Dr. DeGennaro: Mendelian conditions
are rare and often quite severe.
But complex traits like high cholesterol, type 2 diabetes,
rheumatoid arthritis, depression,
coronary heart disease, and obesity
are more common in the population.
Many families seem to have a high incidence of one
of these traits, indicating that they have one or more risk
variants for that condition.
Each complex trait has a different amount
of heritability, which tells us how much of the variation
observed in that trait can be accounted for by genetics.
Genome-wide association studies can provide further insight
into the genetic basis of a disease
by allowing identification of disease-associated variants
and calculation of an odds ratio, which
provides an estimate of how much a variant increases
or decreases risk of a condition.
However, most traits still have a substantial amount
of missing heritability, meaning that we don't yet
understand all of the genetic risk factors.
In addition, while heritability and odds ratios
are predictive at the population level,
many questions remain about how to use this information
to predict risk in an individual.
Predicting the risks associated with genetic diseases
requires an understanding of conditional risk.
Every trait has a general population risk.
For example, nearly 10% of all Americans have type 2 diabetes.
However, the risk that an individual
will develop diabetes within the next decade
may be considerably different than the general population
risk based on factors like age, weight, ethnicity,
physical activity, diet, and family history.
To determine the risk of an individual based on one or more
of these factors, you can look at the risk
of a subset of the population with that same characteristic
or set of characteristics and adjust the risk prediction
of the individual accordingly.
Let's look at an example of how this works in more detail.
Let's look at the risk of coronary heart disease, or CHD,
which is the buildup of plaque in the arteries of the heart
and which substantially increases risk of heart attack
and stroke.
CHD is a complex trait determined by genetics
and the environment.
The risk of an American adult developing complications
of CHD, such as heart attack or stroke, is about 6%
over a 10-year period.
However, if we look at these two individuals, Adriana
and Joseph, you might imagine that their risk
is quite different.
How can we use information about both their genetics
and environment to give them a more accurate picture
of their risk?
To determine the risk of having a CHD-related complication
in the next 10 years, we can take their sex and age
into account.
Adriana is 31 and female, and this lowers her risk compared
to the general population.
Taking only his age and sex into account,
Joseph, who is 47 and male, also has a slight decrease
in his risk.
Now let's consider how traditional risk factors might
impact their individual risks.
Cholesterol levels, particularly high levels
of LDL, or bad cholesterol, and low levels of HDL,
or good cholesterol, increase their risk.
Adding on high blood pressure, smoking,
and the onset of diabetes increases
risk further, though you'll notice
that there is a differential effect on each
of their risks based on their age and sex.
Now let's compare an estimate of risk based on traditional risk
factors to an estimate based on genetic variants associated
with CHD.
There are, of course, Mendelian variants
that can lead to drastically increased risk.
For example, certain rare variants
that impact cholesterol levels lead to early onset
CHD, and increased risk of fatal heart attack, 50
to 100-fold if left untreated.
However, most cases of increased genetic risk
are due to a number of small effect variants.
We don't know all of the variants associated with CHD,
but a risk score can be estimated
by combining the effects of the variants that are currently
known.
In extreme cases, where an individual
has a version of each of these variants that increases risk,
the maximum risk is estimated to be about four
times the baseline risk.
This might seem like a large number,
especially when presented in percent form
as 400% of baseline risk, or a 300% increase
over baseline risk.
But it's important to remember that in a healthy individual,
the baseline risk is relatively low, and the increase in risk
is less than the increase that can be attributed
to traditional risk factors.
In addition, few people carry all of the risk alleles.
More commonly, these variants might
increase risk twofold or less.
Twofold might still sound like a large increase,
but looking at the absolute rather than the relative risk
can provide a more intuitive understanding
of the odds of developing a particular condition.
If you consider the baseline risk of individuals
of similar age, sex, and ethnicity,
which is 4%, or four out of every 100 people,
and convert this twofold increase in relative risk
to an absolute risk, you can see that in the subset
of these individuals who have a similar genetic makeup,
8%, or eight out of every 100, will experience complications
from CHD over the course of 10 years,
while the other 92 will not.
While this is an increase from the baseline risk,
the odds are still low for any individual.
It's also important to keep the relative magnitude of these
effects in mind, because although
an individual's genetics cannot be changed,
lifestyle and medical intervention can often
alleviate risk from traditional risk factors,
which can play a much larger role in determining risk.
Thinking about the probabilities in this way
will give you a more accurate picture of risk.
At present, many questions remain about the variants
that underlie complex diseases.
What can account for the missing heritability?
How can we combine the risks of different variants
in a way that's informative?
What's the interplay between the genetic and environmental
risks?
As we continue to learn more about the underlying genetic
and environmental causes of complex diseases,
we'll be able to use this information
to make better predictions about the risk of an individual.
Ultimately, risk is predictive on a population level,
but refining our predictions by categorizing individuals
into more and more specific subpopulations,
by physiological, genetic, and environmental characteristics
could allow for personalized risk
assessment and more targeted treatment of complex diseases.