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中国循证儿科杂志

中国循证儿科杂志 ›› 2025, Vol. 20 ›› Issue (2): 102-109.DOI: 10.3969/j.issn.1673-5501.2025.02.004

• 论著 • 上一篇    下一篇

基于小于胎龄儿构建目的印记基因的全基因组甲基化分析方法的巢式病例对照研究

俞可欣1a,2,王潇1b,2,肖慧1c,刘仁超1b,吴冰冰1b,程国强1c,王来栓1c,胡黎园1c,董欣然1b,杨琳1a   

  1.  1 复旦大学附属儿科医院，国家儿童医学中心 上海，201102，a 内分泌遗传代谢科，b 分子医学中心，c 新生儿科；2 共同第一作者
  • 收稿日期:2025-03-25 修回日期:2025-01-23 出版日期:2025-04-25 发布日期:2025-04-25
  • 通讯作者: 胡黎园；董欣然；杨琳

Nested case-control study of genome-wide methylation analysis of purpose-imprinted genes in small for gestational age newborns

YU Kexin1a,2, WANG Xiao1b,2, XIAO Hui1c, LIU Renchao1b, WU Bingbing1b, CHENG Guoqiang1c, WANG Laishuan1c, HU Liyuan1c, DONG Xinran1b, YANG Lin1a   

  1. 1 Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China, a Department of Pediatric Endocrinology and Genetic Metabolism, b Molecular Medicine Center, c Department of Neonatology; 2 Co-first author
  • Received:2025-03-25 Revised:2025-01-23 Online:2025-04-25 Published:2025-04-25
  • Contact: HU Liyuan; DONG Xinran; YANG Lin

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摘要： 背景：小于胎龄儿（SGA）是围产期不良结局、生长发育迟缓、神经认知发育障碍的高危人群。在其遗传病因中，除了10%左右的单基因及染色体异常，印记区域/基因缺陷也是重要遗传病因之一。 目的：采用全基因组甲基化芯片检测，基于目的印记基因panel，建立一套可应用于临床的数据分析流程，并应用于常规高通量测序检测阴性的SGA患儿，分析其印记基因/区域缺陷。 设计：巢式病例对照研究。 方法：基于中国新生儿基因组计划（CNGP）队列，纳入2020年7~12月临床外显子检测结果阴性的SGA患儿作为病例组，以1∶ 1的比例行性别及胎龄匹配适于胎龄儿（AGA）作为对照组，采用Methylation 850K阵列进行全基因组甲基化检测。重点分析由269个印记基因组成的目的印记基因panel。利用AGA样本建立稳健的甲基化水平基线，逐个检测SGA个体的目的印记区域/基因甲基化水平，建立甲基化异常值检测分析流程，并使用甲基化特异性多重连接依赖探针扩增（MS-MLPA）和焦磷酸测序对发现的差异甲基化区域（DMR）进行验证。 主要结局指标：SGA印记基因/区域中的DNA甲基化水平。 结果：SGA 50例，AGA 48例。患儿目的印记基因甲基化水平与AGA基线逐个比较后，在5例SGA中发现了3个既往已报道与SGA相关的DMR，其中3例检测到15q11.2-DMR （SNORD116、SNORD115、SNRPN、PWRN1、NDN基因），其中1例DMR区域在MS-MLPA的检测范围内，诊断为Prader Willi综合征。2例检测到20q13.12-DMR （L3MBTL1基因），其中1例同时检测到了7q34-DMR（SVOPL基因）。15q11.2-DMR使用MS-MLPA进行验证，20q13.12-DMR及7q34-DMR位点甲基化改变进行焦磷酸验证。 结论：构建的基于目的印记基因的全基因组DNA甲基化分析流程，在SGA患儿中检测到3个与SGA相关的DMR，其中1例明确诊断。针对15q11-13区域的甲基化位点的分析，拓宽了该区域与SGA相关性的认识。

关键词: 全基因组甲基化, 小于胎龄儿, 差异甲基化区域, 印记基因

Abstract: Background：Small for gestational age (SGA) represents a high-risk group associated with perinatal adverse outcomes, growth retardation, and neurocognitive developmental disorders. Among the genetic causes of SGA, in addition to monogenetic defects and chromosomal abnormalities accounting for approximately 10%, defects in imprinted regions or genes also constitute a significant genetic factor. Objective：The whole-genome methylation microarray (Methylation EPIC BeadChip, Methylation 850K array) was employed to identify the target imprinted gene panel, and a comprehensive data analysis pipeline was developed for clinical implementation. Additionally, it was utilized to investigate imprinted gene/region defects in SGA newborns tested negative in conventional high-throughput sequencing analyses. Design：Nested case-control study. Methods：Based on the SGA cohort of the Chinese Newborn Genome Project (CNGP), SGA newborns with negative clinical exome test results from 2020 July to December were selected as the case group, while appropriate-for-gestational-age (AGA) newborns were matched 1∶ 1 by sex and gestational ages as the control group. Genome-wide methylation detection was performed using the Methylation 850K array. A set of 269 imprinting genes, referred to as target imprinted genes, was analyzed systematically. A robust baseline of methylation levels was established using samples from control group. The methylation levels of target imprinted genes/regions in SGA individuals were assessed individually, and a comprehensive methylation analysis workflow was built. Methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) and pyrosequencing were employed for the validation of differentially methylated regions (DMRs). Main outcome measures：DNA methylation levels in imprinted genes/regions in SGA newborns. Results：50 SGA newborns and 48 AGA newborns were enrolled in this study. After a case-by-case comparison of the methylation levels of imaged genes with the AGA baseline, three SGA-related differential methylation regions (DMRs) were identified in five newborns with SGA. Specifically, the 15q11.2-DMR (comprising SNORD116, SNORD115, SNRPN, PWRN1 and NDN genes) was detected in three neonates with SGA. One case, whose DMR region was within the detection range of MS-MLPA, was diagnosed with Prader Willi syndrome. The 20q13.12-DMR (involving the L3MBTL1 gene) was observed in two neonates with SGA. The 7q34-DMR (associated with the SVOPL gene) was also identified in one of them. Conclusion：In this study, a comprehensive whole-genome DNA methylation analysis pipeline was established. Using these approaches, three SGA-related differentially methylated regions (DMRs) were identified in newborns with SGA. Furthermore, the analysis of methylation sites within the 15q11-13 region expanded our understanding of the correlation between SGA and this genomic locus.

Key words: Genome-wide methylation, Small for gestational age, Differentially methylated region, Imprinted genes