Juan Cigudosa

Supervisor ESR13

Founding Partner of NIMGenetics. Doctor in Biological Sciences, specialist in Human Genetics. He was Chief of the Cytogenetic Unit at the National Oncology Research Center (CNIO), Spain. He trained as a company director at Genoma España and Instituto de Empresa (IE). He has published more than 200 scientific papers in international journals. He is President of the Spanish Association of Human Genetics (AEGH) and member of the Board of Director the European Cytogenetics Association (ECA). He is an international opinion leader for the introduction of genomics in clinical practice, and has led the design and implementation of massive analysis platforms of the genome for genetic diagnostics in Europe and Latin America.

1. Members of the team

  • Dr. Beatriz Maroto, R&D Manager
  • Dr. Sara Álvarez, CMO
  • Dr. Javier Suela, CTO

2. Role in the project

The role of NIMGenetics in the project will be to evaluate how short-term antipsychotic drug responses impact long-term metabolic control to identify and validate Biomarkers with clinically predictive value for targeting drug Induced metabolic dysfunctions in mental disorders, with special focus on schizophrenia. NIMGenetics will also identify genetic and cellular pathways responsible for the association of schizophrenia with metabolic syndrome to design of predictive marker kits for testing adverse secondary metabolic effects of drugs to be used in pharmacological and medical practice and to match drugs to individual patients.

3. TREATMENT project

  • ESR13

    ESR13 will carry out a translational Integrative genomic analysis on human patients samples using bioinformatic strategies. The ESR will study the genomic and expression profiles of a cohort of patients and controls where short term responses to antipsychotic administration have been studied by other participant groups. ESR13 will characterize the different genomic patterns that predict long term metabolic side effects in human patients with the purpose of designing predictive tests for personalized medicine in antipsychotic treatment. The design of a rapid, economic and reliable predictive test for quantification of parameters that predict long-term metabolic dysfunctions that may result from chronic drug administration will be useful for application on diagnosis and follow up of schizophrenic patients and/or other related pathologies.