iTRAQ technology-based identification of human peripheral serum proteins associated with depression

The relevance of endoplasmic reticulum lumen and Anoctamin-8 for major depression: Results from a systems biology study

Major depressive disorder (MDD) is a highly prevalent and debilitating disorder, yet its pathophysiology has not been fully elucidated. The aim of this study is to identify novel potential proteins and biological processes associated with MDD through a systems biology approach. Original articles involving the measurement of proteins in the blood of patients diagnosed with MDD were selected. Data on the differentially expressed proteins (DEPs) in each article were extracted and imported into R, and the pathfindR package was used to identify the main gene ontology terms involved. Data from the STRING database were combined with the DEPs identified in the original studies to create expanded networks of protein-protein interactions (PPIs). An R script was developed to obtain the five most reliable connections from each DEP and to create the networks, which were visualized through Cytoscape software. Out of 510 articles found, eight that contained all the values necessary for the analysis were selected, including 1112 adult patients with MDD and 864 controls. A total of 240 DEPs were identified, with the most significant gene ontology term being "endoplasmic reticulum lumen" (46 DEPs, p-value = 5.5x10-13). An extended PPI network was obtained, where Anoctamin-8 was the most central protein. Using systems biology contributed to the interpretation of data obtained in proteomic studies on MDD and expanded the findings of these studies. The combined use of these methodologies can provide new insights into the pathophysiology of psychiatric disorders, identifying novel biomarkers to improve diagnostic, prognostic, and treatment strategies in MDD.

The use of 4D data-independent acquisition-based proteomic analysis and machine learning to reveal potential biomarkers for stress levels

Research suggests that individuals who experience prolonged exposure to stress may be at higher risk for developing psychological stress disorders. Currently, psychological stress is primarily evaluated by professional physicians using rating scales, which may be prone to subjective biases and limitations of the scales. Therefore, it is imperative to explore more objective, accurate, and efficient biomarkers for evaluating the level of psychological stress in an individual. In this study, we utilized 4D data-independent acquisition (4D-DIA) proteomics for quantitative protein analysis, and then employed support vector machine (SVM) combined with SHAP interpretation algorithm to identify potential biomarkers for psychological stress levels. Biomarkers validation was subsequently achieved through machine learning classification and a substantial amount of a priori knowledge derived from the knowledge graph. We performed cross-validation of the biomarkers using two batches of data, and the results showed that the combination of Glyceraldehyde-3-phosphate dehydrogenase and Fibronectin yielded an average area under the curve (AUC) of 92%, an average accuracy of 86%, an average F1 score of 79%, and an average sensitivity of 83%. Therefore, this combination may represent a potential approach for detecting stress levels to prevent psychological stress disorders.

Serum proteomic changes related to residual impairment in remittent depression are associated with immune and inflammatory processes

In patients with major depressive disorder, various functional areas are impaired, negatively impacting the quality of life. Remission can restore pre-depression functions; however, some patients may still have residual impairments. Distinguishing between near-normal recovery and residual impairment helps identify those at a high risk of relapse risk and helps tailor treatment. Accordingly, we aimed to discover and validate biomarkers that distinguish between near-normal recovery and residual impairment in remission states through serum proteome analysis. Pooled serum and individual serum samples from three groups (depression status, remission status with residual impairment, and remission status with normal recovery) were analyzed using liquid chromatography-tandem mass spectrometry. The combination of four proteins-antithrombin-III, serum amyloid A4 protein, C1q subcomponent subunit B, and serum amyloid P-component-was selected as a candidate biomarker. The trend of protein changes suggests complement C1q subcomponent subunit B and serum amyloid P-component as potential biomarkers for distinguishing remission from residual impairment. Changes in complement C1q subcomponent subunit B and serum amyloid P-component suggest that the complement system and inflammation-related immune mechanisms are associated with residual impairment in remittent major depressive disorder.

Plasma alpha-trypsin inhibitor heavy chain 4 as an age-specific biomarker in the diagnosis and treatment of major depressive disorder

Background

The diagnosis of major depressive disorder (MDD) mainly depends on subjective clinical symptoms, without an acceptable objective biomarker for the clinical application of MDD. Inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) showed a high specificity as biomarker for the diagnosis and treatment of MDD. The present study aimed to investigate differences in plasma ITIH4 in two different aged MDD patients and underlying pathological mechanisms of plasma ITIH4 in the occurrence and development of MDD.

Methods

Sixty-five adult MDD patients, 51 adolescent MDD patients, and 64 healthy controls (HCs) were included in the present study. A 14-days' antidepressive treatment was conducted in all MDD patients. Psychological assessments were performed and plasma ITIH4 and astrocyte-related markers were detected for all participants.

Results

(1) Plasma levels of ITIH4 in adult MDD patients were significantly higher than adolescent MDD patients and HCs, and significantly increased plasma ITIH4 levels was observed in adolescent MDD patients compared with HCs (2). There were positive correlations between plasma ITIH4 levels and 24-item Hamilton Depression Scale (HAMD-24) scores and plasma glial fibrillary acidic protein (GFAP) levels in MDD patients, however, plasma ITIH4 levels were significantly correlated with age just in adult MDD patients (3). Plasma ITIH4 showed area under the curve values of 0.824 and 0.729 to differentiate adult MDD patients and adolescent MDD patients from HCs, respectively (4). There was significant decrease in plasma levels of ITIH4 between before and after antidepressive treatment in adult MDD patients, but not in adolescent MDD patients (5). Changed value of ITIH4 levels were correlated with the changed value of GFAP levels and changed rate of HAMD-24 scores in adult MDD patients following antidepressive treatment.

Conclusion

Plasma ITIH4 may be potential plasma biomarkers of MDD with age-related specificity, which was associated with depressive symptoms astrocyte-related pathologic changes, and antidepressive treatment efficacy.

Serum proteomic analysis uncovers novel serum biomarkers for depression

Objective

The identification of depression primarily relies on the clinical symptoms and psychiatric evaluation of the patient, in the absence of objective and quantifiable biomarkers within clinical settings. This study aimed to explore potential serum biomarkers associated with depression.

Methods

Serum samples from a training group comprising 48 depression patients and 48 healthy controls underwent proteomic analysis. Magnetic bead-based weak cation exchange (MB-WCX) and MALDI-TOF-MS were used in combination. To screen the differential peaks, ClinProTools software was employed. The proteins were identified using LC-MS/MS. ELISA was employed to confirm the expression of entire protein in the serum of the verification cohort, which encompassed 48 individuals who had been diagnosed with Depression and 48 healthy controls who were collected prospectively. Subsequently, logistic regression analysis was conducted to determine the diagnostic efficacy of the aforementioned predictors.

Results

Five potential biomarker peaks indicating depression were identified in serum samples (peak 1, m/z: 1868.21; peak 2, m/z: 1062.35; peak 3, m/z: 1452.12; peak 4, m/z: 1208.72; peak 5, m/z: 1619.58). All of these peaks had higher expression in the pre-therapy group and were confirmed to be Tubulin beta chain (TUBB), Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), Complement component 3 (C3), and Complement C4A precursor (C4A) by ELISA validation. Multivariate logistic regression analysis revealed that serum levels of TUBB, ITIH4, C3, and C4A were significant independent risk factors for the development of depression.

Conclusion

Depression is a prevalent psychiatric condition. Timely detection is challenging, resulting in poor prognoses for patients. Our study on plasma proteomics for depression demonstrated that TUBB, ITIH4, C3, and C4A differentiate between depression patients and healthy controls. The proteins that were identified could potentially function as biomarkers for the diagnosis of depression. Pinpointing these biomarkers could enable early identification of depression, which would advance precise treatment.

Discovery and validation of a protein biomarker for the diagnosis and classification of disease severity of major depressive disorder

BACKGROUND AND AIMS

Diagnosis and classification of disease severity of major depressive disorder (MDD) are determined through a doctor's consultation and questionnaire-based rating scale. This study aimed to identify and validate a serum protein biomarker for diagnosing and classifying the disease severity of MDD.

MATERIALS AND METHODS

Based on the Hamilton Depression Rating Scale (HAMD) score, participants were divided into control, mild, moderate, and severe groups. Samples prepared from collected sera were analyzed using non-targeted qualitative and targeted quantitative tools to identify potential biomarkers.

RESULTS

Four proteins were selected as biomarker candidates, which showed statistically significant consistent tendencies depending on MDD severity. Among them, tetranectin was the only validated protein in the quantitative analysis that showed the same decreasing tendency as that in the qualitative analysis. Furthermore, tetranectin showed fair discrimination performance between the control and MDD group.

CONCLUSIONS

Tetranectin may be a novel potential biomarker for diagnosing and classifying the severity of MDD, though further verification and validation studies of its efficacy are needed.

Effects of Ozone on Sickness and Depressive-like Behavioral and Biochemical Phenotypes and Their Regulation by Serum Amyloid A in Mice

Ozone (O₃) is an air pollutant that primarily damages the lungs, but growing evidence supports the idea that O₃ also harms the brain; acute exposure to O₃ has been linked to central nervous system (CNS) symptoms such as depressed mood and sickness behaviors. However, the mechanisms by which O₃ inhalation causes neurobehavioral changes are limited. One hypothesis is that factors in the circulation bridge communication between the lungs and brain following O₃ exposure. In this study, our goals were to characterize neurobehavioral endpoints of O₃ exposure as they relate to markers of systemic and pulmonary inflammation, with a particular focus on serum amyloid A (SAA) and kynurenine as candidate mediators of O₃ behavioral effects. We evaluated O₃-induced dose-, time- and sex-dependent changes in pulmonary inflammation, circulating SAA and kynurenine and its metabolic enzymes, and sickness and depressive-like behaviors in Balb/c and CD-1 mice. We found that 3 parts per million (ppm) O₃, but not 2 or 1 ppm O₃, increased circulating SAA and lung inflammation, which were resolved by 48 h and was worse in females. We also found that indoleamine 2,3-dioxygenase (Ido1) mRNA expression was increased in the brain and spleen 24 h after 3 ppm O₃ and that kynurenine was increased in blood. Sickness and depressive-like behaviors were observed at all O₃ doses (1-3 ppm), suggesting that behavioral responses to O₃ can occur independently of increased SAA or neutrophils in the lungs. Using SAA knockout mice, we found that SAA did not contribute to O₃-induced pulmonary damage or inflammation, systemic increases in kynurenine post-O₃, or depressive-like behavior but did contribute to weight loss. Together, these findings indicate that acute O₃ exposure induces transient symptoms of sickness and depressive-like behaviors that may occur in the presence or absence of overt pulmonary neutrophilia and systemic increases of SAA. SAA does not appear to contribute to pulmonary inflammation induced by O₃, although it may contribute to other aspects of sickness behavior, as reflected by a modest effect on weight loss.

Combined repetitive transcranial magnetic stimulation and medication treatment for depression is associated with serum amyloid a level: Evidence from naturalistic clinical practice

Objective

Repetitive transcranial magnetic stimulation (rTMS) has a positive effect on patients with depressive disorder, while the underpinning molecular mechanism is unknown. Here, we aimed to investigate the effect of rTMS on serum levels of serum amyloid A (SAA) and testosterone in a real-world setting.

Materials and methods

In total, ninety-seven patients with depressive disorder were treated with medicine and rTMS (the rTMS group) while 122 patients were treated using the medicine only (the control group). Plasma levels of SAA (n = 52) and testosterone (n = 37) were measured before and after 2 weeks of treatment, and the treatment effect was evaluated by Hamilton Rating Scale for Depression (HAMD).

Results

The treatment effect revealed by the percentage of decrease in HAMD in the second week was significantly greater in the rTMS group compared with the control group. No significant difference was found in SAA or testosterone levels between the two groups. However, the percentage of changes in SAA (r = −0.492, p = 0.017) in the second week was significantly correlated with the percentage of decrease in HAMD score in the rTMS group, but not in the control group.

Conclusion

Patients with depression benefit more from combined rTMS and medication treatment in this naturalistic study. Changes in SAA level, but not testosterone level, were related to depressive remission after 2 weeks’ combined treatment.

Plasma proteomic signature of major depressive episode in the elderly

Depression is a complex and multifactorial disease, affecting about 6.5% of the elderly population in what is referred to as late-life depression (LLD). Despite its public health relevance, there is still limited information about the molecular mechanisms of LLD. We analyzed the blood plasma of 50 older adults, 19 with LLD and 31 controls, through untargeted mass spectrometry, and used systems biology tools to identify biochemical pathways and biological processes dysregulated in the disease. We found 96 differentially expressed proteins between LLD patients and control individuals. Using elastic-net regression, we generated a panel of 75 proteins that comprises a potential model for determining the molecular signature of LLD. We also showed that biological pathways related to vesicle-mediated transport and voltage-dependent calcium channels may be dysregulated in LLD. These data can help to build an understanding of the molecular basis of LLD, offering an integrated view of the biomolecular alterations that occur in this disorder. SIGNIFICANCE: Major depressive disorder in the elderly, called late-life depression (LLD), is a common and disabling disorder, with recent prevalence estimates of 6.5% in the general population. Despite the public health relevance, there is still limited information about the molecular mechanisms of LLD. The findings in this paper shed light on LLD heterogeneous biological mechanisms. We uncovered a potential novel biomolecular signature for LLD and biological pathways related to this condition which can be targets for the development of novel interventions for prevention, early diagnosis, and treatment of LLD.

Isobaric Tags for Relative and Absolute Quantitation Identification of Blood Proteins Relevant to Paroxetine Response in Patients With Major Depressive Disorder

OBJECTIVES

Isobaric tags for relative and absolute quantitation (iTRAQ) is a proteomic investigation that could be utilized for rapid identification and quantification of proteins, which we would use to identify differentially expressed proteins in treatment responsive patients with major depressive disorder (MDD).

METHODS

Six treatment responsive patients of MDD were recruited, and their peripheral blood mononuclear cell (PBMC) were collected before and after 4 weeks of paroxetine treatment. iTRAQ and Mascot search engine were used to detect differentially expressed proteins, which were then validated by Western blot.

RESULTS

Two thousand one hundred and fifty three proteins were screened, and seven proteins showed differences of more than two-fold and 62 proteins with a differences of less than two-fold. Six proteins with commercially available antibodies were identified, and were validated by Western blot in 10 paroxetine responsive MDD patients. Putative hydroxypyruvate isomerase (HYI), eukaryotic translation initiation factor 4H (eIF4H), and RNA binding motif 8A (RBM8A) had statistically significant differences before and after treatment in the validation. Data are available via ProteomeXchange with identifier PXD028947.

CONCLUSIONS

By using iTRAQ and Western blot, we were able to identify HYI, eIF4H, and RAM8a to be the potential predictors of paroxetine treatment response in patients with MDD. This finding could help establish future individualized medicine.

Prioritization of human well-being spectrum related GWAS-SNVs using ENCODE-based web-tools predict interplay between PSMC3, ITIH4, and SERPINC1 genes in modulating well-being

Several traits related to positive and negative affect show a high genetic as well as phenotypic correlation with well-being in humans, and are therefore collectively termed as "Well-being spectrum". Genome-Wide Association studies (GWA studies) on "well-being measurement" have led to identification of several genomic variants (Single Nucleotide Variants - SNVs), but very little has been explained with respect to their functionality and mode of alteration of well-being. Utilizing a pool of 1258 GWA studies based SNVs on "well-being measurement", we prioritized the SNVs and tried to annotate well-being related functionality through several bioinformatic tools to predict whether a protein sequence variation affects protein function, as well as experimentally validated datasets available in ENCODE based web-tools namely rSNPBase, RegulomeDB, Haploreg, along with GTEx Portal and STRING based protein interaction networks. Prioritization yielded three key SNVs; rs3781627-A, rs13072536-T and 5877-C potentially regulating three genes, PSMC3, ITIH4 and SERPINC1, respectively. Interestingly, the genes showed well clustered protein-protein interaction (maximum combined confidence score >0.4) with other well-being candidate genes, namely TNF and CRP genes suggesting their important role in modulation of well-being. PSMC3 and ITIH4 genes are also involved in driving acute phase responses signifying a probable cross-talk between well-being and psychoneuroimmunological system. To best of our knowledge this study is the first of its kind where the well-being associated GWA studies-SNVs were prioritized and functionally annotated, majorly based on functional data available in public domain, which revealed PSMC3, ITIH4 and SERPINC1 genes as probable candidates in regulation of well-being spectrum.

Biomarkers of Post-COVID Depression

The COVID-19 pandemic is spreading around the world and 187 million people have already been affected. One of its after-effects is post-COVID depression, which, according to the latest data, affects up to 40% of people who have had SARS-CoV-2 infection. A very important issue for the mental health of the general population is to look for the causes of this complication and its biomarkers. This will help in faster diagnosis and effective treatment of the affected patients. In our work, we focused on the search for major depressive disorder (MDD) biomarkers, which are also present in COVID-19 patients and may influence the development of post-COVID depression. For this purpose, we searched PubMed, Scopus and Google Scholar scientific literature databases using keywords such as 'COVID-19', 'SARS-CoV-2', 'depression', 'post-COVID', 'biomarkers' and others. Among the biomarkers found, the most important that were frequently described are increased levels of interleukin 6 (IL-6), soluble interleukin 6 receptor (sIL-6R), interleukin 1 β (IL-1β), tumor necrosis factor α (TNF-α), interferon gamma (IFN-γ), interleukin 10 (IL-10), interleukin 2 (IL-2), soluble interleukin 2 receptor (sIL-2R), C-reactive protein (CRP), Monocyte Chemoattractant Protein-1 (MCP-1), serum amyloid a (SAA1) and metabolites of the kynurenine pathway, as well as decreased brain derived neurotrophic factor (BDNF) and tryptophan (TRP). The biomarkers identified by us indicate the etiopathogenesis of post-COVID depression analogous to the leading inflammatory hypothesis of MDD.

Potential biomarkers: differentially expressed proteins of the extrinsic coagulation pathway in plasma samples from patients with depression

Depression is a severe disabling psychiatric illness and the pathophysiological mechanisms remain unknown. In previous work, we found the changes in extrinsic coagulation (EC) pathway proteins in depressed patients compared with healthy subjects were significant. In this study, we screened differentially expressed proteins (DEPs) in the EC pathway, and explored the molecular mechanism by constructing a protein-protein interaction (PPI) network. The DEPs of the EC pathwaywere initially screened by isobaric tags for relative and absolute quantification (iTRAQ) in plasma samples obtained from 20 depression patients and 20 healthy controls, and were then identified by Enzyme-linked immunosorbent assays (ELISAs). Ingenuity Pathway Analysis (IPA) software was used to analyse pathway. The differentially expressed genes (DEGs) were identified by analyzing the GSE98793 microarray data from the Gene Expression Omnibus database using the Significance Analysis for Microarrays (SAM, version 4.1) statistical method. Cytoscape version 3.4.0 software was used to construct and visualize PPI networks. The results show that Fibrinogen alpha chain (FGA), Fibrinogen beta chain (FGB), Fibrinogen gamma chain (FGG) and Coagulation factor VII (FVII) were screened in the EC pathway from depression patient samples. FGA, FGB, and FGG were significantly up-regulated, and FVII was down-regulated. Thirteen DEGs related to depression and EC pathways were identified from the microarray database. Among them NF-κB Inhibitor Beta (NFKBIB) and Heat shock protein family B (small) member 1 (HSPB1) were highly correlated with EC pathway. We conclude that EC pathway is associated with depression, which provided clues for the biomarker development and the pathogenesis of depression.

Quantitative Proteomic Approach for Discriminating Major Depressive Disorder and Bipolar Disorder by Multiple Reaction Monitoring-Mass Spectrometry

Because major depressive disorder (MDD) and bipolar disorder (BD) manifest with similar symptoms, misdiagnosis is a persistent issue, necessitating their differentiation through objective methods. This study was aimed to differentiate between these disorders using a targeted proteomic approach. Multiple reaction monitoring-mass spectrometry (MRM-MS) analysis was performed to quantify protein targets regarding the two disorders in plasma samples of 270 individuals (90 MDD, 90 BD, and 90 healthy controls (HCs)). In the training set (72 MDD and 72 BD), a generalizable model comprising nine proteins was developed. The model was evaluated in the test set (18 MDD and 18 BD). The model demonstrated a good performance (area under the curve (AUC) >0.8) in discriminating MDD from BD in the training (AUC = 0.84) and test sets (AUC = 0.81) and in distinguishing MDD from BD without current hypomanic/manic/mixed symptoms (90 MDD and 75 BD) (AUC = 0.83). Subsequently, the model demonstrated excellent performance for drug-free MDD versus BD (11 MDD and 10 BD) (AUC = 0.96) and good performance for MDD versus HC (AUC = 0.87) and BD versus HC (AUC = 0.86). Furthermore, the nine proteins were associated with neuro, oxidative/nitrosative stress, and immunity/inflammation-related biological functions. This proof-of-concept study introduces a potential model for distinguishing between the two disorders.

Exploration of identifying novel serum biomarkers for malignant mesothelioma using iTRAQ combined with 2D-LC-MS/MS

Malignant mesothelioma (MM) is an aggressive cancer linked to asbestos exposure. Its poor prognosis makes early diagnosis extremely important, which would provide an opportunity for early treatment and potentially changing outcomes. This study aimed to explore the underlying mechanisms of MM and discover novel noninvasive biomarkers for the diagnosis of malignant mesothelioma. Using Isobaric tags for relative and absolute quantitation (iTRAQ) combined with two-dimensional liquid chromatography/tandem mass spectrometry (2D LC-MS/MS), a total of 145 differentially expressed serum proteins were identified between MM patients and healthy controls. The identified proteins were further analyzed by bioinformatics, out of which three candidate biomarkers (Filamin A (FLNA), Fibulin 1 (FBLN1) and Thrombospondin-1 (TSP-1)) were validated in large cohorts of patients with asbestos-related diseases including MM patients by ELISA assay. Receiver operating characteristic (ROC) curve analysis showed that serum FLNA, FBLN1 and TSP-1 had high diagnostic values in distinguishing MM patients from healthy controls, individuals with asbestos exposure (AE), and patients with pleural plaques (PP) or asbestosis. Meanwhile, serum FBLN1 and TSP-1 possessed good diagnostic values in distinguishing asbestosis patients from healthy controls and individuals with AE. The combination of FLNA, FBLN1, and TSP-1 proteins had higher sensitivity and specificity in discriminating patients with MM, PP and asbestosis. Our findings indicated that analysis of serum proteome using iTRAQ is a feasible strategy for biomarker discovery, and serum FLNA, FBLN1 and TSP-1 may be promising candidates for diagnosis of malignant mesothelioma and screening of at-risk individuals.

Relationships Between a Range of Inflammatory Biomarkers and Subjective Sleep Quality in Chronic Insomnia Patients: A Clinical Study

PURPOSE

To examine whether associations exist between chronic insomnia disorder (CID) and overlooked inflammatory factors (Serum amyloid protein A [SAA]), tumor necrosis factor [TNF]-α, granulocyte-macrophage colony-stimulating factor [GM-CSF], and regulated on activation and normal T cell expressed and presumably secreted [RANTES]).

PATIENTS AND METHODS

A total of 65 CID patients and 39 sex- and age-matched good sleeper (GS) controls participated in this study. They completed a baseline survey to collect data on demographics, and were elevated sleep and mood by Pittsburgh Sleep Quality Index (PSQI), Athens Insomnia Scale (AIS), 17-item Hamilton Depression Rating Scale (HAMD-17) and 14-item Hamilton Anxiety Rating Scale (HAMA-14), respectively. The blood samples were collected and tested the serum levels of SAA, TNF-α, GM-CSF and RANTES.

RESULTS

The CID group had higher serum levels of SAA, TNF-α, and GM-CSF and a lower level of RANTES than the GS group. In the Spearman correlation analysis, SAA and GM-CSF positively correlated with the PSQI and AIS scores. After controlling for sex, HAMD-17 score, and HAMA-14 score, the partial correlation analysis showed that GM-CSF was positively correlated with PSQI score. Further stepwise linear regression analyses showed that GM-CSF was positively associated with the PSQI and AIS scores, while RANTES was negatively associated with them, and SAA was positively associated with just the AIS score.

CONCLUSION

The serum levels of inflammatory mediators (SAA, TNF-α, and GM-CSF) were significantly elevated and the level of RANTES was significantly decreased in CID patients and, to some extent, the changes are related to the severity of insomnia. These findings may help us to improve interventions to prevent the biological consequences of CID by inhibiting inflammation, thereby promoting health.

Identifying Plasma Biomarkers with high specificity for major depressive disorder: A multi-level proteomics study

BACKGROUND

There are currently no objective diagnostic biomarkers for major depressive disorder (MDD) due to the biological complexity of the disorder. The existence of blood-based biomarkers with high specificity would be convenient for the clinical diagnosis of MDD.

METHODS

A comprehensive plasma proteomic analysis was conducted in a highly homogeneous cohort [7 drug-naïve MDD patients and 7 healthy controls (HCs)], with bioinformatics analysis combined with machine learning used to screen candidate proteins. Verification of reproducibility and specificity was conducted in independent cohorts [60 HCs and 74 MDD, 42 schizophrenia (SZ) and 39 bipolar I disorder (BD-I) drug-naïve patients]. Furthermore, verification of consistency was accomplished by proteomic analysis of postmortem brain tissue from 16 MDD patients and 16 HCs.

RESULTS

Levels of C-reactive protein (CRP), antithrombin III (ATIII), inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) and vitamin D-binding protein (VDB) were significantly higher in MDD patients, both in the discovery cohort and independent replication cohort. In comparison with SZ or BD-I patients, two proteins (VDB and ITIH4) were significantly elevated only in MDD patients. In addition, increased VDB and ITIH4 were observed consistently in both plasma and postmortem dorsolateral prefrontal cortex tissues of MDD patients. Furthermore, a panel consisting of all four plasma proteins was able to distinguish MDD patients from HCs or SZ or BD-I patients with the highest accuracy.

CONCLUSION

Plasma ITIH4 and VDB may be potential plasma biomarkers of MDD with high specificity. The four-protein panel is more suitable as a potential clinical diagnostic marker for MDD.

An Exploratory Pilot Study with Plasma Protein Signatures Associated with Response of Patients with Depression to Antidepressant Treatment for 10 Weeks

Major depressive disorder (MDD) is a leading cause of global disability with a chronic and recurrent course. Recognition of biological markers that could predict and monitor response to drug treatment could personalize clinical decision-making, minimize unnecessary drug exposure, and achieve better outcomes. Four longitudinal plasma samples were collected from each of ten patients with MDD treated with antidepressants for 10 weeks. Plasma proteins were analyzed qualitatively and quantitatively with a nanoflow LC−MS/MS technique. Of 1153 proteins identified in the 40 longitudinal plasma samples, 37 proteins were significantly associated with response/time and clustered into six according to time and response by the linear mixed model. Among them, three early-drug response markers (PHOX2B, SH3BGRL3, and YWHAE) detectable within one week were verified by liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS) in the well-controlled 24 patients. In addition, 11 proteins correlated significantly with two or more psychiatric measurement indices. This pilot study might be useful in finding protein marker candidates that can monitor response to antidepressant treatment during follow-up visits within 10 weeks after the baseline visit.

iTRAQ‑based quantitative proteomics analysis of the potential application of secretoneurin gene therapy for cardiac hypertrophy induced by DL‑isoproterenol hydrochloride in mice

A previous study by our group demonstrated a protective role of the neuropeptide secretoneurin (SN) in DL‑isoproterenol hydrochloride (ISO)‑induced cardiac hypertrophy in mice. To further characterize the molecular mechanism of SN treatment, an isobaric tags for relative and absolute quantification (iTRAQ)‑based quantitative proteomic analysis was applied to identify putative target proteins and molecular pathways. An SN expression vector was injected into the myocardial tissues of mice, and the animals were then subcutaneously injected with ISO (5 mg/kg/day) for 7 days to induce cardiac hypertrophy. The results of echocardiography and hemodynamic measurements indicated that the function of the heart impaired by ISO treatment was significantly ameliorated via SN gene injection. The investigation of heart proteomics was performed by iTRAQ‑based liquid chromatography‑tandem mass spectrometry analysis. A total of 2,044 quantified proteins and 15 differentially expressed proteins were associated with SN overexpression in mice with cardiac hypertrophy. Functional enrichment analysis demonstrated that these effects were possibly associated with metabolic processes. A protein‑protein interaction network analysis was constructed and the data indicated that apolipoprotein C‑III (Apoc3) was associated with the positive effect of SN on the induction of cardiac hypertrophy in mice. The present study proposed a potential mechanism of SN action on Apoc3 upregulation that may contribute to the amelioration of cardiac hypertrophy. These findings can aid the clinical application of SN in patients with cardiac hypertrophy.

Proteomic serum profile in menstrual-related and post menopause migraine

The aim of this pilot study was to analyze the serum proteomic profile of women suffering from menstrual-related migraine (MM group, n = 15) and migraine in post-menopause (PM group, n = 15) in comparison with non-headache control females (C group, n = 15). Serum samples were subjected to two-dimensional gel electrophoresis (2-DE) followed by mass spectrometry (MS) analysis for protein identification. Based on 2D-gel maps and PDQuest 2-D software, 13 differentially expressed spots, corresponding to 12 unique proteins identified by Liquid Chromatography-Electrospray Ionization-Quadrupole-Time of Flight/tandem mass spectrometry (LC-ESI-QToF-MS/MS), were detected in the MM and PM groups vs C group. Five inflammatory and regulatory of vascular integrity proteins (prothrombin, serum amyloid P-component, Ig kappa chain C region, apolipoprotein A-I, serum amyloid A-4 protein) were found deregulated in both MM and PM groups compared to C group; MM group showed the upregulation of other inflammatory protein fragments (inter-alpha-trypsin inhibitor heavy chain H4 and complement C4-A) compared to C group; PM group, in comparison with C group, displayed a noteworthy upregulation of transthyretin and other deregulated proteins (tetranectin, alpha-1-antitrypsin, haptoglobin, apolipoprotein A-IV) playing a role in anti-inflammatory and reparative processes. In conclusion, proteomic analysis was able to reveal differences in protein expression between migraine sufferers and non-headache women; as in other neurological diseases characterized by neuroinflammation, the serum proteome of migraine women presents an abundance of proteins indicative of cellular damage, oxidative stress and inflammation. This relevant inflammatory status, if confirmed in larger series, could represent a target for menstrual-related migraine treatment.

Age-Dependent Changes in the Plasma Proteome of Healthy Adults

OBJECTIVE

Human blood plasma is a complex that communicates with most parts of the body and reflects the changes in the state of an organism. Identifying age-related biomarkers can help predict and monitor age-related physiological decline and diseases and identify new treatments for diseases.

METHODS AND PARTICIPANTS

In this study, TMT-LC-MS/MS was utilized to screen differentially expressed plasma proteins in 118 healthy adults of different ages. Participants were divided into three groups: 21-30 years of age (Young), 41-50 years of age (Middle) and ≥60 years of age (Old).

RESULTS

The number of differentially expressed proteins in the comparisons of Young vs Middle, Middle vs Old and Young vs Old were 82, 22 and 99, respectively. These proteins were involved in numerous physiological processes, such as "negative regulation of smooth muscle cell proliferation" and "blood coagulation". Moreover, when Young was compared with Middle or Old, "complement and coagulation cascades" was the top enriched pathway by KEGG pathway enrichment analysis. Functional phenotyping of the proteome demonstrated that the plasma proteomic profiles of young adults were strikingly dissimilar to those of the middle-aged or older adults.

CONCLUSIONS

The results of this study mapped the variation in the expression of plasma proteins and provided information about possible biomarkers/treatments for different age-related functional disorders.

iTRAQ-based quantitative proteomic analysis provides insight for molecular mechanism of neuroticism

Background

Neuroticism is a core personality trait and a major risk factor for several mental and physical diseases, particularly in females, who score higher on neuroticism than men, on average. However, a better understanding of the expression profiles of proteins in the circulating blood of different neurotic female populations may help elucidate the intrinsic mechanism of neurotic personality and aid prevention strategies on mental and physical diseases associated with neuroticism.

Methods

In our study, female subjects were screened for inclusion by the Eysenck Personality Questionnaire (EPQ), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI) scales and routine physical examination. Subjects who passed the examination and volunteered to participate were grouped by neuroticism using EPQ scores (0 and 1 = low neuroticism group; > 5 = high neuroticism group). Proteins in serum samples of the two neuroticism groups were identified using isobaric tags for relative and absolute quantification (iTRAQ) technology.

Results

A total of 410 proteins exhibited significant differences between high and low neuroticism, 236 proteins were significantly upregulated and 174 proteins were significantly downregulated. Combine the results of GO and KEGG enrichment analysis of differences proteins between high and low neuroticism with the PPI network, it could be observed that the Alpha-synuclein (SNCA), ATP7A protein (ATP7A), Guanine nucleotide-binding protein G(I)/G(S)/G(O) subunit gamma-2 (GNG2), cyclin-dependent kinase 6 (CDK6), myeloperoxidase (MPO), azurocidin (AZU1), Histone H2B type 1-H (HIST1H2BH), Integrin alpha-M (ITGAM) and Matrix metalloproteinase-9 (MMP9) might participate in the intrinsic mechanism of neuroticism by regulating response to catecholamine stimulus, catecholamine metabolic process, limbic system development and transcriptional misregulation in cancer pathway.

Conclusions

Our study revealed the characteristics of the neurotic personality proteome, which might be intrinsic mechanism of the neurotic population.

Proteomics of the mediodorsal thalamic nucleus of rats with stress-induced gastric ulcer

BACKGROUND

Stress-induced gastric ulcer (SGU) is one of the most common visceral complications after trauma. Restraint water-immersion stress (RWIS) can cause serious gastrointestinal dysfunction and has been widely used to study the pathogenesis of SGU to identify medications that can cure the disease. The mediodorsal thalamic nucleus (MD) is the centre integrating visceral and physical activity and contributes to SGU induced by RWIS. Hence, the role of the MD during RWIS needs to be studied.

AIM

To screen for differentially expressed proteins in the MD of the RWIS rats to further elucidate molecular mechanisms of SGU.

METHODS

Male Wistar rats were selected randomly and divided into two groups, namely, a control group and an RWIS group. Gastric mucosal lesions of the sacrificed rats were measured using the erosion index and the proteomic profiles of the MD were generated through isobaric tags for relative and absolute quantitation (iTRAQ) coupled with two-dimensional liquid chromatography and tandem mass spectrometry. Additionally, iTRAQ results were verified by Western blot analysis.

RESULTS

A total of 2853 proteins were identified, and these included 65 dysregulated (31 upregulated and 34 downregulated) proteins (fold change ratio ≥ 1.2). Gene Ontology (GO) analysis showed that most of the upregulated proteins are primarily related to cell division, whereas most of the downregulated proteins are related to neuron morphogenesis and neurotransmitter regulation. Ingenuity Pathway Analysis revealed that the dysregulated proteins are mainly involved in the neurological disease signalling pathways. Furthermore, our results indicated that glycogen synthase kinase-3 beta might be related to the central mechanism through which RWIS gives rise to SGU.

CONCLUSION

Quantitative proteomic analysis elucidated the molecular targets associated with the production of SGU and provides insights into the role of the MD. The underlying molecular mechanisms need to be further dissected.

Brain IGFBP-5 modifies the relation of depressive symptoms to decline in cognition in older persons

BACKGROUND

Brain proteins, including Insulin-like Growth Factor Binding Protein 5 (IGFBP-5), have been associated with cognitive dysfunction in aging. Mechanisms linking depression with cognition are poorly understood. We hypothesize that the association of depressive symptoms with cognition is mediated or modified by brain proteins.

METHODS

IGFBP-5, HSPB2, AK4, ITPK1 and PLXNB1 were measured in dorsolateral prefrontal cortex in 1057 deceased participants, who underwent annual assessments of depressive symptoms and cognition for a mean of 8.9 years. The average number of depressive symptoms per year before a dementia diagnosis was calculated for each person.

RESULTS

A one standard deviation above the mean IGFBP-5 was associated with a 14% higher odds of having more depressive symptoms (p < 0.031). Higher IGFBP-5 was associated with faster decline in global cognition (p < 0.001) and five cognitive domains (p < 0.008), controlling for depressive symptoms. IGFBP-5 moderated the association of depressive symptoms with decline in global cognition (p = 0.045). IGFBP-5 mediated ten percent or less of the total effect of depressive symptoms on decline in global cognition and the cognitive domains (p > 0.070).

LIMITATIONS

Participants were volunteers and self-selection bias limits the generalizability of our findings. In addition, we used self-reported data on depressive symptoms. However, we also used data on depression medications as sensitivity analyses to confirm findings.

CONCLUSIONS

In old age, brain IGFBP-5 is associated with depressive symptoms and cognition. The association of depressive symptoms with cognitive decline is conditional on IGFBP-5.

An analysis of plasma reveals proteins in the acute phase response pathway to be candidate diagnostic biomarkers for depression

Globally, depression is one of the most serious debilitating psychiatric mental disorders. In this study, we validated the expression levels of fibrinogen alpha (FGA), fibrinogen beta (FGB), fibrinogen gamma (FGG), Complement factor B (CFB) and serpin family D member 1(SERPIND1) in the acute phase response signaling pathway in plasma samples using enzyme-linked immunosorbent assay (ELISA).Then illuminate the roles of FGA, FGB, FGG, CFB, SERPIND1 in depression using microarray data. Gene expression dataset GSE98793 was downloaded from the Gene Expression Omnibus database. There were 128 whole blood samples included 64 patients with major depressed patients and 64 healthy controls. Differentially expressed genes (DEGs) were identified, and then protein-protein interaction (PPI) network was constructed to screen crucial genes associated with FGA, FGB, FGG, CFB and SERPIND1. Moreover, gene ontology (GO) biological processes analyses was performed. The ELISA data showed that the expression levels of FGA, FGB, FGG, CFB and SERPIND1 were up-regulated in depressed patients. The enriched GO terms were predominantly associated with the biological processes including more genes were inflammation related. The PPI network was found these five genes interacted with 11 genes. FGA, FGB, FGG, CFB and SERPIND1 may be important in the pathogenesis of depression.

Could a blood test for PTSD and depression be on the horizon?

INTRODUCTION

Depression and posttraumatic stress disorder (PTSD) are two complex and debilitating psychiatric disorders that result in poor life and destructive behaviors against self and others. Currently, diagnosis is based on subjective rather than objective determinations leading to misdiagnose and ineffective treatments. Advances in novel neurobiological methods have allowed assessment of promising biomarkers to diagnose depression and PTSD, which offers a new means of appropriately treating patients. Areas covered: Biomarkers discovery in blood represents a fundamental tool to predict, diagnose, and monitor treatment efficacy in depression and PTSD. The potential role of altered HPA axis, epigenetics, NPY, BDNF, neurosteroid biosynthesis, the endocannabinoid system, and their function as biomarkers for mood disorders is discussed. Insofar, we propose the identification of a biomarker axis to univocally identify and discriminate disorders with large comorbidity and symptoms overlap, so as to provide a base of support for development of targeted treatments. We also weigh in on the feasibility of a future blood test for early diagnosis. Expert commentary: Potential biomarkers have already been assessed in patients' blood and need to be further validated through multisite large clinical trial stratification. Another challenge is to assess the relation among several interdependent biomarkers to form an axis that identifies a specific disorder and secures the best-individualized treatment. The future of blood-based tests for PTSD and depression is not only on the horizon but, possibly, already around the corner.

Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.

Identification of plasma biomarkers for distinguishing bipolar depression from major depressive disorder by iTRAQ-coupled LC-MS/MS and bioinformatics analysis

It is important to differentiate between bipolar disorder (BD) and major depressive disorder (MDD) in the first depressive episode because of the potential treatment implications. Previous studies have mainly focused on the different clinical features or pathological biomarkers to distinguish these two diseases; however, a better understanding of the proteomics profiling of BD may help aid future therapeutic strategies. Here, we applied isobaric tags for relative and absolute quantification (iTRAQ) technology combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins between MDD and bipolar depression (BP). In total, 30 MDD, 30 BP and 30 healthy subjects were included. Proteins from depleted plasma samples were digested into peptides, individually labeled with iTRAQ reagents, combined and subjected to LC-MS/MS and further bioinformatics analyses. Our results showed that 9 proteins were significantly altered between MDD and BP. Briefly, B2RAN2, B4E1B2, APOA1, ENG, SBSN and QSOX2 were up-regulated, whereas ORM1, MRC2 and SLPI were down-regulated. Most identified proteins were related to the immune system. The bioinformatics analysis showed that B2RAN2 (highly similar to vanin-1) was involved in the significantly enriched KEGG pathways "pantothenate and CoA biosynthesis" (P=0.009). B2RAN2 and ENG may play important roles in depression. They may serve as candidate biomarkers for distinguishing MDD and BP. Further validation and investigation are required to illuminate the roles of B2RAN2 and ENG in MDD and BP. The current study provided a potential and novel biomarker panel that may, in turn, aid the diagnosis of BD.

The acute-phase mediator serum amyloid A is associated with symptoms of depression and fatigue

OBJECTIVE

Establish whether inflammatory biomarkers-serum amyloid A (SAA), C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α)-are related to key symptoms of depression, including anxiety and fatigue, in a cross-sectional, out-patient setting to identify biomarkers that reflect psychiatric symptomatology in a naturalistic, real-life population.

METHODS

We measured SAA, CRP, IL-6, and TNF-α in plasma samples from 89 adult psychiatric out-patients by multiplex, high-sensitivity electrochemiluminescent assays. Psychiatric symptoms were evaluated using the Hamilton Depression Rating Scale (HAMD-17), the Patient Health Questionnaire (PHQ-9), and the Center for Epidemiological Studies Depression Scale (CES-D).

RESULTS

Plasma SAA was most robustly associated with depressive symptoms across diagnostic boundaries in this cohort of out-patients. Elevated SAA was significantly associated with higher total scores on the HAMD-17 scale and correlated with multiple scale items that rated symptoms of fatigue and depressed mood, but not with anxiety-related items.

CONCLUSIONS

SAA might constitute a cross-diagnostic marker indicative of depressed mood and fatigue in a naturalistic patient setting. Because SAA activates Toll-like receptors 2 and 4, present on macrophages and glial cells, its association with depression severity could also implicate this inflammatory mediator in the pathogenesis of mood disorders.

Serum Proteome Alterations in Patients with Cognitive Impairment after Traumatic Brain Injury Revealed by iTRAQ-Based Quantitative Proteomics

Background. Cognitive impairment is the leading cause of traumatic brain injury- (TBI-) related disability; however, the underlying pathogenesis of this dysfunction is not completely understood. Methods. Using an isobaric tagging for relative and absolute quantitation- (iTRAQ-) based quantitative proteomic approach, serum samples from healthy control subjects, TBI patients with cognitive impairment, and TBI patients without cognitive impairment were analysed to identify differentially expressed proteins (DEPs) related to post-TBI cognitive impairment. In addition, DEPs were further analysed using bioinformatic platforms and validated using enzyme-linked immunosorbent assays (ELISA). Results. A total of 56 DEPs were identified that were specifically related to TBI-induced cognitive impairment. Bioinformatic analysis revealed that a wide variety of cellular and metabolic processes and some signaling pathways were involved in the pathophysiology of cognitive deficits following TBI. Five randomly selected DEPs were validated using ELISA in an additional 105 cases, and the results also supported the experimental findings. Conclusions. Despite limitations, our findings will facilitate further studies of the pathological mechanisms underlying TBI-induced cognitive impairment and provide new methods for the research and development of neuroprotective agents. However, further investigation on a large cohort is warranted.

iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a gradual lung disease with a survival of less than 5 years post-diagnosis for most patients. Poor molecular description of IPF has led to unsatisfactory interpretation of the pathogenesis of this disease, resulting in the lack of successful treatments. The objective of this study was to discover novel noninvasive biomarkers for the diagnosis of IPF. We employed a coupled isobaric tag for relative and absolute quantitation (iTRAQ)-liquid chromatography–tandem mass spectrometry (LC–MS/MS) approach to examine protein expression in patients with IPF. A total of 97 differentially expressed proteins (38 upregulated proteins and 59 downregulated proteins) were identified in the serum of IPF patients. Using String software, a regulatory network containing 87 nodes and 244 edges was built, and the functional enrichment showed that differentially expressed proteins were predominantly involved in protein activation cascade, regulation of response to wounding and extracellular components. A set of three most significantly upregulated proteins (HBB, CRP and SERPINA1) and four most significantly downregulated proteins (APOA2, AHSG, KNG1 and AMBP) were selected for validation in an independent cohort of IPF and other lung diseases using ELISA test. The results confirmed the iTRAQ profiling results and AHSG, AMBP, CRP and KNG1 were found as specific IPF biomarkers. ROC analysis indicated the diagnosis potential of the validated biomarkers. The findings of this study will contribute in understanding the pathogenesis of IPF and facilitate the development of therapeutic targets.