1 Summary: Disputing other findings, researchers report there is no direct link between inflammation and depression. The study reports depression may only have a link to inflammation as a result of specific lifestyle features, such as smoking or obesity. Source: Leiden University Depression has traditionally been linked to increased inflammation. Innovative research by psychologist Eiko Fried refutes this popular assumption. He shows that specific depression symptoms such as sleeping problems explain this relationship. Publication in Psychological Medicine. Over the past few decades, there have been many studies into the relationship between depression and inflammation in the body. A number of these showed that people with depression have higher inflammation levels in their blood and the conclusion was that inflammation could be a potential marker for diagnosing depression. Traditionally, inflammation is related to the flu or serious diseases such as cardiovascular disease. Some symptoms have more impact Fried and his colleagues have discovered that there is no direct link between depression and inflammation. Depression is a very heterogeneous disorder with many symptoms, and unlike most previous research, Fried included 28 different symptoms of depression and a number of important lifestyle factors. “Some specific depression symptoms appear to be related to increased inflammation, such as sleep problems,” says Fried. Furthermore, obesity and unhealthy lifestyle choices such as smoking appear to be related with increased inflammation. In other words, depression is only linked to inflammation in participants who exhibit very specific features, and not generally. In addition, as is well known in the literature, inflammation is more common in women. Network analyses The study underlines the importance of controlling for covariates, factors that may influence the outcome. For the research, Fried used the database of the Dutch Study on Depression and Anxiety, with the data of more than 2,300 people, along the whole continuum of depression (from healthy to severely depressed). He was able to determine the relationship between individual symptoms and inflammation with the aid of network analyses. These involved large and complex static models that have only just been introduced in psychology. Furthermore, obesity and unhealthy lifestyle choices such as smoking appear to be related with increased inflammation. The image is in the public domain. Hype about biomarkers The findings are important in the current discussion, says Fried. “There is a hype about finding biomarkers, traces of disorders that can be measured in the human body, such as the blood. Over the past 30 years, scientists have been looking for biomarkers for depression hoping to answer the question: can you also measure depression by testing someone’s blood, for example? Instead of conducting extensive diagnostic interviews, psychiatrists could then test someone’s blood. No clinically useful biomarkers have been found so far, and one of the remaining hopes—inflammation—has largely been refuted as well.” Fried adds that the study was in part based on the excellent master’s thesis by Sophia von Stockert. [divider]About this neuroscience research article[/divider] Source: Leiden University Media Contacts: Eiko Fried – Leiden University Image Source: The image is in the public domain. Original Research: Closed access “Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates”. E. I. Fried et al. Psychological Medicine doi:10.1017/S0033291719002770.See alsoFeaturedNeuroscienceOpen Neuroscience Articles·March 17, 2020‘Stealth Transmission’ Fuels Fast Spread of COVID-19 Outbreak Abstract Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates Background Studies investigating the link between depressive symptoms and inflammation have yielded inconsistent results, which may be due to two factors. First, studies differed regarding the specific inflammatory markers studied and covariates accounted for. Second, specific depressive symptoms may be differentially related to inflammation. We address both challenges using network psychometrics. Methods We estimated seven regularized Mixed Graphical Models in the Netherlands Study of Depression and Anxiety (NESDA) data (N = 2321) to explore shared variances among (1) depression severity, modeled via depression sum-score, nine DSM-5 symptoms, or 28 individual depressive symptoms; (2) inflammatory markers C-reactive protein (CRP), interleukin 6 (IL-6), and tumor necrosis factor α (TNF-α); (3) before and after adjusting for sex, age, body mass index (BMI), exercise, smoking, alcohol, and chronic diseases. Results The depression sum-score was related to both IL-6 and CRP before, and only to IL-6 after covariate adjustment. When modeling the DSM-5 symptoms and CRP in a conceptual replication of Jokela et al., CRP was associated with ‘sleep problems’, ‘energy level’, and ‘weight/appetite changes’; only the first two links survived covariate adjustment. In a conservative model with all 38 variables, symptoms and markers were unrelated. Following recent psychometric work, we re-estimated the full model without regularization: the depressive symptoms ‘insomnia’, ‘hypersomnia’, and ‘aches and pain’ showed unique positive relations to all inflammatory markers. Conclusions We found evidence for differential relations between markers, depressive symptoms, and covariates. Associations between symptoms and markers were attenuated after covariate adjustment; BMI and sex consistently showed strong relations with inflammatory markers. [divider]Feel free to share this Psychology News.[/divider] Join our Newsletter I agree to have my personal information transferred to AWeber for Neuroscience Newsletter ( more information ) Sign up to receive the latest neuroscience headlines and summaries sent to your email daily from NeuroscienceNews.comWe hate spam and only use your email to contact you about newsletters. We do not sell email addresses. You can cancel your subscription any time.