Critics of twin studies rely on vulnerable arguments, missing or even reinforcing more fundamental problems

Critics of twin studies as a means of linking human behavior to genes have a history of making vulnerable arguments and of missing or even reinforcing more fundamental problems. This is evident in Brian Palmer’s (2011) Slate article, “Double inanity.”

Consider a 2005 study by Rice University’s John Alford and his colleagues claiming to show that 43 percent of the variation in political ideology in the U.S. could be attributed to genetics… Duke political scientist… Evan Charney and Harvard geneticists Jon Beckwith and Corey Morris examined the flaws in the Alford study—and showed why all the other twin studies on heritability can’t possibly show what they purport to show… Twin studies rest on two fundamental assumptions: 1) Monozygotic twins are genetically identical, and 2) the world treats monozygotic and dizygotic twins equivalently (the so-called “equal environments assumption”). The first is demonstrably and absolutely untrue, while the second has never been proven.

The first more fundamental problem (let us call this MFP #1) is that no logical or empirical connection exists between heritability on one hand, which the so-called “quantitative genetics” estimates based on similarities of observable traits (such as height, IQ test scores,..), and, on the other hand, transmission of genes from parents to offspring.  Palmer as well as Alford assume that the two ideas are connected.*  The Alford study reports on measures of heritability but is titled “Are Political Orientations Genetically Transmitted?”  Palmer leads off by presenting a figure of 50% heritability (from a 2008 study) as “Genes determine 50 percent of the likelihood that you will vote.”  To counter MFP #1 critics need to take every opportunity to clarify—or at least point out—the confusingly multiple meanings of the term genetic, which include: runs in a family, percentage of genes shared (relatedness), associated with similarities of traits in genetically-defined varieties (heritability), predictability of trait changes in specific populations and locations (heritability), transmitted through germline (heritable), inborn, innate, difficult to change by environmental or social factors, etc.

(*In case the reader thinks they are connected because the definition of heritability is the proportion of variance of the trait associated with genetic differences, it is necessary to expand that last misleading shorthand to “associated with differences in the genotypic values,” that is, in the mean value of the trait for a genotype when measured across all environments in which it is raised.  This “genotype” is simply a synonym for variety; it does not refer to the pairs of alleles in the Mendelian sense.)

Now consider the flawed fundamental assumptions cited by Palmer.  The first is that monozygotic (MZ) twins are genetically identical.  This has been central to human twin studies, but such studies can be recalibrated to account for the actual proportion of shared genes in MZ and dizygotic (DZ) twins.  In any case, most of the ways that MZ twins are less than identical in their genes also influence the actual proportion of shared genes in DZ twins.  While departure from previous figures for genes shared in MZ and DZ twins increases the uncertainty (“error”) of heritability estimates, this is not a fatal blow to the method of data analysis involved in twin studies.

The second fundamental assumption cited by Palmer, the equal environment assumption, emerges from discussions that, in line with MFP #1, take heritability as a measure of the influence of genes and the percentage not included in heritability as a measure of the influence of environmental factors.   Disputing the equal environment assumption by examining how well twins share specific environmental factors runs the risk of reinforcing MFP #1.

Let me note three more fundamental problems in twin studies.  The easy slide from the “genetics” of heritability estimation in twin studies to the genetics of identifiable gene sequences is made possible because partitioning of trait variation into components uses models of hypothetical, idealized genes with simple Mendelian inheritance and direct contributions to the trait.  The analysis of trait similarity among relatives can, however, be undertaken without using models of hypothetical genes (Taylor 2012).  Recognizing this possibility makes it easier to dispense with the logically and empirical unjustified assumption that, all other things being equal, similarity in traits for relatives is proportional to the fraction shared by the relatives of all the genes that vary in the population.   After all, as can be shown using plausible models of the contributions of multiple genes to a trait, all other things being equal, ratios of DZ similarity to MZ similarity that are not .5 and vary considerably around their average (Taylor 2012).  MFP #2 then, which affects all twin studies to date, is that heritability estimates based on this assumption are unreliable.

Fundamental problem #3 is that, in analyses of human data, ‘‘genotype–environment interaction’’ variance is discounted or subsumed in an inflated estimate of “heritability.”  To explain this problem, the meaning of genotype-environment interaction in quantitative genetics, including twin studies, first needs clarification.  To aid this clarification, the following note uses variety and location where others might use genotype and environment.

In everyday terms, a high degree of variety–location interaction simply means that the responses of the observed varieties across the range of the observed locations do not parallel one another. That is, one variety may be highest for the trait in one location, but another variety may be highest in another location-or, at least, the difference between any two varieties may change location to location. This classical [quantitative genetics] sense of genotype–environment interaction is distinct from the use of the same term (or, synonymously, ‘‘gene-environment interaction’’) for situations in which the ‘‘genotype’’ denotes a value of a measured genetic factor, the ‘‘environment’’ denotes a value of a measured environmental factor, and an interaction means that the quantitative relation between the trait and one of the factors varies according to the measured value of the other factor (Taylor 2012).

It may be that genotype–environment interaction variance turns out to be a small component of the variance for most human traits.  However, to show this, not assume this, requires data sets that are rare (e.g., for the same population and location data are needed on MZ raised together, MZ raised in independent families, and unrelated sibs raised together).  The implications of MFP #3 are significant:

If it is not assumed that variety–location interaction variance can be discounted in human studies, two common claims become open to question: (a) The effect of family members growing up in the same location (family) is of small importance; (b) The trend for heritability estimates to increase over people’s lifetimes is evidence that ‘‘genetic’’ differences come to eclipse ‘‘environmental’’ differences…. The first claim requires showing not only that the location variance is a small component of the total variance, but also that the variety–location-interaction variance is small. The second claim also requires showing that the variety–location-interaction variance is negligible; otherwise it could equally well be that the interaction component increases over time (Taylor 2012).

The final MFP is a corollary of MFP #1:

the [genetic and environmental] factors underlying the development of observed traits may be heterogeneous, that is, they do have to be the same from one set of relatives to the next, or from one family (location) to the next. It could be that pairs of alleles at a number of loci, say, AAbbccDDee, subject to a sequence of environmental factors, say, FghiJ, are associated, all other things being equal, with the same outcome for the trait as are alleles aabbCCDDEE subject to a sequence of environmental factors FgHiJ (Taylor 2010). If underlying factors can be heterogeneous, the use of heritability as a basis for judging a trait to be a good candidate for molecular research… becomes unreliable (Taylor 2010). (Similarly for research that builds on the other fractions of the variance).

Even if it were to be shown that genetic differences among MZ twins did not qualitatively alter heritability estimates and that the equal environment assumption held in some cases, the four MFP’s render human heritability estimates unreliable quantitatively and as a basis for research into the genetics (in the sense of actual genes) of human behavioral traits.


Taylor, P. J.  (2010) “Three puzzles and eight gaps: What heritability studies and critical commentaries have not paid enough attention to,” Biology & Philosophy, 25:1-31.

Taylor, P. J.  (2012) “A gene-free formulation of classical quantitative genetics used to examine results and interpretations under three standard assumptions,” Acta Biotheoretica, 60(4): 357-378.


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