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A Robust Multivariate Approach Unveils a 1 H-NMR-Based Spectral Metabolomics Signature Predictive of Cardiovascular Disease in People with Type 2 Diabetes: A Prospective Di@bet.es Cohort Study.

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Název: A Robust Multivariate Approach Unveils a 1 H-NMR-Based Spectral Metabolomics Signature Predictive of Cardiovascular Disease in People with Type 2 Diabetes: A Prospective Di@bet.es Cohort Study.
Autoři: Rehues P; Departament de Medicina i Cirurgia, Universitat Rovira i Virgili, Unitat de Recerca En Lípids i Arteriosclerosi, Reus 43201, Spain.; Institut d'Investigació Sanitària Pere Virgili, Reus 43204, Spain.; Centro de Investigación Biomédica En Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid 28029, Spain., Guardiola M; Departament de Medicina i Cirurgia, Universitat Rovira i Virgili, Unitat de Recerca En Lípids i Arteriosclerosi, Reus 43201, Spain.; Institut d'Investigació Sanitària Pere Virgili, Reus 43204, Spain.; Centro de Investigación Biomédica En Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid 28029, Spain., Amigó N; Centro de Investigación Biomédica En Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid 28029, Spain.; Biosfer Teslab, Reus 43206, Spain.; Departament de Ciències Mèdiques Bàsiques, Universitat Rovira i Virgili, Reus 43201, Spain.; Metabolomics Platform, Universitat Rovira i Virgili, Reus 43204, Spain., Rojo-Martínez G; Centro de Investigación Biomédica En Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid 28029, Spain.; UGC endocrinología y Nutrición, Hospital Regional Universitario de Málaga, IBIMA-Plataforma BIONAND, Málaga 29590, Spain., Mallol-Parera R; Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona 08007, Spain., Ribalta J; Departament de Medicina i Cirurgia, Universitat Rovira i Virgili, Unitat de Recerca En Lípids i Arteriosclerosi, Reus 43201, Spain.; Institut d'Investigació Sanitària Pere Virgili, Reus 43204, Spain.; Centro de Investigación Biomédica En Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid 28029, Spain.
Zdroj: Journal of proteome research [J Proteome Res] 2025 Dec 05; Vol. 24 (12), pp. 6131-6141. Date of Electronic Publication: 2025 Nov 19.
Způsob vydávání: Journal Article
Jazyk: English
Informace o časopise: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101128775 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1535-3907 (Electronic) Linking ISSN: 15353893 NLM ISO Abbreviation: J Proteome Res Subsets: MEDLINE
Imprint Name(s): Original Publication: Washington, D.C. : American Chemical Society, c2002-
Výrazy ze slovníku MeSH: Diabetes Mellitus, Type 2*/complications , Diabetes Mellitus, Type 2*/metabolism , Metabolomics*/methods , Cardiovascular Diseases*/metabolism , Cardiovascular Diseases*/diagnosis , Cardiovascular Diseases*/etiology , Cardiovascular Diseases*/complications , Proton Magnetic Resonance Spectroscopy*/methods, Humans ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Multivariate Analysis ; Case-Control Studies ; Cholesterol, LDL/blood ; Risk Factors
Abstrakt: People with type 2 diabetes mellitus (T2DM) are at high risk of cardiovascular disease (CVD), which is often not explained by traditional risk factors such as low-density lipoprotein (LDL) cholesterol. Proton nuclear magnetic resonance ( 1 H NMR) metabolomics is a promising tool to help explain this residual risk. This study aimed to evaluate the incidence of CVD in people with T2DM via untargeted 1 H NMR data. The 1 H NMR raw spectra of 24 cases and 24 controls (with basal T2DM and with/without CVD at follow-up) matched by age, sex, body mass index, and LDL cholesterol from the Di@bet.es cohort were processed, and the peak-picked features ( p = 269) were used in a partial least-squares discriminant analysis classification with repeated double cross-validation and validated against permuted data sets (AUC = 0.758; p -value = 0.011). For each feature, a stringent variable selection method analyzing the distributions of variable importance in projection scores and beta coefficients across all the repeated models was used, yielding a metabolomic signature composed of 16 selected features related to inflammation, triglycerides, muscular function, and HDL particles, together with features putatively arising from albumin, although further validation of the annotations is needed. In summary, untargeted 1 H NMR metabolomics can help assess cardiovascular risk in people with T2DM beyond LDL cholesterol.
Contributed Indexing: Keywords: cardiovascular disease; low molecular-weight metabolites; metabolomics; multivariate data analysis; nuclear magnetic resonance spectroscopy; partial least-squares discriminant analysis; type 2 diabetes mellitus
Substance Nomenclature: 0 (Cholesterol, LDL)
Entry Date(s): Date Created: 20251119 Date Completed: 20251205 Latest Revision: 20251205
Update Code: 20251205
DOI: 10.1021/acs.jproteome.5c00662
PMID: 41258650
Databáze: MEDLINE
Popis
Abstrakt:People with type 2 diabetes mellitus (T2DM) are at high risk of cardiovascular disease (CVD), which is often not explained by traditional risk factors such as low-density lipoprotein (LDL) cholesterol. Proton nuclear magnetic resonance ( <sup>1</sup> H NMR) metabolomics is a promising tool to help explain this residual risk. This study aimed to evaluate the incidence of CVD in people with T2DM via untargeted <sup>1</sup> H NMR data. The <sup>1</sup> H NMR raw spectra of 24 cases and 24 controls (with basal T2DM and with/without CVD at follow-up) matched by age, sex, body mass index, and LDL cholesterol from the Di@bet.es cohort were processed, and the peak-picked features ( p = 269) were used in a partial least-squares discriminant analysis classification with repeated double cross-validation and validated against permuted data sets (AUC = 0.758; p -value = 0.011). For each feature, a stringent variable selection method analyzing the distributions of variable importance in projection scores and beta coefficients across all the repeated models was used, yielding a metabolomic signature composed of 16 selected features related to inflammation, triglycerides, muscular function, and HDL particles, together with features putatively arising from albumin, although further validation of the annotations is needed. In summary, untargeted <sup>1</sup> H NMR metabolomics can help assess cardiovascular risk in people with T2DM beyond LDL cholesterol.
ISSN:1535-3907
DOI:10.1021/acs.jproteome.5c00662