Co-stimulatory pathway competitive assay development using Liquid chromatography-tandem mass spectrometry (LC-MS/MS)

T-cells play a significant role in the development of autoimmune diseases. The CD28-B7 costimulatory pathway is crucial for activating T-cells, and blocking this pathway is essential for treating autoimmune diseases. Therapeutic antibodies and fusion proteins that target costimulatory molecules like CD80, CD86, CTLA-4, and CD28 have been developed to explore the costimulation process and as targeted treatments. To advance our understanding of costimulation in autoimmunity and the inhibition of the costimulatory pathway, it is crucial to have an accurate, precise, and direct method for detecting and quantifying the soluble form of these molecules in body fluids and various biological systems. Herein, we developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantifying the four costimulatory proteins depending on the signature peptides derived from the soluble isoform of these proteins in multiple reaction monitoring (MRM) mode. The method was validated using the US FDA guidelines. The LOQ was determined as ∼0.5 nM for the four analytes, with quantification extended to 20 nM with a correlation coefficient of R2>0.998. The developed MRM method was used to analyze on-bead digested protein mixtures to establish a competitive assay for the CD28-B7 costimulatory pathway using CTLA4-Ig (Abatacept ™) as an FDA-approved drug for rheumatoid arthritis. The IC50 was determined to be 2.99 and 159.8 nM for sCD80 and sCD86, respectively. A straightforward MRM-based competitive assay will advance the knowledge about the costimulatory role in autoimmunity and the autoimmune therapeutic drug discovery, with the need for broad application on different in vitro and in vivo models to discover new targeted inhibitors.

Further delineation of the phenotypic and metabolomic profile of ALDH1L2-related neurodevelopmental disorder

ALDH1L2, a mitochondrial enzyme in folate metabolism, converts 10-formyl-THF (10-formyltetrahydrofolate) to THF (tetrahydrofolate) and CO2. At the cellular level, deficiency of this NADP+-dependent reaction results in marked reduction in NADPH/NADP+ ratio and reduced mitochondrial ATP. Thus far, a single patient with biallelic ALDH1L2 variants and the phenotype of a neurodevelopmental disorder has been reported. Here, we describe another patient with a neurodevelopmental disorder associated with a novel homozygous missense variant in ALDH1L2, Pro133His. The variant caused marked reduction in the ALDH1L2 enzyme activity in skin fibroblasts derived from the patient as probed by 10-FDDF, a stable synthetic analog of 10-formyl-THF. Additional associated abnormalities in these fibroblasts include reduced NADPH/NADP+ ratio and pool of mitochondrial ATP, upregulated autophagy and dramatically altered metabolomic profile. Overall, our study further supports a link between ALDH1L2 deficiency and abnormal neurodevelopment in humans.

Comprehensive metabolomics analysis reveals novel biomarkers and pathways in falsely suspected glutaric aciduria Type-1 newborns

BACKGROUND

Glutaric aciduria type-1 (GA-1) is a rare metabolic disorder due to glutaryl coenzyme A dehydrogenase deficiency, causing elevated levels of glutaryl-CoA and its derivatives. GA-1 exhibits symptoms like macrocephaly, developmental delays, and movement disorders. Timely diagnosis through genetic testing and newborn screening is crucial. However, in some cases, transiently elevated level of glutarylcarnitine (C5DC) challenges accurate diagnosis, highlighting the need for alternative diagnostic methods, like mass spectrometry-based untargeted metabolomics, to identify additional biomarkers for distinguishing falsely suspected GA-1 from healthy newborns.

METHODOLOGY

DBS samples from falsely suspected GA-1 newborns (n = 47) and matched control were collected through the NBS program. Untargeted metabolomics using liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was performed to enable biomarker and pathway investigations for significantly altered metabolites.

RESULTS

582 and 546 were up- and down-regulated metabolites in transient GA-1. 155 endogenous metabolites displayed significant variations compared to the control group. Furthermore, our data identified novel altered metabolic biomarkers, such as N-palmitoylcysteine, heptacarboxyporphyrin, 3-hydroxylinoleoylcarnitine, and monoacylglyceride (MG) (0:0/20:1/0:0), along with perturbed metabolic pathways like sphingolipid and thiamine metabolism associated with the transient elevated C5DC levels in DBS samples.

CONCLUSIONS

A distinct metabolic pattern linked to the transient C5DC elevation in newborns was reported to enhance the prediction of the falsely positive cases, which could help avoiding unnecessary medical treatments and minimizing the financial burdens in the health sector.

Metabolomic Profiling of Blood Plasma in Females with Hyperplasia and Endometrial Cancer

Uterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.

A diagnostic electrochemical aptasensor development for sCD80 protein detection in human serum

Elevating soluble CD80 (sCD80) in human serum is a natural response to autoimmune diseases such as rheumatoid arthritis (RA). The level of sCD80 is associated with RA development and prognosis; therefore, it is potentially used as a biomarker. sCD80 is commonly measured in human serum using immunoassays (e.g., ELISA) with multiple drawbacks, mainly cross-reactivity. Aptamer-based biosensors (aptasensors) development for quantifying and detecting different biological molecules demonstrates applicability in next-generation medicine and biomarker detection. Herein, we selected a specific aptamer for sCD80 by conventional in-vitro selection process (SELEX) with the high-affinity aptamer (Kd = 47.69 nM). A sensitive aptasensor, for the first time, was developed on a screen-printed gold electrode (AuSPE) platform compatible with easy-to-use label-free electrochemical impedance spectroscopy. The immobilization of the aptamer on the gold surface and the presence of sCD80 in a complex with the aptamer were characterized by photo-induced force microscopy, which revealed the uniform assembly of the aptamer monolayer and the distribution of sCD80 on the electrode surface. The developed aptasensor showed a linear performance (0.025-10.0 nM of protein) with a detection limit of 8.0 pM. Furthermore, the aptasensor was tested in a biological matrix, where a linear signal was observed for the increased amount of spiked sCD80 (R2 = 0.9887). The recovery of the spiked amounts ranged from 105 to 125% with coefficient of variation (CV%) <7%, which supported the applicability of this sensor in detecting sCD80 for diagnosis.

Lipidomics Profiling of Metformin-Induced Changes in Obesity and Type 2 Diabetes Mellitus: Insights and Biomarker Potential

Metformin is the first-line oral medication for treating type 2 diabetes mellitus (T2DM). In the current study, an untargeted lipidomic analytical approach was used to investigate the alterations in the serum lipidome of a cohort of 89 participants, including healthy lean controls and obese diabetic patients, and to examine the alterations associated with metformin administration. A total of 115 lipid molecules were significantly dysregulated (64 up-regulated and 51 down-regulated) in the obese compared to lean controls. However, the levels of 224 lipid molecules were significantly dysregulated (125 up-regulated and 99 down-regulated) in obese diabetic patients compared to the obese group. Metformin administration in obese diabetic patients was associated with significant dysregulation of 54 lipid molecule levels (20 up-regulated and 34 down-regulated). Levels of six molecules belonging to five lipid subclasses were simultaneously dysregulated by the effects of obesity, T2DM, and metformin. These include two putatively annotated triacylglycerols (TGs), one plasmenyl phosphatidylcholine (PC), one phosphatidylglycerol (PGs), one sterol lipid (ST), and one Mannosyl-phosphoinositol ceramide (MIPC). This study provides new insights into our understanding of the lipidomics alterations associated with obesity, T2DM, and metformin and offers a new platform for potential biomarkers for the progression of diabetes and treatment response in obese patients.

Label-free quantitative proteomics analysis for type 2 diabetes mellitus early diagnostic marker discovery using data-independent acquisition mass spectrometry (DIA-MS)

Type-2 diabetes mellitus (T2DM) therapy requires early diagnosis and complication avoidance. Unfortunately, current diagnostic markers do not meet these needs. Data-independent acquisition mass spectrometry (DIA-MS) offers a solution for clinical diagnosis, providing reliable and precise sample quantification. This study utilized DIA-MS to investigate proteomic differential expression in the serum of recently diagnosed T2DM patients. The study conducted a comparative protein expression analysis between healthy and recently diagnosed T2DM groups (discovery cohort). A candidate protein was then validated using enzyme-linked immune assay (ELISA) on serum samples collected from T2DM patients (n = 87) and healthy control (n = 60) (validation cohort). A total of 1074 proteins were identified, and 90 were significantly dysregulated between the two groups, including 32 newly associated with T2DM. Among these proteins, the expression of S100 calcium-binding protein A6 (S100A6) was validated by ELISA. It showed a significant increase in T2DM samples compared to the control group. It was evaluated as a biomarker using the receiver operating characteristic (ROC) curve, consistent with the DIA-MS results. Novel proteins are reported to be involved in the development and progression of T2DM. Further studies are required to investigate the differential expression of candidate marker proteins in a larger population of T2DM patients.

Demaghi, a polyherbal formulation, mitigates aluminum chloride-induced neurological impairment in mice: Insights from phytochemical analysis and behavioral assessment

Herbal products have been very popular in Pakistan for their curative significance against various disorders. Demaghi (DEMG) is a widely used herbal product claimed to own natural substances having neuroprotective potential. The current study aims to scientifically validate the chemical composition as well as its neuroprotective claims of this widely used herbal tonic. The commercially available Demaghi product was chemically characterized for its phytocomposition. The mice were treated with two doses of Demaghi (DEMG 50 mg and 100 mg/kg/day), and the effects of its prolonged exposure on animal anxiety, memory, and depression were noted through a series of behavioral tests in the AlCl3-induced memory deficient mice model. Besides that, dissected brains were biochemically analyzed for oxidative stress markers and acetylcholinesterase activity, as well as histopathological changes. The study outcomes showed that DEMG (100 mg/kg/day) has prominent anti-anxiety effects, memory-enhancing properties, and anti-depressants effects observed in the AlCl3-induced memory-deficient mice model. Biochemical assays also showed a greater decrease in oxidative stress of tested animals treated with 100 mg/kg/day of DEMG. The histopathological analysis also revealed that administration of DEMG reduced the AlCl3-induced toxicity. UPLC-MS results revealed the presence of many phytoconstituents, which showed to support cholinergic signaling in in-silico studies. The current research validates the neurological benefits of Demaghi for memory-boosting properties. The phytocompounds present in Demaghi exert neuroprotective effects, possibly by enhancing the cholinergic neurotransmission and combating the neurotoxin-induced oxidative stress.

Proteomics Investigation of the Impact of the Enterococcus faecalis Secretome on MCF-7 Tumor Cells

Breast cancer is the most prevalent form of cancer among women. The microenvironment of a cancer tumor is surrounded by various cells, including the microbiota. An imbalance between microbes and their host may contribute to the development and spread of breast cancer. Therefore, the objective of this study is to investigate the influence of Enterococcus faecalis on a breast cancer cell line (MCF-7) to mimic the luminal A subtype of breast cancer, using an untargeted proteomics approach to analyze the proteomic profiles of breast cancer cells after their treatment with E. faecalis in order to understand the microbiome and its role in the development of cancer. The breast cancer cell line MCF-7 was cultured and then treated with a 10% bacterial supernatant at two time points (24 h and 48 h) at 37 °C in a humidified incubator with 5% CO2. Proteins were then extracted and separated using two-dimensional difference (2D-DIGE) gel electrophoresis, and the statistically significant proteins (p-value < 0.05, fold change > 1.5) were identified via matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS). The protein fingerprints showed a differential protein expression pattern in the cells treated with E. faecalis for 24 and 48 h compared with the control. We found 58 statistically significant proteins changes in the MCF-7 breast cancer cells affected by E. faecalis. Kilin and transgelin were upregulated after 24 h of treatment and could be used as diagnostic and prognostic markers for breast cancer. In addition, another protein involved in the inhibition of cell proliferation was coiled-coil domain-containing protein 154. The protein markers identified in this study may serve as possible biomarkers for breast cancer progression. This promotes their future uses as important therapeutic goals in the treatment and diagnosis of cancer and increases our understanding of the breast microbiome and its role in the development of cancer.

Proteomic Profiling Identifies Distinct Regulation of Proteins in Obese Diabetic Patients Treated with Metformin

Background: Obesity and type 2 diabetes mellitus (T2DM) are characterized by underlying low-grade chronic inflammation. Metformin has been used as the first line of therapy in T2DM as it decreases hepatic glucose production and glucose intestinal absorption, enhances insulin sensitivity and weight loss, and is known to ameliorate inflammation. The mechanisms through which metformin exerts its effect remain unclear. Proteomics has emerged as a unique approach to explore the biological changes associated with diseases, including T2DM. It provides insight into the circulating biomarkers/mediators which could be utilized for disease screening, diagnosis, and prognosis. Methods: This study evaluated the proteomic changes in obese (Ob), obese diabetics (OD), and obese diabetic patients on metformin (ODM) using a 2D DIGE MALDI-TOF mass spectrometric approach. Results: Significant changes in sixteen plasma proteins (15 up and 1 down, ANOVA, p ≤ 0.05; fold change ≥ 1.5) were observed in the ODM group when compared to the Ob and OD groups. Bioinformatic network pathway analysis revealed that the majority of these altered plasma proteins are involved in distinct pathways involving acute-phase response, inflammation, and oxidative response and were centered around HNF4A, ERK, JNK, and insulin signaling pathways. Conclusions: Our study provides important information about the possible biomarkers altered by metformin treatment in obese patients with and without T2DM. These altered plasma proteins are involved in distinct pathways involving acute-phase response, inflammation, and oxidative response and were centered around HNF4A, ERK, JNK, and insulin signaling pathways. The presented proteomic profiling approach may help in identifying potential biomarkers/mediators affected by metformin treatment in T2DM and inform the understanding of metformin's mechanisms of action.

Targeted Metabolomics Analysis of Individuals Carrying the ANGPTL8 R59W Variant

ANGPTL8 is recognized as a regulator of lipid metabolism through its role in inhibiting lipoprotein lipase activity. ANGPTL8 gene variants, particularly rs2278426 leading to the R59W variant in the protein, have been associated with lipid traits in various ethnicities. We aimed to use metabolomics to understand the impact of the ANGPTL8 R59W variant on metabolites in humans. We used the Biocrates-p400 kit to quantify 408 plasma metabolites in 60 adult male Arab individuals from Kuwait and identify differences in metabolite levels between individuals carrying reference genotypes and those with carrier genotypes at ANGPTL8 rs2278426. Individuals with carrier genotypes (CT+TT) compared to those carrying the reference genotype (CC) showed statistically significant differences in the following metabolites: acylcarnitine (perturbs metabolic pathways), phosphatidylcholine (supports liver function and cholesterol levels), cholesteryl ester (brings chronic inflammatory response to lipoprotein depositions in arteries), α-aminoadipic acid (modulates glucose homeostasis), histamine (regulates glucose/lipid metabolism), sarcosine (links amino acid and lipid metabolism), diacylglycerol 42:1 (regulates homeostasis of cellular lipid stores), and lysophosphatidylcholine (regulates oxidative stress and inflammatory response). Functional aspects attributed to these metabolites indicate that the ANGPTL8 R59W variant influences the concentrations of lipid- and inflammation-related metabolites. This observation further highlights the role of ANGPTL8 in lipid metabolism.

Metabolic Alteration of MCF-7 Cells upon Indirect Exposure to E. coli Secretome: A Model of Studying the Microbiota Effect on Human Breast Tissue

According to studies, the microbiome may contribute to the emergence and spread of breast cancer. E. coli is one of the Enterobacteriaceae family recently found to be present as part of the breast tissue microbiota. In this study, we focused on the effect of E. coli secretome free of cells on MCF-7 metabolism. Liquid chromatography-mass spectrometry (LC-MS) metabolomics was used to study the E. coli secretome and its role in MCF-7 intra- and extracellular metabolites. A comparison was made between secretome-exposed cells and unexposed controls. Our analysis revealed significant alterations in 31 intracellular and 55 extracellular metabolites following secretome exposure. Several metabolic pathways, including lactate, aminoacyl-tRNA biosynthesis, purine metabolism, and energy metabolism, were found to be dysregulated upon E. coli secretome exposure. E. coli can alter the breast cancer cells' metabolism through its secretome which disrupts key metabolic pathways of MCF-7 cells. These microbial metabolites from the secretome hold promise as biomarkers of drug resistance or innovative approaches for cancer treatment, either as standalone therapies or in combination with other medicines.

Quantitative analysis of soluble costimulatory molecules as potential diagnostic biomarkers for rheumatoid arthritis using LC-MS/MS in MRM mode

BACKGROUND AND AIMS

Rheumatoid arthritis (RA) is a chronic autoimmune disease. RA-induced immunological responses are coordinated by T-cell stimulation. The costimulatory signal CD28-B7 is essential for T-cell activation by interacting CD28 with CD80 and CD86 costimulatory proteins. CTLA4 is another costimulatory protein that binds to CD80 and CD86 to inhibit T-cell activity. The soluble costimulatory proteins: sCD80, sCD86, sCD28, and sCTLA-4 were detected and quantified in human plasma and correlated with RA development. As potential diagnostic biomarkers for RA, developing a sensitive, specific, and reproducible method for quantifying these costimulatory molecules in human plasma and establishing quantitative ranges for each protein in healthy and RA patients' plasma is essential for advancing the clinical diagnostic and health outcomes.

MATERIALS AND METHODS

A novel quantitative liquid chromatography-tandem spectrometry (LC-MS/MS) technique using multiple reaction monitoring (MRM) modes was developed and validated to measure soluble costimulatory molecules sCTLA4, sCD28, sCD80, and sCD86 in human plasma samples. Furthermore, the method was applied to determine sCTLA4, sCD28, sCD80, and sCD86 levels in plasma samples from RA patients (n = 23) and healthy controls (n = 21).

RESULTS

The method was successfully developed and validated according to international inter- and intra-assay precision and accuracy guidelines. The linearity of the method was achieved between 0.5 nM and 100 nM for each protein with a correlation coefficient of > 0.998. The plasma level of sCTLA4, sCD80, and sCD86 in RA patients was significantly elevated compared to controls. RA patients had 63.32 ± 17.63 nM sCTLA4 and controls 36.05 ± 18.83 nM; p < 0.0001. The performance of the four proteins was determined using ROC curves, where sCTLA4 showed the highest diagnostic and clinical performance compared to the others.

CONCLUSIONS

This study reports the first use of LC-MS/MS in MRM mode to accurately quantify soluble costimulatory molecules in plasma samples as potential RA diagnostic biomarkers. Determination of the reference range for each protein with high selectivity and sensitivity increases the potential for utilizing this method as a clinical diagnostic.

Metabolomic profile of patients on levothyroxine treatment for hypothyroidism

Background

Hypothyroidism is clinically characterized by a decrease in levels of the circulating thyroid hormones namely thyroxine and triiodothyronine. The main treatment for hypothyroidism is thyroid hormone replacement using levothyroxine to normalize serum thyroid hormone levels.

Objectives

In this study, we explored the metabolic changes in the plasma of patients with hypothyroidism after reaching a euthyroid state with levothyroxine treatment.

Methods

Plasma samples from 18 patients diagnosed as overt hypothyroidism were collected before and after levothyroxine treatment upon reaching a euthyroid state and were analyzed by high-resolution mass spectrometry-based metabolomics. Multivariate and univariate analyses evaluated data to highlight potential metabolic biomarkers.

Results

Liquid chromatography-mass spectrometry-based metabolomics revealed a significant decrease in the levels of ceramide, phosphatidylcholine, triglycerides, acylcarnitine, and peptides after levothyroxine treatment; this could indicate a change in the fatty acid transportation system and an enhanced β-oxidation, compared with a hypothyroid state. At the same time, the decrease in the peptides suggested a shift in protein synthesis. In addition, there was a considerable rise in glycocholic acid following therapy, suggesting the involvement of thyroid hormones in stimulating bile acid production and secretion.

Conclusions

A metabolomic analysis of patients with hypothyroidism revealed significant changes in several metabolites and lipids after treatment. This study showed the value of the metabolomics technique in providing a complementary understanding of the pathophysiology of hypothyroidism and as a crucial tool for examining the molecular impact of levothyroxine treatment on hypothyroidism. It was an important tool for investigating the therapeutic effects of levothyroxine on hypothyroidism at the molecular level.

Recent advances in proteomic-based diagnostics of cystic fibrosis

INTRODUCTION

Cystic fibrosis (CF) is a genetic disease characterized by thick and sticky mucus accumulation, which may harm numerous internal organs. Various variables such as gene modifiers, environmental factors, age of diagnosis, and CF transmembrane conductance regulator (CFTR) gene mutations influence phenotypic disease diversity. Biomarkers that are based on genomic information may not accurately represent the underlying mechanism of the disease as well as its lethal complications. Therefore, recent advancements in mass spectrometry (MS)-based proteomics may provide deep insights into CF mechanisms and cellular functions by examining alterations in the protein expression patterns from various samples of individuals with CF.

AREAS COVERED

We present current developments in MS-based proteomics, its application, and findings in CF. In addition, the future roles of proteomics in finding diagnostic and prognostic novel biomarkers.

EXPERT OPINION

Despite significant advances in MS-based proteomics, extensive research in a large cohort for identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers for CF disease is highly needed.

A Distinctive Metabolomics Profile and Potential Biomarkers for Very Long Acylcarnitine Dehydrogenase Deficiency (VLCADD) Diagnosis in Newborns

Very long-chain acylcarnitine dehydrogenase deficiency (VLCADD) is a rare inherited metabolic disorder associated with fatty acid β-oxidation and characterized by genetic mutations in the ACADVL gene and accumulations of acylcarnitines. VLCADD, developed in neonates or later adults, can be diagnosed using newborn bloodspot screening (NBS) or genetic sequencing. These techniques have limitations, such as a high false discovery rate and variants of uncertain significance (VUS). As a result, an extra diagnostic tool is needed to deliver improved performance and health outcomes. As VLCADD is linked with metabolic disturbance, we postulated that newborn patients with VLCADD could display a distinct metabolomics pattern compared to healthy newborns and other disorders. Herein, we applied an untargeted metabolomics approach using liquid chromatography-high resolution mass spectrometry (LC-HRMS) to measure the global metabolites in dried blood spot (DBS) cards collected from VLCADD newborns (n = 15) and healthy controls (n = 15). Two hundred and six significantly dysregulated endogenous metabolites were identified in VLCADD, in contrast to healthy newborns. Fifty-eight and one hundred and eight up- and down-regulated endogenous metabolites were involved in several pathways such as tryptophan biosynthesis, aminoacyl-tRNA biosynthesis, amino sugar and nucleotide sugar metabolism, pyrimidine metabolism and pantothenate, and CoA biosynthesis. Furthermore, biomarker analyses identified 3,4-Dihydroxytetradecanoylcarnitine (AUC = 1), PIP (20:1)/PGF1alpha) (AUC = 0.982), and PIP2 (16:0/22:3) (AUC = 0.978) as potential metabolic biomarkers for VLCADD diagnosis. Our findings showed that compared to healthy newborns, VLCAADD newborns exhibit a distinctive metabolic profile, and identified potential biomarkers that can be used for early diagnosis, which improves the identification of the affected patients earlier. This allows for the timely administration of proper treatments, leading to improved health. However, further studies with large independent cohorts of VLCADD patients with different ages and phenotypes need to be studied to validate our potential diagnostic biomarkers and their specificity and accuracy during early life.

Untargeted Metabolomics Identifies Biomarkers for MCADD Neonates in Dried Blood Spots

Medium-chain acyl-CoA dehydrogenase deficiency (MCADD) is the most common inherited mitochondrial metabolic disease of fatty acid β-oxidation, especially in newborns. MCADD is clinically diagnosed using Newborn Bloodspot Screening (NBS) and genetic testing. Still, these methods have limitations, such as false negatives or positives in NBS and the variants of uncertain significance in genetic testing. Thus, complementary diagnostic approaches for MCADD are needed. Recently, untargeted metabolomics has been proposed as a diagnostic approach for inherited metabolic diseases (IMDs) due to its ability to detect a wide range of metabolic alterations. We performed an untargeted metabolic profiling of dried blood spots (DBS) from MCADD newborns (n = 14) and healthy controls (n = 14) to discover potential metabolic biomarkers/pathways associated with MCADD. Extracted metabolites from DBS samples were analyzed using UPLC-QToF-MS for untargeted metabolomics analyses. Multivariate and univariate analyses were used to analyze the metabolomics data, and pathway and biomarker analyses were also performed on the significantly identified endogenous metabolites. The MCADD newborns had 1034 significantly dysregulated metabolites compared to healthy newborns (moderated t-test, no correction, p-value ≤ 0.05, FC 1.5). A total of 23 endogenous metabolites were up-regulated, while 84 endogenous metabolites were down-regulated. Pathway analyses showed phenylalanine, tyrosine, and tryptophan biosynthesis as the most affected pathways. Potential metabolic biomarkers for MCADD were PGP (a21:0/PG/F1alpha) and glutathione, with an area under the curve (AUC) of 0.949 and 0.898, respectively. PGP (a21:0/PG/F1alpha) was the first oxidized lipid in the top 15 biomarker list affected by MCADD. Additionally, glutathione was chosen to indicate oxidative stress events that could happen during fatty acid oxidation defects. Our findings suggest that MCADD newborns may have oxidative stress events as signs of the disease. However, further validations of these biomarkers are needed in future studies to ensure their accuracy and reliability as complementary markers with established MCADD markers for clinical diagnosis.

Multi-Omics Profiling in PGM3 and STAT3 Deficiencies: A Tale of Two Patients

Hyper-IgE Syndrome (HIES) is a heterogeneous group of primary immune-deficiency disorders characterized by elevated levels of IgE, eczema, and recurrent skin and lung infections. HIES that is autosomally dominant in the signal transducer and activator of transcription 3 (STAT3), and autosomal recessive mutations in phosphoglucomutase 3 (PGM3) have been reported in humans. An early diagnosis, based on clinical suspicion and immunological assessments, is challenging. Patients' metabolomics, proteomics, and cytokine profiles were compared to DOCK 8-deficient and atopic dermatitis patients. The PGM3 metabolomics profile identified significant dysregulation in hypotaurine, hypoxanthine, uridine, and ribothymidine. The eight proteins involved include bifunctional arginine demethylase and lysyl hydroxylase (JMJD1B), type 1 protein phosphatase inhibitor 4 (PPI 4), and platelet factor 4 which aligned with an increased level of the cytokine GCSF. Patients with STAT3 deficiency, on the other hand, showed significant dysregulation in eight metabolites, including an increase in protocatechuic acid, seven proteins including ceruloplasmin, and a plasma protease C1 inhibitor, in addition to cytokine VEGF being dysregulated. Using multi-omics profiling, we identified the dysregulation of endothelial growth factor (EGFR) and tumor necrosis factor (TNF) signaling pathways in PGM3 and STAT3 patients, respectively. Our findings may serve as a stepping stone for larger prospective HIES clinical cohorts to validate their future use as biomarkers.

Biomarker discovery in galactosemia: Metabolomics with UPLC/HRMS in dried blood spots

Introduction:Galactosemia (GAL) is a genetic disorder that results in disturbances in galactose metabolism and can lead to life-threatening complications. However, the underlying pathophysiology of long-term complications in GAL remains poorly understood. Methods: In this study, a metabolomics approach using ultra-performance liquid chromatography coupled with high-resolution mass spectrometry was used to investigate metabolomic changes in dried blood spots of 15 patients with GAL and 39 healthy individuals. Results: The study found that 2,819 metabolites underwent significant changes in patients with GAL compared to the control group. 480 human endogenous metabolites were identified, of which 209 and 271 were upregulated and downregulated, respectively. PA (8:0/LTE4) and ganglioside GT1c (d18:0/20:0) metabolites showed the most significant difference between GAL and the healthy group, with an area under the curve of 1 and 0.995, respectively. Additionally, the study identified potential biomarkers for GAL, such as 17-alpha-estradiol-3-glucuronide and 16-alpha-hydroxy DHEA 3-sulfatediphosphate. Conclusion: This metabolomics study deepened the understanding of the pathophysiology of GAL and presented potential biomarkers that might serve as prognostic biomarkers to monitor the progression or support the clinical diagnosis of GAL.

Lipidomics Profiling of Patients with Low Bone Mineral Density (LBMD)

The relationship between lipid metabolism and bone mineral density (BMD) is still not fully elucidated. Despite the presence of investigations using osteoporotic animal models, clinical studies in humans are limited. In this work, untargeted lipidomics profiling using liquid chromatography-mass spectrometry (LC-MS) analysis of human serum samples was performed to identify the lipidomics profile associated with low bone mineral density (LBMD), with a subsequent examination of potential biomarkers related to OP risk prediction or progression. A total of 69 participants were recruited for this cohort study, including the osteoporotic group (OP, n = 25), osteopenia group (ON, n = 22), and control (Ctrl, n = 22). The LBMD group included OP and ON patients. The lipidomics effect of confounding factors such as age, gender, lipid profile, body mass index (BMD), chronic diseases, and medications was excluded from the dataset. The results showed a clear group separation and clustering between LBMD and Ctrl (Q² = 0.944, R² = 0.991), indicating a significant difference in the lipids profile. In addition, 322 putatively identified lipid molecules were dysregulated, with 163 up- and 159 down-regulated in LBMD, compared with the Ctrl. The most significantly dysregulated subclasses were phosphatidylcholines (PC) (n = 81, 25.16% of all dysregulated lipids 322), followed by triacylglycerol (TG) (n = 65, 20.19%), and then phosphatidylethanolamine (PE) (n = 40, 12.42%). In addition, groups of glycerophospholipids, including LPC (7.45%), LPE (5.59%), and PI (2.48%) were also dysregulated as of LBMD. These findings provide insights into the lipidomics alteration involved in bone remodeling and LBMD. and may drive the development of therapeutic targets and nutritional strategies for OP management.

Proteomics Profiling of Osteoporosis and Osteopenia Patients and Associated Network Analysis

Bone mass reduction due to an imbalance in osteogenesis and osteolysis is characterized by low bone mineral density (LBMD) and is clinically classified as osteopenia (ON) or osteoporosis (OP), which is more severe. Multiple biomarkers for diagnosing OP and its progression have been reported; however, most of these lack specificity. This cohort study aimed to investigate sensitive and specific LBMD-associated protein biomarkers in patients diagnosed with ON and OP. A label-free liquid chromatography-mass spectrometry (LC-MS) proteomics approach was used to analyze serum samples. Patients’ proteomics profiles were filtered for potential confounding effects, such as age, sex, chronic diseases, and medication. A distinctive proteomics profile between the control, ON, and OP groups (Q² = 0.7295, R² = 0.9180) was identified, and significant dysregulation in a panel of proteins (n = 20) was common among the three groups. A comparison of these proteins showed that the levels of eight proteins were upregulated in ON, compared to those in the control and the OP groups, while the levels of eleven proteins were downregulated in the ON group compared to those in the control group. Interestingly, only one protein, myosin heavy chain 14 (MYH14), showed a linear increase from the control to the ON group, with the highest abundance in the OP group. A significant separation in the proteomics profile between the ON and OP groups (Q² = 0.8760, R² = 0.991) was also noted. Furthermore, a total of twenty-six proteins were found to be dysregulated between the ON and the OP groups, with fourteen upregulated and twelve downregulated proteins in the OP, compared to that in the ON group. Most of the identified dysregulated proteins were immunoglobulins, complement proteins, cytoskeletal proteins, coagulation factors, and various enzymes. Of these identified proteins, the highest area under the curve (AUC) in the receiver operating characteristic (ROC) analysis was related to three proteins (immunoglobulin Lambda constant 1 (IGLC1), RNA binding protein (MEX3B), and fibulin 1 (FBLN1)). Multiple reaction monitoring (MRM), LC-MS, was used to validate some of the identified proteins. A network pathway analysis of the differentially abundant proteins demonstrated dysregulation of inflammatory signaling pathways in the LBMD patients, including the tumor necrosis factor (TNF), toll-like receptor (TL4), and interferon-γ (IFNG) signaling pathways. These results reveal the existence of potentially sensitive protein biomarkers that could be used in further investigations of bone health and OP progression.

Tissue-Based Proteomic Profiling in Patients with Hyperplasia and Endometrial Cancer

Uterine cancers are among the most prevalent gynecological malignancies, and endometrial cancer (EC) is the most common in this group. This study used tissue-based proteomic profiling analysis in patients with endometrial cancer and hyperplasia, and control patients. Conventional 2D gel electrophoresis, followed by a mass spectrometry approach with bioinformatics, including a network pathway analysis pipeline, was used to identify differentially expressed proteins and associated metabolic pathways between the study groups. Thirty-six patients (twelve with endometrial cancer, twelve with hyperplasia, and twelve controls) were enrolled in this study. The mean age of the participants was 46–75 years. Eighty-seven proteins were significantly differentially expressed between the study groups, of which fifty-three were significantly differentially regulated (twenty-eight upregulated and twenty-five downregulated) in the tissue samples of EC patients compared to the control (Ctrl). Furthermore, 26 proteins were significantly dysregulated (8 upregulated and 18 downregulated) in tissue samples of hyperplasia (HY) patients compared to Ctrl. Thirty-two proteins (nineteen upregulated and thirteen downregulated) including desmin, peptidyl prolyl cis-trans isomerase A, and zinc finger protein 844 were downregulated in the EC group compared to the HY group. Additionally, fructose bisphosphate aldolase A, alpha enolase, and keratin type 1 cytoskeletal 10 were upregulated in the EC group compared to those in the HY group. The proteins identified in this study were known to regulate cellular processes (36%), followed by biological regulation (16%). Ingenuity pathway analysis found that proteins that are differentially expressed between EC and HY are linked to AKT, ACTA2, and other signaling pathways. The panels of protein markers identified in this study could be used as potential biomarkers for distinguishing between EC and HY and early diagnosis and progression of EC from hyperplasia and normal patients.

Dystrophin Protein Quantification as a Duchenne Muscular Dystrophy Diagnostic Biomarker in Dried Blood Spots Using Multiple Reaction Monitoring Tandem Mass Spectrometry: A Preliminary Study

Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder characterized by progressive muscle loss, leading to difficulties in movement. Mutations in the DMD gene that code for the protein dystrophin are responsible for the development of DMD disorder, where the synthesis of this protein is completely halted. Therefore, circulating dystrophin protein could be a promising biomarker of DMD disease. Current methods for diagnosing DMD have sensitivity, specificity, and reproducibility limitations. Herein, a quantitative liquid chromatography-tandem spectrometry (LC-MS/MS) technique in multiple reaction monitoring (MRM) mode was designed and validated for accurate dystrophin protein measurement in a dried blood spot (DBS). The method was successfully validated on the basis of international guidelines regarding calibration curves, precision, and accuracy. In addition, patients and healthy controls were used to test the amount of dystrophin protein circulating in DBS samples as a potential biomarker for DMD disorders. DMD patients were found to have considerably lower levels than controls. To the best of our knowledge, this is the first study to report dystrophin levels in DBS through LC-MS/MS as a diagnostic marker for DMD to the proposed MRM method, providing a highly specific and sensitive approach to dystrophin quantification in a DBS that can be applied in DMD screening.

Proteomic Analysis of Endometrial Cancer Tissues from Patients with Type 2 Diabetes Mellitus

Endometrial cancer (EC) is the most common form of gynecological cancer. Type 2 diabetes mellitus is associated with an increased risk of EC. Currently, no proteomic studies have investigated the role of diabetes in endometrial cancers from clinical samples. The present study aims to elucidate the molecular link between diabetes and EC using a proteomic approach. Endometrial tissue samples were obtained from age-matched patients (EC Diabetic and EC Non-Diabetic) during surgery. Untargeted proteomic analysis of the endometrial tissues was carried out using a two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF). A total of 53 proteins were identified, with a significant difference in abundance (analysis of variance (ANOVA) test, p ≤ 0.05; fold-change ≥ 1.5) between the two groups, among which 30 were upregulated and 23 downregulated in the EC Diabetic group compared to EC Non-Diabetic. The significantly upregulated proteins included peroxiredoxin-1, vinculin, endoplasmin, annexin A5, calreticulin, and serotransferrin. The significantly downregulated proteins were myosin regulatory light polypeptide 9, Retinol dehydrogenase 12, protein WWC3, intraflagellar transport protein 88 homolog, superoxide dismutase [Cu-Zn], and retinal dehydrogenase 1. The network pathway was related to connective tissue disorder, developmental disorder, and hereditary disorder, with the identified proteins centered around dysregulation of ERK1/2 and F Actin signaling pathways. Cancer-associated protein alterations such as upregulation of peroxiredoxin-1, annexin 5, and iNOS, and downregulation of RDH12, retinaldehyde dehydrogenase 1, SOD1, and MYL 9, were found in the EC tissues of the diabetic group. Differential expression of proteins linked to cancer metastasis, such as the upregulation of vinculin and endoplasmin and downregulation of WWC3 and IFT88, was seen in the patients with diabetes. Calreticulin and alpha-enolase, which might have a role in the interplay between diabetes and EC, need further investigation.

The metabolomics approach revealed a distinctive metabolomics pattern associated with hyperthyroidism treatment

BACKGROUND

Hyperthyroidism is characterized by increased thyroid hormone production, which impacts various processes, including metabolism and energy expenditure. Yet, the underlying mechanism and subsequent influence of these changes are unknown. Metabolomics is a broad analytical method that enables qualitative and quantitative examination of metabolite level changes in biological systems in response to various stimuli, pathologies, or treatments.

OBJECTIVES

This study uses untargeted metabolomics to explore the potential pathways and metabolic patterns associated with hyperthyroidism treatment.

METHODS

The study consisted of 20 patients newly diagnosed with hyperthyroidism who were assessed at baseline and followed up after starting antithyroid treatment. Two blood samples were taken from each patient, pre (hyperthyroid state) and post-treatment (euthyroid state). Hyperthyroid and euthyroid states were identified based on thyroxine and thyroid-stimulating hormone levels. The metabolic alteration associated with antithyroid therapy was investigated using liquid chromatography- high-resolution mass spectrometry. The untargeted metabolomics data was analyzed using both univariate and multivariate analyses using MetaboAnalyst v5.0. The significant metabolic pattern was identified using the lab standard pipeline, which included molecular annotation in the Human Metabolome Database, LipidMap, LipidBlast, and METLIN. The identified metabolites were examined using pathway and network analyses and linked to cellular metabolism.

RESULTS

The results revealed a strong group separation between the pre- and post-hyperthyroidism treatment (Q2 = 0.573, R2 = 0.995), indicating significant differences in the plasma metabolome after treatment. Eighty-three mass ions were significantly dysregulated, of which 53 and 30 characteristics were up and down-regulated in the post-treatment compared to the pre-treatment group, respectively. The medium-chain acylcarnitines, octanoylcarnitine, and decanoylcarnitine, previously found to rise in hyperthyroid patients, were among the down-regulated metabolites, suggesting that their reduction could be a possible biomarker for monitoring euthyroid restoration. Kynurenine is a downregulated tryptophan metabolite, indicating that the enzyme kynurenine 3-hydroxylase, inhibited in hyperthyroidism, is back functioning. L-cystine, a cysteine dimer produced from cysteine oxidation, was among the down-regulated metabolites, and its accumulation is considered a sign of oxidative stress, which was reported to accompany hyperthyroidism; L-cystine levels dropped, this suggests that the plasma level of L-cystine can be used to monitor the progress of euthyroid state restoration.

CONCLUSION

The plasma metabolome of patients with hyperthyroidism before and after treatments revealed differences in the abundance of several small metabolites. Our findings add to our understanding of hyperthyroidism's altered metabolome and associated metabolic processes and shed light on acylcarnitines as a new biomarker for treatment monitoring in conjunction with thyroxine and thyroid-stimulating hormone.

Proteomics Profiling to Distinguish DOCK8 Deficiency From Atopic Dermatitis

Dedicator of cytokinesis 8 deficiency is an autosomal recessive primary immune deficiency disease belonging to the group of hyperimmunoglobulinemia E syndrome (HIES). The clinical phenotype of dedicator of cytokinesis 8 (DOCK8) deficiency, characterized by allergic manifestations, increased infections, and increased IgE levels, overlaps with the clinical presentation of atopic dermatitis (AD). Despite the identification of metabolomics and cytokine biomarkers, distinguishing between the two conditions remains clinically challenging. The present study used a label-free untargeted proteomics approach using liquid-chromatography mass spectrometry with network pathway analysis to identify the differentially regulated serum proteins and the associated metabolic pathways altered between the groups. Serum samples from DOCK8 (n = 10), AD (n = 9) patients and healthy control (Ctrl) groups (n = 5) were analyzed. Based on the proteomics profile, the PLS-DA score plot between the three groups showed a clear group separation and sample clustering (R2 = 0.957, Q2 = 0.732). Significantly differentially abundant proteins (p < 0.05, FC cut off 2) were identified between DOCK8-deficient and AD groups relative to Ctrl (n = 105, and n = 109) and between DOCK8-deficient and AD groups (n = 85). Venn diagram analysis revealed a differential regulation of 24 distinct proteins from among the 85 between DOCK8-deficient and AD groups, including claspin, haptoglobin-related protein, immunoglobulins, complement proteins, fibulin, and others. Receiver-operating characteristic curve (ROC) analysis identified claspin and haptoglobin-related protein, as potential biomarkers with the highest sensitivity and specificity (AUC = 1), capable of distinguishing between patients with DOCK8 deficiency and AD. Network pathway analysis between DOCK8-deficiency and AD groups revealed that the identified proteins centered around the dysregulation of ERK1/2 signaling pathway. Herein, proteomic profiling of DOCK8-deficiency and AD groups was carried out to determine alterations in the proteomic profiles and identify a panel of the potential proteomics biomarker with possible diagnostic applications. Distinguishing between DOCK8-deficiency and AD will help in the early initiation of treatment and preventing complications.

Metabolomics-Microbiome Crosstalk in the Breast Cancer Microenvironment

Breast cancer, the most frequent cancer diagnosed among females, is associated with a high mortality rate worldwide. Alterations in the microbiota have been linked with breast cancer development, suggesting the possibility of discovering disease biomarkers. Metabolomics has emerged as an advanced promising analytical approach for profiling metabolic features associated with breast cancer subtypes, disease progression, and response to treatment. The microenvironment compromises non-cancerous cells such as fibroblasts and influences cancer progression with apparent phenotypes. This review discusses the role of metabolomics in studying metabolic dysregulation in breast cancer caused by the effect of the tumor microenvironment on multiple cells such as immune cells, fibroblasts, adipocytes, etc. Breast tumor cells have a unique metabolic profile through the elevation of glycolysis and the tricarboxylic acid cycle metabolism. This metabolic profile is highly sensitive to microbiota activity in the breast tissue microenvironment. Metabolomics shows great potential as a tool for monitoring metabolic dysregulation in tissue and associating the findings with microbiome expression.

Absolute quantification of senescence mediators in cells using multiple reaction monitoring liquid chromatography-Tandem mass spectrometry

BACKGROUND

The identification of unique senescence markers remains challenging. Current hallmarks of senescent cells, including increased senescence-associated β-galactosidase activity, increased levels of cell cycle regulators such as p16^INK4a, p27, and p53, and altered levels of sirtuins and lamins, are detected commonly by Western blot and immunohistochemistry methods. Mass spectrometry outperforms these conventional quantification methods in terms of high throughput, specificity, and reproducibility.

OBJECTIVES

To develop multiple reaction monitoring-based tandem mass spectrometric senescence assay for simultaneous measuring of p16^INK4a, p27, p53, p53-β, the seven proteins of the sirtuins family and the four transcript variants of lamins proteins in aging cell model and cancerous cell lines.

METHODOLOGY

Multiple reaction monitoring-tandem mass transitions per protein were developed for each signature peptide(s) and stable isotope-labeled internal standard. The developed assay was validated in a matrix using breast cancer MCF7 cell lines according to the US-FDA guidelines for bioanalytical assays.

RESULTS

The analytes chromatographic peaks were baseline separated and showed linear behavior in a wide dynamic range with r² ≥ 0.98. The method for all proteins has passed the inter/intra-day precision and accuracy validation using three levels of quality control samples. The accuracy and the precision for most analytes were 80-120% and ≤20%, respectively. The method's sensitivity for the panels' signature peptides ranged from 1 ng μL^-1 to 1 μg mL^-1. Extraction recovery assessed in two quality control levels was >60% for most analytes. This LC-MS-MS validated senescence assay showed reduced lamin A, lamin A△10, lamin A△50, SIRT1, SIRT3, SIRT5, p53, and p16^INK4a, as well as p53-β induction, are implicated in replicative senescence. Meanwhile, increased lamin C: lamin A ratio was evident and can diagnose breast carcinogenesis. Moreover, in breast cancer metastasis, reduced SIRT2 and p27 and elevated levels of lamin A△50, SIRT5, SIRT7, and p53-β are evident.

CONCLUSION

LC-MS/MS is a potent alternative tool to the currently available assays. The high throughput method established can study senescence's role in different pathophysiological processes.

Molecular and Metabolomic Investigation of Celecoxib Antiproliferative Activity in Mono-and Combination Therapy Against Breast Cancer Cell Models

BACKGROUND

Chronic inflammation plays a crucial role in the initiation, promotion, and invasion of tumors, and thus the antiproliferative effects of numerous anti-inflammatory drugs have been frequently reported in the literature. Upregulation of the pro-inflammatory enzyme cyclooxygenase-2 (COX-2) has been linked to various human cancers, including breast cancer.

OBJECTIVES

This research aims to investigate the antiproliferative activity of different Non-steroidal anti-inflammatory drugs (NSAIDs), including COX-2 selective and non-selective agents, against various breast cancer cell lines and to elucidate possible molecular pathways involved in their activity.

METHODS

The antiproliferative and combined effects of NSAIDs with raloxifene were evaluated by MTT assay. Cell migration was assessed using a wound-healing assay. The mechanism of cell death was determined using the Annexin V-FITC/ propidium iodide staining flow cytometry method. A mass spectrometry-based targeted metabolomics approach was used to profile the metabolomic changes induced in the T47d cells upon drug treatment.

RESULTS

Our results have demonstrated that celecoxib, a potent and selective COX-2 inhibitor, resulted in significant antiproliferative activity against all examined breast cancer cell lines with IC50 values of 95.44, 49.50. and 97.70 μM against MDA-MB-231, T47d, and MCF-7, respectively. Additionally, celecoxib exhibited a synergistic effect against T47d cells combined with raloxifene, a selective estrogen receptor modulator. Interestingly, celecoxib treatment increased cell apoptosis and resulted in substantial inhibition of cancer cell migration. In addition, the metabolomic analysis suggests that celecoxib may have affected metabolites (n = 43) that are involved in several pathways, including the tricarboxylic acid cycle, amino acids metabolism pathways, and energy production pathways in cancer cells.

CONCLUSION

Celecoxib may possess potential therapeutic utility for breast cancer treatment as monotherapy or in combination therapy. The reported metabolic changes taking place upon celecoxib treatment may shed light on possible molecular targets mediating the antiproliferative activity of celecoxib in an independent manner of its COX-2 inhibition.

Metabolomics Profiling of Cystic Renal Disease towards Biomarker Discovery

Simple Summary

Cystic renal disease (CRD) is a group of diseases characterized by abnormal sacs, or cysts, in the kidneys. CRD can be detected using certain imaging modalities (i.e., ultrasound). Patients with CRD might be symptoms-free, while others can show symptoms long after cysts development. Although these cysts represent structural changes, we hypothesized that they have an underlying biochemical alteration. If so, this would open the floor for potential biomarker discovery, which would aid in CRD diagnosis and, possibly, treatment. On that basis, this study focuses on identifying biomarkers for CRD. To achieve that, we employed a metabolomics-based approach to identify intermediate molecules inside the cells that are byproducts of biochemical reactions. We used dry blood spots and serum samples of CRD patients and healthy controls to study the differences in their metabolomic profile. Our results suggest that certain metabolites, including uridine diphosphate, cystine-5-diphosphate, and morpholine, are potential biomarkers for CRD. The affected biochemical pathways in CRD include aminoacyl-tRNA biosynthesis, purine, pyrimidine, glutathione, TCA cycle, and some amino acid metabolism. These preliminary results could be the starting point for possible diagnostic and therapeutic approaches for CRD in the future.

Abstract

Cystic renal disease (CRD) comprises a heterogeneous group of genetic and acquired disorders. The cystic lesions are detected through imaging, either incidentally or after symptoms develop, due to an underlying disease process. In this study, we aim to study the metabolomic profiles of CRD patients for potential disease-specific biomarkers using unlabeled and labeled metabolomics using low and high-resolution mass spectrometry (MS), respectively. Dried-blood spot (DBS) and serum samples, collected from CRD patients and healthy controls, were analyzed using the unlabeled and labeled method. The metabolomics profiles for both sets of samples and groups were collected, and their data were processed using the lab’s standard protocol. The univariate analysis showed (FDR p < 0.05 and fold change 2) was significant to show a group of potential biomarkers for CRD discovery, including uridine diphosphate, cystine-5-diphosphate, and morpholine. Several pathways were involved in CRD patients based on the metabolic profile, including aminoacyl-tRNA biosynthesis, purine and pyrimidine, glutathione, TCA cycle, and some amino acid metabolism (alanine, aspartate and glutamate, arginine and tryptophan), which have the most impact. In conclusion, early CRD detection and treatment is possible using a metabolomics approach that targets alanine, aspartate, and glutamate pathway metabolites.

Effective removal of heavy metals from industrial effluent wastewater by a multi metal and drug resistant Pseudomonas aeruginosa strain RA-14 using integrated sequencing batch reactor

Sequencing batch reactor (SBR) is useful in removal of both non-biodegradable and biodegradable contaminants from wastewater. The main aim of the present investigation was to evaluate the potential of biocatalyst strain RA-14 on heavy metal removal under SBR. The selected strain was screened from the soil sediment contaminated with heavy metals. It was able to survive at different (Hg²⁺, Pb²⁺, Zn²⁺, Cu²⁺, Cd²⁺ and Ni²⁺) heavy metals (>500 ppm). The bacterial strain RA-14 showed maximum bioaccumulation potential than other strains. Heavy metal resistance patterns of Pb²⁺ > Cu² > Cd²⁺ > Hg²⁺, Ni²⁺ and Zn² was observed. Strain RA-14 was resistant to penicillin-G, nalidixic acid, ceftazidime, cefotaxime, kanamycin and ampicillin. The results revealed that bioaccumulation activities were improved at pH 7.0 (83.2 ± 1.8%), 40 °C (89.34 ± 3%) and affected at higher pH values and temperature. The results showed that contact time and initial Lead concentration was also affected Lead accumulation. The heavy metal tolerant strain RA-14 was further investigated towards heavy metal removal in SBR. Heavy metal was removed in SBR within 10 h of hydraulic retention time. Heavy metal removal was high at 2 mg/L (0.33 mg/L Cu²⁺, 0.33 mg/L Hg²⁺, 0.33 mg/L Pb²⁺, 0.33 mg/L Zn²⁺, 0.33 mg/L Cd²⁺ and 0.33 mg/L Ni²⁺) heavy metals. Total nitrogen, biological oxygen demand (BOD) and chemical oxygen demand (COD) of treated water in SBR was removed and the removal efficacy was 91.3 ± 2.1%, 97.6 ± 3.3%, and 94.3 ± 4.4%, respectively in 10 h hydraulic retention time. However, the efficiency of BOD, COD and total nitrogen content removal was decreased, due to the reduced metabolic process of bacteria after 10 h. The SBR reactor proved to be an efficient method for the treatment of various heavy metals from the wastewater.

A Metabolic Pattern in Healthy Subjects Given a Single Dose of Metformin: A Metabolomics Approach

Metformin is a widely prescribed medication for the treatment of type 2 diabetes mellitus (T2DM). It possesses effective roles in various disorders, including cancer, dyslipidemia, and obesity. However, the underlying mechanisms of metformin's multiple benefits are not fully understood. Herein, a mass spectrometry-based untargeted metabolomics approach was used to investigate the metabolic changes associated with the administration of a single dose of metformin in the plasma of 26 healthy subjects at five-time points; pre-dose, before the maximum concentration of metformin (C_max), C_max, after C_max, and 36 h post-dose. A total of 111 metabolites involved in various biochemical processes were perturbed, with branched-chain amino acid (BCAA) being the most significantly altered pathway. Additionally, the Pearson similarity test revealed that 63 metabolites showed a change in their levels dependent on metformin level. Out of these 63, the level of 36 metabolites was significantly altered by metformin. Significantly altered metformin-dependent metabolites, including hydroxymethyl uracil, propionic acid, glycerophospholipids, and eicosanoids, pointed to fundamental biochemical processes such as lipid network signaling, energy homeostasis, DNA lesion repair mechanisms, and gut microbiota functions that could be linked to the multiple beneficial roles of metformin. Thus, the distinctive metabolic pattern linked to metformin administration can be used as a metabolic signature to predict the potential effect and mechanism of actions of new chemical entities during drug development.

Obesity Connected Metabolic Changes in Type 2 Diabetic Patients Treated With Metformin

Metformin is widely used in the treatment of Type 2 Diabetes Mellitus (T2DM). However, it is known to have beneficial effects in many other conditions, including obesity and cancer. In this study, we aimed to investigate the metabolic effect of metformin in T2DM and its impact on obesity. A mass spectrometry (MS)-based metabolomics approach was used to analyze samples from two cohorts, including healthy lean and obese control, and lean as well as obese T2DM patients on metformin regimen in the last 6 months. The results show a clear group separation and sample clustering between the study groups due to both T2DM and metformin administration. Seventy-one metabolites were dysregulated in diabetic obese patients (30 up-regulated and 41 down-regulated), and their levels were unchanged with metformin administration. However, 30 metabolites were dysregulated (21 were up-regulated and 9 were down-regulated) and then restored to obese control levels by metformin administration in obese diabetic patients. Furthermore, in obese diabetic patients, the level of 10 metabolites was dysregulated only after metformin administration. Most of these dysregulated metabolites were dipeptides, aliphatic amino acids, nucleic acid derivatives, and urea cycle components. The metabolic pattern of 62 metabolites was persistent, and their levels were affected by neither T2DM nor metformin in obesity. Interestingly, 9 metabolites were significantly dysregulated between lean and obese cohorts due to T2DM and metformin regardless of the obesity status. These include arginine, citrulline, guanidoacetic acid, proline, alanine, taurine, 5-hydroxyindoleacetic acid, and 5-hydroxymethyluracil. Understanding the metabolic alterations taking place upon metformin treatment would shed light on possible molecular targets of metformin, especially in conditions like T2DM and obesity.

Tissue Lipidomic Alterations Induced by Prolonged Dexamethasone Treatment

Dexamethasone is a synthetic glucocorticoid medication vastly used to treat abnormal immune responses and inflammation. Although the medication is well-established in the medical community, the prolonged treatment with high dosages of dexamethasone may lead to severe adverse effects through mechanisms that are not yet well-known. Lipids are a large class of hydrophobic molecules involved in energy storage, signaling, modulation of gene expression, and membranes. Hence, untargeted lipidomics may help unravel the biochemical alterations following prolonged treatment with high dosages of dexamethasone. We performed comprehensive lipidomic analyses of brain, heart, kidney, liver, and muscle samples obtained from rats that were treated with intramuscular injections of dexamethasone for 14 weeks compared to healthy controls. The employed methodology and statistical analysis showed that phosphatidic acids, glycerophospholipids, plasmalogens, and fatty acids are deeply affected by prolonged use of the medication. Brain tissue was only mildly affected, but skeletal muscle showed a strong accumulation of lipids that may be correlated with alterations in the energy metabolism, myopathy, and oxidative processes. This work provides new insights into the mechanisms of action and adverse effects for one of the most commonly prescribed class of drugs in the world.

Distinctive metabolic profiles between Cystic Fibrosis mutational subclasses and lung function

INTRODUCTION

Cystic fibrosis (CF) is a lethal multisystemic disease of a monogenic origin with numerous mutations. Functional defects in the cystic fibrosis transmembrane conductance receptor (CFTR) protein based on these mutations are categorised into distinct classes having different clinical presentations and disease severity.

OBJECTIVES

The present study aimed to create a comprehensive metabolomic profile of altered metabolites in patients with CF, among different classes and in relation to lung function.

METHODS

A chemical isotope labeling liquid chromatography-mass spectrometry metabolomics was used to study the serum metabolic profiles of young and adult CF (n = 39) patients and healthy controls (n = 30). Comparisons were made at three levels, CF vs. controls, among mutational classes of CF, between CF class III and IV, and correlated the lung function findings.

RESULTS

A distinctive metabolic profile was observed in the three analyses. 78, 20, and 13 significantly differentially dysregulated metabolites were identified in the patients with CF, among the different classes and between class III and IV, respectively. The significantly identified metabolites included amino acids, di-, and tri-peptides, glutathione, glutamine, glutamate, and arginine metabolism. The top significant metabolites include 1-Aminopropan-2-ol, ophthalmate, serotonin, cystathionine, and gamma-glutamylglutamic acid. Lung function represented by an above-average FEV1% level was associated with decreased glutamic acid and increased guanosine levels.

CONCLUSION

Metabolomic profiling identified alterations in different amino acids and dipeptides, involved in regulating glutathione metabolism. Two metabolites, 3,4-dihydroxymandelate-3-O-sulfate and 5-Aminopentanoic acid, were identified in common between the three anlayses and may represent as highly sensitive biomarkers for CF.

Distinctive Metabolomics Patterns Associated With Insulin Resistance and Type 2 Diabetes Mellitus

Obesity is associated with an increased risk of insulin resistance (IR) and type 2 diabetes mellitus (T2DM) which is a multi-factorial disease associated with a dysregulated metabolism and can be prevented in pre-diabetic individuals with impaired glucose tolerance. A metabolomic approach emphasizing metabolic pathways is critical to our understanding of this heterogeneous disease. This study aimed to characterize the serum metabolomic fingerprint and multi-metabolite signatures associated with IR and T2DM. Here, we have used untargeted high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) to identify candidate biomarkers of IR and T2DM in sera from 30 adults of normal weight, 26 obese adults, and 16 adults newly diagnosed with T2DM. Among the 3633 peak pairs detected, 62% were either identified or matched. A group of 78 metabolites were up-regulated and 111 metabolites were down-regulated comparing obese to lean group while 459 metabolites were up-regulated and 166 metabolites were down-regulated comparing T2DM to obese groups. Several metabolites were identified as IR potential biomarkers, including amino acids (Asn, Gln, and His), methionine (Met) sulfoxide, 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, serotonin, L-2-amino-3-oxobutanoic acid, and 4,6-dihydroxyquinoline. T2DM was associated with dysregulation of 42 metabolites, including amino acids, amino acids metabolites, and dipeptides. In conclusion, these pilot data have identified IR and T2DM metabolomics panels as potential novel biomarkers of IR and identified metabolites associated with T2DM, with possible diagnostic and therapeutic applications. Further studies to confirm these associations in prospective cohorts are warranted.

Lipidome Alterations Induced by Cystic Fibrosis, CFTR Mutation, and Lung Function

Cystic fibrosis is a genetic pathology characterized by abnormal accumulation of mucus in the respiratory, gastrointestinal, and reproductive tracts, caused by mutations in the CFTR gene. Although the classical presentation of the condition is well known, there is still a need for a better characterization of metabolic alterations related to cystic fibrosis and different genotypic mutations. We employed untargeted, comprehensive lipidomics of blood serum samples to investigate alterations in the lipid metabolism related to the pathology, mutation classes, and lung function decline. Six unique biomarker candidates were able to independently differentiate diseased individuals from healthy controls with excellent performance. Cystic fibrosis patients showed dyslipidemia for most lipid subclasses, with significantly elevated odd-chain and polyunsaturated fatty acyl lipids. Phosphatidic acids and diacylglycerols were particularly affected by different genotypic mutation classes. We selected a biomarker panel composed of four lipids, including two ceramides, one sphingomyelin, and one fatty acid, which correctly classified all validation samples from classes III and IV. A biomarker panel of five oxidized lipids was further selected to differentiate patients with reduced lung function, measured as predicted FEV1%. Our results indicate that cystic fibrosis is deeply related to lipid metabolism and provide new clues for the investigation of the disease mechanisms and therapeutic targets.

Serum-Based Proteomics Profiling in Adult Patients with Cystic Fibrosis

Cystic fibrosis (CF), the most common lethal autosomal recessive disorder among Caucasians, is caused by mutations in the CF transmembrane conductance regulator (CFTR) chloride channel gene. Despite significant advances in the management of CF patients, novel disease-related biomarkers and therapies must be identified. We performed serum proteomics profiling in CF patients (n = 28) and healthy subjects (n = 10) using the 2D-DIGE MALDI-TOF proteomic approach. Out of a total of 198 proteins identified, 134 showed a statistically significant difference in abundance and a 1.5-fold change (ANOVA, p < 0.05), including 80 proteins with increased abundance and 54 proteins with decreased abundance in CF patients. A multiple reaction monitoring-mass spectrometry analysis of six differentially expressed proteins identified by a proteomic approach (DIGE-MALD-MS) showed a significant increase in C3 and CP proteins and a decrease in APOA1, Complement C1, Hp, and RBP4proteins compared with healthy controls. Fifteen proteins were identified as potential biomarkers for CF diagnosis. An ingenuity pathway analysis of the differentially regulated proteins indicates that the central nodes dysregulated in CF subjects involve pro-inflammatory cytokines, ERK1/2, and P38 MAPK, which are primarily involved in catalytic activities and metabolic processes. The involved canonical pathways include those related to FXR/RXR, LXR/RXR, acute phase response, IL12, nitric oxide, and reactive oxygen species in macrophages. Our data support the current efforts toward augmenting protease inhibitors in patients with CF. Perturbations in lipid and vitamin metabolism frequently observed in CF patients may be partly due to abnormalities in their transport mechanism.

Targeted Metabolomics Analysis on Obstructive Sleep Apnea Patients after Multilevel Sleep Surgery

BACKGROUND

Obstructive sleep apnea (OSA) is caused by partial or complete obstruction of the upper airways. Corrective surgeries aim at removing obstructions in the nasopharynx, oropharynx, and hypopharynx. OSA is associated with an increased risk of various metabolic diseases. Our objective was to evaluate the effect of surgery on the plasma metabolome.

METHODS

This study included 39 OSA patients who underwent Multilevel Sleep Surgery (MLS). Clinical and anthropometric measures were taken at baseline and five months after surgery.

RESULTS

The mean Apnea-Hypopnea Index (AHI) significantly dropped from 22.0 ± 18.5 events/hour to 8.97 ± 9.57 events/hour (p-Value < 0.001). Epworth's sleepiness Score (ESS) dropped from 12.8 ± 6.23 to 2.95 ± 2.40 (p-Value < 0.001), indicating the success of the surgery in treating OSA. Plasma levels of metabolites, phosphocholines (PC) PC.41.5, PC.42.3, ceremide (Cer) Cer.44.0, and triglyceride (TG) TG.53.6, TG.55.6 and TG.56.8 were decreased (p-Value < 0.05), whereas lysophosphatidylcholines (LPC) 20.0 and PC.39.3 were increased (p-Value < 0.05) after surgery.

CONCLUSION

This study highlights the success of MLS in treating OSA. Treatment of OSA resulted in an improvement of the metabolic status that was characterized by decreased TG, PCs, and Cer metabolites after surgery, indicating that the success of the surgery positively impacted the metabolic status of these patients.

Anti-VCAM-1 and Anti-IL4Rα Aptamer-Conjugated Super Paramagnetic Iron Oxide Nanoparticles for Enhanced Breast Cancer Diagnosis and Therapy

The surface protein overexpressed on cancer cells can be used as biomarkers for early detection of specific diseases. Anti-VCAM-1 and anti-IL4Rα DNA aptamers specific to VCAM-1 and IL4Rα receptors that are overexpressed in 4T1 tumor-bearing mice could be used as potential biomarker for both diagnostic and therapeutic applications in cancer biology. Cell Viability and luciferase assay of 4T1-Luc2 cancer cells in the presence of anti-VCAM-1 ssDNA or anti-IL4Rα RNA aptamers was assessed by monitoring the changes in the absorbance and the fluorescence of Alamar blue dye. The aptamer-conjugated SPIO magnetic beads, used for the selective targeting to tumor sites, were monitored using noninvasive MRI and Bioluminescence imaging (BLI). Cell viability and luciferase assays showed that both anti-VCAM-1 and anti-IL4Rα aptamers favor the depletion of cancer cells and limit tumor progression. Microscopic analyses confirmed that the target specific aptamers significantly trigger tumor cell apoptosis and limit cancer cell growth in vitro. The intravenous injection of SPIO nanoparticle-conjugated aptamers were further confirmed using noninvasive MRI and Bioluminescence imaging. Anti-VCAM1 and anti-IL4Rα aptamers, specific to VCAM-1 and IL4Rα receptors overexpressed in 4T1-Luc2 tumor-bearing mice, were used as diagnostic and therapeutic tools.

Dried Blood Spot-Based Metabolomic Profiling in Adults with Cystic Fibrosis

Mucoviscidosis of the respiratory, gastrointestinal, and genitourinary tracts is the major pathology in patients with cystic fibrosis (CF), a lethal monogenic panethnic and multisystemic disease most commonly identified in Caucasians. Currently, the measurement of immuno reactive trypsinogen in dry blood spots (DBSs) is the gold-standard method for initial newborn screening for CF, followed by targeted CF transmembrane regulator (CFTR) mutation analysis, and ultimate confirmation with abnormally elevated sweat chloride. Previous metabolomics studies in patients with CF reported on different biomarkers such as breath 2-aminoacetophenone produced during acute and chronic infection in human tissues, including the lungs of CF patients. Herein, we used liquid and gas chromatography-mass spectrometry-based targeted metabolomics profiling to identify potentially reliable, sensitive, and specific biomarkers in DBSs collected from 69 young and adult people including CF patients (n = 39) and healthy control (n = 30). A distinctive metabolic profile including 26 significantly differentially expressed metabolites involving amino acids, glycolysis, mitochondrial and peroxisomal metabolism, and sorbitol pathways was identified. Specifically, the osmolyte (sorbitol) was remarkably downregulated in CF patients compared to healthy controls indicating perturbation in the sorbitol pathway, which may be responsible for the mucoviscidosis seen in patients with CF. The significance of our findings is supported by the clinical utility of inhaled mannitol and hypertonic saline in patients with CF. The systemic administration of sorbitol in such patients may confer additional benefits beyond the respiratory system, especially in those with misfolded CFTR proteins.

Selection, characterization, and electrochemical biosensing application of DNA aptamers for sepiapterin

Sepiapterin reductase deficiency (SR) is a rare inborn disorder of neurotransmitter metabolism. The early diagnosis of SR disease should be achieved through the determination of the sepiapterin level in body fluids of suspected patients. Here, we report the selection, identification, and characterization of DNA aptamers against sepiapterin. The aptamer selection was achieved via the systematic evolution of ligand by the exponential enrichment technique. After ten rounds of selection, high-affinity aptamers were identified. The binding affinities of the selected aptamers were evaluated using fluorescence binding assays showing dissociation constants ranging from 37.3 to 79.0 nM. The highest affinity aptamer was then integrated into a competitive electrochemical biosensor. The biosensor achieved outstanding sensitivity with a detection limit of 0.8 pg/ml which was much lower than the reported chromatographic method for sepiapterin quantification. The aptasensor has also shown a high degree of selectivity against the closely-related compound. The aptasensor was then challenged by detecting the sepiapterin in spiked serum samples where a good recovery percentage was achieved.

Caveolin-1 Y14 phosphorylation suppresses tumor growth while promoting invasion

Caveolin-1 is a transmembrane protein with both tumor promoter and suppressor functions that remain poorly understood. Cav1 phosphorylation by Src kinase on tyrosine 14 is closely associated with focal adhesion dynamics and tumor cell migration, however the role of pCav1 in vivo in tumor progression remains poorly characterized. Herein, we expressed phosphomimetic Y14D, wild type, and non-phosphorylatable Y14F forms of Cav1 in MDA-MB-435 cancer cells. Expression of Cav1Y14D reduced cell proliferation and induced the TP53 tumor suppressor. Ectopic expression in MDA-MB-435 cells of Y14 phosphorylatable Cav1 was required for induction of TP53 in response to oxidative stress. Cav1Y14D promotes an apparent reversal of the Warburg effect and markedly inhibited tumor growth in vivo. However, Cav1 induced pseudopodial recruitment of glycolytic enzymes, and time-lapse intravital imaging showed increased invadopodia protrusion and extravasation into blood vessels for Cav1WT and Y14D but not for Y14F. Our results suggest that Cav1 Y14 phosphorylation levels play a role in the conflicting demands on metabolic resources associated with cancer cell proliferation versus motility.

Metabolomics Distinguishes DOCK8 Deficiency from Atopic Dermatitis: Towards a Biomarker Discovery

Bi-allelic mutations in the dedicator of cytokinesis 8 (DOCK8) are responsible for a rare autosomal recessive primary combined immunodeficiency syndrome, characterized by atopic dermatitis, elevated serum Immunoglobulin E (IgE) levels, recurrent severe cutaneous viral infections, autoimmunity, and predisposition to malignancy. The molecular link between DOCK8 deficiency and atopic skin inflammation remains unknown. Severe atopic dermatitis (AD) and DOCK8 deficiency share some clinical symptoms, including eczema, eosinophilia, and increased serum IgE levels. Increased serum IgE levels are characteristic of, but not specific to allergic diseases. Herein, we aimed to study the metabolomic profiles of DOCK8-deficient and AD patients for potential disease-specific biomarkers using chemical isotope labeling liquid chromatography-mass spectrometry (CIL LC-MS). Serum samples were collected from DOCK8-deficient (n = 10) and AD (n = 9) patients. Metabolomics profiling using CIL LC-MS was performed on patient samples and compared to unrelated healthy controls (n = 33). Seven metabolites were positively identified, distinguishing DOCK8-deficient from AD patients. Aspartic acid and 3-hydroxyanthranillic acid (3HAA, a tryptophan degradation pathway intermediate) were up-regulated in DOCK8 deficiency, whereas hypotaurine, leucyl-phenylalanine, glycyl-phenylalanine, and guanosine were down-regulated. Hypotaurine, 3-hydroxyanthranillic acid, and glycyl-phenyalanine were identified as potential biomarkers specific to DOCK8 deficiency. Aspartate availability has been recently implicated as a limiting metabolite for tumour growth and 3HAA; furthermore, other tryptophan metabolism pathway-related molecules have been considered as potential novel targets for cancer therapy. Taken together, perturbations in tryptophan degradation and increased availability of aspartate suggest a link of DOCK8 deficiency to oncogenesis. Additionally, perturbations in taurine and dipeptides metabolism suggest altered antixidation and cell signaling states in DOCK8 deficiency. Further studies examining the mechanisms underlying these observations are necessary.

Exposures and Health Effects of Bioaerosols in Seafood Processing Workers - a Position Statement

Occupational hazards exist in the processing of seafood both in land-based facilities as well as on board vessels. Recent findings on occupational injury and respiratory health risks among seafood processing workers were presented and discussed at the IFISH5 conference. Particular emphasis was put on the challenges that im/migrant workers encounter, the greater risks onboard factory vessels, especially where processing machinery are retrofitted to older vessels not primarily designed for this purpose, and the difficulties in assessing and preventing bioaerosol exposures and associated respiratory health risks despite recent advances in characterising agents responsible for allergic and non-allergic reactions. Based on appraisal of existing knowledge in the published literature and new findings presented at the conference, recommendations for immediate actions as well as for future research have been proposed. Among these include the importance of improving extraction ventilation systems, optimising machinery performance, enclosure of bioaerosol sources, improved work organization, and making special efforts to identify and support the needs of im/migrant workers to ensure they also benefit from such improvements. There is a need for studies that incorporate longitudinal study designs, have improved exposure and diagnostic methods, and that address seafood processing in countries with high seafood processing activities such as Asia and those that involve im/migrant workers worldwide. The medical and scientific community has an important role to play in prevention but cannot do this in isolation and should cooperate closely with hygienists, engineers, and national and international agencies to obtain better health outcomes for workers in the seafood industry.

Proteomic Analysis of Morphologically Changed Tissues after Prolonged Dexamethasone Treatment

Prolonged dexamethasone (Dex) administration leads to serious adverse and decrease brain and heart size, muscular atrophy, hemorrhagic liver, and presence of kidney cysts. Herein, we used an untargeted proteomic approach using liquid chromatography-tandem mass spectrometry (LC-MS/MS) for simultaneous identification of changes in proteomes of the major organs in Sprague–Dawley (SD rats post Dex treatment. The comparative and quantitative proteomic analysis of the brain, heart, muscle, liver, and kidney tissues revealed differential expression of proteins (n = 190, 193, 39, 230, and 53, respectively) between Dex-treated and control rats. Functional network analysis using ingenuity pathway analysis (IPA revealed significant differences in regulation of metabolic pathways within the morphologically changed organs that related to: (i) brain—cell morphology, nervous system development, and function and neurological disease; (ii) heart—cellular development, cellular function and maintenance, connective tissue development and function; (iii) skeletal muscle—nucleic acid metabolism, and small molecule biochemical pathways; (iv) liver—lipid metabolism, small molecular biochemistry, and nucleic acid metabolism; and (v) kidney—drug metabolism, organism injury and abnormalities, and renal damage. Our study provides a comprehensive description of the organ-specific proteomic profilesand differentially altered biochemical pathways, after prolonged Dex treatement to understand the molecular basis for development of side effects.

Metabolomics toward personalized medicine

Metabolomics, which is the metabolites profiling in biological matrices, is a key tool for biomarker discovery and personalized medicine and has great potential to elucidate the ultimate product of the genomic processes. Over the last decade, metabolomics studies have identified several relevant biomarkers involved in complex clinical phenotypes using diverse biological systems. Most diseases result in signature metabolic profiles that reflect the sums of external and internal cellular activities. Metabolomics has a major role in clinical practice as it represents >95% of the workload in clinical laboratories worldwide. Many of these metabolites require different analytical platforms, such as Nuclear Magnetic Resonance (NMR), Mass Spectrometry (MS), and Ultra Performance Liquid Chromatography (UPLC), while many clinically relevant metabolites are still not routinely amenable to detection using currently available assays. Combining metabolomics with genomics, transcriptomics, and proteomics studies will result in a significantly improved understanding of the disease mechanisms and the pathophysiology of the target clinical phenotype. This comprehensive approach will represent a major step forward toward providing precision medical care, in which individual is accounted for variability in genes, environment, and personal lifestyle. In this review, we compare and evaluate the metabolomics strategies and studies that focus on the discovery of biomarkers that have "personalized" diagnostic, prognostic, and therapeutic value, validated for monitoring disease progression and responses to various management regimens.