I know just enough about statistics to find a lot of medical research horrifying. Doctors as a group tend to be borderline math-illiterate and they are impressed by findings that are very poorly supported by the statistics they choose to produce. Often they seem to be dazzled by the features of the software they employ without understanding GIGO.
So when you look at studies, you have to read the full text very carefully, look at what they say they were doing and then see if the methodology they used really does provide the answers. Did they ignore and fail to control for important variables? Were the matched groups really matched--I have seen many studies where two groups have significantly different makeups but are considered to be matched.
Then look at the way the results are presented. If all you see is a bunch of averages with large standard deviations, be wary when those are used to show one group had an important difference from another. If there are no subanalyses that break out different sub groups, be wary, too. And last, but not least, check out the statistical significance. I have seen quite a few studies where the results were not statistically significant reported to say that though the results didn't reach significance they showed the result "trending" towards whatever outcome the researcher hoped to find. That, of course, means as much as saying that the in a coin flip, the coin came up heads 7 times out of 10 so that was a "headsy" coin.
And yet though this is Statistics 101, I had a long discussion with a biology professor whose research has been featured in the media who was astonished to learn that statistically insignificant data "trending" in that way was actually meaningless, since she sees that all the time in research she reviews.
And that doesn't begin to get into the way that statistics are manipulated by those with agendas, like drug companies, to make a result seem more impressive than it is. Where the incidence of some disease is 5 in 100,000 and the drug cuts it to 4 in 100,000 and the research is titled "Drug lowers risk of Disease by 20% and doctors are urged to prescribe it on that basis, not understanding how "risk" statistics are calculated.
Epidemiology is all about statistics, but unfortunately, it is a field where they are often badly misapplied. And you probably didn't have trained epidemiologists analyzing that MODY2 data. So be cautious.
My guess is that people with blood sugars that reach into the mid 200s have the same health as other people whose blood sugar reaches those heights. We know for a fact that until very recently, a good chunk of all Type 2 diabetics were undiagnosed at the time when their blood sugars were in that range, and so they formed part of that "normal" comparator group.
Unless the study screened those normal people with OGTT (which never happens in big studies because it is too expensive), I'd be very cautious about any result that was based on "normal" vs something else. The high end of normal is full of people with undiagnosed diabetes. Some huge percent of people with Type 2 have diabetic complications on the day of diagnosis, which means they have had diabetes post meal for as long as ten years, but weren't diagnosed due to the reliance on FBS. The move to diagnose people with A1c probably makes this worse. All it takes is a little anemia or certain ethnic genes and you have a lovely A1c and very high blood sugars.