Leveraging large-scale datasets and single cell omics data to develop a polygenic score for cisplatin-induced ototoxicity.

IF 3.8 3区 医学 Q2 GENETICS & HEREDITY Human Genomics Pub Date : 2024-10-08 DOI:10.1186/s40246-024-00679-5
Deanne Nixie R Miao, MacKenzie A P Wilke, John Pham, Feryal Ladha, Mansumeet Singh, Janilyn Arsenio, Emilia Luca, Alain Dabdoub, Wejian Yang, Jun J Yang, Britt I Drögemöller
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引用次数: 0

Abstract

Background: Cisplatin-induced ototoxicity (CIO), characterized by irreversible and progressive bilateral hearing loss, is a prevalent adverse effect of cisplatin chemotherapy. Alongside clinical risk factors, genetic variants contribute to CIO and genome-wide association studies (GWAS) have highlighted the polygenicity of this adverse drug reaction. Polygenic scores (PGS), which integrate information from multiple genetic variants across the genome, offer a promising tool for the identification of individuals who are at higher risk for CIO. Integrating large-scale hearing loss GWAS data with single cell omics data holds potential to overcome limitations related to small sample sizes associated with CIO studies, enabling the creation of PGSs to predict CIO risk.

Results: We utilized a large-scale hearing loss GWAS and murine inner ear single nuclei RNA-sequencing (snRNA-seq) data to develop two polygenic scores: a hearing loss PGS (PGSHL) and a biologically informed PGS for CIO (PGSCIO). The PGSCIO included only variants which mapped to genes that were differentially expressed within cochlear cells that showed differential abundance in the murine snRNA-seq data post-cisplatin treatment. Evaluation of the association of these PGSs with CIO in our target CIO cohort revealed that PGSCIO demonstrated superior performance (P = 5.54 × 10- 5) relative to PGSHL (P = 2.93 × 10- 3). PGSCIO was also associated with CIO in our test cohort (P = 0.04), while the PGSHL did not show a significant association with CIO (P = 0.52).

Conclusion: This study developed the first PGS for CIO using a large-scale hearing loss dataset and a biologically informed filter generated from cisplatin-treated murine inner ear snRNA-seq data. This innovative approach offers new avenues for developing PGSs for pharmacogenomic traits, which could contribute to the implementation of tailored therapeutic interventions. Further, our approach facilitated the identification of specific cochlear cells that may play critical roles in CIO. These novel insights will guide future research aimed at developing targeted therapeutic strategies to prevent CIO.

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利用大规模数据集和单细胞 omics 数据开发顺铂诱发耳毒性的多基因评分。
背景:顺铂诱导的耳毒性(CIO)是顺铂化疗的一种常见不良反应,其特征是不可逆转的进行性双侧听力损失。除临床风险因素外,遗传变异也是导致 CIO 的原因之一,而全基因组关联研究(GWAS)则强调了这种药物不良反应的多基因性。多基因评分(PGS)整合了来自全基因组多个基因变异的信息,为识别CIO高风险个体提供了一种前景广阔的工具。将大规模听力损失 GWAS 数据与单细胞 omics 数据相结合,有可能克服与 CIO 研究相关的样本量小的局限性,从而创建预测 CIO 风险的 PGS:我们利用大规模听力损失 GWAS 和小鼠内耳单核 RNA 序列(snRNA-seq)数据开发了两种多基因评分:听力损失 PGS(PGSHL)和针对 CIO 的生物知情 PGS(PGSCIO)。PGSCIO 只包含映射到在顺铂治疗后小鼠 snRNA-seq 数据中显示出不同丰度的耳蜗细胞内差异表达基因的变异。在我们的目标 CIO 队列中评估这些 PGS 与 CIO 的关联时发现,相对于 PGSHL(P = 2.93 × 10-3),PGSCIO 表现出更优越的性能(P = 5.54 × 10-5)。在我们的测试队列中,PGSCIO 与 CIO 也有关联(P = 0.04),而 PGSHL 与 CIO 没有显著关联(P = 0.52):本研究利用大规模听力损失数据集和顺铂处理的小鼠内耳 snRNA-seq 数据生成的生物信息过滤器,首次开发了针对 CIO 的 PGS。这种创新方法为开发药物基因组特征的 PGS 提供了新途径,有助于实施量身定制的治疗干预措施。此外,我们的方法还有助于鉴定可能在 CIO 中发挥关键作用的特定耳蜗细胞。这些新颖的见解将指导未来的研究,以开发预防 CIO 的靶向治疗策略。
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来源期刊
Human Genomics
Human Genomics GENETICS & HEREDITY-
CiteScore
6.00
自引率
2.20%
发文量
55
审稿时长
11 weeks
期刊介绍: Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics. Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.
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