: The spread of COVID-19 is showing huge, unexplained, differences between northern and southern Italy. We hypothesized that the regional prevalence of specific class I human leukocyte antigen (HLA) alleles, which shape the anti-viral immune response, might partly underlie these differences. Through an ecological approach, we analyzed whether a set of HLA alleles (A, B, C), known to be involved in the immune response against infections, correlates with COVID-19 incidence. COVID-19 data were provided by the National Civil Protection Department, whereas HLA allele prevalence was retrieved through the Italian Bone-Marrow Donors Registry. Among all the alleles, HLA-A*25, B*08, B*44, B*15:01, B*51, C*01, and C*03 showed a positive log-linear correlation with COVID-19 incidence rate fixed on 9 April 2020 in proximity of the national outbreak peak (Pearson's coefficients between 0.50 and 0.70, p-value < 0.0001), whereas HLA-B*14, B*18, and B*49 showed an inverse log-linear correlation (Pearson's coefficients between -0.47 and -0.59, p-value < 0.0001). When alleles were examined simultaneously using a multiple regression model to control for confounding factors, HLA-B*44 and C*01 were still positively and independently associated with COVID-19: a growth rate of 16% (95%CI: 0.1-35%) per 1% point increase in B*44 prevalence; and of 19% (95%CI: 1-41%) per 1% point increase in C*01 prevalence. Our epidemiologic analysis, despite the limits of the ecological approach, is strongly suggestive of a permissive role of HLA-C*01 and B*44 towards SARS-CoV-2 infection, which warrants further investigation in case-control studies. This study opens a new potential avenue for the identification of sub-populations at risk, which could provide Health Services with a tool to define more targeted clinical management strategies and priorities in vaccination campaigns.

HLA-B*44 and C*01 Prevalence Correlates with Covid19 Spreading across Italy

Pentimalli, Francesca;
2020-01-01

Abstract

: The spread of COVID-19 is showing huge, unexplained, differences between northern and southern Italy. We hypothesized that the regional prevalence of specific class I human leukocyte antigen (HLA) alleles, which shape the anti-viral immune response, might partly underlie these differences. Through an ecological approach, we analyzed whether a set of HLA alleles (A, B, C), known to be involved in the immune response against infections, correlates with COVID-19 incidence. COVID-19 data were provided by the National Civil Protection Department, whereas HLA allele prevalence was retrieved through the Italian Bone-Marrow Donors Registry. Among all the alleles, HLA-A*25, B*08, B*44, B*15:01, B*51, C*01, and C*03 showed a positive log-linear correlation with COVID-19 incidence rate fixed on 9 April 2020 in proximity of the national outbreak peak (Pearson's coefficients between 0.50 and 0.70, p-value < 0.0001), whereas HLA-B*14, B*18, and B*49 showed an inverse log-linear correlation (Pearson's coefficients between -0.47 and -0.59, p-value < 0.0001). When alleles were examined simultaneously using a multiple regression model to control for confounding factors, HLA-B*44 and C*01 were still positively and independently associated with COVID-19: a growth rate of 16% (95%CI: 0.1-35%) per 1% point increase in B*44 prevalence; and of 19% (95%CI: 1-41%) per 1% point increase in C*01 prevalence. Our epidemiologic analysis, despite the limits of the ecological approach, is strongly suggestive of a permissive role of HLA-C*01 and B*44 towards SARS-CoV-2 infection, which warrants further investigation in case-control studies. This study opens a new potential avenue for the identification of sub-populations at risk, which could provide Health Services with a tool to define more targeted clinical management strategies and priorities in vaccination campaigns.
2020
COVID-19
HLA class I
SARS-Cov2
coronavirus
viral infection susceptibility
COVID-19
Coronavirus Infections
Gene Frequency
HLA-B44 Antigen
HLA-C Antigens
Humans
Italy
Pandemics
Pneumonia, Viral
Prevalence
Registries
Regression Analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12572/9266
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