Potential Candidates for Biomarkers in Bipolar Disorder: A Proteomic Approach through Systems Biology

From blood to brain: Exploring the role of fibrinogen in the pathophysiology of depression and other neurological disorders

Recent findings indicate that fibrinogen, a protein involved in blood clotting, plays a significant role in neuroinflammation and mood disorders. Elevated fibrinogen levels are consistently observed in individuals with depression, potentially contributing to microglial activation. This could impair fibrinolysis and contribute to a pro-inflammatory environment in the brain. This neuroinflammatory response can impair neuroplasticity, a key process for learning, memory, and mood regulation. Fibrinogen may also indirectly influence neurotransmitters like serotonin, which play a vital role in mood regulation. Furthermore, fibrinogen's interaction with astrocytes may trigger a cascade of events leading to demyelination, a process where the protective sheath around nerve fibers deteriorates. This can disrupt communication within the nervous system and contribute to depression symptoms. Intriguingly, targeting fibrinogen or related pathways holds promise for therapeutic interventions. For instance, modulating PAI-1 (Plasminogen activator inhibitor-1) activity or inhibiting fibrinogen's interaction with brain cells could be potential strategies. This review explores the multifaceted relationship between fibrinogen and neurological disorders with a focus on depression highlighting its potential as a therapeutic target. Further research is necessary to fully elucidate the mechanisms underlying this association and develop effective therapeutic strategies targeting the fibrinolytic system for mood disorders.

Integrated proteomic and genomic analysis to identify predictive biomarkers for valproate response in bipolar disorder: a 6-month follow-up study

BACKGROUND

Several genetic studies have been undertaken to elucidate the intricate interplay between genetics and drug responses in bipolar disorder (BD). However, there has been notably limited research on biomarkers specifically linked to valproate, with only a few studies investigating integrated proteomic and genomic factors in response to valproate treatment. Therefore, this study aimed to identify biological markers for the therapeutic response to valproate treatment in BD. Patients with BD in remission were assessed only at baseline, whereas those experiencing acute mood episodes were evaluated at three points (baseline, 8 ± 2 weeks, and 6 ± 1 months). The response to valproate treatment was measured using the Alda scale, with individuals scoring an Alda A score ≥ 5 categorized into the acute-valproate responder (acute-VPAR) group. We analyzed 158 peptides (92 proteins) from peripheral blood samples using multiple reaction monitoring mass spectrometry, and proteomic result-guided candidate gene association analyses, with 1,627 single nucleotide variants (SNVs), were performed using the Korean chip.

RESULTS

The markers of 37 peptides (27 protein) showed temporal upregulation, indicating possible association with response to valproate treatment. A total of 58 SNVs in 22 genes and 37 SNVs in 16 genes showed nominally significant associations with the Alda A continuous score and the acute-VPAR group, respectively. No SNVs reached the genome-wide significance threshold; however, three SNVs (rs115788299, rs11563197, and rs117669164) in the secreted phosphoprotein 2 gene reached a gene-based false discovery rate-corrected significance threshold with response to valproate treatment. Significant markers were associated with the pathophysiological processes of bipolar disorders, including the immune response, acute phase reaction, and coagulation cascade. These results suggest that valproate effectively suppresses mechanisms associated with disease progression.

CONCLUSIONS

The markers identified in this study could be valuable indicators of the underlying mechanisms associated with response to valproate treatment.

Olink proteomics analysis uncovers inflammatory proteins in patients with different states of bipolar disorder

STUDY DESIGN

A prospective study.

BACKGROUND

This study aims to investigate the relationship between different states of bipolar disorder (BD) and plasma inflammatory proteins, which may be used as their biomarkers.

MATERIALS AND METHODS

We totally collected admission plasma from 16 healthy subjects and 32 BD patients, including 16 patients with BD manic episodes (BD-M) and 16 patients with BD depressive episodes (BD-D). Ten samples in each group were analyzed by proximity extension assays of 92 inflammation-related proteins, and all samples were verified by ELISA. Receiver-operating characteristic (ROC) curve analysis was performed to identify the diagnostic ability and cut-off values of potential biomarkers.

RESULTS

Our findings showed that BD patients had significantly higher levels of IL6, MCP-1, TGF-α, IL8, and IL10-RB in comparison with healthy subjects, and their cut-off values were 0.531 pg/ml, 0.531 pg/ml, 0.469 pg/ml, 0.406 pg/ml, and 0.406 pg/ml, respectively. The levels of IL6, MCP-1, TGF-α, and IL8 in BD-M patients were significantly greater than in healthy individuals, and their cut-off values were 0.813 pg/ml, 0.688 pg/ml, 0.438 pg/ml, and 0.625 pg/ml, respectively. Moreover, we found cut-off values of 0.500 pg/mL and 0.688 ng/mL for TGF-α and β-NGF, respectively, even though the levels in the BD-D group were much higher than in the control group. Furthermore, BD-M patients had significantly higher levels of IL6, FGF-19, IFN-γ, and IL-17C in comparison with BD-D patients. Likewise, 0.687 pg/ml, 0.500 pg/ml, 0.438 pg/ml, and 0.375 pg/ml were their cut-off values, respectively. Our findings also showed that the combination of these proteins had the highest diagnostic accuracy.

CONCLUSIONS

Our findings showed that plasma inflammatory proteins were related to BD and its subtypes, which may be utilized as potential biomarkers of different stages of BD. Furthermore, we also found their cut-off values and their combinations to have the highest diagnostic accuracy, providing clinicians with a new method to rapidly differentiate BD and its subtypes and manage early targeted interventions.

Proteomic insights into mental health status: plasma markers in young adults

Global emphasis on enhancing prevention and treatment strategies necessitates an increased understanding of the biological mechanisms of psychopathology. Plasma proteomics is a powerful tool that has been applied in the context of specific mental disorders for biomarker identification. The p-factor, also known as the "general psychopathology factor", is a concept in psychopathology suggesting that there is a common underlying factor that contributes to the development of various forms of mental disorders. It has been proposed that the p-factor can be used to understand the overall mental health status of an individual. Here, we aimed to discover plasma proteins associated with the p-factor in 775 young adults in the FinnTwin12 cohort. Using liquid chromatography-tandem mass spectrometry, 13 proteins with a significant connection with the p-factor were identified, 8 of which were linked to epidermal growth factor receptor (EGFR) signaling. This exploratory study provides new insight into biological alterations associated with mental health status in young adults.

[Growth factors PDGF-AA, PDGF-BB and BDNF as potential differentiating biomarkers of unipolar and bipolar depression]

OBJECTIVE

To establish the differences and identify the prognostic value of biological markers - platelet growth factors PDGF-AA, PDGF-BB and brain-derived neurotrophic growth factor (BDNF) - for the differential diagnosis of patients with unipolar and bipolar depression using machine learning.

MATERIAL AND METHODS

The study included 79 patients aged 48 [34; 57] years, including 35 people with bipolar depression (ICD-10. F31) and 44 people with unipolar depression (F32-33). Clinical assessment of the patients' condition was carried out using the Hamilton Depression Rating Scale (HDRS-17) and the Hamilton Anxiety Rating Scale (HARS). The concentration of growth factors in the blood serum of patients was determined using multiplex analyzers Magpix and Luminex 200 (Luminex, USA). To build a predictive model, the support vector machine was used.

RESULTS

Patients with bipolar depression showed statistically significant higher concentrations of PDGF-AA and PDGF-BB, as well as lower concentrations of BDNF. When constructing a predictive model, it was possible to separate patients with unipolar and bipolar depression according to all three biomarkers; the sensitivity and specificity of the model were 0.96±0.06 and 0.95±0.05, respectively.

CONCLUSIONS

The study of concentrations of BDNF and platelet-derived growth factors shows statistically significant differences in indicators in the case of unipolar and bipolar depression, which can potentially be used as prognostic biomarkers for differential diagnosis in appropriate clinical cases.

Differences in intracellular protein levels in monocytes and CD4+ lymphocytes between bipolar depressed patients and healthy controls: A pilot study with tyramine-based signal-amplified flow cytometry

BACKGROUND

Molecular biomarkers for bipolar disorder (BD) that distinguish it from other manifestations of depressive symptoms remain unknown. The aim of this study was to determine if a very sensitive tyramine-based signal-amplification technology for flow cytometry (CellPrint™) could facilitate the identification of cell-specific analyte expression profiles of peripheral blood cells for bipolar depression (BPD) versus healthy controls (HCs).

METHODS

The diagnosis of psychiatric disorders was ascertained with Mini International Neuropsychiatric Interview for DSM-5. Expression levels for eighteen protein analytes previously shown to be related to bipolar disorder were assessed with CellPrint™ in CD4⁺ T cells and monocytes of bipolar patients and HCs. Implementation of protein-protein interaction (PPI) network and pathway analysis was subsequently used to identify new analytes and pathways for subsequent interrogations.

RESULTS

Fourteen drug-naïve or -free patients with bipolar I or II depression and 17 healthy controls (HCs) were enrolled. The most distinguishable changes in analyte expression based on t-tests included GSK3β, HMGB1, IRS2, phospho-GSK3αβ, phospho-RELA, and TSPO in CD4⁺ T cells and calmodulin, GSK3β, IRS2, and phospho-HS1 in monocytes. Subsequent PPI and pathway analysis indicated that prolactin, leptin, BDNF, and interleukin-3 signal pathways were significantly different between bipolar patients and HCs.

LIMITATION

The sample size of the study was small and 2 patients were on medications.

CONCLUSION

In this pilot study, CellPrint™ was able to detect differences in cell-specific protein levels between BPD patients and HCs. A subsequent study including samples from patients with BPD, major depressive disorder, and HCs is warranted.

Brain-derived Neurotrophic Factor and High Sensitive C-reactive Protein in Bipolar Depression and Unipolar Depression: The Practical Usage as a Discriminatory Tool

Objective

Brain-derived neurotrophic factor (BDNF) and high sensitive C-reactive protein (hs-CRP) have been reported to play roles in depression and bipolar disorder (BD). However, the probable discriminatory properties of these biologic markers are less investigated. We aimed to assess the serum BDNF and hs-CRP levels among Iranian patients with major depressive disorder (MDD) and BD during a depressive episode and investigate the optimum cut-off point for differential diagnosis of BD and MDD.

Methods

We recruited 30 patients with MDD, 30 with BD in depressive mood and 30 healthy comparators. Blood sample was taken from each participant to measure BDNF and hs-CRP levels. We also used receiver operating characteristic (ROC) curve analysis to find an optimal cut-off point for differentiating MDD from BD according to pre-defined variables.

Results

The mean age of total study population was 37.3 ± 5.0 years (males: 49%). BDNF was significantly lower in patients with BD, followed by MDD subjects and healthy controls 541.0 ± 601.0 pg/ml vs. 809.5 ± 433.3 pg/ml vs. 1,482.1 ± 519.8, respectively, p < 0.001). The area under curve of ROC curve analysis for BD versus MDD was 0.704 (95% confidence interval: 0.564-0.844, p = 0.007). We also found that the BDNF cut-off value of 504 could appropriately distinguished BD from MDD (sensitivity: 73%, specificity: 70%). No significant association were identified in terms of hs-CRP levels.

Conclusion

Patients suffering from BD had lowest BDNF levels compared to MDD or healthy adults and this biomarker could play a practical role differentiating MDD from BD. Several studies are required confirming our outcomes.

Variations in olfactory function among bipolar disorder patients with different episodes and subtypes

Purpose

Most studies on olfactory function in individuals with bipolar disorder (BD) have not distinguished between the different subtypes or between the acute phase (mania or depression) and euthymic state. In this study, we compared olfactory function among BD patients with different subtypes and episodes to explore the potential use of olfactory function as a biomarker for the early identification of BD.

Patients and methods

The study sample consisted of 117 BD patients who were hospitalized between April 2019 and June 2019, and 47 healthy volunteers as controls. The BD patients were divided into a bipolar I disorder (BD I) (n = 86) and bipolar II disorder (BD II) group (n = 31) according to the different subtypes, and divided into depressive BD (n = 36), manic BD (n = 44), or euthymic BD (n = 37) groups according to the types of episodes they experienced. We assessed olfactory sensitivity (OS) and olfactory identification (OI) via the Sniffin' Sticks test and used the Hamilton Depression Rating Scale (HAMD) and Young Manic Rating Scale (YMRS) to evaluate BD characteristics among all subjects.

Results

Compared with controls, the participants with BD showed decreased OS and OI. We found statistically significant differences in OS and OI between the BD I group and controls, as well as differences in OS between the BD I and BD II group. Least-significant difference multiple comparisons revealed statistically significant differences in OS between the depressive BD group, manic BD group and controls and also between the manic BD and euthymic BD group. OI was positively correlated with the YMRS score in the BD I group and OS was negatively correlated with the HAMD score in the BD II group.

Conclusion

This may be the first study to compare olfactory function in patients with BD I vs. BD II via pairwise comparisons. Our findings suggest that OS may have potential as a biomarker for distinguishing the different subtypes of BD and as a state-related biomarker for differentiating the acute phase from the euthymic state of BD. However, further prospective research is warranted.

Current Status of Therapeutic Drug Monitoring in Mental Health Treatment: A Review

Therapeutic drug monitoring (TDM) receives growing interest in different psychiatric clinical settings (emergency, inpatient, and outpatient services). Despite its usefulness, TDM remains underemployed in mental health. This is partly due to the need for evidence about the relationship between drug serum concentration and efficacy and tolerability, both in the general population and even more in subpopulations with atypical pharmacokinetics. This work aims at reviewing the scientific literature published after 2017, when the most recent guidelines about the use of TDM in mental health were written. We found 164 pertinent records that we included in the review. Some promising studies highlighted the possibility of correlating early drug serum concentration and clinical efficacy and safety, especially for antipsychotics, potentially enabling clinicians to make decisions on early laboratory findings and not proceeding by trial and error. About populations with pharmacokinetic peculiarities, the latest studies confirmed very common alterations in drug blood levels in pregnant women, generally with a progressive decrease over pregnancy and a very relevant dose-adjusted concentration increase in the elderly. For adolescents also, several drugs result in having different dose-related concentration values compared to adults. These findings stress the recommendation to use TDM in these populations to ensure a safe and effective treatment. Moreover, the integration of TDM with pharmacogenetic analyses may allow clinicians to adopt precise treatments, addressing therapy on an individual pharmacometabolic basis. Mini-invasive TDM procedures that may be easily performed at home or in a point-of-care are very promising and may represent a turning point toward an extensive real-world TDM application. Although the highlighted recent evidence, research efforts have to be carried on: further studies, especially prospective and fixed-dose, are needed to replicate present findings and provide clearer knowledge on relationships between dose, serum concentration, and efficacy/safety.