Defining the Human Insulin Resistance Molecular Network; SIGNATURE
Insulin resistance (IR) is inherent to metabolic diseases incl. type 2 diabetes. There is emerging evidence that even among healthy people there is a large heterogeneity in insulin sensitivity, which partly explains why the mechanisms behind IR remain unresolved. This proposal focuses on the interindividual diversity of IR including the heterogeneity in response to short-term life-style interventions known to modify IR, e.g. inactivity and diet. In a smaller cohort, we will, in exceptional detail, examine individual variations at baseline and in response to the interventions at a physiological and molecular level to predict discrete IR signatures. The relevance of these mechanisms for health will be assessed by genetic approaches, using data from large-scale genetic populations. The identified molecular signatures will be validated by various approaches. These signatures will be invaluable for diagnostic and therapeutic purposes, enabling individualized strategies to prevent diseases.
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Imported from OpenAIRE | Grant NNF24OC0085866.
Open sourceOverview
Grant agreement NNF24OC0085866
Open sourceInsulin resistance (IR) is inherent to metabolic diseases incl. type 2 diabetes. There is emerging evidence that even among healthy people there is a large heterogeneity in insulin sensitivity, which partly explains why the mechanisms behind IR remain unresolved. This proposal focuses on the interindividual diversity of IR including the heterogeneity in response to short-term life-style interventions known to modify IR, e.g. inactivity and diet. In a smaller cohort, we will, in exceptional detail, examine individual variations at baseline and in response to the interventions at a physiological and molecular level to predict discrete IR signatures. The relevance of these mechanisms for health will be assessed by genetic approaches, using data from large-scale genetic populations. The identified molecular signatures will be validated by various approaches. These signatures will be invaluable for diagnostic and therapeutic purposes, enabling individualized strategies to prevent diseases.