Back

Amino acid profiling of COVID-19 patients blood serum

Russkikh, Y.; Sushentseva, N.; Popov, O.; Apalko, S.; Shimansky, V. S.; Asinovskaya, A.; Mosenko, S.; Sarana, A.; Scherbak, S.

2024-03-06 infectious diseases
10.1101/2024.03.05.24303773 medRxiv
Show abstract

Main objectives of this study were to analyse metabolomic profile features of patients with COVID-19 using mass spectrometry techniques while taking into account the clinical and laboratory history, and to study the relationship between the severity of COVID-19 symptoms and the concentration of primary metabolites, primarily amino acids. We used frozen blood serum samples of 935 COVID-19 patients from the City Hospital No. 40 biobank collection. Metabolomic profile was studied by HPLS-MS/MS method. R programming language was used for statistical data processing. The difference of metabolic profile of patients with COVID-19 depending on the severity of the disease was revealed based on the performed analysis - for 52 out of 84 detected compounds there were differences with reliability p<0,01. Statistically significant differences in concentration were recorded for organic acids, amino acids and their derivatives. Using samples from the biobank collection, a metabolomic study of the biomaterial of patients hospitalised with the diagnosis of COVID-19 was carried out. According to the results obtained, kynurenine, phenylalanine and acetylcarnitine were associated with the severity of COVID-19 infection.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Metabolomics
11 papers in training set
Top 0.1%
14.6%
2
Scientific Reports
3102 papers in training set
Top 2%
14.6%
3
PLOS ONE
4510 papers in training set
Top 15%
12.7%
4
Heliyon
146 papers in training set
Top 0.4%
3.6%
5
Frontiers in Medicine
113 papers in training set
Top 1%
3.6%
6
Frontiers in Molecular Biosciences
100 papers in training set
Top 0.6%
3.1%
50% of probability mass above
7
Journal of Medical Virology
137 papers in training set
Top 1%
2.8%
8
International Journal of Molecular Sciences
453 papers in training set
Top 6%
1.9%
9
Biomedicines
66 papers in training set
Top 0.7%
1.8%
10
Frontiers in Microbiology
375 papers in training set
Top 6%
1.5%
11
BMC Microbiology
35 papers in training set
Top 0.7%
1.5%
12
Frontiers in Cellular and Infection Microbiology
98 papers in training set
Top 4%
1.4%
13
Journal of Proteome Research
215 papers in training set
Top 1%
1.4%
14
BMC Infectious Diseases
118 papers in training set
Top 4%
1.0%
15
Frontiers in Nutrition
23 papers in training set
Top 1%
0.9%
16
BioMed Research International
25 papers in training set
Top 3%
0.9%
17
Archives of Clinical and Biomedical Research
28 papers in training set
Top 2%
0.9%
18
PeerJ
261 papers in training set
Top 13%
0.8%
19
Analytical and Bioanalytical Chemistry
17 papers in training set
Top 0.3%
0.8%
20
Journal of Proteomics
27 papers in training set
Top 0.4%
0.8%
21
Diagnostics
48 papers in training set
Top 2%
0.8%
22
Molecular Omics
21 papers in training set
Top 0.3%
0.8%
23
Journal of Translational Medicine
46 papers in training set
Top 3%
0.7%
24
Journal of Clinical Virology
62 papers in training set
Top 1.0%
0.7%
25
Journal of Clinical Medicine
91 papers in training set
Top 7%
0.7%
26
JMIRx Med
31 papers in training set
Top 2%
0.7%
27
Cell Death Discovery
51 papers in training set
Top 2%
0.5%
28
Frontiers in Pharmacology
100 papers in training set
Top 6%
0.5%
29
Biology Open
130 papers in training set
Top 4%
0.5%
30
PLOS Neglected Tropical Diseases
378 papers in training set
Top 6%
0.5%