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The Genetics of Partnership Dissolution

By on January 20, 2025 in Articles

Ruth Eva Jørgensen, Rosa Cheesman, Ole A. Andreassen, Torkild Hovde Lyngstad

Sociological Science January 20, 2025
10.15195/v12.a4

Abstract

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There is a genetic component to divorce risk, but little is known about which and how genetically influenced traits are involved. This study makes three major contributions to address these gaps. First, we link genetic data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) to population register data and estimate the total influence of common genetic variants on partnership dissolution (N = 121, 408). Then, we identify heritable traits associated with partnership dissolution using event-history analysis and a broad set of polygenic indices. Finally, we assess whether associations are robust to controls for confounding in within-sibling models. Significant heritability estimates were found for both females (h2SNP = 0.09; SE = 0.01; p < 0.0001) and males (h2SNP = 0.03; SE = 0.01; p < 0.0001). Genetic dispositions for educational attainment and other sociodemographic factors decrease the probability of partnership dissolution, whereas dispositions for internalizing symptoms and risk behavior increase the likelihood of partnership dissolution. Integrating genetics and sociodemographic approaches can shed new light on the causes of partnership dynamics by helping us understand what drives the selection processes throughout the life course.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Ruth Eva Jørgensen: Department of Sociology and Human Geography, University of Oslo.*
E-mail: r.e.jorgensen@sosgeo.uio.no

Rosa Cheesman: PPROMENTA, Department of Psychology, University of Oslo
E-mail: r.c.g.cheesman@psykologi.uio.no

Ole A. Andreassen: NORMENT, Department of Clinical Medicine, University of Oslo
E-mail: ole.andreassen@medisin.uio.no

Torkild Hovde Lyngstad: Department of Sociology and Human Geography, University of Oslo
E-mail: t.h.lyngstad@sosgeo.uio.no

Acknowledgements: This research is part of the OPENFLUX project, which has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 818420). The Norwegian Mother, Father, and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this on-going cohort study. We thank the Norwegian Institute of Public Health (NIPH) for generating high-quality genomic data. This research is part of the HARVEST collaboration, supported by the Research Council of Norway (#229624). We also thank the NORMENT Centre for providing genotype data, funded by the Research Council of Norway (#223273), Southeast Norway Health Authority, and KG Jebsen Stiftelsen. We further thank the Center for Diabetes Research, the University of Bergen, for providing genotype data and performing quality control and imputation of the data funded by the ERC AdG project SELECTionPREDISPOSED, Stiftelsen Kristian Gerhard Jebsen, Trond Mohn Foundation, the Research Council of Norway, the Novo Nordisk Foundation, the University of Bergen, and the Western Norway Health Authorities (Helse Vest). The version of the genotype data used is MobaPyschGen v1. We are very grateful to Alexandra Havdahl and Elizabeth Corfield for access to this version of the data. The authors are grateful to the Sociological Science editors and reviewers for feedback.

Supplemental Materials

Reproducibility Package: See paper for data availability statement. Access to administrative data from Statistics Norway can be applied for at Statistics Norway (https://www.ssb.no/mikrodata/) and access to MoBa Genetics can be applied for at the Norwegian Public Health Institute (https://www.fhi.no/studier/moba/). Code for data preparation and analysis is available at https://github.com/torkildl/genetics-dissolution.

  • Citation: Jørgensen, Ruth Eva, Rosa Cheesman, Ole A. Andreassen, Torkild Hovde Lyngstad. 2025. “The Genetics of Partnership Dissolution” Sociological Science 12: 76-96.
  • Received: October 24, 2024
  • Accepted: December 7, 2024
  • Editors: Arnout van de Rijt, Bart Bonikowski
  • DOI: 10.15195/v12.a4

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The Bell Curve Revisited: Testing Controversial Hypotheses with Molecular Genetic Data

By on July 5, 2016 in Articles

Dalton Conley, Benjamin Domingue

Sociological Science, July 5, 2016
DOI 10.15195/v3.a23

Abstract
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In 1994, the publication of Herrnstein’s and Murray’s The Bell Curve resulted in a social science maelstrom of responses. In the present study, we argue that Herrnstein’s and Murray’s assertions were made prematurely, on their own terms, given the lack of data available to test the role of genotype in the dynamics of achievement and attainment in U.S. society. Today, however, the scientific community has access to at least one dataset that is nationally representative and has genome-wide molecular markers. We deploy those data from the Health and Retirement Study in order to test the core series of propositions offered by Herrnstein and Murray in 1994. First, we ask whether the effect of genotype is increasing in predictive power across birth cohorts in the middle twentieth century. Second, we ask whether assortative mating on relevant genotypes is increasing across the same time period. Finally, we ask whether educational genotypes are increasingly predictive of fertility (number ever born [NEB]) in tandem with the rising (negative) association of educational outcomes and NEB. The answers to these questions are mostly no; while molecular genetic markers can predict educational attainment, we find little evidence for the proposition that we are becoming increasingly genetically stratified.

Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Dalton Conley: Department of Sociology, Princeton University
Email: dconley@princeton.edu

Benjamin Domingue: Graduate School of Education, Stanford University
Email: bdomingue@stanford.edu

Acknowledgements: Funding for this study was provided by the Russell Sage Foundation, Grant 83-15-29. This research uses data from the HRS, which is sponsored by the National Institute on Aging (Grants NIA U01AG009740, RC2AG036495, and RC4AG039029) and conducted by the University of Michigan.

Supplemental Material

  • Citation: Conley, Dalton, and Benjamin Domingue. 2016. “The Bell Curve Revisited: Testing Controversial Hypotheses with Molecular Genetic Data.” Sociological Science 3: 520-539.
  • Received: January 19, 2016
  • Accepted: February 22, 2016
  • Editors: Stephen Morgan
  • DOI: 10.15195/v3.a23


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