Metabolomics signature associated with circulating serum selenoprotein P levels

Gamma-glutamyl-leucine levels are causally associated with elevated cardio-metabolic risks

Objective

Gamma-glutamyl dipeptides are bioactive peptides involved in inflammation, oxidative stress, and glucose regulation. Gamma-glutamyl-leucine (Gamma-Glu-Leu) has been extensively reported to be associated with the risk of cardio-metabolic diseases, such as obesity, metabolic syndrome, and type 2 diabetes. However, the causality remains to be uncovered. The aim of this study was to explore the causal-effect relationships between Gamma-Glu-Leu and metabolic risk.

Materials and methods

In this study, 1,289 subjects were included from a cross-sectional survey on metabolic syndrome (MetS) in eastern China. Serum Gamma-Glu-Leu levels were measured by untargeted metabolomics. Using linear regressions, a two-stage genome-wide association study (GWAS) for Gamma-Glu-Leu was conducted to seek its instrumental single nucleotide polymorphisms (SNPs). One-sample Mendelian randomization (MR) analyses were performed to evaluate the causality between Gamma-Glu-Leu and the metabolic risk.

Results

Four SNPs are associated with serum Gamma-Glu-Leu levels, including rs12476238, rs56146133, rs2479714, and rs12229654. Out of them, rs12476238 exhibits the strongest association (Beta = -0.38, S.E. = 0.07 in discovery stage, Beta = -0.29, S.E. = 0.14 in validation stage, combined P-value = 1.04 × 10^-8). Each of the four SNPs has a nominal association with at least one metabolic risk factor. Both rs12229654 and rs56146133 are associated with body mass index, waist circumference (WC), the ratio of WC to hip circumference, blood pressure, and triglyceride (5 × 10^-5 < P < 0.05). rs56146133 also has nominal associations with fasting insulin, glucose, and insulin resistance index (5 × 10^-5 < P < 0.05). Using the four SNPs serving as the instrumental SNPs of Gamma-Glu-Leu, the MR analyses revealed that higher Gamma-Glu-Leu levels are causally associated with elevated risks of multiple cardio-metabolic factors except for high-density lipoprotein cholesterol and low-density lipoprotein cholesterol (P > 0.05).

Conclusion

Four SNPs (rs12476238, rs56146133, rs2479714, and rs12229654) may regulate the levels of serum Gamma-Glu-Leu. Higher Gamma-Glu-Leu levels are causally linked to cardio-metabolic risks. Future prospective studies on Gamma-Glu-Leu are required to explain its role in metabolic disorders.

Increases in Hepatokine Selenoprotein P Levels Are Associated With Hepatic Hypoperfusion and Predict Adverse Prognosis in Patients With Heart Failure

Background

Although multiorgan networks are involved in the pathophysiology of heart failure (HF), interactions of the heart and the liver have not been fully understood. Hepatokines, which are synthesized and secreted from the liver, have regulatory functions in peripheral tissues. Here, we aimed to clarify the clinical impact of the hepatokine selenoprotein P in patients with HF.

Methods and Results

This is a prospective observational study that enrolled 296 participants consisting of 253 hospitalized patients with HF and 43 control subjects. First, we investigated selenoprotein P levels and found that its levels were significantly higher in patients with HF than in the controls. Next, patients with HF were categorized into 4 groups according to the presence of liver congestion using shear wave elastography and liver hypoperfusion by peak systolic velocity of the celiac artery, which were both assessed by abdominal ultrasonography. Selenoprotein P levels were significantly elevated in patients with HF with liver hypoperfusion compared with those without but were not different between the patients with and without liver congestion. Selenoprotein P levels were negatively correlated with peak systolic velocity of the celiac artery, whereas no correlations were observed between selenoprotein P levels and shear wave elastography of the liver. Kaplan‐Meier analysis demonstrated that patients with HF with higher selenoprotein P levels were significantly associated with increased adverse cardiac outcomes including cardiac deaths and worsening HF.

Conclusions

Liver‐derived selenoprotein P correlates with hepatic hypoperfusion and may be a novel target involved in cardiohepatic interactions as well as a useful biomarker for predicting prognosis in patients with HF.

A Comprehensive Review on Selenium and Its Effects on Human Health and Distribution in Middle Eastern Countries

Selenium (Se) is an important microelement with numerous positive effects on human health and diseases. It is important to specify that the status and consumption of Se are for a specific community as the levels of Se are extremely unpredictable between different populations and regions. Our existing paper was based on the impacts of Se on human health and disease along with data on the Se levels in Middle Eastern countries. Overall, the findings of this comprehensive review show that the consumption and levels of Se are inadequate in Middle Eastern nations. Such findings, together with the growing awareness of the importance of Se to general health, require further work primarily on creating an acceptable range of blood Se concentration or other measures to determine optimal Se consumption and, consequently, to guarantee adequate Se supplementation in populations at high risk of low Se intake.

Metabolomic architecture of obesity implicates metabolonic lactone sulfate in cardiometabolic disease

OBJECTIVE

Identify and characterize circulating metabolite profiles associated with adiposity to inform precision medicine.

METHODS

Untargeted plasma metabolomic profiles in the Insulin Resistance Atherosclerosis Family Study (IRASFS) Mexican American cohort (n = 1108) were analyzed for association with anthropometric (body mass index, BMI; waist circumference, WC; waist-to-hip ratio, WHR) and computed tomography measures (visceral adipose tissue, VAT; subcutaneous adipose tissue, SAT; visceral-to-subcutaneous ratio, VSR) of adiposity. Genetic data, inclusive of genome-wide array-based genotyping, whole exome sequencing (WES) and whole genome sequencing (WGS), were evaluated to identify the genetic contributors. Phenotypic and genetic association signals were replicated across ancestries. Transcriptomic data were analyzed to explore the relationship between genetic and metabolomic data.

RESULTS

A partially characterized metabolite, tentatively named metabolonic lactone sulfate (X-12063), was consistently associated with BMI, WC, WHR, VAT, and SAT in IRASFS Mexican Americans (P_MA <2.02 × 10^-27). Trait associations were replicated in IRASFS African Americans (P_AA < 1.12 × 10^-07). Expanded analyses revealed associations with multiple phenotypic measures of cardiometabolic health, e.g. insulin sensitivity (S_I), triglycerides (TG), diastolic blood pressure (DBP) and plasminogen activator inhibitor-1 (PAI-1) in both ancestries. Metabolonic lactone sulfate levels were heritable (h² > 0.47), and a significant genetic signal at the ZSCAN25/CYP3A5 locus (P_MA = 9.00 × 10^-41, P_AA = 2.31 × 10^-10) was observed, highlighting a putative functional variant (rs776746, CYP3A5∗3). Transcriptomic analysis in the African American Genetics of Metabolism and Expression (AAGMEx) cohort supported the association of CYP3A5 with metabolonic lactone sulfate levels (P_FDR = 6.64 × 10^-07).

CONCLUSIONS

Variant rs776746 is associated with a decrease in the transcript levels of CYP3A5, which in turn is associated with increased metabolonic lactone sulfate levels and poor cardiometabolic health.

Interplay between Oxidative Stress and Metabolic Derangements in Non-Alcoholic Fatty Liver Disease: The Role of Selenoprotein P

Background: Pathogenetic mechanisms involved in the progression of non-alcoholic fatty liver disease (NAFLD) are complex and multifactorial. We investigated oxidative stress through the measurement of selenoprotein P (SeP) in serum and we explored its relation to metabolic derangements and liver damage in a group of non-diabetic NAFLD subjects. Methods: 57 NAFLD patients underwent a double-tracer oral glucose tolerance test (OGTT). Insulin resistance (IR) components were calculated at baseline as follows: hepatic-IR = (endogenous glucose production*insulin); peripheral-IR = (glucose rate of disappearance(Rd)); adipose-tissue(AT)-IR as Lipo-IR = (glycerol rate of appearance (Ra)*insulin) or AT-IR = (free fatty acids (FFAs)*insulin). The lipid and amino acid (AA) profiles were assessed by gas chromatography–mass spectrometry. SeP levels were measured by enzyme immunosorbent assay. Results: Circulating SeP correlated with insulin (r_S = 0.28), FFAs (r_S = 0.42), glucose Rd (r_S = −0.33) and glycerol Ra (r_S = −0.34); consistently, SeP levels correlated with Lipo-IR and AT-IR (r_S > 0.4). Among the AA and lipid profiles, SeP inversely correlated with serine (r_S = −0.31), glycine (r_S = −0.44) and branched chain AA (r_S = −0.32), and directly correlated with saturated (r_S = 0.41) and monounsaturated FFAs (r_S = 0.40). Hepatic steatosis and fibrosis increased in subjects with higher levels of SeP. In multivariable regression analysis, SeP was associated with the degree of hepatic fibrosis (t = 2.4, p = 0.022). Conclusions: SeP levels were associated with an altered metabolic profile and to the degree of hepatic fibrosis, suggesting a role in the pathogenesis of NAFLD.

Blood Metabolomic Profiling Confirms and Identifies Biomarkers of Food Intake

Metabolomics can be a tool to identify dietary biomarkers. However, reported food-metabolite associations have been inconsistent, and there is a need to explore further associations. Our aims were to confirm previously reported food-metabolite associations and to identify novel food-metabolite associations. We conducted a cross-sectional analysis of data from 849 participants (57% men) of the PopGen cohort. Dietary intake was obtained using FFQ and serum metabolites were profiled by an untargeted metabolomics approach. We conducted a systematic literature search to identify previously reported food-metabolite associations and analyzed these associations using linear regression. To identify potential novel food-metabolite associations, datasets were split into training and test datasets and linear regression models were fitted to the training datasets. Significant food-metabolite associations were evaluated in the test datasets. Models were adjusted for covariates. In the literature, we identified 82 food-metabolite associations. Of these, 44 associations were testable in our data and confirmed associations of coffee with 12 metabolites, of fish with five, of chocolate with two, of alcohol with four, and of butter, poultry and wine with one metabolite each. We did not identify novel food-metabolite associations; however, some associations were sex-specific. Potential use of some metabolites as biomarkers should consider sex differences in metabolism.