Genetic aspects of intelligence.

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Annu. Rev. Genet. 1975.9:387-405. Downloaded from www.annualreviews.org by Memorial University of Newfoundland on 08/04/14. For personal use only.

INTELLIGENCE R. C. Lewontin

Museum of Comparative Zoology, Harvard University, Cambridge, Massachusetts

02138

WHAT IS THE QUESTION? What do we really mean when we say we want to understand the genetics of IQ (or nose length)? There are three levels at which we might be operating. Most basically, we might want to know how the primary products of all the structural genes and their controlling elements enter into the synthetic and metabolic processes that underlie central nervous activity and the way in which that activity is modulated by external inputs. It is in this sense that we understand the genetics of protein coat formation in A phage. But no serious person would suggest that genetic analysis of intelligence in man is anywhere near such a level of understanding. We may even doubt that when the tools and concepts for such an analysis become available, anyone will bother using them for an analysis of intelligence. Second, and much closer to what is possible in higher organisms, we may be content to carry out a phenogenetic analysis at a gross phenomenological level. That is, we may simply wish to get our hands on as many different genotypes as possible, allow these genotypes to develop in a wide range of environments, varying in as many different environmental dimensions as seem relevant for the species, and plot the norms of reaction for the various genotypes. Indeed, this study of norms of reaction is the proper object of research-if we are interested in knowing how various historical changes in human social organi zation and educational practice will affect human behavior. This is the only correct sense in which we can study the "nature-nuture" problem, the problem of the interacting genetic and environmental causes of phenotype (31). It is in this sense that we analyze the genetics of larval viability in Drosophila (8). But even this level of investigation is denied us for human traits, most especially behavioral traits, because we simply cannot replicate human genotypes over and over and follow their development in different environments. Indeed, we do not even know what we mean by environment in this case since it presumably includes the overwhelming complexity of social milieu and is itself an autocor related developmental process. 387


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Third, if we have the basic phenogenetic information embodied in the norms of reaction, we could study the population genetics of intelligence by charac terizing the joint frequency distribution of genotypes and environments and then use the norms of reaction to relate this joint frequency distribution to the frequency distribution of some measure of intelligence in a population. This is the operation we must perform if we wish to ask what the population consequences would be of some social or educational policy that would change the distribution of environments or the assortment of genotypes among environ ments. It is in this sense that we understand the population genetics of sickle-cell. anemia. But this level of study is also barred to us in the case of human behavior both for the reason that we cannot measure the norms of reaction of particular genotypes and because we cannot enumerate human genotypes. (There exist various prescriptions for enumerating human environments, but we do not know whether they take into account all or any rele\!ant variables). Thus we see that since there is no present way to enumerate human genotypes nor to characterize their norms of reaction with respect to any human behavioral trait, we are unable to answer questions such as "How much can we boost IQ and scholastic achievement? " (22) especially when an untold diversity of human social and individual environments are yet to be encountered. This last point needs emphasis. Even if we could measure norms of reaction for human genotypes and these norms were characterized only over the present range of environments, we could not know what future environments would bring. So, for example, the statement, "There is no reason to believe that the IQ's of deprived children, given an environment of abundance, would rise to a higher level than the already privileged children's IQ " [Jensen (22) p. 91] is historically incorrect. For example, the expectation of life of the most "deprived " class at present in the United States is twice as high as was the average expectation of life of the British nobility in the 17th century. If we cannot study the genetics of intelligence in any of the senses discussed, what can we do and what questions can be asked? All that remains is to take the standard approach of biometrical genetics and to try to partition the total variation in observed phenotypes in a population into genotypic components, environmental components, and genotype-environment interaction components. This procedure, which is used for measured characters in a great variety of organisms, is emphatically not a partition of causes in any global sense, but a local analysis, valid only for a particular population in a particular range of environments (31). It partitions the total phenotypic variance present in the character into (a) variation among mean phenotypes of different genotypes, averaged over environment, the genetic variance; (b) variation among mean phenotypes in different environments averaged over genotypes, the environmental variance; (c) variance not accounted for by the two previous categories, the genotype-environment interaction variance. It may be possible, with proper experimental designs, to further subdivide the genetic variance into contributions from the additive and nonadditive effects of genes. What questions can be answered once this analysis has been made? First, we may ask the qualitative question whether genes matter at all in the variation of the character, that is,


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are the genetic and/or genotype-environment interaction variances different from zero. Note that this is not the same as asking whether genes matter at all in the determination of the character since the genetic variance could be zero either because genes are really irrelevant to the character in a causative sense, or because the particular population has no relevant genetic variation at that time. Second, we may want to get an intuitive feeling for the "importance" of genetic variation in the population and a reasonable measure of this relative importance is the broad heritability h82, which is the ratio of the genetic variance to the total variance. This descriptive measure has no prescriptive power and certainly does not measure how sensitive the character might be to environmental change. A character may have a broad heritability of 1.0 yet be drastically altered by a change in environment. This is the case of "inborn errors of metabolism, " such a s Wilson's disease (resulting from the retention o f copper), which have a heritability of 1.0 yet may be treated by appropriate dietary intervention. Finally, we might want to know what the effect on the population mean would be if there were natural or artificial selection in favor of a high or low score for the character. For this purpose, we need the narrow heritability, hN2, which is the ratio of the additive genetic variance to the total variance. Narrow heri tability could also be used to predict a change in phenotypic variance for a character if the pattern of assortative mating in the population changed. Neither narrow nor broad heritability, which are measured within populations, has anything to say about the causes of differences between populations. It appears, then, that no very pressing or compelling social or scientific questions can be asked from a genetic analysis of variance of intelligence. Jencks (21, p. 76) comes to this conclusion from the point of view of the social scientist when he says, "Indeed, our main conclusion after some years of work on this problem is that mathematical estimates of heritability tell us almost nothing about anything important. "

THE THEORY No new or original theory is required to apply the methods of quantitative genetics to human intelligence. The foundations of the theory were laid down by Fisher in 1918 (13) with important reformulations and additions by Wright (52) and Mather (34), especially Wright's method of path coefficients (53). All techniques are based upon the same general conceptual framework. Inheritance generally means the passage of information relating to phenotype from parent to offspring so that relatives of various degrees resemble each other to a greater or lesser degree. But inheritance may be by way of Mendelian genes or by way of social and cultural phenomena, including the inheritance of property, for example. The "genetic problem" is then to distinguish the similarity between relatives that arises from genetic inheritance from that which arises from non genetic inheritance and social correlations. To do this, the theory of Mendelian inheritance is used to predict the genetic correlation between relatives; the predictions are compared with the observed correlations, and from these com parisons estimates are made of how much of the population variation can be


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ascribed to genetic variation. Of course, the pattern of observed correlation might be explained entirely by some hypothesis of environmental pattern of similarity, but the asymmetry of the procedure, ascribing to environmental variation only what has not been already explained genetically, is rationalized on the basis of simplicity. That is, the genetic explanation is said to have an exact form given by Mendel's laws, while an environmental explanation of the same facts is, in some sense, ad hoc (23). Unfortunately, the situation is not so neat. The "exact " genetic prediction depends upon unknown parameters of gene action, allele frequency, and genotypic assortative mating. As shown by Fisher, the number of gene action parameters (additive effect, dominance devia tion, epistatic interactions) goes up exponentially with the number of loci. The problem is even more complex than he made it because he ignored the phenom enon of linkage. Even under the most simplifying assumptions allowable, it is at least necessary to estimate an average additive effect, dominance effect, and assortative mating parameter; the predicted correlation between relatives on a genetic basis is a function of these parameters. The parameters must be estimated from the data to which the model is to be fitted, so that, in part at least, the genetic model is ad hoc, and the number of degrees of freedom left to actually test the genetic model is not great. Superimposed on this problem is the fact that any reasonable environmental hypothesis predicts data with the same general structure as the genetic hypothesis, i.e. that correlation decreases progressively with more distant relationship. Since, in any case, the correlation between monozygotic twins cannot exceed 1.0 and the correlation between unrelated persons cannot be lower than 0, there is a serious problem of deciding whether a genetic model with four parameters estimated from the data is really to be preferred to an arbitrary model that predicts some rate of decrease of ' environmental similarity with distance of relationship. An illustration or this problem is the work of Eaves (9) on IQ similarities between individuals related to each other through four ancestral generations. The phenotypic correlation between relatives separated by n + 1 steps from their closest common ancestor is r n

=

1 (n + I)An-IC 1(I - C ) C1 C 2( I + A )n + 2

2

1.

2

where A is the genotypic correlation between mates, C1 is the broad heritability of the trait, and C2 is the proportion of genetic variance that is additive. Evalua tion of these quantities requires separate estimates of environmental variation within and between families, an estimate of the genotypic assortative mating parameter, and an estimate of additive and nonadditive components of genetic variance. The data were insufficient for this purpose so a variety of arbitrary sets of values were postulated for assortative mating and for the relationship between dominance and between-family environmental variance. Of the various choices tried, the best-fit model gave a narrow heritability of about 0.6 and a genotypic assortative mating correlation of 0.27. The reader may note that equation I predicts that correlation between relatives falls off exponentially

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with degree of relationship with three parameters to be fitted. It is hard to know in what way such a "model" is more concrete than an arbitrary power series. There is something of the fallacy of misplaced concreteness here. No matter how exact a model I have of a phenomenon, if the model only predicts a power-series relationship with unknown parameters to be estimated from the

data, then the degree of fit of the prediction to the observations cannot favor the model over any other with a similar number of undefined parameters. A similar criticism of Jensen's (22) tabulation of observed and "theoretical" corre lations between relatives has been made by Kamin (27) who points out that much of the good fit of the genetic theory comes from using the data to construct the theory. Another difficulty evident in both Eaves' paper and Kamin's analysis of Jensen is that dominance and between-family environmental variation are reciprocally related in the theory so that large compensating variation in these parameters leaves the prediction unchanged. This means, in turn, that heritability estimates may vary widely for the same data since h2 is very sensitive to changes in the underlying model that do not change the fit of the observations. Hogarth ( 19) has examined in some detail the sensitivity of heritability estimates to

assumptions about assortative mating and the environmental variance within families, expressed as the difference in environmental correlation in monozygotic and dizygotic twin pairs. His conclusions are that many different underlying

genetic models may produce very similar observed correlations between relatives so that working backward from observed correlation to genetic-environmental models is very unreliable. In particular, assumptions about correlations between genotype and environment turned out to be critical. All of the difficulties discussed above arise because both environmental and genetic theories predict qualitatively the same results, a decreasing similarity with decreasing relationship. The way to get around this problem is to break the connection between genetic relationship and environmental relationship.

In experimental plants and animals this is done by randomizing relatives over environment. In the human species, this means adoption studies. Haseman & Elston ( 16) and Jincks & Fulker (25) have shown how estimates of heritability are necessarily biased when the only data available are from relatives of different degree without fostering or adoption studies. Thus the widel y used estimates of broad heritability that depend on the difference and monozygotic twin correlations, r, such as (rMZ - rDz) /( 1 - rDZ) H 2(rMZ- rDZ) /rMZ HR H2 (rMZ- RDz) /(l - PDZ) =

=

=

Holzinger (20) Nichols (36)

2. 3.

Jensen

4.

(22)

(where PDZ is the genetic correlation between DZ twins) or the so-called MAV A estimates of Cattell (6) are all upwardly biased estimates that leave out environ mental variance either within or between families. No data, no matter how

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extensive, or no matter what degree of genetic relationship, that does not break the relation of genetic to environmental similarity arising from human family structure can give an unbiased estimate of heritability. lincks & Fulker show

that to estimate broad heritability, it is necessary to estimate four parameters, G1, G2 , E1, and E2 , the genetic and environmental variances within and between families, and, at the same time, to test four assumptions: 1. No genotype-en vironment interaction, 2. No environmental correlations, 3. G1 + G2 total genetic variance in the population whenG1 andG2 are estimated for a particular kind of relationship, say sibs, 4. El and E2 do not depend on the genetic relationship; for example, that the family environments of MZ and DZ twins are the same within and between families. Layzer (29) has emphasized the importance that assumptions 2 and 4 play in all heritability estimations. To carry out the necessary estimation and tests, Jincks & Fulker describe a minimal set of data consisting of MZ twins raised together, DZ twins raised together, and either MZ or DZ twins raised "apart. " By apart is meant that the twins must be randomized over home environments, a problem to which we shall return. If, in addition to the minimal set, there are also data on other degrees of relationship, for example parent-offspring and full-sib correlations, a further subdivision of genetic variance into additive and dominance compo nents can be made. The methods suggested, however, fail to take into account either epistatic interactions or linkage between genes, both of which will bias the estimate of dominance variance. Finally, the theory developed by Mather (34) is used by them to estimate the number of loci segregating for intelligence. This technique is quite useless, however, since it takes no account of linkage or gene frequencies and is the weakest part of Mather's theoretical apparatus. In addition to the classical methods of analysis of variance, there exists an alternate scheme of analysing causes: Wright's method of path coefficients (53). This technique involves the drawing up of a specific scheme of causational paths showing all the relationships among the variables, and then assignment of numerical values, the path coefficients, to each causal link. While the same data on correlations between relatives are used as in analysis of variance, path analysis has the advantage that all of the assumptions about causation are explicit in the particular model used. So, for example, if there is a path in the model from father's genotype to child's genotype, and thence to child's phenotype, but none from father's genotype to father's phenotype and thence from father's phenotype to child's phenotype, then it is immediately clear that the model assumes no direct causal relationship between father's IQ and child's IQ, but only the indirect one via the genes. The disadvantage of the scheme is that it requires many more observed correlations to solve the model and thus almost inevitably requires the assembly of data from a diversity of sources and studies [see, for example, Appendix B in Jencks (21) and Rao, Morton & Yee (39)]. The other difficulty with path analysis is that there is seldom a test of the structural sensitivity of the modeL That is, what effect does leaving out one pathway in the model have on the estimates of the remaining paths? Some insight into the structural problem is provided by MacLean, Morton & Lew


=


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(33). As with the requirements for the analysis of variance, there is an absolute requirement for information on adopted children and on correlations between mates in order to work out heritabilities, and, in fact, path analysis is a form of the analysis of covariance, although a particularly illuminating one. The final element of theory that needs to be brought in is the statistical theory of sampling. How certain are estimates of components of variation and heritability? The general sampling theory of heritability is spottily developed, except insofar as the sampling theory of the analysis of variance is known. Standard errors of broad heritability estimates from a variety of standard methods (all of which are biased in human populations) have been worked out by Klein, DeFries & Finkbeiner (28) and their conclusion is that "quantita tive genetic analysis should not be undertaken unless resources are available . . . [for] . . . testing of at least 400 families of four members each. " There are no such studies known to me.

REQUIREMENTS OF A PROPER STUDY If we accept, for the moment, the limited objective of analyzing the total variance for IQ performance into genetic and environmental components, it is fairly easy to specify the requirements that any observations must meet to qualify as a proper experiment whose results are worthy of serious consideration. I. Sample sizes must be large, a few hundred families of each type in the investigation (28). 2. A single set of test instruments, standardized for age and sex in the popula tion to be sampled, must be used for all comparisons. The standardization for age is particularly important since twins are necessarily the same age and therefore more similar than other degrees of relationship. If identical twins are in the study, then sex standardization is also essential. 3. The test instruments must be administered in such a way that the method of administration and the evaluation of the results are independent oCknowledge about the relationship between the subjects tested. So, for example, an individual oral test cannot be used on twin pairs by the same examiner, since the examiner will form judgments about the similarity of the twins on the basis of appearance, speech, etc. 4. The relationship pairs (sibs, twins, parent and offspring, etc) must be chosen as a representative sample over relevant environmental variables, relative to the population to be described. Thus, if it is the white population of the United States that is the population within which heritability is to be estimated, pairs must be chosen in proportion to their representation in that population by social class, education, urban or rural upbringing, religion, etc, including every variable known to show a correlation with performance on the test. Otherwise the heri tability will be overestimated because important sources of environmental variance between families will be left out. On the other hand, if there really were genetic differences between ethnic or national groups, then the sample would need to be representative for these groups as well or else a component of genetic variation will be left out.


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5. There must be no assumption that within-family environment variance is the same for various relationship groups. It cannot be assumed that MZ and DZ twins, or that like sexed and unliked sexed DZ twins, or that biological sibs and foster sibs, are raised in environments of equal similarity. 6. Most central of all, the study must randomize members of a genetic pair over relevant environments. That is, twins must be raised "apart," or children raised apart from their parents, or sibs raised apart. Apart means at random with respect to environmental variables known or suspected to be relevant. Special care must be taken that adoption or fostering practices are not selective, but that children are truly adopted at random with respect to the characteristics of their parents. It is insufficient to show, post facto, that there is no significant correlation between, say, foster parents and biological parents, if the foster and biological parent groups each come from a very restricted socioeconomic range, as is usually the case. A ny study that does not include as its basic data adopted or foster reared pairs of relatives in which the foster environments are randomized, will overestimate the genetic components of variance by an unknown amount. If,

in addition, some statement is to be made about genetic differences between groups, such as social classes or races, then a special form of requirement 6 must be met. The environments of the groups must be equalized at least for the life histories of the persons being measured. For social classes, this might be possible by randomized adoptions or institutionalized upbringing, although it does not, in fact, happen, but for race it is difficult to see under what circum stances white and black children could be brought up under identical circum stances. In fact, no study of the genetics of IQ has even come close to fulfilling the six requirements and most studies fail all tests in a significant way. There are, for example, no twin pairs raised in randomized environments, no randomized placements of adopted children, few studies of any kind with sample sizes over 100, and, needless to s.ay, no study of race or social class differences that

randomizes individuals in these categories.

PRIMARY DATA The data on which genetic analysis of intelligence has been attempted consists of a heterogeneous assembly of psychological and performance tests carried out on individuals of different degrees of relationship. A thorough method� ological statistical analysis of the scores of papers dealing with such data is yet to be made, although it is presently being carried out by Dr. M. Schiff and colleagues at INSERM in Paris. The best-known reviews of primary data are those of Erlenmeyer-Kimling & Jarvik (12) and a derivative one by Jensen (22) (his Table 2). Both of these compilations have been severely criticized in detail by Kamin (27) and the reader must be extremely cautious in referring to them without comparing them to Kamin's analysis. Their unreliability rises from several sources: (a) many of the papers report several different correlations for the same data because of different methods of analysis by the original authors; (b) some of the primary data papers are unaccountably left out of



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the summary tabulations; (c) there are errors in reporting the number of studies (3 studies of siblings raised apart are reported as 33 studies by Jensen). Moreover, the summaries do not reveal which comparisons of relatives were made together in the same studies by the same tests and which were made independently. This is extremely important because different populations are tested and different test instruments are used in various studies. The quantitative geneticist is struck immediately with the wide variety of so-called IQ tests, many of them not having been standardized for age or sex in the same population that is under examina tion. My own cursory survey of the literature has revealed the following nonex haustive list: Stanford Binet (many studies), Otis IQ (20), Stanford Achievement (35), National Merit Achievement (36), Raven's Progressive Matrices (15), Do minoes (44), Mill-Hill (44), Wechsler Intelligence Scale for Children (WISC) (38, 51), Japanese version of WISC (47), Danish translation of the Wechsler Bellevue Intelligence Scores (26), Iowa Basic Skills Vocabulary (46), PMA (49), unspecified group tests, and "final assessments"

(5). Because so many analyses

of heritability, especially by path coefficients, require bringing together informa tion from different correlations, this immense heterogeneity of tests renders any result of numerical analysis virtually meaningless. It is rather like doing a genetic analysis of "size" in cattle by using mixtures of data from weight, height, tail length, hoof size, and loudness of moo, all of which can reasonably be said to be related to size. Because of the criticality of adoption studies, it is to these we must look for a reasonably homogeneous sample, using the same tests and including the minimal set of relationships, such as MZ twins raised together, DZ twins raised together, and MZ twins raised apart. There is only one such corpus of data, the work of Cyril Burt and colleagues (3-4-5). It is not surprising that such immense emphasis has been placed on this work and that estimates of heritability make major use of it (22, 25, 39). Because the only other data on twins raised apart are the 37 pairs studied by Shields (44), the 19 pairs by Newman et al (35), and the 12 pairs of luel-Nielsen (26), any estimate of heritability is almost critically dependent on the Burt data. Unfortunately, the entire body of Burt's work on the heritability of IQ must be totally excluded from the realm of science. The brilliant detective work of Kamin (27), now completely confirmed by Jensen (24), has revealed the following points, among others: I. No description of the test administered is given for many studies, and Burt gives contradictory general descriptions of the same tests in different papers. 2. Scores for identical twins were "adjusted" by subjective "final assessments" where Burt felt that tests did not adequately reveal the underlying similarities.

3. Sample sizes are either not given or are self-contradictory in descriptions of the same studies. 4. The correlations for MZ twins raised apart (0.771) and MZ twins raised together (0.944) maintain these values, identical to the third decimal place, in three successive studies even though new twin pairs are added.

In view of these facts, and in view of the fact that Burt's original data are no longer in existence, we have no choice but to exclude the entirety of Burt's work on IQ from scientific consideration.


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Although we must conclude that there are no scientific data of any magnitude on which we can make an unbiased estimate of heritability of any measure of intelligence, we could settle for something less and ask whether there are data that would at least answer the qualitative question of whether there is any genetic variance for measures of IQ in any population. For this purpose, a variety of partial data sets, not sufficent for quantitative heritability estimates, will do. For example, if sibs or MZ twins raised apart are nevertheless correlated in their IQ, and if adopted children correlate with their biological parents, or if biological sibs in a family were more highly correlated than were foster children in a family, there would be prima facie evidence of some heritability. Each of these adoption studies has certain special requirements that must be met, however, if the tests are to be valid. In all cases, the fostering or adoption must be truly random and this is a severe problem in actual human adoptions. Thus the high correlation between "separated" MZ twins in the Shields (44) study cannot be interpreted because, in 30 of the 40 pairs studied, the "separated" twins were raised by members of the same family or attended the same school, and a further six were raised by family friends (27). The Skodak & Skeels study (45) of 100 adopted children is the only one in which the correlation of adopted children's IQ with biological mother's IQ (r

=

0.44) is reported.

There was, however, strong selective placement in this study, with the children of mothers with higher IQs being placed in homes with much higher incomes and a variety of other social variables characteristic of higher social status than were the children of low IQ mothers. The other relevant studies are those of Freeman et al (14), Burks (2), and Leahy (30). In the Freeman study the correlation of adoptive parents' IQ with that of their biological child (0.35) was slightly lower than was their correlation with their adopted child (0.39), thus showing no effect of genes at all. On the other hand, the Leahy study showed a higher correlation of midparent with biological child (0.36) than with adopted child (0.18), providing evidence for genetic effects. The Burks study, unfortunately, only compares adopted children with adoptive parents (r 0.20) and biological parents with biological children (r 0.57) in a different group of families with quite different socioeconomic characteristics. I have quite deliberately not discussed the large number of simple comparisons of dizygotic and monozygotic twins, such as the widely quoted studies by Vandenberg (50), because any such comparison must assume that the environ mental similarities for dizygotic twins are the same as for monozygotic. The environmental dissimilarities will be completely confounded with genetic dif ferences. The comparison of dizygotic with monozygotic twins is a special case of a general statistical and methodological problem that is usually swept under the rug in science. A comparison between two groups or treatments in an experiment ' is always a compound comparison and the two groups will have the same value of some variable only if a large number of things are true. In statistical termi nology, a test of the difference between two groups is the test of a "compound hypothesis. " For example, monozygotic twins will have the same IQ correlation =

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as dizygotic twins only if there is no genetic variation for IQ and if the environ mental correlations are the same for both classes of twins, and if the test procedures do not allow conscious or unconscious bias by the test, and so on and so forth. What the investigator does is then to divide this set of requirements into two classes. One he calls the "hypothesis to be tested" and the other he calls the "assumptions. " Usually the assumptions are quickly disposed of (some times in a footnote) and the investigator then tests the hypothesis. But assumption and hypothesis are really completely symmetrical and the decision about which requirements belong in the untested assumptions and which in the tested hy pothesis is up to the subjective impressions of the investigator and his readers. Thus, the comparison between monozygotic and dizygotic twins can either be a test of the presence of genetic variance on the assumption of equal environ mental correlation, or a test of the hypothesis of equal environmental correlation on the assumption of no genetic variation (or, indeed, a test of experimenter bias on the assumption of no genetic or environmental differences). The proce dure is entirely symmetrical in any objective sense. It is not the purpose of this review to discuss evidence that environmental factors are important in influencing performance on IQ tests. All writers agree, and all studies agree, that there is some effect of environment. We must, however, address one point, and that is the claim that IQ is highly heritable and therefore not much difference in IQ can be induced by change in circumstance. The logic of the proposition is in error, but, in addition, there is some evidence that large differences in IQ can be traced to change of circumstance. In the Skodak & Skeels work (45), the mean IQ of adopted children was 117, the mean IQ of their biological mothers was 86, corresponding to a large difference in socioeconomic classes of adoptive and biological parents. The environmental elements may be quite subtle. Record et al (40) found that the mean IQ at age I I of twins was 95.2 if both survived, but if one was still born or died in the first four weeks, the mean IQ of the survivor was 98.8 as compared to 99.5 for singleton births. Since the mean birth weight of a single twin survivor was less than if both twins survived, the lower IQ of twins clearly has nothing to do with pre- or perinatal events, but results from postnatal interaction, probably with the parents.

ANALYSES AND REVIEWS I have already pointed out that there is a large volume of analysis and review of primary data. The most sophisticated statistical analysis by means of the analysis of variance is that of Jincks & Fulker (25). Unfortunately, the estimates of broad heritability are derived from the Shields data (hB2- � 0.7) and the Burt data (hB2 0.86, hN2 0.71) both of which are useless, but for different reasons. The Shields data simply do not have the major component of be tween-family environmental variance, while the Burt numbers are not scientific data in any sense that we understand the term as we have noted before. The major analyses by path coefficients are those of Jencks (21) and Rao et al (39). =

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They depend, to some extent, on flawed data including Burt's. The more serious difficulty is that they depend on a heterogeneous assemblage of correlations from different populations using very different measures of intelligence for different parts of the path analysis. Moreover, it is not clear how sensitive Jencks's analyses are to the particular model structures he postulates. Jencks estimates a heritability of about 0.45 with a further 20% of the variance being ascribed to the correlation between environment and genotype. The Rao et al analysis yields the interesting result that heritability of child's IQ is 0.752, but of adult's IQ is only O. l 21! Beyond these purely statistical reanalyses of data, there have been several general books and articles on the subject that have attempted to put the problem in a social and political perspective as well as attempting to synthesize the entire field. Kamin's book (27) demolishes a good deal of the shabby work in the subject and asks hard methodological questions about the relevant studies. An equally critical argument, but from the standpoint of philosophers of science, attacking nearly all the logic and programmatic conclusions of both Jensen (22) and Herrnstein (18) is contained in Block & Dworkin (I). The original article by Jensen (22) and his more recent book (23) are the major attempts to present the view that IQ te:;ts meas ure intelligem:e, that IQ is highly heritable, and that major social, political, and educational policy issues depend upon the high heritability of IQ. There are a number of serious errors of understanding in both Jensen's paper and book, the most serious of which I discuss in the next section, and a number of misrepresentations of the data being commented on, the most serious of which are reviewed in Chapter 6 of Kamin. There is, however, one point, also noted by Kamin, that raises doubts about the quality of Jensen's scholarship. Figure 6 on page 50 of Jensen's paper (22) shows the median correlations between IQs of four degrees of relationship when the individuals were raised together and when they were raised apart. The caption of the figure reads: "Median values of all correlations reported in the literature up to 1963 for the indicated kinships (after Erlenmeyer-Kimling and Jarvik, 1963). Note consistency of the differences in correlations for relatives reared together and apart. " Indeed, it is this consistency of the four differences that Jensen calls attention to on his pages 50 and 51 as strong evidence for a heritability of IQ of about 0.75. Of the four comparisons given, one is for DZ twins. The fact is, however, that no one has ever reported a study of DZ twins raised apart. Neither Erlenmeyer-Kimling & Jarvik, nor Burt, nor Jincks & Fulker, nor Jencks, nor even Jensen himself give any reference to such data. They simply do not exist and the "data" point is a pure invention. The invention is not Jensen's however, since he has subsequently stated that he copied the figure, without attribution, from Heber et al (17).

RACE, SOCIAL CLASS, AND IQ A review on genetic aspects of intelligence is not an appropriate place to review the evidence on the socioeconomic concomitants of IQ scores. There are, how ever, two claims about group differences in IQ that need a brief examination.


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Jensen (22, p. 144) makes the claim that high heritability of IQ leads to the conclusion that the observed difference in mean IQ between black and white children is largely genetic in origin. This manifestly incorrect claim was sub sequently modified by Jensen to the assertion that "the higher the within-group heritability the greater is the plausibility, or the a priori probability that genetic differences exist between groups. A similar claim for the cause of the difference in mean IQ between social and occupational classes is made by Herrnstein (18) on the same grounds. Jensen supports this claim of a positive relation between the heritability within and between groups in part by reference to a formula of DeFries (7). This relates the interpopulation heritability hr2 to the intrapopulation heritability hw2, by means of the intraclass phenotypic corre lation t and the intraclass genotypic correlation r: ,


"

(I - t)r (I - r)t

5.

So for a fixed set of intraclass correlations, Jensen argues, the greater hw2, the greater hr2• But this is an illusion because the intraclass correlations are defined by the ratio of between-population variance to within-population variances. That is, although hf2 appears in equation 5 as the dependent variable and hw2 as the independent, in a causal sense both hf2 and hw 2 are independent variables defining rand t. The equation is a rearrangement of the circular tautology:

h} h�

air a} a�w T

=--=

w

a� a2gw

air +

a�w +

a2w

a!f a2if

a} + a� a} a2f + a2w

r( l - t) ( I - r)t

6.

Aside from this point, Jensen and Herrnstein's argument is incorrect from the basic theory of population genetics. From an evolutionary standpoint, all those forces that tend to increase genetic variation within populations, tend to decrease

the variation between populations and vice versa. Thus, mutation increases the variation within populations but decreases genetic differences between popula tions. Migration acts in the same way. Genetic drift and isolation between populations acts in the opposite sense, decreasing variation within populations and increasing it between populations. Directional selection establishes the same alleles in all populations. Incompatibility selection decreases variation within populations and increases variation between populations. Heterosis maintains

similar variation in all populations. Thus, the forces of evolution all act in opposite directions on the variation within and between populations. It is hard to see what sort of a priori argument leads one to expect high heritability both

within and between populations.


400

LEWONTIN

An attempt has been made by Scarr-Salapatek (41) to estimate heritabilities of IQ in American blacks in contrast to whites. However, the data available were not sufficient to carry out this estimation properly (10) so her conclusion of lower heritability in blacks is in doubt. However, her data will give an overestimate of the heritability, as noticed by Schwartz & Schwartz (42), and they calculate the upper limit of h2 from her data as only 0.15. The argument that there is a genetic difference between blacks and whites in IQ would be supported if black and white children, raised in the same environment, nevertheless showed significant differences in IQ. Tizard (48) has compared 64 black, white, and "mixed parentage" children in Dr. Bernardo's Homes in Britain. She found no significant differences between the groups, although white children had the lowest average scores on three tests. The mean IQ of the children was slightly higher than the population at large, indicating that the orphanages in question are extraordinary ones. Children returned to their mothers did not have significantly different IQs from those kept in the institution, but children who had been adopted by unrelated foster parents showed a 10 point rise in IQ. At least in this study, race is not a relevant variable, but fostering is. Another, much larger study in which socioeconomic status (SES) of blacks and whites was equal was carried out in Baltimore, Philadelphia, and Boston (37). Within cities, the SES distribution of blacks and whites was the same and so were the IQ distributions of the children. Between cities, there was a significant difference in SES scores and the IQ distributions of both races also differed between cities, in the same direction as SES. Again, race seems not to be the relevant variable, while socioeconomic variables do make a difference. This latter study, however, shows why equalization of SES distribution between races, rather than actually raising children together as in the Tizard study, leads to ambiguity. For it can be argued that the black families with the same SES distributions as the white families were the upper end of the black distribution at large and therefore might be expected to have higher IQs than blacks in general. Only studies in which a random group of children are raised in the same environments can resolve this confusion. Finally, Loehlin et al (32) attempted to correlate the IQ of American blacks with their probable degree of white ancestry as judged by blood group similar ities. The data, at face value, showed the IQ of blacks to be lowered by white ancestry, but the effect was not statistically significant.

THE STATE OF THE FIELD Why are the pages of the Annual Review of Genetics taken up with an article on the genetics of intelligence? It might be argued that the influence of genes on any trait in any species is a valid subject of scientific enquiry, since, after all, geneticists are objective scientists who are simply curious about nature in all of its manifestations. But that surely cannot be the answer since, for example, genetic aspects of snout length in pigs is not a subject that receives much attention. Perhaps the genetics of intelligence is intrinsically more interesting



40 1

than snout length in swine because somehow research in this field has revealed some fundamental information about the way genes mediate the development of behavior. But that is not true, clearly. All research on the genetics of normal human intelligence has been of a statistical nature, using the techniques of biometrical genetics to estimate genetic and environmental sources of variation in specific populations. There has not been, and in the present state of develop mental and neural biology cannot be, any attempt to analyze cellular and developmental mechanisms of gene action in influencing cognitive traits. Nor can it be maintained that work on the biometrical genetics of intelligence has somehow led to progress in biometrical genetics as a general approach. On the contrary, because of the impossibility of control and manipulation of human environments and mating, man is among the worst choices of experimental organisms for testing the methods of quantitative genetics. It is an uphill struggle to get basic estimates of genetic and environmental variances and covariances for any traits in man, while these statistics are easy to obtain in Drosophila, maize, and mice. Neither is it the case that any discoveries on the genetics of intelligence have created a flurry of scientific interest among geneticists. Among the scientific symposia organized by the most recent International Con gress of Human Genetics ( 1971) and International Congress of Genetics ( 1973), none was on the subject of the genetics of intelligence. If the genetics of intelligence is not scientifically very interesting in the most general sense, then perhaps it is simply that everything we can know about our own species is worth knowing. But surely we do not even want to argue that position since then we may look forward to a review on the genetic aspects of nose length in man! No, in the end we must admit that those who place an importance on research into the genetics of intelligence must believe this work to be of social and political interest. They must believe that important questions of social and individual policy will be answered and that recom mendations for social policy will flow from the outcome of such research. Indeed, several of the writers on the subject, including Jensen (22), Herrnstein ( 18), Jencks (21), and Eckland ( I I) are quite explicit in asserting that the outcome of social policy, especially educational policy, but also policy aimed at income redistribution and employment, depends on the outcome of research on the genetics of intelligence. It might be argued that even though the motivation for research might be social and political, the outcome of that research is part of the objective world of scientific fact. But that is not true. Sherwood & Nataupsky (43) found a multiple correlation of 0.55 between the conclusions reached by investigators on the subject of black-white IQ differences and biographical characteristics of the investigators themselves. Research workers who were raised in urban environments, had poorly educated parents, did not themselves excel in grade averages in their own schooling, were second-born children, and had foreign born grandparents found either no differences between black and white IQs or else interpreted the differences found to be environmental. Investigators, on the other hand, from rural environments, with better educated parents, with


402

LEWONTIN

high scholastic achievement, first-born, and the grandchildren of native born, found blacks to be genetically inferior to whites in IQ. The reader should note that we are not referring to public opinion surveys and their social determinants, but to conclusions reached by investigators in more than 80 published research papers in scientific journals. I have gone through this argument because it is only in the light of the specifically political and social motivation that underlies the work in this field that the scientific state of the field can be understood by geneticists. Otherwise, the geneticist, accustomed to a certain standard of empirical and logical demon stration, will be at a loss to understand how we can engage in a serious consid eration of a body of data and analysis that largely fails to meet the minimum criteria for scientific work even by the not overly rigorous canons of population genetics. Thus, my own attitude toward the subject oscillates between shrugging off most of the work in the field as scientifically incompetent or worse, and the strong desire to deal seriously with it because so many people take its claims seriously. The pathological state of the field is revealed by a number of symptoms: I. An excessive ratio of works of tabulation, secondary analyses, reanalyses, and interpretation to works of primary data acquisition on which the analyses are based. In view of the fact that most data "papers" are monographs or books, the page ratio is staggering. 2. Extremely low sample sizes in many empirical studies. Thus, the absolutely critical studies of monozygotic twins raised apart upon which so many of the analyses have been based comprise 53 pairs [Burt (5)], 37 pairs [Shields (44)], 19 pairs [Newman et al (35)], and 12 pairs [luel-Nielsen (26)]. Of course, these twin cases are difficult to find, but the average sample size in 7 American studies of unrelated children raised in the same family is only 37! [See summary in lencks (21) p. 291.] 3. Experimental designs that in the great majority of cases are structurally inadequate to estimate the quantities claimed to be of interest. So, for example, the very large National Merit study (36) whose 687 monozygotic twin pairs and 482 dizygotic twin pairs make it the only such study with adequate sample sizes, is simply incapable of yielding estimates of heritability because no study consisting of only such twin pairs can do so (25). 4. Elementary errors in understanding and use of basic concepts in popUlation genetics as, for example, repeated assertions that high within-group estimates of heritability are evidence for high heritability among groups (I 8, 22, 23) or the repeated use of estimates of broad heritability to make assertions about the outcome of assortative mating and evolution in populations (18, 22) or the failure to understand the population consequences of Mendelian segregation and reassortment (18). 5. Most disturbing of all, a carelessness, shabbiness, and intellectual dishonesty in the presentation of both primary results and their secondary reporting and analysis, amounting in some cases to misrepresentation. If the most blatant cases are not willful fraud, at the very least they place their perpetrators outside


403

the pale of scholarship. I have discussed only two cases, but a thorough revelation of the sins of omission and commission, large and small, can be found in chapters 3-6 of Kamin (27).


CONCLUSION The problems of estimating the heritable components of variation for any human metrical character are very great and have not been understood by mostJtuman behavioral geneticists. The problem boils down to breaking the correlation between genetic and environmental similarity. This means, in turn, that adoption studies are essential, that these studies must be reasonably large, and, most important of all, that they must be scrupulous in the randomization of individuals over the range of environments obtainable in the population at large. This is a very difficult problem, but the failure to adhere to clean experimental design renders all work uni nterpretabl e . It is sim pl y not true that approximate designs give approximate results. Because we know so little about human environments and the way they influence behavioral traits, rough arguments will not do. What is true for estimation of heritability within populations is doubly true for making statements about genetic differences between race and socioeconomic classes. No design conceivable can randomize black and white children over family environments. Finally, from a scientific standpoint or from one of valid inferences about social policy, the problem of assaying the genetic components of IQ test dif ferences seems utterly trivial and hardly worth the immense effort that would need to be expended to carry out decent studies. Literature Cited

I. Block, N. J., Dworkin, O . 1974. IQ: h e ritability and inequality. Philos. Public Affairs 3 : 3 3 1 -409, 4:40-99 2. Burks, B. S. 1928. The relative influence of nature and nurture upon mental de

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velopment: a comparative study offoster parent-foster child and true parent-true child resemblance. Yearh. Nat. Soc. Study Educ. 27(1)2 19-3 16 Burt, C. 1955. The evidence for the concept of intelligence. Br. J. Educ. Psychol. 25: 1 58-77 Burt, C. 1958. The inheritance of mental ability. A m. Psychol. 1 3 : 1 - 1 5 Burt, C. 1 966. The genetic determination of differences in intelligence: a study of monozygotic twins reared together and apart. Br. J. Psychol. 57: 137-53 Cattell, R. B. 1963. The interaction of hereditary and environmental influ ences. Br. J. Stat. Psychol. 16: 1 9 1 -2 1 0 DeFries, 1 . C . 1972. Quantitative aspects of genetics and environment in the de termination of behavior. In Genetics,

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1 4. Freeman, F. N . , Holzin�er, K. J., Mitchell, B. C. 1928. The mfluence of environment on the intelligence, school achievement and conduct of foster chil dren. Yearb. Nat. Soc. Study Educ. 27:(1) 103-2 1 7 1 5. Guttman, R. 1973. Genetic analxsis of analytical spatial ability: Raven s pro gressive matrices. Behav. Genet. 4: 273-84 1 6. Haseman, J. K., Elston, R. C. 1 970. The estimation ofgenetic variance from twin data. Behav. Genet. 1(1): 1 1 - 1 9 1 7 . Heber, R . , Dever, R . , Conry, J. 1968. The influence of environmental and genetic variables on intellectual devel opment. In Behavioral Research in Mental Retardation, ed. H . Prehm. L. Hamerlynck, J. Crosson. Eugene, Oreg.: Univ. Oregon Press 1 8. Herrnstein, R. J. 1973. IQ in the Meri tocracy. Boston: Atlantic Monthly Press 19. Hogarth, R. M. 1974. Monozygotic and dizygotic twins reared together: sensi tivity of heritability estimates. Br. J. Math. Stat. Psychol. 27: 1 - \ 3 20. Holzinger, K . J. 1 929. The relative effect of nature and nurture influences on twin differences. J. Educ. Psychol. 20: 245-48 2 1 . Jencks, C. 1 972. Ineguality: A Reassess ment of the Effect oJ Family and School ing in America. New York: Basic Books 22. Jensen, A. R. 1969. How much can we boost IQ and scholastic achievement? Harv. Educ. Rev. 39: 1 - 1 23 23. Jensen, A. R. 1 973. Educability and Group Differences. New York: Harper & Row 24. Jensen, A. R. 1 974. Kinship correlations reported by Sir Cyril Burt. Behav. Genet. 4:1 -28 25. Jincks, J. L., Fulker, D. W. 1970. Com parison of the biometrical, genetical, MAVA, and classical approaches to the analysis of human behavior. Psychol. B ull. 73: 3 1 1 -49 26. Juel-Nielsen, N. 1965. Individual and e n v i r o n m e n t : A p s yc h i a t r i c psychological investigation o f mon ozygotic twins reared apart. A cta Psy chiatr. Neurol. Scand. Monogr. Suppl. 1 83 27. Kamin, L. J. 1974. The Science and Politics of r Q. Potomac, Md: Lawrence Erlbaum; New York: Wiley 28. Klein, T. W., DeFries, J. c., Finkbeiner, C. T. 1973. Heritability and genetic cor relation: standard errors of estimates and sample size. Behav. Genet. 3 : 355-64 29. Layzer, D. 1 974. Heritability of IQ scores: science or numerology? Science 1 83: 1 259-66

30. Leahy, A. M. 1935. Nature-nuture and intelligence. Genet. Psychol. Monogr. 1 7 : 24 f-305 3 1 . Lewontin, R. C. 1974. The analysis of variance and the a � alysis of causes. Am. J. Hum. Genet. 26.400-4 1 1 32. Loehlin, J. c., Vandenberg, S.C., Os borne, R. T. 1973. Blood group genes and negro-white ability differences. Behav. Genet. 3: 263-70 33. MacLean, C. J., Morton, N. E., Lew, R. 1975. Analysis offamily resemblance IV. Operational characteristics of segrega tion analyses. A m. J. Hum. Genet. 27:365-84 34. Mather, R. 1 949. Biometrical Genetics: The Study of Continuous" Variation. London: Methuen 35. Newman, H. H., Freeman, F. N., Hol zinger, K. J. 1937. Twins: A Study of Heredity and Environment. C hicago. Univ. Chicago Press 36. Nichols, R. C. 1965. The national merit twin study. In Methods and Goals in Human Behavior Genetics, ed. S. G . Vandenberg. New York: Academic 37. Nichols, P. L., Anderson, E. 1 973 . Intel lectual performance, race and socio economIc status. Soc. BioI. 4: 367-74 38. Owen, D. R., Sines, J. O. 1970. Heri tability of personality in children. Behav. Genet. 1 : 135-47 39. Rao, D. c., Morton, N. E., Yee, S. 1 974. Analysis of family resemblances. II. A linear model for familial correlation. Am. J. Hum. Genet. 26:33 1-59 40. Record, R. G . , McKeown, T., Edwards, J. H. 1970. An investigation of the dif ference in measured intelligence be tween twins and single births. A nn. Hum. Genet. 34: 1 1 -20 4 1 . Scarr-Salapatek, S. 197 1 . Race, social class and IQ. Science 174: 1 285-95 42. Schwartz, M., Schwartz, J. 1973. Evi dence against a genetical component to performance in fQ tests. Nature London 248: 84-85 43. Sherwood, J. J., Nataupsky, M. 1968. Predicting the conclUSIOns of negro white intelligence research from oio graphical characteristics of the investi gators. J. Pers. Soc. Psychol. 8: 53-58 44. S h ields, J . 1 962. Monozygotic Twins Brought Up Apart and Brought Up To gether. London: Oxford Umv. Press 45. Skodak, M . , Skeels, H. M. 1949. A final follow-up study of one h undred adopted children. 1. Genet. Psychol. 75:85.- 1 25 46. Snider, B. 1955. A comparative study of achievement test scores offraternal and identical twins and siblings. PhD diss., State Univ. Iowa [Cited by Kamin (27)]



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Micro-insemination: genetic aspects.

Genetic aspects of febrile convulsions.

Genetic aspects of human lupus.

Genetic aspects of breast cancer.

[Genetic aspects of erectile dysfunction].

Genetic aspects of multidrug resistance.

Genetic aspects of cerebral palsy.

Genetic aspects of cerebrovascular disease.

Genetic aspects of human obesity.

Genetic aspects of Wilson's disease.

Ethical aspects of genetic screening.

Legal aspects of genetic information.

L5. Genetic aspects of preeclampsia.

Genetic aspects of nutritional rickets.

Genetic aspects of nutritional rickets.

Tuberous sclerosis complex: genetic aspects.

Genetic and environmental stability of intelligence in childhood and adolescence.

The genetic correlation between intelligence and speed of information processing.

Genetic aspects of disease in cattle.

Genetic aspects of some orofacial anomalies.

Recurrent aphthous stomatitis: genetic aspects of etiology.

[Morphological and genetic aspects of Spitz tumors].

Genetic and molecular aspects of demyelination.

Genetic aspects of nonconvulsive status epilepticus.