6.10: Case Study Parmacogenomics Conclusion and Chapter Summary

Case Study Conclusion: Pharmacogenomics

Arya asked their doctor about Pharmacogenomics. The doctor explains to Arya that Pharmacogenomics is the tailoring of drug treatments to people’s genetic makeup, a form of ‘personalized medicine’.

Figure \(\PageIndex{1}\): Glucose insulin release.

Figure \(\PageIndex{1}\) shows a beta cell of the pancreas. As the blood glucose rises, it enters the cell via the GLUT 2 channel. After entering into the cell, it causes the production of ATP that closes the potassium pump. As potassium stops exiting the cell, it causes calcium channels to open and, finally, that causes insulin release from the cells. This process is even more complicated as many enzymes and proteins are skipped in this brief description of the pathway. The sulfonylurea-based drugs force the closing of a potassium pump by attaching it. This causes the release of insulin by skipping many steps. Because many enzymes and other proteins are involved in this complicated process, people respond differently to medicines. Most respond well and their health improves. Some do not gain any benefits from the treatment, and a minority suffer from side effects. After you take a drug, it is processed (metabolized) by your body. How the drug is processed and how you respond to it is determined, in part, by your genes. Understanding how different genetics affect and how a drug is processed can help doctors to more accurately determine which drug and which dose is best for individual patients. In this chapter, you learned what the genome is and how to recognize genes in the genome. In pharmacogenomics, scientists look at the genome of an individual to identify the genetic factors that influence his or her response to a drug. By finding these genes, medical researchers hope to develop genetic tests that will predict how patients will respond to a drug. This is personalized medicine. The reason people vary in their responses to drug treatments lies in the genetic differences, or variation, between them. Following the Human Genome Project, research has focused on comparing human genomes to understand genetic variation and work out which genetic variants are important in health and in the way we respond to drugs. We also learned in this chapter that two types of variation are common in the human genome: 1) Single nucleotide polymorphisms (SNPs): changes in single nucleotide bases (A, C, G, and T). This was the case in Arya’s physical response to the sulfonylurea. 2) Structural variation: changes affecting chunks of DNA that can consequently alter the structure of the entire chromosome. Structural variation can happen in a number of ways, for example, Copy number variation (CNV): when there is an increase or decrease in the amount of DNA. This can be due to: deletion, where an entire block of DNA is missing; insertion, where a block of DNA is added in duplication; or where there are additional copies of a section of DNA. Inversion: when chromosome breaks in two places and the resulting piece of DNA is reversed and reinserted back into the chromosome (the opposite way round). Translocation: when genetic material is exchanged between two different chromosomes. SNPs are like changing a single letter in the metaphorical 'recipe book of life', while structural variation is the equivalent of whole paragraphs or pages being lost or repeated. Scientists have been aware of SNPs for a long time, but the extent of structural variation was only revealed when it was possible to sequence and compare many genomes. The structural variation appears to be quite common, affecting around 12 percent of the genome. It has been found to cause a variety of genetic conditions.

Finding disease variants

Humans share around 99.5 percent of their genomes. The 0.5 percent that differs between each of us affects our susceptibility to disease and response to drugs. Although this doesn’t sound like a lot, it still means that there are millions of differences between the DNA of two individuals. For example, because SNPs are common in the genome, it is difficult to work out which single letter changes cause disease and which are passengers that have just come along for the ride and have no effect on health.

So how is it possible to know which genetic variants cause disease and which are passengers?

The way scientists look at disease variants is to compare the genetic makeup of a large number of people who have a specific disease with those who do not. This allows scientists to look for genetic variants that are more common in people with a disease compared to people without the disease. For example, if a particular genetic variant is present in 80 percent of patients with the disease but only 20 percent of the healthy population it suggests that this variant is increasing the risk of that disease. However, looking for a disease that is caused by variants in a single gene is the simplest example. There are many complex diseases where variants in many different genes might be involved. As well as the transcriptional and translational regulation of some enzyme production may vary due to the genetic variation in the enhancer and repressors of a gene. So, for this type of comparison to be effective very large groups of people need to be studied, usually in the tens of thousands, to find the variants that have subtle effects on disease risk. Researchers also try to pick individuals with similar phenotypes, in both the diseased and healthy groups, so that the disease genes are easier to identify and study.