Personalized Nutrition II

More on Zeevi et al. (2015) (this is a follow-up to part 1)

I like this study a lot, or at least the fundamentals… or new tools that it might bring to the table.  Like, we know sleep and physical activity are important, and we know all calories aren’t created equal.  This study is the next level, showing there are even big differences in specific carb-rich foods depending on who’s eating them.

And more interestingly, if I’m interpreting the results of the intervention study correctly (which may not be the case), gut microbial responses to specific foods were very individualized… and predictable!

But first, the main part of the study — standardized meals (after overnight fast): 50g carbs from glucose, white bread, bread and butter, bread and dark chocolate, and fructose.  All repeated at least once (except fructose).  Everyone responded pretty similarly to fructose (little to no blood glucose spike), but a wide range of responses to glucose.

PPGR = PostPrandial Glucose Response

 

glucose and fructose

 

Bread:

 

bread

 

The range of PPGR to bread was ~15 to 79!

Again, here are some of the findings I found most interesting (besides the huge range in glycemic response to bread):

 

 

banana and cookie

 

Participant #468 has a consistently higher response to glucose than to white bread.  Participant #663 is the opposite.  And participant #445 is still winning.

I truly wonder if there’s a gut microbe (or something) that’s involved here…

 

 

This graph is interesting:

 

Carb content and PPGR

 

Different carb-rich foods are listed on the bottom.  The green boxes show that most of these data came from meals of roughly 25-35g carbs.  The blue lines show the average PPGR.

SAME carb content, VERY DIFFERENT PPGR.

#IIFYM?!

O_o

Rice and potatoes have a high glycemic index and accordingly, are more toward the right side of the figure (ie, higher PPGR); ice cream and dark chocolate have a lower glycemic index and appear on the left side of the figure (ie, lower PPGR).  But the ranges in response are HUGE (eg, see pita).

 

 

Part 2. the follow-up/intervention study: people were assigned a low or high PPGR diet for one week each.  Notably, not everyone’s low PPGR diet was the same, eg, the ‘healthy’ low PPGR diet for participant #445 could have cookies but not bananas, and the opposite for participant #644.

 

It worked:

 

Postprandial glucose response success

 

The ‘biome went wild, as expected, because of the non-uniformity of individual PPGRs (I think).  There are a few ways to consider these data: 1) find correlations between microbes and baseline PPGR; 2) did the species that were correlated with high/low PPGR increase/decrease on the high/low PPGR diet? …and 3) does this make any sense?

A lot of Bacteriodetes predicted a good response to bread and butter, whereas a lot of Proteobacteria predicted the opposite.

Some species negatively associated with T2DM, like Roseburia inulinivorans, Eubacterium eligens, and Bacteroides vulgatus, all increased following the good diet and decreased following the bad diet.

 

Differential glucose responses

 

One KEY point here is that many of these changes are in line with previous findings, suggesting we’re at least starting to crack the ‘biome puzzle.

And one COOL point is that, recall, the microbial changes on a good diet were similar regardless of whether said diet had cookies or not!  in other words (if I’m interpreting this correctly), if cookies spike your blood glucose, then you wouldn’t experience the beneficial changes in your ‘biome that participant #445 did.

Consults are open, contact me if you’re interested: drlagakos@gmail.com

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