Abstract
Introduction
Psoriasis is a chronic inflammatory skin condition affecting 0.1–1.5% of the global population. The condition is linked to impaired quality of life and increased morbidity. Brain-derived neurotrophic factor (BDNF) is a neurotrophin associated with neuronal development and synaptic plasticity; its dysregulation has been implicated in the pathogenesis of psoriasis. This study systematically reviews and analyzes the relationship between BDNF levels and psoriasis.
Methods
A systematic review and meta-analysis were conducted by the PRISMA 2020 guidelines. Comprehensive searches were performed on MEDLINE, Scopus, EMBASE, and Web of Science databases up to January 19th, 2024. Eligible studies measured circulating BDNF levels in psoriasis patients and compared them with healthy controls. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of included studies. Meta-analyses were performed using standardized mean differences (SMD) with either fixed or random-effects models based on heterogeneity measures.
Results
Six studies met the inclusion criteria, with data from 2006 to 2020. Meta-analysis revealed a significant reduction in BDNF levels in psoriasis patients compared to healthy controls (SMD −0.577, 95% CI [−0.915, −0.239], p = 0.0008). Heterogeneity was substantial (I2 = 70.2%). Sensitivity analysis identified one study as a major contributor to heterogeneity. No significant factors contributing to heterogeneity were identified through meta-regression.
Conclusion
This study found a significant reduction in BDNF levels in psoriasis patients, suggesting a potential link between BDNF dysregulation and the pathophysiology of psoriasis. Understanding the role of BDNF in these conditions may inform future research and therapeutic strategies for patients suffering from both. Further research is needed to explore the relationship and the mechanisms underlying the associations of psoriasis and any probable related comorbidities, such as depression.
Supplementary Information
The online version contains supplementary material available at 10.1186/s42358-025-00515-x.
Keywords: Psoriasis, BDNF, Brain-derived neurotrophic factor, Psoriasis lesion
Introduction
Psoriasis, affecting an estimated 0.1–1.5% of the worldwide population, is a chronic inflammatory condition often observed in primary healthcare settings. It is characterized by the presence of scaly red plaques on the skin, which can manifest either locally or extensively, and is associated with substantial morbidity beyond its dermatological symptoms [1–3].
Psoriasis’s impact on mental well-being is theorized to involve dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis during stress, leading to increased pro-inflammatory mediators. Additionally, mood disorders such as depression are linked to the immune system, as evidenced by elevated inflammatory cytokine levels and chronic inflammation [4]. Despite substantial progress in comprehending the underlying mechanisms of psoriasis and disorders like depression individually, the complex interplay between these two conditions remains a topic of ongoing investigation and examination [5]. One major comorbidity is depression. Depression impacts around 20% of individuals in the Western world who have psoriasis. Research conducted in Sweden revealed elevated rates of depression among psoriasis sufferers in comparison to those without the condition, particularly among women and younger demographics [6, 7]. Another study suggests that individuals with psoriasis are 1.5 times more likely to exhibit depressive symptoms and experience a higher prevalence of anxiety symptoms (ranging from 20% to 50%) compared to individuals without psoriasis [8]. The link between the nervous system and psoriasis is evident from the improvement of psoriasis lesions after removing cutaneous sensory nerves. Studies suggest neurotropism may contribute to skin inflammation through mast cell activation, while neuropeptides and their receptors influence skin cell growth and death. Brain-derived neurotrophic factor (BDNF) impacts keratinocyte proliferation and apoptosis via its main receptor, tyrosine kinase B (TrkB) [9]. Brain-derived neurotrophic factor (BDNF) is a neurotrophin linked with neuroplasticity, neuronal development, and synaptic efficacy and plays roles in memory, learning, and various cognitive functions [10]. Research suggests a common decrease in BDNF levels in psoriasis and depression, potentially linking the two conditions. Additionally, studies indicate an association between BDNF/TrkB signaling and the serotonin (5-HT) system, possibly explaining BDNF’s influence on depressive behaviors. Changes in BDNF/TrkB signaling are commonly implicated in various human pathologies due to their central role in cellular function [11].
This paper aims to thoroughly explore the relationship between BDNF levels and psoriasis by reviewing existing literature. We’ll analyze findings from clinical studies, experiments, and mechanistic research to understand how BDNF dysregulation may impact the development and severity of psoriasis. Through this exploration, we seek to provide valuable insights that could inform future research and treatment strategies for individuals affected by psoriasis.
Materials and methods
This systematic review and meta-analysis were conducted in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines [12].
Search strategy
We conducted comprehensive online searches of the MEDLINE, Scopus, EMBASE, and Web of Science databases up to January 19th, 2024, to identify relevant studies. To ensure thorough coverage, we also manually reviewed the reference lists of all relevant publications identified through our searches. There were no restrictions on language, publication date, or publication status, including online first or already-published articles. The detailed search strategy is provided in Supplementary Material 1. Two authors (MSS and NS) independently screened the titles and abstracts of the identified records, with any disagreements resolved by a third reviewer (SM).
Eligibility criteria
Eligibility for inclusion in this systematic review and meta-analysis was restricted to studies investigating circulating blood levels of brain-derived neurotrophic factor (BDNF) in individuals with psoriasis. We imposed no limitations concerning the language of publication or the date of publication. The primary endpoint of interest was the comparison of BDNF levels between psoriasis patients and healthy control subjects (HCs). Studies exclusively reporting BDNF levels in psoriasis patients without a corresponding healthy control group were not considered. Additionally, we excluded review articles, books, book chapters, studies conducted on animal models, research focusing on the tissue expression of BDNF, in vitro studies or cell culture investigations, and studies centered on the genetic polymorphisms of BDNF without direct measurement of its levels.
Data extraction and quality assessment
The data extraction process involved two authors conducting a two-stage screening of both titles/abstracts and full texts, which facilitated the identification of eligible studies. They independently extracted data and evaluated the risk of bias. In instances of discrepancy regarding data extraction or quality assessment, a third investigator was consulted for resolution. The extracted information from these studies encompassed various aspects, such as Author, Year, Country, Study Design, Protocol for BDNF Measurement (Serum, Plasma), Sample Size (for both Psoriasis patients and Healthy Controls), Diagnostic Criteria, Age, Gender Ratio, BDNF Levels, and the Key Significant Findings.
The Newcastle–Ottawa Scale (NOS) was utilized to assess the quality of the included studies [13]. This scale allows for a rating between 0 and 9 stars, based on specific criteria: the selection process of the study samples, the comparability between cases and controls, and the robustness of the outcome assessment. Studies achieving a star rating between 7 and 9 were deemed high quality, those with 4 to 6 stars were considered of moderate quality, and studies with less than 4 stars were categorized as having low quality.
Statistical analysis
The standardized mean difference (SMD) was used to measure the effect in this study. The choice between a fixed-effects model and a random-effects model for the primary analysis was based on heterogeneity measures. We used the Q statistic and I2 index to detect heterogeneity across studies. According to the Cochrane criteria, an I2 < 40% indicates that discrepancy across investigations is not significant; thus, in this scenario, the fixed-effects approach was utilized. When I2estimations exceeded 40%, the random-effects model was applied as the analytical model.
Since our data were already reported as mean and standard deviation (SD), there was no need for transformation of values reported as medians or ranges. To explore potential sources of heterogeneity further, particularly in meta-analyses with substantial heterogeneity, sensitivity analyses such as Leave-One-Out Analyses were conducted. This method involves sequentially removing one study at a time and recalculating the overall effect size to assess the influence of individual studies on the pooled estimate.
Publication bias was evaluated using funnel plots and Egger’s test. Funnel plots were used to visually identify potential bias, while Egger’s test [14]provided an objective statistical assessment of funnel plot asymmetry.
All statistical analyses and visualizations were performed using R version 4.0.4 (R Core Team [2020], Vienna, Austria). The following packages were utilized: “meta” (version 4.17–0), “metaphor” (version 2.4–0), “diameter” (version 0.0–9), and “tidyverse” (version 1.3.0). A p-value of < 0.05 was considered statistically significant.
Results
Study selection
The study selection process is shown in Fig. 1. The database search led to the finding of 164 articles. After removing 59 duplications, 105 articles were retrieved for preliminary screening. According to the inclusion and exclusion criteria, the full texts of 13 articles were reviewed. Three articles that didn’t have accessible full texts were excluded. Two studies were excluded since these manuscripts did not have a control group. Two other studies didn’t have enough available data for both case and control groups. Finally, six studies were included in this study.
Fig. 1.

Flow diagram summarizing the selection of eligible studies based on the PRISMA guidelines
Descriptive findings
Characteristics of the included studies
Table 1 summarizes six studies published between 2006 and 2020 that provided original data on BDNF blood levels in psoriasis patients and healthy controls (HCs) [10, 15–19]. Psoriasis patients were primarily diagnosed using the Psoriasis Area and Severity Index (PASI) criteria. Two studies directly compared BDNF levels between psoriasis patients and HCs [16, 19], while the other four studies provided additional data on BDNF levels in various subgroups of psoriasis patients, including those with comorbid conditions such as metabolic syndrome and depression.
Table 1.
Baseline characteristics of included studies
| Study ID | Patients | Controls | Results | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Author, Year | Country | Study Design | BDNF measurement protocol | Source (Serum, Plasma) | NO | Diagnostic criteria | Age (mean ± SD), years | Female/Male | BDNF levels (mean ± SD), ng/ml | PASI Score | NO | Age (mean ± SD), years | Female/Male | BDNF levels (mean ± SD), pg/ml | Investigate markers | Main significant findings |
| Bulur et al. 2017 | Turkey | Cross-sectional | ELISA method | Serum | 39 patinets with Mets and 21 patients without Mets |
Mets: National Cholesterol Education Program’s ATP III guidelines Psoriasis: PASI |
Patients with MetS: 39.00 ± 13.59 Patients Without MetS: 46.95 ± 10.68 |
26/34 |
Patients with MetS: 3.15 ± 2.44 Patients Without MetS: 3.00 ± 2.99 Total: 3.09 ± 2.63 |
Without MetS: 12.29 ± 5.39, With MetS: 13.58 ± 7.28 | 15 | 36.73 ± 10.07 | 8/7 | 5.39 ± 3.65 |
BDNF NGF TNF-α c |
Serum BDNF levels were significantly higher in healthy controls compared to psoriasis patients (p = 0.017), with no significant difference between psoriasis patients with and without MetS. Epidermal and dermal infiltration of BDNF was also lower in psoriasis patients. |
| Vinnik et al. 2016 | Kazakhstan | Case-control | ELISA method (Promega, US; G7610) | Serum | 33 | PASI | 35.1 ± 2.3 | NA | 40.12 ± 1.61 | 17.9 ± 1.6 (Week 0), 7.7 ± 1.6 (Week 10) | 49 | 34.9 ± 1.3 | 26/23 | 40.49 ± 0.45 |
BDNF Total IgE SNP |
BDNF Levels: PS cohort 1 (autumn/winter) showed stable BDNF levels, while PS cohort 2 (spring/summer) had a significant decrease to 35.04 ± 1.56 ng/ml by week 10 (p < 0.002). Seasonal Influence: Autumn/winter onset had stable BDNF, while spring/summer onset led to a pronounced reduction. Significance: Seasonal factors like sunlight in spring/summer may impact immune and neurotrophic pathways, lowering BDNF in psoriasis. |
| Brunoni et al. 2015 | Brazil | Cross-sectional | ELISA method (Promega, Switzerland) | Plasma | 94 | 57.2 ± 8.2 | 41/53 | 3.41 ± 3.12 | 307 | 57.4 ± 7.6 | 140/167 | 5.95 ± 6.3 | BDNF | Decreased BDNF plasma levels found in psoriasis patients compared to controls, indicating potential brain-skin connection. | ||
| Aksoy et al. 2020 | Turkey | Prospective | proBDNF ELISA Kit (R&D Systems human Pro-BDNF) and Human BDNF ELISA Kit (R&D Systems Quantikine ELISA Human BDNF Immunoassay) | Serum | 31 | PASI | 36.8 ± 11.6 | 10/21 | 32.45 ± 9.94 | 10.04 ± 6.5 (baseline), 2.94 ± 5.5 (after treatment) | 31 | 35.7 ± 11.4 | 10/21 | 32.89 ± 8.85 |
BDNF proBDNF |
Initial measurements showed no significant differences in BDNF levels between psoriasis patients, diseased controls, and healthy individuals, suggesting no direct link between BDNF levels and psoriasis presence. After 12 weeks of antipsoriatic treatment, pro-BDNF levels and their ratios to BDNF decreased significantly, whereas BDNF levels themselves remained unchanged. Despite clinical improvements in psoriasis severity and depression, BDNF levels stayed constant, indicating they might not correlate closely with these clinical changes. |
| Fathy et al. 2015 | Egypt | cross-sectional | Quantitative sandwich enzyme immunoassay technique supplied from R&D Systems (Minneapolis, Minnesota, USA) | Serum | 30 | PASI | 43.2±14.9 | 11/19 |
Without depression: 25.2 ± 6.5 With depression: 16.9 ± 2.5 Totally: 20.49 ± 4.2 |
20.8 ± 18.8 | 30 | 35.9 ± 12.3 | 13/17 | 26.5 ± 3.6 | BDNF | Lower serum BDNF levels are found in psoriasis and depressed patients, indicating BDNF could be a biomarker for depression in those with psoriasis, independent of disease severity. |
| Raap et al. 2006 | Germany | cross-sectional | ELISA method (R&D Systems, Wiesbaden, Germany) | Serum | 23 | PASI | 29 ± 7 | NA | 5.24 ± 2.97 | 5.0 ± 8.2 | 33 | 36 ± 13 | NA | 6.97 ± 3.57 |
BDNF NGF |
BDNF levels are significantly elevated in both types of atopic dermatitis compared to psoriasis and healthy subjects, with a marked correlation to disease severity in intrinsic AD. Psoriasis shows lower BDNF levels. |
Abbreviations: ELISA: Enzyme-Linked Immunosorbent Assay; MetS: Metabolic Syndrome; BDNF: Brain-derived neurotrophic factor; NGF: Nerve growth factor; TNF-α: Tumor Necrosis Factor-alpha; TNF-α SNP: Tumor Necrosis Factor-alpha Single Nucleotide Polymorphism; PASI: Psoriasis Area and Severity Index; proBDNF: pro-Brain-derived neurotrophic factor
The mean ± SD age range for psoriasis patients across studies varied from 29 ± 7 to 57.2 ± 8.2 years, while for HCs, it ranged from 35.7 ± 11.6 to 57.4 ± 7.6 years. The gender distribution varied, with some studies reporting a higher number of male participants among psoriasis patients. All studies used enzyme-linked immunosorbent assay (ELISA) to measure BDNF levels, employing different kits like Promega or R&D Systems. Most studies assessed serum BDNF levels, except for Brunoni et al. [10], which measured plasma BDNF levels.
The methodological quality of studies
All included studies were assessed for quality using the Newcastle-Ottawa Scale (NOS) for cross-sectional studies. The studies were rated as “Good,” with scores ranging from 7 to 9 out of a possible 9 points. This indicates high methodological quality across various criteria, reflecting consistent and reliable standards in selection, comparability, and outcome assessment. Detailed results of the quality assessment are provided in Table 2.
Table 2.
Newcastle-Ottawa Scale (NOS) risk of bias assessment of the included studies
| Author, Year | Selection (0–5) |
Comparability (0–2) | Exposure/outcome (0–3) | Total score (0–10) |
|---|---|---|---|---|
| Raap et al. 2013 | 4 | 0 | 3 | 7 |
| Aksoy et al. 2014 | 4 | 2 | 3 | 9 |
| Bulur et al. 2016 | 4 | 1 | 3 | 8 |
| Brunoni et al. 2018 | 4 | 1 | 3 | 8 |
| Fathy et al. 2019 | 4 | 0 | 3 | 7 |
| Vinnik et al. 2021 | 4 | 2 | 3 | 9 |
Statistical analyses
Comparison of BDNF levels in psoriasis patients versus healthy controls (HCs)
A meta-analysis of the six studies identified a statistically significant reduction in blood BDNF concentrations in psoriasis patients compared to healthy controls (SMD −0.5770, 95% CI [−0.9152; −0.2388], p = 0.0008). The analysis showed significant heterogeneity among studies (I2 = 70.2%, test of heterogeneity: Q = 16.64, p < 0.01) with a variance of τ2 = 0.1192 [0.0261; 1.2637]. The prediction interval ranged from −1.65 to 0.49, highlighting a general trend of reduced BDNF levels in psoriasis patients, though potential variations in future studies are plausible (Fig. 2).
Fig. 2.

Forest plot of meta-analysis of BDNF levels in psoriasis patients compared to controls
Publication bias
Egger’s test was not performed due to the small number of studies included. However, the funnel plot appeared visually asymmetric, indicating potential publication bias (Fig. 3).
Fig. 3.

A: The funnel plot; B: counter-enhanced funnel plot
Sensitivity analysis
A sensitivity analysis was conducted to examine the impact of individual studies on overall heterogeneity. When the study by Fathy et al. was excluded, heterogeneity (I2) decreased significantly to 2%, indicating that this study was a primary contributor to the observed variability. In contrast, excluding any of the other five studies resulted in heterogeneity remaining above 69%. Despite these findings, the overall pooled estimate remained consistent, underscoring the robustness of the meta-analysis results (Fig. 4).
Fig. 4.

Results of sensitivity analysis (leave-one-out analysis) of the meta-analysis a: sorted by effect Sizes; b: sorted by I2
Meta-regression
We performed a meta-regression analysis to explore factors contributing to the heterogeneity in BDNF levels between psoriasis patients and healthy controls. The study considered sample size, mean age, and PASI score as potential moderators. None of these factors showed a statistically significant effect on BDNF levels (all p > 0.05), and they did not account for any variance (R2 Analog = 0.00%). Detailed results are presented in Table 3, and the relationships are visually represented in the bubble plots in Fig. 5.
Table 3.
Meta-regression of BDNF levels in psoriasis patients and healthy controls
| Moderator | No. of comparisons |
No. of subjects | Meta-regression | R2 Analog (Proportion of variance explained) (%) |
|||
|---|---|---|---|---|---|---|---|
| IHD | HC | Slope | 95% CI | P value | |||
| Sample size | 6 | 271 | 465 | 0.0015 | [−0.0146; 0.0176] | 0.8532 | 0.00% |
|
Age (mean, years) |
5 | 240 | 434 | −0.0023 | [−0.0497; 0.0451] | 0.9252 | 0.00% |
| PASI | 5 | 177 | 158 | −0.0494 | [−0.1343; 0.0355] | 0.2543 | 0.00% |
Fig. 5.

Bubble plot of meta-regression A: Sample Size; B: Mean Age; C: Pasi Score
Discussion
In this study, we compared BDNF levels in psoriasis patients and healthy controls. Our findings demonstrate a significant reduction in BDNF levels in psoriatic patients, supporting the role of neurotrophic factors like BDNF in the pathophysiology of psoriasis.
Brain-derived neurotrophic factor (BDNF) is a crucial neurotrophin involved in neuronal survival, growth, and maintenance, particularly in brain circuits associated with emotional and cognitive functions [20]. It is widely distributed throughout the brain and is essential for neuronal survival, growth, and plasticity [21]. BDNF is involved in various neurological functions, including:
Synaptic plasticity: BDNF modulates the strength and efficacy of synaptic connections, which is crucial for learning and memory processes [22].
Neurogenesis: It promotes the growth and differentiation of new neurons, particularly in areas like the hippocampus [22].
Neuroprotection: BDNF has been shown to have protective effects against neurodegeneration [23].
Neurotransmitter regulation: It influences the function of various neurotransmitter systems, including glutamatergic, GABAergic, serotonergic, and dopaminergic pathways [24, 25].
These roles underscore BDNF’s importance in brain function and its potential influence on mental health.
The physiological functions of BDNF extend beyond the central nervous system. Recent research has implicated BDNF in various peripheral processes, including inflammation and immune responses. This broader role of BDNF may explain its involvement in psoriasis, a chronic inflammatory skin condition characterized by the rapid growth of skin cells and the formation of thick, red, scaly patches. Psoriasis affects approximately 2% of the global population and can significantly impair the quality of life for those affected [26]. In consistent with our result, Brunoni et al. [10] observed decreased BDNF plasma levels in psoriasis patients (3.4 ± 3.12 ng/ml) compared to controls (5.94 ± 6.3 ng/ml).
In contrast, Bulur et al. [16] found higher BDNF levels in healthy controls (5.39 ± 3.65 ng/ml) compared to psoriasis patients with MetS (3.15 ± 2.44 ng/ml), implying a disrupted protective mechanism in the disease.
As depression is attributed to BDNF level reduction demonstrated in previous studies, and recent studies focused on BDNF levels changes in psoriasis patients and the relationship to depression, we reviewed them. There is substantial evidence showing a significant comorbidity between psoriasis and depression, affecting a notable portion of psoriasis patients [27]. Studies indicate that individuals with psoriasis are more likely to exhibit depressive symptoms compared to those without the condition [28]. This relationship appears to be bidirectional, with depression potentially exacerbating psoriasis symptoms and vice versa, profoundly impacting patients’ quality of life and overall well-being [29]. Studies with different depression diagnostic scales were conducted with controversies in results to find out any association between these two conditions based on BDNF levels [9, 15, 17, 30, 31]. Although the reviewed studies consistently report altered BDNF levels in patients with psoriasis and depression, suggesting a potential link between these conditions, there were many controversies. Sjahrir et al. [9] found that lower serum BDNF levels (9.12 ± 1.81 ng/ml) correlated with increased severity of both depression and psoriasis in patients with psoriasis vulgaris, supporting the hypothesis that BDNF dysregulation could be a common pathway linking these conditions. In contrast, Aksoy et al. [15] reported no significant differences in BDNF levels between psoriasis patients (32.45 ± 9.94 ng/ml) and controls (32.88 ± 8.84 ng/ml), suggesting that BDNF might not be directly linked to the presence of psoriasis but could be influenced by other factors such as disease duration or treatment. Vinnik et al. [19] found that serum BDNF levels in psoriasis patients were similar to those of healthy controls at symptom onset and after 10 weeks (40.49 ± 0.45 ng/ml), suggesting that BDNF levels might remain stable over the disease course. On the other hand, Raap et al. [18] found significantly lower BDNF levels in psoriasis patients (5.24 ± 2.97 ng/ml) compared to those with atopic dermatitis (6.97 ± 3.57 ng/ml), highlighting disease-specific differences in BDNF regulation.
Studies by Effendy et al. [31] and Fathy et al. [17] reported correlations between lower BDNF levels (9.12 ± 1.81 ng/ml and 20.49 ± 4.2 ng/ml, respectively) and increased depression severity in psoriasis patients. These findings suggest that BDNF could serve as a biomarker for depression in psoriasis patients, potentially aiding in early diagnosis and targeted treatment strategies. It should be noted that these studies differed in depression scales such as BDI-I [15, 17], BDI-II [9], HADS [31], and HAM-D [19], and some of them didn’t have the data for the control group. Moreover, Tohid et al. [32] mention that reduced blood levels of BDNF are observed in both depression and psoriasis, further supporting the connection between these conditions. By expanding our understanding of BDNF’s role in these conditions, we can better develop targeted therapies and improve the quality of life for patients suffering from psoriasis and depression. These discrepancies highlight the need for further research to understand the factors contributing to variations in BDNF levels among different patient populations and study designs.
Recognizing BDNF’s role in both depression and inflammatory conditions like psoriasis could significantly influence patient care and future research directions. For example, treatments that target BDNF enhancement—such as specific exercise regimens or medications aimed at boosting neurotrophic factors—could be valuable in managing both conditions simultaneously. This also suggests the potential for BDNF levels to serve as a biomarker for assessing disease severity or treatment response in patients with comorbid psoriasis and depression. Future research could focus on identifying which factors (e.g., disease duration, inflammatory load, or treatment type) impact BDNF levels, further clarifying its role in disease mechanisms, and guiding the development of therapies that address both physical and psychological symptoms in affected patients. Additionally, large-scale studies could help resolve conflicting findings on BDNF levels in psoriasis patients, leading to more standardized treatment approaches.
Limitations
It should be noted that the included studies varied in their design, BDNF measurement protocols, sample sizes, and populations. This heterogeneity makes direct comparisons challenging and may affect the generalizability of the findings. Furthermore, most of the included studies were cross-sectional, which limits the ability to infer causality between BDNF levels, psoriasis, and any probable association with depression. Longitudinal studies are needed to establish temporal relationships and causative links. Differences in the methods used to measure BDNF levels (e.g., serum vs. plasma, different ELISA kits) can lead to variability in results, potentially affecting the consistency and reliability of findings across studies. Moreover, many studies did not account for potential confounding factors such as medication use, disease severity, duration, and lifestyle factors, which could influence BDNF levels and the observed relationships. Studies included diverse populations from different geographic regions, which may have different genetic, environmental, and lifestyle factors affecting BDNF levels and the association with psoriasis and depression. As previous studies worked on depression, psoriasis, and BDNF levels, which didn’t have sufficient data, pooling data and running a meta-analysis could not be conducted. As previously mentioned in the discussion part, some didn’t have control, and all were different in depression diagnostic scales, which led to bias. This limitation emphasized the lack of efficient data to explain and suggested that researchers conduct more studies focusing on these probable underlying relationships.
Future directions
These findings have several important implications. BDNF’s involvement in psoriasis suggests it could be a valuable biomarker for identifying patients at risk, potentially allowing for earlier intervention and more personalized treatment strategies. Future research should focus on understanding the mechanisms by which BDNF influences psoriasis and depression and any other comorbidities, to screen patients earlier, investigate the effects of different treatments on BDNF levels, and explore BDNF’s role in other inflammatory conditions. Additionally, studies should aim to clarify the factors contributing to the variability in BDNF levels observed across different populations, which could improve our understanding of the pathophysiology of psoriasis and its association with depression.
Conclusion
This review highlights the significant reduction of BDNF levels in psoriasis patients. The evidence suggests that BDNF dysregulation may contribute to the development and severity of the condition. Understanding the underlying cause and relationship with other comorbidities like depression could inform future research and lead to improved treatment strategies for individuals affected by psoriasis and its psychological comorbidities.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
Not applicable.
Author contributions
S.M: drafting of the manuscript, study conception and design, data acquisition/ M.S, N.S, and S.A: drafting of the manuscript, data acquisition/P.S: data analysis, drafting of the manuscript/ M.V and F.B: critical revision/.
Funding
This study did not receive any specific grant from funding agencies.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Mohammad Sharifi Sarasyabi and Niloofar Seighali contributed equally to this work.
Change history
1/29/2026
This article has been updated to correct the missing ORCIDS.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
No datasets were generated or analysed during the current study.
