Suppr超能文献

早产的遗传学

Genetics of preterm labour.

作者信息

Orsi Nicolas M, Gopichandran Nadia, Simpson Nigel A B

机构信息

Perinatal Research Group, The YCR & Liz Dawn Pathology & Translational Sciences Centre Level 4, Leeds Institute of Molecular Medicine, St James's University Hospital, Leeds LS9 7TF, UK.

出版信息

Best Pract Res Clin Obstet Gynaecol. 2007 Oct;21(5):757-72. doi: 10.1016/j.bpobgyn.2007.03.020. Epub 2007 May 8.

Abstract

The identification of women at risk of preterm labour remains an important challenge. While current prevention programmes rely on overt clinical and environmental parameters, the clustering of preterm labour within families and recurrence in susceptible women presents the case for a complex underlying genetic predisposition. Genetic polymorphisms are useful markers to identify high risk groups, although they provide little information either to their underlying functionality or the pathophysiological mechanisms involved; these must be validated through complementary analytical approaches. Data interpretation and inter-study comparisons must be made with caution, taking into account population size, study power, racial differences, inclusion/exclusion criteria and any underlying gene-environment and feto-maternal interactions. Large-scale, multicentre genetic studies coupled with high-throughput screening techniques are the most viable approaches to identify multilocus preterm labour susceptibility screening panels. Preventive strategies may then be applied to those women most likely to benefit from intervention.

摘要

识别有早产风险的女性仍然是一项重大挑战。虽然目前的预防方案依赖于明显的临床和环境参数,但早产在家族中的聚集以及易感女性的复发表明存在复杂的潜在遗传易感性。基因多态性是识别高危人群的有用标志物,尽管它们几乎没有提供关于其潜在功能或所涉及的病理生理机制的信息;这些必须通过补充分析方法进行验证。在进行数据解释和研究间比较时必须谨慎,要考虑到人群规模、研究效能、种族差异、纳入/排除标准以及任何潜在的基因-环境和胎儿-母体相互作用。大规模、多中心的基因研究与高通量筛选技术相结合是识别多位点早产易感性筛查面板的最可行方法。然后可以将预防策略应用于最有可能从干预中受益的女性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验