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.

Discovery and validation of metabolite markers in bloodstains for bloodstain age estimation.

Bloodstain age estimation involves measuring time-dependent changes in the levels of biomolecules in bloodstains. Although several studies have identified bloodstain metabolites as markers for estimating bloodstain age, none have considered sex, age-related metabolomic differences, or long-time bloodstain age. Therefore, we aimed to identify metabolite markers for estimating the age of bloodstains at weekly intervals within 28 days and validate them through multiple reaction monitoring. Adenosine 5'-monophosphate, choline, and pyroglutamic acid were selected as markers. Seven metabolites were validated, including five previously reported metabolites, ergothioneine, hypoxanthine, L-isoleucine, L-tryptophan, and pyroglutamic acid. Choline and hypoxanthine can be used to differentiate bloodstains between days 0 and 14 after deposition at weekly intervals, whereas L-isoleucine and L-tryptophan can help distinguish bloodstains between 7 days before and 14 days after deposition. Evaluation of the changes in metabolite levels according to sex and age revealed that the average levels of all seven metabolites were higher in women on day 0. Moreover, the level of ergothioneine was significantly higher in elderly individuals than in young individuals at all time points. In this study, we confirmed the potential effectiveness of metabolites in bloodstains as forensic markers and provided a new perspective on metabolomic approaches linked to forensic science.

Effect of environmental conditions on bloodstain metabolite analysis.

Establishing a correlation between environmental variables and chemical change can significantly improve the quality of research in multiple fields. Among various environmental variables, temperature and humidity are closely related to the rate of chemical reactions. This study aimed to confirm changes in metabolite markers that were previously discovered in other temperature and humidity environment conditions and to confirm the possibility that they could act as markers. After blood collection from the subjects and bloodstain preparation, the quantitative values of the bloodstain metabolites were confirmed (when the age of the bloodstain was within a month) under eight environmental conditions (4 °C/30%, 4 °C/60%, 25 °C/30%, 25 °C/60%, 25 °C/90%, 40 °C/30%, 40 °C/60%, and 40 °C/90%). Age-of-bloodstain estimation models were constructed to confirm the applicability of bloodstain metabolites as markers for bloodstain age in various environments. The average concentration of metabolite markers exhibited a decreasing trend with the age of the bloodstain, which transformed into an increasing trend from day 7 onwards. In terms of temperature and humidity, 25 °C and 90%, respectively, showed the most dissimilar metabolite change pattern compared to other conditions. The age-of-bloodstain estimation models developed here have an R-square value of up to 0.92 for each condition and an R-square value of 0.71 when all environmental conditions were combined. The findings herein highlight the immense potential of blood metabolites for field application, confirming the possibility of predicting metabolite changes from the rates of their chemical reactions and validating the importance of metabolites as age-of-bloodstain markers under various environmental conditions.

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.

Bloodstain Metabolite Markers: Discovery and Validation for Estimating Age of Bloodstain within 7 Days.

Metabolomic research using analytical chemistry methods has been carried out in a wide range of research fields. However, research combining forensic science and metabolomics is rare. Determining the age of bloodstains could provide key information regarding when a crime was committed. Currently, validated methods for estimating the age of bloodstains are unavailable. Metabolites are intermediate and final products of chemical reactions. Therefore, they are less likely to be degraded than other components of blood under field conditions. In this study, metabolites in bloodstains were analyzed using liquid chromatography-mass spectrometry to discover and validate metabolic markers for determining the age of bloodstains within a week post-bleeding. Nontargeted analysis of bloodstain metabolites revealed statistically significant differences over time. Quantitative analysis of identified candidates via multiple reaction monitoring confirmed the statistical significance according to the age of bloodstain. Pyroglutamic acid, l-glutamine, acetylcarnitine, and adenosine 5'-monophosphate were selected as the final markers. The content of each marker exhibited a statistically significant and consistent tendency to decrease with the age of bloodstain. Furthermore, the effect of hemolysis was considered according to the blood fraction spots of the four markers. This study is the first to identify and validate metabolite markers that may help determine the age of bloodstains within a week post-bleeding. If applied to crime scenes as indicators of the age of bloodstains, they can be used as innovative and important tools for reconstructing crime scenes, suggesting initial investigative direction. This study highlights the forensic utility of blood metabolites ex vivo.

Discovery of donor age markers from bloodstain by LC-MS/MS using a metabolic approach.

Bloodstains are frequently encountered at crime scenes and they provide important evidence about the incident, such as information about the victim or suspect and the time of death or other events. Efforts have been made to identify the age of the bloodstain's donor through genomic approaches, but there are some limitations, such as the availability of databases and the quality dependence of DNA. There is a need for the development of a tool that can obtain information at once from a small blood sample. The aim of this study is to identify bloodstain metabolite candidates that can be used to determine donor age. We prepared bloodstain samples and analyzed metabolites using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Eighteen molecular features (MFs) were selected as candidates using volcano plots and multivariate analysis. Based on the MS/MS spectrum of the MFs, the following nine metabolites were identified from the METaboliteLINk database: Δ2-cis eicosenoic acid, ergothioneine, adenosine 5'-monophosphate, benzaldehyde, phenacylamine, myristic acid ethyl ester, p-coumaric acid, niacinamide, and N-arachidonoyl-L-alanine. These nine age markers at high or low abundances could be used to estimate the age of a bloodstain's donor. This study was the first to develop metabolite age markers that can be used to analyze crime scene bloodstains.

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.

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.

Spatiotemporal expression of aquaporin 9 is critical for the antral growth of mouse ovarian follicles†.

Although a few aquaporins (AQPs) expressed in granulosa cells have been postulated to mediate fluid passage into the antrum, the specific expression of AQPs in different follicle cell types and stages and their roles have not been evaluated extensively. The spatiotemporal expression of aquaporin (Aqp) 7, 8, and 9 and the functional roles of Aqp9 in antral growth and ovulation were examined using a superovulation model and 3-dimensional follicle culture. Aqp9 was expressed at a high level in the rapid growth phase (24-48 h post equine chorionic gonadotropin (eCG) for superovulation induction) compared to Aqp7 (after human chorionic gonadotropin (hCG)) and Aqp8 (8-24 h post eCG and 24 h post hCG). A dramatic increase in the expression and localization of Aqp9 mRNA in theca cells was observed, as evaluated using quantitative reverse transcription-polymerase (RT-PCR) coupled with laser capture microdissection and immunohistochemistry. AQP9 was located primarily on the theca cells of the tertiary and preovulatory follicles but not on the ovulated follicles. In phloretin-treated mice, the diameter of the preovulatory follicles and the number of ovulated oocytes decreased. Consistent with these findings, knocking down Aqp9 expression with an Aqp9 siRNA inhibited follicle growth (0.28:1 = siRNA:control) and decreased the number of ovulated follicles (0.36:1 = siRNA:control) during in vitro growth and ovulation induction. Based on these results, the expression of AQPs is under the control of the physiological status, and AQP9 expression in theca during folliculogenesis is required for antral growth and ovulation in a tissue-specific and stage-dependent manner.

Metabolomic profiling of bloodstains on various absorbent and non-absorbent surfaces.

Bloodstains found at crime scenes contain immense information about the crime; thus, studies involving analysis of small molecules in bloodstains have been conducted. However, most of these studies have not accounted for the difference in the results of small molecule analysis due to the surface of bloodstains. To evaluate the "surface effect," we prepared bloodstains on seven surfaces, including both absorbent and non-absorbent surfaces, and performed global small molecule analysis by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). We used three indicators: (1) count recovery rate (%) of molecular features (MFs), (2) the number of MFs extracted from the surface without bloodstains, and (3) difference in abundance recovery rate (%) of MFs, to determine the ranking of the seven surfaces in the order of their similarity with blood. We also confirmed the correlation between each surface and blood through multivariate analysis. We found that the non-absorbent surfaces ranked better than the absorbent surfaces; wooden flooring was ranked as the most efficient surface, followed by stainless, vinyl flooring, glass, tile, filter paper, and mixed cotton. This study will help in the selection of the most efficient surface for collection of bloodstains for small molecule analysis from a crime scene. This is the first study to identify the effects of surface on extraction of global small molecules from bloodstains; it will help forensic scientists in obtaining more accurate information from small molecules present in the bloodstains collected at the field. Graphical abstract.

Comparison of Swabbing Solution Volume and gDNA Extraction Kits on DNA Recovery from Rigid Surface.

For bacteria sampling studies, various collection methods have been used to identify bacteria. To obtain accurate information about bacteria, high quality samples should be obtained. In order to obtain a high quality sample, a stable and large number of DNA copies must be collected. This study compared the efficiency of different methods of bacterial gDNA extraction and bacteria collection according to swabbing solution volumes and types. The efficiency of bacterial genomic DNA extraction was compared using a AccuPrep® Genomic DNA Extraction kit, a QIAamp® DNA Mini kit, and a MOBIO® DNeasy PowerSoil kit. The DNA Mini kit was shown to extract the highest amount of gDNA, and sub-experiments were conducted using this kit. Phosphate-buffered saline and phosphate-buffered saline with 0.1% Tween 20 were used as collection solutions of various volumes (0, 40, 50, 60, 70, 80, 90, 100, 110, and 120 µL) using cotton swabs. Bacteria collection efficiency was highest when 70 µL PBS was used. The target strains collected in this experiment were Staphylococcus aureus and Escherichia coli, and these were quantified using the number of colony-forming units, DNA concentrations, and the number of DNA copies. These results can be used to efficiently bacterial collection for experiments in various fields.

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.

Estimation of Age of Bloodstains by Mass-Spectrometry: A Metabolomic Approach.

Bloodstains are common evidence in crime scenes, containing significant information, including genetic information. Although efforts have been made to reliably determine the time of incident by analyzing the elapsed time of the bloodstain, there has been limited success. To identify candidate metabolites in bloodstains over time, we prepared bloodstain samples using filter paper and analyzed the metabolites by high-performance liquid chromatography-mass spectrometry (HPLC-MS)/MS over a 21-day period. Using Venn diagrams and by multivariate analysis, we selected 62 candidate molecular features. We found by partial least-squares discriminant analysis (PLS-DA) that the group can be classified with an accuracy of 75.0%, and the R2 and Q2 values were 0.7513 and 0.6998, respectively. Five metabolites were successfully identified based on candidate molecular features. The level of two metabolites, l-tryptophan and ergothioneine, decreased with time. The concentration of candidate metabolites that we propose reliably increased or decreased with time, thus, enabling the measurement of elapsed time of the bloodstain. This study is the first to identify markers used to analyze the elapsed time of bloodstains through metabolomics analysis.

The relationship between morningness-eveningness and resilience in mood disorder patients.

BACKGROUND: There is some evidence that resilience is related to mental illness. Patients with a mood disorder have a tendency to show eveningness, and they tend to be less resilient. However, no study has investigated the association between resilience and morningness-eveningness in patients with a mood disorder. The aim of this study was to explore whether morningness-eveningness is related to resilience in patients with a mood disorder. METHODS: We recruited 224 patients with major depressive disorder (MDD), 77 with bipolar disorder (BD), and 958 control participants. Morningness-eveningness and resilience were evaluated using the Composite Scale of Morningness (CS) and the Connor-Davidson Resilience Scale (CD-RISC), respectively. RESULTS: The CD-RISC scores were significantly lower in patients with MDD, followed by those with BD, than those of the control group. The CD-RISC score was positively correlated with the CS score in patients with MDD and BD. Multiple linear regression analyses revealed that the CS score was significantly associated with the CD-RISC score after controlling for the possible influence of age, gender, length of education, economic status, onset age, and suicide attempt history in the MDD group. However, the association did not reach statistical significance in patients with BD. CONCLUSIONS: Higher resilience was positively correlated with morningness in patients with MDD or BD. In multiple regression analysis, a significant linear relationship was observed between resilience and morningness only in patients with MDD. The biological mechanism underlying the relationship between morningness-eveningness and resilience should be explored.

Genetic association study of CSNK1E gene in bipolar disorder and circadian characteristics.

BACKGROUND: A circadian rhythm disturbance is one of the essential components of the phenotype of bipolar disorder. It has been reported that casein kinase 1 epsilon (CSNK1E), a member of the clock gene family, is associated with psychiatric phenotypes. OBJECTIVES: We performed a genetic association study to determine the genetic role of CSNK1E in bipolar disorder and circadian rhythm disturbances in the Korean population. METHODS: The present study included 215 patients with bipolar disorder and 773 controls. Circadian characteristics were measured by the Korean version of the Composite Scale of Morningness (CS). Single-nucleotide polymorphisms (SNPs) of CSNK1E, rs1534891 and rs2075984, were genotyped. Chi-square analyses were performed to evaluate associations involving alleles and genotypes. Haplotype analysis was also performed, and the permutation p value was calculated. We also tested further associations involving these SNPs and scores on the CS. RESULTS: We found a positive association between SNP rs2075984 and bipolar disorder in both the allelic (p = .003) and genotypic (p = .006) distributions. No allelic or genotypic association between SNP rs1534891 and bipolar disorder was observed. A significant association of haplotype with bipolar disorder was found (p = .033). However, no association between the CS and the genotype of either SNP was found in the total sample. CONCLUSION: CSNK1E SNP rs2075984 seemed to play a significant role in the development of bipolar disorder in this Korean sample. This association does not seem to relate to the phase preference measured by the CS. Further studies on CSNK1E with larger samples and more SNPs are necessary.

Identification and Validation of SAA4 as a Rheumatoid Arthritis Prescreening Marker by Liquid Chromatography Tandem-mass Spectrometry.

Rheumatoid arthritis (RA) is a chronic autoimmune disease that progresses into systemic inflammation and joint deformity. RA diagnosis is a complicated procedure, and early diagnostic methods are insufficient. Therefore, in this study, we attempted to identify new markers to improve the accuracy of RA prescreening. e identified differentially expressed proteins (DEPs) by using liquid chromatography tandem-mass spectrometry in health-prescreening sera with high rheumatoid factor (RF) values, and compared the findings with those from sera with normal RF values. We identified 93 DEPs; of these, 36 were upregulated, and 57 were downregulated in high-RF sera. Pathway analysis revealed that these DEPs were related to immune responses. Additionally, four DEPs were statistically analyzed by proteomic analysis; of these, SAA4 was significantly validated in individual enzyme-linked immunosorbent assays. Moreover, SAA4 was significantly upregulated in RA patients (n = 40, 66.43 ± 12.97 ng/mL) compared with normal controls (n = 40, 4.79 ± 0.95 ng/mL) and had a higher area under the curve than C-reactive protein. Thus, we identified SAA4 as a protein that was positively correlated with RF and RA. SAA4 may represent a novel prescreening marker for the diagnosis of RA.

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 mechanism of activated thrombus formation in patients with stroke and atrial fibrillation.

Stroke is an acute cerebrovascular disease in which blood flow to the brain is suddenly disrupted, causing damage to nerve cells. It involves complex and diverse pathophysiological processes and the treatment strategies are also diverse. The treatment for patients with stroke and atrial fibrillation (AF) is aimed at suppressing thrombus formation and migration. However, information regarding the protein networking involved in different thrombus formation pathways in patients with AF and stroke is insufficient. We performed protein profiling of patients with ischemic stroke with and without AF to investigate the mechanisms of thrombus formation and its pathophysiological association while providing helpful information for treating and managing patients with AF. These two groups were compared to identify the protein networks related to thrombus formation in AF. We observed that patients with ischemic stroke and AF had activated inflammatory responses induced by C-reactive protein, lipopolysaccharide-binding protein, and alpha-1-acid glycoprotein 1. In contrast, thyroid hormones were increased due to a decrease in transthyretin and retinol-binding protein 4 levels. The mechanism underlying enhanced cardiac activity, vasodilation, and the resulting thrombosis pathway were confirmed in AF. These findings will play an essential role in improving the prevention and treatment of AF-related stroke.

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 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.