AGBT: Eric Boerwinkle, University of Texas School of Public Health

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.

Translational Applications:

  • 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..

Early results:

  1. spiked in internal control to confirm that they could find known mutations.  (worked.)
  2. Examined previously implicated genes (3 of them)
  3. 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.]

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