Understanding the links between inflammation and depression, and the potential roles of sociodemographic and other non-genetic factors in mediating or moderating this association.
Principal Investigator:
Professor Chris Dickens
Approved Research ID:
8009
Approval date:
September 1st 2015
Lay summary
We aim to understand the role of inflammation in predicting the development of depression among adults in the UK. Our study will address the following questions. I. Does genetic variation associated with variation in levels of key inflammatory mediators [i.e. interleukin -1beta, interleukin 1 receptor antagonist, interleukin 2, interleukin 6, tumour necrosis factor alpha, interleukin 10, interferon gamma] predict depression: i. In the Biobank population , ii. Among people with chronic physical illness II. Which socio-demographic and other non-genetic risk factors i) predict depression ii) potentially moderate or mediates the association between inflammation and depression. Our research meets the stated aims of the Biobank to improve the prevention and treatment of serious illnesses. Depression is ranked No.3 on the WHO?s list of causes of Global Burden of Disease and projected to rise to No.1 by 2020. By elucidating basic mechanisms underlying the development, maintenance and relapse of depression in the population at large and / or among people with chronic physical health problems, our research has potential to help identify people at greatest risk of developing depression, and to possibly contribute to the development of novel interventions to prevent and treat depression. Initially we will conduct an analysis of the prevalence of depression using data from the Biobank and linked databases. We will then compare depressed and non-depressed participants on a range of variables that have been shown in previous studies to be associated with the onset of depression and which were recorded in the Biobank baseline assessment. Once genetic data are available we will compare depressed and non-depressed for differences in the frequency of the genetic markers that have been shown to be linked to inflammation, to see whether there is an association between genes for inflammation and depression. We require access to data from the whole cohort. No samples are required at this time.