A protein-truncating mutation in CCNB3 in a patient with recurrent miscarriages and failure of meiosis I

遗传学 生物 突变 植入失败 减数分裂 基因 医学 生物信息学 怀孕 不育
作者
Maryam Rezaei,William Buckett,Eric Bareke,Urvashi Surti,Jacek Majewski,Rima Slim
出处
期刊:Journal of Medical Genetics [BMJ]
卷期号:59 (6): 568-570 被引量:12
标识
DOI:10.1136/jmedgenet-2021-107875
摘要

Recurrent miscarriage (RM) is defined by the occurrence of at least two pregnancy losses prior to 22 weeks of gestation and affects up to 5% of couples trying to conceive.1–3 RM has a significant emotional impact on couples and the repetitive nature intensifies the grief experienced. A recessive missense in cyclin B3 ( CCNB3 ) has recently been shown in two sisters with RM and triploidy of maternal origin.4 Here, we report a novel recessive CCNB3 mutation, c.4091+1G>A, p.Val1321Glyfs*4, in a patient with 16 RM and show that one of her miscarriages is triploid digynic resulted from the failure of meiosis I. RM is clinically and genetically highly heterogeneous. After comprehensive clinical and laboratory testing, in 50% of couples, no abnormalities are identified, and such cases are categorised as RM of unexplained clinical aetiology. To date, little is known about their genetic causes, and known genes explain only a minority of cases. One of the many factors that have hampered our understanding of the genetics of recurrent miscarriages is their complexity, genetic heterogeneity and the difficulties in homogenising these entities to simplify their studies. In many cases of recurrent miscarriages of unknown clinical aetiology, it is impossible to know whether the defect originates from the male or the female, and whether it is in a dominant or a recessive state. Also, it is impossible to know if the defect is transmitted from the parents to the miscarried conception or if it occurred de novo in the miscarriage. While the germline origin of male causes of miscarriages could be sometimes diagnosed based on semen analysis, diagnosing the origin of female causes of miscarriages is more challenging; in many cases, it is impossible to distinguish germline from uterine or systemic defects. Consequently, despite the use of next-generation sequencing, which has greatly facilitated …
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
fg2477完成签到,获得积分10
3秒前
科研通AI2S应助天真的眼睛采纳,获得10
3秒前
科研通AI6.4应助是奶柚啊采纳,获得10
3秒前
李健应助欢喜的祥采纳,获得10
3秒前
4秒前
SJR发布了新的文献求助10
6秒前
yuxixi完成签到,获得积分0
6秒前
不过尔尔完成签到,获得积分10
9秒前
Wang完成签到 ,获得积分10
9秒前
隐形曼青应助zhuzhu采纳,获得10
11秒前
青橘短衫完成签到,获得积分10
15秒前
机智的顺溜应助sky采纳,获得10
15秒前
卓隶完成签到,获得积分10
16秒前
无花果应助sdl采纳,获得10
17秒前
雪白的威完成签到,获得积分10
18秒前
蓝色完成签到,获得积分10
19秒前
SBoot完成签到,获得积分10
20秒前
21秒前
21秒前
勤劳的西西完成签到,获得积分10
23秒前
24秒前
KevinLeng完成签到,获得积分10
24秒前
24秒前
CodeCraft应助LI369258采纳,获得10
26秒前
xml发布了新的文献求助10
26秒前
27秒前
30秒前
小羊完成签到,获得积分10
30秒前
Samuel发布了新的文献求助10
31秒前
小金完成签到,获得积分10
34秒前
36秒前
爆米花应助dundun1采纳,获得10
36秒前
37秒前
38秒前
38秒前
酷波er应助晾猫人采纳,获得10
39秒前
40秒前
飞乐扣发布了新的文献求助10
41秒前
孙漂亮完成签到,获得积分10
41秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 800
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Materials selection in mechanical design 500
Bounds for Statistical Estimation in Semiparametric Models 500
Climate change and sports: Statistics report on climate change and sports 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6476575
求助须知:如何正确求助?哪些是违规求助? 8278879
关于积分的说明 17655345
捐赠科研通 5558490
什么是DOI,文献DOI怎么找? 2910586
邀请新用户注册赠送积分活动 1887589
关于科研通互助平台的介绍 1740833