Serum metabolomic abnormalities in survivors of non-severe COVID-19

Abstract

Metabolic reprogramming is a distinctive characteristic of SARS-CoV-2 infection, which refers to metabolic changes in hosts triggered by viruses for their survival and spread. It is current urgent to understand the metabolic health status of COVID-19 survivors and its association with long-term health consequences of infection, especially for the predominant non-severe patients. Herein, we show systemic metabolic signatures of survivors of non-severe COVID-19 from Wuhan, China at six months after discharge using metabolomics approaches. The serum amino acids, organic acids, purine, fatty acids and lipid metabolism were still abnormal in the survivors, but the kynurenine pathway and the level of itaconic acid have returned to normal. These metabolic abnormalities are associated with liver injury, mental health, energy production, and inflammatory responses. Our findings identify and highlight the metabolic abnormalities in survivors of non-severe COVID-19, which provide information on biomarkers and therapeutic targets of infection and cues for post-hospital care and intervention strategies centered on metabolism reprogramming.

Keywords: COVID-19 survivors; Health consequences; Metabolic abnormalities; Metabolomics.

Figure 1

Abnormal serum metabolites associated with the history of SARS-CoV-2 infection. (a) OPLS-DA score plot (R²Y = 0.96, p = 0.003; Q² = 0.60, p < 0.001 for permutation test) obtained from modelling metabolic profile in the survivors of non-severe COVID-19 (red) and controls (blue). Volcano plots for differential metabolites in all (b), young (c), and elder (d) samples. (e) Heat maps of top differential metabolites in all, young, and elder samples. The color of each column represents the logarithm of fold change of metabolites with base 2, and p values were calculated using a student's t-test, ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001. (f) The main KEGG pathways disturbed in survivors of non-severe COVID-19.

Figure 2

Disorders in targeted metabolites in survivors of non-severe COVID-19. Heatmap representation of Z-score transformed concentrations of the amino acids and amino acid derivatives, organic acids and neurotransmitters. Each column represents a single sample, and the dark red in color scale is for the highest value, white is for the midpoint value and dark blue is for the lowest value.

Figure 3

Metabolic network of significantly changed lipid classes in all, young and elder survivors of non-severe COVID-19. Bars in all graphs represent mean abundance of controls (light blue column) and survivors (pink column) in different subgroups, error bars represent standard deviation. The normalized total peak abundance of individual lipid class is shown on the Y-axis. Red, green, black and gray colors are significantly up-regulated, down-regulated, unchanged and undetected lipids or metabolites, and the arrows indicate the direction of metabolism. The dotted-line box includes all free fatty acids (FFA), which convert to Acyl-CoA for participate the synthesis of LPA and PA. p values were calculated using a student's t-test, ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001. MUFA: monounsaturated fatty acids, PUFA: polyunsaturated fatty acids, MHFA: mono-hydroxyl fatty acids; DHFA: di-hydroxyl fatty acids, G6P: glucose-6-phosphate, Glyeraldehyde-3-P: glyeraldehyde-3-phosphate, Glycerol-3-P: glycerol-3-phosphate, PC: phosphatidylcholines, LysoPC: lysophosphatidylcholines, PA: phosphatidic acids, LysoPA: lyso phosphatidic acids, PE: phosphatidylethanolamines, LysoPE: lisophosphatidylethanolamines, PS: phosphatidylserines, MG: monoglycerides, DG: diglycerides, and TG: triglyceride.

Figure 4

Abnormalities of body metabolism in survivors of non-severe COVID-19.