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Bailey AH, Knobe J. Biological Essentialism Correlates With (But Doesn't Cause?) Intergroup Bias. PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN 2024; 50:1080-1097. [PMID: 36978264 DOI: 10.1177/01461672231158095] [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: 03/30/2023]
Abstract
People with biological essentialist beliefs about social groups also tend to endorse biased beliefs about individuals in those groups, including intensified emphasis on the group, stereotypes, and prejudices. These correlations could be due to biological essentialism causing bias, and some experimental studies support this causal direction. Given this prior work, we expected to find that biological essentialism would lead to increased bias compared with a control condition and set out to extend this prior work in a new direction (regarding "value-based" essentialism). But although the manipulation affected essentialist beliefs and essentialist beliefs were correlated with group emphasis (Study 1), stereotyping (Studies 2, 3a, 3b, and 3c), prejudice (Studies 3a), there was no evidence that biological essentialism caused these outcomes (NTotal = 1,903). Given these findings, our initial research question became moot. We thus focus on reexamining the relationship between essentialism and bias.
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Affiliation(s)
- April H Bailey
- University of New Hampshire, Durham, USA
- Yale University, New Haven, CT, USA
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2
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Martschenko DO, Grannuci A, Cho MK. "Ethical Responsibility Very Often Gets Drowned Out": A Qualitative Interview Study of Genome Scientists' and ELSI Scholars' Perspectives on the Role and Relevance of ELSI Expertise. AJOB Empir Bioeth 2024:1-12. [PMID: 38916600 DOI: 10.1080/23294515.2024.2370769] [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: 06/26/2024]
Abstract
BACKGROUND Genome scientists and Ethical, Legal, and Social Implications of genetics (ELSI) scholars commonly inhabit distinct research cultures - utilizing different research methods, asking different research questions, and valuing different types of knowledge. Collaborations between these two communities are frequently called for to enhance the ethical conduct of genomics research. Yet, little has been done to qualitatively compare genome scientists' and ELSI scholars' perspectives on collaborations with each other and the factors that may affect these collaborations. METHODS 20 semi-structured interviews with US-based genome scientists and ELSI scholars were conducted between June-September 2021. Interviews were analyzed using inductive thematic analysis. RESULTS Genome scientists and ELSI scholars provided different understandings of the value and goals of their collaborations with each other. Genome scientists largely perceived ELSI expertise to be relevant for human subjects research; they described ELSI scholars as communicators who help the public and/or study participants better understand genomics research. In comparison, ELSI scholars viewed themselves as developing and implementing policies; they expressed frustration at how scientists can misunderstand their research methods or negatively perceive them. A combination of factors - both structural (e.g., criteria for promotion) and cultural (e.g., perceptions of what colleagues value and respect) - seemed to shape these diverging perspectives. CONCLUSION Academic institutions, funders, and researchers commonly call for collaborations between genome scientists and ELSI scholars, but under-consider how their different conceptual frameworks, research methods, goals, norms, and values, conjoin to affect such partnerships. Acknowledging, exploring, and addressing the complex interplay between these factors could help to more effectively facilitate collaborations between genome scientists and ELSI scholars.
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Affiliation(s)
- Daphne O Martschenko
- Stanford Center for Biomedical Ethics and Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Anna Grannuci
- Stanford Center for Biomedical Ethics and Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Mildred K Cho
- Stanford Center for Biomedical Ethics and Department of Pediatrics, Stanford University, Stanford, CA, USA
- Stanford Center for Biomedical Ethics and Department of Medicine, Stanford University, Stanford, CA, USA
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3
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Trejo S. Exploring the Fetal Origins Hypothesis Using Genetic Data. SOCIAL FORCES; A SCIENTIFIC MEDIUM OF SOCIAL STUDY AND INTERPRETATION 2024; 102:1555-1581. [PMID: 38638179 PMCID: PMC11021852 DOI: 10.1093/sf/soae018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/12/2023] [Accepted: 11/23/2023] [Indexed: 04/20/2024]
Abstract
Birth weight is a robust predictor of valued life course outcomes, emphasizing the importance of prenatal development. But does birth weight act as a proxy for environmental conditions in utero, or do biological processes surrounding birth weight themselves play a role in healthy development? To answer this question, we leverage variation in birth weight that is, within families, orthogonal to prenatal environmental conditions: one's genes. We construct polygenic scores in two longitudinal studies (Born in Bradford, N = 2008; Wisconsin Longitudinal Study, N = 8488) to empirically explore the molecular genetic correlates of birth weight. A 1 standard deviation increase in the polygenic score is associated with an ~100-grams increase in birth weight and a 1.4 pp (22 percent) decrease in low birth weight probability. Sibling comparisons illustrate that this association largely represents a causal effect. The polygenic score-birth weight association is increased for children who spend longer in the womb and whose mothers have higher body mass index, though we find no differences across maternal socioeconomic status. Finally, the polygenic score affects social and cognitive outcomes, suggesting that birth weight is itself related to healthy prenatal development.
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Affiliation(s)
- Sam Trejo
- Princeton University, Department of Sociology and Office of Population Research, United States
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Zhang M, Jiang Z, Zhao K, Zhang Y, Xu M, Xu X. Effects of polygenes, parent-child relationship and frustration on junior high school students' aggressive behaviors. Psych J 2024; 13:265-275. [PMID: 38151799 PMCID: PMC10990803 DOI: 10.1002/pchj.717] [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: 06/24/2023] [Accepted: 10/24/2023] [Indexed: 12/29/2023]
Abstract
The effects of the interaction between polygenes and the parent-child relationship on junior high school students' aggressive behaviors were explored through the frameworks of gene-endophenotype-behavior and neurophysiological basis. A total of 892 junior high school students participated in this study. They were asked to complete self-reported questionnaires, and saliva samples were collected. Results showed that 5-HTTLPR, MAOA-uVNTR, COMT (rs4680), and Taq1 (rs1800497) of the DRD2 gene affected students' aggressive behaviors in an accumulative way. The polygenic risk score explained 3.4% of boys' aggression and 1.1% of girls' aggression. The interactions between polygenic risk score and parent-child conflict significantly affected the aggressive behaviors of male students, but did not show any significant effect on those of female students. The interactional effect of polygenic risk score and parent-child conflict on junior high school students' aggressive behaviors was completely mediated by frustration. However, the interaction effect of polygenic risk score and parent-child affinity on aggression was not affected by frustration. This study helps us better understand junior high school students' aggressive behaviors and promotes the prevention and correction of adolescents' problem behaviors.
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Affiliation(s)
- Minghao Zhang
- School of Educational ScienceLudong UniversityYantaiChina
- Collaborative Innovation Center for the Mental Health of Youth from the Era of Conversion of New and Old Kinetic Energy along the Yellow River Basin, Ludong UniversityYantaiChina
| | - Zhenli Jiang
- College of Safety and Environmental EngineeringShandong University of Science and TechnologyQingdaoChina
| | - Kedi Zhao
- Factor‐Inwentash Faculty of Social WorkUniversity of TorontoTorontoOntarioCanada
| | - Yaohua Zhang
- School of Educational ScienceLudong UniversityYantaiChina
- Collaborative Innovation Center for the Mental Health of Youth from the Era of Conversion of New and Old Kinetic Energy along the Yellow River Basin, Ludong UniversityYantaiChina
| | - Min Xu
- School of Educational ScienceLudong UniversityYantaiChina
- Collaborative Innovation Center for the Mental Health of Youth from the Era of Conversion of New and Old Kinetic Energy along the Yellow River Basin, Ludong UniversityYantaiChina
| | - Xiaohui Xu
- School of Educational ScienceLudong UniversityYantaiChina
- Collaborative Innovation Center for the Mental Health of Youth from the Era of Conversion of New and Old Kinetic Energy along the Yellow River Basin, Ludong UniversityYantaiChina
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5
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Graf GHJ, Aiello AE, Caspi A, Kothari M, Liu H, Moffitt TE, Muennig PA, Ryan CP, Sugden K, Belsky DW. Educational Mobility, Pace of Aging, and Lifespan Among Participants in the Framingham Heart Study. JAMA Netw Open 2024; 7:e240655. [PMID: 38427354 PMCID: PMC10907927 DOI: 10.1001/jamanetworkopen.2024.0655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 01/04/2024] [Indexed: 03/02/2024] Open
Abstract
Importance People who complete more education live longer lives with better health. New evidence suggests that these benefits operate through a slowed pace of biological aging. If so, measurements of the pace of biological aging could offer intermediate end points for studies of how interventions to promote education will affect healthy longevity. Objective To test the hypothesis that upward educational mobility is associated with a slower pace of biological aging and increased longevity. Design, Setting, and Participants This prospective cohort study analyzed data from 3 generations of participants in the Framingham Heart Study: (1) the original cohort, enrolled beginning in 1948; (2) the Offspring cohort, enrolled beginning in 1971; and (3) the Gen3 cohort, enrolled beginning in 2002. A 3-generation database was constructed to quantify intergenerational educational mobility. Mobility data were linked with blood DNA-methylation data collected from the Offspring cohort in 2005 to 2008 (n = 1652) and the Gen3 cohort in 2009 to 2011 (n = 1449). Follow-up is ongoing. Data analysis was conducted from June 2022 to November 2023 using data obtained from the National Institutes of Health database of Genotypes and Phenotypes (dbGaP). Exposure Educational mobility was measured by comparing participants' educational outcomes with those of their parents. Main Outcomes and Measures The pace of biological aging was measured from whole-blood DNA-methylation data using the DunedinPACE epigenetic clock. For comparison purposes, the analysis was repeated using 4 other epigenetic clocks. Survival follow-up was conducted through 2019. Results This study analyzed data from 3101 participants from the Framingham Heart Study; 1652 were in the Offspring cohort (mean [SD] age, 65.57 [9.22] years; 764 [46.2%] male) and 1449 were in the Gen3 cohort (mean [SD] age, 45.38 [7.83] years; 691 [47.7%] male). Participants who were upwardly mobile in educational terms tended to have slower pace of aging in later life (r = -0.18 [95% CI, -0.23 to -0.13]; P < .001). This pattern of association was similar across generations and held in within-family sibling comparisons. There were 402 Offspring cohort participants who died over the follow-up period. Upward educational mobility was associated with lower mortality risk (hazard ratio, 0.89 [95% CI, 0.81 to 0.98]; P = .01). Slower pace of aging accounted for approximately half of this association. Conclusions and Relevance This cohort study's findings support the hypothesis that interventions to promote educational attainment may slow the pace of biological aging and promote longevity. Epigenetic clocks have potential as near-term outcome measures of intervention effects on healthy aging. Experimental evidence is needed to confirm findings.
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Affiliation(s)
- Gloria H. J. Graf
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
- Robert N. Butler Columbia Aging Center, New York, New York
| | - Allison E. Aiello
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
- Robert N. Butler Columbia Aging Center, New York, New York
| | - Avshalom Caspi
- Department of Psychology & Neuroscience, Duke University, Durham, North Carolina
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina
- PROMENTA, University of Oslo, Oslo, Norway
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, King’s College London, London, United Kingdom
| | - Meeraj Kothari
- Robert N. Butler Columbia Aging Center, New York, New York
| | - Hexuan Liu
- School of Criminal Justice, University of Cincinnati, Cincinnati, Ohio
- Institute for Interdisciplinary Data Science, University of Cincinnati, Cincinnati, Ohio
| | - Terrie E. Moffitt
- Department of Psychology & Neuroscience, Duke University, Durham, North Carolina
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina
- PROMENTA, University of Oslo, Oslo, Norway
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, King’s College London, London, United Kingdom
| | - Peter A. Muennig
- Department of Health Policy and Management, Columbia University Mailman School of Public Health, New York, New York
| | - Calen P. Ryan
- Robert N. Butler Columbia Aging Center, New York, New York
| | - Karen Sugden
- Department of Psychology & Neuroscience, Duke University, Durham, North Carolina
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina
| | - Daniel W. Belsky
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
- Robert N. Butler Columbia Aging Center, New York, New York
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Fletcher J, Wu Y, Li T, Lu Q. Interpreting polygenic score effects in sibling analysis. PLoS One 2024; 19:e0282212. [PMID: 38358994 PMCID: PMC10868763 DOI: 10.1371/journal.pone.0282212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 02/09/2023] [Indexed: 02/17/2024] Open
Abstract
Researchers often claim that sibling analysis can be used to separate causal genetic effects from the assortment of biases that contaminate most downstream genetic studies (e.g. polygenic score predictors). Indeed, typical results from sibling analysis show large (>50%) attenuations in the associations between polygenic scores and phenotypes compared to non-sibling analysis, consistent with researchers' expectations about bias reduction. This paper explores these expectations by using family (quad) data and simulations that include indirect genetic effect processes and evaluates the ability of sibling analysis to uncover direct genetic effects of polygenic scores. We find that sibling analysis, in general, fail to uncover direct genetic effects; indeed, these models have both upward and downward biases that are difficult to sign in typical data. When genetic nurture effects exist, sibling analysis creates "measurement error" that attenuates associations between polygenic scores and phenotypes. As the correlation between direct and indirect effect changes, this bias can increase or decrease. Our findings suggest that interpreting results from sibling analysis aimed at uncovering direct genetic effects should be treated with caution.
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Affiliation(s)
- Jason Fletcher
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, United States of America
| | - Yuchang Wu
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI, United States of America
| | - Tianchang Li
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI, United States of America
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, United States of America
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Aw AJ, McRae J, Rahmani E, Song YS. Highly parameterized polygenic scores tend to overfit to population stratification via random effects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.27.577589. [PMID: 38352303 PMCID: PMC10862757 DOI: 10.1101/2024.01.27.577589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Polygenic scores (PGSs), increasingly used in clinical settings, frequently include many genetic variants, with performance typically peaking at thousands of variants. Such highly parameterized PGSs often include variants that do not pass a genome-wide significance threshold. We propose a mathematical perspective that renders the effects of many of these non-significant variants random rather than causal, with the randomness capturing population structure. We devise methods to assess variant effect randomness and population stratification bias. Applying these methods to 141 traits from the UK Biobank, we find that, for many PGSs, the effects of non-significant variants are considerably random, with the extent of randomness associated with the degree of overfitting to population structure of the discovery cohort. Our findings explain why highly parameterized PGSs simultaneously have superior cohort-specific performance and limited generalizability, suggesting the critical need for variant randomness tests in PGS evaluation. Supporting code and a dashboard are available at https://github.com/songlab-cal/StratPGS.
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Affiliation(s)
- Alan J. Aw
- Department of Statistics, University of California, Berkeley
- Center for Computational Biology, University of California, Berkeley
- Artificial Intelligence Laboratory, Illumina Inc
| | - Jeremy McRae
- Artificial Intelligence Laboratory, Illumina Inc
| | - Elior Rahmani
- Department of Computational Medicine, University of California, Los Angeles
| | - Yun S. Song
- Department of Statistics, University of California, Berkeley
- Center for Computational Biology, University of California, Berkeley
- Computer Science Division, University of California, Berkeley
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8
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Martschenko DO, Matthews LJ, Sabatello M. Social and Behavioral Genomics: What Does It Mean for Pediatrics? J Pediatr 2024; 264:113735. [PMID: 37722558 DOI: 10.1016/j.jpeds.2023.113735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/08/2023] [Accepted: 09/13/2023] [Indexed: 09/20/2023]
Affiliation(s)
| | - Lucas J Matthews
- Department of Psychiatry, Columbia University, New York, NY; The Hastings Center, Garrison, NY; Research Foundation for Mental Hygiene, New York, NY
| | - Maya Sabatello
- Center for Precision Medicine and Genomics, Department of Medicine, Columbia University, New York, NY; Division of Ethics, Department of Medical Humanities and Ethics, Columbia University, New York, NY
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Koellinger PD, Okbay A, Kweon H, Schweinert A, Linnér RK, Goebel J, Richter D, Reiber L, Zweck BM, Belsky DW, Biroli P, Mata R, Tucker-Drob EM, Harden KP, Wagner G, Hertwig R. Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G). PLoS One 2023; 18:e0294896. [PMID: 38019829 PMCID: PMC10686514 DOI: 10.1371/journal.pone.0294896] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 11/12/2023] [Indexed: 12/01/2023] Open
Abstract
The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment.
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Affiliation(s)
- Philipp D. Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Annemarie Schweinert
- Department of Economics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Richard Karlsson Linnér
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Economics, Leiden Law School, Leiden University, Leiden, The Netherlands
| | - Jan Goebel
- German Socio-Economic Panel Study, Deutsches Institut für Wirtschaftsforschung (DIW Berlin), Berlin, Germany
| | - David Richter
- Educational Science and Psychology, Freie Universität Berlin, Berlin, Germany
- SHARE Berlin, Berlin, Germany
| | - Lisa Reiber
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
| | | | - Daniel W. Belsky
- Department of Epidemiology and Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York, United States of America
- PROMENTA Center, University of Oslo, Oslo, Norway
| | - Pietro Biroli
- Department of Economics, University of Bologna, Bologna, Italy
| | - Rui Mata
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
- Faculty of Psychology, University of Basel, Basel, Switzerland
| | - Elliot M. Tucker-Drob
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, Texas, United States of America
| | - K. Paige Harden
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, Texas, United States of America
| | - Gert Wagner
- Educational Science and Psychology, Freie Universität Berlin, Berlin, Germany
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
- Federal Institute for Population Research, Wiesbaden, Germany
| | - Ralph Hertwig
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
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Buedo P, Bianchini A, Klas K, Waligora M. Bioethics of somatic gene therapy: what do we know so far? Curr Med Res Opin 2023; 39:1355-1365. [PMID: 37772315 DOI: 10.1080/03007995.2023.2257600] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 09/07/2023] [Indexed: 09/30/2023]
Abstract
OBJECTIVE To provide a systematic overview of bioethical debate on somatic gene therapy as documented in the scientific literature. METHODS We performed a systematic review of reasons, following Strech and Sofaer approach, which is a method to systematically identify and classify arguments (reasons) used in the scientific literature. We identified 217 eligible publications retrieved from PubMed, Lilacs, PhilPapers, and Google Scholar. A meta-synthesis was performed to analyze the data. RESULTS We extracted 189 arguments. Arguments were grouped into 23 categories. Twelve categories were classified as research-related, including the risk/benefit ratio, priorities and limits, informed consent, review, and monitoring. Eleven were classified as society-related, including population impact, human identity, public perception, human health. CONCLUSION Our study provides a database of existing challenges and arguments of somatic gene therapy and may serve as the basis of normative analysis. By presenting collected arguments, we contribute to the discussion about the ethics and social dimensions of somatic gene therapy.
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Affiliation(s)
- Paola Buedo
- Research Ethics in Medicine Study Group (REMEDY), Jagiellonian University Medical College, Krakow, Poland
| | - Alahi Bianchini
- Instituto de Investigaciones Jurídicas y Sociales Ambrosio Lucas Gioja, Universidad de Buenos Aires, Buenos Aires, Argentina - Programa de Bioética, FLACSO Argentina, Buenos Aires, Argentina
| | - Katarzyna Klas
- Research Ethics in Medicine Study Group (REMEDY), Jagiellonian University Medical College, Krakow, Poland
| | - Marcin Waligora
- Research Ethics in Medicine Study Group (REMEDY), Jagiellonian University Medical College, Krakow, Poland
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Burt CH. Polygenic scores for social science: Clarification, consensus, and controversy. Behav Brain Sci 2023; 46:e232. [PMID: 37694994 PMCID: PMC10723835 DOI: 10.1017/s0140525x23000845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
In this response, I focus on clarifying my arguments, highlighting consensus, and addressing competing views about the utility of polygenic scores (PGSs) for social science. I also discuss an assortment of expansions to my arguments and suggest alternative approaches. I conclude by reiterating the need for caution and appropriate scientific skepticism.
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Affiliation(s)
- Callie H Burt
- Department of Criminal Justice & Criminology, Center for Research on Interpersonal Violence (CRIV), Georgia State University, Atlanta, GA, USA ; www.callieburt.org
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12
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Moore DS. Polygenic scores ignore development and epigenetics, dramatically reducing their value. Behav Brain Sci 2023; 46:e220. [PMID: 37695006 DOI: 10.1017/s0140525x22002473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Polygenic scores cannot elucidate the mechanisms that produce behavioral phenotypes (including "intelligence"). Therefore, they are unlikely to yield helpful interventions. Moreover, they are poor predictors of individuals' developmental outcomes. Burt's critique is well-supported by the details of molecular biology. Specifically, experiences affect epigenetic factors that influence phenotypes via how the genome functions, a fact that lends support to Burt's conclusions.
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Affiliation(s)
- David S Moore
- Psychology Field Group, Pitzer College, Claremont, CA, ; http://pzacad.pitzer.edu/~dmoore/
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Freitag EW, Kelsey CM. Taking a lifespan approach to polygenic scores. Behav Brain Sci 2023; 46:e215. [PMID: 37694999 PMCID: PMC10519617 DOI: 10.1017/s0140525x2200245x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
This commentary is a call to action for researchers to create and use genome-wide association studies (GWASs) with previously missed age groups (e.g., infancy, elderly), which will improve our ability to ask important developmental questions using genetic data to trace pathways across the lifespan.
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Affiliation(s)
- Eloise W Freitag
- Department of Molecular & Cellular Biology, Harvard University, Cambridge, MA,
| | - Caroline M Kelsey
- Department of Pediatrics, Division of Developmental Medicine, Boston Children's Hospital, Brookline, MA,
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Morrison CL, Winiger EA, Rieselbach MM, Vetter C, Wright KP, LeBourgeois MK, Friedman NP. Sleep Health at the Genomic Level: Six Distinct Factors and Their Relationships With Psychopathology. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:530-540. [PMID: 37519468 PMCID: PMC10382696 DOI: 10.1016/j.bpsgos.2022.07.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/01/2022] [Accepted: 07/07/2022] [Indexed: 11/22/2022] Open
Abstract
Background Poor sleep is associated with many negative health outcomes, including multiple dimensions of psychopathology. In the past decade, sleep researchers have advocated for focusing on the concept of sleep health as a modifiable health behavior to mitigate or prevent these outcomes. Sleep health dimensions often include sleep efficiency, duration, satisfaction, regularity, timing, and daytime alertness. However, there is no consensus on how to best operationalize sleep health at the phenotypic and genetic levels. In some studies, specific sleep health domains were examined individually, while in others, sleep health domains were examined together (e.g., with an aggregate sleep health score). Methods Here, we compared alternative sleep health factor models using genomic structural equation modeling on summary statistics from previously published genome-wide association studies of self-reported and actigraphic sleep measures with effective sample sizes up to 452,633. Results Our best-fitting sleep health model had 6 correlated genetic factors pertaining to 6 sleep health domains: circadian preference, efficiency, alertness, duration, noninsomnia, and regularity. All sleep health factors were significantly correlated (|rgs| = 0.11-0.51), except for the circadian preference factor with duration and noninsomnia. Better sleep health was generally significantly associated with lower genetic liability for psychopathology (|rgs| = 0.05-0.48), yet the 6 sleep health factors showed divergent patterns of associations with different psychopathology factors, especially when controlling for covariance among the sleep health factors. Conclusions These results provide evidence for genetic separability of sleep health constructs and their differentiation with respect to associations with mental health.
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Affiliation(s)
- Claire L. Morrison
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
| | - Evan A. Winiger
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Maya M. Rieselbach
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
| | - Céline Vetter
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado
| | - Kenneth P. Wright
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado
| | | | - Naomi P. Friedman
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
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15
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Bonilla C, Herrera G, Sans M. What can Mendelian randomization contribute to biological anthropology? AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2023. [PMID: 37114747 DOI: 10.1002/ajpa.24750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 03/27/2023] [Accepted: 04/09/2023] [Indexed: 04/29/2023]
Abstract
Uncovering causal relationships between exposures and outcomes can be difficult in observational studies because of the potential for confounding and reverse causation to produce biased estimates. Conversely, randomized controlled trials (RCTs) provide the strongest evidence for causality but they are not always feasible. Mendelian randomization (MR) is a method that aims to strengthen causal inference using genetic variants as proxies or instrumental variables (IVs) for exposures, to overcome the above-mentioned biases. Since allele segregation occurs at random from parents to offspring, and alleles for a trait assort independently from those for other traits, MR studies have frequently been compared to "natural" RCTs. In biological anthropology (BA) relationships between variables of interest are usually evaluated using observational data, often remaining descriptive, and other approaches to causal inference have seldom been implemented. Here, we propose the use of MR to investigate cause and effect relationships in BA studies and provide examples to show how that can be done across areas of BA relevance, such as adaptation to the environment, nutrition and life history theory. While we consider MR a useful addition to the biological anthropologist's toolbox, we advocate the adoption of a wide range of methods, affected by different types of biases, in order to better answer the important causal questions for the discipline.
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Affiliation(s)
- Carolina Bonilla
- Departamento de Medicina Preventiva, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Guadalupe Herrera
- Departamento de Antropología Biológica, Facultad de Humanidades y Ciencias de la Educación, Universidad de la República, Montevideo, Uruguay
- Departamento de Métodos Cuantitativos, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
- Departamento de Medicina Preventiva y Social, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Mónica Sans
- Departamento de Antropología Biológica, Facultad de Humanidades y Ciencias de la Educación, Universidad de la República, Montevideo, Uruguay
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16
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Herle M, Pickles A, Pain O, Viner R, Pingault JB, De Stavola BL. Could interventions on physical activity mitigate genomic liability for obesity? Applying the health disparity framework in genetically informed studies. Eur J Epidemiol 2023; 38:403-412. [PMID: 36905531 PMCID: PMC10082115 DOI: 10.1007/s10654-023-00980-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/24/2023] [Indexed: 03/12/2023]
Abstract
Polygenic scores (PGS) are now commonly available in longitudinal cohort studies, leading to their integration into epidemiological research. In this work, our aim is to explore how polygenic scores can be used as exposures in causal inference-based methods, specifically mediation analyses. We propose to estimate the extent to which the association of a polygenic score indexing genetic liability to an outcome could be mitigated by a potential intervention on a mediator. To do this this, we use the interventional disparity measure approach, which allows us to compare the adjusted total effect of an exposure on an outcome, with the association that would remain had we intervened on a potentially modifiable mediator. As an example, we analyse data from two UK cohorts, the Millennium Cohort Study (MCS, N = 2575) and the Avon Longitudinal Study of Parents and Children (ALSPAC, N = 3347). In both, the exposure is genetic liability for obesity (indicated by a PGS for BMI), the outcome is late childhood/early adolescent BMI, and the mediator and potential intervention target is physical activity, measured between exposure and outcome. Our results suggest that a potential intervention on child physical activity can mitigate some of the genetic liability for childhood obesity. We propose that including PGSs in a health disparity measure approach, and causal inference-based methods more broadly, is a valuable addition to the study of gene-environment interplay in complex health outcomes.
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Affiliation(s)
- Moritz Herle
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, UK.
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK.
| | - Andrew Pickles
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, UK
| | - Oliver Pain
- Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Russell Viner
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Jean-Baptiste Pingault
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
- Division of Psychology and Language Sciences, Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Bianca L De Stavola
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
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17
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Abdellaoui A, Yengo L, Verweij KJH, Visscher PM. 15 years of GWAS discovery: Realizing the promise. Am J Hum Genet 2023; 110:179-194. [PMID: 36634672 PMCID: PMC9943775 DOI: 10.1016/j.ajhg.2022.12.011] [Citation(s) in RCA: 75] [Impact Index Per Article: 75.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
It has been 15 years since the advent of the genome-wide association study (GWAS) era. Here, we review how this experimental design has realized its promise by facilitating an impressive range of discoveries with remarkable impact on multiple fields, including population genetics, complex trait genetics, epidemiology, social science, and medicine. We predict that the emergence of large-scale biobanks will continue to expand to more diverse populations and capture more of the allele frequency spectrum through whole-genome sequencing, which will further improve our ability to investigate the causes and consequences of human genetic variation for complex traits and diseases.
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Affiliation(s)
- Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - Loic Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
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18
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Laricchiuta D, Panuccio A, Picerni E, Biondo D, Genovesi B, Petrosini L. The body keeps the score: The neurobiological profile of traumatized adolescents. Neurosci Biobehav Rev 2023; 145:105033. [PMID: 36610696 DOI: 10.1016/j.neubiorev.2023.105033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 12/13/2022] [Accepted: 01/02/2023] [Indexed: 01/05/2023]
Abstract
Trauma-related disorders are debilitating psychiatric conditions that affect people who have directly or indirectly witnessed adversities. Experiencing multiple types of traumas appears to be common during childhood, and even more so during adolescence. Dramatic brain/body transformations occurring during adolescence may provide a highly responsive substrate to external stimuli and lead to trauma-related vulnerability conditions, such as internalizing (anxiety, depression, anhedonia, withdrawal) and externalizing (aggression, delinquency, conduct disorders) problems. Analyzing relations among neuronal, endocrine, immune, and biochemical signatures of trauma and internalizing and externalizing behaviors, including the role of personality traits in shaping these conducts, this review highlights that the marked effects of traumatic experience on the brain/body involve changes at nearly every level of analysis, from brain structure, function and connectivity to endocrine and immune systems, from gene expression (including in the gut) to the development of personality.
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Affiliation(s)
- Daniela Laricchiuta
- Department of Philosophy, Social Sciences & Education, University of Perugia, Perugia, Italy.
| | - Anna Panuccio
- Laboratory of Experimental and Behavioral Neurophysiology, IRCCS Fondazione Santa Lucia, Rome, Italy; Department of Psychology, University Sapienza of Rome, Rome, Italy
| | - Eleonora Picerni
- Laboratory of Experimental and Behavioral Neurophysiology, IRCCS Fondazione Santa Lucia, Rome, Italy; Department of Neuroscience Imaging and Clinical Sciences, University "G. d'Annunzio" of Chieti-Pescara, Chieti, Italy
| | | | | | - Laura Petrosini
- Laboratory of Experimental and Behavioral Neurophysiology, IRCCS Fondazione Santa Lucia, Rome, Italy
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19
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Valge M, Meitern R, Hõrak P. Mothers of small-bodied children and fathers of vigorous sons live longer. Front Public Health 2023; 11:1057146. [PMID: 36761140 PMCID: PMC9905732 DOI: 10.3389/fpubh.2023.1057146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 01/09/2023] [Indexed: 01/27/2023] Open
Abstract
Life-history traits (traits directly related to survival and reproduction) co-evolve and materialize through physiology and behavior. Accordingly, lifespan can be hypothesized as a potentially informative marker of life-history speed that subsumes the impact of diverse morphometric and behavioral traits. We examined associations between parental longevity and various anthropometric traits in a sample of 4,000-11,000 Estonian children in the middle of the 20th century. The offspring phenotype was used as a proxy measure of parental genotype, so that covariation between offspring traits and parental longevity (defined as belonging to the 90th percentile of lifespan) could be used to characterize the aggregation between longevity and anthropometric traits. We predicted that larger linear dimensions of offspring associate with increased parental longevity and that testosterone-dependent traits associate with reduced paternal longevity. Twelve of 16 offspring traits were associated with mothers' longevity, while three traits (rate of sexual maturation of daughters and grip strength and lung capacity of sons) robustly predicted fathers' longevity. Contrary to predictions, mothers of children with small bodily dimensions lived longer, and paternal longevity was not linearly associated with their children's body size (or testosterone-related traits). Our study thus failed to find evidence that high somatic investment into brain and body growth clusters with a long lifespan across generations, and/or that such associations can be detected on the basis of inter-generational phenotypic correlations.
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20
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Menta G, Lepinteur A, Clark AE, Ghislandi S, D'Ambrosio C. Maternal genetic risk for depression and child human capital. JOURNAL OF HEALTH ECONOMICS 2023; 87:102718. [PMID: 36565586 DOI: 10.1016/j.jhealeco.2022.102718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 12/09/2022] [Accepted: 12/09/2022] [Indexed: 06/17/2023]
Abstract
We here address the causal relationship between the maternal genetic risk for depression and child human capital using UK birth-cohort data. We find that an increase of one standard deviation (SD) in the maternal polygenic risk score for depression reduces their children's cognitive and non-cognitive skill scores by 5 to 7% of a SD throughout adolescence. Our results are robust to a battery of sensitivity tests addressing, among others, concerns about pleiotropy and dynastic effects. Our Gelbach decomposition analysis suggests that the strongest mediator is genetic nurture (through maternal depression itself), with genetic inheritance playing only a marginal role.
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Affiliation(s)
- Giorgia Menta
- Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg
| | | | - Andrew E Clark
- University of Luxembourg, Luxembourg; Paris School of Economics - CNRS, France
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21
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Asbury K, McBride T, Bawn R. Can genomic research make a useful contribution to social policy? ROYAL SOCIETY OPEN SCIENCE 2022; 9:220873. [PMID: 36425516 PMCID: PMC9682296 DOI: 10.1098/rsos.220873] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
As genetic research into outcomes beyond health gathers pace, largely through the use of genome-wide association studies, interest from policy-makers has grown. In the last year, two UK reports have explored the policy implications of genomic research, one from the UK Government Office for Science and one from the Early Intervention Foundation. In this article, we explore areas of consensus between these two reports and use them to propose priorities for policy-makers as we prepare for what some have termed a 'genetic revolution'. Both reports agree on two clear recommendations for science and policy communities. One of these relates to public education and engagement, and the other to ensuring that genomic databases are ancestrally diverse. Both reports agree that-even if it is found to be a viable and ethical idea in the medium-term future-DNA data should not be incorporated into social policy before these two issues have been comprehensively addressed. In the article, we argue that scientists are taking the lead on tackling the diversity deficit but that there is a clear role for policy-makers to play in addressing low genetic literacy in society, and that this is a matter of urgency.
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Affiliation(s)
- Kathryn Asbury
- Department of Education, University of York, York YO10 5DD, UK
| | - Tom McBride
- Ending Youth Violence Lab, Behavioural Insights Team, London SW1H 9NP, UK
| | - Rosie Bawn
- Department of Education, University of York, York YO10 5DD, UK
- University of Exeter, Stocker Road, Exeter EX4 4PY, UK
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22
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Reply to Qiu et al.: Hunting for leadership "causal" genes: Mission possible? Proc Natl Acad Sci U S A 2022; 119:e2208115119. [PMID: 35787186 PMCID: PMC9303985 DOI: 10.1073/pnas.2208115119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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23
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Holden LR, Haughbrook R, Hart SA. Developmental behavioral genetics research on school achievement is missing vulnerable children, to our detriment. New Dir Child Adolesc Dev 2022; 2022:47-55. [PMID: 36162231 PMCID: PMC9713684 DOI: 10.1002/cad.20485] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Gene-environment processes tell us how genetic predispositions and environments work together to influence children in schools. One type of gene-environment process that has been extensively studied using behavioral genetics methods is a gene-by-environment interaction. A gene-by-environment interaction shows us when the effect of your context on a phenotype differs depending on your genetic predispositions, or vice versa, when the effect of your genetic predispositions on a phenotype differs depending on your context. Developmental behavioral geneticists interested in children's school achievement have examined many different contexts within the gene-by-environment interaction model, including contexts measured from within children's home and school environments. However, this work has been overwhelmingly focused on WEIRD samples children, leaving us with non-inclusive scientific evidence. This can lead to detrimental outcomes when we overgeneralize this non-inclusive scientific evidence to racialized groups. We conclude with a call to include racialized children in more research samples.
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Affiliation(s)
| | | | - Sara A Hart
- Florida State University, Tallahassee, Florida, USA
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24
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Kweon H, Aydogan G, Dagher A, Bzdok D, Ruff CC, Nave G, Farah MJ, Koellinger PD. Human brain anatomy reflects separable genetic and environmental components of socioeconomic status. SCIENCE ADVANCES 2022; 8:eabm2923. [PMID: 35584223 PMCID: PMC9116589 DOI: 10.1126/sciadv.abm2923] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Socioeconomic status (SES) correlates with brain structure, a relation of interest given the long-observed relations of SES to cognitive abilities and health. Yet, major questions remain open, in particular, the pattern of causality that underlies this relation. In an unprecedently large study, here, we assess genetic and environmental contributions to SES differences in neuroanatomy. We first establish robust SES-gray matter relations across a number of brain regions, cortical and subcortical. These regional correlates are parsed into predominantly genetic factors and those potentially due to the environment. We show that genetic effects are stronger in some areas (prefrontal cortex, insula) than others. In areas showing less genetic effect (cerebellum, lateral temporal), environmental factors are likely to be influential. Our results imply a complex interplay of genetic and environmental factors that influence the SES-brain relation and may eventually provide insights relevant to policy.
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Affiliation(s)
- Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands
| | - Gökhan Aydogan
- Zürich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, 8006 Zürich, Switzerland
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montreal Neurological Institute (MNI), McGill University, Montreal, QC H3A 2B4, Canada
| | - Danilo Bzdok
- McConnell Brain Imaging Centre, Montreal Neurological Institute (MNI), McGill University, Montreal, QC H3A 2B4, Canada
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, QC H3A 2B4, Canada
- School of Computer Science, McGill University, Montreal, QC H3A 2A7, Canada
- Mila-Quebec Artificial Intelligence Institute, Montreal, QC H2S 3H1, Canada
| | - Christian C. Ruff
- Zürich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, 8006 Zürich, Switzerland
| | - Gideon Nave
- Marketing Department, the Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Martha J. Farah
- Center for Neuroscience & Society, University of Pennsylvania, Philadelphia, PA 19104, USA
- Corresponding author. (M.J.F.); (P.D.K.)
| | - Philipp D. Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI 53706, USA
- Corresponding author. (M.J.F.); (P.D.K.)
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25
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Burt CH. Challenging the utility of polygenic scores for social science: Environmental confounding, downward causation, and unknown biology. Behav Brain Sci 2022; 46:e207. [PMID: 35551690 PMCID: PMC9653522 DOI: 10.1017/s0140525x22001145] [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: 11/06/2022]
Abstract
The sociogenomics revolution is upon us, we are told. Whether revolutionary or not, sociogenomics is poised to flourish given the ease of incorporating polygenic scores (or PGSs) as "genetic propensities" for complex traits into social science research. Pointing to evidence of ubiquitous heritability and the accessibility of genetic data, scholars have argued that social scientists not only have an opportunity but a duty to add PGSs to social science research. Social science research that ignores genetics is, some proponents argue, at best partial and likely scientifically flawed, misleading, and wasteful. Here, I challenge arguments about the value of genetics for social science and with it the claimed necessity of incorporating PGSs into social science models as measures of genetic influences. In so doing, I discuss the impracticability of distinguishing genetic influences from environmental influences because of non-causal gene-environment correlations, especially population stratification, familial confounding, and downward causation. I explain how environmental effects masquerade as genetic influences in PGSs, which undermines their raison d'être as measures of genetic propensity, especially for complex socially contingent behaviors that are the subject of sociogenomics. Additionally, I draw attention to the partial, unknown biology, while highlighting the persistence of an implicit, unavoidable reductionist genes versus environments approach. Leaving sociopolitical and ethical concerns aside, I argue that the potential scientific rewards of adding PGSs to social science are few and greatly overstated and the scientific costs, which include obscuring structural disadvantages and cultural influences, outweigh these meager benefits for most social science applications.
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Affiliation(s)
- Callie H Burt
- Department of Criminal Justice & Criminology, Center for Research on Interpersonal Violence (CRIV), Georgia State University, Atlanta, GA, USA ; www.callieburt.org
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26
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Sauce B, Liebherr M, Judd N, Klingberg T. The impact of digital media on children's intelligence while controlling for genetic differences in cognition and socioeconomic background. Sci Rep 2022; 12:7720. [PMID: 35545630 PMCID: PMC9095723 DOI: 10.1038/s41598-022-11341-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 04/12/2022] [Indexed: 12/17/2022] Open
Abstract
Digital media defines modern childhood, but its cognitive effects are unclear and hotly debated. We believe that studies with genetic data could clarify causal claims and correct for the typically unaccounted role of genetic predispositions. Here, we estimated the impact of different types of screen time (watching, socializing, or gaming) on children’s intelligence while controlling for the confounding effects of genetic differences in cognition and socioeconomic status. We analyzed 9855 children from the USA who were part of the ABCD dataset with measures of intelligence at baseline (ages 9–10) and after two years. At baseline, time watching (r = − 0.12) and socializing (r = − 0.10) were negatively correlated with intelligence, while gaming did not correlate. After two years, gaming positively impacted intelligence (standardized β = + 0.17), but socializing had no effect. This is consistent with cognitive benefits documented in experimental studies on video gaming. Unexpectedly, watching videos also benefited intelligence (standardized β = + 0.12), contrary to prior research on the effect of watching TV. Although, in a posthoc analysis, this was not significant if parental education (instead of SES) was controlled for. Broadly, our results are in line with research on the malleability of cognitive abilities from environmental factors, such as cognitive training and the Flynn effect.
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Affiliation(s)
- Bruno Sauce
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Magnus Liebherr
- Department of General Psychology: Cognition, University Duisburg-Essen, Duisburg, Germany
| | - Nicholas Judd
- Department of Neuroscience, Karolinska Institutet, Solna, Sweden
| | - Torkel Klingberg
- Department of Neuroscience, Karolinska Institutet, Solna, Sweden.
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27
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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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28
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Visscher PM. Genetics of cognitive performance, education and learning: from research to policy? NPJ SCIENCE OF LEARNING 2022; 7:8. [PMID: 35508631 PMCID: PMC9068617 DOI: 10.1038/s41539-022-00124-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 03/24/2022] [Indexed: 06/14/2023]
Affiliation(s)
- Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, 4072, Australia.
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29
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Isungset MA, Freese J, Andreassen OA, Lyngstad TH. Birth order differences in education originate in postnatal environments. PNAS NEXUS 2022; 1:pgac051. [PMID: 36713322 PMCID: PMC9802280 DOI: 10.1093/pnasnexus/pgac051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 04/27/2022] [Indexed: 02/01/2023]
Abstract
Siblings share many environments and much of their genetics. Yet, siblings turn out different. Intelligence and education are influenced by birth order, with earlier-born siblings outperforming later-borns. We investigate whether birth order differences in education are caused by biological differences present at birth, that is, genetic differences or in utero differences. Using family data that spans two generations, combining registry, survey, and genotype information, this study is based on the Norwegian Mother, Father, and Child Cohort Study (MoBa). We show that there are no genetic differences by birth order as captured by polygenic scores (PGSs) for educational attainment. Earlier-born have lower birth weight than later-born, indicating worse uterine environments. Educational outcomes are still higher for earlier-born children when we adjust for PGSs and in utero variables, indicating that birth order differences arise postnatally. Finally, we consider potential environmental influences, such as differences according to maternal age, parental educational attainment, and sibling genetic nurture. We show that birth order differences are not biological in origin, but pinning down their specific causes remains elusive.
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Affiliation(s)
- Martin Arstad Isungset
- Department of Sociology and Human Geography, University of Oslo, PO Box 1096, Blindern, 0317 Oslo, Norway
| | - Jeremy Freese
- Department of Sociology, Stanford University, Stanford, CA 94305, USA
| | - Ole A Andreassen
- Institute of Clinical Medicine, University of Oslo, PO Box 4956, Nydalen, 0424 Oslo, Norway
- NORMENT,Division of Mental Health and Addiction, Oslo University Hospital, Kirkeveien 166, 0450, Oslo, Norway
| | - Torkild Hovde Lyngstad
- Department of Sociology and Human Geography, University of Oslo, PO Box 1096, Blindern, 0317 Oslo, Norway
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30
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Chang CC, Cox DTC, Fan Q, Nghiem TPL, Tan CLY, Oh RRY, Lin BB, Shanahan DF, Fuller RA, Gaston KJ, Carrasco LR. People's desire to be in nature and how they experience it are partially heritable. PLoS Biol 2022; 20:e3001500. [PMID: 35113853 PMCID: PMC8812842 DOI: 10.1371/journal.pbio.3001500] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 11/29/2021] [Indexed: 01/08/2023] Open
Abstract
Nature experiences have been linked to mental and physical health. Despite the importance of understanding what determines individual variation in nature experience, the role of genes has been overlooked. Here, using a twin design (TwinsUK, number of individuals = 2,306), we investigate the genetic and environmental contributions to a person's nature orientation, opportunity (living in less urbanized areas), and different dimensions of nature experience (frequency and duration of public nature space visits and frequency and duration of garden visits). We estimate moderate heritability of nature orientation (46%) and nature experiences (48% for frequency of public nature space visits, 34% for frequency of garden visits, and 38% for duration of garden visits) and show their genetic components partially overlap. We also find that the environmental influences on nature experiences are moderated by the level of urbanization of the home district. Our study demonstrates genetic contributions to individuals' nature experiences, opening a new dimension for the study of human-nature interactions.
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Affiliation(s)
- Chia-Chen Chang
- Department of Biological Sciences, National University of Singapore, Singapore
| | - Daniel T C Cox
- Environment & Sustainability Institute, University of Exeter, Penryn, Cornwall, United Kingdom
| | - Qiao Fan
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore
| | | | - Claudia L Y Tan
- Department of Biological Sciences, National University of Singapore, Singapore
| | - Rachel Rui Ying Oh
- School of Biological Sciences, Centre for Biodiversity and Conservation Sciences, University of Queensland, Brisbane, Australia
| | - Brenda B Lin
- CSIRO Land & Water Flagship, Dutton Park, Queensland, Australia
| | - Danielle F Shanahan
- Centre for People and Nature, Zealandia Ecosanctuary, Wellington, New Zealand.,Victoria University of Wellington, Wellington, New Zealand
| | - Richard A Fuller
- School of Biological Sciences, Centre for Biodiversity and Conservation Sciences, University of Queensland, Brisbane, Australia
| | - Kevin J Gaston
- Environment & Sustainability Institute, University of Exeter, Penryn, Cornwall, United Kingdom
| | - L Roman Carrasco
- Department of Biological Sciences, National University of Singapore, Singapore
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31
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Winterton A, Bettella F, de Lange AMG, Haram M, Steen NE, Westlye LT, Andreassen OA, Quintana DS. Oxytocin-pathway polygenic scores for severe mental disorders and metabolic phenotypes in the UK Biobank. Transl Psychiatry 2021; 11:599. [PMID: 34824196 PMCID: PMC8616952 DOI: 10.1038/s41398-021-01725-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 09/26/2021] [Accepted: 10/19/2021] [Indexed: 02/07/2023] Open
Abstract
Oxytocin is a neuromodulator and hormone that is typically associated with social cognition and behavior. In light of its purported effects on social cognition and behavior, research has investigated its potential as a treatment for psychiatric illnesses characterized by social dysfunction, such as schizophrenia and bipolar disorder. While the results of these trials have been mixed, more recent evidence suggests that the oxytocin system is also linked with cardiometabolic conditions for which individuals with severe mental disorders are at a higher risk for developing. To investigate whether the oxytocin system has a pleiotropic effect on the etiology of severe mental illness and cardiometabolic conditions, we explored oxytocin's role in the shared genetic liability of schizophrenia, bipolar disorder, type-2 diabetes, and several phenotypes linked with cardiovascular disease and type 2 diabetes risk using a polygenic pathway-specific approach. Analysis of a large sample with about 480,000 individuals (UK Biobank) revealed statistically significant associations across the range of phenotypes analyzed. By comparing these effects to those of polygenic scores calculated from 100 random gene sets, we also demonstrated the specificity of many of these significant results. Altogether, our results suggest that the shared effect of oxytocin-system dysfunction could help partially explain the co-occurrence of social and cardiometabolic dysfunction in severe mental illnesses.
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Affiliation(s)
- Adriano Winterton
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Ann-Marie G de Lange
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Marit Haram
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nils Eiel Steen
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo and Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Daniel S Quintana
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo and Oslo University Hospital, Oslo, Norway.
- Department of Psychology, University of Oslo, Oslo, Norway.
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway.
- NevSom, Department of Rare Disorders, Oslo University Hospital, Oslo, Norway.
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32
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Chang CC, Nghiem TPL, Fan Q, Tan CLY, Oh RRY, Lin BB, Shanahan DF, Fuller RA, Gaston KJ, Carrasco LR. Genetic Contribution to Concern for Nature and Proenvironmental Behavior. Bioscience 2021. [DOI: 10.1093/biosci/biab103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Earth is undergoing a devastating extinction crisis caused by human impacts on nature, but only a fraction of society is strongly concerned and acting on the crisis. Understanding what determines people's concern for nature, environmental movement activism, and personal conservation behavior is fundamental if sustainability is to be achieved. Despite its potential importance, the study of the genetic contribution to concern for nature and proenvironmental behaviors has been neglected. Using a twin data set (N = 2312), we show moderate heritability (30%–40%) for concern for nature, environmental movement activism, and personal conservation behavior and high genetic correlations between them (.6–.7), suggesting a partially shared genetic basis. Our results shed light on the individual variation in sustainable behaviors, highlighting the importance of understanding both the environmental and genetic components in the pursuit of sustainability.
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Affiliation(s)
| | | | - Qiao Fan
- Duke-NUS Medical School, Singapore
| | | | - Rachel Rui Ying Oh
- Centre for Biodiversity and Conservation Sciences, University of Queensland, Brisbane, Australia
| | - Brenda B Lin
- CSIRO Land and Water Flagship, Dutton Park, Queensland, Australia
| | | | - Richard A Fuller
- Centre for Biodiversity and Conservation Sciences, University of Queensland, Brisbane, Australia
| | - Kevin J Gaston
- Environment and Sustainability Institute, University of Exeter, Penryn, United Kingdom
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33
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Ho TC, King LS. Mechanisms of neuroplasticity linking early adversity to depression: developmental considerations. Transl Psychiatry 2021; 11:517. [PMID: 34628465 PMCID: PMC8501358 DOI: 10.1038/s41398-021-01639-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 09/11/2021] [Accepted: 09/23/2021] [Indexed: 12/17/2022] Open
Abstract
Early exposure to psychosocial adversity is among the most potent predictors of depression. Because depression commonly emerges prior to adulthood, we must consider the fundamental principles of developmental neuroscience when examining how experiences of childhood adversity, including abuse and neglect, can lead to depression. Considering that both the environment and the brain are highly dynamic across the period spanning gestation through adolescence, the purpose of this review is to discuss and integrate stress-based models of depression that center developmental processes. We offer a general framework for understanding how psychosocial adversity in early life disrupts or calibrates the biobehavioral systems implicated in depression. Specifically, we propose that the sources and nature of the environmental input shaping the brain, and the mechanisms of neuroplasticity involved, change across development. We contend that the effects of adversity largely depend on the developmental stage of the organism. First, we summarize leading neurobiological models that focus on the effects of adversity on risk for mental disorders, including depression. In particular, we highlight models of allostatic load, acceleration maturation, dimensions of adversity, and sensitive or critical periods. Second, we expound on and review evidence for the formulation that distinct mechanisms of neuroplasticity are implicated depending on the timing of adverse experiences, and that inherent within certain windows of development are constraints on the sources and nature of these experiences. Finally, we consider other important facets of adverse experiences (e.g., environmental unpredictability, perceptions of one's experiences) before discussing promising research directions for the future of the field.
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Affiliation(s)
- Tiffany C Ho
- Department of Psychiatry and Behavioral Sciences and Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
| | - Lucy S King
- Department of Psychiatry and Behavioral Sciences, Tulane University School of Medicine, New Orleans, LA, USA
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
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34
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Visscher PM, Yengo L, Cox NJ, Wray NR. Discovery and implications of polygenicity of common diseases. Science 2021; 373:1468-1473. [PMID: 34554790 PMCID: PMC9945947 DOI: 10.1126/science.abi8206] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
The sequencing of the human genome has allowed the study of the genetic architecture of common diseases: the number of genomic variants that contribute to risk of disease and their joint frequency and effect size distribution. Common diseases are polygenic, with many loci contributing to phenotype, and the cumulative burden of risk alleles determines individual risk in conjunction with environmental factors. Most risk loci occur in noncoding regions of the genome regulating cell- and context-specific gene expression. Although the effect sizes of most risk alleles are small, their cumulative effects in individuals, quantified as a polygenic (risk) score, can identify people at increased risk of disease, thereby facilitating prevention or early intervention.
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Affiliation(s)
- Peter M. Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia,Corresponding author.
| | - Loic Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
| | - Nancy J. Cox
- Vanderbilt Genetics Institute and Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia,Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
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35
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36
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Boardman JD, Fletcher JM. Evaluating the Continued Integration of Genetics into Medical Sociology. JOURNAL OF HEALTH AND SOCIAL BEHAVIOR 2021; 62:404-418. [PMID: 34355610 PMCID: PMC8771926 DOI: 10.1177/00221465211032581] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The 2010 special issue of Journal of Health and Social Behavior, titled "Fifty Years of Medical Sociology," defined the contours of the medical sociological perspective. We use this as a backdrop to outline and assess the continued integration of genetics into medical sociology research. We contend that the explosion of genetic and epigenetic data in population health data sources has made the medical sociological perspective increasingly relevant to researchers outside of sociology, including public health, epidemiology, and quantitative genetics. We describe vast, underappreciated, and mostly unsolved challenges that limit the scientifically appropriate interest in incorporating genetics into existing paradigms. It is our hope that medical sociologists continue this integration but redouble efforts to maintain the core insights in social science research, such as the importance of environmental and structural (i.e., nonbiological) factors in determining health processes and outcomes and the use of rich, integrated, and rigorous empirical analyses.
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37
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Bann D. The scope of health injustice. Eur J Public Health 2021; 31:458-459. [PMID: 33523113 DOI: 10.1093/eurpub/ckaa230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- David Bann
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
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38
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“The elephant in the room”: social responsibility in the production of sociogenomics research. BIOSOCIETIES 2021; 17:713-731. [DOI: 10.1057/s41292-021-00239-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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39
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Wu Y, Zhong X, Lin Y, Zhao Z, Chen J, Zheng B, Li JJ, Fletcher JM, Lu Q. Estimating genetic nurture with summary statistics of multigenerational genome-wide association studies. Proc Natl Acad Sci U S A 2021; 118:e2023184118. [PMID: 34131076 PMCID: PMC8237646 DOI: 10.1073/pnas.2023184118] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Marginal effect estimates in genome-wide association studies (GWAS) are mixtures of direct and indirect genetic effects. Existing methods to dissect these effects require family-based, individual-level genetic, and phenotypic data with large samples, which is difficult to obtain in practice. Here, we propose a statistical framework to estimate direct and indirect genetic effects using summary statistics from GWAS conducted on own and offspring phenotypes. Applied to birth weight, our method showed nearly identical results with those obtained using individual-level data. We also decomposed direct and indirect genetic effects of educational attainment (EA), which showed distinct patterns of genetic correlations with 45 complex traits. The known genetic correlations between EA and higher height, lower body mass index, less-active smoking behavior, and better health outcomes were mostly explained by the indirect genetic component of EA. In contrast, the consistently identified genetic correlation of autism spectrum disorder (ASD) with higher EA resides in the direct genetic component. A polygenic transmission disequilibrium test showed a significant overtransmission of the direct component of EA from healthy parents to ASD probands. Taken together, we demonstrate that traditional GWAS approaches, in conjunction with offspring phenotypic data collection in existing cohorts, could greatly benefit studies on genetic nurture and shed important light on the interpretation of genetic associations for human complex traits.
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Affiliation(s)
- Yuchang Wu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
| | - Xiaoyuan Zhong
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706
| | - Yunong Lin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706
| | - Zijie Zhao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706
| | - Jiawen Chen
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514
| | - Boyan Zheng
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
- Department of Sociology, University of Wisconsin-Madison, Madison, WI 53706
| | - James J Li
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
- Department of Psychology, University of Wisconsin-Madison, Madison, WI 53706
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53706
| | - Jason M Fletcher
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
- Department of Sociology, University of Wisconsin-Madison, Madison, WI 53706
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI 53706
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706;
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706
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40
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Shero J, van Dijk W, Edwards A, Schatschneider C, Solari EJ, Hart SA. The practical utility of genetic screening in school settings. NPJ SCIENCE OF LEARNING 2021; 6:12. [PMID: 34075049 PMCID: PMC8169884 DOI: 10.1038/s41539-021-00090-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 04/19/2021] [Indexed: 06/12/2023]
Abstract
Can genetic screening be used to personalize education for students? Genome-wide association studies (GWAS) screen an individual's DNA for specific variations in their genome, and how said variations relate to specific traits. The variations can then be assigned a corresponding weight and summed to produce polygenic scores (PGS) for given traits. Though first developed for disease risk, PGS is now used to predict educational achievement. Using a novel simulation method, this paper examines if PGS could advance screening in schools, a goal of personalized education. Results show limited potential benefits for using PGS to personalize education for individual students. However, further analysis shows PGS can be effectively used alongside progress monitoring measures to screen for learning disability risk. Altogether, PGS is not useful in personalizing education for every child but has potential utility when used simultaneously with additional screening tools to help determine which children may struggle academically.
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Affiliation(s)
- J Shero
- Department of Psychology, Florida State University, Tallahassee, FL, USA.
| | - W van Dijk
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA
| | - A Edwards
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - C Schatschneider
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA
| | - E J Solari
- Department of Curriculum Instruction and Education, University of Virginia, Charlottesville, VA, USA
| | - S A Hart
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA
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41
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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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42
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Lenneis A, Vainik U, Teder-Laving M, Ausmees L, Lemola S, Allik J, Realo A. Personality traits relate to chronotype at both the phenotypic and genetic level. J Pers 2021; 89:1206-1222. [PMID: 33998684 DOI: 10.1111/jopy.12645] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 05/06/2021] [Accepted: 05/08/2021] [Indexed: 12/16/2022]
Abstract
INTRODUCTION Diurnal preferences have been linked to personality but often with mixed results. The present study examines the relationships between sleep timing (chronotype), diurnal preferences, and the Five-Factor Model of personality traits at the phenotypic and genetic level. METHODS Self- and informant-reports of the NEO Personality Inventory-3, self-reports of the Munich Chronotype Questionnaire, and DNA samples were available for 2,515 Estonian adults (Mage = 45.76 years; 59% females). Genetic correlations were obtained through summary statistics of genome-wide association studies. RESULTS Results showed that higher Conscientiousness and lower Openness to Experience were significant predictors of earlier chronotype. At the level of facets, we found that more straightforward (A2) and excitement-seeking (E5), yet less self-disciplined (C5) people were more likely to have later chronotypes. The nuance-level Polypersonality score was correlated with chronotype at r = .28 (p < .001). Conscientiousness and Openness were genetically related with diurnal preferences. The polygenic score for morningness-eveningness significantly predicted the Polypersonality score. CONCLUSION Phenotypic measures of chronotype and personality showed significant associations at all three of levels of the personality hierarchy. Our findings indicate that the relationship between personality and morningness-eveningness is partly due to genetic factors. Future studies are necessary to further refine the relationship.
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Affiliation(s)
- Anita Lenneis
- Department of Psychology, University of Warwick, Warwick, UK
| | - Uku Vainik
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Institute of Psychology, University of Tartu, Tartu, Estonia
| | | | - Liisi Ausmees
- Institute of Psychology, University of Tartu, Tartu, Estonia
| | - Sakari Lemola
- Department of Psychology, University of Warwick, Warwick, UK.,Department of Psychology, University of Bielefeld, Bielefeld, Germany
| | - Jüri Allik
- Institute of Psychology, University of Tartu, Tartu, Estonia.,The Estonian Academy of Sciences, Tallinn, Estonia
| | - Anu Realo
- Department of Psychology, University of Warwick, Warwick, UK.,Institute of Psychology, University of Tartu, Tartu, Estonia
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Genomic selection signatures in autism spectrum disorder identifies cognitive genomic tradeoff and its relevance in paradoxical phenotypes of deficits versus potentialities. Sci Rep 2021; 11:10245. [PMID: 33986442 PMCID: PMC8119484 DOI: 10.1038/s41598-021-89798-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 04/26/2021] [Indexed: 11/18/2022] Open
Abstract
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder characterized by paradoxical phenotypes of deficits as well as gain in brain function. To address this a genomic tradeoff hypothesis was tested and followed up with the biological interaction and evolutionary significance of positively selected ASD risk genes. SFARI database was used to retrieve the ASD risk genes while for population datasets 1000 genome data was used. Common risk SNPs were subjected to machine learning as well as independent tests for selection, followed by Bayesian analysis to identify the cumulative effect of selection on risk SNPs. Functional implication of these positively selected risk SNPs was assessed and subjected to ontology analysis, pertaining to their interaction and enrichment of biological and cellular functions. This was followed by comparative analysis with the ancient genomes to identify their evolutionary patterns. Our results identified significant positive selection signals in 18 ASD risk SNPs. Functional and ontology analysis indicate the role of biological and cellular processes associated with various brain functions. The core of the biological interaction network constitutes genes for cognition and learning while genes in the periphery of the network had direct or indirect impact on brain function. Ancient genome analysis identified de novo and conserved evolutionary selection clusters. The de-novo evolutionary cluster represented genes involved in cognitive function. Relative enrichment of the ASD risk SNPs from the respective evolutionary cluster or biological interaction networks may help in addressing the phenotypic diversity in ASD. This cognitive genomic tradeoff signatures impacting the biological networks can explain the paradoxical phenotypes in ASD.
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44
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Deary IJ, Hill WD, Gale CR. Intelligence, health and death. Nat Hum Behav 2021; 5:416-430. [PMID: 33795857 DOI: 10.1038/s41562-021-01078-9] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 02/15/2021] [Indexed: 02/06/2023]
Abstract
The field of cognitive epidemiology studies the prospective associations between cognitive abilities and health outcomes. We review research in this field over the past decade and describe how our understanding of the association between intelligence and all-cause mortality has consolidated with the appearance of new, population-scale data. To try to understand the association better, we discuss how intelligence relates to specific causes of death, diseases/diagnoses and biomarkers of health through the adult life course. We examine the extent to which mortality and health associations with intelligence might be attributable to people's differences in education, other indicators of socioeconomic status, health literacy and adult environments and behaviours. Finally, we discuss whether genetic data provide new tools to understand parts of the intelligence-health associations. Social epidemiologists, differential psychologists and behavioural and statistical geneticists, among others, contribute to cognitive epidemiology; advances will occur by building on a common cross-disciplinary knowledge base.
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Affiliation(s)
- Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
| | - W David Hill
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Catharine R Gale
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.,MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
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45
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Armstrong‐Carter E, Wertz J, Domingue BW. Genetics and Child Development: Recent Advances and Their Implications for Developmental Research. CHILD DEVELOPMENT PERSPECTIVES 2021. [DOI: 10.1111/cdep.12400] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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Odintsova VV, Rebattu V, Hagenbeek FA, Pool R, Beck JJ, Ehli EA, van Beijsterveldt CEM, Ligthart L, Willemsen G, de Geus EJC, Hottenga JJ, Boomsma DI, van Dongen J. Predicting Complex Traits and Exposures From Polygenic Scores and Blood and Buccal DNA Methylation Profiles. Front Psychiatry 2021; 12:688464. [PMID: 34393852 PMCID: PMC8357987 DOI: 10.3389/fpsyt.2021.688464] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/15/2021] [Indexed: 11/13/2022] Open
Abstract
We examined the performance of methylation scores (MS) and polygenic scores (PGS) for birth weight, BMI, prenatal maternal smoking exposure, and smoking status to assess the extent to which MS could predict these traits and exposures over and above the PGS in a multi-omics prediction model. MS may be seen as the epigenetic equivalent of PGS, but because of their dynamic nature and sensitivity of non-genetic exposures may add to complex trait prediction independently of PGS. MS and PGS were calculated based on genotype data and DNA-methylation data in blood samples from adults (Illumina 450 K; N = 2,431; mean age 35.6) and in buccal samples from children (Illumina EPIC; N = 1,128; mean age 9.6) from the Netherlands Twin Register. Weights to construct the scores were obtained from results of large epigenome-wide association studies (EWASs) based on whole blood or cord blood methylation data and genome-wide association studies (GWASs). In adults, MSs in blood predicted independently from PGSs, and outperformed PGSs for BMI, prenatal maternal smoking, and smoking status, but not for birth weight. The largest amount of variance explained by the multi-omics prediction model was for current vs. never smoking (54.6%) of which 54.4% was captured by the MS. The two predictors captured 16% of former vs. never smoking initiation variance (MS:15.5%, PGS: 0.5%), 17.7% of prenatal maternal smoking variance (MS:16.9%, PGS: 0.8%), 11.9% of BMI variance (MS: 6.4%, PGS 5.5%), and 1.9% of birth weight variance (MS: 0.4%, PGS: 1.5%). In children, MSs in buccal samples did not show independent predictive value. The largest amount of variance explained by the two predictors was for prenatal maternal smoking (2.6%), where the MSs contributed 1.5%. These results demonstrate that blood DNA MS in adults explain substantial variance in current smoking, large variance in former smoking, prenatal smoking, and BMI, but not in birth weight. Buccal cell DNA methylation scores have lower predictive value, which could be due to different tissues in the EWAS discovery studies and target sample, as well as to different ages. This study illustrates the value of combining polygenic scores with information from methylation data for complex traits and exposure prediction.
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Affiliation(s)
- Veronika V Odintsova
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Valerie Rebattu
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - René Pool
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jeffrey J Beck
- Avera Institute for Human Genetics, Sioux Falls, SD, United States
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, SD, United States
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Lannie Ligthart
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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Blanc J, Berg JJ. How well can we separate genetics from the environment? eLife 2020; 9:64948. [PMID: 33355092 PMCID: PMC7758058 DOI: 10.7554/elife.64948] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 12/18/2020] [Indexed: 11/16/2022] Open
Abstract
A simulation study demonstrates a better method for separating genetic effects from environmental effects in genome-wide association studies, but there is still some way to go before this becomes a "solved" problem.
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Affiliation(s)
- Jennifer Blanc
- Human Genetics, University of Chicago, Chicago, United States
| | - Jeremy J Berg
- Human Genetics, University of Chicago, Chicago, United States
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48
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Privé F, Arbel J, Vilhjálmsson BJ. LDpred2: better, faster, stronger. Bioinformatics 2020; 36:5424-5431. [PMID: 33326037 PMCID: PMC8016455 DOI: 10.1093/bioinformatics/btaa1029] [Citation(s) in RCA: 243] [Impact Index Per Article: 60.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 11/24/2020] [Accepted: 12/01/2020] [Indexed: 12/20/2022] Open
Abstract
Motivation Polygenic scores have become a central tool in human genetics research. LDpred is a popular method for deriving polygenic scores based on summary statistics and a matrix of correlation between genetic variants. However, LDpred has limitations that may reduce its predictive performance. Results Here, we present LDpred2, a new version of LDpred that addresses these issues. We also provide two new options in LDpred2: a ‘sparse’ option that can learn effects that are exactly 0, and an ‘auto’ option that directly learns the two LDpred parameters from data. We benchmark predictive performance of LDpred2 against the previous version on simulated and real data, demonstrating substantial improvements in robustness and predictive accuracy compared to LDpred1. We then show that LDpred2 also outperforms other polygenic score methods recently developed, with a mean AUC over the 8 real traits analyzed here of 65.1%, compared to 63.8% for lassosum, 62.9% for PRS-CS and 61.5% for SBayesR. Note that LDpred2 provides more accurate polygenic scores when run genome-wide, instead of per chromosome. Availability and implementation LDpred2 is implemented in R package bigsnpr. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Florian Privé
- National Centre for Register-Based Research, Aarhus University, Aarhus, 8210, Denmark
| | - Julyan Arbel
- Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble, 38000, France
| | - Bjarni J Vilhjálmsson
- National Centre for Register-Based Research, Aarhus University, Aarhus, 8210, Denmark.,Bioinformatics Research Centre, Aarhus University, Aarhus, 8000, Denmark
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49
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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: 12] [Impact Index Per Article: 3.0] [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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Domingue BW, Trejo S, Armstrong-Carter E, Tucker-Drob EM. Interactions between Polygenic Scores and Environments: Methodological and Conceptual Challenges. SOCIOLOGICAL SCIENCE 2020; 7:465-486. [PMID: 36091972 PMCID: PMC9455807 DOI: 10.15195/v7.a19] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Interest in the study of gene-environment interaction has recently grown due to the sudden availability of molecular genetic data-in particular, polygenic scores-in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened when used to integrate observational genomic and social science data. We articulate some of these key challenges, provide new perspectives on the study of gene-environment interactions, and end by offering some practical guidance for conducting research in this area. Given the sudden availability of well-powered polygenic scores, we anticipate a substantial increase in research testing for interaction between such scores and environments. The issues we discuss, if not properly addressed, may impact the enduring scientific value of gene-environment interaction studies.
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