ENVB 437 Lecture 17: Eukaryotic cells and viruses – lecture 17 (March 19th 2018)
4 Jun 2018
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Eukaryotic cells and viruses – lecture 17 (march 19th 2018)
Slide 77 – according to last years slides; 82 this year
- Collecting health parameters and blood parameters let you know how people are aging and allows you to get
indicators of cancers by generalising with this data
Slide 78
- These enzymes inactivate the medication for tumour growth
- There is a W/W (biallelic)
o TPMT activity is indicated by the N distribution in green
- W/M
o RMPT activity is considerably reduced
- M/M
o Even less activity
- All of these medications, are prescribed in terms of a normal dose – decided by experimentation based on how
the average person responds to a drug
o But the receiver might not be an average responder
o The dose is adjusted after depending on how you react to it
- Because in the heterozygote, the enzyme has a low reactivity in the individuals who would correspondingly
have a high concentration in the blood stream
o Goes hand in hand with the toxicity that occurs from the drug
▪ If the person is deficient in TPMT, they will experience higher kevels if toxicity associated
with that drug
o Have to calculate to eve out the toxicity
Slide 79
- Another example has to do with antidepressants and the particular enzyme CYP2D6 – metabolises a lot of the
depressants
o A lot of variation in the activity
- Ethiopians have more gene duplications
- Others have splicing which results in inactivation of the enzyme
- If you treat individuals for neurological disorders than you can’t really have an idea of the drug you give them
o With the genotype, it would help because you could adjust the dose according to their genotype
▪ You can start with the correct drug dose rather than only after seeing how it affects them
Slide 80
- Also consider genotypes according to the blood brain barrier
o Varying amounts of the drug would be delivered across the BBB for different individuals
Slide 81
- Considerably more genetic variation in humans than previously expected
- The individual genome length could be up to 9m bp
- The more we sequence the more SNPs can be potentially useful markers for different phenotypes
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