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Comput Struct Biotechnol J. 2021 Jun 27;19:3747-3754. doi: 10.1016/j.csbj.2021.06.040. eCollection 2021.
2
A comparison of genotyping arrays.基因分型芯片比较。
Eur J Hum Genet. 2021 Nov;29(11):1611-1624. doi: 10.1038/s41431-021-00917-7. Epub 2021 Jun 18.
3
Reply to Unreliability of genotyping arrays for detecting very rare variants in human genetic studies: Example from a recent study of MC4R.对人类遗传学研究中基因分型阵列检测极罕见变异的不可靠性的回应:来自近期一项黑素皮质素4受体(MC4R)研究的实例
Cell. 2021 Apr 1;184(7):1652-1653. doi: 10.1016/j.cell.2021.03.014.
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Unreliability of genotyping arrays for detecting very rare variants in human genetic studies: Example from a recent study of MC4R.基因分型阵列在人类遗传学研究中检测极罕见变异的不可靠性:来自近期一项黑素皮质素4受体(MC4R)研究的实例
Cell. 2021 Apr 1;184(7):1651. doi: 10.1016/j.cell.2021.03.015.
5
Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation.使用 SNP 芯片检测罕见的致病性变异:回顾性、基于人群的诊断评估。
BMJ. 2021 Feb 15;372:n214. doi: 10.1136/bmj.n214.
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Consumer Testing for Disease Risk: ACOG Committee Opinion, Number 816.消费者疾病风险检测:ACOG 委员会意见,816 号。
Obstet Gynecol. 2021 Jan 1;137(1):e1-e6. doi: 10.1097/AOG.0000000000004200.
7
Opportunistic genomic screening. Recommendations of the European Society of Human Genetics.机会性基因组筛查。欧洲人类遗传学学会的建议。
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8
Validation of the BOADICEA model and a 313-variant polygenic risk score for breast cancer risk prediction in a Dutch prospective cohort.验证 BOADICEA 模型和一个包含 313 个变异的多基因风险评分在荷兰前瞻性队列中对乳腺癌风险预测的性能。
Genet Med. 2020 Nov;22(11):1803-1811. doi: 10.1038/s41436-020-0884-4. Epub 2020 Jul 6.
9
Direct-to-consumer genetic testing.直接面向消费者的基因检测。
BMJ. 2019 Oct 16;367:l5688. doi: 10.1136/bmj.l5688.
10
Pharmacogenetic content of commercial genome-wide genotyping arrays.商业全基因组基因分型阵列的药物遗传学内容。
Pharmacogenomics. 2018 Oct;19(15):1159-1167. doi: 10.2217/pgs-2017-0129. Epub 2018 Oct 1.

基因芯片技术在医学遗传学中的诊断应用

Array genotyping as diagnostic approach in medical genetics.

机构信息

Institute of Human Genetics, Medical University Innsbruck, Innsbruck, Austria.

JSI Medical Systems GmbH, Ettenheim, Germany.

出版信息

Mol Genet Genomic Med. 2022 Sep;10(9):e2016. doi: 10.1002/mgg3.2016. Epub 2022 Aug 1.

DOI:10.1002/mgg3.2016
PMID:35912641
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9482391/
Abstract

Genotyping arrays are by far the most widely used genetic tests but are not generally utilized for diagnostic purposes in a medical context. In the present study, we examined the diagnostic value of a standard genotyping array (Illumina Global Screening Array) for a range of indications. Applications included stand-alone testing for specific variants (32 variants in 10 genes), first-tier array variant screening for monogenic conditions (10 different autosomal recessive metabolic diseases), and diagnostic workup for specific conditions caused by variants in multiple genes (suspected familial breast and ovarian cancer, and hypercholesterolemia). Our analyses showed a high analytical sensitivity and specificity of array-based analyses for validated and non-validated variants, and identified pitfalls that require attention. Ethical-legal assessment highlighted the need for a software solution that allows for individual indication-based consent and the reliable exclusion of non-consented results. Cost/time assessment revealed excellent performance of diagnostic array analyses, depending on indication, proband data, and array design. We have implemented some analyses in our diagnostic portfolio, but array optimization is required for the implementation of other indications.

摘要

基因分型芯片是迄今为止应用最广泛的遗传检测方法,但通常不用于医学背景下的诊断目的。在本研究中,我们研究了标准基因分型芯片(Illumina Global Screening Array)在一系列适应证中的诊断价值。应用包括针对特定变异的独立检测(10 个基因中的 32 个变异)、针对单基因疾病的一线芯片变异筛查(10 种不同的常染色体隐性代谢疾病),以及针对由多个基因变异引起的特定疾病的诊断性检查(疑似家族性乳腺癌和卵巢癌以及高胆固醇血症)。我们的分析表明,基于阵列的分析对于经过验证和未经验证的变异具有较高的分析灵敏度和特异性,并确定了需要注意的缺陷。伦理法律评估强调需要一种软件解决方案,该解决方案允许基于个体适应证的同意,并可靠地排除未经同意的结果。成本/时间评估表明,根据适应证、先证者数据和阵列设计,诊断性阵列分析的性能非常出色。我们已经在我们的诊断组合中实施了一些分析,但对于其他适应证的实施还需要进行阵列优化。