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Compare and contrast the information that has been obtained about quantitative traits from twin studies
and GWAS
Genome Wide Association Studies (GWAS) and twin studies provide researchers with vital tools to study
quantitative traits. Quantitative traits are continuously measured complex traits such as height or weight,
which are more difficult to account for than other traits, because these traits have a combined effect of
many genetic quantities. These traits include several complex diseases such as schizophrenia, diabetes,
coronary artery disease, hypertension and other traits including intelligence, human longevity and
depression, which are controlled by multiple genes with various effects. Some of the multivariate traits
described above are associated with parameters like gender or age. In addition, genetic predisposition may
play a critical role in the behaviour and personality of an individual. Twin studies are a method of genetic
study that attempt to comparatively review the relative significance of genetic (i.e. heritable) influences and
environmental influences upon presented phenotypes. The classical twin study compares trait resemblance
between monozygotic twins (share almost identical genomes) with dizygotic twins (share half of genetic
makeup). While twin studies estimate the degree heritability for a particular complex trait using the ACE
model—joins aspects of additive genetics (A), common environment (C) and the unique environment (E)—
GWAS looks for a given trait from individuals of a study cohort and attempts to identify whether a single
nucleotide polymorphism (SNP) is associated with the trait. Each study is powerful in its own domain, but
there are many differences between them that are important to note, to fully understand what is learnt
from them.
Geneticists have long attempted to learn more about trait heritability. Whether or not a trait, and often
more specifically whether a disease is heritable and therefore due greater to a genetic component rather
than environmental factors is an important question in the field of genetic epidemiology. By estimating the
heritability of genetic variants from monozygotic and dizygotic twins, intrinsically regulating epigenetic
mechanisms can be further mapped; also enhancing knowledge about associations between genetic variants
and disease. Assessing the proportion of genetic inheritance and the environmental influences on such a
disease helps to explain the onset and distribution of the disease in the general population, and develop
proper agents to control the spread of the disease. Sophisticated gene expression, gene regulation and
epigenetic regulation limits information learned from GWAS of complex traits as it does not provide a true
measure of heritability, leading to some papers reporting complex traits are ‘missing heritability’, when in
reality heritability has not been assessed properly. The introduction of small effect alleles and rare variants
leaves unanswered questions that neither twin studies nor GWAS seem to account for.
Acquiring twins with relatively identical genetic information and coming from a uniquely shared
environment helps the interpretation of data and enhances what is learned from these studies. In classical
twin studies looking at intelligence, it is found that heritability of intelligence due to genetic factors increases
as the individual gets older, while the shared environmental factors decrease and are greatest at an early
age. This suggests that intelligence of the twins is dependent to interaction between themselves during prepubescent development. As the twins grow older, becoming more independent of each other, shared
environmental factors decrease and unique environmental factors i.e. unique life decisions tend to increase.
Smoking has a large proportion of heritability explained by shared environmental factors as one twin’s
decisions will influence the other one’s life choices. From twin studies, it is shown how manifestation of
some complex traits goes beyond the genetic makeup of the individual. By knowing that one individuals
decisions can be influenced by his twin, choosing twins [for a study] that are older from the start takes into
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effect that they are able to think for themselves, making the information learned more applicable to the
external population. Doing so includes unique environmental factors from undetermined and random life
events that can place certain pressure on the person’s genetic makeup. It is this genetic shielding that
protects individuals from the environmental factors that can give rise to a trait, such as a disease causing
gene. On the contrary, data collected from GWAS decays in the interpretation step as it is difficult to define
if a complex trait is directly expressed due to genetic predisposition or environmental factors as several
studies do not recruit twins are test subjects.
Twin studies have and continue to be a better model for studying the genetic basis of human behaviour and
interaction. Purely as it is easier to make and correlate such observations than when scanning the genome
for SNPs under GWAS. Consequently they have highlighted fundamental aspects of human nature that are
heritable: extroversion/introversion, openness, agreeableness, and neuroticism. Furthermore, some aspects
of our personality are surprisingly less influenced by the environment but rather more fixed by our genetics.
In the Minnesota twin study, a pair of twins separated at birth and raised under different living conditions
(economical and social), showed remarkable similarity in behaviour. Dubbed the “giggle twins” – these
women enjoyed pranks, would laugh easily, and had a sense of humour that formed a key aspect of who
they were. Work by Dr. Helen Fisher suggests that our personalities are influenced biologically to a great
extent by the ratio of receptor genes we inherit primarily for testosterone, oestrogen, dopamine, and
serotonin. Those with a higher level of dopamine receptors and hence higher exposure, labelled “explorers”
are far more willing to take risks, are curious and explore be it sexually or via adventurous sport. These
individuals are also more susceptible to drug addiction due to higher dopamine activity. Such ground
breaking studies and their thought provoking knowledge is made possible by initial revelations found under
twin studies – not GWAS.
However, for certain characteristics GWAS and twin studies are in agreement, and prove a useful source of
checking the robustness of a conclusion gained from one approach via comparison with the other. In the
complex case of schizophrenia, SNPs associated with disease as well as a twin studies categorising illness
based on symptoms suggest many subtypes of the mental disorder exist. Such results enable specific
treatment options to be considered when treating each subtype in the future; but what GWAS has
succeeded at more is in providing candidate genes for traits, as associated SNPs identified tend to be near
genes actually involved and less often within the genes responsible. Scanning around SNPs, genes for traits
such as longevity can be located, and knocked out in model organisms to confirm their predicted role. For
instance, one candidate gene implicated in longevity is MAD1; it is part of the mitotic-spindle checkpoint
ensuring that microtubules are correctly attached to the chromosomes before proceeding onto anaphase. It
is a feasible candidate gene, regulating a vital function, which when prone to error is likely to cause
problems. This candidate gene was found by GWAS – not twin studies.
Twin studies were the first to show differences in traits – be it longevity or postnatal depression – depending
on sex. Analysing the percentage of variance of cognitive/personality traits and cardiovascular risk factors,
using ACE, against men and women shows close similarity of inheritance of the traits between sexes.
However, carrying out sex differentiated analysis on significant SNPs, by GWAS, has found different
susceptibility to coronary artery disease and Crohn’s disease between males and females. Another
advantage of information from twin studies over GWAS is the ability of twin studies to look at time and age
in correspondence to gene expression of traits, and furthermore heritability. Time and age have a significant
impact upon gene expression; an example of this is the longitudinal genetic study of verbal and nonverbal IQ
from early childhood to young adulthood, where Dutch twin pairs were measured in IQ at ages 5, 6, 10, 12
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and 18 years old. Heritability was shown to increase with age. This shows that twin studies can be used to
investigate the effect of time and age has on gene expression based on heritability differences due to change
of age. GWAS however, is only beginning to take time and age into account. New methods mean gene
expression can be integrated as provided by Illumina HumanHT-12 Gene Expression BeadChip, allowing
whole-genome gene expression within a trait based GWAS. It can be used to screen for functional category
enrichment within genes and to show any hidden variability in a supposedly uniform phenotype by GWAS.
This means despite initial advantages provided by twin studies regarding role of age and gender, GWAS is
catching up.
What we have and will learn, from twin studies and GWAS is that both are susceptible to the advancing
technology and research. In the case of twin studies, current work on discordant identical twins –
genetically identical, but displaying significant differences in certain traits – is key to understanding
epigenetic influence. Take IQ – one study found low methylation of promoter regions and hence high gene
expression of genes involved ion channels in the twin who performed worse in IQ tests; thus, it could be
corresponded with this discordant trait. Though not necessarily a causal relationship, it provides a clue as to
identifying and better understanding discordant traits and disease patterns. Hence, this move away from
classical to non-classical twin studies is an important step in understanding why one twin may develop
cancer whilst the other does not, even when living under same lifestyle. For GWAS, work published by
ENCODE of “functional elements” (80 percent) in the human genome surprisingly correlate with SNPs
associated with disease or traits – most of these are genetic switches encoding non-coding RNA, which up or
down-regulate several genes in relation to gene expression in the whole genome. Thus, it may be the
switches that are vital and not the genes with regard to differences in quantitative traits. Whole
chromosomal regions, often on separate chromosomes were also found to interact and share regulatory
regions, such as enhancers. Therefore, this new research highlights the complexity of the human genome, as
well as providing enriched data for future studies and improved incarnations of GWAS.
To conclude, both GWAS and twin studies provide us with important data concerning complex traits. When
researchers are dealing with complex traits that are associated with the environment, twin studies are
proven to be more useful. Since environmental factors can be important in the expression of particular
multivariate traits, twin studies have the advantage to monitor individuals through a time of shared
environment and follow onto adulthood, which presents the unique environment. Therefore, we can learn
about how a complex trait develops and estimate its heritability by looking at a time scale of multiple
environmental insults. However, what we learn from twin studies is limited when applying it to the general
population, because twins are a selected group and do not represent the whole population. On the other
hand, GWAS helps to provide a physical area of the genome that is responsible for the specific complex trait,
and by exploiting linkage disequilibrium and association analysis, information on how it is passed on to
subsequent generations can be learned. Avoiding ascertainment bias for twin studies and ensuring the
collection of enough data for statistical analysis in GWAS, both study methods prove to be quite successful.
It is the growing fusion of twin studies and GWAS that strengthens our understanding on how rare variants
that are common to infectious diseases arise from genetic footprints, from ancestor populations, by
scanning associations within the genome, and assessing environmental pressures; thus giving out an
estimate on how much of the phenotypic variance is due to additive genetic effects and random
environmental factors.