Plasma metabolites associated with cognitive function across race/ethnicities affirming the importance of healthy nutrition

Untargeted Metabolite Profiling Reveals Acute Toxicity of Pentosidine on Adipose Tissue of Rats

Background: Pentosidine is an advanced glycation end product that is commonly found in heat-processed foods. Pentosidine has been involved in the occurrence and development of some chronic diseases. It was reported that pentosidine exposure can impair the function of the liver and kidneys. Adipose tissue, as an active endocrine organ, plays an important role in maintaining the normal physiological function of cells. However, the metabolic mechanism that causes pentosidine to induce toxicity in adipose tissue remains unclear. Methods: In the study, thirty male Sprague-Dawley rats were divided into a normal diet group, low dose group, and high dose group. A non-targeted metabolomics approach was used to compare the metabolic profiles of adipose tissue between the pentosidine and normal diet groups. Furthermore, histopathological observation and body weight change analysis were performed to test the results of the metabolomics analysis. Results: A total of forty-two differential metabolites were identified. Pentosidine mainly disturbed twelve metabolic pathways, such as ascorbate and aldarate metabolism, glycine, serine, and threonine metabolism, sulfur metabolism, pyruvate metabolism, etc. Additionally, pyruvic acid was identified as a possible key upregulated metabolite involved in thirty-four metabolic pathways. α-Ketoglutaric acid was named as a probable key downregulated metabolite involved in nineteen metabolic pathways based on enrichment network analysis. In addition, histopathological analysis and body weight changes confirmed the results of the metabolomics analysis. Conclusions: These results provided a new perspective for the molecular mechanisms of adipose tissue toxicity induced by pentosidine.

Untargeted Metabolome Atlas for Sleep Phenotypes in the Hispanic Community Health Study/Study of Latinos

Sleep is essential to maintaining health and wellbeing of individuals, influencing a variety of outcomes from mental health to cardiometabolic disease. This study aims to assess the relationships between various sleep phenotypes and blood metabolites. Utilizing data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep phenotypes, grouped in several domains (i.e., sleep disordered breathing (SDB), sleep duration, timing, insomnia symptoms, and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualize and interpret the associations between sleep phenotypes and metabolites. The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, some xenobiotic metabolites were associated with sleep duration and heart rate phenotypes (e.g. 1H-indole-7-acetic acid, 4-allylphenol sulfate), while ketone bodies and fatty acid metabolism metabolites were associated with sleep timing measures (e.g. 3-hydroxybutyrate (BHBA), 3-hydroxyhexanoylcarnitine (1)). Heart rate phenotypes had the overall largest number of detected metabolite associations. Many of these associations were shared with both SDB and with sleep timing phenotypes, while SDB phenotypes shared relatively few metabolite associations with sleep duration measures. A number of metabolites were associated with multiple sleep phenotypes, from a few domains. The amino acids vanillylmandelate (VMA) and 1-carboxyethylisoleucine were associated with the greatest number of sleep phenotypes, from all domains other than insomnia. This atlas of sleep-metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health.

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.

Inferring Causal Relationships Between Metabolites and Polycystic Ovary Syndrome Using Summary Statistics from Genome‑Wide Association Studies

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. Previous studies have suggested that metabolites may play a pivotal mediating role in the progression of phenotypic variations. Although several metabolites had been identified as potential markers for PCOS, the relationship between blood metabolites and PCOS was not comprehensively explored. Previously, Pickrell et al. designed a robust approach to infer evidence of a causal relationship between different phenotypes using independently putative causal SNPs. Our previous paper extended this approach to make it more suitable for cases where only a few independently putative causal SNPs were identified to be significantly associated with the phenotypes (i.e., metabolites). When the most significant SNPs in each independent locus (the independent lead SNPs) with p-values of < 1 × 10-5 were used, 3 metabolites (2-tetradecenoyl carnitine, threitol, 1-docosahexaenoylglycerophosphocholine) causally influencing PCOS and 2 metabolites (asparagine and phenyllactate) influenced by PCOS were identified, (relative likelihood r < 0.01). Under a less stringent threshold of r < 0.05, 7 metabolites (trans-4-hydroxyproline, glutaroyl carnitine, stachydrine, undecanoate, 7-Hoca, N-acetylalanine and 2-hydroxyisobutyrate) were identified. Taken together, this study can provide novel insights into the pathophysiological mechanisms underlying PCOS; whether these metabolites can serve as biomarkers to predict PCOS in clinical practice warrants further investigations.

Metabolites and Cognitive Decline in a Puerto Rican Cohort

Background

Recent studies have identified plasma metabolites associated with cognitive decline and Alzheimer's disease; however, little research on this topic has been conducted in Latinos, especially Puerto Ricans.

Objective

This study aims to add to the growing body of metabolomics research in Latinos to better understand and improve the health of this population.

Methods

We assessed the association between plasma metabolites and global cognition over 12 years of follow-up in 736 participants of the Boston Puerto Rican Health Study (BPRHS). Metabolites were measured with untargeted metabolomic profiling (Metabolon, Inc) at baseline. We used covariable adjusted linear mixed models (LMM) with a metabolite * time interaction term to identify metabolites (of 621 measured) associated with ∼12 years cognitive trajectory.

Results

We observed strong inverse associations between medium-chain fatty acids, caproic acid, and the dicarboxylic acids, azelaic and sebacic acid, and global cognition. N-formylphenylalanine, a tyrosine pathway metabolite, was associated with improvement in cognitive trajectory.

Conclusions

The metabolites identified in this study are generally consistent with prior literature and highlight a role medium chain fatty acid and tyrosine metabolism in cognitive decline.

Research progress of metabolomics in cervical cancer

INTRODUCTION

Cervical cancer threatens women's health seriously. In recent years, the incidence of cervical cancer is on the rise, and the age of onset tends to be younger. Prevention, early diagnosis and specific treatment have become the main means to change the prognosis of cervical cancer patients. Metabolomics research can directly reflect the changes of biochemical processes and microenvironment in the body, which can provide a comprehensive understanding of the changes of metabolites in the process of disease occurrence and development, and provide new ways for the prevention and diagnosis of diseases.

OBJECTIVES

The aim of this study is to review the metabolic changes in cervical cancer and the application of metabolomics in the diagnosis and treatment.

METHODS

PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2022.

RESULTS

With the emergence of metabolomics, metabolic regulation and cancer research are further becoming a focus of attention. By directly reflecting the changes in the microenvironment of the body, metabolomics research can provide a comprehensive understanding of the patterns of metabolites in the occurrence and development of diseases, thus providing new ideas for disease prevention and diagnosis.

CONCLUSION

With the continuous, in-depth research on metabolomics research technology, it will bring more benefits in the screening, diagnosis and treatment of cervical cancer with its advantages of holistic and dynamic nature.