Project ID NS-MH2024_22

ThemeNS-MH

Co Supervisor 1A Institute of Psychiatry, Psychology & Neuroscience, School of Academic Psychiatry, Department of Psychosis StudiesWebsite

Co Supervisor 1B Institute of Psychiatry, Psychology & Neuroscience, School of Academic Psychiatry, Department of Psychological MedicineWebsite

Additional Supervisor Dr Ottavia Dipasquale

Relationship between brain energetic dysfunction and network activity in schizophrenia and treatment resistance

There is an urgent need for new treatments for schizophrenia. The greatest requirement is for novel therapeutics for patients who fail to respond to conventional antipsychotic drugs, which can be termed treatment-resistant schizophrenia (TRS). Development of novel therapeutics requires deeper understanding of the underlying neurobiological processes.

It is well-established that schizophrenia is associated with alterations in brain network activity. Synaptic transmission and network activity carry high energy demands, and the ability of the brain to meet these demands is vital for healthy brain functioning and cognition. In separate studies, schizophrenia has been associated with brain energetic dysfunction, including decreases in glucose utilisation, increases in lactate and impaired mitochondrial function.

Combined PET-MRI neuroimaging technology now allows brain glucose utilisation and network activity to be measured simultaneously. This PhD will combine these techniques to test, for the first time, the hypotheses that reductions in glucose utilisation are linked to dysfunction of brain network activity in schizophrenia, and that this breakdown in the relationship is most marked in patients with TRS.

The project will involve working alongside other members of the study team to recruit participants with a diagnosis of schizophrenia and healthy volunteers and acquire the PET-MRI and clinical data. The student will develop advanced skills in analysing PET glucose utilisation and resting state fMRI data and combining these data modalities. Depending on the student’s interests, there will also be opportunity to learn about or incorporate other imaging modalities, peripheral (blood) measures or clinical data including on cognition. The student will be supported in presenting and publishing their work throughout the PhD.

Year 1 – At the start of the PhD the student will be provided with the necessary training to work on the practical aspects of the project, including in participant recruitment and assessment, good clinical practice, and MRI / PET safety training. The emphasis will be on recruiting participants to the research study and acquiring the PET and MRI data. In parallel the student will begin to develop their technical skills in PET and MRI image analysis using existing datasets, and deeply familiarise themselves with the research area and develop PhD-level academic writing, for example by conducting a systematic review / meta-analysis.
Year 2 – Participant recruitment, assessment and scan acquisition will continue until the end of year 2. The student will consolidate their image analysis skills by pre-processing and quality checking the data as they are acquired, ready for statistical analyses in year 3. In doing so they will finalise the specific hypotheses they wish to test during their PhD and develop the associated analysis plans. Academic writing will continue through publication of the review / meta-analysis and writing of introduction and methods sections, and our departmental seminars provide a friendly and supportive forum to practice oral presentation skills. Years 3 and 4; The focus of years 3 and 4 is final data analyses and writing up the results for journal publications and the thesis. The student will be supported and encouraged to present their work at national and international conferences, which also provide excellent opportunities to meet others working in their field of research.

Representative Publications

Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis. Merritt, K., et al., Egerton A., 2023. Molecular Psychiatry doi: 10.1038/s41380-023-01991-7.
Anterior cingulate glutamate metabolites as a predictor of antipsychotic response in first episode psychosis: data from the STRATA collaboration. Egerton A., et al., 2023 Neuropsychopharmacology doi: 10.1038/s41386-022-01508-w.
Subcortical volume reduction and cortical thinning 3 months after switching to clozapine in treatment resistant schizophrenia. Krajner F., et al Egerton A., 2022 Schizophrenia doi: 10.1038/s41537-022-00230-2.

Dwyer DB, Chand GB, Pigoni A, Khuntia A, Wen J, Antoniades M, Hwang G, Erus G, Doshi J, Srinivasan D, Varol E, Kahn RS, Schnack HG, Meisenzahl E, Wood SJ, Zhuo C, Sotiras A, Shinohara RT, Shou H, Fan Y, Schaulfelberger M, Rosa P, Lalousis PA, Upthegrove R, Kaczkurkin AN, Moore TM, Nelson B, Gur RE, Gur RC, Ritchie MD, Satterthwaite TD, Murray RM, Di Forti M, Ciufolini S, Zanetti MV, Wolf DH, Pantelis C, Crespo-Facorro B, Busatto GF, Davatzikos C, Koutsouleris N, Dazzan P. Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium. Mol Psychiatry. 2023 May 5. doi: 10.1038/s41380-023-02069-0. Epub ahead of print. PMID: 37147389.

Ajnakina O, Das T, Lally J, Di Forti M, Pariante CM, Marques TR, Mondelli V, David AS, Murray RM, Palaniyappan L, Dazzan P. Structural Covariance of Cortical Gyrification at Illness Onset in Treatment Resistance: A Longitudinal Study of First-Episode Psychoses. Schizophr Bull. 2021 Oct 21;47(6):1729-1739. doi: 10.1093/schbul/sbab035. PMID: 33851203; PMCID: PMC8530394.

Dazzan P, Lawrence AJ, Reinders AATS, Egerton A, van Haren NEM, Merritt K, Barker GJ, Perez-Iglesias R, Sendt KV, Demjaha A, Nam KW, Sommer IE, Pantelis C, Wolfgang Fleischhacker W, van Rossum IW, Galderisi S, Mucci A, Drake R, Lewis S, Weiser M, Martinez Diaz-Caneja CM, Janssen J, Diaz-Marsa M, Rodríguez-Jimenez R, Arango C, Baandrup L, Broberg B, Rostrup E, Ebdrup BH, Glenthøj B, Kahn RS, McGuire P; OPTiMiSE study group. Symptom Remission and Brain Cortical Networks at First Clinical Presentation of Psychosis: The OPTiMiSE Study. Schizophr Bull. 2021 Mar 16;47(2):444-455. doi: 10.1093/schbul/sbaa115. PMID: 33057670; PMCID: PMC7965060.