Differences Between Adolescent Depression and Healthy Controls in Biomarkers Associated With Immune or Inflammatory Processes: A Systematic Review and Meta-Analysis
Article information
Abstract
Objective
Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression.
Methods
Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis.
Results
Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers.
Conclusion
Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.
INTRODUCTION
Adolescent depression is a major public health concern and the third leading cause of disability in adolescents worldwide [1]. Globally, epidemiological studies have consistently shown a high prevalence of adolescent depression with an increasing trend. In the U.S., a nationally representative survey of adolescents aged 12–17 years showed that the prevalence of depression increased from 8.1% in 2009 to 15.8% in 2019 [2]. In China, a meta-analysis of 18 studies covering 29,626 participants showed that the pooled prevalence of depressive symptoms was 19.85% in Chinese children and adolescents [3]. Adolescent depression is associated with a wide range of adverse health outcomes that persist into adulthood, including low academic attainment, substance abuse, obesity, social impairment, and suicidality [4].
Despite the high prevalence and high morbidity of adolescent depression, the pathophysiology of depression remains unclear, and current pharmacologic interventions are only effective on less than one-third of patients [5]. Therefore, recent research efforts have been directed toward searching for biomarkers as specific indicators of depression to guide further effective intervention and prevention. Biomarkers are defined as “an indicator of normal biological processes, pathogenic processes or responses to an exposure or intervention.” [6] These biomarkers provide objective measurements that complement traditional subjective assessments, enabling a deeper comprehension of the underlying molecular mechanisms involved in depression. Blood-based biomarkers provide researchers with unique insights into the pathophysiology of depression, allowing them to investigate probable pathways that contribute to its genesis and maintenance.
Growing evidence suggests that immune system dysregulation and aberrant inflammatory responses may play a role in the etiology of depression [5]. Researchers can get valuable insights into the physiological symptoms of depression and potential intervention targets by assessing specific biomarkers related to immune activation and inflammation in the blood. However, most biomarkers of depression are deprived of the adult population, which may not be typical in the pediatric population [7]. Existing depression theories assume that adult models are equally applicable to adolescents, which may not be true since children and adults may have different etiologies, clinical manifestations, and treatment responses of depression [8]. It is thus crucial to examine biomarkers specific to adolescent depression to gain a deeper understanding of the pathophysiology of adolescent depression and guide targeted and effective interventions.
Although a number of studies have investigated biomarkers associated with depression in adolescents, many lack rigorous comparisons with healthy controls. This limitation prevents one from discerning whether the observed biomarker changes are specific to depression or influenced by other external factors such as infections, lifestyle differences, or other underlying diseases. In this study, we strictly required the inclusion of a healthy control group, and in contrast to previous meta-analyses that chose the correlation coefficient r as a statistic and focused on the overall link between depression and inflammation [9], we focused more on direct comparisons between the depressed and healthy groups in each study, and the statistic we chose was the standardized mean difference (SMD), which ensured that the comparisons were specific and clear, and reduced the confounding effects of confounding factors. Additionally, the latest year of publication of the articles included in our meta-analysis was 2023, which is more recent than previous similar literature, and we believe that there is a degree of updating of the real-time nature of results in this area.
Our findings would offer fresh insights into the complex interplay between immune and inflammatory processes, blood-based biomarkers, and adolescent depression and direct future intervention and prevention efforts.
METHODS
Search strategy and selection criteria
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [10], we comprehensively searched electronic databases, including PubMed, Web of Science, and Elsevier ScienceDirect. A protocol was registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) on June 2024 (registration number: INPLASY202460114). The search strategy utilized a combination of relevant keywords and medical subject headings (MeSH) terms related to adolescent depression, biological biomarkers, and immune or inflammatory processes. The specific search terms included “adolescent depression,” “biomarkers,” “biological marker,” “immune,” and “inflammation.” The search was conducted for articles published between January 2004 and February 2024 to capture studies reflecting recent advancements in biomarker research and ensure methodological consistency. We included studies on adolescent depression that satisfied the following conditions: 1) Participants were adolescents aged 12–24 years; 2) participants had an initial diagnosis of depression based on a diagnostic system such as the International Classification of Disease, Diagnostic and Statistical Manual of Mental Disorders, or Research Diagnostic Criteria; 3) measurable biomarkers related to inflammation or immunity in the participants’ blood were collected; 4) the study included a healthy control group; 5) the study was available online in English; 6) the study design was either a cross-sectional study or a case-control study; 7) peer-reviewed publications in the past 20 years. We excluded manuscripts based on non-human studies, studies with inadequate evaluation methods (significant flaws in study design, such as inappropriate statistical methods), insufficient data (key data such as means and standard deviations were not reported or could not be obtained), or unclear findings (studies with ambiguous or contradictory conclusions), and studies reported in conferences, abstracts, editorials, or letters only. When multiple manuscripts were based on a single cohort, the manuscript with the largest sample was included. Boolean operators like “AND” and “OR” were used to combine the search phrases properly. In addition to database searches, we manually searched the reference lists of relevant studies and review articles to identify additional pertinent articles. Duplicate records were removed using EndNote software, and initial screening based on titles and abstracts was performed independently by two reviewers (Jiao Li and Yan Zhang). Full-text articles were then assessed for eligibility by the same reviewers (Qiangli Dong), with discrepancies resolved through discussion.
Data extraction and quality assessment
An independent reviewer (Jiao Li) read through the titles and abstracts of all possibly qualifying studies found during the initial search. Full-text review was conducted independently by two reviewers (Jiao Li and Yan Zhang), with Qiangli Dong serving as a third reviewer to resolve any discrepancies. A standardized data extraction form was used to collect the following information: 1) study characteristics, such as author, year, sample size, and study design; 2) participant characteristics, such as age, gender, clinical diagnosis, and specific biomarkers related to immune-inflammatory processes; and 3) the major findings, defined as any differences in the blood biomarkers between depressed adolescent patients and healthy controls. Besides, we attempted to investigate the following secondary outcomes when relevant data were available: relationships among immune and inflammatory biomarkers, cognition, and functioning (e.g., symptom rating scales like the Hamilton Depression Rating Scale). The correlation coefficients for these relationships were directly extracted from the included studies that reported them. The Newcastle-Ottawa Scale (NOS) [11], a widely acknowledged tool for measuring methodological quality, was used to assess the quality of the observational studies. The NOS provides a thorough framework for evaluating non-randomized study selection, comparability, and outcome assessment.
Data synthesis and analysis
We conducted a meta-analysis to evaluate the association between biomarkers and depression by comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls if two or more studies reported them. A random-effects model of the DerSimonian and Laird method was used when the I2 between the multiple studies included was greater than 25% [12,13]. Statistical pooling of the data was performed by applying appropriate methods, such as inverse variance weighting for continuous outcomes. χ2 tests for heterogeneity were performed, and I2 was calculated to assess heterogeneity. Data on medians, quartiles, and ranges were used to infer means and standard deviations when required, using the formulas proposed by Hozo et al. [14]. Specifically, this method was applied in one of the included studies [15]. All statistical analyses were conducted through Review Manager 5.4. (Cochrane Collaboration) and SPSS 29.0 (IBM Corp). All p-values were two-sided and were deemed statistically significant if they were less than 0.05. The risk of publication bias was assessed qualitatively due to the limited number of included studies for most biomarkers, with most biomarkers being reported in only two studies. Factors such as study sample size, geographic location, and result consistency were also considered in this evaluation.
RESULTS
Search results
After deleting duplicates, 285 citations were initially identified for title and abstract screening, among which 249 were excluded, leading to 36 full-text publications evaluated for eligibility. After screening for full text, 27 studies were excluded based on our inclusion and exclusion criteria, leading to nine studies in the final meta-analyses (Figure 1).
Selection of included studies.
Sample characteristics and study quality
Nine studies were included for data extraction, including seven case-control studies and two cross-sectional studies [15-23]. Table 1 summarizes the full details of the included studies. Sample sizes ranged from 11 to 184, with three studies having sample sizes of less than 50 participants [17-19]. Only seven studies considered the relationship between baseline and follow-up depression severity [15,17,18,20-23]. The included studies exhibited heterogeneity in their diagnostic methods, encompassing a range of symptom scores and interviewing techniques.
Baseline characteristics of included studies
Table 2 presents the quality assessment results of the seven case-control studies using the NOS. Each study received a score of 6 stars or higher, indicating that the included studies adequately addressed the selection, comparability, and exposure criteria. The quality assessment underscores the overall high standard of the studies included in this review. The methodological rigor of studies examining the relationship between adolescent depression and biomarkers related to immune or inflammatory processes is emphasized by the uniformity of the scores, particularly in terms of selection and exposure.
Bias assessment according to the Newcastle-Ottawa criteria for case-control studies
In all included studies, cytokines (such as interleukin [IL]-1β, IL-2, IL-6, IFN-γ, tumor necrosis factor-α [TNF-α], and IL-10) were measured using enzyme-linked immunosorbent assay (ELISA) techniques. Vitamin D levels were assessed using high-pressure liquid chromatography (HPLC), and NFκB activity was measured using biosensor assays. Hemogram parameters like white blood cells (WBC), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were measured using automated hematology analyzers. Blood samples were collected from participants, processed to separate serum or plasma, and then analyzed. These diverse methods ensured accurate and reliable measurement of biomarkers relevant to immune and inflammatory processes.
Meta-analytic results for included studies
Compared to the healthy controls, the depressed adolescents had significantly higher values in the following indicators: PLR, WBC, NLR, platelet, TNF-α, IL-1β, neutrophil, mean platelet volume (MPV), mean corpuscular volume (MCV), and IL-8. Additionally, the depressed adolescents had lower procalcitonin (PCT) levels than the healthy controls. Nonetheless, the two groups showed no statistically significant differences in the following indicators: hemoglobin (Hb), lymphocyte, hematocrit (HCT), IL-10, IL-6, red blood cells (RBC), mean corpuscular hemoglobin (MCH), red cell distribution width (RDW), and mean corpuscular hemoglobin concentration (MCHC) (Table 3). What is noteworthy is that MCV, PCT, and IL-8 are markers that were only reported in one study.
Biomarkers in patients with depression compared with healthy control individuals
Table 4 lists all biomarkers for depressed adolescents reported by two or more studies. The weighted mean differences and SMDs offered a quantitative perspective on the disparities in the biomarkers between the two groups. The random-effects model allowed for the pooling of data across studies, providing a more generalized view of biomarker variations in this population. Furthermore, Figure 2 illustrates the forest plot corresponding to each biomarker. The qualitative assessment did not reveal evidence of publication bias across the included studies. Figure 3 is a dot plot presenting the biomarkers correlated with depression sores and their corresponding correlation coefficients. As shown in the chart, the biomarkers were positively or negatively correlated with depression severity to varying degrees. It should be clarified that the study by Zajkowska et al. [23] (2023) was included to show correlation coefficients between biomarkers and depression severity, but the study did not provide the direct data needed for group comparisons (Supplementary Table 1).
Differences in the biomarkers in adolescents with depression compared with healthy control individuals measured in 2 or more studies
Forest plot of biomarkers measured in 2 or more studies in adolescents with depression versus healthy controls. PLR, platelet-tolymphocyte ratio; WBC, white blood cells; NLR, neutrophil-to-lymphocyte ratio; TNF-α, tumor necrosis factor-α; IL-1β, interleukin 1β; Hb, hemoglobin; MPV, mean platelet volume; HCT, hematocrit; IL-10, interleukin 10; IL-6, interleukin 6.
Dot plot of biomarkers significantly associated with patients’ mean scores on depression-related scales. NLR, neutrophilto-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; MPV, mean platelet volume; BDI, Beck Depression Inventory; CDI, Child Depression Inventory; DASS-D, Depression Anxiety Stress Scales–Depression; HMD, Hamilton Depression Rating Scale; CDRS-R, Children’s Depression Rating Scale-Revised; BDI-II, Beck Depression Inventory-II; STAI, State-Trait Anxiety Inventory; MFQ-C, Mood and Feelings Questionnaire-Child version.
DISCUSSION
This is a meta-analysis that requires the inclusion of healthy control groups to compare blood inflammatory and immune biomarkers in adolescents with depression. By comparing the blood biomarkers between adolescents with depression and healthy control individuals, we found 10 biomarkers that were significantly higher and one biomarker that was significantly lower in adolescents with depression. Our findings support the activated inflammatory response and immunoregulatory hypotheses in depression, suggesting a possible link between inflammation and the pathophysiology of adolescent depression [24-26]. This comprehensive review offers a novel insight into the hematological and inflammatory changes in adolescents with depression, contributing valuable information to the field and potentially guiding future therapeutic strategies.
Neutrophils, as first responders in the innate immune response, release reactive oxygen species and proteolytic enzymes, which can exacerbate neuroinflammation by compromising the integrity of the blood-brain barrier (BBB). This allows peripheral immune cells and inflammatory cytokines to infiltrate the central nervous system, potentially disrupting neural circuits involved in mood regulation [27,28]. Platelets, on the other hand, play a role in inflammation and tissue repair. Platelets can release serotonin and pro-inflammatory mediators (e.g., platelet factor 4), which may contribute to the pathogenesis of depression by affecting synaptic plasticity and neural excitability [29,30]. NLR and the PLR are two indicators of inflammation ratios, often elevated in patients with depression, reflecting the pathophysiological role of chronic low-grade inflammation [31]. In addition, the results summarized in Figure 3 also showed that NLR and PLR were positively correlated with depression severity, further supporting the inflammation hypothesis. Noteworthily, previous studies have also revealed that NLR and PLR are related to other psychiatric diseases such as schizophrenia, attention-deficit/hyperactivity disorder (ADHD), and seizures [32-34]. However, the usefulness of NLR and PLR in identifying patients with depression has not yet been precisely demonstrated. Inflammatory and immune biomarkers are less affected by exercise, catecholamine release, and other confounding variables and thus provide more robust results [35]. Our findings further suggest that neutrophils, platelets, NLR, and PLR may be objective indicators for detecting adolescent depression.
WBC produce cytokines and play a key role in coordinating innate and adaptive immune responses [36]. Our study showed elevated levels of WBC in adolescents with depression, supporting the inflammation hypothesis in adolescent depression. Beydoun et al. [37] conducted a longitudinal study and proposed the hypothesis that baseline leukocyte-related metrics predicted later depressive symptoms, which overruled the previous hypothesis that baseline depressive symptoms predicted leukocyte-related metrics. The underlying mechanism for the association between WBC and depressive symptoms may be explained by depression-induced unhealthy behaviors, such as a sedentary lifestyle and overeating, which can lead to obesity and inflammation [38]. The increased WBC may also be caused by the depression stimulating bone marrow hematopoietic stem cells, which causes an increase in cortisol and, ultimately, leukocytosis [39]. WBC are relatively understudied biomarkers of inflammation in adolescent depression [37], and our findings provide a direction for future studies.
TNF-α, IL-1β, and IL-8 are three proinflammatory cytokines that can be produced by immune cells such as microglia. They play an important role in the onset and development of depression, including adolescent depression. Our study showed elevated levels of TNF-α, IL-1β, and IL-8 in adolescents with depression, supporting the inflammation hypothesis in adolescent depression. Studies have shown that these pro-inflammatory cytokines can respond to stress-induced neuroinflammation, which can affect neuronal and astrocyte function, leading to depression [40]. According to the psycho-neuro-inflammatory theory, proinflammatory cytokines such as TNF-α and IL-1β can stimulate the hypothalamic-pituitary-adrenal axis, leading to the release of corticotrophin-releasing hormone [41], and our study added further empirical evidence to the theory.
MPV is an indicator of platelet activity. Our study showed increased platelet activation in adolescents with depression, which may be associated with changes in the concentrations of pentraxin and epinephrine, upregulation of their corresponding receptors, and altered second messenger transduction [42]. Although MCV and PCT have only been reported in a single study included in this review, these findings provide preliminary evidence suggesting potential differences in inflammatory responses between adolescents with depression and healthy controls. The higher MCV in the depression group may indicate alterations in RBC morphology or function, which may be associated with nutritional deficiencies, oxidative stress, or other pathophysiological processes in depression [43]. On the other hand, the lower levels of PCT in the depression group may reflect variations in the acute phase response, indicating a potentially different pattern of immune response in depressed adolescents compared to healthy controls. These findings highlight the need for further research into the roles of immune and inflammatory processes in adolescent depression. Future studies with larger sample sizes and more comprehensive assessments of immune and inflammatory biomarkers are necessary to validate these findings and explore their clinical implications.
What is particularly noteworthy is that many studies have demonstrated significant differences in IL-6 between adult depression and healthy controls [40,44]. However, our meta-analysis focusing on adolescent depression showed no significant difference in IL-6 between depression and healthy groups. Several factors could account for this unexpected finding. First, IL-6 levels are highly dynamic and may be influenced by acute stress, diurnal variations, and environmental factors such as sleep disturbances or recent infections, which are particularly prevalent during adolescence [45]. These fluctuations might mask significant differences in baseline IL-6 levels between groups. Second, medication use, such as antidepressants or anti-inflammatory drugs, could have confounded IL-6 measurements, as these are known to modulate inflammatory responses [46,47]. Besides, it is unknown whether this suggests differences in the characteristics of inflammatory markers between adolescent and adult depression or whether it is due to study heterogeneity, which warrants future research.
Our findings suggest that elevated levels of these markers may reflect underlying systemic inflammation, providing clues to understanding the biological mechanisms contributing to depression in adolescents. In clinical practice, these markers may have potential as supplementary diagnostic tools to complement the current subjective diagnostic methods for depression. Additionally, measuring these biomarkers could provide insights into treatment response and effectiveness in depression management. However, their elevation is not specific to depression, so further research is needed to verify their specificity and improve their diagnostic accuracy and clinical utility.
Limitation
Our study has several limitations. First, the heterogeneity of antidepressant treatment profiles in the included studies may cause potential confounding and affect the reliability of our combined results. For example, previous research has shown that tricyclic antidepressants decrease the release of proinflammatory cytokines from monocytes in microglial cell cultures [48]. Hence, the effects of antidepressants may have obscured differences in inflammatory and immune markers between depressed patients and controls. Second, inflammatory and immune profiles may be different in subtypes of depression, which may also account for the heterogeneity of individual research articles. Third, we only included nine studies in the meta-analysis, which may affect the robustness and generalizability of our findings. Given the complex nature of immune and inflammatory processes in adolescent depression, a larger pool of studies can potentially reveal more nuanced insights and strengthen the reliability of the observed associations. Additionally, we only included articles published in English to ensure data consistency and readability, which may introduce potential language bias. Future research should aim to include a broader array of studies to confirm these results and possibly uncover additional biomarkers significant to adolescent depression compared to healthy controls.
Conclusions
This systematic review and meta-analysis have identified a range of various inflammatory and immunological biomarkers that are significantly different in depressed adolescents as compared to healthy controls, implying that immune and inflammatory processes are implicated in adolescent depression. However, due to a scarcity of relevant literature and small sample sizes in some studies, it is difficult to analyze potential biomarker interactions or identify unique depression phenotypes. As a result, more high-quality research, especially larger cohort studies with an integrated strategy and a larger number of biomarkers, is required to validate these putative depression biomarkers and build the groundwork for the development of more effective and targeted intervention and prevention programs for adolescent depression.
Supplementary Materials
The Supplement is available with this article at https://doi.org/10.30773/pi.2024.0295.
Biomarkers and specific correlation coefficients significantly associated with patients’ mean scores on depression-related scales
Notes
Availability of Data and Material
All data generated or analyzed during the study are included in this published article (and its supplementary information files).
Conflicts of Interest
The authors have no potential conflicts of interest to disclose.
Author Contributions
Conceptualization: Jiao Li, Yan Zhang. Data curation: Jiao Li, Pule Liu. Formal analysis: Jiao Li, Ning Yang. Funding acquisition: Yan Zhang, Qiangli Dong. Project administration: Yan Zhang, Qiangli Dong. Visualization: Wenchong Dai, Jing Du. Writing—original draft: Jiao Li, Yan Zhang. Writing—review & editing: Jiao Li, Yan Zhang, Qiangli Dong.
Funding Statement
This research was supported by the STI2030-Major Projects (YZ, grant number 2021ZD020200); the Personality characteristics, genetic polymorphisms and brain magnetic resonance imaging changes in adolescent depressive disorders project, (QLD, grant number 21JRIRA125).
Acknowledgments
We would like to express our gratitude to all the researchers and authors of the studies included in this systematic review and meta-analysis for their valuable contributions to the field.