Cerebrospinal Fluid Homovanillic and 5-Hydroxyindoleacetic Acids in a Large Pediatric Population; Establishment of Reference Intervals and Impact of Disease and Medication.

BACKGROUND: Cerebrospinal fluid (CSF) homovanillic (HVA), and 5-hydroxyindoleacetic acids (5-HIAA) are biomarkers of neurological diseases affecting the dopaminergic and serotoninergic pathways. Establishing reference intervals for these metabolites faces the challenges of a lack of healthy controls and a negative correlation with age, making stratified intervals unrealistic. We propose a pipeline to determine continuous reference intervals for HVA and 5-HIAA using an indirect method. We also studied the confounding effects of different variables and explored the impact of antiepileptic and neuroleptic treatments on HVA and 5-HIAA values. METHODS: The study used least squares regression to fit age-concentration curves from a cohort of pediatric patients (n = 1533), where the residuals represent metabolite values excluding age effect. Presuming that HVA and 5-HIAA primary deficiencies characterize a distinct subpopulation, we fitted a two-component finite mixture model in age-normalized data and set reference intervals at the central 95% of the nondeficient population. RESULTS: Patients with primary genetic deficiencies of HVA and/or 5-HIAA consistently fall outside the proposed continuous reference intervals. Using the new continuous reference intervals reduces the number of secondary deficiencies detected compared with using stratified values. No correlations were observed between CSF HVA and 5-HIAA values across the studied drug categories (antiseizure and neuroleptic medications). In addition, biopterin values positively influenced both metabolite concentrations. CONCLUSION: The proposed continuous reference intervals caused a substantial reduction in the number of secondary deficiencies detected, most of which demonstrated no conclusive correlations between the diseases and altered HVA and 5-HIAA values.

The Lipidomic Profile Is Associated with the Dietary Pattern in Subjects with and without Diabetes Mellitus from a Mediterranean Area.

Lipid functions can be influenced by genetics, age, disease states, and lifestyle factors, particularly dietary patterns, which are crucial in diabetes management. Lipidomics is an expanding field involving the comprehensive exploration of lipids from biological samples. In this cross-sectional study, 396 participants from a Mediterranean region, including individuals with type 1 diabetes (T1D), type 2 diabetes (T2D), and non-diabetic individuals, underwent lipidomic profiling and dietary assessment. Participants completed validated food frequency questionnaires, and lipid analysis was conducted using ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC/MS). Multiple linear regression models were used to determine the association between lipid features and dietary patterns. Across all subjects, acylcarnitines (AcCa) and triglycerides (TG) displayed negative associations with the alternate Healthy Eating Index (aHEI), indicating a link between lipidomic profiles and dietary habits. Various lipid species (LS) showed positive and negative associations with dietary carbohydrates, fats, and proteins. Notably, in the interaction analysis between diabetes and the aHEI, we found some lysophosphatidylcholines (LPC) that showed a similar direction with respect to aHEI in non-diabetic individuals and T2D subjects, while an opposite direction was observed in T1D subjects. The study highlights the significant association between lipidomic profiles and dietary habits in people with and without diabetes, particularly emphasizing the role of healthy dietary choices, as reflected by the aHEI, in modulating lipid concentrations. These findings underscore the importance of dietary interventions to improve metabolic health outcomes, especially in the context of diabetes management.

Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus.

BACKGROUND: In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state. METHODS: An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D. RESULTS: A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D. CONCLUSIONS: Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.

Circulating metabolomic and lipidomic changes in subjects with new-onset type 1 diabetes after optimization of glycemic control.

AIMS: To uncover novel candidate metabolomic and lipidomic biomarkers in newly-diagnosed type 1 diabetes (T1DM) after achieving optimal glucose control. METHODS: Comprehensive lipidomic and metabolomic analysis was performed in serum of 12 adults with T1DM at onset and after achieving optimal glycemic control (HbA1c < 7 %) (after 2-6 months). RESULTS: After intensive therapy, subjects (mean age 25.2 years, 58.3 % men) showed decreases in blood glucose (p < 0.001), HbA1c [11.5 % (9.2-13.4) to 6.2 % (5.2 - 6.7); p < 0.001] and changes in 51 identified lipids. Among these changes, we found that triglycerides (TG) containing medium chain fatty acids (TG45:0, TG47:1), sphingomyelins (SM) (SM(d18:2/20:0), SM42:4)), and phosphatidylcholines (PC) (PC(O-26:2), PC(O-30:0), PC(O-32:0), PC(O-42:6), PC(O-44:5), PC(O-38:3), PC(O-33:0), PC(O-46:8), PC(O-44:6), PC(O-40:3), PC(O-42:4), PC(O-46:7), PC(O-46:6), PC(O-44:5), PC(O-42:3), PC(O-44:4)) decreased; whereas PC(35:1), PC(37:1) and TG containing longer chain fatty acids (TG(52:1), TG(55:7), TG(51:2), TG(53:3), TG52:2), TG(53:2), TG(57:3), TG(61:3), TG(61:2) increased. Further, dihydro O-acylceramide (18:1/18:0/16:0), diacylglycerophosphoethanolamine (PE(34:1)), diacylglycerophosphoinositol (PI(38:6), and dihydrosphingomyelins (dihydroSM(36:0), dihydroSM(40:0), dihydroSM(41:0), dihydroSM(42:0)) increased. Uric acid, mannitol, and mannitol-1-acetate levels also increased. CONCLUSIONS: Our data uncovered potential favorable changes in the metabolism of glycerophospholipids, glycerolipids, and sphingolipids in new-onset T1DM after achieving optimal glycemic control. Further research on their potential role in developing diabetes-related complications is needed.

Advanced lipoprotein profile in individuals with normal and impaired glucose metabolism.

INTRODUCTION AND OBJECTIVES: Several types of lipoproteins beyond low-density lipoproteins (LDL) are causally related to cardiovascular disease. We aimed to analyze an advanced lipoprotein profile in individuals with normal and impaired glucose metabolism from different cohorts of a Mediterranean region. METHODS: Cross-sectional study in 929 participants (463 normoglycemia, 250 prediabetes, and 216 type 2 diabetes mellitus) with normal renal function, free from cardiovascular disease, and without lipid-lowering treatment. Conventional and advanced (nuclear magnetic resonance [NMR] spectroscopy) lipoprotein profiles were analyzed. RESULTS: Compared with men, normoglycemic women showed lower serum triglyceride and LDL cholesterol concentrations, lower total LDL particles (P) as well as their subclasses and their cholesterol and triglyceride content, higher high-density lipoproteins (HDL)-P and all HDL-related variables (P≤ .05 for all comparisons). Compared with normoglycemic participants, diabetic participants showed higher large and small very LDL-P concentrations (P <.05) and lower total HDL-P and medium HDL-P concentrations (P <.05). Waist circumference and Fatty Liver Index were positively associated with a proatherogenic profile. CONCLUSIONS: Women had a better advanced lipoprotein profile than did men. Adiposity indexes related to insulin-resistance were positively associated with a proatherogenic lipid profile. NMR revealed altered lipoprotein particles other than LDL in participants with diabetes, frequently associated with an increased cardiovascular risk. Our findings support the usefulness of extended lipoprotein analysis by NMR spectroscopy to uncover new therapeutic targets to prevent cardiovascular events in at-risk participants.

Circulating CD5L is associated with cardiovascular events and all-cause mortality in individuals with chronic kidney disease.

This study assessed the association of CD5L and soluble CD36 (sCD36) with the risk of a cardiovascular event (CVE), including CV death and all-cause mortality in CKD. We evaluated the association of CD5L and sCD36 with a predefined composite CV endpoint (unstable angina, myocardial infarction, transient ischemic attack, cerebrovascular accident, congestive heart failure, arrhythmia, peripheral arterial disease [PAD] or amputation by PAD, aortic aneurysm, or death from CV causes) and all-cause mortality using Cox proportional hazards regression, adjusted for CV risk factors. The analysis included 1,516 participants free from pre-existing CV disease followed up for 4 years. The median age was 62 years, 38.8% were female, and 26.8% had diabetes. There were 98 (6.5%) CVEs and 72 (4.8%) deaths, of which 26 (36.1%) were of CV origin. Higher baseline CD5L concentration was associated with increased risk of CVE (HR, 95% CI, 1.17, 1.0-1.36), and all-cause mortality (1.22, 1.01-1.48) after adjusting for age, sex, diabetes, systolic blood pressure, dyslipidemia, waist circumference, smoking, and CKD stage. sCD36 showed no association with adverse CV outcomes or mortality. Our study showed for the first time that higher concentrations of CD5L are associated with future CVE and all-cause mortality in individuals with CKD.

mWISE: An Algorithm for Context-Based Annotation of Liquid Chromatography-Mass Spectrometry Features through Diffusion in Graphs.

Untargeted metabolomics using liquid chromatography coupled to mass spectrometry (LC-MS) allows the detection of thousands of metabolites in biological samples. However, LC-MS data annotation is still considered a major bottleneck in the metabolomics pipeline since only a small fraction of the metabolites present in the sample can be annotated with the required confidence level. Here, we introduce mWISE (metabolomics wise inference of speck entities), an R package for context-based annotation of LC-MS data. The algorithm consists of three main steps aimed at (i) matching mass-to-charge ratio values to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, (ii) clustering and filtering the potential KEGG candidates, and (iii) building a final prioritized list using diffusion in graphs. The algorithm performance is evaluated with three publicly available studies using both positive and negative ionization modes. We have also compared mWISE to other available annotation algorithms in terms of their performance and computation time. In particular, we explored four different configurations for mWISE, and all four of them outperform xMSannotator (a state-of-the-art annotator) in terms of both performance and computation time. Using a diffusion configuration that combines the biological network obtained from the FELLA R package and raw scores, mWISE shows a sensitivity mean (standard deviation) across data sets of 0.63 (0.07), while xMSannotator achieves a sensitivity of 0.55 (0.19). We have also shown that the chemical structures of the compounds proposed by mWISE are closer to the original compounds than those proposed by xMSannotator. Finally, we explore the diffusion prioritization separately, showing its key role in the annotation process. mWISE is freely available on GitHub (https://github.com/b2slab/mWISE) under a GPL license.

The Circulating Fatty Acid Transporter Soluble CD36 Is Not Associated with Carotid Atherosclerosis in Subjects with Type 1 and Type 2 Diabetes Mellitus.

This study aimed to determine the association of fatty acid transporter plasma soluble cluster of differentiation 36 (sCD36) with subclinical carotid atherosclerosis (SCA). A cross-sectional study was conducted in 1023 subjects, 225 with type 1 diabetes (T1D), 276 with type 2 diabetes (T2D) and 522 who were nondiabetic. Carotid atherosclerotic plaque (CAP) presence was determined using B-mode carotid ultrasound imaging. sCD36 were analysed by ELISA, and CD36 surface receptor and mRNA expression were measured by flow cytometry and real-time PCR. Logistic regression models were used to evaluate sCD36 as a biomarker of SCA. Up to 376 (36.75%) participants had at least one CAP, 76 T1D, 164 T2D and 136 without diabetes, while the remaining 647 (63.25%) did not have any CAP. There were no differences in sCD36 between patients with and without CAP in T1D (p = 0.287) or T2D (p = 0.513). Although nondiabetic subjects with plaques had lower sCD36 levels than those without (p = 0.023), the multivariate models revealed no association of sCD36 with CAP in any of the three study groups. No differences were found in surface CD36 or CD36 mRNA expression between the patients with and without CAP. sCD36 is not associated with SCA in type 1 or type 2 diabetic or in nondiabetic subjects.