| Title: | Systemic inflammation, multimorbidity and specific types of depressive symptoms |
| Lead Institution: | University College London |
| Principal investigator: | Professor Mika Kivimaki |
Application 60565
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About
Depression is a complex and debilitating mental health condition, which affects approximately 4% of the UK population. The causes of depression remain poorly understood. Previous research suggests that the immune system may play an important role in the development of the disease. Specifically, elevated levels of inflammation in the periphery of the body have been linked to structural and functional changes in the brain and depression. However, while this association has been observed in some studies, other studies have not found evidence for such a relationship. Interestingly, health behaviours (e.g. sleep, diet, physical activity), a range of mental and physical conditions, multimorbidity, and their risk factors have also been implicated in both the development of depression and the regulation of inflammatory processes. The first objective of this study is to test whether people with elevated levels of inflammation are more likely to be depressed and present with specific changes in the structure of the brain. Moreover, we will explore the possibility of inflammation being associated only with specific types of depressive symptoms. Depression is characterised by a variety of symptoms, including cognitive-affective (e.g. low mood, loss of pleasure) and somatic (e.g. lack of energy, sleep problems) symptoms. We hypothesise that inflammation may be particularly important for the manifestation of somatic symptoms. Second, we will examine whether behavioural factors (sleep, diet and physical activity) and physical health conditions (e.g. cardiovascular disease) influence the relationship between inflammation and depression. Lastly, we aim to investigate the direction of the association between inflammation and depression - i.e. whether inflammation is a cause, consequence or only correlate of depression. Accordingly, we will use novel statistical approaches to test whether a summary score of genetic variants associated with inflammation is causally related to depression, and/or vice versa (i.e. whether genetic variants associated with depression are causally related to inflammation). The proposed research project will take approximately 24 months to complete. We anticipate that our findings will have substantial public health implications, which ultimately benefit people with depression and inflammatory diseases. Specifically, depending on the results of our study, it may inform the design of future trials testing the efficacy of anti-inflammatory/anti-depressant drugs on depression/inflammation. Importantly, prevention is better than treatment. Our findings may also have the potential to provide direction for the development of tailored programmes preventing the occurrence of the disease in the first place.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 11516 | Estimating Dementia Risk Using Multifactorial Prediction Models | Mika Kivimäki (+10) | 2023 | JAMA Network Open |
| 11240 | Severe Infection and Risk of Cardiovascular Disease: A Multicohort Study | Pyry N. Sipilä (+13) | 2023 | Circulation |
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