Twin study: Wikis


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Twin studies are one of a family of designs in behavior genetics which aid the study of individual differences by highlighting the role of environmental and genetic causes on behavior.

Twins are invaluable for studying these important questions because they disentangle the sharing of genes and environments. If we observe that children in a family are more similar than might be expected by chance, this may reflect shared environmental influences common to members of family - class, parenting styles, education etc. - but they will also reflect shared genes, inherited from parents.

The twin design compares the similarity of monozygotic or identical twins, who share nearly 100% of their genetic polymorphisms, to that of dizygotic or fraternal twins, who share only 50% of their polymorphisms. By studying many hundreds of families of twins, researchers can then understand more about the role of genetic effects and the effects of shared and unique environment effects.

Modern twin studies have shown that almost all traits are in part influenced by genetic differences, with some characteristics showing a strong influence (e.g. height), others an intermediate level (e.g. IQ) and some more complex heritabilities, with evidence for different genes affecting different elements of the trait - for instance Autism.



Francis Galton laid the foundations of behavior genetics as a branch of science.

While twins have been of interest to scholars since early civilization, such as the early physician Hippocrates (5th c. BCE), who attributed similar diseases in twins to shared material circumstances, and the stoic philosopher Posidonius (1st c. BCE), who attributed such similarities to shared astrological sex circumstances, the modern history of the twin study derives from Sir Francis Galton's pioneering use of twins to study the role of genes and environment on human development and behavior. Galton, however, was unaware of the critical genetic difference between MZ and DZ twins. [1]

This factor was still not understood when the first study using psychological tests was conducted by Edward Thorndike (1905) using 50-pairs of twin. Notably this paper was perhaps the first statement of the idea (formulated as a testable hypothesis) that C (family effects) decline with age: comparing 9-10 and 13-14 year old twin-pairs, and normal siblings born within a few years of one another.

Fatefully, however, Thorndike incorrectly reasoned that his data gave support for their being one, not two types of twins: Missing the critical distinction that makes within-family twin studies such a powerful resource in psychology and medicine. This mistake was repeated by Ronald Fisher (1919), who argued

"The preponderance of twins of like sex, does indeed become a new problem, because it has been formerly believed to be due to the proportion of identical twins. So far as I am aware, however, no attempt has been made to show that twins are sufficiently alike to be regarded as identical really exist in sufficient numbers to explain the proportion of twins of like sex." [2].

The first published twin study utilizing the distinction between MZ and DZ twins is sometimes cited as that of the German geneticist Hermann Werner Siemens in 1924 [3]. Chief among Siemens' innovations was the "polysymptomatic similarity diagnosis". This allowed him to overcome the barrier that had stumped Fisher and was a staple in twin research prior to the advent of molecular markers. Wilhelm Weinberg , however, had already by 1910 used the MZ-DZ distinction to calculate their respective rates from the ratios of same- and opposite-sex twins in a maternity population, worked out partitioning of covariation amongst relatives into genetic and environmental elements (anticipating Fisher and Wright) including the effect of dominance on relative's similarity, and begun the first classic-twin studies. [4]


The power of twin designs arises from the fact that twins may be either monozygotic (MZ: developing from a single fertilized egg and therefore sharing all of their alleles) – or dizygotic (DZ: developing from two fertilized eggs and therefore sharing on average 50% of their polymorphic alleles, the same level of genetic similarity as found in non-twin siblings). These known differences in genetic similarity, together with a testable assumption of equal environments for MZ and DZ twins (Bouchard & Propping, 1993) creates the basis for the twin design for exploring the effects of genetic and environmental variance on a phenotype (Neale & Cardon, 1992).

The basic logic of the twin study can be understood with very little mathematics beyond an understanding of correlation and the concept of variance.

Like all behavior genetic research, the classic twin study begins from assessing the variance of a behavior (called a phenotype by geneticists) in a large group, and attempts to estimate how much of this is due to genetic effects (heritability), how much appears to be due to shared environmental effects, and how much is due to unique environmental effects - events that occur to one twin but not another, or events that affect each twin in different ways.

Typically these three components are called A (additive genetics) C (common environment) and E (unique environment); the so-called ACE Model. It is also possible to examine non-additive genetics effects (often denoted D for dominance (ADE model); see below for more complex twin designs).

Given the ACE model, researchers can determine what proportion of variance in a trait is heritable, versus the proportions which are due to shared environment or unshared environment. While nearly all research is carried out using SEM programs such as the freeware Mx, the essential logic of the twin design is as follows:

Monozygous (MZ) twins raised in a family share both 100% of their genes, and all of the shared environment. Any differences arising between them in these circumstances are random (unique). The correlation we observe between MZ twins provides an estimate of A + C . Dizygous (DZ) twins have a common shared environment, and share on average 50% of their genes: so the correlation between DZ twins is a direct estimate of ½A + C . If r is the rate observed for a particular trait, then:

rmz = A + C
rdz = ½A + C

These two equations allow us to derive A, C, and E :

A = 2 (rmzrdz)
C = rmzA = 2 rdzrmz
E = 1 – rmz

Where rmz and rdz are simply the correlations of the trait in MZ and DZ twins respectively. Twice difference between MZ and DZ twins gives us A: the additive genetic effect. C is simply the MZ correlation minus our estimate of A. The random (unique) factor E is estimated directly by how much the MZ twin correlation deviates from 1. (Jinks & Fulker, 1970; Plomin, DeFries , McClearn, & McGuffin, 2001).

Modern Modeling

Beginning in the 1970s, research transitioned to modeling genetic, environmental effects using maximum likelihood methods (Martin & Eaves, 1977). While computationally much more complex, this approach has numerous benefits rendering it almost universal in current research.

A principle benefit of modeling is the ability to explicitly compare models: Rather than simply returning a value for each component, the modeler can compute confidence intervals on parameters, and also drop or add paths. Thus, for instance an AE model can be objectively compared to a full ACE model, to test for effect of family or shared environment on behavior. Modeling also allows multivariate modeling: This is invaluable in answering questions about the genetic relationship between apparently different variables: For instance do IQ and long-term memory share genes? Do they share environmental causes? Additional benefits include the ability to deal with interval, threshold, and continuous data, retaining full information from data with missing values, integrating the latent modeling with measured variables, be they measured environments, or, now, measured molecular genetic markers such as SNPs. In addition, models avoid constraint problems in the crude correlation method: all parameters will lie, as they should between 0-1 (standardized).

Modeling tools such as openMx (Neale, Boker, Xie, & Maes, 2002) and other applications suited to constraints and multiple groups have made the new techniques accessible to reasonably skilled users.



It can be seen from the modelling above, that the main assumption of the twin study is that of equal environments. At an intuitive level, this seems reasonable – why would parents note that two children shared their hair and eye color, and then contrive to make their IQs identical? Indeed, how could they?

This assumption, however, has been directly tested. An interesting case occurs where parents believe their twins to be non-identical when in fact they are genetically MZ. Studies of a range of psychological traits indicate that these children remain as concordant as MZs raised by parents who treated them as identical (Kendler, Neale, Kessler, Heath, & Eaves, 1993).

Measured similarity: A direct test of assumptions in twin designs

A particularly powerful technique for testing the twin method has recently been reported by Visscher et al. Instead of using twins, this group took advantage of the fact that while siblings on average share 50% of their genes, the actual gene-sharing for individual sibling pairs varies around this value, essentially creating a continuum of genetic similarity or "twinness" within families. Estimates of heritability based on direct estimates of gene sharing confirm those from the twin method, providing support for the assumptions of the method.

Extended twin designs and more complex genetic models

The basic or classical twin-design contains only MZ and DZ twins raised in their biological family. This represents only a sub-set of the possible genetic and environmental relationships. It is fair to say, therefore, that the heritability estimates from twin designs represent a first step in understanding the genetics of behavior.

The variance partitioning of the twin study into additive genetic, shared, and unshared environment is a first approximation to a complete analysis taking into account gene-environment covariance and interaction, as well as other non-additive effects on behavior. The revolution in molecular genetics has provided more effective tools for describing the genome, and many researchers are pursuing molecular genetics in order to directly assess the influence of alleles and environments on traits.

An initial limitation of the twin design is that is does not afford an opportunity to consider both Shared Environment and Non-additive genetic effects simultaneously. This limit can be addressed by including additional siblings to the design.

A second limitation is that gene-environment correlation is not detectable as a distinct effect. Addressing this limit requires incorporating adoption models, or children-of-twins designs, to assess family influences uncorrelated with shared genetic effects.


The Twin Method has been subject to criticism from statistical genetics, statistics, and psychology, with some arguing that conclusions reached via this method are ambiguous or meaningless. Core elements of these criticisms and their rejoinders are listed below:

Criticisms of Statistical Methods

It has been argued that the statistical underpinnings of twin research are invalid. Such statistical critiques argue that heritability estimates used for most twin studies rest on restrictive assumptions which are usually not tested, and if they are, are often found to be violated by the data.

For example, Peter Schonemann has criticized methods for estimating heritability developed in the 1970s. He has also argued that the heritability estimate from a twin study may reflect factors other than shared genes. Using the statistical models published in Loehlin and Nichols (1976)[5], the narrow heritability’s of HR of responses to the question “did you have your back rubbed” has been shown to work out to .92 heritable for males and .21 heritable for females, and the question “Did you wear sunglasses after dark?” is 130% heritable for males and 103% for females [6] [7]

Responses to Statistical Critiques

In the days before the computer, statisticians were forced to use methods which were computationally tractable, at the cost of known limitations. Since the 1980s these approximate statistical methods have been discarded: Modern twin methods based on structural equation modeling are not subject to the limitations and heritability estimates such as those noted above are impossible. Critically, the newer methods allow for explicit testing of the role of different pathways and incorporation and testing of complex effects.

Sampling: Twins as representative members of the population

The results of twin studies cannot be automatically generalized beyond the population in which they have been derived. It is therefore important to understand the particular sample studied, and the nature of twins themselves.

Twins are not a random sample of the population, and they differ in their developmental environment. In this sense they are not representative [8]

For example: Dizygotic (DZ) twin births are affected by many factors. Some women frequently produce more than one egg at each menstrual period and, therefore, are more likely to have twins. This tendency may run in the family either in the mother's or father's side of the family, and often runs through both. Women over the age of 35 are more likely to produce two eggs. Women who have three or more children are also likely to have dizygotic twins. Artificial induction of ovulation and in vitro fertilization-embryo replacement can also give rise to DZ and MZ twins [9] [10] [11][12] [13] [14].

Response to representativeness of twins

Twins differ very little from non-twin siblings. Measured studies on the personality and intelligence of twins suggest that they have scores on these traits very similar to those of non-twins (for instance Deary et al. 2006).

Observational nature of twin studies

For very obvious reasons, studies of twins are with almost no exceptions observational. This contrasts with, for instance, studies in plants or in animal breeding where the effects of experimentally randomized genotypes and environment combinations are measured. In human studies, we observe rather than control the exposure of individuals to different environments. [15] [16] [17] [18]

Response to the observational nature of twin studies

The observational study and its inherent confounding of causes is common in psychology. Twin studies are in part motivated by an attempt to take advantage of the random assortment of genes between members of a family to help understand these correlations. Thus, while the twin study tells us only how genes and families affect behavior within the observed range of environments, and with the caveat that often genes and environments will covary, this is argued to be a considerable advance over the alternative, which is no knowledge of the different roles of genes and environment whatsoever.

Advanced Methodology


The effects of genes depend on the environment they are in. Possible complex genetic effects include G*E interactions, in which the effects of a gene allele differ across different environments. Simple examples would include situations where a gene multiplies the effect of an environment (in this case the slope of response to an environment would differ between genotypes).

A second effect is "GE correlation", in which certain allelles occur more frequently than others in certain environments. If a gene causes a person to enjoy reading, then children with this allele are likely to be raised in households with books in them (due to GE correlation: one or both of their parents has the allele and therefore both accumulates a book collection and passes on the book-reading allele). Such effects can be assessed by measuring the purported environmental correlate (in this case books in the home) directly.

Often the role of environment seems maximal very early in life, and decreases rapidly after compulsory education begins. This is observed for instance in reading [19] as well as intelligence[20]. This is an example of a G*Age effect and allows an examination of both GE correlations due to parental environments (these are broken up with time), and of G*E correlations caused by individuals actively seeking certain environments [21].

Continuous variable or Correlational studies

While concordance studies compare traits which are either present or absent in each twin, correlational studies compare the agreement in continuously varying traits across twins.


Pairwise concordance

Fig 2. Heritability for nine psychological traits as estimated from twin studies. All sources are twins raised together (sample size shown inside bars). As outlined above, identical twins (MZ twins) are twice as genetically similar as fraternal twins (DZ twins) and so heritability (h2) is approximately twice the difference in correlation between MZ and DZ twins. Unique environmental variance (e2) is reflected by the degree to which identical twins raised together are dissimilar, and is approximated by 1-MZ correlation. The effect of shared environment (c2) contributes to similarity in all cases and is approximated by the DZ correlation minus the difference between MZ and DZ correlations.

For a group of twins, pairwise concordance is defined as C/(C+D), where C is the number of concordant pairs and D is the number of discordant pairs.

For example, a group of 10 twins have been pre-selected to have one affected member (of the pair). During the course of the study four other previously non-affected members become affected, giving a pairwise concordance of 4/(4+6) or 4/10 or 40%.

Fig 1. Twin concordances for seven psychological traits (sample size shown inside bars).

Probandwise concordance

For a group of twins in which at least one member of each pair is affected, probandwise concordance is a measure of the proportion of twins who have the illness who have an affected twin and can be calculated with the formula of 2C/(2C+D), in which C is the number of concordant pairs and D is the number of discordant pairs.

For example, consider a group of 10 twins that have been pre-selected to have one affected member. During the course of the study, four other previously non-affected members become affected, giving a probandwise concordance of 8/(8+6) or 8/14 or 57%.

See also

Further reading

  • Textbook, software, and example scripts for twin research
  • Jang, K.L., McCrae, R.R., Angleitner, A. Riemann, R. & Livesley, W.J. (1998). Heritability of facet-level traits in a cross-cultural twin sample: support for a hierarchical model of personality. Journal of Personality and Social Psychology 74:1556-1565.
  • Plomin, DeFries, McClearn & McGuffin (2000). Behavioral Genetics: A Primer 4th edition. W.H.Freeman & Co Ltd.
  • Nancy L. Segal (2005) Indivisible by Two: Lives of Extraordinary Twins. New York, Harvard University Press.

Critical Accounts

This book has been critically reviewed for the American Psychological Association. Hanson, D. R. (2005). 'The Gene Illusion Confusion: A review of The Gene Illusion: Genetic Research in Psychiatry and Psychology Under the Microscope by Jay Joseph' [Electronic Version]. PsycCritiques, 50, e14.

And in reply to this article see:

External links

Academic bodies

Several academic bodies exist to support behavior genetic research, including the Behavior Genetics Association [3], the International Society for Twin Studies, and the International Behavioural and Neural Genetics Society [4]. Behavior genetic work also features prominently in several more general societies, for instance the International Society of Psychiatric Genetics. [5].


Prominent specialist journals in the field include Behavior Genetics, Genes, Brain and Behavior, and Twin Research and Human Genetics.


The following Twin Studies are ongoing studies that are recruiting subjects:


  1. ^ R. D. Rende, R. Plomin and S. G. Vandenberg. (1990). Who discovered the twin method? Behav Genet, 20, 277-85
  2. ^ R. A. Fisher. (1919). The Genesis of Twins. Genetics, 4, 489-99
  3. ^ H. W. Siemens. (1924). Die zwillingspathologie; ihre bedeutung, ihre methodik, ihre bisherigen ergebnisse. Journal
  4. ^ Crow, James F. (1999). "Hardy, Weinberg and language impediments". Genetics 152: 821–825. PMID 1460671.  
  5. ^ Loehlin, J. C., & Nichols, R. C. (1976). Heredity, environment, and personality: A study of 850 sets of twins. Austin, TX: University of Texas Press.
  6. ^ Peter Schonemann (1997) Models and muddles of heritability. Genetica, 99, 97-108:
  7. ^ Peter Schonemann (1995). Totems of the IQ Myth: General Ability (g) and its Heritabilities (h², HR). 1995 Meetings of the American Association for the Advancement of Sciences
  8. ^ Record, R. G., McKeown, T., & Edwards, J. H. (1970). An investigation of the difference in the measured intelligence between twins and single births. Annals of Human Genetics, 34, 11-20.
  9. ^ Clegg, A., & Woollet, A. (1983). Twins. London: Century Publishing Co.
  10. ^ Corson, S.L. Dickey, R. P., Gocial, B., Batzer, F. R., Eisenberg, E. Huppert, L., & Maislin, G. (1989). Outcome in 242 in vitro fertilization-embryo replacement or gamete intrafallopian transfer-induced pregnancies. Fertility and Sterility, 51, 644-650
  11. ^ Derom, C. Vietlinck, R., Derom, R., Van Den Berghe, H. & Thiery, M. (1987). Increased MZ twinning rate after ovulation induction. Lancet, 1236-1238.
  12. ^ Edwards, R. G., Mettler, L., & Walters, D. E. (1986). Identical twins and in vitro fertilization. Journal of in Vitro Fertilization and Embryo Transfer, 3, 114-117.
  13. ^ Leigh, G. (1983). All about twins. London: Routledge & Kegan.
  14. ^ Christiane Capron, Adrian R. Vetta, Michel Duyme and Atam Vetta (1999). Misconceptions of biometrical IQists. Cahiers de Psychologie Cognitive/Current Psychology of Cognition 1999, 18 (2), 115-160
  15. ^ Kempthorne O. (1997). Heritability: uses and abuses. Genetica, Volume 99, Numbers 2-3, 1997 , pp. 109-112(4)
  16. ^ Kendler, K. S., & Gruenberg, A. M. (1984). An independent analysis of the Danish adoption study of schizophrenia. Archives of General Psychiatry, 41, 555-564
  17. ^ Lewontin, R. C., Rose, S., & Kamin, L. J. (1984). Not in Our Genes. New York: Pantheon.
  18. ^ Rose, R. J. (1982, p. 960). Separated twins: Data and their limits. Science, 215, 959-960.
  19. ^ B. Byrne, S. Wadsworth, R. Corley, S. Samuelsson, P. Quain, J. C. DeFries, E. Willcutt and R. K. Olson. (2005). Longitudinal twin study of early literacy development: Preschool and kindergarten phases. Scientific Studies of Reading, 9, 219-235.
  20. ^ I. J. Deary, F. M. Spinath and T. C. Bates. (2006). Genetics of intelligence. European Journal of Human Genetics, 14, 690-700
  21. ^ R. Plomin and D. Daniels. (1987). Why are children in the same family so different from one another? Behavioral and Brain Sciences, 10, 1-16


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