The inheritance of general cognitive ability

National IQ Means, Calibrated and Transformed from Educational Attainment and Their Underlying Gene Frequencies.

European Journal for High Ability 5 (1994) 58-67

Mathematical giftedness and family relationship
Volkmar Weiss

From 1963 to 1971 about 2.8 million East German school children participated in nine nationwide mathematical competitions. The 1329 most successful participants were selected for further study. In 1970/71 and in two follow-ups in 1983 and 1993, data on 23,000 relatives of these children were gathered. The data indicated the existence of a strong relationship between mathematical-technical giftedness in school and achievement in life. There was evidence from the distribution of high professional achievement among the relatives that such achievement needs not only nurture but also an appropriate genetic background, which seems to be transmitted as a simple Mendelian trait, now open to investigation by molecular genetics.

From 1963 to 1971 about 2.8 million East German school children participated in nine nationwide mathematical competitions (for a review, see Engel, 1990). In the first stage of the selection process (Luther, 1988), repeated each year in each school, nearly all “mentally normal” students aged between 10 and 18 years took part. The second and third stages were organised at district and county levels, respectively. The fourth stage, a two day paper and pencil examination under close supervision and restricted to students between 15 and 18 years, was reached by the 1329 most successful participants in the third stage. In terms of psychometry, this selection process fulfilled the requirements of a standardised school achievement test. This is important to the argument of this paper as in East Germany IQ testing was officially forbidden (see for background information Weiss, 1991, 1993), and for that reason it was quite impossible to administer IQ tests to the participants and their relatives. However, from the high degree of selection it could be concluded that the IQ of the young people was 130 or higher.

In 1970, in order to obtain data about the background of the gifted, questionnaires were distributed to their parents. Not only a sample of the parents filled in information on their jobs and occupations, but this information was also obtained for all first and second degree relatives of the participants, for all male relatives of the third degree and for female cousins and the cousins of the parents. Altogether, from 524 returned questionnaires and from the files of the 1329 mathematically gifted students data on about 20,000 individuals were obtained.

Because there was no IQ testing, IQs of parents were estimated on the basis of occupation. Although this may be seen as a methodological weakness, Terman (1925) also faced this problem. His “Barr scale rating of occupational status” was methodologically similar to the present approach. Twenty judges rated a list of 121 representative occupations on a scale of 0 to 100, according to the grade of intelligence which each was believed to demand. The occupational distribution of the Terman gifted group is very similar to the distribution of the East German mathematically gifted. In a study by Wilson et al. (1978) various socioeconomic indexes and the Hollingshead Occupational Scale (McCall, 1977) were used to generate occupational status scores for each subject. The IQs predicted by these scores differed from empirically obtained IQs by fewer than 5 points in 37 percent of cases, fewer than 10 points in 66 percent, fewer than 15 points in 88 percent. Very similar results were obtained by Karzmark et al. (1985) using only years of education. By combining years of education, occupational status and school achievement, the present approach could be expected to have achieved a comparable range of error. Moreover, in 1978 it was possible to test the IQs of 124 mathematically highly gifted children (see Weiss 1982), selected on the same basis as the present group. The mean IQ of this sample was 135 ± 9, supporting the IQ estimates made on the basis of occupations.

The files of the students indicated their aspiration to obtain university degrees as mathematicians, physicists, engineers and as experts in finance. In 1983, in a first follow up study, it could be confirmed that 92 percent of all participants did in fact obtain such a degree; in addition, 7 percent, obtained a degree in non-mathematically oriented fields such as medicine, biology or the humanities. Considering the 92 percent rate of correct classification by profession alone, and using more conventional terminology, it was possible to speak of a penetrance of 0.92. Only 1 percent obtained no degree at all. In 1983 62 percent of all participants held jobs at universities, in computer centers and in other research institutions. Half of them excelled in creativity and obtained patents for inventions and honours for discoveries.

Of the fathers of the gifted youngsters, 43 percent also belonged to the same group with professional qualifications as high as those of the 92 percent of the students already mentioned above. In addition 24 percent of the fathers had university degrees in less mathematically oriented fields (compared with 7 percent among the gifted individuals). A total of 25.5 percent of the fathers were clerks or skilled workers in jobs such as bookkeepers, mechanic, tool fitter or draughtsman. Only 7.5 percent of all fathers were skilled workers with jobs such as mason, butcher, electrician or locksmith. However, it was remarkable that in nearly all such cases questionnaire data revealed above average achievement in school mathematics and in job performance. A locksmith, for example, was solely responsible for a plant and had been honoured as an innovator. Consequently, the assumption that the IQ of these men was in most cases in the upper range of their respective professions and about 110 seems to be justified. Only 1 percent of all fathers were unskilled workers, and in most such cases reasons were given why a professional career had been impossible (for example, diabetes or invalidity as a consequence of World War II).

For the mothers the results were not so clear cut: 37 percent of them were in jobs formerly typically done by females, such as secretary, stenotypist, bookkeeper, teacher and laboratory assistant and requiring above average intelligence. Some mothers were housewives without any profession, but with a number of children and a high school leaving examination (Abitur). School achievement and the confirmed correlation of IQ about 0.50 between husband and wife (Garrison et al., 1968) suggest that even such mothers probably had fairly high IQs.

The following empirical findings were especially impressive:

1. In cases where the gifted youngsters had a father who was a graduate in mathematics, physics or engineering (i.e., who belonged to the same professional group as 92 percent of the participants themselves), all sibs of the participants were above average in ability. In such families the mother could be in any profession or be a housewife.

2. In cases where the gifted student had a father who did not belong to the group just mentioned, the sibs could have any job or profession. Indeed, 14 percent of these sibs (see Weiss, 1982) were in jobs requiring no more than average intelligence. In the questionnaires in such cases the parents had written expressively “without special interests”, “”without special achievements”, “average achievements”, whereas for the gifted children and other sibs they had given very detailed information about achievement and honours in school and about job performance.

3. Even more impressive was a finding among the collaterals (i.e., sibs of parents of the gifted youngsters and their respective spouses): Parents who both belonged to the same high IQ group as the gifted students nearly always had children (i.e. cousins of the gifted group) who were all of the same above average IQ. Unskilled parental pairs mostly only had children in unskilled jobs. Parental pairs where both spouses had an estimated IQ of about 110 had children who were scattered over all possible jobs and professions.

By classifying jobs and professions according to estimated level of intelligence of people in them, the empirical findings suggested the following hypothesis: Assuming that all the mathematically gifted students and the professional group to which 92 percent of them belong would be homozygous for a Mendelian allele M1 (hence having the genotype M1M1), the unskilled workers and people in jobs requiring average IQ would be M2M2, the jobs requiring an IQ of about 110 would be heterozygous M1M2. There should be an error of classification between 10 percent and 20 percent – compare this with the 92 percent of gifted students who could be classified correctly on the basis of only their profession – and correct classification is more difficult for women then for men. Misclassification cannot be completely avoided, and is a consequence of a large number of biological and social influences (among them effects of other genetic loci and personality factors, disease, accidents, damage during development, social inequality of opportunity) and missing or incomplete information. Obviously, given a misclassification (or penetrance in conventional terminology) between 10 percent (for males) and 20 percent (for females), even in cases of M1M1-M1M1 marriages, 100 percent M1M1 offspring (itself bearing the same possible range between 75 percent and 100 percent (see Table 1), for M1M1-M1M2 marriages between 50 percent and 75 percent, for M1M2-M1M2 marriages between 25 percent and 50 percent, and even for M2M2-M2M2 marriages the proportion of M1M1 offspring cannot be zero, but should be between zero and 25 percent.

The terminology of genetics is not always consistent: geneticists speak of the gene frequency of the allele M1, but of the genotype M1M1. It is also quite correct to speak of major genes (Weiss, 1992a) instead of alleles of the major gene locus M. Of course, the allele M2 could also be understood as an abstraction, and be in reality a series of n alleles with small differences, but with a large difference from the M1 allele or an allele-1 series. In fact, every major gene concept is an abstraction with regard to minor genes and environmental influences (in a broad sense).

The hypothesis of a major gene locus of general intelligence with an autosomal allele M1 in the homozygous state as the prerequisite for an IQ of 119 and higher was tested in the families of the sibs of the parents of the mathematically gifted students (i.e., their aunts and uncles). Accordingly, the total numbers in Table 1 are the first cousins of the gifted group.

Table 1. Distribution of collaterals under the assumption of Mendelian segregation at a major gene locus (gene frequency M1 ≈ 0.20) of general intelligence*
Marriage combination	Percentage according to Mendelian rules with IQ 119 and higher		Total number of cousins of gifted students with IQ 119
Marriage combination	Expected range	Empirical value	And higher	Below
I. (both spouses with IQ 119 and higher)	75-100	81	47	11
II. (one spouse with IQ 119 and higher)	50-75	62	172	105
III. (both spouses below IQ 119; at least one spouse above IQ 104)	25-50	30	147	339
IV. (both spouses below IQ 105)	0-25	12	56	426
Total			422 32 percent	661 68 percent
* Two thirds of all cousins were citizens of East Germany, one third of West Germany. Data from Weiss (1982a, p. 108).

During the last two decades several authors (e.g., Stafford, 1972) have advanced hypotheses on an X-chromosome linked inheritance of mathematical or spatial ability. In the case of X-linked recessive inheritance of a gene influencing mathematical ability, male subjects scoring very high in such an ability should have a larger number of male relatives (brothers of the mothers; fathers of mothers) on their mothers’ side who also excel in such abilities than among the relatives of their fathers.

There was not the least hint of this in the present data, obtained from thousands of male relatives on both the maternal and the paternal side. The hypothesis of the X-linked inheritance of mathematical ability was rejected by Weiss (1972). What was revealed by the questionnaires in the present study was a different structure of interests and social values for males and females. Even among the present sample of highly gifted subjects, 47 percent of the females were interested in literature, but only 15 percent of males were; 68 percent of the girls could play a musical instrument, but only 31 percent of the boys could; 43 percent of boys were amateurs in electronics and related fields, but only 11 percent of the girls were. What cannot be ruled out by the present data is that autosomal genes are also regulated and influenced by genes located on sex chromosomes. This is, however, a different issue, and (for example, hormonal) regulation of mental traits by sex chromosomes should not be confounded with linkage to such chromosomes.

Twenty three year follow up of the gifted group

Monozygotic twins of the gifted students share all their genes with them, sibs and parents half of their genes, grandfathers and cousins an eighth. Therefore, in terms of classical genetics it is easy to draw conclusions about the underlying gene frequency in the total population from the frequencies of genotypes among the relatives of homozygous subjects. Because of historical change in occupational structure and underlying IQ requirements, the problem here is far more complicated. In 1993, 97 percent (n= 357) of all male gifted students were in professions typical for mathematical-technical giftedness and M1M1, respectively. Among the male relatives the figures were 55 percent (n=77) of the sons, 49 percent (n=220) of the brothers, 40 percent (n=346) of the fathers, 18 percent (n=570) of the male cousins, 22 percent (n=76) of the nephews, 14 percent (n=615) of the uncles, 11 percent (n=2250) of the male cousins of the parents, 9 percent (n=681) of the grandfathers, 5 percent (n=1996) of the uncles of the parents and 4 percent (n=1290) of the greatgrandfathers. Theoretically, in a classical Mendelian case the percentage among uncles and grandfathers, for example, should be the same. The difference in the present data is due to historical change in the occupational structure. (The mean year of birth for the uncles was 1917, for the grandfathers 1887, for the brothers of the gifted youngsters 1947.) Taking account of this change, it was estimated that the gene frequency p of the hypothetical major gene M1 of general intelligence is about 0.2 (Weiss, 1973), of the gene M2 the frequency q is about 0.8. From the Hardy Weinberg law of population genetics, where p2 + 2pq + q2 = 1, it follows that the frequency of M1M1 should be 0.04, that of M1M2 0.32 and of M2M2 0.64. However, assortative marriage for IQ with about r = 0.50 has the consequence that the percentage of M1M1 heterozygotes in the total population is reduced, from which follow frequencies of about 5 percent for, 27 percent for M1M2 and 68 percent M2M2 (Weiss, 1982). The medians of the cumulated percentiles (M2M2 34; M1M2 81.5; M2M2 97.5) correspond to the following median IQs: M2M2 – 94; M1M2 – 112; M1M1 – 130.

However, most of the children of the gifted students were still attending school in 1993. Of 440 children, 85.5 percent were attending a school with a high school leaving examination (Abitur) or had already passed such an examination. In the case of the sibs of the gifted participants (n=351) the figure was 60 percent. In the former East Germany this percentage for the general population was 12 percent; after German reunification this type of school is expanding (Weiss, 1993), and a good estimate for the weighted mean over the corresponding recent years is 19 percent. The percentile score of 81 corresponds to an IQ of 112, the median of the phenotype M1M2. Because n M1M2-M1M2 marriages with 100 children should divide theoretically into 25 M1M1 (all with Abitur), 50 M1M2 and 25 M2M2 children (all without Abitur), and half of the M1M2 offspring should attend a high school, the expected value in this marriage group (both parents M1M2) for obtaining Abitur should be 50 percent (see Table 3).

Table 2

Percentage obtaining the Abitur (German high school leaving examination)

among the children of highly gifted participants M1M1

Marriage combination of participant and spouse

Children with Abitur

Children without Abitur

Percentage

obtained

Percentage

expected*

Percentage

obtained

Percentage

expected*

both spouses with IQ 124 and higher –

M1M1 x M1M1

93.4

100

6.6

242

participant with spouse with IQ below 124 –

M1M1 x M1M2

75.5

25.5

184

* These percentages would be expected under the assumption of Mendelian segregation and a cutoff IQ of 112 for obtaining Abitur.

In social reality a 100 percent fit between theory and empirical results cannot be expected. For example, of the 16 children (the 6.6 percent in the first line of Table 2) not fitting the theory (they did not pass the Abitur), one was physically and mentally disabled, two were from broken marriages, two were midwives, two nurses, three “students” (stated in this way in the questionnaires without further details, i.e. Abitur is not impossible), and five males were already in highly qualified technical jobs.

Table 3

Percentage obtaining the Abitur (German high school leaving examination)

among the nephews and nieces of highly gifted participants M1M1

Sibs of participants and respective spouses

Children with Abitur

Children without Abitur

Percentage

obtained

Percentage

expected*

Percentage

obtained

Percentage

expected*

both spouses with IQ 124 and higher –

M1M1 x M1M1

91.4

100

8.6

one spouse with IQ 124 and higher; the other with IQ below 124 –

M1M1 x M1M2

71.5

28.5

130

both spouses with IQ between 104 and 124 –

M1M2 x M1M2

52.3

47.7

107

one spouse with IQ

below 105 –

M1M2 x M2M2

6.9

93.1

both spouses with IQ

below 105 –

M2M2 x M2M2

100

* These percentages would be expected under the assumption of Mendelian segregation and a cutoff IQ of 112 for obtaining Abitur.

Comparing the results in Tables 2 and 3, it is necessary to consider that the participants were classified with 100 percent certainty into M1M1. For their sibs, however, in most cases only information about their occupations was available. Hence, the expected rate of misclassification in Table 3 should be higher than in Table 2 (compare the respective first line in both tables), even for M1M1-M1M1 marriages.

Outlook

The most convincing evidence for the major gene theory will come neither from inferences based on occupational stratification nor from psychometric data (Eysenck, 1986, 1987) but from segregation analysis using more basic variables (Lehrl and Fischer, 1990), especially biochemical ones. To prove the existence of the major gene locus of human intelligence will be a discovery of centennial importance, and therefore for some people it is the stuff of science fiction, for others of nightmares (Weiss, 1991). Since the existence of a major gene locus is now accepted as possible (Frank, 1985), it was the aim of the present study to find ways to promote the discovery of the underlying genetic polymorphism. A great deal is already known about this polymorphism: Since 1971 (Weiss, 1972, 1973) its gene frequency and its strong correlation with social status; since 1979 (Weiss et al. 1986) its distribution properties; since 1982 (Lehrl et al., 1991) its probable involvement with brain energy metabolism (see Weiss, 1992b).

In population studies a mean enzyme activity of about 24 U glutathione peroxidase activity (GSHPx/g Hb) was found. By contrast, 100 healthy university students had a mean of 40.5, which is one of the arguments for the association of high IQ with high GSHPx activity. Brugge et al. (1992) confirmed a correlation (discovered in 1979) between GSHPx activity and a short term memory score (see Lehrl et al., 1991). In the same year the redox modulation by oxidized glutathione of NMDA receptor mediated synaptic activity in the hippocampus was discovered (Tauck, 1992). During recent years, molecular genetics has made such dramatic progress that in view of the compelling evidence for a genetic and hence biochemical background of mathematical technical giftedness and high intelligence (as outlined here and in Weiss, 1992a), there is no question that the details of the connection will be worked out.

References

Brugge, K.L., Nichols, S., Delis, Saitoh, T. and Truaner, D. (1992) The role of alterations in free radical metabolism in mediating cognitive impairments. In J. Emerit and B. Chance (eds.), Free radicals and aging. Basel: Birkhäuser, pp. 190-198. – see www.v-weiss.de/homocysteine.html

Engel, W. (1990) Entdeckung und Förderung mathematischer Begabungen in der DDR. Zeitschrift für Didaktik der Mathematik 1: 23-32.

Eysenck, H.J. (1986) The theory of intelligence and the psychophysiology of cognition. In R.J. Sternberg (ed.), Advances in the psychology of human intelligence. Vol. 3. Hillsdale, NJ: Erlbaum, pp. 1-34.

Frank, H. (1985) Is intelligence measurable and is it inherited? Folia humanistica 23: 671-691.

Garrison, R.J., Anderson, V.E. and Reed, S.C. (1968) Assortative marriage. Eugenics Quarterly 15: 113-127.

Karzmark, P., Heaton, R.K., Grant, I. And Matthews, C.G. (1985) Use of demographic variables to predict full scale IQ: a replication and extension. Journal of Clinical and Experimental Neuropsychology 7: 412-420.

Lehrl, S. and Fischer, B. (1990) A basic information psychological parameter (BIP) for the reconstruction of concepts of intelligence. European Journal of Personality 4: 259-286. - see The Basic Period of Individual Mental Speed (BIP)

Luther, S. (1988) Früherkennung und Frühförderung mathematisch-technischer Begabungen. Diss., Greifswald: Ernst-Moritz-Arndt-Universität.

McCall, R.M. (1977) Childhood IQ’s as predictor of adult educational and occupational status. Science 197: 482-483.

Stafford, R.E. (1972) Hereditary and environmental components of quantitative reasoning. Review of Educational Research 42: 183-201.

Tauck, D.L. (1992) Redox modulation of NMDA receptor-mediated synaptic activity in the hippocampus. Neuroreport 3: 781-784. – see www.v-weiss.de/homocysteine.html

Terman, L.M. (1925) Genetic studies of genius. Vol. 1. Mental and physical traits of a thousand gifted children. Stanford: Stanford University Press. – see www.v-weiss.de/table.html

Weiss, V. (1972) Empirische Untersuchungen zu einer Hypothese über den autosomal-rezessiven Erbgang der mathematisch-technischen Begabung. Biologisches Zentralblatt 91: 429-535. – see www.v-weiss.de/intellig.html

Weiss, V. (1973) Die Prüfung von Hypothesen bei den synchron zum Probanden lebenden Seitenverwandten als Methode der Humangenetik. Biometrische Zeitschrift 15: 259-270. – see www.v-weiss.de/table.html

Weiss, V. (1991) It could be Neo-Lysenkoism, if there was ever a break in continuity! Mankind Quarterly 31: 231-253. – see www.v-weiss.de/lysenkoism.html

Weiss, V. (1992a) Major genes of general intelligence. Personality and individual Differences 13: 1115-1134. – see www.v-weiss.de/majgenes.html

Weiss, V. (1992b) The relationship between short-term memory capacity and EEG power spectral density. Biological Cybernetics 68: 165-172. - see www.v-weiss.de/publ9-e.html

Weiss, V. (1993) Leistungsstufen der Begabung und dreigliedriges Schulsystem. Zeitschrift für Pädagogische Psychologie. 7: 171-183 und 197-299. – see www.v-weiss.de/pisa3.html

Weiss, V., Lehrl, S. und Frank, H. (1986) Psychogenetik der Intelligenz. Dortmund: Modernes Lernen. – see www.v-weiss.de/iq-falle.html

Detlef H. Rost: Klare Worte zur Hochbegabungs-Diskussion

Homepage