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Many different things can be seen in any landscape, depending on your focal point.
Image by Nicooo76 via Pixabay. |
When
photographing a landscape, different photographers choose different
perspectives. Some capture a wide-angle view, while others focus on particular
details.
It’s
no different for researchers who use genome-wide association studies (GWAS) to
investigate the genetic landscape of type 2 diabetes (T2D). A common perspective
is to study the wide range of variants that are significantly associated with
the presence of T2D in patients. But it can also be very informative to
concentrate on individual traits related to the physiology of T2D. In a
new paper in Diabetes, co-first authors Geoffrey
Walford, Stefan Gustafsson, Denis Rybin, and fellow members of the
Meta-Analyses of Glucose and Insulin-related traits Consortium (
MAGIC) took
this focused perspective to discover associations of genetic variants with
insulin sensitivity.
Along
with reduced insulin levels, the loss of insulin sensitivity (often termed
insulin resistance) is a major hallmark of T2D. When muscle, liver, and fat
cells become less able to respond to insulin, blood glucose levels rise.
Since this can contribute to development of T2D and exacerbate its symptoms,
knowing which genetic variants are associated with sensitivity to insulin could
be informative for understanding pathways that contribute to T2D risk.
But
insulin sensitivity is difficult to measure. Earlier GWAS have used simple
estimates of insulin sensitivity, such as fasting levels of insulin, and have
discovered a handful of genetic variants that influence insulin sensitivity. The
“gold standard” test, the euglycemic clamp, involves giving patients continuous
infusions of insulin and glucose and monitoring their blood glucose every few
minutes. It’s expensive and time-consuming—not a test that is practical to
perform on the tens of thousands of subjects that are commonly used in GWAS.
The
authors wondered whether they could instead use an index that combines several
measurements, each relatively easy to make. It’s an index with a long name: the
modified Stumvoll Insulin Sensitivity Index (ISI). Developed by Stumvoll and
colleagues in 2001, this index can be derived in a variety of ways. The authors
chose the ISI requiring just three measurements: fasting insulin levels;
glucose levels two hours after a glucose load; and insulin levels two hours
after a glucose load. This ISI is as good as or better than other estimates of
insulin sensitivity and correlates well with the euglycemic clamp.
So
the researchers looked for variants associated with the Stumvoll ISI in nearly
17,000 participants in the discovery phase of the work. They added another
13,300 in the replication phase, adding up to about 30,000 in the combined
meta-analysis. Since obesity, measured by body mass index (BMI), can affect
insulin sensitivity, the authors added BMI to some of their statistical models.
First,
the authors found associations between the ISI and other variants already known
to affect simple measures of insulin sensitivity. This provided reassurance
that the ISI was properly detecting genetic influences on insulin sensitivity. After
discovery, replication, and meta-analysis, two novel genetic variants were
associated with ISI at genome-wide significance (
P-value < 5.0
×10
-8)
in a model that tested the effect of the variant, age, sex, and the interaction
between the variant and BMI: variant
rs12454712, near the gene
BCL2, and variant
rs10506418, near
the gene
FAM19A2.
How might these variants affect insulin sensitivity?
There’s a lot more work to be done before that question can be answered. Additional
studies will need to clarify whether these variants, which are near BCL2 and FAM19A2, affect these or other genes, and then how these variants
actually cause changes in insulin sensitivity.
There are some clues already in
the published literature. The variant rs12454712
near BCL2 has previously been
found to be associated with T2D, supporting the hypothesis that this region of
the genome contributes to T2D risk
through reducing insulin sensitivity. And the gene itself (BCL2) has already been implicated in glycemic metabolism:
inhibiting bcl2 improves glucose
tolerance in a mouse model, while a drug that inhibits the protein product of
the gene (BCL2) increases blood glucose levels in certain chronic lymphocytic
leukemia patients. So there’s even more reason to suspect that the rs12454712 variant might affect insulin
sensitivity via BCL2.
There is as yet no evidence linking the protein FAM19A2
function to glucose metabolism, so the jury is out on whether the variant rs10506418 affects FAM19A2 or some other nearby gene.
By focusing on a detail of the T2D-related genetic landscape,
this study has teased out two variants that may give us clues about the
physiology of insulin sensitivity and the development of T2D. And that’s a
valuable addition to our overall picture of T2D genetics!
