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kayell

'Personalized Nutrition by Prediction of Glycemic Responses'

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kayell

http://www.cell.com/cell/fulltext/S0092-8674(15)01481-6

 

Dietary intake is a central determinant of blood glucose levels, and thus, in order to achieve normal glucose levels it is imperative to make food choices that induce normal postprandial (post-meal) glycemic responses (PPGR; Gallwitz, 2009). Postprandial hyperglycemia is an independent risk factor for the development of TIIDM (American Diabetes Association., 2015a), cardiovascular disease (Gallwitz, 2009), and liver cirrhosis (Nishida et al., 2006) and is associated with obesity (Blaak et al., 2012), and enhanced all-cause mortality in both TIIDM (Cavalot et al., 2011) and cancer (Lamkin et al., 2009).

"Despite their importance, no method exists for predicting PPGRs to food. The current practice is to use the meal carbohydrate content (American Diabetes Association, 2015b, Bao et al., 2011), even though it is a poor predictor of the PPGR (Conn and Newburgh, 1936)...

Here, we set out to quantitatively measure individualized PPGRs, characterize their variability across people, and identify factors associated with this variability. To this end, we continuously monitored glucose levels during an entire week in a cohort of 800 healthy and prediabetic individuals and also measured blood parameters, anthropometrics, physical activity, and self-reported lifestyle behaviors, as well as gut microbiota composition and function. Our results demonstrate high interpersonal variability in PPGRs to the same food. We devised a machine learning algorithm that integrates these multi-dimensional data and accurately predicts personalized PPGRs, which we further validated in an independently collected 100-person cohort. Moreover, we show that personally tailored dietary interventions based on these predictions result in significantly improved PPGRs accompanied by consistent alterations to the gut microbiota."

 

I WANT the program they used.

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dowling gram

 

 Our results demonstrate high interpersonal variability in PPGRs to the same food.-----

I WANT the program they used

 

" high interpersonal variability" --A long winded way to say every diabetic is different and has different BG reactions to food.

 

The only program that matters is what your meter says. No program can take into account all the variables that each diabetic faces. No 2 diabetics are exactly the same and can eat exactly the same things.

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kayell

Read the paper - their algorithm was able to learn from study participants reactions to different foods, different exercise regimes, etc and to make predictions on what would work for each individual. 

 

"Our algorithm takes as input a comprehensive clinical and microbiome profile and employs a data-driven unbiased approach to infer the major factors that are predictive of PPGRs. Introspecting the resulting algorithm shows that its predictions integrate multiple diverse features that are unrelated to the content of the meal itself. These include contents of previous meals, time since sleep, proximity to exercise, and several microbiome-based factors. With respect to microbiome factors, our algorithm identifies multiple functional pathways and bacterial taxa as either beneficial or non-beneficial, such that in participants with increasing levels for these factors the algorithm predicts a lower or higher PPGR, respectively. In many such cases, microbiome factors found to be beneficial with respect to PPGRs are also negatively associated with risk factors such as HbA1c% and cholesterol levels."

 

And more. This is more than just meter reading, although CGMs were involved. IMO this has the potential to make as much difference for diabetics as personal glucose monitors did. It's the next step.

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Ela

Yeah, this should be wonderful.....How much should I bet that it is NOT the next step and nobody (in official medical world) will ever discuss it or take it into consideration?  Individualized approach?  Yeah, right.  I wish.  It's just too complicated for the regular doctors.  Oh, and they're not paid enough either to do such complicated things. 

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predb4

machine language is incomplete.

 

and there is also intra-person variability, as the disease progresses, your reaction to a certain food may vary.

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