Inflammatory phenotype of depression symptom structure: A network perspective

Perceived Control and Inflammation: Mediating and Moderating Effects in the Relationship Between Cumulative Trauma and Depression

OBJECTIVE

The effects of trauma exposure on depression risk and severity are well established, but psychosocial and biological factors that impact or explain those relationships remain poorly understood. This study examined the moderating and mediating effects of perceived control and inflammation in the relationship between trauma and depression.

METHODS

Moderation analyses and longitudinal mediation analyses were conducted on data from 945 adults who completed all three waves (spanning around 19 years) of the Midlife Development in the United States (MIDUS) study and the MIDUS Biomarker Study. Data were collected during a phone interview, self-report surveys distributed in the mail, and an in-person blood draw. Two dimensions of perceived control-mastery and constraints-were examined separately in all analyses.

RESULTS

Perceived control did not significantly moderate the relationship between trauma and depression severity at MIDUS 2 ( b = 0.03, SE = .02, p = .091). Constraints significantly mediated the relationship between trauma and MIDUS 3 depression (indirect effect = 0.03, SE = 0.01, p = .016) but not after accounting for MIDUS 2 depression. Perceived control did not have a significant moderating effect in the relationships between trauma and inflammation or inflammation and depression.

CONCLUSIONS

Findings from this study revealed that perceived control may be better characterized as an explanatory factor rather than a buffer in trauma-associated depression. Perceived constraints in particular may be a useful treatment target for trauma-associated depression. Further research is needed to examine whether these results generalize to populations other than among mostly non-Hispanic White adults in the United States.

Effects of elevated emotional symptoms on metabolic disease development: a 10-year follow-up study

Background

In recent decades, the relationship between emotional disorders (i.e., depression and anxiety) and alterations in physiological functions (i.e., inflammation or metabolism) have been well supported. However, studies on a symptom-based approach have provided mixed results. Our study aims to gain insight into how subclinical statuses, featured by elevated depressive and/or anxious symptoms, may influence immunometabolic alterations in the concurrent relationship; and the development of metabolic diseases at 10-year follow-up: diabetes, hypertension and hypercholesterolemia.

Methods

Data from 758 Greek adults [394 men (aged 41 ± 10 years) and 364 women (aged 37 ± 12 years)] were used. Four groups were created according to the levels of depressive and anxiety symptoms: (1) control group (CG), (2) depressive group (DG), (3) anxiety group (AG) and (4) depressive and anxiety group (DAG). Multi-indicator multi-causes (MIMIC) modeling was used to estimate metabolic function and inflammatory response scores, on a wide selection of blood biomarkers. Finally, a binary logistic regression was carried out to study the influence of symptoms on the development of the aforementioned metabolic diseases on a 10-year follow-up.

Results

Group membership was not associated with metabolic function score. Conversely, DAG membership was related with higher inflammatory response score (B = 0.20, CI95 = 0.01, 0.40), with respect to the CG (p < 0.05). Both age and sex were significant variables in the calculation of both scores. Regarding disease at 10-year follow-up effect, risk of developing diabetes, hypertension and hypercholesterolemia was associated with age and socioeconomic status. Moreover, DG membership was significant for diabetes risk (OR = 2.08, CI95 = 1.00, 4.22) and DAG for hypercholesterolemia (OR = 1.68, CI95 = 1.16, 2.43).

Limitations

Data on anti-inflammatory drugs and psychopharmacological medication were not collected in this study.

Conclusions

Elevated symptoms of depression and anxiety accounts for inflammatory alterations at concurrent relationship and a higher risk of 10-year follow-up metabolic diseases.

Networks of C-reactive protein and depression symptoms in patients with stable coronary heart disease: Findings from the Heart and Soul Study

OBJECTIVE

Research addressing the associations between C-reactive protein (CRP) and depression among patients with stable coronary heart disease (CHD) has produced inconsistent results. This might be attributable to varying associations of CRP with specific depression symptom profiles. We responded to this challenge using various network analysis techniques.

METHODS

A total of 967 outpatients with documented CHD were drawn from the baseline cross-sectional data of the Heart and Soul Study. We first estimated mixed graphical models that included CRP and individual depression symptoms, before and after adjusting for relevant covariates, to explore whether CRP is correlated with specific facets of depression. We also investigated whether CRP levels moderated the associations between specific depression symptoms using moderated network models. Finally, we performed a network comparison test and compared the symptom network properties between non-elevated and elevated CRP groups.

RESULTS

In the network model without covariates, CRP was positively associated with fatigue, appetite changes, and psychomotor problems. CRP maintained its negative association with concentration difficulty regardless of covariate adjustment. Few symptom-symptom associations, especially those involving appetite changes, were moderated by CRP. Further, the elevated CRP group showed greater overall symptom connectivity as compared to the non-elevated group.

CONCLUSION

This study segues into CRP-depression relationship with sophisticated methodology.

Immunometabolic alterations in older adults with heightened depressive symptom trajectories: a network approach

Objective: To analyse the patterns of relationships between depressive symptoms and immunometabolic markers across longitudinal depression status in older people. Methods: A sample of 3349 older adults (55.21% women; initial age: m = 58.44, sd = 5.21) from the English Longitudinal Study of Ageing was used. Participants were classified according to their longitudinal depression status: minimal depressive symptoms (n = 2736), depressive episode onset (n = 481), or chronic depression (n = 132). Network analysis was used to study the relationships between depression symptoms (CES-D 8 items), inflammatory (white blood cell, C-reactive protein, fibrinogen) and metabolic biomarkers (metabolic syndrome markers). Results: Network structure remained invariant across groups. The minimal symptom group had higher overall strength than both clinical groups (p < .01). Moreover, significant relationships between symptoms and markers were observed across group-specific networks. C-reactive protein and effort symptom were positively connected in the minimal symptom group but not in the other groups. Loneliness and diastolic blood pressure were positively associated only in the chronic depression group. Finally, metabolic markers were identified as central nodes in the clinical status networks. Conclusion: The network analysis constitutes a useful approach to disentangle pathophysiological relationships that may maintain mental disorders in old age.

Mediation of the Association Between Vascular Risk Factors and Depressive Symptoms by C-Reactive Protein

Background

This study examined whether C-reactive protein (CRP), a marker of low-grade systemic inflammation, mediates the association between vascular risk factor (VRF) burden and depressive symptoms.

Methods

We drew on the prospective design of the UK Biobank to include participants with longitudinal data on VRF burden, CRP, and depressive symptoms. Total, direct, and indirect effects were estimated using regression-based mediation models while controlling for confounding by sociodemographic factors, baseline CRP, and baseline depression. Sensitivity analyses probed the robustness of results to unmeasured confounding.

Results

We analyzed data from 10,470 participants from the UK Biobank (mean age = 56.75 years at baseline). Net of covariates, VRFs at baseline were associated with higher depressive symptoms at follow-up (total effect = 0.099; 95% CI, 0.002-0.163). CRP mediated this association (indirect effect = 0.010; 95% CI, 0.004-0.017), accounting for 10.0% (95% CI, 0.3%-30.0%) of the total effect of VRF burden on depressive symptoms. Exploratory analyses suggested that the total and indirect effects pertained to somatic depressive symptoms (tiredness and appetite).

Conclusions

These results suggest that inflammation-promoting effects of VRFs may contribute to depressive symptoms in mid- and later life. However, the mediating pathway via CRP explains only a small part of the association between VRFs and depression after accounting for important covariates and may pertain to specific depressive symptoms. Future studies leveraging similar longitudinal designs are needed to further disentangle the time-varying effects between VRFs, inflammation, and certain depressive symptoms while addressing important confounders.

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

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.

Disentangling heterogeneity of psychosis expression in the general population: sex-specific moderation effects of environmental risk factors on symptom networks

BACKGROUND

Psychosis expression in the general population may reflect a behavioral manifestation of the risk for psychotic disorder. It can be conceptualized as an interconnected system of psychotic and affective experiences; a so-called 'symptom network'. Differences in demographics, as well as exposure to adversities and risk factors, may produce substantial heterogeneity in symptom networks, highlighting potential etiological divergence in psychosis risk.

METHODS

To explore this idea in a data-driven way, we employed a novel recursive partitioning approach in the 2007 English National Survey of Psychiatric Morbidity (N = 7242). We sought to identify 'network phenotypes' by explaining heterogeneity in symptom networks through potential moderators, including age, sex, ethnicity, deprivation, childhood abuse, separation from parents, bullying, domestic violence, cannabis use, and alcohol.

RESULTS

Sex was the primary source of heterogeneity in symptom networks. Additional heterogeneity was explained by interpersonal trauma (childhood abuse and domestic violence) in women and domestic violence, cannabis use, ethnicity in men. Among women, especially those exposed to early interpersonal trauma, an affective loading within psychosis may have distinct relevance. Men, particularly those from minority ethnic groups, demonstrated a strong network connection between hallucinatory experiences and persecutory ideation.

CONCLUSION

Symptom networks of psychosis expression in the general population are highly heterogeneous. The structure of symptom networks seems to reflect distinct sex-related adversities, etiologies, and mechanisms of symptom-expression. Disentangling the complex interplay of sex, minority ethnic group status, and other risk factors may help optimize early intervention and prevention strategies in psychosis.

Importance of immunometabolic markers for the classification of patients with major depressive disorder using machine learning

BACKGROUND

Although there is scientific evidence of the presence of immunometabolic alterations in major depression, not all patients present them. Recent studies point to the association between an inflammatory phenotype and certain clinical symptoms in patients with depression. The objective of our study was to classify major depression disorder patients using supervised learning algorithms or machine learning, based on immunometabolic and oxidative stress biomarkers and lifestyle habits.

METHODS

Taking into account a series of inflammatory and oxidative stress biomarkers (C-reactive protein (CRP), tumor necrosis factor (TNF), 4-hydroxynonenal (HNE) and glutathione), metabolic risk markers (blood pressure, waist circumference and glucose, triglyceride and cholesterol levels) and lifestyle habits of the participants (physical activity, smoking and alcohol consumption), a study was carried out using machine learning in a sample of 171 participants, 91 patients with depression (71.42% women, mean age = 50.64) and 80 healthy subjects (67.50% women, mean age = 49.12). The algorithm used was the support vector machine, performing cross validation, by which the subdivision of the sample in training (70%) and test (30%) was carried out in order to estimate the precision of the model. The prediction of belonging to the patient group (MDD patients versus control subjects), melancholic type (melancholic versus non-melancholic patients) or resistant depression group (treatment-resistant versus non-treatment-resistant) was based on the importance of each of the immunometabolic and lifestyle variables.

RESULTS

With the application of the algorithm, controls versus patients, such as patients with melancholic symptoms versus non-melancholic symptoms, and resistant versus non-resistant symptoms in the test phase were optimally classified. The variables that showed greater importance, according to the results of the area under the ROC curve, for the discrimination between healthy subjects and patients with depression were current alcohol consumption (AUC = 0.62), TNF-α levels (AUC = 0.61), glutathione redox status (AUC = 0.60) and the performance of both moderate (AUC = 0.59) and vigorous physical exercise (AUC = 0.58). On the other hand, the most important variables for classifying melancholic patients in relation to lifestyle habits were past (AUC = 0.65) and current (AUC = 0.60) tobacco habit, as well as walking routinely (AUC = 0.59) and in relation to immunometabolic markers were the levels of CRP (AUC = 0.62) and glucose (AUC = 0.58). In the analysis of the importance of the variables for the classification of treatment-resistant patients versus non-resistant patients, the systolic blood pressure (SBP) variable was shown to be the most relevant (AUC = 0.67). Other immunometabolic variables were also among the most important such as TNF-α (AUC = 0.65) and waist circumference (AUC = 0.64). In this case, sex (AUC = 0.59) was also relevant along with alcohol (AUC = 0.58) and tobacco (AUC = 0.56) consumption.

CONCLUSIONS

The results obtained in our study show that it is possible to predict the diagnosis of depression and its clinical typology from immunometabolic markers and lifestyle habits, using machine learning techniques. The use of this type of methodology could facilitate the identification of patients at risk of presenting depression and could be very useful for managing clinical heterogeneity.

C-Reactive Protein and Specific Depression Symptoms Among Older Adults: An Exploratory Investigation of Multi-Plane Networks Using Cross-Sectional Data From NHANES (2017-2020)

INTRODUCTION

Studies investigating the association between C-reactive protein (CRP) and depression among older adults have yielded inconsistent results. We suspect that this may be due to varying associations between CRP and particular depression symptom criteria, and we addressed this challenge using network analysis.

METHODS

We used cross-sectional data from prepandemic National Health and Nutrition Examination Survey questionnaires (2017-2020) and included a sample of 1698 adults aged 65 years or older. Depression symptoms were assessed using the Patient Health Questionnaire-9. Unregularized Mixed Graphical Models were estimated using the R package mgm before and after adjusting for relevant sociodemographic, clinical, and lifestyle covariates.

RESULTS

In the model with no covariates, the only symptom criterion associated with CRP was "appetite problems." This association remained robust after controlling for all covariates. Although not associated with CRP, other criteria such as "fatigue" and "concentration difficulty" showed associations with important covariates for older adults such as white blood cell count or hemoglobin, respectively.

DISCUSSION

The CRP-related variability in the depression symptom network that we have demonstrated may help explain the reported inconsistencies. The present study stands as exploratory, and future research should focus on applying longitudinal designs and including several other inflammatory proteins and covariates that were not measured in the current network model.

Allostatic load as a mediator of childhood maltreatment and adulthood depressive symptoms: A longitudinal analysis

Childhood maltreatment (CM) is associated with several negative outcomes in adulthood, including major depression. People who experience CM that go on to develop symptoms of major depression in adulthood tend to have earlier depressive symptom onset and greater symptom severity than those who do not experience CM. Studies have utilized allostatic load (AL) to understand how CM "gets under the skin" to contribute to depressive symptoms. However, studies largely utilize cross-sectional designs and limited biomarkers. The present study uses data from Wave 2 and Wave 3 of the Midlife Development in the United States study in regression-based analyses, examining if AL mediates the relationship between CM and the number of depressive symptoms in adulthood. AL was measured at Wave 2 using the system risk method with 27 biomarkers across seven different systems. CM was measured using the Childhood Trauma Questionnaire at Wave 2. Number of depressive symptoms were measured using the Composite International Diagnostic Interview-Short Form at Wave 3. Past month perceived stress, age, household income, education, sex, racial/ethnic identity, and current prescription medication use at Wave 2 were included as controls. Analyses identified that CM was associated with AL cross-sectionally, and that both CM and AL at were associated with the number of depressive symptoms prospectively. AL partially mediated the effects of CM on the number of depressive symptoms. The present study is the first to identify the mediating role of AL in the relationship between CM and adulthood depressive symptoms in a longitudinal design.

Does the moderator matter? Identification of multiple moderators of the association between peripheral inflammatory markers and depression severity in a large racially diverse community cohort

Depressive symptomology has been linked to low-grade peripheral inflammatory markers (PIMs), specifically C-reactive protein (CRP) and white blood cell count (WBC). However, such associations may be affected by multiple moderators (including race/ethnicity), though few well-powered and racially diverse studies have examined this. We examined 31 moderators of PIM-depression relationships in a large racially diverse cohort (n = 21,570). We also examined if associations between PIM and depression severity were dependent on clinical cutpoints for moderate depressive symptoms and elevated CRP. We found several positive moderators of PIM-depression relationships for both WBC and CRP: ongoing medication use (antidepressant, statin, or any prescription drug), presence of sleep concerns, and poor health status (β's = 0.06-0.21, p's < 0.05). For both WBC and CRP, individuals of non-Hispanic White race/ethnicity were found to have stronger PIM-depression associations overall relative to minoritized groups (B's = 0.14 to 1.01, p's < 0.05). For CRP, stronger PIM-depression relationships existed for individuals with moderate (or greater) depression severity or elevated CRP (B's = 0.27 to 0.49, p's < 0.05). Thus, a wide range of moderators appears to affect PIM-depression associations. These results could help identify participants with strong coupling of PIM-depression severity, to guide future research and personalized treatments for depression and to indicate gaps in the applicability of widely referenced theoretical models among racial/ethnic minoritized groups.

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

BACKGROUND

Prioritizing the maintenance of healthy cognitive aging and personalizing preventive interventions to enhance their effectiveness is crucial as the global population ages. Systemic inflammation and depression in older people have been associated with decreased levels of cognition but results have been inconsistent.

AIMS

To explore the interactive network of inflammation, depression and cognition by sex in older people.

METHODS

We used novel network analysis to explore the unique associations between inflammatory biomarkers, depression, cognition, and somatic, genetic, and lifestyle risk factors in an older (aged 70-90 years), non-demented, community-dwelling sample from the longitudinal Sydney Memory and Aging Study (N = 916) at baseline and at a two-year follow-up.

RESULTS

The networks of biomarkers, depression, cognition, and relevant covariates were significantly different between males and females. A stable negative link between depression and cognition was found in females only; a stable positive association between biomarker interleukin-6 and depression was found in females only; and a stable positive association between biomarker interleukin-8 and alcohol was found in females only. For both males and females, a stable, positive relationship was found between the presence of APOE-ε4 gene and biomarker C-reactive protein; between education and cognition; and between biomarker interleukin-6 and all other biomarkers.

CONCLUSIONS

These findings suggest different psychophysiological mechanisms underlie the interactive network of biomarkers, depression and cognition in males and females that should be considered when designing personalized preventive interventions to maintain cognitively healthy aging.

Inflammatory cytokines and callosal white matter microstructure in adolescents

Adolescent depression is characterized by heightened inflammation and altered connectivity of fronto-cingulate-limbic tracts, including the genu of the corpus callosum (CCG) and the uncinate fasciculus (UF). No studies, however, have yet examined the association between inflammation, measured by peripheral levels of cytokines, and white matter connectivity of fronto-cingulate-limbic tracts in adolescents. Here, 56 depressed adolescents (32 females, 3 non-binary; 16.23 ± 1.28 years) and 19 controls (10 females; 15.72 ± 1.17 years) completed a diffusion-weighted MRI scan at 3 Tesla. We conducted deterministic tractography to segment bilateral corpus callosum (genu and splenium) and UF and computed mean fractional anisotropy (FA) in each tract. A subset of participants (43 depressed and 17 healthy controls) also provided dried blood spot samples from which we assayed interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-ɑ) using a Luminex multiplex array. Depressed participants did not differ from controls in FA of the corpus callosum or UF (all FDR-corrected ps > 0.056) but exhibited higher levels of inflammation than did controls (IL-6: β = 0.91, FDR-corrected p = 0.006; TNF-α: β = 0.76, FDR-corrected p = 0.006). Although diagnostic group did not moderate the associations between inflammatory cytokines and FA in the CCG and UF, across both groups, greater peripheral inflammation was associated with lower FA in the CCG (IL-6: β = -0.38; FDR-corrected p = 0.044; TNF-ɑ: β = -0.41, FDR-corrected p = 0.044). This study is the first to examine associations between peripheral inflammation and white matter microstructure of fronto-cingulate-limbic tracts in depressed and nondepressed adolescents. Future mechanistic studies are needed to confirm our findings; nevertheless, our results suggest that heightened inflammation is an important component of neurophenotypes that are relevant to adolescent depression.

C-Reactive Protein as a Biomarker for Major Depressive Disorder?

The etiopathogenesis of depression is not entirely understood. Several studies have investigated the role of inflammation in major depressive disorder. The present work aims to review the literature on the association between C-Reactive Protein (CRP) and depression. A systematic review was performed for the topics of ‘CRP’ and ‘depression’ using the PubMed database from inception to December 2021. Fifty-six studies were identified and included in the review. Evidence suggested the presence of dysregulation in the inflammation system in individuals with depression. In most studies, higher blood CRP levels were associated with greater symptom severity, a specific pattern of depressive symptoms, and a worse response to treatment. Moreover, about one-third of depressed patients showed a low-grade inflammatory state, suggesting the presence of a different major depressive disorder (MDD) subgroup with a distinct etiopathogenesis, clinical course, treatment response, and prognosis, which could benefit from monitoring of CRP levels and might potentially respond to anti-inflammatory treatments. This work provides robust evidence about the potential role of CRP and its blood levels in depressive disorders. These findings can be relevant to developing new therapeutic strategies and better understanding if CRP may be considered a valuable biomarker for depression.

Linking childhood trauma and cytokine levels in depressed adolescents

BACKGROUND

Evidence supports raised circulating levels of inflammatory mediators, such as interleukin-6 (IL-6) and tumor necrosis factor (TNFα), among clinically depressed adults, although preliminary findings in adolescents are mixed. Independently, meta-analyses identify correlations between childhood trauma and elevated cytokine levels in adulthood. Here, we examine the possible role of individual differences in exposure to childhood trauma in contributing to variability in cytokine levels in depressed adolescents.

METHODS

52 depressed adolescents and 20 healthy adolescents completed measures of childhood trauma and provided blood for the assessment of plasma IL-6 and TNFα. Cross-sectional associations of childhood trauma and cytokine measures were assessed in both depressed and healthy adolescents, along with exploratory analysis of childhood trauma subtypes. Longitudinal relationships between childhood trauma and cytokine measures were also studied in an exploratory fashion within a subset of depressed participants (n = 36).

RESULTS

Higher childhood trauma (particularly emotional abuse) was positively associated with TNFα in depressed adolescents. Childhood trauma was not linked to longitudinal changes in cytokine levels.

DISCUSSION

In depressed adolescents, childhood trauma may relate to higher levels of the proinflammatory cytokine TNFα and contribute to heterogeneity in cytokine elevation among depressed adolescents. Such findings may ultimately help guide more effective individualized treatments for adolescents with depression.

Building a replicable and clinically-impactful immunopsychiatry: Methods, phenotyping, and theory integration

Immunopsychiatry is a subfield of psychoneuroimmunology that integrates immunological and psychopathological processes with promise for improving the classification, identification, and treatment of psychopathology. Using research on the relationship between inflammation and depression as a running example, this mini-review will discuss three areas of work that should be emphasized in future research to maximize the replicability and clinical impact of the field: 1) methodology with respect to planning data collection and statistical analyses with measurement properties and conceptually important sources of variance in mind, 2) characterizing inflammatory phenotypes of psychopathology, and 3) the integration of inflammatory processes into robust, extant psychosocial theoretical frameworks of psychopathology risk. Consistent, parallel growth in all three areas will ensure immunopsychiatry research is replicable, contributes to understanding of how (and for whom) the immune system is associated with psychiatric symptoms, and increases the flexibility and power of personalized treatment planning.

Inflammation and depression: Research designs to better understand the mechanistic relationships between depression, inflammation, cognitive dysfunction, and their shared risk factors

There is convergent evidence that the immune system is dysregulated in some depressed individuals. A psychoneuroimmunology-based understanding of depression is advancing rapidly; however, a question of fundamental importance is poorly understood: does inflammation play a causal role in the etiology of depression or are elevated inflammatory biomarkers a downstream effect of depressive behaviors? Although longitudinal studies suggest that the relationship between depression and inflammation is characterized by complex bidirectional associations, existing prospective, longitudinal research designs are poorly equipped to investigate the dynamic interplay of depression and inflammation that unfolds over a relatively short time period. In addition, the precise role played by multiple, shared, and overlapping risk factors (e.g., diet, adiposity, stress, sleep dysregulation) in the etiology of depression and a pro-inflammatory phenotype (or both) is poorly understood. In this manuscript, I highlight the benefits of research designs that (i) manipulate constructs of interest (depression/inflammation) using intervention or treatment designs and (ii) use intensive sampling approaches with an ultimate goal of better understanding the temporal sequence and causal relationships of depression, inflammation, cognitive dysfunction, and their shared risk factors. For instance, are improved depressive symptoms a downstream effect of changes in inflammatory activity caused by increases in exercise or, alternatively, are changes in inflammatory activity and depression sequelae of improvements in sleep quality caused by increases in exercise? Potential benefits of these research designs are discussed in terms of their contribution to a better understanding of the etiology of depression and a pro-inflammatory phenotype, their relevance to structural health inequalities, and better characterizing the heterogeneous clinical presentation of depression, particularly relating to the etiology of cognitive dysfunction in depression.