| Autor: |
Seyed Aria Nejadghaderi, Ehsan Nazemalhosseini-Mojarad, Asra Fazlollahi, Ali Pirsadeghi, Ainaz Khalili, Rasoul Ebrahimi, Nima Rezaei |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Translational Medicine Communications, Vol 9, Iss 1, Pp 1-7 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2396-832X |
| DOI: |
10.1186/s41231-024-00177-9 |
| Popis: |
Abstract Background SARS-CoV-2 caused an outbreak in late December 2019. It has been suggested that gut microbiota dysbiosis influences the severity, mortality, and quality of life of patients with COVID-19. So, identifying the gut microbiota pattern could be helpful to determine the prognosis of the disease, and maybe determine some potential treatment approaches. Our aim will be to compare gut microbiota patterns between patients with severe or non-severe COVID-19, and healthy controls. Methods We will include 183 samples: 122 samples from COVID-19 patients, including 61 severe patients and 61 non-severe patients, and 61 samples from healthy controls. Total bacterial DNA will be extracted from samples and 16 S rRNA gene will be amplified through two polymerase chain reaction (PCR) stages. Fecal samples will be analyzed using a targeted metabolomics technique. The differences in each RNA or DNA expression between patients with severe COVID-19, patients with non-severe COVID-19, and controls will be compared. Also, we will assess the relationships between each DNA or RNA and the risk of COVID-19 severity, sort of clinical manifestations, and comorbidities. Concurrent medication data will be collected and patients will also be grouped based on their drug history. Results We hypothesize that the gut microbiota composition will be affected by the COVID-19 severity and there might be differences in terms of sex and age. Conclusions The results of our study could be the backbone for further trials which might lead to the development of prognostic factors and treatment options. Further studies can also consider the limitations of the study like potential confounders and selection and recall biases. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
Full text from SpringerLink