Some of us will never get faster. Now we know why
#26
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The abstract of the paper that explains the test:
https://www.ncbi.nlm.nih.gov/pubmed/20133430
In a nutshell:
"VO2max responses to endurance training can be predicted by measuring a approximately 30-gene RNA expression signature in muscle prior to training."
https://www.ncbi.nlm.nih.gov/pubmed/20133430
In a nutshell:
"VO2max responses to endurance training can be predicted by measuring a approximately 30-gene RNA expression signature in muscle prior to training."
#27
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The abstract of the paper that explains the test:
https://www.ncbi.nlm.nih.gov/pubmed/20133430
In a nutshell:
"VO2max responses to endurance training can be predicted by measuring a approximately 30-gene RNA expression signature in muscle prior to training."
https://www.ncbi.nlm.nih.gov/pubmed/20133430
In a nutshell:
"VO2max responses to endurance training can be predicted by measuring a approximately 30-gene RNA expression signature in muscle prior to training."
Those Affymetrix gene chips for DNA and RNA are quite variable in their data precision and reliability. When they were invented, they were hailed as the be-all end-all of genomics, but in practice, it's closer to a random crapshoot than anything else. I'm actually not exaggerating this at all - if you try and submit a paper where they main claims are based mostly on Affymetrix chip data, no matter how convincing, you will get instantly rejected by all the top journals (Cell, Science, Nature) unless you have much more substantive proof backing up the finding. This is largely why that paper, despite it's pretty ambitious claim that they can explain a whopping 30% of VO2 with simple gene analysis, is not published in one of these top journals. If Affymetrix data was rock-solid, it would have shot right to the top, as that sort of data if rock solid would completely change the way we train and study top athletes right now today.
I've seen so many PhD proposals by colleagues based on Affymetrix data that seemed so exciting and promising because it seemed to correlate "X" gene with this great phenomena, be totally shot down when you actually do the validation work. In our lab and others we collaborated with, it was known that you could almost always get Affymetrix data to be a supporting figure of any phenomena you chose to study - just repeat the chip analysis a few times until the variability in the results gives you the result you want. I know this sounds incredible cynical, but it's absolutely true. There are no major papers that rely solely on Affymetrix data because of this well known variability. You MUST back up your findings with prospective experimental trials to get reviewers to believe you.
I actually fully believe that this type of genetic analysis will absolutely become integral to elite athlete training and selection in the future, but we're nowhere near that level today. Papers like this one are interesting, but until they prove that their Affymetrix data is more than random variation, we've got a long way to go before that day.
Last edited by hhnngg1; 10-10-12 at 07:45 PM.
#28
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Yeah, sorry to say this is the mentality I'm talking about. ![Big Grin](https://www.bikeforums.net/images/smilies/biggrin.gif)
As far as I know there are no studies to support this assertion; it's just an assumption based on observing traits and results whose origins are not necessarily genetic. You cannot possibly know the genetic makeup of Rider X unless you've actually tested their DNA, any more than you could prove paternity based on visual observation.
![Big Grin](https://www.bikeforums.net/images/smilies/biggrin.gif)
As far as I know there are no studies to support this assertion; it's just an assumption based on observing traits and results whose origins are not necessarily genetic. You cannot possibly know the genetic makeup of Rider X unless you've actually tested their DNA, any more than you could prove paternity based on visual observation.