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.

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.

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).

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.

Scar theory proposes that heightened depression and anxiety precede and predict worse cognitive functioning outcomes, whereas the vulnerability theory posits the opposite pathway. However, most investigations on this topic have been cross-sectional, precluding causal inferences. Thus, we used cross-lagged prospective network analyses to facilitate causal inferences in understanding the relations between psychopathology and cognitive functioning components.

Racially-diverse midlife women (n = 1816) participated in the Study of Women's Health Across the Nation at two time-points, spanning one year apart. Five psychopathology (anxiety severity, depressed mood, somatic symptoms, positive affect, interpersonal problems) and four cognitive functioning nodes (working memory (WM), processing speed (PS), facial recognition (FCR), and verbal memory (VRM)) were assessed. All analyses adjusted for age, menopausal status, estradiol, and follicle-stimulating hormones.

Contemporaneous networks yielded notable inverse between-node relations (edges) between interpersonal problems and reduced FCR and PS, and between depressed mood and lower FCR, VRM, or PS. Nodes that had the highest likelihood to bridge other constructs were positive affect, anxiety severity, WM, and VRM. Temporal networks produced edges consistent with the scar (v. vulnerability) hypotheses. Higher somatic symptoms were related to reduced PS and WM, and greater depressed mood was correlated with lower future PS and WM. Also, higher anxiety severity coincided with decreased future PS and WM. Greater positive affect was associated with stronger future PS, FCR, and WM. Also, positive affect had the strongest relations with other nodes.

Findings suggest the importance of targeting symptoms and cognitive functioning simultaneously.

Scar models posit that heightened anxiety and depression can increase the risk for subsequent reduced executive function (EF) through increased inflammation across months. However, the majority of past research on this subject used cross-sectional designs. We therefore examined if elevated generalized anxiety disorder (GAD), major depressive disorder (MDD), and panic disorder (PD) symptoms forecasted lower EF after 20 months through heightened inflammation.

Community-dwelling adults partook in this study (n = 614; MAGE = 51.80 years, 50% females). Time 1 (T1) symptom severity (Composite International Diagnostic Interview – Short Form), T2 (2 months after T1) inflammation serum levels (C-reactive protein, fibrinogen, interleukin-6), and T3 (20 months after T1) EF (Brief Test of Adult Cognition by Telephone) were assessed. Structural equation mediation modeling was performed.

Greater T1 MDD and GAD (but not PD) severity predicted increased T2 inflammation (Cohen's d = 0.21–1.92). Moreover, heightened T2 inflammation forecasted lower T3 EF (d = −1.98 to −1.87). T2 inflammation explained 25–32% of the negative relations between T1 MDD or GAD and T3 EF. T1 GAD severity predicting T3 EF via T2 inflammation path was stronger among younger (v. older) adults. Direct effects of T1 MDD, GAD, and PD forecasting decreased T3 EF were found (d = −2.02 to −1.92). Results remained when controlling for socio-demographic, physical health, and lifestyle factors.

Inflammation can function as a mechanism of the T1 MDD or GAD–T3 EF associations. Interventions that successfully treat depression, anxiety, and inflammation-linked disorders may avert EF decrements.