Good bodybuilders and bodybuilding coaches have long known that everyone’s a bit different: Finding the unique dietary formula that works for the individual is vital for success. Well, there are loads of studies showing biological interindividuality when it comes to things like drug metabolism (e.g., yohimbine (1, 5, 6)] and adaptation to training(3, 11, 14).
Nutritional science has also borne out what bodybuilders have known for decades: Even simple meal responses like the rise in blood sugar can be highly variable, both for the same person even even if eating the same meal(13), and among individuals(12). Glycemic response can also change over time as the diet changes(15).
Some recent, very cool research has started to unravel the mystery of this biological black box(15). Israeli scientists hooked up blood glucose monitors to 800 people (that’s a large sample size, by the way) eating a variety of standardized meals (>456,000 meals in total!) over the course of many weeks. Using these data, they developed a complex mathematical algorithm to predict the main factors involved in the glucose response to a meal. Of course, age, BMI (an indicator of body composition), morning glucose, and the glycemic index of the foods eaten – the regular cast of characters – all predicted (higher) glucose levels in the ways one would expect.
Still, though, a large part of the variability was undetermined, i.e., the subjects were still unique “snowflakes” when it came to post-meal glycemic responses.
Here’s the cool part: The enzymatic activity and species of the “probiotic” bacteria – the ones that live in our guts – were significantly predictive of glucose tolerance. In other words, the symbiotic bugs in our microbiome are representative of (and somehow contribute to) our glucose tolerance [An important side note: Glucose tolerance is an important predictor of metabolic health and morbidity(2, 4, 7, 9, 10).]
But it gets even cooler: Changing your diet will transform the probiotic populations in your gut, too! The researchers took a subsample of 100 subjects and made personalized diets, based on those individuals’ normal eating patterns. The crafty dieticians used the newly-derived algorithm to prescribe a week of “bad” foods that would, cause high glycemic responses, and, during another week, issued a “good” food meal plan composed of low glycemic index meals.
The diets not only affected glucose control as expected, but they also shifted the gut bacteria to a healthier profile!
The bottom line: As you may have already known, simply eating low glycemic foods / meals will improves glycemic control, and we now know that doing so shifts the gut microbiome to a healthier profile as well. This makes sense, of course, given that dietary supplementation with probiotics themselves has this effect(8). So now we have even more evidence that you “are” what you eat, and this includes the bugs in your belly!
Dr. Scott Stevenson, PhD is the author of Fortitude Training, co-author of John Meadows’ The Brutality of Mountain Dog Training, and a bodybuilding physiologist, coach and a competitor himself. You can contact Scott for appearances and consultation via http://www.drscottstevenson.com.
- Berlan M, Le Verge R, Galitzky J, and Le Corre P. Alpha 2-adrenoceptor antagonist potencies of two hydroxylated metabolites of yohimbine. Br J Pharmacol 108: 927-932, 1993. http://www.ncbi.nlm.nih.gov/pubmed/8097957
- Henriquez S, Jara N, Bunout D, Hirsch S, de la Maza MP, Leiva L, and Barrera G. Variability of formulas to assess insulin sensitivity and their association with the Matsuda index. Nutricion hospitalaria 28: 1594-1598, 2013.
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- Krotkiewski M, Björntorp P, Sjöström L, and Smith U. Impact of obesity on metabolism in men and women. Importance of regional adipose tissue distribution. Journal of Clinical Investigation 72: 1150-1162, 1983. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1129283/
- Le Corre P, Dollo G, Chevanne F, and Le Verge R. Biopharmaceutics and metabolism of yohimbine in humans. Eur J Pharm Sci 9: 79-84, 1999. http://www.ncbi.nlm.nih.gov/pubmed/10494000
- Le Corre P, Parmer RJ, Kailasam MT, Kennedy BP, Skaar TP, Ho H, Leverge R, Smith DW, Ziegler MG, Insel PA, Schork NJ, Flockhart DA, and O’Connor D T. Human sympathetic activation by alpha2-adrenergic blockade with yohimbine: Bimodal, epistatic influence of cytochrome P450-mediated drug metabolism. Clin Pharmacol Ther 76: 139-153, 2004. http://www.ncbi.nlm.nih.gov/pubmed/15289791
- Pereira MA, Kartashov AI, Ebbeling CB, Linda Van H, and et al. Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis. The Lancet 365: 36-42, 2005. http://search.proquest.com/docview/198999154?accountid=458
- Ruan Y, Sun J, He J, Chen F, Chen R, and Chen H. Effect of Probiotics on Glycemic Control: A Systematic Review and Meta-Analysis of Randomized, Controlled Trials. PLoS One 10: e0132121, 2015. https://doi.org/10.1371/journal.pone.0132121
- Sacks FM, Carey VJ, Anderson CA, Miller ER, 3rd, Copeland T, Charleston J, Harshfield BJ, Laranjo N, McCarron P, Swain J, White K, Yee K, and Appel LJ. Effects of high vs low glycemic index of dietary carbohydrate on cardiovascular disease risk factors and insulin sensitivity: the OmniCarb randomized clinical trial. Jama 312: 2531-2541, 2014.
- Stumvoll M, Mitrakou A, Pimenta W, Jenssen T, Yki-Jarvinen H, Van Haeften T, Renn W, and Gerich J. Use of the oral glucose tolerance test to assess insulin release and insulin sensitivity. Diabetes Care 23: 295-301, 2000.
- Timmons JA. Variability in training-induced skeletal muscle adaptation. J Appl Physiol 110: 846 – 853, 2011.
- Vega-Lopez S, Ausman LM, Griffith JL, and Lichtenstein AH. Interindividual variability and intra-individual reproducibility of glycemic index values for commercial white bread. Diabetes Care 30: 1412-1417, 2007. http://www.ncbi.nlm.nih.gov/pubmed/17384339
- Vrolix R, and Mensink RP. Variability of the glycemic response to single food products in healthy subjects. Contemporary clinical trials 31: 5-11, 2010.
- Wernbom M, Augustsson J, and Thomee R. The influence of frequency, intensity, volume and mode of strength training on whole muscle cross-sectional area in humans. Sports Med 37: 225-264, 2007. http://www.ncbi.nlm.nih.gov/pubmed/17326698
- Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, Suez J, Mahdi JA, Matot E, Malka G, Kosower N, Rein M, Zilberman-Schapira G, Dohnalova L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, and Segal E. Personalized Nutrition by Prediction of Glycemic Responses. Cell 163: 1079-1094, 2015.