REVIEWInflammation and clinical response to treatment in depression: A meta-analysis
Introduction
An aberrant inflammatory profile has been widely demonstrated in depressive disorders and is believed to contribute to some of the biological mechanisms associated with disease onset and treatment response (Dowlati et al., 2010, Miller et al., 2009, Smith, 1991). Recent evidence suggests that levels of inflammation might be modifiable with pharmacological treatment (Hannestad et al., 2011, Hiles et al., 2012, Janssen et al., 2010) and preliminary evidence indicates that treatment resistance might be associated with heightened inflammation. Additionally, non-steroidal anti-inflammatory drugs might be beneficial as adjunctive treatments in unipolar (Akhondzadeh et al., 2009, Muller et al., 2006) and bipolar (Nery et al., 2008) disorders and the TNFα antagonist infliximab may particularly benefit depressed individuals with a history of treatment resistance and high inflammation (Raison et al., 2013). Treatment non-response contributes greatly to the burden of affective illnesses (Gibson et al., 2010); it is common, affecting at least a third of patients (Warden et al., 2007), and is generally associated with poorer long-term outcomes (Fekadu et al., 2009). To improve the rate and robustness of clinical response in depression there is a need for novel treatment strategies (Kupfer et al., 2012), including enhancing the personalisation of treatment provision using stratification. As such, research has been increasingly focusing on the importance of effectively screening for predictors of response across depressed populations, and using putative biomarker signatures prior to treatment provision may help to identify objective biological differences between patients who do or do not respond to treatments. Measuring ‘panels’ of biomarkers may assist with the discovery of biological signatures for disorders such as depression (Schmidt et al., 2011), which also may be supported using meta-analytic techniques that provide greater statistical power than individual studies. Combining these two approaches may be useful for identifying inflammatory relationships with depressed state and response to treatment, particularly as studies measuring different (but similar) data points cannot otherwise be compared in a high-powered analysis. We describe a new methodology of combining inflammatory data from different biomarkers together to enable a substantially higher statistical power.
Another important factor in this relationship is whether inflammatory profiles within a depressed state might differ between individuals with unipolar and bipolar diagnoses: although this has not been established there is some indicative evidence that inflammation is not elevated in bipolar depressed state (Munkholm et al., 2013), as opposed to mania and euthymia.
With the aim of expanding on previous work, we investigated studies measuring inflammatory biomarkers in depression in relation to treatment response and hypothesised that (a) non-responsive patients would have higher levels of inflammation at baseline than responders; (b) patients would show a decrease in levels of inflammation after a course of treatment, but that; (c) treatment refractoriness would be characterised by persistently high levels of inflammation.
Section snippets
Criteria for study inclusion
A systematic search of the literature was conducted to obtain all studies that measured inflammatory responses in depression at baseline and following a course of treatment, and that also assessed treatment response. A priori inclusion criteria required eligible studies to be in English, measure in vivo at least one peripheral biomarker purporting to measure inflammation in human subjects classified as being in a depressive episode according to a clinician-rated standardised measure of
Results
The literature search yielded a total of 2053 articles, of which 35 met inclusion criteria (see Figure 1 and Table 1 for details and reasons for exclusion). All included studies investigated unipolar major depression except for one that only included bipolar diagnosed patients in a depressive episode (Tsai et al., 2014), and three that included both bipolar and unipolar depression (Himmerich et al., 2006, Landmann et al., 1997, Maes et al., 1995) but did not compare inflammation between the two
Discussion
To our knowledge this is the first meta-analysis to investigate systematically the relationship between inflammation and treatment resistance in depression, both as a predictive marker and in maintenance of the illness. We found that prospectively-determined treatment resistance is associated with continued elevations in inflammation, in that there is a decrease in TNFα levels over time in treatment-responsive but not in treatment-resistant patients. We also examined a novel method for merging
Role of funding source
This paper presents independent research partly funded by the National Institute for Health Research (NIHR) and the NIHR Biomedical Resource Centre for Mental Health; the NIHR had no further involvement in the methodology, findings or development of this paper.
Contributors
R Strawbridge, Prof. Cleare & Dr. Papadopoulos conceived the design and methodology. R Strawbridge conducted the systematic review and meta-analysis, as well as primarily writing the manuscript. Dr. Arnone advised on and contributed to
Acknowledgements
We thank Dr. Rudolf Uher, Dr. Reiji Yoshimura, Dr. Livia Carvalho, Professor Hubertus Himmerich, Dr. Po-See Chen, Dr. Tony Harley, and Dr. Marcus Ising for kindly providing us with data from their studies.
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