The role of subgenual frontal connectivity in predicting response to serotonergic medications
Lead Research Organisation:
King's College London
Department Name: Psychological Medicine
Abstract
There is an urgent need to develop imaging biomarkers of response to antidepressant medications in major depressive disorder (MDD). This serves the development of individualised treatment algorithms. We have recently shown that subgenual frontal (SF) functional connectivity alterations predict subsequent recurrence in MDD patients whose symptoms were remitted. Dunlop et al., (2017) have shown that resting state SF fMRI connectivity accurately predicts non-response to antidepressant medications in treatment-naïve patients. This demonstrates the high potential of SF connectivity as a biomarker of response to antidepressant treatment and recurrence risk in MDD. It is unknown, however, whether these findings generalise to patients with early treatment resistance as seen in UK primary care. Furthermore, the function of the SF cortex and its connectivity is still disputed. To address these questions, during year 1 & 2, the student will acquire resting state fMRI and cognitive data in 24 patients independently recruited for an NIHR-funded trial of a novel computerised decision support algorithm for antidepressant medications in primary care. We expect about 50% of patients to respond to treatment with serotonergic drugs. This will allow us to compare baseline MRI scans of treatment responders with non-responders. Year 3 and 4 will be devoted to completing analysis and write-up of journal manuscripts investigating 1) whether SF connectivity predicts subsequent response to treatment and 2) whether it is associated with individual differences on novel cognitive tests of blame attribution in social interactions.Training in clinical assessment, as well as fMRI data acquisition and analysis, will be provided.
Publications

Duan S
(2023)
Remote virtual reality assessment elucidates self-blame-related action tendencies in depression
in Journal of Psychiatric Research


Fennema D
(2024)
Neural responses to facial emotions and subsequent clinical outcomes in difficult-to-treat depression.
in Psychological medicine

Fennema D
(2023)
Self-blame-selective hyper-connectivity between anterior temporal and subgenual cortices predicts prognosis in major depressive disorder
in NeuroImage: Clinical


Fennema D
(2021)
Internal reliability of blame-related functional MRI measures in major depressive disorder.
in NeuroImage. Clinical


Harrison P
(2021)
Development and validation of the Maudsley Modified Patient Health Questionnaire (MM-PHQ-9).
in BJPsych open


Lawrence AJ
(2022)
Neurocognitive Measures of Self-blame and Risk Prediction Models of Recurrence in Major Depressive Disorder.
in Biological psychiatry. Cognitive neuroscience and neuroimaging
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
MR/N013700/1 | 30/09/2016 | 29/09/2025 | |||
2064430 | Studentship | MR/N013700/1 | 30/09/2018 | 29/06/2022 | Diede Fennema |
Description | Scients Postdoctoral Fellowship Award |
Amount | £215,000 (GBP) |
Organisation | Scients Institute, USA |
Sector | Charity/Non Profit |
Country | United States |
Start | 06/2022 |
End | 06/2025 |
Title | Text-based version of the Moral Sentiment and Action Tendencies (MSAT) task |
Description | The MSAT is based on the value-related moral sentiment task (VMST), which has been validated in previous studies (Green et al., 2012; Green et al., 2013; Zahn et al., 2007; Zahn et al., 2009; Zahn et al., 2015). The MSAT task investigates the neurocognitive underpinnings of blame-related emotions, presenting short written statement describing hypothetical social behaviours, in which either the participant (self-agency) or their best friend (other-agency) acts counter to social and moral values. |
Type Of Material | Physiological assessment or outcome measure |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | The tool has been used to validate a novel virtual reality (VR) assessment of blame-related action tendencies, which showed that people with depression exhibit a maladaptive profile: particularly in the other-agency condition, rather than feeling like verbally attacking their friend, they were prone to feeling like hiding, and punishing themselves (Duan et al., 2023). |
URL | https://gitlab.pavlovia.org/diedef92/adess_msat |
Description | Oxford University - Implicit faces fMRI paradigm |
Organisation | University of Oxford |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | One of the aims of the PhD project was to reproduce findings by the collaborator, related to predicting response to antidepressant treatment. The fMRI paradigm used by the collaborator was slightly modified for use in this project, but analysis approach was kept the same. |
Collaborator Contribution | The collaborator provided the fMRI paradigm, e.g. timings and faces. |
Impact | None yet. |
Start Year | 2018 |
Description | Podcast "Lefgasten" [Daredevils] |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Public/other audiences |
Results and Impact | My old schoolteacher (and head of school) invited me for a podcast to discuss what I have been up to since leaving secondary school. She has developed her own method to deal with performance anxiety, written a book about it and gives workshops, and she is trying to gain more familiarity of her methods with a podcast. In this podcast, we discussed my current PhD project and what kind of implications it could have for primary care. Please note that the podcast is in Dutch. |
Year(s) Of Engagement Activity | 2021 |
URL | https://soundcloud.com/lefgasten/over-diede-fennema |