Tuesday, June 19, 2018

Ummm....can we identify people from proteomic samples...?


I didn't make it to a poster by some of these authors on the final day of ASMS but it is something I've thought about at least once a day since.  You can check out the study here.

Actually, this one is also really interesting.

You know when they do the DNA forensics stuff that they really only look at small bits of the DNA -- just enough to determine match against random occurrence. The early stuff was just restriction digests and running gels and trying to match the gels. Actually -- found a good WikiPedia post here.  I think the newer stuff is all SNP. Full DNA sequencing is still about $1k -- which is a LOT of donuts --  which is still far too expensive to be practical for law enforcement, even without the data processing.

If we're looking at small snipets of DNA -- what are the odds that small snipets of protein would have enough info to do the same thing? This team is building an increasing amount of evidence that there is and it, quite likely, exists in our data and we can find it if we really look for it.

That's great for forensics -- but -- umm....


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If this is true --- this could be seriously bad, right?!!?!  I don't know how things are in the civilized world, but in my country if you get sick you die when you run out of money to pay for your medical care. We have "insurance" companies that we pay our entire lives that make their fortunes on gambling that we won't ever get sick enough that they'll lose money on us. And if we do need their services it is in their best interest that they find a way to not pay for our medical care.

Now...this is obviously stretching it and might sound like I need an aluminum foil hat....

Yo...so what if I'm one of the control samples in a big study that is on Massive that you could find by ProteomeXchange....and you could figure out from the RAW data that -- 1) that sample is from me and 2) in that dataset you can see that I have 2 of the single amino acid variants (SAAV) in PARKIN1 that we generally consider sub-ideal to have?  Could that one day be used by some enterprising insurance company scientist to build a case for why they don't have to cover my medical bills anymore?

Obviously this is just an extrapolation -- there are hundreds of variables here. Even if I had that level of insight going into a sample -- it's pretty darned hard to prove SAAVs and this forensics profiling doesn't sound real easy either, our coverage is extremely sample dependent...and on and on...but it's interesting to think about, right?

Also, thanks to legislation passed during our last federal administration here, bankruptcy rates due to health care costs are not nearly as common as they were (#1 cause of bankruptcy in the U.S. in 2013).  This legislation has been under a lot of fire recently, but its still standing.

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