Yes, it exists: http://genomera.com
They're actively running experiments and collecting data but are in "beta testing" and are very exclusive on whom they allow to join. I'm disappointed they didn't choose me when I filled out their request for a beta invite.
A huge problem with collecting data like this in the US population, is that everyone has a similar diet. There's so few people totally excluding gluten, you can't expect to measure it's effects with epidemiological diet surveys: you need to actually do a controlled trial where you tell people to avoid it.
In China where only about half of people eat foods with gluten the biggest epidemiological study ever performed (the China Study) did find that wheat intake was independently correlated with overall mortality (http://rawfoodsos.com/the-china-study/). They never published this finding themselves, but the correlation is clearly there in the data.
There's a lot of question about their methodology- they didn't keep or report data on individuals, but lumped whole communities together as single data points. There's likely a lot of highly correlated regional habits that weren't on the questionnaire, and I tend to find the whole study pretty questionable. For the most part, it's just comparing the health of rural farmers with wealthier urban Chinese- the two groups have radically different health, lifestyle, and diets and we can only control for the few questions they actually asked.
Perhaps now that gluten avoidance seems to be becoming a "fad diet" in western countries, suddenly it will be possible to actually collect good data on this.
That looks like it could prove really useful / interesting; thanks for linking.
I guess the entry requirements for beta are strict because they're trying to keep to a small set of variables for the people to check? It would have been really interesting to spy in on though. Regarding the China study, it sounds either like there was no effort to control for other obvious/statistically-true correlates or that there is no possible overlap at all to abstract a controlled comparison from. A fraction of that data might be useful (all data is useful! ...yum!). I th...
Nutrition is a case where we have to try to make the best possible use of the data we have no matter how terrible, because we have to eat something now to sustain us while we plan and conduct more experiments.
I want to apply Bayes theorem to make rational health decisions from relatively weak data. I am generally wondering how one can synthesize historical human experiences with incomplete scientific data, in order to make risk-adverse and healthy decisions about human nutrition given limited research.
Example question/hypothesis: Does gluten cause health problems (ie exhibit chronic toxicity) in non-coeliac humans? Is there enough evidence to suggest that avoiding gluten might be a prudent risk-adverse decision for non-coeliacs?
We have some (mostly in vitro) scientific data suggesting that gluten may cause health problems in non-coeliac humans (such as these articles http://evolvify.com/the-case-against-gluten-medical-journal-references/). Let's say for the sake of arguing, that I can somehow convert these studies into a non-unity likelihood ratio for gluten toxicity in humans (although suggestions are welcome here too).
However, we also have prior information that a population of humans has been consuming gluten containing foods for at least 10,000 years, without any blatantly obvious toxic effects. Is there some way to convert this observation (and observations like this) into a prior probability distribution?