An epidemiological introduction to human metabolomic investigations

DHA-enriched phosphatidylserine alleviates bisphenol A-induced liver injury through regulating glycerophospholipid metabolism and the SIRT1-AMPK pathway

To investigate the alleviating effect and mechanism of the docosahexaenoic acid-enriched phosphatidylserine (DHA-PS) on bisphenol A (BPA)-induced liver injury in mice, the murine liver injury model was established by gavage of BPA (5 mg/kg) or co-administration of BPA and DHA-PS (50 mg/kg or 100 mg/kg) for 6 weeks. The results showed that after administration of 100 mg/kg DHA-PS, the liver index, serum levels of AST, ALT, TC, TG, NEFA, and LDL-C in mice were significantly decreased, while HDL-C was significantly increased. The LPS, IL-6, IL-1β, TNF-α, and MDA levels in liver tissues were effectively down-regulated, and IL-10, SOD, GSH-Px, and CAT levels were effectively up-regulated. The H&E and Oil Red O staining results showed that liver damage was notably repaired and lipid deposition was notably reduced after DHA-PS administration. Furthermore, metabolomics and immunohistochemical studies revealed that DHA-PS mainly regulates glycerophospholipid metabolism and the SIRT1-AMPK pathway to improve metabolic disorders of the liver caused by BPA. Therefore, DHA-PS could potentially alleviate BPA-induced murine liver injury through suppressing inflammation and oxidative stress, and modulating lipid metabolism disorders.

Estimating Gestational Age and Prediction of Preterm Birth Using Metabolomics Biomarkers

Preterm birth (PTB) is a leading cause of morbidity and mortality in children aged under 5 years globally, especially in low-resource settings. It remains a challenge in many low-income and middle-income countries to accurately measure the true burden of PTB due to limited availability of accurate measures of gestational age (GA), first trimester ultrasound dating being the gold standard. Metabolomics biomarkers are a promising area of research that could provide tools for both early identification of high-risk pregnancies and for the estimation of GA and preterm status of newborns postnatally.

A metabolomics study on carcinogenesis of ground-glass nodules

Objective

This study aimed to identify differential metabolites and key metabolic pathways between lung adenocarcinoma (LUAD) tissues and normal lung (NL) tissues using metabolomics techniques, to discover potential biomarkers for the early diagnosis of lung cancer.

Material and Methods

Forty-five patients with primary ground-glass nodules (GGN) identified on computed tomography imaging and who were willing to undergo surgery at Shanghai General Hospital from December 2021 to December 2022 were recruited to the study. All participants underwent video thoracoscopy surgery with segmental or wedge resection of the lung. Tissue samples for pathological examination were collected from the site of ground-glass nodules (GGN) lesion and 3 cm away from the lesion (NL). The pathology results were 35 lung adenocarcinoma (LUAD) cases (13 invasive adenocarcinoma, 14 minimally invasive adenocarcinoma, and eight adenocarcinoma in situ), 10 benign samples, and 45 NL tissues. For the untargeted metabolomics technique, 25 LUAD samples were assigned as the case group and 30 NL tissues as the control group. For the targeted metabolomics technique, ten LUAD samples were assigned as the case group and 15 NL tissues as the control group. Samples were analyzed by untargeted and targeted metabolomics, with liquid chromatography-tandem mass spectrometry detection used as part of the experimental procedure.

Results

Untargeted metabolomics revealed 164 differential metabolites between the case and control groups, comprising 110 up regulations and 54 down regulations. The main metabolic differences found by the untargeted method were organic acids and their derivatives. Targeted metabolomics revealed 77 differential metabolites between the case and control groups, comprising 69 up regulations and eight down regulations. The main metabolic changes found by the targeted method were fatty acids, amino acids, and organic acids. The levels of organic acids such as lactic acid, fumaric acid, and malic acid were significantly increased in LUAD tissue compared to NL. Specifically, an increased level of L-lactic acid was found by both untargeted (variable importance in projection [VIP] = 1.332, fold-change [FC] = 1.678, q = 0.000) and targeted metabolomics (VIP = 1.240, FC = 1.451, q = 0.043). Targeted metabolomics also revealed increased levels of fumaric acid (VIP = 1.481, FC = 1.764, q = 0.106) and L-malic acid (VIP = 1.376, FC = 1.562, q = 0.012). Most of the 20 differential fatty acids identified were downregulated, including dodecanoic acid (VIP = 1.416, FC = 0.378, q = 0.043) and tridecane acid (VIP = 0.880, FC = 0.780, q = 0.106). Furthermore, increased levels of differential amino acids were found in LUAD samples.

Conclusion

Lung cancer is a complex and heterogeneous disease with diverse genetic alterations. The study of metabolic profiles is a promising research field in this cancer type. Targeted and untargeted metabolomics revealed significant differences in metabolites between LUAD and NL tissues, including elevated levels of organic acids, decreased levels of fatty acids, and increased levels of amino acids. These metabolic features provide valuable insights into LUAD pathogenesis and can potentially serve as biomarkers for prognosis and therapy response.

Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls

AIMS

Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD.

MATERIALS AND METHODS

We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis.

RESULTS

The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered.

CONCLUSIONS

We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.

N-nitrosamines induced gender-dimorphic effects on infant rats at environmental levels

The safety of drinking water has always been a concern for people all over the world. N-nitrosamines (NAs), a kind of nitrogenous disinfection by-products (N-DBPs), are generally detected as a mixture in drinking water at home and abroad. Studies have shown that individual NAs posed strong carcinogenicity at high concentrations. However, health risks of NAs at environmental levels (concentrations in drinking water) are still unclear. Therefore, the potential health risks of environmentally relevant NAs exposure in drinking water needs to be conducted. In this study, blood biochemical analysis and metabolomics based on nuclear magnetic resonance (NMR) were performed to comprehensively investigate NAs induced metabolic disturbance in infant rats at environmental levels. Results of blood biochemical indices analysis indicated that AST in the serum of male rats in NAs-treated group exhibited a significant gender-specific difference. Multivariate statistics showed that two and eight significantly disturbed metabolic pathways were identified in the serum samples of NAs-treated male and female rats, respectively. In the urine samples of NAs-treated female rats, glycine, serine, and threonine metabolism pathway was significantly disturbed; while three significantly disturbed metabolic pathways were found in the urine of NAs-treated male rats. Finally, results of spearman correlation coefficients suggested that the disturbances of metabolism profile in serum and urine were correlated with changes in the gut microbiota (data derived from our published paper). Data presented here aimed to generate new health risk data of NAs mixture exposure at environmental levels and provide theoretical support for drinking water safety management. ENVIRONMENTAL IMPLICATION: N-nitrosamines (NAs) are a kind of nitrogenous disinfection by-products (N-DBPs) generated during drinking water disinfection processes. Herein, health risks of NAs at environmental levels (concentrations in drinking water) are investigated using blood biochemical analysis and nuclear magnetic resonance (NMR)-based metabolomics. Results confirmed NAs induced gender-specific on the metabolism in rat and the disturbances of metabolism profile in serum and urine were correlated with changes in the gut microbiota. Data presented here aimed to generate new health risk data of NAs mixture exposure at environmental levels and provide theoretical support for drinking water safety management.

Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium

INTRODUCTION

Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility.

OBJECTIVE

The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework.

METHODS

We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure.

RESULTS

Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction.

CONCLUSIONS

Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.