Medicine:Metabolic Score for Insulin Resistance

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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.[1][2] It was developed by the Metabolic Research Disease Unit at the Instituto Nacional de Ciencias Médicas Salvador Zubirán[3] and validated against the euglycemic hyperinsulinemic clamp and the frequently-sampled intravenous glucose tolerance test in Mexican population.[1] It is a non-insulin-based alternative to insulin-based methods to quantify peripheral insulin sensitivity and an alternative to 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.[1]

Derivation and validation

METS-IR was generated using linear regression against the M-value adjusted by lean body mass obtained from the glucose clamp technique in Mexican subjects with and without type 2 diabetes mellitus. It is estimated using fasting laboratory values including glucose (in mg/dL), triglycerides (mg/dL) and high-density lipoprotein cholesterol (HDL-C, in mg/dL) along with body-mass index (BMI). The index can be estimated using the following formula:[citation needed]

[math]\displaystyle{ METS-IR =\frac{\ln[2*Glucose (mg/dL) + Triglycerides (mg/dL)]*BMI (kg/m^2)}{\ln[HDL-C (mg/dL)]} }[/math]

The index holds a significant correlation with the M-value adjusted by lean mass (ρ = −0.622) obtained from the euglycemic hyperinsulinaemic clamp study adjusted for age and gender as well as minimal model estimates of glucose sensitivity.[4] In an open population cohort study in Mexican population, METS-IR was shown to predict incident type 2 diabetes mellitus and a value of METS-IR >50.0 suggested up to three-fold higher risk of developing type 2 diabetes after an average of three years.[1] In a nation-wide population-based study of Chinese subjects, METS-IR was also shown to identify subjects with metabolic syndrome independent of adiposity.[5] METS-IR also predicts visceral fat content, subcutaneous adipose tissue, fasting insulin levels and ectopic fat accumulation in liver and pancreas.[1]

Comparison to other indexes

METS-IR was compared against other non-insulin-based methods to approximate insulin sensitivity including the Triglyceride-Glucose index (TyG),[6] the triglyceride to HDL-C ratio,[7] and the TyG-BMI index,[8] yielding a higher correlation and area under the receiving operating characteristic curve compared to these other measures.[1] When assessing its utility for identifying metabolic syndrome in Chinese subjects, Yu et al. suggested that the TyG and TG/HDL-C indexes had superior performance in their population owing to ethnic-specific variations in body composition.[9] Given the role of ethnicity in modifying the performance of insulin sensitivity fasting-based indexes, further evaluations in different populations are required to establish performance of non-insulin-based methods.[10]

See also

References

  1. ↑ 1.0 1.1 1.2 1.3 1.4 1.5 Bello-Chavolla, Omar Yaxmehen; Almeda-Valdes, Paloma; Gomez-Velasco, Donaji; Viveros-Ruiz, Tannia; Cruz-Bautista, Ivette; Romo-Romo, Alonso; Sánchez-Lázaro, Daniel; Meza-Oviedo, Dushan et al. (2018). "METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity and incident type 2 diabetes". European Journal of Endocrinology 178 (5): 533–544. doi:10.1530/EJE-17-0883. PMID 29535168. 
  2. ↑ Yılmaz, Abdulkerim; Kaya, Süheyla Uzun; Kalkan, Göknur; Öztürk, Banu; Şahin, Şafak; Kutlutürk, Faruk; Taşlıyurt, Türker; Bilir, Yeliz (2014-07-16). "Prevalence of Metabolic Syndrome and Insulin Resistance in Patients with Psoriasis". Turkey: Government of Turkey. pp. 1–5. http://dergipark.gov.tr/gopctd/95643. 
  3. ↑ "Unidad de Investigación de Enfermedades Metabólicas". http://www.innsz.mx/opencms/contenido/investigacion/uiem/informacion-profesionales-salud.html. 
  4. ↑ Finegood, Diane T.; Dunaif, Andrea; McDonald, Cheryl (2000-07-01). "Minimal-Model Estimates of Insulin Sensitivity Are Insensitive to Errors in Glucose Effectiveness". The Journal of Clinical Endocrinology & Metabolism 85 (7): 2504–2508. doi:10.1210/jcem.85.7.6681. ISSN 0021-972X. PMID 10902801. 
  5. ↑ Yu, Xinwen; Wang, Li; Zhang, Wencheng; Ming, Jie; Jia, Aihua; Xu, Shaoyong; Li, Qiaoyue; Ji, Qiuhe (2018). "Fasting triglycerides and glucose index is more suitable for the identification of metabolically unhealthy individuals in the Chinese adult population: A nationwide study". Journal of Diabetes Investigation 10 (4): 1050–1058. doi:10.1111/jdi.12975. ISSN 2040-1124. PMID 30417578. 
  6. ↑ Guerrero-Romero, Fernando; Simental-Mendía, Luis E.; González-Ortiz, Manuel; Martínez-Abundis, Esperanza; Ramos-Zavala, María G.; Hernández-González, Sandra O.; Jacques-Camarena, Omar; Rodríguez-Morán, Martha (July 2010). "The product of triglycerides and glucose, a simple measure of insulin sensitivity. Comparison with the euglycemic-hyperinsulinemic clamp". The Journal of Clinical Endocrinology and Metabolism 95 (7): 3347–3351. doi:10.1210/jc.2010-0288. ISSN 1945-7197. PMID 20484475. 
  7. ↑ Giannini, Cosimo; Santoro, Nicola; Caprio, Sonia; Kim, Grace; Lartaud, Derek; Shaw, Melissa; Pierpont, Bridget; Weiss, Ram (August 2011). "The Triglyceride-to-HDL Cholesterol Ratio". Diabetes Care 34 (8): 1869–1874. doi:10.2337/dc10-2234. ISSN 0149-5992. PMID 21730284. 
  8. ↑ Ko, Yu-Lin; Sun, Yu-Chen; Teng, Ming-Sheng; Hsu, Lung-An; Chou, Hsin-Hua; Wu, Semon; Er, Leay-Kiaw (2016-03-01). "Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals". PLOS ONE 11 (3): e0149731. doi:10.1371/journal.pone.0149731. ISSN 1932-6203. PMID 26930652. Bibcode: 2016PLoSO..1149731E. 
  9. ↑ Sniderman, Allan D.; Tchernof, André; Bondy, Gregory P.; Kohli, Simi; Lear, Scott A. (2009-12-01). "Ethnic Variation in Fat and Lean Body Mass and the Association with Insulin Resistance". The Journal of Clinical Endocrinology & Metabolism 94 (12): 4696–4702. doi:10.1210/jc.2009-1030. ISSN 0021-972X. PMID 19820012. 
  10. ↑ Butte, Atul J.; Patel, Chirag J.; Toda, Kyoko; Yamada, Satoru; Tojjar, Damon; Kodama, Keiichi (2013-06-01). "Ethnic Differences in the Relationship Between Insulin Sensitivity and Insulin Response: A systematic review and meta-analysis". Diabetes Care 36 (6): 1789–1796. doi:10.2337/dc12-1235. ISSN 1935-5548. PMID 23704681. PMC 3661854. http://care.diabetesjournals.org/content/36/6/1789. 

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