One of the most fascinating parts of wearing a continuous glucose monitor (CGM), is the individuality you start to notice in your glucose. Even within families, people will have vastly different glucose responses to the same meal or even fruit. One of the most varied reports we have from users is apples vs bananas - many users find they have a large rush in response to one or the other, some however find they rush to neither or both, and we have no way of knowing which without visibility.
This bio-individuality is something the scientific community are calling ‘glucotype’, akin to your glucose fingerprint so to speak. But WHY do we all react differently?
Let’s start at the beginning; glucose is impacted by a multitude of factors, many of which interact with each other. These factors can be broken into 2 categories:
- Intrinsic: Things about that individual, genetics, age, biological sex and microbiome. These factors will cause differences between individuals (for the same meal)
- Extrinsic: Factors outside the individual, like the way the meal was cooked. Extrinsic factors account for differences within an individual
A glucose response to a meal will be influenced by factors intrinsic to the individual (things about that individual e.g., nutritional status) and extrinsic to the individual (factors outside the individual e.g., the way the meal was cooked). Extrinsic factors account for differences within an individual, whereas intrinsic factors will cause differences between individuals (for the same meal).
So what are some of these factors?
Regular readers of the blog will be familiar with many factors that impact the way a specific meal will influence someone’s glucose.
These include (but are not limited to):
- Meal macronutrient order
- Adding acid (such as apple cider vinegar)
- Prior fasting
- Nutritional status
- How quickly you eat
- How well you chew your food
Perhaps the easiest way to explain the intrinsic factors which impact glycemic responses are to explain carbohydrate absorption, and thus where differences may be in the process. For this, we will talk about this process in three parts based on where they occur; mouth, stomach and intestine.
In the mouth, the food is chewed and as mentioned above both global speed of eating and amount of chewing will impact the glycemic response to food. This is where mechanical and chemical digestion of carbohydrates begins. Something that may not make initial sense, is that increased chewing creates a more significant glycemic response, that does not mean chewing is bad, though. It also means you are more satiated and satisfied post meal (the body is complex).
Beyond chewing (aka mastication for those playing scrabble) the digestive process is aided by the impact of salivary amylase. This is an enzyme in the saliva that helps break down carbohydrates. It is at this point we see one of our first diversions in bio individuality. It turns out that a gene variant in the gene coding for amylase (AMY1 - the geneticists are a logical bunch when it comes to naming) changes the glycemic response to food.
In the stomach the food now mixes with stomach acid, forming what is called chyme. The stomach churns and mixes to help further break down chyme. There is no further action of amylase and other enzymes here due to the acidic environment, but the mechanical breakdown continues via peristalsis (the name for the churning of the stomach).
The Small Intestine
The chyme exits the stomach and enters the small intestine, where carbohydrates are absorbed. At this stage, the pancreas performs its exocrine function (not endocrine - referring to hormones, where it would release insulin) whereby it releases amylase and other enzymes related to digestion of fat and protein, not carbohydrates. Carbohydrates are actively absorbed in the small intestine via a range of transporters. As discussed regularly in sports nutrition, the gut is trainable, yielding an increase in these transporters and thus an increase in the carbohydrate absorption capacity.
Some factors that impact differences in digestion of carbohydrates are difficult to locate in their action. These include the gut microbiome (as measured by stool samples). Traditionally stool sampling yields more information about the colonic/large intestinal microbiome, but may reflect a more global microbiome and hence influence carbohydrate digestion which largely occurs higher up the digestive tract.
The Role of Insulin and Removal of Glucose from the Blood
Other, more global factors with respect to glycemic responses include some genes many of which relate to insulin in some way. This is because regardless of absorption, the other side of the equation in glycemia is removal of glucose from the blood - either by insulin or by insulin independent mechanisms (like going for a walk). So any genes (or other factors) that impact insulin will impact glycemia.
The TCF7L2 gene specifically influences insulin secretion from the pancreas. Whereas KCNJ11 gene influences the way that pancreatic beta cells (the ones that secrete insulin) work. Whilst PPARγ on the other hand, influences insulin sensitivity.
As should be obvious now, there are a myriad of factors that impact carbohydrate absorption and glucose metabolism. Some of these are covered above, though there are almost certainly many more differences at any level of absorption or metabolism. Largely the WHY of this doesn’t matter as much as the THAT of it when it comes to individuals. That is, the fact that you are unique is more important than why, and means that using a CGM is far more insightful for bio individuality than following a number of ‘hacks’ for glucose.
Hall H, Perelman D, Breschi A, Limcaoco P, Kellogg R, McLaughlin T, Snyder M. Glucotypes reveal new patterns of glucose dysregulation. PLoS Biol. 2018 Jul 24;16(7):e2005143. doi: 10.1371/journal.pbio.2005143. PMID: 30040822; PMCID: PMC6057684.
Saito Y, Kajiyama S, Nitta A, Miyawaki T, Matsumoto S, Ozasa N, Kajiyama S, Hashimoto Y, Fukui M, Imai S. Eating Fast Has a Significant Impact on Glycemic Excursion in Healthy Women: Randomized Controlled Cross-Over Trial. Nutrients. 2020 Sep 10;12(9):2767. doi: 10.3390/nu12092767. PMID: 32927895; PMCID: PMC7551722.
Ranawana, V., Leow, MS. & Henry, C. Mastication effects on the glycaemic index: impact on variability and practical implications. Eur J Clin Nutr 68, 137–139 (2014). https://doi.org/10.1038/ejcn.2013.231
Farrell, M., Ramne, S., Gouinguenet, P. et al. Effect of AMY1 copy number variation and various doses of starch intake on glucose homeostasis: data from a cross-sectional observational study and a crossover meal study. Genes Nutr 16, 21 (2021). https://doi.org/10.1186/s12263-021-00701-8
Barber TM, Bhatti AA, Elder PJD, Ball SP, Calvez R, Ramsden DB, Cuthbertson DJ, Pfeiffer AF, Burnett D, Weickert MO. AMY1 Gene Copy Number Correlates With Glucose Absorption and Visceral Fat Volume, but Not with Insulin Resistance. J Clin Endocrinol Metab. 2020 Oct 1;105(10):dgaa473. doi:10.1210/clinem/dgaa473. PMID: 32697825.
Bayer S, Reik A, von Hesler L, Hauner H, Holzapfel C. Association between Genotype and the Glycemic Response to an Oral Glucose Tolerance Test: A Systematic Review. Nutrients. 2023; 15(7):1695. https://doi.org/10.3390/nu15071695
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, Dohnalová L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, Segal E. Personalized Nutrition by Prediction of Glycemic Responses. Cell. 2015 Nov 19;163(5):1079-1094. doi: 10.1016/j.cell.2015.11.001. PMID: 26590418.
Korem T, Zeevi D, Zmora N, Weissbrod O, Bar N, Lotan-Pompan M, Avnit-Sagi T, Kosower N, Malka G, Rein M, Suez J, Goldberg BZ, Weinberger A, Levy AA, Elinav E, Segal E. Bread Affects Clinical Parameters and Induces Gut Microbiome-Associated Personal Glycemic Responses. Cell Metab. 2017 Jun 6;25(6):1243-1253.e5. doi: 10.1016/j.cmet.2017.05.002. PMID: 28591632.