Metabolomic study for essential hypertension patients based on dried blood spot mass spectrometry approach

Causal association between blood metabolites and risk of hypertension: a Mendelian randomization study

Background

Previous studies have indicated a strong link between blood metabolites and hypertension, however the causality of metabolites and hypertension is unknown.

Methods

Two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between 486 blood metabolites and essential hypertension (EHT). Blood metabolite GWAS data was utilized as the exposure, with EHT GWAS data as the outcome. To further verify the results, another different source of EHT GWAS data was repeatedly analyzed. The major MR analytic approach used to determine causality was inverse variance weighted (IVW), with MR-Egger, Weighted Median, and MR-PRESSO models serving as supplements. We used the Cochran Q test to examine heterogeneity. Horizontal pleiotropy was examined using MR-Egger intercept and MR-PRESSO global test. The MR Steiger test confirmed the causal relationship between blood metabolites and EHT.

Results

In this study, nine blood metabolites associated with EHT were preliminarily identified by MR analysis, including four known metabolites (N-acetylornithine, X-12510-2-aminooctanoic acid, creatine, hexadecanedioate) and five unknown metabolites. Then another source of EHT GWAS data was repeatedly analyzed for further verification, and two overlapped metabolites (N-acetylornithine, X-12510-2-aminooctanoic acid) were found. There was a negative correlation between N-acetylornithine and EHT (OR = 0.987, 95% CI = 0.980-0.993, P = 1.01 × 10-4), Cochran's Q test suggested there was no heterogeneity (Q = 31.7586, P = 0.1331), MR-Egger intercept and MR-PRESSO global test suggested there was no horizontal pleiotropy (P > 0.05), Leave-one-out analysis indicated that no single single-nucleotide polymorphism (SNP) had a significant effect on the results, and MR Steiger test confirmed that the direction of causality was correct (P < 0.001). There was a negative correlation between X-12510-2-aminooctanoic acid and EHT (OR = 0.982, 95% CI = 0.972-0.993, P = 0.0017), and there was no evidence of heterogeneity or pleiotropy in multiple sensitivity analyses.

Conclusion

The study discovered some blood metabolites causally linked to EHT, which might lead to new understandings of the pathophysiology of hypertension.

A Systematic Literature Review on the Use of Dried Biofluid Microsampling in Patients With Kidney Disease

BACKGROUND

Kidney disease is fairly unique due to the lack of symptoms associated with disease activity, and it is therefore dependent on biological monitoring. Dried biofluids, particularly dried capillary blood spots, are an accessible, easy-to-use technology that have seen increased utility in basic science research over the past decade. However, their use is yet to reach the kidney patient population clinically or in large-scale discovery science initiatives. The aim of this study was to systematically evaluate the existing literature surrounding the use of dried biofluids in kidney research.

METHODS

A systematic literature review was conducted using three search engines and a predefined search term strategy. Results were summarised according to the collection method, type of biofluid, application to kidney disease, cost, sample stability and patient acceptability.

RESULTS

In total, 404 studies were identified and 67 were eligible. In total, 34,739 patients were recruited to these studies with a skew towards male participants (> 73%). The majority of samples were blood, which was used either for monitoring anti-rejection immunosuppressive drug concentrations or for kidney function. Dried biofluids offered significant cost savings to the patient and healthcare service. The majority of patients preferred home microsampling when compared to conventional monitoring.

CONCLUSION

There is an unmet need in bringing dried microsampling technology to advance kidney disease despite its advantages. This technology provides an opportunity to upscale patient recruitment and longitudinal sampling, enhance vein preservation and overcome participation bias in research.

Hydrogen-Rich Water Ameliorates Metabolic Disorder via Modifying Gut Microbiota in Impaired Fasting Glucose Patients: A Randomized Controlled Study

OBJECTIVE

Molecular hydrogen (H₂) exhibits antioxidant, anti-inflammatory and anti-apoptotic effects, and has shown benefits in glucose and lipid metabolism in certain animal metabolic disorder models. However, the potential benefits of H₂ treatment in individuals with impaired fasting glucose (IFG) has seldom been studied. This randomized controlled study (RCT) aims to investigate the effects of hydrogen-rich water (HRW) on IFG subjects and explore the underlying mechanism involved.

METHODS

Seventy-three patients with IFG were enrolled in a randomized, double-blind, placebo-controlled clinical study. These patients were assigned to receive either 1000 mL per day of HRW or placebo pure water (no H₂ infusion) for a duration of eight weeks. Metabolic parameters and fecal gut microbiota were assessed at baseline (week 0) and at week 8. A combined analysis of metabolomics and intestinal microbiota was conducted to investigate the correlation between the effect of H₂ on the metabolisms and the diversity of intestinal flora in the IGF patients.

RESULTS

Both pure water and HRW demonstrated a significant reduction in fasting blood glucose in IFG patients, with a significant difference between pure water and HRW after eight weeks. Among IFG patients with abnormal pre-experimental fatty liver, 62.5% (10/16) in the HRW group and 31.6% (6/19) in the pure water group achieved remission. Furthermore, 16S RNA analysis revealed HRW-modified gut microbiota dysbiosis in the fecal samples of IGF patients. Through Pearson correlation analysis, the differential gut microbiota obtained by 16S analysis was found to be highly correlated with nine metabolites.

CONCLUSION

H₂ slightly improved metabolic abnormalities and gut microbiota dysbiosis, providing a novel target and theoretical basis for the prevention and treatment of blood glucose regulation in patients with IFG.

Integration of serum metabolomics and network pharmacology reveals the immunoenhancing mechanisms of Qishenbuqi capsules

Introduction

Qishenbuqi capsule (QSBQC), a listed Chinese patent prescription, comprises of 4 herbs. Clinically, it has been shown to improve immune functions.

Methods

Subjects with Qi deficiency and non-Qi deficiency were recruited, who then took QSBQC for 4 weeks. Traditional Chinese medicine (TCM) syndrome scores and the levels of white blood cells, CD3+ T cells (CD3+), CD4+ T cells (CD3+CD4+), CD8+ T cells (CD3+CD8+), and CD4+/CD8+ were determined. Serum metabolomics was used to explore the metabolic mechanisms of QSBQC on improving immunity. Meanwhile, the potential active ingredients, targets, and pathways of QSBQC on enhancing immunity were screened by network pharmacology.

Results

QSBQC significantly improved TCM syndrome scores and increased the number of CD8+ T cells of both Qi deficiency and non-Qi deficiency subjects. Serum metabolomics revealed that QSBQC regulated 18 differential metabolites and 8 metabolic pathways of Qi deficiency, and 12 differential metabolites and 7 metabolic pathways of non-Qi deficiency subjects. The "herbs-compounds-pathways" diagram showed that PQ-2, cimifugin, and divaricatol were the main active components. Pathways in cancer and arginine and proline metabolism could be the most important pathways.

Conclusion

Our research revealed the immunoenhancing mechanisms of QSBQC and improved the combination of TCM theory and modern western medicine theory.

Circ_0000284: A risk factor and potential biomarker for prehypertension and hypertension

CircRNAs have been shown to be involved in the development of certain diseases, but their application in prehypertension and hypertension remains unclear. We aimed to explore the potential role of circ_0000284 in revealing the molecular regulatory mechanisms of prehypertension and hypertension. We enrolled a total of 100 patients with normal blood pressure, 100 patients with prehypertension and 100 patients with hypertension. The expression of circ_0000284 among the groups was detected by real-time fluorescence quantitative polymerase chain reaction (qRT‒PCR). Multivariate logistic models were constructed combining conventional risk factors with circ_0000284. A receiver operating characteristic curve (ROC) was used to analyze the diagnostic value of circRNAs in the clinical model. Spearman correlation was used to analyze the correlation of circ_0000284 and the biochemical characteristics of all subjects. The results showed that circ_0000284 was differentially expressed among the normal blood pressure group, prehypertensive group and hypertensive group and showed a significantly upregulated trend in the progression to hypertension (P < 0.05). The ROC curve revealed a high diagnostic ability of circ_0000284 in hypertension in the clinical model (AUC = 0.812). Circ_0000284 also presented a certain ability for early diagnosis of prehypertension (AUC = 0.628). Spearman correlation showed that circ_0000284 was positively correlated with Na and CKMB. Our study suggested that upregulated expression of circ_0000284 was an independent risk factor for prehypertension and hypertension. Circ_0000284 was a potential fingerprint for the early diagnosis of hypertension and distinguished the intermediate stage of hypertension development. Moreover, our study provided new insight into the correlation between circ_0000284 and cardiac injury in the progression to hypertension.

Association of plasma acylcarnitines and amino acids with hypertension: A nationwide metabolomics study

BACKGROUND

Identification of metabolomics profile in subjects with different blood pressure, including normal blood pressure, elevated blood pressure, stage 1 hypertension, and stage 2 hypertension, would be a promising strategy to understand the pathogenesis of hypertension. Thus, we conducted this study to investigate the association of plasma acylcarnitines and amino acids with hypertension in a large Iranian population.

METHODS

1200 randomly selected subjects from the national survey on the Surveillance of Risk Factors of Non-Communicable Diseases in Iran (STEPs 2016) were divided into four groups based on the ACC/AHA hypertension criteria: normal blood pressure (n = 293), elevated blood pressure (n = 135), stage 1 hypertension (n = 325), and stage 2 hypertension (n = 447). Plasma concentrations of 30 acylcarnitines and 20 amino acids were measured using a targeted approach with flow-injection tandem mass spectrometry. Univariate and multivariate logistic regression analysis was applied to estimate the association between metabolites level and the risk of hypertension. Age, sex, BMI, total cholesterol, triglyceride, HDL cholesterol, fasting plasma glucose, use of oral glucose-lowering drugs, statins, and antihypertensive drugs were adjusted in regression analysis.

RESULTS

Of 50 metabolites, 34 were associated with an increased likelihood of stage 2 hypertension and 5 with a decreased likelihood of stage 2 hypertension. After full adjustment for potential confounders, 5 metabolites were still significant risk markers for stage 2 hypertension including C0 (OR = 0.75; 95%CI: 0.63, 0.90), C12 (OR = 1.18; 95%CI: 1.00, 1.40), C14:1 (OR = 1.20; 95%CI: 1.01, 1.42), C14:2 (OR = 1.19; 95%CI: 1.01, 1.41), and glycine (OR = 0.81; 95%CI: 0.68, 0.96). An index that included glycine and serine also showed significant predictive value for stage 2 hypertension after full adjustment (OR = 0.86; 95%CI: 0.75, 0.98).

CONCLUSIONS

Five metabolites were identified as potentially valuable predictors of stage 2 hypertension.

Application of Metabolomics in Childhood Leukemia Diagnostics

Metabolomics is a new field of science dealing with the study and analysis of metabolites formed in living cells. The biological fluids used in this test method are: blood, blood plasma, serum, cerebrospinal fluid, saliva and urine. The most popular methods of assessing the composition of metabolites include nuclear magnetic resonance spectroscopy and mass spectrometry (MS) in combination with gas chromatography–MS or liquid chromatography–MS. Metabolomics is used in many areas of medicine. The variability of biochemical processes in neoplastic cells in relation to healthy cells is the starting point for this type of research. The aim of the research currently being carried out is primarily to find biomarkers for quick diagnosis of the disease, assessment of its advancement and treatment effectiveness. The development of metabolomics may also contribute to the individualization of treatment of patients, adjusting drugs depending on the metabolic profile, and thus may improve the effectiveness of therapy, reduce side effects and help to improve the quality of life of patients. Here, we review the current and potential applications of metabolomics, focusing on its use as a biomarker method for childhood leukemia.

Graphic abstract

Metabolic Profiling and Metabolites Fingerprints in Human Hypertension: Discovery and Potential

Early detection of pathogenesis through biomarkers holds the key to controlling hypertension and preventing cardiovascular complications. Metabolomics profiling acts as a potent and high throughput tool offering new insights on disease pathogenesis and potential in the early diagnosis of clinical hypertension with a tremendous translational promise. This review summarizes the latest progress of metabolomics and metabolites fingerprints and mainly discusses the current trends in the application in clinical hypertension. We also discussed the associated mechanisms and pathways involved in hypertension's pathogenesis and explored related research challenges and future perspectives. The information will improve our understanding of the development of hypertension and inspire the clinical application of metabolomics in hypertension and its associated cardiovascular complications.

How Perturbated Metabolites in Diabetes Mellitus Affect the Pathogenesis of Hypertension?

The presence of hypertension (HTN) in type 2 diabetes mellitus (DM) is a common phenomenon in more than half of the diabetic patients. Since HTN constitutes a predictor of vascular complications and cardiovascular disease in type 2 DM patients, it is of significance to understand the molecular and cellular mechanisms of type 2 DM binding to HTN. This review attempts to understand the mechanism via the perspective of the metabolites. It reviewed the metabolic perturbations, the biological function of perturbated metabolites in two diseases, and the mechanism underlying metabolic perturbation that contributed to the connection of type 2 DM and HTN. DM-associated metabolic perturbations may be involved in the pathogenesis of HTN potentially in insulin, angiotensin II, sympathetic nervous system, and the energy reprogramming to address how perturbated metabolites in type 2 DM affect the pathogenesis of HTN. The recent integration of the metabolism field with microbiology and immunology may provide a wider perspective. Metabolism affects immune function and supports immune cell differentiation by the switch of energy. The diverse metabolites produced by bacteria modified the biological process in the inflammatory response of chronic metabolic diseases either. The rapidly evolving metabolomics has enabled to have a better understanding of the process of diseases, which is an important tool for providing some insight into the investigation of diseases mechanism. Metabolites served as direct modulators of biological processes were believed to assess the pathological mechanisms involved in diseases.

Identification of biomarkers for essential hypertension based on metabolomics

AIM

Essential hypertension (EH) is one of the most important public health problems worldwide. However, the pathogenesis of EH is unclear and early diagnostic methods are lacking. Metabolomics demonstrates great potential for biomarker discovery and the mechanistic exploration of metabolic diseases.

DATA SYNTHESIS

This review included human and animal metabolomics studies related to EH in the PubMed and Web of Science databases between February 1996 and May 2020. The study designs, EH standards, and reported metabolic biomarkers were systematically examined and compared. The pathway analysis was conducted through the online software MetaboAnalyst 4.0. Twenty-two human studies and fifteen animal studies were included in this systematic review. There were many frequently reported biomarkers with consistent trends (e.g., pyruvate, lactic acid, valine, and tryptophan) in human and animal studies, and thus had potential as biomarkers of EH. In addition, several shared metabolic pathways, including alanine, aspartate, and glutamate metabolism, aminoacyl-tRNA biosynthesis, and arginine biosynthesis, were identified in human and animal metabolomics studies. These biomarkers and pathways, closely related to insulin resistance, the inflammatory state, and impaired nitric oxide production, were demonstrated to contribute to EH development.

CONCLUSIONS

This study summarized valuable metabolic biomarkers and pathways that could offer opportunities for the early diagnosis or prediction of EH and the discovery of the metabolic mechanisms of EH.

A Novel Dried Blood Spot Detection Strategy for Characterizing Cardiovascular Diseases

Cardiovascular diseases (CVDs) are the leading cause of death in China. Conventional diagnostic methods are dependent on advanced instruments, which are expensive, inaccessible, and inconvenient in underdeveloped areas. To build a novel dried blood spot (DBS) detection strategy for imaging CVDs, in this study, a total of 12 compounds, including seven amino acids [homocysteine (Hcy), isoleucine (Ile), leucine (Leu), valine (Val), phenylalanine (Phe), tyrosine (Tyr), and tryptophan (Trp)], three amino acid derivatives [choline, betaine, and trimethylamine N-oxide (TMAO)], L-carnitine, and creatinine, were screened for their ability to identify CVD. A rapid and reliable method was established for the quantitative analysis of the 12 compounds in DBS. A total of 526 CVD patients and 200 healthy volunteers in five provinces of China were recruited and divided into the following groups: stroke, coronary heart disease, diabetes, and high blood pressure. The orthogonal projection to latent structures-discriminant analysis (OPLSDA) model was used to characterize the difference between each CVD group. Marked differences between the groups based on the OPLSDA model were observed. Based on the model, the patients in the three training sets were mostly accurately categorized into the appropriate group. In addition, the receiver operating characteristic (ROC) curves and logistic regression of each metabolite chosen by the OPLSDA model had an excellent predictive value in both the test and validation groups. DBS detection of 12 biomarkers was sensitive and powerful for characterizing different types of CVD. Such differentiation may reduce unnecessary invasive coronary angiography, enhance predictive value, and complement current diagnostic methods.

Association of -344C/T polymorphism in the aldosterone synthase (CYP11B2) gene with cardiac and cerebrovascular events in Chinese patients with hypertension

Objective

Several recent studies have shown that the aldosterone synthase gene (CYP11B2) −344C/T polymorphism is related to cardiovascular diseases. However, whether the −344C allele influences the incidence of cardiovascular diseases in Chinese patients with hypertension is unclear.

Methods

Chinese patients with essential hypertension were genotyped for the −344C/T polymorphism in CYP11B2 (n = 755; CC, n = 112; CT, n = 361; TT, n = 282) and followed for 11 years for major adverse cardiovascular events (MACEs), including stroke, onset of coronary artery disease (CAD), and CAD-related death. Established cardiovascular risk factors were used to adjust the multivariate Cox analysis.

Results

After a mean follow-up period of 7.60 ± 1.12 years, a significantly higher incidence of MACEs was seen in patients with the CC genotype than in those with the CT and TT genotypes. The CC variant was significantly and independently predictive of MACEs (hazard ratio = 2.049), CAD (hazard ratio = 1.754), and stroke (hazard ratio = 2.588), but not CAD-related stroke or death.

Conclusion

The CYP11B2 −344 CC genotype is a risk factor for CAD and stroke, independent of other established cardiovascular risk factors in Chinese patients with hypertension.

Genomic Determinants of Hypertension With a Focus on Metabolomics and the Gut Microbiome

Epidemiologic and genomic studies have progressively improved our understanding of the causation of hypertension and the complex relationship with diet and environment. The majority of Mendelian forms of syndromic hypotension and hypertension (HTN) have all been linked to mutations in genes whose encoded proteins regulate salt-water balance in the kidney, supporting the primacy of the kidneys in blood pressure regulation. There are more than 1,477 single nucleotide polymorphisms associated with blood pressure and hypertension and the challenge is establishing a causal role for these variants. Hypertension is a complex multifactorial phenotype and it is likely to be influenced by multiple factors including interactions between diet and lifestyle factors, microbiome, and epigenetics. Given the finite genetic variability that is possible in humans, it is likely that incremental gains from single marker analyses have now plateaued and a greater leap in our understanding of the genetic basis of disease will come from integration of other omics and the interacting environmental factors. In this review, we focus on emerging results from the microbiome and metabolomics and discuss how leveraging these findings may facilitate a deeper understanding of the interrelationships between genomics, diet, and microbial ecology in humans in the causation of essential hypertension.

A metabolomic study for chronic heart failure patients based on a dried blood spot mass spectrometry approach

Objective: a dried blood spot (DBS) method integrated with direct infusion mass spectrometry (MS) focused on a metabolomic analysis was applied to detect and compare the difference of metabolites between the heart failure (HF) patients and non-HF patients in order to facilitate the early detection of heart failures, provide targeted intervention and offer prognostic insights. Methods: the method we used was an untargeted metabolic approach. The dry blood spot mass spectrometry (DBS) was used to analyze 23 types of amino acids and 26 types of carnitine in blood samples. In the current study, 49 metabolites were selected to establish the PLS-DA model to compare the differences between the 117 HF patients and 118 non-HF patients, which inclined to detect the difference between the two groups. Multiple algorithms were run for selecting different metabolites as potential biomarkers. Ten-fold cross validation method was used to verify and evaluate the selected potential biomarkers. Results: through significant analysis of the microarrays (SAM) and analysis of 9 parameters, 8 metabolites showed significant discrepancies between the HF and non-HF groups. Among these metabolites, the levels of 5 metabolites were increased, and the other 3 metabolites were decreased in the HF group compared with the non-HF group. However, 7 metabolites including Asn, C0, C14, C4DC, C5-OH, C6 and Glu were selected to distinguish the HF group from the non-HF group with specificity and sensitivity of 0.8475 and 0.8974, respectively. Conclusion: metabolomic study for chronic heart failure (CHF) patients based on the dried blood spot mass spectrometry approach would be beneficial to understand the metabolic pathway of HF, and probably work as biomarkers to predict the prognosis of HF and provide the basis for an individualized treatment.

A dried blood spot method with mass spectrometry focused on metabolomics analysis was applied to detect and compare the difference in metabolites between heart failure (HF) patients and non-HF patients in order to facilitate the early detection and treatment of heart failure.

Metabolomics and adductomics of newborn bloodspots to retrospectively assess the early-life exposome

PURPOSE OF REVIEW

Exposomics studies can measure health-relevant chemical exposures during a lifetime and estimate the 'internal' environment. However, sampling limitations make these features difficult to capture directly during the critical neonatal time period.

RECENT FINDINGS

We review the use of newborn dried bloodspots (DBS) archived from newborn screening programs for exposomic analysis in epidemiological children's health studies. Emerging 'omics technologies such as adductomics and metabolomics have been adapted for DBS analysis, and these technologies can now provide valuable etiological information on the complex interplay between exposures, biological response, and population phenotypes.

SUMMARY

Adductomics and metabolomics of DBS can provide robust measurements for retrospective epidemiological investigations. With extensive bioarchiving programs in the United States and other countries, DBS are poised to substantially aid epidemiological studies, particularly for rare and low-frequency childhood diseases and disorders.

Efficacy and safety of different doses of azilsartan medoxomil in patients with hypertension: A protocol of a network meta-analysis

BACKGROUND

Hypertension is one of the most common chronic diseases and an increasingly public-health challenge worldwide. Previous meta-analyses evaluated the effects of azilsartan medoxomil compared to placebo or other antihypertensive drugs in patients with hypertension. However, it is still unclear which dose of azilsartan is optimal. This study will perform a network meta-analysis to assess the efficacy and safety of different doses of azilsartan medoxomil in patients with hypertension.

METHODS

PubMed, EMBASE.com, the Cochrane library, Scopus, and Web of Science were searched from inception to May 2019. Randomized controlled trials reporting efficacy and safety of different doses of azilsartan medoxomil on hypertension will be included if they compared 1 dose of azilsartan medoxomil with another dose of azilsartan medoxomil or with a placebo. Risk of bias of the included trials will be evaluated according to the Cochrane Handbook 5.1.0. NMA will be performed in a Bayesian hierarchical framework using WinBUGS 14.

RESULTS

The results will be submitted to a peer-reviewed journal for publication.

CONCLUSION

This study will summarize all the available data to provide reliable evidence of the value of different doses of azilsartan medoxomil for the treatment of hypertension.

PROSPERO REGISTRATION NUMBER

CRD42019136882.

UPLC-QTOF/MS-based metabolomics reveals the mechanism of chronic unpredictable mild stress-induced hypertension in rats

Hypertension is a common chronic disease, and it is the strongest risk factor for cardiovascular disease. Recently, the number of patients with hypertension-related complications has increased significantly, adding a heavy burden to the public health system. It is known that chronic stress plays an important role in the pathogenesis of cardiovascular diseases such as hypertension and stroke. However, the impact of hypertension on the dysfunctions induced by chronic stress remains poorly understood. In this study, using LC-MS-based metabolomics, we established a chronic stress model to demonstrate the mechanisms of stress-induced hypertension. We found that 30 metabolites in chronically stressed rats were changed; of these metabolites, seven had been upregulated, and 23 had been downregulated, including amino acids, phospholipids, carnitines and fatty acids, many of which are involved in amino acid metabolism, cell membrane injury, ATP supply and inflammation. These metabolites are engaged in dysregulated pathways and will provide a targeted approach to study the mechanism of stress-induced hypertension.