Table1_Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip.DOCX

Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay’s performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes.
Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets.
Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100% phenotype inter-run concordance.
Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

背景：基因微阵列（Microarray）是一项成熟且被广泛应用的技术，可对人类基因组上数十万余个基因座进行检测分析。结合基因型填充（imputation）技术以覆盖芯片设计未包含的常见变异，可为大规模遗传学研究提供高性价比的解决方案。除科研应用外，该技术还可应用于药物基因组学（pharmacogenomics）、营养遗传学（nutrigenetics）以及复杂疾病风险预测相关检测。然而，搭建临床报告工作流程需对检测实验的性能进行全面评估，这可通过验证性研究实现。本研究针对基于因美纳（Illumina）全球筛查芯片（Global Screening Array）搭建的、用于25个药物基因组学相关基因的遗传检测工作流程开展了临床前验证。
方法：为评估本工作流程的准确性，我们开展了多项临床前验证研究。本文呈现的是准确性与精密度评估的结果，共涉及73株细胞系。本次评估纳入的参考材料来自瓶中基因组（Genome-In-A-Bottle, GIAB）项目、遗传检测参考材料协调计划（Genetic Testing Reference Material Coordination Program, GeT-RM），以及1000基因组计划（1000 Genomes Project, 1KGP）的额外样本。我们针对各检测适应症的靶标基因座的基因型分型结果，与已确立的金标准数据集进行了准确性评估。
结果：在单样本分析中，我们测得平均分析灵敏度为99.39%，特异性为99.98%。我们进一步依托GeT-RM目录中已确立的双倍型（diplotype）数据，或基于1KGP基因型分型结果，对星号等位基因（star-allele）分型的准确性进行了评估。在14个可进行星号等位基因分型的药物基因组学相关基因中，我们测得平均双倍型一致率为96.47%。最后，我们评估了重复实验间结果的可重复性，测得不同批次间的双倍型一致率为99.48%，表型一致率为100%。
结论：本项全面的验证研究证实了所搭建工作流程的稳健性与可靠性，表明其具备进一步开发以应用于实际检测的条件。