Lysophospholipids as Predictive Markers of ST-Elevation Myocardial Infarction (STEMI) and Non-ST-Elevation Myocardial Infarction (NSTEMI)

Shenxiang Suhe pill improves cardiac function through modulating gut microbiota and serum metabolites in rats after acute myocardial infarction

CONTEXT

Shenxiang Suhe pill (SXSH), a traditional Chinese medicine, is clinically effective against coronary heart disease, but the mechanism of cardiac-protective function is unclear.

OBJECTIVE

We investigated the cardiac-protective mechanism of SXSH via modulating gut microbiota and metabolite profiles.

MATERIALS AND METHODS

Sprague-Dawley (SD) male rats were randomly divided into 6 groups (n = 8): Sham, Model, SXSH (Low, 0.063 g/kg; Medium, 0.126 g/kg; High, 0.252 g/kg), and Ato (atorvastatin, 20 mg/kg). Besides the Sham group, rats were modelled with acute myocardial infarction (AMI) by ligating the anterior descending branch of the left coronary artery (LAD). After 3, 7, 14 days' administration, ultrasound, H&E staining, serum enzymic assay, 16S rRNA sequencing were conducted to investigate the SXSH efficacy. Afterwards, five groups of rats: Sham, Model, Model-ABX (AMI with antibiotics-feeding), SXSH (0.126 g/kg), SXSH-ABX were administrated for 14 days to evaluate the gut microbiota-dependent SXSH efficacy, and serum untargeted metabolomics test was performed.

RESULTS

0.126 g/kg of SXSH intervention for 14 days increased ejection fraction (EF, 78.22%), fractional shortening (FS, 109.07%), and aortic valve flow velocities (AV, 21.62%), reduced lesion area, and decreased serum LDH (8.49%) and CK-MB (10.79%). Meanwhile, SXSH upregulated the abundance of Muribaculaceae (199.71%), Allobaculum (1744.09%), and downregulated Lactobacillus (65.51%). The cardiac-protective effect of SXSH was disrupted by antibiotics administration. SXSH altered serum metabolites levels, such as downregulation of 2-n-tetrahydrothiophenecarboxylic acid (THTC, 1.73%), and lysophosphatidylcholine (lysoPC, 4.61%).

DISCUSSION AND CONCLUSION

The cardiac-protective effect and suggested mechanism of SXSH could provide a theoretical basis for expanding its application in clinic.

Identification of urine biomarkers predictive of prolonged QTc interval in multidrug-resistant tuberculosis patients treated with bedaquiline

The most frequent adverse event associated with bedaquiline (BDQ) is the QTc interval prolongation; however, there was no biomarkers that could be used to predict the occurrence of QTc prolongation in BDQ-treated patients. In this study, we employed the ultra-high performance liquid chromatography-MS/MS (UHPLC-MS/MS) to generate metabolic profiling for the discovery of potential predictive urine biomarkers of QTc prolongation in these patients. Untargeted metabolomic technique was used to concentrate the differential metabolic pathway, and targeted metabolomic technique was subsequently performed to identify predictive biomarkers for QTc prolongation. A total of 45 rifampicin-resistant TB (RR-TB) and multidrug-resistant TB (MDR-TB) patients were enrolled in our study, including 15 RR/MDR-TB patients with QTc interval prolongation (QIP) and 30 RR/MDR-TB patients with QTc interval un-prolongations (QIU). Untargeted technique revealed that the lipid metabolism was the most differential metabolic pathway between two groups. Further targeted technique identified four differential metabolites, including betaine, LPE (18:2), LPE (20:3), and LPE (20:4). The combined analysis of metabolisms revealed that the combined use of LPE (20:3) and LPE (20:4) had the best performance for predicting the occurrence of QTc prolongation in TB patients, yielding a sensitivity of 87.4% and a specificity of 78.5%. In addition, with the progression of BDQ treatment, the LPEs exhibited persistent difference in the BDQ-treated TB patients experiencing QTc interval prolongation. In conclusion, our data demonstrate that the combined use of LPE (20:3) and LPE (20:4) yields promising performance for predicting the occurrence of QTc interval prolongation in BDQ-treated patients.

Metabolomics Analysis Identifies Differential Metabolites as Biomarkers for Acute Myocardial Infarction

Myocardial infarction (MI), including ST-segment elevation MI (STEMI) and non-ST-segment elevation MI (NSTEMI), is still a leading cause of death worldwide. Metabolomics technology was used to explore differential metabolites (DMs) as potential biomarkers for early diagnosis of STEMI and NSTEMI. In the study, 2531 metabolites, including 1925 DMs, were discovered. In the selected 27 DMs, 14 were successfully verified in a new cohort, and the AUC values were all above 0.8. There were 10 in STEMI group, namely L-aspartic acid, L-acetylcarnitine, acetylglycine, decanoylcarnitine, hydroxyphenyllactic acid, ferulic acid, itaconic acid, lauroylcarnitine, myristoylcarnitine, and cis-4-hydroxy-D-proline, and 5 in NSTEMI group, namely L-aspartic acid, arachidonic acid, palmitoleic acid, D-aspartic acid, and palmitelaidic acid. These 14 DMs may be developed as biomarkers for the early diagnosis of MI with high sensitivity and specificity. These findings have particularly important clinical significance for NSTEMI patients because these patients have no typical ECG changes.

Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

Proteomics and Precise Exercise Phenotypes in Heart Failure With Preserved Ejection Fraction: A Pilot Study

BACKGROUND

While exercise impairments are central to symptoms and diagnosis of heart failure with preserved ejection fraction (HFpEF), prior studies of HFpEF biomarkers have mostly focused on resting phenotypes. We combined precise exercise phenotypes with cardiovascular proteomics to identify protein signatures of HFpEF exercise responses and new potential therapeutic targets.

METHODS AND RESULTS

We analyzed 277 proteins (Olink) in 151 individuals (N=103 HFpEF, 48 controls; 62±11 years; 56% women) with cardiopulmonary exercise testing with invasive monitoring. Using ridge regression adjusted for age/sex, we defined proteomic signatures of 5 physiological variables involved in HFpEF: peak oxygen uptake, peak cardiac output, pulmonary capillary wedge pressure/cardiac output slope, peak pulmonary vascular resistance, and peak peripheral O2 extraction. Multiprotein signatures of each of the exercise phenotypes captured a significant proportion of variance in respective exercise phenotypes. Interrogating the importance (ridge coefficient magnitude) of specific proteins in each signature highlighted proteins with putative links to HFpEF pathophysiology (eg, inflammatory, profibrotic proteins), and novel proteins linked to distinct physiologies (eg, proteins involved in multiorgan [kidney, liver, muscle, adipose] health) were implicated in impaired O2 extraction. In a separate sample (N=522, 261 HF events), proteomic signatures of peak oxygen uptake and pulmonary capillary wedge pressure/cardiac output slope were associated with incident HFpEF (odds ratios, 0.67 [95% CI, 0.50-0.90] and 1.43 [95% CI, 1.11-1.85], respectively) with adjustment for clinical factors and B-type natriuretic peptides.

CONCLUSIONS

The cardiovascular proteome is associated with precision exercise phenotypes in HFpEF, suggesting novel mechanistic targets and potential methods for risk stratification to prevent HFpEF early in its pathogenesis.

Pleiotropic Effects of Influenza Vaccination

Influenza vaccines are designed to mimic natural influenza virus exposure and stimulate a long-lasting immune response to future infections. The evolving nature of the influenza virus makes vaccination an important and efficacious strategy to reduce healthcare-related complications of influenza. Several lines of evidence indicate that influenza vaccination may induce nonspecific effects, also referred to as heterologous or pleiotropic effects, that go beyond protection against infection. Different explanations are proposed, including the upregulation and downregulation of cytokines and epigenetic reprogramming in monocytes and natural killer cells, imprinting an immunological memory in the innate immune system, a phenomenon termed "trained immunity". Also, cross-reactivity between related stimuli and bystander activation, which entails activation of B and T lymphocytes without specific recognition of antigens, may play a role. In this review, we will discuss the possible nonspecific effects of influenza vaccination in cardiovascular disease, type 1 diabetes, cancer, and Alzheimer's disease, future research questions, and potential implications. A discussion of the potential effects on infections by other pathogens is beyond the scope of this review.

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.