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1.
Hum Genomics ; 18(1): 94, 2024 Sep 04.
Article in English | MEDLINE | ID: mdl-39227859

ABSTRACT

BACKGROUND: The architecture and dynamics of T cell populations are critical in orchestrating the immune response to SARS-CoV-2. In our study, we used T Cell Receptor sequencing (TCRseq) to investigate TCR repertoires in 173 post-infection COVID-19 patients. METHODS: The cohort included 98 mild and 75 severe cases with a median age of 53. We amplified and sequenced the TCR ß chain Complementary Determining Region 3 (CDR3b) and performed bioinformatic analyses to assess repertoire diversity, clonality, and V/J allelic usage between age, sex and severity groups. CDR3b amino acid sequence inference was performed by clustering structural motifs and filtering validated reactive CDR3b to COVID-19. RESULTS: Our results revealed a pronounced decrease in diversity and an increase in clonal expansion in the TCR repertoires of severe COVID-19 patients younger than 55 years old. These results reflect the observed trends in patients older than 55 years old (both mild and severe). In addition, we identified a significant reduction in the usage of key V alleles (TRBV14, TRBV19, TRBV15 and TRBV6-4) associated with disease severity. Notably, severe patients under 55 years old had allelic patterns that resemble those over 55 years old, accompanied by a skewed frequency of COVID-19-related motifs. CONCLUSIONS: Present results suggest that severe patients younger than 55 may have a compromised TCR repertoire contributing to a worse disease outcome.


Subject(s)
COVID-19 , Complementarity Determining Regions , SARS-CoV-2 , Severity of Illness Index , Humans , COVID-19/genetics , COVID-19/immunology , COVID-19/virology , Male , Middle Aged , Female , SARS-CoV-2/immunology , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , Adult , Aged , Complementarity Determining Regions/genetics , Complementarity Determining Regions/immunology , Spain , T-Lymphocytes/immunology , Receptors, Antigen, T-Cell, alpha-beta/genetics , Receptors, Antigen, T-Cell, alpha-beta/immunology , Receptors, Antigen, T-Cell/genetics , Receptors, Antigen, T-Cell/immunology , Alleles
2.
Hum Genomics ; 17(1): 50, 2023 06 07.
Article in English | MEDLINE | ID: mdl-37287057

ABSTRACT

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.


Subject(s)
COVID-19 , Female , Humans , COVID-19/genetics , Angiotensin-Converting Enzyme 2/genetics , SARS-CoV-2/genetics , Genetic Markers , Databases, Factual , Serine Endopeptidases/genetics , Myxovirus Resistance Proteins
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