FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Animals (Basel) / Development of a Web App to Convert Blood Insulin Concentrat...
Animals : an open access journal from MDPI2023; 13(17); 2704; doi: 10.3390/ani13172704

Development of a Web App to Convert Blood Insulin Concentrations among Various Immunoassays Used in Horses.

Abstract: The measurement of the blood insulin concentration, and comparison to cut-offs, is essential in diagnosing insulin dysregulation, a common equine endocrinopathy. However, different insulin assays provide disparate results. We aimed to ease comparison between assays by compiling original and published data into a web app to convert insulin measurements from one assay to another. Data were available for ADVIA Centaur insulin chemiluminescent immunoassay (CLIA), Beckman Coulter insulin radioimmunoassay (RIA), Immulite 1000 CLIA, Immulite 2000 CLIA, Immulite 2000 XPi CLIA, Mercodia equine insulin enzyme-linked immunosorbent assay (ELISA), and Millipore porcine insulin RIA. Linear models were fitted for 13 assay pairs using non-decreasing splines, and integrated into this app. Assay comparisons including data from several studies showed a lower performance. This indicates technical variation between laboratories, which has not been described before, but is relevant when diagnostic measurements and cut-offs are provided by different laboratories. Nevertheless, the models' overall high performance (median = 0.94; range 0.57-1.00) supports their use to interpret results from diagnostic insulin measurements when the reference assay is unavailable, and to compare values obtained from different assays.
Get Full Text
Publication Date: 2023-08-24 PubMed ID: 37684968PubMed Central: PMC10487020DOI: 10.3390/ani13172704Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research revolves around the creation of a web application designed to convert various insulin measurement metrics from different immunoassays, specifically for horse blood insulin concentrations. The web application is a solution to resolve discrepancies in blood insulin measurements from different tests and to streamline diagnosis of insulin dysregulation in horses.

Background and Aim

  • The study commences with the importance of accurately measuring blood insulin concentration in horses for diagnosing insulin dysregulation, a recognized equine endocrine disorder.
  • However, it notes that different types of insulin assays often provide varied results, posing a challenge for accurate diagnosis.
  • In response to this issue, the research aims to develop a web application that can convert insulin measurements from one type of assay to another, effectively allowing for straightforward comparisons.

Methodology

  • The researchers compiled original and previously published data relevant to several commonly used assays. This included the ADVIA Centaur insulin chemiluminescent immunoassay (CLIA), Beckman Coulter insulin radioimmunoassay (RIA), Immulite 1000 CLIA, Immulite 2000 CLIA, Immulite 2000 XPi CLIA, Mercodia equine insulin enzyme-linked immunosorbent assay (ELISA), and Millipore porcine insulin RIA.
  • The data collected was then used to create linear models for 13 different assay pairings using non-decreasing splines. These models were then integrated into the web application.

Results and Findings

  • The study found some variations in performance when assay data from different studies were compared. This highlighted previously unexplained technical variations between laboratories, which could significantly impact diagnosis if measurements and cut-offs provided by these different laboratories were to be compared.
  • Despite such variations, the models’ largely high performance rates (median = 0.94; range 0.57-1.00) suggest that they may be employed to interpret results from different insulin measurement tests, especially when the reference assay is not available.
  • The models in the application can also facilitate the comparison of blood insulin concentration levels obtained from different assays. Thus, the application can contribute to more accurate and consistent diagnoses of insulin dysregulation in horses.

Cite This Article

APA
Delarocque J, Feige K, Carslake HB, Durham AE, Fey K, Warnken T. (2023). Development of a Web App to Convert Blood Insulin Concentrations among Various Immunoassays Used in Horses. Animals (Basel), 13(17), 2704. https://doi.org/10.3390/ani13172704

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 13
Issue: 17
PII: 2704

Researcher Affiliations

Delarocque, Julien
  • Clinic for Horses, University of Veterinary Medicine Hannover, Foundation, Bünteweg 9, 30559 Hannover, Germany.
Feige, Karsten
  • Clinic for Horses, University of Veterinary Medicine Hannover, Foundation, Bünteweg 9, 30559 Hannover, Germany.
Carslake, Harry B
  • Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst, Neston CH64 7TE, Cheshire, UK.
Durham, Andy E
  • The Liphook Equine Hospital, Forest Mere, Liphook GU30 7JG, Hampshire, UK.
Fey, Kerstin
  • Equine Clinic, Internal Medicine, Faculty of Veterinary Medicine, Justus-Liebig-University of Giessen, Frankfurter Str. 126, 35392 Giessen, Germany.
Warnken, Tobias
  • Clinic for Horses, University of Veterinary Medicine Hannover, Foundation, Bünteweg 9, 30559 Hannover, Germany.

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 51 references
  1. Frank N, Tadros E.M. Insulin Dysregulation. Equine Vet. J. 2014;46:103–112.
    doi: 10.1111/evj.12169pubmed: 24033478google scholar: lookup
  2. Asplin K.E, Sillence M.N, Pollitt C.C, McGowan C.M. Induction of Laminitis by Prolonged Hyperinsulinaemia in Clinically Normal Ponies. Vet. J. 2007;174:530–535.
    doi: 10.1016/j.tvjl.2007.07.003pubmed: 17719811google scholar: lookup
  3. Bailey S.R, Habershon-Butcher J.L, Ransom K.J, Elliott J, Menzies-Gow N.J. Hypertension and Insulin Resistance in a Mixed-Breed Population of Ponies Predisposed to Laminitis. Am. J. Vet. Res. 2008;69:122–129.
    doi: 10.2460/ajvr.69.1.122pubmed: 18167097google scholar: lookup
  4. Luthersson N, Mannfalk M, Parkin T.D.H, Harris P. Laminitis: Risk Factors and Outcome in a Group of Danish Horses. J. Equine Vet. Sci. 2017;53:68–73.
    doi: 10.1016/j.jevs.2016.03.006google scholar: lookup
  5. Karikoski N.P, Horn I, McGowan T.W, McGowan C.M. The Prevalence of Endocrinopathic Laminitis among Horses Presented for Laminitis at a First-Opinion/Referral Equine Hospital. Domest. Anim. Endocrinol. 2011;41:111–117.
    doi: 10.1016/j.domaniend.2011.05.004pubmed: 21696910google scholar: lookup
  6. Durham A.E, Frank N, McGowan C.M, Menzies-Gow N.J, Roelfsema E, Vervuert I, Feige K, Fey K. ECEIM Consensus Statement on Equine Metabolic Syndrome. J. Vet. Intern. Med. 2019;33:335–349.
    doi: 10.1111/jvim.15423pmc: PMC6430910pubmed: 30724412google scholar: lookup
  7. Bertin F.R, de Laat M.A. The Diagnosis of Equine Insulin Dysregulation. Equine Vet. J. 2017;49:570–576.
    doi: 10.1111/evj.12703pubmed: 28543410google scholar: lookup
  8. Lindåse S, Nostell K, Askerfelt I, Bröjer J. A Modified Oral Sugar Test for Evaluation of Insulin and Glucose Dynamics in Horses. Acta Vet. Scand. 2015;57:55–63.
    doi: 10.1186/1751-0147-57-S1-O4pmc: PMC5073908pubmed: 27766982google scholar: lookup
  9. Smith S, Harris P.A, Menzies-Gow N.J. Comparison of the In-Feed Glucose Test and the Oral Sugar Test. Equine Vet. J. 2016;48:224–227.
    doi: 10.1111/evj.12413pubmed: 25582152google scholar: lookup
  10. Dunbar L.K, Mielnicki K.A, Dembek K.A, Toribio R.E, Burns T.A. Evaluation of Four Diagnostic Tests for Insulin Dysregulation in Adult Light-Breed Horses. J. Vet. Intern. Med. 2016;30:885–891.
    doi: 10.1111/jvim.13934pmc: PMC4913564pubmed: 27013065google scholar: lookup
  11. Jocelyn N.A, Harris P.A, Menzies-Gow N.J. Effect of Varying the Dose of Corn Syrup on the Insulin and Glucose Response to the Oral Sugar Test. Equine Vet. J. 2018;50:836–841.
    doi: 10.1111/evj.12826pubmed: 29504630google scholar: lookup
  12. Warnken T, Delarocque J, Schumacher S, Huber K, Feige K. Retrospective Analysis of Insulin Responses to Standard Dosed Oral Glucose Tests (OGTs) via Naso-Gastric Tubing towards Definition of an Objective Cut-off Value. Acta Vet. Scand. 2018;60:4.
    doi: 10.1186/s13028-018-0358-8pmc: PMC5775575pubmed: 29351765google scholar: lookup
  13. Van Den Wollenberg L, Vandendriessche V, van Maanen K, Counotte G.H.M. Comparison of Two Diagnostic Methods to Detect Insulin Dysregulation in Horses Under Field Conditions. J. Equine Vet. Sci. 2020;88:102954.
    doi: 10.1016/j.jevs.2020.102954pubmed: 32303301google scholar: lookup
  14. Frank N, Bailey S, Bertin F.-R, Burns T, de Laat M, Durham A, Kritchevsky J, Menzies-Gow N. Recommendations for the Diagnosis and Treatment of Equine Metabolic Syndrome (EMS). Equine Endocrinol. Group 2022.
  15. Öberg J, Bröjer J, Wattle O, Lilliehöök I. Evaluation of an Equine-Optimized Enzyme-Linked Immunosorbent Assay for Serum Insulin Measurement and Stability Study of Equine Serum Insulin. Comp. Clin. Path. 2011;21:1291–1300.
    doi: 10.1007/s00580-011-1284-6google scholar: lookup
  16. Tinworth K.D, Wynn P.C, Boston R.C, Harris P.A, Sillence M.N, Thevis M, Thomas A, Noble G.K. Evaluation of Commercially Available Assays for the Measurement of Equine Insulin. Domest. Anim. Endocrinol. 2011;41:81–90.
    doi: 10.1016/j.domaniend.2011.05.001pubmed: 21741576google scholar: lookup
  17. Borer-Weir K.E, Bailey S.R, Menzies-Gow N.J, Harris P.A, Elliott J. Evaluation of a Commercially Available Radioimmunoassay and Species-Specific ELISAs for Measurement of High Concentrations of Insulin in Equine Serum. Am. J. Vet. Res. 2012;73:1596–1602.
    doi: 10.2460/ajvr.73.10.1596pubmed: 23013186google scholar: lookup
  18. Banse H.E, McCann J, Yang F, Wagg C, McFarlane D. Comparison of Two Methods for Measurement of Equine Insulin. J. Vet. Diagn. Investig. 2014;26:527–530.
    doi: 10.1177/1040638714536560pubmed: 24928598google scholar: lookup
  19. Warnken T, Huber K, Feige K. Comparison of Three Different Methods for the Quantification of Equine Insulin. BMC Vet. Res. 2016;12:196.
    doi: 10.1186/s12917-016-0828-zpmc: PMC5016943pubmed: 27613127google scholar: lookup
  20. Carslake H.B, Pinchbeck G.L, McGowan C.M. Evaluation of a Chemiluminescent Immunoassay for Measurement of Equine Insulin. J. Vet. Intern. Med. 2017;31:568–574.
    doi: 10.1111/jvim.14657pmc: PMC5354037pubmed: 28124389google scholar: lookup
  21. Ho E.N.M, Wan T.S.M, Wong A.S.Y, Lam K.K.H, Stewart B.D. Doping Control Analysis of Insulin and Its Analogues in Equine Plasma by Liquid Chromatography—Tandem Mass Spectrometry. J. Chromatogr. A. 2008;1201:183–190.
    doi: 10.1016/j.chroma.2008.04.060pubmed: 18501368google scholar: lookup
  22. . NIBSC—Products—Insulin. .
  23. Robbins D.C, Andersen L, Bowsher R, Chance R, Dinesen B, Frank B, Gingerich R, Goldstein D, Widemeyer H.-M, Haffner S. Report of the American Diabetes Association’s Task Force on Standardization of the Insulin Assay. Diabetes 1996;45:242–256.
    doi: 10.2337/diab.45.2.242pubmed: 8549870google scholar: lookup
  24. Staten M.A, Stern M.P, Miller W.G, Steffes M.W, Campbell S.E. Insulin Assay Standardization. Diabetes Care 2010;33:205–206.
    doi: 10.2337/dc09-1206pmc: PMC2797975pubmed: 20040676google scholar: lookup
  25. Hörber S, Achenbach P, Schleicher E, Peter A. Harmonization of Immunoassays for Biomarkers in Diabetes Mellitus. Biotechnol. Adv. 2020;39:107359.
    doi: 10.1016/j.biotechadv.2019.02.015pubmed: 30802485google scholar: lookup
  26. Carslake H.B, Pinchbeck G.L, McGowan C.M. Equine Metabolic Syndrome in UK Native Ponies and Cobs Is Highly Prevalent with Modifiable Risk Factors. Equine Vet. J. 2021;53:923–934.
    doi: 10.1111/evj.13378pmc: PMC8451835pubmed: 33128277google scholar: lookup
  27. R Core Team. R: A Language and Environment for Statistical Computing. 2023.
  28. Mullen K.M, van Stokkum I.H.M. Nnls: The Lawson-Hanson Algorithm for Non-Negative Least Squares (NNLS). 2012.
  29. Wang W, Yan J. Shape-Restricted Regression Splines with R Package. J. Data Sci. 2021;19:498–517.
    doi: 10.6339/21-JDS1020google scholar: lookup
  30. ECMA International. ECMA-262–ECMAScript® 2022 Language Specification. 2022.
  31. World Wide Web Consortium. HTML 5.3. 2023.
  32. World Wide Web Consortium. CSS Snapshot 2023. 2023.
  33. The Apache Software Foundation. Apache License. 2004.
  34. de Laat M.A, Warnken T, Delarocque J, Reiche D.B, Grob A.J, Feige K, Carslake H.B, Durham A.E, Sillence M.N, Thane K.E. Carbohydrate Pellets to Assess Insulin Dysregulation in Horses. J. Vet. Intern. Med. 2022;37:302–314.
    doi: 10.1111/jvim.16621pmc: PMC9889680pubmed: 36583553google scholar: lookup
  35. Lindåse S, Nostell K, Bergsten P, Forslund A, Bröjer J. Evaluation of Fasting Plasma Insulin and Proxy Measurements to Assess Insulin Sensitivity in Horses. BMC Vet. Res. 2021;17:78.
    doi: 10.1186/s12917-021-02781-5pmc: PMC7885592pubmed: 33588833google scholar: lookup
  36. Olley R.B, Carslake H.B, Ireland J.L, McGowan C.M. Comparison of Fasted Basal Insulin with the Combined Glucose-Insulin Test in Horses and Ponies with Suspected Insulin Dysregulation. Vet. J. 2019;252:105351.
    doi: 10.1016/J.TVJL.2019.105351pubmed: 31554591google scholar: lookup
  37. Menzies-Gow N.J, Harris P.A, Elliott J. Prospective Cohort Study Evaluating Risk Factors for the Development of Pasture-Associated Laminitis in the United Kingdom. Equine Vet. J. 2017;49:300–306.
    doi: 10.1111/evj.12606pubmed: 27363591google scholar: lookup
  38. Meier A.D, de Laat M.A, Reiche D.B, Pollitt C.C, Walsh D.M, McGree J.M, Sillence M.N. The Oral Glucose Test Predicts Laminitis Risk in Ponies Fed a Diet High in Nonstructural Carbohydrates. Domest. Anim. Endocrinol. 2018;63:1–9.
    doi: 10.1016/j.domaniend.2017.10.008pubmed: 29172109google scholar: lookup
  39. Carter R.A, Treiber K.H, Geor R.J, Douglass L, Harris P.A. Prediction of Incipient Pasture-Associated Laminitis from Hyperinsulinaemia, Hyperleptinaemia and Generalised and Localised Obesity in a Cohort of Ponies. Equine Vet. J. 2009;41:171–178.
    doi: 10.2746/042516408X342975pubmed: 19418747google scholar: lookup
  40. Frank N, Bailey S.R, Bertin F.R, de Laat M.A, Durham A.E, Kritchevsky J, Menzies-Gow N. Recommendations for the Diagnosis and Treatment of Equine Metabolic Syndrome (EMS). Equine Endocrinol. Group 2020.
  41. Köller G, Bassewitz K, Schusser G.F. Referenzbereiche von Insulin, Insulinähnlichem Wachstumsfaktor 1 (IGF-1) Und Adrenokortikotropem Hormon Bei Ponys. Tierarztl. Prax. Ausg. G Grosstiere—Nutztiere 2016;44:19–25.
    doi: 10.15653/TPG-150428pubmed: 26758970google scholar: lookup
  42. Fitzgerald D.M, Walsh D.M, Sillence M.N, Pollitt C.C, de Laat M.A. Insulin and Incretin Responses to Grazing in Insulin-Dysregulated and Healthy Ponies. J. Vet. Intern. Med. 2018;33:225–232.
    doi: 10.1111/jvim.15363pmc: PMC6335545pubmed: 30506731google scholar: lookup
  43. Hart K.A, Wochele D.M, Norton N.A, Mcfarlane D, Wooldridge A.A, Frank N. Effect of Age, Season, Body Condition, and Endocrine Status on Serum Free Cortisol Fraction and Insulin Concentration in Horses. J. Vet. Intern. Med. 2016;30:653–663.
    doi: 10.1111/jvim.13839pmc: PMC4913614pubmed: 26860336google scholar: lookup
  44. Rapson J.L, Schott H.C, Nielsen B.D, McCutcheon L.J, Harris P.A, Geor R.J. Effects of Age and Diet on Glucose and Insulin Dynamics in the Horse. Equine Vet. J. 2018;50:690–696.
    doi: 10.1111/evj.12812pubmed: 29356053google scholar: lookup
  45. Morgan R.A, McGowan T.W, Mcgowan C.M. Prevalence and Risk Factors for Hyperinsulinaemia in Ponies in Queensland, Australia. Aust. Vet. J. 2014;92:101–106.
    doi: 10.1111/avj.12159pubmed: 24673135google scholar: lookup
  46. Nielsen B.D, O’Connor-Robison C.I, Spooner H.S, Shelton J. Glycemic and Insulinemic Responses Are Affected by Age of Horse and Method of Feed Processing. J. Equine Vet. Sci. 2010;30:249–258.
    doi: 10.1016/j.jevs.2010.03.008google scholar: lookup
  47. Borer K.E, Bailey S.R, Menzies-Gow N.J, Harris P.A, Elliott J. Effect of Feeding Glucose, Fructose, and Inulin on Blood Glucose and Insulin Concentrations in Normal Ponies and Those Predisposed to Laminitis. J. Anim. Sci. 2012;90:3003–3013.
    doi: 10.2527/jas.2011-4236pubmed: 22966077google scholar: lookup
  48. Pratt-Phillips S, Kutzner-Mulligan J, Marvin R, Brown H, Sykes C, Federico J. The Effect of Feeding Two or Three Meals Per Day of Either Low or High Nonstructural Carbohydrate Concentrates on Postprandial Glucose and Insulin Concentrations in Horses. J. Equine Vet. Sci. 2014;34:1251–1256.
    doi: 10.1016/j.jevs.2014.08.004google scholar: lookup
  49. Bamford N.J, Baskerville C.L, Harris P.A, Bailey S.R. Postprandial Glucose, Insulin, and Glucagon-like Peptide-1 Responses of Different Equine Breeds Adapted to Meals Containing Micronized Maize. J. Anim. Sci. 2015;93:3377–3383.
    doi: 10.2527/jas.2014-8736pubmed: 26440006google scholar: lookup
  50. Youden W.J. Index for Rating Diagnostic Tests. Cancer 1950;3:32–35.
    doi: 10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3pubmed: 15405679google scholar: lookup
  51. Knowles E.J, Elliott J, Harris P.A, Chang Y, Menzies-Gow N.J. Predictors of Laminitis Development in a Cohort of Nonlaminitic Ponies. Equine Vet. J. 2023;55:12–23.
    doi: 10.1111/evj.13572pmc: PMC10084125pubmed: 35263471google scholar: lookup

Citations

This article has been cited 0 times.
Subscribe to our newsletter
Join 99,344 horse owners like you who receive our email updates on horse health and nutrition.