Uncovering the health implications of abandoned mines through protein profiling of local residents.

Residents in areas with abandoned mines risk significant exposure to abundant heavy metals in the environment. However, current clinical indicators cannot fully reflect the health changes associated with abandoned mine exposure. The aim of this study was to identify biological changes in the residents of abandoned mine areas via proteomic analysis of their blood. Blood samples were collected from abandoned mine and control areas, and mass spectrometry was used for protein profiling. A total of 138 unique or common proteins that were differentially expressed in low-exposure abandoned mine area (LoAMA) or high-exposure abandoned mine area (HiAMA) compared to non-exposure control area (NEA) were analyzed, and identified 4 clusters based on functional similarity. Among the 10 proteins that showed specific change in LoAMA, 4 proteins(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) were cluded in cluster 1(plasma lipoprotein remodeling), and linked to proteins that showed specific change in protein expression in HiAMA. Therefore, it is suggested that 4 proteins are changed at low exposure to an abandoned mine (or initial exposure), and then at high exposure, changes in various proteins involved in linked plasma lipoprotein remodeling are induced, which might triggered by the 4 proteins. Interestingly, in addition to plasma lipoprotein remodeling, proteins involved in other functional networks were changed in the high exposure group. These were all directly or indirectly linked to the 4 biomarkers(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) that changed during low exposure. This suggests their potential utility in identifying areas impacted by abandoned mines. Especially, proteins involved in lipid metabolism and renal function-related diseases in individuals exposed to heavy metals in abandoned mine areas were correlated. Chronic kidney disease is predominantly instigated by cardiovascular disease and is commonly accompanied by dyslipidemia.

Cadmium-associated protein changes in residents of contaminated areas: Abandoned mine and smelter.

Cadmium (Cd), a serious environmental contaminant, is associated with adverse health effects. However, the specific changes that the human body experiences in response to exposure to varying concentrations of cadmium remain unknown. The high levels of heavy metal contamination, especially Cd, in abandoned mines and smelter sites make them ideal locations to investigate the physiological manifestations of Cd exposure. This study found that individuals inhabiting abandoned mine and smelter areas had higher concentrations of Cd in their urine and blood compared to those living outside these areas (i.e., the controls). Furthermore, proteomic profiling of blood samples from all study groups was performed to identify proteomic biomarkers associated with chronic and severe Cd exposure. This analysis showed statistically significant correlations between urine Cd levels and sixteen proteins. Among these proteins, seven exhibited significantly altered expressions in samples from contaminated areas compared with those from control areas. Therefore, these proteins were selected as potential markers representing Cd-related protein alterations. Multiple reaction monitoring analysis was performed to validate the expression patterns of the proteins and four proteins were found to exhibit consistent trends. The findings show that Cd exposure significantly affects the expression of certain proteins in the human body. Understanding the underlying mechanisms and diseases associated with Cd-induced protein alterations can aid in the development of effective preventive and therapeutic strategies for individuals exposed to Cd-linked pollution.

Discovery and validation of protein biomarkers for monitoring the effectiveness of drug treatment for major depressive disorder.

Major depressive disorder (MDD) has a high prevalence worldwide. Although the economic burden of depression increases annually, the proportion of patients with MDD receiving treatment did not increase between 2010 and 2018, suggesting an unmet treatment need. The burden of long-term treatment for depression is borne by patients. In this context, biomarkers associated with drug-treatment responses can be used as reference indicators to reduce unnecessary treatment and costs. Changes in biomolecules in response to drug treatment for depression and drug-treatment response markers have been studied extensively. The Hamilton Depression Rating Scale (HAM-D) is mainly used as an indicator of response and remission; however, it is difficult to determine whether the medication contributes to recovery when evaluating the effect of drug treatment for depression based on this assessment. Therefore, it is necessary to monitor the effect of medication compared to normal health conditions. Here, serum protein levels were compared using liquid chromatography-tandem mass spectrometry among a group of patients with depression who did not receive medication, a group of patients receiving medication, and a control group. Eight selected biomarkers, including Apolipoproteins A-I, Complement factor H, Complement C5, Complement C1q subcomponent subunit B, Alpha-2-HS-glycoprotein, Complement C1q subcomponent subunit C, Vitamin D-binding protein and Corticosteroid-binding globulin were distinguished between disease states, and protein levels in the drug-treated group were similar to those in the control group. These markers can be used to monitor the effectiveness of drug treatment.

Serum Protein Profiling Reveals a Decrease in Apolipoprotein A-IV During a Clinical Depressive Mood State.

Purpose: Depressive mood is a major psychiatric symptom that causes serious disturbances in daily life. Unlike physical symptoms, psychiatric symptoms are more difficult to evaluate objectively. Therefore, we aimed to discover biomarkers that reflect changes in serum protein metabolism during a clinical depressive mood. Methods: Serum protein profiling was conducted in participants who were not experiencing a current depressive episode (healthy individuals and patients in remission). Serum proteins were identified and quantified using liquid chromatography-tandem mass spectrometry. Differentially expressed proteins with a p-value <0.05 were selected, and candidate biomarkers were verified using multiple reaction monitoring analysis for absolute quantification. Results: Apolipoprotein A-IV levels were lower in the group with a current episode of depression than in the remission and healthy control groups. Further, fibronectin levels were also lower in the group with a current episode of depression than in the healthy control group but not in the remission group. Conclusion: We found that apolipoprotein A-IV-mediated inflammation is involved in clinical depressive moods, possibly by inducing neurological changes in the brain. Therefore, apolipoprotein A-IV and fibronectin levels may be explored as potentially novel biomarkers for detecting a current episode of depression.

Potential Biomarkers to Distinguish Type 1 Myocardial Infarction in Troponin-Elevated Diseases.

Classifying myocardial infarction by subtype is crucial for appropriate patient management. Although troponin is currently the most commonly used biomarker, it is not a specific marker for myocardial infarction and cannot distinguish subtypes. Furthermore, previous studies have confirmed that proteins known as myocardial infarction markers could function to distinguish the type of myocardial infarction. Therefore, we identify a marker that can distinguish type 1 myocardial infarction from other diseases with elevated troponin. We used mass spectrometry to compare type 1 myocardial infarction with other conditions characterized by troponin elevation and identified new candidate markers for disease classification. We then verified these markers, along with those already known to be associated with cardiovascular disease and plaque rupture. We identified α-1 acid glycoprotein 2, corticosteroid-binding globulin, and serotransferrin as potential distinguishing markers. The presence of these markers and other parameters, such as chest pain, electrocardiogram, and troponin levels from the complementary diagnostic processes, could provide valuable information to specifically diagnose type 1 myocardial infarction.

Validation of the Metabolite Ergothioneine as a Forensic Marker in Bloodstains.

Ergothioneine, which is a naturally occurring metabolite, generally accumulates in tissues and cells subjected to oxidative stress, owing to its structural stability at physiological pH; therefore, it has been attracting attention in various biomedical fields. Ergothioneine has also been suggested as a potential forensic marker, but its applicability has not yet been quantitatively validated. In this study, quantitative analysis of ergothioneine in bloodstains was conducted to estimate the age of bloodstains and that of bloodstain donors. Blood from youth and elderly participants was used to generate bloodstains. After extracting metabolites from the bloodstains under prevalent age conditions, ergothioneine levels were quantified by mass spectrometry via multiple reaction monitoring. The concentration of ergothioneine in day 0 bloodstains (fresh blood), was significantly higher in the elderly group than in the youth group, but it did not differ by sex. Statistically significant differences were observed between the samples from the two age groups on days 0, 5 and 7, and on days 2 and 3 compared with day 0. The findings suggest that ergothioneine can be used to estimate the age of bloodstains and of the donor; it could be useful as a potential marker in reconstructing crime scenes.

Discovery and validation of acetyl-L-carnitine in serum for diagnosis of major depressive disorder and remission status through metabolomic approach.

Major depressive disorder (MDD) is one of the most common psychiatric disorders that accompany psychophysiological and mood changes. However, the pathophysiology-based disease mechanism of MDD is not yet fully understood, and diagnosis is also conducted through interviews with clinicians and patients. Diagnosis and treatment of MDD are limited due to the absence of biomarkers underlying the pathophysiological mechanisms of MDD. Although various attempts have been made to discover metabolite biomarkers for the diagnosis and treatment response of MDD, problems with sample size and consistency of results have limited clinical application. In addition, it was reported that future biomarker studies must consider exposure to antidepressants, which is the main cause of heterogeneity in depression subgroups. Therefore, the purpose of this study is to discover and validate biomarkers for the diagnosis of depression in consideration of exposure to drug treatment including antidepressants that contribute to the heterogeneity of the MDD subgroup. In the biomarker discovery and validation set, the disease group consisted of a mixture of patients exposed and unexposed to drug treatment including antidepressants for the treatment of MDD. The serum metabolites that differed between the MDD patients and the control group were profiled using mass spectrometry. The validation set including the remission group was used to verify the effectiveness as a biomarker for the diagnosis of depression and determination of remission status. The presence of different metabolites between the two groups was confirmed through serum metabolite profiling between the MDD patient group and the control group. Finally, Acetylcarnitine was selected as a biomarker. In validation, acetylcarnitine was significantly decreased in MDD and was distinguished from remission status. This study confirmed that the discovered acetylcarnitine has potential as a biomarker for diagnosing depression and determining remission status, regardless of exposure to drug treatment including antidepressants.

Serum proteomic analysis of major depressive disorder patients and their remission status: Novel biomarker set of zinc-alpha-2-glycoprotein and keratin type II cytoskeletal 1.

Major depressive disorder (MDD) is the most common mood disorder, and causes various mental, physical and cognitive symptoms. Clinicians diagnose MDD using multiple interviews and overall impression during the interviews, which makes MDD diagnosis highly subjective. To overcome this, we investigated novel protein biomarker for MDD. Serum from each subject were analyzed using nano liquid chromatography-triple time-of-flight mass spectrometry. We identified two proteins, zinc-alpha-2-glycoprotein (ZA2G) and keratin type II cytoskeletal 1 (K2C1), as final biomarkers. These biomarkers were downregulated during depression (p < 0.05, AUC of ROC >0.7). ZA2G is related to tryptophan metabolism, which is a main serotonin synthesis pathway. K2C1 is involved in the kinin-kallikrein system, which produces bradykinin, an anti-inflammatory mediator in the brain. Our results suggest that the two protein candidates are related to inflammation and that MDD is highly associated with inflammation. Finally, since all subjects in the two groups were taking antidepressants, our results suggest that the identified biomarkers could determine the presence or absence of illness and could be used to monitor therapeutic effects.

Serum biomarker discovery related to pathogenesis in acute coronary syndrome by proteomic approach.

Acute coronary syndrome (ACS) results from inadequate supply of blood flow from the coronary arteries to the heart or ischemia. ACS has an extremely high morbidity and mortality. The levels of biomarkers currently used for detection of ACS also increase in response to myocardial necrosis and other diseases and are not elevated immediately after symptoms appear, thus limiting their diagnostic capacity. Therefore, we aimed to discover new ACS diagnostic biomarkers with high sensitivity and specificity that are specifically related to ACS pathogenesis. Sera from 50 patients with ACS and healthy controls (discovery cohort) each were analyzed using mass spectrometry (MS) to identify differentially expressed proteins, and protein candidates were evaluated as ACS biomarkers in 120 people in each group (validation cohort). α-1-acid glycoprotein 1 (AGP1), complement C5 (C5), leucine-rich α-2-glycoprotein (LRG), and vitronectin (VN) were identified as biomarkers whose levels increase and gelsolin (GSN) as a biomarker whose levels decrease in patients with ACS. We concluded that these biomarkers are associated with the pathogenesis of ACS and can predict the onset of ACS prior to the appearance of necrotic biomarkers.

Discovery of Screening Biomarkers for Major Depressive Disorder in Remission by Proteomic Approach.

Major depressive disorder (MDD) is a common disorder involving depressive mood and decreased motivation. Due to its high heterogeneity, novel biomarkers are required to diagnose MDD. In this study, a proteomic method was used to identify a new MDD biomarker. Using sequential window acquisition of all theoretical mass spectra acquisitions and multiple reaction monitoring analysis via mass spectrometry, relative and absolute quantification of proteins in the sera was performed. The results of the relative quantitation by sequential window acquisition for all theoretical mass spectra data showed that seven proteins were significantly differently expressed between MDD patients and other patients with remission status. However, absolute quantification by multiple reaction monitoring analysis identified prothrombin as the only significantly upregulated protein in the depressive state compared to remission (p < 0.05) and was, thus, subsequently selected as an MDD biomarker. The area under the curve for prothrombin was 0.66. Additionally, increased prothrombin/thrombin induced hyper-activation of platelets via activating protease-activated receptors, a feature associated with MDD; specifically, activated platelets secrete various molecules related to MDD, including brain-derived neurotropic factors and serotonin. Therefore, prothrombin is a potential screening, prognostic, and diagnostic marker for MDD.

Biomarker Discovery of Acute Coronary Syndrome Using Proteomic Approach.

Acute coronary syndrome (ACS) is a condition in which the coronary artery supplying blood to the heart is infarcted via formation of a plaque and thrombus, resulting in abnormal blood supply and high mortality and morbidity. Therefore, the prompt and efficient diagnosis of ACS and the need for new ACS diagnostic biomarkers are important. In this study, we aimed to identify new ACS diagnostic biomarkers with high sensitivity and specificity using a proteomic approach. A discovery set with samples from 20 patients with ACS and 20 healthy controls was analyzed using mass spectrometry. Among the proteins identified, those showing a significant difference between each group were selected. Functional analysis of these proteins was conducted to confirm their association with functions in the diseased state. To determine ACS diagnostic biomarkers, standard peptides of the selected protein candidates from the discovery set were quantified, and these protein candidates were validated in a validation set consisting of the sera of 50 patients with ACS and 50 healthy controls. We showed that hemopexin, leucine-rich α-2-glycoprotein, and vitronectin levels were upregulated, whereas fibronectin level was downregulated, in patients with ACS. Thus, the use of these biomarkers may increase the accuracy of ACS diagnosis.

Serum biomarker panel for the diagnosis of rheumatoid arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune disease of inflammatory joint damage, wherein C-reactive protein and autoantibodies including rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP) are rapidly elevated. These serological factors are diagnostic markers of RA; however, their sensitivity and specificity for prediction warrant improvement for an early and accurate diagnosis. METHODS: We aimed to identify alternative biomarkers by serum protein profiling using LC-MS/MS. We performed statistical and functional analysis of differentially expressed proteins to identify biomarker candidates complementing conventional serological tests. RESULTS: Seven biomarker candidates were verified through multiple reaction monitoring-based quantitative analysis, of which angiotensinogen (AGT), serum amyloid A-4 protein (SAA4), vitamin D-binding protein (VDBP), and retinol-binding protein-4 (RBP4) had an area under the curve over 0.8, thus distinguishing RA patients, including seronegative (RF- and anti-CCP-negative) RA patients, from healthy controls. CONCLUSIONS: Therefore, among seronegative RA patients, a four-biomarker panel (AGT, SAA4, VDBP, and RBP4) can prevent false negatives and help diagnose RA accurately.

A discovery of screening markers for rheumatoid arthritis by liquid chromatography mass spectrometry: A metabolomic approach.

AIM: This study aimed to discover serum metabolite biomarkers for potential use in screening for rheumatoid arthritis (RA). METHODS: The sera from 43 healthy controls (HCs) and 49 RA patients were globally analyzed using high-performance liquid chromatography- tandem mass spectrometry. Molecular features (MFs) from samples were analyzed using volcano plots, partial least squares discriminant analysis, and variable importance in projection scores to select candidates. The spectra of candidate MFs were matched with the METLIN database. We confirmed the association between candidates and RA and analyzed the receiver-operating characteristic (ROC) curves. RESULTS: We selected a total of 57 candidate MFs that had a fold change ≥1.5, P value ≤.05, and over 80% of frequency. Among them, 18 MFs were identified as metabolites with the METLIN database. Six metabolites (dehydroepiandrosterone sulfate, androsterone sulfate, γ-linolenic acid, 9[E],11[E]-conjugated linoleic acid, docosahexaenoic acid, and docosapentaenoic acid [22n-3]) out of the 18 were associated with mechanisms of RA and were selected as final candidates. ROC curve analysis revealed their area under the curve (AUC) values were all above 0.75 and the combined AUC of the six candidates was 0.89. CONCLUSION: Using six candidates as a marker set showed potential in distinguishing RA patients from HCs, based on high AUC values. Therefore, we propose that a marker set of these six candidates has potential clinical application in RA screening.

Proteomics Reveals Plasma Biomarkers for Ischemic Stroke Related to the Coagulation Cascade.

Stroke has a high incidence rate and often leads to permanent disability, particularly if it is not treated promptly. However, no blood biomarkers for early diagnosis are available to date. Therefore, we sought to detect stroke-specific blood biomarkers by identifying proteins associated with the underlying coagulation mechanism, which accounts for more than 80% of all stroke cases. Protein profiling was performed using blood samples from 16 healthy controls and 18 patients who suffered a stroke as the discovery set. We identified upregulated proteins (> 1.5-fold change and p value < 0.05) in patients who suffered a stroke relative to the corresponding levels in healthy controls by nano-liquid chromatography-tandem mass spectrometry using data-independent acquisition based on sequential window acquisition of all theoretical mass spectra, which was developed to improve the consistency and accuracy of candidate proteins. Pathway analysis confirmed that the upregulated proteins were mainly involved in blood coagulation. Among these, we selected prothrombin, plasminogen, fibrinogen alpha-chain, and histidine-rich glycoprotein as candidate biomarkers. Multiple reaction monitoring analysis was performed on a validation set of 61 serum samples (31 healthy controls and 30 stroke patients) to assess the diagnostic value of the candidate biomarkers. All four proteins showed higher expression levels in patients with stroke than in healthy controls. The areas under the receiver operating characteristic curve were greater than 0.9, confirming their clinical value. These four blood coagulation proteins may help in diagnosing stroke more accurately and quickly.

Proteomics-Based Identification of Diagnostic Biomarkers Related to Risk Factors and Pathogenesis of Ischemic Stroke.

Ischemic stroke is caused by blood clot formation and consequent vessel blockage. Proteomic approaches provide a cost-effective alternative to current diagnostic methods, including computerized tomography (CT) scans and magnetic resonance imaging (MRI). To identify diagnostic biomarkers associated with ischemic stroke risk factors, we performed individual proteomic analysis of serum taken from 20 healthy controls and 20 ischemic stroke patients. We then performed SWATH analysis, a data-independent method, to assess quantitative changes in protein expression between the two experimental conditions. Our analysis identified several candidate protein biomarkers, 11 of which were validated by multiple reaction monitoring (MRM) analysis as novel diagnostic biomarkers associated with ischemic stroke risk factors. Our study identifies new biomarkers associated with the risk factors and pathogenesis of ischemic stroke which, to the best of our knowledge, were previously unknown. These markers may be effective in not only the diagnosis but also the prevention and management of ischemic stroke.

Proteomics Approach for the Discovery of Rheumatoid Arthritis Biomarkers Using Mass Spectrometry.

Rheumatoid arthritis is an autoimmune disease that causes serious functional loss in patients. Early and accurate diagnosis of rheumatoid arthritis may attenuate its severity. Despite a diagnosis guideline in the 2010 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) classification criteria for rheumatoid arthritis, the practical difficulties in its diagnosis highlight the need of developing new methods for diagnosing rheumatoid arthritis. The current study aimed to identify rheumatoid arthritis diagnostic biomarkers by using a proteomics approach. Serum protein profiling was conducted using mass spectrometry, and five distinguishable biomarkers were identified therefrom. In the validation study, the five biomarkers were quantitatively verified by multiple reaction monitoring (MRM) analysis. Two proteins, namely serum amyloid A4 and vitamin D binding protein, showed high performance in distinguishing patients with rheumatoid arthritis from healthy controls. Logistic analysis was conducted to evaluate how accurately the two biomarkers distinguish patients with rheumatoid arthritis from healthy controls. The classification accuracy was 86.0% and 81.4% in patients with rheumatoid arthritis and in healthy controls, respectively. Serum amyloid A4 and vitamin D binding protein could be potential biomarkers related to the inflammatory response and joint destruction that accompany rheumatoid arthritis.

Proteomics Analysis for Verification of Rheumatoid Arthritis Biomarker Candidates Using Multiple Reaction Monitoring.

PURPOSE: Rheumatoid arthritis (RA) is an autoimmune disease in which autoantibodies attack the synovial membrane, causing joint inflammation. Blood tests would offer a powerful, minimally invasive method for early diagnosis of RA. However, no reliable biomarkers for RA are presently available. The aim is to develop biomarkers for RA by multiple reaction monitoring (MRM)-based quantification of candidate biomarkers. EXPERIMENTAL DESIGN: Proteomics approaches are commonly used to identify and verify disease biomarkers. For discovery of biomarkers for RA, SWATH acquisition is performed and selected candidate biomarkers are validated by MRM. Target serum proteins are compared between patients with RA and healthy controls divided into three groups based on rheumatoid factor level. RESULTS: A total of 45 differentially expressed proteins are identified, as determined by SWATH acquisition. Of these, 13 proteins are selected as novel candidate biomarkers. A total of five proteins (transthyretin, gelsolin, angiotensinogen, lipopolysaccharide-binding protein, and protein S100-A9) are shown to have the potential to distinguish patients with RA from healthy controls. CONCLUSIONS AND CLINICAL RELEVANCE: These five proteins may improve the efficiency of diagnosis of RA. MRM can be used to easily diagnose RA by detecting five proteins simultaneously in a single sample with high sensitivity.

A rhodamine based fluorescent probe validates substrate and cellular hypoxia specific NADH expression.

Herein, we report a rhodamine-based redox probe (MQR) to visualize cytosolic NADH in the cellular milieu. Its high sensitivity and selectivity allowed it to track the alteration of the NADH level under metabolic perturbation, suggesting its potential as a useful tool to study the association between the NADH level and metabolic abnormalities with clinical significance.

Bicalutamide enhances fodrin-mediated apoptosis through calpain in LNCaP.

Prostate cancer is the most common cancer in men, and before it progresses and metastasizes, the anticancer drug bicalutamide is often administered to patients. Many cases of androgen-dependent prostate cancer develop resistance during treatment with bicalutamide. Therefore, the effect of bicalutamide on androgen-dependent LNCaP prostate cancer cells is of clinical interest. The aim of this study was to demonstrate the effects of the anticancer drug bicalutamide on LNCaP prostate cancer cells by using a proteomics approach. Based on the results, 314 proteins were differentially expressed between the LNCaP and LNCaP treated with bicalutamide. The apoptosis pathway associated with differentially expressed proteins was shown in the Kyoto Encyclopedia of Gene and Genome pathway mapper. The Kyoto Encyclopedia of Gene and Genome pathway mapper results revealed that the fodrin-mediated apoptosis pathway is associated with the actions of bicalutamide and Western blotting was performed to validate these results. Impact statement We studied bicalutamide's anticancer action by using proteomics. The effect of bicalutamide on androgen-exposed LNCaP cells was also studied. KEGG identified >1.8-fold differentially expressed proteins between test group cells. KEGG mapper showed fodrin-mediated apoptosis involvement in bicalutamide's action. The anticancer effects of bicalutamide, which was further confirmed using Western blotting. Therefore, this drug is a potential candidate for understanding bicalutamide's effect on LNCaP and fodrin can be used as a biomarker monitoring status in metastatic carcinoma.

Development of a Novel Diagnostic Biomarker Set for Rheumatoid Arthritis Using a Proteomics Approach.

BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune disease that starts with inflammation of the synovial membrane. Studies have been conducted to develop methods for efficient diagnosis of RA and to identify the mechanisms underlying RA development. Blood samples can be useful for detecting disturbance of homeostasis in patients with RA. Nanoliquid chromatography-tandem mass spectrometry (LC-MS/MS) is an efficient proteomics approach to analyze blood sample and quantify serum proteins. METHODS: Serum samples of 18 healthy controls and 18 patients with RA were analyzed by LC-MS/MS. Selected candidate biomarkers were validated by enzyme-linked immunosorbent assay (ELISA) using sera from 43 healthy controls and 44 patients with RA. RESULTS: Thirty-eight proteins were significantly differentially expressed by more than 2-fold in healthy controls and patients with RA. Based on a literature survey, we selected six candidate RA biomarkers. ELISA was used to evaluate whether these proteins effectively allow distinguishing patients with RA from healthy controls and monitoring drug efficacy. SAA4, gelsolin, and vitamin D-binding protein were validated as potential biomarkers of RA for screening and drug efficacy monitoring of RA. CONCLUSIONS: We identified a panel of three biomarkers for RA which has potential for application in RA diagnosis and drug efficacy monitoring. Further, our findings will aid in understanding the pathogenesis of RA.