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• genetics, genomics and molecular biology
• cell and developmental biology/regenerative medicine
• neuroscience and mental health

• Medicine

• Neuropsychiatry
• Psychiatry

Our multidisciplinary team is dedicated to understanding the molecular basis of the major psychotic disorders (schizophrenia/bipolar disorder) as a means of improving patient care. We have one of the world's largest patient cohorts (>3,000 cases) and our work has delivered new, often unexpected insights into the complex molecular etiology underlying these disorders. We work with international network of collaborators and our funders include SFI, HRB, Wellcome Trust and National Institute of Health (US). As a group we have published >200 publications in journals including Nature, Nature Genetics, Human Molecular Genetics, JAMA Psychiatry & Molecular Psychiatry. Our member's research interests include clinical research, neuropsychology, brain imaging, genomics, biostatistics and molecular biology.

1. Understanding a novel risk mechanism for psychosis. We identified a novel chromosomal duplication at the gene PAK7 which increases risk of schizophrenia ten-fold. Further work is required to characterize and test family members of carriers of this mutation. With colleagues in Edinburgh we have generated a human cellular model for the mutation (using iPS technology). Much of the focus of this project would be on characterizing the molecular mechanism involved and understanding how it impacts on dynamic synaptic function using a range of cellular models and molecular techniques.

2. Characterizing genetic risk in first episode patients. This project involves a combination of clinical research and biostatistics. The purpose being to use existing understanding of the molecular etiology of psychosis to characterize genetic risk, or potentially genetic subtypes, within patients at the onset of illness and explore their impact on predicting illness course or treatment response.

3. Are their rare diseases lost within psychiatric patient cohorts? This project involves clinical and genomics research. This will use genomic sequence data to identify 'hidden' genetic relatedness within our large patient cohort. Using this information we will investigate whether these individuals share unusual family history profiles, clinical features (e.g. early age at onset, catatonia, co-morbidities) and whether they share rare, highly penetrant risk mutations.