Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230032, Anhui, China.
Institute of Dermatology, Anhui Medical University, Hefei, 230022, Anhui, China.
Arch Dermatol Res. 2019 May;311(4):277-285. doi: 10.1007/s00403-019-01902-3. Epub 2019 Mar 2.
To verify whether PsA-associated HLA alleles proposed in other populations are also related to PsA in Chinese Han population, a study of PsA susceptible alleles in the HLA-A, HLA-B, HLA-C and HLA-DRB1 alleles was presented for Chinese Han population. Genotyping was performed by Illumina Miseq platform (Illumina, USA). 50 subtypes and 77 subtypes of HLA-A, HLA-B, HLA-C and HLA-DRB1 with minor allele frequency (MAF) > 1% were genotyped from two-digit and four-digit resolution analysis in 111 PsA and 207 HCs (healthy controls) collected from Chinese Han population, respectively. Data handling, quality control and association analysis were performed using SPSS 25.0 software. In risk estimate, by mean of Bonferroni correction, a newfound four-digit allele HLA-A01:01 [P = 5.5 × 10, OR 3.35 (1.69-6.66)], four-digit allele HLA-C06:02 [P = 8.5 × 10, OR 3.80 (2.23-6.47)] and six two-digit alleles HLA-A01 [P = 5.2 × 10, OR 3.43 (1.89-6.23)], HLA-B13 [P = 4.0 × 10, OR 2.65 (1.76-4.01)], HLA-B27 [P = 7.5 × 10, OR 5.84 (2.09-16.29)], HLA-B57 [P = 5.8 × 10, OR 20.10 (4.65-86.83)], HLA-C03 [P = 2.1 × 10, OR 0.40 (0.25-0.65)], HLA-C06 [P = 1.9 × 10, OR 4.48 (2.95-6.81)] showed statistical significance by the univariate binary logistic regression analysis. Besides, in the binary logistic regression analysis with multiple variables, when the two alleles HLA-A01:01 and HLA-C06:02 were considered as covariates, HLA-A01:01 [P = 2.7 × 10,OR 2.95 (1.46-5.98)] also showed significant association for PsA as risk factor, but may be not the main risk factor [HLA-C06:02, P = 3.0 × 10, OR 3.68 (2.13-6.37)]. When all the above two-digit alleles were included as covariates, HLA-A01 [P = 4.8 × 10, OR 2.00 (1.01-3.94)], HLA-B13 [P = 4.2 × 10, OR 2.62 (1.65-4.16)], HLA-B27 [P = 1.7 × 10, OR 7.62 (2.64-21.96)], HLA-B57 [P = 2.97 × 10, OR 15.90 (3.55-71.18)], HLA-C06 [P = 6.1 × 10, OR 2.70 (1.66-4.40)] showed significant for PsA as risk factors, HLA-C03 [OR 0.65 (0.39-1.09), P = 0.10] showed no association with PsA. In conclusion, we assessed HLA-A, HLA-B, HLA-C and HLA-DRB1 alleles in PsA cohort of Chinese Han population, found HLA-A01:01 and HLA-A01 may be the susceptible genes associated with PsA, and also confirmed the association of four loci with PsA in Chinese Han population. These findings may extend the susceptibility HLA alleles of PsA and help in developing possible genetic markers to predict PsA.
为了验证在其他人群中提出的与 PsA 相关的 HLA 等位基因是否也与中国汉族人群的 PsA 相关,对中国汉族人群中 HLA-A、HLA-B、HLA-C 和 HLA-DRB1 中的 PsA 易感等位基因进行了研究。通过 Illumina Miseq 平台(Illumina,美国)进行基因分型。从两位和四位分辨率分析中分别对来自中国汉族人群的 111 例 PsA 和 207 例健康对照(HC)中的 HLA-A、HLA-B、HLA-C 和 HLA-DRB1 的 50 个亚型和 77 个亚型进行基因分型,这些亚型的次要等位基因频率(MAF)>1%。使用 SPSS 25.0 软件进行数据处理、质量控制和关联分析。在风险估计中,通过 Bonferroni 校正,新发现的四位 HLA-A01:01 [P=5.5×10,OR 3.35(1.69-6.66)]、四位 HLA-C06:02 [P=8.5×10,OR 3.80(2.23-6.47)] 和六位两位 HLA-A01 [P=5.2×10,OR 3.43(1.89-6.23)]、HLA-B13 [P=4.0×10,OR 2.65(1.76-4.01)]、HLA-B27 [P=7.5×10,OR 5.84(2.09-16.29)]、HLA-B57 [P=5.8×10,OR 20.10(4.65-86.83)]、HLA-C03 [P=2.1×10,OR 0.40(0.25-0.65)]、HLA-C06 [P=1.9×10,OR 4.48(2.95-6.81)]在单变量二分类逻辑回归分析中具有统计学意义。此外,在多变量二分类逻辑回归分析中,当考虑 HLA-A01:01 和 HLA-C06:02 两个等位基因为协变量时,HLA-A01:01 [P=2.7×10,OR 2.95(1.46-5.98)] 也与 PsA 作为风险因素显著相关,但可能不是主要风险因素 [HLA-C06:02,P=3.0×10,OR 3.68(2.13-6.37)]。当将所有上述两位 HLA 等位基因纳入协变量时,HLA-A01 [P=4.8×10,OR 2.00(1.01-3.94)]、HLA-B13 [P=4.2×10,OR 2.62(1.65-4.16)]、HLA-B27 [P=1.7×10,OR 7.62(2.64-21.96)]、HLA-B57 [P=2.97×10,OR 15.90(3.55-71.18)]、HLA-C06 [P=6.1×10,OR 2.70(1.66-4.40)]作为 PsA 的风险因素具有统计学意义,HLA-C03 [OR 0.65(0.39-1.09),P=0.10]与 PsA 无关联。总之,我们评估了中国汉族人群中 PsA 队列的 HLA-A、HLA-B、HLA-C 和 HLA-DRB1 等位基因,发现 HLA-A01:01 和 HLA-A01 可能是与 PsA 相关的易感基因,并在汉族人群中证实了与四个位点与 PsA 的关联。这些发现可能扩展了 PsA 的易感 HLA 等位基因,并有助于开发可能的遗传标记来预测 PsA。