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New approaches in precision psychiatry: Exploring genomic markers and linked health records to predict symptom improvement and drug response in schizophrenia. 

John Grace QC PhD Scholarship 2022 - Cardiff University


Supervisors: Professor Michael C. O’Donovan and Dr. Antonio F. Pardiñas

Lay Summary: Not everyone with schizophrenia responds in the same way to the same drug treatments. In fact, nearly a third of people do not benefit even after several treatments have been tried. We do not know why this happens, although we think genetic differences between people are part of the answer. What we do know is that poor response to treatment can have a very bad impact on quality of life, and that people with schizophrenia and their families think that finding out how to improve treatment response is a high priority. It is very difficult to do research on this topic because large amounts of complicated data are needed, which are hard to collect using the sort of methods that have been possible until very recently. In Cardiff, we can now overcome this problem. Over many years, we have recruited large numbers of people who have given us samples of DNA to study genetic influences on schizophrenia. Thanks to our research collaborations with other institutions and the NHS, we can now look at the connections between that genetic information and lots of data available on medical records. Importantly, we can do this in a way that keeps the identities of the people we are studying secret, unknown to us and anyone else. We will use this new information to see how people respond to different treatments they receive. We will also be able to see how people respond differently depending on their genes and other possibly important factors such as symptoms, age, and sex. We think that the results of this project can show us how information that is collected as a matter of routine when people use health services can help to identify the treatment for individuals that is the safest for them and also gives them the best benefits.

Aims: Our main hypothesis is that treatment response in schizophrenia is a complex construct with biological and environmental influences, related to the presence and intensity of specific symptoms. Thus, this PhD project will use unique datasets to assess how genetic, demographic, environmental and clinical information can be combined to predict the effects of antipsychotic treatment. Primarily, the PhD candidate will evaluate the association between standardised symptom scales and (i) composite metrics of psychiatric genomic risk known as polygenic scores, (ii) pharmacogenomic markers with known functional consequences for the activity of drug-metabolising enzymes and (iii) extensive non-genetic information derived from clinical interview records. The study will be based upon thoroughly characterised patient cohorts recruited by our research group and our close collaborators, most of which can be linked to NHS electronic health records (eHR). The candidate will also develop skills in the computational discipline of Natural Language Processing (NLP) to enhance these cohorts through the extraction of data from routinely collected clinical notes, enabling the assessment of environmental risk factors and construction of longitudinal symptom profiles. 

Research Student: Siobhan Lock

Hi, I’m Siobhan and I will be starting my PhD at Cardiff University in October 2022.


I completed a BSc in Psychology with a Professional Placement at Cardiff University, where I was able to gain experience in neuroimaging and behavioural genetics research. Following a final year project that explored the impact of CYFIP1 haploinsufficiency on brain structure and behaviour, I decided to undertake an MSc in Bioinformatics and Genetic Epidemiology – also at Cardiff. Currently, I’m completing my MSc project which is looking at exploring the impact of pharmacogenomic variants on medication use in individuals with schizophrenia.

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Schizophrenia has long been an area of interest for me, and I have enjoyed learning about it at various levels of my education. I am looking forward to using genomic data and electronic health records to examine the various factors that influence treatment outcomes. I am excited to be given the opportunity to work on a project of this scope, which has the potential to positively impact individuals with schizophrenia. I can’t wait to get started with Dr. Pardiñas and the team and I am incredibly grateful to Mental Health Research UK for funding this project.

Progress Report Year 1, 2023


As part of my first year, I have been spending a bit of time getting to grips with new statistical methods including regression modelling to help me explore associations between predictor and outcome variables, and structural equation modelling to explore whether any variables mediate these associations. I also improved my skills with R and Python, which are computer programs that I use for data analysis.


My first project involved using cellular, genetic, and medication data in a sample of individuals with treatment-resistant schizophrenia. Clozapine, an antipsychotic, can on very rare occasions lead to white blood cell loss. White blood cells are a key part of our immune system, and therefore a reduction in this cell type could increase the risk of people developing infections. Neutrophils are a type of white blood cell that is particularly affected by clozapine. Therefore, we wanted to see if we could identify any risk factors that are related to lower levels of neutrophils in a group of people taking clozapine.


I found that neutrophil levels were significantly associated with clozapine dose, and plasma levels of clozapine and its metabolite, clozapine. I saw that the significant association between clozapine dose and neutrophil count was mediated in part by plasma clozapine and norclozapine concentrations, as shown in the figure below. This means that plasma concentrations of clozapine and norclozapine both play a part in explaining the overall effect of clozapine dose on absolute neutrophil count. Finally, we saw evidence that genetic variation in a key clozapine-metabolising enzyme was associated with neutrophil counts.

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Figure 1. Path diagram showing association between clozapine dose and lowest absolute neutrophil count with plasma clozapine concentration and plasma norclozapine concentration as mediators. Plot edges are labelled with standardised regression coefficients. M = Mediator.                                 * p<0.05   ** p<0.01   *** p<0.001


In the future, a more complete understanding of the impact of clozapine on neutrophils may help clinicians to identify patients at greatest risk of these side effects, and then introduce preventative measures to help mitigate these reactions.


I presented this research as a poster at the launch of Cardiff University’s Centre for Neuropsychiatric Genetics and Genomics (poster link). I had a great time talking about my findings with other researchers and interested members of the public. In October, I am being supported by MHRUK to present this work at the World Congress of Psychiatric Genetics in Montreal. The conference will be an amazing opportunity to learn about the latest work in psychiatric genetics alongside meeting other researchers in the field.

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