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Schizophrenia interactome derived repurposable drugs and randomized control trials of two candidates.
Ganapathiraju, Madhavi K; Triptish, Bhatia; Deshpande, Smita; Wesesky, Maribeth; Wood, Joel; Nimgaonkar, Vishwajit L.
  • Ganapathiraju MK; Department of Biomedical Informatics and Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA; Carnegie Mellon University in Qatar, Doha, Qatar. Electronic address: madhavi@pitt.edu.
  • Triptish B; Dept. of Psychiatry, Centre of Excellence in Mental Health, ABVIMS- Dr Ram Manohar Lohia Hospital, New Delhi 110001, India.
  • Deshpande S; Department of Psychiatry, St John's Medical College Hospital, Koramangala, Bengaluru, Karnataka 560034, India.
  • Wesesky M; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
  • Wood J; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
  • Nimgaonkar VL; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Veterans Administration Pittsburgh Healthcare System, Pittsburgh, PA, USA. Electronic address: VishwajitNL@upmc.edu.
Biol Psychiatry ; 2024 Jun 29.
Article en En | MEDLINE | ID: mdl-38950808
ABSTRACT
There is a substantial unmet need for effective and patient-acceptable drugs to treat severe mental illnesses like schizophrenia. Computational analysis of genomic, transcriptomic, and pharmacologic data generated in the past two decades enables repurposing of drugs or compounds with acceptable safety profiles, namely those that are FDA-approved or reached late stages in clinical trials. We developed a rational approach to achieve this computationally for schizophrenia by studying drugs that target the proteins in its protein interaction network ('interactome'). This involved contrasting the transcriptomic modulations observed in the disorder and the drug; our analyses resulted in 12 candidate drugs, 9 of which had additional supportive evidence their target networks were enriched for pathways relevant to schizophrenia etiology or for genes that had an association with diseases pathogenically similar to schizophrenia. To translate these computational results to the clinic, these shortlisted drugs must be tested empirically through randomized controlled trials (RCT), where their prior safety approvals obviate the need for time-consuming phase I and II studies. We selected two among the shortlisted candidates based on likely adherence and side effect profiles. We are testing them through adjunctive RCTs for patients with schizophrenia or schizoaffective disorder who experienced incomplete resolution of psychotic features with conventional treatment. The integrated computational analysis for identifying and ranking drugs for clinical trials can be iterated as additional data are obtained. Our approach could be expanded to enable disease subtype-specific drug discovery in future and should also be exploited for other psychiatric disorders.
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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article