anthony P Khawaja
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom; Institute of Ophthalmology, University College London, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Siegfried K Wagner
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom; Institute of Ophthalmology, University College London, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
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Ingold N, Seviiri M, Ong JS, Neale RE, Pandeya N, Whiteman DC, Olsen CM, Martin NG, Duffy DL, Khosrotehrani K, Hayward N, Montgomery GW, MacGregor S, Law MH. Exploring the Germline Genetics of In Situ and Invasive Cutaneous Melanoma: A Genome-Wide Association Study Meta-Analysis. JAMA Dermatol 2024; 160:964-971. [PMID: 39141363 PMCID: PMC11325244 DOI: 10.1001/jamadermatol.2024.2601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 05/10/2024] [Indexed: 08/15/2024]
Abstract
Importance It is unknown whether germline genetic factors influence in situ melanoma risk differently than invasive melanoma risk. Objective To determine whether differences in risk of in situ melanoma and invasive melanoma are heritable. Design, Setting, and Participants Three genome-wide association study meta-analyses were conducted of in situ melanoma vs controls, invasive melanoma vs controls, and in situ vs invasive melanoma (case-case) using 4 population-based genetic cohorts: the UK Biobank, the FinnGen cohort, the QSkin Sun and Health Study, and the Queensland Study of Melanoma: Environmental and Genetic Associations (Q-MEGA). Melanoma status was determined using International Statistical Classification of Diseases and Related Health Problems codes from cancer registry data. Data were collected from 1987 to 2022, and data were analyzed from September 2022 to June 2023. Exposure In situ and invasive cutaneous melanoma. Main Outcomes and Measures To test whether in situ and invasive melanoma have independent heritable components, genetic effect estimates were calculated for single-nucleotide variants (SNV; formerly single-nucleotide polymorphisms) throughout the genome for each melanoma. Then, SNV-based heritability was estimated, the genetic correlation between melanoma subtypes was assessed, and polygenic risk scores (PRS) were generated for in situ vs invasive status in Q-MEGA participants. Results A total of 6 genome-wide significant loci associated with in situ melanoma and 18 loci with invasive melanoma were identified. A strong genetic correlation (genetic r = 0.96; 95% CI, 0.76-1.15) was observed between the 2 classifications. Notably, loci near IRF4, KLF4, and HULC had significantly larger effects for in situ melanoma compared with invasive melanoma, while MC1R had a significantly larger effect on invasive melanoma compared with in situ melanoma. Heritability estimates were consistent for both, with in situ melanoma heritability of 6.7% (95% CI, 4.1-9.3) and invasive melanoma heritability of 4.9% (95% CI, 2.8-7.2). Finally, a PRS, derived from comparing invasive melanoma with in situ melanoma genetic risk, was on average significantly higher in participants with invasive melanoma (odds ratio per 1-SD increase in PRS, 1.43; 95% CI, 1.16-1.77). Conclusions and Relevance There is much shared genetic architecture between in situ melanoma and invasive melanoma. Despite indistinguishable heritability estimates between the melanoma classifications, PRS suggest germline genetics may influence whether a person gets in situ melanoma or invasive melanoma. PRS could potentially help stratify populations based on invasive melanoma risk, informing future screening programs without exacerbating the current burden of melanoma overdiagnosis.
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Affiliation(s)
- Nathan Ingold
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Mathias Seviiri
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jue Sheng Ong
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Rachel E. Neale
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Public Health, The University of Queensland, Brisbane, Australia
| | - Nirmala Pandeya
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - David C. Whiteman
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Catherine M. Olsen
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - David L. Duffy
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Kiarash Khosrotehrani
- The University of Queensland, Frazer Institute, Experimental Dermatology Group, Dermatology Research Centre, Woolloongabba, Australia
| | - Nicholas Hayward
- Oncogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Grant W. Montgomery
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Matthew H. Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia
- Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Science, The University of Queensland, St Lucia, Australia
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6
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Strike LT, Kerestes R, McMahon KL, de Zubicaray GI, Harding IH, Medland SE. Heritability of cerebellar subregion volumes in adolescent and young adult twins. Hum Brain Mapp 2024; 45:e26717. [PMID: 38798116 PMCID: PMC11128777 DOI: 10.1002/hbm.26717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 04/23/2024] [Accepted: 05/06/2024] [Indexed: 05/29/2024] Open
Abstract
Twin studies have found gross cerebellar volume to be highly heritable. However, whether fine-grained regional volumes within the cerebellum are similarly heritable is still being determined. Anatomical MRI scans from two independent datasets (QTIM: Queensland Twin IMaging, N = 798, mean age 22.1 years; QTAB: Queensland Twin Adolescent Brain, N = 396, mean age 11.3 years) were combined with an optimised and automated cerebellum parcellation algorithm to segment and measure 28 cerebellar regions. We show that the heritability of regional volumetric measures varies widely across the cerebellum (h 2 $$ {h}^2 $$ 47%-91%). Additionally, the good to excellent test-retest reliability for a subsample of QTIM participants suggests that non-genetic variance in cerebellar volumes is due primarily to unique environmental influences rather than measurement error. We also show a consistent pattern of strong associations between the volumes of homologous left and right hemisphere regions. Associations were predominantly driven by genetic effects shared between lobules, with only sparse contributions from environmental effects. These findings are consistent with similar studies of the cerebrum and provide a first approximation of the upper bound of heritability detectable by genome-wide association studies.
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Affiliation(s)
- Lachlan T. Strike
- Psychiatric Genetics, QIMR Berghofer Medical Research InstituteBrisbaneAustralia
- School of Psychology and Counselling, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
- School of Biomedical Sciences, Faculty of MedicineUniversity of QueenslandBrisbaneAustralia
| | - Rebecca Kerestes
- Department of Neuroscience, Central Clinical SchoolMonash UniversityMelbourneAustralia
| | - Katie L. McMahon
- School of Clinical Sciences, Centre for Biomedical TechnologiesQueensland University of TechnologyBrisbaneQueenslandAustralia
| | - Greig I. de Zubicaray
- School of Psychology and Counselling, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
| | - Ian H. Harding
- Department of Neuroscience, Central Clinical SchoolMonash UniversityMelbourneAustralia
- Cerebellum and Neurodegeneration, QIMR Berghofer Medical Research InstituteBrisbaneAustralia
| | - Sarah E. Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research InstituteBrisbaneAustralia
- School of Psychology and Counselling, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
- School of PsychologyUniversity of QueenslandBrisbaneAustralia
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7
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Cheek CL, Lindner P, Grigorenko EL. Statistical and Machine Learning Analysis in Brain-Imaging Genetics: A Review of Methods. Behav Genet 2024; 54:233-251. [PMID: 38336922 DOI: 10.1007/s10519-024-10177-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 01/24/2024] [Indexed: 02/12/2024]
Abstract
Brain-imaging-genetic analysis is an emerging field of research that aims at aggregating data from neuroimaging modalities, which characterize brain structure or function, and genetic data, which capture the structure and function of the genome, to explain or predict normal (or abnormal) brain performance. Brain-imaging-genetic studies offer great potential for understanding complex brain-related diseases/disorders of genetic etiology. Still, a combined brain-wide genome-wide analysis is difficult to perform as typical datasets fuse multiple modalities, each with high dimensionality, unique correlational landscapes, and often low statistical signal-to-noise ratios. In this review, we outline the progress in brain-imaging-genetic methodologies starting from early massive univariate to current deep learning approaches, highlighting each approach's strengths and weaknesses and elongating it with the field's development. We conclude by discussing selected remaining challenges and prospects for the field.
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Affiliation(s)
- Connor L Cheek
- Texas Institute for Evaluation, Measurement, and Statistics, University of Houston, Houston, TX, USA.
- Department of Physics, University of Houston, Houston, TX, USA.
| | - Peggy Lindner
- Texas Institute for Evaluation, Measurement, and Statistics, University of Houston, Houston, TX, USA
- Department of Information Science Technology, University of Houston, Houston, TX, USA
| | - Elena L Grigorenko
- Texas Institute for Evaluation, Measurement, and Statistics, University of Houston, Houston, TX, USA
- Department of Psychology, University of Houston, Houston, TX, USA
- Baylor College of Medicine, Houston, TX, USA
- Sirius University of Science and Technology, Sochi, Russia
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Gordon SD, Duffy DL, Whiteman DC, Olsen CM, McAloney K, Adsett JM, Garden NA, Cross SM, List-Armitage SE, Brown J, Beck JJ, Mbarek H, Medland SE, Montgomery GW, Martin NG. GWAS of Dizygotic Twinning in an Enlarged Australian Sample of Mothers of DZ Twins. Twin Res Hum Genet 2023:1-12. [PMID: 37994447 DOI: 10.1017/thg.2023.45] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Female fertility is a complex trait with age-specific changes in spontaneous dizygotic (DZ) twinning and fertility. To elucidate factors regulating female fertility and infertility, we conducted a genome-wide association study (GWAS) on mothers of spontaneous DZ twins (MoDZT) versus controls (3273 cases, 24,009 controls). This is a follow-up study to the Australia/New Zealand (ANZ) component of that previously reported (Mbarek et al., 2016), with a sample size almost twice that of the entire discovery sample meta-analysed in the previous article (and five times the ANZ contribution to that), resulting from newly available additional genotyping and representing a significant increase in power. We compare analyses with and without male controls and show unequivocally that it is better to include male controls who have been screened for recent family history, than to use only female controls. Results from the SNP based GWAS identified four genomewide significant signals, including one novel region, ZFPM1 (Zinc Finger Protein, FOG Family Member 1), on chromosome 16. Previous signals near FSHB (Follicle Stimulating Hormone beta subunit) and SMAD3 (SMAD Family Member 3) were also replicated (Mbarek et al., 2016). We also ran the GWAS with a dominance model that identified a further locus ADRB2 on chr 5. These results have been contributed to the International Twinning Genetics Consortium for inclusion in the next GWAS meta-analysis (Mbarek et al., in press).
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Affiliation(s)
- Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - David L Duffy
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - David C Whiteman
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Catherine M Olsen
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jessica M Adsett
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Natalie A Garden
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Simone M Cross
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Joy Brown
- Independent researcher, Invercargill, New Zealand
| | - Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, South Dakota, USA
| | | | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Grant W Montgomery
- Institute of Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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Mulder TA, Campbell PJ, Taylor PN, Peeters RP, Wilson SG, Medici M, Dayan C, Jaddoe VVW, Walsh JP, Martin NG, Tiemeier H, Korevaar TIM. Genetic determinants of thyroid function in children. Eur J Endocrinol 2023; 189:164-174. [PMID: 37530217 PMCID: PMC10402705 DOI: 10.1093/ejendo/lvad086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/20/2023] [Accepted: 06/06/2023] [Indexed: 08/03/2023]
Abstract
OBJECTIVE Genome-wide association studies in adults have identified 42 loci associated with thyroid stimulating hormone (TSH) and 21 loci associated with free thyroxine (FT4) concentrations. While biologically plausible, age-dependent effects have not been assessed. We aimed to study the association of previously identified genetic determinants of TSH and FT4 with TSH and FT4 concentrations in newborns and (pre)school children. METHODS We selected participants from three population-based prospective cohorts with data on genetic variants and thyroid function: Generation R (N = 2169 children, mean age 6 years; N = 2388 neonates, the Netherlands), the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 3382, age 7.5 years, United Kingdom), and the Brisbane Longitudinal Twin Study (BLTS; N = 1680, age 12.1 years, Australia). The association of single nucleotide polymorphisms (SNPs) with TSH and FT4 concentrations was studied with multivariable linear regression models. Weighted polygenic risk scores (PRSs) were defined to combine SNP effects. RESULTS In childhood, 30/60 SNPs were associated with TSH and 11/31 SNPs with FT4 after multiple testing correction. The effect sizes for AADAT, GLIS3, TM4SF4, and VEGFA were notably larger than in adults. The TSH PRS explained 5.3%-8.4% of the variability in TSH concentrations; the FT4 PRS explained 1.5%-4.2% of the variability in FT4 concentrations. Five TSH SNPs and no FT4 SNPs were associated with thyroid function in neonates. CONCLUSIONS The effects of many known thyroid function SNPs are already apparent in childhood and some might be notably larger in children as compared to adults. These findings provide new knowledge about genetic regulation of thyroid function in early life.
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Affiliation(s)
- Tessa A Mulder
- Generation R Study Group, Erasmus University Medical Center, Rotterdam, CA 3000, The Netherlands
- Department of Internal Medicine, Academic Center for Thyroid Diseases, Erasmus University Medical Center, Rotterdam, CA 3000, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Center, Rotterdam, CA 3000, The Netherlands
| | - Purdey J Campbell
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia
| | - Peter N Taylor
- Thyroid Research Group, Cardiff University School of Medicine, Cardiff, CF14 4YS, United Kingdom
| | - Robin P Peeters
- Department of Internal Medicine, Academic Center for Thyroid Diseases, Erasmus University Medical Center, Rotterdam, CA 3000, The Netherlands
| | - Scott G Wilson
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia
- School of Biomedical Sciences, University of Western Australia, Perth, WA 6009, Australia
- Department of Twin Research & Genetic Epidemiology, King's College London, London, WC2R 2LS, United Kingdom
| | - Marco Medici
- Department of Internal Medicine, Academic Center for Thyroid Diseases, Erasmus University Medical Center, Rotterdam, CA 3000, The Netherlands
| | - Colin Dayan
- Center for Endocrine and Diabetes Science, Cardiff University School of Medicine, Cardiff, CF14 4YS, United Kingdom
| | - Vincent V W Jaddoe
- Generation R Study Group, Erasmus University Medical Center, Rotterdam, CA 3000, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3000 CA, The Netherlands
| | - John P Walsh
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia
- Medical School, The University of Western Australia, Crawley, WA 6009, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Center, Rotterdam, CA 3000, The Netherlands
- Department of Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States
| | - Tim I M Korevaar
- Department of Internal Medicine, Academic Center for Thyroid Diseases, Erasmus University Medical Center, Rotterdam, CA 3000, The Netherlands
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10
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Strike LT, Hansell NK, Chuang KH, Miller JL, de Zubicaray GI, Thompson PM, McMahon KL, Wright MJ. The Queensland Twin Adolescent Brain Project, a longitudinal study of adolescent brain development. Sci Data 2023; 10:195. [PMID: 37031232 PMCID: PMC10082846 DOI: 10.1038/s41597-023-02038-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 02/22/2023] [Indexed: 04/10/2023] Open
Abstract
We describe the Queensland Twin Adolescent Brain (QTAB) dataset and provide a detailed methodology and technical validation to facilitate data usage. The QTAB dataset comprises multimodal neuroimaging, as well as cognitive and mental health data collected in adolescent twins over two sessions (session 1: N = 422, age 9-14 years; session 2: N = 304, 10-16 years). The MRI protocol consisted of T1-weighted (MP2RAGE), T2-weighted, FLAIR, high-resolution TSE, SWI, resting-state fMRI, DWI, and ASL scans. Two fMRI tasks were added in session 2: an emotional conflict task and a passive movie-watching task. Outside of the scanner, we assessed cognitive function using standardised tests. We also obtained self-reports of symptoms for anxiety and depression, perceived stress, sleepiness, pubertal development measures, and risk and protective factors. We additionally collected several biological samples for genomic and metagenomic analysis. The QTAB project was established to promote health-related research in adolescence.
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Affiliation(s)
- Lachlan T Strike
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia.
- School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia.
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, QLD, 4006, Brisbane, Australia.
| | - Narelle K Hansell
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia
| | - Kai-Hsiang Chuang
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia
- The University of Queensland, Centre for Advanced Imaging, Brisbane, QLD 4072, Australia
| | - Jessica L Miller
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia
| | - Greig I de Zubicaray
- School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Katie L McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Margaret J Wright
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia
- The University of Queensland, Centre for Advanced Imaging, Brisbane, QLD 4072, Australia
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11
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Mitchell BL, Hansell NK, McAloney K, Martin NG, Wright MJ, Renteria ME, Grasby KL. Polygenic influences associated with adolescent cognitive skills. INTELLIGENCE 2022. [DOI: 10.1016/j.intell.2022.101680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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12
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Zakharin M, Bates TC. Testing heritability of moral foundations: Common pathway models support strong heritability for the five moral foundations. EUROPEAN JOURNAL OF PERSONALITY 2022. [DOI: 10.1177/08902070221103957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Moral Foundations Theory (MFT) predicts that moral behaviour reflects at least five foundational traits, each hypothesised to be heritable. Here, we report two independent twin studies (total n = 2020), using multivariate multi-group common pathway models to test the following three predictions from the MFT: (1) The moral foundations will show significant heritability; (2) The moral foundations will each be genetically distinct and (3) The clustering of moral concerns around individualising and binding domains will show significant heritability. Supporting predictions 1 and 3, Study 1 showed evidence for significant heritability of two broad moral factors corresponding to individualising and binding domains. In Study 2, we added the second dataset, testing replication of the Study 1 model in a joint approach. This further corroborated evidence for heritable influence, showed strong influences on the individualising and binding domains (h2 = 49% and 66%, respectively) and, partially supporting prediction 2, showed foundation-specific, heritable influences on Harm/Care, Fairness/Reciprocity and Purity/Sanctity foundations. A general morality factor was required, also showing substantial genetic effects (40%). These findings indicate that moral foundations have significant genetic bases. These influenced the individual foundations themselves as well as a general concern for the individual, for the group, and overall moral concern.
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Affiliation(s)
- Michael Zakharin
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Timothy C Bates
- Department of Psychology, University of Edinburgh, Edinburgh, UK
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13
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Morosoli JJ, Barlow FK, Colodro-Conde L, Medland SE. Genetic and Environmental Influences on Biological Essentialism, Heuristic Thinking, Need for Closure, and Conservative Values: Insights From a Survey and Twin Study. Behav Genet 2022; 52:170-183. [DOI: 10.1007/s10519-022-10101-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 03/19/2022] [Indexed: 11/24/2022]
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14
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Wang W, Zakharin M, Bates TC. Who Believes in the Species? Three-Factor Structure and Heritability of Generativity. Twin Res Hum Genet 2022; 25:1-9. [PMID: 35466909 DOI: 10.1017/thg.2022.8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Erikson asked what makes some people care for the future of the species and others not, calling this 'generativity vs. stagnation'. In three studies, we addressed structure of this trait and its heritability. Study 1 (N = 1570), using structural models of the Loyola Generativity Scale , revealed three correlated factors consisting of (1) Establishing and aiding the next generation; (2) Maintaining the world; and (3) Symbolic immortality through a positive legacy. Study 2 (N = 311) successfully replicated this structure in an independent UK sample. Study 3 tested genetic and environmental influences on generativity. All three factors showed significant and substantial heritable influence. A general factor was required, which was also heritable. In resolving previous uncertainty over the transmission of generativity across generations, shared environmental transmission models fit poorly. Substantial unique environmental effects suggest strong cultural impacts on concern for the species. Generativity researchers may usefully adopt this three-factor scoring system, allowing research on the predictive power of each component of generativity as well as molecular genetic or biological studies.
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Affiliation(s)
- Wenlu Wang
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Michael Zakharin
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Timothy C Bates
- Department of Psychology, University of Edinburgh, Edinburgh, UK
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15
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O’Callaghan VS, Hansell NK, Guo W, Carpenter JS, Shou H, Strike LT, Crouse JJ, McAloney K, McMahon KL, Byrne EM, Burns JM, Martin NG, Hickie IB, Merikangas KR, Wright MJ. Genetic and environmental influences on sleep-wake behaviors in adolescence. SLEEP ADVANCES : A JOURNAL OF THE SLEEP RESEARCH SOCIETY 2021; 2:zpab018. [PMID: 37193570 PMCID: PMC10104400 DOI: 10.1093/sleepadvances/zpab018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 09/23/2021] [Indexed: 05/18/2023]
Abstract
Study Objectives To investigate the influence of genetic and environmental factors on sleep-wake behaviors across adolescence. Methods Four hundred and ninety-five participants (aged 9-17; 55% females), including 93 monozygotic and 117 dizygotic twin pairs, and 75 unmatched twins, wore an accelerometry device and completed a sleep diary for 2 weeks. Results Individual differences in sleep onset, wake time, and sleep midpoint were influenced by both additive genetic (44%-50% of total variance) and shared environmental (31%-42%) factors, with a predominant genetic influence for sleep duration (62%) and restorative sleep (43%). When stratified into younger (aged 9-14) and older (aged 16-17) subsamples, genetic sources were more prominent in older adolescents. The moderate correlation between sleep duration and midpoint (rP = -.43, rG = .54) was attributable to a common genetic source. Sleep-wake behaviors on school and nonschool nights were correlated (rP = .44-.72) and influenced by the same genetic and unique environmental factors. Genetic sources specific to night-type were also identified, for all behaviors except restorative sleep. Conclusions There were strong genetic influences on sleep-wake phenotypes, particularly on sleep timing, in adolescence. Moreover, there may be common genetic influences underlying both sleep and circadian rhythms. The differences in sleep-wake behaviors on school and nonschool nights could be attributable to genetic factors involved in reactivity to environmental context.
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Affiliation(s)
| | - Narelle K Hansell
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Wei Guo
- Genetic Epidemiology Branch, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA
| | | | - Haochang Shou
- Genetic Epidemiology Branch, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Lachlan T Strike
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Jacob J Crouse
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | - Enda M Byrne
- Institute of Molecular Bioscience, University of Queensland, Brisbane, Australia
- Child Health Research Centre, University of Queensland, Brisbane, Australia
| | - Jane M Burns
- Young and Well Cooperative Research Centre, Melbourne, Australia
| | | | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Kathleen R Merikangas
- Genetic Epidemiology Branch, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
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16
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Beck JJ, Pool R, van de Weijer M, Chen X, Krapohl E, Gordon SD, Nygaard M, Debrabant B, Palviainen T, van der Zee MD, Baselmans B, Finnicum CT, Yi L, Lundström S, van Beijsterveldt T, Christiansen L, Heikkilä K, Kittelsrud J, Loukola A, Ollikainen M, Christensen K, Martin NG, Plomin R, Nivard M, Bartels M, Dolan C, Willemsen G, de Geus E, Almqvist C, Magnusson PKE, Mbarek H, Ehli EA, Boomsma DI, Hottenga JJ. Genetic meta-analysis of twin birth weight shows high genetic correlation with singleton birth weight. Hum Mol Genet 2021; 30:1894-1905. [PMID: 33955455 PMCID: PMC8444448 DOI: 10.1093/hmg/ddab121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/19/2021] [Accepted: 04/20/2021] [Indexed: 01/09/2023] Open
Abstract
Birth weight (BW) is an important predictor of newborn survival and health and has associations with many adult health outcomes, including cardiometabolic disorders, autoimmune diseases and mental health. On average, twins have a lower BW than singletons as a result of a different pattern of fetal growth and shorter gestational duration. Therefore, investigations into the genetics of BW often exclude data from twins, leading to a reduction in sample size and remaining ambiguities concerning the genetic contribution to BW in twins. In this study, we carried out a genome-wide association meta-analysis of BW in 42 212 twin individuals and found a positive correlation of beta values (Pearson's r = 0.66, 95% confidence interval [CI]: 0.47-0.77) with 150 previously reported genome-wide significant variants for singleton BW. We identified strong positive genetic correlations between BW in twins and numerous anthropometric traits, most notably with BW in singletons (genetic correlation [rg] = 0.92, 95% CI: 0.66-1.18). Genetic correlations of BW in twins with a series of health-related traits closely resembled those previously observed for BW in singletons. Polygenic scores constructed from a genome-wide association study on BW in the UK Biobank demonstrated strong predictive power in a target sample of Dutch twins and singletons. Together, our results indicate that a similar genetic architecture underlies BW in twins and singletons and that future genome-wide studies might benefit from including data from large twin registers.
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Affiliation(s)
- Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57108, USA
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - René Pool
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Margot van de Weijer
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Xu Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Eva Krapohl
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Scott D Gordon
- Genetic Epidemiology Laboratory, QIMR Berghofer, Brisbane, Queensland, Australia
| | - Marianne Nygaard
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Birgit Debrabant
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Teemu Palviainen
- University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Matthijs D van der Zee
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Bart Baselmans
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Casey T Finnicum
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57108, USA
| | - Lu Yi
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | - Toos van Beijsterveldt
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Lene Christiansen
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Kauko Heikkilä
- University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Julie Kittelsrud
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57108, USA
| | - Anu Loukola
- University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Miina Ollikainen
- University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Kaare Christensen
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Nicholas G Martin
- Genetic Epidemiology Laboratory, QIMR Berghofer, Brisbane, Queensland, Australia
| | - Robert Plomin
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Michel Nivard
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Conor Dolan
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Eco de Geus
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hamdi Mbarek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Erik A Ehli
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57108, USA
| | - Dorret I Boomsma
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57108, USA
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
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17
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van der Laan CM, Morosoli-García JJ, van de Weijer SGA, Colodro-Conde L, Lupton MK, Mitchell BL, McAloney K, Parker R, Burns JM, Hickie IB, Pool R, Hottenga JJ, Martin NG, Medland SE, Nivard MG, Boomsma DI. Continuity of Genetic Risk for Aggressive Behavior Across the Life-Course. Behav Genet 2021; 51:592-606. [PMID: 34390460 PMCID: PMC8390412 DOI: 10.1007/s10519-021-10076-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/23/2021] [Indexed: 11/24/2022]
Abstract
We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N = 13,471) and Australia (N = 5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12-70 years, Australia: 16-73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a 'rolling weights' model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41-70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life.
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Affiliation(s)
- Camiel M van der Laan
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.
- The Netherlands Institute for the Study of Crime and Law Enforcement, Amsterdam, The Netherlands.
| | | | - Steve G A van de Weijer
- The Netherlands Institute for the Study of Crime and Law Enforcement, Amsterdam, The Netherlands
| | | | | | | | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Richard Parker
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jane M Burns
- Faculty of Health Sciences, The University of Sydney, Sydney, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - René Pool
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | | | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Michel G Nivard
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
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18
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Morosoli JJ, Colodro-Conde L, Barlow FK, Medland SE. Investigating perceived heritability of mental health disorders and attitudes toward genetic testing in the United States, United Kingdom, and Australia. Am J Med Genet B Neuropsychiatr Genet 2021; 186:341-352. [PMID: 34562071 DOI: 10.1002/ajmg.b.32875] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 08/12/2021] [Accepted: 09/03/2021] [Indexed: 11/07/2022]
Abstract
Our beliefs about the heritability of psychiatric traits may influence how we respond to the use of genetic information in this area. In the present study, we aim to inform future education campaigns as well as genetic counseling interventions by exploring common fears and misunderstandings associated with learning about genetic predispositions for mental health disorders. We surveyed 3,646 genetic research participants from Australia, and 960 members of the public from the United Kingdom, and the United States, and evaluated attitudes toward psychiatric genetic testing. Participants were asked hypothetical questions about their interest in psychiatric genetic testing, perceived usefulness of psychiatric genetic testing, and beliefs about malleability of behavior, among others. We also asked them to estimate the heritability of alcohol dependence, schizophrenia, and major depression. We found a high interest in psychiatric genetic testing. In most cases, more than a third of the participants showed serious concerns related to learning about personal genetic predisposition, such as not wanting to have children if they knew they had a high genetic predisposition, or not wanting to choose a partner with a high genetic predisposition for a mental health problem. Finally, we found a significant association between most participants' attitudes and their lay estimates of heritability, which highlights the complexity of educating the public about genetics.
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Affiliation(s)
- José Juan Morosoli
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.,School of Psychology, University of Queensland, Brisbane, Queensland, Australia
| | - Lucía Colodro-Conde
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.,School of Psychology, University of Queensland, Brisbane, Queensland, Australia
| | - Fiona Kate Barlow
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.,School of Psychology, University of Queensland, Brisbane, Queensland, Australia
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19
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van Eijk L, Zhu D, Couvy-Duchesne B, Strike LT, Lee AJ, Hansell NK, Thompson PM, de Zubicaray GI, McMahon KL, Wright MJ, Zietsch BP. Are Sex Differences in Human Brain Structure Associated With Sex Differences in Behavior? Psychol Sci 2021; 32:1183-1197. [PMID: 34323639 PMCID: PMC8726594 DOI: 10.1177/0956797621996664] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Accepted: 12/13/2020] [Indexed: 11/17/2022] Open
Abstract
On average, men and women differ in brain structure and behavior, raising the possibility of a link between sex differences in brain and behavior. But women and men are also subject to different societal and cultural norms. We navigated this challenge by investigating variability of sex-differentiated brain structure within each sex. Using data from the Queensland Twin IMaging study (n = 1,040) and Human Connectome Project (n = 1,113), we obtained data-driven measures of individual differences along a male-female dimension for brain and behavior based on average sex differences in brain structure and behavior, respectively. We found a weak association between these brain and behavioral differences, driven by brain size. These brain and behavioral differences were moderately heritable. Our findings suggest that behavioral sex differences are, to some extent, related to sex differences in brain structure but that this is mainly driven by differences in brain size, and causality should be interpreted cautiously.
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Affiliation(s)
- Liza van Eijk
- Centre for Psychology and Evolution, School of Psychology, University of Queensland
- Queensland Brain Institute, University of Queensland
- Australian e-Health Research Centre, CSIRO, Herston, Australia
- Department of Psychology, James Cook University
| | - Dajiang Zhu
- Department of Computer Science and Engineering, The University of Texas at Arlington
| | | | | | | | | | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
| | | | - Katie L. McMahon
- Herston Imaging Research Facility and School of Clinical Sciences, Queensland University of Technology
| | - Margaret J. Wright
- Queensland Brain Institute, University of Queensland
- Centre for Advanced Imaging, University of Queensland
| | - Brendan P. Zietsch
- Centre for Psychology and Evolution, School of Psychology, University of Queensland
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20
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Bainomugisa CK, Sutherland HG, Parker R, Mcrae AF, Haupt LM, Griffiths LR, Heath A, Nelson EC, Wright MJ, Hickie IB, Martin NG, Nyholt DR, Mehta D. Using Monozygotic Twins to Dissect Common Genes in Posttraumatic Stress Disorder and Migraine. Front Neurosci 2021; 15:678350. [PMID: 34239411 PMCID: PMC8258453 DOI: 10.3389/fnins.2021.678350] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 05/31/2021] [Indexed: 01/03/2023] Open
Abstract
Epigenetic mechanisms have been associated with genes involved in Posttraumatic stress disorder (PTSD). PTSD often co-occurs with other health conditions such as depression, cardiovascular disorder and respiratory illnesses. PTSD and migraine have previously been reported to be symptomatically positively correlated with each other, but little is known about the genes involved. The aim of this study was to understand the comorbidity between PTSD and migraine using a monozygotic twin disease discordant study design in six pairs of monozygotic twins discordant for PTSD and 15 pairs of monozygotic twins discordant for migraine. DNA from peripheral blood was run on Illumina EPIC arrays and analyzed. Multiple testing correction was performed using the Bonferroni method and 10% false discovery rate (FDR). We validated 11 candidate genes previously associated with PTSD including DOCK2, DICER1, and ADCYAP1. In the epigenome-wide scan, seven novel CpGs were significantly associated with PTSD within/near IL37, WNT3, ADNP2, HTT, SLFN11, and NQO2, with all CpGs except the IL37 CpG hypermethylated in PTSD. These results were significantly enriched for genes whose DNA methylation was previously associated with migraine (p-value = 0.036). At 10% FDR, 132 CpGs in 99 genes associated with PTSD were also associated with migraine in the migraine twin samples. Genes associated with PTSD were overrepresented in vascular smooth muscle, axon guidance and oxytocin signaling pathways, while genes associated with both PTSD and migraine were enriched for AMPK signaling and longevity regulating pathways. In conclusion, these results suggest that common genes and pathways are likely involved in PTSD and migraine, explaining at least in part the co-morbidity between the two disorders.
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Affiliation(s)
- Charlotte K Bainomugisa
- Centre for Genomics and Personalised Health, School of Biomedical Science, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Heidi G Sutherland
- Centre for Genomics and Personalised Health, School of Biomedical Science, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD, Australia.,Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Kelvin Grove, QLD, Australia
| | - Richard Parker
- QIMR Berghofer Medical Research Institute, Royal Brisbane Hospital, Herston, QLD, Australia
| | - Allan F Mcrae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Larisa M Haupt
- Centre for Genomics and Personalised Health, School of Biomedical Science, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD, Australia.,Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Kelvin Grove, QLD, Australia
| | - Lyn R Griffiths
- Centre for Genomics and Personalised Health, School of Biomedical Science, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD, Australia.,Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Kelvin Grove, QLD, Australia
| | - Andrew Heath
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
| | - Elliot C Nelson
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia.,Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Ian B Hickie
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Royal Brisbane Hospital, Herston, QLD, Australia
| | - Dale R Nyholt
- Centre for Genomics and Personalised Health, School of Biomedical Science, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Divya Mehta
- Centre for Genomics and Personalised Health, School of Biomedical Science, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD, Australia
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21
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Crouse JJ, Ho N, Scott J, Martin NG, Couvy-Duchesne B, Hermens DF, Parker R, Gillespie NA, Medland SE, Hickie IB. Days out of role and somatic, anxious-depressive, hypo-manic, and psychotic-like symptom dimensions in a community sample of young adults. Transl Psychiatry 2021; 11:285. [PMID: 33986245 PMCID: PMC8119948 DOI: 10.1038/s41398-021-01390-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/25/2021] [Accepted: 04/14/2021] [Indexed: 02/03/2023] Open
Abstract
Improving our understanding of the causes of functional impairment in young people is a major global challenge. Here, we investigated the relationships between self-reported days out of role and the total quantity and different patterns of self-reported somatic, anxious-depressive, psychotic-like, and hypomanic symptoms in a community-based cohort of young adults. We examined self-ratings of 23 symptoms ranging across the four dimensions and days out of role in >1900 young adult twins and non-twin siblings participating in the "19Up" wave of the Brisbane Longitudinal Twin Study. Adjusted prevalence ratios (APR) and 95% confidence intervals (95% CI) quantified associations between impairment and different symptom patterns. Three individual symptoms showed significant associations with days out of role, with the largest association for impaired concentration. When impairment was assessed according to each symptom dimension, there was a clear stepwise relationship between the total number of somatic symptoms and the likelihood of impairment, while individuals reporting ≥4 anxious-depressive symptoms or five hypomanic symptoms had greater likelihood of reporting days out of role. Furthermore, there was a stepwise relationship between the total number of undifferentiated symptoms and the likelihood of reporting days out of role. There was some suggestion of differences in the magnitude and significance of associations when the cohort was stratified according to sex, but not for age or twin status. Our findings reinforce the development of early intervention mental health frameworks and, if confirmed, support the need to consider interventions for subthreshold and/or undifferentiated syndromes for reducing disability among young people.
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Affiliation(s)
- Jacob J Crouse
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia.
| | - Nicholas Ho
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Jan Scott
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia
- Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle, UK
- Diderot University, Paris, France
- Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Baptiste Couvy-Duchesne
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- ARAMIS Laboratory, Paris Brain Institute, Paris, France
| | - Daniel F Hermens
- Thompson Institute, University of the Sunshine Coast, Birtinya, Australia
| | - Richard Parker
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Virginia, USA
| | - Sarah E Medland
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Ian B Hickie
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia
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22
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Lafontaine N, Campbell PJ, Castillo-Fernandez JE, Mullin S, Lim EM, Kendrew P, Lewer M, Brown SJ, Huang RC, Melton PE, Mori TA, Beilin LJ, Dudbridge F, Spector TD, Wright MJ, Martin NG, McRae AF, Panicker V, Zhu G, Walsh JP, Bell JT, Wilson SG. Epigenome-Wide Association Study of Thyroid Function Traits Identifies Novel Associations of fT3 With KLF9 and DOT1L. J Clin Endocrinol Metab 2021; 106:e2191-e2202. [PMID: 33484127 PMCID: PMC8063248 DOI: 10.1210/clinem/dgaa975] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Indexed: 12/12/2022]
Abstract
CONTEXT Circulating concentrations of free triiodothyronine (fT3), free thyroxine (fT4), and thyrotropin (TSH) are partly heritable traits. Recent studies have advanced knowledge of their genetic architecture. Epigenetic modifications, such as DNA methylation (DNAm), may be important in pituitary-thyroid axis regulation and action, but data are limited. OBJECTIVE To identify novel associations between fT3, fT4, and TSH and differentially methylated positions (DMPs) in the genome in subjects from 2 Australian cohorts. METHOD We performed an epigenome-wide association study (EWAS) of thyroid function parameters and DNAm using participants from: Brisbane Systems Genetics Study (median age 14.2 years, n = 563) and the Raine Study (median age 17.0 years, n = 863). Plasma fT3, fT4, and TSH were measured by immunoassay. DNAm levels in blood were assessed using Illumina HumanMethylation450 BeadChip arrays. Analyses employed generalized linear mixed models to test association between DNAm and thyroid function parameters. Data from the 2 cohorts were meta-analyzed. RESULTS We identified 2 DMPs with epigenome-wide significant (P < 2.4E-7) associations with TSH and 6 with fT3, including cg00049440 in KLF9 (P = 2.88E-10) and cg04173586 in DOT1L (P = 2.09E-16), both genes known to be induced by fT3. All DMPs had a positive association between DNAm and TSH and a negative association between DNAm and fT3. There were no DMPs significantly associated with fT4. We identified 23 differentially methylated regions associated with fT3, fT4, or TSH. CONCLUSIONS This study has demonstrated associations between blood-based DNAm and both fT3 and TSH. This may provide insight into mechanisms underlying thyroid hormone action and/or pituitary-thyroid axis function.
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Affiliation(s)
- Nicole Lafontaine
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
- Medical School, University of Western Australia, Crawley, WA, Australia
- Correspondence: Nicole Lafontaine, MBBS, BMedSci, RACP, Department of Endocrinology & Diabetes, Level 1, Building C, QEII Medical Centre, Sir Charles Gairdner Hospital, Hospital Ave, Nedlands, WA 6009, Australia.
| | - Purdey J Campbell
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
| | | | - Shelby Mullin
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
| | - Ee Mun Lim
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
- Pathwest Laboratory Medicine, Nedlands, WA, Australia
| | | | | | - Suzanne J Brown
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
| | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Phillip E Melton
- School of Biomedical Sciences, University of Western Australia, Perth, Australia
- School of Pharmacy and Biomedical Sciences, Curtin University, Perth, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Trevor A Mori
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Perth, WA, Australia
| | - Lawrence J Beilin
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Perth, WA, Australia
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Tim D Spector
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | | | - Allan F McRae
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
| | - Vijay Panicker
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - John P Walsh
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
- Medical School, University of Western Australia, Crawley, WA, Australia
| | - Jordana T Bell
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
| | - Scott G Wilson
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
- School of Biomedical Sciences, University of Western Australia, Perth, Australia
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23
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16Up: Outline of a Study Investigating Wellbeing and Information and Communication Technology Use in Adolescent Twins. Twin Res Hum Genet 2021; 23:345-357. [PMID: 33509317 DOI: 10.1017/thg.2020.83] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The '16Up' study conducted at the QIMR Berghofer Medical Research Institute from January 2014 to December 2018 aimed to examine the physical and mental health of young Australian twins aged 16-18 years (N = 876; 371 twin pairs and 18 triplet sets). Measurements included online questionnaires covering physical and mental health as well as information and communication technology (ICT) use, actigraphy, sleep diaries and hair samples to determine cortisol concentrations. Study participants generally rated themselves as being in good physical (79%) and mental (73%) health and reported lower rates of psychological distress and exposure to alcohol, tobacco products or other substances than previously reported for this age group in the Australian population. Daily or near-daily online activity was almost universal among study participants, with no differences noted between males and females in terms of frequency or duration of internet access. Patterns of ICT use in this sample indicated that the respondents were more likely to use online information sources for researching physical health issues than for mental health or substance use issues, and that they generally reported partial levels of satisfaction with the mental health information they found online. This suggests that internet-based mental health resources can be readily accessed by adolescent Australians, and their computer literacy augurs well for future access to online health resources. In combination with other data collected as part of the ongoing Brisbane Longitudinal Twin Study, the 16Up project provides a valuable resource for the longitudinal investigation of genetic and environmental contributions to phenotypic variation in a variety of human traits.
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Smith K, Hatemi PK. Are Moral Intuitions Heritable? HUMAN NATURE-AN INTERDISCIPLINARY BIOSOCIAL PERSPECTIVE 2021; 31:406-420. [PMID: 33420605 DOI: 10.1007/s12110-020-09380-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/30/2020] [Indexed: 10/22/2022]
Abstract
Two prominent theoretical frameworks in moral psychology, Moral Foundations and Dual Process Theory, share a broad foundational assumption that individual differences in human morality are dispositional and in part due to genetic variation. The only published direct test of heritability, however, found little evidence of genetic influences on moral judgments using instrumentation approaches associated with Moral Foundations Theory. This raised questions about one of the core assumptions underpinning intuitionist theories of moral psychology. Here we examine the heritability of moral psychology using the moral dilemmas approach commonly used in Dual Process Theory research. Using such measures, we find consistent and significant evidence of heritability. These findings have important implications not only for understanding which measures do, or do not, tap into the genetically influenced aspects of moral decision-making, but in better establishing the utility and validity of different intuitionist theoretical frameworks and the source of why people differ in those frameworks.
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Affiliation(s)
- Kevin Smith
- University of Nebraska, 509 Oldfather Hall, Lincoln, NE, 68588, USA
| | - Peter K Hatemi
- Pennsylvania State University, 307 Pond Lab, University Park, PA, 16802, USA.
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25
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Hatemi PK, McDermott R. Dispositional Fear and Political Attitudes. HUMAN NATURE-AN INTERDISCIPLINARY BIOSOCIAL PERSPECTIVE 2020; 31:387-405. [PMID: 33269419 DOI: 10.1007/s12110-020-09378-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/05/2020] [Indexed: 01/21/2023]
Abstract
Previous work proposes that dispositional fear exists predominantly among political conservatives, generating the appearance that fears align strictly along party lines. This view obscures evolutionary dynamics because fear evolved to protect against myriad threats, not merely those in the political realm. We suggest prior work in this area has been biased by selection on the dependent variable, resulting from an examination of exclusively politically oriented fears that privilege conservative values. Because the adaptation regulating fear should be based upon both universal and ancestral-specific selection pressures combined with developmental and individual differences, the elicitation of it should prove variable across the ideological continuum dependent upon specific combinations of fear and value domains. In a sample of ~ 1,600 Australians assessed with a subset of the Fear Survey Schedule II, we find fears not infused with political content are differentially influential across the political spectrum. Specifically, those who are more fearful of sharp objects, graveyards, and urinating in public are more socially conservative and less supportive of gay rights. Those who are more fearful of death are more supportive of gay rights. Those who are more fearful of suffocating and swimming alone are more concerned about emissions controls and immigration, while those who are more fearful of thunderstorms are also more anti-immigration. Contrary to existing research, both liberals and conservatives are more fearful of different circumstances, and the role of dispositional fears are attitude-specific.
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26
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Comparison of Genome-Wide Association Scans for Quantitative and Observational Measures of Human Hair Curvature. Twin Res Hum Genet 2020; 23:271-277. [PMID: 33190678 DOI: 10.1017/thg.2020.78] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Previous genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10-09; observational measure lead SNP rs11803731, p = 2.1 × 10-17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures.
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27
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The Academic Development Study of Australian Twins (ADSAT): Research Aims and Design. Twin Res Hum Genet 2020; 23:165-173. [PMID: 32482186 DOI: 10.1017/thg.2020.49] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The Academic Development Study of Australian Twins was established in 2012 with the purpose of investigating the relative influence of genes and environments in literacy and numeracy capabilities across two primary and two secondary school grades in Australia. It is the first longitudinal twin project of its kind in Australia and comprises a sample of 2762 twin pairs, 40 triplet sets and 1485 nontwin siblings. Measures include standardized literacy and numeracy test data collected at Grades 3, 5, 7 and 9 as part of the National Assessment Program: Literacy and Numeracy. A range of demographic and behavioral data was also collected, some at multiple longitudinal time points. This article outlines the background and rationale for the study and provides an overview for the research design, sample and measures collected. Findings emerging from the project and future directions are discussed.
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28
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Nick Martin and the Genetics of Depression: Sample Size, Sample Size, Sample Size. Twin Res Hum Genet 2020; 23:109-111. [PMID: 32383421 DOI: 10.1017/thg.2020.13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Nick Martin is a pioneer in recognizing the need for large sample size to study the complex, heterogeneous and polygenic disorders of common mental disorders. In the predigital era, questionnaires were mailed to thousands of twin pairs around Australia. Always quick to adopt new technology, Nick's studies progressed to phone interviews and then online. Moreover, Nick was early to recognize the value of collecting DNA samples. As genotyping technologies improved over the years, these twin and family cohorts were used for linkage, candidate gene and genome-wide association studies. These cohorts have underpinned many analyses to disentangle the complex web of genetic and lifestyle factors associated with mental health. With characteristic foresight, Nick is chief investigator of our Australian Genetics of Depression Study, which has recruited 16,000 people with self-reported depression (plus DNA samples) over a time frame of a few months - analyses are currently ongoing. The mantra of sample size, sample size, sample size has guided Nick's research over the last 30 years and continues to do so.
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29
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Campbell PJ, Brown SJ, Kendrew P, Lewer M, Lim EM, Joseph J, Cross SM, Wright MJ, Martin NG, Wilson SG, Walsh JP. Changes in Thyroid Function Across Adolescence: A Longitudinal Study. J Clin Endocrinol Metab 2020; 105:5700334. [PMID: 31922575 DOI: 10.1210/clinem/dgz331] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 01/09/2020] [Indexed: 02/13/2023]
Abstract
OBJECTIVE There are no large, longitudinal studies of thyroid function across adolescence. The aims of this study were to examine longitudinal trends in thyrotropin (TSH), free triiodothyronine (fT3) and free thyroxine (fT4) and determine age-specific reference ranges. METHODS Thyroid function was assessed in 3415 participants in the Brisbane Longitudinal Twin Study at ages 12, 14, and 16, using the Abbott ARCHITECT immunoassay. Longitudinal analyses were adjusted for body mass index and puberty. RESULTS In girls, mean fT4 (± SE) increased between age 12 and 14 (by 0.30 ± 0.08 pmol/L; P < 0.001), while remaining unchanged in boys; from age 14 to 16, fT4 increased in both girls (by 0.42 ± 0.07 pmol/L; P < 0.001) and boys (0.64 ± 0.07 pmol/L, P < 0.001). There was a slight increase in fT3 from age 12 to 14 years in girls (by 0.07 ± 0.03 pmol/L; P = 0.042), with a more marked increase in boys (0.29 ± 0.03 pmol/L; P < 0.001), followed by a decrease from age 14 to 16 in both sexes (girls, by 0.53 ± 0.02 pmol/L; P < 0.001; boys, by 0.62 ± 0.03 pmol/L; P < 0.001). From age 12 to 14, TSH showed no significant change in girls or boys, then levels increased from age 14 to 16 in both sexes (in girls, by 4.9%, 95% CI: 2.4%-10.3%, P = 0.020; in boys, by 7.2%, 95% CI: 3.0%-11.6%, P = 0.001). Reference ranges differed substantially from adults, particularly for fT4 and fT3. CONCLUSIONS Thyroid function tests in adolescents display complex, sexually dimorphic patterns. Implementation of adolescence-specific reference ranges may be appropriate.
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Affiliation(s)
- Purdey J Campbell
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
| | - Suzanne J Brown
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
| | | | | | - Ee Mun Lim
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
- Pathwest Laboratory Medicine, Nedlands, WA, Australia
| | - John Joseph
- Pathwest Laboratory Medicine, Nedlands, WA, Australia
| | - Simone M Cross
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | | | - Scott G Wilson
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
- School of Biomedical Sciences, University of Western Australia, Crawley, WA, Australia
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - John P Walsh
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
- Medical School, University of Western Australia, Crawley, WA, Australia
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Mitchell BL, Cuéllar-Partida G, Grasby KL, Campos AI, Strike LT, Hwang LD, Okbay A, Thompson PM, Medland SE, Martin NG, Wright MJ, Rentería ME. Educational attainment polygenic scores are associated with cortical total surface area and regions important for language and memory. Neuroimage 2020; 212:116691. [PMID: 32126298 DOI: 10.1016/j.neuroimage.2020.116691] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 02/06/2020] [Accepted: 02/26/2020] [Indexed: 02/01/2023] Open
Abstract
It is well established that higher cognitive ability is associated with larger brain size. However, individual variation in intelligence exists despite brain size and recent studies have shown that a simple unifactorial view of the neurobiology underpinning cognitive ability is probably unrealistic. Educational attainment (EA) is often used as a proxy for cognitive ability since it is easily measured, resulting in large sample sizes and, consequently, sufficient statistical power to detect small associations. This study investigates the association between three global (total surface area (TSA), intra-cranial volume (ICV) and average cortical thickness) and 34 regional cortical measures with educational attainment using a polygenic scoring (PGS) approach. Analyses were conducted on two independent target samples of young twin adults with neuroimaging data, from Australia (N = 1097) and the USA (N = 723), and found that higher EA-PGS were significantly associated with larger global brain size measures, ICV and TSA (R2 = 0.006 and 0.016 respectively, p < 0.001) but not average thickness. At the regional level, we identified seven cortical regions-in the frontal and temporal lobes-that showed variation in surface area and average cortical thickness over-and-above the global effect. These regions have been robustly implicated in language, memory, visual recognition and cognitive processing. Additionally, we demonstrate that these identified brain regions partly mediate the association between EA-PGS and cognitive test performance. Altogether, these findings advance our understanding of the neurobiology that underpins educational attainment and cognitive ability, providing focus points for future research.
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Affiliation(s)
- Brittany L Mitchell
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
| | - Gabriel Cuéllar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Katrina L Grasby
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Adrian I Campos
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Lachlan T Strike
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Liang-Dar Hwang
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sarah E Medland
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nicholas G Martin
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Miguel E Rentería
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
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31
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Gillespie NA, Bates TC, Hickie IB, Medland SE, Verhulst B, Kirkpatrick RM, Kendler KS, Martin NG, Benotsch EG. Genetic and environmental risk factors in the non-medical use of over-the-counter or prescribed analgesics, and their relationship to major classes of licit and illicit substance use and misuse in a population-based sample of young adult twins. Addiction 2019; 114:2229-2240. [PMID: 31313399 PMCID: PMC6868294 DOI: 10.1111/add.14750] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 12/03/2018] [Accepted: 07/09/2019] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND AIMS The non-medical use of over-the-counter or prescribed analgesics (NMUA) is a significant public health problem. Little is known about the genetic and environmental etiology of NMUA and how these risks relate to other classes of substance use and misuse. Our aims were to estimate the heritability NMUA and sources of genetic and environmental covariance with cannabis and nicotine use, cannabis and alcohol use disorders and nicotine dependence in Australian twins. DESIGN Biometrical genetic analyses or twin methods using structural equation univariate and multivariate modeling. SETTING Australia. PARTICIPANTS A total of 2007 young adult twins [66% female; μage = 25.9, standard deviation (SD) = 3.6, range = 18-38] from the Brisbane Longitudinal Twin Study retrospectively assessed between 2009 and 2016. MEASUREMENTS Self-reported NMUA (non-opioid or opioid-based), life-time nicotine, cannabis and opioid use, DSM-V cannabis and alcohol use disorders and the Fagerström Test for Nicotine Dependence. FINDINGS Life-time NMUA was reported by 19.4% of the sample. Univariate heritability explained 46% [95% confidence interval (CI) = 0.29-0.57] of the risks in NMUA. Multivariate analyses revealed that NMUA is moderately associated genetically with cannabis (rg = 0.41) and nicotine (rg = 0.45) use and nicotine dependence (rg = 0.34). In contrast, the genetic correlations with cannabis (rg = 0.15) and alcohol (rg = 0.07) use disorders are weak. CONCLUSIONS In young male and female adults in Australia, the non-medical use of over-the-counter or prescribed analgesics appears to have moderate heritability. NMUA is moderately associated with cannabis and nicotine use and nicotine dependence. Its genetic etiology is largely distinct from that of cannabis and alcohol use disorders.
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Affiliation(s)
- Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, VA, USA
- QIMR Berghofer Medical Research Institute, QLD, Australia
| | | | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, NSW, Australia
| | | | - Brad Verhulst
- Psychology Department, Michigan State University, MI, USA
| | - Robert M Kirkpatrick
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, VA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, VA, USA
| | | | - Eric G Benotsch
- Psychology Department, Virginia Commonwealth University, VA, USA
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32
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Twenty-Five and Up (25Up) Study: A New Wave of the Brisbane Longitudinal Twin Study. Twin Res Hum Genet 2019; 22:154-163. [PMID: 31198126 DOI: 10.1017/thg.2019.27] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The aim of the 25 and Up (25Up) study was to assess a wide range of psychological and behavioral risk factors behind mental illness in a large cohort of Australian twins and their non-twin siblings. Participants had already been studied longitudinally from the age of 12 and most recently in the 19Up study (mean age = 26.1 years, SD = 4.1, range = 20-39). This subsequent wave follows up these twins several years later in life (mean age = 29.7 years, SD = 2.2, range = 22-44). The resulting data set enables additional detailed investigations of genetic pathways underlying psychiatric illnesses in the Brisbane Longitudinal Twin Study (BLTS). Data were collected between 2016 and 2018 from 2540 twins and their non-twin siblings (59% female, including 341 monozygotic complete twin-pairs, 415 dizygotic complete pairs and 1028 non-twin siblings and singletons). Participants were from South-East Queensland, Australia, and the sample was of predominantly European ancestry. The 25Up study collected information on 20 different mental disorders, including depression, anxiety, substance use, psychosis, bipolar and attention-deficit hyper-activity disorder, as well as general demographic information such as occupation, education level, number of children, self-perceived IQ and household environment. In this article, we describe the prevalence, comorbidities and age of onset for all 20 examined disorders. The 25Up study also assessed general and physical health, including physical activity, sleep patterns, eating behaviors, baldness, acne, migraines and allergies, as well as psychosocial items such as suicidality, perceived stress, loneliness, aggression, sleep-wake cycle, sexual identity and preferences, technology and internet use, traumatic life events, gambling and cyberbullying. In addition, 25Up assessed female health traits such as morning sickness, breastfeeding and endometriosis. Furthermore, given that the 25Up study is an extension of previous BLTS studies, 86% of participants have already been genotyped. This rich resource will enable the assessment of epidemiological risk factors, as well as the heritability and genetic correlations of mental conditions.
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Hwang LD, Lin C, Gharahkhani P, Cuellar-Partida G, Ong JS, An J, Gordon SD, Zhu G, MacGregor S, Lawlor DA, Breslin PAS, Wright MJ, Martin NG, Reed DR. New insight into human sweet taste: a genome-wide association study of the perception and intake of sweet substances. Am J Clin Nutr 2019; 109:1724-1737. [PMID: 31005972 PMCID: PMC6537940 DOI: 10.1093/ajcn/nqz043] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 03/01/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Individual differences in human perception of sweetness are partly due to genetics; however, which genes are associated with the perception and the consumption of sweet substances remains unclear. OBJECTIVE The aim of this study was to verify previous reported associations within genes involved in the peripheral receptor systems (i.e., TAS1R2, TAS1R3, and GNAT3) and reveal novel loci. METHODS We performed genome-wide association scans (GWASs) of the perceived intensity of 2 sugars (glucose and fructose) and 2 high-potency sweeteners (neohesperidin dihydrochalcone and aspartame) in an Australian adolescent twin sample (n = 1757), and the perceived intensity and sweetness and the liking of sucrose in a US adult twin sample (n = 686). We further performed GWASs of the intake of total sugars (i.e., total grams of all dietary mono- and disaccharides per day) and sweets (i.e., handfuls of candies per day) in the UK Biobank sample (n = ≤174,424 white-British individuals). All participants from the 3 independent samples were of European ancestry. RESULTS We found a strong association between the intake of total sugars and the single nucleotide polymorphism rs11642841 within the FTO gene on chromosome 16 (P = 3.8 × 10-8) and many suggestive associations (P < 1.0 × 10-5) for each of the sweet perception and intake phenotypes. We showed genetic evidence for the involvement of the brain in both sweet taste perception and sugar intake. There was limited support for the associations with TAS1R2, TAS1R3, and GNAT3 in all 3 European samples. CONCLUSIONS Our findings indicate that genes additional to those involved in the peripheral receptor system are also associated with the sweet taste perception and intake of sweet-tasting foods. The functional potency of the genetic variants within TAS1R2, TAS1R3, and GNAT3 may be different between ethnic groups and this warrants further investigations.
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Affiliation(s)
- Liang-Dar Hwang
- The University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute, Brisbane, Queensland, Australia
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine
| | - Cailu Lin
- Monell Chemical Senses Center, Philadelphia, PA
| | - Puya Gharahkhani
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Gabriel Cuellar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine
| | - Jue-Sheng Ong
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine
| | - Jiyuan An
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Paul A S Breslin
- Monell Chemical Senses Center, Philadelphia, PA
- Department of Nutritional Sciences, School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ
| | - Margaret J Wright
- Queensland Brain Institute
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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Associations between brain structure and perceived intensity of sweet and bitter tastes. Behav Brain Res 2019; 363:103-108. [PMID: 30703394 DOI: 10.1016/j.bbr.2019.01.046] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 01/12/2019] [Accepted: 01/25/2019] [Indexed: 12/22/2022]
Abstract
Functional neuroimaging studies have identified brain regions associated with human taste perception, but only a few have investigated the associations with brain structure. Here, in this exploratory study, we examined the association between the volumes of 82 regions of interest (ROI) and the perceived intensities of sweet (a weighted mean rating of glucose, fructose, aspartame, neohesperidin dihydrochalcone) and bitter (propylthiouracil, quinine, caffeine) substances in a large Australian healthy cohort from the Queensland Twin IMaging (QTIM, n = 559) study and the perceived intensity of quinine in a large U.S. healthy cohort from the Human Connectome Project (HCP, n = 1101). In QTIM, the volumes of 3 cortical (right cuneus gyrus, left transverse temporal gyrus, right inferior temporal gyrus) and one subcortical structure (both left and right caudate) were associated with more than one taste stimulus (P < 0.05) and tended to be associated with both sweet and bitter tastes in the same direction, suggesting these ROIs were more broadly tuned for taste sensation. A further 11 ROIs were associated with a specific taste (sweetness: 4; propylthiouracil: 3; caffeine: 2; quinine: 2). In HCP, volumes of 5 ROIs were associated with quinine bitterness. The quinine-left entorhinal cortex association was found in both QTIM (r = -0.12, P = 3.7 × 10-3) and HCP (r = -0.06, P = 2.0 × 10-2). This study provides the first evidence that, even in healthy people, variation in brain structure is associated with taste intensity ratings, and provides new insights into the brain gustatory circuit.
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Lazaroo NK, Bates TC, Hansell NK, Wright MJ, Martin NG, Luciano M. Genetic Structure of IQ, Phonemic Decoding Skill, and Academic Achievement. Front Genet 2019; 10:195. [PMID: 30949193 PMCID: PMC6436069 DOI: 10.3389/fgene.2019.00195] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 02/25/2019] [Indexed: 11/13/2022] Open
Abstract
The aim of this study was to examine whether phonemic decoding skill (deficits of which characterize dyslexia) shares genetic and/or environmental covariance with scholastic abilities independent of general intelligence. Non-word reading ability, verbal and non-verbal IQ, and standardized academic achievement (Queensland Core Skills Test; QCST) were measured in Australian twins (up to 876 twin pairs and 80 singleton twins). Multivariate genetic analysis showed the presence of a general genetic factor, likely reflecting crystallized ability, which accounted for 45-76% of phenotypic variance in QCST scores, 62% of variance in Verbal IQ, 23% of variance in Performance IQ, and 19% of variance in phonological reading ability. The phonemic decoding genetic factor (explaining 48% of variance in phonemic decoding) was negatively associated with mathematical achievement scores (0.4%). Shared effects of common environment did not explain the relationship between reading ability and academic achievement beyond those also influencing IQ. The unique environmental reading factor (accounting for 26% of variance) influenced academic abilities related to written expression. Future research will need to address whether these reading-specific genetic and unique environment relationships arise from causal effects of reading on scholastic abilities, or whether both share a common influence, such as pleiotropic genes/environmental factors.
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Affiliation(s)
- Nikita K. Lazaroo
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Timothy C. Bates
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Narelle K. Hansell
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Margaret J. Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Michelle Luciano
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, United Kingdom
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Half the Genetic Variance in Vitamin D Concentration is Shared with Skin Colour and Sun Exposure Genes. Behav Genet 2019; 49:386-398. [DOI: 10.1007/s10519-019-09954-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 03/01/2019] [Indexed: 01/05/2023]
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Social Competence in Parents Increases Children’s Educational Attainment: Replicable Genetically-Mediated Effects of Parenting Revealed by Non-Transmitted DNA. Twin Res Hum Genet 2019; 22:1-3. [DOI: 10.1017/thg.2018.75] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
AbstractWe recently reported an association of offspring educational attainment with polygenic risk scores (PRS) computed on parent’s non-transmitted alleles for educational attainment using the second GWAS meta-analysis article on educational attainment published by the Social Science Genetic Association Consortium. Here we test the replication of these findings using a more powerful PRS from the third GWAS meta-analysis article by the Consortium. Each of the key findings of our previous paper is replicated using this improved PRS (N = 2335 adolescent twins and their genotyped parents). The association of children’s attainment with their own PRS increased substantially with the standardized effect size, moving from β = 0.134, 95% CI = 0.079, 0.188 for EA2, to β = 0.223, 95% CI = 0.169, 0.278, p < .001, for EA3. Parent’s PRS again predicted the socioeconomic status (SES) they provided to their offspring and increased from β = 0.201, 95% CI = 0.147, 0.256 to β = 0.286, 95% CI = 0.239, 0.333. Importantly, the PRS for alleles not transmitted to their offspring — therefore acting via the parenting environment — was increased in effect size from β = 0.058, 95% CI = 0.003, 0.114 to β = 0.067, 95% CI = 0.012, 0.122, p = .016. As previously found, this non-transmitted genetic effect was fully accounted for by parental SES. The findings reinforce the conclusion that genetic effects of parenting are substantial, explain approximately one-third the magnitude of an individual’s own genetic inheritance and are mediated by parental socioeconomic competence.
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Ong JS, Hwang LD, Zhong VW, An J, Gharahkhani P, Breslin PAS, Wright MJ, Lawlor DA, Whitfield J, MacGregor S, Martin NG, Cornelis MC. Understanding the role of bitter taste perception in coffee, tea and alcohol consumption through Mendelian randomization. Sci Rep 2018; 8:16414. [PMID: 30442986 PMCID: PMC6237869 DOI: 10.1038/s41598-018-34713-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 10/19/2018] [Indexed: 12/21/2022] Open
Abstract
Consumption of coffee, tea and alcohol might be shaped by individual differences in bitter taste perception but inconsistent observational findings provide little insight regarding causality. We conducted Mendelian randomization analyses using genetic variants associated with the perception of bitter substances (rs1726866 for propylthiouracil [PROP], rs10772420 for quinine and rs2597979 for caffeine) to evaluate the intake of coffee, tea and alcohol among up to 438,870 UK Biobank participants. A standard deviation (SD) higher in genetically predicted bitterness of caffeine was associated with increased coffee intake (0.146 [95%CI: 0.103, 0.189] cups/day), whereas a SD higher in those of PROP and quinine was associated with decreased coffee intake (-0.021 [-0.031, -0.011] and -0.081 [-0.108, -0.054] cups/day respectively). Higher caffeine perception was also associated with increased risk of being a heavy (>4 cups/day) coffee drinker (OR 1.207 [1.126, 1.294]). Opposite pattern of associations was observed for tea possibly due to the inverse relationship between both beverages. Alcohol intake was only negatively associated with PROP perception (-0.141 [-1.88, -0.94] times/month per SD increase in PROP bitterness). Our results reveal that bitter perception is causally associated with intake of coffee, tea and alcohol, suggesting a role of bitter taste in the development of bitter beverage consumption.
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Affiliation(s)
- Jue-Sheng Ong
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.
- School of Medicine, University of Queensland, Brisbane, Australia.
| | - Liang-Dar Hwang
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.
- School of Medicine, University of Queensland, Brisbane, Australia.
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, Australia.
| | - Victor W Zhong
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jiyuan An
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | - Paul A S Breslin
- Monell Chemical Senses Center, Philadelphia, PA, 19104, USA
- Department of Nutritional Sciences, School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, 4072, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Science, Bristol Medical School, University of Bristol, Canynge Hall, Whiteladies Road, Bristol, BS8 2PS, UK
| | - John Whitfield
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | | | - Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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Niemi MEK, Martin HC, Rice DL, Gallone G, Gordon S, Kelemen M, McAloney K, McRae J, Radford EJ, Yu S, Gecz J, Martin NG, Wright CF, Fitzpatrick DR, Firth HV, Hurles ME, Barrett JC. Common genetic variants contribute to risk of rare severe neurodevelopmental disorders. Nature 2018; 562:268-271. [PMID: 30258228 DOI: 10.1038/s41586-018-0566-4] [Citation(s) in RCA: 223] [Impact Index Per Article: 31.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 09/04/2018] [Indexed: 01/20/2023]
Abstract
There are thousands of rare human disorders that are caused by single deleterious, protein-coding genetic variants1. However, patients with the same genetic defect can have different clinical presentations2-4, and some individuals who carry known disease-causing variants can appear unaffected5. Here, to understand what explains these differences, we study a cohort of 6,987 children assessed by clinical geneticists to have severe neurodevelopmental disorders such as global developmental delay and autism, often in combination with abnormalities of other organ systems. Although the genetic causes of these neurodevelopmental disorders are expected to be almost entirely monogenic, we show that 7.7% of variance in risk is attributable to inherited common genetic variation. We replicated this genome-wide common variant burden by showing, in an independent sample of 728 trios (comprising a child plus both parents) from the same cohort, that this burden is over-transmitted from parents to children with neurodevelopmental disorders. Our common-variant signal is significantly positively correlated with genetic predisposition to lower educational attainment, decreased intelligence and risk of schizophrenia. We found that common-variant risk was not significantly different between individuals with and without a known protein-coding diagnostic variant, which suggests that common-variant risk affects patients both with and without a monogenic diagnosis. In addition, previously published common-variant scores for autism, height, birth weight and intracranial volume were all correlated with these traits within our cohort, which suggests that phenotypic expression in individuals with monogenic disorders is affected by the same variants as in the general population. Our results demonstrate that common genetic variation affects both overall risk and clinical presentation in neurodevelopmental disorders that are typically considered to be monogenic.
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Affiliation(s)
- Mari E K Niemi
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Hilary C Martin
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Daniel L Rice
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | | | - Scott Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Martin Kelemen
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jeremy McRae
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Elizabeth J Radford
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.,Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Sui Yu
- Department of Genetics and Molecular Pathology, SA Pathology, Women's and Children's Hospital, Adelaide, South Australia, Australia
| | - Jozef Gecz
- Adelaide Medical School and Robinson Research Institute, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia.,South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Caroline F Wright
- University of Exeter Medical School, Institute of Biomedical and Clinical Science, RILD, Royal Devon & Exeter Hospital, Exeter, UK
| | - David R Fitzpatrick
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Helen V Firth
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.,Department of Clinical Genetics, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Hwang LD, Gharahkhani P, Breslin PAS, Gordon SD, Zhu G, Martin NG, Reed DR, Wright MJ. Bivariate genome-wide association analysis strengthens the role of bitter receptor clusters on chromosomes 7 and 12 in human bitter taste. BMC Genomics 2018; 19:678. [PMID: 30223776 PMCID: PMC6142396 DOI: 10.1186/s12864-018-5058-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Accepted: 09/06/2018] [Indexed: 12/24/2022] Open
Abstract
Background Human perception of bitter substances is partially genetically determined. Previously we discovered a single nucleotide polymorphism (SNP) within the cluster of bitter taste receptor genes on chromosome 12 that accounts for 5.8% of the variance in the perceived intensity rating of quinine, and we strengthened the classic association between TAS2R38 genotype and the bitterness of propylthiouracil (PROP). Here we performed a genome-wide association study (GWAS) using a 40% larger sample (n = 1999) together with a bivariate approach to detect previously unidentified common variants with small effects on bitter perception. Results We identified two signals, both with small effects (< 2%), within the bitter taste receptor clusters on chromosomes 7 and 12, which influence the perceived bitterness of denatonium benzoate and sucrose octaacetate respectively. We also provided the first independent replication for an association of caffeine bitterness on chromosome 12. Furthermore, we provided evidence for pleiotropic effects on quinine, caffeine, sucrose octaacetate and denatonium benzoate for the three SNPs on chromosome 12 and the functional importance of the SNPs for denatonium benzoate bitterness. Conclusions These findings provide new insights into the genetic architecture of bitter taste and offer a useful starting point for determining the biological pathways linking perception of bitter substances. Electronic supplementary material The online version of this article (10.1186/s12864-018-5058-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Liang-Dar Hwang
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia. .,Queensland Brain Institute, University of Queensland, Brisbane, Queensland, 4072, Australia. .,Faculty of Medicine, University of Queensland, Brisbane, Queensland, 4006, Australia. .,University of Queensland Diamantina Institute, University of Queensland, Translational Research Institute, Brisbane, Queensland, 4102, Australia.
| | - Puya Gharahkhani
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia
| | - Paul A S Breslin
- Monell Chemical Senses Center, Philadelphia, Pennsylvania, 19104, USA.,Department of Nutritional Sciences, School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia
| | - Danielle R Reed
- Monell Chemical Senses Center, Philadelphia, Pennsylvania, 19104, USA
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, 4072, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, 4072, Australia
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42
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Cuellar-Partida G, Williams KM, Yazar S, Guggenheim JA, Hewitt AW, Williams C, Wang JJ, Kho PF, Saw SM, Cheng CY, Wong TY, Aung T, Young TL, Tideman JWL, Jonas JB, Mitchell P, Wojciechowski R, Stambolian D, Hysi P, Hammond CJ, Mackey DA, Lucas RM, MacGregor S. Genetically low vitamin D concentrations and myopic refractive error: a Mendelian randomization study. Int J Epidemiol 2018; 46:1882-1890. [PMID: 28586461 DOI: 10.1093/ije/dyx068] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2017] [Indexed: 01/08/2023] Open
Abstract
Background Myopia prevalence has increased in the past 20 years, with many studies linking the increase to reduced time spent outdoors. A number of recent observational studies have shown an inverse association between vitamin D [25(OH)D] serum levels and myopia. However, in such studies it is difficult to separate the effects of time outdoors and vitamin D levels. In this work we use Mendelian randomization (MR) to assess if genetically determined 25(OH)D levels contribute to the degree of myopia. Methods We performed MR using results from a meta-analysis of refractive error (RE) genome-wide association study (GWAS) that included 37 382 and 8 376 adult participants of European and Asian ancestry, respectively, published by the Consortium for Refractive Error And Myopia (CREAM). We used single nucleotide polymorphisms (SNPs) in the DHCR7, CYP2R1, GC and CYP24A1 genes with known effects on 25(OH)D concentration as instrumental variables (IV). We estimated the effect of 25(OH)D on myopia level using a Wald-type ratio estimator based on the effect estimates from the CREAM GWAS. Results Using the combined effect attributed to the four SNPs, the estimate for the effect of 25(OH)D on refractive error was -0.02 [95% confidence interval (CI) -0.09, 0.04] dioptres (D) per 10 nmol/l increase in 25(OH)D concentration in Caucasians and 0.01 (95% CI -0.17, 0.19) D per 10 nmol/l increase in Asians. Conclusions The tight confidence intervals on our estimates suggest the true contribution of vitamin D levels to degree of myopia is very small and indistinguishable from zero. Previous findings from observational studies linking vitamin D levels to myopia were likely attributable to the effects of confounding by time spent outdoors.
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Affiliation(s)
- Gabriel Cuellar-Partida
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,University of Queensland Diamantina Institute, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Katie M Williams
- Department of Ophthalmology.,Department of Ophthalmology and Twin Research, King's College London, London, UK
| | - Seyhan Yazar
- Lions Eye Institute, University of Western Australia, Perth, WA, Australia
| | | | - Alex W Hewitt
- Menzies Research Institute Tasmania, University of Tasmania, Hobart, Australia
| | - Cathy Williams
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Jie Jin Wang
- Centre for Vision Research, Department of Ophthalmology and Westmead Institute for Medical Research, University of Sydney, Camperdown, NSW, Australia
| | - Pik-Fang Kho
- Department of Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD,Australia
| | - Seang Mei Saw
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Graduate Medical School.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Graduate Medical School.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Graduate Medical School.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Graduate Medical School.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Terri L Young
- Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - J Willem L Tideman
- Department of Ophthalmology and Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jost B Jonas
- Beijing Institute of Ophthalmology, Capital University of Medical Science, Beijing Ophthalmology & Visual Sciences Key Laboratory, Beijing, China.,Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University Heidelberg, Seegartenklinik Heidelberg, Germany
| | | | - Paul Mitchell
- Centre for Vision Research, Department of Ophthalmology and Westmead Institute for Medical Research, University of Sydney, Camperdown, NSW, Australia
| | | | - Dwight Stambolian
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, PA, USA
| | - Pirro Hysi
- Department of Ophthalmology and Twin Research, King's College London, London, UK
| | - Christopher J Hammond
- Department of Ophthalmology.,Department of Ophthalmology and Twin Research, King's College London, London, UK
| | - David A Mackey
- Lions Eye Institute, University of Western Australia, Perth, WA, Australia
| | - Robyn M Lucas
- National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University, Canberra, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
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The Genetic Relationship Between Psychological Distress, Somatic Distress, Affective Disorders, and Substance Use in Young Australian Adults: A Multivariate Twin Study. Twin Res Hum Genet 2018; 21:347-360. [DOI: 10.1017/thg.2018.33] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Psychological distress (PSYCH), somatic distress (SOMA), affective disorders (AD), and substance use (SU) frequently co-occur. The genetic relationship between PSYCH and SOMA, however, remains understudied. We examined the genetic and environmental influences on these two disorders and their comorbid AD and SU using structural equation modeling. Self-reported PSYCH and SOMA were measured in 1,548 twins using the two subscales of a 12-item questionnaire, the Somatic and Psychological Health Report. Its reliability and psychometric properties were examined. Six ADs, involvement of licit and illicit substance, and two SU disorders were obtained from 1,663–2,132 twins using the World Mental Health Composite International Diagnostic Interview and/or from an online adaption of the same. SU phenotypes (heritability: 49–79%) were found to be more heritable than the affective disorder phenotypes (heritability: 32–42%), SOMA (heritability: 25%), and PSYCH (heritability: 23%). We fit separate non-parametric item response theory models for PSYCH, SOMA, AD, and SU. The IRT scores were used as the refined phenotypes for fitting multivariate genetic models. The best-fitting model showed the similar amount of genetic overlap between PSYCH–AD (genetic correlationrG= 0.49) and SOMA–AD (rG=0.53), as well as between PSYCH–SU (rG= 0.23) and SOMA–SU (rG= 0.25). Unique environmental factors explained 53% to 76% of the variance in each of these four phenotypes, whereas additive genetic factors explained 17% to 46% of the variance. The covariance between the four phenotypes was largely explained by unique environmental factors. Common genetic factor had a significant influence on all the four phenotypes, but they explained a moderate portion of the covariance.
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Liu Y, Gillespie NA, Ye L, Zhu G, Duffy DL, Martin NG. The Relationship Between Personality and Somatic and Psychological Distress: A Comparison of Chinese and Australian Adolescents. Behav Genet 2018; 48:315-322. [PMID: 29872974 DOI: 10.1007/s10519-018-9905-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 05/30/2018] [Indexed: 12/18/2022]
Abstract
The extent to which correlations between personality domains and physical and psychological health generalize cross-culturally is unclear. We compared the strength of associations between the personality domains and somatic and psychological distress in Chinese (N = 2069) and a genetically informative sample of Australian (N = 2936) adolescents. We also examined the genetic and environmental etiology between personality, somatic and psychological distress in an Australian sample of 390 monozygotic twins and 698 dizygotic twins. In both populations, personality was assessed using the Junior Eysenck Personality Questionnaire. Somatic and psychological distress was assessed using the Somatic and Psychological Health Report. We found significant cultural differences in the relationship between adolescents' personality traits and somatic and psychological distress. Extraversion was positively associated with somatic distress in the Chinese but not in Australian adolescents. In the Australian twins, genetic covariation between neuroticism and somatic and psychological distress was stronger compared to the genetic associations between either psychoticism or extraversion with psychological distress.
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Affiliation(s)
- Yangyang Liu
- Department of Psychology, Nanjing University, Hankoulu#22, Nanjing, People's Republic of China.
- Tianjin University, Tianjin, People's Republic of China.
| | - Nathan A Gillespie
- Tianjin University, Tianjin, People's Republic of China
- Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
| | - Lin Ye
- Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Gu Zhu
- Tianjin University, Tianjin, People's Republic of China
- Queensland Institute of Medical Research, Brisbane, Australia
| | - David L Duffy
- Tianjin University, Tianjin, People's Republic of China
- Queensland Institute of Medical Research, Brisbane, Australia
| | - Nicholas G Martin
- Tianjin University, Tianjin, People's Republic of China
- Queensland Institute of Medical Research, Brisbane, Australia
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Fernández E, Collins MO, Frank RAW, Zhu F, Kopanitsa MV, Nithianantharajah J, Lemprière SA, Fricker D, Elsegood KA, McLaughlin CL, Croning MDR, Mclean C, Armstrong JD, Hill WD, Deary IJ, Cencelli G, Bagni C, Fromer M, Purcell SM, Pocklington AJ, Choudhary JS, Komiyama NH, Grant SGN. Arc Requires PSD95 for Assembly into Postsynaptic Complexes Involved with Neural Dysfunction and Intelligence. Cell Rep 2018; 21:679-691. [PMID: 29045836 PMCID: PMC5656750 DOI: 10.1016/j.celrep.2017.09.045] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Revised: 08/03/2017] [Accepted: 09/13/2017] [Indexed: 12/12/2022] Open
Abstract
Arc is an activity-regulated neuronal protein, but little is known about its interactions, assembly into multiprotein complexes, and role in human disease and cognition. We applied an integrated proteomic and genetic strategy by targeting a tandem affinity purification (TAP) tag and Venus fluorescent protein into the endogenous Arc gene in mice. This allowed biochemical and proteomic characterization of native complexes in wild-type and knockout mice. We identified many Arc-interacting proteins, of which PSD95 was the most abundant. PSD95 was essential for Arc assembly into 1.5-MDa complexes and activity-dependent recruitment to excitatory synapses. Integrating human genetic data with proteomic data showed that Arc-PSD95 complexes are enriched in schizophrenia, intellectual disability, autism, and epilepsy mutations and normal variants in intelligence. We propose that Arc-PSD95 postsynaptic complexes potentially affect human cognitive function. TAP tag and purification of endogenous Arc protein complexes from the mouse brain PSD95 is the major Arc binding protein, and both assemble into 1.5-MDa supercomplexes PSD95 is essential for recruitment of Arc to synapses Mutations and genetic variants in Arc-PSD95 are linked to cognition
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Affiliation(s)
- Esperanza Fernández
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; KU Leuven, Center for Human Genetics and Leuven Institute for Neurodegenerative Diseases (LIND), and VIB Center for the Biology of Disease, Leuven, Belgium
| | - Mark O Collins
- Proteomic Mass Spectrometry, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK
| | - René A W Frank
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | - Fei Zhu
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Maksym V Kopanitsa
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Synome Ltd., Moneta Building, Babraham Research Campus, Cambridge, UK
| | - Jess Nithianantharajah
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Sarah A Lemprière
- Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - David Fricker
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Synome Ltd., Moneta Building, Babraham Research Campus, Cambridge, UK
| | - Kathryn A Elsegood
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Catherine L McLaughlin
- Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Mike D R Croning
- Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Colin Mclean
- School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh, UK
| | - J Douglas Armstrong
- School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh, UK
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, UK
| | - Giulia Cencelli
- KU Leuven, Center for Human Genetics and Leuven Institute for Neurodegenerative Diseases (LIND), and VIB Center for the Biology of Disease, Leuven, Belgium; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Claudia Bagni
- KU Leuven, Center for Human Genetics and Leuven Institute for Neurodegenerative Diseases (LIND), and VIB Center for the Biology of Disease, Leuven, Belgium; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Menachem Fromer
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Shaun M Purcell
- Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Andrew J Pocklington
- Institute of Psychological Medicine & Clinical Neurosciences, University of Cardiff, Cardiff, Wales, UK
| | - Jyoti S Choudhary
- Proteomic Mass Spectrometry, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK
| | - Noboru H Komiyama
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK
| | - Seth G N Grant
- Genes to Cognition Programme, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK; Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK.
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Scott J, Davenport TA, Parker R, Hermens DF, Lind PA, Medland SE, Wright MJ, Martin NG, Gillespie NA, Hickie IB. Pathways to depression by age 16 years: Examining trajectories for self-reported psychological and somatic phenotypes across adolescence. J Affect Disord 2018; 230:1-6. [PMID: 29355726 DOI: 10.1016/j.jad.2017.12.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 10/16/2017] [Accepted: 12/03/2017] [Indexed: 01/12/2023]
Abstract
BACKGROUND Sex differences in rates of depression emerge during adolescence. However, it is unclear whether symptom patterns and trajectories differ significantly according to gender in youth. Barriers to research include the fact that most self-report tools are weighted towards psychological rather than somatic symptoms. METHODS Data were collected on symptoms of depression in about 1800 individuals at ages 12, 14 and 16 years. Odds ratios and 95% confidence intervals were used to examine the trajectory of psychological and somatic phenotypes and self-reported depression caseness over time. RESULTS At age 12, 24% of participants met criteria for self-reported depression caseness. Although there was only a small incremental increase in the prevalence over time (about 5%), 57% of participants met criteria for self-reported depression caseness at least once. Generic symptoms at age 12 were associated with depression longitudinally, although early transition to caseness was reported in females only. Categorization as a psychological phenotype at age 12 predicted depression at age 14 and/or 16 years, especially in females. The somatic phenotype was more common in males, but showed a weaker association with self-reported depression caseness over time. LIMITATIONS Depression was assessed by self-report; only 30% of participants had ratings for age 12, 14 and 16. CONCLUSIONS Although sub-threshold psychological and somatic syndromes often co-occur in cases of self-reported depression in adolescence, longitudinally they may represent independent symptom trajectories. However, it is important to remember that self-reported depression is indicative of, but not confirmation of a depressive episode that meets diagnostic criteria.
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Affiliation(s)
- Jan Scott
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK; Brain & Mind Centre, University of Sydney, Sydney, Australia.
| | | | - Richard Parker
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | - Penelope A Lind
- Queensland Brain Institute, the University of Queensland, Brisbane, Australia
| | - Sarah E Medland
- Centre for Advanced Imaging, the University of Queensland, Brisbane, Australia
| | - Margaret J Wright
- Queensland Brain Institute, the University of Queensland, Brisbane, Australia; Centre for Advanced Imaging, the University of Queensland, Brisbane, Australia
| | - Nicholas G Martin
- Queensland Brain Institute, the University of Queensland, Brisbane, Australia
| | - Nathan A Gillespie
- Centre for Advanced Imaging, the University of Queensland, Brisbane, Australia; Virginia Institute for Psychiatric and Behavioral Genetics, VCU, Richmond, VA, USA
| | - Ian B Hickie
- Brain & Mind Centre, University of Sydney, Sydney, Australia
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The Nature of Nurture: Using a Virtual-Parent Design to Test Parenting Effects on Children's Educational Attainment in Genotyped Families. Twin Res Hum Genet 2018. [DOI: 10.1017/thg.2018.11] [Citation(s) in RCA: 103] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Research on environmental and genetic pathways to complex traits such as educational attainment (EA) is confounded by uncertainty over whether correlations reflect effects of transmitted parental genes, causal family environments, or some, possibly interactive, mixture of both. Thus, an aggregate of thousands of alleles associated with EA (a polygenic risk score; PRS) may tap parental behaviors and home environments promoting EA in the offspring. New methods for unpicking and determining these causal pathways are required. Here, we utilize the fact that parents pass, at random, 50% of their genome to a given offspring to create independent scores for the transmitted alleles (conventional EA PRS) and a parental score based on allelesnot transmittedto the offspring (EA VP_PRS). The formal effect of non-transmitted alleles on offspring attainment was tested in 2,333 genotyped twins for whom high-quality measures of EA, assessed at age 17 years, were available, and whose parents were also genotyped. Four key findings were observed. First, the EA PRS and EA VP_PRS were empirically independent, validating the virtual-parent design. Second, in this family-based design, children's own EA PRS significantly predicted their EA (β = 0.15), ruling out stratification confounds as a cause of the association of attainment with the EA PRS. Third, parental EA PRS predicted the SES environment parents provided to offspring (β = 0.20), and parental SES and offspring EA were significantly associated (β = 0.33). This would suggest that the EA PRS is at least as strongly linked to social competence as it is to EA, leading to higher attained SES in parents and, therefore, a higher experienced SES for children. In a full structural equation model taking account of family genetic relatedness across multiple siblings the non-transmitted allele effects were estimated at similar values; but, in this more complex model, confidence intervals included zero. A test using the forthcoming EA3 PRS may clarify this outcome. The virtual-parent method may be applied to clarify causality in other phenotypes where observational evidence suggests parenting may moderate expression of other outcomes, for instance in psychiatry.
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Binz T, Rietschel L, Streit F, Hofmann M, Gehrke J, Herdener M, Quednow B, Martin N, Rietschel M, Kraemer T, Baumgartner M. Endogenous cortisol in keratinized matrices: Systematic determination of baseline cortisol levels in hair and the influence of sex, age and hair color. Forensic Sci Int 2018; 284:33-38. [DOI: 10.1016/j.forsciint.2017.12.032] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 12/15/2017] [Accepted: 12/16/2017] [Indexed: 01/03/2023]
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Rietschel L, Streit F, Zhu G, McAloney K, Frank J, Couvy-Duchesne B, Witt SH, Binz TM, McGrath J, Hickie IB, Hansell NK, Wright MJ, Gillespie NA, Forstner AJ, Schulze TG, Wüst S, Nöthen MM, Baumgartner MR, Walker BR, Crawford AA, Colodro-Conde L, Medland SE, Martin NG, Rietschel M. Hair Cortisol in Twins: Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes. Sci Rep 2017; 7:15351. [PMID: 29127340 PMCID: PMC5703444 DOI: 10.1038/s41598-017-11852-3] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 08/30/2017] [Indexed: 12/19/2022] Open
Abstract
Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.
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Affiliation(s)
- Liz Rietschel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, Research Department, University of Bern, Bern, Switzerland.
- SRH University Heidelberg, Academy for Psychotherapy, Heidelberg, Germany.
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Gu Zhu
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research, Brisbane, Australia
| | - Kerrie McAloney
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research, Brisbane, Australia
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Baptiste Couvy-Duchesne
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research, Brisbane, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tina M Binz
- Zurich Institute of Forensic Medicine, Centre for Forensic Hair Analysis, University of Zurich, Zurich, Switzerland
| | - John McGrath
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, Australia
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Narelle K Hansell
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Nathan A Gillespie
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research, Brisbane, Australia
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Life & Brain Center, Department of Genomics, University of Bonn, Bonn, Germany
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
- Human Genomics Research Group, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Thomas G Schulze
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, USA
- Institute of Psychiatric Phenomics and Genomics (IPPG), Medical Center of the University of Munich, Campus Innenstadt, Munich, DE, Germany
- Human Genetics Branch, NIMH Division of Intramural Research Programs, Bethesda, USA
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Goettingen, DE, Germany
| | - Stefan Wüst
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Institute of Experimental Psychology, University of Regensburg, Regensburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Life & Brain Center, Department of Genomics, University of Bonn, Bonn, Germany
| | - Markus R Baumgartner
- Zurich Institute of Forensic Medicine, Centre for Forensic Hair Analysis, University of Zurich, Zurich, Switzerland
| | - Brian R Walker
- British Heart Foundation Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Andrew A Crawford
- British Heart Foundation Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Lucía Colodro-Conde
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research, Brisbane, Australia
| | - Sarah E Medland
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research, Brisbane, Australia
| | - Nicholas G Martin
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research, Brisbane, Australia
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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Abstract
Acne vulgaris is a skin disease with a multifactorial and complex pathology. While several twin studies have estimated that acne has a heritability of up to 80%, the genomic elements responsible for the origin and pathology of acne are still undiscovered. Here we performed a twin-based structural equation model, using available data on acne severity for an Australian sample of 4,491 twins and their siblings aged from 10 to 24. This study extends by a factor of 3 an earlier analysis of the genetic factors of acne. Acne severity was rated by nurses on a 4-point scale (1 = absent to 4 = severe) on up to three body sites (face, back, chest) and on up to three occasions (age 12, 14, and 16). The phenotype that we analyzed was the most severe rating at any site or age. The polychoric correlation for monozygotic twins was higher (r MZ = 0.86, 95% CI [0.81, 0.90]) than for dizygotic twins (r DZ = 0.42, 95% CI [0.35, 0.47]). A model that includes additive genetic effects and unique environmental effects was the most parsimonious model to explain the genetic variance of acne severity, and the estimated heritability was 0.85 (95% CI [0.82, 0.87]). We then conducted a genome-wide analysis including an additional 271 siblings - for a total of 4,762 individuals. A genome-wide association study (GWAS) scan did not detect loci associated with the severity of acne at the threshold of 5E-08 but suggestive association was found for three SNPs: rs10515088 locus 5q13.1 (p = 3.9E-07), rs12738078 locus 1p35.5 (p = 6.7E-07), and rs117943429 locus 18q21.2 (p = 9.1E-07). The 5q13.1 locus is close to PIK3R1, a gene that has a potential regulatory effect on sebocyte differentiation.
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