Glucotypes reveal new patterns of glucose dysregulation
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 qua...
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| description | 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. |
| doi_str_mv | 10.1371/journal.pbio.2005143 |
| format | Article |
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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.</description><identifier>ISSN: 1545-7885</identifier><identifier>ISSN: 1544-9173</identifier><identifier>EISSN: 1545-7885</identifier><identifier>DOI: 10.1371/journal.pbio.2005143</identifier><identifier>PMID: 30040822</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Aged ; Biology and Life Sciences ; Blood glucose ; Blood Glucose - metabolism ; Blood Glucose Self-Monitoring ; Carbohydrate Metabolism ; Clustering ; Cohort Studies ; Consumption ; Dextrose ; Diabetes ; Diabetes mellitus ; Diabetes mellitus (non-insulin dependent) ; Diabetes Mellitus, Type 2 - blood ; Diabetes Mellitus, Type 2 - diagnosis ; Diagnostic systems ; Endocrinology ; Female ; Glucose ; Glucose monitoring ; Heterogeneity ; Homeostasis ; Humans ; Hyperglycemia ; Hyperglycemia - blood ; Hyperglycemia - diagnosis ; Insulin ; Insulin - metabolism ; Insulin resistance ; International conferences ; Internet ; Intervention ; Lifestyles ; Male ; Meals ; Medicine and Health Sciences ; Middle Aged ; Phenotyping ; Physiological aspects ; Physiology ; Public health ; Secretion ; Supervision ; Variability ; Visualization</subject><ispartof>PLoS biology, 2018-07, Vol.16 (7), p.e2005143</ispartof><rights>COPYRIGHT 2018 Public Library of Science</rights><rights>2018 Hall et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2018 Hall et al 2018 Hall et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c695t-e34f6b26e59e6b7df803a4c00f2019326eb09f1c07d7282ef81cf1c678ec9fee3</citedby><cites>FETCH-LOGICAL-c695t-e34f6b26e59e6b7df803a4c00f2019326eb09f1c07d7282ef81cf1c678ec9fee3</cites><orcidid>0000-0001-6464-6693</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6057684/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6057684/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30040822$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hall, Heather</creatorcontrib><creatorcontrib>Perelman, Dalia</creatorcontrib><creatorcontrib>Breschi, Alessandra</creatorcontrib><creatorcontrib>Limcaoco, Patricia</creatorcontrib><creatorcontrib>Kellogg, Ryan</creatorcontrib><creatorcontrib>McLaughlin, Tracey</creatorcontrib><creatorcontrib>Snyder, Michael</creatorcontrib><title>Glucotypes reveal new patterns of glucose dysregulation</title><title>PLoS biology</title><addtitle>PLoS Biol</addtitle><description>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. 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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.</description><subject>Adult</subject><subject>Aged</subject><subject>Biology and Life Sciences</subject><subject>Blood glucose</subject><subject>Blood Glucose - metabolism</subject><subject>Blood Glucose Self-Monitoring</subject><subject>Carbohydrate Metabolism</subject><subject>Clustering</subject><subject>Cohort Studies</subject><subject>Consumption</subject><subject>Dextrose</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Diabetes Mellitus, Type 2 - blood</subject><subject>Diabetes Mellitus, Type 2 - diagnosis</subject><subject>Diagnostic systems</subject><subject>Endocrinology</subject><subject>Female</subject><subject>Glucose</subject><subject>Glucose monitoring</subject><subject>Heterogeneity</subject><subject>Homeostasis</subject><subject>Humans</subject><subject>Hyperglycemia</subject><subject>Hyperglycemia - 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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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>30040822</pmid><doi>10.1371/journal.pbio.2005143</doi><orcidid>https://orcid.org/0000-0001-6464-6693</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adult Aged Biology and Life Sciences Blood glucose Blood Glucose - metabolism Blood Glucose Self-Monitoring Carbohydrate Metabolism Clustering Cohort Studies Consumption Dextrose Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 2 - blood Diabetes Mellitus, Type 2 - diagnosis Diagnostic systems Endocrinology Female Glucose Glucose monitoring Heterogeneity Homeostasis Humans Hyperglycemia Hyperglycemia - blood Hyperglycemia - diagnosis Insulin Insulin - metabolism Insulin resistance International conferences Internet Intervention Lifestyles Male Meals Medicine and Health Sciences Middle Aged Phenotyping Physiological aspects Physiology Public health Secretion Supervision Variability Visualization |
| title | Glucotypes reveal new patterns of glucose dysregulation |
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