Khor Seik-Soon, Omae Yosuke, Nishida Nao, Sugiyama Masaya, Kinoshita Noriko, Suzuki Tetsuya, Suzuki Michiyo, Suzuki Satoshi, Izumi Shinyu, Hojo Masayuki, Ohmagari Norio, Mizokami Masashi, Tokunaga Katsushi
Genome Medical Science Project, National Center for Global Health and Medicine Hospital, Tokyo, Japan.
Genome Medical Sciences Project, National Center for Global Health and Medicine, Ichikawa, Japan.
Front Immunol. 2021 Apr 22;12:658570. doi: 10.3389/fimmu.2021.658570. eCollection 2021.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 2019 (COVID-19) was announced as an outbreak by the World Health Organization (WHO) in January 2020 and as a pandemic in March 2020. The majority of infected individuals have experienced no or only mild symptoms, ranging from fully asymptomatic cases to mild pneumonic disease. However, a minority of infected individuals develop severe respiratory symptoms. The objective of this study was to identify susceptible HLA alleles and clinical markers that can be used in risk prediction model for the early identification of severe COVID-19 among hospitalized COVID-19 patients. A total of 137 patients with mild COVID-19 (mCOVID-19) and 53 patients with severe COVID-19 (sCOVID-19) were recruited from the Center Hospital of the National Center for Global Health and Medicine (NCGM), Tokyo, Japan for the period of February-August 2020. High-resolution sequencing-based typing for eight HLA genes was performed using next-generation sequencing. In the HLA association studies, HLA-A11:01:01:01 [P = 0.013, OR = 2.26 (1.27-3.91)] and HLA-C12:02:02:01-HLA-B52:01:01:02 [P = 0.020, OR = 2.25 (1.24-3.92)] were found to be significantly associated with the severity of COVID-19. After multivariate analysis controlling for other confounding factors and comorbidities, HLA-A11:01:01:01 [P = 3.34E-03, OR = 3.41 (1.50-7.73)], age at diagnosis [P = 1.29E-02, OR = 1.04 (1.01-1.07)] and sex at birth [P = 8.88E-03, OR = 2.92 (1.31-6.54)] remained significant. The area under the curve of the risk prediction model utilizing HLA-A*11:01:01:01, age at diagnosis, and sex at birth was 0.772, with sensitivity of 0.715 and specificity of 0.717. To the best of our knowledge, this is the first article that describes associations of HLA alleles with COVID-19 at the 4-field (highest) resolution level. Early identification of potential sCOVID-19 could help clinicians prioritize medical utility and significantly decrease mortality from COVID-19.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）是导致2019冠状病毒病（COVID-19）的病毒，2020年1月世界卫生组织（WHO）宣布其爆发，2020年3月宣布其为大流行病。大多数感染者没有症状或只有轻微症状，范围从完全无症状病例到轻度肺炎疾病。然而，少数感染者会出现严重的呼吸道症状。本研究的目的是确定可用于风险预测模型的易感HLA等位基因和临床标志物，以便在住院的COVID-19患者中早期识别严重COVID-19。2020年2月至8月期间，从日本东京国立全球健康与医学中心（NCGM）中央医院招募了137例轻度COVID-19（mCOVID-19）患者和53例重度COVID-19（sCOVID-19）患者。使用下一代测序对8个HLA基因进行基于高分辨率测序的分型。在HLA关联研究中，发现HLA-A11:01:01:01 [P = 0.013，OR = 2.26（1.27 - 3.91）]和HLA-C12:02:02:01 - HLA-B52:01:01:02 [P = 0.020，OR = 2.25（1.24 - 3.92）]与COVID-19的严重程度显著相关。在控制了其他混杂因素和合并症的多变量分析后，HLA-A11:01:01:01 [P = 3.34E-03，OR = 3.41（1.50 - 7.73）]、诊断时年龄[P = 1.29E-02，OR = 1.04（1.01 - 1.07）]和出生时性别[P = 8.88E-03，OR = 2.92（1.31 - 6.54）]仍然具有显著性。利用HLA-A*11:01:01:01、诊断时年龄和出生时性别的风险预测模型的曲线下面积为0.772，敏感性为0.715，特异性为0.717。据我们所知，这是第一篇在4字段（最高）分辨率水平描述HLA等位基因与COVID-19关联的文章。早期识别潜在严重COVID-19患者有助于临床医生优化医疗资源利用，并显著降低COVID-19的死亡率。
