Just occurred to me that while I checked in with all my PIs doing this sort of work, I forgot to post a quick note here about various developments that bolster and make full use of genome-wide association studies. For starters, researchers can now request individual-level genotype and phenotype data from dbGaP, the NLM’s database of Genotype and Phenotype. Of course, this is not a simple request and in fact involves your Authorized Signing Official, who must co-sign on behalf of your institution – so everyone is held accountable for how you handle these sensitive and valuable data.
Issues regarding obtaining informed consent to permit such broad sharing of matched phenotype-genotype data are very much on the minds of NIH folks these days. This notice reminds researchers they cannot attempt “to identify or contact study participants from whom phenotype data and DNA were collected.” Think about that for a moment, and then think about those Signing Officials thinking about this potential snake’s nest of liability. (never mind how they will monitor use of the data to ensure it remains within the specifics of the data access request and that data are not shared with any unauthorized users, intentionally or not)
The NHGRI just received proposals in response to an RFA for GWAS based on tissue obtained during routine clinical care and stored in a central biorepository (versus specific research tissue banks) matched with data mined from the patient’s electronic medical record. Oh, and while you’re at it, solve the informed consent conundrum – with reconsenting for the short term while developing a durable advanced directive from patients seeking routine medical care that allows all their genetic & biological & medical record data to be bundled together & shared universally so they can be used as cases, controls, or both, depending on the requesting investigator’s research focus. Piece of cake.
Anyway, lots of incredible data are being delivered to this database, such as that from NHGRI’s Genetic Association Information Network, NEI’s Age-Related Eye Diseases Study, NINDS’s Parkinsonism Study, NIDDK’s diabetic nephropathy in type 1 DM, and a slew of NIMH projects. More diabetes, IBD, Framingham, and other rich datasets will be coming along. Statistical geneticists, welcome to the land of plenty.