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The value of sociogenomics in understanding genetic evolution in contemporary human populations

Published online by Cambridge University Press:  11 September 2023

Ze Hong*
Affiliation:
Department of Sociology, Zhejiang University, Hangzhou, Zhejiang, China Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA ze_hong@g.harvard.edu; https://kevinhong.home.blog/

Abstract

Burt's target article oddly misses the important intellectual contribution of sociogenomics to our understanding of genetic evolution in contemporary human populations. Although social scientists' immediate research agendas are often not evolutionary in nature, I call for a better appreciation of the role of sociogenomics in answering important evolutionary questions.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

“Sociogenomics” has recently become a “buzzword” in the social sciences that traditionally ignored the contribution of genetic factors in human behavior and social phenomena. As Burt noted, there have been prominent proposals to incorporate genomic methods into social scientists' toolkit and better appreciate the insights generated by genetic data (Mills & Tropf, Reference Mills and Tropf2020). Although I am sympathetic to Burt's call for more caution in including genetic considerations in social science research, I argue that Burt ignores one important aspect to which genetic data may greatly and uniquely contribute, and that is the study of genetic evolution in contemporary societies (I am disheartened that Burt's article does not mention “evolution” a single time).

It may be worth pointing out that the term “sociogenomics” was first proposed in evolutionary biology where researchers were deeply concerned with how the genetic basis of social behavior affects evolution (Robinson, Reference Robinson1999; Robinson, Grozinger, & Whitfield, Reference Robinson, Grozinger and Whitfield2005). Of course, sociologists' focus on contemporary social issues often makes genetic evolution, which could take considerable time, seem irrelevant, but this impression is false. In fact, natural selection is very much still operating in contemporary human populations (Milot et al., Reference Milot, Mayer, Nussey, Boisvert, Pelletier and Reále2011; Nettle & Pollet, Reference Nettle and Pollet2008; Stearns, Byars, Govindaraju, & Ewbank, Reference Stearns, Byars, Govindaraju and Ewbank2010), and some of the most influential papers on the sociogenomics of educational attainment (e.g., Beauchamp, Reference Beauchamp2016; Kong et al., Reference Kong, Frigge, Thorleifsson, Stefansson, Young, Zink and Stefansson2017) are very explicit in the use of polygenic scores to understand natural selection in contemporary human populations. Beauchamp (Reference Beauchamp2016), for example, shows that natural selection has been slowly favoring lower educational attainment among individuals of European ancestry in a representative US sample. Kong et al. (Reference Kong, Frigge, Thorleifsson, Stefansson, Young, Zink and Stefansson2017) present similar findings in a large Icelandic sample. These findings make perfect sense given the robust negative association between fertility and educational attainment (Ní Bhrolcháin & Beaujouan, Reference Ní Bhrolcháin and Beaujouan2012; Soares, Reference Soares2005): The fact that individuals with higher educational attainment tend to produce fewer children means that the genetic component will decline as long as the heritability is not exhausted (though this association is sometimes mediated by socioeconomic status; see Hugh-Jones & Abdellaoui, Reference Hugh-Jones and Abdellaoui2022). Empirical data in the form of heritability estimates and polygenic scores thus nicely confirm our intuition and give us a sense of the rate of natural selection (regarding the genetic component) for specific traits. As such, sociogenomics is no different in principle from nonsocial genomics which has made tremendous progress in understanding how our physical and physiological traits have responded to natural selection (Guo et al., Reference Guo, Wu, Zhu, Zheng, Trzaskowski, Zeng and Yang2018).

In general, knowing the genetic architecture of a trait (including psychological and behavioral ones) that is significantly associated with fertility is indispensable for understanding how various evolutionary forces may act on the trait, the potential genetic response, and how the phenotypic expression of the trait may change in the future. In this respect, empirical studies in sociogenomics could offer crucial guidance for theoretical and simulation models. Inspired by Beauchamp and Kong et al.'s work, I have modeled the on-going natural selection of educational attainment in contemporary societies where I show that depending on how the trait is determined by genetics and environment, we may expect rather different short-term evolutionary trajectories of both the genotype and phenotype (Hong, Reference Hong2020). This type of work is necessarily provocative in the current socio-political climate, but I suggest that the genetic and cultural evolution of human behavior are both meaningful and worthy scientific endeavors, and the fact that psychological and behavioral traits are the result of complex interactions between genes and environment should not scare researchers away; rather, in the age of drastic cultural change and demographic shift (Colleran, Reference Colleran2016; Jensen & Levin, Reference Jensen, Levin and Schafer2007), it is more pressing than ever to leverage insights from different disciplines to understand how fertility is associated with various traits as well as the genetic and cultural consequences, and social scientists and geneticists alike should better appreciate the value of GWASs and polygenic scores in answering important evolutionary questions.

Acknowledgments

I thank Nick Patterson for his thoughts and comments that partly inspired this commentary.

Financial support

This work was supported by the Issachar Fund and the Templeton Religion Trust.

Competing interest

None.

References

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