HLA-B*44 and C*01 Prevalence Correlates with Covid19 Spreading across Italy
HLA-B*44 and C*01 Prevalence Correlates with Covid19 Spreading across Italy
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DOI：
10.3390/ijms21155205
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发表时间：
2020-08-01
影响因子：
5.6
通讯作者：
Giordano, Antonio
中科院分区：
文献类型：
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作者：
Correale, Pierpaolo;Mutti, Luciano;Giordano, Antonio
COVID-19的传播在北方和意大利南部之间显示出巨大的、无法解释的差异。我们推测，特定的人类白细胞抗原（HLA）等位基因，形成抗病毒免疫反应的区域流行率，可能部分地造成这些差异。通过生态学方法，我们分析了已知参与抗感染免疫反应的一组HLA等位基因（A、B、C）是否与COVID-19发病率相关。COVID-19数据由国家民防部门提供，而HLA等位基因患病率则通过意大利骨髓捐献者登记处检索。在所有等位基因中，HLA-A*25、B*08、B*44、B*15：01、B*51、C*01和C*03与2020年4月9日全国疫情高峰附近的COVID-19发病率呈正对数线性相关（皮尔逊系数在0.50和0.70之间，p值< 0.0001），而HLA-B*14、B*18和B*49呈负对数线性相关（皮尔逊系数在-0.47和-0.59之间，p值< 0.0001）。当使用多元回归模型同时检查等位基因以控制混杂因素时，HLA-B*44和C*01仍然与COVID-19呈正相关且独立相关：增长率为16% B*44患病率每增加1个百分点，增加19%（95%CI：1-41%）; C*01患病率每增加1%。我们的流行病学分析，尽管生态学方法的限制，强烈提示HLA-C*01和B*44对SARS-CoV-2感染的容许作用，这需要在病例对照研究中进一步调查。这项研究开辟了一个新的潜在途径，用于识别处于风险中的亚群，这可以为卫生服务部门提供一种工具，以确定更有针对性的临床管理策略和疫苗接种活动的优先事项。
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.