Literature DB >> 31615595

Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates.

E I Fried1, S von Stockert2, J M B Haslbeck2, F Lamers3, R A Schoevers4, B W J H Penninx5.   

Abstract

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.

Entities:  

Keywords:  Body mass index; depression; individual depressive symptoms; inflammation; network analysis

Year:  2019        PMID: 31615595     DOI: 10.1017/S0033291719002770

Source DB:  PubMed          Journal:  Psychol Med        ISSN: 0033-2917            Impact factor:   7.723


  30 in total

1.  Toward a Complex Network of Risks for Psychosis: Combining Trauma, Cognitive Biases, Depression, and Psychotic-like Experiences on a Large Sample of Young Adults.

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2.  Connecting the dots: a comparison of network analysis and exploratory factor analysis to examine psychosocial syndemic indicators among HIV-negative sexual minority men.

Authors:  J S Lee; S A Bainter; A W Carrico; T R Glynn; B G Rogers; C Albright; C O'Cleirigh; K H Mayer; S A Safren
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Review 3.  Major Depressive Disorder in Older Patients as an Inflammatory Disorder: Implications for the Pharmacological Management of Geriatric Depression.

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Journal:  Drugs Aging       Date:  2021-04-29       Impact factor: 3.923

4.  Networks of inflammation, depression, and cognition in aging males and females.

Authors:  Rebecca A Chalmers; Matti Cervin; Carol Choo; Bernhard T Baune; Julian N Trollor; Katya Numbers; Perminder S Sachdev; Henry Brodaty; Nicole A Kochan; Oleg N Medvedev
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Review 5.  Beyond diagnoses and total symptom scores: Diversifying the level of analysis in psychoneuroimmunology research.

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6.  Reward Responsiveness and Ruminative Styles Interact to Predict Inflammation and Mood Symptomatology.

Authors:  Daniel P Moriarity; Tommy Ng; Madison K Titone; Iris K-Y Chat; Robin Nusslock; Gregory E Miller; Lauren B Alloy
Journal:  Behav Ther       Date:  2019-11-26

7.  Network analyses reveal which symptoms improve (or not) following an Internet intervention (Deprexis) for depression.

Authors:  Michael C Mullarkey; Aliza T Stein; Rahel Pearson; Christopher G Beevers
Journal:  Depress Anxiety       Date:  2019-11-11       Impact factor: 6.505

8.  Inflammatory phenotype of depression symptom structure: A network perspective.

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Journal:  Brain Behav Immun       Date:  2020-12-09       Impact factor: 7.217

9.  How handling extreme C-reactive protein (CRP) values and regularization influences CRP and depression criteria associations in network analyses.

Authors:  Daniel P Moriarity; Sarah R Horn; Marin M Kautz; Jonas M B Haslbeck; Lauren B Alloy
Journal:  Brain Behav Immun       Date:  2020-10-22       Impact factor: 7.217

10.  The importance of transdiagnostic symptom level assessment to understanding prognosis for depressed adults: analysis of data from six randomised control trials.

Authors:  C O'Driscoll; J E J Buckman; E I Fried; R Saunders; Z D Cohen; G Ambler; R J DeRubeis; S Gilbody; S D Hollon; T Kendrick; D Kessler; G Lewis; E Watkins; N Wiles; S Pilling
Journal:  BMC Med       Date:  2021-05-06       Impact factor: 8.775

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