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1.
Hum Genomics ; 17(1): 50, 2023 06 07.
Artigo em Inglês | MEDLINE | ID: covidwho-20239372

RESUMO

BACKGROUND: The use of molecular biomarkers for COVID-19 remains unconclusive. The application of a molecular biomarker in combination with clinical ones that could help classifying aggressive patients in first steps of the disease could help clinician and sanitary system a better management of the disease. Here we characterize the role of ACE2, AR, MX1, ERG, ETV5 and TMPRSS2 for trying a better classification of COVID-19 through knowledge of the disease mechanisms. METHODS: A total of 329 blood samples were genotyped in ACE2, MX1 and TMPRSS2. RNA analyses were also performed from 258 available samples using quantitative polymerase chain reaction for genes: ERG, ETV5, AR, MX1, ACE2, and TMPRSS2. Moreover, in silico analysis variant effect predictor, ClinVar, IPA, DAVID, GTEx, STRING and miRDB database was also performed. Clinical and demographic data were recruited from all participants following WHO classification criteria. RESULTS: We confirm the use of ferritin (p < 0.001), D-dimer (p < 0.010), CRP (p < 0.001) and LDH (p < 0.001) as markers for distinguishing mild and severe cohorts. Expression studies showed that MX1 and AR are significantly higher expressed in mild vs severe patients (p < 0.05). ACE2 and TMPRSS2 are involved in the same molecular process of membrane fusion (p = 4.4 × 10-3), acting as proteases (p = 0.047). CONCLUSIONS: In addition to the key role of TMPSRSS2, we reported for the first time that higher expression levels of AR are related with a decreased risk of severe COVID-19 disease in females. Moreover, functional analysis demonstrates that ACE2, MX1 and TMPRSS2 are relevant markers in this disease.


Assuntos
COVID-19 , Feminino , Humanos , COVID-19/genética , Enzima de Conversão de Angiotensina 2/genética , SARS-CoV-2/genética , Marcadores Genéticos , Bases de Dados Factuais , Serina Endopeptidases/genética , Proteínas de Resistência a Myxovirus
2.
Front Immunol ; 13: 1094644, 2022.
Artigo em Inglês | MEDLINE | ID: covidwho-2309812

RESUMO

Background: Approximately 13.8% and 6.1% of coronavirus disease 2019 (COVID-19) patients require hospitalization and sometimes intensive care unit (ICU) admission, respectively. There is no biomarker to predict which of these patients will develop an aggressive stage that we could improve their quality of life and healthcare management. Our main goal is to include new markers for the classification of COVID-19 patients. Methods: Two tubes of peripheral blood were collected from a total of 66 (n = 34 mild and n = 32 severe) samples (mean age 52 years). Cytometry analysis was performed using a 15-parameter panel included in the Maxpar® Human Monocyte/Macrophage Phenotyping Panel Kit. Cytometry by time-of-flight mass spectrometry (CyTOF) panel was performed in combination with genetic analysis using TaqMan® probes for ACE2 (rs2285666), MX1 (rs469390), and TMPRSS2 (rs2070788) variants. GemStone™ and OMIQ software were used for cytometry analysis. Results: The frequency of CD163+/CD206- population of transitional monocytes (T-Mo) was decreased in the mild group compared to that of the severe one, while T-Mo CD163-/CD206- were increased in the mild group compared to that of the severe one. In addition, we also found differences in CD11b expression in CD14dim monocytes in the severe group, with decreased levels in the female group (p = 0.0412). When comparing mild and severe disease, we also found that CD45- [p = 0.014; odds ratio (OR) = 0.286, 95% CI 0.104-0.787] and CD14dim/CD33+ (p = 0.014; OR = 0.286, 95% CI 0.104-0.787) monocytes were the best options as biomarkers to discriminate between these patient groups. CD33 was also indicated as a good biomarker for patient stratification by the analysis of GemStone™ software. Among genetic markers, we found that G carriers of TMPRSS2 (rs2070788) have an increased risk (p = 0.02; OR = 3.37, 95% CI 1.18-9.60) of severe COVID-19 compared to those with A/A genotype. This strength is further increased when combined with CD45-, T-Mo CD163+/CD206-, and C14dim/CD33+. Conclusions: Here, we report the interesting role of TMPRSS2, CD45-, CD163/CD206, and CD33 in COVID-19 aggressiveness. This strength is reinforced for aggressiveness biomarkers when TMPRSS2 and CD45-, TMPRSS2 and CD163/CD206, and TMPRSS2 and CD14dim/CD33+ are combined.


Assuntos
COVID-19 , Qualidade de Vida , Humanos , Feminino , Pessoa de Meia-Idade , Antígenos CD/metabolismo , Receptores de Superfície Celular/metabolismo , Biomarcadores , Serina Endopeptidases/genética , Lectina 3 Semelhante a Ig de Ligação ao Ácido Siálico
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