Population stratification within-families

Burt rightly notes that the problem of population stratification haunts all interpretations of GWASs/PGSs and cannot be easily eliminated. BG researchers, however, seem to agree with Zaidi and Mathieson (cited by Burt) that “family-based studies are immune to stratification,” and present the equivalent of a randomized controlled trial (RCT; Harden, Reference Harden2021). However, children are not merely passive vehicles of additive G and E effects. They actively constructive perceptions of their worlds and creatively react to them.

Burt (target article, sect. 5.1.2, para. 7) mentions family dynamics that create “micro-stratification” within families. However, such dynamics also interact with wider social contexts to further generate spurious SNP–trait correlations in GWASs/PGSs. Facial appearance; height; weight; body shape; subclinical medical conditions such as myopia; hair form; and skin color (e.g., Hall, Reference Hall2017), are all subject to positive/negative feedback from peers and teachers, as well as siblings and parents, acting to cultural norms. They create unequal psychological effects and reactions that course through individuals' school and occupational careers (Kraft, Kraft, Hagen, & Espeseth, Reference Kraft, Kraft, Hagen and Espeseth2022; Wilkinson & Pickett, Reference Wilkinson and Pickett2018). Yet all will involve hundreds or thousands of SNPs covarying non-causally with psychological traits, and producing spurious GWAS/PGS results. They completely confound the preconditions for an RCT that Harden (Reference Harden2021) and others recommend.

Genetic causes

Burt says that “no serious scientist can suggest that genetic differences do not influence – in some complex, context-dependent way – developmental differences” (target article, sect. 6, para. 6). But we need to be clear that “influence” is not necessarily tractable as prediction. Unfortunately, prediction in BG is still dominated by the Galton/Fisher model. Despite acknowledging roles for the “environment,” “interactions,” and so on, mere attenuation of linear/additive genetic effects is assumed. So we get genomes described as “blueprints” (Plomin, Reference Plomin2019); or even as “cookbooks” (Harden, Reference Harden2021); whereas Madole and Harden (Reference Madole and Harden2023) assert that PGSs reveal an individual's “genetic propensity for a trait” (Madole & Harden, Reference Madole and Harden2023; sect. 3.1, para. 4); and that “the parental genotype causes an increase in their education” (Madole & Harden, Reference Madole and Harden2023; note 4). Burt (e.g., target article, sect. 6, para. 6) reveals the fallacies, and the dangers, in such logic.

But so do waves of recent research in molecular biology. The creative, anticipatory dynamics mentioned above, at the socio-cognitive level, have evolutionary precursors in learning/cognitive functions in cells, physiology, brain, and behavior (Lyon, Keijzer, Arendt, & Levin, Reference Lyon, Keijzer, Arendt and Levin2021; Richardson, Reference Richardson2020; Shapiro, Reference Shapiro2020). Development of form and variation does not start with gene transcription. DNA can do nothing until activated by the organism. That arises from vast signaling and metabolic networks monitoring the dynamic complexity and changeability of most natural environments. Their precursors in cytoplasm are inherited with genes, and their developmental fates are best described as emergent intelligent systems in which statistical patterns predict impending states by assimilating the covariance structures of the past and present (Richardson, Reference Richardson2021; Shapiro, Reference Shapiro2020).

That fundamental, multi-level, intelligence is seen in the context-dependent recruitment of transcription factors, cofactors, enhancers, promoters, and so on (Isbel, Grand, & Schübeler, Reference Isbel, Grand and Schübeler2022). Alternative splicing produces a diversity of proteins from the same gene (Wright, Smith, & Jiggins, Reference Wright, Smith and Jiggins2022). A single gene can be associated with the development of a variety of structures and functions (Watanabe et al., Reference Watanabe, Stringer, Frei, Mirkov, de Leeuw, Polderman and Posthuma2019). And multiple alternative pathways to desirable structural/functional endpoints are constructed in spite of genetic variation (Biddle, Martinez-Corral, Wong, & Gunawardena, Reference Biddle, Martinez-Corral, Wong and Gunawardena2021; Wagner & Wright, Reference Wagner and Wright2007).

Not even mutations comprise the random genetic lottery that Harden (Reference Harden2021) imagines (Monroe et al., Reference Monroe, Srikant, Carbonell-Bejerano, Becker, Lensink, Exposito-Alonso and Weigel2022). There are also processes – what Shapiro calls natural genetic engineering (NGE) – through which intelligent cells can themselves change genetic information: “NGE is shorthand to summarize all the biochemical mechanisms cells have to cut, splice, copy, polymerize and otherwise manipulate the structure of internal DNA molecules…Totally novel sequences can result from de novo untemplated polymerization or reverse transcription of processed RNA molecules” (Shapiro, Reference Shapiro2013, p. 287).

In other words, genes are best described as intermediary resource-providers for the organism as a whole: Servants to intelligent systems, not autonomous instructors. With the exception of relatively rare disorders or single-gene (Mendelian) variations, there are no independent “effects” of genomes. This is why Noble (Reference Noble2016) says we've had things the wrong way around in our descriptions of genetic causes. Baverstock (Reference Baverstock2021) uses the analogy of genes as the merchants that provide the necessary materials to build a house, but are neither the architect nor the builder. He calls for a “Copernican revolution” in our geno-centric view of living things.

Help or hindrance?

Burt asks if PGSs will ever be useful and urges caution. Fundamentally, though, it's the scientific framework – the Galton/Fisher model of heredity – that is the root of the problem. It persists, attracts funding and research effort, in spite of the logical, epistemological, and statistical errors described by Kempthorne (Reference Kempthorne1978) and others, because it affirms prior socioeconomic structures. Until that model is replaced by a more biologically realistic one it will be more of a hindrance to the advancement of knowledge than a help.