SPINA-GR | |
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Reference range | 1.41–9.00 mol/s |
Calculator | https://doi.org/10.5281/zenodo.7479856 |
Purpose | Medical diagnosis, research |
Test of | Insulin sensitivity |
SPINA-GR is a calculated biomarker for insulin sensitivity. [1] [a] It represents insulin receptor gain.
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]
[I](∞): Fasting Insulin plasma concentration (μU/mL)
[G](∞): Fasting blood glucose concentration (mg/dL)
G1: Parameter for pharmacokinetics (154.93 s/L)
DR: EC50 of insulin at its receptor (1,6 nmol/L)
GE: Effector gain (50 s/mol)
P(∞): Constitutive endogenous glucose production (150 μmol/s)
Compared to healthy volunteers, SPINA-GR is significantly reduced in persons with prediabetes and diabetes mellitus, and it correlates with the M value in glucose clamp studies, triceps skinfold, subscapular skinfold and (better than HOMA-IR and QUICKI) with the two-hour value in oral glucose tolerance testing (OGTT), glucose rise in OGTT, waist-to-hip ratio, body fat content (measured via DXA) and the HbA1c fraction. [1]
Both in the FAST study, an observational case-control sequencing study including 300 persons from Germany, and in a large sample from the NHANES study, SPINA-GR differed more clearly between subjects with and without diabetes than the corresponding HOMA-IR, HOMA-IS and QUICKI indices. [3]
Together with the secretory capacity of pancreatic beta cells (SPINA-GBeta), SPINA-GR provides the foundation for the definition of a fasting based disposition index of insulin-glucose homeostasis (SPINA-DI). [3]
In combination with SPINA-GBeta and whole-exome sequencing, calculating SPINA-GR 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). [4]
In lean subjects it is significantly higher than in a population with obese persons. [1] In several populations, SPINA-GR 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. [3]
In a longitudinal evaluation of the NHANES study, a large sample of the general US population, over 10 years, reduced SPINA-DI, calculated as the product of SPINA-GBeta times SPINA-GR, significantly predicted all-cause mortality [5] .
Insulin resistance (IR) is a pathological condition in which cells in insulin-sensitive tissues in the body fail to respond normally to the hormone insulin or downregulate insulin receptors in response to hyperinsulinemia.
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The homeostatic model assessment (HOMA) is a method used to quantify insulin resistance and beta-cell function. It was first described under the name HOMA by Matthews et al. in 1985.
The quantitative insulin sensitivity check index (QUICKI) is derived using the inverse of the sum of the logarithms of the fasting insulin and fasting glucose:
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The Metabolic Score for Insulin Resistance (METS-IR) is a metabolic index developed with the aim to quantify peripheral insulin sensitivity in humans; it was first described under the name METS-IR by Bello-Chavolla et al. in 2018. It was developed by the Metabolic Research Disease Unit at the Instituto Nacional de Ciencias Médicas Salvador Zubirán and validated against the euglycemic hyperinsulinemic clamp and the frequently-sampled intravenous glucose tolerance test in Mexican population. It is a non-insulin-based alternative to insulin-based methods to quantify peripheral insulin sensitivity and an alternative to SPINA Carb, the Homeostatic Model Assessment (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI). METS-IR is currently validated for its use to assess cardio-metabolic risk in Latino population.
SPINA-GBeta is a calculated biomarker for pancreatic beta cell function. It represents the maximum amount of insulin that beta cells can produce per time-unit.
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