Dataset Information

Nuclear Magnetic Resonance-Based Lipidomics in the Assessment of Cardiometabolic Risk in Type 1 Diabetes: An Exploratory Analysis.

ABSTRACT:

Introduction

Cardiovascular disease (CVD) is the leading cause of mortality in type 1 diabetes (T1D). However, there is a need for daily practice tools for identifying those more prone to suffer from these events. We aimed to assess the relationships between nuclear magnetic resonance (¹H NMR)-based lipidomic analysis and several CVD risk variables (including preclinical carotid atherosclerosis) in individuals with T1D at high risk.

Methods

We included patients with T1D without CVD, with at least one of the following: age ≥ 40 years, diabetic kidney disease, or ≥ 10 years of evolution with another risk factor. The presence of plaque (intima-media thickness > 1.5 mm) was determined by standardized ultrasonography protocol. Lipidomic analysis was performed by ¹H NMR. Bivariate and multivariate-adjusted differences in ¹H NMR lipidomics were evaluated.

Results

We included n = 131 participants (49.6% female, age 46.4 ± 10.3 years, diabetes duration 27.0 ± 9.5 years, 47.3% on statins). Carotid plaques were present in 28.2% of the individuals (n = 12, with ≥ 3 plaques). Glucose (HbA1c), anthropometric (body mass index and waist circumference), and insulin resistance-related (fatty liver index and estimated glucose disposal rate) variables were those most associated with ¹H NMR-derived lipidomic analysis (p < 0.01 for all). Regarding preclinical atherosclerosis, sphingomyelin was independently associated with carotid plaque presence (for 0.1 mmol/L increase, OR 0.50 [0.28-0.86]; p = 0.013), even after adjusting for age, sex, hypertension, statin use, mean 5-year HbA1c and diabetes duration. Furthermore, linoleic acid and ω-6 fatty acids remained independently associated with higher plaque burden (≥ 3 plaques) in multivariate models (0.17 [0.03-0.93] and 0.27 [0.07-0.97], respectively; p < 0.05 for both).

Conclusion

In our preliminary study of individuals with T1D at high risk, several ¹H NMR-derived lipidomic parameters were independently associated with preclinical atherosclerosis. Specifically, ω-6 fatty acids and linoleic acid seem promising for identifying those with higher plaque burden.

SUBMITTER: Seres-Noriega T

PROVIDER: S-EPMC9981843 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Publications

Nuclear Magnetic Resonance-Based Lipidomics in the Assessment of Cardiometabolic Risk in Type 1 Diabetes: An Exploratory Analysis.

Serés-Noriega Tonet T Ortega Emilio E Perea Verónica V Giménez Marga M Boswell Laura L Mariaca Karla K Font Carla C Mesa Alex A Viñals Clara C Blanco Jesús J Vinagre Irene I Pané Adriana A Esmatjes Enric E Conget Ignacio I Amor Antonio J AJ

Diabetes therapy : research, treatment and education of diabetes and related disorders 20230203 3

<h4>Introduction</h4>Cardiovascular disease (CVD) is the leading cause of mortality in type 1 diabetes (T1D). However, there is a need for daily practice tools for identifying those more prone to suffer from these events. We aimed to assess the relationships between nuclear magnetic resonance (<sup>1</sup>H NMR)-based lipidomic analysis and several CVD risk variables (including preclinical carotid atherosclerosis) in individuals with T1D at high risk.<h4>Methods</h4>We included patients with T1D ...[more]

PMID: 36732434

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Project description:Magnetic resonance imaging (MRI) has evolved rapidly over the past few decades as one of the most flexible tools in medical research and diagnostic imaging. MRI facilities are important sources of multiple exposure to electromagnetic fields for both patients and health-care staff, due to the presence of electromagnetic fields of multiple frequency ranges, different temporal variations, and field strengths. Due to the increasing use and technological advancements of MRI systems, clearer insights into exposure assessment and a better understanding of possible harmful effects due to long-term exposures are highly needed. In the present exploratory study, exposure assessment and biomonitoring of MRI workers at the Radio-diagnostics Unit of the National Cancer Institute of Naples "Pascale Foundation" (Naples, Italy) have been carried out. In particular, exposure to the MRI static magnetic field (SMF) has been evaluated by means of personal monitoring, while an application tool has been developed to provide an estimate of motion-induced, time-varying electric fields. Measurement results have highlighted a high day-to-day and worker-to-worker variability of the exposure to the SMF, which strongly depends on the characteristics of the environment and on personal behaviors, and the developed application tool can be adopted as an easy-to-use tool for rapid and qualitative evaluation of motion-induced, time-varying electric field exposure. Regarding biomonitoring, the 24 workers of the Radio-diagnostics Unit were enrolled to evaluate both spontaneous and mitomycin C-induced chromosomal fragility in human peripheral blood lymphocytes, by means of the cytokinesis-block micronucleus assay. The study subjects were 12 MRI workers, representative of different professional categories, as the exposed group, and 12 workers with no MRI exposure history, as the reference group. The results show a high worker-to-worker variability for both field exposure assessment and biomonitoring, as well as several critical issues and practicalities to be faced with in this type of investigations. The procedures for risk assessment and biomonitoring proposed here can be used to inform future research in this field, which will require a refinement of exposure assessment methods and an enlargement of the number of subjects enrolled in the biomonitoring study to gain robust statistics and reliable results.

Dataset Information

Nuclear Magnetic Resonance-Based Lipidomics in the Assessment of Cardiometabolic Risk in Type 1 Diabetes: An Exploratory Analysis.

Introduction

Methods

Results

Conclusion

Publications

Nuclear Magnetic Resonance-Based Lipidomics in the Assessment of Cardiometabolic Risk in Type 1 Diabetes: An Exploratory Analysis.

Similar Datasets

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