Removing the Rose-Tinted Glasses: The effects of antidepressant drug withdrawal on mood and neurocognitive function

Lead Research Organisation: University of Bath
Department Name: Psychology

Abstract

Depression is among the most common and costly mental health conditions in the UK with over 70 million prescriptions for antidepressants, such as SSRIs, in 2018 alone. Indeed, the number of prescriptions has doubled in the past decade. Many individuals are on antidepressants for a sustained period of time which is not ideal given their negative side effects, such as nausea, insomnia and sexual dysfunction. The cost to the NHS is also substantial. It is estimated that >50% of patients can safely withdraw from medication but it is currently difficult to predict which patients can stop taking SSRIs and which cannot (risk of relapse). Thus, finding ways of distinguishing between transient withdrawal effects and indicators of depressive relapse is vital in improving patient outcomes and potentially reducing the burden on the NHS.
Biases in emotion processing and emotion dysregulation have consistently been observed in depression. Research has demonstrated a role of negatively-biased emotion processing in the development of depressive symptoms and has suggested that antidepressants work by targeting these negative biases. Such effects occur within hours or days after starting treatment, potentially leading to increases in positive mood over the course of weeks. However, whilst these changes are well-documented, little is known about the effects of antidepressant withdrawal on emotion processing and mood. Is there a re-establishment of low-level negative biases in emotion processing during withdrawal and does the re-emergence of emotional biases or dysregulation predict later mood disturbances or depressive relapse? This information might be key as early changes in emotion processing, after SSRI withdrawal, may serve as warning signs of relapse.
The project's aims are twofold, firstly to characterise mood and emotion processing changes associated with withdrawal over time in order to better understand the effects of antidepressant withdrawal and their time course. Secondly, to enable the identification of early markers of symptom and mood changes that might aid in predicting depressive relapse. To address these aims, we will study primary care patients. The project will involve a novel combination of experience sampling, network analyses and neurocognitive testing (focusing on emotion processing).
We will combine research methods to provide new insights and an in-depth understanding of antidepressant withdrawal effects. The project will be relevant to researchers, clinicians, patients taking SSRIs, NHS commissioners and policy makers. From a scientific perspective, emotion processing changes occurring after antidepressant withdrawal will be characterised, which could inform and potentially modify theories of antidepressant action. Whereas from a clinical perspective, characterising mood changes and other withdrawal symptoms and the associated network analysis will inform antidepressant withdrawal management. The project spans ESRC and MRC priorities and has the potential to lead to methodological innovations that will be relevant to a wide audience of social scientists.
We hope the project will identify early markers of depressive relapse that can be targeted specifically to prevent relapse (while also helping those who can withdraw safely to do so). This research is urgently needed to help patients withdraw from antidepressants safely and effectively, and to reduce the personal, societal and economic costs of sustained antidepressant use.

Specialist training in Aberdeen and Amsterdam may be sought.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ES/P000630/1 01/10/2017 30/09/2027
2381093 Studentship ES/P000630/1 28/09/2020 27/12/2023 Raqeeb Mahmood