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      Hereditary severe insulin resistance syndrome: Pathogenesis, pathophysiology, and clinical management


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          Severe insulin resistance has been linked to some of the most globally prevalent disorders, such as diabetes mellitus, nonalcoholic fatty liver disease, polycystic ovarian syndrome, and hypertension. Hereditary severe insulin resistance syndrome (H-SIRS) is a rare disorder classified into four principal categories: primary insulin receptor defects, lipodystrophies, complex syndromes, and obesity-related H-SIRS. Genes such as INSR, AKT2, TBC1D4, AGPAT2, BSCL2, CAV1, PTRF, LMNA, PPARG, PLIN1, CIDEC, LIPE, PCYT1A, MC4R, LEP, POMC, SH2B1, RECQL2, RECQL3, ALMS1, PCNT, ZMPSTE24, PIK3R1, and POLD1 have been linked to H-SIRS. Its clinical features include insulin resistance, hyperglycemia, hyperandrogenism, severe dyslipidemia, fatty liver, abnormal topography of adipose tissue, and low serum leptin and adiponectin levels. Diagnosis of H-SIRS is based on the presence of typical clinical features associated with the various H-SIRS forms and the identification of mutations in H-SIRS-linked genes by genetic testing. Diet therapy, insulin sensitization, exogenous insulin therapy, and leptin replacement therapy have widely been adopted to manage H-SIRS. The rarity of H-SIRS, its highly variable clinical presentation, refusal to be tested for genetic mutations by patients’ family members who are not severely sick, unavailability of genetic testing, and testing expenses contribute to the delayed or underdiagnoses of H-SIRS. Early diagnosis facilitates early management of the condition, which results in improved glycemic control and delayed onset of diabetes and other complications related to severe insulin resistance. The use of updated genetic sequencing technologies is recommended, and long-term studies are required for genotype–phenotype differentiation and formulation of diagnostic and treatment protocols.

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          Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage.

          Insulin resistance contributes to the pathophysiology of diabetes and is a hallmark of obesity, metabolic syndrome, and many cardiovascular diseases. Therefore, quantifying insulin sensitivity/resistance in humans and animal models is of great importance for epidemiological studies, clinical and basic science investigations, and eventual use in clinical practice. Direct and indirect methods of varying complexity are currently employed for these purposes. Some methods rely on steady-state analysis of glucose and insulin, whereas others rely on dynamic testing. Each of these methods has distinct advantages and limitations. Thus, optimal choice and employment of a specific method depends on the nature of the studies being performed. Established direct methods for measuring insulin sensitivity in vivo are relatively complex. The hyperinsulinemic euglycemic glucose clamp and the insulin suppression test directly assess insulin-mediated glucose utilization under steady-state conditions that are both labor and time intensive. A slightly less complex indirect method relies on minimal model analysis of a frequently sampled intravenous glucose tolerance test. Finally, simple surrogate indexes for insulin sensitivity/resistance are available (e.g., QUICKI, HOMA, 1/insulin, Matusda index) that are derived from blood insulin and glucose concentrations under fasting conditions (steady state) or after an oral glucose load (dynamic). In particular, the quantitative insulin sensitivity check index (QUICKI) has been validated extensively against the reference standard glucose clamp method. QUICKI is a simple, robust, accurate, reproducible method that appropriately predicts changes in insulin sensitivity after therapeutic interventions as well as the onset of diabetes. In this Frontiers article, we highlight merits, limitations, and appropriate use of current in vivo measures of insulin sensitivity/resistance.
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            The integrative biology of type 2 diabetes

            Obesity and type 2 diabetes are the most frequent metabolic disorders, but their causes remain largely unclear. Insulin resistance, the common underlying abnormality, results from imbalance between energy intake and expenditure favouring nutrient-storage pathways, which evolved to maximize energy utilization and preserve adequate substrate supply to the brain. Initially, dysfunction of white adipose tissue and circulating metabolites modulate tissue communication and insulin signalling. However, when the energy imbalance is chronic, mechanisms such as inflammatory pathways accelerate these abnormalities. Here we summarize recent studies providing insights into insulin resistance and increased hepatic gluconeogenesis associated with obesity and type 2 diabetes, focusing on data from humans and relevant animal models.
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              PTRF-Cavin, a conserved cytoplasmic protein required for caveola formation and function.

              Caveolae are abundant cell-surface organelles involved in lipid regulation and endocytosis. We used comparative proteomics to identify PTRF (also called Cav-p60, Cavin) as a putative caveolar coat protein. PTRF-Cavin selectively associates with mature caveolae at the plasma membrane but not Golgi-localized caveolin. In prostate cancer PC3 cells, and during development of zebrafish notochord, lack of PTRF-Cavin expression correlates with lack of caveolae, and caveolin resides on flat plasma membrane. Expression of PTRF-Cavin in PC3 cells is sufficient to cause formation of caveolae. Knockdown of PTRF-Cavin reduces caveolae density, both in mammalian cells and in the zebrafish. Caveolin remains on the plasma membrane in PTRF-Cavin knockdown cells but exhibits increased lateral mobility and accelerated lysosomal degradation. We conclude that PTRF-Cavin is required for caveola formation and sequestration of mobile caveolin into immobile caveolae.

                Author and article information

                Genes Dis
                Genes Dis
                Genes & Diseases
                Chongqing Medical University
                11 April 2022
                September 2023
                11 April 2022
                : 10
                : 5
                : 1846-1856
                [1]National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, and Department of Endocrinology and Metabolism, The Second XiangYa Hospital of Central South University, Changsha, Hunan 410011, China
                Author notes
                []Corresponding author. National Clinical Research Center for Metabolic Diseases, the Second XiangYa Hospital of Central South University, 139 Renmin Middle Road, Changsha, Hunan 410011, China. houdezhou@ 123456csu.edu.cn

                These authors share the first authorship.

                © 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                : 9 February 2022
                : 24 March 2022
                : 27 March 2022
                Review Article

                diabetes,genetics,insulin resistance,lipodystrophy,pathophysiology,therapy


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