英国埃克塞特大学医学院Wright CF团队对使用SNP芯片检测罕见致病变异进行了一项基于人群的回顾性诊断评估。2021年2月16日，该研究发表在《英国医学杂志》上。

为了确定SNP芯片的敏感性和特异性是否足以检测临床非选择人群中的罕见病原体变异，研究组进行了一项回顾性、基于人群的诊断评估。

英国生物样本库招募了49 908人，他们拥有SNP芯片和下一代测序数据，另外还有21人购买了消费者基因测试，并通过个人基因组计划在线分享了他们的数据。研究组观察使用SNP芯片进行基因分型（即在特定基因组位置识别正确的DNA碱基），与测序相比，根据人群中该基因型的频率所划分的结果。BRCA1和BRCA2基因中的罕见致病变异被选为英国生物样本库中临床可行的变异详细分析样本，并通过癌症登记数据在参与者中评估BRCA相关癌症（乳腺癌、卵巢癌、前列腺癌和胰腺癌）。

总体而言，与测序相比，使用SNP芯片进行基因分型表现良好；108 574个常见变异的灵敏度、特异性、阳性预测值和阴性预测值均高于99%，这些变异直接在SNP芯片上进行基因分型，并在英国生物库中进行测序。然而，随着变异频率的降低，真阳性结果的可能性显著降低；对于在人群中非常罕见的变异，英国生物库中的频率低于0.001%，阳性预测值非常低，测序数据仅证实了来自SNP芯片的4757个杂合基因型中的16%。

来自个人基因组计划的SNP芯片数据的结果相似，20/21的被分析个体至少有一个假阳性的罕见致病性变体的基因分型错误。对于BRCA1和BRCA2基因中的致病性变体（它们各自非常罕见），英国生物库中SNP芯片与测序的总体性能指标为：敏感性34.6%，特异性98.3%，阳性预测值4.2%，阴性预测值99.9%。SNP芯片阳性的英国生物库参与者中BRCA相关癌症的发生率与年龄匹配的对照组相差不大，因为绝大多数变异是假阳性，而测序阳性的参与者风险却显著增加，比值比为4.05。

研究结果表明，SNP芯片对于非常罕见的致病性变体的基因分型非常不可靠，不应在未经验证的情况下用于指导健康决策。

附：英文原文

Title: Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation

Author: Weedon MN, Jackson L, Harrison JW, Ruth KS, Tyrrell J, Hattersley AT, Wright CF

Issue&Volume: 2021/02/16

Abstract:

Objective To determine whether the sensitivity and specificity of SNP chips are adequate for detecting rare pathogenic variants in a clinically unselected population.

Design Retrospective, population based diagnostic evaluation.

Participants 49908 people recruited to the UK Biobank with SNP chip and next generation sequencing data, and an additional 21 people who purchased consumer genetic tests and shared their data online via the Personal Genome Project.

Main outcome measures Genotyping (that is, identification of the correct DNA base at a specific genomic location) using SNP chips versus sequencing, with results split by frequency of that genotype in the population. Rare pathogenic variants in the BRCA1 and BRCA2 genes were selected as an exemplar for detailed analysis of clinically actionable variants in the UK Biobank, and BRCA related cancers (breast, ovarian, prostate, and pancreatic) were assessed in participants through use of cancer registry data.

Results Overall, genotyping using SNP chips performed well compared with sequencing; sensitivity, specificity, positive predictive value, and negative predictive value were all above 99% for 108574 common variants directly genotyped on the SNP chips and sequenced in the UK Biobank. However, the likelihood of a true positive result decreased dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency below 0.001% in UK Biobank, the positive predictive value was very low and only 16% of 4757 heterozygous genotypes from the SNP chips were confirmed with sequencing data. Results were similar for SNP chip data from the Personal Genome Project, and 20/21 individuals analysed had at least one false positive rare pathogenic variant that had been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, which are individually very rare, the overall performance metrics for the SNP chips versus sequencing in the UK Biobank were: sensitivity 34.6%, specificity 98.3%, positive predictive value 4.2%, and negative predictive value 99.9%. Rates of BRCA related cancers in UK Biobank participants with a positive SNP chip result were similar to those for age matched controls (odds ratio 1.31, 95% confidence interval 0.99 to 1.71) because the vast majority of variants were false positives, whereas sequence positive participants had a significantly increased risk (odds ratio 4.05, 2.72 to 6.03).

Conclusions SNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.

DOI: 10.1136/bmj.n214

Source: bmj.com/content/372/bmj.n214