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      Finnish-specific AKT2 gene variant leads to impaired insulin signalling in myotubes

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          Abstract

          Finnish-specific gene variant p.P50T/ AKT2 (minor allele frequency (MAF) = 1.1%) is associated with insulin resistance and increased predisposition to type 2 diabetes. Here, we have investigated in vitro the impact of the gene variant on glucose metabolism and intracellular signalling in human primary skeletal muscle cells, which were established from 14 male p.P50T/ AKT2 variant carriers and 14 controls. Insulin-stimulated glucose uptake and glucose incorporation into glycogen were detected with 2-[1,2- 3H]-deoxy-D-glucose and D-[ 14C]-glucose, respectively, and the rate of glycolysis was measured with a Seahorse XF e96 analyzer. Insulin signalling was investigated with Western blotting. The binding of variant and control AKT2-PH domains to phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P 3) was assayed using PIP Strips TM Membranes. Protein tyrosine kinase and serine-threonine kinase assays were performed using the PamGene® kinome profiling system. Insulin-stimulated glucose uptake and glycogen synthesis in myotubes in vitro were not significantly affected by the genotype. However, the insulin-stimulated glycolytic rate was impaired in variant myotubes. Western blot analysis showed that insulin-stimulated phosphorylation of AKT-Thr 308, AS160-Thr 642 and GSK3β-Ser 9 was reduced in variant myotubes compared to controls. The binding of variant AKT2-PH domain to PI(3,4,5)P 3 was reduced as compared to the control protein. PamGene® kinome profiling revealed multiple differentially phosphorylated kinase substrates, e.g. calmodulin, between the genotypes. Further in silico upstream kinase analysis predicted a large-scale impairment in activities of kinases participating, for example, in intracellular signal transduction, protein translation and cell cycle events. In conclusion, myotubes from p.P50T/ AKT2 variant carriers show multiple signalling alterations which may contribute to predisposition to insulin resistance and T2D in the carriers of this signalling variant.

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          Most cited references48

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
            • Record: found
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            Adjusting batch effects in microarray expression data using empirical Bayes methods.

            Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches difficult. The ability to combine microarray data sets is advantageous to researchers to increase statistical power to detect biological phenomena from studies where logistical considerations restrict sample size or in studies that require the sequential hybridization of arrays. In general, it is inappropriate to combine data sets without adjusting for batch effects. Methods have been proposed to filter batch effects from data, but these are often complicated and require large batch sizes ( > 25) to implement. Because the majority of microarray studies are conducted using much smaller sample sizes, existing methods are not sufficient. We propose parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples. We illustrate our methods using two example data sets and show that our methods are justifiable, easy to apply, and useful in practice. Software for our method is freely available at: http://biosun1.harvard.edu/complab/batch/.
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              Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

              The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.

                Author and article information

                Journal
                J Mol Endocrinol
                J Mol Endocrinol
                JME
                Journal of Molecular Endocrinology
                Bioscientifica Ltd (Bristol )
                0952-5041
                1479-6813
                21 November 2022
                01 February 2023
                : 70
                : 2
                : e210285
                Affiliations
                [1 ]Minerva Foundation Institute for Medical Research , Tukholmankatu, Helsinki, Finland
                [2 ]Department of Medicine , University of Helsinki and Helsinki University Hospital, Haartmaninkatu, Helsinki, Finland
                [3 ]Pam Gene International B.V. , Wolvenhoek, BJ ´s-Hertogenbosch, The Netherlands
                [4 ]Department of Anatomy , Faculty of Medicine, Haartmaninkatu, University of Helsinki, Helsinki, Finland
                [5 ]Turku PET Centre , University of Turku, Kiinamyllynkatu, Turku, Finland
                [6 ]Turku PET Centre , Turku University Hospital, Kiinamyllynkatu, Turku, Finland
                [7 ]Institute of Clinical Medicine , Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Puijonlaaksontie, Kuopio, Finland
                Author notes
                Correspondence should be addressed to H A Koistinen: heikki.koistinen@ 123456helsinki.fi

                *(S Mäkinen and N Datta contributed equally to this work)

                Author information
                http://orcid.org/0000-0003-2586-8992
                http://orcid.org/0000-0001-7870-070X
                Article
                JME-21-0285
                10.1530/JME-21-0285
                9874976
                36409629
                ac588630-11ab-41fc-a57e-25a0be2d5363
                © The authors

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 21 September 2022
                : 21 November 2022
                Categories
                Research

                Endocrinology & Diabetes
                akt2,glucose metabolism,insulin signalling,insulin resistance,kinase activity,primary muscle cells

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