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So my name is Ruth Loos,
I'm a professor
of Preventive Medicine
at the Icahn School of Medicine
at Mount Sinai in New York,
and my lecture is on the Genetic
Epidemiology of Obesity.
And I have structured
my lecture in a way
that we start in
the early years in 1960s,
and go in chronological way
from the heritability
to more recent insights
in biology using genetics.
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The first period that
we cover is the period
from the 1960s to the 1990s,
and that's when
genetic epidemiology
became a more
formal discipline.
At that time,
epidemiologists did not have
wide access
to genetic information,
so they relied on relatedness
to infer influences of genes.
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From the 1960s to the 1990s,
the methods that were applied
to gain insights in the
genetic contribution to obesity
were descriptive epidemiology,
familial aggregation,
heritability studies,
and segregation analyses.
And I'm going to give you
an example for each of these.
So first, descriptive
epidemiology,
there, genetic epidemiologists
relied on relatedness
within ethnic
or within racial groups
and it's assumed that
some populations are more
at risk to develop disease
such as obesity
than other populations.
And a nice example here
is given with this picture
from the Pima Indians.
Descriptive epidemiology
is basically searching for
patterns in variation
in disease risks within
racially related individuals
or ethnically
related individuals
and comparing them
with other ethnicities or races.
It should be emphasized
that this type of studies
only provide clues
to whether genes
or environment is involved.
It does not really quantify
how much genes contribute.
So it's mainly
hypothesis generating.
I'm going to tell you
a little bit more about
these Pima Indians
which is a classical example
in the genetic
epidemiology of obesity.
