{ "abstract": "Prediabetes, a subclinical state of high glucose, carries a risk of transitioning to diabetes. One cause of prediabetes is insulin resistance, which impairs the ability of insulin to control blood glucose. However, many individuals with high insulin resistance retain normal glucose due to compensation by enhanced insulin secretion by beta cells. Individuals seem to differ in their maximum compensation level, termed beta cell carrying capacity, such that low carrying capacity is associated with a higher risk of prediabetes and diabetes. Carrying capacity has not been quantified using a mathematical model and at present cannot be estimated from measured glucose and insulin levels in patients, unlike insulin resistance and beta cell function which can be estimated using HOMA-IR and HOMA-B formula. Here we present a mathematical model of beta cell compensation and carrying capacity, and develop a new formula called HOMA-C to estimate it from glucose and insulin measurements. HOMA-C estimates the maximal potential beta cell function of an individual, rather than the current beta cell function. It uses prediabetes as a stress and estimates carrying capacity using the gap between secreted insulin and the needed amount of insulin for homeostasis. We test this approach using longitudinal cohorts of prediabetic people, finding 10-fold variation in carrying capacity. Low HOMA-C associates with higher risk of transitioning to diabetes in a one-year follow up. The interpretation of HOMA-C as a carrying capacity relies on a mathematical model and requires further experimental testing. Quantification of beta cell carrying capacity may help to better understand this understudied risk factor for diabetes. Author summary: Prediabetes is a common condition of elevated glucose. Many patients with prediabetes transition into type 2 diabetes, and it is difficult to predict who will transition. One major risk factor is thought to be an inability of beta cells to compensate for deterioration of other physiological parameters, especially insulin sensitivity. The limit for this compensation, in terms of beta cell functional mass, is called beta cell carrying capacity, but there is no way currently to estimate a person’s carrying capacity. Here we use mathematical modeling and a prediabetes longitudinal cohort to develop a method to estimate carrying capacity using fasting insulin and glucose lab tests. This method offers a way for researchers to study the underexplored risk factor of low beta cell carrying capacity, with the aim of preventing the transition to type 2 diabetes. We note that further experimental testing is required to understand HOMA-C and its distinction from HOMA-B.", "abstract_shown": true, "affiliations": [ "Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel", "Unité de Chronobiologie théorique, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium", "Department of Computer Sciences and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel", "Division of Maternal Fetal Medicine, Helen Schneider Women’s Hospital, Rabin Medical Center, Petah Tikva, Israel", "Jesse and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center, Petah Tikva, Israel", "Faculty of Medicine and Health Sciences, Tel Aviv University, Tel Aviv, Israel" ], "article_type": "Research Article", "arxiv": null, "author_total": 12, "authors": [ { "affs": [ 0 ], "name": "Aurore Woller" }, { "affs": [ 1 ], "name": "Yuval Tamir" }, { "affs": [ 2 ], "name": "Alon Bar" }, { "affs": [ 3 ], "name": "Avi Mayo" }, { "affs": [ 4 ], "name": "Michal Rein" }, { "affs": [ 5 ], "name": "Anastasia Godneva" }, { "name": "Netta Mendelson Cohen" }, { "name": "Eran Segal" }, { "name": "Yoel Toledano" }, { "name": "Smadar Shilo" }, { "name": "Didier Gonze" }, { "name": "Uri Alon" } ], "bibtex": "https://research.draconitic.com/paper/92hbx8fst0kxd.bib", "cited_by": 5, "doi": "10.1371/journal.pcbi.1014589", "fulltext_url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014589", "id": "92hbx8fst0kxd", "issns": [ "1553-7358" ], "landing_url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014589", "language": null, "licence": "CC-BY-4.0", "licence_label": "CC BY 4.0", "licence_source": "journal", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "openalex", "2746|Pancreatic function and diabetes" ], [ "plos", "/Biology and life sciences/Biochemistry/Hormones/Insulin" ], [ "plos", "/Biology and life sciences/Ecology/Ecological metrics/Carrying capacity" ], [ "plos", "/Biology and life sciences/Physiology/Endocrine physiology/Insulin resistance" ], [ "plos", "/Biology and life sciences/Physiology/Physiological parameters/Body weight/Obesity" ], [ "plos", "/Biology and life sciences/Population biology/Population metrics/Carrying capacity" ], [ "plos", "/Ecology and environmental sciences/Ecology/Ecological metrics/Carrying capacity" ], [ "plos", "/Medicine and health sciences/Endocrinology/Diabetic endocrinology/Insulin" ], [ "plos", "/Medicine and health sciences/Endocrinology/Endocrine disorders/Diabetes mellitus" ], [ "plos", "/Medicine and health sciences/Endocrinology/Endocrine physiology/Insulin resistance" ], [ "plos", "/Medicine and health sciences/Epidemiology/Medical risk factors" ], [ "plos", "/Medicine and health sciences/Medical conditions/Metabolic disorders/Diabetes mellitus" ], [ "plos", "/Physical sciences/Chemistry/Chemical compounds/Organic compounds/Carbohydrates/Monosaccharides/Glucose" ], [ "plos", "/Physical sciences/Chemistry/Organic chemistry/Organic compounds/Carbohydrates/Monosaccharides/Glucose" ], [ "plos", "/Research and analysis methods/Mathematical and statistical techniques/Mathematical models" ] ], "openalex": "W7213347431", "pdf_url": "https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1014589&type=printable", "pmcid": null, "pmid": null, "published": "2026-09-15", "publisher": "Public Library of Science", "ris": "https://research.draconitic.com/paper/92hbx8fst0kxd.ris", "sources": [ { "first_seen": "2026-10-30T12:17:49Z", "native_id": "10.1371/journal.pcbi.1014589", "source": "plos", "url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014589" } ], "subjects": [ { "field": "biology", "origin": "plos:ecology", "subfield": "ecology" }, { "field": "medicine", "origin": "plos:endocrinology", "subfield": "endocrinology-metabolism" }, { "field": "medicine", "origin": "plos:physiology", "subfield": "physiology" } ], "title": "Quantification of beta-cell carrying capacity in prediabetes", "title_text": "Quantification of beta-cell carrying capacity in prediabetes", "type": "peer-reviewed", "updated_at": "2026-10-30T12:17:49Z", "url": "https://research.draconitic.com/paper/92hbx8fst0kxd", "venue": "PLOS Computational Biology", "versions": [] }