Open Access
Metabolites, volume 12, issue 12, pages 1185
Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults
Shestakova Ksenia M.
1
,
Kukharenko Alexey V
2
,
Markin Pavel A
1
,
Kozhevnikova Maria
3
,
Korobkova Ekaterina O
3
,
Brito Alex
2
,
Baskhanova Sabina N
1
,
Mesonzhnik Natalia V.
1
,
Belenkov Yuri N.
3
,
Pyatigorskaya Natalia V
4
,
Tobolkina Elena
5
,
Rudaz Serge
5
,
3
Publication type: Journal Article
Publication date: 2022-11-27
Biochemistry
Molecular Biology
Endocrinology, Diabetes and Metabolism
Abstract
Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p < 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling.
Citations by journals
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1
2
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Scientific Reports
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Scientific Reports
2 publications, 28.57%
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Journal of Pharmaceutical and Biomedical Analysis
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Journal of Pharmaceutical and Biomedical Analysis
1 publication, 14.29%
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Journal of Cardiovascular Development and Disease
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Journal of Cardiovascular Development and Disease
1 publication, 14.29%
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Metabolomics
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Metabolomics
1 publication, 14.29%
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Ukrainian Biochemical Journal
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Ukrainian Biochemical Journal, 1, 14.29%
Ukrainian Biochemical Journal
1 publication, 14.29%
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Metabolites
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Metabolites
1 publication, 14.29%
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1
2
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Citations by publishers
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1
2
3
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Springer Nature
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Springer Nature
3 publications, 42.86%
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Multidisciplinary Digital Publishing Institute (MDPI)
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Multidisciplinary Digital Publishing Institute (MDPI)
2 publications, 28.57%
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Elsevier
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Elsevier
1 publication, 14.29%
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Palladin Institute of Biochemistry of the NASU
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Palladin Institute of Biochemistry of the NASU, 1, 14.29%
Palladin Institute of Biochemistry of the NASU
1 publication, 14.29%
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1
2
3
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Moskaleva N. E. et al. Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults // Metabolites. 2022. Vol. 12. No. 12. p. 1185.
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Moskaleva N. E., Shestakova K. M., Kukharenko A. V., Markin P. A., Kozhevnikova M., Korobkova E. O., Brito A., Baskhanova S. N., Mesonzhnik N. V., Belenkov Y. N., Pyatigorskaya N. V., Tobolkina E., Rudaz S., Appolonova S. A. Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults // Metabolites. 2022. Vol. 12. No. 12. p. 1185.
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TY - JOUR
DO - 10.3390/metabo12121185
UR - https://doi.org/10.3390%2Fmetabo12121185
TI - Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults
T2 - Metabolites
AU - Moskaleva, Natalia E.
AU - Shestakova, Ksenia M.
AU - Kukharenko, Alexey V
AU - Markin, Pavel A
AU - Korobkova, Ekaterina O
AU - Brito, Alex
AU - Baskhanova, Sabina N
AU - Mesonzhnik, Natalia V.
AU - Belenkov, Yuri N.
AU - Pyatigorskaya, Natalia V
AU - Tobolkina, Elena
AU - Rudaz, Serge
AU - Appolonova, Svetlana A
AU - Kozhevnikova, Maria
PY - 2022
DA - 2022/11/27 00:00:00
PB - Multidisciplinary Digital Publishing Institute (MDPI)
SP - 1185
IS - 12
VL - 12
SN - 2218-1989
ER -
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@article{2022_Moskaleva,
author = {Natalia E. Moskaleva and Ksenia M. Shestakova and Alexey V Kukharenko and Pavel A Markin and Ekaterina O Korobkova and Alex Brito and Sabina N Baskhanova and Natalia V. Mesonzhnik and Yuri N. Belenkov and Natalia V Pyatigorskaya and Elena Tobolkina and Serge Rudaz and Svetlana A Appolonova and Maria Kozhevnikova},
title = {Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults},
journal = {Metabolites},
year = {2022},
volume = {12},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
month = {nov},
url = {https://doi.org/10.3390%2Fmetabo12121185},
number = {12},
pages = {1185},
doi = {10.3390/metabo12121185}
}
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MLA
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Moskaleva, Natalia E., et al. “Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults.” Metabolites, vol. 12, no. 12, Nov. 2022, p. 1185. https://doi.org/10.3390%2Fmetabo12121185.