Comorbidity-associated glutamine deficiency is a predisposition to severe COVID-19

Abstract

SARS-CoV-2 vaccinations have greatly reduced COVID-19 cases, but we must continue to develop our understanding of the nature of the disease and its effects on human immunity. Previously, we suggested that a dysregulated STAT3 pathway following SARS-Co-2 infection ultimately leads to PAI-1 activation and cascades of pathologies. The major COVID-19-associated metabolic risks (old age, hypertension, cardiovascular diseases, diabetes, and obesity) share high PAI-1 levels and could predispose certain groups to severe COVID-19 complications. In this review article, we describe the common metabolic profile that is shared between all of these high-risk groups and COVID-19. This profile not only involves high levels of PAI-1 and STAT3 as previously described, but also includes low levels of glutamine and NAD⁺, coupled with overproduction of hyaluronan (HA). SARS-CoV-2 infection exacerbates this metabolic imbalance and predisposes these patients to the severe pathophysiologies of COVID-19, including the involvement of NETs (neutrophil extracellular traps) and HA overproduction in the lung. While hyperinflammation due to proinflammatory cytokine overproduction has been frequently documented, it is recently recognized that the immune response is markedly suppressed in some cases by the expansion and activity of MDSCs (myeloid-derived suppressor cells) and FoxP3⁺ Tregs (regulatory T cells). The metabolomics profiles of severe COVID-19 patients and patients with advanced cancer are similar, and in high-risk patients, SARS-CoV-2 infection leads to aberrant STAT3 activation, which promotes a cancer-like metabolism. We propose that glutamine deficiency and overproduced HA is the central metabolic characteristic of COVID-19 and its high-risk groups. We suggest the usage of glutamine supplementation and the repurposing of cancer drugs to prevent the development of severe COVID-19 pneumonia.

Fig. 1. Roles of glutamine.

The pleiotropic roles of glutamine as a nitrogen donor, in the formation of a redox regulator (glutathione), and as an epigenetic regulator for CD4⁺ T cell differentiation (α-Ketoglutarate). Nitrogen donor legends are modified from Zhang et al. [49]. GS glutamine synthetase, GLS glutaminase, GLUD1 Glutamate dehydrogenase 1, ALT alanine aminotransferase, AST aspartate aminotransferase.

Fig. 2. NAD⁺ biosynthetic pathways.

NAD⁺ is produced through three independent pathways: the de novo synthesis, Preiss-Handler, and salvage pathways. The QPRT and CD38 enzymes are responsible for the decline in NAD⁺ levels with age. The de novo synthesis pathway from diet-derived tryptophan occurs through the kynurenine pathway. The first step in this pathway is the conversion of tryptophan to N-formylkin. After two more reaction steps, N-formylkin is transformed into QA, which is then converted into NAMN by the rate-limiting enzyme, QPRT. NAMN is a shared metabolite with the Preiss-Handler pathway, which uses NA from a dietary source. NAMN is then transformed into NAAD. The final step of both the de novo and Preiss-Handler pathways requires glutamine as a gamma-amide nitrogen donor to transform NAAD into NAD⁺ with NADS. The NAD⁺ salvage pathway uses NAM, which is either generated as a by-product of the enzymatic activities of NAD⁺-consuming enzymes such as SIRTs and CD38, or derived from food. NAM is transformed into NMN to make NAD⁺. NR is also a precursor of NMN. NR and NMN are potent NAD⁺ boosters in vivo. N-formylkin N-formylkynurenine, QA quinolinic acid, QPRT Quinolinate phosphoribosyl transferase, NAMN nicotinic acid mononucleotide, NA nicotinic acid, NAAD nicotinic acid adenine dinucleotide, NAM nicotinamide, NR nicotinamide riboside, NMN nicotinamide mononucleotide.

Fig. 3. HBP and hyaluronan.

Schematic representation of metabolic pathways that lead to the production of substrates for the HAS2 enzyme, UDP-GlcUA and UDP-GlcNAc. The monomer unit of HA is shown. LMW-HA activates PAI-1 and promotes a hyaluronan storm. HMW-HA contributes to immunosuppression. UDP-Glc is released from the infected cells and serves as a danger signal to neighboring cells, resulting in NETs formation. Glc-6P glucose-6 phosphate, UDP-Glc uridine diphosphate glucose, UDP-GlcUA uridine diphosphate glucuronic acid, F-6P fructose-6 phosphate, GlcN-6p glucosamine 6-phosphate, UDP-GlcNAc uridine 5ʹ-diphospho-N-acetylglucosamine, GFAT glutamine-fructose-6-phosphate transaminase, HAS2 hyaluronan synthase 2, HA hyaluronan.

Fig. 4. Synergistic metabolic pathways that lead to a hyaluronan storm, NETosis, coagulopathy, and immune suppression.

Before the SARS-CoV-2 infection, comorbidity-associated glutamine deficiency (1) and comorbidity-associated NAD⁺ deficiency (2) lead to low α-KG (4) and impaired SIRT1 activity (3), respectively. This results in the hyperproduction of HA and PAI-1, and immunodeficiency. After SARS-CoV-2 infection, STAT3 is activated through the EGFR pathway (5) and the extracellular UDP-Glucose-stimulated P2RY14 pathway (6). Activated STAT3 can induce the transcription of HAS2 (7). The HAS2 enzyme is stabilized by O-GlcNAcylation, and HA is produced (8). In addition, a critical HAS2 negative regulator, SIRT1 (3), is neutralized by SARS-CoV-2 infection and low NAD⁺ levels. This results in increased HAS2 activity and higher HA levels, and contributes to a hyaluronan storm. LMW-HA derived from excess HA production stimulates the production of PAI-1 (9), and PAI-1 indirectly activates STAT3 (10) leading to coagulopathy. Danger signals, such as UDP-glucose, activate the innate immune responses and the formation of NETS (NETosis), thus exacerbating the coagulopathy. Glutamine deficiency during the infection leads to immunosuppression through the increase in the populations of systemic TI-Tregs (tumor-infiltrating-like Tregs) (11) and MDSCs (12). TI-Tregs are increased by the over-production of HMW-HA. Details of these events are described in the main text.