Challenges in screening for de novo noncoding variants contributing to genetically complex phenotypes.
Challenges in screening for de novo noncoding variants contributing to genetically complex phenotypes.
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DOI：
10.1016/j.xhgg.2023.100210
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发表时间：
2023-07-13
期刊：
影响因子：
--
通讯作者：
Boyle, Alan P.
中科院分区：
文献类型：
--
作者：
Castro, Christopher P.;Diehl, Adam G.;Boyle, Alan P.
了解复杂的异质性疾病（如自闭症谱系障碍（ASD））的遗传基础是人类医学的一个持续挑战。由于其表型的复杂性，这些疾病的遗传机制可能是高度可变的个体患者。此外，它们的遗传性大部分无法用已知的调节或编码变体来解释。事实上，有证据表明，许多因果遗传变异源于正在进行的突变引起的罕见和新生变异。这些变异主要发生在非编码区，可能影响与感兴趣的表型相关的基因的调控过程。然而，由于没有统一的代码来评估调节功能，因此很难将这些突变分为可能的功能性和非功能性子集。这使得寻找复杂疾病与潜在因果性从头单核苷酸变异（dnSNV）之间的关联成为一项艰巨的任务。到目前为止，大多数已发表的研究都在努力寻找ASD患者的dnSNV与任何一类已知调控元件之间的任何显著关联。我们试图找出造成这种情况的根本原因，并提出克服这些挑战的战略。我们发现，与以前的说法相反，未能找到强大的统计富集的主要原因不仅是抽样家庭的数量，而且用于优先考虑dnSNVs的注释的质量和与ASD的相关性，以及dnSNVs本身的可靠性。我们提出了一个建议，以设计未来的研究，这将有助于研究人员避免常见的陷阱。由于自闭症等复杂疾病的变异性和难以捉摸的遗传性，揭开其遗传基础仍然具有挑战性。研究人员努力寻找罕见遗传变异与这些疾病之间的重要联系。这项研究强调了需要更好的数据质量，相关的注释和改进的研究设计，以克服这些障碍。
Understanding the genetic basis for complex, heterogeneous disorders, such as autism spectrum disorder (ASD), is a persistent challenge in human medicine. Owing to their phenotypic complexity, the genetic mechanisms underlying these disorders may be highly variable across individual patients. Furthermore, much of their heritability is unexplained by known regulatory or coding variants. Indeed, there is evidence that much of the causal genetic variation stems from rare and de novo variants arising from ongoing mutation. These variants occur mostly in noncoding regions, likely affecting regulatory processes for genes linked to the phenotype of interest. However, because there is no uniform code for assessing regulatory function, it is difficult to separate these mutations into likely functional and nonfunctional subsets. This makes finding associations between complex diseases and potentially causal de novo single-nucleotide variants (dnSNVs) a difficult task. To date, most published studies have struggled to find any significant associations between dnSNVs from ASD patients and any class of known regulatory elements. We sought to identify the underlying reasons for this and present strategies for overcoming these challenges. We show that, contrary to previous claims, the main reason for failure to find robust statistical enrichments is not only the number of families sampled, but also the quality and relevance to ASD of the annotations used to prioritize dnSNVs, and the reliability of the set of dnSNVs itself. We present a list of recommendations for designing future studies of this sort that will help researchers avoid common pitfalls. Unraveling the genetic basis of complex disorders like autism remains challenging due to their variability and elusive heritability. Researchers struggle to find significant links between rare genetic variants and these conditions. This study highlights the need for better data quality, relevant annotations, and improved study designs to overcome these obstacles.
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DOI：
10.1093/bioinformatics/btq033
发表时间：
2010-03-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Quinlan AR;Hall IM
通讯作者：
Hall IM
DOI：
10.1109/tvcg.2014.2346248
发表时间：
2014-12
影响因子：
5.2
作者：
Lex A;Gehlenborg N;Strobelt H;Vuillemot R;Pfister H
通讯作者：
Pfister H
影响因子：
12.3
作者：
McLaren W;Gil L;Hunt SE;Riat HS;Ritchie GR;Thormann A;Flicek P;Cunningham F
通讯作者：
Cunningham F
影响因子：
64.8
作者：
Iossifov, Ivan;O'Roak, Brian J.;Sanders, Stephan J.;Ronemus, Michael;Krumm, Niklas;Levy, Dan;Stessman, Holly A.;Witherspoon, Kali T.;Vives, Laura;Patterson, Karynne E.;Smith, Joshua D.;Paeper, Bryan;Nickerson, Deborah A.;Dea, Jeanselle;Dong, Shan;Gonzalez, Luis E.;Mandell, Jeffrey D.;Mane, Shrikant M.;Murtha, Michael T.;Sullivan, Catherine A.;Walker, Michael F.;Waqar, Zainulabedin;Wei, Liping;Willsey, A. Jeremy;Yamrom, Boris;Lee, Yoon-ha;Grabowska, Ewa;Dalkic, Ertugrul;Wang, Zihua;Marks, Steven;Andrews, Peter;Leotta, Anthony;Kendall, Jude;Hakker, Inessa;Rosenbaum, Julie;Ma, Beicong;Rodgers, Linda;Troge, Jennifer;Narzisi, Giuseppe;Yoon, Seungtai;Schatz, Michael C.;Ye, Kenny;McCombie, W. Richard;Shendure, Jay;Eichler, Evan E.;State, Matthew W.;Wigler, Michael
通讯作者：
Wigler, Michael
影响因子：
64.8
作者：
Kong A;Frigge ML;Masson G;Besenbacher S;Sulem P;Magnusson G;Gudjonsson SA;Sigurdsson A;Jonasdottir A;Jonasdottir A;Wong WS;Sigurdsson G;Walters GB;Steinberg S;Helgason H;Thorleifsson G;Gudbjartsson DF;Helgason A;Magnusson OT;Thorsteinsdottir U;Stefansson K
通讯作者：
Stefansson K