Genetics of primary ovarian insufficiency: new developments and opportunities.
Genetics of primary ovarian insufficiency: new developments and opportunities.
复制标题
原发性卵巢功能不全的遗传学：新进展和机遇
DOI：
10.1093/humupd/dmv036
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发表时间：
2015-11
影响因子：
13.3
通讯作者：
Chen ZJ
中科院分区：
文献类型：
--
作者：
Qin Y;Jiao X;Simpson JL;Chen ZJ
原发性卵巢功能不全(POI)以明显的异质性为特征，但有显著的遗传贡献。识别确切的致病基因一直具有挑战性，许多发现都是无法复制的。现在是时候对该领域进行评估，概述已取得的进展，概述争议，并预测未来在阐明POI遗传学方面的方向。使用PubMed和谷歌学者检索截至2015年5月发表的原创文章，确定POI的遗传病因学研究。如果进行了染色体分析、候选基因筛选和全基因组研究，则包括这些研究。确定的文章仅限于英文全文论文。长期以来，染色体异常一直被认为是POI的常见原因，目前估计患病率为10-13%。利用传统的核型方法，已检测到X单体、嵌合体、X染色体缺失和重排、X常染色体易位和等位染色体。根据候选基因研究，在至少一个群体中明确具有有害影响的单基因扰动似乎也包括骨形态发生蛋白15(BMP15)、孕酮受体膜组件1(PGRMC1)和X染色体上的脆性X智力低下1(FMR1)预突变；生长分化因子9(GDF9)、卵泡发生特异性bHLH转录因子(Fig1a)、新生卵巢同源盒基因(NOBOX)、核受体亚家族5、A组成员1(NR5A1)和纳米同源基因3(NANOS3)，但大多数在被研究的单个群体中发现不超过1-2%。全基因组方法利用全基因组关联研究揭示了不是基于候选基因预测的基因座，但仍然很难定位致病基因，而且易感基因并不总是重复的。细胞基因组学方法(阵列CGH)已经确定了其他感兴趣的区域，但研究没有显示出一致的结果，阵列的分辨率各不相同，复制也很少见。非综合征POI家系的全外显子组测序最近才开始，发现基质抗原3(STAG3)、突触膜复合体中心元件1(SYCE1)、微小染色体维持复合体成分8和9(MCM8、MCM9)以及ATP依赖的DNA解旋酶同源基因(HFM1)发生突变。考虑到候选基因分析的进展缓慢以及可用于GWAS的样本量相对较小，基于家族的全外显子组和全基因组测序似乎是检测与POI相关的潜在基因的最有前途的方法。综上所述，细胞遗传学、细胞基因组学(阵列CGH)和外显子组测序方法在20-25%的∼病例中揭示了遗传原因。发现剩余的致病基因将不仅通过全基因组方法在多个群体中涉及更大的队列，而且还将结合环境暴露和探索基因内和基因间区域的信号通路，这些信号通路指向调控基因和网络的扰动。
Primary ovarian insufficiency (POI) is characterized by marked heterogeneity, but with a significant genetic contribution. Identifying exact causative genes has been challenging, with many discoveries not replicated. It is timely to take stock of the field, outlining the progress made, framing the controversies and anticipating future directions in elucidating the genetics of POI. A search for original articles published up to May 2015 was performed using PubMed and Google Scholar, identifying studies on the genetic etiology of POI. Studies were included if chromosomal analysis, candidate gene screening and a genome-wide study were conducted. Articles identified were restricted to English language full-text papers. Chromosomal abnormalities have long been recognized as a frequent cause of POI, with a currently estimated prevalence of 10–13%. Using the traditional karyotype methodology, monosomy X, mosaicism, X chromosome deletions and rearrangements, X-autosome translocations, and isochromosomes have been detected. Based on candidate gene studies, single gene perturbations unequivocally having a deleterious effect in at least one population include Bone morphogenetic protein 15 (BMP15), Progesterone receptor membrane component 1 (PGRMC1), and Fragile X mental retardation 1 (FMR1) premutation on the X chromosome; Growth differentiation factor 9 (GDF9), Folliculogenesis specific bHLH transcription factor (FIGLA), Newborn ovary homeobox gene (NOBOX), Nuclear receptor subfamily 5, group A, member 1 (NR5A1) and Nanos homolog 3 (NANOS3) seem likely as well, but mostly being found in no more than 1–2% of a single population studied. Whole genome approaches have utilized genome-wide association studies (GWAS) to reveal loci not predicted on the basis of a candidate gene, but it remains difficult to locate causative genes and susceptible loci were not always replicated. Cytogenomic methods (array CGH) have identified other regions of interest but studies have not shown consistent results, the resolution of arrays has varied and replication is uncommon. Whole-exome sequencing in non-syndromic POI kindreds has only recently begun, revealing mutations in the Stromal antigen 3 (STAG3), Synaptonemal complex central element 1 (SYCE1), minichromosome maintenance complex component 8 and 9 (MCM8, MCM9) and ATP-dependent DNA helicase homolog (HFM1) genes. Given the slow progress in candidate-gene analysis and relatively small sample sizes available for GWAS, family-based whole exome and whole genome sequencing appear to be the most promising approaches for detecting potential genes responsible for POI. Taken together, the cytogenetic, cytogenomic (array CGH) and exome sequencing approaches have revealed a genetic causation in ∼20–25% of POI cases. Uncovering the remainder of the causative genes will be facilitated not only by whole genome approaches involving larger cohorts in multiple populations but also incorporating environmental exposures and exploring signaling pathways in intragenic and intergenic regions that point to perturbations in regulatory genes and networks.