STratifying Resilience and Depression Longitudinally (STRADL)
Approved Research ID: 4844
Approval date: September 27th 2014
Lay summaryProgress in understanding the causes of major depressive disorder has been slow. Dividing depression into subtypes, a process called stratification, could ultimately lead to faster progress. We will stratify or divide individuals with MDD and depressive syndromes into more similar groups of people in UK Biobank. Our aims are to: 1. Identify and describe specific subtypes of depression 2. Identify the causes underlying different types of depression using GWAS and MRI 3. Test whether resistance to depression (i.e. resilience) to depression can be accurately measured. 4. Identify the mechanisms underlying resilience using genetic and brain imaging data. This research seeks to use the medical, cognitive, imaging and genetic data from UKBiobank to study the mechanisms of common medical conditions and use them as a platform to better diagnosis. These aims are consistent with UK Biobank's. Providing this information will help to identify new drug targets for depression. Stratifying depression into more homogenous categories will provide better 'disease' targets for other research studies because there will be less lumping together of individuals with different causes for their illness within the same broad category of depression. We will test whether these sub-classes of depression and depressive symptom have neurobiological associations in UKbiobank by comparing them with depressed individuals as w whole, as well as controls, using MRI and genetic data. We will firstly examine the associations of depression with cognition (baseline measures and web-based measures of attention and memory, for example), brain structure, function and connection strength (MRI). We will examine the association of different depression types with biological intermediates (measurable variables important in the causation of depression) using a technique called polygenic profiling. We will also compare resilient and non-resilient individuals. We are interested in the full UKbiobank cohort for most analyses - and the subgroup of UKbiobank with genetic and imaging (brain MRI) data for more detailed analysis. We appreciate the time scale for the availability of genotyping and imaging data.
- Genetic and shared couple environmental contributions to smoking and alcohol use in the UK population
- Genetic correlations between pain phenotypes and depression and neuroticism
- Genome-wide association study of knee pain identifies associations with GDF5 and COL27A1 in UK Biobank
- White Matter Microstructure and Its Relation to Longitudinal Measures of Depressive Symptoms in Mid- and Late Life.
- Stratifying major depressive disorder by polygenic risk for schizophrenia in relation to structural brain measures.
- Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions
- Insulin resistance: Genetic associations with depression and cognition in population based cohorts
- Impact of polygenic risk for Schizophrenia on cortical structure in UK Biobank
- Association of Whole-Genome and NETRIN1 Signaling Pathway-Derived Polygenic Risk Scores for Major Depressive Disorder and White Matter Microstructure in the UK Biobank.
- Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank
- Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways
- A Genome-Wide Association Study Finds Genetic Associations with Broadly-Defined Headache in UK Biobank (N = 223,773)
- Genome-Wide Association Study Meta-Analysis of the Alcohol Use Disorders Identification Test (AUDIT) in Two Population-Based Cohorts
- Resting-State Connectivity and Its Association With Cognitive Performance, Educational Attainment, and Household Income in the UK Biobank
- Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression
- Genome-wide Regional Heritability Mapping Identifies a Locus Within the TOX2 Gene Associated With Major Depressive Disorder
- Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112 117)
- Assessing the presence of shared genetic architecture between Alzheimer’s disease and major depressive disorder using genome-wide association data
- Haplotype-based association analysis of general cognitive ability in Generation Scotland, the English Longitudinal Study of Ageing, and UK Biobank
- Genome-wide haplotype-based association analysis of major depressive disorder in Generation Scotland and UK Biobank
- Intelligence and neuroticism in relation to depression and psychological distress: Evidence from two large population cohorts
- Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank.
- Do regional brain volumes and major depressive disorder share genetic architecture? A study of Generation Scotland (n=19 762), UK Biobank (n=24 048) and the English Longitudinal Study of Ageing (n=5766)
- A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway Is Associated With Major Depressive Disorder
- Automated Classification of Depression From Structural Brain Measures Across Two Independent Community-Based Cohorts
- Genetic Stratification of Depression in UK Biobank
- A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank
- CRISPR disruption and UK Biobank analysis of a highly conserved polymorphic enhancer suggests a role in male anxiety and ethanol intake.