Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

Lipid and metabolic alteration involvement in physiotherapy for chronic nonspecific low back pain

BACKGROUND

Chronic nonspecific low back pain (cNLBP) is a common health problem worldwide, affecting 65-80% of the population and greatly affecting people's quality of life and productivity. It also causes huge economic losses. Manual therapy (MT) and therapeutic exercise (TE) are effective treatment options for cNLBP physiotherapy-based treatment. However, the underlying mechanisms that promote cNLBP amelioration by MT or TE are incompletely understood.

METHODS

Seventeen recruited subjects were randomly divided into an MT group and a TE group. Subjects in the MT group performed muscular relaxation, myofascial release, and mobilization for 20 min during each treatment session. The treatment lasted for a total of six sessions, once every two days. Subjects in the TE group completed motor control and core stability exercises for 30 min during each treatment session. The motor control exercise included stretching of the trunk and extremity muscles through trunk and hip rotation and flexion training. Stabilization exercises consisted of the (1) bridge exercise, (2) single-leg-lift bridge exercise, (3) side bridge exercise, (4) two-point bird-dog position with an elevated contralateral leg and arm, (5) bear crawl exercise, and (6) dead bug exercise. The treatment lasted for a total of six sessions, with one session every two days. Serum samples were collected from subjects before and after physiotherapy-based treatment for lipidomic and metabolomic measurements.

RESULTS

Through lipidomic analysis, we found that the phosphatidylcholine/phosphatidylethanolamine (PC/PE) ratio decreased and the sphingomyelin/ceramide (SM/Cer) ratio increased in cNLBP patients after MT or TE treatment. In addition, eight metabolites enriched in pyrimidine and purine differed significantly in cNLBP patients who received MT treatment. A total of nine metabolites enriched in pyrimidine, tyrosine, and galactose pathways differed significantly in cNLBP patients after TE treatment during metabolomics analysis.

CONCLUSION

Our study was the first to elucidate the alterations in the lipidomics and metabolomics of cNLBP physiotherapy-based treatment and can expand our knowledge of cNLBP physiotherapy-based treatment.

Comprehensive metabolomic characterization of atrial fibrillation

Background

Using human humoral metabolomic profiling, we can discover the diagnostic biomarkers and pathogenesis of disease. The specific characterization of atrial fibrillation (AF) subtypes with metabolomics may facilitate effective and targeted treatment, especially in early stages.

Objectives

By investigating disturbed metabolic pathways, we could evaluate the diagnostic value of biomarkers based on metabolomics for different types of AF.

Methods

A cohort of 363 patients was enrolled and divided into a discovery and validation set. Patients underwent an electrocardiogram (ECG) for suspected AF. Groups were divided as follows: healthy individuals (Control), suspected AF (Sus-AF), first diagnosed AF (Fir-AF), paroxysmal AF (Par-AF), persistent AF (Per-AF), and AF causing a cardiogenic ischemic stroke (Car-AF). Serum metabolomic profiles were determined by gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Metabolomic variables were analyzed with clinical information to identify relevant diagnostic biomarkers.

Results

The metabolic disorders were characterized by 16 cross-comparisons. We focused on comparing all of the types of AF (All-AFs) plus Car-AF vs. Control, All-AFs vs. Car-AF, Par-AF vs. Control, and Par-AF vs. Per-AF. Then, 117 and 94 metabolites were identified by GC/MS and LC-QTOF-MS, respectively. The essential altered metabolic pathways during AF progression included D-glutamine and D-glutamate metabolism, glycerophospholipid metabolism, etc. For differential diagnosis, the area under the curve (AUC) of specific metabolomic biomarkers ranged from 0.8237 to 0.9890 during the discovery phase, and the predictive values in the validation cohort were 78.8–90.2%.

Conclusions

Serum metabolomics is a powerful way to identify metabolic disturbances. Differences in small–molecule metabolites may serve as biomarkers for AF onset, progression, and differential diagnosis.

KATP channel dependent heart multiome atlas

Plasmalemmal ATP sensitive potassium (K_ATP) channels are recognized metabolic sensors, yet their cellular reach is less well understood. Here, transgenic Kir6.2 null hearts devoid of the K_ATP channel pore underwent multiomics surveillance and systems interrogation versus wildtype counterparts. Despite maintained organ performance, the knockout proteome deviated beyond a discrete loss of constitutive K_ATP channel subunits. Multidimensional nano-flow liquid chromatography tandem mass spectrometry resolved 111 differentially expressed proteins and their expanded network neighborhood, dominated by metabolic process engagement. Independent multimodal chemometric gas and liquid chromatography mass spectrometry unveiled differential expression of over one quarter of measured metabolites discriminating the Kir6.2 deficient heart metabolome. Supervised class analogy ranking and unsupervised enrichment analysis prioritized nicotinamide adenine dinucleotide (NAD⁺), affirmed by extensive overrepresentation of NAD⁺ associated circuitry. The remodeled metabolome and proteome revealed functional convergence and an integrated signature of disease susceptibility. Deciphered cardiac patterns were traceable in the corresponding plasma metabolome, with tissue concordant plasma changes offering surrogate metabolite markers of myocardial latent vulnerability. Thus, Kir6.2 deficit precipitates multiome reorganization, mapping a comprehensive atlas of the K_ATP channel dependent landscape.

Integrative Metabolomics, Proteomics and Transcriptomics Analysis Reveals Liver Toxicity of Mesoporous Silica Nanoparticles

As pharmaceutical excipients, mesoporous silica nanoparticles (MSNs) have attracted considerable concern based on potential risks to the public. The impact of MSNs on biochemical metabolism is poorly understood, and few studies have compared the effects of MSNs administered via different routes. To evaluate the hepatotoxicity of MSNs, metabolomics, proteomics and transcriptomic analyses were performed in mice after intravenous (20 mg/kg/d) or oral ad-ministration (200 mg/kg/d) of MSNs for 10 days. Intravenous injection induced significant hepatic injury based on pathological inspection and increased the levels of AST/ALT and the inflammatory factors IL-6, IL-1β and TNF-a. Omics data suggested intravenous administration of MSNs perturbed the following metabolites: succinate, hypoxanthine, GSSG, NADP+, NADPH and 6-phosphogluconic acid. In addition, increases in GPX, SOD3, G6PD, HK, and PFK at proteomic and transcriptomic levels suggested elevation of glycolysis and pentose phosphate pathway, synthesis of glutathione and nucleotides, and antioxidative pathway activity, whereas oxidative phosphorylation, TCA and mitochondrial energy metabolism were reduced. On the other hand, oral administration of MSNs disturbed inflammatory factors and metabolites of ribose-5-phosphate, 6-phosphogluconate, GSSG, and NADP+ associated with the pentose phosphate pathway, glutathione synthesis and oxidative stress albeit to a lesser extent than intravenous injection despite the administration of a ten-fold greater dose. Overall, systematic biological data suggested that intravenous injection of nanoparticles of pharmaceutical excipients substantially affected hepatic metabolism function and induced oxidative stress and inflammation, whereas oral administration exhibited milder effects compared with intravenous injection.

Plasma Metabolomics Reveals Diagnostic Biomarkers and Risk Factors for Esophageal Squamous Cell Carcinoma

Esophageal squamous carcinoma (ESCC) has a high morbidity and mortality rate. Identifying risk metabolites associated with its progression is essential for the early prevention and treatment of ESCC. A total of 373 ESCC, 40 esophageal squamous dysplasia (ESD), and 218 healthy controls (HC) subjects were enrolled in this study. Gas chromatography-mass spectrometry (GC/MS) was used to acquire plasma metabolic profiles. Receiver operating characteristic curve (ROC) and adjusted odds ratio (OR) were calculated to evaluate the potential diagnosis and prediction ability markers. The levels of alpha-tocopherol and cysteine were progressively decreased, while the levels of aminomalonic acid were progressively increased during the various stages (from precancerous lesions to advanced-stage) of exacerbation in ESCC patients. Alpha-tocopherol performed well for the differential diagnosis of HC and ESD/ESCC (AUROC>0.90). OR calculations showed that a high level of aminomalonic acid was not only a risk factor for further development of ESD to ESCC (OR>13.0) but also a risk factor for lymphatic metastasis in ESCC patients (OR>3.0). A low level of alpha-tocopherol was a distinguished independent risk factor of ESCC (OR< 0.5). The panel constructed by glycolic acid, oxalic acid, glyceric acid, malate and alpha-tocopherol performed well in distinguishing between ESD/ESCC from HC in the training and validation set (AUROC>0.95). In conclusion, the oxidative stress function was impaired in ESCC patients, and improving the body’s antioxidant function may help reduce the early occurrence of ESCC.

Defining Acute Coronary Syndrome through Metabolomics

As an emerging platform technology, metabolomics offers new insights into the pathomechanisms associated with complex disease conditions, including cardiovascular diseases. It also facilitates assessing the risk of developing the disease before its clinical manifestation. For this reason, metabolomics is of growing interest for understanding the pathogenesis of acute coronary syndromes (ACS), finding new biomarkers of ACS, and its associated risk management. Metabolomics-based studies in ACS have already demonstrated immense potential for biomarker discovery and mechanistic insights by identifying metabolomic signatures (e.g., branched-chain amino acids, acylcarnitines, lysophosphatidylcholines) associated with disease progression. Herein, we discuss the various metabolomics approaches and the challenges involved in metabolic profiling, focusing on ACS. Special attention has been paid to the clinical studies of metabolomics and lipidomics in ACS, with an emphasis on ischemia/reperfusion injury.

Evaluation of the combined toxicity of multi-walled carbon nanotubes and cadmium on earthworms in soil using multi-level biomarkers

The coexistence of multi-walled carbon nanotubes (MWCNTs) with cadmium (Cd) in soil may cause the combined biological effects, but few study reported about their joint toxic effects on earthworms. Therefore, this study investigated the effects of sub-lethal levels of MWCNTs (10, 50, 100 mg/kg) and Cd (2.0, 10 mg/kg) on earthworms Eisenia fetida for 14 days. The changes in multi-level biomarkers of growth inhibition rate, cytochrome P450 isoenzymes (CYP1A2, 2C9 and 3A4), and small molecular metabolites (metabolomics) were determined. The toxic interaction between MWCNTs and Cd was characterized by the combination of the biomarker integration index (BRI), joint effect index concentration addition index (CAI), and the effect concentration addition index (EAI). The results showed that the single MWCNTs exposure caused insignificant change in most biomarkers, while the combined exposure of MWCNTs (50-100 mg/kg) and 10 mg/kg Cd led to significant changes in ten most important metabolites identified by metabolomics and activities of CYP1A2, 2C9, and 3A4. Compared with the toxicity of Cd alone, the combined toxicity of the mixture was significantly reduced. According to the integration of BRI and CAI/EAI, a clearly antagonistic interaction at relatively low effects was observed between MWCNTs and Cd. The responses of multiple biomarkers suggest the toxic action mode of the mixture on earthworms was related to the oxidative injury, and the disruption of amino acid, purine, and pyrimidine metabolism, and the urea cycle.