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Carobene A, Kilpatrick E, Bartlett WA, Fernández Calle P, Coşkun A, Díaz-Garzón J, Jonker N, Locatelli M, Sandberg S, Aarsand AK. The biological variation of insulin resistance markers: data from the European Biological Variation Study (EuBIVAS). Clin Chem Lab Med 2024; 0:cclm-2024-0672. [PMID: 38987271 DOI: 10.1515/cclm-2024-0672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 06/18/2024] [Indexed: 07/12/2024]
Abstract
OBJECTIVES An insulin resistant state is characteristic of patients with type 2 diabetes, polycystic ovary syndrome, and metabolic syndrome. Identification of insulin resistance (IR) is most readily achievable using formulae combining plasma insulin and glucose results. In this study, we have used data from the European Biological Variation Study (EuBIVAS) to examine the biological variability (BV) of IR using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and the Quantitative Insulin sensitivity Check Index (QUICKI). METHODS Ninety EuBIVAS non-diabetic subjects (52F, 38M) from five countries had fasting HOMA-IR and QUICKI calculated from plasma glucose and insulin samples collected concurrently on 10 weekly occasions. The within-subject (CVI) and between-subject (CVG) BV estimates with 95 % CIs were obtained by CV-ANOVA after analysis of trends, variance homogeneity and outlier removal. RESULTS The CVI of HOMA-IR was 26.7 % (95 % CI 25.5-28.3), driven largely by variability in plasma insulin and the CVI for QUICKI was 4.1 % (95 % CI 3.9-4.3), reflecting this formula's logarithmic transformation of glucose and insulin values. No differences in values or BV components were observed between subgroups of men or women below and above 50 years. CONCLUSIONS The EuBIVAS, by utilising a rigorous experimental protocol, has produced robust BV estimates for two of the most commonly used markers of insulin resistance in non-diabetic subjects. This has shown that HOMA-IR, in particular, is highly variable in the same individual which limits the value of single measurements.
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Affiliation(s)
- Anna Carobene
- Laboratory Medicine, 48455 IRCCS San Raffaele Scientific Institute , Milano, Italy
| | | | | | | | - Abdurrahman Coşkun
- School of Medicine, Acibadem Mehmet Ali Aydınlar University, Istanbul, Türkiye
| | - Jorge Díaz-Garzón
- Department of Laboratory Medicine, Hospital Universitario La Paz, Madrid, Spain
| | - Niels Jonker
- Certe, Wilhelmina Ziekenhuis Assen, Assen, The Netherlands
| | - Massimo Locatelli
- Laboratory Medicine, 48455 IRCCS San Raffaele Scientific Institute , Milano, Italy
| | - Sverre Sandberg
- Norwegian Porphyria Centre, Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway
- Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway
- Department of Global Health and Primary Care, Faculty of Medicine, University of Bergen, Bergen, Norway
| | - Aasne K Aarsand
- Norwegian Porphyria Centre, Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway
- Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway
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Isokuortti E, Zhou Y, Peltonen M, Bugianesi E, Clement K, Bonnefont-Rousselot D, Lacorte JM, Gastaldelli A, Schuppan D, Schattenberg JM, Hakkarainen A, Lundbom N, Jousilahti P, Männistö S, Keinänen-Kiukaanniemi S, Saltevo J, Anstee QM, Yki-Järvinen H. Use of HOMA-IR to diagnose non-alcoholic fatty liver disease: a population-based and inter-laboratory study. Diabetologia 2017; 60:1873-1882. [PMID: 28660493 DOI: 10.1007/s00125-017-4340-1] [Citation(s) in RCA: 80] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Accepted: 05/15/2017] [Indexed: 12/13/2022]
Abstract
AIMS/HYPOTHESIS Recent European guidelines for non-alcoholic fatty liver disease (NAFLD) call for reference values for HOMA-IR. In this study, we aimed to determine: (1) the upper limit of normal HOMA-IR in two population-based cohorts; (2) the HOMA-IR corresponding to NAFLD; (3) the effect of sex and PNPLA3 genotype at rs738409 on HOMA-IR; and (4) inter-laboratory variations in HOMA-IR. METHODS We identified healthy individuals in two population-based cohorts (FINRISK 2007 [n = 5024] and the Programme for Prevention of Type 2 Diabetes in Finland [FIN-D2D; n = 2849]) to define the upper 95th percentile of HOMA-IR. Non-obese individuals with normal fasting glucose levels, no excessive alcohol use, no known diseases and no use of any drugs were considered healthy. The optimal HOMA-IR cut-off for NAFLD (liver fat ≥5.56%, based on the Dallas Heart Study) was determined in 368 non-diabetic individuals (35% with NAFLD), whose liver fat was measured using proton magnetic resonance spectroscopy (1H-MRS). Samples from ten individuals were simultaneously analysed for HOMA-IR in seven European laboratories. RESULTS The upper 95th percentiles of HOMA-IR were 1.9 and 2.0 in healthy individuals in the FINRISK (n = 1167) and FIN-D2D (n = 459) cohorts. Sex or PNPLA3 genotype did not influence these values. The optimal HOMA-IR cut-off for NAFLD was 1.9 (sensitivity 87%, specificity 79%). A HOMA-IR of 2.0 corresponded to normal liver fat (<5.56% on 1H-MRS) in linear regression analysis. The 2.0 HOMA-IR measured in Helsinki corresponded to 1.3, 1.6, 1.8, 1.8, 2.0 and 2.1 in six other laboratories. The inter-laboratory CV% of HOMA-IR was 25% due to inter-assay variation in insulin (25%) rather than glucose (5%) measurements. CONCLUSIONS/INTERPRETATION The upper limit of HOMA-IR in population-based cohorts closely corresponds to that of normal liver fat. Standardisation of insulin assays would be the first step towards definition of normal values for HOMA-IR.
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Affiliation(s)
- Elina Isokuortti
- Minerva Foundation Institute for Medical Research, Biomedicum Helsinki 2 U, Tukholmankatu 8, FIN - 00290, Helsinki, Finland.
- Department of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
| | - You Zhou
- Systems Immunity University Research Institute, Cardiff University, Cardiff, UK
- Division of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK
| | - Markku Peltonen
- National Institute for Health and Welfare, Helsinki, Finland
| | - Elisabetta Bugianesi
- Division of Gastroenterology, Department of Medical Sciences, University of Torino, Torino, Italy
| | - Karine Clement
- Institute of Cardiometabolism and Nutrition (ICAN), Pitié-Salpêtrière Hospital, Paris, France
- Sorbonne Université, UPMC University Paris 06, UMR_S 1166, Inserm, Paris, France
| | - Dominique Bonnefont-Rousselot
- Department of Metabolic Biochemistry, La Pitié Salpêtrière-Charles Foix University Hospital (AP-HP), Paris, France
- Department of Biochemistry, Faculty of Pharmacy, Paris Descartes University, Paris, France
- CNRS UMR8258 - Inserm U1022, Faculty of Pharmacy, Paris Descartes University, Paris, France
| | - Jean-Marc Lacorte
- Institute of Cardiometabolism and Nutrition (ICAN), Pitié-Salpêtrière Hospital, Paris, France
- Sorbonne Université, UPMC University Paris 06, UMR_S 1166, Inserm, Paris, France
- Department of Endocrine and Oncological Biochemistry, La Pitié Salpêtrière-Charles Foix University Hospital (AP-HP), Paris, France
| | - Amalia Gastaldelli
- Cardiometabolic Risk Laboratory, Institute of Clinical Physiology, CNR, Pisa, Italy
| | - Detlef Schuppan
- Institute of Translational Immunology, Research Center of Immune Therapy, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Jörn M Schattenberg
- Department of Medicine I, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Antti Hakkarainen
- Helsinki Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Nina Lundbom
- Helsinki Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | | | - Satu Männistö
- National Institute for Health and Welfare, Helsinki, Finland
| | | | - Juha Saltevo
- Department of Medicine, Central Finland Central Hospital, Jyväskylä, Finland
| | - Quentin M Anstee
- Institute of Cellular Medicine, The Medical School, Newcastle University, Newcastle upon Tyne, UK
- Liver Unit, Newcastle Upon Tyne Hospitals NHS Trust, Freeman Hospital, Newcastle upon Tyne, UK
| | - Hannele Yki-Järvinen
- Minerva Foundation Institute for Medical Research, Biomedicum Helsinki 2 U, Tukholmankatu 8, FIN - 00290, Helsinki, Finland
- Department of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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Borai A, Livingstone C, Kaddam I, Ferns G. Selection of the appropriate method for the assessment of insulin resistance. BMC Med Res Methodol 2011; 11:158. [PMID: 22112229 PMCID: PMC3258205 DOI: 10.1186/1471-2288-11-158] [Citation(s) in RCA: 159] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2011] [Accepted: 11/23/2011] [Indexed: 12/15/2022] Open
Abstract
Insulin resistance is one of the major aggravating factors for metabolic syndrome. There are many methods available for estimation of insulin resistance which range from complex techniques down to simple indices. For all methods of assessing insulin resistance it is essential that their validity and reliability is established before using them as investigations. The reference techniques of hyperinsulinaemic euglycaemic clamp and its alternative the frequently sampled intravenous glucose tolerance test are the most reliable methods available for estimating insulin resistance. However, many simple methods, from which indices can be derived, have been assessed and validated e.g. homeostasis model assessment (HOMA), quantitative insulin sensitivity check index (QUICKI). Given the increasing number of simple indices of IR it may be difficult for clinicians and researchers to select the most appropriate index for their studies. This review therefore provides guidelines and advices which must be considered before proceeding with a study.
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Affiliation(s)
- Anwar Borai
- Department of Pathology, King Khalid National Guard Hospital, Jeddah, Saudi Arabia.
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