Depressive symptoms predict longitudinal changes of chronic inflammation at the transition to adulthood

Abstract

Background: Inflammation is closely related to poor mental and physical health, including depressive symptoms and its specific symptoms. To reveal the linear and nonlinear relationships between depressive symptoms and chronic inflammation levels, and perform further analysis of the associations between symptom-specificity of depressive symptoms and inflammation among young adults by using a prospective design.

Methods: In this longitudinal study, we examined college students recruited from two universities in China, who were examined at baseline and 2-years follow-up. Depressive symptoms were measured by applying the Patient Health Questionnaire 9 (PHQ-9) at baseline. Plasma levels of four inflammatory biomarkers, including interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and C reactive protein (CRP) were assayed at baseline and 2-year follow-up. In addition to the conventional generalized linear models, as well as restricted cubic splines were innovatively used to analyze the cross-sectional and longitudinal nonlinear relationships between depressive symptoms and inflammatory biomarkers.

Results: Generalized linear model analysis revealed that there were no statistical associations between depressive symptoms and any inflammatory biomarker levels. The results of the restricted cubic spline demonstrated a U-shaped nonlinear association between depressive symptoms and ΔIL-1β or ΔTNF-α (changes in baseline and 2-year follow-up), but these associations disappeared after adjusting the confounders. Symptom-specificity of depressive symptoms such as sleeping problems and suicidal ideation were associated with lower IL-1β at baseline or changes in IL-1β levels. Sleeping problems and psychomotor changes at baseline were associated with higher CRP at 2-year follow-up. Suicidal ideation at baseline was associated with changes in TNF-α levels.

Conclusion: Our findings suggested that symptom-specificity of depressive symptoms was associated with inflammation during a 2-year follow-up at the transition to adulthood. Simultaneously, more research is warranted to seek the directionality of depressive symptoms and chronic inflammation.

Keywords: Depressive symptoms; dose-response relationship; follow-up study; inflammatory biomarkers; young adults.

Figure 1

Restricted cubic spline models of the associations between PHQ-9 total scores and inflammatory biomarkers at baseline (n=723). IL-1β, interleukin-1β; IL-6, interleukin-6; TNF-α, tumor necrosis factor-α; CRP, C reactive protein. ^a The blue plot represented the crude model which was not adjusted by any variables, and the red plot represented the adjusted model which was adjusted by residential area, self-reported family economy, self-rated health condition, father’s education level, mother’s education level, cigarette use and alcohol use.

Figure 2

Restricted cubic spline models of the associations between PHQ-9 scores at baseline and inflammatory biomarkers at follow-up (n=248). IL-1β, interleukin-1β; IL-6, interleukin-6; TNF-α, tumor necrosis factor-α; CRP, C reactive protein. ^a The blue plot represented the crude model which was not adjusted by any variables, and the red plot represented the adjusted model which was adjusted by residential area, self-reported family economy, self-rated health condition, father’s education level, mother’s education level, cigarette use and alcohol use. ^b F represented 2-year follow-up.

Figure 3

Restricted cubic spline models of the associations between PHQ-9 scores at baseline and changes in inflammatory biomarkers (n=248). IL-1β, interleukin-1β; IL-6, interleukin-6; TNF-α, tumor necrosis factor-α; CRP, C reactive protein. ^a The blue plot represented the crude model which was not adjusted by any variables, and the red plot represented the adjusted model which was adjusted by residential area, self-reported family economy, self-rated health condition, father’s education level, mother’s education level, cigarette use and alcohol use. ^b Δ represented changes between 2-year follow-up with baseline.

Figure 4

Generalized linear models of the associations between symptom-specificity of depressive symptoms and inflammatory biomarkers at baseline (n=723). IL-1β, interleukin-1β; IL-6, interleukin-6; TNF-α, tumor necrosis factor-α; CRP, C reactive protein. ^a The blue plot represented the crude model which was not adjusted by any variables, and the red plot represented the adjusted model which was adjusted by residential area, self-reported family economy, self-rated health condition, father’s education level, mother’s education level, cigarette use and alcohol use.

Figure 5

Generalized linear models of the associations between symptom-specificity of depressive symptoms at baseline and inflammatory biomarkers at follow-up (n=248). IL-1β, interleukin-1β; IL-6, interleukin-6; TNF-α, tumor necrosis factor-α; CRP, C reactive protein. ^a The blue plot represented the crude model which was not adjusted by any variables, and the red plot represented the adjusted model which was adjusted by residential area, self-reported family economy, self-rated health condition, father’s education level, mother’s education level, cigarette use and alcohol use. ^b F represented 2-year follow-up.

Figure 6

Generalized linear models of the associations between symptom-specificity of depressive symptoms at baseline and changes in inflammatory biomarkers between follow-up and baseline (n=248). IL-1β, interleukin-1β; IL-6, interleukin-6; TNF-α, tumor necrosis factor-α; CRP, C reactive protein. ^a The blue plot represented the crude model which was not adjusted by any variables, the red plot represented adjusted model which was adjusted by residential area, self-reported family economy, self-rated health condition, father’s education level, mother’s education level, cigarette use and alcohol use. ^b Δ represented changes between 2-year follow-up with baseline.