https://socictopen.socict.org/files/original/f152d0b87b1c238edb54d3f075f11746.pdf ab2e27c6e358fcc4bbf6c8b6cbba6c76 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource HLA-B*44 and C*01 Prevalence Correlates with Covid19 Spreading across Italy Creator An entity primarily responsible for making the resource Luciano Mutti, Antonio Giordano, Pierpaolo Correale, Francesca Pentimalli, Giovanni Baglio, Rita Emilena Saladino, Pierpaolo Sileri Description An account of the resource 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. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource coronavirus, covid-19, SARS-CoV-2, HLA class I, viral infection susceptibility Identifier An unambiguous reference to the resource within a given context 10.3390/ijms21155205 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Chemistry