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

处理极端C反应蛋白(CRP)值和正则化如何影响网络分析中CRP与抑郁症诊断标准的关联

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Abstract

Increasingly, it has been recognized that analysis at the symptom, rather than diagnostic, level will drive progress in the field of immunopsychiatry. Network analysis offers a useful tool in this pursuit with the ability to identify associations between immune markers and individual symptoms, independent of all other variables modeled. However, investigation into how methodological decisions (i.e., including vs. excluding participants with C-reactive protein (CRP) >10 mg/L, regularized vs. nonregularized networks) influence results is necessary to establish best practices for the use of network analysis in immunopsychiatry. In a sample of 3,464 adult participants from the 2015-2016 National Health and Nutrition Examination Survey dataset, this study found consistent support for associations between CRP and fatigue and changes in appetite and some support for additional CRP-criterion associations. Methodologically, results consistently demonstrated that including individuals with CRP >10 mg/L and estimating nonregularized networks provided better estimates of these associations. Thus, we recommend considering the use of nonregularized networks in immunopsychiatry and inclusion of cases with CRP values >10 mg/L when testing the association between CRP and depression criteria, unless contraindicated by the research question being tested. Additionally, results most consistently suggest that CRP is uniquely related to fatigue and changes in appetite, supporting their inclusion in an immunometabolic phenotype of depression. Finally, these associations suggest that fatigue and changes in appetite might be particularly receptive to anti-inflammatory treatments. However, future research with more nuanced measures is necessary to parse out whether appetite increases or decreases drive this association. Further, longitudinal research is an important next step to test how these relationships manifest over time.

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