A major focus in pharmacogenomics is to examine how differences in gene expression
correlate with drug response or disease risk.
Small variations in our DNA can correlate with individual differences in response to a
medication or disease risk. In many cases, these variations occur within the DNA sequences
of our genes and influence how the gene's products work.
Changing the DNA sequence isn't the only way to affect a gene, though. Altering the level
of gene expression - thus increasing or decreasing the amount of
RNA or protein made - can
influence biological processes just as dramatically.
Gene expression and obesity
Let's look at obesity as an example of how gene expression can correlate
with disease risk:
Obesity is a major health risk in America that threatens children and adults alike. It
can lead to heart disease, high blood pressure and diabetes, especially as people age. A
complex medical condition, obesity is influenced by diet, exercise, metabolism - and genetics.
Shan, age 17, is more than 40 pounds overweight relative to his height. His parents and
grandparents are all overweight as well.
Allen is similar to Shan with respect to age, height, diet and exercise habits, but he
is not overweight. Furthermore, no one in Allen's family is overweight.
Both Shan's and Allen's families volunteer to participate in a university study to
identify genes that play a role in obesity. How will the researchers approach this question?
Measuring levels of gene expression
Each cell type has a unique expression profile.
Three generations of family members provide cell samples (liver and fat cells) to the
researchers. Liver and fat cells were chosen because they are important in metabolism
and making fats.
- The researchers will use an approach called gene expression profiling to identify
active and inactive genes in a cell or tissue.
- Expression profiling then tells the scientist which genes may play a role in obesity.
- Scientists run similar expression profile studies on all the family members, as well
as on those of other study participants.
Once the scientists compare the results from everyone in the study, they have a good
idea which genes play a role in obesity. This information will be used in several future applications:
- Creating diagnostic tests to predict whether a patient has a genetic predisposition to obesity.
- One test might examine the DNA sequence of a person's obesity-related genes,
in order to detect genetic signatures that predict a predisposition to obesity.
- Another test might examine a tissue sample for abnormal gene expression patterns
that indicate a predisposition to obesity.
- Designing Drugs
- Designing drugs intended to treat or prevent obesity. This could be done by
isolating the protein products of the identified obesity genes, determining their molecular
structures and functions, and making drugs to inhibit them.
- Designing drugs to control expression of obesity genes. These drugs
would interact directly with DNA in key cells and tissues to prevent genes that are
activated in obesity from being turned on -- or, conversely, to prevent genes that are
inactivated during obesity from being turned off.
Supported by a Science Education Partnership
Award (SEPA) [No. 1 R25 RR16291-01] from the National Center for Research Resources, a component of the
National Institutes of Health, Department of Health and Human Services. The contents provided
here are solely the responsibility of the authors and do not necessarily represent the official
views of NCRR or NIH.
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