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Do twin studies overestimate heritability?

Do twin studies overestimate heritability?



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Do twin studies overestimate heritability (for instance by putting the interaction between environment and genome under the label "heritable")? If so why? Would you have any research papers to point me to?


It seems likely that some percentage of twin studies would fail to account for all the systematic environmental variables that connect their twins. In this case, the effects of these variables would still cause a correlation, which would be attributed to heritability. "A second look at twin studies" by Lea Winerman discusses examples of these types of variables.


Methods

Sample

Twins were recruited from the Norwegian Twin Registry (NTR). The registry comprises several cohorts of twins 75,76 , and the current study drew a random sample from the cohort born 1945–1960. In 2010, questionnaires were sent to a total of 2,136 twins. After reminders, 1,516 twins responded, yielding a response rate of 71%. Of the participants, 1,272 individuals were pair responders, and 244 were single responders. Zygosity has previously been determined based on questionnaire items shown to classify correctly 97–98% of the twins 77 . The cohort, as registered in the NTR, consists only of same-sex twins, and the study sample consisted of 290 monozygotic (MZ) male twins, 247 dizygotic (DZ) male twins, 456 MZ female twins and 523 DZ female twins. The age range of the sample was 50–65 years (mean = 57.11, sd = 4.5). The study was approved by the Regional Committee for Medical and Health Research Ethics of South-East Norway, and informed consent was obtained from all participants. All methods were performed in accordance with relevant guidelines and regulations.

Measures

Life satisfaction was measured with the Satisfaction With Life Scale (SWLS) developed by Ed Diener and colleagues 78,79 . The SWLS contains five items, such as “I am satisfied with my life”. Response options range from 1 = strongly disagree to 7 = strongly agree. The SWLS is widely used in wellbeing research, and has well-established psychometric properties 80 . Cronbach’s alpha in the current sample was 0.91.

Personality was measured by the NEO-PI-R 45,81 . The NEO-PI-R contains 240 items tapping the five general factors of personality, namely neuroticism, extraversion, openness to experience, agreeableness and conscientiousness. Within each of these factors, or domains, the NEO-PI-R measures six facets, or sub-factors (see results section for overview of all 30 facets). Each of these facets is measured by eight items. Response options range from 1 = strongly disagree to 5 = strongly agree. The NEO-PI-R is a well-established instrument, with sound psychometric properties 41 . In the current sample alphas for the five factors were 0.92 (neuroticism), 0.87 (extraversion), 0.88 (openness), 0.84 (agreeableness) and 0.87 (conscientiousness). Alphas for the facets ranged from 0.47 (C5 self-discipline) to 0.85 (N1 anxiety), with a mean of 0.67.

Analyses

Correlations were used to examine the bivariate associations between life satisfaction and personality traits and their facets. Next, we used regression analyses to (a) examine the unique contributions from the five broad personality traits, and to (b) identify the facets that are important for the association between personality and life satisfaction. Due to the non-independence of observations within twin pairs we used Generalized Estimating Equations (GEE) to account for the paired structure to obtain correct standard errors and significance levels. Further, to adjust for multiple testing we performed subsequent analyses with Bonferroni correction and the False Discovery Rate (FDR) approach 63 .

Based on the regression analyses we conducted two sets of multivariate biometric analyses to estimate the genetic and environmental contributions to the associations between personality and life satisfaction. The first set examined the relation between the major big five factors and life satisfaction. The second set of analyses focused on the specific facets that uniquely predicted life satisfaction. In order to focus on facets with substantive effects, we chose to retain only facets yielding regression betas >0.10, and with p < 0.01.

Standard Cholesky models 82,83 were used to estimate the genetic and environmental contributions to variance and covariance in personality and life satisfaction. All models were run with the OpenMx package in R 84 . The biometric models take advantage of the basic premise that MZ twins share 100% of their genes, whereas DZ twins share on average 50% of their segregating genes. Generally, the models allow for estimating three major sources of variance, including additive genetic factors (A), common environment (C) and non-shared environment (E). In addition, non-additive genetic effects (D) may be tested, but are only indicated if the observed MZ-correlations are more than twice the DZ-correlations. A Cholesky model is a structural equation model comprising the measured variables as observed phenotypes and the A, C and E components as latent factors (for illustration see Fig. 1). Models are constrained so that latent A-factors correlate perfectly among MZ-twins, and at 0.5 among DZ-twins. C-factors are correlated at unity for both zygosity groups, and E-factors are by definition uncorrelated. Different models are compared to determine the presence of the genetic and environmental effects (e.g., the fit of an ACE model is compared to an AE model) or sex-differences. In line with standard practice, we tested different types of sex-limitation models 85 . First, common sex-limitation models allow parameter estimates to vary across sex, involving differences in magnitude for genetic and environmental effects. Second, scalar sex-limitation allows the unstandardized variance-covariance matrices to vary across sex, but standardized parameters (e.g., heritabilities) are constrained to be equal. Finally, the sex-limitation models were compared with models having all parameters constrained to equal across sex. To assess models and identify the best fitting model we used the minus2LogLikelihood difference (Δ − 2LL) test, and the Akaike Information Criterion (AIC) 86 .

Data availability

The dataset analyzed during the current study may be requested from the Norwegian Twin Registry. Restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Information about data access is available here: https://www.fhi.no/en/studies/norwegian-twin-registry/


Behavioral Genetics of Aggression and Intermittent Explosive Disorder

Catherine Tuvblad , . Linda Booij , in Intermittent Explosive Disorder , 2019

Metaanalyses and Systematic Reviews Summarizing Studies Examining the Influence of Genetic and Environmental Factors on Aggressive Behavior

There have been a few metaanalyses and systematic reviews of twin and adoption studies of aggressive behavior and the wider construct of antisocial behavior. Antisocial behavior is broader in scope than aggression as it also includes nonaggressive behaviors, e.g., littering, vandalism, and lying which are considered antisocial behaviors, which are not necessarily aggressive. These studies are summarized in Table 1 . Together these studies show that about half or more of the variance in aggressive behavior is explained by heritable influences ( Burt, 2009 Ferguson, 2010 Mason & Frick, 1994 Miles & Carey, 1997 Rhee & Waldman, 2002 ). Two metaanalyses have examined nonadditive genetic effects. Only one found significant nonadditive genetic effects for broader concept of antisocial behavior, but not for aggressive behavior ( Burt, 2009 Rhee & Waldman, 2002 ) It is important to note that genetic influences are consistently found across these reviews, while shared environmental influences are relatively small or nonexistent. Family similarity in aggressive behavior therefore seems to primarily be the result of shared genes, not environment.

Table 1 . Summary of Metaanalysis and Systematic Reviews: Aggressive Behavior

Author, YearMeasureEstimates
(Mason &amp Frick, 1994)
12 twin studies (3795 twin pairs)
3 adoption studies (338 adoptees)
Antisocial behaviora 2 48%
(Miles &amp Carey, 1997)
20 twin studies (1757 twins)
4 adoption studies 3157 adoptees)
Aggressive behaviora 2 50%
(Rhee &amp Waldman, 2002)
41 twin studies
10 adoption studies
Antisocial behaviora 2 32% d 2 9% c 2 16% e 2 43%
(Rhee &amp Waldman, 2002)
41 twin studies
10 adoption studies
Aggressive behaviora 2 44% c 2 6% e 2 50%
( Burt, 2009 )
15 twin studies
4 adoption studies
Aggressive behaviora 2 65% c 2 5% e 2 30%
( Ferguson, 2010 )
38 twin studies
Antisocial behaviora 2 56% c 2 11% e 2 31%
( Tuvblad &amp Baker, 2011 )
33 twin studies
4 adoption studies
Aggressive behaviora 2 50% c 2 0% e 2 50%

Note. a 2 , genetic effects c 2 , shared environmental effects d 2 , dominant effects e 2 , nonshared environmental effects.


Twin Studies, Adoption Studies, and Fallacious Reasoning

Twin and adoption studies have been used for decades on the basis that genetic and environmental causes of traits and their variation in the population could be easily partitioned by two ways: one way is to adopt twins into separate environments, the other to study reared-together or reared-apart twins. Both methods rest on a large number of (invalid) assumptions. These assumptions are highly flawed and there is no evidential basis to believe these assumptions, since the assumptions have been violated which invalidates said assumptions.

Plomin et al write (2013) write: For nearly a century, twin and adoption studies have yielded substantial estimates of heritability for cognitive abilities.

But the validity of the “substantial estimates of heritability for cognitive abilities” is strongly questioned due to unverified (and false) assumptions that these researchers make.

Adoption studies

The problem with adoption studies are numerous, not least: restricted range of adoptive families selective placement late separation parent-child attachment disturbance problems with the tests (on personality, ‘IQ’) the non-representativeness of adoptees compared to non-adoptees and the reliability of the characteristic in question.

In selective placement, the authorities attempt to place children in homes close to their biological parents. They gage how “intelligent” they believe they are (on the basis of parental SES and the child’s parent’s perceived ‘intelligence’), thusly this is a pretty huge confound for adoption studies.

According to adoption researcher Harry Munsinger, a “possible source of bias in adoption studies is selective placement of adopted children in adopting homes that are similar to their biological parents’ social and educational backgrounds.” He recognized that “‘fitting the home to the child’ has been the standard practice in most adoption agencies, and this selective placement can confound genetic endowment with environmental influence to invalidate the basic logic of an adoptive study (Munsinger, 1975, p. 627). Clearly, agency policies of “fitting the home to the child” are a far cry from random placement of adoptees into a wide range of adoptive homes. (Joseph, 2015: 30-1)

Richardson and Norgate (2005) argue that simple additive effects for both genetic and environmental effects are false that IQ is not a quantitative trait while other interactive effects could explain the IQ correlation.

1) Assignment is nonrandom. 2) They look for adoptive homes that reflect the social class of the biological mother. 3) This range restriction reduces the correlation estimates between adopted children and adopted parents. 4) Adoptive mothers come from a narrow social class. 5) Their average age at testing will be closet to their biological parents than adopted parents. 6) They experience the womb of their mothers. 7) Stress in the womb can alter gene expression. 8) Adoptive parents are given information about the birth family which may bias their treatment. 9) Biological mothers and adopted children show reduced self-esteem and are more vulnerable to changing environments which means they basically share environment. 10) Conscious or unconscious aspects of family treatment may make adopted children different from other adopted family members. 11) Adopted children also look more like their biological parents than their adoptive parents which means they’ll be treated accordingly.

Twin studies

Personally, my favorite thing to discuss. Twin studies rest on the erroneous assumption that DZ and MZ environments are equal that they get treated equally the same. This is false, MZ twins get treated more similarly than DZ twins, which twin researchers have conceded decades ago. But in order to save their field, they attempt to use circular argumentation, known as Argument A. Argument A states that MZTs (monozygotic twins reared together) are more genetically similar than DZTs (dizygotic twins reared together) and thusly this causes greater behavioral similarity. But this is based on circular reasoning: the researchers already implicitly assumed that genes played a role in their premise and, not surprisingly, in their conclusion genes are the cause for the similarities of the MZTs. So Argument A is used, twin researchers circularly assume that MZTs greater behavioral similarity is due to genetic similarity, while their argument that genetic factors explain the greater behavioral similarity of MZTs is a premise and conclusion of their argument. “X is true because Y is true Y is true because X is true.” (Also see Joseph et al, 2015.)

We have seen that circular reasoning is “empty reasoning in which the conclusion rests on an assumption whose validity is dependent on the conclusion” (Reber, 1985, p. 123).A circular argument consists of “using as evidence a fact which is authenticated by the very conclusion it supports,” which “gives us two unknowns so busy chasing each other’s tails that neither has time to attach itself to reality” (Pirie, 2006, p. 27) (Joseph, 2016: 164).

Even if Argument A is accepted, the causes of behavioral similarities between MZ/DZ twins could still come down to environment. Think of any type of condition that is environmentally caused but is due to people liking what causes the condition. There are no “genes for” that condition, but their liking the thing that caused the condition caused an environmental difference.

Argument B also exists. Those that use Argument B also concede that MZs experience more similar environments, but then argue that in order to show that twin studies, and the EEA, are false, critics must show that MZT and DZT environments differ in the aspects that are relevant to the behavior in question (IQ, schizophrenia, etc).

An example of an Argument B environmental factor relevant to a characteristic or disorder is the relationship between exposure to trauma and post-traumatic stress disorder (PTSD). Because trauma exposure is (by definition) an environmental factor known to contribute to the development of PTSD, a finding that MZT pairs are more similarly exposed to trauma than DZT pairs means that MZT pairs experience more similar “trait-relevant” environments than DZTs. Many twin researchers using Argument B would conclude that the EEA is violated in this case. (Joseph, 2016: 165)

So twin researchers need to rule out and identify “trait-relevant factors” which contribute to the cause of said trait, along with experiencing more similar environments, invalidates genetic interpretations made using Argument B. But Argument A renders Argument B irrelevant because even if critics can show that MZTs experience more similar “trait-relevant environments”, they could still argue that the twin method is valid by stating that (in Argument A fashion) MZTs create and elicit more similar trait-relevant environments.

One more problem with Argument A is that it shows that twins behave accordingly to “inherited environment-creating blueprint” (Joseph, 2016: 164) but at the same time shows that parents and other adults are easily able to change their behaviors to match that of the behaviors that the twins show, which in effect, allows them to “create” or “elicit” their own environments. But the adults’ “environment-creating behavior and personality” should be way more unchangeable than the twins’ since along with the presumed genetic similarity, adults have “experienced decades of behavior-molding peer, family, religious, and other socialization influences” (Joseph, 2016: 165).

Whether or not circular arguments are “useful” or not has been debated in the philosophical literature for some time (Hahn, Oaksford, and Corner, 2005). However, assuming, in your premise, that your conclusion is valid is circular and therefore While circular arguments are deductively valid, “it falls short of the ultimate goal of argumentative discourse: Whatever evaluation is attached to the premise is transmitted to the conclusion, where it remains the same no increase in degree of belief takes place” (Hahn, 2011: 173).

However, Hahn (2011: 180) concludes that “the existence of benign circularities makes clear that merely labeling something as circular is not enough to dismiss it an argument for why the thing in question is bad still needs to be made.” This can be simply shown: The premise that twin researchers use (that genes cause similar environments to be constructed) is in their conclusion. They state in their premise that MZT behavioral similarity is due to greater MZT genetic similarity in comparison to DZTs (100 vs. 50 percent). Then, in the conclusion, they re-state that the behavioral similarities of MZTs is due to their genetic similarity compared to DZTs (100 vs. 50 percent). Thus, a convincing argument for conclusion C (that genetic similarity explains MZT behavioral similarity) cannot rest on the assumptionthat conclusion C is correct. Thus, Argument A is fallacious due to its circularity.

What causes MZT behavioral similarities is their more similar environment: they get treated the same by peers and parents, and have higher rates of identity confusion and had a closer emotional bond compared to DZTs. The twin method is based on the (erroneous) assumption that MZT and DZT pairs experience roughly equal environments, which twin researchers conceded was false decades ago.

We have shown, first, that the EEA may not hold, and that well-demonstrated treatment effects can, therefore, explain part of the classic MZ–DZ differences. Using published correlations, we have also shown how sociocognitive interactions, in which DZ twins strive for a relative ‘apartness’, could further depress DZ correlations, thereby possibly explaining another part of the differences. We conclude that further conclusions about genetic or environmental sources of variance from MZ–DZ twin data should include thorough attempts to validate the EEA with the hope that these interactions and their implications will be more thoroughly understood.

Of course, even if twin studies were valid and the EEA was true/ the auxiliary arguments used were true, this would still not mean that heritability estimates would be of any use to humans, since we cannot control environments as we do in animal breeding studies (Schonemann, 1997 Moore and Shenk, 2016). I have chronicled how 1) the EEA is false and how flawed twin studies are 2) how flawed heritability estimates are 3) how heritability does not (and cannot) show causation and 4) the genetic reductionist model that behavioral geneticists rely on is flawed (Lerner and Overton, 2017).

So we can (1) accept the EEA, that the greater behavioral resemblance indicates the importance of genetic factors underlying most human behavioral differences and behavioral disorders or we can (2) reject the EEA and state that the greater behavioral resemblance is due to nongenetic (environmental) factors, which means that all genetic interpretations of MZT/DZT studies must be rejected. Thus, using (2), we can infer that all twin studies measure is similarity of the environment of DZTs, and it is, in fact, not measuring genetic factors. Accepting explanation 2 does not mean that “twin studies overestimate heritability, or that researchers should assess the EEA on a study-by-study basis, but instead indicates that the twin method is no more able than a family study to disentangle the potential influences of genes and environment” (Joseph, 2016: 181).

What it does mean, however, is that we can, logically, discard all past, future, and present MZT and DZT comparisons and these genetic interpretations must be outright rejected, due to the falsity of the EEA and the fallaciousness of the auxiliary arguments made in order to save the EEA and the twin method overall.

There are further problems with twin studies and heritability estimates. Epigenetic supersimilarity (ESS) also confounds the relationship. Due to the existence of ESS “human MZ twins clearly cannot be viewed as the epigenetic equivalent of isogenic inbred mice, which originate from separate zygotes. To the extent that epigenetic variation at ESS loci influences human phenotype, as our data indicate, the existence of ESS establishes a link between early embryonic epigenetic development and adult disease and may call into question heritability estimates based on twin studies” (Van Baak et al, 2018). In other words, ESS is an unrecognized phenomenon that contributes to the phenotypic similarity of MZs, which calls into question the usefulness of heritability studies using twins. The uterine environment has been noted to be a confound by numerous authors (Devlin, Daniels, and Roeder, 1997 Charney, 2012 Ho, 2013 Moore and Shenk, 2016).

Adoption studies fall prey to numerous pitfalls, most importantly, that children are adopted into similar homes compared to their birth parents, which restricts the range of environments for adoptees. Adoption placement is also non-random, the children are placed into homes that are similar to their biological parents. Due to these confounds (and a whole slew of other invalidating problems), adoption studies cannot be said to show genetic causation, nor can they separate genetic from environmental factors.

Twin studies suffer from the biggest flaw of all: the falsity of the EEA. Since the EEA is false—which has been recognized by both critics and supporters of the assumption—the supporters of the assumption have attempted to redefine the EEA in two ways: (1) that MZTs experience more similar environments due to genetic similarity (Argument A) and (2) that it is not whether MZTs experience more similar environments, but whether or not they share more similar trait-relevant environments. Thus, unless these twin researchers are able to identify trait-relevant factors that contribute to the trait in question, we must conclude that (along with the admission from twin researchers that the EEA is false that MZTs experience more similar environments than DZTs) genetic interpretations made using Argument B are thusly invalidated. Fallacious reasoning (“X causes Y Y causes X) does not help any twin argument. Because their conclusion is already implicitly assumed in their premise.

The existence of ESS (epigenetic supersimilarity) further shows how invalid the twin method truly is, because the confounding starts in the womb. Attempts can be made (however bad) to control for shared environment by adopting different twins into different homes, but they still shared a uterine environment which means they shared an environment, which means it is a confound and it cannot be controlled for (Charney, 2012).

Adoption and twin studies are highly flawed. Like family studies, twin studies are no more able to disentangle genetic from environmental effects than a family study, and thus twin studies cannot separate genes from environment. Last, and surely not least, it is fallacious to assume that genes can be separated so neatly into “heritability estimates” as I have noted in the past. Heritability estimates cannot show genetic causation, nor can it show how malleable a trait is. They’re just (due to how we measure) flawed measures that we cannot fully control so we must make a number of (false) assumptions that then invalidate the whole paradigm. The EEA is false, all auxiliary arguments made to save the EEA are fallacious adoption studies are hugely confounded twin studies are confounded due to numerous reasons, most importantly the uterine environment (Van Baak et al, 2018).


A Swedish national twin study of criminal behavior and its violent, white-collar and property subtypes

Background: We sought to clarify the etiological contribution of genetic and environmental factors to total criminal behavior (CB) measured as criminal convictions in men and women, and to violent (VCB), white-collar (WCCB) and property criminal behavior (PCB) in men only.

Method: In 21 603 twin pairs from the Swedish Twin Registry, we obtained information on all criminal convictions from 1973 to 2011 from the Swedish Crime Register. Twin modeling was performed using the OpenMx package.

Results: For all criminal convictions, heritability was estimated at around 45% in both sexes, with the shared environment accounting for 18% of the variance in liability in females and 27% in males. The correlation of these risk factors across sexes was estimated at +0.63. In men, the magnitudes of genetic and environmental influence were similar in the three criminal conviction subtypes. However, for violent and white-collar convictions, nearly half and one-third of the genetic effects were respectively unique to that criminal subtype. About half of the familial environmental effects were unique to property convictions.

Conclusions: The familial aggregation of officially recorded CB is substantial and results from both genetic and familial environmental factors. These factors are moderately correlated across the sexes suggesting that some genetic and environmental influences on criminal convictions are unique to men and to women. Violent criminal behavior and property crime are substantially influenced respectively by genetic and shared environmental risk factors unique to that criminal subtype.


A Brief History of Twin Studies

On Tuesday, NASA astronaut Scott Kelly and Russian cosmonaut Mikhail Kornienko touched down in Kazakhstan after spending a whopping 340 days aboard the International Space Station (ISS).

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As part of NASA’s "Year in Space" project, Kelly and his Earth-bound identical twin brother, retired astronaut Mark Kelly, provided samples of blood, saliva and urine and underwent a barrage of physical and psychological tests designed to study the effects of long-duration spaceflight on the human body.

Studies of identical and fraternal twins have long been used to untangle the influences of genes and the environment on particular traits. Identical twins share all of their genes, while fraternal twins only share 50 percent. If a trait is more common among identical twins than fraternal twins, it suggests genetic factors are partly responsible.

"Twins studies are the only real way of doing natural experiments in humans," says Tim Spector, a professor of genetic epidemiology at Kings College, London. "By studying twins, you can learn a great deal about what makes us tick, what makes us different, and particularly the roles of nature versus nature that you just can't get any other way.”

Spector is director of the TwinsUK Registry, which includes data from 12,000 twins and is used to study the genetic and environmental causes of age-related complex traits and diseases. He estimates that twins research is currently being conducted in more than 100 countries, and that most of those projects draw upon information contained in large databases such as the TwinsUK Registry.

While it may be a while before we see results from the astronaut twins, researchers are hopeful that the opportunity will yield some unique insights into human health. Here are some examples of what we've learned from past twins studies—both famous and infamous:

The Birth of Eugenics

Victorian scientist Francis Galton, a half-cousin of Charles Darwin, was one of the first people to recognize the value of twins for studying the heritability of traits. In an 1875 paper titled "The History of Twins," Galton used twins to estimate the relative effects of nature versus nature (a term that Galton himself coined). But his firm belief that human intelligence is largely a matter of nature led him to a darker path: He became a vocal proponent of eugenics (another term that he coined) and the idea that "a highly gifted race of men" could be produced through selective breeding.

Genes and I.Q.

In 2003, Eric Turkheimer, a psychology professor at the University of Virginia, took a fresh look at the research on the heritability of I.Q., which relied heavily on twin studies. Turkheimer noticed that most of the studies that found I.Q. is largely due to genetics involved twins from middle-class backgrounds, and he wondered what the pattern was among poorer people. When he looked at twins from poor families, he found that the I.Q.s of identical twins varied just as much as the I.Q.s of fraternal twins. In other words, the impact of growing up poor can overwhelm a child's natural intellectual gifts.

Genetic Basis for Everyday Diseases

Working with data and biological samples in the TwinsUK Registry, Spector and his colleagues have shown in more than 600 published papers that many common diseases such as osteoarthritis, cataracts and even back pain have a clear genetic basis to them. "When I started in this field, it was thought that only 'sexy' diseases [such as cancer] were genetic," Spector says. "Our findings changed that perception."

Heritable Eating Disorders

One of the newer twin registries to come online, the Michigan State University Twin Registry (MSUTR) was founded in 2001 to study genetic and environmental influences on a wide range of psychiatric and medical disorders. One of the most surprising findings to come out of the group's research is that many eating disorders such as anorexia have a genetic component to them.

"People thought for the longest time that it was due entirely to culture, the media and social factors,” says MSUTR co-director Kelly Klump. "Because of twins studies, we now know that genes account for the same amount of variability in eating disorders as they do in schizophrenia and bipolar disorder. We would have never known that without twins studies."

The Genetics of Obesity

A classic twin study conducted by geneticist Claude Bouchard in 1990 looked at the importance of genes for body-fat storage. Bouchard, now at Louisiana State University, housed a dozen lean young male twins in a dormitory and overfed them by 1,000 calories a day for three months. Although every participant was heavier by the end of the experiment, the amount of weight and fat gained varied considerably, from 9 pounds to 29 pounds. Weight gain within pairs of twins was much more similar than weight gain between different twin pairs, and the twins in each pair tended to gain weight in the same places, whether it be in the abdomen, buttocks or thighs.

Untangling the "Gay Gene"

Numerous twin studies have attempted to elucidate the importance of genes in sexual orientation. In 2008, researchers led by Niklas Langström, a psychiatrist at the Karolinska Institute in Stockholm, drew upon the treasure trove of twin data contained in the Swedish Twin Registry, the largest in the world, to investigate genetic and environmental influences that determine whether or not a person is gay. The scientists found that genetics accounted for only 35 percent of the differences between identical and fraternal gay men and even less—roughly 18 percent—in gay women.

The study, one of the most comprehensive to date, indicates that a complex interplay of genetics and environmental factors work together to shape people’s sexual orientations. But like other twins studies on this controversial subject, Langström’s study was criticized for possible recruitment bias, since only 12 percent of the males in the Swedish registry were included in the study.

Twins Reared Apart

In 1979, Thomas Bouchard conducted what is perhaps the most fascinating twin study yet. Then director of the Minnesota Center for Twin and Family Research, Bouchard looked at identical and fraternal twins separated in infancy and reared apart. He found that identical twins who had different upbringings often had remarkably similar personalities, interests and attitudes. In one of the most famous examples, Bouchard came across twins who had been separated from birth and reunited at the age of 39.

"The twins," Bouchard later wrote, "were found to have married women named Linda, divorced, and married the second time to women named Betty. One named his son James Allan, the other named his son James Alan, and both named their pet dogs Toy."

But MSUTR's Klump is quick to point out that Bouchard's findings are not proof of genetic determinism. "What they show is that we we enter the world not as random beings or blank slates,” Klump says. “As we walk through life, we have a lot of free choice, but some portion of that free choice is probably based on things that we're really good at and things that we like to do. Bouchard's study tells us that there is a dynamic interplay between what we like, what we want and the environments that we choose."

About Ker Than

Ker Than is a freelance science writer living in the Bay Area. He has written for National Geographic, New Scientist, and Popular Science.


Evolution of Twin Studies

The similarity between twins has been a source of curiosity since time immemorial. The idea of using twins to study the heritability of traits can be traced back to the British researcher Sir Francis Galton. His pioneering work The History of Twins in 1875 inspired much debate by suggesting that England's 𠇌hief men of genius” were the product more of good breeding (nature) than of good rearing (nurture). Based on the similarities he found between twins from 80 questionnaires, Galton proudly announced his conclusion to the world that nature soundly beats nurture, though his sample was too small and consisted of all upper-class individals, without any control group. After nearly five decades, in the 1920s researchers “perfected' Galton's methods by comparing identical and fraternal twins and inferring heritability from the differences between the two.(3)

The first reported classical twin study was a study performed by Walter Jablonski in 1922, investigating the contribution of heredity to refraction in human eyes. Jablonski examined the eyes of 52 twin pairs and by comparing the size of within-pair differences between identical and nonidentical twins was able to infer the heritability of a trait.(4)

Even later, in 1990, Thomas J. Bouchard, Jr. and his colleagues (including esteemed twin researcher Nancy L. Segal) at the University of Minnesota conducted one of the most famous research studies on genetic influence in humans. They studied identical twins separated since birth and raised by different families (adoption studies), and so assumed that similarities, if found any, must be those that are heavily influenced by a person's genetic heritage. The study was invoked by the sensational news reports of two identical twins reunited after a lifetime apart. James Lewis and James Springer were separated 4 weeks after birth and each infant was taken in by a different adoptive family. When they were reunited at the age of 39, an extraordinary collection of coincidences emerged. Both of the “Jim twins” had married and divorced women named Linda. Both had second marriages with women named Betty. Both had police training and worked part-time with law enforcement agencies. Both had childhood pets named Toy. They had identical drinking and smoking patterns, and both chewed their fingernails to the nub. Their firstborn sons were named James Alan Lewis and James Allan Springer.(5) Bouchard and Segal reported that about 70% of the variance in intelligence quotient (IQ) found in their particular sample of identical twins was found to be associated with genetic variation. Furthermore, identical twins reared apart were eerily similar to identical twins reared together in various measures of personality, personal mannerisms, expressive social behavior, and occupational and leisure-time interests. However, they did not find outstanding similarities between identical twins on measures such as standardized personality tests. Still, Bouchard's findings can be interpreted as strong support for genetic influences on personality. Bouchard's data set was unique and probably a one-time event in history because modern adoption agencies no longer break up sets of identical twins.(6,7)

The modern-day classical twin study design relies on studying twins raised in the same family environments, which provides control not only for genetic background but also for shared environment in early life. As monozygotic (identical) twins develop from a single egg fertilized by a single sperm, which splits after the egg starts to develop, they are expected to share all of their genes, whereas dizygotic (fraternal) twins share only about 50% of them, which is the same as nontwin siblings.(8) Thus, if any excess similarity is seen between the identical twins when a researcher compares the similarity between sets of identical twins to the similarity between sets of fraternal twins for a trait or condition, then most probably the reason behind this similarity is due to genes rather than environment.

Some assumptions are also made in twin studies one of them is the assumption of random mating, which assumes that people are as likely to choose partners who are different from themselves as they are to choose partners who are similar for a particular trait. If, instead, people tend to choose mates like themselves, then fraternal twins could share a greater percentage of their genes than expected. In the case of nonrandom mating, fraternal twins would have more genetically influenced traits in common than expected because the genes they receive from their mothers and fathers would be similar to each other. Similarly, the assumption of equal environments is also made, which assumes that fraternal and identical twins raised in the same homes experience similar environments. It is assumed that genes and the environment typically make only separate and distinct contributions to a trait. In general, it is also assumed that only one type of genetic mechanism—usually additive—operates for a particular trait. However, traits can be inherited through different genetic mechanisms. Additive genetic mechanisms mix together the effects of each allele. For example, if genes for curly hair were additive, a curly-haired father and a straight-haired mother might have a child who has wavy hair.(8)

There can be variations in the classical model, which may sometimes provide an added advantage, for example if twins are followed up over longer duration of time in longitudinal manner to assess the development of adult-onset traits and conditions. This slight deviation will allow for a more complete and accurate assessment of environmental factors over time. Similarly, on combining with molecular genetics, information about the presence or absence of specific genetic variants to determine the impact on the trait of interest can be explored. The advances in molecular genetics have substantiated hypotheses generated by the traditional twin research design by pinpointing the effects of a particular gene. Depending on the objectives of the study, one may need only monozygotic or dizygotic twins, or a combination of the two.(8)


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When we take a closer look at how a human is created and how our genes are developed, we get a clearer understanding how different people truly are even when born into the same household with the same parents. Humans have different chromosomes, DNA, and genes. These genes according to David Myers believes, “You have 30,000 or so gene words” (2011), that is a lot of gene words for a person’s personality to develop from.

When we think about God, who created each one of us. “We are the clay, you are the potter we are all the work of your hand” (Isaiah 64:8). I am overwhelmed by the realization of how much God loves us, to create us all differently. We are an original, no two people have the same fingerprint or identical DNA. You and I are masterpieces, “…I am fearfully and wonderfully made: marvelous are your works…” (Psalm 139) Advantages and disadvantages in using twins to analyze genetic heritability.

Being created unique and differently, still raises the age-old question, how much does enviroment (nurture) influence personality? Parents still do influence a child’s attitude, value, manners, faith, and politics. Suppose you take identical twins, and the parents divorce and each parent takes one child and raises them differently. According to behavior geneticists the twins could still have the same likes, dislikes, mannerisms, laugh, sense of humar, and tastes in spouses. In conclusion, genetic heritability is still a mystery.

Myers, D.G. (2011). Exploring Psychology: Eighth edition in modules. New York, NY: Worth Publishers.

Re: Topic 4 DQ 1

The advantage is you have two genetically identical people that came from the same egg (monozygotic) and are virtually a carbon copy on one and another. Analyzing the set of twins can give you duplicate results and verifying the results will not be as difficult if they are the only set of children in the family. If they have other siblings then you have two sets of results that can be verified or contested with the other sibling(s). If the heritability results match then we can see we do inherit some of our personality genes from our parents. The disadvantage is they are both raised in the same environment and one can say the environment has an influence in shaping a portion of their personality. Another advantage is the nonadditive effect for monozygotic twins. The probability of sharing exact combination of genes is greater in monozygotic twins than it is with dizygotic twins. Nonadditive effects strengthen the genetic heritability in monozygotic twins but not in dizygotic twins. One serious ethical issue I can see is separating monozygotic or dizygotic twins at birth and separating them by distance and economical tiers to validate the genetic heritability. Advantages and disadvantages in using twins to analyze genetic heritability.

Topic 4 DQ 1

The different types of twins include identical and fraternal twins. Identical twins are made when a fertilized egg is split thus creating twins. Fraternal twins are made when two eggs are fertilized at the same time. Each set of twins are unique and different in their own ways. However, one major advantage to twins is their genetic makeup. Twin A and twin B always have the same DNA which can somewhat be looked at as variables. One twin could technically be the dependent variable and the other the dependent due. Advantages and disadvantages in using twins to analyze genetic heritability. For example, if trying to research if breast milk really is best for a baby a mother could breast feed baby A and formula feed baby B. Using the twins that have the same genetic makeup leave less margin for error in my opinion. To look at this from a personality psychological stand point let’s take the movie parent trap. Identical twin girls are separated and live two completely different life styles. If we were trying to see if the twins developed any personality traits from their other parent it would be easier because we would not have the actual parents personality shaping how they are. It would be considered an outside factor because they are not influenced every day by their superego. However, if they were to be raised in the same environment this would leave to the possibility of disadvantages of both their mother and father having an effect on their personalities Advantages and disadvantages in using twins to analyze genetic heritability. Although I believe it is unethical to purposely separate twins I do believe there can be positives to it and if done in a good way can be beneficial. For example, I have three sets of twins in my class one set of parents is very adamant about them being together at all times the other two could careless as long as it does not affect their behavior in a negative way. We separate twin O and twin J at meal times because we know if they are together they tend to throw food, kick their friends, and not eat. However, at nap time we have them together because they sleep better when near each other. In my opinion, if done in a manner that does not separate them fully it is best for both twins. Advantages and disadvantages in using twins to analyze genetic heritability


Key Study: The Minnesota Twin Study of Twins Reared Apart

Understanding how and why twin studies are used is an important topic in biological psychology because they can give us important insights into the extent to which our behaviour is nature (genetics) or nurture.

Context

Is our behaviour a product of nature or nurture? In other words, are we born the way we are, or have we become this way through years of experiences? This is the classic question in psychology and one that Bouchard and his colleagues have attempted to answer since 1979 at their Minnesota Centre for Twin and Family Research (MICTFR) .

In this time, over 100 sets of reared-apart twins and triplets have participated in the research. Rigorous analysis of scores of data has enabled the researchers to draw some strong conclusions. The following “study” is similar to the Vietnam Head Injury Study (read more here) in that it is one report from an ongoing longitudinal study.

Twin and kinship studies are used to determine heritability – the extent to which variations in behaviour can be attributed to genetic factors. e.g. 50% heritability for IQ means that differences in IQ are half (50%) due to genetics, and the other half is environment.

Monozygotic (identical) twins have 100% of their DNA in common, whereas dizygotic (fraternal) twins have on average 50% of their DNA in common. Twin studies compare similarities in behaviour between MZ and DZ twins. Comparing similarities in behaviour between MZ and DZ twins allows researchers to see the extent to which these variations are based on genetics.

If two identical twins grow up to be completely different from one another, we can assume that their environments were more influential in their behaviour than genetics. However, if they grow up similar despite very different childhoods, we can . conclude genetics is more important. This is basically how twin studies work, although they are more scientific in their approach.

In adoption studies (like the one below), the can also compare MZT twins (monozygotic together twins) – those who have been raised in the same household and those who have been raised apart (MZA). This allows researchers to compare the variable of the environmental influences on behaviour (because genetics is a constant variable between these two groups).

The behaviour we will focus on in this particular review is intelligence (IQ).

Methods

The researchers for this study (and continual studies) don’t gather all their data at once, but continually, as they find participants to take part in the research. The participants come from mainly the UK and USA, but have also included Australia, Canada, China, New Zealand, Sweden and Germany.

They become involved either because:

  • the twins, a friend or family member finds out about the research
  • someone involved in the adoption process works with the MICTFR to put them in contact with the twin
  • Or…one twin becomes aware that they may have a twin somewhere and they contact the MICTFR and ask for their help in finding their separated twin.

Twin study by Bouchard et al. (1990)

For this study, the average age of the twins when they participate in this study was 41, which is important because most twin research prior to this focused on adolescents. The twins spent an average of 5 months together before being separated and reunited (on average) around 30 years of age.

Physical and psychological data was gathered in a number of different ways, which took around 50 hours. Methods were triangulated, either using researcher triangulation or methodological triangulation. For instance, when measuring IQ, three different IQ tests were used to gather and triangulate the data. And two different researchers conducted similar tests on the same participants. Controls were also established, like conducting the IQ tests on the twins at the same time but in different rooms under strict supervision by researchers.

Can you think of any ethical issues with this study?

To control for confounding variables in the environment, rigorous data was gathered on the childhood environments of the participants. For instance, a “Moos Family Environment Scale” was used to compare the impressions of the participants’ childhoods and a questionnaire was given to measure access to physical facilities, such as material possessions and cultural, mechanical and scientific goods. For instance, were their dictionaries, artworks and power tools in the house when they were growing up? This type of data enables researchers to draw conclusions regarding socio-economic environment of the families and where the participants grew up.

Results

The analysis of the data revealed no significant difference between MZA twins (reared apart) and MZT twins (reared together) in regards to personality measures such as temperament, hobbies, interests, career pursuits or social attitudes.

Similar to previous research, this study also concluded that about 70% of differences between IQs in twins is due to genetic variation (70% heritability) the remaining 30% of difference is caused by environmental factors, which is similar to previous research.

There was also evidence from this study that suggested that twins that spend more time together after they are re-united are more similar. However, the data also suggested that it is the level of similarity between the twins that determines how much time they spend together, not the other way around.

Through their analysis of genetic and environmental variance, Bouchard et. al. concluded that genetics are an important factor in determining behaviour, but environment is also important. In addition to other research that suggests IQ similarities between children and adults increase over time , the researchers conclude that it can be our genetics that determines our environmental experiences. For example, if we have a naturally introverted disposition due to genetics, this will influence our psychological and personal experiences in life. If we think about neuroplasticity (the brain’s ability to change as a result of experience), you should be able to see how our intelligence may be malleable and this malleability is caused by a combination of genetic and environmental factors.

Critical Thinking Questions

  • How do the results of this study show intelligence is influenced by genetics and/or our environment? ( Application)
  • What are some relevant ethical considerations particular to this study? ( Analysis)
  • What are the strengths and limitations of this longitudinal study? ( Evaluation)
Bouchard, Thomas J, Jr. Lykken, David T. McGue, Matthew. Segal, Nancy L and Tellegen, Auke. “ Sources of Human Psychological Differences: The Minnesota Study of Twins Researched Apart.” Sciences, New Series, Vol. 250 (1990), pp223-8. Accessed from web.missouri.edu

The film “Three Identical Strangers” provides us with an interesting first-hand look into the world of psychological studies on twins separated at birth (link).

Travis Dixon is an IB Psychology teacher, author, workshop leader, examiner and IA moderator.


5. Twin and molecular studies give different estimates of heritability

Comparison of results of twin and molecular genetic studies reveals a puzzle: the genetic findings from molecular studies do not come close to explaining the high levels of heritability found in twin studies.

This problem of ‘missing heritability’ is not restricted to reading difficulties, but is seen even for physical phenotypes such as height [27], where measurement is straightforward and very large sample sizes have been used. There are essentially two ways of accounting for missing heritability: either the GWA method does not account for all aspects of heritability or twin studies overestimate heritability.

Recent advances in statistical methods have confirmed that traditional GWA does indeed underestimate overall genetic effects on a trait, and it has been argued that we should talk of ‘hidden’ rather than ‘missing’ heritability [28]. A GWA study involves looking at each DNA variant separately to see whether the degree of association surpasses a stringent threshold. This means that weak but genuine associations with the phenotype may get missed. To address this issue, methods have been developed for comparing similarity between individuals on an entire collection of SNPs and then relating this similarity metric to phenotypic similarity. This approach, genome-wide complex trait analysis (GCTA), which does not identify specific genes associated with disorder, has been shown to account for substantially more phenotypic variance than conventional GWA methods [29]. To date, there has been one GCTA study focused on reading ability, and, as with studies of other phenotypes, it found substantially more evidence for genotype–phenotype association than a conventional GWA study (variance accounted for by SNPs = 0.28), but less than was observed in a twin analysis based on the same sample (heritability = 0.73) [30]. While bearing in mind that the sample sizes available for studies of reading disability have been relatively small, and so may miss genuine but small effects, it would appear that here, as for other traits, some ‘missing heritability’ remains to be explained.

(a) Rare variants and copy number variants

As Gibson [31] noted, people have tended to contrast two models of inheritance. The ‘infinitesimal’ model, which is often assumed in dyslexia, is poetically described by Kirkpatrick et al. [32] as involving common variants that are �h Lilliputian in effect size, but together, are legion in number’ and add together to create risk. By contrast, in the ‘rare allele’ model, the effects of risk variants are large, but the individual variants each account for only a tiny proportion of cases. Of course, these are not mutually exclusive and both models may well apply to dyslexia. Both are difficult to verify in a GWA study, which will not detect very small effects of common variants, or large effects of very rare variants.

Great excitement was caused in 2006 when it was shown that copy number variations (CNVs) are remarkably common in the general population [33]. Although people mostly have two copies of each strand of DNA—one from each parent𠅎veryone has segments of the genome where chunks of DNA are deleted or duplicated𠅌NVs. Those affecting non-coding stretches of DNA may have little or no effect, but if the duplications or deletions include genes, then the CNV is likely to have functional consequences. CNVs could potentially account for individual differences, but on the other hand, the fact they are common in the general population means that it would be dangerous to assume that a particular CNV found in an individual necessarily plays a role in their disorder [34].

To date, few studies have assessed the role of CNVs in the aetiology of common neurodevelopmental disorders. The frequency of large CNVs is increased in cases of intellectual disability or autism, but in dyslexia the rate is closely similar to that found in unaffected controls [35]. This does not mean that CNVs are never implicated in dyslexia, but they do not seem to be a common cause.

(b) Gene–gene interaction

Two genetic variants that individually cause only mild risk for disorder may exert a much greater effect in combination—if, for instance, they are involved in the same neural pathway. To date, this idea of a 𠆍ouble hit’ on a neural circuit has been developed in the context of individuals with relatively large structural genetic changes and severe phenotypes [36] however, the same logic could apply to combinations of common variants leading to milder phenotypes. Two common variants that independently exert only a small effect might together be more detrimental in combination. Because MZ twins share the same DNA sequence, they will be identical for such gene–gene combinations, whereas in DZ twins, if genes are inherited separately, then the odds of the detrimental combination is lower than the odds of inheriting just one detrimental variant. Thus, in the presence of gene–gene interactions (epistasis), twin studies will overestimate heritability if an additive model is assumed.

(c) Gene𠄾nvironment interaction

Gene𠄾nvironment interaction refers to the situation where the impact of genetic variation depends on the environmental context [37]. One way of testing for such interaction is to consider whether different levels of a measured environmental variable are associated with different levels of heritability. This was done in a study using DeFries𠄿ulker analysis with the CLDRC sample by Friend et al. [19]. As well as reporting overall heritability, these authors subdivided twins according to parental educational level. Heritability of poor reading was higher for children with highly educated parents (, 95% confidence interval: 0.55𠄰.88) than for those with less well-educated parents (, 95% confidence interval: 0.32𠄰.66). The authors concluded that the effect of genes will be particularly evident in children who fail to learn to read despite good environmental support. This makes intuitive sense [21], but it is noteworthy that the finding was not replicated in another study that looked at the same question using slightly different methods [17].

The possibility that genetic effects may vary with the environment has implications for ‘missing heritability’. Most twin studies focus on twins who are growing up together. Consider the situation depicted in figure 3 : in panel (a), we have a trait affected by both genes and shared environment, with no interaction between the two. Panel (b) shows a gene × shared environment interaction (G × C). In a twin study, overall estimates of heritability will be similar for both these situations. Because the twin study compares similarity of MZ and DZ twins, it effectively controls for G × C effects, because C is by definition the same for the two members of the twin pair. However, a GWA study, which focuses on the regression of phenotype on genotype, may have weaker power to detect association in the gene × environment interaction case, because much of the variability in the phenotype is caused by environmental variation.

Illustration of (a) additive and (b) interactive gene𠄾nvironment effects at a single locus. The genotype is aa, aA or AA, corresponding to 0, 1 or 2 copies of the major allele.


Twin Studies, Adoption Studies, and Fallacious Reasoning

Twin and adoption studies have been used for decades on the basis that genetic and environmental causes of traits and their variation in the population could be easily partitioned by two ways: one way is to adopt twins into separate environments, the other to study reared-together or reared-apart twins. Both methods rest on a large number of (invalid) assumptions. These assumptions are highly flawed and there is no evidential basis to believe these assumptions, since the assumptions have been violated which invalidates said assumptions.

Plomin et al write (2013) write: For nearly a century, twin and adoption studies have yielded substantial estimates of heritability for cognitive abilities.

But the validity of the “substantial estimates of heritability for cognitive abilities” is strongly questioned due to unverified (and false) assumptions that these researchers make.

Adoption studies

The problem with adoption studies are numerous, not least: restricted range of adoptive families selective placement late separation parent-child attachment disturbance problems with the tests (on personality, ‘IQ’) the non-representativeness of adoptees compared to non-adoptees and the reliability of the characteristic in question.

In selective placement, the authorities attempt to place children in homes close to their biological parents. They gage how “intelligent” they believe they are (on the basis of parental SES and the child’s parent’s perceived ‘intelligence’), thusly this is a pretty huge confound for adoption studies.

According to adoption researcher Harry Munsinger, a “possible source of bias in adoption studies is selective placement of adopted children in adopting homes that are similar to their biological parents’ social and educational backgrounds.” He recognized that “‘fitting the home to the child’ has been the standard practice in most adoption agencies, and this selective placement can confound genetic endowment with environmental influence to invalidate the basic logic of an adoptive study (Munsinger, 1975, p. 627). Clearly, agency policies of “fitting the home to the child” are a far cry from random placement of adoptees into a wide range of adoptive homes. (Joseph, 2015: 30-1)

Richardson and Norgate (2005) argue that simple additive effects for both genetic and environmental effects are false that IQ is not a quantitative trait while other interactive effects could explain the IQ correlation.

1) Assignment is nonrandom. 2) They look for adoptive homes that reflect the social class of the biological mother. 3) This range restriction reduces the correlation estimates between adopted children and adopted parents. 4) Adoptive mothers come from a narrow social class. 5) Their average age at testing will be closet to their biological parents than adopted parents. 6) They experience the womb of their mothers. 7) Stress in the womb can alter gene expression. 8) Adoptive parents are given information about the birth family which may bias their treatment. 9) Biological mothers and adopted children show reduced self-esteem and are more vulnerable to changing environments which means they basically share environment. 10) Conscious or unconscious aspects of family treatment may make adopted children different from other adopted family members. 11) Adopted children also look more like their biological parents than their adoptive parents which means they’ll be treated accordingly.

Twin studies

Personally, my favorite thing to discuss. Twin studies rest on the erroneous assumption that DZ and MZ environments are equal that they get treated equally the same. This is false, MZ twins get treated more similarly than DZ twins, which twin researchers have conceded decades ago. But in order to save their field, they attempt to use circular argumentation, known as Argument A. Argument A states that MZTs (monozygotic twins reared together) are more genetically similar than DZTs (dizygotic twins reared together) and thusly this causes greater behavioral similarity. But this is based on circular reasoning: the researchers already implicitly assumed that genes played a role in their premise and, not surprisingly, in their conclusion genes are the cause for the similarities of the MZTs. So Argument A is used, twin researchers circularly assume that MZTs greater behavioral similarity is due to genetic similarity, while their argument that genetic factors explain the greater behavioral similarity of MZTs is a premise and conclusion of their argument. “X is true because Y is true Y is true because X is true.” (Also see Joseph et al, 2015.)

We have seen that circular reasoning is “empty reasoning in which the conclusion rests on an assumption whose validity is dependent on the conclusion” (Reber, 1985, p. 123).A circular argument consists of “using as evidence a fact which is authenticated by the very conclusion it supports,” which “gives us two unknowns so busy chasing each other’s tails that neither has time to attach itself to reality” (Pirie, 2006, p. 27) (Joseph, 2016: 164).

Even if Argument A is accepted, the causes of behavioral similarities between MZ/DZ twins could still come down to environment. Think of any type of condition that is environmentally caused but is due to people liking what causes the condition. There are no “genes for” that condition, but their liking the thing that caused the condition caused an environmental difference.

Argument B also exists. Those that use Argument B also concede that MZs experience more similar environments, but then argue that in order to show that twin studies, and the EEA, are false, critics must show that MZT and DZT environments differ in the aspects that are relevant to the behavior in question (IQ, schizophrenia, etc).

An example of an Argument B environmental factor relevant to a characteristic or disorder is the relationship between exposure to trauma and post-traumatic stress disorder (PTSD). Because trauma exposure is (by definition) an environmental factor known to contribute to the development of PTSD, a finding that MZT pairs are more similarly exposed to trauma than DZT pairs means that MZT pairs experience more similar “trait-relevant” environments than DZTs. Many twin researchers using Argument B would conclude that the EEA is violated in this case. (Joseph, 2016: 165)

So twin researchers need to rule out and identify “trait-relevant factors” which contribute to the cause of said trait, along with experiencing more similar environments, invalidates genetic interpretations made using Argument B. But Argument A renders Argument B irrelevant because even if critics can show that MZTs experience more similar “trait-relevant environments”, they could still argue that the twin method is valid by stating that (in Argument A fashion) MZTs create and elicit more similar trait-relevant environments.

One more problem with Argument A is that it shows that twins behave accordingly to “inherited environment-creating blueprint” (Joseph, 2016: 164) but at the same time shows that parents and other adults are easily able to change their behaviors to match that of the behaviors that the twins show, which in effect, allows them to “create” or “elicit” their own environments. But the adults’ “environment-creating behavior and personality” should be way more unchangeable than the twins’ since along with the presumed genetic similarity, adults have “experienced decades of behavior-molding peer, family, religious, and other socialization influences” (Joseph, 2016: 165).

Whether or not circular arguments are “useful” or not has been debated in the philosophical literature for some time (Hahn, Oaksford, and Corner, 2005). However, assuming, in your premise, that your conclusion is valid is circular and therefore While circular arguments are deductively valid, “it falls short of the ultimate goal of argumentative discourse: Whatever evaluation is attached to the premise is transmitted to the conclusion, where it remains the same no increase in degree of belief takes place” (Hahn, 2011: 173).

However, Hahn (2011: 180) concludes that “the existence of benign circularities makes clear that merely labeling something as circular is not enough to dismiss it an argument for why the thing in question is bad still needs to be made.” This can be simply shown: The premise that twin researchers use (that genes cause similar environments to be constructed) is in their conclusion. They state in their premise that MZT behavioral similarity is due to greater MZT genetic similarity in comparison to DZTs (100 vs. 50 percent). Then, in the conclusion, they re-state that the behavioral similarities of MZTs is due to their genetic similarity compared to DZTs (100 vs. 50 percent). Thus, a convincing argument for conclusion C (that genetic similarity explains MZT behavioral similarity) cannot rest on the assumptionthat conclusion C is correct. Thus, Argument A is fallacious due to its circularity.

What causes MZT behavioral similarities is their more similar environment: they get treated the same by peers and parents, and have higher rates of identity confusion and had a closer emotional bond compared to DZTs. The twin method is based on the (erroneous) assumption that MZT and DZT pairs experience roughly equal environments, which twin researchers conceded was false decades ago.

We have shown, first, that the EEA may not hold, and that well-demonstrated treatment effects can, therefore, explain part of the classic MZ–DZ differences. Using published correlations, we have also shown how sociocognitive interactions, in which DZ twins strive for a relative ‘apartness’, could further depress DZ correlations, thereby possibly explaining another part of the differences. We conclude that further conclusions about genetic or environmental sources of variance from MZ–DZ twin data should include thorough attempts to validate the EEA with the hope that these interactions and their implications will be more thoroughly understood.

Of course, even if twin studies were valid and the EEA was true/ the auxiliary arguments used were true, this would still not mean that heritability estimates would be of any use to humans, since we cannot control environments as we do in animal breeding studies (Schonemann, 1997 Moore and Shenk, 2016). I have chronicled how 1) the EEA is false and how flawed twin studies are 2) how flawed heritability estimates are 3) how heritability does not (and cannot) show causation and 4) the genetic reductionist model that behavioral geneticists rely on is flawed (Lerner and Overton, 2017).

So we can (1) accept the EEA, that the greater behavioral resemblance indicates the importance of genetic factors underlying most human behavioral differences and behavioral disorders or we can (2) reject the EEA and state that the greater behavioral resemblance is due to nongenetic (environmental) factors, which means that all genetic interpretations of MZT/DZT studies must be rejected. Thus, using (2), we can infer that all twin studies measure is similarity of the environment of DZTs, and it is, in fact, not measuring genetic factors. Accepting explanation 2 does not mean that “twin studies overestimate heritability, or that researchers should assess the EEA on a study-by-study basis, but instead indicates that the twin method is no more able than a family study to disentangle the potential influences of genes and environment” (Joseph, 2016: 181).

What it does mean, however, is that we can, logically, discard all past, future, and present MZT and DZT comparisons and these genetic interpretations must be outright rejected, due to the falsity of the EEA and the fallaciousness of the auxiliary arguments made in order to save the EEA and the twin method overall.

There are further problems with twin studies and heritability estimates. Epigenetic supersimilarity (ESS) also confounds the relationship. Due to the existence of ESS “human MZ twins clearly cannot be viewed as the epigenetic equivalent of isogenic inbred mice, which originate from separate zygotes. To the extent that epigenetic variation at ESS loci influences human phenotype, as our data indicate, the existence of ESS establishes a link between early embryonic epigenetic development and adult disease and may call into question heritability estimates based on twin studies” (Van Baak et al, 2018). In other words, ESS is an unrecognized phenomenon that contributes to the phenotypic similarity of MZs, which calls into question the usefulness of heritability studies using twins. The uterine environment has been noted to be a confound by numerous authors (Devlin, Daniels, and Roeder, 1997 Charney, 2012 Ho, 2013 Moore and Shenk, 2016).

Adoption studies fall prey to numerous pitfalls, most importantly, that children are adopted into similar homes compared to their birth parents, which restricts the range of environments for adoptees. Adoption placement is also non-random, the children are placed into homes that are similar to their biological parents. Due to these confounds (and a whole slew of other invalidating problems), adoption studies cannot be said to show genetic causation, nor can they separate genetic from environmental factors.

Twin studies suffer from the biggest flaw of all: the falsity of the EEA. Since the EEA is false—which has been recognized by both critics and supporters of the assumption—the supporters of the assumption have attempted to redefine the EEA in two ways: (1) that MZTs experience more similar environments due to genetic similarity (Argument A) and (2) that it is not whether MZTs experience more similar environments, but whether or not they share more similar trait-relevant environments. Thus, unless these twin researchers are able to identify trait-relevant factors that contribute to the trait in question, we must conclude that (along with the admission from twin researchers that the EEA is false that MZTs experience more similar environments than DZTs) genetic interpretations made using Argument B are thusly invalidated. Fallacious reasoning (“X causes Y Y causes X) does not help any twin argument. Because their conclusion is already implicitly assumed in their premise.

The existence of ESS (epigenetic supersimilarity) further shows how invalid the twin method truly is, because the confounding starts in the womb. Attempts can be made (however bad) to control for shared environment by adopting different twins into different homes, but they still shared a uterine environment which means they shared an environment, which means it is a confound and it cannot be controlled for (Charney, 2012).

Adoption and twin studies are highly flawed. Like family studies, twin studies are no more able to disentangle genetic from environmental effects than a family study, and thus twin studies cannot separate genes from environment. Last, and surely not least, it is fallacious to assume that genes can be separated so neatly into “heritability estimates” as I have noted in the past. Heritability estimates cannot show genetic causation, nor can it show how malleable a trait is. They’re just (due to how we measure) flawed measures that we cannot fully control so we must make a number of (false) assumptions that then invalidate the whole paradigm. The EEA is false, all auxiliary arguments made to save the EEA are fallacious adoption studies are hugely confounded twin studies are confounded due to numerous reasons, most importantly the uterine environment (Van Baak et al, 2018).


Key Study: The Minnesota Twin Study of Twins Reared Apart

Understanding how and why twin studies are used is an important topic in biological psychology because they can give us important insights into the extent to which our behaviour is nature (genetics) or nurture.

Context

Is our behaviour a product of nature or nurture? In other words, are we born the way we are, or have we become this way through years of experiences? This is the classic question in psychology and one that Bouchard and his colleagues have attempted to answer since 1979 at their Minnesota Centre for Twin and Family Research (MICTFR) .

In this time, over 100 sets of reared-apart twins and triplets have participated in the research. Rigorous analysis of scores of data has enabled the researchers to draw some strong conclusions. The following “study” is similar to the Vietnam Head Injury Study (read more here) in that it is one report from an ongoing longitudinal study.

Twin and kinship studies are used to determine heritability – the extent to which variations in behaviour can be attributed to genetic factors. e.g. 50% heritability for IQ means that differences in IQ are half (50%) due to genetics, and the other half is environment.

Monozygotic (identical) twins have 100% of their DNA in common, whereas dizygotic (fraternal) twins have on average 50% of their DNA in common. Twin studies compare similarities in behaviour between MZ and DZ twins. Comparing similarities in behaviour between MZ and DZ twins allows researchers to see the extent to which these variations are based on genetics.

If two identical twins grow up to be completely different from one another, we can assume that their environments were more influential in their behaviour than genetics. However, if they grow up similar despite very different childhoods, we can . conclude genetics is more important. This is basically how twin studies work, although they are more scientific in their approach.

In adoption studies (like the one below), the can also compare MZT twins (monozygotic together twins) – those who have been raised in the same household and those who have been raised apart (MZA). This allows researchers to compare the variable of the environmental influences on behaviour (because genetics is a constant variable between these two groups).

The behaviour we will focus on in this particular review is intelligence (IQ).

Methods

The researchers for this study (and continual studies) don’t gather all their data at once, but continually, as they find participants to take part in the research. The participants come from mainly the UK and USA, but have also included Australia, Canada, China, New Zealand, Sweden and Germany.

They become involved either because:

  • the twins, a friend or family member finds out about the research
  • someone involved in the adoption process works with the MICTFR to put them in contact with the twin
  • Or…one twin becomes aware that they may have a twin somewhere and they contact the MICTFR and ask for their help in finding their separated twin.

Twin study by Bouchard et al. (1990)

For this study, the average age of the twins when they participate in this study was 41, which is important because most twin research prior to this focused on adolescents. The twins spent an average of 5 months together before being separated and reunited (on average) around 30 years of age.

Physical and psychological data was gathered in a number of different ways, which took around 50 hours. Methods were triangulated, either using researcher triangulation or methodological triangulation. For instance, when measuring IQ, three different IQ tests were used to gather and triangulate the data. And two different researchers conducted similar tests on the same participants. Controls were also established, like conducting the IQ tests on the twins at the same time but in different rooms under strict supervision by researchers.

Can you think of any ethical issues with this study?

To control for confounding variables in the environment, rigorous data was gathered on the childhood environments of the participants. For instance, a “Moos Family Environment Scale” was used to compare the impressions of the participants’ childhoods and a questionnaire was given to measure access to physical facilities, such as material possessions and cultural, mechanical and scientific goods. For instance, were their dictionaries, artworks and power tools in the house when they were growing up? This type of data enables researchers to draw conclusions regarding socio-economic environment of the families and where the participants grew up.

Results

The analysis of the data revealed no significant difference between MZA twins (reared apart) and MZT twins (reared together) in regards to personality measures such as temperament, hobbies, interests, career pursuits or social attitudes.

Similar to previous research, this study also concluded that about 70% of differences between IQs in twins is due to genetic variation (70% heritability) the remaining 30% of difference is caused by environmental factors, which is similar to previous research.

There was also evidence from this study that suggested that twins that spend more time together after they are re-united are more similar. However, the data also suggested that it is the level of similarity between the twins that determines how much time they spend together, not the other way around.

Through their analysis of genetic and environmental variance, Bouchard et. al. concluded that genetics are an important factor in determining behaviour, but environment is also important. In addition to other research that suggests IQ similarities between children and adults increase over time , the researchers conclude that it can be our genetics that determines our environmental experiences. For example, if we have a naturally introverted disposition due to genetics, this will influence our psychological and personal experiences in life. If we think about neuroplasticity (the brain’s ability to change as a result of experience), you should be able to see how our intelligence may be malleable and this malleability is caused by a combination of genetic and environmental factors.

Critical Thinking Questions

  • How do the results of this study show intelligence is influenced by genetics and/or our environment? ( Application)
  • What are some relevant ethical considerations particular to this study? ( Analysis)
  • What are the strengths and limitations of this longitudinal study? ( Evaluation)
Bouchard, Thomas J, Jr. Lykken, David T. McGue, Matthew. Segal, Nancy L and Tellegen, Auke. “ Sources of Human Psychological Differences: The Minnesota Study of Twins Researched Apart.” Sciences, New Series, Vol. 250 (1990), pp223-8. Accessed from web.missouri.edu

The film “Three Identical Strangers” provides us with an interesting first-hand look into the world of psychological studies on twins separated at birth (link).

Travis Dixon is an IB Psychology teacher, author, workshop leader, examiner and IA moderator.


A Brief History of Twin Studies

On Tuesday, NASA astronaut Scott Kelly and Russian cosmonaut Mikhail Kornienko touched down in Kazakhstan after spending a whopping 340 days aboard the International Space Station (ISS).

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As part of NASA’s "Year in Space" project, Kelly and his Earth-bound identical twin brother, retired astronaut Mark Kelly, provided samples of blood, saliva and urine and underwent a barrage of physical and psychological tests designed to study the effects of long-duration spaceflight on the human body.

Studies of identical and fraternal twins have long been used to untangle the influences of genes and the environment on particular traits. Identical twins share all of their genes, while fraternal twins only share 50 percent. If a trait is more common among identical twins than fraternal twins, it suggests genetic factors are partly responsible.

"Twins studies are the only real way of doing natural experiments in humans," says Tim Spector, a professor of genetic epidemiology at Kings College, London. "By studying twins, you can learn a great deal about what makes us tick, what makes us different, and particularly the roles of nature versus nature that you just can't get any other way.”

Spector is director of the TwinsUK Registry, which includes data from 12,000 twins and is used to study the genetic and environmental causes of age-related complex traits and diseases. He estimates that twins research is currently being conducted in more than 100 countries, and that most of those projects draw upon information contained in large databases such as the TwinsUK Registry.

While it may be a while before we see results from the astronaut twins, researchers are hopeful that the opportunity will yield some unique insights into human health. Here are some examples of what we've learned from past twins studies—both famous and infamous:

The Birth of Eugenics

Victorian scientist Francis Galton, a half-cousin of Charles Darwin, was one of the first people to recognize the value of twins for studying the heritability of traits. In an 1875 paper titled "The History of Twins," Galton used twins to estimate the relative effects of nature versus nature (a term that Galton himself coined). But his firm belief that human intelligence is largely a matter of nature led him to a darker path: He became a vocal proponent of eugenics (another term that he coined) and the idea that "a highly gifted race of men" could be produced through selective breeding.

Genes and I.Q.

In 2003, Eric Turkheimer, a psychology professor at the University of Virginia, took a fresh look at the research on the heritability of I.Q., which relied heavily on twin studies. Turkheimer noticed that most of the studies that found I.Q. is largely due to genetics involved twins from middle-class backgrounds, and he wondered what the pattern was among poorer people. When he looked at twins from poor families, he found that the I.Q.s of identical twins varied just as much as the I.Q.s of fraternal twins. In other words, the impact of growing up poor can overwhelm a child's natural intellectual gifts.

Genetic Basis for Everyday Diseases

Working with data and biological samples in the TwinsUK Registry, Spector and his colleagues have shown in more than 600 published papers that many common diseases such as osteoarthritis, cataracts and even back pain have a clear genetic basis to them. "When I started in this field, it was thought that only 'sexy' diseases [such as cancer] were genetic," Spector says. "Our findings changed that perception."

Heritable Eating Disorders

One of the newer twin registries to come online, the Michigan State University Twin Registry (MSUTR) was founded in 2001 to study genetic and environmental influences on a wide range of psychiatric and medical disorders. One of the most surprising findings to come out of the group's research is that many eating disorders such as anorexia have a genetic component to them.

"People thought for the longest time that it was due entirely to culture, the media and social factors,” says MSUTR co-director Kelly Klump. "Because of twins studies, we now know that genes account for the same amount of variability in eating disorders as they do in schizophrenia and bipolar disorder. We would have never known that without twins studies."

The Genetics of Obesity

A classic twin study conducted by geneticist Claude Bouchard in 1990 looked at the importance of genes for body-fat storage. Bouchard, now at Louisiana State University, housed a dozen lean young male twins in a dormitory and overfed them by 1,000 calories a day for three months. Although every participant was heavier by the end of the experiment, the amount of weight and fat gained varied considerably, from 9 pounds to 29 pounds. Weight gain within pairs of twins was much more similar than weight gain between different twin pairs, and the twins in each pair tended to gain weight in the same places, whether it be in the abdomen, buttocks or thighs.

Untangling the "Gay Gene"

Numerous twin studies have attempted to elucidate the importance of genes in sexual orientation. In 2008, researchers led by Niklas Langström, a psychiatrist at the Karolinska Institute in Stockholm, drew upon the treasure trove of twin data contained in the Swedish Twin Registry, the largest in the world, to investigate genetic and environmental influences that determine whether or not a person is gay. The scientists found that genetics accounted for only 35 percent of the differences between identical and fraternal gay men and even less—roughly 18 percent—in gay women.

The study, one of the most comprehensive to date, indicates that a complex interplay of genetics and environmental factors work together to shape people’s sexual orientations. But like other twins studies on this controversial subject, Langström’s study was criticized for possible recruitment bias, since only 12 percent of the males in the Swedish registry were included in the study.

Twins Reared Apart

In 1979, Thomas Bouchard conducted what is perhaps the most fascinating twin study yet. Then director of the Minnesota Center for Twin and Family Research, Bouchard looked at identical and fraternal twins separated in infancy and reared apart. He found that identical twins who had different upbringings often had remarkably similar personalities, interests and attitudes. In one of the most famous examples, Bouchard came across twins who had been separated from birth and reunited at the age of 39.

"The twins," Bouchard later wrote, "were found to have married women named Linda, divorced, and married the second time to women named Betty. One named his son James Allan, the other named his son James Alan, and both named their pet dogs Toy."

But MSUTR's Klump is quick to point out that Bouchard's findings are not proof of genetic determinism. "What they show is that we we enter the world not as random beings or blank slates,” Klump says. “As we walk through life, we have a lot of free choice, but some portion of that free choice is probably based on things that we're really good at and things that we like to do. Bouchard's study tells us that there is a dynamic interplay between what we like, what we want and the environments that we choose."

About Ker Than

Ker Than is a freelance science writer living in the Bay Area. He has written for National Geographic, New Scientist, and Popular Science.


Evolution of Twin Studies

The similarity between twins has been a source of curiosity since time immemorial. The idea of using twins to study the heritability of traits can be traced back to the British researcher Sir Francis Galton. His pioneering work The History of Twins in 1875 inspired much debate by suggesting that England's 𠇌hief men of genius” were the product more of good breeding (nature) than of good rearing (nurture). Based on the similarities he found between twins from 80 questionnaires, Galton proudly announced his conclusion to the world that nature soundly beats nurture, though his sample was too small and consisted of all upper-class individals, without any control group. After nearly five decades, in the 1920s researchers “perfected' Galton's methods by comparing identical and fraternal twins and inferring heritability from the differences between the two.(3)

The first reported classical twin study was a study performed by Walter Jablonski in 1922, investigating the contribution of heredity to refraction in human eyes. Jablonski examined the eyes of 52 twin pairs and by comparing the size of within-pair differences between identical and nonidentical twins was able to infer the heritability of a trait.(4)

Even later, in 1990, Thomas J. Bouchard, Jr. and his colleagues (including esteemed twin researcher Nancy L. Segal) at the University of Minnesota conducted one of the most famous research studies on genetic influence in humans. They studied identical twins separated since birth and raised by different families (adoption studies), and so assumed that similarities, if found any, must be those that are heavily influenced by a person's genetic heritage. The study was invoked by the sensational news reports of two identical twins reunited after a lifetime apart. James Lewis and James Springer were separated 4 weeks after birth and each infant was taken in by a different adoptive family. When they were reunited at the age of 39, an extraordinary collection of coincidences emerged. Both of the “Jim twins” had married and divorced women named Linda. Both had second marriages with women named Betty. Both had police training and worked part-time with law enforcement agencies. Both had childhood pets named Toy. They had identical drinking and smoking patterns, and both chewed their fingernails to the nub. Their firstborn sons were named James Alan Lewis and James Allan Springer.(5) Bouchard and Segal reported that about 70% of the variance in intelligence quotient (IQ) found in their particular sample of identical twins was found to be associated with genetic variation. Furthermore, identical twins reared apart were eerily similar to identical twins reared together in various measures of personality, personal mannerisms, expressive social behavior, and occupational and leisure-time interests. However, they did not find outstanding similarities between identical twins on measures such as standardized personality tests. Still, Bouchard's findings can be interpreted as strong support for genetic influences on personality. Bouchard's data set was unique and probably a one-time event in history because modern adoption agencies no longer break up sets of identical twins.(6,7)

The modern-day classical twin study design relies on studying twins raised in the same family environments, which provides control not only for genetic background but also for shared environment in early life. As monozygotic (identical) twins develop from a single egg fertilized by a single sperm, which splits after the egg starts to develop, they are expected to share all of their genes, whereas dizygotic (fraternal) twins share only about 50% of them, which is the same as nontwin siblings.(8) Thus, if any excess similarity is seen between the identical twins when a researcher compares the similarity between sets of identical twins to the similarity between sets of fraternal twins for a trait or condition, then most probably the reason behind this similarity is due to genes rather than environment.

Some assumptions are also made in twin studies one of them is the assumption of random mating, which assumes that people are as likely to choose partners who are different from themselves as they are to choose partners who are similar for a particular trait. If, instead, people tend to choose mates like themselves, then fraternal twins could share a greater percentage of their genes than expected. In the case of nonrandom mating, fraternal twins would have more genetically influenced traits in common than expected because the genes they receive from their mothers and fathers would be similar to each other. Similarly, the assumption of equal environments is also made, which assumes that fraternal and identical twins raised in the same homes experience similar environments. It is assumed that genes and the environment typically make only separate and distinct contributions to a trait. In general, it is also assumed that only one type of genetic mechanism—usually additive—operates for a particular trait. However, traits can be inherited through different genetic mechanisms. Additive genetic mechanisms mix together the effects of each allele. For example, if genes for curly hair were additive, a curly-haired father and a straight-haired mother might have a child who has wavy hair.(8)

There can be variations in the classical model, which may sometimes provide an added advantage, for example if twins are followed up over longer duration of time in longitudinal manner to assess the development of adult-onset traits and conditions. This slight deviation will allow for a more complete and accurate assessment of environmental factors over time. Similarly, on combining with molecular genetics, information about the presence or absence of specific genetic variants to determine the impact on the trait of interest can be explored. The advances in molecular genetics have substantiated hypotheses generated by the traditional twin research design by pinpointing the effects of a particular gene. Depending on the objectives of the study, one may need only monozygotic or dizygotic twins, or a combination of the two.(8)


A Swedish national twin study of criminal behavior and its violent, white-collar and property subtypes

Background: We sought to clarify the etiological contribution of genetic and environmental factors to total criminal behavior (CB) measured as criminal convictions in men and women, and to violent (VCB), white-collar (WCCB) and property criminal behavior (PCB) in men only.

Method: In 21 603 twin pairs from the Swedish Twin Registry, we obtained information on all criminal convictions from 1973 to 2011 from the Swedish Crime Register. Twin modeling was performed using the OpenMx package.

Results: For all criminal convictions, heritability was estimated at around 45% in both sexes, with the shared environment accounting for 18% of the variance in liability in females and 27% in males. The correlation of these risk factors across sexes was estimated at +0.63. In men, the magnitudes of genetic and environmental influence were similar in the three criminal conviction subtypes. However, for violent and white-collar convictions, nearly half and one-third of the genetic effects were respectively unique to that criminal subtype. About half of the familial environmental effects were unique to property convictions.

Conclusions: The familial aggregation of officially recorded CB is substantial and results from both genetic and familial environmental factors. These factors are moderately correlated across the sexes suggesting that some genetic and environmental influences on criminal convictions are unique to men and to women. Violent criminal behavior and property crime are substantially influenced respectively by genetic and shared environmental risk factors unique to that criminal subtype.


5. Twin and molecular studies give different estimates of heritability

Comparison of results of twin and molecular genetic studies reveals a puzzle: the genetic findings from molecular studies do not come close to explaining the high levels of heritability found in twin studies.

This problem of ‘missing heritability’ is not restricted to reading difficulties, but is seen even for physical phenotypes such as height [27], where measurement is straightforward and very large sample sizes have been used. There are essentially two ways of accounting for missing heritability: either the GWA method does not account for all aspects of heritability or twin studies overestimate heritability.

Recent advances in statistical methods have confirmed that traditional GWA does indeed underestimate overall genetic effects on a trait, and it has been argued that we should talk of ‘hidden’ rather than ‘missing’ heritability [28]. A GWA study involves looking at each DNA variant separately to see whether the degree of association surpasses a stringent threshold. This means that weak but genuine associations with the phenotype may get missed. To address this issue, methods have been developed for comparing similarity between individuals on an entire collection of SNPs and then relating this similarity metric to phenotypic similarity. This approach, genome-wide complex trait analysis (GCTA), which does not identify specific genes associated with disorder, has been shown to account for substantially more phenotypic variance than conventional GWA methods [29]. To date, there has been one GCTA study focused on reading ability, and, as with studies of other phenotypes, it found substantially more evidence for genotype–phenotype association than a conventional GWA study (variance accounted for by SNPs = 0.28), but less than was observed in a twin analysis based on the same sample (heritability = 0.73) [30]. While bearing in mind that the sample sizes available for studies of reading disability have been relatively small, and so may miss genuine but small effects, it would appear that here, as for other traits, some ‘missing heritability’ remains to be explained.

(a) Rare variants and copy number variants

As Gibson [31] noted, people have tended to contrast two models of inheritance. The ‘infinitesimal’ model, which is often assumed in dyslexia, is poetically described by Kirkpatrick et al. [32] as involving common variants that are �h Lilliputian in effect size, but together, are legion in number’ and add together to create risk. By contrast, in the ‘rare allele’ model, the effects of risk variants are large, but the individual variants each account for only a tiny proportion of cases. Of course, these are not mutually exclusive and both models may well apply to dyslexia. Both are difficult to verify in a GWA study, which will not detect very small effects of common variants, or large effects of very rare variants.

Great excitement was caused in 2006 when it was shown that copy number variations (CNVs) are remarkably common in the general population [33]. Although people mostly have two copies of each strand of DNA—one from each parent𠅎veryone has segments of the genome where chunks of DNA are deleted or duplicated𠅌NVs. Those affecting non-coding stretches of DNA may have little or no effect, but if the duplications or deletions include genes, then the CNV is likely to have functional consequences. CNVs could potentially account for individual differences, but on the other hand, the fact they are common in the general population means that it would be dangerous to assume that a particular CNV found in an individual necessarily plays a role in their disorder [34].

To date, few studies have assessed the role of CNVs in the aetiology of common neurodevelopmental disorders. The frequency of large CNVs is increased in cases of intellectual disability or autism, but in dyslexia the rate is closely similar to that found in unaffected controls [35]. This does not mean that CNVs are never implicated in dyslexia, but they do not seem to be a common cause.

(b) Gene–gene interaction

Two genetic variants that individually cause only mild risk for disorder may exert a much greater effect in combination—if, for instance, they are involved in the same neural pathway. To date, this idea of a 𠆍ouble hit’ on a neural circuit has been developed in the context of individuals with relatively large structural genetic changes and severe phenotypes [36] however, the same logic could apply to combinations of common variants leading to milder phenotypes. Two common variants that independently exert only a small effect might together be more detrimental in combination. Because MZ twins share the same DNA sequence, they will be identical for such gene–gene combinations, whereas in DZ twins, if genes are inherited separately, then the odds of the detrimental combination is lower than the odds of inheriting just one detrimental variant. Thus, in the presence of gene–gene interactions (epistasis), twin studies will overestimate heritability if an additive model is assumed.

(c) Gene𠄾nvironment interaction

Gene𠄾nvironment interaction refers to the situation where the impact of genetic variation depends on the environmental context [37]. One way of testing for such interaction is to consider whether different levels of a measured environmental variable are associated with different levels of heritability. This was done in a study using DeFries𠄿ulker analysis with the CLDRC sample by Friend et al. [19]. As well as reporting overall heritability, these authors subdivided twins according to parental educational level. Heritability of poor reading was higher for children with highly educated parents (, 95% confidence interval: 0.55𠄰.88) than for those with less well-educated parents (, 95% confidence interval: 0.32𠄰.66). The authors concluded that the effect of genes will be particularly evident in children who fail to learn to read despite good environmental support. This makes intuitive sense [21], but it is noteworthy that the finding was not replicated in another study that looked at the same question using slightly different methods [17].

The possibility that genetic effects may vary with the environment has implications for ‘missing heritability’. Most twin studies focus on twins who are growing up together. Consider the situation depicted in figure 3 : in panel (a), we have a trait affected by both genes and shared environment, with no interaction between the two. Panel (b) shows a gene × shared environment interaction (G × C). In a twin study, overall estimates of heritability will be similar for both these situations. Because the twin study compares similarity of MZ and DZ twins, it effectively controls for G × C effects, because C is by definition the same for the two members of the twin pair. However, a GWA study, which focuses on the regression of phenotype on genotype, may have weaker power to detect association in the gene × environment interaction case, because much of the variability in the phenotype is caused by environmental variation.

Illustration of (a) additive and (b) interactive gene𠄾nvironment effects at a single locus. The genotype is aa, aA or AA, corresponding to 0, 1 or 2 copies of the major allele.


Methods

Sample

Twins were recruited from the Norwegian Twin Registry (NTR). The registry comprises several cohorts of twins 75,76 , and the current study drew a random sample from the cohort born 1945–1960. In 2010, questionnaires were sent to a total of 2,136 twins. After reminders, 1,516 twins responded, yielding a response rate of 71%. Of the participants, 1,272 individuals were pair responders, and 244 were single responders. Zygosity has previously been determined based on questionnaire items shown to classify correctly 97–98% of the twins 77 . The cohort, as registered in the NTR, consists only of same-sex twins, and the study sample consisted of 290 monozygotic (MZ) male twins, 247 dizygotic (DZ) male twins, 456 MZ female twins and 523 DZ female twins. The age range of the sample was 50–65 years (mean = 57.11, sd = 4.5). The study was approved by the Regional Committee for Medical and Health Research Ethics of South-East Norway, and informed consent was obtained from all participants. All methods were performed in accordance with relevant guidelines and regulations.

Measures

Life satisfaction was measured with the Satisfaction With Life Scale (SWLS) developed by Ed Diener and colleagues 78,79 . The SWLS contains five items, such as “I am satisfied with my life”. Response options range from 1 = strongly disagree to 7 = strongly agree. The SWLS is widely used in wellbeing research, and has well-established psychometric properties 80 . Cronbach’s alpha in the current sample was 0.91.

Personality was measured by the NEO-PI-R 45,81 . The NEO-PI-R contains 240 items tapping the five general factors of personality, namely neuroticism, extraversion, openness to experience, agreeableness and conscientiousness. Within each of these factors, or domains, the NEO-PI-R measures six facets, or sub-factors (see results section for overview of all 30 facets). Each of these facets is measured by eight items. Response options range from 1 = strongly disagree to 5 = strongly agree. The NEO-PI-R is a well-established instrument, with sound psychometric properties 41 . In the current sample alphas for the five factors were 0.92 (neuroticism), 0.87 (extraversion), 0.88 (openness), 0.84 (agreeableness) and 0.87 (conscientiousness). Alphas for the facets ranged from 0.47 (C5 self-discipline) to 0.85 (N1 anxiety), with a mean of 0.67.

Analyses

Correlations were used to examine the bivariate associations between life satisfaction and personality traits and their facets. Next, we used regression analyses to (a) examine the unique contributions from the five broad personality traits, and to (b) identify the facets that are important for the association between personality and life satisfaction. Due to the non-independence of observations within twin pairs we used Generalized Estimating Equations (GEE) to account for the paired structure to obtain correct standard errors and significance levels. Further, to adjust for multiple testing we performed subsequent analyses with Bonferroni correction and the False Discovery Rate (FDR) approach 63 .

Based on the regression analyses we conducted two sets of multivariate biometric analyses to estimate the genetic and environmental contributions to the associations between personality and life satisfaction. The first set examined the relation between the major big five factors and life satisfaction. The second set of analyses focused on the specific facets that uniquely predicted life satisfaction. In order to focus on facets with substantive effects, we chose to retain only facets yielding regression betas >0.10, and with p < 0.01.

Standard Cholesky models 82,83 were used to estimate the genetic and environmental contributions to variance and covariance in personality and life satisfaction. All models were run with the OpenMx package in R 84 . The biometric models take advantage of the basic premise that MZ twins share 100% of their genes, whereas DZ twins share on average 50% of their segregating genes. Generally, the models allow for estimating three major sources of variance, including additive genetic factors (A), common environment (C) and non-shared environment (E). In addition, non-additive genetic effects (D) may be tested, but are only indicated if the observed MZ-correlations are more than twice the DZ-correlations. A Cholesky model is a structural equation model comprising the measured variables as observed phenotypes and the A, C and E components as latent factors (for illustration see Fig. 1). Models are constrained so that latent A-factors correlate perfectly among MZ-twins, and at 0.5 among DZ-twins. C-factors are correlated at unity for both zygosity groups, and E-factors are by definition uncorrelated. Different models are compared to determine the presence of the genetic and environmental effects (e.g., the fit of an ACE model is compared to an AE model) or sex-differences. In line with standard practice, we tested different types of sex-limitation models 85 . First, common sex-limitation models allow parameter estimates to vary across sex, involving differences in magnitude for genetic and environmental effects. Second, scalar sex-limitation allows the unstandardized variance-covariance matrices to vary across sex, but standardized parameters (e.g., heritabilities) are constrained to be equal. Finally, the sex-limitation models were compared with models having all parameters constrained to equal across sex. To assess models and identify the best fitting model we used the minus2LogLikelihood difference (Δ − 2LL) test, and the Akaike Information Criterion (AIC) 86 .

Data availability

The dataset analyzed during the current study may be requested from the Norwegian Twin Registry. Restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Information about data access is available here: https://www.fhi.no/en/studies/norwegian-twin-registry/


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When we take a closer look at how a human is created and how our genes are developed, we get a clearer understanding how different people truly are even when born into the same household with the same parents. Humans have different chromosomes, DNA, and genes. These genes according to David Myers believes, “You have 30,000 or so gene words” (2011), that is a lot of gene words for a person’s personality to develop from.

When we think about God, who created each one of us. “We are the clay, you are the potter we are all the work of your hand” (Isaiah 64:8). I am overwhelmed by the realization of how much God loves us, to create us all differently. We are an original, no two people have the same fingerprint or identical DNA. You and I are masterpieces, “…I am fearfully and wonderfully made: marvelous are your works…” (Psalm 139) Advantages and disadvantages in using twins to analyze genetic heritability.

Being created unique and differently, still raises the age-old question, how much does enviroment (nurture) influence personality? Parents still do influence a child’s attitude, value, manners, faith, and politics. Suppose you take identical twins, and the parents divorce and each parent takes one child and raises them differently. According to behavior geneticists the twins could still have the same likes, dislikes, mannerisms, laugh, sense of humar, and tastes in spouses. In conclusion, genetic heritability is still a mystery.

Myers, D.G. (2011). Exploring Psychology: Eighth edition in modules. New York, NY: Worth Publishers.

Re: Topic 4 DQ 1

The advantage is you have two genetically identical people that came from the same egg (monozygotic) and are virtually a carbon copy on one and another. Analyzing the set of twins can give you duplicate results and verifying the results will not be as difficult if they are the only set of children in the family. If they have other siblings then you have two sets of results that can be verified or contested with the other sibling(s). If the heritability results match then we can see we do inherit some of our personality genes from our parents. The disadvantage is they are both raised in the same environment and one can say the environment has an influence in shaping a portion of their personality. Another advantage is the nonadditive effect for monozygotic twins. The probability of sharing exact combination of genes is greater in monozygotic twins than it is with dizygotic twins. Nonadditive effects strengthen the genetic heritability in monozygotic twins but not in dizygotic twins. One serious ethical issue I can see is separating monozygotic or dizygotic twins at birth and separating them by distance and economical tiers to validate the genetic heritability. Advantages and disadvantages in using twins to analyze genetic heritability.

Topic 4 DQ 1

The different types of twins include identical and fraternal twins. Identical twins are made when a fertilized egg is split thus creating twins. Fraternal twins are made when two eggs are fertilized at the same time. Each set of twins are unique and different in their own ways. However, one major advantage to twins is their genetic makeup. Twin A and twin B always have the same DNA which can somewhat be looked at as variables. One twin could technically be the dependent variable and the other the dependent due. Advantages and disadvantages in using twins to analyze genetic heritability. For example, if trying to research if breast milk really is best for a baby a mother could breast feed baby A and formula feed baby B. Using the twins that have the same genetic makeup leave less margin for error in my opinion. To look at this from a personality psychological stand point let’s take the movie parent trap. Identical twin girls are separated and live two completely different life styles. If we were trying to see if the twins developed any personality traits from their other parent it would be easier because we would not have the actual parents personality shaping how they are. It would be considered an outside factor because they are not influenced every day by their superego. However, if they were to be raised in the same environment this would leave to the possibility of disadvantages of both their mother and father having an effect on their personalities Advantages and disadvantages in using twins to analyze genetic heritability. Although I believe it is unethical to purposely separate twins I do believe there can be positives to it and if done in a good way can be beneficial. For example, I have three sets of twins in my class one set of parents is very adamant about them being together at all times the other two could careless as long as it does not affect their behavior in a negative way. We separate twin O and twin J at meal times because we know if they are together they tend to throw food, kick their friends, and not eat. However, at nap time we have them together because they sleep better when near each other. In my opinion, if done in a manner that does not separate them fully it is best for both twins. Advantages and disadvantages in using twins to analyze genetic heritability


Behavioral Genetics of Aggression and Intermittent Explosive Disorder

Catherine Tuvblad , . Linda Booij , in Intermittent Explosive Disorder , 2019

Metaanalyses and Systematic Reviews Summarizing Studies Examining the Influence of Genetic and Environmental Factors on Aggressive Behavior

There have been a few metaanalyses and systematic reviews of twin and adoption studies of aggressive behavior and the wider construct of antisocial behavior. Antisocial behavior is broader in scope than aggression as it also includes nonaggressive behaviors, e.g., littering, vandalism, and lying which are considered antisocial behaviors, which are not necessarily aggressive. These studies are summarized in Table 1 . Together these studies show that about half or more of the variance in aggressive behavior is explained by heritable influences ( Burt, 2009 Ferguson, 2010 Mason & Frick, 1994 Miles & Carey, 1997 Rhee & Waldman, 2002 ). Two metaanalyses have examined nonadditive genetic effects. Only one found significant nonadditive genetic effects for broader concept of antisocial behavior, but not for aggressive behavior ( Burt, 2009 Rhee & Waldman, 2002 ) It is important to note that genetic influences are consistently found across these reviews, while shared environmental influences are relatively small or nonexistent. Family similarity in aggressive behavior therefore seems to primarily be the result of shared genes, not environment.

Table 1 . Summary of Metaanalysis and Systematic Reviews: Aggressive Behavior

Author, YearMeasureEstimates
(Mason &amp Frick, 1994)
12 twin studies (3795 twin pairs)
3 adoption studies (338 adoptees)
Antisocial behaviora 2 48%
(Miles &amp Carey, 1997)
20 twin studies (1757 twins)
4 adoption studies 3157 adoptees)
Aggressive behaviora 2 50%
(Rhee &amp Waldman, 2002)
41 twin studies
10 adoption studies
Antisocial behaviora 2 32% d 2 9% c 2 16% e 2 43%
(Rhee &amp Waldman, 2002)
41 twin studies
10 adoption studies
Aggressive behaviora 2 44% c 2 6% e 2 50%
( Burt, 2009 )
15 twin studies
4 adoption studies
Aggressive behaviora 2 65% c 2 5% e 2 30%
( Ferguson, 2010 )
38 twin studies
Antisocial behaviora 2 56% c 2 11% e 2 31%
( Tuvblad &amp Baker, 2011 )
33 twin studies
4 adoption studies
Aggressive behaviora 2 50% c 2 0% e 2 50%

Note. a 2 , genetic effects c 2 , shared environmental effects d 2 , dominant effects e 2 , nonshared environmental effects.