Changes in Amino Acid and Acylcarnitine Plasma Profiles for Distinguishing Patients with Multiple Sclerosis from Healthy Controls

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Changes in Amino Acid and Acylcarnitine Plasma Profiles for Distinguishing Patients with Multiple Sclerosis from Healthy Controls. / Kasakin, Marat F.; Rogachev, Artem D.; Zaigraev, Vladimir J. и др.

в: Multiple sclerosis international, Том 2020, 9010937, 15.07.2020.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

BibTeX

@article{7bfef965080a414e8f89b75da4f9dda8,

title = "Changes in Amino Acid and Acylcarnitine Plasma Profiles for Distinguishing Patients with Multiple Sclerosis from Healthy Controls",

abstract = "McDonald criteria and magnetic resonance imaging (MRI) are used for the diagnosis of multiple sclerosis (MS); nevertheless, it takes a considerable amount of time to make a clinical decision. Amino acid and fatty acid metabolic pathways are disturbed in MS, and this information could be useful for diagnosis. The aim of our study was to find changes in amino acid and acylcarnitine plasma profiles for distinguishing patients with multiple sclerosis from healthy controls. We have applied a targeted metabolomics approach based on tandem mass-spectrometric analysis of amino acids and acylcarnitines in dried plasma spots followed by multivariate statistical analysis for discovery of differences between MS (n=16) and control (n=12) groups. It was found that partial least square discriminant analysis yielded better group classification as compared to principal component linear discriminant analysis and the random forest algorithm. All the three models detected noticeable changes in the amino acid and acylcarnitine profiles in the MS group relative to the control group. Our results hold promise for further development of the clinical decision support system.",

keywords = "METABOLISM, METABOLOMICS, BIOMARKERS",

author = "Kasakin, {Marat F.} and Rogachev, {Artem D.} and Zaigraev, {Vladimir J.} and Koval, {Vladimir V.} and Pokrovsky, {Andrey G.}",

note = "Copyright {\textcopyright} 2020 Marat F. Kasakin et al.",

year = "2020",

month = jul,

day = "15",

doi = "10.1155/2020/9010937",

language = "English",

volume = "2020",

journal = "Multiple sclerosis international",

issn = "2090-2654",

publisher = "Hindawi Publishing Corporation",

}

RIS

TY - JOUR

T1 - Changes in Amino Acid and Acylcarnitine Plasma Profiles for Distinguishing Patients with Multiple Sclerosis from Healthy Controls

AU - Kasakin, Marat F.

AU - Rogachev, Artem D.

AU - Zaigraev, Vladimir J.

AU - Koval, Vladimir V.

AU - Pokrovsky, Andrey G.

PY - 2020/7/15

Y1 - 2020/7/15

N2 - McDonald criteria and magnetic resonance imaging (MRI) are used for the diagnosis of multiple sclerosis (MS); nevertheless, it takes a considerable amount of time to make a clinical decision. Amino acid and fatty acid metabolic pathways are disturbed in MS, and this information could be useful for diagnosis. The aim of our study was to find changes in amino acid and acylcarnitine plasma profiles for distinguishing patients with multiple sclerosis from healthy controls. We have applied a targeted metabolomics approach based on tandem mass-spectrometric analysis of amino acids and acylcarnitines in dried plasma spots followed by multivariate statistical analysis for discovery of differences between MS (n=16) and control (n=12) groups. It was found that partial least square discriminant analysis yielded better group classification as compared to principal component linear discriminant analysis and the random forest algorithm. All the three models detected noticeable changes in the amino acid and acylcarnitine profiles in the MS group relative to the control group. Our results hold promise for further development of the clinical decision support system.

AB - McDonald criteria and magnetic resonance imaging (MRI) are used for the diagnosis of multiple sclerosis (MS); nevertheless, it takes a considerable amount of time to make a clinical decision. Amino acid and fatty acid metabolic pathways are disturbed in MS, and this information could be useful for diagnosis. The aim of our study was to find changes in amino acid and acylcarnitine plasma profiles for distinguishing patients with multiple sclerosis from healthy controls. We have applied a targeted metabolomics approach based on tandem mass-spectrometric analysis of amino acids and acylcarnitines in dried plasma spots followed by multivariate statistical analysis for discovery of differences between MS (n=16) and control (n=12) groups. It was found that partial least square discriminant analysis yielded better group classification as compared to principal component linear discriminant analysis and the random forest algorithm. All the three models detected noticeable changes in the amino acid and acylcarnitine profiles in the MS group relative to the control group. Our results hold promise for further development of the clinical decision support system.

KW - METABOLISM

KW - METABOLOMICS

KW - BIOMARKERS

U2 - 10.1155/2020/9010937

DO - 10.1155/2020/9010937

M3 - Article

C2 - 32733709

VL - 2020

JO - Multiple sclerosis international

JF - Multiple sclerosis international

SN - 2090-2654

M1 - 9010937

ER -

ID: 25566040