Eran Segal (Solve grantee): Personalised microbiome-based diets for blood glucose regulation

As far as I know it will. The route will just be a bit different. Any glucose not converted to fat will either be stored temporarily in the liver as glycogen or burnt off. Your hypothalamus will adjust how much is burnt off so that your temperature stays at 36.5. If glycogen hangs around long enough in the liver and is excess to requirement it will be converted into fat all the same. Calories cannot 'get lost in the system' except as in diabetes by coming out in the urine if the glucose spikes too high.

 

I had a look at this article. Thanks for posting, @Sasha. What struck me was not the individual variability, but rather the consistency in the direction of the key effects. Yes, the magnitude of each effect varies across individuals, but they were always in the same direction.

These factors increase post-meal glycemic responses (which is bad):
The meal’s sodium content
The meal's carbohydrate content
The meal's dietary fibre content (it has an immediate negative effect, but paradoxically, higher fibre intake over the past 24 hours has a beneficial effect)
The time that has passed since last sleeping (so GR is more rapid for meals taken later in the day)

These factors decrease post-meal glycemic responses (i.e. they are good):
The meal's fat content
The meal’s water content
The meal’s alcohol content (!)

These individual variables increase post-meal glycemic responses (which is bad)
The person's cholesterol levels (the higher your cholesterol, the faster the release)
The person's age (the older you are, the faster the release)
(I didn't see the results reported here, but I'm inferring that BMI is also a negative factor here - the higher your BMI, the faster the release).

So in other words, there's lot of useful general dietary info here, even if you don't look at the individual tailoring thing.

 

I wondered this too @adreno, when I was reading Sasha's paper on healthies (the one I described above). Some of the microbiome features they explored were associated with broader individual factors, such as BMI, age and cholesterol levels. So a simpler approach would be to target those (except of course age, unless you've discovered the fountain of youth!).

 

I've decided to try tracking various breakfasts that I eat, to see which produces the highest sugar response.

I'm taking baseline sugar at time zero (thankfully these readings are now in range - when I'd try this in April all my initial morning readings were higher than they ought to be!). Then I'm taking glucose readings every 10 mins til I have two successive readings below the previous one.

I'm going to try each breakfast more than once. Will let you know how I get on.

 

Dr. Eran Segal gives an update on his Ramsay 2017 ME/CFS project

https://www.youtube.com/watch?v=UorZUHULM4c