ISIS Report 25/01/12
Mystery of Missing Heritability Solved?
Genome-wide scans for genes that determine susceptibility
to common diseases have yielded little because most of those genes do not exist;
disease genomics is a science fantasy that wastes time and money while the health
of the nation deteriorates Dr. Mae-Wan
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Where are all the promised genes?
When the human genome sequence was announced in 2000,
President Clinton said it would “revolutionise the diagnosis, prevention and
treatment of most, if not all human diseases.” Ten years on, and Fortune
magazine called it: “The great DNA letdown”. A poll by science journal Nature
returned the verdict: “the hoped for revolution against human disease has not
That is as some of us had
predicted in 2000 ( Human
Genome -The Biggest Sellout in Human History, ISIS TWN report) and before
 Genetic Engineering Dream or
Nightmare, ISIS publication).
The human genome project has generated
reams and reams of data since its inception, but there is little progress even in
the apparently simple task of finding the genes responsible for susceptibility
to common diseases (see  Ten years of the
Human Genome, SiS 48).
Top geneticists now admit that human
genetics has been haunted by the mystery of “missing heritability” of common
traits. Genome-wide association studies (GWAS, see Box 1) – the current gold
standard for the most exhaustive gene hunt that can be performed - have
identified ~2 000 genetic variants associated with 165 common diseases and
traits; but these variants appear to explain only a tiny fraction of the
heritability in most cases [4, 5].
Genome wide association studies
Genome wide association
studies (GWAS) involves rapidly scanning markers across the complete genomes of
many people to find associations of genetic variants to particular diseases or
traits. Typically, thousands or tens of thousands of individuals are scanned,
simultaneously for up to 550 000 single nucleotide polymorphisms (SNPs) –
common differences in single nucleotides at specific sites across the human
genome with frequencies > 5 % - using DNA microarrays (chips).
Heritability is technically the
proportion of the variability of the trait in a population due to genes.
Variability is measured statistically as variance, the sum of the
squared individual deviation from the population mean. Heritability is commonly
referred to as the ‘genetic component’ of the variance as opposed to the
proportion due to the environment, the ‘environmental component’. Note that
heritability refers to the variation, and not to the trait itself.
Heritability changes according to the environment. It is not uncommon for the
heritability of traits such as milk yield or height of a plant from the same
genetic strain to change substantially from one year to the next. However,
there is a tendency for some scientists as well as the popular media to
mistakenly assume that any trait with a large heritability means it is predominantly
genetically determined, which is definitely not the case.
No genes for common diseases?
Nevertheless, the hunt for genes determining susceptibility
to common diseases has continued for decades, spurred on over the past 5 years
by the availability of DNA chips that allow genome wide scans for more than 500
000 SNPs simultaneously.
Eric Lander and his team at Board
Institute MIT & Harvard, Harvard, Massachusetts in the United States are
among those suggesting that much of the missing heritability never existed in
the first place . They base their argument on biometrical genetics, a
mathematical discipline that deals with continuously varying traits, such as
crop yields, height, body mass, IQ scores, or disease states that fall on a
continuum, as for example, blood glucose, blood pressure, or some measure of
I should point out
that one arrives at precisely the same conclusion given the pervasive epigenetic
influences of the environment on development [1-3], which have been abundantly confirmed
and extended since the human genome was sequenced (see  Death of the Central Dogma and other
articles in the series, SiS 24;  Epigenetic Inheritance
- What Genes Remember and other articles in the series, SiS 41;  Nurturing Nature, ISIS
This convergence of
molecular and biometrical genetic analyses is the most conclusive refutation of
the reductionist, genetic determinist paradigm of linear causation from
genes to traits that
had made the Human Genome Project seem such a compelling undertaking; only to
thoroughly discredit it as a result (see  Living with the Fluid Genome,
now know that much
of the variation may come from individual experiences of the environment;
furthermore, those experiences can mark and change genes, influencing the
development of the individual and in many case, the individual’s offspring.
Genes and environment operate in enormously complex feed-forward and feed-back networks
that straddle generations. This fundamentally circular causation between
genes and environment means that genetic and environmental contributions are
inseparable, and any attempt at assigning linear effects to single genes is
doomed to failure.
We shall see how
genetic determinism is finally unravelling within the heart of the genetics
establishment, beginning with the findings of Lander’s team with regard to
common disease traits and continuing with the intelligence and IQ debate ( No Genes
for Intelligence in the Human Genome, SiS 53).
The genetic component has been greatly over-estimated
Specifically, Lander and colleagues show that the missing
heritability arises from an overestimate of total heritability (the genetic
component of the variation in the trait) which implicitly assumes that no gene
interactions (or gene environment interactions) exist, an assumption clearly
unjustified. Including gene interactions gives a much smaller total
heritability. In short , “missing heritability need not directly correspond
to missing variants, because current estimates of total heritability may be
significantly inflated by genetic interactions.”
Actually, gene interactions do
belong to the ‘genetic component’ of heritability. In biometrical genetics,
‘broad sense heritability’ H2 includes additive genetic
effects as well as effects due to gene interactions and any non-additive,
nonlinear effects due to genes. But broad sense heritability is very difficult
to determine. In practice, only the ‘narrow sense heritability h2
(the additive, linear effects due to genes) can be estimated. Narrow sense
heritability applies strictly to ‘polygenic’ traits due to many genes each with
a small additive effect, and is implicitly assumed to apply to all polygenic
traits, beginning with the pioneers of biometrical genetics (see later).
Geneticists therefore define the proportion
of heritability of a trait explained, pexplained,
as a ratio of phenotypic variance explained by the additive effects of known genetic
variants, h2known, to the phenotypic variance that
can be attributed to the additive effects of all variants, including those not
yet discovered, h2all (Equation 1).
pexplained = h2known/
The nominator h2known can be
calculated directly from the measured effects of the variants, but the
denominator h2all must be inferred indirectly from
The prevailing view among geneticists is that
the missing heritability is due to additional variants yet to be discovered,
either common alleles with moderate-to-small effects or rare alleles (frequency
< 1 %) with large effects [4, 5].
The other possibility, favoured by Lander’s
team, is that the missing heritability does not actually exist, and is an
artefact arising from the total heritability h2all being
over-estimated in the first place, by ignoring the impacts of gene
For example, Crohn’s disease (inflammatory
disease of the bowel) has so far 71 risk associated loci identified. Under the
usual assumption of additive effects, these loci explain 21.5 % of the
estimated total heritability. Genetic interactions could account for the
remaining nearly 80 % missing heritability. Why then, has genetic interaction never
been detected in population analyses? Lander and colleagues point out that to
detect gene interactions for Crohn’s disease may require sample sizes in the
range of 500 000 individuals, which is rarely attained.
interaction, or epitasis, is well-known and pervasive. It is epitomised
by the findings of project ENCODE (Encyclopedia of DNA elements) organised by
the US National Human Genome Research Institute, in which a consortium of 35
research groups went through 1 % of the human genome with a fine-tooth comb to
find out exactly how genes work . They discovered that  “genes appear
to operate in a complex network, and interact and overlap with one another and
with other components in ways not fully understood.” Essentially, the ‘gene’ as
a well-defined, separate unit of structure or function no longer applies.
Instead, genes exist in bits strewn across the genome, structurally and functionally
intertwined with other genes.
How phantom heritability arises
Lander and colleagues point out  that in calculating the
explained heritability (Eq. 1), the numerator h2known is
estimated based on the effects of the individual genetic variants. The problem
comes in estimating the denominator h2all. Because
not all the variants are known, their contribution must be inferred based on
phenotypic correlations in a population. This gives an apparent heritability,
h2pop. And the missing heritability is then
estimated by assuming that h2all = h2pop.
However, there is no guarantee that h2all
= h2pop, unless the trait is strictly additive,
and neither gene-gene interaction nor gene-environment interaction exists. For
traits with gene interaction, which would realistically apply to practically
all common traits and diseases, h2pop may
significantly exceed h2all. In that case, even
when all the variants for the trait have been identified, the missing
will not diminish to zero, instead, it converges to 1 – (h2all/
h2pop), which Lander and colleagues refer to as’phantom
Simple model shows how genetic interactions create
To show how genetic interactions create phantom
heritability, Lander and colleagues introduced a simple model in which a trait
depends on input from more than one processes, Phantom heritability – that
which remains missing even when all genetic variants have been identified –
grows quickly with the number of inputs, approaching 100 % of the total
variation. For Crohn’s disease, for example, just 3 inputs are sufficient to
account for 80 % of the phantom heritability.
interactions can produce additional phantom heritability, (as indeed other
unaccounted sources such as epigenetic effects).
Twin studies deeply flawed
The typical framework for analysing human traits depends on
a systematic denial of epistasis, assuming that genes act in a purely additive
way, each gene contributing a small amount to the trait, which is summed up
depending on how many of those genes are present.
One measure of apparent heritability h2pop
(ACE) assumes additive genetic variance, as well as common environmental and
unique environment variance components, and a usual definition for apparent
heritability is h2pop (ACE) = 2(rMZ
– rDZ), where rMZ and rDZ
are the phenotypic (measured trait) correlations between monozygotic twins (sharing
100 % of their genes) and dizygotic twins (sharing 50 % of their genes); while
the environment they share is assumed to be common, including the maternal
h2pop (ACE) = h2all
+ W (2)
where W represents the sum of variances due to all possible
higher order additive and non-additive interactions between genes. The crucial
point is that if there are any gene interactions, then W > 0 , so h2pop
(ACE) overestimates h2all.
Unfortunately, there has been no
way to estimate W from population data. In most human studies, the solution is
to assume there is no gene interactions, in which case W = 0. Thus, twin studies
systematically overestimate the genetic contribution to disease and other
traits, most notably, and controversially IQ (see ).
Additive assumption fundamental to biometrical genetics
Lander and colleagues are not the first to expose the
fundamentally flawed assumptions of classical biometrical genetics. Helen
Wallace of UK-based GeneWatch has published a similar critique 5 years earlier
: gene-gene and gene-environment interactions could reduce the calculated
heritability considerably below that predicted by the standard twin-studies
method based on pioneering British geneticist Ronald Fisher’s 1918 assumption
that genes act additively.
The major implication is that the hunt for susceptibility
genes is practically useless. Indeed, Lander and colleagues  and others  see
the primary purpose of medical genetics as the identification of underlying
pathways and processes analogous to the hunt for mutants in model organisms;
and not in “explaining heritability” or “predicting personalized patient risk.”
But there are much wider implications on
health policies. Governments and companies have been keen to set up whole
genome biobanks ever since the human genome sequence was announced (see  Human DNA 'BioBank'
Worthless and other articles in the series, SiS 13/14). The UK
government is now pushing to let companies gain access to public health records
to drive discovery in disease genomics . But if the genetic contribution to
disease is largely a phantom, what is the point of integrating whole genome
sequences with electronic medical records as most of this information is likely
to be clinically useless for most people [14, 16]?
There are vested interests that want to keep
the genetic myth alive. As Wallace points out, the evidence she presented in
2006, and Lander and colleagues presented in 2011 has had no impact on gene
testing companies such as Illumina and 23andMe, which continue to claim that
everyone will have their genome mapped or sequenced in future, at birth or as a
routine part of healthcare. The Director of the National Institutes of Health
Francis Collins has echoed these claims in his populist book The Language of
Life . Wallace is convinced, as I am, that  “whole
genome sequencing of everyone, leading to the “prediction and prevention” of
disease, is a science fantasy and a massive waste of money.”
A fraction of the resources divested into
much needed primary health care and disease
prevention through nutritional and other environmental/social interventions
will do infinitely more to improve the health (as well as brain power) of the
There are 2 comments on this article so far. Add your comment
|Todd Millions Comment left 29th January 2012 09:09:13|
An old item,but one seldom broached on this-Do these studies consider that dad may not in fact be father?Even were clan Millions not Yorkies,the amusing fact is,the usual overall factor applied too this is one in seven-aren't.So family studies not based on maternal lines could be quite off.
Some what like the lifespan studies that show married men live longer.The flaw in these is the men are ask how old they are.Birthdate derived data,tend too show same span.But for some reason too married men,it tends too SEEM- MUCH longer.
|MRS Carol Jewell Comment left 19th February 2012 14:02:02|
Simplyfying how we detect damage (ill health) to the body would go a long way in preventing chronic illnessess. Today doctors, through their own ignorance, have taken to "blame the patient" culture like a pack of wolves. But we know that in the main today, doctors are not doctors, they are greedy, selfish and ruthless business men. WE hear much too much about synthetic science and far too little about natural science. Natural science of course is about the importance of cellular activity and how to put it right, when it has gone wrong . But then if we did that (which is entirely how it should be) we would surely cure the patient...............but rob the greedy pimps masquerading as doctors/ physicians/ consultants/ etc etc etc out of their lucrative earnings. How do these people sleep at night?