Glucotypes reveal new patterns of glucose dysregulation

Abstract

Diabetes is an increasing problem worldwide; almost 30 million people, nearly 10% of the population, in the United States are diagnosed with diabetes. Another 84 million are prediabetic, and without intervention, up to 70% of these individuals may progress to type 2 diabetes. Current methods for quantifying blood glucose dysregulation in diabetes and prediabetes are limited by reliance on single-time-point measurements or on average measures of overall glycemia and neglect glucose dynamics. We have used continuous glucose monitoring (CGM) to evaluate the frequency with which individuals demonstrate elevations in postprandial glucose, the types of patterns, and how patterns vary between individuals given an identical nutrient challenge. Measurement of insulin resistance and secretion highlights the fact that the physiology underlying dysglycemia is highly variable between individuals. We developed an analytical framework that can group individuals according to specific patterns of glycemic responses called “glucotypes” that reveal heterogeneity, or subphenotypes, within traditional diagnostic categories of glucose regulation. Importantly, we found that even individuals considered normoglycemic by standard measures exhibit high glucose variability using CGM, with glucose levels reaching prediabetic and diabetic ranges 15% and 2% of the time, respectively. We thus show that glucose dysregulation, as characterized by CGM, is more prevalent and heterogeneous than previously thought and can affect individuals considered normoglycemic by standard measures, and specific patterns of glycemic responses reflect variable underlying physiology. The interindividual variability in glycemic responses to standardized meals also highlights the personal nature of glucose regulation. Through extensive phenotyping, we developed a model for identifying potential mechanisms of personal glucose dysregulation and built a webtool for visualizing a user-uploaded CGM profile and classifying individualized glucose patterns into glucotypes.

Author summary

One in 10 individuals is affected by diabetes, a condition involving abnormal regulation of blood glucose. Currently, diabetes is assessed using single-time or average measurements of blood glucose, without consideration for how blood glucose fluctuates over time. We used continuous glucose monitoring (CGM) technology to evaluate how blood glucose fluctuates in individuals over time. We found that many individuals considered nondiabetic by standard measures, in fact, experienced frequent elevations in blood glucose levels into the impaired glucose-tolerant or diabetic range. We developed a model for determining the “glucotype” of an individual, a more comprehensive measure of the pattern of glucose excursions than the standard laboratory tests in current use. We also built a web tool for interactively visualizing an individual’s glucose profile and performing glucotype assessment. With greater adoption of CGM technology, glucotype assessment may become an important tool in early identification of those at risk for type 2 diabetes and/or cardiovascular disease.

Cohort characteristics

We recruited 57 healthy participants without prior diagnosis of diabetes. We monitored their blood glucose using CGM in their normal environment, and we extensively characterized them with clinical metabolic phenotypes including whole-body insulin resistance and insulin secretion. The cohort composition was 32 females and 25 males, with an age range of 25 to 76. On screening tests, 5 met criteria for having type 2 diabetes, defined as HbA1c ≥ 6.5%, fasting blood glucose ≥ 126 mg/dL, or 2-hour glucose during 75 gram OGTT ≥ 200 mg/dL; 14 had prediabetes, defined as HbA1c > 5.7% and < 6.5%, fasting blood glucose 100–125 mg/dL, or 2-hour glucose during OGTT 140–199 mg/dL; the remainder were normoglycemic, defined as fasting and 2-hour OGTT plasma glucose and HbA1c below the diagnostic thresholds for prediabetes and diabetes. Mean fasting glucose was 93 mg/dL, 2-hour glucose 125 mg/dL, and HbA1c 5.4%. Insulin resistance, quantified by the steady-state plasma glucose (SSPG) test, in which a higher value indicates relative resistance to insulin-mediated glucose uptake, ranged from 45 mg/dL to 335 mg/dL, reflecting great heterogeneity in the cohort. This measure was particularly variable among the normoglycemic and prediabetic group. Thirty subjects completed the standardized meal testing portion of the study. Characteristics of this cohort mirrored the original cohort: 20 females and 10 males, with age ranging from 25 to 65, of which 3 and 7 individuals were diagnosed with diabetes and prediabetes, respectively.

Glucose patterns and standardized meals

To better assess glucose variability among individuals, we next subjected a subset of the participants (30) to 3 standardized meals, which contain similar calories but vary in their amounts of proteins, fat, and fiber. Meals were consumed at breakfast, which is when participants had a stable baseline. The meals were cornflakes and milk (low fiber and high sugar), a peanut butter sandwich (higher fat and higher protein), and a PROBAR protein bar (moderate fat and protein. Each participant received the meal twice, and for each participant, good reproducibility was observed between replicates (0.5 and 0.4 average Pearson’s correlation coefficients between replicates and between individuals, respectively, p-value = 1e – 08, wilcoxon test).

Several types of meal responses were found in the cohort. The vast majority (60%) of the responses to milk/cereal were classified as severe variability, whereas the responses to the PROBAR protein bar and to bread and peanut butter varied among individuals. Importantly, 16 subjects who were classified as “normal” based on current clinical tests for diagnosing diabetes had glucose levels in the prediabetic (>140 mg/dL) or diabetic (>200 mg/dL) range after the consumption of 1 or more of the standardized meals. Additionally, 25 subjects had higher glycemic responses measured by CGM following mixed meals than the responses noted on the OGTT, even with similar carbohydrate loading.

Diabetes classification and variability frequency

In order to determine the clinical relevance of these glucotypes in relation to diabetes classification, we examined the frequency of these classes in comparison with diabetes diagnosis using the OGTT results. A principal component analysis was then used to separate participants by their ability to maintain glucose homeostasis as assessed by clinical glucose metabolic phenotypes and CGM metrics, such as mean amplitude of glycemic response. The first two components explained slightly over half of the variation in blood sugar control (51%). Glucose control decreases along both principal component one and principal component two, such that the nondiabetic participants are located in the lower-left corner. Many of those with prediabetes were already dominated by severely variable glycemic signatures, which would be expected of diabetic individuals. Furthermore, we observed that even participants clinically undiagnosed with diabetes or prediabetes can have glucose spikes in prediabetic or diabetic range according to the ADA thresholds . Indeed, normoglycemic patients classified as severe glucotype (24% of normoglycemic) can reach prediabetic glucose levels up to 15% of the duration of CGM recordings and diabetic glucose levels during 2% of the recordings. Thus, normoglycemic individuals can exhibit severe glucotypes with postprandial response similar or exceeding those of diabetics.

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