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Fieder M, Huber S. Genetic Predisposition of Different Social Status Indicators in Men and Women. Twin Res Hum Genet 2024:1-11. [PMID: 39248653 DOI: 10.1017/thg.2024.23] [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: 09/10/2024]
Abstract
Although there is evidence that social status has a genetic basis, it is less known whether the genetic predisposition differs between men and women as well as among different status indicators and whether there are any intercorrelations among predispositions of status indicators. We therefore investigated the genetic predisposition for different indicators of social status separately for men and women, using polygenic scores obtained from the Wisconsin Longitudinal Study. We used multivariate polygenic regression of 7 different social status indicators on a total of 24 different polygenic scores. We find that in both men and women, wages and education show more associations with polygenic scores than the other status indicators. Also, the genetic predispositions for education and wages are correlated in both men and women, whereas in men more than in women, the genetic predispositions seem to cluster into wages and education on the one hand, and status indicators of position in the hierarchy, on the other hand, with being in a management position somewhere in between. These findings are consistent with an assumption of two different forms of selection pressure associated with either cognitive skill or dominance, which holds true particularly in men. We conclude that the genetic predisposition to higher social status may have changed even though the importance of the cultural trait of social status may have been very constant. Social status may thus be an example of a social trait of constant importance, but with a changing genetic predisposition.
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Affiliation(s)
- Martin Fieder
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Susanne Huber
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
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Zheng B, Fletcher JM, Song J, Lu Q. Analysis of Sex-Specific Gene-by-Cohort and Genetic Correlation-by-Cohort Interaction in Educational and Reproductive Outcomes Using the UK Biobank Data. JOURNAL OF HEALTH AND SOCIAL BEHAVIOR 2024; 65:432-448. [PMID: 37572045 DOI: 10.1177/00221465231188166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/14/2023]
Abstract
Synthesizing prior gene-by-cohort (G×C) interaction studies, we theorize that changes in genetic effects by social conditions depend on the level of resource constraints, the distribution and use of resources, structural constraints, and constraints on individual choice. Motivated by the theory, we explored several sex-specific G×C trends across a set of outcomes using 30 birth cohorts of UK Biobank data (N = 400,000). We find that genetic coefficients on years of schooling and secondary educational attainment substantially decrease, but genetic coefficients on college attainments only moderately increase. On the other hand, genetic coefficients for education ranks are stable. Genetic coefficients on reproductive behavior increase for younger cohorts. Additional genetic-correlation-by-cohort analysis shows shifting genetic correlations between education and reproductive behavior. Our results suggest that the G×C patterns are highly heterogenous and that social and genetic factors jointly shape the diversity of human phenotypes.
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Affiliation(s)
- Boyan Zheng
- University of Wisconsin-Madison, Madison, WI, USA
| | | | - Jie Song
- University of Wisconsin-Madison, Madison, WI, USA
| | - Qiongshi Lu
- University of Wisconsin-Madison, Madison, WI, USA
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3
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Baker S, Biroli P, van Kippersluis H, von Hinke S. Advantageous early-life environments cushion the genetic risk for ischemic heart disease. Proc Natl Acad Sci U S A 2024; 121:e2314056121. [PMID: 38917008 PMCID: PMC11228495 DOI: 10.1073/pnas.2314056121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 04/18/2024] [Indexed: 06/27/2024] Open
Abstract
In one of the first papers on the impact of early-life conditions on individuals' health in older age, Barker and Osmond [Lancet, 327, 1077-1081 (1986)] show a strong positive relationship between infant mortality rates in the 1920s and ischemic heart disease in the 1970s. We merge historical data on infant mortality rates to 370,000 individual records in the UK Biobank using information on local area and year of birth. We replicate the association between the early-life infant mortality rate and later-life ischemic heart disease in our sample. We then go "beyond Barker," by showing considerable genetic heterogeneity in this association that is robust to within-area as well as within-family analyses. We find no association between the polygenic index and heart disease in areas with the lowest infant mortality rates, but a strong positive relationship in areas characterized by high infant mortality. These findings suggest that advantageous environments can cushion one's genetic disease risk.
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Affiliation(s)
- Samuel Baker
- School of Economics, University of Bristol, Bristol BS8 1TU, United Kingdom
| | - Pietro Biroli
- Department of Economic Sciences, University of Bologna, Bologna, Italy
| | - Hans van Kippersluis
- Erasmus School of Economics, Erasmus University Rotterdam, 3062 PA Rotterdam, The Netherlands
| | - Stephanie von Hinke
- School of Economics, University of Bristol, Bristol BS8 1TU, United Kingdom
- Institute for Fiscal Studies, London WC1E 7AE, United Kingdom
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4
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Wan X, Yu H, Yang M, Hou W, Xie J, Xu K, Ma Y, Ma R, Wang F, Xu P. Study on the causal relationship between educational attainment and delirium: A two-sample Mendelian randomization study. Heliyon 2024; 10:e28697. [PMID: 38571646 PMCID: PMC10988048 DOI: 10.1016/j.heliyon.2024.e28697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 01/26/2024] [Accepted: 03/22/2024] [Indexed: 04/05/2024] Open
Abstract
This study aimed to investigate whether there is a causal relationship between educational attainment and delirium at the genetic level using the Mendelian randomization method, and provide new evidence for studies in this field. We found a causal relationship between educational attainment and delirium at the genetic level after excluding confounders using Mendelian randomization. The inverse variance weighting method of random effects was the main analysis method. The weighted median and Mendelian Randomization-Egger methods, as well as simple, and weighted modes were used as supplementary analysis methods. Additionally, horizontal pleiotropy tests were conducted, including the Mendelian Randomization-Egger intercept test and Mendelian Randomization Pleiotropy RESidual Sum and Outlier. Cochran's Q statistic was used to assess the size of heterogeneity. We retrieved all second single nucleotide polymorphism features and performed multivariate Mendelian randomization to adjust for the effect of potential confounders on our results. The inverse variance weighting suggested a negative correlation between genetically predicted educational attainment and delirium (0.67[0.49-0.92], p = 0.013); Mendelian Randomization Pleiotropy RESidual Sum and Outlier (0.67[0.49-0.92], p = 0.013) and multivariate Mendelian randomization (0.52[0.33-0.82], p = 0.005) results were generally consistent with the inverse variance weighting method. The Mendelian Randomization-Egger, simple, and weighted mode results were consistent with the inverse variance weighting results. Our results were not affected by pleiotropy or heterogeneity (p > 0.05, for both pleiotropy and heterogeneity). In addition, the "leave-one-out" analysis showed that the results of our Mendelian randomization analysis were not influenced by individual single nucleotide polymorphisms. Studies have found a causal relationship between educational attainment and delirium at the genetic level; higher educational attainment may be a protective factor against delirium. Clinically, more attention should be paid to patients at a high risk of delirium with low educational attainment.
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Affiliation(s)
| | | | - Mingyi Yang
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Weikun Hou
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Jiale Xie
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Ke Xu
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Yujie Ma
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Rui Ma
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Fan Wang
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Peng Xu
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
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Ren Z, Wesselius A, Stehouwer CDA, Brouwers MCGJ. Relationship between educational attainment and non-alcoholic fatty liver disease: A two-sample Mendelian randomization study. Dig Liver Dis 2024; 56:565-570. [PMID: 38104027 DOI: 10.1016/j.dld.2023.11.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/28/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Observational studies have identified an inverse association between education and non-alcoholic fatty liver disease (NAFLD). However, it is not possible to establish causality for this relationship. AIMS To gain more insight into the causal nature of the relationship between education and NAFLD. METHODS We performed two-sample Mendelian randomization (MR) analyses using summary-level, large-scale datasets to study the association of genetically predicted educational attainment (n = 1271 genetic instruments, obtained from 1,131,881 participants) with risk of NAFLD (i.e., liver fat [n = 32,858 participants] and electronic health record (EHR)-based NAFLD [n = 778,614 participants]). In sensitivity analyses, educational attainment was replaced by three education-related traits (i.e., genetically predicted cognition, math ability and highest math). RESULTS Inverse-variance weighted method showed a statistically significant association between genetically predicted educational attainment and liver fat (beta: -0.251, 95%CI: -0.305; -0.198) and EHR-based NAFLD (OR: 0.609, 95%CI: 0.547; 0.677). MR-Egger regression did not show statistically significant intercepts. Similar findings were obtained when other MR tests were used or when educational attainment was replaced by education-related traits. CONCLUSIONS This study suggests a causal, protective effect of higher education on NAFLD risk. Societal interventions targeted at people with low education are needed to alleviate the burden of NAFLD.
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Affiliation(s)
- Zhewen Ren
- Department of Internal Medicine, Division of Endocrinology and Metabolic Diseases, Maastricht University Medical Center, Maastricht, the Netherlands; Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands; NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
| | - Anke Wesselius
- NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands; Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
| | - Coen D A Stehouwer
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands; Department of Internal Medicine, Division of General Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Martijn C G J Brouwers
- Department of Internal Medicine, Division of Endocrinology and Metabolic Diseases, Maastricht University Medical Center, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands; CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands.
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Sunde HF, Eftedal NH, Cheesman R, Corfield EC, Kleppesto TH, Seierstad AC, Ystrom E, Eilertsen EM, Torvik FA. Genetic similarity between relatives provides evidence on the presence and history of assortative mating. Nat Commun 2024; 15:2641. [PMID: 38531929 PMCID: PMC10966108 DOI: 10.1038/s41467-024-46939-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 03/13/2024] [Indexed: 03/28/2024] Open
Abstract
Assortative mating - the non-random mating of individuals with similar traits - is known to increase trait-specific genetic variance and genetic similarity between relatives. However, empirical evidence is limited for many traits, and the implications hinge on whether assortative mating has started recently or many generations ago. Here we show theoretically and empirically that genetic similarity between relatives can provide evidence on the presence and history of assortative mating. First, we employed path analysis to understand how assortative mating affects genetic similarity between family members across generations, finding that similarity between distant relatives is more affected than close relatives. Next, we correlated polygenic indices of 47,135 co-parents from the Norwegian Mother, Father, and Child Cohort Study (MoBa) and found genetic evidence of assortative mating in nine out of sixteen examined traits. The same traits showed elevated similarity between relatives, especially distant relatives. Six of the nine traits, including educational attainment, showed greater genetic variance among offspring, which is inconsistent with stable assortative mating over many generations. These results suggest an ongoing increase in familial similarity for these traits. The implications of this research extend to genetic methodology and the understanding of social and economic disparities.
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Affiliation(s)
- Hans Fredrik Sunde
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
- Department of Psychology, University of Oslo, Oslo, Norway.
| | | | - Rosa Cheesman
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Elizabeth C Corfield
- Nic Waals Institute, Lovisenberg Diakonale Hospital, Oslo, Norway
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Thomas H Kleppesto
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Eivind Ystrom
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Espen Moen Eilertsen
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Fartein Ask Torvik
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
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Liu Y, Wang Z, Li D, Lv B. Bilirubin and postpartum depression: an observational and Mendelian randomization study. Front Psychiatry 2024; 15:1277415. [PMID: 38525255 PMCID: PMC10957769 DOI: 10.3389/fpsyt.2024.1277415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 02/12/2024] [Indexed: 03/26/2024] Open
Abstract
Background Postpartum depression (PPD) is one of the most common complications of delivery and is usually disregarded. Several risk factors of PPD have been identified, but its pathogenesis has not been completely understood. Serum bilirubin has been found to be a predictor of depression, whose relationship with PPD has not been investigated. Methods Observational research was performed followed by a two-sample Mendelian randomization (MR) analysis. From 2017 to 2020, the clinical data of pregnant women were retrospectively extracted. Logistic regression and random forest algorithm were employed to assess the risk factors of PPD, including the serum levels of total bilirubin and direct bilirubin. To further explore their potential causality, univariable and multivariable Mendelian randomization (MVMR) were conducted. Sensitivity analyses for MR were performed to test the robustness of causal inference. Results A total of 1,810 patients were included in the PPD cohort, of which 631 (34.87%) were diagnosed with PPD. Compared with the control group, PPD patients had a significantly lower level of total bilirubin (9.2 μmol/L, IQR 7.7, 11.0 in PPD; 9.7 μmol/L, IQR 8.0, 12.0 in control, P < 0.001) and direct bilirubin (2.0 μmol/L, IQR 1.6, 2.6 in PPD; 2.2 μmol/L, IQR 1.7, 2.9 in control, P < 0.003). The prediction model identified eight independent predictive factors of PPD, in which elevated total bilirubin served as a protective factor (OR = 0.94, 95% CI 0.90-0.99, P = 0.024). In the MR analyses, genetically predicted total bilirubin was associated with decreased risk of PPD (IVW: OR = 0.86, 95% CI 0.76-0.97, P = 0.006), which remained consistent after adjusting educational attainment, income, and gestational diabetes mellitus. Conversely, there is a lack of solid evidence to support the causal relationship between PPD and bilirubin. Conclusion Our results suggested that decreased total bilirubin was associated with the incidence of PPD. Future studies are warranted to investigate its potential mechanisms and illuminate the pathogenesis of PPD.
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Affiliation(s)
- Yi Liu
- Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
| | - Zhihao Wang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Duo Li
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China
| | - Bin Lv
- Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
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Gorelik AJ, Paul SE, Miller AP, Baranger DAA, Lin S, Zhang W, Elsayed NM, Modi H, Addala P, Bijsterbosch J, Barch DM, Karcher NR, Hatoum AS, Agrawal A, Bogdan R, Johnson EC. Associations Between Polygenic Scores for Cognitive and Non-cognitive Factors of Educational Attainment and Measures of Behavior, Psychopathology, and Neuroimaging in the Adolescent Brain Cognitive Development Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.27.23297675. [PMID: 37961716 PMCID: PMC10635216 DOI: 10.1101/2023.10.27.23297675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background Both cognitive and non-cognitive (e.g., traits like curiosity) factors are critical for social and emotional functioning and independently predict educational attainment. These factors are heritable and genetically correlated with a range of health-relevant traits and behaviors in adulthood (e.g., risk-taking, psychopathology). However, whether these associations are present during adolescence, and to what extent these relationships diverge, could have implications for adolescent health and well-being. Methods Using data from 5,517 youth of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and outcomes related to cognition, socioeconomic status, risk tolerance and decision-making, substance initiation, psychopathology, and brain structure. Results Cognitive and non-cognitive PGSs were both positively associated with cognitive performance and family income, and negatively associated with ADHD and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk-taking, delayed discounting, and anorexia, as well as lower likelihood of nicotine initiation. The cognitive PGS was further associated with cognition scores and anorexia in within-sibling analyses, suggesting these results do not solely reflect the effects of assortative mating or passive gene-environment correlations. The cognitive PGS showed significantly stronger associations with cortical volumes than the non-cognitive PGS and was associated with right hemisphere caudal anterior cingulate and pars-orbitalis in within-sibling analyses, while the non-cognitive PGS showed stronger associations with white matter fractional anisotropy and a significant within-sibling association for right superior corticostriate-frontal cortex. Conclusions Our findings suggest that PGSs for cognitive and non-cognitive factors show similar associations with cognition and socioeconomic status as well as other psychosocial outcomes, but distinct associations with regional neural phenotypes in this adolescent sample.
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Affiliation(s)
- Aaron J Gorelik
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Sarah E Paul
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Alex P Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - David A A Baranger
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Shuyu Lin
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Wei Zhang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Nourhan M Elsayed
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Hailey Modi
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Pooja Addala
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Janine Bijsterbosch
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Deanna M Barch
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Nicole R Karcher
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Alexander S Hatoum
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Ryan Bogdan
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
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Lahtinen H, Korhonen K, Martikainen P, Morris T. Polygenic Prediction of Education and Its Role in the Intergenerational Transmission of Education: Cohort Changes Among Finnish Men and Women Born in 1925-1989. Demography 2023; 60:1523-1547. [PMID: 37728435 DOI: 10.1215/00703370-10963788] [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] [Indexed: 09/21/2023]
Abstract
Major changes in the educational distribution of the population and in institutions over the past century have affected the societal barriers to educational attainment. These changes can possibly result in stronger genetic associations. Using genetically informed, population-representative Finnish surveys linked to administrative registers, we investigated the polygenic associations and intergenerational transmission of education for those born between 1925 and 1989. First, we found that a polygenic index (PGI) designed to capture genetic predisposition to education strongly increased the predictiveness of educational attainment in pre-1950s cohorts, particularly among women. When decomposing the total contribution of PGI across different educational transitions, the transition between the basic and academic secondary tracks was the most important. This transition accounted for 60-80% of the total PGI-education association among most cohorts. The transition between academic secondary and higher tertiary levels increased its contribution across cohorts. Second, for cohorts born between 1955 and 1984, we observed that one eighth of the association between parental and one's own education is explained by the PGI. There was also an increase in the intergenerational correlation of education among these cohorts, which was partly explained by an increasing association between family education of origin and the PGI.
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Affiliation(s)
- Hannu Lahtinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Max Planck-University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
| | - Kaarina Korhonen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Max Planck-University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
| | - Pekka Martikainen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Max Planck Institute for Demographic Research, Rostock, Germany
- Max Planck-University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
| | - Tim Morris
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
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10
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Gu P, Pu B, Liu T, Yue D, Xin Q, Li HS, Yang BL, Ke DZ, Zheng XH, Zeng ZP, Zhang ZQ. Appraising causal risk and protective factors for rheumatoid arthritis. Bone Joint Res 2023; 12:601-614. [PMID: 37732818 PMCID: PMC10512867 DOI: 10.1302/2046-3758.129.bjr-2023-0118.r1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/22/2023] Open
Abstract
Aims Mendelian randomization (MR) is considered to overcome the bias of observational studies, but there is no current meta-analysis of MR studies on rheumatoid arthritis (RA). The purpose of this study was to summarize the relationship between potential pathogenic factors and RA risk based on existing MR studies. Methods PubMed, Web of Science, and Embase were searched for MR studies on influencing factors in relation to RA up to October 2022. Meta-analyses of MR studies assessing correlations between various potential pathogenic factors and RA were conducted. Random-effect and fixed-effect models were used to synthesize the odds ratios of various pathogenic factors and RA. The quality of the study was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines. Results A total of 517 potentially relevant articles were screened, 35 studies were included in the systematic review, and 19 studies were eligible to be included in the meta-analysis. Pooled estimates of 19 included studies (causality between 15 different risk factors and RA) revealed that obesity, smoking, coffee intake, lower education attainment, and Graves' disease (GD) were related to the increased risk of RA. In contrast, the causality contribution from serum mineral levels (calcium, iron, copper, zinc, magnesium, selenium), alcohol intake, and chronic periodontitis to RA is not significant. Conclusion Obesity, smoking, education attainment, and GD have real causal effects on the occurrence and development of RA. These results may provide insights into the genetic susceptibility and potential biological pathways of RA.
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Affiliation(s)
- Peng Gu
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Bin Pu
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Teng Liu
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Dan Yue
- Southwest Medical University, Luzhou, China
| | - Qiao Xin
- Jiangxi University of Chinese Medicine, Nanchang, China
| | - Hai-Shan Li
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Bai-Lin Yang
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Dao-Ze Ke
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiao-Hui Zheng
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhan-Peng Zeng
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China
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11
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Byrne B, Olson RK. Addressing genetic essentialism: Sharpening context in behavior genetics. Behav Brain Sci 2023; 46:e187. [PMID: 37694902 DOI: 10.1017/s0140525x22002266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Evidence of a causal role for genes in human behavior underpins genetic essentialism, the scientifically flawed and socially hazardous idea that heritable characteristics are immutable. Behavior geneticists can challenge this idea by designing research that brings the contextual dependence of heritability estimates into sharper focus, and by incorporating a relevant statement into research reports and public outreach.
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Affiliation(s)
- Brian Byrne
- University of New England, Armidale, NSW, Australia www.une.edu.au/staff-profiles/hass/bbyrne
| | - Richard K Olson
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA /ibg/richard-k-olson
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12
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Wolfram T, Morris D. Conventional twin studies overestimate the environmental differences between families relevant to educational attainment. NPJ SCIENCE OF LEARNING 2023; 8:24. [PMID: 37460608 PMCID: PMC10352382 DOI: 10.1038/s41539-023-00173-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 07/04/2023] [Indexed: 07/20/2023]
Abstract
Estimates of shared environmental influence on educational attainment (EA) using the Classical Twin Design (CTD) have been enlisted as genetically sensitive measures of unequal opportunity. However, key assumptions of the CTD appear violated for EA. In this study we compared CTD estimates of shared environmental influence on EA with estimates from a Nuclear Twin and Family Design (NTFD) in the same 982 German families. Our CTD model estimated shared environmental influence at 43%. After accounting for assortative mating, our best fitting NTFD model estimated shared environmental influence at 26%, disaggregating this into twin-specific shared environments (16%) and environmental influences shared by all siblings (10%). Only the sibling shared environment captures environmental influences that reliably differ between families, suggesting the CTD substantially overestimates between-family differences in educational opportunity. Moreover, parental education was found to have no environmental effect on offspring education once genetic influences were accounted for.
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Affiliation(s)
- Tobias Wolfram
- Department of Sociology, University of Bielefeld, Niedersachen, Germany.
- Department of Sociology, ENSAE/CREST, Paris, France.
| | - Damien Morris
- Social, Genetic & Developmental Psychiatry Centre, King's College London, London, United Kingdom
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13
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Wang M. Estimating the parental age effect on intelligence with controlling for confounding effects from genotypic differences. PERSONALITY AND INDIVIDUAL DIFFERENCES 2023. [DOI: 10.1016/j.paid.2023.112137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
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14
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Harden KP. Genetic determinism, essentialism and reductionism: semantic clarity for contested science. Nat Rev Genet 2023; 24:197-204. [PMID: 36316396 DOI: 10.1038/s41576-022-00537-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/20/2022] [Indexed: 02/19/2023]
Abstract
Research linking genetic differences with human social and behavioural phenotypes has long been controversial. Frequently, debates about the ethical, social and legal implications of this area of research centre on questions about whether studies overtly or covertly perpetuate genetic determinism, genetic essentialism and/or genetic reductionism. Given the prominent role of the '-isms' in scientific discourse and criticism, it is important for there to be consensus and clarity about the meaning of these terms. Here, the author integrates scholarship from psychology, genetics and philosophy of science to provide accessible definitions of genetic determinism, genetic reductionism and genetic essentialism. The author provides linguistic and visual examples of determinism, reductionism and essentialism in science and popular culture, discusses common misconceptions and concludes with recommendations for science communication.
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Affiliation(s)
- K Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, TX, USA.
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15
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Arpawong TE, Gatz M, Zavala C, Gruenewald TL, Walters EE, Prescott CA. Nature, Nurture, and the Meaning of Educational Attainment: Differences by Sex and Socioeconomic Status. Twin Res Hum Genet 2023; 26:1-9. [PMID: 36912114 PMCID: PMC10497722 DOI: 10.1017/thg.2023.6] [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] [Indexed: 03/14/2023]
Abstract
Estimated heritability of educational attainment (EA) varies widely, from 23% to 80%, with growing evidence suggesting the degree to which genetic variation contributes to individual differences in EA is highly dependent upon situational factors. We aimed to decompose EA into influences attributable to genetic propensity and to environmental context and their interplay, while considering influences of rearing household economic status (HES) and sex. We use the Project Talent Twin and Sibling Study, drawn from the population-representative cohort of high school students assessed in 1960 and followed through 2014, to ages 68-72. Data from 3552 twins and siblings from 1741 families were analyzed using multilevel regression and multiple group structural equation models. Individuals from less-advantaged backgrounds had lower EA and less variation. Genetic variance accounted for 51% of the total variance, but within women and men, 40% and 58% of the total variance respectively. Men had stable genetic variance on EA across all HES strata, whereas high HES women showed the same level of genetic influence as men, and lower HES women had constrained genetic influence on EA. Unexpectedly, middle HES women showed the largest constraints in genetic influence on EA. Shared family environment appears to make an outsized contribution to greater variability for women in this middle stratum and whether they pursue more EA. Implications are that without considering early life opportunity, genetic studies on education may mischaracterize sex differences because education reflects different degrees of genetic and environmental influences for women and men.
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Affiliation(s)
- Thalida Em Arpawong
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
| | - Margaret Gatz
- Department of Psychology, Dornsife School of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Center for Economic and Social Research, Dornsife School of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Catalina Zavala
- Department of Psychology, Dornsife School of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | | | - Ellen E. Walters
- Center for Economic and Social Research, Dornsife School of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Carol A. Prescott
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
- Department of Psychology, Dornsife School of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
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16
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Evolving the blank slate. Behav Brain Sci 2022; 45:e155. [PMID: 36098399 DOI: 10.1017/s0140525x21001680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
We support Uchiyama et al. in the value of genetics, sample diversification, and context measurement. Against the example of vitamins, we highlight the intransigence of many phenotypes. We caution that while culture can mask genetic differences, the dependence of behaviour on genetics is reinvented and unmasked by novel challenges across generations.
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Vellani V, Garrett N, Gaule A, Patil KR, Sharot T. Quantifying the heritability of belief formation. Sci Rep 2022; 12:11833. [PMID: 35821231 PMCID: PMC9276818 DOI: 10.1038/s41598-022-15492-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 06/24/2022] [Indexed: 11/09/2022] Open
Abstract
Individual differences in behaviour, traits and mental-health are partially heritable. Traditionally, studies have focused on quantifying the heritability of high-order characteristics, such as happiness or education attainment. Here, we quantify the degree of heritability of lower-level mental processes that likely contribute to complex traits and behaviour. In particular, we quantify the degree of heritability of cognitive and affective factors that contribute to the generation of beliefs about risk, which drive behavior in domains ranging from finance to health. Monozygotic and dizygotic twin pairs completed a belief formation task. We first show that beliefs about risk are associated with vividness of imagination, affective evaluation and learning abilities. We then demonstrate that the genetic contribution to individual differences in these processes range between 13.5 and 39%, with affect evaluation showing a particular robust heritability component. These results provide clues to which mental factors may be driving the heritability component of beliefs formation, which in turn contribute to the heritability of complex traits.
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Affiliation(s)
- Valentina Vellani
- Affective Brain Lab, Department of Experimental Psychology, University College London, London, WC1H 0AP, UK.
- The Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, WC1B 5EH, UK.
| | - Neil Garrett
- School of Psychology, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
| | - Anne Gaule
- Developmental Risk and Resilience Unit, Department of Experimental Psychology, University College London, London, WC1H 0AP, UK
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine (INM-7), Forschungszentrum Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Tali Sharot
- Affective Brain Lab, Department of Experimental Psychology, University College London, London, WC1H 0AP, UK.
- The Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, WC1B 5EH, UK.
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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18
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Social and genetic associations with educational performance in a Scandinavian welfare state. Proc Natl Acad Sci U S A 2022; 119:e2201869119. [PMID: 35709318 DOI: 10.1073/pnas.2201869119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Recent research has suggested that across Western developed societies, the influence of genetics on educational outcomes is relatively constant. However, the degree to which family environment matters varies, such that countries with high levels of intergenerational mobility have weaker associations of family background. Research in this vein has relied on twin-based estimates, which involve variance decomposition, so direct assessment of the association of genes and environments is not possible. In the present study, we approach the question by directly measuring the impact of child genotype, parental genetic nurture, and parental realized education on educational achievement in primary and secondary school. We deploy data from a social democratic context (Norway) and contrast our findings with those derived from more liberal welfare state contexts. Results point to genetics only confounding the relationship between parent status and offspring achievement to a small degree. Genetic nurture associations are similar to those in other societies. We find no, or very small, gene-environment interactions and parent-child genotype interactions with respect to test scores. In sum, in a Scandinavian welfare state context, both genetic and environmental associations are of similar magnitude as in societies with less-robust efforts to mitigate the influence of family background.
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Knigge A, Maas I, Stienstra K, de Zeeuw EL, Boomsma DI. Delayed tracking and inequality of opportunity: Gene-environment interactions in educational attainment. NPJ SCIENCE OF LEARNING 2022; 7:6. [PMID: 35508471 PMCID: PMC9068802 DOI: 10.1038/s41539-022-00122-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 03/18/2022] [Indexed: 06/14/2023]
Abstract
There are concerns that ability tracking at a young age increases unequal opportunities for children of different socioeconomic background to develop their potential. To disentangle family influence and potential ability, we applied moderation models to twin data on secondary educational track level from the Netherlands Twin Register (N = 8847). Delaying tracking to a later age is associated with a lower shared environmental influence and a larger genetic influence on track level in adolescence. This is in line with the idea that delaying tracking improves equality of opportunity. Our results further suggest that this is mostly because delaying tracking reduces the indirect influence of family background on track level via the test performance of students. Importantly, delaying tracking improves the realization of genetic potential especially among students with low test scores, while it lowers shared environmental influence on track level for students of all test performance levels.
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Affiliation(s)
- Antonie Knigge
- Department of Sociology/ICS, Utrecht University, Utrecht, The Netherlands.
| | - Ineke Maas
- Department of Sociology/ICS, Utrecht University, Utrecht, The Netherlands
- Department of Sociology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Kim Stienstra
- Department of Sociology/ICS, Utrecht University, Utrecht, The Netherlands
| | - Eveline L de Zeeuw
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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20
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21
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Ujma PP, Eszlári N, Millinghoffer A, Bruncsics B, Török D, Petschner P, Antal P, Deakin B, Breen G, Bagdy G, Juhász G. Genetic effects on educational attainment in Hungary. Brain Behav 2022; 12:e2430. [PMID: 34843176 PMCID: PMC8785634 DOI: 10.1002/brb3.2430] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 06/08/2021] [Accepted: 10/25/2021] [Indexed: 01/12/2023] Open
Abstract
INTRODUCTION Educational attainment is a substantially heritable trait, and it has recently been linked to specific genetic variants by genome-wide association studies (GWASs). However, the effects of such genetic variants are expected to vary across environments, including countries and historical eras. METHODS We used polygenic scores (PGSs) to assess molecular genetic effects on educational attainment in Hungary, a country in the Central Eastern European region where behavioral genetic studies are in general scarce and molecular genetic studies of educational attainment have not been previously published. RESULTS We found that the PGS is significantly associated with the attainment of a college degree as well as the number of years in education in a sample of Hungarian study participants (N = 829). PGS effect sizes were not significantly different when compared to an English (N = 976) comparison sample with identical measurement protocols. In line with previous Estonian findings, we found higher PGS effect sizes in Hungarian, but not in English participants who attended higher education after the fall of Communism, although we lacked statistical power for this effect to reach significance. DISCUSSION Our results provide evidence that polygenic scores for educational attainment have predictive value in culturally diverse European populations.
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Affiliation(s)
- Péter P Ujma
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary.,National Institute of Clinical Neuroscience, Budapest, Hungary
| | - Nóra Eszlári
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary.,NAP-2-SE New Antidepressant Target Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary
| | - András Millinghoffer
- NAP-2-SE New Antidepressant Target Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary.,Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary
| | - Bence Bruncsics
- Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary
| | - Dóra Török
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary
| | - Péter Petschner
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary.,MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary
| | - Péter Antal
- Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary
| | - Bill Deakin
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Manchester Academic Health Sciences Centre, Manchester, UK.,Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - György Bagdy
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary.,NAP-2-SE New Antidepressant Target Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary.,MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary
| | - Gabriella Juhász
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary.,SE-NAP 2 Genetic Brain Imaging Migraine Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary
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22
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Huang G, Cai J, Li W, Zhong Y, Liao W, Wu P. Causal relationship between educational attainment and the risk of rheumatoid arthritis: a Mendelian randomization study. BMC Rheumatol 2021; 5:47. [PMID: 34670623 PMCID: PMC8529827 DOI: 10.1186/s41927-021-00216-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 07/03/2021] [Indexed: 11/10/2022] Open
Abstract
Background Educational attainment is moderately heritable and inversely associated with the risk of rheumatoid arthritis. However, the causality from educational attainment on rheumatoid arthritis remained unknown. Here, we aimed to determine whether educational attainment is causally associated with rheumatoid arthritis (RA) by using Mendelian randomization (MR) approach. Methods Summary statistics data for RA were obtained from an available, published meta-analysis of genome-wide association studies (GWAS) that included 14,361 RA cases and 43,923 controls of European ancestry. The instrumental variables for educational attainment were obtained from a GWAS meta-analysis that included over 1 million individuals (N = 1,131,881) of European ancestry. MR analyses were mainly performed using the inverse-variance weighted (IVW) method. Sensitivity analyses were further performed to test the robustness of the association using the weighted median method, MR-Egger, Cochran Q test, “leave-one-out” analysis and MR-PRESSO test. Results A total of 387 SNPs were employed as instrumental variables in our MR analysis. Genetically predicted higher educational attainment was associated with a significantly lower risk of RA using the IVW method (odds ratio [OR] = 0.42, 95% confidence interval [CI]: 0.34–0.52; p = 1.78 × 10− 14). The weighted median method and MR Egger regression analysis yielded consistent results. The effect estimate remained robust after the outlier variants and SNPs (associated with the confounding factors) were excluded. “Leave-one-out” analysis confirmed the stability of our results. Additionally, the results suggested the absence of the horizontal pleiotropy. Conclusions The MR analysis supported a potential inverse causative relationship between educational attainment and the risk of RA. Supplementary Information The online version contains supplementary material available at 10.1186/s41927-021-00216-0.
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Affiliation(s)
- Guiwu Huang
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China
| | - Jiahao Cai
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Wenchang Li
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China
| | - Yanlin Zhong
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China
| | - Weiming Liao
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China
| | - Peihui Wu
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
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Abstract
Behavioral genetics and cultural evolution have both revolutionized our understanding of human behavior-largely independent of each other. Here we reconcile these two fields under a dual inheritance framework, offering a more nuanced understanding of the interaction between genes and culture. Going beyond typical analyses of gene-environment interactions, we describe the cultural dynamics that shape these interactions by shaping the environment and population structure. A cultural evolutionary approach can explain, for example, how factors such as rates of innovation and diffusion, density of cultural sub-groups, and tolerance for behavioral diversity impact heritability estimates, thus yielding predictions for different social contexts. Moreover, when cumulative culture functionally overlaps with genes, genetic effects become masked, unmasked, or even reversed, and the causal effects of an identified gene become confounded with features of the cultural environment. The manner of confounding is specific to a particular society at a particular time, but a WEIRD (Western, educated, industrialized, rich, democratic) sampling problem obscures this boundedness. Cultural evolutionary dynamics are typically missing from models of gene-to-phenotype causality, hindering generalizability of genetic effects across societies and across time. We lay out a reconciled framework and use it to predict the ways in which heritability should differ between societies, between socioeconomic levels and other groupings within some societies but not others, and over the life course. An integrated cultural evolutionary behavioral genetic approach cuts through the nature-nurture debate and helps resolve controversies in topics such as IQ.
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24
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Raffington L, Mallard T, Harden KP. Polygenic Scores in Developmental Psychology: Invite Genetics In, Leave Biodeterminism Behind. ANNUAL REVIEW OF DEVELOPMENTAL PSYCHOLOGY 2020; 2:389-411. [PMID: 38249435 PMCID: PMC10798791 DOI: 10.1146/annurev-devpsych-051820-123945] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
Abstract
Polygenic scores offer developmental psychologists new methods for integrating genetic information into research on how people change and develop across the life span. Indeed, polygenic scores have correlations with developmental outcomes that rival correlations with traditional developmental psychology variables, such as family income. Yet linking people's genetics with differences between them in socially valued developmental outcomes, such as educational attainment, has historically been used to justify acts of state-sponsored violence. In this review, we emphasize that an interdisciplinary understanding of the environmental and structural determinants of social inequality, in conjunction with a transactional developmental perspective on how people interact with their environments, is critical to interpreting associations between polygenic measures and phenotypes. While there is a risk of misuse, early applications of polygenic scores to developmental psychology have already provided novel findings that identify environmental mechanisms of life course processes that can be used to diagnose inequalities in social opportunity.
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Affiliation(s)
- Laurel Raffington
- Department of Psychology, University of Texas, Austin, Texas 78712, USA
- Population Research Center, University of Texas, Austin, Texas 78712, USA
| | - Travis Mallard
- Department of Psychology, University of Texas, Austin, Texas 78712, USA
| | - K Paige Harden
- Department of Psychology, University of Texas, Austin, Texas 78712, USA
- Population Research Center, University of Texas, Austin, Texas 78712, USA
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25
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Engzell P, Tropf FC. Reply to Morris: Heritability of education remains associated with social mobility. Proc Natl Acad Sci U S A 2020; 117:28566-28567. [PMID: 33144510 PMCID: PMC7682564 DOI: 10.1073/pnas.2017308117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Affiliation(s)
- Per Engzell
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford OX1 1JD, United Kingdom;
- Nuffield College, University of Oxford, Oxford OX1 1NF, United Kingdom
- Swedish Institute for Social Research, Stockholm University, 106 91 Stockholm, Sweden
| | - Felix C Tropf
- Nuffield College, University of Oxford, Oxford OX1 1NF, United Kingdom
- Laboratoire de Sociologie Quantitative, École Nationale de la Statistique et de l'Administration Économique, 99120 Palaiseau, France
- Department of Sociology, Center for Research in Economics and Statistics, 99120 Palaiseau, France
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26
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Too early to declare a general law of social mobility and heritability for education. Proc Natl Acad Sci U S A 2020; 117:28564-28565. [PMID: 33144511 DOI: 10.1073/pnas.2011334117] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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27
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de Zwarte SMC, Brouwer RM, Agartz I, Alda M, Alonso‐Lana S, Bearden CE, Bertolino A, Bonvino A, Bramon E, Buimer EEL, Cahn W, Canales‐Rodríguez EJ, Cannon DM, Cannon TD, Caseras X, Castro‐Fornieles J, Chen Q, Chung Y, De la Serna E, del Mar Bonnin C, Demro C, Di Giorgio A, Doucet GE, Eker MC, Erk S, Fatjó‐Vilas M, Fears SC, Foley SF, Frangou S, Fullerton JM, Glahn DC, Goghari VM, Goikolea JM, Goldman AL, Gonul AS, Gruber O, Hajek T, Hawkins EL, Heinz A, Hidiroglu Ongun C, Hillegers MHJ, Houenou J, Hulshoff Pol HE, Hultman CM, Ingvar M, Johansson V, Jönsson EG, Kane F, Kempton MJ, Koenis MMG, Kopecek M, Krämer B, Lawrie SM, Lenroot RK, Marcelis M, Mattay VS, McDonald C, Meyer‐Lindenberg A, Michielse S, Mitchell PB, Moreno D, Murray RM, Mwangi B, Nabulsi L, Newport J, Olman CA, van Os J, Overs BJ, Ozerdem A, Pergola G, Picchioni MM, Piguet C, Pomarol‐Clotet E, Radua J, Ramsay IS, Richter A, Roberts G, Salvador R, Saricicek Aydogan A, Sarró S, Schofield PR, Simsek EM, Simsek F, Soares JC, Sponheim SR, Sugranyes G, Toulopoulou T, Tronchin G, Vieta E, Walter H, Weinberger DR, Whalley HC, Wu M, Yalin N, Andreassen OA, Ching CRK, Thomopoulos SI, van Erp TGM, Jahanshad N, Thompson PM, Kahn RS, van Haren NEM. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder. Hum Brain Mapp 2020; 43:414-430. [PMID: 33027543 PMCID: PMC8675411 DOI: 10.1002/hbm.25206] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 08/28/2020] [Accepted: 09/03/2020] [Indexed: 12/25/2022] Open
Abstract
First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.
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Affiliation(s)
- Sonja M. C. de Zwarte
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Rachel M. Brouwer
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,Department of PsychiatryDiakonhjemmet HospitalOsloNorway
| | - Martin Alda
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada,National Institute of Mental HealthKlecanyCzech Republic
| | - Silvia Alonso‐Lana
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Carrie E. Bearden
- Semel Institute for Neuroscience and Human Behavior, University of CaliforniaCaliforniaLos AngelesUSA,Department of PsychologyUniversity of CaliforniaCaliforniaLos AngelesUSA
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Aurora Bonvino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Elvira Bramon
- Division of Psychiatry, Neuroscience in Mental Health Research DepartmentUniversity College LondonLondonUK
| | - Elizabeth E. L. Buimer
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Wiepke Cahn
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Erick J. Canales‐Rodríguez
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Dara M. Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Tyrone D. Cannon
- Department of PsychologyYale UniversityNew HavenConnecticutUSA,Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUK
| | - Josefina Castro‐Fornieles
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA
| | - Yoonho Chung
- Department of PsychologyYale UniversityNew HavenConnecticutUSA
| | - Elena De la Serna
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Caterina del Mar Bonnin
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Caroline Demro
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | | | - Gaelle E. Doucet
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA,Boys Town National Research HospitalOmahaNEUSA
| | - Mehmet Cagdas Eker
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey
| | - Susanne Erk
- Research Division of Mind and Brain, Department of Psychiatry and PsychotherapyCharité Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of HealthBerlinGermany
| | - Mar Fatjó‐Vilas
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Scott C. Fears
- Department of Psychiatry and Biobehavioral ScienceUniversity of CaliforniaLos AngelesCaliforniaUSA,Center for Neurobehavioral GeneticsUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Sonya F. Foley
- Cardiff University Brain Research Imaging Centre, Cardiff UniversityCardiffUK
| | - Sophia Frangou
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Janice M. Fullerton
- Neuroscience Research AustraliaSydneyAustralia,School of Medical Sciences, University of New South WalesSydneyAustralia
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA,Tommy Fuss Center for Neuropsychiatric Disease ResearchBoston Children's HospitalBostonMassachusettsUSA,Harvard Medical SchoolBostonMassachusettsUSA
| | - Vina M. Goghari
- Department of Psychology and Graduate Department of Psychological Clinical ScienceUniversity of TorontoTorontoOntarioCanada
| | - Jose M. Goikolea
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Aaron L. Goldman
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA
| | - Ali Saffet Gonul
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey,Department of Psychiatry and Behavioral SciencesMercer University School of MedicineMaconGeorgiaUSA
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Tomas Hajek
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada,National Institute of Mental HealthKlecanyCzech Republic
| | - Emma L. Hawkins
- Division of PsychiatryRoyal Edinburgh Hospital, University of EdinburghEdinburghUK
| | - Andreas Heinz
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey
| | | | - Manon H. J. Hillegers
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center‐Sophia Children's HospitalRotterdamNetherlands
| | - Josselin Houenou
- APHP, Mondor University HospitalsCréteilFrance,INSERM U955 Team 15 "Translational Psychiatry"CréteilFrance,NeuroSpin neuroimaging platform, Psychiatry Team, UNIACT Lab, CEA SaclayGif‐Sur‐YvetteFrance
| | - Hilleke E. Hulshoff Pol
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Christina M. Hultman
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Martin Ingvar
- Section for Neuroscience, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden,Department of NeuroradiologyKarolinska University HospitalStockholmSweden
| | - Viktoria Johansson
- Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden
| | - Fergus Kane
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Matthew J. Kempton
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Marinka M. G. Koenis
- Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA,Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA
| | - Miloslav Kopecek
- National Institute of Mental HealthKlecanyCzech Republic,Department of Psychiatry, Third Faculty of MedicineCharles UniversityPragueCzech Republic
| | - Bernd Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Stephen M. Lawrie
- Division of PsychiatryRoyal Edinburgh Hospital, University of EdinburghEdinburghUK
| | - Rhoshel K. Lenroot
- Neuroscience Research AustraliaSydneyAustralia,School of Psychiatry, University of New South WalesSydneyAustralia,Department of Psychiatry and Behavioral SciencesUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Machteld Marcelis
- Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | - Venkata S. Mattay
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA,Departments of Neurology and RadiologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Andreas Meyer‐Lindenberg
- Department of Psychiatry and PsychotherapyCentral Institute of Mental Health, Medical Faculty Mannheim, University of HeidelbergMannheimGermany
| | - Stijn Michielse
- Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | | | - Dolores Moreno
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Child and Adolescent Psychiatry DepartmentHospital General Universitario Gregorio Marañón (IiSGM), School of Medicine, Universidad ComplutenseMadridSpain
| | - Robin M. Murray
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Benson Mwangi
- Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Leila Nabulsi
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Jason Newport
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada
| | - Cheryl A. Olman
- Department of Psychology and Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Jim van Os
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | | | - Aysegul Ozerdem
- Department of Psychiatry, Faculty of MedicineDokuz Eylül UniversityIzmirTurkey,Department of NeurosciencesHealth Sciences Institute, Dokuz Eylül UniversityIzmirTurkey,Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Marco M. Picchioni
- Department of Forensic and Neurodevelopmental ScienceInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Camille Piguet
- INSERM U955 Team 15 "Translational Psychiatry"CréteilFrance,NeuroSpin neuroimaging platform, Psychiatry Team, UNIACT Lab, CEA SaclayGif‐Sur‐YvetteFrance,Department of Psychiatry, Faculty of MedicineUniversity of GenevaGenevaSwitzerland,School of Medicine, Universitat Internacional de CatalunyaBarcelonaSpain
| | - Edith Pomarol‐Clotet
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Joaquim Radua
- Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Early Psychosis: Interventions and Clinical‐detection (EPIC) lab, Department of Psychosis StudiesInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUK
| | - Ian S. Ramsay
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Anja Richter
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Gloria Roberts
- School of Psychiatry, University of New South WalesSydneyAustralia
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Aybala Saricicek Aydogan
- Department of NeurosciencesHealth Sciences Institute, Dokuz Eylül UniversityIzmirTurkey,Department of Psychiatry, Faculty of MedicineIzmir Katip Çelebi UniversityIzmirTurkey
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Peter R. Schofield
- School of Medical Sciences, University of New South WalesSydneyAustralia,Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA
| | | | - Fatma Simsek
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey,Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK,Cigli State HospitalDepartment of PsychiatryIzmirTurkey
| | - Jair C. Soares
- Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Scott R. Sponheim
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA,Minneapolis VA Health Care SystemMinneapolisMinnesotaUSA
| | - Gisela Sugranyes
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Timothea Toulopoulou
- Department of PsychologyBilkent UniversityAnkaraTurkey,Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Giulia Tronchin
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Eduard Vieta
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Henrik Walter
- Research Division of Mind and Brain, Department of Psychiatry and PsychotherapyCharité Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of HealthBerlinGermany
| | - Daniel R. Weinberger
- Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Heather C. Whalley
- Department of Psychology, Faculty of ArtsDokuz Eylül UniversityİzmirTurkey
| | - Mon‐Ju Wu
- Department of Psychology and Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Nefize Yalin
- Centre for Affective Disorders, Department of Psychological MedicineInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA,Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - René S. Kahn
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Neeltje E. M. van Haren
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center‐Sophia Children's HospitalRotterdamNetherlands
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28
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Lövdén M, Fratiglioni L, Glymour MM, Lindenberger U, Tucker-Drob EM. Education and Cognitive Functioning Across the Life Span. Psychol Sci Public Interest 2020; 21:6-41. [PMID: 32772803 PMCID: PMC7425377 DOI: 10.1177/1529100620920576] [Citation(s) in RCA: 418] [Impact Index Per Article: 104.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Cognitive abilities are important predictors of educational and occupational performance, socioeconomic attainment, health, and longevity. Declines in cognitive abilities are linked to impairments in older adults' everyday functions, but people differ from one another in their rates of cognitive decline over the course of adulthood and old age. Hence, identifying factors that protect against compromised late-life cognition is of great societal interest. The number of years of formal education completed by individuals is positively correlated with their cognitive function throughout adulthood and predicts lower risk of dementia late in life. These observations have led to the propositions that prolonging education might (a) affect cognitive ability and (b) attenuate aging-associated declines in cognition. We evaluate these propositions by reviewing the literature on educational attainment and cognitive aging, including recent analyses of data harmonized across multiple longitudinal cohort studies and related meta-analyses. In line with the first proposition, the evidence indicates that educational attainment has positive effects on cognitive function. We also find evidence that cognitive abilities are associated with selection into longer durations of education and that there are common factors (e.g., parental socioeconomic resources) that affect both educational attainment and cognitive development. There is likely reciprocal interplay among these factors, and among cognitive abilities, during development. Education-cognitive ability associations are apparent across the entire adult life span and across the full range of education levels, including (to some degree) tertiary education. However, contrary to the second proposition, we find that associations between education and aging-associated cognitive declines are negligible and that a threshold model of dementia can account for the association between educational attainment and late-life dementia risk. We conclude that educational attainment exerts its influences on late-life cognitive function primarily by contributing to individual differences in cognitive skills that emerge in early adulthood but persist into older age. We also note that the widespread absence of educational influences on rates of cognitive decline puts constraints on theoretical notions of cognitive aging, such as the concepts of cognitive reserve and brain maintenance. Improving the conditions that shape development during the first decades of life carries great potential for improving cognitive ability in early adulthood and for reducing public-health burdens related to cognitive aging and dementia.
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Affiliation(s)
- Martin Lövdén
- Aging Research Center, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden
| | - Laura Fratiglioni
- Aging Research Center, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Stockholm Gerontology Research Center, Stockholm, Sweden
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, United Kingdom
| | - Elliot M. Tucker-Drob
- Department of Psychology and Population Research Center, University of Texas at Austin
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29
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Silventoinen K, Jelenkovic A, Sund R, Latvala A, Honda C, Inui F, Tomizawa R, Watanabe M, Sakai N, Rebato E, Busjahn A, Tyler J, Hopper JL, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Calais-Ferreira L, Oliveira VC, Ferreira PH, Medda E, Nisticò L, Toccaceli V, Derom CA, Vlietinck RF, Loos RJF, Siribaddana SH, Hotopf M, Sumathipala A, Rijsdijk F, Duncan GE, Buchwald D, Tynelius P, Rasmussen F, Tan Q, Zhang D, Pang Z, Magnusson PKE, Pedersen NL, Dahl Aslan AK, Hwang AE, Mack TM, Krueger RF, McGue M, Pahlen S, Brandt I, Nilsen TS, Harris JR, Martin NG, Medland SE, Montgomery GW, Willemsen G, Bartels M, van Beijsterveldt CEM, Franz CE, Kremen WS, Lyons MJ, Silberg JL, Maes HH, Kandler C, Nelson TL, Whitfield KE, Corley RP, Huibregtse BM, Gatz M, Butler DA, Tarnoki AD, Tarnoki DL, Park HA, Lee J, Lee SJ, Sung J, Yokoyama Y, Sørensen TIA, Boomsma DI, Kaprio J. Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts. Sci Rep 2020; 10:12681. [PMID: 32728164 PMCID: PMC7391756 DOI: 10.1038/s41598-020-69526-6] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 07/10/2020] [Indexed: 01/07/2023] Open
Abstract
We investigated the heritability of educational attainment and how it differed between birth cohorts and cultural-geographic regions. A classical twin design was applied to pooled data from 28 cohorts representing 16 countries and including 193,518 twins with information on educational attainment at 25 years of age or older. Genetic factors explained the major part of individual differences in educational attainment (heritability: a2 = 0.43; 0.41-0.44), but also environmental variation shared by co-twins was substantial (c2 = 0.31; 0.30-0.33). The proportions of educational variation explained by genetic and shared environmental factors did not differ between Europe, North America and Australia, and East Asia. When restricted to twins 30 years or older to confirm finalized education, the heritability was higher in the older cohorts born in 1900-1949 (a2 = 0.44; 0.41-0.46) than in the later cohorts born in 1950-1989 (a2 = 0.38; 0.36-0.40), with a corresponding lower influence of common environmental factors (c2 = 0.31; 0.29-0.33 and c2 = 0.34; 0.32-0.36, respectively). In conclusion, both genetic and environmental factors shared by co-twins have an important influence on individual differences in educational attainment. The effect of genetic factors on educational attainment has decreased from the cohorts born before to those born after the 1950s.
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Affiliation(s)
- Karri Silventoinen
- Department of Social Research, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014, Helsinki, Finland.
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan.
| | - Aline Jelenkovic
- Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country, Leioa, Spain
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Reijo Sund
- Department of Social Research, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014, Helsinki, Finland
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Antti Latvala
- Department of Social Research, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014, Helsinki, Finland
| | - Chika Honda
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Fujio Inui
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
- Faculty of Health Science, Kio University, Nara, Japan
| | - Rie Tomizawa
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Mikio Watanabe
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Norio Sakai
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Esther Rebato
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | | | - Jessica Tyler
- Twins Research Australia, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, VIC, Australia
| | - John L Hopper
- Twins Research Australia, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, VIC, Australia
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Juan R Ordoñana
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain
- IMIB-Arrixaca, Murcia, Spain
| | - Juan F Sánchez-Romera
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain
- IMIB-Arrixaca, Murcia, Spain
| | - Lucia Colodro-Conde
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Lucas Calais-Ferreira
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Vinicius C Oliveira
- Pós-Graduação em Reabilitação e Desempenho Funcional, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, Brazil
| | - Paulo H Ferreira
- Musculoskeletal Health Research Group, Faculty of Health Sciences, The University of Sydney, Sydney, Australia
| | - Emanuela Medda
- Istituto Superiore di Sanità - Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Lorenza Nisticò
- Istituto Superiore di Sanità - Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Virgilia Toccaceli
- Istituto Superiore di Sanità - Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Catherine A Derom
- Centre of Human Genetics, University Hospitals Leuven, Leuven, Belgium
- Department of Obstetrics and Gynaecology, Ghent University Hospitals, Ghent, Belgium
| | | | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, Icahn School of Medicine At Mount Sinai, New York, NY, USA
| | - Sisira H Siribaddana
- Institute of Research and Development, Battaramulla, Sri Lanka
- Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka Saliyapura, Anuradhapura, Sri Lanka
| | - Matthew Hotopf
- Institute of Psychiatry Psychology and Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Athula Sumathipala
- Institute of Research and Development, Battaramulla, Sri Lanka
- Research Institute for Primary Care and Health Sciences, School for Primary Care Research (SPCR), Faculty of Health, Keele University, Staffordshire, UK
| | - Fruhling Rijsdijk
- Social Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Glen E Duncan
- Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Dedra Buchwald
- Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Per Tynelius
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Finn Rasmussen
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Qihua Tan
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Department of Public Health, Qingdao University Medical College, Qingdao, China
| | - Zengchang Pang
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna K Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Amie E Hwang
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
- USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Thomas M Mack
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
- USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, Riverside, CA, 92521, USA
| | - Ingunn Brandt
- Division of Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Thomas S Nilsen
- Division of Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Jennifer R Harris
- Division of Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Nicholas G Martin
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Sarah E Medland
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Gonneke Willemsen
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, Amsterdam, The Netherlands
| | | | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, CA, USA
- VA San Diego Center of Excellence for Stress and Mental Health, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Judy L Silberg
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Hermine H Maes
- Department of Human and Molecular Genetics, Psychiatry and Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Tracy L Nelson
- Department of Health and Exercise Sciences and Colorado School of Public Health, Colorado State University, Fort Collins, USA
| | | | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA
| | | | - Margaret Gatz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - David A Butler
- Health and Medicine Division, The National Academies of Sciences, Engineering, and Medicine, Washington, DC, USA
| | - Adam D Tarnoki
- Medical Imaging Centre, Semmelweis University, Budapest, Hungary
- Hungarian Twin Registry, Budapest, Hungary
| | - David L Tarnoki
- Medical Imaging Centre, Semmelweis University, Budapest, Hungary
- Hungarian Twin Registry, Budapest, Hungary
| | - Hang A Park
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
- Department of Emergency Medicine, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea
| | - Jooyeon Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Soo Ji Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
- Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Joohon Sung
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
- Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Yoshie Yokoyama
- Department of Public Health Nursing, Osaka City University, Osaka, Japan
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Centre for Basic Metabolic Research (Section of Metabolic Genetics), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health (Section of Epidemiology), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
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Halpern-Manners A, Marahrens H, Neiderhiser JM, Natsuaki MN, Shaw DS, Reiss D, Leve LD. The Intergenerational Transmission of Early Educational Advantages: New Results Based on an Adoption Design. RESEARCH IN SOCIAL STRATIFICATION AND MOBILITY 2020; 67:100486. [PMID: 32724268 PMCID: PMC7386403 DOI: 10.1016/j.rssm.2020.100486] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Sociological research has traditionally emphasized the importance of post-birth factors (i.e., social, economic, and cultural capital) in the intergenerational transmission of educational advantages, to the neglect of potentially consequential pre-birth endowments (e.g., heritable traits) that are passed from parent to child. In this study, we leverage an experiment of nurture-children who were adopted at birth into nonrelative families-in an effort to simultaneously model the effects associated with both pathways. To do so, we fit a series of simple linear regression models that relate the academic achievement of adopted children to the educational attainments of their adoptive and biological parents, using U.S. data from a recent nationwide sample of birth and adoptive families (the Early Growth and Development Study). Because our dataset includes both "genetic" and "environmental" relatives, but not "genetic-and-environmental" relatives, the separate contributions of each pathway can be identified, as well as possible interactions between the two. Our results show that children's early achievements are influenced not only by the attainments of their adoptive parents, but also the attainments of their birth parents-suggesting the presence of environmental and genetically mediated effects. Supplementary analyses provide little evidence of effect moderation, using both distal and proximate measures of the childhood environment to model gene-by-environment interactions. These findings are robust to a variety of parameterizations, withstand a series of auxiliary checks, and remain intact even after controlling for intrauterine exposures and other measurable variables that could compromise our design. The implications of our results for theory and research in the stratification literature, and for those interested in educational mobility, are discussed.
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Affiliation(s)
| | | | | | | | | | - David Reiss
- Child Study Center, Yale School of Medicine, Yale University
| | - Leslie D. Leve
- Department of Counseling Psychology and Human Services, University of Oregon
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31
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Lin MJ. The social and genetic inheritance of educational attainment: Genes, parental education, and educational expansion. SOCIAL SCIENCE RESEARCH 2020; 86:102387. [PMID: 32056570 DOI: 10.1016/j.ssresearch.2019.102387] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Revised: 08/07/2019] [Accepted: 11/12/2019] [Indexed: 06/10/2023]
Abstract
Recently, several genome-wide association studies of educational attainment have found education-related genetic variants and enabled the integration of human inheritance into social research. This study incorporates the newest education polygenic score (Lee et al., 2018) into sociological research, and tests three gene-environment interaction hypotheses on status attainment. Using the Health and Retirement Study (N = 7599), I report three findings. First, a standard deviation increase in the education polygenic score is associated with a 58% increase in the likelihood of advancing to the next level of education, while a standard deviation increase in parental education results in a 53% increase. Second, supporting the Saunders hypothesis, the genetic effect becomes 11% smaller when parental education is one standard deviation higher, indicating that highly educated parents are more able to preserve their family's elite status in the next generation. Finally, the genetic effect is slightly greater for the younger cohort (1942-59) than the older cohort (1920-41). The findings strengthen the existing literature on the social influences in helping children achieve their innate talents.
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Affiliation(s)
- Meng-Jung Lin
- Department of Sociology, University of North Carolina at Chapel Hill, 155 Hamilton Hall CB 3210, Chapel Hill, NC 27599, USA.
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33
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Rimfeld K, Malanchini M, Hannigan LJ, Dale PS, Allen R, Hart S, Plomin R. Teacher assessments during compulsory education are as reliable, stable and heritable as standardized test scores. J Child Psychol Psychiatry 2019; 60:1278-1288. [PMID: 31079420 PMCID: PMC6848749 DOI: 10.1111/jcpp.13070] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/03/2019] [Indexed: 11/27/2022]
Abstract
BACKGROUND Children in the UK go through rigorous teacher assessments and standardized exams throughout compulsory (elementary and secondary) education, culminating with the GCSE exams (General Certificate of Secondary Education) at the age of 16 and A-level exams (Advanced Certificate of Secondary Education) at the age of 18. These exams are a major tipping point directing young individuals towards different lifelong trajectories. However, little is known about the associations between teacher assessments and exam performance or how well these two measurement approaches predict educational outcomes at the end of compulsory education and beyond. METHODS The current investigation used the UK-representative Twins Early Development Study (TEDS) sample of over 5,000 twin pairs studied longitudinally from childhood to young adulthood (age 7-18). We used teacher assessment and exam performance across development to investigate, using genetically sensitive designs, the associations between teacher assessment and standardized exam scores, as well as teacher assessments' prediction of exam scores at ages 16 and 18, and university enrolment. RESULTS Teacher assessments of achievement are as reliable, stable and heritable (~60%) as test scores at every stage of the educational experience. Teacher and test scores correlate strongly phenotypically (r ~ .70) and genetically (genetic correlation ~.80) both contemporaneously and over time. Earlier exam performance accounts for additional variance in standardized exam results (~10%) at age 16, when controlling for teacher assessments. However, exam performance explains less additional variance in later academic success, ~5% for exam grades at 18, and ~3% for university entry, when controlling for teacher assessments. Teacher assessments also predict additional variance in later exam performance and university enrolment, when controlling for previous exam scores. CONCLUSIONS Teachers can reliably and validly monitor students' progress, abilities and inclinations. High-stakes exams may shift educational experience away from learning towards exam performance. For these reasons, we suggest that teacher assessments could replace some, or all, high-stakes exams.
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Affiliation(s)
- Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London UK
| | - Margherita Malanchini
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London UK
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
| | - Laurie J. Hannigan
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London UK
| | - Philip S. Dale
- Department of Speech and Hearing Sciences, The University of New Mexico, Albuquerque, NM, USA
| | - Rebecca Allen
- Institute of Education, University College London, London, UK
| | - Sara Hart
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London UK
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34
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Liu H. Genetic architecture of socioeconomic outcomes: Educational attainment, occupational status, and wealth. SOCIAL SCIENCE RESEARCH 2019; 82:137-147. [PMID: 31300074 DOI: 10.1016/j.ssresearch.2019.04.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 03/19/2019] [Accepted: 04/18/2019] [Indexed: 06/10/2023]
Abstract
This study takes a socio-genomic approach to examine the complex relationships among three important socioeconomic outcomes: educational attainment, occupational status, and wealth. Using more than 8,000 genetic samples from the Health and Retirement study, it first estimates the collective influence of genetic variants across the whole human genome to each of the three socioeconomic outcomes. It then tests genetic correlations among three socioeconomic outcomes, and examines the extent to which genetic influences on occupational status and wealth are mediated by educational attainment. Analyses using the genomic-relatedness-matrix restricted maximum likelihood method show significant genetic correlations among the three outcomes, and provide evidence for both mediated and independent genetic influences. A polygenic score analysis demonstrates the utility of findings in socio-genomic studies to address genetic confounding in causal relationships among the three socioeconomic outcomes.
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Affiliation(s)
- Hexuan Liu
- School of Criminal Justice, The University of Cincinnati, USA; Institute for Interdisciplinary Data Science, The University of Cincinnati, USA.
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Karhula A, Erola J, Raab M, Fasang A. Destination as a process: Sibling similarity in early socioeconomic trajectories. ADVANCES IN LIFE COURSE RESEARCH 2019; 40:85-98. [PMID: 36694414 DOI: 10.1016/j.alcr.2019.04.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 04/01/2019] [Accepted: 04/04/2019] [Indexed: 06/17/2023]
Abstract
This paper proposes a process-oriented life course perspective on intergenerational mobility by comparing the early socioeconomic trajectories of siblings to those of unrelated persons. Based on rich Finnish register data (N = 21,744), the findings show that social origin affects not only final outcomes at given points in the life course but also longitudinal socioeconomic trajectories from ages 17-35 in early adulthood. We contribute to previous literature in three ways. First, we show that there is a pronounced similarity in the early socioeconomic trajectories of siblings. This similarity is stronger for same-sex siblings and stronger for brothers than for sisters. Second, we show that sibling similarity in full trajectories cannot be reduced to similarity in outcomes, i.e., siblings are not only more similar in the final outcomes that they obtain but also in the pathways that lead them to these outcomes. Third, our findings support that sibling similarity follows a U-shaped pattern by social class, i.e., similarity is especially strong in disadvantaged trajectories, weak among middle-class young adults, and increases again within the most advantaged trajectories. We conclude that measures of social mobility that concentrate on final outcomes are at risk of underestimating the association between social origin and destination because social inequalities are formed across the life course, not just at the end of specific life phases.
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Affiliation(s)
- Aleksi Karhula
- Department of Social Research, University of Turku, 20014, Finland; INVEST Research flagship Center, University of Turku, Finland.
| | - Jani Erola
- Department of Social Research, University of Turku, 20014, Finland; INVEST Research flagship Center, University of Turku, Finland
| | - Marcel Raab
- Department of Sociology, University of Mannheim, Germany
| | - Anette Fasang
- WZB Berlin Social Science Center, Humboldt-University Berlin, Germany
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36
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Roos JM, Nielsen F. Outrageous fortune or destiny? Family influences on status achievement in the early life course. SOCIAL SCIENCE RESEARCH 2019; 80:30-50. [PMID: 30955560 DOI: 10.1016/j.ssresearch.2018.12.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 06/19/2018] [Accepted: 12/07/2018] [Indexed: 06/09/2023]
Abstract
Psychologists using quantitative studies of the trait intelligence have established with much confidence that the impact of genes on intelligence increases with age, while the environmental effect of the family of origin declines. We examined the conjecture that a similar trend of increasing effect of genes/declining family environmental effect characterizes other status-related outcomes when arranged in typical age-graded sequence over adolescence and early adulthood. We used DeFries-Fulker (1985) (DF) analysis with longitudinal data on 1,576 pairs of variously-related young adult siblings (MZ twins; DZ twins; full siblings; half siblings; cousins; and nonrelated siblings; mean age 28) to estimate univariate quantitative genetic decompositions for fifteen status-related outcomes roughly ordered along the early life course: Verbal IQ, High school GPA, College plans, High school graduation, Some college, College graduation, Graduate school, Educational attainment, Occupational education, Occupational wages, Personal earnings, Household income, Household assets, Home ownership, and Subjective social status, with and without covariate controls for Age, Female gender, and Race/ethnicity (black, Hispanic, other; reference white). Results for successive outcomes did not support the conjecture of increasing heritability with maturity. Rather, the impacts of both the genes and the family environment tended to decline over the life course, resulting in a downward trend in family influences from all sources. There was some evidence of a recrudescence in relative influence of the family environment for outcomes related to the household that are often shared with a spouse, such as home ownership, suggesting a role of assortative mating in status reproduction. Other findings and limitations of the study are discussed.
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Affiliation(s)
- J Micah Roos
- Virginia Polytechnic Institute and State University, United States.
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37
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Rosenström T, Czajkowski NO, Ystrom E, Krueger RF, Aggen SH, Gillespie NA, Eilertsen E, Reichborn-Kjennerud T, Torvik FA. Genetically Informative Mediation Modeling Applied to Stressors and Personality-Disorder Traits in Etiology of Alcohol Use Disorder. Behav Genet 2018; 49:11-23. [PMID: 30536213 DOI: 10.1007/s10519-018-9941-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 11/27/2018] [Indexed: 01/10/2023]
Abstract
A statistical mediation model was developed within a twin design to investigate the etiology of alcohol use disorder (AUD). Unlike conventional statistical mediation models, this biometric mediation model can detect unobserved confounding. Using a sample of 1410 pairs of Norwegian twins, we investigated specific hypotheses that DSM-IV personality-disorder (PD) traits mediate effects of childhood stressful life events (SLEs) on AUD, and that adulthood SLEs mediate effects of PDs on AUD. Models including borderline PD traits indicated unobserved confounding in phenotypic path coefficients, whereas models including antisocial and impulsive traits did not. More than half of the observed effects of childhood SLEs on adulthood AUD were mediated by adulthood antisocial and impulsive traits. Effects of PD traits on AUD 5‒10 years later were direct rather than mediated by adulthood SLEs. The results and the general approach contribute to triangulation of developmental origins for complex behavioral disorders.
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Affiliation(s)
- Tom Rosenström
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway.
| | - Nikolai Olavi Czajkowski
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Eivind Ystrom
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- PharmacoEpidemiology and Drug Safety Research Group, School of Pharmacy, University of Oslo, Oslo, Norway
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, USA
| | - Steven H Aggen
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Nathan A Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Espen Eilertsen
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Fartein Ask Torvik
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
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38
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Zavala C, Beam CR, Finch BK, Gatz M, Johnson W, Kremen WS, Neiderhiser JM, Pedersen NL, Reynolds CA. Attained SES as a moderator of adult cognitive performance: Testing gene-environment interaction in various cognitive domains. Dev Psychol 2018; 54:2356-2370. [PMID: 30335430 PMCID: PMC6263814 DOI: 10.1037/dev0000576] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
We examined whether attained socioeconomic status (SES) moderated genetic and environmental sources of individual differences in cognitive performance using pooled data from 9 adult twin studies. Prior work concerning SES moderation of cognitive performance has focused on rearing SES. The current adult sample of 12,196 individuals (aged 27-98 years) allowed for the examination of common sources of individual differences between attained SES and cognitive performance (signaling potential gene-environment correlation mechanisms, rGE), as well as sources of individual differences unique to cognitive performance (signaling potential gene-environment interaction mechanisms, G × E). Attained SES moderated sources of individual differences in 4 cognitive domains, assessed via performance on 5 cognitive tests ranging 2,149 to 8,722 participants. Attained SES moderated common sources of influences for 3 domains and influences unique to cognition in all 4 domains. The net effect was that genetic influences on the common pathway tended to be relatively more important at the upper end of attained SES indicating possible active rGE, whereas, genetic influences for the unique pathway were proportionally stable or less important at the upper end of attained SES. As a noted exception, at the upper end of attained SES, genetic influences unique to perceptual speed were amplified and genetic influences on the common pathway were dampened. Accounting for rearing SES did not alter attained SES moderation effects on cognitive performance, suggesting mechanisms germane to adulthood. Our findings suggest the importance of gene-environment mechanisms through which attained SES moderates sources of individual differences in cognitive performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Affiliation(s)
| | | | | | | | - Wendy Johnson
- Centre for Cognitive Ageing & Cognitive Epidemiology and Department of Psychology, University of Edinburgh
| | - William S Kremen
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California
| | | | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, University of Southern California
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39
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Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, Nguyen-Viet TA, Bowers P, Sidorenko J, Karlsson Linnér R, Fontana MA, Kundu T, Lee C, Li H, Li R, Royer R, Timshel PN, Walters RK, Willoughby EA, Yengo L, Alver M, Bao Y, Clark DW, Day FR, Furlotte NA, Joshi PK, Kemper KE, Kleinman A, Langenberg C, Mägi R, Trampush JW, Verma SS, Wu Y, Lam M, Zhao JH, Zheng Z, Boardman JD, Campbell H, Freese J, Harris KM, Hayward C, Herd P, Kumari M, Lencz T, Luan J, Malhotra AK, Metspalu A, Milani L, Ong KK, Perry JRB, Porteous DJ, Ritchie MD, Smart MC, Smith BH, Tung JY, Wareham NJ, Wilson JF, Beauchamp JP, Conley DC, Esko T, Lehrer SF, Magnusson PKE, Oskarsson S, Pers TH, Robinson MR, Thom K, Watson C, Chabris CF, Meyer MN, Laibson DI, Yang J, Johannesson M, Koellinger PD, Turley P, Visscher PM, Benjamin DJ, Cesarini D. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet 2018; 50:1112-1121. [PMID: 30038396 PMCID: PMC6393768 DOI: 10.1038/s41588-018-0147-3] [Citation(s) in RCA: 1313] [Impact Index Per Article: 218.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 04/30/2018] [Indexed: 02/06/2023]
Abstract
Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
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Affiliation(s)
- James J Lee
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Robbee Wedow
- Department of Sociology, University of Colorado Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA
| | - Aysu Okbay
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Edward Kong
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - Omeed Maghzian
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - Meghan Zacher
- Department of Sociology, Harvard University, Cambridge, MA, USA
| | - Tuan Anh Nguyen-Viet
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Peter Bowers
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - Julia Sidorenko
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Richard Karlsson Linnér
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Institute for Behavior and Biology, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Mark Alan Fontana
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
- Center for the Advancement of Value in Musculoskeletal Care, Hospital for Special Surgery, New York, NY, USA
| | - Tushar Kundu
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Chanwook Lee
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - Hui Li
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - Ruoxi Li
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Rebecca Royer
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Pascal N Timshel
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen, Denmark
- Statens Serum Institut, Department of Epidemiology Research, Copenhagen, Denmark
| | - Raymond K Walters
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Emily A Willoughby
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Loïc Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Maris Alver
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Yanchun Bao
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - David W Clark
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | | | - Peter K Joshi
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland
| | - Kathryn E Kemper
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | | | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Joey W Trampush
- BrainWorkup, LLC, Santa Monica, CA, USA
- Department of Psychiatry and Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Shefali Setia Verma
- Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, PA, USA
| | - Yang Wu
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Max Lam
- Institute of Mental Health, Singapore, Singapore
- Genome Institute, Singapore, Singapore
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, China
| | - Jason D Boardman
- Department of Sociology, University of Colorado Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Jeremy Freese
- Department of Sociology, Stanford University, Stanford, CA, USA
| | - Kathleen Mullan Harris
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Pamela Herd
- Institute for Social and Economic Research, University of Essex, Colchester, UK
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, USA
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - Todd Lencz
- Departments of Psychiatry and Molecular Medicine, Hofstra Northwell School of Medicine, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, CA, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Anil K Malhotra
- Departments of Psychiatry and Molecular Medicine, Hofstra Northwell School of Medicine, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, CA, USA
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Ken K Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - John R B Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Marylyn D Ritchie
- Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, PA, USA
| | - Melissa C Smart
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Blair H Smith
- Division of Population Health Sciences, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
- Medical Research Institute, University of Dundee, Dundee, UK
| | | | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - James F Wilson
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - Dalton C Conley
- Department of Sociology, Princeton University, Princeton, NJ, USA
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Steven F Lehrer
- School of Policy Studies, Queen's University, Kingston, Ontario, Canada
- Department of Economics, New York University Shanghai, Pudong, Shanghai, China
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sven Oskarsson
- Department of Government, Uppsala University, Uppsala, Sweden
| | - Tune H Pers
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen, Denmark
- Statens Serum Institut, Department of Epidemiology Research, Copenhagen, Denmark
| | - Matthew R Robinson
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Kevin Thom
- Department of Economics, New York University, New York, NY, USA
| | - Chelsea Watson
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Christopher F Chabris
- Autism and Developmental Medicine Institute, Geisinger Health System, Lewisburg, PA, USA
| | - Michelle N Meyer
- Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA
| | - David I Laibson
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - Jian Yang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Philipp D Koellinger
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Institute for Behavior and Biology, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Patrick Turley
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia.
| | - Daniel J Benjamin
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA.
- National Bureau of Economic Research, Cambridge, MA, USA.
- Department of Economics, University of Southern California, Los Angeles, CA, USA.
| | - David Cesarini
- National Bureau of Economic Research, Cambridge, MA, USA
- Department of Economics, New York University, New York, NY, USA
- Center for Experimental Social Science, New York University, New York, NY, USA
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40
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Berggren R, Nilsson J, Lövdén M. Education Does Not Affect Cognitive Decline in Aging: A Bayesian Assessment of the Association Between Education and Change in Cognitive Performance. Front Psychol 2018; 9:1138. [PMID: 30034354 PMCID: PMC6043857 DOI: 10.3389/fpsyg.2018.01138] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Accepted: 06/14/2018] [Indexed: 11/25/2022] Open
Abstract
Education is positively associated with level of cognitive function but the association between education and rate of cognitive decline remains unresolved, partly for methodological reasons. In this article, we address this issue using linear mixed models and Bayesian hypothesis testing, using data from the Betula cohort-sequential longitudinal study. Our results support the null hypothesis that education does not alter the rate of cognitive decline for visuospatial ability, semantic knowledge, and episodic memory. We propose that education is only a relevant variable for understanding cognitive performance in older age because of the association between performance and education that is formed in early development.
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Affiliation(s)
- Rasmus Berggren
- Aging Research Center, Karolinska Institutet, Stockholm University, Stockholm, Sweden
| | - Jonna Nilsson
- Aging Research Center, Karolinska Institutet, Stockholm University, Stockholm, Sweden
| | - Martin Lövdén
- Aging Research Center, Karolinska Institutet, Stockholm University, Stockholm, Sweden
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41
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Rimfeld K, Krapohl E, Trzaskowski M, Coleman JRI, Selzam S, Dale PS, Esko T, Metspalu A, Plomin R. Genetic influence on social outcomes during and after the Soviet era in Estonia. Nat Hum Behav 2018; 2:269-275. [PMID: 29881783 PMCID: PMC5986072 DOI: 10.1038/s41562-018-0332-5] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Accepted: 02/06/2018] [Indexed: 11/09/2022]
Abstract
The etiology of individual differences in educational attainment and occupational status includes genetic as well as environmental factors1-5 and can change as societies change3,6,7. The extent of genetic influence on these social outcomes can be viewed as an index of success in achieving meritocratic values of equality of opportunity by rewarding talent and hard work, which are to a large extent influenced by genetic factors, rather than rewarding environmentally driven privilege. To the extent that the end of the Soviet Union and the independence of Estonia led to an increase in meritocratic selection of individuals in education and occupation, genetic influence should be higher in the post-Soviet era than in the Soviet era. Here we confirmed this hypothesis: DNA differences (single-nucleotide polymorphisms, SNPs) explained twice as much variance in educational attainment and occupational status in the post-Soviet era compared to the Soviet era in both polygenic score analyses and SNP heritability analyses of 12 500 Estonians. This is the first demonstration of a change in the extent of genetic influence in the same population following a massive and abrupt social change - in this case, the shift from a communist to a capitalist society.
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Affiliation(s)
- Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Eva Krapohl
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Maciej Trzaskowski
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Jonathan R I Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health Research Biomedical Research Centre, South London and Maudsley National Health Service Trust, London, UK
| | - Saskia Selzam
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Philip S Dale
- Department of Speech and Hearing Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Tonu Esko
- Estonian Genome Centre, University of Tartu, Tartu, Estonia
| | | | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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42
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Association of Educational Level and Marital Status With Obesity: A Study of Chinese Twins. Twin Res Hum Genet 2018; 21:126-135. [PMID: 29559026 DOI: 10.1017/thg.2018.8] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The prevalence of overweight and obesity is growing rapidly in many countries. Socioeconomic inequalities might be important for this increase. The aim of this study was to determine associations of body mass index (BMI), overweight and obesity with educational level and marital status in Chinese twins. Participants were adult twins recruited through the Chinese National Twin Registry (CNTR), aged 18 to 79 years, and the sample comprised 10,448 same-sex twin pairs. Current height, weight, educational attainment, and marital status were self-reported. Regression analyses and structural equation models were conducted to evaluate BMI, overweight, and obesity associated with educational level and marital status in both sexes. At an individual level, both educational level and marital status were associated with higher BMI and higher risk of being overweight and obesity in men, while in women the effects of educational level on BMI were in the opposite direction. In within-Monozygotic (MZ) twin-pair analyses, the effects of educational level on BMI disappeared in females. Bivariate structural equation models showed that genetic factors and shared environmental confounded the relationship between education and BMI in females, whereas marital status was associated with BMI on account of significant positive unique environmental correlation apart in both sexes. The present data suggested that marital status and BMI were associated, independent of familiar factors, for both sexes of this study population, while common genetic and shared environmental factors contributed to education-associated disparities in BMI in females.
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43
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Abstract
Does general intelligence exist across species, and has it been a target of natural selection? These questions can be addressed with genomic data, which can rule out artifacts by demonstrating that distinct cognitive abilities are genetically correlated and thus share a biological substrate. This work has begun with data from humans and can be extended to other species; it should focus not only on general intelligence but also specific capacities like language and spatial ability.
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44
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Schwabe I, Janss L, van den Berg SM. Can We Validate the Results of Twin Studies? A Census-Based Study on the Heritability of Educational Achievement. Front Genet 2017; 8:160. [PMID: 29123543 PMCID: PMC5662588 DOI: 10.3389/fgene.2017.00160] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Accepted: 10/10/2017] [Indexed: 11/13/2022] Open
Abstract
As for most phenotypes, the amount of variance in educational achievement explained by SNPs is lower than the amount of additive genetic variance estimated in twin studies. Twin-based estimates may however be biased because of self-selection and differences in cognitive ability between twins and the rest of the population. Here we compare twin registry based estimates with a census-based heritability estimate, sampling from the same Dutch birth cohort population and using the same standardized measure for educational achievement. Including important covariates (i.e., sex, migration status, school denomination, SES, and group size), we analyzed 893,127 scores from primary school children from the years 2008-2014. For genetic inference, we used pedigree information to construct an additive genetic relationship matrix. Corrected for the covariates, this resulted in an estimate of 85%, which is even higher than based on twin studies using the same cohort and same measure. We therefore conclude that the genetic variance not tagged by SNPs is not an artifact of the twin method itself.
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Affiliation(s)
- Inga Schwabe
- Department of Research Methodology, Measurement and Data Analysis (OMD), University of Twente, Enschede, Netherlands.,Department of Methodology and Statistics, Tilburg University, Tilburg, Netherlands
| | - Luc Janss
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Stéphanie M van den Berg
- Department of Research Methodology, Measurement and Data Analysis (OMD), University of Twente, Enschede, Netherlands
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45
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The Contribution of Genes and the Environment to Educational and Socioeconomic Attainments in Australia. Twin Res Hum Genet 2017; 20:281-289. [DOI: 10.1017/thg.2017.32] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
This article analyzes the contribution of genetics and the environment to educational attainment, occupational status, and income using data from over 1,100 monozygotic and 400 dizygotic Australian twin pairs aged from 18 to 99. The respective heritability estimates were 0.54, 0.37, and 0.18. The bivariate heritabilities were 0.71 for educational attainment and occupational status, 0.37 for education and income, and 0.61 for occupational status and income. There were no gender and cohort differences in the heritabilities for education and occupation, but for income, contrary to expectations, the heritabilities were significantly higher among women and for the older cohort (aged 50 or older). The sizable contribution of genes to these socioeconomic outcomes suggests that standard sociological and economic theories on the socioeconomic career require substantial modification to accommodate the role of genetics.
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46
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What Explains the Heritability of Completed Fertility? Evidence from Two Large Twin Studies. Behav Genet 2016; 47:36-51. [PMID: 27522223 DOI: 10.1007/s10519-016-9805-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Accepted: 08/08/2016] [Indexed: 10/21/2022]
Abstract
In modern societies, individual differences in completed fertility are linked with genotypic differences between individuals. Explaining the heritability of completed fertility has been inconclusive, with alternative explanations centering on family formation timing, pursuit of education, or other psychological traits. We use the twin subsample from the Midlife Development in the United States study and the TwinsUK study to examine these issues. In total, 2606 adult twin pairs reported on their completed fertility, age at first birth and marriage, level of education, Big Five personality traits, and cognitive ability. Quantitative genetic Cholesky models were used to partition the variance in completed fertility into genetic and environmental variance that is shared with other phenotypes and residual variance. Genetic influences on completed fertility are strongly related to family formation timing and less strongly, but significantly, with psychological traits. Multivariate models indicate that family formation, demographic, and psychological phenotypes leave no residual genetic variance in completed fertility in either dataset. Results are largely consistent across U.S. and U.K. sociocultural contexts.
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47
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Conley D, Domingue B. The Bell Curve Revisited: Testing Controversial Hypotheses with Molecular Genetic Data. SOCIOLOGICAL SCIENCE 2016; 3:520-539. [PMID: 29130056 PMCID: PMC5679002 DOI: 10.15195/v3.a23] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
In 1994, the publication of Herrnstein's and Murray's The Bell Curve resulted in a social science maelstrom of responses. In the present study, we argue that Herrnstein's and Murray's assertions were made prematurely, on their own terms, given the lack of data available to test the role of genotype in the dynamics of achievement and attainment in U.S. society. Today, however, the scientific community has access to at least one dataset that is nationally representative and has genome-wide molecular markers. We deploy those data from the Health and Retirement Study in order to test the core series of propositions offered by Herrnstein and Murray in 1994. First, we ask whether the effect of genotype is increasing in predictive power across birth cohorts in the middle twentieth century. Second, we ask whether assortative mating on relevant genotypes is increasing across the same time period. Finally, we ask whether educational genotypes are increasingly predictive of fertility (number ever born [NEB]) in tandem with the rising (negative) association of educational outcomes and NEB. The answers to these questions are mostly no; while molecular genetic markers can predict educational attainment, we find little evidence for the proposition that we are becoming increasingly genetically stratified.
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Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, Turley P, Chen GB, Emilsson V, Meddens SFW, Oskarsson S, Pickrell JK, Thom K, Timshel P, de Vlaming R, Abdellaoui A, Ahluwalia TS, Bacelis J, Baumbach C, Bjornsdottir G, Brandsma JH, Pina Concas M, Derringer J, Furlotte NA, Galesloot TE, Girotto G, Gupta R, Hall LM, Harris SE, Hofer E, Horikoshi M, Huffman JE, Kaasik K, Kalafati IP, Karlsson R, Kong A, Lahti J, van der Lee SJ, deLeeuw C, Lind PA, Lindgren KO, Liu T, Mangino M, Marten J, Mihailov E, Miller MB, van der Most PJ, Oldmeadow C, Payton A, Pervjakova N, Peyrot WJ, Qian Y, Raitakari O, Rueedi R, Salvi E, Schmidt B, Schraut KE, Shi J, Smith AV, Poot RA, St Pourcain B, Teumer A, Thorleifsson G, Verweij N, Vuckovic D, Wellmann J, Westra HJ, Yang J, Zhao W, Zhu Z, Alizadeh BZ, Amin N, Bakshi A, Baumeister SE, Biino G, Bønnelykke K, Boyle PA, Campbell H, Cappuccio FP, Davies G, De Neve JE, Deloukas P, Demuth I, Ding J, Eibich P, Eisele L, Eklund N, Evans DM, Faul JD, Feitosa MF, Forstner AJ, Gandin I, Gunnarsson B, Halldórsson BV, Harris TB, Heath AC, Hocking LJ, Holliday EG, Homuth G, Horan MA, Hottenga JJ, de Jager PL, Joshi PK, Jugessur A, Kaakinen MA, Kähönen M, Kanoni S, Keltigangas-Järvinen L, Kiemeney LALM, Kolcic I, Koskinen S, Kraja AT, Kroh M, Kutalik Z, Latvala A, Launer LJ, Lebreton MP, Levinson DF, Lichtenstein P, Lichtner P, Liewald DCM, Loukola A, Madden PA, Mägi R, Mäki-Opas T, Marioni RE, Marques-Vidal P, Meddens GA, McMahon G, Meisinger C, Meitinger T, Milaneschi Y, Milani L, Montgomery GW, Myhre R, Nelson CP, Nyholt DR, Ollier WER, Palotie A, Paternoster L, Pedersen NL, Petrovic KE, Porteous DJ, Räikkönen K, Ring SM, Robino A, Rostapshova O, Rudan I, Rustichini A, Salomaa V, Sanders AR, Sarin AP, Schmidt H, Scott RJ, Smith BH, Smith JA, Staessen JA, Steinhagen-Thiessen E, Strauch K, Terracciano A, Tobin MD, Ulivi S, Vaccargiu S, Quaye L, van Rooij FJA, Venturini C, Vinkhuyzen AAE, Völker U, Völzke H, Vonk JM, Vozzi D, Waage J, Ware EB, Willemsen G, Attia JR, Bennett DA, Berger K, Bertram L, Bisgaard H, Boomsma DI, Borecki IB, Bültmann U, Chabris CF, Cucca F, Cusi D, Deary IJ, Dedoussis GV, van Duijn CM, Eriksson JG, Franke B, Franke L, Gasparini P, Gejman PV, Gieger C, Grabe HJ, Gratten J, Groenen PJF, Gudnason V, van der Harst P, Hayward C, Hinds DA, Hoffmann W, Hyppönen E, Iacono WG, Jacobsson B, Järvelin MR, Jöckel KH, Kaprio J, Kardia SLR, Lehtimäki T, Lehrer SF, Magnusson PKE, Martin NG, McGue M, Metspalu A, Pendleton N, Penninx BWJH, Perola M, Pirastu N, Pirastu M, Polasek O, Posthuma D, Power C, Province MA, Samani NJ, Schlessinger D, Schmidt R, Sørensen TIA, Spector TD, Stefansson K, Thorsteinsdottir U, Thurik AR, Timpson NJ, Tiemeier H, Tung JY, Uitterlinden AG, Vitart V, Vollenweider P, Weir DR, Wilson JF, Wright AF, Conley DC, Krueger RF, Davey Smith G, Hofman A, Laibson DI, Medland SE, Meyer MN, Yang J, Johannesson M, Visscher PM, Esko T, Koellinger PD, Cesarini D, Benjamin DJ. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 2016; 533:539-42. [PMID: 27225129 PMCID: PMC4883595 DOI: 10.1038/nature17671] [Citation(s) in RCA: 750] [Impact Index Per Article: 93.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Accepted: 03/16/2016] [Indexed: 01/15/2023]
Abstract
Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
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Affiliation(s)
- Aysu Okbay
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, 3062 PA, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, 3062 PA, The Netherlands
| | - Jonathan P Beauchamp
- Department of Economics, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Mark Alan Fontana
- Center for Economic and Social Research, University of Southern California, Los Angeles, California 90089-3332, USA
| | - James J Lee
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota 55455, USA
| | - Tune H Pers
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts 2116, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen 2100, Denmark
- Statens Serum Institut, Department of Epidemiology Research, Copenhagen 2300, Denmark
| | - Cornelius A Rietveld
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, 3062 PA, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, 3062 PA, The Netherlands
| | - Patrick Turley
- Department of Economics, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Guo-Bo Chen
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Valur Emilsson
- Icelandic Heart Association, Kopavogur 201, Iceland
- Faculty of Pharmaceutical Sciences, University of Iceland, Reykjavík 107, Iceland
| | - S Fleur W Meddens
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, 3062 PA, The Netherlands
- Department of Complex Trait Genetics, VU University, Center for Neurogenomics and Cognitive Research, Amsterdam, 1081 HV, The Netherlands
- Amsterdam Business School, University of Amsterdam, Amsterdam, 1018 TV, The Netherlands
| | - Sven Oskarsson
- Department of Government, Uppsala University, Uppsala 751 20, Sweden
| | | | - Kevin Thom
- Department of Economics, New York University, New York, New York 10012, USA
| | - Pascal Timshel
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark Lyngby 2800, Denmark
| | - Ronald de Vlaming
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, 3062 PA, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, 3062 PA, The Netherlands
| | - Abdel Abdellaoui
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, 1081 BT, The Netherlands
| | - Tarunveer S Ahluwalia
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen 2100, Denmark
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen 2820, Denmark
- Steno Diabetes Center, Gentofte 2820, Denmark
| | - Jonas Bacelis
- Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, Gothenburg 416 85, Sweden
| | - Clemens Baumbach
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | | | - Johannes H Brandsma
- Department of Cell Biology, Erasmus Medical Center Rotterdam, 3015 CN, The Netherlands
| | - Maria Pina Concas
- Istituto di Ricerca Genetica e Biomedica U.O.S. di Sassari, National Research Council of Italy, Sassari 07100, Italy
| | - Jaime Derringer
- Psychology, University of Illinois, Champaign, Illinois 61820, USA
| | | | - Tessel E Galesloot
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, 6500 HB, The Netherlands
| | - Giorgia Girotto
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste 34100, Italy
| | - Richa Gupta
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
| | - Leanne M Hall
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Edith Hofer
- Department of Neurology, General Hospital and Medical University Graz, Graz 8036, Austria
- Institute for Medical Informatics, Statistics and Documentation, General Hospital and Medical University Graz, Graz 8036, Austria
| | - Momoko Horikoshi
- Oxford Centre for Diabetes, Endocrinology &Metabolism, University of Oxford, Oxford OX3 7LE, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Jennifer E Huffman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Kadri Kaasik
- Institute of Behavioural Sciences, University of Helsinki, 00014 Helsinki, Finland
| | - Ioanna P Kalafati
- Nutrition and Dietetics, Health Science and Education, Harokopio University, Athens 17671, Greece
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 77, Sweden
| | | | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, 00014 Helsinki, Finland
- Folkhälsan Research Centre, 00014 Helsingfors, Finland
| | - Sven J van der Lee
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
| | - Christiaan deLeeuw
- Department of Complex Trait Genetics, VU University, Center for Neurogenomics and Cognitive Research, Amsterdam, 1081 HV, The Netherlands
- Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, 6525 EC, The Netherlands
| | - Penelope A Lind
- Quantitative Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia
| | | | - Tian Liu
- Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK
- NIHR Biomedical Research Centre, Guy's and St. Thomas' Foundation Trust, London SE1 7EH, UK
| | - Jonathan Marten
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Michael B Miller
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota 55455, USA
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Christopher Oldmeadow
- Public Health Stream, Hunter Medical Research Institute, New Lambton, NSW 2305, Australia
- Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2300, Australia
| | - Antony Payton
- Centre for Integrated Genomic Medical Research, Institute of Population Health, The University of Manchester, Manchester M13 9PT, UK
- Human Communication and Deafness, School of Psychological Sciences, The University of Manchester, Manchester M13 9PL, UK
| | - Natalia Pervjakova
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Department of Health, THL-National Institute for Health and Welfare, 00271 Helsinki, Finland
| | - Wouter J Peyrot
- Psychiatry, VU University Medical Center &GGZ inGeest, Amsterdam, 1081 HL, The Netherlands
| | - Yong Qian
- Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland 21224, USA
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20521 Turku, Finland
| | - Rico Rueedi
- Department of Medical Genetics, University of Lausanne, Lausanne 1005, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Erika Salvi
- Department Of Health Sciences, University of Milan, Milano 20142, Italy
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen 45147, Germany
| | - Katharina E Schraut
- Centre for Global Health Research, The Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland 20892-9780, USA
| | - Albert V Smith
- Icelandic Heart Association, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Raymond A Poot
- Department of Cell Biology, Erasmus Medical Center Rotterdam, 3015 CN, The Netherlands
| | - Beate St Pourcain
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol BS1 2LY, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | | | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, 9700 RB, The Netherlands
| | - Dragana Vuckovic
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste 34100, Italy
| | - Juergen Wellmann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster 48149, Germany
| | - Harm-Jan Westra
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
- Partners Center for Personalized Genetic Medicine, Boston, Massachusetts 02115, USA
| | - Jingyun Yang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois 60612, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Zhihong Zhu
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Behrooz Z Alizadeh
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, 9713 GZ, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
| | - Andrew Bakshi
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Sebastian E Baumeister
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
- Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg D-93053, Germany
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Pavia 27100, Italy
| | - Klaus Bønnelykke
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen 2820, Denmark
| | - Patricia A Boyle
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois 60612, USA
- Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois 60612, USA
| | - Harry Campbell
- Centre for Global Health Research, The Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH8 9AG, UK
| | | | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | | | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Ilja Demuth
- The Berlin Aging Study II; Research Group on Geriatrics, Charité - Universitätsmedizin Berlin, Germany, Berlin 13347, Germany
- Institute of Medical and Human Genetics, Charité-Universitätsmedizin, Berlin, Berlin 13353, Germany
| | - Jun Ding
- Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland 21224, USA
| | - Peter Eibich
- German Socio- Economic Panel Study, DIW Berlin, Berlin 10117, Germany
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Lewin Eisele
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen 45147, Germany
| | - Niina Eklund
- Department of Health, THL-National Institute for Health and Welfare, 00271 Helsinki, Finland
| | - David M Evans
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- The University of Queensland Diamantina Institute, The Translational Research Institute, Brisbane, QLD 4102, Australia
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Mary F Feitosa
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri 63018, USA
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, Bonn 53127, Germany
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn 53127, Germany
| | - Ilaria Gandin
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste 34100, Italy
| | | | - Bjarni V Halldórsson
- deCODE Genetics/Amgen Inc., Reykjavik 101, Iceland
- Institute of Biomedical and Neural Engineering, School of Science and Engineering, Reykjavik University, Reykjavik 101, Iceland
| | - Tamara B Harris
- Laboratory of Epidemiology, Demography, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892-9205, USA
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Lynne J Hocking
- Division of Applied Health Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK
| | - Elizabeth G Holliday
- Public Health Stream, Hunter Medical Research Institute, New Lambton, NSW 2305, Australia
- Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2300, Australia
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17475, Germany
| | - Michael A Horan
- Manchester Medical School, The University of Manchester, Manchester M13 9PT, UK
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, 1081 BT, The Netherlands
| | - Philip L de Jager
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Program in Translational NeuroPsychiatric Genomics, Departments of Neurology &Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA
- Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Peter K Joshi
- Centre for Global Health Research, The Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Astanand Jugessur
- Department of Genes and Environment, Norwegian Institute of Public Health, N-0403 Oslo, Norway
| | - Marika A Kaakinen
- Department of Genomics of Common Disease, Imperial College London, London, W12 0NN, UK
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, 33521 Tampere, Finland
- Department of Clinical Physiology, University of Tampere, School of Medicine, 33014 Tampere, Finland
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | | | - Lambertus A L M Kiemeney
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, 6500 HB, The Netherlands
| | - Ivana Kolcic
- Public Health, Medical School, University of Split, 21000 Split, Croatia
| | - Seppo Koskinen
- Department of Health, THL-National Institute for Health and Welfare, 00271 Helsinki, Finland
| | - Aldi T Kraja
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri 63018, USA
| | - Martin Kroh
- German Socio- Economic Panel Study, DIW Berlin, Berlin 10117, Germany
| | - Zoltan Kutalik
- Department of Medical Genetics, University of Lausanne, Lausanne 1005, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Institute of Social and Preventive Medicine, Lausanne University Hospital (CHUV), Lausanne 1010, Switzerland
| | - Antti Latvala
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
| | - Lenore J Launer
- Neuroepidemiology Section, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892-9205, USA
| | - Maël P Lebreton
- Amsterdam Business School, University of Amsterdam, Amsterdam, 1018 TV, The Netherlands
- Amsterdam Brain and Cognition Center, University of Amsterdam, Amsterdam, 1018 XA, The Netherlands
| | - Douglas F Levinson
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94305-5797, USA
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 77, Sweden
| | - Peter Lichtner
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - David C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | | | - Anu Loukola
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
| | - Pamela A Madden
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Tomi Mäki-Opas
- Department of Health, THL-National Institute for Health and Welfare, 00271 Helsinki, Finland
| | - Riccardo E Marioni
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Pedro Marques-Vidal
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne 1011, Switzerland
| | | | - George McMahon
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Christa Meisinger
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Yusplitri Milaneschi
- Psychiatry, VU University Medical Center &GGZ inGeest, Amsterdam, 1081 HL, The Netherlands
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Grant W Montgomery
- Molecular Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia
| | - Ronny Myhre
- Department of Genes and Environment, Norwegian Institute of Public Health, N-0403 Oslo, Norway
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Dale R Nyholt
- Molecular Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia
- Institute of Health and Biomedical Innovation, Queensland Institute of Technology, Brisbane, QLD 4059, Australia
| | - William E R Ollier
- Centre for Integrated Genomic Medical Research, Institute of Population Health, The University of Manchester, Manchester M13 9PT, UK
| | - Aarno Palotie
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- The Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Psychiatric &Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 77, Sweden
| | - Katja E Petrovic
- Department of Neurology, General Hospital and Medical University Graz, Graz 8036, Austria
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Katri Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, 00014 Helsinki, Finland
- Folkhälsan Research Centre, 00014 Helsingfors, Finland
| | - Susan M Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Antonietta Robino
- Medical Genetics, Institute for Maternal and Child Health IRCCS "Burlo Garofolo", Trieste 34100, Italy
| | - Olga Rostapshova
- Department of Economics, Harvard University, Cambridge, Massachusetts 02138, USA
- Social Impact, Arlington, Virginia 22201, USA
| | - Igor Rudan
- Centre for Global Health Research, The Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Aldo Rustichini
- Department of Economics, University of Minnesota Twin Cities, Minneapolis, Minnesota 55455, USA
| | - Veikko Salomaa
- Department of Health, THL-National Institute for Health and Welfare, 00271 Helsinki, Finland
| | - Alan R Sanders
- Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem, Evanston, Illinois 60201-3137, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois 60637, USA
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, 00300 Helsinki, Finland
| | - Helena Schmidt
- Department of Neurology, General Hospital and Medical University Graz, Graz 8036, Austria
- Research Unit for Genetic Epidemiology, Institute of Molecular Biology and Biochemistry, Center of Molecular Medicine, General Hospital and Medical University, Graz, Graz 8010, Austria
| | - Rodney J Scott
- Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2300, Australia
- Information Based Medicine Stream, Hunter Medical Research Institute, New Lambton, NSW 2305, Australia
| | - Blair H Smith
- Medical Research Institute, University of Dundee, Dundee DD1 9SY, UK
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Jan A Staessen
- Research Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Science, University of Leuven, Leuven 3000, Belgium
- R&D VitaK Group, Maastricht University, Maastricht, 6229 EV, The Netherlands
| | - Elisabeth Steinhagen-Thiessen
- The Berlin Aging Study II; Research Group on Geriatrics, Charité - Universitätsmedizin Berlin, Germany, Berlin 13347, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig Maximilians-Universität, Munich 81377, Germany
| | - Antonio Terracciano
- Department of Geriatrics, Florida State University College of Medicine, Tallahassee, Florida 32306, USA
| | - Martin D Tobin
- Department of Health Sciences and Genetics, University of Leicester, Leicester LE1 7RH, UK
| | - Sheila Ulivi
- Medical Genetics, Institute for Maternal and Child Health IRCCS "Burlo Garofolo", Trieste 34100, Italy
| | - Simona Vaccargiu
- Istituto di Ricerca Genetica e Biomedica U.O.S. di Sassari, National Research Council of Italy, Sassari 07100, Italy
| | - Lydia Quaye
- Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
| | - Cristina Venturini
- Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK
- NIHR Biomedical Research Centre, Guy's and St. Thomas' Foundation Trust, London SE1 7EH, UK
| | - Anna A E Vinkhuyzen
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17475, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Judith M Vonk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Diego Vozzi
- Social Impact, Arlington, Virginia 22201, USA
| | - Johannes Waage
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen 2820, Denmark
- Steno Diabetes Center, Gentofte 2820, Denmark
| | - Erin B Ware
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan 48109, USA
- Research Center for Group Dynamics, Institute for Social Research, University of Michigan, Ann Arbor, Michigan 48104, USA
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, 1081 BT, The Netherlands
| | - John R Attia
- Public Health Stream, Hunter Medical Research Institute, New Lambton, NSW 2305, Australia
- Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2300, Australia
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois 60612, USA
| | - Klaus Berger
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, 9700 RB, The Netherlands
| | - Lars Bertram
- Platform for Genome Analytics, Institutes of Neurogenetics &Integrative and Experimental Genomics, University of Lübeck, Lübeck 23562, Germany
- Neuroepidemiology and Ageing Research Unit, School of Public Health, Faculty of Medicine, Imperial College of Science, Technology and Medicine, London SW7 2AZ, UK
| | - Hans Bisgaard
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen 2820, Denmark
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, 1081 BT, The Netherlands
| | - Ingrid B Borecki
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri 63018, USA
| | - Ute Bültmann
- Department of Health Sciences, Community &Occupational Medicine, University of Groningen, University Medical Center Groningen, Groningen, 9713 AV, The Netherlands
| | | | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari 9042, Italy
| | - Daniele Cusi
- Department Of Health Sciences, University of Milan, Milano 20142, Italy
- Institute of Biomedical Technologies, Italian National Research Council, Segrate (Milano) 20090, Italy
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - George V Dedoussis
- Nutrition and Dietetics, Health Science and Education, Harokopio University, Athens 17671, Greece
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
| | - Johan G Eriksson
- Folkhälsan Research Centre, 00014 Helsingfors, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, 00014 Helsinki, Finland
| | - Barbara Franke
- Departments of Human Genetics and Psychiatry, Donders Centre for Neuroscience, Nijmegen, 6500 HB, The Netherlands
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, 9700 RB, The Netherlands
| | - Paolo Gasparini
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste 34100, Italy
- Medical Genetics, Institute for Maternal and Child Health IRCCS "Burlo Garofolo", Trieste 34100, Italy
- Sidra, Experimental Genetics Division, Sidra, Doha 26999, Qatar
| | - Pablo V Gejman
- Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem, Evanston, Illinois 60201-3137, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois 60637, USA
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Hans-Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
- Department of Psychiatry and Psychotherapy, HELIOS-Hospital Stralsund, Stralsund 18437, Germany
| | - Jacob Gratten
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Patrick J F Groenen
- Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, 3062 PA, The Netherlands
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, 9700 RB, The Netherlands
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, 9700 RB, The Netherlands
- Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, 1105 AZ, The Netherlands
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
- Generation Scotland, Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | | | - Wolfgang Hoffmann
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Elina Hyppönen
- Centre for Population Health Research, School of Health Sciences and Sansom Institute, University of South Australia, Adelaide, SA 5000, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
- Population, Policy and Practice, UCL Institute of Child Health, London WC1N 1EH, UK
| | - William G Iacono
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota 55455, USA
| | - Bo Jacobsson
- Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, Gothenburg 416 85, Sweden
- Department of Genes and Environment, Norwegian Institute of Public Health, N-0403 Oslo, Norway
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment &Health, School of Public Health, Imperial College London, London W2 1PG, UK
- Center for Life Course Epidemiology, Faculty of Medicine, University of Oulu, 90014 Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, 90029 Oulu, Finland
- Biocenter Oulu, University of Oulu, 90014 Oulu, Finland
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen 45147, Germany
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
- Department of Health, THL-National Institute for Health and Welfare, 00271 Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Terho Lehtimäki
- Fimlab Laboratories, 33520 Tampere, Finland
- Department of Clinical Chemistry, University of Tampere, School of Medicine, 33014 Tampere, Finland
| | - Steven F Lehrer
- Economics, NYU Shanghai, 200122 Pudong, China
- Policy Studies, Queen's University, Kingston, Ontario K7L 3N6, Canada
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 77, Sweden
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia
| | - Matt McGue
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota 55455, USA
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia
| | - Neil Pendleton
- Centre for Clinical and Cognitive Neuroscience, Institute Brain Behaviour and Mental Health, Salford Royal Hospital, Manchester M6 8HD, UK
- Manchester Institute for Collaborative Research in Ageing, University of Manchester, Manchester M13 9PL, UK
| | - Brenda W J H Penninx
- Psychiatry, VU University Medical Center &GGZ inGeest, Amsterdam, 1081 HL, The Netherlands
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Department of Health, THL-National Institute for Health and Welfare, 00271 Helsinki, Finland
| | - Nicola Pirastu
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste 34100, Italy
| | - Mario Pirastu
- Istituto di Ricerca Genetica e Biomedica U.O.S. di Sassari, National Research Council of Italy, Sassari 07100, Italy
| | - Ozren Polasek
- Centre for Global Health Research, The Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH8 9AG, UK
- Faculty of Medicine, University of Split, Split 21000, Croatia
| | - Danielle Posthuma
- Department of Complex Trait Genetics, VU University, Center for Neurogenomics and Cognitive Research, Amsterdam, 1081 HV, The Netherlands
- Department of Clinical Genetics, VU Medical Centre, Amsterdam, 1081 HV, The Netherlands
| | - Christine Power
- Population, Policy and Practice, UCL Institute of Child Health, London WC1N 1EH, UK
| | - Michael A Province
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri 63018, USA
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK
| | - David Schlessinger
- Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland 21224, USA
| | - Reinhold Schmidt
- Department of Neurology, General Hospital and Medical University Graz, Graz 8036, Austria
| | - Thorkild I A Sørensen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen 2100, Denmark
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Institute of Preventive Medicine. Bispebjerg and Frederiksberg Hospitals, The Capital Region, Frederiksberg 2000, Denmark
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK
| | - Kari Stefansson
- deCODE Genetics/Amgen Inc., Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen Inc., Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - A Roy Thurik
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, 3062 PA, The Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, 3062 PA, The Netherlands
- Montpellier Business School, Montpellier 34080, France
- Panteia, Zoetermeer, 2715 CA, The Netherlands
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
| | - Joyce Y Tung
- 23andMe, Inc., Mountain View, California 94041, USA
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Peter Vollenweider
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne 1011, Switzerland
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
- Centre for Global Health Research, The Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Alan F Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Dalton C Conley
- Department of Sociology, New York University, New York, New York 10012, USA
- School of Medicine, New York University, New York, New York 10016, USA
| | - Robert F Krueger
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota 55455, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands
| | - David I Laibson
- Department of Economics, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Sarah E Medland
- Quantitative Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia
| | - Michelle N Meyer
- Bioethics Program, Union Graduate College - Icahn School of Medicine at Mount Sinai, Schenectady, New York 12308, USA
| | - Jian Yang
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
- The University of Queensland Diamantina Institute, The Translational Research Institute, Brisbane, QLD 4102, Australia
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm 113 83, Sweden
| | - Peter M Visscher
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
- The University of Queensland Diamantina Institute, The Translational Research Institute, Brisbane, QLD 4102, Australia
| | - Tõnu Esko
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts 2116, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Philipp D Koellinger
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, 3062 PA, The Netherlands
- Department of Complex Trait Genetics, VU University, Center for Neurogenomics and Cognitive Research, Amsterdam, 1081 HV, The Netherlands
- Amsterdam Business School, University of Amsterdam, Amsterdam, 1018 TV, The Netherlands
| | - David Cesarini
- Department of Economics, New York University, New York, New York 10012, USA
- Research Institute for Industrial Economics, Stockholm 10215, Sweden
| | - Daniel J Benjamin
- Center for Economic and Social Research, University of Southern California, Los Angeles, California 90089-3332, USA
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Haworth CMA, Nelson SK, Layous K, Carter K, Jacobs Bao K, Lyubomirsky S, Plomin R. Stability and Change in Genetic and Environmental Influences on Well-Being in Response to an Intervention. PLoS One 2016; 11:e0155538. [PMID: 27227410 PMCID: PMC4881940 DOI: 10.1371/journal.pone.0155538] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 04/29/2016] [Indexed: 12/03/2022] Open
Abstract
Genetic and environmental influences on complex traits can change in response to developmental and environmental contexts. Here we explore the impact of a positive activity intervention on the genetic and environmental influences on well-being and mental health in a sample of 750 adolescent twins. Twins completed a 10-week online well-being intervention, consisting of kindness and gratitude tasks and matched control activities. The results showed significant improvements both in well-being and in internalizing symptoms in response to the intervention activities. We used multivariate twin analyses of repeated measures, tracking stability and change in genetic and environmental influences, to assess the impact of this environmental intervention on these variance components. The heritability of well-being remained high both before and after the intervention, and the same genetic effects were important at each stage, even as well-being increased. The overall magnitude of environmental influences was also stable across the intervention; however, different non-shared environmental influences emerged during the intervention. Our study highlights the value of exploring the innovations in non-shared environmental influences that could provide clues to the mechanisms behind improvements in well-being. The findings also emphasize that even traits strongly influenced by genetics, like well-being, are subject to change in response to environmental interventions.
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Affiliation(s)
- Claire M. A. Haworth
- MRC Integrative Epidemiology Unit, School of Experimental Psychology & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - S. Katherine Nelson
- Department of Psychology, Sewanee: The University of the South, Sewanee, United States of America
| | - Kristin Layous
- Department of Psychology, University of California Riverside, Riverside, United States of America
| | - Kathryn Carter
- Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, United Kingdom
| | - Katherine Jacobs Bao
- Department of Psychology, University of California Riverside, Riverside, United States of America
| | - Sonja Lyubomirsky
- Department of Psychology, University of California Riverside, Riverside, United States of America
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, United Kingdom
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