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How Can Pharmacogenomics Biomarkers Be Translated into Patient Benefit

Published online by Cambridge University Press:  15 April 2020

D. Collier
Affiliation:
Neuroscience Genetics, Eli Lilly and Company Ltd, Windlesham Surrey, United Kingdom
E. Achilla
Affiliation:
Health Services and Population Research, King's College London, London, United Kingdom
G. Breen
Affiliation:
Social Genetic and Developmental Psychiatry, King's College London, London, United Kingdom
S. Curran
Affiliation:
Social Genetic and Developmental Psychiatry, King's College London, London, United Kingdom
D. Dima
Affiliation:
Social Genetic and Developmental Psychiatry, King's College London, London, United Kingdom
R. Flanagan
Affiliation:
Clinical Biochemistry, King's College Hospital, London, United Kingdom
J. Frank
Affiliation:
Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim, Germany
S. Frangou
Affiliation:
Psychiatry, Mount Sinai School of Medicine, New York, USA
C. Gasse
Affiliation:
National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
I. Giegling
Affiliation:
Psychiatry, University of Halle-Wittenberg, Halle, Germany
M. Rietschel
Affiliation:
Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim, Germany
D. Rujescu
Affiliation:
Psychiatry, University of Halle-Wittenberg, Halle, Germany
J. Maccabe
Affiliation:
Psychosis Studies, King's College London, London, United Kingdom
P. McCrone
Affiliation:
Health Services and Population Research, King's College London, London, United Kingdom
J. Mill
Affiliation:
Medical School, University of Exeter Medical School, Exeter, United Kingdom
E. Sigurdsson
Affiliation:
Psychiatry, Landspitali National University Hospital, Reykjavik, Iceland
H. Stefansson
Affiliation:
Genetics, deCODE Genetics, Reykjavik, Iceland
J. Walters
Affiliation:
MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
M. Verbelen
Affiliation:
Social Genetic and Developmental Psychiatry, King's College London, London, United Kingdom

Abstract

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Treatment resistant schizophrenia (TRS) is one of the most disabling of psychiatric disorders, affecting about 1/3 of patients. First-line treatments include both atypical and typical antipsychotics. The original atypical, clozapine, is a final option, and although it has been shown to be the only effective treatment for TRS, many patients do not respond well to clozapine. Clozapine use is related to adverse events, most notably agranulocytosis, a potentially fatal blood disorder which affects about 1% of those prescribed clozapine and requires regular blood monitoring. This as a barrier to prescription and there is a long delay in access for TRS patients, of five or more years, from first antipsychotic prescription. Better tools to predict treatment resistance and to identify risk of adverse events would allow faster and safer access to clozapine for patients who are likely to benefit from it. The CRESTAR project (www.crestar-project.eu) is a European Framework 7 collaborative project that aims to develop tools to predict i) treatment response, particularly patients who are less likely to respond to usual antipsychotics, indicating treatment with clozapine as early as possible, ii) patients who are at high or low risk of adverse events and side effects, iii) extreme TRS patients so that they can be stratified in clinical trials for novel treatments. CRESTAR has addressed these questions by examining genome-wide association data, genome sequence, epigenetic biomarkers and epidemiological data in European patient cohorts characterized for treatment response, and adverse drug reaction using data from clozapine therapeutic drug monitoring and linked National population medical and pharmacy databases, to identify predictive factors. In parallel CRESTAR will perform health economic research on potential benefits, and ethics and patient-centred research with stakeholders.

Type
Article: 0094
Copyright
Copyright © European Psychiatric Association 2015
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