Gene Mutations Linked to Statin Resistance
Scientists at Duke University Medical Center have identified
genetic mutations that may help explain why some people don't
respond very well to statins, drugs taken by millions of
Americans to fight high cholesterol and prevent coronary artery
The findings, published in the Dec. 17 issue of
Circulation: Cardiovascular Genetics, suggest that
some patients may fail to see lower LDL cholesterol levels from
taking the drugs -- no matter what the dose -- because of their
Statins are generally effective in lowering low-density
lipoprotein cholesterol, or LDL (the so-called "bad"
cholesterol) -- even slashing LDL levels in half, in some
cases. But in about 20 percent of patients, statins fail
to bring LDL into target range, a phenomenon known as "statin
Geoffrey Ginsburg, MD, PhD, director of the Center for Genomic
Medicine in Duke's Institute for Genome Science & Policy,
says race, age and smoking status may exert modest influence on
statin response, but he believes genetic variation may play a
more powerful role.
To find out, Duke researchers randomly assigned 509 patients
with high cholesterol to receive the lowest dose of one of
three statins for eight weeks. Afterward, participants took the
highest recommended dose of the same drug for a second, 8-week
period. The statins tested included atorvastatin (Lipitor),
simvastatin (Zocor), and pravastatin (Pravachol).
Researchers wanted to study statins at two dose levels because
the results could help answer an important clinical question:
If a low or moderate dose of a statin isn't lowering LDL to
target levels - the definition of statin resistance - could
more of the drug overcome that?
"This is the first study we know of that looked at the value of
dose escalation among statin resistant patients," says Deepak
Voora, MD, a cardiologist at Duke and the lead author of the
study. "What the research told us, among other things, is that
dose escalation is not the best choice for statin resistant
patients. The better option would be to simply switch them to
the most potent statin available."
Using a database of previously determined genes believed to be
important in cholesterol management, researchers selected 31
genes and 489 mutations to study statin resistance in the
patients at both the high and low dose levels.
In correlating the presence or absence of mutations with
response to the statins, investigators found only one - a
mutation in the ABCA1 gene, a gene involved in cholesterol
transport - that appeared to be associated with a diminished
response to statins at the lower dose level. While the
low dose statins did cause the LDL levels to decline among the
carriers of that mutation, their LDL levels feel far less than
did the LDL levels of patients who did not carry the mutation
(24 percent vs. 32 percent, respectively).
The ABCA1 mutation was also significantly associated with
resistance at the higher statin dose, as was a second mutation,
an alteration in the APOE gene.
Both carriers of the APOE and the ABCA1 mutations showed an
improved response to the higher dose of the statins, but it was
still significantly weaker than that of the non-carriers'
response to the higher drug dose.
Investigators also discovered that older patients and
nonsmokers were more likely to have a more robust response to
statin therapy than were younger patients and patients who
Ginsburg says this study underscores the value of genetic
testing and the role it can play in selecting the most
appropriate therapy for an individual patient, a key principle
of predictive, or personalized medicine.
"There are likely more genes involved in statin resistance, so
much more research needs to be done before we can fully
understand which patients won't respond well to particular
statins," says Ginsburg. "Studies like this one, however, move
us one step closer to the time when we'll routinely use genetic
testing to guide patient care."
The study was funded by Genaissance Pharmaceuticals (which is
now known as Clinical Data Inc.). Duke University investigators
conducted the genetic analyses.
Colleagues from Duke who contributed to the study include Svati
Shah, Jun Zhai, and David Crosslin. Additional co-authors
include Carol Reed and Benjamin Salisbury, from PGxHealth, a
division of Clinical Data Inc.; and Chad Messer, formerly of