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早产的靶向测序与荟萃分析

Targeted Sequencing and Meta-Analysis of Preterm Birth.

作者信息

Uzun Alper, Schuster Jessica, McGonnigal Bethany, Schorl Christoph, Dewan Andrew, Padbury James

机构信息

Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, Rhode Island, United States of America.

Brown Alpert Medical School, Providence, Rhode Island, United States of America.

出版信息

PLoS One. 2016 May 10;11(5):e0155021. doi: 10.1371/journal.pone.0155021. eCollection 2016.

Abstract

Understanding the genetic contribution(s) to the risk of preterm birth may lead to the development of interventions for treatment, prediction and prevention. Twin studies suggest heritability of preterm birth is 36-40%. Large epidemiological analyses support a primary maternal origin for recurrence of preterm birth, with little effect of paternal or fetal genetic factors. We exploited an "extreme phenotype" of preterm birth to leverage the likelihood of genetic discovery. We compared variants identified by targeted sequencing of women with 2-3 generations of preterm birth with term controls without history of preterm birth. We used a meta-genomic, bi-clustering algorithm to identify gene sets coordinately associated with preterm birth. We identified 33 genes including 217 variants from 5 modules that were significantly different between cases and controls. The most frequently identified and connected genes in the exome library were IGF1, ATM and IQGAP2. Likewise, SOS1, RAF1 and AKT3 were most frequent in the haplotype library. Additionally, SERPINB8, AZU1 and WASF3 showed significant differences in abundance of variants in the univariate comparison of cases and controls. The biological processes impacted by these gene sets included: cell motility, migration and locomotion; response to glucocorticoid stimulus; signal transduction; metabolic regulation and control of apoptosis.

摘要

了解基因对早产风险的影响,可能会促使开发出用于治疗、预测和预防早产的干预措施。双胞胎研究表明,早产的遗传度为36%-40%。大型流行病学分析支持早产复发主要源于母亲,父亲或胎儿的遗传因素影响较小。我们利用早产的“极端表型”来提高基因发现的可能性。我们比较了有两代或三代早产史的女性与无早产史的足月对照者通过靶向测序鉴定出的变异。我们使用一种元基因组双聚类算法来识别与早产协同相关的基因集。我们从5个模块中鉴定出33个基因,包括217个变异,这些在病例组和对照组之间存在显著差异。外显子文库中最常被鉴定和关联的基因是IGF1、ATM和IQGAP2。同样,SOS1、RAF1和AKT3在单倍型文库中出现频率最高。此外,在病例组和对照组的单变量比较中,SERPINB8、AZU1和WASF3的变异丰度存在显著差异。这些基因集影响的生物学过程包括:细胞运动、迁移和移动;对糖皮质激素刺激的反应;信号转导;代谢调节和细胞凋亡控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d352/4862658/7ede6fe7a2c2/pone.0155021.g001.jpg

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