| Literature DB >> 35923801 |
Rohit Sharma1, Praveen Kumar2, Abdur Rauf3, Ashun Chaudhary4, Pradeep Kumar Prajapati5, Talha Bin Emran6,7, Clara Mariana Gonçalves Lima8, Carlos Adam Conte-Junior9.
Abstract
The second wave of coronavirus disease 2019 (COVID-19) caused severe infections with high mortality. An increase in the cases of COVID-19-associated mucormycosis (CAM) was reported predominantly in India. Commonly present in immunocompromised individuals, mucormycosis is often a life-threatening condition. Confounding factors and molecular mechanisms associated with CAM are still not well understood, and there is a need for careful research in this direction. In this review, a brief account of the diagnosis, management, and advancement in drug discovery for mucormycosis has been provided. Here, we summarize major factors that dictate the occurrence of mucormycosis in COVID-19 patients through the analysis of published literature and case reports. Major predisposing factors to mucormycosis appear to be uncontrolled diabetes, steroid therapy, and certain cancers. At the molecular level, increased levels of iron in COVID-19 might contribute to mucormycosis. We have also discussed the potential role and regulation of iron metabolism in COVID-19 patients in establishing fungal growth. Other factors including diabetes prevalence and fungal spore burden in India as contributing factors have also been discussed.Entities:
Keywords: COVID-19; GRP78; SARS-CoV-2; amphotericin-B; diabetes; hepcidin; mucormycosis; steroids
Mesh:
Year: 2022 PMID: 35923801 PMCID: PMC9339637 DOI: 10.3389/fcimb.2022.937481
Source DB: PubMed Journal: Front Cell Infect Microbiol ISSN: 2235-2988 Impact factor: 6.073
Worldwide reported cases of COVID-19-associated mucormycosis.
| Country | N | MeanAge, years | Gender | Comorbidity | Treatment | Infection Site | Outcome | References (PMID) |
|---|---|---|---|---|---|---|---|---|
|
| 1 | 53 | M = 1 | Leukemia = 1 | Steroids = 1 | Pulmonary = 1 | Dead = 1 | 33513875 |
|
| 1 | 86 | M = 1 | None = 1 | None = 1 | Gastrointestinal = 1 | Dead = 1 | 33207116 |
|
| 20 | 52.15 | F = 9, M = 11 | Diabetes = 17, Leukemia = 2, Renal disease = 1 | None = 20 | ROCM = 20 | Alive = 11, Dead = 9 | 34087330, 34124087 |
|
| 1 | 55 | M = 1 | Lymphoma = 1 | None = 1 | Pulmonary = 1 | Dead =1 | 33527098 |
|
| 68 | 51.52 | F = 15, M = 53 | Diabetes = 49, None = 12, Hypothyroidism = 1, Renal transplant = 2, Coronary artery disease = 1, Hypertension = 2, Rheumatoid arthritis = 1 | Steroids = 54, None = 14 | Gastrointestinal = 2, Osteomyelitis = 2, Pulmonary = 2, ROCM = 62 | None = 2, Alive = 48, Dead = 18 | 33145132, 33463566, 33544266, 33716414, 33727483, 33903850, 33964720, 34011758, 34026593, 34052046, 34081817, 34128074, 34167998, 34177157, 34178609, 34181023, 34215642 |
|
| 19 | 51.63 | F = 8, M = 11 | Diabetes = 15, Hematological malignancy = 2, Hypertension = 1, None = 1 | Steroids = 11, None = 8 | ROCM = 19 | Alive = 11, Dead = 8 | 33713565, 34096653, 34237015, 33843287 |
|
| 1 | 66 | M = 1 | Hypertension = 1 | None = 1 | Pulmonary = 1 | Dead = 1 | 33331988 |
|
| 1 | 24 | F = 1 | Diabetes = 1 | None = 1 | None = 1 | Dead = 1 | 33575155 |
|
| 4 | 60 | M = 4 | Diabetes = 2, None = 2 | Steroids = 4 | ROCM = 1, Pulmonary = 3 | Alive = 1, Dead = 3 | 34114540 |
|
| 2 | 55 | M = 2 | Diabetes, Renal disease = 1, Renal disease = 1 | Steroids = 2 | ROCM = 1, Musculoskeletal = 1 | Alive = 2 | 34038014 |
|
| 11 | 51.72 | F = 9, M = 2 | Diabetes = 8, Hypertension = 2, Myelodysplastic syndrome = 1 | Steroids = 11 | ROCM | Alive = 4, Dead = 7 | 34057620 |
|
| 2 | 22 | M = 2 | None = 2 | Steroids = 1, None = 1 | Pulmonary = 2 | Dead = 2 | 34075329, 32844161 |
|
| 10 | 55.6 | F = 1, M = 9 | None = 3, Heart transplant = 1, Diabetes = 6 | Steroids = 7, None = 2, Vaccine = 1 | Pulmonary = 3, Cutaneous = 1, Multiple/Thoracic = 1, ROCM = 5 | Alive = 4, Dead = 6 | 33670842, 33752571, 33752571, 33857916, 32983308, 33842203, 33984095, 33229953, 34222572, 32972795 |
ROCM, rhino-orbito-cerebral mucormycosis.
Figure 1Some of the major observable factors in COVID-19-associated mucormycosis. (A) Mean age of patients is ~54 years. (B) Most of the cases were reported from India (>48%). (C) Majority of the patients were diabetic (~70%). (D) Rhino-orbito-cerebral mucormycosis (ROCM) predominated in occurrence (~85%). (E) Men (~75% of total patients) were infected more than women. (F) Approximately 65% of patients underwent steroid therapy. (G) More than 41% of mucormycosis infections resulted in patient death.
Figure 2Major risk factors in CAM. Fungal infections typically occur due to a compromised immune status. Several factors such as diabetes, iron metabolism, COVID-19 treatments, steroid therapy, organ transplants, and certain cancers represent the major risk factors for mucormycosis. Apart from these, fungal spore burden, prevalence of diabetes, zinc supplements, and hospital environment might also contribute to mucormycosis cases post-COVID-19. COVID-19, Coronavirus disease 2019; GRP-78, glucose-regulated protein 78; CAM, COVID-19 associated mucormycosis; GIDM, Glucocorticoid-Induced Diabetes Mellitus; ICU, Intensive Care Unit.
Figure 3GRP78, COVID-19, and mucormycosis. Mucorale fungi utilize GRP78 receptor for host cell invasion. SARS-CoV-2 infection increases the expression of GRP78 and hence might promote mucormycosis. Diabetic ketoacidosis and steroid usage are also known to upregulate GRP78 expression. GRP-78, glucose-regulated protein 78; SARS CoV-2, Severe acute respiratory syndrome coronavirus 2; Ace 2, Angiotensin-converting enzyme 2; CotH3, spore coat protein homolog 3.
Figure 4Mucorales iron metabolism. Iron is required for Mucorale growth. Fungi can obtain iron through permease Ftr1 and Fob1/2 system. Strong iron affinity molecules can obtain iron from the iron chelator, deferoxamine, which is ultimately acquired by fungi for growth. Iron-binding activity of transferrin is impaired in DKA patients: low pH dissociates iron from transferrin and high glucose concentrations can glycosylate transferrin, resulting in the release of free iron. Ketone bodies impair phagocytosis and dampen the immune response in DKA patients. Ftr1: high-affinity iron permease 1 (Fe TRansporter); Fob1/2, ferrioxamine binding (Fob) proteins 1/2; BHB, Beta-Hydroxybutyrate; DKA, Diabetic ketoacidosis.
Figure 5Regulation of iron stores by hepcidin during COVID-19. Hepcidin levels are increased following IL-6-mediated action on hepatocytes. Hepcidin sequesters iron levels inside the cells by downregulating ferroportin (Fpn). The decrease in iron levels leads to anemia and ultimately culminates in hypoxemia. Hepcidin-mediated decrease in iron levels may provide protection against pathogens such as mucorales fungi. IL-6, Interleukin-6; Fpn, Ferroportin.