Zum Stand der Verhaltensgenetik

Ein interessanter Artikel zum Stand der Verhaltensgenetik:

Behavior genetics studies how genetic differences among people contribute to differences in their psychology and behavior. Here, I describe how the conclusions and methods of behavior genetics have evolved in the postgenomic era in which the human genome can be directly measured. First, I revisit the first law of behavioral genetics stating that everything is heritable, and I describe results from large-scale meta-analyses of twin data and new methods for estimating heritability using measured DNA. Second, I describe new methods in statistical genetics, including genome-wide association studies and polygenic score analyses. Third, I describe the next generation of work on gene environment interaction, with a particular focus on how genetic influences vary across sociopolitical contexts and exogenous environments. Genomic technology has ushered in a golden age of new tools to address enduring questions about how genes and environments combine to create unique human lives.

Quelle:  “Reports of My Death Were Greatly Exaggerated”: Behavior Genetics in the Postgenomic Era

In dem Artikel gibt es eine interessante Grafik, die den in Studien festgestellten Grad der Vererblichkeit mit den Annahmen in der Bevölkerung zur Vererblichkeit vergleicht:

Da sieht man zum Beispiel, dass die Veerbbarkeit politischer Ansichten unterschätzt wird, die der sexuellen Orientierung hingegen überschätzt wird. Letzteres dürfte aber auch damit zusammenhängen, dass sexuelle Orientierung oft weniger eine genetische Sache ist, sondern eine hormonelle (was zusammen hängen kann, aber nicht muss) und die Leute das nicht so passend differenzieren.

Interessant ist auch, dass die Kosten für Genanyalsen stark zurück gegangen sind:

The Human Genome Project, which took over a decade to complete, sequenced a complete human genome at a cost of approximately $3 billion. Now, a few decades later, the cost of whole-genome sequencing has plummeted, now being less than $1,000 per person. And the cost of whole-genome sequencing, which measures every DNA letter in a person’s genome, still far exceeds the cost of genotyping a person on a genome-wide single nucleotide polymorphism (SNP) array. Unlike whole-genome sequencing, a SNP array measures only a fraction of the genome, focusing on several million genetic variants that commonly vary between humans. SNP genotyping from noninvasive samples of human saliva is now available for less than $60 per person

Von 3 Milliarden pro vollständige Gensequenzierung auf ca 1000 Euro.

Gleichzeitig bringen große Datenbanken mit „Genmaterial“ auch neue Formen der Analyse:

elationship, not their perceived zygosity (Conley et al. 2013). Even more compellingly, genome-wide data can be used for so-called assumption-free methods that estimate heritability based on measured genetic relatedness (Visscher et al. 2006). One such method relies on the fact that sibling pairs randomly vary in the extent to which they inherit the same DNA segments from their parents (referred to as identity-by-descent sharing). The expectation is that siblings will share 50% of their segregating genetic variance on average, but this expectation is like the expectation that a coin will land on heads 50% of the time. In reality, any one pair of siblings can be more or less genetically similar, and variation across sibling pairs in their extent of identity-by-descent sharing can be leveraged to estimate heritability directly from DNA.
Just as a twin model estimates heritability by testing whether dizygotic twins are more different in their phenotype than monozygotic twins, the assumption-free method for estimating heritability tests whether sibling pairs who have less identity-by-descent sharing are more different in their
phenotypes than sibling pairs who have more. Other DNA-based methods for estimating heritability leverage small differences in the extent of measured genetic similarity found among pairs of people who would not typically be considered relatives (Yang et al. 2010): Are pairs of people who are more genetically similar also more phenotypically similar?

Hier wird darauf abgestellt, dass Geschwister nur theoretisch die gleichen Gene haben, theoretisch könnten sie sich sehr stark unterscheiden, zb wenn der eine mehr Gene vom Vater und der andere mehr Gene der Mutter erhalten hat oder eben der eine die „gerade“ 50% der Mutter und die „ungeraden“ des Vaters und der andere die „ungeraden“ 50% der Mutter und die „geraden“ des Vaters.

Damit kann man vergleichen wie die Unterschiede zwischen genetisch „gleicheren“ und „Ungleicheren“ Geschwistern sind. Eine spannende Sache.

Und zur Berücksichtigung in der Wissenschaft:

The DNA revolution has confirmed what we have known for some time: Genetic differences between people are a nonignorable source of heterogeneity in psychological and behavioral traits, including cognition, achievement, personality, psychopathology, social relationships, health behaviors, fertility, and beyond. One corollary of this conclusion is that genetic differences potentially confound nearly all correlational studies of the relationships between individual psychological outcomes and people’s environmental contexts. This is because environments are not purely exogenously imposed on the individual. Rather, they are selected or actively crafted, either by the individual or by other people (such as parents) who are genetic relatives.

Das große Dilemma der Sozialwissenschaften: Ihre Theorien versuchen aus dem sozialen Theorien über Personen aufzustellen, sie lassen dabei aber dann üblicherweise einen großen Punkt unberücksichtigt, eben zB das Kinder und Eltern nicht einfach nur mit einem bestimmten Erziehungsstil aufeinander einwirken, sondern eben sich auch noch gemeinsame Gene teilen. Diese wiederum können sowohl die Vorliebe für bestimmte Erziehungsstile aber auch die Empfänglichkeit für diese betreffen. Und noch schlimmer: Leute, die aus genetischen Gründen einen bestimmten Erziehungsstil bevorzugen könnten auch noch viele andere Punkte gemeinsam haben, etwa bestimmte Familienstrukten errichten, in besseren oder schlechteren Gegenden wohnen, mehr oder weniger Zeit mit ihren Kindern verbringen oder im Schnitt mehr Geld verdienen und damit ihren Kindern andere Möglichkeiten bieten können.

This is not a new observation. The problem of genetic confounding for social science, particularly for the nonexperimental research designs that are commonly employed in fields such as developmental and clinical psychology, has been repeatedly and cogently articulated for at least the past half-century. Yet, as Freese (2008, p. S19) noted,

Many quarters of social science still practice a kind of epistemological tacit collusion, in which genetic confounding potentially poses significant problems for inference but investigators do not address it in their own work or raise it in evaluating the work of others. Such practice implies wishful assumptions if our world is one in which “everything is heritable.”

Unfortunately, Freese’s (2008) assessment remains true more than a decade later. Perusing the contents of a single issue of a prominent journal in developmental psychology, for instance, one will find studies relating maternal depression and child intelligence, parental problem drinking and child sleep, maternal language and child executive function, child perceptions of caregivers and asthma-related immune function, family turbulence and child internalizing behaviors, parental structuring and child emotional eating, and maternal postpartum depression and child behavior problems. All of these studies use data from genetic relatives with only a cursory mention, at best, of the possibility that observed associations might be due to genetic inheritance. Whether one’s
research goals are to identify targets for intervention or contribute to a basic understanding of developmental processes, the continued proliferation of research studies with, as Freese (2008, p. S19) describes it, an “incisive, significant, and easily explained flaw” represents an enormous
waste of scientific resources.

Das Problem gut zusammengefasst. Was müsste sich ändern, damit das nicht mehr geschieht? In sozialwissenschaftlichen Zeitschriften müsste sich bei den Prüfern der eingereichten Artikel die Erkenntnis durchsetzen, dass Genetik eine Rolle spielt. Aber das führt dann entweder dazu, dass man seine eigene Studie indirekt entwertet, weil man hinzusetzen muss, dass die gefundenen Ergebnisse zumindest einmal nicht auf genetische Ursachen hin überprüft worden sind und dies erheblichen Einfluss haben kann oder die Forscher in dem Bereich müssten entweder in Kooperation mit Genetikern arbeiten oder zumindest auf dem Gebiet selbst ein gewisses Fachwissen aufbauen, was dann wieder schwierig ist.

Was hat man in den Studien so herausgefunden:

As genetic data have become more common (see the section titled Heritability in the Post-Genomic Era), GWAS research has accelerated rapidly. There have now been large-scale (N 30,000–1,500,000) GWASs conducted for a wide variety of phenotypes relevant for psychology, including psychiatric diseases, subjective well-being, personality traits, risk-taking behavior, substance use behaviors, educational attainment, cognitive ability, noncognitive skills, and body mass index (Buniello et al. 2019).
Overall, GWAS results have yielded two general lessons for psychology. First, traits of interest to psychologists are massively polygenic, meaning that they are associated with thousands upon thousands of genetic variants scattered throughout the genome, each of which has a tiny effect.
This has been called the fourth law of behavior genetics (Chabris et al. 2015).
Second, the aggregate predictive power of measured genetic variants, in some cases, rivals the predictive power of traditional social science variables, such as family socioeconomic status (SES) (Lee et al. 2018).

Also einmal die erneute Bestätigung, dass viele psychologische Züge durch eine Vielzahl von Genen beeinflusst werden und dann, dass die Vorhersagekraft an die der in den Sozialwissenschaften verwendeten Variabeln heranreicht. Letzteres könnte auch daran liegen, dass bestimmte Variabeln in den Sozialwissenschaften eben mit bestimmten psychologischen Zügen in enger Verbindung stehen.

In dem Zusammenhang mit der Erkenntnis, dass viele Züge auf einer Vielzahl von Genen beruhen und in Verbindung mit besseren Analysefähigkeiten sind dann auch eine Vielzahl von Studien überprüft worden, die auf der Suche nach DEM Gen für einen bestimmten Charakterzug oder andere Eigenschaften waren.

Given what we now know about the effect size of individual genetic variants in relation to psychological and behavioral traits (R2 0.1%), it is clear that psychological studies that interrogated single candidate genes, such as 5HTTLPR (a variant of the serotonin transporter gene), were massively underpowered statistically, and their results were false positives (Chabris et al. 2012). This methodological flaw—insufficient statistical power—is even more pronounced for studies of candidate gene × environment interaction (cG × E), such as studies of the interaction between 5HTTLPR and life stress on depression (Caspi et al. 2003). As early as 2011, analysts warned that most positive cG × E findings were false discoveries (Duncan & Keller 2011). In the next decade, subsequent review and editorial statements about candidate gene and cG × E findings warned that “it now seems likely that many of the published findings of the last decade are wrong or misleading and have not contributed to real advances in knowledge” (Hewitt 2012, p. 1), and that “the first decade of cG × E has produced few, if any, reliable results” (Duncan et al. 2014, p. 258).
Most recently, an analysis using preregistered analysis plans and samples as large as ∼400,000 people concluded that there was “no support for historical candidate gene or candidate gene-by interaction hypotheses for major depression across multiple large samples” (Border et al. 2019).

Also Single Candidate Gen Ansätze sind mit erheblicher Vorsicht zu genießen, eben weil meist eine Vielzahl von Genen eine Rolle spielen.
Deswegen ist eine Suche nach dem „Schwulengen“ auch relativ sinnlos. Eher werden es viele Gene sein, die beispielsweise jeweils für sich den prenatalen Testosteronspiegel leicht absenken und dann in einem Zusammenspiel (und auch einer Kombination von Genen, die ihn evtl sonst anheben, aber hier nicht zum Einsatz kommen) Homosexualität erzeugen können.

Dann zu der etwa gleichen Vorhersagekraft zu anderen Variabeln aus der Soziologie:

The extremely small effect sizes of associations with individual genetic variants means that the types of samples that psychologists typically work with (with N ranging from tens to thousands) are not useful for discovering new genetic variants that are relevant for social and behavioral phenotypes or for following up the effects of individual variants. However, the effects of genetic variants scattered throughout the genome can be aggregated together in the form of a polygenic score. Briefly, polygenic scoring takes the summary statistics from a GWAS and uses them as a type of scoring key for genetic data from a new (independent) sample of people. A person’s allele count (0, 1, or 2) at each SNP is multiplied by that SNP’s beta weight from the GWAS, and then the weighted counts are summed across the genome. The resulting polygenic score is a single number for each person that reflects an estimate, based entirely on DNA information, of their likelihood to display the target phenotype.
Because of differences between human populations in genetic ancestry, polygenic scores created using GWASs conducted in one population are generally less predictive of phenotypes in other populations (Duncan et al. 2019). Moreover, average polygenic scores cannot be compared across different ancestral groups (Martin et al. 2017). Currently, the vast majority of GWASs are conducted with European-ancestry populations, with large amounts of data coming from just a few countries, such as the United States and Iceland (Martin et al. 2019). Criticisms of the Eurocentrism of genetic research mirror criticisms of psychology’s focus on so-called WEIRD (Western, educated, industrialized, rich, and democratic) populations (Henrich et al. 2010).

Island bietet sich an, weil es eine recht überschaubare Bevölkerung mit hohem Verwandschaftsgrad hat und in ärmeren Ländern lässt sich eben schwieriger arbeiten.

Und zu den weiteren Schwierigkeiten in den „Poligenetic Scores“:

Unfortunately, the burgeoning predictive power of polygenic scores has led some high-profile academics to oversell them, referring to polygenic scores as fortune-tellers (Plomin 2018) or as measures of inborn or innate traits (Murray 2020). These statements reinforce the tendency to interpret genetic associations as evidence for genetic determinism or genetic essentialism (DarNimrod & Heine 2011) and are not supported by the evidence.

First, the magnitudes of the correlations with even the best polygenic scores, while mirroring the effect sizes typical in social and behavioral science, are far from the level of prediction accuracy necessary for valid individual prediction (Morris et al. 2019). Non-heritable variation in the phenotype, sampling error in the original GWAS used to create the polygenic score (Dudbridge 2013), as well as differences in sample composition between the original GWAS sample and the polygenic score sample (Mostafavi et al. 2020) attenuate the predictive power of the polygenic score.

Second, associations with polygenic scores—like the SNP associations detected in GWAS— can be tapping uncorrected population stratification, that is, they could be driven by environmental differences that systematically covary with genetics. The effect size of polygenic scores obtained from sibling fixed-effects models (i.e., from within-family designs) is a better measure of the association free from population stratification, as genes are randomized within sibling pairs (Trejo & Domingue 2019). Often, for behavioral and social phenotypes like education or childbearing, the within-family effect size is about half the between-family effect size (Lee et al. 2018, Mostafavi et al. 2020).

Third, even the causal effects of genetic variation might depend on transactions with environmental processes (Tucker-Drob et al. 2013). For instance, genetically influenced early traits in children might elicit greater cognitive stimulation from caregivers, which further facilitates the development of intelligence (Tucker-Drob & Harden 2012). Such “outside the skin” processes for genotype–phenotype relationships are expected to be the norm for psychological development. Other research has found that the polygenic score of a focal person is associated with their phenotype because it is indirectly measuring the genotype of the focal person’s parent, who is providing environments relevant for the phenotype. One clever demonstration of this was a study showing that polygenic scores are less predictive of a person’s educational attainment if they are adopted than if they are raised by their biological parents (Cheesman et al. 2019). In the case of adoptees who are not genetically related to their parents, the polygenic score is not revealing anything about the environment provided by those parents.

Also eine Karstellung, dass man aus der Score erst einmal nichts über das Individuum sagen kann (sondern eher nur über den Schnitt und gewisse Tendenzen).

Und zu Anwendungen der Score:

There are, of course, some differences between polygenic scores and other social science variables that make them interesting for research purposes. DNA sequence is fixed at conception; thus, polygenic scores do not change over the course of an individual’s lifespan. As such, they are immune from reciprocal causation. This makes them useful for studying recursive processes, such as peer influence or academic achievement. For instance, one study examined the peer metagenomic context to study peer influences on smoking (Sotoudeh et al. 2019). One person’s behavior might change their peers’ behavior, but it cannot change their peers’ DNA. Consequently, relationships between peer DNA and one person’s smoking can offer new insights about peer influence. Another study used polygenic scores to examine students’ trajectories through the high school math curriculum. Unlike measures of math ability or interest, which are dynamic and could be affected by the difficulty of one’s previous math classes, polygenic scores are inert and can thus be used as molecular tracers to see how students with fixed characteristics progress in their STEM education (Harden et al. 2019)

Man kann also mit diesem Werkzeug durchaus interessante Forschung betreiben.

Auch interessant: Folgestudien:

The immutability of polygenic scores also makes it possible for researchers to add genetic information long after the conclusion of the study. For example, people who participated in a study of early childhood intervention could be genotyped as adults, thus adding a new source of
information about their childhood that is not tainted by recollection biases or errors (see Rietveld et al. 2013, supplement, for a discussion of this idea). Moreover, a person’s genetic information can be used to create multiple polygenic scores—as many as there are available GWASs—and these polygenic scores can be updated as new genetic insights become available, without new contact with the participants.

Finde ich einen spannenden Bereich, weil es für alte Ergebnisse mögicherweise neue Erklärungen gibt.

Dann ein Ausblick auf die Zukunft, auch gerade zur Forschung über Gene-Umwelt-Interaktionen:

In the following sections, I consider three streams of research on gene–environment interplay, broadly defined:
(a) research that uses genetic information to reveal the ways that social privilege is transmitted across generations;
(b) research that considers how genetic influences vary as a function of sociopolitical or historical context, the life course, and other social structures; and
(c) research that uses exogenous environments (e.g., interventions, policy reforms, and natural experiments) to understand the mechanisms of genetic effects and heterogeneity in response to environmental change.

Throughout, I focus on examples from genetic research on cognitive ability and educational attainment but suggest how similar designs could be used for the study of other psychological phenotypes.

Dazu dann im Einzelnen:

Studying the Genetic Lottery Reveals the Importance of the Social Lottery

The importance of genetic influences is often misinterpreted to mean that family-level environments, such as school contexts, neighborhood conditions, family SES, and parenting behaviors, are unimportant. One prominent behavioral geneticist, for instance, summarized twin studies as demonstrating that parents and schools “matter, but don’t make a difference” (Plomin 2018, p. 82). This is false. Twin and adoption studies do indeed pose a challenge to a naïve environmentalism that presumes that all correlations between parents and children are due to the effects of the former on the latter. Resemblance among family members for some psychological phenotypes is, indeed, primarily due to the fact that they are genetically related (Polderman et al. 2015). But twin studies (in conjunction with molecular genetic studies, which are discussed in more detail below) provide some of the strongest evidence that families reproduce their social privilege across generations through environmental mechanisms, not just genetic ones.When it comes to whether one is poor or rich, educated or uneducated, the family-level environment in which the person was raised does certainly make a difference.

Also auch hier wieder etwas, was deutlich macht, dass es ein Zusammenspiel gibt und nicht eine Variante allein relevant ist.

Evidence from twin and adoption studies.

The importance of shared environmental influences is most clearly apparent for educational attainment, defined as the number of years of schooling that one completes. People with more education make more money, are more likely to be employed in prestigious occupations, are more likely to be married and to avoid nonmarital childbearing, have higher subjective well-being, and live longer (Case & Deaton 2017, Deaton
2013). A meta-analysis of 15 twin studies spanning 10 countries found that 36% of the variance in educational attainment, on average, was due to environmental factors shared by children raised in the same home, i.e., the family-level environment (Branigan et al. 2013). In one-third of the included studies, the proportion of variance attributable to the shared environment exceeded the estimated heritability; that is, for many cohorts of people, the social lottery remains even more important than the genetic lottery in shaping how far they go in school.

Shared environmental influences on educational outcomes are also evident at earlier points in the educational trajectory. Whereas more basic cognitive abilities like executive functioning and processing speed are nearly perfectly heritable even in childhood (Engelhardt et al. 2015), academic skills in reading and mathematics, which are the direct targets of instruction, show substantial shared environmental variance, even when all participants are drawn from schools in a single geographical area (Engelhardt et al. 2019, Rimfeld et al. 2018b).

In Germany, shared environmental influences are minimal for cognitive test performance but are substantial in relation to whether a student is tracked into gymnasium, i.e., the college-preparatory academic track that permits matriculation to university (Schulz et al. 2017). In societies that reproduce privilege across generations, the family environment in which one is raised makes a difference in how far one goes in school.

Also ein erheblicher Einfluss sowohl der sozialen Umstände als auch der genetischen. Und für Deutschland das Ergebnis, dass Kinder aus „gutem Haus“ eher aufs Gymnasium gehen und Kinder aus „weniger guten Haus“ es trotz gleicher Noten dann eher bei der Realschule belassen.

In contrast to what is seen for educational attainment, most studies find a minimal effect of shared environmental factors on cognitive abilities, particularly when measured in adulthood. It has been suggested, however, that this near-zero main effect of the family-level environment masks the heterogeneity of the effects of the shared environment across the SES spectrum. An early paper by Turkheimer et al. (2003) analyzed data from a sample of twins with an unusual overrepresentation of children in poverty and found substantial effects of the shared environment on cognitive ability at age 7. Subsequent research on the genotype × SES interaction effect yielded mixed results, with several studies finding null effects or even effects in the opposite direction. However, a meta-analysis of this literature (Tucker-Drob & Bates 2016) found evidence of a significant interaction effect (albeit with a smaller effect size than estimated by Turkheimer and colleagues, an example of the winner’s curse), particularly in the United States.
The importance of the shared environment for cognitive ability has also been demonstrated using adoption studies. In particular, population-wide data from Sweden allowed researchers to estimate the impact of the family environment using a unique sample of male-male sibling pairs where one brother was adopted while the other brother was raised by his biological parents (Kendler et al. 2015). The IQ score of the adopted brother was, on average, ∼4 points higher, an increase that varied with the education level of the adopting parents.

Jetzt sind 4 Punkte auch nicht die Welt, aber dennoch eine interessante Studie.
Und dann eine Besprechung von Score Studien:

Evidence from polygenic score analyses.

In addition to evidence from classical twin studies and adoption studies, the advent of polygenic scores has provided even more evidence that families reproduce their social privilege through environmental mechanisms. One particularly noteworthy study analyzed a large sample of trios (a focal person and both of their parents) from Iceland, using a design that allows researchers to examine the genetic variants that children inherit from their parents as well as the genetic variants that they do not inherit (Koellinger & Harden 2018, Kong et al. 2018). (Recall that humans are diploid organisms with two copies of every gene, only one of which is randomly transmitted to any child.) If the parental genes that a child does not inherit are nevertheless associated with the child’s phenotype, this association must be due to environmental transmission from parent to child, as genetic inheritance has been ruled out by design. This is exactly what was observed for educational attainment: The nontransmitted parental genotypes were associated with the child’s educational attainment.
Other research has compared how children with similar polygenic scores fare differently in life as a function of their social background. A notable study by Belsky and colleagues (2018), which pooled data from five samples that spanned several countries and birth cohorts, examined how
polygenic scores created from a GWAS of educational attainment predicted intergenerational social mobility, i.e., whether a person’s increased or decreased in social class relative to their parents They found that higher polygenic scores predicted greater social mobility, even when comparing within sibling pairs. As sibling genetic differences are random, the within-family analysis is compelling evidence that genetic differences between people are causally related to social mobility. At the same time, children with high polygenic scores who were raised in low-SES families still ended up worse off, as adults, than children with low polygenic scores who were raised in high-SES families.

Das zeigt also auch wieder einen deutlichen Einfluss sowohl der Gene als auch des Umfeldes. Aber selbst Kinder mit einer „Guten Veranlagung“ die in Familien mit einem „schlechteren sozialen Umfeld“ aufgewachsen sind haben schlechter abgeschnitten als Kinder mit einer „schlechteren Veranlagung“ in „guten Familien“, wenn ich es richtig verstehe.

Hier der Abstract der Studie dazu:

A summary genetic measure, called a “polygenic score,” derived from a genome-wide association study (GWAS) of education can modestly predict a person’s educational and economic success. This prediction could signal a biological mechanism: Educationlinked genetics could encode characteristics that help people get ahead in life. Alternatively, prediction could reflect social history: People from well-off families might stay well-off for social reasons, and these families might also look alike genetically.

A key test to distinguish biological mechanism from social history is if people with higher education polygenic scores tend to climb the social ladder beyond their parents’ position. Upward mobility would indicate education-linked genetics encodes characteristics that foster success. We tested if education-linked polygenic scores predicted social mobility in >20,000 individuals in five longitudinal studies in the United States, Britain, and New Zealand. Participants with higher polygenic scores achieved more education and career success and accumulated more wealth. However, they also tended to come from better-off families. In the key test, participants with higher polygenic scores tended to be upwardly mobile compared with their parents. Moreover, in sibling-difference analysis, the sibling with the higher polygenic score was more upwardly mobile. Thus, education GWAS discoveries are not mere correlates of privilege; they influence social mobility within a life. Additional analyses
revealed that a mother’s polygenic score predicted her child’s attainment over and above the child’s own polygenic score, suggesting parents’ genetics can also affect their children’s attainment through environmental pathways. Education GWAS discoveries affect socioeconomic attainment through influence on individuals’ family-oforigin environments and their social mobility.

Klingt etwas anders als in der Zusammenfassung in dem hier besprochenen Artikel, vielleicht muss ich mir die Studie noch mal genauer anschauen, das Thema an sich ist ja sehr interessant.

A complementary analysis of overlapping data (from the Health and Retirement Survey) from an independent group of investigators found additional evidence for an interaction between polygenic score and child SES in predicting rates of college graduation, with stronger genetic associations evident among high-SES families (Papageorge & Thom 2019). [The direction of this interaction is consistent with twin studies of G × SES interactions (Tucker-Drob & Bates 2016).] A college degree, in turn, was a strong predictor of labor market earnings at all levels of the polygenic score.

An interaction between polygenic score and social privilege was also evident in a study that we conducted on the relationship between educational attainment polygenic scores and progress through the high school math curriculum (Harden et al. 2019). On average, higher polygenic scores were associated with tracking to more advanced math classes at the transition to high school and with greater persistence in math across all four years of high school, even when controlling for family SES and math course grades in the previous year. However, students at socioeconomically advantaged schools (those primarily serving families with higher levels of parental education) were buffered from dropping out of math even if they had relatively low polygenic scores. Together, these studies reveal environmentally rooted inequities in the extent to which genetic differences between people are translated into human capital and socioeconomic attainments.

Ich persönlich finde solche Studien wesentlich informativer als die einfache Behauptung, dass es alles rein sozial ist.

Genetic Influences in Sociopolitical and Historical Context

The biologist Richard Lewontin was one of the twentieth century’s most vehement critics of behavioral genetics. In a still widely cited paper, Lewontin (1974) took aim at twin studies, and more generally, at linear regression models, path analysis, and the analysis of variance. He criticized the results of twin models, because they depend on the particular distribution of genes and environments in the population being studied, for having a “historical (i.e., spatiotemporal) limitation”; the “spatiotemporally local analysis of variance” was described as “useless,” in contrast to the “global analysis” of “functional relations,” i.e., mechanisms of gene action.

Lewontin was correct, of course, that behavioral genetic methods are local analyses that make statements about specific populations of people living in a specific time and place; but the biologist’s trash has turned out to be the psychologist’s and sociologist’s treasure. Nearly a half-century after Lewontin’s critique, it is now clear that analyzing genetic associations with human psychological outcomes in spatiotemporally local samples has yielded interesting insights about how such associations differ across historical and sociopolitical context—and how they do not.

One major theme that has emerged from historical and cross-national comparisons of twin data is that heritabilities are generally higher at times and places that provide large amounts of social opportunity. Four recent papers, in particular, support this idea.
First, data from the World Bank on national differences in intergenerational social mobility, defined by the parent-child correlation in years of schooling, were matched to results from twin studies of educational attainment (Engzell & Tropf 2019). In countries with lower social mobility (such as Italy and the United States), shared environmental variance in educational attainment was higher (and heritability was lower) than in countries with higher social mobility (such as Denmark).

Das wäre ja interessant auch wenn ich jetzt nicht gedacht hätte, dass Dänemark eher Aufstiegsmöglichkeiten bietet als Italien. Aber es macht durchaus Sinn, dass jemand mit „Guten Genen“ auch Gelegenheiten haben muss um aufzusteigen bzw diese dann auch besser nutzen kann.

Second, an earlier paper compared just two twin samples and similarly concluded that “family background buys an education in Minnesota but not Sweden” ( Johnson et al. 2010).

Vielleicht liegt es daran, dass Unis in den USA sehr teuer sind und sich daher soziales „Startkapital“ eher auswirkt.

Third, within the United States, the association between polygenic score and educational attainment differed by birth cohort and gender. In an older birth cohort (born 1939–1940), the genetic association was stronger for men than for women. However, as structural constraints on women’s access to education diminished over the course of the twentieth century, the gender difference in the predictive power of the polygenic score similarly diminished; that is, social opportunity led to stronger genetic associations.

Auch ein klassiker: Um so gleicher die Möglichkeiten für alle werden, um so mehr Gewicht haben biologische Unterschiede.

Fourth, analyses of data from Estonia show a similar pattern, albeit over a more dramatic social transition (Rimfeld et al. 2018a). The heritability of educational attainment, as estimated based on measured DNA rather than twin data, was compared for Estonians who came of age during and after the Soviet regime. In comparison to earlier cohorts who were raised in a totalitarian government that provided little social opportunity, later cohorts of Estonians showed higher heritability of educational attainment.

Das Öffnen von Möglichkeiten nach dem Ende der Sovietunion lässt sicherlich interessante Studien zu.

Together, these results reveal that more open societies—e.g., those with intergenerational social mobility, gender equality in education, and nontotalitarian government—are typically associated with stronger effects of genetics and weaker effects of the family social background.Whether or not inequalities tied to genetics are more palatable than inequalities tied to family social class is a different question. As political philosopher John Rawls stated, “once we are troubled by the influence of either social contingencies or natural chance on the determination of distributive shares, we are bound on reflection to be bothered by the influence of the other. From a moral standpoint the two seem equally arbitrary” [Rawls 1999 (1971), pp. 64–65].

Vielleicht auch ein Grund, warum soziologische Theorien mit der Eröffnung von weiteren Möglichkeiten weniger überzeugend sind bzw warum biologische Erklärungen an Raum gewonnen haben

Und noch aus der Zusammenfassung:

The study of how genes contribute to individual differences in human psychology will probably always be an object of fascination and fear. The field of behavioral genetics connects some of our most cherished aspects of human identity and our most prized accomplishments to an accident of birth that preceded our conscious awareness. This fascination and fear fuel continuing controversies over statistical parameters like heritability and over the legitimacy of conducting behavioral genetic research at all. In the past few decades, there have been incredible technological advances that have made it possible to measure the human genome directly. This genomic technology has not, as some people feared, vindicated a biodeterministic view of human development. As described in this article, genetic studies have provided some of the strongest evidence for the continued importance of the social environment for the human life course. At the same time, neither has genomic technology invalidated the central methods and conclusions of human behavioral genetics. Instead, the future of behavior genetics is both more nuanced and more scientifically interesting than the picture painted by its ardent champions or its vociferous critics.
Never before have behavior geneticists had such a wide array of powerful tools; never before have the methodological and theoretical challenges of connecting DNA to human thoughts, feelings, behaviors, and identities been more apparent.

Und das Gebiet wird sich immer noch weiter entwickeln. Allein schon weil Auswertungen noch billiger und einfacher werden.

Die Zusammenfassung:

SUMMARY POINTS
1. Genetic differences between people matter for every aspect of their thinking, feeling, and behavior. Psychological characteristics and behaviors are typically influenced by very many genes.
2. We can now measure the human genome cheaply and easily. Results from genomic research have validated many of the assumptions of traditional behavioral genetics, and family studies are more important than ever.
3. Studies on candidate gene × environment interactions, as well as studies that correlate aspects of child development with aspects of environments provided by biological relatives, continue to be popular within psychology. These studies are methodologically flawed, are unlikely to yield true insights, and waste valuable scientific resources.
4. Advances in genotyping technology, open science practices, massive sample sizes, and large-scale international collaborations have finally begun to yield replicable knowledge about specific genes associated with human psychology and behavior. This knowledge can most readily be put to use by psychological researchers in the form of polygenic scores.
5. Genetic research has provided strong evidence that families reproduce their social privilege across generations via environmental mechanisms. It has also shown that the effects

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