Descripción del proyecto
Predicción de la diabetes de tipo 2 con biomarcadores epigenéticos
La diabetes de tipo 2 (DT2) es una enfermedad prevalente con importantes repercusiones a nivel mundial. Los modelos predictivos actuales se limitan a los estadios prediabéticos y dificultan la intervención preventiva. El proyecto PredRegNetworks, financiado por el Consejo Europeo de Investigación, introduce un método innovador que utiliza nuevos biomarcadores epigenéticos. La idea detrás de este método se fundamenta en el papel de los potenciadores y silenciadores en las redes reguladoras. Aprovechando estos conocimientos, se prevé que los modelos de predicción de enfermedades propuestos alcancen una precisión de nivel clínico incluso en personas no diabéticas. Estos modelos innovadores permitirán identificar a personas de riesgo mucho antes de que se manifiesten síntomas clínicos, lo cual ofrece una oportunidad transformadora para la actuación temprana y los tratamientos preventivos. La validación de este método podría conllevar el desarrollo de una prueba clínica innovadora para hacer frente a la DT2.
Objetivo
Type 2 Diabetes Mellitus (T2DM) is a heterogeneous disease, associated with mortality and severe morbidity, and affecting hundreds of millions of people around the globe. Despite some misconception accepted in the public, current models to predict the onset of T2DM have insufficient power, and are generally limited to individuals that already progressed into pre-diabetes states, at which the assignment of disease-preventing treatments is largely ineffective. Clinical-level prediction power (AUC>0.9) among non-diabetic individuals would enable effective pre-emptive strategies, but the way to produce such predictions remined unknown. Based on a new understanding of enhancer-silencer regulatory networks, I have developed a new class of supreme epigenetic biomarkers. Disease-prediction models that built on the basis of these novel understanding and biomarkers, significantly overpower the best currently-available prediction models. Importantly, these pioneering models can identify the people at risk well before the appearance of any clinical symptoms. Strong preliminary evidence signified the potential to develop the first clinical test to identify the risk to develop T2DM and associated diseases among non-pre-diabetic individuals at the required prediction power, and in time to deliver effective disease-preventing treatments. Validation of these results and demonstration of the effectiveness of the new clinical-level test will allows the directions of the effective (though expensive) preventing treatments to the people at risk, thus dramatically improve the way we are dealing with this harmful disease.
Ámbito científico
Palabras clave
Programa(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Régimen de financiación
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsInstitución de acogida
91904 Jerusalem
Israel