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 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. [1]

Contents

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 ]

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

Related Research Articles

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Metabolic syndrome is a clustering of at least three of the following five medical conditions: abdominal obesity, high blood pressure, high blood sugar, high serum triglycerides, and low serum high-density lipoprotein (HDL).

Insulin resistance (IR) is a pathological condition in which cells either fail to respond normally to the hormone insulin or downregulate insulin receptors in response to hyperinsulinemia.

<span class="mw-page-title-main">Diabetic ketoacidosis</span> Medical condition

Diabetic ketoacidosis (DKA) is a potentially life-threatening complication of diabetes mellitus. Signs and symptoms may include vomiting, abdominal pain, deep gasping breathing, increased urination, weakness, confusion and occasionally loss of consciousness. A person's breath may develop a specific "fruity" smell. The onset of symptoms is usually rapid. People without a previous diagnosis of diabetes may develop DKA as the first obvious symptom.

<span class="mw-page-title-main">Glucose tolerance test</span> Medical test of how quickly glucose is cleared from the blood

The glucose tolerance test is a medical test in which glucose is given and blood samples taken afterward to determine how quickly it is cleared from the blood. The test is usually used to test for diabetes, insulin resistance, impaired beta cell function, and sometimes reactive hypoglycemia and acromegaly, or rarer disorders of carbohydrate metabolism. In the most commonly performed version of the test, an oral glucose tolerance test (OGTT), a standard dose of glucose is ingested by mouth and blood levels are checked two hours later. Many variations of the GTT have been devised over the years for various purposes, with different standard doses of glucose, different routes of administration, different intervals and durations of sampling, and various substances measured in addition to blood glucose.

<span class="mw-page-title-main">Type 2 diabetes</span> Form of diabetes mellitus

Type 2 diabetes (T2D), formerly known as adult-onset diabetes, is a form of diabetes mellitus that is characterized by high blood sugar, insulin resistance, and relative lack of insulin. Common symptoms include increased thirst, frequent urination, fatigue and unexplained weight loss. Symptoms may also include increased hunger, having a sensation of pins and needles, and sores (wounds) that do not heal. Often symptoms develop slowly. Long-term complications from high blood sugar include heart disease, stroke, diabetic retinopathy, which can result in blindness, kidney failure, and poor blood flow in the lower-limbs, which may lead to amputations. The sudden onset of hyperosmolar hyperglycemic state may occur; however, ketoacidosis is uncommon.

<span class="mw-page-title-main">Adipose tissue</span> Loose connective tissue composed mostly by adipocytes

Adipose tissue is a loose connective tissue composed mostly of adipocytes. It also contains the stromal vascular fraction (SVF) of cells including preadipocytes, fibroblasts, vascular endothelial cells and a variety of immune cells such as adipose tissue macrophages. Its main role is to store energy in the form of lipids, although it also cushions and insulates the body.

<span class="mw-page-title-main">Gestational diabetes</span> Medical condition

Gestational diabetes is a condition in which a person without diabetes develops high blood sugar levels during pregnancy. Gestational diabetes generally results in few symptoms; however, it increases the risk of pre-eclampsia, depression, and of needing a Caesarean section. Babies born to individuals with poorly treated gestational diabetes are at increased risk of macrosomia, of having hypoglycemia after birth, and of jaundice. If untreated, diabetes can also result in stillbirth. Long term, children are at higher risk of being overweight and of developing type 2 diabetes.

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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:

<span class="mw-page-title-main">Prediabetes</span> Predisease state of hyperglycemia with high risk for diabetes

Prediabetes is a component of metabolic syndrome and is characterized by elevated blood sugar levels that fall below the threshold to diagnose diabetes mellitus. It usually does not cause symptoms but people with prediabetes often have obesity, dyslipidemia with high triglycerides and/or low HDL cholesterol, and hypertension. It is also associated with increased risk for cardiovascular disease (CVD). Prediabetes is more accurately considered an early stage of diabetes as health complications associated with type 2 diabetes often occur before the diagnosis of diabetes.

<span class="mw-page-title-main">Chemerin</span> Protein-coding gene in the species Homo sapiens

Chemerin, also known as retinoic acid receptor responder protein 2 (RARRES2), tazarotene-induced gene 2 protein (TIG2), or RAR-responsive protein TIG2 is a protein that in humans is encoded by the RARRES2 gene.

Acquired generalized lipodystrophy (AGL), also known as Lawrence syndrome and Lawrence–Seip syndrome, is a rare skin condition that appears during childhood or adolescence, characterized by fat loss affecting large areas of the body, particularly the face, arms, and legs. There are four types of lipodystrophy based on its onset and areas affected: acquired or inherited, and generalized or partial. Both acquired or inherited lipodystrophy present as loss of adipose tissues, in the absence of nutritional deprivation. The near-total loss of subcutaneous adipose tissue is termed generalized lipodystrophy while the selective loss of adipose tissues is denoted as partial lipodystrophy. Thus, as the name suggests, AGL is a near-total deficiency of adipose tissues in the body that is developed later in life. It is an extremely rare disease with only about 100 cases reported worldwide. There are three main etiologies of AGL suspected: autoimmune, panniculitis-associated, or idiopathic. After its onset, the disease progresses over a few days, weeks, months, or even in years. Clinical presentations of AGL are similar to other lipodystrophies, including metabolic complications and hypoleptinemia. Treatments are also similar and mainly supportive for symptomatic alleviation. Although HIV- or drug-induced lipodystrophy are types of acquired lipodystrophy, their origins are very specific and distinct and hence are usually not discussed with AGL.

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<span class="mw-page-title-main">Disposition index</span>

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Diabetes mellitus (DM) is a type of metabolic disease characterized by hyperglycemia. It is caused by either defected insulin secretion or damaged biological function, or both. The high-level blood glucose for a long time will lead to dysfunction of a variety of tissues.

SPINA-GR is a calculated biomarker for insulin sensitivity. It represents insulin receptor gain.

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References

  1. 1 2 3 4 5 6 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; Vargas-Vázquez, Arsenio (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". Journal of Contemporary Medicine. Turkey: Government of Turkey. pp. 1–5. Retrieved 2019-01-03.
  3. ↑ "Unidad de Investigación de Enfermedades Metabólicas". www.innsz.mx. Retrieved 2019-01-03.
  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. PMC   6626942 . 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. PMC   3142016 . 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. Bibcode:2016PLoSO..1149731E. doi: 10.1371/journal.pone.0149731 . ISSN   1932-6203. PMC   4773118 . PMID   26930652.
  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. PMC   3661854 . PMID   23704681.
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