Genetic nature or genetic nurture? Introducing social genetic parameters to quantify bias in polygenic score analyses
Abstract
Results from a genome-wide association study (GWAS) can be used to generate a polygenic score (PGS), an individual-level measure summarizing identified genetic influence on a trait dispersed across the genome. For complex, behavioral traits, the association between an individual's PGS and their phenotype may contain bias (from geographic, ancestral, and/or socioeconomic confounding) alongside the causal effect of the individual's genes. We formalize the introduction of a different source of bias in regression models using PGSs: the effects of parental genes on offspring outcomes, known as genetic nurture. GWAS do not discriminate between the various pathways through which genes become associated with outcomes, meaning existing PGSs capture both direct genetic effects and genetic nurture effects. We construct a theoretical model for genetic effects and show that the presence of genetic nurture biases PGS coefficients from both naïve OLS (between-family) and family fixed effects (within-family) regressions. This bias is in opposite directions; while naïve OLS estimates are biased away from zero, family fixed effects estimates are biased toward zero. We quantify this bias using two novel parameters: (1) the genetic correlation between the direct and nurture effects and (2) the ratio of the SNP heritabilities for the direct and nurture effects.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The within-family effect of cogPGS was roughly two-thirds of the between-family effect for intelligence at baseline, in line with the literature.
“We found the within-family effect of cogPGS to be roughly two-thirds of the between-family effect for intelligence (at baseline), in line with the literature43,44.”
From The impact of digital media on children’s intelligence while controlling for genetic differences in cognition and socioeconomic background (2022) · cites this paper as [44]
Cites
Introductory Econometrics: A Modern Approach
Wooldridge, J. M. (1999) · Cited by 14,354 · see citing works
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559 · see citing works
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works
10 Years of GWAS Discovery: Biology, Function, and Translation
Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.005 · Cited by 3,719 · see citing works
23andMe Research Team, Lee, J. J., COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0147-3 · Cited by 2,470 · cited 7× · see citing works
“2018), cognitive ability (Lee et al. 2018), depressive symptoms (Turley et al.”
InfluentialMeta-analysis of the heritability of human traits based on fifty years of twin studies
Polderman, T. J. C., Benyamin, B., de Leeuw, C. A., Sullivan, P. F., van Bochoven, A., Visscher, P. M., & Posthuma, D. (2015) · Nature Genetics · doi:10.1038/ng.3285 · Cited by 2,467 · cited 2× · see citing works
“Recent meta-analyses of twin studies support the linear, additive model for genetic e ff ects (Polderman et al. 2015).”
Yengo, L., Sidorenko, J., Kemper, K. E., Zheng, Z., Wood, A. R., Weedon, M. N., Frayling, T. M., Hirschhorn, J. N., Yang, J., & Visscher, P. M. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy271 · Cited by 2,305 · see citing works
The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.3097 · Cited by 1,853 · see citing works
The personal and clinical utility of polygenic risk scores
Torkamani, A., Wineinger, N. E., & Topol, E. J. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0018-x · Cited by 1,605 · see citing works
Power and predictive accuracy of polygenic risk scores
Dudbridge, F. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003348 · Cited by 1,509 · cited 1× · see citing works
“To increase statistical power and simplify computation, researchers often summarize the relevant genetics of individual i into a single linear predictor called a PGS (Dudbridge 2013).”
Genes mirror geography within Europe
Novembre, J., Johnson, T., Bryc, K., Kutalik, Z., Boyko, A. R., Auton, A., Indap, A., King, K. S., Bergmann, S., Nelson, M. R., et al. (2008) · Nature · doi:10.1038/nature07331 · Cited by 1,479 · see citing works
Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations
Martin, A. R., Gignoux, C. R., Walters, R. K., Wojcik, G. L., Neale, B. M., Gravel, S., Daly, M. J., Bustamante, C. D., & Kenny, E. E. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.03.004 · Cited by 1,391 · see citing works
Multi-trait analysis of genome-wide association summary statistics using MTAG
23andMe Research Team, Turley, P., Social Science Genetic Association Consortium, Walters, R. K., Maghzian, O., Okbay, A., Lee, J. J., Fontana, M. A., Nguyen-Viet, T. A., Wedow, R., et al. (2018) · Nature Genetics · doi:10.1038/s41588-017-0009-4 · Cited by 1,112 · see citing works
Study, L. C., Okbay, A., Baselmans, B. M. L., De Neve, J.-E., Turley, P., Nivard, M. G., Fontana, M. A., Meddens, S. F. W., Linnér, R. K., Rietveld, C. A., et al. (2016) · Nature Genetics · doi:10.1038/ng.3552 · Cited by 1,013 · see citing works
How to Interpret a Genome-wide Association Study
Pearson, T. A. (2008) · JAMA · doi:10.1001/jama.299.11.1335 · Cited by 964 · see citing works
The nature of nurture: Effects of parental genotypes
Kong, A., Thorleifsson, G., Frigge, M. L., Vilhjalmsson, B. J., Young, A. I., Thorgeirsson, T. E., Benonisdottir, S., Oddsson, A., Halldorsson, B. V., Masson, G., et al. (2018) · Science · doi:10.1126/science.aan6877 · Cited by 949 · see citing works
Evolutionary consequences of indirect genetic effects
Wolf, J. B., Brodie, E. D., Cheverud, J. M., Moore, A. J., & Wade, M. J. (1998) · Trends in Ecology & Evolution · doi:10.1016/s0169-5347(97)01233-0 · Cited by 830 · see citing works
GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment
Rietveld, C. A., Medland, S. E., Derringer, J., Yang, J., Esko, T., Martin, N. W., Westra, H.-J., Shakhbazov, K., Abdellaoui, A., Agrawal, A., et al. (2013) · Science · doi:10.1126/science.1235488 · Cited by 827 · see citing works
Hyde, C. L., Nagle, M. W., Tian, C., Chen, X., Paciga, S. A., Wendland, J. R., Tung, J. Y., Hinds, D. A., Perlis, R. H., & Winslow, A. R. (2016) · Nature Genetics · doi:10.1038/ng.3623 · Cited by 784 · see citing works
Moore, A. J., Brodie, E. D., & Wolf, J. B. (1997) · Evolution · doi:10.1111/j.1558-5646.1997.tb01458.x · Cited by 768 · see citing works
Warrington, N. M., Beaumont, R. N., Horikoshi, M., Day, F. R., Helgeland, Ø., Laurin, C., Bačelis, J., Peng, S., Hao, K., Feenstra, B., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0403-1 · Cited by 574 · see citing works
Cohort Profile: The National Longitudinal Study of Adolescent to Adult Health (Add Health)
Harris, K. M., Halpern, C. T., Whitsel, E. A., Hussey, J. M., Killeya‐Jones, L. A., Tabor, J. W., & Dean, S. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz115 · Cited by 552 · see citing works
Trans-ethnic association study of blood pressure determinants in over 750,000 individuals
Understanding Society Scientific Group, Giri, A., Program, M. V., Hellwege, J. N., Keaton, J. M., Park, J., Qiu, C., Warren, H. R., Torstenson, E. S., Kovesdy, C. P., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0303-9 · Cited by 444 · see citing works
A scientometric review of genome-wide association studies
Mills, M. C., & Rahal, C. (2018) · Communications Biology · doi:10.1038/s42003-018-0261-x · Cited by 430 · see citing works
The Fourth Law of Behavior Genetics
Chabris, C. F., Lee, J. J., Cesarini, D. A., Benjamin, D. J., & Laibson, D. (2015) · Current Directions in Psychological Science · doi:10.1177/0963721415580430 · Cited by 361 · see citing works
Moore, A. J., Brodie, E. D., & Wolf, J. B. (1997) · Evolution · doi:10.2307/2411187 · Cited by 332 · see citing works
Genetic analysis of social-class mobility in five longitudinal studies
Belsky, D. W., Domingue, B. W., Wedow, R., Arseneault, L., Boardman, J. D., Caspi, A., Conley, D., Fletcher, J. M., Freese, J., Herd, P., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1801238115 · Cited by 315 · cited 8× · see citing works
“While this value could in fact be negative, existing evidence suggests that ρg is typically positive (Armstrong-Carter et al. 2019; Bates et al. 2018; Belsky et al. 2018; Kong et al. 2018; Wertz et al. 2018).”
InfluentialSelf-citationComparing Within- and Between-Family Polygenic Score Prediction
Selzam, S., Ritchie, S. J., Pingault, J.-B., Reynolds, C. A., O’Reilly, P. F., & Plomin, R. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.06.006 · Cited by 289 · see citing works
Domingue, B. W., Belsky, D. W., Conley, D., Harris, K. M., & Boardman, J. D. (2015) · AERA Open · doi:10.1177/2332858415599972 · Cited by 265 · see citing works
Self-citationBelsky, D. W., Moffitt, T. E., Corcoran, D. L., Domingue, B., Harrington, H., Hogan, S., Houts, R., Ramrakha, S., Sugden, K., Williams, B. S., et al. (2016) · Psychological Science · doi:10.1177/0956797616643070 · Cited by 260 · see citing works
Self-citationIdeas previas y cambio conceptual
Garcés, S. B. (2018) · Educación Química · doi:10.22201/fq.18708404e.2004.3.66178 · Cited by 199 · see citing works
Bergsma, R., Kanis, E., Knol, E. F., & Bijma, P. (2008) · Genetics · doi:10.1534/genetics.107.084236 · Cited by 178 · see citing works
Beaumont, R. N., Warrington, N. M., Cavadino, A., Tyrrell, J., Nodzenski, M., Horikoshi, M., Geller, F., Myhre, R., Richmond, R. C., Paternoster, L., et al. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddx429 · Cited by 174 · see citing works
Education can reduce health differences related to genetic risk of obesity
Barcellos, S., Carvalho, L., & Turley, P. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1802909115 · Cited by 163 · see citing works
Hamer, D. H., & Sirota, L. A. (2000) · Molecular Psychiatry · doi:10.1038/sj.mp.4000662 · Cited by 158 · see citing works
Bates, T. C., Maher, B. S., Medland, S. E., McAloney, K., Wright, M. J., Hansell, N. K., Kendler, K. S., Martin, N. G., & Gillespie, N. A. (2018) · Twin Research and Human Genetics · doi:10.1017/thg.2018.11 · Cited by 157 · see citing works
Is Biology Destiny? Birth Weight and Differential Parental Treatment
Hsin, A. (2012) · Demography · doi:10.1007/s13524-012-0123-y · Cited by 146 · see citing works
Petfield, D., Chenoweth, S. F., Rundle, H. D., & Blows, M. W. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0409378102 · Cited by 143 · see citing works
Belsky, D. W., Moffitt, T. E., Baker, T. B., Biddle, A. K., Evans, J. P., Harrington, H. L., Houts, R., Meier, M. H., Sugden, K., Williams, B. S., et al. (2013) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.736 · Cited by 139 · see citing works
Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study
Papageorge, N., & Thom, K. (2016) · Journal of the European Economic Association · doi:10.1093/jeea/jvz072 · Cited by 131 · see citing works
Conley, D., & Fletcher, J. (2017) · Cited by 125 · see citing works
Integrating Genetics and Social Science: Genetic Risk Scores
Belsky, D. W., & Israel, S. (2014) · Biodemography and Social Biology · doi:10.1080/19485565.2014.946591 · Cited by 114 · see citing works
Replicability and Robustness of Genome-Wide-Association Studies for Behavioral Traits
Rietveld, C. A., Conley, D., Eriksson, N., Esko, T., Medland, S. E., Vinkhuyzen, A. A. E., Yang, J., Boardman, J. D., Chabris, C. F., Dawes, C. T., et al. (2014) · Psychological Science · doi:10.1177/0956797614545132 · Cited by 111 · cited 2× · see citing works
“Thus, validating PGSs within families is vitally important for sifting out causation from correlation among the genetics identified in GWASs of complex traits (Belsky et al. 2018; Domingue et al. 2015; Lee et al. 2018; Rietveld et al. 2014).”
Self-citationMortality selection in a genetic sample and implications for association studies
Domingue, B. W., Belsky, D. W., Harrati, A., Conley, D., Weir, D. R., & Boardman, J. D. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx041 · Cited by 97 · see citing works
Self-citationDomingue, B., Belsky, D. W., Fletcher, J. M., Conley, D., Boardman, J. D., & Harris, K. (2017) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1711803115 · Cited by 91 · see citing works
Self-citationWertz, J., Moffitt, T. E., Agnew‐Blais, J. C., Arseneault, L., Belsky, D. W., Corcoran, D. L., Houts, R., Matthews, T., Prinz, J. A., Richmond‐Rakerd, L. S., et al. (2019) · Child Development · doi:10.1111/cdev.13329 · Cited by 91 · see citing works
The Arrival of Social Science Genomics
Jeremy Freese, A. (2018) · Contemporary Sociology A Journal of Reviews · doi:10.1177/0094306118792214a · Cited by 73 · see citing works
Parental investment responses to a low birth weight outcome: who compensates and who reinforces?
Restrepo, B. (2016) · Journal of Population Economics · doi:10.1007/s00148-016-0590-3 · Cited by 71 · see citing works
Wedow, R., Zacher, M. L., Huibregtse, B. M., Harris, K. M., Domingue, B. W., & Boardman, J. D. (2018) · American Sociological Review · doi:10.1177/0003122418785368 · Cited by 68 · see citing works
Self-citationMartschenko, D. O., Trejo, S., & Domingue, B. W. (2019) · AERA Open · doi:10.1177/2332858418810516 · Cited by 64 · see citing works
Self-citationTrejo, S., Belsky, D. W., Boardman, J., Jeremy Freese, A., Harris, K. M., Herd, P., Sicinski, K., & Domingue, B. W. (2018) · Sociological Science · doi:10.15195/v5.a22 · Cited by 62 · see citing works
Self-citationMachiavellianism in Indian management
Cyriac, K., & Dharmaraj, R. (1994) · Journal of Business Ethics · doi:10.1007/bf00871674 · Cited by 52 · see citing works
Effects of the peer metagenomic environment on smoking behavior
Sotoudeh, R., Harris, K. M., & Conley, D. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1806901116 · Cited by 40 · see citing works
The social genome: Current findings and implications for the study of human genetics
Domingue, B. W., & Belsky, D. W. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006615 · Cited by 36 · see citing works
Self-citationThe early-life environment of a pig shapes the phenotypes of its social partners in adulthood
Canario, L., Lundeheim, N., & Bijma, P. (2017) · Heredity · doi:10.1038/hdy.2017.3 · Cited by 27 · see citing works
Dissecting indirect genetic effects from peers in laboratory mice
Baud, A., Casale, F. P., Barkley‐Levenson, A. M., Farhadi, N., Montillot, C., Yalcin, B., Nicod, J., Palmer, A. A., & Stegle, O. (2021) · Genome biology · doi:10.1186/s13059-021-02415-x · Cited by 27 · see citing works
Analysis of Polygenic Score Usage and Performance in Diverse Human PopulationsPreprint
Duncan, L. E., Shen, H., Gelaye, B., Ressler, K. J., Feldman, M. W., Peterson, R., & Domingue, B. W. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/398396 · Cited by 23 · see citing works
Self-citationDissecting indirect genetic effects from peers in laboratory micePreprint
Baud, A., Casale, F. P., Barkley‐Levenson, A. M., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/302349 · Cited by 7 · see citing works
Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement StudyPreprint
Papageorge, N., & Thom, K. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2982606 · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., Sidorenko, J., Kweon, H., Goldman, G., Gjorgjieva, T., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01016-z · Cited by 654 · see citing works
Nurture might be nature: cautionary tales and proposed solutions
Hart, S. A., Little, C., & van Bergen, E. (2021) · npj Science of Learning · doi:10.1038/s41539-020-00079-z · Cited by 165 · see citing works
Mendelian imputation of parental genotypes improves estimates of direct genetic effects
Young, A. I., Nehzati, S. M., Benonisdottir, S., Okbay, A., Jayashankar, H., Lee, C., Cesarini, D., Benjamin, D. J., Turley, P., & Kong, A. (2022) · Nature Genetics · doi:10.1038/s41588-022-01085-0 · Cited by 144 · see citing works
Gene-environment dependencies lead to collider bias in models with polygenic scores
Akimova, E. T., Breen, R., Brazel, D. M., & Mills, M. C. (2021) · Scientific Reports · doi:10.1038/s41598-021-89020-x · Cited by 80 · see citing works
Sauce, B., Liebherr, M., Judd, N., & Klingberg, T. (2022) · Scientific Reports · doi:10.1038/s41598-022-11341-2 · Cited by 74 · see citing works
Veller, C., & Coop, G. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002511 · Cited by 78 · see citing works
Nivard, M. G., Belsky, D. W., Harden, K. P., Baier, T., Andreassen, O. A., Ystrøm, E., van Bergen, E., & Lyngstad, T. H. (2024) · Nature Human Behaviour · doi:10.1038/s41562-023-01796-2 · Cited by 65 · see citing works
Wu, Y., Zhong, X., Lin, Y., Zhao, Z., Chen, J. C., Zheng, B., Li, J. J., Fletcher, J. M., & Lu, Q. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2023184118 · Cited by 57 · see citing works
Carvalho, C. M., Wendt, F. R., Maihofer, A. X., Stein, D. J., Stein, M. B., Sumner, J. A., Hemmings, S. M. J., Nievergelt, C. M., Koenen, K. C., Gelernter, J. E., et al. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0655-6 · Cited by 46 · see citing works
Armstrong‐Carter, E., Trejo, S., Hill, L. J. B., Crossley, K. L., Mason, D., & Domingue, B. W. (2020) · Psychological Science · doi:10.1177/0956797620917209 · Cited by 43 · see citing works
Self-citationIndirect Genetic Effects: A Cross-disciplinary Perspective on Empirical Studies
Baud, A., McPeek, S. J., Chen, N. X., & Hughes, K. A. (2021) · Journal of Heredity · doi:10.1093/jhered/esab059 · Cited by 44 · see citing works
Human genetics and epigenetics of alcohol use disorder
Zhou, H., & Gelernter, J. E. (2024) · Journal of Clinical Investigation · doi:10.1172/jci172885 · Cited by 39 · see citing works
Family disadvantage, gender, and the returns to genetic human capital*
Ronda, V., Agerbo, E., Bleses, D., Mortensen, P. B., Børglum, A., Mors, O., Rosholm, M., Hougaard, D. M., Nordentoft, M., & Werge, T. (2021) · Scandinavian Journal of Economics · doi:10.1111/sjoe.12462 · Cited by 38 · see citing works
Sibling validation of polygenic risk scores and complex trait prediction
Lello, L., Raben, T. G., & Hsu, S. (2020) · Scientific Reports · doi:10.1038/s41598-020-69927-7 · Cited by 33 · see citing works
Interpreting polygenic score effects in sibling analysis
Fletcher, J. M., Wu, Y., Li, T., & Lu, Q. (2024) · PLoS ONE · doi:10.1371/journal.pone.0282212 · Cited by 29 · see citing works
The “Golden Age” of Behavior Genetics?
Charney, E. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916211041602 · Cited by 29 · see citing works
Domingue, B. W., & Fletcher, J. M. (2020) · Behavior Genetics · doi:10.1007/s10519-020-10000-4 · Cited by 27 · see citing works
Self-citationWidén, E., Raben, T. G., Lello, L., & Hsu, S. (2021) · Genes · doi:10.3390/genes12070991 · Cited by 33 · see citing works
The production of within-family inequality: Insights and implications of integrating genetic data
Fletcher, J. M., Wu, Y., Zhao, Z., & Lu, Q. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgad121 · Cited by 28 · see citing works
Causal interpretations of family GWAS in the presence of heterogeneous effects
Veller, C., Przeworski, M., & Coop, G. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2401379121 · Cited by 27 · see citing works
Higbee, D., Granell, R., Hemani, G., Smith, G. D., & Dodd, J. W. (2021) · BMC Pulmonary Medicine · doi:10.1186/s12890-021-01611-6 · Cited by 26 · see citing works
Schaefer, J. D., Jang, S.-K., Clark, D. A., Deak, J. D., Hicks, B. M., Iacono, W. G., Liu, M., McGue, M. K., Vrieze, S. I., & Wilson, S. (2021) · Psychological Medicine · doi:10.1017/s0033291721004116 · Cited by 23 · see citing works
A polygenic score for educational attainment partially predicts voter turnout
Dawes, C. T., Okbay, A., Oskarsson, S., & Rustichini, A. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2022715118 · Cited by 23 · see citing works
Judd, N., Sauce, B., & Klingberg, T. (2022) · npj Science of Learning · doi:10.1038/s41539-022-00148-5 · Cited by 25 · see citing works
Ghirardi, G., & Bernardi, F. (2025) · Social Science Research · doi:10.1016/j.ssresearch.2025.103174 · Cited by 24 · see citing works
The Meaning of “Cause” in GeneticsPreprint
Lynch, K. E. (2021) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a040519 · Cited by 22 · see citing works
Social-Science Genomics: Progress, Challenges, and Future Directions
Benjamin, D., Cesarini, D., Turley, P., & Young, A. S. (2024) · doi:10.3386/w32404 · Cited by 20 · see citing works
Ghirardi, G., Gil-Hernández, C. J., Bernardi, F., van Bergen, E., & Demange, P. (2024) · Research in Social Stratification and Mobility · doi:10.1016/j.rssm.2024.100960 · Cited by 16 · see citing works
The Economics and Econometrics of Gene–Environment Interplay
Biroli, P., Galama, T. J., von Hinke, S., van Kippersluis, H., Rietveld, C. A., & Thom, K. (2025) · The Review of Economic Studies · doi:10.1093/restud/rdaf034 · Cited by 16 · see citing works
Luck, lottery, or legacy? The problem of confounding. A reply to Harden
Coop, G., & Przeworski, M. (2022) · Evolution · doi:10.1111/evo.14588 · Cited by 9 · see citing works
Buser, T., Ahlskog, R., Johannesson, M., Koellinger, P., & Oskarsson, S. (2024) · Labour Economics · doi:10.1016/j.labeco.2024.102544 · Cited by 6 · see citing works
Genetic nurture: estimating the direct genetic effects of pediatric anthropometric traits
Ghatan, S., de Vries, J., Pingault, J., Jaddoe, V. W. V., Cecil, C. A. M., Felix, J. F., Rivadeneira, F., & Medina‐Gómez, C. (2025) · Human Molecular Genetics · doi:10.1093/hmg/ddaf117 · Cited by 7 · see citing works
Heritable environments: bias due to conditioning on a collider in models with polygenic scoresPreprint
Akimova, E. T., Breen, R., Brazel, D. M., & Mills, M. C. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.02.364539 · Cited by 8 · see citing works
Buser, T., Ahlskog, R., Johanneson, M., Koellinger, P., & Oskarsson, S. (2021) · Social Science Research Network · doi:10.2139/ssrn.3938154 · Cited by 3 · see citing works
Mental Health Effects of Income over the Adult Life Course
Rauf, T. (2023) · Socius Sociological Research for a Dynamic World · doi:10.1177/23780231231186072 · Cited by 8 · see citing works
Class, genes, and rationality: A gene–environment interaction approach to ideology
Ahlskog, R. (2024) · Political Psychology · doi:10.1111/pops.13023 · Cited by 6 · see citing works
Pereira, R. D. (2021) · SSRN Electronic Journal · doi:10.1101/2021.12.14.472565 · Cited by 5 · see citing works
Beyond Barker: Infant Mortality at Birth and Ischaemic Heart Disease in Older AgePreprint
Baker, S., Biroli, P., van Kippersluis, H., & von Hinke, S. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4114876 · Cited by 6 · see citing works
Exploring the Fetal Origins Hypothesis Using Genetic Data
Trejo, S. (2024) · Social Forces · doi:10.1093/sf/soae018 · Cited by 8 · see citing works
Self-citationConfounding fuels misinterpretation in human genetics
Benning, J. W., Carlson, J., Smith, O. S., Shaw, R. G., & Harpak, A. (2025) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2025.1615 · Cited by 5 · see citing works
Alemu, R. G., Terskaya, A., Howell, M., Guan, J., Sands, H., Kleinman, A., Bann, D., Morris, T., Ploubidis, G. B., Fitzsimons, E., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.14.653986 · Cited by 8 · see citing works
Wang, Z., Grosvenor, L. P., Ray, D., Cheng, T., Ruczinski, I., Beaty, T. H., Volk, H. E., Ladd‐Acosta, C., & Chatterjee, N. (2026) · Nature Genetics · doi:10.1038/s41588-026-02601-2 · Cited by 4 · see citing works
Decomposing heritability and genetic covariance by direct and indirect effect paths
Song, J., Zou, Y., Wu, Y., Miao, J., Yu, Z., Fletcher, J. M., & Lu, Q. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010620 · Cited by 4 · see citing works
Nogel, M. (2024) · Forensic Science International Digital Investigation · doi:10.1016/j.fsidi.2024.301696 · Cited by 4 · see citing works
A Wolf in Sheep's Clothing: Idealisations and the aims of polygenic scores
Serpico, D. (2023) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2023.10.006 · Cited by 3 · see citing works
Pettersson, O. (2025) · Behavior Genetics · doi:10.1007/s10519-025-10219-z · Cited by 3 · see citing works
Bright, J. K., Rayner, C., Freeman, Z., Zavos, H. M. S., Ahmadzadeh, Y. I., Viding, E. M., & McAdams, T. A. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-02920-6 · Cited by 3 · see citing works
Exploring Genetic Influences on Birth WeightPreprint
Trejo, S. (2020) · doi:10.31235/osf.io/7j59q · Cited by 3 · see citing works
Self-citationDoes standard adjustment for genomic population structure capture direct genetic effects?Preprint
Sotoudeh, R., Trejo, S., Harpak, A., & Conley, D. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.03.592431 · Cited by 3 · see citing works
Self-citationTrejo, S., & Kanopka, K. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2405725121 · Cited by 2 · see citing works
Self-citationGenetic Endowments, Income Dynamics, and Wealth Accumulation Over the LifecyclePreprint
Barth, D. J., Papageorge, N., Thom, K., & Velásquez‐Giraldo, M. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4182029 · Cited by 2 · see citing works
Pettersson, O. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.02.565287 · Cited by 2 · see citing works
Genetics for ‘equality’? The politics of knowledge production in educational genomics
Kotouza, D. (2025) · History of the Human Sciences · doi:10.1177/09526951251314314 · Cited by 1 · see citing works
Quantifying direct genetic signal captured by principal component adjustment
Sotoudeh, R., Trejo, S., Harpak, A., & Conley, D. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2525790123 · Cited by 1 · see citing works
Self-citationPaternal Incarceration, Polygenic Scores, and Children’s Educational Attainment
Liu, H., & Clark, B. (2022) · Journal of Developmental and Life-Course Criminology · doi:10.1007/s40865-022-00213-y · Cited by 1 · see citing works
Pereira, R. D. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4116304 · Cited by 1 · see citing works
Sbarra, D. A., Trejo, S., Harden, K. P., Oliver, J. C., & Klimentidis, Y. C. (2023) · doi:10.31234/osf.io/g5vk4 · Cited by 1 · see citing works
Self-citationGenetic Endowments, Income Dynamics, and Wealth Accumulation Over the LifecyclePreprint
Barth, D. J., Papageorge, N., Thom, K., & Giraldo, M. V. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4190172
Bernardi, F., & Ghirardi, G. (2023) · doi:10.31235/osf.io/rgzd7
Economic Preferences, Genes, and Childhood DisadvantagePreprint
Dawson, C. (2025) · doi:10.31234/osf.io/p97f5_v1
Pettersson, O. (2025) · Political Behavior · doi:10.1007/s11109-025-10096-6
Higbee, D., Granell, R., Hemani, G., Smith, G. D., & Dodd, J. W. (2021) · Figshare · doi:10.6084/m9.figshare.15040929
Genetic risk for ADHD and later-life health and wellbeing: individual and spousal spillovers
Gaggero, A., Gil, J., & Jiménez‐Rubio, D. (2026) · The Journal of the Economics of Ageing · doi:10.1016/j.jeoa.2026.100619
Dawson, C. (2026) · Communications psychology · doi:10.1038/s44271-026-00421-y
Ethical Priorities Among Commercial Genomics Professionals
Walker, A. N. (2026) · Journal of Bioethical Inquiry · doi:10.1007/s11673-026-10559-3
Gholipourshahraki, T., Barry, C.-J. S., Plana‐Ripoll, O., Bulik, C. M., Benros, M. E., Mortensen, P. B., Agerbo, E., Petersen, L. V., & Vilhjálmsson, B. J. (2026) · medRxiv · doi:10.64898/2026.07.28.26359090
Malawsky, D., Hegemann, L., Wootton, O., Havdahl, A., Sunde, H., & Martin, H. (2026) · bioRxiv · doi:10.64898/2026.09.01.748516
Perry, L. C., Chevalier, N., & Luciano, M. (2026) · Child Development · doi:10.1093/chidev/aacag193
- Authors
- Trejo, S., & Domingue, B. W.
- Affiliations
- Stanford University (US)
- Corresponding author
- Trejo, Sam
- Venue
- Biodemography and Social Biology
- Publisher
- Informa UK Limited
- Published
- 2018-10-02
- Volume
- 64
- Issue
- 3-4
- Pages
- 187-215
- ISSN
- 1948-5565 (ISSN-L)
- 1948-5573
- OpenAlex
- W2996316818
- Cited by
- 69
- References
- 57
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 14 · 2023: 7 · 2022: 11 · 2021: 13 · 2020: 6
- FWCI
- 2.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biodemography and Social Biology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Social Sciences › Sociology and Political Science › Intergenerational and Educational Inequality Studies
- Keywords
- polygenic risk score, genetic nurture, direct genetic effects, family fixed effects, genetic correlation, SNP heritability
- MeSH terms
- Genotype, Humans, Models, Genetic, Phenotype, Bias, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review