Researchers build tool that catches glucose ‘spikers’

By Naveed Saleh, MD, MS, for MDLinx
Published September 14, 2018

Key Takeaways

Normoglycemic individuals experience substantial glucose variability that peaks at prediabetic and diabetic levels, as measured by continuous glucose monitoring (CGM), according to a new study published in PLOS Biology.

“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,” wrote the authors, led by Heather Hall, PhD, Stanford University, Stanford, CA.

Type 2 diabetes is currently diagnosed via single-time-point measurements of serum glucose (ie, fasting blood samples) or average blood glucose levels during a period of 3 months (ie, Hb1AC). Both of these approaches fail to assess glucose fluctuations over time. Emerging research, however, has indicated that this condition is physiologically and genetically heterogeneous.

In the current study, researchers utilized CGM to assess the frequency and patterns of postprandial glucose elevations, as well as how patterns vary among patients administered identical nutrient challenges.

“Using our detailed clinical and CGM measurements, we developed models for glucose dysregulation at an individual level and related these patterns to standard measures of glucose intolerance and diabetes as well as clinical metabolic measures, including whole-body insulin resistance and insulin secretion,” the authors wrote.

The researchers recruited 57 participants without prior diabetes diagnosis (median age=51 years; 32 women). Of this sample, five patients met screening criteria for diabetes, 14 met criteria for prediabetes, and 38 patients were normoglycemic. The team monitored serum glucose in the normal environment by means of CGM and categorized patients into clinical phenotypes.

A subsample of 30 participants (20 women; 3 with diabetes; 7 with prediabetes) finished a standardized meal testing component of the study. Three types of breakfast were consumed:

  • Cornflakes with milk (low fiber/high sugar)
  • Peanut butter sandwich (high fat/high protein)
  • Protein bar (moderate fat/moderate protein).

Overall, the researchers analyzed nearly 500,000 CGM measurements among 57 participants and discovered substantial intra- and interpersonal variability. Notably, measurement of insulin resistance and secretion highlights the considerable variability underlying dysglycemia among individuals.

By spectral clustering, they characterized three glucotypes by increasing average glucose and increasing variability: low, moderate, and severe. These glucotypes accounted for 73% of the observed variance.

The proportion of time that participants spent in patterns of low and severe variability was associated with glycemia associated with diabetes risk. Nevertheless, the researchers observed all three glucotype patterns within standard classification categories based on fasting and 2-hour glucose or HbA1C, thus indicating that the status quo classification schemes are reductive.

For example, in 25% of normoglycemic individuals, drastic serum glucose variability was observed, with glucose levels reaching prediabetic levels 15% of the time and diabetic levels 2% of the time.

“We speculate that an increase in glucose variability might thus precede the currently used measures defining abnormal glucose levels and thus represent an even earlier stage of ‘prediabetes,’” the researchers wrote. “Longer-term studies are warranted to define whether identification of a ‘severe glucotype’ via CGM has greater predictive value for development of type 2 diabetes than do traditional tests.”

Of interest, the team found that cornflakes and milk yielded glucose elevation to the prediabetic range in 80% of study participants, thus suggesting that this food may be unhealthy for the majority of people.

Dr. Snyder and colleagues also developed a model for identifying potential mechanisms of glucose dysregulation and created a webtool for displaying a user-uploaded CGM profile and classifying personal glucose patterns into glucotypes.

"We were very surprised to see blood sugar in the prediabetic and diabetic range in these people so frequently,” said Michael Snyder, PhD, professor and chair of genetics at Stanford, and senior author of the study. "The idea is to try to find out what makes someone a ‘spiker’ and be able to give them actionable advice to shift them into the low glucotype."

This study was funded by the NIH.

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