Urinary metabolomics profiling by cardiovascular risk factors in young adults: the African Prospective study on Early Detection and Identification of Cardiovascular disease and Hypertension study

Exploring the interplay between kidney function and urinary metabolites in young adults: the African-PREDICT study

The exposure to modifiable risk factors at young ages have been linked to premature fatal and non-fatal cardiovascular and kidney outcomes. The use of urinary metabolomics has shown strong predictability of kidney function and cardiovascular disease (CVD). We therefore determined the associations between estimated glomerular filtration rate (eGFR) and urinary metabolites in young adults with and without CVD risk factors. Apparently healthy Black and White sexes were included (aged 20-30 years) and categorised by the presence or absence of risk factors, i.e., obesity, physical inactivity, smoking, excessive alcohol intake, masked hypertension, hyperglycemia, dyslipidemia and low socio-economic status, forming the CVD risk group (N = 1036), CVD risk clusters (i.e. presenting with 1 CVD risk factor (N = 344), 2 CVD risk factors (N = 360) and 3 + CVD risk factors (N = 332)) and the control group (N = 166). eGFR was calculated with CKD-EPI equations. A targeted metabolomics approach using liquid chromatography-tandem mass spectrometry was used to measure amino acids and acylcarnitines. Lower cystatin C-based eGFR were indicated in the CVD risk group, 2 and 3 + CVD risk clusters compared to the control group (all P ≤ 0.033). In the CVD risk group, eGFR associated positively with histidine, lysine, asparagine, glycine, serine, glutamine, dimethylglycine, threonine, alanine, creatine, cystine, methionine, tyrosine, pyroglutamic acid, leucine/isoleucine, aspartic acid, tryptophan, glutamic acid, free carnitine, acetylcarnitine, propionylcarnitine, isovalerylcarnitine, octanoylcarnitine and decanoylcarnitine (all P ≤ 0.044), with similar results found in the CVD risk clusters, particularly the 2 CVD risk cluster. eGFR was positively associated with metabolites linked to aromatic amino acid and branched-chain amino acid metabolism, energy metabolism and oxidative stress. These findings may indicate altered reabsorption of these metabolites or altered metabolic regulation to preserve renal health in the setting of CVD risk factors at this young age without established CVD.

Metabolomic Insights on Potassium Excretion, Blood Pressure, and Glucose Homeostasis: The African-PREDICT Study

BACKGROUND

Low-potassium intake is associated with a higher risk of type 2 diabetes and hypertension. Both conditions occur more frequently in Black populations, who also consume less potassium-rich foods.

OBJECTIVES

Using metabolomics to identify dysregulated metabolic pathways associated with low-potassium excretion may procure more accurate entry points for nutritional prevention and intervention for type 2 diabetes and hypertension.

METHODS

A total of 440 White and 350 Black adults from the African-PREDICT study (aged 20-30 y) were included. Twenty-four-hour blood pressure (BP) was measured. Potassium, sodium, and fasting glucose concentrations were analyzed in 24-h urine and plasma samples. Liquid chromatography-tandem mass spectrometry-based metabolomics included the analyses of amino acids and acylcarnitines in spot urine samples.

RESULTS

Black participants had lower urinary potassium concentrations than Whites (36.6 compared with 51.1 mmol/d; P < 0.001). In White but not Black adults, urinary potassium correlated positively with 2-aminoadipic acid (2-AAA) (r = 0.176), C3-[propionyl]carnitine (r = 0.137), C4-[butyryl]carnitine (r = 0.169) and C5-[isovaleryl]carnitine (r = 0.167) in unadjusted and 2-AAA (r = 0.158) and C4-carnitine (r = 0.160) in adjusted analyses (all P < 0.05 and q < 0.05). Elevated C0-, C3-, and C5-carnitine in turn were positively associated with systolic BP (Black and White groups), diastolic BP (Black group), and glucose (White group) (all P < 0.05).

CONCLUSIONS

Racial differences are an important consideration when investigating nutrient-metabolite relationships and the role thereof in cardiovascular disease. Only in White adults did urinary potassium associate with 2-AAA and short-chain acylcarnitines. These metabolites were positively related to BP and fasting plasma glucose concentrations. In White adults, the metabolomic profiles related to potassium excretion may contribute to BP regulation and glucose homeostasis. This trial was registered at clinicaltrials.gov as NCT03292094.

Biochemical Profiling of Urine Metabolome in Premature Infants Based on LC-MS Considering Maternal Influence

In this study, Liquid Chromatography-Mass Spectrometry (LC-MS)-based metabolomics profiling was conducted to elucidate the urinary profiles of premature infants during early and late postnatal stages. As a result, we discovered significant excretion of maternal drugs in early-stage infants and identified crucial metabolites like hormones and amino acids. These findings shed light on the maternal impact on neonatal metabolism and underscore the beneficial effects of breastfeeding on the metabolism of essential amino acids in infants. This research not only enhances our understanding of maternal-infant nutritional interactions and their long-term implications for preterm infants but also offers critical insights into the biochemical characteristics and physiological mechanisms of preterm infants, laying a groundwork for future clinical studies focused on neonatal development and health.

CARDPSoML: Comparative approach to analyze and predict cardiovascular disease based on medical report data and feature fusion approach

Background and Aims

Diabetes patients are at high risk for cardiovascular disease (CVD), which makes early identification and prompt management essential. To diagnose CVD in diabetic patients, this work attempts to provide a feature-fusion strategy employing supervised learning classifiers.

Methods

Preprocessing patient data is part of the method, and it includes important characteristics connected to diabetes including insulin resistance and blood glucose levels. Principal component analysis and wavelet transformations are two examples of feature extraction techniques that are used to extract pertinent characteristics. The supervised learning classifiers, such as neural networks, decision trees, and support vector machines, are then trained and assessed using these characteristics.

Results

Based on the area under the receiver operating characteristic curve, sensitivity, specificity, and accuracy, these classifiers' performance is closely evaluated. The assessment findings show that the classifiers have a good accuracy and area under the receiver operating characteristic curve value, suggesting that the suggested strategy may be useful in diagnosing CVD in patients with diabetes.

Conclusion

The recommended method shows potential as a useful tool for developing clinical decision support systems and for the early detection of CVD in diabetes patients. To further improve diagnostic skills, future research projects may examine the use of bigger and more varied datasets as well as different machine learning approaches. Using an organized strategy is a crucial first step in tackling the serious problem of CVD in people with diabetes.

Role of untargeted omics biomarkers of exposure and effect for tobacco research

Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.

Early vascular ageing phenotypes and urinary targeted metabolomics in children and young adults: the ExAMIN Youth SA and African-PREDICT studies

Some individuals are susceptible to accelerated biological ageing, resulting in premature alterations in arterial structure and function. Identifying early-onset vascular ageing characterised by arterial stiffening is vital for intervention and preventive strategies. We stratified and phenotyped healthy children (5-9 yrs) and young adults (20-30 yrs) into their vascular ageing extremes established by carotid-femoral pulse wave velocity (cfPWV) percentiles (i.e., healthy vascular ageing (HVA) and early vascular ageing (EVA)). We compared anthropometric, cardiovascular, and metabolomic profiles and explored associations between cfPWV and urinary metabolites. Children and adults in the EVA groups displayed higher levels of adiposity, cardiovascular, and lifestyle risk factors (adults only) (all p ≤ 0.018). In adults, several urinary metabolites were lower in the EVA group (all q ≤ 0.039) when compared to the HVA group, with no differences observed in children. In multiple regression analysis (adults only), we found inverse associations between cfPWV with histidine (adj. R2 = 0.038; β = -0.192; p = 0.013) and beta-alanine (adj. R2 = 0.034; β = -0.181; p = 0.019) in the EVA group, but with arginine (adj. R2 = 0.021; β = -0.160; p = 0.024) in the HVA group. The inverse associations of beta-alanine and histidine with cfPWV in the EVA group is suggestive that asymptomatic young adults who present with an altered metabolomic and less desired cardiovascular profile in combination with unfavourable lifestyle behaviours may be predisposed to early-onset vascular ageing. Taken together, screening on both a phenotypic and metabolic level may prove important in the early detection, prevention, and intervention of advanced biological ageing.

Using urinary metabolomics to identify metabolic pathways linked to cardiac structural alterations in young adults: The African-PREDICT study

BACKGROUND AND AIMS

Risk factor exposure from young ages was shown to contribute to cardiovascular events - cardiac hypertrophy, which may be accompanied by an altered metabolism. To determine how early metabolic alterations associate with myocardial structural changes, we profiled urinary metabolites in young adults with cardiovascular disease (CVD) risk factor(s) and a control group without CVD risk factors.

METHODS AND RESULTS

We included healthy adults (N = 1202), aged 20-30 years, stratified based on risk factors, i.e., obesity, physical inactivity, elevated blood pressure (BP), hyperglycemia, dyslipidemia, low socio-economic status, smoking and excessive alcohol use - forming the CVD risk group (N = 1036) and the control group (N = 166). Relative wall thickness (RWT) and left ventricular mass index (LVMi) were measured using echocardiography. Targeted metabolomics data were obtained using a liquid chromatography-tandem mass spectrometry method. Clinic systolic BP, 24 h BP and RWT were higher in the CVD risk group compared to the control group (all P ≤ 0.031). Exclusively in the CVD risk group, RWT associated with creatine and dodecanoylcarnitine; while LVMi associated with glycine, serine, glutamine, threonine, alanine, citrulline, creatine, proline, pyroglutamic acid and glutamic acid (all P ≤ 0.040). Exclusively in the control group, LVMi associated with propionylcarnitine and butyrylcarnitine (all P ≤ 0.009).

CONCLUSION

In young adults without CVD, but with CVD risk factors, LVMi and RWT associated with metabolites linked energy metabolism (shifting from solely fatty acid oxidation to glycolysis, with impaired creatine kinase activity) and oxidative stress. Our findings support early onset metabolic changes accompanying cardiac structural alterations due to lifestyle and behavioural risk factors.

Markers of arterial stiffness and urinary metabolomics in young adults with early cardiovascular risk: the African-PREDICT study

INTRODUCTION

Increased exposure to risk factors in the young and healthy contributes to arterial changes, which may be accompanied by an altered metabolism.

OBJECTIVES

To increase our understanding of early metabolic alterations and how they associate with markers of arterial stiffness, we profiled urinary metabolites in young adults with cardiovascular disease (CVD) risk factor(s) and in a control group without CVD risk factors.

METHODS

We included healthy black and white women and men (N = 1202), aged 20-30 years with a detailed CVD risk factor profile, reflecting obesity, physical inactivity, smoking, excessive alcohol intake, masked hypertension, hyperglycemia, dyslipidemia and low socio-economic status, forming the CVD risk group (N = 1036) and the control group (N = 166). Markers of arterial stiffness, central systolic blood pressure (BP) and pulse wave velocity were measured. A targeted metabolomics approach was followed by measuring amino acids and acylcarnitines using a liquid chromatography-tandem mass spectrometry method.

RESULTS

In the CVD risk group, central systolic BP (adjusted for age, sex, ethnicity) was negatively associated with histidine, arginine, asparagine, serine, glutamine, dimethylglycine, threonine, GABA, proline, methionine, pyroglutamic acid, aspartic acid, glutamic acid, branched chain amino acids (BCAAs) and butyrylcarnitine (all P ≤ 0.048). In the same group, pulse wave velocity (adjusted for age, sex, ethnicity, mean arterial pressure) was negatively associated with histidine, lysine, threonine, 2-aminoadipic acid, BCAAs and aromatic amino acids (AAAs) (all P ≤ 0.044). In the control group, central systolic BP was negatively associated with pyroglutamic acid, glutamic acid and dodecanoylcarnitine (all P ≤ 0.033).

CONCLUSION

In a group with increased CVD risk, markers of arterial stiffness were negatively associated with metabolites related to AAA and BCAA as well as energy metabolism and oxidative stress. Our findings may suggest that metabolic adaptations may be at play in response to increased CVD risk to maintain cardiovascular integrity.