G Protein–Coupled Receptor Kinase 2 Plays a Relevant Role in Insulin Resistance and Obesity
Authors: Sonia Fernández-Veledo
Iria Nieto-Vazquez
Guillermo Zalba
Lucia Garcia-Guerra
Cristina Murga
Rocio Vila-Bedmar
Javier Díez
Margarita Lorenzo
María Jurado-Pueyo
Federico Mayor Jr
Journal: Diabetes (2010)
Discipline: CLINICAL MEDICINE
Keywords: Insulin resistance; G protein-coupled receptor kinase 2 (GRK2); metabolic disorders; type 2 diabetes; obesity
Affiliations: Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, Complutense University, Madrid, Spain.

Abstract:  Objective: Insulin resistance is associated with the pathogenesis of metabolic disorders as type 2 diabetes and obesity. Given the emerging role of signal transduction in these syndromes, we set out to explore the possible role that G protein-coupled receptor kinase 2 (GRK2), first identified as a G protein-coupled receptor regulator, could have as a modulator of insulin responses. Research design and methods: We analyzed the influence of GRK2 levels in insulin signaling in myoblasts and adipocytes with experimentally increased or silenced levels of GRK2, as well as in GRK2 hemizygous animals expressing 50% lower levels of this kinase in three different models of insulin resistance: tumor necrosis factor-α (TNF-α) infusion, aging, and high-fat diet (HFD). Glucose transport, whole-body glucose and insulin tolerance, the activation status of insulin pathway components, and the circulating levels of important mediators were measured. The development of obesity and adipocyte size with age and HFD was analyzed. Results: Altering GRK2 levels markedly modifies insulin-mediated signaling in cultured adipocytes and myocytes. GRK2 levels are increased by ∼2-fold in muscle and adipose tissue in the animal models tested, as well as in lymphocytes from metabolic syndrome patients. In contrast, hemizygous GRK2 mice show enhanced insulin sensitivity and do not develop insulin resistance by TNF-α, aging, or HFD. Furthermore, reduced GRK2 levels induce a lean phenotype and decrease age-related adiposity. Conclusions: Overall, our data identify GRK2 as an important negative regulator of insulin effects, key to the etiopathogenesis of insulin resistance and obesity, which uncovers this protein as a potential therapeutic target in the treatment of these disorders. 

Retracted: Yes

PubPeer comments:
 Just one of the many medRxiv COVID-19 papers using insurance data. Only 2 authors had data access while numerous others  contributed to data analysis . The study uses the same ethics approval as used for several other studies ([1] 30316-7 fulltext),[2] , [3] ), all issued by Witten Herdecke, an [institution](http: www.ifaemm.de) that is [known for defending the scientific basis of homeopathy] . Is this really a cohort study? The definition of cohort studies has been broadened from the earlier prospective analysis of risk factors in a population identified by period of birth to any longitudinal analysis. At least some different exposure (COVID-19 or no COVID-19) should have been included however. Age and sex cohort effect can then be fitted while none of that was done here. So this is more a retrospective narrative analysis - in a highly selected sample that uses only AOK (lower social insurance data) - it uses only hospital data (numerous patients never reach a hospital) - it assumes no exposure no disease if there are no data, eg there are no missings in this dataset - inclusion criteria have been changed from the earlier report [1] 30316-7 fulltext) from 10.021 patients between Feb 26, 2020, and April 19, 2020 to 11.459 patients between Feb 1 to April 30, 2020 for unknown reasons - the authors argue that they cannot exclude residual confounding while IMHO the authors did not exclude ANY type confounding in the current analysis - allegedly  hospital data are of high quality while we know for decades that hospitals are money-making companies that adjust to a market - neither was the study pre-registered nor is there any clear study question that is being answered Even worse, the authors do not know the main reason for hospitalization. we limited the analysis to those patients with a COVID-19- related principal diagnosis of respiratory failure, pulmonary embolism, viral infection, sepsis or renal failure ... We excluded 2780 patients who did not suffer from a COVID-19-related principal diagnosis ... So they enrich for a diagnosis, run a logistic regression model and show an  odds ratio for this diagnosis? ![file] Beyond the fact that a hazard ratio would be more suitable the result is just some kind of self fulfilling prophecy. BTW with non-parallel K-P curves, why not using stratifed Cox models? ,