Title: Surprising Breakthrough: 20% of Apparently Healthy Individuals Found to Exhibit Prediabetic Metabolism
Researchers at Klick Labs have introduced a groundbreaking analytical technique capable of identifying a precursor to prediabetes known as impaired glucose homeostasis (IGH) through continuous glucose monitor (CGM) data analysis. Astonishingly, this novel approach revealed that 20% of the study participants, initially classified as healthy, displayed glucose metabolism patterns resembling those with prediabetes. This discovery holds the potential to revolutionize early detection and management of diabetes.
Klick Labs, specializing in continuous glucose monitoring (CGM) data analysis, has developed a pioneering method for detecting early signs of Type 2 diabetes.
A team of scientists from Klick Labs has devised an innovative approach to identify early signs of the body’s inability to regulate blood sugar levels before reaching a prediabetic state.
Their research, published in Mayo Clinic Proceedings: Digital Health, unveils a new analytical process that identifies a stage prior to prediabetes, known as impaired glucose homeostasis (IGH). Utilizing their proprietary mathematical model on data collected from continuous glucose monitors (CGMs), the researchers discovered that approximately 20% of subjects, previously considered healthy by medical standards, exhibited a glucose metabolism pattern similar to individuals with prediabetes.
Jaycee Kaufman, the study’s lead author and a research scientist at Klick Labs, explained, “For people with diabetes, blood glucose levels can rise and fall like a wild roller-coaster ride with steep drops and peaks. We found a similar pattern in patients with IGH, albeit those patterns were more like gentle waves than dramatic peaks, but intervention on this population could limit the likelihood of progression to full diabetes.”
During the study, 384 participants wore a CGM for two weeks and were assessed by physicians. Based on guidelines from the American Diabetes Association, they were initially diagnosed as diabetic, prediabetic, or healthy. However, after applying the mathematical model, the patients were re-categorized into two groups based on their glucose homeostasis parameters: effective or impaired.
Yan Fossat, Vice President of Klick Labs, expressed surprise, stating, “What was most surprising is that 20 percent of participants, who were assessed using the standard screening tools for diabetes and cleared as healthy by a physician, were then found to have impaired glucose homeostasis—reinforcing it is now possible to provide an earlier, more accurate and sensitive assessment of people’s diabetic status.”
In the United States, about 34 million people have diabetes, and one in three Americans have prediabetes or diabetes. In Canada, approximately 11.7 million people are living with diabetes or prediabetes. Alarmingly, over 80% of individuals with prediabetes in the U.S. are unaware of their condition.
Given research suggesting the possibility of reversing or slowing diabetes progression, the demand for screening tools that can identify at-risk individuals is growing. Current screening and monitoring methods involve reviewing risk factors such as age, BMI, and family history, and diagnosis relies primarily on blood tests like glycated hemoglobin (HbA1c) and Oral Glucose Tolerance Test (OGTT).
Fossat emphasized the significance of their new analysis method, stating, “This new method of analysis is a major step forward in the prevention and management of diabetes. Early detection and intervention are critical in the management of Type 2 diabetes, so our method has the potential to have a significant impact on the lives of millions of people worldwide.”
The study received funding from Mitacs.
These findings are the latest in Klick’s ongoing work in the diabetes space. Their previous study, “Homeostasis as a proportional–integral control system,” published in Nature Digital Medicine in 2020, also utilized mathematical modeling to uncover some of the underlying changes in how glucose is regulated. This research was conducted in collaboration with Ontario Tech University, Lennaert van Veen, Professor of Mathematics in the Faculty of Science, and partially funded by a Mitacs grant.
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Frequently Asked Questions (FAQs) about early diabetes detection
Q: What did the researchers at Klick Labs unveil?
A: The researchers at Klick Labs unveiled a new analytical method capable of detecting impaired glucose homeostasis (IGH), a precursor to prediabetes, by analyzing data from continuous glucose monitors. This breakthrough technique identified 20% of apparently healthy study participants as having glucose metabolism similar to individuals with prediabetes, which could lead to improved early detection and management of diabetes.
Q: How does the new analytical process work?
A: The new analytical process developed by Klick Labs utilizes a proprietary mathematical model on data gathered from continuous glucose monitors (CGMs). The scientists identified a stage called impaired glucose homeostasis (IGH), which occurs before prediabetes, and applied the model to classify participants’ glucose homeostasis parameters as either effective or impaired. This process allowed them to identify individuals with early signs of diabetes, even among those initially classified as healthy by standard screening tools.
Q: What implications does the study’s finding have?
A: The study’s finding has significant implications for diabetes prevention and management. By identifying individuals with impaired glucose homeostasis at an earlier stage, healthcare professionals can intervene to limit the likelihood of progression to full diabetes. Early detection and intervention are crucial in managing Type 2 diabetes, and this new analytical method has the potential to positively impact the lives of millions of people worldwide.
Q: How many participants were involved in the study, and what were the criteria for their classification?
A: The study involved 384 participants who wore continuous glucose monitors (CGMs) for a two-week period. Initially, the participants were diagnosed as diabetic, prediabetic, or healthy based on guidelines outlined by the American Diabetes Association. After applying the mathematical model developed by Klick Labs, the participants were re-classified into two groups based on their glucose homeostasis parameters: effective or impaired.
Q: How common is diabetes and prediabetes in the United States and Canada?
A: In the United States, approximately 34 million people have diabetes, and one in three Americans have prediabetes or diabetes. In Canada, there are about 11.7 million individuals living with diabetes or prediabetes. Alarmingly, more than 80% of those with prediabetes in the U.S. are unaware of their condition, highlighting the importance of improved screening tools and early detection methods.
Q: What are the current methods for diabetes screening and monitoring?
A: Currently, diabetes screening and monitoring involve reviewing risk factors such as age, BMI, and family history. Diagnosis primarily relies on blood tests like glycated hemoglobin (HbA1c) and Oral Glucose Tolerance Test (OGTT). However, the new analytical process developed by Klick Labs offers a more accurate and sensitive assessment of diabetic status, providing an early detection method beyond the standard screening tools.
Q: How was the research funded?
A: The research conducted by Klick Labs was funded by Mitacs, which supported their groundbreaking work in diabetes detection and management. This funding allowed the researchers to develop and apply their proprietary mathematical model and contribute to advancements in the field of diabetes research.
Q: What other work has Klick Labs done in the field of diabetes research?
A: In addition to this recent study, Klick Labs has been actively engaged in diabetes research. Their previous study, “Homeostasis as a proportional–integral control system,” published in Nature Digital Medicine in 2020, utilized mathematical modeling to uncover underlying changes in how glucose is regulated. This research was conducted in collaboration with Ontario Tech University and Professor Lennaert van Veen, and it was also supported in part by a Mitacs grant.
More about early diabetes detection
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Mayo Clinic Proceedings: Digital Health – The research study on impaired glucose homeostasis (IGH) was published in this journal, providing in-depth details of the new analytical process.
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Nature Digital Medicine – This journal published Klick Labs’ previous study, “Homeostasis as a proportional–integral control system,” which delved into understanding changes in glucose regulation through mathematical modeling.
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American Diabetes Association – This organization provides guidelines and resources for diabetes screening, diagnosis, and management, as well as raising awareness about diabetes and prediabetes.
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Mitacs – The research conducted by Klick Labs was funded by Mitacs, an organization that supports various research projects and collaborations.
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Continuous Glucose Monitoring (CGM) – This link provides information about continuous glucose monitoring, which was utilized by Klick Labs in their research for detecting early indications of diabetes.
