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.

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.

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.

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).

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.

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.

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.

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.

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).

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.

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.