Prospective network analysis of proinflammatory proteins, lipid markers, and depression components in midlife community women

Abstract

Background Vulnerability theories propose that suboptimal levels of lipid markers and proinflammatory proteins predict future heightened depression. Scar models posit the reverse association. However, most studies that tested relationships between non-specific immune/endocrine markers and depression did not separate temporal inferences between people and within-person and how different immunometabolism markers related to unique depression symptoms. We thus used cross-lagged prospective network analyses (CLPN) to investigate this topic. Methods Community midlife women (n = 2224) completed the Center for Epidemiologic Studies-Depression scale and provided biomarker samples across five time-points spanning 9 years. CLPN identified significant relations (edges) among components (nodes) of depression (depressed mood, somatic symptoms, interpersonal issues), lipid markers [insulin, fasting glucose, triglycerides, low-density lipoprotein-cholesterol (LDL), high-density lipoprotein-cholesterol (HDL)], and proinflammatory proteins [C-reactive protein (CRP), fibrinogen], within and across time-points. All models adjusted for age, estradiol, follicle-stimulating hormone, and menopausal status. Results In within-person temporal networks, higher CRP and HDL predicted all three depression components (d = 0.131–2.112). Increased LDL preceded higher depressed mood and interpersonal issues (v. somatic symptoms) (d = 0.251–0.327). Elevated triglycerides predicted more somatic symptoms (v. depressed mood and interpersonal problems) (d = 0.131). More interpersonal problems forecasted elevated fibrinogen and LDL levels (d = 0.129–0.331), and stronger somatic symptoms preceded higher fibrinogen levels (d = 0.188). Conclusions Results supported both vulnerability and scar models. Long-term dysregulated immunometabolism systems, social disengagement, and related patterns are possible mechanistic accounts. Cognitive-behavioral therapies that optimize nutrition and physical activity may effectively target depression.

Symptom Network Analysis Tools for Applied Researchers with Cross-Sectional and Panel Data – A Brief Overview and Multiverse Analysis

“…The proportion of times an edge is present in each of the bootstrapped samples allows researchers to judge the stability of the network. Previously, edges included in more than 50% of times were considered stable (Zainal & Newman, 2022). The bootstrapping analysis indicated sufficient stability of the network structures (see Figures S3-S5).…”

“…A network is essentially a graphical representation consisting of both nodes (variables) and edges (associations between variables). As such, the versatile use of network modeling approaches, as a statistical toolbox, has expanded beyond the focus of symptoms to also integrate other sources of data in a network, including brain markers (Blanken et al, 2021), polygenic risk scores (Isvoranu et al, 2020) proteins and lipid markers (Zainal & Newman, 2022), as well as performance-based measures of cognition (Karalunas et al, 2021). Thus, SYMPTOM NETWORK MODELING TOOLS 4 network modeling has become a useful tool for investigating complex relationships among various factors in a range of different domains.…”

Vitamin B12, Folate, Homocysteine, Inflammatory Mediators (Interleukin-6, Tumor Necrosis Factor-α and C-Reactive Protein) Levels in Adolescents with Anxiety or Depressive Symptoms

“… 30 Persistent chronic inflammation can dysregulate the hypothalamic-pituitary-adrenal (HPA) axis function, disturb neurotransmitter metabolism, impair neurons, and alter neural activity in the brain regions involved in emotion regulation, which results in anxiety and depression symptoms. 31–33 …”

“…30 Persistent chronic inflammation can dysregulate the hypothalamic-pituitary-adrenal (HPA) axis function, disturb neurotransmitter metabolism, impair neurons, and alter neural activity in the brain regions involved in emotion regulation, which results in anxiety and depression symptoms. [31][32][33] The key mediators of innate and adaptive immunity, called inflammatory mediators, especially tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and C-reactive protein (CRP), play a great role in the pathophysiology of depression and anxiety. 32 Evidence supported that patients with depression or anxiety had higher TNF-α, IL-6, or CRP levels, which were positively correlated with the severity of anxiety and depression symptoms.…”

Understanding the protective effect of social support on depression symptomatology from a longitudinal network perspective

“…The cross-lagged panel network (CLPN) model that combines the cross-lagged model and network model of mental disorders enables modelling of temporal effects between individual nodes within the network using panel data 13. The CLPN methodology has been applied in a few depression studies 14–16. Although there have recently been emerging longitudinal network studies of cognitive factors and depressive symptoms,17 18 to our knowledge, no similar study has been conducted to investigate the relationship between social support and depressive symptoms.…”