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基于染色体构象核型分析(C-MoKa)对妊娠失败和流产患者染色体异常的综合分析。

Comprehensive analysis of chromosome abnormalities by chromosome conformation based karyotyping (C-MoKa) in patients with conception failure and pregnancy loss.

作者信息

Bao Xiao, Yang Yuxia, Niu Wenbin, Wang Yimin, Shi Hao, Zou Yangyun, Liu Yidong, Wan Cheng, Ren Jun, Lu Sijia, Sun Yingpu

机构信息

Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Henan Key Laboratory of Reproduction and Genetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Yikon Genomics, Suzhou 215000, China.

出版信息

Clin Chim Acta. 2025 Feb 1;567:120089. doi: 10.1016/j.cca.2024.120089. Epub 2024 Dec 12.

Abstract

BACKGROUND

Chromosome abnormalities are a leading cause of conception failure and pregnancy loss. While traditional cytogenetics technologies like karyotyping have been helpful in identifying structural variations (SVs), they face challenges in detecting complex rearrangements and cryptic structures. In this study, we developed a new method called chromosome conformation based karyotyping (C-MoKa) to comprehensively detect different types of chromosomal abnormalities in patients with conception failure and pregnancy loss.

METHODS

A total of 70 clinical samples exhibiting known results of SVs, mosaic aneuploidies, copy number variations (CNVs) and uniparental disomy (UPD) were included in our cohort and underwent C-MoKa analysis. The results obtained from different techniques, including karyotyping, CNV-seq, and CMA were compared and analyzed.

RESULTS

Distinct chromosomal conformation patterns of various variations were observed and analyzed in clinical samples. Our C-MoKa method not only validated all the findings of karyotyping, CNV-seq and CMA, but also provided more detailed results. It demonstrated superior fragment resolution (<500 Kb) and more precise breakpoints (>100 kb). Moreover, C-MoKa showed higher sensitivity in decoding intricate rearrangements in a single test.

CONCLUSIONS

Our results highlight the potential utility of C-MoKa in precisely unraveling SVs, mosaic aneuploidies, CNVs, and UPD in clinical settings, which can significantly impact further clinical decision-making.

摘要

背景

染色体异常是受孕失败和流产的主要原因。虽然传统的细胞遗传学技术如核型分析有助于识别结构变异(SVs),但在检测复杂重排和隐匿结构方面面临挑战。在本研究中,我们开发了一种名为基于染色体构象的核型分析(C-MoKa)的新方法,以全面检测受孕失败和流产患者的不同类型染色体异常。

方法

我们的队列纳入了70份临床样本,这些样本展示了已知的SVs、嵌合非整倍体、拷贝数变异(CNVs)和单亲二体(UPD)结果,并进行了C-MoKa分析。对包括核型分析、CNV测序和CMA在内的不同技术获得的结果进行了比较和分析。

结果

在临床样本中观察并分析了各种变异的不同染色体构象模式。我们的C-MoKa方法不仅验证了核型分析、CNV测序和CMA的所有结果,还提供了更详细的结果。它展示了卓越的片段分辨率(<500 Kb)和更精确的断点(>100 kb)。此外,C-MoKa在单次检测中解码复杂重排时表现出更高的灵敏度。

结论

我们的结果凸显了C-MoKa在临床环境中精确解析SVs、嵌合非整倍体、CNVs和UPD的潜在效用,这可能会对进一步的临床决策产生重大影响。

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