Understanding the neural mechanisms of antidepressant withdrawal and links with depressive symptoms, reward processing and relapse

点击翻译按钮获取中文摘要

In 2021, 1 in 6 adults in the UK suffered from depression and the NHS spent £14.3 billion on mental health services. Research efforts must be focused on trying to improve current understanding of the efficacy, as well as side-effects, of treatments for depression. The Medical Research Council have included advances in mental health diagnosis and treatment as a research priority in the Strategic Delivery Plan for 2022 - 2025. Antidepressants (AD) are a leading treatment for depression and individuals are taking ADs for increasingly longer periods of time. Selective serotonin reuptake inhibitors (SSRI) are the most widely prescribed AD due to the fewer side effects they are associated with compared to other types of ADs. AD withdrawal occurs when a patient stops taking their ADs and is more likely after a protracted period of AD use (more than four to six weeks). Withdrawal symptoms can include nausea, fatigue, sensory and emotional disturbances and may emerge a few days following AD cessation and can last up to a year: often leading to depression relapse. Whilst there is greater knowledge on the side-effects of ADs for physical and psychological function, there is less understanding on the impact of AD discontinuation on mood and cognition. Clinicians would benefit substantially if they could predict which patients will experience withdrawal symptoms and depression relapse so they could provide additional support to those most vulnerable. Impairments in reward processing have been linked with core depressive symptoms, such as anhedonia, loss of appetite and social withdrawal. SSRIs are thought to work by altering monoamine transmission that in turns reinstates reward insensitivity and allows depressed individuals to be more receptive to rewarding experiences. Research has shown reward responsiveness to improve in the first two weeks of taking ADs. However, current knowledge is lacking on the nature by which deficits in reward processing may re-emerge following AD discontinuation. For example, it is not clear whether there are domain-specific deficits in reward sensitivity related to AD withdrawal, or if reward insensitivity is linked to specific withdrawal effects. Neural markers of altered reward sensitivity have predicted later depression symptoms in adults and adolescents. If alterations in reward sensitivity do occur following AD discontinuation, and are associated with specific AD withdrawal symptoms, these neural responses could provide a valuable predictive biomarker for depression relapse. In my PhD, I will investigate the longitudinal effects of AD discontinuation on neural mechanisms of reward and analyse how this relates to daily mood, withdrawal symptoms and depression relapse in a primary care cohort. I will use a range of research methods, including event-related potentials (ERPs), ecological momentary assessment (EMA) and neurocognitive tasks. In my first year, I will conduct a community study to establish the validity of these measures for my main longitudinal study with clinical patients. Using healthy volunteers, I will confirm the re-test reliability of reward-related ERPs and pilot a daily EMA protocol across a one-week period. In my main study, I will use these measures to monitor withdrawal in primary care patients 1-week, 2-week, 3-months and 6 months from AD discontinuation. I will also obtain pre-baseline measures for intra-individual comparisons with follow-up assessments. At each time point I will measure sensitivity to reward using ERPs and neurocognitive assessments; I will also conduct clinical interviews at the baseline and 6-month follow-up assessments. Patients will also complete daily EMA surveys to assess mood, depressive symptoms, and sensitivity to social rewards. Following data collection, I plan to triangulate ERP, EMA, neurocognitive and clinical data using advanced computational methods to determine whether any of the assessments included predict later depression relapse.