• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

人类复杂疾病遗传学中罕见变异的独特作用。

Unique roles of rare variants in the genetics of complex diseases in humans.

机构信息

Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.

Laboratory for Molecular Science for Drug Discovery, Graduate School of Medical Life Science, Yokohama City University, Kanagawa, Japan.

出版信息

J Hum Genet. 2021 Jan;66(1):11-23. doi: 10.1038/s10038-020-00845-2. Epub 2020 Sep 18.

DOI:10.1038/s10038-020-00845-2
PMID:32948841
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7728599/
Abstract

Genome-wide association studies have identified >10,000 genetic variants associated with various phenotypes and diseases. Although the majority are common variants, rare variants with >0.1% of minor allele frequency have been investigated by imputation and using disease-specific custom SNP arrays. Rare variants sequencing analysis mainly revealed have played unique roles in the genetics of complex diseases in humans due to their distinctive features, in contrast to common variants. Unique roles are hypothesis-free evidence for gene causality, a precise target of functional analysis for understanding disease mechanisms, a new favorable target for drug development, and a genetic marker with high disease risk for personalized medicine. As whole-genome sequencing continues to identify more rare variants, the roles associated with rare variants will also increase. However, a better estimation of the functional impact of rare variants across whole genome is needed to enhance their contribution to improvements in human health.

摘要

全基因组关联研究已经确定了 >10,000 个与各种表型和疾病相关的遗传变异。虽然大多数是常见的变异,但具有 >0.1%的次要等位基因频率的罕见变异已经通过基因分型和使用特定于疾病的定制 SNP 阵列进行了研究。罕见变异测序分析主要揭示了由于其独特的特征,在人类复杂疾病的遗传学中发挥了独特的作用,与常见变异不同。独特的作用是对基因因果关系的无假设证据,是理解疾病机制的功能分析的精确目标,是药物开发的新有利目标,也是个性化医学中具有高疾病风险的遗传标记。随着全基因组测序不断识别更多的罕见变异,罕见变异相关的作用也将增加。然而,需要更好地估计整个基因组中罕见变异的功能影响,以增强它们对改善人类健康的贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9c8/7728599/e033b494c713/10038_2020_845_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9c8/7728599/e033b494c713/10038_2020_845_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9c8/7728599/e033b494c713/10038_2020_845_Fig1_HTML.jpg

相似文献

1
Unique roles of rare variants in the genetics of complex diseases in humans.人类复杂疾病遗传学中罕见变异的独特作用。
J Hum Genet. 2021 Jan;66(1):11-23. doi: 10.1038/s10038-020-00845-2. Epub 2020 Sep 18.
2
Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits.与复杂性状相关的罕见变异的分析与解释方法。
Curr Protoc Hum Genet. 2019 Apr;101(1):e83. doi: 10.1002/cphg.83. Epub 2019 Mar 8.
3
Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits.全基因组测序和在隔离人群中的推断鉴定与医学相关的复杂特征的遗传关联。
Nat Commun. 2017 May 26;8:15606. doi: 10.1038/ncomms15606.
4
Molecular genetic studies of complex phenotypes.复杂表型的分子遗传学研究。
Transl Res. 2012 Feb;159(2):64-79. doi: 10.1016/j.trsl.2011.08.001. Epub 2011 Aug 31.
5
Rare variant genotype imputation with thousands of study-specific whole-genome sequences: implications for cost-effective study designs.利用数千个特定研究的全基因组序列进行罕见变异基因型填充:对具有成本效益的研究设计的影响。
Eur J Hum Genet. 2015 Jul;23(7):975-83. doi: 10.1038/ejhg.2014.216. Epub 2014 Oct 8.
6
Genomic Analysis in the Age of Human Genome Sequencing.人类基因组测序时代的基因组分析。
Cell. 2019 Mar 21;177(1):70-84. doi: 10.1016/j.cell.2019.02.032.
7
Imputation-based assessment of next generation rare exome variant arrays.基于插补法的新一代罕见外显子变异阵列评估
Pac Symp Biocomput. 2014:241-52.
8
Personalised analytics for rare disease diagnostics.个性化分析在罕见病诊断中的应用。
Nat Commun. 2019 Nov 21;10(1):5274. doi: 10.1038/s41467-019-13345-5.
9
Incorporating Non-Coding Annotations into Rare Variant Analysis.将非编码注释纳入罕见变异分析。
PLoS One. 2016 Apr 29;11(4):e0154181. doi: 10.1371/journal.pone.0154181. eCollection 2016.
10
Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees.利用家系评估罕见变异对 2 型糖尿病及相关特征的贡献。
Proc Natl Acad Sci U S A. 2018 Jan 9;115(2):379-384. doi: 10.1073/pnas.1705859115. Epub 2017 Dec 26.

引用本文的文献

1
BiU-Net: A Biologically Informed U-Net for Genotype Imputation.BiU-Net:一种用于基因型插补的基于生物学信息的U-Net
Res Sq. 2025 Aug 26:rs.3.rs-6797863. doi: 10.21203/rs.3.rs-6797863/v1.
2
Pharmacogenomics of steroid-induced ocular hypertension: relationship to high-tension glaucomas and new pathophysiologic insight.类固醇性高眼压症的药物基因组学:与高眼压型青光眼的关系及新的病理生理学见解
medRxiv. 2025 Aug 13:2025.08.11.25333245. doi: 10.1101/2025.08.11.25333245.
3
Noncoding rare variant associations with blood traits in 166,740 UK Biobank genomes.

本文引用的文献

1
Prevalence and Spectrum of Pathogenic Germline Variants in Japanese Patients With Early-Onset Colorectal, Breast, and Prostate Cancer.日本早发性结直肠癌、乳腺癌和前列腺癌患者中致病种系变异的患病率及谱系
JCO Precis Oncol. 2020 Nov;4:183-191. doi: 10.1200/PO.19.00224.
2
The effect of LRRK2 loss-of-function variants in humans.LRRK2 功能丧失变异在人类中的影响。
Nat Med. 2020 Jun;26(6):869-877. doi: 10.1038/s41591-020-0893-5. Epub 2020 May 27.
3
Transcript expression-aware annotation improves rare variant interpretation.转录本表达感知注释可提高罕见变异的解读。
166740例英国生物银行基因组中与血液性状相关的非编码罕见变异
Nat Genet. 2025 Aug 6. doi: 10.1038/s41588-025-02288-x.
4
Unraveling the enigma of mental disorders: a genetics-first approach and the role of mouse models based on rare disease-susceptible genome variants.揭开精神障碍之谜:遗传学优先方法及基于罕见病易感基因组变异的小鼠模型的作用。
Nagoya J Med Sci. 2025 May;87(2):196-210. doi: 10.18999/nagjms.87.2.196.
5
varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction.可变CADD:大量的常见遗传变异有助于全基因组致病性预测。
Genome Med. 2025 Aug 4;17(1):84. doi: 10.1186/s13073-025-01517-6.
6
Common and rare genetic variants show network convergence for a majority of human traits.常见和罕见基因变异在大多数人类性状上呈现网络汇聚现象。
medRxiv. 2025 Jun 28:2025.06.27.25330419. doi: 10.1101/2025.06.27.25330419.
7
Assessing the performance of 28 pathogenicity prediction methods on rare single nucleotide variants in coding regions.评估28种致病性预测方法对编码区罕见单核苷酸变异的性能。
BMC Genomics. 2025 Jul 7;26(1):641. doi: 10.1186/s12864-025-11787-4.
8
Mitochondrial haplogroup A2 is associated with increased COVID-19 mortality in an admixed Brazilian population.线粒体单倍群A2与巴西混血人群中新冠病毒疾病(COVID-19)死亡率增加有关。
Sci Rep. 2025 Jul 1;15(1):22391. doi: 10.1038/s41598-025-03578-4.
9
Rare genetic variants and severe COVID-19 in previously healthy admixed Latin American adults.先前健康的拉丁裔成年混血人群中的罕见基因变异与重症新冠肺炎
Sci Rep. 2025 Jul 2;15(1):23074. doi: 10.1038/s41598-025-08416-1.
10
Identifying Rare Germline Variants Associated with Metastatic Prostate Cancer Through an Extreme Phenotype Study.通过极端表型研究鉴定与转移性前列腺癌相关的罕见种系变异。
medRxiv. 2025 Apr 29:2025.04.28.25326584. doi: 10.1101/2025.04.28.25326584.
Nature. 2020 May;581(7809):452-458. doi: 10.1038/s41586-020-2329-2. Epub 2020 May 27.
4
Evaluating drug targets through human loss-of-function genetic variation.通过人类功能丧失性遗传变异评估药物靶点。
Nature. 2020 May;581(7809):459-464. doi: 10.1038/s41586-020-2267-z. Epub 2020 May 27.
5
A structural variation reference for medical and population genetics.医学和人群遗传学的结构变异参考
Nature. 2020 May;581(7809):444-451. doi: 10.1038/s41586-020-2287-8. Epub 2020 May 27.
6
Non-coding and Loss-of-Function Coding Variants in TET2 are Associated with Multiple Neurodegenerative Diseases.非编码和 TET2 功能丧失编码变异与多种神经退行性疾病相关。
Am J Hum Genet. 2020 May 7;106(5):632-645. doi: 10.1016/j.ajhg.2020.03.010. Epub 2020 Apr 23.
7
Population Screening for Inherited Predisposition to Breast and Ovarian Cancer.遗传性乳腺癌和卵巢癌易感性的人群筛查。
Annu Rev Genomics Hum Genet. 2020 Aug 31;21:373-412. doi: 10.1146/annurev-genom-083118-015253. Epub 2020 Apr 21.
8
A Multi-Omics Perspective of Quantitative Trait Loci in Precision Medicine.精准医学中定量性状基因座的多组学视角
Trends Genet. 2020 May;36(5):318-336. doi: 10.1016/j.tig.2020.01.009. Epub 2020 Feb 24.
9
Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases.评估数字表型学以增强人类疾病的遗传研究。
Am J Hum Genet. 2020 May 7;106(5):611-622. doi: 10.1016/j.ajhg.2020.03.007. Epub 2020 Apr 9.
10
NCCN Guidelines Insights: Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic, Version 1.2020.NCCN 指南解读:遗传/家族性高风险评估:乳腺、卵巢和胰腺,第 1.2020 版。
J Natl Compr Canc Netw. 2020 Apr;18(4):380-391. doi: 10.6004/jnccn.2020.0017.