Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge
Plasma glucose and insulin responses following an oral glucose challenge are representative of glucose tolerance and insulin resistance, key indicators of type 2 diabetes mellitus pathophysiology. A large heterogeneity in individuals' challenge test responses has been shown to underlie the effe...
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| Veröffentlicht in: | PLoS computational biology 2021-03, Vol.17 (3), p.e1008852-e1008852 |
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| creator | Erdős, Balázs van Sloun, Bart Adriaens, Michiel E O'Donovan, Shauna D Langin, Dominique Astrup, Arne Blaak, Ellen E Arts, Ilja C W van Riel, Natal A W |
| description | Plasma glucose and insulin responses following an oral glucose challenge are representative of glucose tolerance and insulin resistance, key indicators of type 2 diabetes mellitus pathophysiology. A large heterogeneity in individuals' challenge test responses has been shown to underlie the effectiveness of lifestyle intervention. Currently, this heterogeneity is overlooked due to a lack of methods to quantify the interconnected dynamics in the glucose and insulin time-courses. Here, a physiology-based mathematical model of the human glucose-insulin system is personalized to elucidate the heterogeneity in individuals' responses using a large population of overweight/obese individuals (n = 738) from the DIOGenes study. The personalized models are derived from population level models through a systematic parameter selection pipeline that may be generalized to other biological systems. The resulting personalized models showed a 4-5 fold decrease in discrepancy between measurements and model simulation compared to population level. The estimated model parameters capture relevant features of individuals' metabolic health such as gastric emptying, endogenous insulin secretion and insulin dependent glucose disposal into tissues, with the latter also showing a significant association with the Insulinogenic index and the Matsuda insulin sensitivity index, respectively. |
| doi_str_mv | 10.1371/journal.pcbi.1008852 |
| format | Article |
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A large heterogeneity in individuals' challenge test responses has been shown to underlie the effectiveness of lifestyle intervention. Currently, this heterogeneity is overlooked due to a lack of methods to quantify the interconnected dynamics in the glucose and insulin time-courses. Here, a physiology-based mathematical model of the human glucose-insulin system is personalized to elucidate the heterogeneity in individuals' responses using a large population of overweight/obese individuals (n = 738) from the DIOGenes study. The personalized models are derived from population level models through a systematic parameter selection pipeline that may be generalized to other biological systems. The resulting personalized models showed a 4-5 fold decrease in discrepancy between measurements and model simulation compared to population level. 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| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central |
| subjects | Adult Biology and Life Sciences Blood Glucose - drug effects Blood Glucose - physiology Blood sugar Computer applications Customization Development and progression Diabetes Diabetes Mellitus, Type 2 - blood Diabetes Mellitus, Type 2 - metabolism Diabetes Mellitus, Type 2 - physiopathology Female Glucose Glucose - administration & dosage Glucose - metabolism Glucose - pharmacology Glucose tolerance Glucose Tolerance Test Health aspects Heterogeneity Homeostasis Humans Insulin Insulin resistance Insulin Resistance - physiology Intervention Male Medicine and Health Sciences Metabolism Metabolites Middle Aged Musculoskeletal system Parameter estimation Patient-Specific Modeling Physical Sciences Physiological aspects Physiology Plasma Population Postprandial Period - drug effects Postprandial Period - physiology Research and Analysis Methods Type 2 diabetes Values |
| title | Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T03%3A58%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Personalized%20computational%20model%20quantifies%20heterogeneity%20in%20postprandial%20responses%20to%20oral%20glucose%20challenge&rft.jtitle=PLoS%20computational%20biology&rft.au=Erd%C5%91s,%20Bal%C3%A1zs&rft.date=2021-03-31&rft.volume=17&rft.issue=3&rft.spage=e1008852&rft.epage=e1008852&rft.pages=e1008852-e1008852&rft.issn=1553-7358&rft.eissn=1553-7358&rft_id=info:doi/10.1371/journal.pcbi.1008852&rft_dat=%3Cgale_plos_%3EA658711614%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2513683898&rft_id=info:pmid/33788828&rft_galeid=A658711614&rft_doaj_id=oai_doaj_org_article_85352599a5ff40cbafd7a1b72f6e5ee7&rfr_iscdi=true |