SPINA-GBeta
| SPINA-GBeta | |
|---|---|
| Reference range | 0.64–3.73 pmol/s |
| Calculator | https://doi.org/10.5281/zenodo.7479856 |
| Purpose | Medical diagnosis, research |
| Test of | Pancreatic beta cell function |
SPINA-GBeta is a calculated biomarker for pancreatic beta cell function.[1][a] It represents the maximum amount of insulin that beta cells can produce per time-unit (e.g. in one second).
How to determine GBeta
[edit]The index is derived from a mathematical model of insulin-glucose homeostasis.[2] For diagnostic purposes, it is calculated from fasting insulin and glucose concentrations with:
.[1]
({D}_{\beta }+\left[G\right](\infty ))}{{G}_{3}[G](\infty )}}}](https://wikimedia.riteme.site/api/rest_v1/media/math/render/svg/f2f50477c6037130824999c266a2e0f28baa0099)
[I](∞): Fasting Insulin plasma concentration (μU/mL)
[G](∞): Fasting blood glucose concentration (mg/dL)
Dβ: EC50 for glucose at beta cells (7 mmol/L)
G3: Parameter for pharmacokinetics (58,8 s/L)
Clinical significance
[edit]Validity
[edit]SPINA-GBeta significantly correlates with the M value in glucose clamp studies and (better than HOMA-Beta) with the two-hour value in oral glucose tolerance testing (OGTT), glucose rise in OGTT, subscapular skinfold, truncal fat content and the HbA1c fraction.[1]
It has the additional advantage that it circumvents the HOMA-blind zone, which renders the calculation of HOMA-Beta impossible if the fasting glucose concentration is 3.5 mmol/L (63 mg/dL) or below.[3] Unlike HOMA-Beta, SPINA-Beta can be sensibly calculated in the whole range of measurements.[1]
Reliability
[edit]In repeated measurements, SPINA-GBeta had higher retest reliability than HOMA-Beta, a measurement for beta cell function from the homeostasis model assessment.[1][4]
Clinical utility
[edit]In the FAST study, an observational case-control sequencing study including 300 persons from Germany, SPINA-GBeta differed more clearly between subjects with and without diabetes than the corresponding HOMA-Beta index.[4]
Scientific implications and other uses
[edit]Together with the reconstructed insulin receptor gain (SPINA-GR), SPINA-GBeta provides the foundation for the definition of a fasting based disposition index of insulin-glucose homeostasis (SPINA-DI).[4]
In combination with SPINA-GR and whole-exome sequencing, calculating SPINA-GBeta helped to identify a new form of monogenetic diabetes (MODY) that is characterised by primary insulin resistance and results from a missense variant of the type 2 ryanodine receptor (RyR2) gene (p.N2291D).[5]
Pathophysiological implications
[edit]In several populations, SPINA-GBeta correlated with the area under the glucose curve and 2-hour concentrations of glucose, insulin and proinsulin in oral glucose tolerance testing, concentrations of free fatty acids, ghrelin and adiponectin, and the HbA1c fraction.[4]
Predictive aspects
[edit]In a longitudinal evaluation of the NHANES study, a large sample of the general US population, over 10 years, reduced SPINA-GBeta significantly predicted all-cause mortality[6].
See also
[edit]Notes
[edit]- ^ SPINA is an acronym for "structure parameter inference approach".
References
[edit]- ^ a b c d e Dietrich, JW; Dasgupta, R; Anoop, S; Jebasingh, F; Kurian, ME; Inbakumari, M; Boehm, BO; Thomas, N (21 October 2022). "SPINA Carb: a simple mathematical model supporting fast in-vivo estimation of insulin sensitivity and beta cell function". Scientific Reports. 12 (1): 17659. Bibcode:2022NatSR..1217659D. doi:10.1038/s41598-022-22531-3. PMC 9587026. PMID 36271244.
- ^ Dietrich, Johannes W.; Böhm, Bernhard (27 August 2015). "Die MiMe-NoCoDI-Plattform: Ein Ansatz für die Modellierung biologischer Regelkreise". GMDS 2015; 60. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik: Biometrie und Epidemiologie e.V. (GMDS). doi:10.3205/15gmds058.
- ^ Cersosimo, E; Solis-Herrera, C; Trautmann, ME; Malloy, J; Triplitt, CL (January 2014). "Assessment of pancreatic β-cell function: review of methods and clinical applications". Current Diabetes Reviews. 10 (1): 2–42. doi:10.2174/1573399810666140214093600. PMC 3982570. PMID 24524730.
- ^ a b c d Dietrich, Johannes W.; Abood, Assjana; Dasgupta, Riddhi; Anoop, Shajith; Jebasingh, Felix K.; Spurgeon, R.; Thomas, Nihal; Boehm, Bernhard O. (2 January 2024). "A novel simple disposition index ( SPINA-DI ) from fasting insulin and glucose concentration as a robust measure of carbohydrate homeostasis". Journal of Diabetes. 16 (9): e13525. doi:10.1111/1753-0407.13525. PMC 11418405. PMID 38169110. S2CID 266752689.
- ^ Bansal, Vikas; Winkelmann, Bernhard R.; Dietrich, Johannes W.; Boehm, Bernhard O. (20 February 2024). "Whole-exome sequencing in familial type 2 diabetes identifies an atypical missense variant in the RyR2 gene". Frontiers in Endocrinology. 15. doi:10.3389/fendo.2024.1258982. PMC 10913019. PMID 38444585.
- ^ Dietrich, Johannes W. (2024). "P4-Endokrinologie – Kybernetische Perspektiven eines neuen Ansatzes" (PDF). Leibniz Online. 54. doi:10.53201/LEIBNIZONLINE54.