Recipient organisationCardiff UniversitySource-published name: Cardiff University
Funding£2.2M
PeriodMar 2024 — Feb 2029
In plain English
AI plain-English summary
A person with schizophrenia has a roughly one-in-three chance that standard antipsychotic drugs will not relieve their symptoms. This research tackles the biological roots of that treatment resistance, which affects around a third of patients and contributes to poor long-term outcomes. The team will analyse genetic data from a large international consortium to identify DNA variants linked to treatment response, hospitalisation, and social functioning. If successful, the work could make it possible to predict early on which patients need different or more intensive treatment, rather than discovering resistance through trial and error. That would allow clinicians to tailor therapy from the start, reducing time spent on ineffective drugs and their side effects. The project also aims to uncover fundamental biological processes behind treatment resistance, which may point towards entirely new drug targets. This is primarily fundamental science—understanding why some people’s brains respond to antipsychotics and others do not—but it is a necessary step before precision psychiatry can become a practical reality.
View original technical description
Schizophrenia (SZ) is a severe psychiatric disorder that has a profound impact on the individual and society. Over half of people with SZ have long-term psychiatric problems, 80-90% are unemployed, and life expectancy is reduced by 10-20 years. These outcomes have not changed over recent decades. Current antipsychotic treatment often causes major adverse effects and is not effective in treating symptoms in around 30% of those with SZ (termed treatment resistant SZ - TRS). Developing more effective and acceptable treatments for SZ is a priority for patients but has proven a major challenge for researchers given we know little about the biological processes that cause the condition, and even less about what influences good or bad outcomes, response to existing treatments, and we do not have established ways of identifying specific groups of people with SZ that may benefit from different treatment approaches. Precision medicine seeks to address these issues with the aim of developing more targeted treatments, minimising adverse effects and improving patient outcomes. In other areas of medicine, genetics has been central to the success of precision medicine. We have led international research over the last decade that has confirmed the important contribution genetics makes to SZ risk. In this programme we will use this experience, and apply modern genetic tools, to advance precision medicine approaches in psychosis and SZ by investigating the genetic basis of TRS and wider patient outcomes. We have designed the research programme in consultation with patients who have lived experience of psychosis, and informed by these discussions, we will focus our projects on TRS and other outcomes prioritised by patients including (minimising) hospitalisation and relationship and occupational functioning. We have shown that genetics contributes to whether symptoms respond to treatment, and we will now identify both common and rare genetic variants (risk alleles) that are associated with TRS and the other outcomes. We require very large datasets to address these aims so we will bring together a consortium of international researchers and genetic and clinical data from 103,478 research participants. We will use these risk alleles to identify genes associated with treatment outcomes and will analyse them with other biological datasets to gain insights into the biological processes involved in these treatment outcomes. In addition, we will conduct analyses to identify existing medications that may impact TRS and alter outcomes. The potential impact of precision medicine is likely to be greatest if it is possible to differentiate between those who need new or more intensive early interventions and those who are expected to do well with existing interventions. Genetic risk scores represent the total amount, or sometimes the particular patterns, of genetic variants that influence a condition, or any other partly heritable characteristic, that a person carries. In other common illness, genetic risk scores are starting to be helpful in predicting course, outcomes, and the need for particular treatments. We aim to see if genetic risk scores based on the DNA variants that influence outcome can be used to predict those outcomes in people with schizophrenia, to influence TRS and outcomes in SZ. We believe completion of these aims will deliver important insights into the feasibility of precision medicine in SZ and will enhance our understanding of the fundamental biology of TRS and patient outcomes in SZ, highlighting potential novel treatment targets and identifying separate groups of people with psychosis and SZ who would benefit from different therapeutic approaches.
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