Title: Life after GWAS
By phone – and tweeing is acceptable… Isn’t technology wonderful?
Background: Standard GWAS algorithm. Find Genes -> Characterize Genes -> Define Functional Mutations -> Experimental Systems -> (Predictions/diagnosis/pharmacogenetics/Gene Interaction/etc)
Collaborations are an integral part of the work. Large cohorts are important.
Through July 2010, there are 904 pubished GWA for 165 traits – this is not insignificant. GWAS has played an important part in understanding disease. Need to appreciate the successes, even if there’s a lot further to go.
Mechanisms: Fine Mapping, Epidemiology, Translation, Resequencing and Biology. Focus on the last 3. (Fine mapping doesn’t make for a good talk…)
Eventually, GWAS will re-invigorate the old biochemistry fields (metabolism) by better understanding what’s going on. [paraphrased, but nice to hear it.]
First set of data: Atherosclerosis Risk in Communities, based on random sample of ~16k individuals, followed longitudinally. Annual follow up. The idea is to look at interaction between genes and environment.
Discussion of a few genes and their impact on the disease. [not going to directly copy the data, but a short discussion of risk factor.] Slides on putting it in context in the genome, and then doing functional analysis using a mouse knock out model.
- Novel drug targets
- updated prevention strategies
- new risk assessment algorithms
- Tailored therapies based on genotypes. [not going to talk about it, but a very important part of the future of medicine.]
[Skipping examples, of how you might apply this type of information to influence patient treatment and how you might apply it to large groups to modify treatment guidelines.]
Next section on resequencing.
Example of Permanent Neonatal Diabetes – dogma is that is dominant, and a few mutations have been found, but the majority causes were not know, or rather the cause was unknown in the majority of patients. [Skipped background, which is probably available on the web.]
Two papers, but work in progress: Voight et al, 2010, Dupuis et al (2010) – Both Nat Genet 42. 31 loci mentioned in first paper, 18 in second.
Wanted to confirm known genes, and to identify novel genes..
- spiked in internal control to confirm that they could find known mutations. (worked.)
- Examined previously implicated genes (3 of them)
- Examined T2DM genes. (None found)
Novel mutations in novel genes. Cryptic “inbreeding”.
[Unfortunately, I had a meeting, and had to run, as the talk had already gone over by 10 mintues, so I missed the section on Gout. Overall, a well delivered talk for someone who wasn’t able to attend in person.]