Role of inflammation on the neurobiological features of depression & potential stratification
Project Details - Role of inflammation on the neurobiological features of depression & potential stratification
|Supervisor(s): Dr Heather C Whalley, Prof Jonathan Cavanagh & Prof Andrew M McIntosh|
|Centre/Institute: Centre for Clinical Brain Sciences|
Major depressive disorder (MDD) is a heritable and disabling psychiatric condition which is the leading cause of disability worldwide. MDD is attributable to the effects and interactions of genetic and environmental factors, although the pathophysiological mechanisms remain poorly understood. Previous imaging studies have reported alterations in brain regions and connecting tracts within affect- and reward-processing networks, but the direction of causality remains unclear (Whalley et al., 2013; Shen et al., 2017). Increasing evidence also suggests that MDD is not a unitary disorder but is likely to represent a grouping of conditions with diverse aetiologies with the resulting heterogeneity hampering progress.
There are increasingly compelling data implicating immune/inflammatory molecules in MDD pathophysiology (Leighton et al., 2017). There are also strong indications of a key role for early life adversity and related stress-HPA axis activation (Baumeister et al., 2016). These responses may have neurotoxic effects in the brain, ultimately resulting in the clinical symptoms and progression of the disorder. However, the effects of peripheral inflammation on brain structure and function in-vivo in the disorder remain poorly understood. Further, whether affected individuals with an inflammatory aetiology, or vulnerability, constitute a definable neurobiological sub-strata of MDD also remains unknown, but has strong implications for specific and mechanistically-tailored treatment.
Using one of the largest single imaging studies of depression to date with neuroimaging and peripheral markers of immune-mediated inflammatory responses (STRADL n~1000, a subset of a larger cohort study Generation Scotland n=23,000 with in depth genotyping and phenotyping and access to birth cohort data), the project aims to:
This proposal benefits greatly from the existing strong interdisciplinary Sackler collaboration between the University of Edinburgh and the University of Glasgow. As part of this PhD, extensive training in a wide variety of quantitative skills will be undertaken, including in MR image processing, the use of widely used neuroimaging software packages such as SPM, and FSL, as well as machine learning approaches to classification of neuroimaging data. A thorough understanding would also be gained of the complex modeling procedures offered by the powerful statistical package ‘R’, as well as familiarisation with access procedures and use of large, locally and publicly available cohorts. In addition, there is also opportunity to maximize the use of these cohorts with available genomics data and linkage to e-health records. The PhD the candidate will also gain experience in the interface between neuro- and immunobiology through supervisory links at the University of Glasgow.
The training outcomes would therefore culminate in a sound understanding of techniques at the forefront of neuroimaging, neuroinflammation and psychiatry as applied to a large data sources in the context of transforming depression research.
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