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Heterogeneity in depression: examining hypothesis-driven subtypes in longitudinal genetically informed cohorts

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  • Full or part time
    Dr Rice
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Depression is common and is one of the leading causes of disability worldwide. Despite its societal importance, relatively little is known about what causes depression. However, it is recognised that multiple causal factors are involved with both environmental and genetic factors contributing. There is considerable heterogeneity both in the types of symptoms exhibited by depressed individuals and in the long-term trajectory of symptoms. It is possible that there are sub-types of depression with different causal factors. For instance, the relative contribution of genetic influences appears to be greater for more severe depressive symptoms (Riglin et al., 2015), lowest for childhood onset depressive symptoms (Rice et al., 2002) and vary according to whether depression co-occurs with other difficulties such as antisocial behaviour (Riglin et al., 2015). This proposal aims to synthesise findings from genetic epidemiology and developmental psychopathology to generate and test hypotheses about subtypes of depression. This information will help to further understanding about the causes of depression and may ultimately help to improve services for depressed people and their families.

Findings from family, twin and longitudinal studies of depression suggest that particular factors may be important to consider for identifying depression sub-types. 1) Several studies suggest that adolescent onset depression that recurs in adult life may indicate a subtype of depression which has a particularly malignant long-term trajectory which is more common in those with a family history of depression (Rice, 2010). 2) Depression that co-occurs with antisocial behaviour problems may differ from depression that does not co-occur with these problems and ‘co-occurring depression’ may be common in children (Riglin et al., 2015).

The aim of this project is to investigate whether there are subtypes of depression with differing genetic and environmental risk factor profiles and associated phenotypic and functional outcomes. For example, in relation to the first hypothesis, adolescent onset depression that recurs in adult life would be expected to show moderate to high heritability, to be associated with family history of depression, and genetic risk burden (polygenic risk score) for depression as well as with depression-related outcomes in adult life such as symptom trajectory and service use. In order to address the primary research question, longitudinal genetically informed data with rich phenotypic information and information on environmental risk and protective factors is required. The project will utilise several unique datasets well suited for addressing the research question:

1. Cardiff Study of All Wales and North England Twins (CaStANET): a study of 1500 adolescent twin pairs.
2. The Early Prediction of Adolescent Depression (EPAD) study: a longitudinal study of 335 offspring of depressed parents.
3. 1958 National Child Development Study (NCDS): a longitudinal birth cohort of 17000 individuals.
4. The Avon Longitudinal Study of Parents and Children (ALSPAC): a longitudinal birth cohort of 14000 mothers and children.
5. The Psychiatric Genomics Consortium (PGC): genome-wide genotype and summary genome-wide association and genetic risk data from approximately 17000 affected and 26000 individuals unaffected by major depressive disorder.

The MRC CNGG provides an ideal environment in which to address this research question due to the exceptional local computational infrastructure, readily available training opportunities and the centre’s internationally recognised research excellence in the area of psychiatric genetics. This project is supported by supervisors with expertise in depression, genetic epidemiology, statistics and genomics meaning that the student will have access to a broad array of relevant expertise.

The most appropriate of the available data sets will be selected to test key hypotheses. Longitudinal data sets will be analysed using appropriate techniques (e.g. latent profile analysis, latent class growth curve analysis) to assess whether there are sub-groups of individuals with differing trajectories of depressive symptomatology. Heritability of profiles can be tested in the twin sample and in studies containing genome-wide genotype data. Polygenic risk profiles for depression will be derived, from best-available data (e.g. PGC) in individuals with genome-wide genotype data. Associations between trajectory grouping with polygenic risk scores, social risk factors and clinical and functional outcome will be examined. Replication will be sought in the most appropriate available data set. Training in all relevant methods will be provided. This project would suit a student with a psychology, statistical or bioinformatics background.

Funding Notes

UK Research Council eligibility conditions apply

Full awards (fees plus maintenance stipend) are open to UK Nationals and EU students who can satisfy UK residency requirements

How good is research at Cardiff University in Psychology, Psychiatry and Neuroscience?

FTE Category A staff submitted: 69.33

Research output data provided by the Research Excellence Framework (REF)

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