Metabolomics Panel Associated with Cystic Fibrosis-Related Diabetes toward Biomarker Discovery.

The most prevalent comorbidity among cystic fibrosis (CF) patients is cystic fibrosis-related diabetes (CFRD). CFRD has been linked to one of the worse clinical outcomes and a higher mortality. Improved clinical results have been related to earlier diagnosis and treatment of CFRD. Therefore, the present study aimed to investigate the metabolome of human serum of patients with CFRD. This might aid in identifying novel biomarkers linked with the pathophysiology of CFRD and its diagnosis. The liquid chromatography-high-resolution mass spectrometry (LC-HRMS) metabolomics approach was utilized for serum samples from patients with CF (n = 36) and healthy controls (n = 36). Nine patients in the CF group had CFRD, and 27 were non-CFRD patients (nCFRD). A total of 2328 metabolites were significantly altered in CF compared with the healthy control. Among those, 799 significantly dysregulated metabolites were identified between CFRD and nCFRD. Arachidonic acid (AA), ascorbate, and aldarate metabolism were the most common metabolic pathways dysregulated in CF. l-Homocysteic acid (l-HCA) levels were significantly reduced in CF and CFRD compared to the control and nCFRD, respectively. In addition, gamma-glutamylglycine and l-5-hydroxytryptophan (5-HTP) had the highest discrimination between CFRD and nCFRD with AUC (0.716 and 0.683, respectively). These biomarkers might serve as diagnostic biomarkers and aid in understanding potential metabolic changes linked to CF and CFRD.

Proteomics of Penicillium chrysogenum for a Deeper Understanding of Lead (Pb) Metal Bioremediation.

Penicillium chrysogenum (P. chrysogenum), a ubiquitous filamentous fungus, has demonstrated remarkable potential in the bioremediation of lead-contaminated environments. Its inherent tolerance and bioaccumulation capacity for lead (Pb), coupled with its relatively rapid growth rate, make it an attractive candidate for bioremediation applications. This study aims to identify the proteomic changes in P. chrysogenuminduced by Pb metal stress and unravel the roles of identified proteins in molecular mechanisms and cellular responses. Untargeted proteomic analysis 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-MS). This study reported the identification of 43 statistically significant proteins (24 upregulated and 19 downregulated, ANOVA, p ≤ 0.05; fold change ≥1.5) in P. chrysogenum as a consequence of Pb treatment. Proteins were grouped according to their function into 18 groups from which 13 proteins were related to metabolism, 11 were related to cellular process and signaling, and 19 proteins were related to information storage and processing. The current study is considered the first report about the proteomics study of P. chrysogenum under Pb stress conditions, where upregulated proteins could better explain the mechanism of tolerance and Pb toxicity removal. Our research has provided a thorough understanding of the molecular and cellular processes involved in fungal-metal interactions, paving the way for the development of innovative molecular markers for heavy metal myco-remediation. To the best of our knowledge, this study of P. chrysogenum provides valuable insights toward growing research in comprehending the metal-microbe interactions. This will facilitate development of novel molecular markers for metal bioremediation.

Plasma-based proteomic profiling identifies the distinct regulation of proteins in hyperplasia and endometrial cancer.

BACKGROUND: Among gynaecological malignancies, endometrial cancer (EC) is the most prevalent type of uterine cancer affecting women. This study explored the proteomic profiles of plasma samples obtained from EC patients, those with hyperplasia (Hy), and a control group (CO). A combination of techniques, such as 2D-DIGE, mass spectrometry, and bioinformatics, including pathway analysis, was used to identify proteins with modified expression levels, biomarkers and their associated metabolic pathways in these groups. METHODS: Thirty-four patients, categorized into three groups-10 with EC, 12 with Hy, and 12 CO-between the ages of 46 and 75 years old were included in the study. Untargeted proteomic analysis was carried out using two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). RESULTS: In all three groups, 114 proteins that were significantly (p ≤ 0.05 and fold change ≥ 1.5) altered were successfully identified using peptide mass fingerprints (PMFs). Compared with those in the control group (CO), the EC samples had 85 differentially expressed proteins (39 upregulated and 46 downregulated), and in the Hy group, 81 proteins were dysregulated (40 upregulated and 41 downregulated) compared to those in the CO group, while 33 proteins exhibited differential regulation (12 upregulated and 21 downregulated) in the EC plasma samples compared to those in the Hy group. Vitamin D binding protein and complement C3 distinguished Hy and EC from CO with the greatest changes in expression. Among the differentially expressed proteins identified, enzymes with catalytic activity represented the largest group (42.9%). In terms of biological processes, most of the proteins were involved in cellular processes (28.8%), followed by metabolic processes (16.7%). STRING analysis for protein interactions revealed that the significantly differentially abundant proteins in the three groups are involved in three main biological processes: signalling of complement and coagulation cascades, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), and plasma lipoprotein assembly, remodelling, and clearance. CONCLUSION: The identified plasma protein markers have the potential to serve as biomarkers for differentiating between EC and Hy, as well as for early diagnosis and monitoring of cancer progression.

Plasma Proteomic Signature of Endometrial Cancer in Patients with Diabetes.

The incidence and mortality of endometrial cancer (EC) have increased in recent years. There is mounting evidence that diabetes may play a role in the greater incidence of EC. The molecular mechanisms of the interaction between type 2 diabetes and EC are not yet clearly understood yet. The present study was undertaken to investigate the plasma proteomics of EC patients with diabetes in comparison to those of EC patients without diabetes. Plasma samples were obtained from age-matched patients (EC diabetic and EC nondiabetic). Untargeted proteomic analysis was carried out using a two-dimensional differential gel electrophoresis coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Of the 33 proteins identified, which significantly differed in the plasma abundance between groups, 17 were upregulated and 16 were downregulated. The majority of the altered proteins are involved in the acute phase reaction, cholesterol metabolism, scavenging of heme from plasma, and plasma lipoprotein assembly and mobilization. α-2-macroglobulin, Ras association domain-containing protein 3, apolipoprotein A-I, α-1B-glycoprotein, and zinc-α-2-glycoprotein were significantly upregulated. The significantly downregulated proteins included haptoglobin, apolipoprotein A-IV, hemopexin, and α-1-antichymotrypsin. The differential expression of proteins found in patients who had EC and diabetes indicated severe disease and a poor prognosis. The protein interaction analysis showed dysregulation of cholesterol metabolism and heme scavenging pathways in these patients.

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.

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.

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.

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.

Transcriptomic and Proteomic Analysis Reveals the Potential Role of RBMS1 in Adipogenesis and Adipocyte Metabolism.

Adipocytes play a critical role in maintaining a healthy systemic metabolism by storing and releasing energy in the form of fat and helping to regulate glucose and lipid levels in the body. Adipogenesis is the process through which pre-adipocytes are differentiated into mature adipocytes. It is a complex process involving various transcription factors and signaling pathways. The dysregulation of adipogenesis has been implicated in the development of obesity and metabolic disorders. Therefore, understanding the mechanisms that regulate adipogenesis and the factors that contribute to its dysregulation may provide insights into the prevention and treatment of these conditions. RNA-binding motif single-stranded interacting protein 1 (RBMS1) is a protein that binds to RNA and plays a critical role in various cellular processes such as alternative splicing, mRNA stability, and translation. RBMS1 polymorphism has been shown to be associated with obesity and type 2 diabetes, but the role of RBMS1 in adipose metabolism and adipogenesis is not known. We show that RBMS1 is highly expressed during the early phase of the differentiation of the murine adipocyte cell line 3T3-L1 and is significantly upregulated in the adipose tissue depots and adipocytes of high-fat-fed mice, implying a possible role in adipogenesis and adipose metabolism. Knockdown of RBMS1 in pre-adipocytes impacted the differentiation process and reduced the expression of some of the key adipogenic markers. Transcriptomic and proteomic analysis indicated that RBMS1 depletion affected the expression of several genes involved in major metabolic processes, including carbohydrate and lipid metabolism. Our findings imply that RBMS1 plays an important role in adipocyte metabolism and may offer novel therapeutic opportunity for metabolic disorders such as obesity and type 2 diabetes.

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 ß-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.

Proteomic Profiling Reveals Cytotoxic Mechanisms of Action and Adaptive Mechanisms of Resistance in Porphyromonas gingivalis: Treatment with Juglans regia and Melaleuca alternifolia.

The increasing trend in the rise of antibiotic-resistant bacteria pushes research to discover new efficacious antibacterial agents from natural and synthetic sources. Porphyromonas gingivalis is a well-known bacterium commonly known for causing periodontal disease, and it is associated with the pathogenesis of life-changing systemic conditions such as Alzheimer's. Proteomic research can be utilized to test new antibacterial drugs and understand the adaptive resistive mechanisms of bacteria; hence, it is important in the drug discovery process. The current study focuses on identifying the antibacterial effects of Juglans regia (JR) and Melaleuca alternifolia (MA) on P. gingivalis and uses proteomics to identify modes of action while exploring its adaptive mechanisms. JR and MA extracts were tested for antibacterial efficacy using the agar well diffusion assay. A proteomic study was conducted identifying upregulated and downregulated proteins compared to control by 2D-DIGE analysis, and proteins were identified using MADLI-TOF/MS. The bacterial inhibition for JR was 20.14 ± 0.2, and that for MA was 19.72 ± 0.5 mm. Out of 88 differentially expressed proteins, there were 17 common differentially expressed proteins: 10 were upregulated and 7 were downregulated in both treatments. Among the upregulated proteins were Arginine-tRNA ligase, ATP-dependent Clp protease proteolytic, and flavodoxins. In contrast, down-regulated proteins were ATP synthase subunit alpha and quinone, among others, which are known antibacterial targets. STRING analysis indicated a strong network of interactions between differentially expressed proteins, mainly involved in protein translation, post-translational modification, energy production, metabolic pathways, and protein repair and degradation. Both extracts were equi-efficacious at inhibiting P. gingivalis and displayed some overlapping proteomic profiles. However, the MR extract had a greater fold change in its profile than the JA extract. Downregulated proteins indicated similarity in the mode of action, and upregulated proteins appear to be related to adaptive mechanisms important in promoting repair, growth, survival, virulence, and resistance. Hence, both extracts may be useful in preventing P. gingivalis-associated conditions. Furthermore, our results may be helpful to researchers in identifying new antibiotics which may offset these mechanisms of resistance.

Urinary Proteome Differences in Patients with Type 2 Diabetes Pre and Post Liraglutide Treatment.

Diabetes mellitus is a chronic multisystem disease with a high global prevalence. The glucagon-like peptide-1 (GLP-1) receptor agonist liraglutide is known to lower glucose levels and reduce weight. However, the mechanisms underlying the benefits of liraglutide treatment in patients with type 2 diabetes mellitus (T2DM) remain unclear. Twelve male patients with T2DM (pre and post liraglutide treatment) and HbA1c between 8% and 11% were recruited. In the present study, a two-dimensional difference gel electrophoresis (2D-DIGE) matrix-assisted laser desorption/ionization-time of flight (MALDI TOF) mass spectrometric approach combined with bioinformatics and network pathway analysis was used to explore the urine proteomic profile. The mean age of the patients was 52.4 ± 7.5 years. After treatment with liraglutide, a statistically significant change (p < 0.006) was observed in HbA1c with no significant changes in body weight or markers of dyslipidemia. Two-dimensional difference gel electrophoresis identified significant changes (≥1.5-fold change, ANOVA, p ≤ 0.05) in 32 proteins (4 down- and 28 upregulated) in liraglutide post treatment compared to the pre-treatment state. Albumin, serotransferrin, metallothionein-2 (MT-2), and keratins K1 and K10 were found to be upregulated after liraglutide treatment. The patients showed significant improvement in glycemic control after the 12-week treatment with liraglutide. The renoprotective effect of liraglutide may be linked to the increased urinary abundance of MT-2 and the decreased abundance of zinc alpha 2-glycoprotein (ZAG) and Alpha-1 antitrypsin (α1-AT). More studies are needed to elucidate the molecular mechanisms behind the renoprotective effects of liraglutide.

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.

Lipids Alterations Associated with Metformin in Healthy Subjects: An Investigation Using Mass Spectrometry Shotgun Approach.

Metformin is an orally effective insulin-sensitizing drug widely prescribed for treating type 2 diabetes mellitus (T2DM). Metformin has been reported to alter lipid metabolism. However, the molecular mechanisms behind its impact on lipid metabolism remain partially explored and understood. In the current study, mass spectrometry-based lipid profiling was used to investigate the lipidomic changes in the serum of 26 healthy individuals after a single-dose intake of metformin. Samples were analyzed at five-time points: preadministration, before the maximum concentration of metformin (Cmax), Cmax, after Cmax, and 36 h post-administration. A total of 762 molecules were significantly altered between the five-time points. Based on a comparison between baseline level and Cmax, metformin significantly increased and decreased the level of 33 and 192 lipids, respectively (FDR ≤ 0.05 and fold change cutoff of 1.5). The altered lipids are mainly involved in arachidonic acid metabolism, steroid hormone biosynthesis, and glycerophospholipid metabolism. Furthermore, several lipids acted in an opposed or similar manner to metformin levels and included fatty acyls, sterol lipids, glycerolipids, and glycerophospholipids. The significantly altered lipid species pointed to fundamental lipid signaling pathways that could be linked to the pleiotropic effects of metformin in T2DM, insulin resistance, polycystic ovary syndrome, cancer, and cardiovascular diseases.

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.

Proteomic profiling of thyroid tissue in patients with obesity and benign diffuse goiter.

Goiter is a term to describe the enlargement of the thyroid gland. The pathophysiology and molecular changes behind development of diffuse benign goiter remains unclear. The present study targeted to identify and describe the alterations in the thyroid tissue proteome from patients (obese euthyroid) with benign diffuse goiter (BDG) using proteomics approach. Thyroid tissue samples, from 7 age and sex matched, patients with BDG and 7 controls were obtained at the time of surgery. An untargeted proteomic analysis of the thyroid tissue was performed out utilizing two-dimensional difference (2D-DIGE) in gel electrophoresis followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for identification of the proteins. Progenesis software was used to identify changes in expression of tissue proteins and found statistically significant differences in abundance in a total of 90 proteins, 46 up and 44 down (1.5-fold change, ANOVA, p ≤ 0.05) in BDG compared to the control group. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) identified dysregulation of signalling pathways linked to ERK1/2, Glutathione peroxidase and NADPH oxidase associated to organismal injury and abnormalities, endocrine system disorders and cancer. The thyroid tissue proteome in patients with BDG revealed a significant decrease in thyroglobulin along with dysregulation of glycolysis and an increase in prooxidant peroxidase enzymes. Dysregulation of metabolic pathways related to glycolysis, redox proteins, and the proteins associated with maintaining the cytoskeletal structure of the thyrocytes was also identified.

Genomic, Proteomic, and Phenotypic Spectrum of Novel O-Sialoglycoprotein Endopeptidase Variant in Four Affected Individuals With Galloway-Mowat Syndrome.

Galloway-Mowat syndrome is a rare autosomal recessive disease characterized by a unique combination of renal and neurological manifestations, including early-onset steroid-resistant nephrotic syndrome, microcephaly, psychomotor delay, and gyral abnormalities of the brain. Most patients die during early childhood. Here, we identified a novel homozygous O-sialoglycoprotein endopeptidase (OSGEP) variant, NM_017807.3:c.973C>G (p.Arg325Gly), in four affected individuals in an extended consanguineous family from Saudi Arabia. We have described the detailed clinical characterization, brain imaging results, and muscle biopsy findings. The described phenotype varied from embryonic lethality to early pregnancy loss or death at the age of 9. Renal disease is often the cause of death. Protein modeling of this OSGEP variant confirmed its pathogenicity. In addition, proteomic analysis of the affected patients proposed a link between the KEOPS complex function and human pathology and suggested potential pathogenic mechanisms.