Dataset Information

Screening of Gene Expression Markers for Corona Virus Disease 2019 Through Boruta_MCFS Feature Selection.

ABSTRACT: Since the first report of SARS-CoV-2 virus in Wuhan, China in December 2019, a global outbreak of Corona Virus Disease 2019 (COVID-19) pandemic has been aroused. In the prevention of this disease, accurate diagnosis of COVID-19 is the center of the problem. However, due to the limitation of detection technology, the test results are impossible to be totally free from pseudo-positive or -negative. Improving the precision of the test results asks for the identification of more biomarkers for COVID-19. On the basis of the expression data of COVID-19 positive and negative samples, we first screened the feature genes through ReliefF, minimal-redundancy-maximum-relevancy, and Boruta_MCFS methods. Thereafter, 36 optimal feature genes were selected through incremental feature selection method based on the random forest classifier, and the enriched biological functions and signaling pathways were revealed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Also, protein-protein interaction network analysis was performed on these feature genes, and the enriched biological functions and signaling pathways of main submodules were analyzed. In addition, whether these 36 feature genes could effectively distinguish positive samples from the negative ones was verified by dimensionality reduction analysis. According to the results, we inferred that the 36 feature genes selected via Boruta_MCFS could be deemed as biomarkers in COVID-19.

SUBMITTER: Sun Y

PROVIDER: S-EPMC9258782 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The association of liver biochemistry with clinical outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is currently unclear, and the utility of longitudinally measured liver biochemistry as prognostic markers for mortality is unknown. We aimed to determine whether abnormal liver biochemistry, assessed at baseline and at repeat measures over time, was associated with death in hospitalized patients with COVID-19 compared to those without COVID-19, in a United Kingdom population. We extracted routinely collected clinical data from a large teaching hospital in the United Kingdom, matching 585 hospitalized patients who were SARS-CoV-2 real-time reverse transcription-polymerase chain reaction (RT-PCR) positive to 1,165 hospitalized patients who were RT-PCR negative for age, sex, ethnicity, and preexisting comorbidities. A total of 26.8% (157/585) of patients with COVID-19 died compared to 11.9% (139/1,165) in the group without COVID-19 (P < 0.001). At presentation, a significantly higher proportion of the group with COVID-19 had elevated alanine aminotransferase (20.7% vs. 14.6%, P = 0.004) and hypoalbuminemia (58.7% vs. 35.0%, P < 0.001) compared to the group without COVID-19. Within the group with COVID-19, those with hypoalbuminemia at presentation had 1.83-fold increased hazards of death compared to those with normal albumin (adjusted hazard ratio [HR], 1.83; 95% confidence interval [CI], 1.25-2.67), while the hazard of death was ~4-fold higher in those aged ≥75 years (adjusted HR, 3.96; 95% CI, 2.59-6.04) and ~3-fold higher in those with preexisting liver disease (adjusted HR, 3.37; 95% CI, 1.58-7.16). In the group with COVID-19, alkaline phosphatase (ALP) increased (R = 0.192, P < 0.0001) and albumin declined (R = -0.123, P = 0.0004) over time in patients who died. Conclusion: In this United Kingdom population, liver biochemistry is commonly deranged in patients with COVID-19. Baseline hypoalbuminemia and rising ALP over time could be prognostic markers for death, but investigation of larger cohorts is required to develop a better understanding of the relationship between liver biochemistry and disease outcome.

Project description:In December 2019 a novel coronavirus SARS-CoV-2 emerged in the Hunan seafood market in Wuhan, China, and soon became a global health problem. Since its outbreak, SARS-CoV-2 has had a major impact on clinical diagnostic laboratories. The scientific community has quickly risen to the occasion and reports of new developments have arrived at an unprecedented scale. At present, there is a growing list of over 400 SARC-CoV-2 diagnostic tests either in development or approved for clinical use. This presentation reviews the current laboratory methods available for testing COVID- 19 in microbiology laboratories and also provides an insight into the future diagnostics approaches. Proper respiratory specimen collected at the appropriate time and from the right anatomical site is critical in the accurate and timely diagnosis of SARSCoV2. While oropharyngeal and nasopharyngeal swabs are recommended for the detection of early infection, other lower respiratory tract specimens like the sputum and bronchoalveolar lavage are used for late detection and monitoring of patients with severe COVID-19 pneumonia. Real-time RT-PCR based molecular assay remains the test of choice for the etiological diagnosis of SARS-CoV-2 while serological tests are being introduced as supplementary tools. Finally, there is an urgent need for scaling up the diagnostic capacity by the introduction of reliable and accurate point-of-care tests which will assist in effective control of this outbreak. These assays can be used in the local hospitals and clinics bearing the burden of identifying and treating patients. Highlights • Since its outbreak, SARS-CoV-2 has had a major impact on clinical diagnostic laboratories.• At present, there is a growing list of over 400 SARC-CoV-2 diagnostic tests either in development or approved for clinical use.• Real-time RT-PCR based molecular assay remains the test of choice for the etiological diagnosis of SARS-CoV-2.• Oropharyngeal and nasopharyngeal swabs are recommended for the detection of early infection.• Lower respiratory tract specimens can be used for late detection and monitoring of patients with severe COVID-19 pneumonia.• There is an urgent need for scaling up the diagnostic capacity by the introduction of reliable and accurate point-of-care tests.

Dataset Information

Screening of Gene Expression Markers for Corona Virus Disease 2019 Through Boruta_MCFS Feature Selection.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets