Understanding the effect of anti-psychotic medication on cellular metabolism.
Understanding the effect of anti-psychotic medication on cellular metabolism.
批准号:
2746429
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
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英文摘要
Antipsychotic medications are the mainstay of treatment of psychosis. One of the major side-effects of these medications is metabolic impairment, which increases the risk of cardiometabolic diseases. Patients with psychosis are twice as likely, compared to general populations, to die of cardiometabolic diseases. Antipsychotics differ in their propensity to cause metabolic derangements: clozapine and olanzapine (high risk), risperidone and quetiapine (moderate risk), and haloperidol and lurasidone (low risk). Patients also differ in their susceptibility to develop metabolic side-effects with different antipsychotics. It is only after patients are on antipsychotic treatment, often for weeks and months, before these side-effects become problematic and strategies, like lifestyle changes and medications like metformin, to mitigate these are instituted. Besides increasing the risk of cardiometabolic diseases, these side-effects also affect the therapeutic relationship adversely, contribute to poor treatment concordance and increase the risk of relapse. There is a critical need for a a better understanding of the cellular response to these medications which will lead to strategies to inform treatment options, which minimise cardiometabolic risks and reduce associated morbidity and mortality.Mitochondrial dysfunction is a crucial process that can explain antipsychotic induced metabolic derangements. Mitochondrial metabolism can be accurately profiled using high-resolution respirometry (HRR) techniques. The student will use HRR to accurately define the metabolic signatures that different antipsychotics elicit in cell lines, primary cells and human treated and untreated (control) blood cells, to stratify the risk of developing metabolic syndrome and identify which among the treatment options, like metformin, mitigate or reverse those changes. Using detailed metabolic profiling, they will be able to specify precisely which molecules and pathways are indicative of onset and amelioration of metabolic syndromes. There is potential for the student to work towards development of a set of biomarkers that characterise the effects of each of the medications currently used in the clinic. Respirometry information will be enriched with proteomics analysis of treated and untreated cells to define the molecular pathways associated with metabolic perturbations. Epigenetic analysis will define regulatory mechanisms that may be important in controlling the side effects.
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