【佳學(xué)基因檢測】遺傳變異分類標準與指南——行業(yè)質(zhì)量要求、規(guī)范

【佳學(xué)基因檢測】遺傳變異分類標準與指南——行業(yè)質(zhì)量要求、規(guī)范

人類基因序列變化數(shù)據(jù)庫導(dǎo)讀

人類基因信息的破解與解密與解碼包含基因序列的獲取，變異序列的描述與分類、變異序列對疾病治與發(fā)展的影響。根據(jù)佳學(xué)基因的控制標準，基因序列變化的生物學(xué)意義與性質(zhì)和數(shù)量兩個方面來描述。這其中的任何一個環(huán)節(jié)都可以從根本上使得同一個個體的基因檢測檢測結(jié)果截然不同。佳學(xué)基因在多個地方描述了基因解碼與基因檢測的重大區(qū)別。本文介紹了國際上基因序列變化的分類標準的描述，以促進從業(yè)者可以具備賊基本的質(zhì)量標準。

免責聲明

These ACMG Standards and Guidelines were developed primarily as an educational resource for clinical laboratory geneticists to help them provide quality clinical laboratory services. Adherence to these standards and guidelines is voluntary and does not necessarily assure a successful medical outcome. These Standards and Guidelines should not be considered inclusive of all proper procedures and tests or exclusive of other procedures and tests that are reasonably directed to obtaining the same results. In determining the propriety of any specific procedure or test, the clinical laboratory geneticist should apply his or her own professional judgment to the specific circumstances presented by the individual patient or specimen. Clinical laboratory geneticists are encouraged to document in the patient’s record the rationale for the use of a particular procedure or test, whether or not it is in conformance with these Standards and Guidelines. They also are advised to take notice of the date any particular guideline was adopted and to consider other relevant medical and scientific information that becomes available after that date. It also would be prudent to consider whether intellectual property interests may restrict the performance of certain tests and other procedures.

ACMG制定的標準與指南作為教育資源旨在幫助臨床遺傳學(xué)家提供優(yōu)質(zhì)的臨床檢驗服務(wù)。遵循該標準和指南屬于自愿行為并且不一定能夠確保一個成功的醫(yī)療結(jié)局。該標準和指南并不囊括所有合適的流程和檢測，也不排斥其他可以獲得相同結(jié)果的流程和檢測。臨床實驗室遺傳學(xué)家應(yīng)該利用自己的專業(yè)知識，依據(jù)病人或樣本的具體情況來判斷某一具體的流程或檢測的合理性。我們鼓勵臨床實驗室遺傳學(xué)家記錄對病人使用的某一具體流程或檢測的原理，不管這個原理與這些標準與指南是否符合。同時建議臨床實驗室遺傳學(xué)家關(guān)注指南的采用時間，應(yīng)考慮到此后更新的一些相關(guān)醫(yī)療和科學(xué)信息。還需謹慎考慮到知識產(chǎn)權(quán)可能會限制某些檢測或流程的使用。

 

摘要

The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants.1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next-generation sequencing. By adopting and leveraging next-generation sequencing, clinical laboratories are now performing an ever-increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes, and epigenetic assays for genetic disorders. By virtue of increased complexity, this shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context the ACMG convened a workgroup in 2013 comprising representatives from the ACMG, the Association for Molecular Pathology (AMP), and the College of American Pathologists to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP, and College of American Pathologists stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories, including genotyping, single genes, panels, exomes, and genomes. This report recommends the use of specific standard terminology—“pathogenic,” “likely pathogenic,” “uncertain significance,” “likely benign,” and “benign”—to describe variants identified in genes that cause Mendelian disorders. Moreover, this recommendation describes a process for classifying variants into these five categories based on criteria using typical types of variant evidence (e.g., population data, computational data, functional data, segregation data). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a Clinical Laboratory Improvement Amendments–approved laboratory, with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or the equivalent.

美國醫(yī)學(xué)遺傳學(xué)與基因組學(xué)學(xué)會(The American College of Medical Genetics and Genomics，ACMG)曾制定過序列變異解讀指南。在過去的十年中，隨著新一代高通量測序的出現(xiàn)，測序技術(shù)有了快速發(fā)展。利用新一代測序技術(shù)，臨床實驗室檢測遺傳性疾病的產(chǎn)品種類不斷增加，包括基因分型、單基因、基因包、外顯子組、基因組、轉(zhuǎn)錄組和表觀遺傳學(xué)檢測。隨著技術(shù)的復(fù)雜性日益增加，基因檢測在序列解讀方面不斷面臨著新的挑戰(zhàn)。因此ACMG在2013年成立了一個工作組來重新審視和修訂序列變異解讀的標準和指南，工作組包括ACMG、分子病理協(xié)會(the Association for Molecular Pathology，AMP)和美國病理學(xué)家協(xié)會(the College of American Pathologists，CAP)的代表。該工作組由臨床實驗室主任和臨床醫(yī)生組成。本報告代表了工作組中來自ACMG，AMP和CAP的專家意見。本報告提出的建議可應(yīng)用于臨床實驗室的各種基因檢測方法，包括基因分型、單基因、基因包、外顯子組和基因組。本報告建議使用特定標準術(shù)語來描述孟德爾疾病相關(guān)的基因變異——“致病的”、“可能致病的”、“意義不明確的”、“可能良性的”和“良性的”。此外，本報告描述了基于典型的數(shù)據(jù)類型(如人群數(shù)據(jù)，計算數(shù)據(jù)，功能數(shù)據(jù)，共分離數(shù)據(jù))對變異進行五級分類的標準過程。由于臨床基因檢測分析和解讀中不斷增加的復(fù)雜性，ACMG強烈建議臨床分子基因檢測應(yīng)在符合臨床實驗室改進修正案(CLIA)認證的實驗室中進行，其檢測結(jié)果應(yīng)由通過職業(yè)認證的臨床分子遺傳學(xué)家或分子遺傳病理學(xué)家或相同職能的專業(yè)人員解讀。

 

Key Words 關(guān)鍵詞

ACMG laboratory guideline; clinical genetic testing; interpretation; reporting; sequence variant terminology; variant reporting

ACMG實驗室指南；臨床遺傳檢測；解讀；報告；序列變異術(shù)語；變異報告

 

1.引言

Clinical molecular laboratories are increasingly detecting novel sequence variants in the course of testing patient specimens for a rapidly increasing number of genes associated with genetic disorders. While some phenotypes are associated with a single gene, many are associated with multiple genes. Our understanding of the clinical significance of any given sequence variant falls along a gradient, ranging from those in which the variant is almost certainly pathogenic for a disorder to those that are almost certainly benign. While the previous American College of Medical Genetics and Genomics (ACMG) recommendations provided interpretative categories of sequence variants and an algorithm for interpretation, the recommendations did not provide defined terms or detailed variant classification guidance.1 This report describes updated standards and guidelines for the classification of sequence variants using criteria informed by expert opinion and empirical data.

隨著遺傳病患者樣本中所檢測基因數(shù)目的快速增加，臨床分子實驗室檢測到越來越多的新的序列變異。某些表型僅與單個基因相關(guān)，而多數(shù)表型與多個基因相關(guān)。對某個給定序列變異的臨床意義進行分級解讀，從某個變異幾乎可以肯定是某種疾病的致病性變異到幾乎可以肯定是良性變異。雖然ACMG之前的建議提供了序列變異的解讀分類及解讀的算法，但并沒有提供明確的術(shù)語或詳細的變異分類指導(dǎo)。本研究依據(jù)專家意見及經(jīng)驗數(shù)據(jù)，闡述了賊新的序列變異分類標準和指南。

 

2.方法

In 2013 a workgroup consisting of ACMG, Association for Molecular Pathology (AMP), and College of American Pathologists members, representing clinical laboratory directors and clinicians, was formed with the goal of developing a recommendation for the use of standard terminology for classifying sequence variants using available evidence weighted according to a system developed through expert opinion, workgroup consensus, and community input. To assess the views of the clinical laboratory community, surveys were sent to over 100 sequencing laboratories in the United States and Canada that were listed in GeneTests.org, requesting input on terminology preferences and evaluation of evidence for classifying variants. Laboratory testing experience included rare disease as well as pharmacogenomics and somatic cancer testing. The first survey, aimed at assessing terminology preferences, was sent in February 2013, and the results were presented in an open forum at the 2013 ACMG annual meeting including over 75 attendees. Survey respondents represented more than 45 laboratories in North America. The outcome of the survey and open forum indicated that (i) a five-tier terminology system using the terms “pathogenic,” “likely pathogenic,” “uncertain significance,” “likely benign,” and “benign” was preferred and already in use by a majority of laboratories, and (ii) the first effort of the workgroup should focus on Mendelian and mitochondrial variants.

2013年，ACMG，AMP和CAP的成員，代表臨床實驗室主任和臨床醫(yī)生成立了一個工作組，該工作組依據(jù)專家建議、工作組共識和公眾反饋開發(fā)了一種可以對現(xiàn)有的證據(jù)進行加權(quán)的系統(tǒng)，并應(yīng)用此系統(tǒng)對序列變異進行標準分類。為了評估臨床實驗室的觀點，對列入GeneTests.org上位于美國和加拿大的超過100家的測序?qū)嶒炇疫M行了調(diào)研，要求各實驗室填寫參考術(shù)語及變異分類的評估證據(jù)。這些實驗室有檢測包括罕見病、藥物基因組學(xué)和癌癥體細胞突變的經(jīng)驗。先進次調(diào)研于2013年2月開展，該調(diào)研旨在評估參考術(shù)語的偏好，調(diào)研結(jié)果公布在同年ACMG年會公開論壇上，該年會有超過75個與會者參加。調(diào)研結(jié)果代表超過45個位于北美的實驗室。調(diào)研和公開論壇的結(jié)果表明: (i) 五級術(shù)語系統(tǒng)“致病的”、“可能致病的”、“意義不明確的”、“可能良性的”和“良性的”是優(yōu)選承認的，且已在多數(shù)實驗室使用; (ii) 工作組的首要重點應(yīng)著重于孟德爾疾病和線粒體變異。

In the first survey, laboratories also were asked to provide their protocols for variant assessment, and 11 shared their methods. By analyzing all the protocols submitted, the workgroup developed a set of criteria to weight variant evidence and a set of rules for combining criteria to arrive at one of the five classification tiers. Workgroup members tested the scheme within their laboratories for several weeks using variants already classified in their laboratories and/or by the broader community. In addition, typical examples of variants harboring the most common types of evidence were tested for classification assignment to ensure the system would classify those variants according to current approaches consistently applied by workgroup members. A second survey was sent in August 2013 to the same laboratories identified through GeneTests. org as well as through AMP’s listserv of ~2,000 members, along with the proposed classification scheme and a detailed supplement describing how to use each of the criteria. Laboratories were asked to use the scheme and to provide feedback as to the suitability and relative weighting of each criteria, the ease of use of the classification system, and whether they would adopt such a system in their own laboratory. Responses from over 33 laboratories indicated majority support for the proposed approach, and feedback further guided the development of the proposed standards and guidelines.

在先進次調(diào)研中，參與的實驗室被要求提供他們的變異評估方法，賊終有11個實驗室提供并分享了他們的變異評估方法。通過分析所有提交的方法，工作組制定了一組準則，包括變異證據(jù)評估的加權(quán)標準體系和應(yīng)用這個標準將變異歸類為五類的分類準則。在今后的幾周時間里，工作組成員通過在自己實驗室或其他機構(gòu)已進行分類的變異來驗證這個方案。另外，還將典型變異的常見證據(jù)進行分類，來測試工作組成員達成一致的現(xiàn)有方法是否可以對這些變異進行分類。2013年8月，第二次調(diào)研在GeneTests.org上的相同實驗室以及AMP清單上的約2000個單位中進行，同時給各單位提供了分類方案和詳細的方案補充說明，要求各實驗室使用該分類方案并對以下內(nèi)容進行反饋，包括各標準的適宜性和每個標準的相對權(quán)重、分類體系的易用性以及他們是否會在自己的實驗室采用這樣的體系。來自超過33個實驗室的答復(fù)表明多數(shù)實驗室支持所推薦的分類方案，同時，他們的反饋進一步地指導(dǎo)了標準和指南的完善。

In November 2013 the workgroup held a workshop at the AMP meeting with more than 50 attendees, presenting the revised classification criteria and two potential scoring systems. One system is consistent with the approach presented here and the other is a point system whereby each criterion is given a number of points, assigning positive points for pathogenic criteria and negative points for benign criteria, with the total defining the variant class. With an audience-response system, the participants were asked how they would weight each criterion (as strong, moderate or supporting, or not used) during evaluation of variant evidence. Again, the responses were incorporated into the classification system presented here. It should be noted that while the majority of respondents did favor a point system, the workgroup felt that the assignment of specific points for each criterion implied a quantitative level of understanding of each criterion that is currently not supported scientifically and does not take into account the complexity of interpreting genetic evidence.

2013年11月，工作組在AMP會議期間舉行了超過50人參加的研討會，提出了修訂后的分類標準和兩個評分體系。一個體系與這里介紹的方法是一致的，另一個體系則是一個分數(shù)體系，每一項標準都有一個分數(shù)，正分數(shù)為致病標準，負分數(shù)為良性標準，根據(jù)總分數(shù)進行變異分類。參與者使用此系統(tǒng)并進行反饋，回答在評估變異證據(jù)過程中他們?nèi)绾螜?quán)衡各個標準(如強、中度或支持、或不使用)。參與者的反饋結(jié)果再次綜合到這里介紹的分類體系中。但要指出的是，雖然大多數(shù)回復(fù)更傾向于分數(shù)評價體系，但本工作組認為，每個標準中具體分數(shù)的設(shè)置 量化了對每個標準的理解，但是這一量化指標目前缺乏科學(xué)依據(jù)，并且沒有考慮遺傳證據(jù)解讀時的復(fù)雜性。

The workgroup also evaluated the literature for recommendations from other professional societies and working groups that have developed variant classification guidelines for wellstudied genes in breast cancer, colon cancer, and cystic fibrosis and statistical analysis programs for quantitative evaluation of variants in select diseases.While those variant analysis guidelines are useful in a specific setting, it was difficult to apply their proposed criteria to all genes and in different laboratory settings. The variant classification approach described in this article is meant to be applicable to variants in all Mendelian genes, whether identified by single gene tests, multigene panels, exome sequencing, or genome sequencing. We expect that this variant classification approach will evolve as technology and knowledge improve. We should also note that those working in specific disease groups should continue to develop more focused guidance regarding the classification of variants in specific genes given that the applicability and weight assigned to certain criteria may vary by gene and disease.

工作組還評估了文獻中推薦的其他專業(yè)協(xié)會和工作組在乳腺癌、結(jié)腸癌和囊性纖維化中已制定的變異分類指南，以及在特定疾病中應(yīng)用統(tǒng)計分析來進行變異定量評估的方法。這些變異分析指南在特定條件下是有效的，但很難將他們推薦的標準應(yīng)用于所有基因變異及不同的實驗室條件。本文描述的變異分類方法適用于所有孟德爾基因變異，包括單基因、多基因包、外顯子組和基因組測序發(fā)現(xiàn)的變異。期望這種變異分類方法會隨著技術(shù)和知識水平的提高而與時俱進。由于不同基因和不同疾病中的應(yīng)用和加權(quán)評估的標準可能不同，特定疾病組的工作應(yīng)繼續(xù)，以制定更有針對性的具體基因的變異分類指南。

 

3.總論

3.1 術(shù)語

A mutation is defined as a permanent change in the nucleotide sequence, whereas a polymorphism is defined as a variant with a frequency above 1%. The terms “mutation” and “polymorphism,” however, which have been used widely, often lead to confusion because of incorrect assumptions of pathogenic and benign effects, respectively. Thus, it is recommended that both terms be replaced by the term “variant” with the following modifiers: (i) pathogenic, (ii) likely pathogenic, (iii) uncertain significance, (iv) likely benign, or (v) benign. Although these modifiers may not address all human phenotypes, they comprise a five-tier system of classification for variants relevant to Mendelian disease as addressed in this guidance. It is recommended that all assertions of pathogenicity (including “likely pathogenic”) be reported with respect to a condition and inheritance pattern (e.g., c.1521_1523delCTT (p.Phe508del), pathogenic, cystic fibrosis, autosomal recessive).

突變是指核苷酸序列的有效、悠久、長期、很久性改變，而多態(tài)性是指頻率超過1%的變異。雖然術(shù)語“突變”和“多態(tài)性”已被廣泛使用，但由于這兩個術(shù)語已經(jīng)錯誤地與致病性和良性結(jié)果關(guān)聯(lián)了起來，所以往往會造成混淆。因此，建議使用“變異”加以下修飾詞替代上述兩個術(shù)語: 致病性的、可能致病性的、意義不明確的、可能良性的或良性的。雖然這些修飾詞不可能適用所有的人類表型，但是正如本指南提出的它包含了孟德爾疾病相關(guān)的變異分類五級系統(tǒng)。建議所有致病性(包括可能致病)的結(jié)論需要注明疾病及相應(yīng)的遺傳模式(如c.1521_1523delCTT(p.Phe508del)，致病性，囊性纖維化，常染色體隱性遺傳)。

It should be noted that some laboratories may choose to have additional tiers (e.g., subclassification of variants of uncertain significance, particularly for internal use), and this practice is not considered inconsistent with these recommendations. It should also be noted that the terms recommended here differ somewhat from the current recommendations for classifying copy-number variants detected by cytogenetic microarray.6 The schema recommended for copy-number variants, while also including five tiers, uses “uncertain clinical significance— likely pathogenic” and “uncertain clinical significance—likely benign.” The majority of the workgroup was not supportive of using “uncertain significance” to modify the terms “likely pathogenic” or “likely benign” given that it was felt that the criteria presented here to classify variants into the “likely” categories included stronger evidence than outlined in the copy-number variant guideline and that combining these two categories would create confusion for the health-care providers and individuals receiving clinical reports. However, it was felt that the use of the term “likely” should be restricted to variants where the data support a high likelihood that it is pathogenic or a high likelihood that it is benign. Although there is no quantitative definition of the term “likely,” guidance has been proposed in certain variant classification settings. A survey of the community during an ACMG open forum, however, suggested a much wider range of uses of the term “likely.” Recognizing this, we propose that the terms “likely pathogenic” and “likely benign” be used to mean greater than 90% certainty of a variant either being diseasecausing or benign to provide laboratories with a common, albeit arbitrary, definition. Similarly, the International Agency for Research on Cancer guideline supports a 95% level of certainty of pathogenicity, but the workgroup (confirmed by feedback during the ACMG open forum) felt that clinicians and patients were willing to tolerate a slightly higher chance of error, leading to the 90% decision. It should also be noted that at present most variants do not have data to support a quantitative assignment of variant certainty to any of the five categories given the heterogeneous nature of most diseases. It is hoped that over time experimental and statistical approaches to objectively assign pathogenicity confidence to variants will be developed and that more rigorous approaches to defining what the clinical community desires in terms of confidence will more fully inform terminologies and likelihoods.

應(yīng)當注意的是，一些實驗室可能選擇其他等級(如意義不明確的變異的子分類，特別是內(nèi)部使用時)，這種做法不被認為與指南不一致。還應(yīng)當指出的是，某種程度上本指南推薦的術(shù)語與細胞遺傳學(xué)基因芯片檢測的拷貝數(shù)變異分類不同。雖然拷貝數(shù)變異分類系統(tǒng)也包括五級分類標準，但是它使用“臨床意義不明確-可能致病的”和“臨床意義不明確-可能良性的”。由于本指南提出的“可能的”變異分類標準比拷貝數(shù)變異分類指南中用到的“可能的”包含更強的證據(jù)，合并這兩個“可能的”分類會使醫(yī)務(wù)工作者和臨床報告接收者產(chǎn)生混淆，因此大多數(shù)工作組成員不支持使用“意義不明確的”來修飾“可能致病的”或“可能良性的”。然而，有人認為“可能的”一詞的使用應(yīng)限于有數(shù)據(jù)支持其致病性或良性可能性很大的變異。雖然對“可能的”一詞沒有量化的定義，但是在某些變異分類系統(tǒng)中已有指導(dǎo)性意見。然而，ACMG開放論壇的一項調(diào)查建議“可能的”這一術(shù)語具有更廣泛的適用性。認識到這一點，建議術(shù)語“可能致病的”和“可能良性的”用來說明一個具有大于90%可能引起致病或者可能良性的變異，盡管是人為的界定，但還是給實驗室提供了一種共同的定義。類似地，國際癌癥機構(gòu)指南支持致病性的確定水平為95%，但是工作組(通過ACMG公開論壇期間的反饋確認)認為，臨床醫(yī)生和患者愿意容忍略高的錯誤機會，從而做出確定為90%的決定。還應(yīng)當指出的是，考慮到多數(shù)疾病具有異質(zhì)性，目前大多數(shù)變異沒有數(shù)據(jù)能將它們量化性地歸于上述五個變異類別之一。希望隨著時間的推移，能夠建立實驗和統(tǒng)計方法來客觀地賦予變異的致病可信度，并且采用更嚴格的方法來定義臨床專業(yè)人員所期望達到的可信度，從而能更完整的詮釋這些術(shù)語及可能性。

The use of new terminologies may require education of the community. Professional societies are encouraged to engage in educating all laboratories as well as health-care providers on the use of these terms, and laboratories also are encouraged to directly educate their ordering physicians.

新術(shù)語的使用可能需要專業(yè)培訓(xùn)，鼓勵專業(yè)團隊對所有實驗室和醫(yī)務(wù)工作者進行這些術(shù)語的培訓(xùn)，也鼓勵實驗室直接對其開具檢測報告單的醫(yī)生進行培訓(xùn)教育。

3.2 命名

A uniform nomenclature, informed by a set of standardized criteria, is recommended to ensure the unambiguous designation of a variant and enable effective sharing and downstream use of genomic information. A standard gene variant nomenclature (http://www.hgvs.org/mutnomen) is maintained and versioned by the Human Genome Variation Society (HGVS), and its use is recommended as the primary guideline for determining variant nomenclature except as noted. Laboratories should note the version being used in their test methods. Tools are available to provide correct HGVS nomenclature for describing variants (https://mutalyzer.nl). Clinical reports should include sequence reference(s) to ensure unambiguous naming of the variant at the DNA level, as well as to provide coding and protein nomenclature to assist in functional interpretations (e.g., “g.” for genomic sequence, “c.” for coding DNA sequence, “p.” for protein, “m.” for mitochondria).

建議通過一套規(guī)范的標準對變異進行統(tǒng)一命名來確保變異的明確定義，并實現(xiàn)基因組信息的有效共享和下游使用。標準的基因變異命名由人類基因組變異協(xié)會(the Human Genome Variation Society，HGVS)維護和版本化(https://www.hgvs.org/mutnomen)，除非另有說明，一般推薦該命名法作為確定變異命名的首要準則。實驗室應(yīng)該注意他們在實驗方法中所使用的版本。當描述變異時，可利用這些工具提供正確的HGVS命名(http://mutalyzer.nl)。臨床報告應(yīng)該包含參考序列以確保該變異在DNA水平上的明確命名，并提供編碼和蛋白質(zhì)命名法來協(xié)助功能注釋(如“g”為基因組序列，“c”為編碼DNA序列，“p”為蛋白質(zhì)，“m”為線粒體)。

The coding nomenclature should be described using the “A” of the ATG translation initiation codon as position number 1. Where historical alternate nomenclature has been used, current nomenclature should be used with an additional notation of the historical naming. The reference sequence should be complete and derived from either the National Center for Biotechnology Information RefSeq database (http://www.ncbi.nlm.nih.gov/RefSeq/) with the version number or the Locus Reference Genomic database (http:// www.lrg-sequence.org). Genomic coordinates should be used and defined according to a standard genome build (e.g., hg19) or a genomic reference sequence that covers the entire gene (including the 5′ and 3′ untranslated regions and promoter). A reference transcript for each gene should be used and provided in the report when describing coding variants. The transcript should represent either the longest known transcript and/or the most clinically relevant transcript. Communitysupported reference transcripts can often be identified through Locus Reference Genomic, the Consensus CDS Database, the Human Gene Mutation Database (http://www.hgmd. cf.ac.uk), ClinVar (http://www.ncbi.nlm.nih.gov/clinvar), or a locus-specific database. However, laboratories should evaluate the impact of the variant on all clinically relevant transcripts, including alternate transcripts that contain additional exons or extended untranslated regions, when there are known variants in these regions that are clinically interpretable.

編碼命名應(yīng)該使用翻譯起始密碼子ATG中的“A”作為位置編號1來描述。在傳統(tǒng)命名已被使用的地方，當今命名應(yīng)該對傳統(tǒng)命名進行額外注釋。參考序列應(yīng)該是完整的，并來源于具有版本號的美國生物技術(shù)信息參考序列數(shù)據(jù)庫(http://www.ncbi.nlm.nih.gov/Refseq/)或LRG數(shù)據(jù)庫(http://www.lrg-sequence.org)?；蚪M坐標應(yīng)根據(jù)標準基因組版本(如hg19)或覆蓋整個基因(包括5’和3’非翻譯區(qū)以及啟動子)的基因組參考序列來界定。當描述編碼變異時，應(yīng)該在報告中使用和提供每個基因的一個參考轉(zhuǎn)錄本。該轉(zhuǎn)錄本應(yīng)該是賊長的已知轉(zhuǎn)錄本或者是賊具臨床相關(guān)性的轉(zhuǎn)錄本。協(xié)會支持的參考轉(zhuǎn)錄本通常可以通過LRG數(shù)據(jù)庫(http://www.lrg-sequence.org)、CDS共識數(shù)據(jù)庫(https://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi)、人類基因突變數(shù)據(jù)庫(http://www.hgmd.cf.ac.uk)、ClinVar (http://www.ncbi.nlm.nih.gov/clinvar)或特異基因座數(shù)據(jù)庫來確定。然而，當這些區(qū)域發(fā)生臨床可解釋的已知變異時，實驗室應(yīng)該評估該變異對所有臨床相關(guān)的轉(zhuǎn)錄本的影響，包括含有其他外顯子或非翻譯區(qū)延伸的可變剪切轉(zhuǎn)錄本。

Not all types of variants (e.g., complex variants) are covered by the HGVS recommendations, but possible descriptions for complex variants have been reported. In addition, this ACMG recommendation supports three specific exceptions to the HGVS nomenclature rules: (i) “X” is still considered acceptable for use in reporting nonsense variants in addition to the current HGVS recommendation of “*” and “Ter”; (ii) it is recommended that exons be numbered according to the chosen reference transcript used to designate the variant; and (iii) the term “pathogenic” is recommended instead of “affects function” because clinical interpretation is typically directly evaluating pathogenicity.

HGVS(https://www.hgvs.org/mutnomen)并未覆蓋所有類型的變異(如復(fù)雜變異)，但是復(fù)雜變異的可能描述已被報道。此外，ACMG支持HGVS命名規(guī)則之外的三種特殊例外: (i) 除了當今HGVS推薦的“*”和“Ter”，“X”仍然被認為用于報告無義變異; (ii) 建議根據(jù)指定變異選擇的參考轉(zhuǎn)錄本對外顯子進行編號; (iii) 通常因為臨床解釋直接評估致病性，所以推薦使用術(shù)語“致病性”而不是“影響功能”。

3.3 文獻及數(shù)據(jù)庫使用

A large number of databases contain a growing number of variants that are continuously being discovered in the human genome. When classifying and reporting a variant, clinical laboratories may find valuable information in databases, as well as in the published literature. As noted above, sequence databases can also be used to identify appropriate reference sequences. Databases can be useful for gathering information but should be used with caution.

目前人類基因組中大量變異不斷被發(fā)現(xiàn)，且已被許多數(shù)據(jù)庫廣泛收錄。當臨床實驗室需要對某一變異進行分類并出具報告時，可在已有的數(shù)據(jù)庫及發(fā)表的文獻中尋找到有價值的參考信息。如上文提及，序列數(shù)據(jù)庫還可用于確定合適的參考序列。數(shù)據(jù)庫有助于信息收集，但需謹慎使用。

Population databases (Table 1) are useful in obtaining the frequencies of variants in large populations. Population databases cannot be assumed to include only healthy individuals and are known to contain pathogenic variants. These population databases do not contain extensive information regarding the functional effect of these variants or any possible associated phenotypes. When using population databases, one must determine whether healthy or disease cohorts were used and, if possible, whether more than one individual in a family was included, as well as the age range of the subjects.

人群數(shù)據(jù)庫(表1)適用于獲取某變異在大規(guī)模人群中發(fā)生頻率的相關(guān)信息。需要注意的是，人群數(shù)據(jù)庫中的信息不僅來源于健康個體，也包含致病性的變異。另外，人群數(shù)據(jù)庫并不包含變異的功能效應(yīng)及可能關(guān)聯(lián)的表型等相關(guān)信息。在使用人群數(shù)據(jù)庫時，須明確數(shù)據(jù)庫收錄的是健康群體的信息還是患病群體的信息; (如能確認)數(shù)據(jù)庫是否收錄了同一家庭多名成員的信息以及數(shù)據(jù)庫收錄的受試者的年齡范圍。

Disease databases (Table 1) primarily contain variants found in patients with disease and assessment of the variants’ pathogenicity. Disease and gene-specific databases often contain variants that are incorrectly classified, including incorrect claims published in the peer-reviewed literature, because many databases do not perform a primary review of evidence. When using disease databases, it is important to consider how patients were ascertained, as described below.

疾病數(shù)據(jù)庫(表1)主要包含病患中發(fā)現(xiàn)的變異以及對其致病性的評估。疾病數(shù)據(jù)庫和特定基因的數(shù)據(jù)庫常包含一些分類錯誤的變異，這些變異在已發(fā)表的同行評審的文獻中被錯誤判定，而多數(shù)數(shù)據(jù)庫在收錄變異相關(guān)信息時并未對證據(jù)進行基本的審核。因此，在使用疾病數(shù)據(jù)庫時，考慮患者是如何被確診的尤為重要，如下所述:

When using databases, clinical laboratories should (i) determine how frequently the database is updated, whether data curation is supported, and what methods were used for curation;(ii) confirm the use of HGVS nomenclature and determine the genome build and transcript references used for naming variants; (iii) determine the degree to which data are validated for analytical accuracy (e.g., low-pass nextgeneration sequencing versus Sanger-validated variants) and evaluate any quality metrics that are provided to assess data accuracy, which may require reading associated publications; and (iv) determine the source and independence of the observations listed.

當使用數(shù)據(jù)庫時，臨床實驗室應(yīng)做到: (i) 確定數(shù)據(jù)庫的更新頻率，確定數(shù)據(jù)庫收錄相關(guān)數(shù)據(jù)時是否進行了?？保约安捎檬裁捶椒ㄟM行數(shù)據(jù)?？? (ii) 確認采用HGVS命名體系，并確定描述變異的基因組版本和轉(zhuǎn)錄本參考序列; (iii) 確定數(shù)據(jù)分析正確度的驗證程度(如變異是源自于低覆蓋的新一代測序，還是通過了Sanger測序驗證)，并分析用于評估數(shù)據(jù)正確度的各種指標，要獲得這些信息可能需要閱讀相關(guān)的文獻; (iv) 確定收錄對象的來源及其少有性。

Variant assessment also includes searching the scientific and medical literature. Literature using older nomenclature and classification or based on a single observation should be used with caution. When identifying individuals and families with a variant, along with associated phenotypes, it is important to consider how patients were ascertained. This caveat is important when assessing data from publications because affected individuals and related individuals are often reported multiple times, depending on the context and size of the study. This may be due to authorship overlap, interlaboratory collaborations, or a proband and family members being followed across different clinical systems. This may mistakenly lead to duplicate counting of affected patients and a false increase in variant frequency. Overlapping authorship or institutions is the first clue to the potential for overlapping data sets.

變異解讀也需要檢索科學(xué)和醫(yī)學(xué)文獻。在參考一些采用舊的命名和分類系統(tǒng)或基于單一觀察結(jié)果的文獻時需要慎重。在參考攜帶某一變異并伴有相關(guān)表型的個體和家系的信息時，考慮患者是如何被確診尤為重要。在評估這些文獻的數(shù)據(jù)時需要謹慎客觀，這是由于受累患者及相關(guān)個體在基于不同背景和規(guī)模的研究中常常被多次重復(fù)報道。重復(fù)報道的發(fā)生可能是由于作者重疊、實驗室間合作或先證者及其家庭成員同時被不同臨床系統(tǒng)隨訪。而這些重復(fù)報道可能會導(dǎo)致受累個體被錯誤地重復(fù)計數(shù)，進而使變異頻率假性增高。作者或其研究機構(gòu)互相重疊是發(fā)現(xiàn)數(shù)據(jù)集重復(fù)的先進線索。

Clinical laboratories should implement an internal system to track all sequence variants identified in each gene and clinical assertions when reported. This is important for tracking genotype–phenotype correlations and the frequency of variants in affected and normal populations. Clinical laboratories are encouraged to contribute to variant databases, such as ClinVar, including clinical assertions and evidence used for the variant classification, to aid in the continued understanding of the impact of human variation. Whenever possible, clinical information should be provided following Health Insurance Portability and Accountability Act regulations for privacy. Clinical laboratories are encouraged to form collaborations with clinicians to provide clinical information to better understand how genotype influences clinical phenotype and to resolve differences in variant interpretation between laboratories. Because of the great potential to aid clinical laboratory practice, efforts are underway for clinical variant databases to be expanded and standardized. Standardization will provide easier access to updated information as well as facilitate submission from the clinical laboratory. For example, the ClinVar database allows for the deposition of variants with clinical observations and assertions, with review status tracked to enable a more transparent view of the levels of quality of the curation.

臨床實驗室應(yīng)建立一個內(nèi)部系統(tǒng)對已報告的基因序列變異及臨床診斷進行記錄。這對于分析基因型-表型之間的相關(guān)性，以及該變異在患者和正常人群中的發(fā)生頻率尤為重要。臨床實驗室也應(yīng)該積極提交變異數(shù)據(jù)到相關(guān)數(shù)據(jù)庫，如ClinVar數(shù)據(jù)庫，包含提交臨床評估信息以及用于變異分類的證據(jù)，以幫助人們不斷加深對人類遺傳變異所產(chǎn)生的效應(yīng)的理解。在任何時候，提供臨床數(shù)據(jù)應(yīng)遵循“健康保險攜帶和責任法案 (HIPAA)”對個人隱私保護的規(guī)定。臨床實驗室應(yīng)與臨床醫(yī)生合作，以獲得臨床信息，從而更好地理解基因型是如何影響臨床表型的，并解決不同實驗室對遺傳變異解讀存在差異的問題。臨床變異數(shù)據(jù)庫極大地促進臨床實驗室工作的開展，因此需對其進行擴展并標準化。標準化便于臨床實驗室獲取數(shù)據(jù)庫的賊新信息，同時有助于提交更新的信息。例如，ClinVar數(shù)據(jù)庫允許變異連同臨床表型和診斷相關(guān)信息一并提交，同時追蹤提交變異的審核狀態(tài)，以便對校勘質(zhì)量的水平提供一個更加透明的概貌。

3.4 生物信息學(xué)計算預(yù)測程序

A variety of in silico tools, both publicly and commercially available, can aid in the interpretation of sequence variants. The algorithms used by each tool may differ but can include determination of the effect of the sequence variant at the nucleotide and amino acid level, including determination of the effect of the variant on the primary and alternative gene transcripts, other genomic elements, as well as the potential impact of the variant on the protein. The two main categories of such tools include those that predict whether a missense change is damaging to the resultant protein function or structure and those that predict whether there is an effect on splicing (Table 2). Newer tools are beginning to address additional noncoding sequences.

各種公共和商業(yè)化計算機工具可以輔助解讀序列變異。每種工具使用的算法可能有差異，但都會包含序列變異在核苷酸及氨基酸水平上作用影響的判斷，包括變異對主要轉(zhuǎn)錄本，可變轉(zhuǎn)錄本，其他基因組元件影響作用的確認，也包括對蛋白質(zhì)潛在影響作用的判定。這些工具主要分為兩類: 一類可以預(yù)測錯義變異是否會破壞蛋白質(zhì)的功能或結(jié)構(gòu); 另一種可以預(yù)測是否影響剪接(表2)。新的工具已可以處理額外的非編碼序列。

The impact of a missense change depends on criteria such as the evolutionary conservation of an amino acid or nucleotide, the location and context within the protein sequence, and the biochemical consequence of the amino acid substitution. The measurement of one or a combination of these criteria is used in various in silico algorithms that assess the predicted impact of a missense change. Several efforts have evaluated the performance of available prediction software to compare them with each other and to assess their ability to predict “known” disease-causing variants. In general, most algorithms for missense variant prediction are 65–80% accurate when examining known disease variants. Most tools also tend to have low specificity, resulting in overprediction of missense changes as deleterious, and are not as reliable at predicting missense variants with a milder effect.18 The in silico tools more commonly used for missense variant interpretation in clinical laboratories include PolyPhen2, SIFT, and MutationTaster. A list of in silico tools used to predict missense variants can be found in Table 2.

錯義改變的影響作用是由不同的條件決定的，例如一個氨基酸或核苷酸的進化保守性、其在蛋白質(zhì)序列中的位置及其上下游序列，以及氨基酸置換導(dǎo)致的生化結(jié)果等。對各種計算機算法中的一個或幾個條件進行評測可以進一步評估錯義改變帶來的影響。已經(jīng)有一些工作在評估預(yù)測軟件的預(yù)測性能，是通過對這些預(yù)測軟件之間的相互比較評估他們預(yù)測已知致病突變的能力來實現(xiàn)的。一般情況下，多數(shù)算法預(yù)測已知致病的錯義突變的正確率能達到65%~80%。但是大多數(shù)工具的特異性較低，導(dǎo)致有些錯義改變被過度預(yù)測為有害突變，而且對于影響較小的錯義變異的預(yù)測也不高效。目前臨床實驗室常用的錯義變異解讀工具有PolyPhen 2，SIFT和MutationTaster。用于預(yù)測錯義變異的生物信息分析工具見表2。

Multiple software programs have been developed to predict splicing as it relates to the creation or loss of splice sites at the exonic or intronic level. In general, splice site prediction tools have higher sensitivity (~90–100%) relative to specificity (~60–80%) in predicting splice site abnormalities. Some of the in silico tools commonly used for splice site variant interpretation are listed in Table 2.

目前已開發(fā)出許多用于預(yù)測剪接的軟件，這是基于內(nèi)含子或外顯子水平上剪接位點的丟失或產(chǎn)生原理基礎(chǔ)上而完成的。一般情況下，相對于特異性(60%~80%)，預(yù)測工具在預(yù)測剪接位點異常方面具有較高的敏感性(~90%~100%)。一些常用的剪接位點預(yù)測分析計算工具見表2。

While many of the different software programs use different algorithms for their predictions, they have similarities in their underlying basis; therefore, predictions combined from different in silico tools are considered as a single piece of evidence in sequence interpretation as opposed to independent pieces of evidence. The use of multiple software programs for sequence variant interpretation is also recommended because the different programs each have their own strengths and weaknesses, depending on the algorithm; in many cases performance can vary by the gene and protein sequence. These are only predictions, however, and their use in sequence variant interpretation should be implemented carefully. It is not recommended that these predictions be used as the sole source of evidence to make a clinical assertion.

雖然許多不同的分析軟件程序使用不同的算法進行預(yù)測，但其基本原理是相似的; 因此，在序列解讀中，不同軟件工具組合的預(yù)測結(jié)果被視為單一證據(jù)而不是相互獨立的證據(jù)。因為每個軟件工具基于他們使用的算法都各有優(yōu)缺點，所以仍然建議使用多種軟件進行序列變異解讀; 很多情況下，預(yù)測性可能因為基因和蛋白質(zhì)序列的不同而有差異。無論如何，這些軟件分析結(jié)果只是預(yù)測，他們在序列變異解讀中的應(yīng)用應(yīng)該慎重。不建議僅使用這些預(yù)測結(jié)果作為少有證據(jù)來源進行臨床判斷。

 

4. 序列變異解讀的擬定標準

The following approach to evaluating evidence for a variant is intended for interpretation of variants observed in patients with suspected inherited (primarily Mendelian) disorders in a clinical diagnostic laboratory setting. It is not intended for the interpretation of somatic variation, pharmacogenomic (PGx) variants, or variants in genes associated with multigenic non- Mendelian complex disorders. Care must be taken when applying these rules to candidate genes (“genes of uncertain significance” (GUS)) in the context of exome or genome studies (see Special Considerations below) because this guidance is not intended to fulfill the needs of the research community in its effort to identify new genes in disease.

以下評估變異證據(jù)的方法是用了解釋在臨床診斷實驗室中具有疑似遺傳(主要指孟德爾遺傳)疾病患者的變異。并不適用于解讀體細胞變異、藥物基因組(PGx)變異、或者是多基因非孟德爾復(fù)雜疾病相關(guān)的基因變異。在外顯子組或基因組研究中，對候選基因(意義不明確的基因(GUS))應(yīng)用這些準則時應(yīng)當謹慎(見下面注意事項)，因為本指南目的不是滿足鑒定新致病基因的研究需求。

Although these approaches can be used for evaluating variants found in healthy individuals or secondary to the indication for testing, further caution must be used, as noted in several parts of the guideline, given the low prior likelihood that most variants unrelated to the indication are pathogenic. Although we expect that, in general, these guidelines will apply for variant classification regardless of whether the variant was identified through analysis of a single gene, gene panel, exome, genome, or transcriptome, it is important to consider the differences between implicating a variant as pathogenic (i.e., causative) for a disease and a variant that may be predicted to be disruptive/ damaging to the protein for which it codes, but is not necessarily implicated in a disease. These rules are intended to determine whether a variant in a gene with a definitive role in a Mendelian disorder may be pathogenic for that disorder. Pathogenicity determination should be independent of interpreting the cause of disease in a given patient. For example, a variant should not be reported as pathogenic in one case and not pathogenic in another simply because the variant is not thought to explain disease in a given case. Pathogenicity should be determined by the entire body of evidence in aggregate, including all cases studied, arriving at a single conclusion.

雖然這些方法可用于評估在健康個體中發(fā)現(xiàn)的變異或與測試指征不相關(guān)的變異，但是正如在指南的幾個部分中所述，對于與指征無關(guān)的有較低先驗致病性的變異時需更加謹慎。盡管期望本指南適用于變異分類，無論其是通過分析單基因，基因包，外顯子組，基因組或者轉(zhuǎn)錄組而鑒定的，重要的是要關(guān)注與疾病有關(guān)的致病變異和雖然預(yù)測為對蛋白有破壞/損傷但卻與疾病無充分關(guān)聯(lián)的變異之間的區(qū)別。這些規(guī)則旨在確定在孟德爾遺傳病中有明確作用的基因的變異是否對該遺傳疾病是致病的。針對具體的病人，致病性判定應(yīng)該獨立于對疾病病因的解讀。例如，某變異在一個案例中被評估為“致病的”，而在另一個案例中，由于不能解釋該疾病，就對這個位點不給出“致病的”評價，這樣的情況是先進不允許的。確定致病性需要將全部的證據(jù)匯集在一起，包括所有的案例分析，賊終得出一個結(jié)論。

This classification approach may be somewhat more stringent than laboratories have applied to date. They may result in a larger proportion of variants being categorized as uncertain significance. It is hoped that this approach will reduce the substantial number of variants being reported as “causative” of disease without having sufficient supporting evidence for that classification. It is important to keep in mind that when a clinical laboratory reports a variant as pathogenic, health-care providers are highly likely to take that as “actionable” and to alter the treatment or surveillance of a patient or remove such management in a genotype-negative family member, based on that determination (see How Should Health-Care Providers Use These Guidelines and Recommendations, below).

此指南的分類方法可能比目前實驗室應(yīng)用的標準更為嚴格。這將導(dǎo)致很大一部分的變異被歸類為“意義不明確的”。希望這種方法可以大量減少那些沒有足夠分類證據(jù)支持而報告為致病原因的變異。需要注意的是，當臨床實驗室報告一個變異為“致病的”時，醫(yī)療單位很可能把其當作“可指導(dǎo)臨床作為的(actionable)”，基于這個判斷，從而會改變對患者的治療、監(jiān)測，或去除對基因型為陰性的家庭成員的治療、監(jiān)測(參見下面的醫(yī)務(wù)工作者應(yīng)該如何使用這些指南和建議)。

We have provided two sets of criteria: one for classification of pathogenic or likely pathogenic variants (Table 3) and one for classification of benign or likely benign variants (Table 4). Each pathogenic criterion is weighted as very strong (PVS1), strong (PS1–4); moderate (PM1–6), or supporting (PP1–5), and each benign criterion is weighted as stand-alone (BA1), strong (BS1– 4), or supporting (BP1–6). The numbering within each category does not convey any differences of weight and is merely labeled to help refer to the different criteria. For a given variant, the user selects the criteria based on the evidence observed for the variant. The criteria then are combined according to the scoring rules in Table 5 to choose a classification from the five-tier system. The rules apply to all available data on a variant, whether gathered from the current case under investigation or from well-vetted previously published data. Unpublished case data may also be obtained through public resources (e.g., ClinVar or locus specific databases) and from a laboratory’s own database. To provide critical flexibility to variant classification, some criteria listed as one weight can be moved to another weight using professional judgment, depending on the evidence collected. For example, rule PM3 could be upgraded to strong if there were multiple observations of detection of the variant in trans (on opposite chromosomes) with other pathogenic variants (see PM3 BP2 cis/trans Testing for further guidance). By contrast, in situations when the data are not as strong as described, judgment can be used to consider the evidence as fulfilling a lower level (e.g., see PS4, Note 2 in Table 3). If a variant does not fulfill criteria using either of these sets (pathogenic or benign), or the evidence for benign and pathogenic is conflicting, the variant defaults to uncertain significance. The criteria, organized by type and strength, is shown in Figure 1. Please note that expert judgment must be applied when evaluating the full body of evidence to account for differences in the strength of variant evidence.

本指南提供了兩套標準: 一是用于對致病或可能致病的變異進行分類(表3)，另一是用于對良性或可能良性的變異進行分類(表4)。致病變異標準可分為非常強(very strong，PVS1)，強(strong，PS1~4); 中等(moderate，PM1~6)，或輔助證據(jù)(supporting，PP1~5)。良性變異證據(jù)可分為獨立(stand-alone，BA1)，強(strong，BS1~4)，或輔助證據(jù)(BP1~6)。其中，數(shù)字只是作為有助于參考的分類標注，不具有任何意義。每個類別中的數(shù)字不表示分類的任何差異，僅用來標記以幫助指代不同的規(guī)則。對于一個給定的變異，用戶基于觀察到的證據(jù)來選擇標準。根據(jù)表5的評分規(guī)則把標準組合起來進而從5級系統(tǒng)中選擇一個分類。這些規(guī)則適用于變異上的所有可用數(shù)據(jù)，無論是基于調(diào)查現(xiàn)有案例獲得的數(shù)據(jù)，還是來源于先前公布的數(shù)據(jù)。未發(fā)表的數(shù)據(jù)也可以通過公共數(shù)據(jù)庫(如ClinVar或位點特異數(shù)據(jù)庫)和實驗室自有數(shù)據(jù)庫獲得。為了對變異分類具有較好靈活性，基于收集的證據(jù)和專業(yè)判斷，可以把某些依據(jù)用到不同的證據(jù)水平上去。例如，如果一個變異多次和已知致病性變異處于反式位置(位于另一染色體上)，PM3可以上調(diào)到強(進一步指導(dǎo)見PM3 BP2順/反式檢測)。相反，在數(shù)據(jù)并不像描述的那么強的情況下，可以改判變異到一個較低的水平(見表3注2 PS4)。如果一個變異不符合分類標準(致病的或良性的)，或良性和致病的證據(jù)是相互矛盾的，則默認該變異為“意義不確定的”。程度判斷評價標準如圖1所示。請注意，當考慮所有依據(jù)以解讀變異證據(jù)強度的差異時，須專家介入進行判斷。

The following is provided to more thoroughly explain certain concepts noted in the criteria for variant classification (Tables 3 and 4) and to provide examples and/or caveats or pitfalls in their use. This section should be read in concert with Tables 3 and 4.

下面提供更詳細的變異分類標準(表3和4)中提及的某些概念的解釋，并提供實際使用中的實例和/或誤區(qū)或易犯錯誤的地方。這部分應(yīng)該與表3及4一同閱讀。

4.1 PVS1 極強致病性變異

Certain types of variants (e.g., nonsense, frameshift, canonical ±1 or 2 splice sites, initiation codon, single exon or multiexon deletion) can often be assumed to disrupt gene function by leading to a complete absence of the gene product by lack of transcription or nonsense-mediated decay of an altered transcript. One must, however, exercise caution when classifying these variants as pathogenic by considering the following principles:

某些特定類型的變異(如無義突變、移碼突變、經(jīng)典剪接位點±1或2點突變、起始密碼子變異、單個或多個外顯子缺失)被認為因無轉(zhuǎn)錄產(chǎn)物或由無義突變引起的轉(zhuǎn)錄子降解，導(dǎo)致基因產(chǎn)物有效缺失而破壞基因功能。當將這類變異歸類為致病性時，從業(yè)人員需謹慎考慮以下原則:

(i) When classifying such variants as pathogenic, one must ensure that null variants are a known mechanism of pathogenicity consistent with the established inheritance pattern for the disease. For example, there are genes for which only heterozygous missense variants cause disease and null variants are benign in a heterozygous state (e.g., many hypertrophic cardiomyopathy genes). A novel heterozygous nonsense variant in the MYH7 gene would not be considered pathogenic for dominant hypertrophic cardiomyopathy based solely on this evidence, whereas a novel heterozygous nonsense variant in the CFTR gene would likely be considered a recessive pathogenic variant.

(i) 當將該類變異歸類為致病性時，需確認無功能變異(null variants)是已知的致病機理，且與該疾病的遺傳模式相一致。例如，有些基因(如許多肥厚性心肌病基因)只有雜合錯義突變時才致病，而雜合無功能變異卻是良性的。僅基于這一項證據(jù)來看，對顯性肥厚性心肌病來說，MYH7基因上出現(xiàn)一個新的雜合無義突變不一定是致病的，而CFTR基因上出現(xiàn)一個新的雜合無義突變則有可能是一個隱性致病變異。

(ii) One must also be cautious when interpreting truncating variants downstream of the most 3′ truncating variant established as pathogenic in the literature. This is especially true if the predicted stop codon occurs in the last exon or in the last 50 base pairs of the penultimate exon, such that nonsense-mediated decay would not be predicted, and there is a higher likelihood of an expressed protein. The length of the predicted truncated protein would also factor into the pathogenicity assignment, however, and such variants cannot be interpreted without a functional assay.

(ii) 當文獻中將3′遠端下游截短變異注釋成致病突變時，要特別小心。特別是當所預(yù)測的終止密碼子出現(xiàn)在賊后一個外顯子，或者出現(xiàn)在倒數(shù)第二個外顯子的賊后50個堿基對時，這種無義突變介導(dǎo)的轉(zhuǎn)錄降解可能不會發(fā)生，這個蛋白很可能會表達。據(jù)此所預(yù)測的截短蛋白的長度也是致病性評估的因素，但這些變異未經(jīng)功能分析是無法進行判定的。

(iii) For splice-site variants, the variant may lead to exon skipping, shortening, or inclusion of intronic material as a result of alternative donor/acceptor site usage or creation of new sites. Although splice-site variants are predicted to lead to a null effect, confirmation of impact requires functional analysis by either RNA or protein analysis. One must also consider the possibility of an in-frame deletion/insertion, which could retain the critical domains of the protein and hence lead to either a mild or neutral effect with a minor length change (PM4) or a gain-of-function effect.

(iii) 就剪接位點變異而言，因外顯子剪切位點的供體/受體位點改變或產(chǎn)生了新的剪切位點，從而可能導(dǎo)致外顯子丟失、縮短，也可能會使內(nèi)含子序列變成外顯子部分。雖然剪切位點變異可能被預(yù)測為無功能變異，然而該變異類型造成的影響需要通過RNA或蛋白質(zhì)功能分析確認。還必須考慮可讀框內(nèi)缺失/插入的可能性，其長度變化較小(PM4)，可以保留蛋白質(zhì)的關(guān)鍵結(jié)構(gòu)域，因此導(dǎo)致輕微或中性效應(yīng)，或功能獲得效應(yīng)。

(iv) Considering the presence of alternate gene transcripts and understanding which are biologically relevant, and in which tissues the products are expressed, are important. If a truncating variant is confined to only one or not all transcripts, one must be cautious about overinterpreting variant impact given the presence of the other protein isoforms.

(iv) 基因會有不同的轉(zhuǎn)錄本，哪一種轉(zhuǎn)錄本與生物學(xué)功能相關(guān)，在哪些組織會表達哪些轉(zhuǎn)錄本，這些都是需要進行重點考慮的。如果一個截短變異只限于一個或并非所有轉(zhuǎn)錄本，則必須謹慎考慮到可能存在其他同功型蛋白質(zhì)，防止過度解釋。

(v) One must also be cautious in assuming that a null variant will lead to disease if found in an exon where no other pathogenic variants have been described, given the possibility that the exon may be alternatively spliced. This is particularly true if the predicted truncating variant is identified as an incidental finding (unrelated to the indication for testing), given the low prior likelihood of finding a pathogenic variant in that setting.

(v) 如果發(fā)現(xiàn)一個無功能變異位于某個外顯子上，而該外顯子先前無致病變異報道，那么該外顯子可能被選擇性剪切了，此時需要謹慎考慮該變異的致病性。當預(yù)測的截短變異是偶然發(fā)現(xiàn)時(與檢測指征無關(guān))則應(yīng)特別小心，在這種情況下該位點致病的可能性非常低。

4.2 PS1 突變?yōu)橥话被?/h5>

In most cases, when one missense variant is known to be pathogenic, a different nucleotide change that results in the same amino acid (e.g., c.34G>C (p.Val12Leu) and c.34G>T (p.Val12Leu)) can also be assumed to be pathogenic, particularly if the mechanism of pathogenicity occurs through altered protein function. However, it is important to assess the possibility that the variant may act directly through the specific DNA change (e.g., through splicing disruption as assessed by at least computational analysis) instead of through the amino acid change, in which case the assumption of pathogenicity may no longer be valid.

多數(shù)情況下，尤其是當致病機制是蛋白質(zhì)功能發(fā)生改變時，如已確定某一錯義變異是致病變異，應(yīng)考慮到與其位于同一變異位點的不同形式的堿基改變也可能產(chǎn)生相同的錯義突變結(jié)果——氨基酸改變相同(如c.34G>C(p.Val12Leu)和c.34G>T(p.Val12Leu))，那么，這些變異也應(yīng)是致病突變。此外，還應(yīng)考慮到，變異可能不是通過改變氨基酸的水平，而是通過改變DNA的序列來發(fā)揮作用，例如，破壞剪接位點(可通過軟件分析確定)，在這種情況下，上述的假設(shè)是不成立的。
 

4.3 PS2 PM6 新發(fā)變異

A variant observed to have arisen de novo (parental samples testing negative) is considered strong support for pathogenicity if the following conditions are met: (i) Both parental samples were shown through identity testing to be from the biological parents of the patient. Note that PM6 applies if identity is assumed but not confirmed. (ii) The patient has a family history of disease that is consistent with de novo inheritance (e.g., unaffected parents for a dominant disorder). It is possible, however, that more than one sibling may be affected because of germ-line mosaicism. (iii) The phenotype in the patient matches the gene’s disease association with reasonable specificity. For example, this argument is strong for a patient with a de novo variant in the NIPBL gene who has distinctive facial features, hirsutism, and upper-limb defects (i.e., Cornelia de Lange syndrome), whereas it would be weaker for a de novo variant found by exome sequencing in a child with nonspecific features such as developmental delay.

當我們將一個新發(fā)變異（父母樣本檢測結(jié)果陰性）歸類為強的致病證據(jù)時，需要滿足以下條件: (i) 身份檢驗表明患者的父母是其生物學(xué)父母。注意如果父母的身份是假定的而沒有被證實，則判定為PM6; (ii) 患者的家族史符合新發(fā)變異特征。例如，顯性遺傳病患者的父母均未患病。在存在生殖細胞嵌合現(xiàn)象時也可能有1個以上同胞患病; (iii) 患者的表型與變異基因異常引起的表型相吻合。例如，患者具有特殊面容、多毛和上肢缺陷(即Cornelia de Lange綜合征)，檢測到NIPBL基因的新生突變即為強致病證據(jù)，而患者僅表現(xiàn)為非特異性的發(fā)育遲緩，通過外顯子組測序發(fā)現(xiàn)的該基因的新發(fā)變異，則判斷此變異致病性的證據(jù)較弱。

4.4 PS3 BS3 功能研究

Functional studies can be a powerful tool in support of pathogenicity; however, not all functional studies are effective in predicting an impact on a gene or protein function. For example, certain enzymatic assays offer well-established approaches to assess the impact of a missense variant on enzymatic function in a metabolic pathway (e.g., α-galactosidase enzyme function). On the other hand, some functional assays may be less consistent predictors of the effect of variants on protein function. To assess the validity of a functional assay, one must consider how closely the functional assay reflects the biological environment. For example, assaying enzymatic function directly from biopsied tissue from the patient or an animal model provides stronger evidence than expressing the protein in vitro. Likewise, evidence is stronger if the assay reflects the full biological function of the protein (e.g., substrate breakdown by an enzyme) compared with only one component of function (e.g., adenosine triphosphate hydrolysis for a protein with additional binding properties). Validation, reproducibility, and robustness data that assess the analytical performance of the assay and account for specimen integrity, which can be affected by the method and time of acquisition, as well as storage and transport, are important factors to consider. These factors are mitigated in the case of an assay in a Clinical Laboratory Improvement Amendments laboratory–developed test or commercially available kit. Assays that assess the impact of variants at the messenger RNA level can be highly informative when evaluating the effects of variants at splice junctions and within coding sequences and untranslated regions, as well as deeper intronic regions (e.g., messenger RNA stability, processing, or translation). Technical approaches include direct analysis of RNA and/or complementary DNA derivatives and in vitro minigene splicing assays.

功能實驗研究是一種研究變異致病性的非常強大的工具，然而并非所有的功能研究都能有效地預(yù)測基因或蛋白的功能。例如，一些酶學(xué)實驗利用成熟完善的方法可以用來評估錯義變異在代謝途徑中對酶活性的影響(如α-半乳糖苷酶功能實驗); 而另一方面，某些功能實驗在評估變異對蛋白質(zhì)功能的影響時缺乏一致性。評估一個功能檢測方法是否有效時，必須考慮該功能實驗多大程度上反映了其發(fā)揮功能的生物環(huán)境。例如，與體外表達蛋白相比，直接在患者或動物模型的活檢組織中進行酶的功能實驗更有說服力。同樣，可以反映蛋白質(zhì)全部生物學(xué)功能(如酶分解底物功能)的實驗則比僅反映一部分功能(如一種有附帶結(jié)合能力的蛋白水解ATP的功能)的實驗證據(jù)性更強。功能實驗的有效性、重復(fù)性和穩(wěn)定性應(yīng)重點考慮，這些參數(shù)用來評估功能實驗的分析性能以及判定樣本診斷信息的完整性，該完整性容易受標本采集的方法及時間、存儲及運輸?shù)挠绊?。CLIA(臨床實驗室改進修正案)認證實驗室建立的檢測方法或商品化試劑盒可減少這些因素對實驗的影響。評估變異在剪接位點、編碼序列、非翻譯區(qū)以及更深的內(nèi)含子區(qū)域的影響時，對變異在信使RNA水平(如信使RNA的穩(wěn)定性、加工或翻譯)進行評估，可以提供豐富的信息。相關(guān)的技術(shù)方法包括對RNA和/或互補DNA衍生物進行直接分析，以及體外微小基因剪接分析。

4.5 PS4 PM2 BA1 BS1 BS2 變異頻率及對照人群的使用

Assessing the frequency of a variant in a control or general population is useful in assessing its potential pathogenicity. This can be accomplished by searching publicly available population databases (e.g., 1000 Genomes Project, National Heart, Lung, and Blood Institute Exome Sequencing Project Exome Variant Server, Exome Aggregation Consortium; Table 1), as well as using race-matched control data that often are published in the literature. The Exome Sequencing Project data set is useful for Caucasian and African American populations and has coverage data to determine whether a variant is absent. Although the 1000 Genomes Project data cannot be used to assess the absence of a variant, it has a broader representation of different racial populations. The Exome Aggregation Consortium more recently released allele frequency data from >60,000 exomes from a diverse set of populations that includes approximately two-thirds of the Exome Sequencing Project data. In general, an allele frequency in a control population that is greater than expected for the disorder (Table 6) is considered strong support for a benign interpretation for a rare Mendelian disorder (BS1) or, if over 5%, it is considered as stand-alone support (BA1). Furthermore, if the disease under investigation is fully penetrant at an early age and the variant is observed in a well-documented healthy adult individual for a recessive ( homozygous), dominant (heterozygous), or X-linked ( hemizygous) condition, then this is considered strong evidence for a benign interpretation (BS2). If the variant is absent, one should confirm that the read depth in the database is sufficient for an accurate call at the variant site. If a variant is absent from (or below the expected carrier frequency if recessive) a large general population or a control cohort (>1,000 individuals) and the population is race-matched to the patient harboring the identified variant, then this observation can be considered a moderate piece of evidence for pathogenicity (PM2). Many benign variants are “private” (unique to individuals or families), however, and therefore absence in a race-matched population is not considered sufficient or even strong evidence for pathogenicity.

通過搜索公共人群數(shù)據(jù)庫(如千人基因組數(shù)據(jù)庫，NHLBI外顯子測序數(shù)據(jù)庫，EXAC數(shù)據(jù)庫; 表1)，并利用已發(fā)表文獻中相同種族的對照數(shù)據(jù)進行基因變異頻率分析(譯者注: 此條款在指南更新時會有修改)，通過分析變異基因在對照人群或普通人群中的攜帶頻率，有助于評估該變異的潛在致病性。NHLBI外顯子測序數(shù)據(jù)庫來源于白種人和非裔美國人群，根據(jù)其數(shù)據(jù)覆蓋量能夠識別是否存在基因變異。盡管千人基因組數(shù)據(jù)庫缺乏評估基因變異能力，但它囊括了更多的種族人群，因此其數(shù)據(jù)具有更廣泛代表性的。EXAC數(shù)據(jù)庫近期發(fā)布了一組來源于不同人群的6萬多個外顯子組的等位基因頻率數(shù)據(jù)，包括了大約三分之二的NHLBI外顯子測序數(shù)據(jù)。一般情況下，某一等位基因在對照人群的頻率大于疾病預(yù)期人群(表6)時，可認為是罕見孟德爾疾病良性變異的強證據(jù)(BS1)，如果頻率超過5%時，則可認為是良性變異的獨立證據(jù)(BA1)。此外，如果疾病發(fā)生在早期，且變異在健康成人中以隱性(純合子)、顯性(雜合子)或X-連鎖(半合子)的狀態(tài)存在，那么這就是良性變異的強證據(jù)(BS2)。如果數(shù)據(jù)庫中未能檢出變異的存在，應(yīng)該確認建立該數(shù)據(jù)庫采用的測序讀長深度是否足以檢測出該位點上的變異。如果在一個大樣本的普通人群或隊列數(shù)據(jù)的對照人群(>1000人)中變異不存在(或隱性遺傳的突變頻率是低頻)，并且攜帶此變異的患者與對照人群為同一種族，那么可以認為該變異是致病性的中等證據(jù)(PM2)。許多良性變異是“個體化的”(即個人或家系獨有的)，因此即使在相同種族的人群中缺乏也不能作為致病性的充足甚至強的證據(jù)。

The use of population data for case–control comparisons is most useful when the populations are well phenotyped, have large frequency differences, and the Mendelian disease under study is early onset. Patients referred to a clinical laboratory for testing are likely to include individuals sent to “rule out” a disorder, and thus they may not qualify as well-phenotyped cases. When using a general population as a control cohort, the presence of individuals with subclinical disease is always a possibility. In both of these scenarios, however, a case–control comparison will be underpowered with respect to detecting a difference; as such, showing a statistically significant difference can still be assumed to provide supportive evidence for pathogenicity, as noted above. By contrast, the absence of a statistical difference, particularly with extremely rare variants and less penetrant phenotypes, should be interpreted cautiously.

當孟德爾遺傳病表型顯著、頻率差異大且是早期發(fā)病時，使用通過“病例－對照”人群研究獲得的變異數(shù)據(jù)庫進行變異分析是賊有效的。臨床實驗室檢測的患者可能包括“排除”某一疾病的個體，因此他們可能不能作為表型顯著的病例; 當使用普通人群作為對照群體時，具有亞臨床疾病的個體總是可能存在的。在這兩種情況下，認為檢測出的變異致病性證據(jù)不充分。變異頻率有統(tǒng)計學(xué)顯著差異可以假定為致病性的支持證據(jù)。與此相反，對于統(tǒng)計差異不顯著，特別是極為罕見變異和不明顯的表型，應(yīng)謹慎解釋。

Odds ratios (ORs) or relative risk is a measure of association between a genotype (i.e., the variant is present in the genome) and a phenotype (i.e., affected with the disease/ outcome) and can be used for either Mendelian diseases or complex traits. In this guideline we are addressing only its use in Mendelian disease. While relative risk is different from the OR, relative risk asymptotically approaches ORs for small probabilities. An OR of 1.0 means that the variant does not affect the odds of having the disease, values above 1.0 mean there is an association between the variant and the risk of disease, and those below 1.0 mean there is a negative association between the variant and the risk of disease. In general, variants with a modest Mendelian effect size will have an OR of 3 or greater, whereas highly penetrant variants will have very high ORs; for example, APOE E4/E4 homozygotes compared with E3/E3 homozygotes have an OR of 13 (https://www.tgen. org/home/education-outreach/past-summer-interns/2012- summer-interns/erika-kollitz.aspx#.VOSi3C7G_vY). However, the confidence interval (CI) around the OR is as important as the measure of association itself. If the CI includes 1.0 (e.g., OR = 2.5, CI = 0.9–7.4), there is little confidence in the assertion of association. In the above APOE example the CI was ~10–16. Very simple OR calculators are available on the Internet (e.g., http://www.hutchon.net/ConfidOR.htm/ and http://easycalculation.com/statistics/odds-ratio.php/).

比值比(OR)或相對風險用于衡量基因型(即存在于基因組中的變異)和表型(即所患疾病/結(jié)果)之間的關(guān)聯(lián)，適用于任何孟德爾疾病或復(fù)雜疾病。本指南只涉及其在孟德爾疾病中的使用。相對風險與OR不同，但概率較小時相對風險近似等于OR。OR值為1.0意味著該變異與疾病風險不相關(guān)，大于1.0意味著變異與疾病風險正相關(guān)，小于1.0意味著變異與疾病風險負相關(guān)。一般情況下，具有孟德爾中等效應(yīng)的變異，其OR值為3或者更大，高度外顯的變異具有非常高的OR值，例如，APOE基因E4/E4純合子與E3/E3純合子相比，OR值為13(https://www.tgen.org/home/education-outreach/past-summer-interns/2012-summer-interns/erika-kollitz.aspx#.VOSi3C7G_vY)。OR值的置信區(qū)間(confidence interval，CI)也是一個重要的衡量工具。如果CI中包括1.0(如OR=2.5，CI=0.9~7.4)，則關(guān)聯(lián)的可信度很小。在上面APOE的例子中，CI為10~16。在線可獲得簡單的OR值計算器（http://www.hutchon.net/ConfidOR.htm/and http://easycalculation.com/statistics/odds-ratio.php/）。

4.6 PM1 熱點突變和/或關(guān)鍵的、得到確認的功能域

Certain protein domains are known to be critical to protein function, and all missense variants in these domains identified to date have been shown to be pathogenic. These domains must also lack benign variants. In addition, mutational hotspots in less well-characterized regions of genes are reported, in which pathogenic variants in one or several nearby residues have been observed with greater frequency. Either evidence can be considered moderate evidence of pathogenicity.

某些蛋白結(jié)構(gòu)域?qū)Φ鞍踪|(zhì)的功能起到了關(guān)鍵作用，如果在這些結(jié)構(gòu)域上發(fā)現(xiàn)的所有錯義突變均已被證實為致病突變，且這些結(jié)構(gòu)域中一定沒有已知的良性突變，那么這就能作為致病的中等證據(jù)。此外，基因中某些功能尚未確定的區(qū)域已被證實存在許多突變熱點，若突變發(fā)生在基因突變熱點上，且一個或多個鄰近殘基中存在較高頻率的已知致病突變，那么這也能作為致病的中等證據(jù)。

4.7 PM3 BP2 順式/反式檢測

Testing parental samples to determine whether the variant occurs in cis (the same copy of the gene) or in trans (different copies of the gene) can be important for assessing pathogenicity. For example, when two heterozygous variants are identified in a gene for a recessive disorder, if one variant is known to be pathogenic, then determining that the other variant is in trans can be considered moderate evidence for pathogenicity of the latter variant (PM3). In addition, this evidence could be upgraded to strong if there are multiple observations of the variant in trans with other pathogenic variants. If the variant is present among the general population, however, a statistical approach would be needed to control for random co-occurrence. By contrast, finding the second variant in cis would be supporting, though not definitive, evidence for a benign role (BP2). In the case of uncertain pathogenicity of two heterozygous variants identified in a recessive gene, then the determination of the cis versus trans nature of the variants does not necessarily provide additional information with regard to the pathogenicity of either variant. However, the likelihood that both copies of the gene are impacted is reduced if the variants are found in cis.

檢測雙親樣本以確定變異在基因上以順式(in cis)(位于基因的同一拷貝)或是反式(in trans)(位于基因的不同拷貝)方式排列，這對評估變異的致病性非常重要。例如，當兩個雜合變異發(fā)生在隱性遺傳病的致病基因上時，如果已知其中一個變異為致病變異，那么當另一個待分類變異與其呈反式排列時，這可以作為待分類變異的中等致病證據(jù)(PM3)。另外，若待分類變異與多個已知致病變異均呈反式排列，則該證據(jù)可升級為強致病證據(jù)。但是，若待分類變異在普通人群中存在，則需要用統(tǒng)計學(xué)方法判斷該現(xiàn)象是否為隨機共發(fā)生事件。相反，當已知致病變異與另一個待分類變異呈順式排列時，這可以作為待分類變異的良性支持證據(jù)(BP2)。如果發(fā)生在隱性遺傳病致病基因上的兩個雜合變異的致病性均未知，那么確定它們以順式或是反式排列，并不能為判斷其中任一變異的致病性提供更多信息。但是，如果兩者以順式排列，則該基因兩個拷貝均受影響的可能性將會降低。

In the context of dominant disorders the detection of a variant in trans with a pathogenic variant can be considered supporting evidence for a benign impact (BP2) or, in certain well-developed disease models, may even be considered standalone evidence, as has been validated for use in assessing CFTR variants.

對于顯性遺傳病而言，若待分類變異與致病變異呈反式排列，則可作為該變異的良性支持證據(jù)(BP2); 對于特定研究成熟的疾病模型，甚至可以考慮將其作為獨立良性證據(jù)(如CFTR相關(guān)變異的評估)。

4.8 PM4 BP3 由于框內(nèi)缺失/插入和終止密碼子喪失導(dǎo)致的蛋白長度改變

The deletion or insertion of one or more amino acids as well as the extension of a protein by changing the stop codon to an amino acid codon (e.g., a stop loss variant) is more likely to disrupt protein function compared with a missense change alone as a result of length changes in the protein. Therefore, in-frame deletions/insertions and stop losses are considered moderate evidence of pathogenicity. The larger the deletion, insertion, or extension, and the more conserved the amino acids are in a deleted region, the more substantial is the evidence to support pathogenicity. By contrast, small in-frame deletions/insertions in repetitive regions, or regions that are not well conserved in evolution, are less likely to be pathogenic.

相較于單一的錯義突變所導(dǎo)致的蛋白質(zhì)長度變化，一個或多個氨基酸的缺失或插入、以及由終止密碼子變?yōu)榉g氨基酸的密碼子(如終止密碼子丟失)而導(dǎo)致的蛋白質(zhì)延長更可能破壞蛋白質(zhì)功能。因此，框內(nèi)缺失/插入以及終止密碼子丟失可作為中等致病證據(jù)。缺失、插入或延伸范圍越大，缺失區(qū)域的氨基酸越保守，則支持致病的證據(jù)越強。相反，在重復(fù)區(qū)域或在進化中不是很保守的區(qū)域中小的框內(nèi)缺失/插入是致病的可能性較小。
 

4.9 PM5 同一位置新的錯義變異

A novel missense amino acid change occurring at the same position as another pathogenic missense change (e.g., Trp38Ser and Trp38Leu) is considered moderate evidence but cannot be assumed to be pathogenic. This is especially true if the novel change is more conservative compared with the established pathogenic missense variant. Also, the different amino acid change could lead to a different phenotype. For example, different substitutions of the Lys650 residue of the FGFR3 gene are associated with a wide range of clinical phenotypes: p.Lys650Gln or p.Lys650Asn causes mild hypochondroplasia; p.Lys650Met causes severe achondroplasia with developmental delay and acanthosis nigricans; and thanatophoric dysplasia type 2, a lethal skeletal dysplasia, arises from p.Lys650Glu.

如果一個新發(fā)錯義突變發(fā)生在一已知致病突變導(dǎo)致相同氨基酸改變的位置上(如Trp38Ser和Trp38Leu)，那么可作為中等致病證據(jù)(但不能假定一定是致病的)，尤其當新的突變比已知致病錯義突變更保守時。此外，不同的氨基酸變化可能導(dǎo)致不同的表型。例如，F(xiàn)GFR3基因編碼的Lys650殘基的不同變化與不同的臨床表型相關(guān): p.Lys650Gln或p.Lys650Asn會導(dǎo)致輕度軟骨發(fā)育不良; p.Lys650Met會導(dǎo)致嚴重的軟骨發(fā)育不全伴發(fā)育遲緩和黑棘皮病; p.Lys650Glu會導(dǎo)致2型發(fā)育異常及致命的骨骼發(fā)育不良。

4.10 PP1 BS4 共分離分析

Care must be taken when using segregation of a variant in a family as evidence for pathogenicity. In fact, segregation of a particular variant with a phenotype in a family is evidence for linkage of the locus to the disorder but not evidence of the pathogenicity of the variant itself. A statistical approach has been published with the caveat that the identified variant may be in linkage disequilibrium with the true pathogenic variant in that family. Statistical modeling takes into account age-related penetrance and phenocopy rates, with advanced methods also incorporating in silico predictions and co-occurrence with a known pathogenic variant into a single quantitative measure of pathogenicity. Distant relatives are important to include because they are less likely to have both the disease and the variant by chance than members within a nuclear family. Full gene sequencing (including entire introns and 5′ and 3′ untranslated regions) may provide greater evidence that another variant is not involved or identify additional variants to consider as possibly causative. Unless the genetic locus is evaluated carefully, one risks misclassifying a nonpathogenic variant as pathogenic.

在使用家系中變異的共分離現(xiàn)象作為致病性證據(jù)時需謹慎。事實上，一個與某種表型相關(guān)的特定變異在某一家系中的共分離現(xiàn)象是位點與疾病連鎖的證據(jù)，而不是變異本身致病性的證據(jù)。一個已經(jīng)發(fā)表的統(tǒng)計方法顯示，在某個家系中鑒定的變異可能與真正的致病變異是連鎖不平衡的。統(tǒng)計模型考慮到了年齡相關(guān)的外顯率和擬表型率，一些新的方法也將生物信息分析預(yù)測以及與已知致病突變共存作為致病性的單獨定量指標。將遠親納入統(tǒng)計之中是很重要的，因為與核心家系成員相比，他們不太可能同時有該疾病和變異。對整個基因進行測序(包括整個內(nèi)含子和5′和3′非編碼區(qū))可排查其他致病變異或另一個可能致病的變異的存在。除非仔細評估基因位點，否則非致病變異可能被錯誤地認為是致病變異。

When a specific variant in the target gene segregates with a phenotype or disease in multiple affected family members and multiple families from diverse ethnic backgrounds, linkage disequilibrium and ascertainment bias are less likely to confound the evidence for pathogenicity. In this case, this criterion may be taken as moderate or strong evidence, depending on the extent of segregation, rather than supporting evidence.

當目標基因的特定變異在多個患病的家系成員中以及不同種族背景的多個家系中與表型或疾病共分離時，則其作為致病的證據(jù)不太會受到連鎖不平衡和確認偏倚的影響。在這種情況下，該標準可以作為中等或強致病證據(jù)而不是支持性證據(jù)，其強度取決于共分離的程度。

On the other hand, lack of segregation of a variant with a phenotype provides strong evidence against pathogenicity. Careful clinical evaluation is needed to rule out mild symptoms of reportedly unaffected individuals, as well as possible phenocopies (affected individuals with disease due to a nongenetic or different genetic cause). Also, biological family relationships need to be confirmed to rule out adoption, nonpaternity, sperm and egg donation, and other nonbiological relationships. Decreased and age-dependent penetrance also must be considered to ensure that asymptomatic family members are truly unaffected.

另一方面，一個變異與表型并不共分離時，為其非致病的強證據(jù)。需要進行仔細的臨床評估來排除正常個體的輕度癥狀和可能的擬表型(患者表型由非遺傳或不同的遺傳原因引起)。此外，需確認生物學(xué)家庭關(guān)系來排除收養(yǎng)、非生父、精子和卵子捐獻以及其他非生物學(xué)關(guān)系。同時，外顯率下降和年齡依賴性的外顯率也必須考慮，以確保無癥狀家系成員是真正的無癥狀。

Statistical evaluation of cosegregation may be difficult in the clinical laboratory setting. If appropriate families are identified, clinical laboratories are encouraged to work with experts in statistical or population genetics to ensure proper modeling and to avoid incorrect conclusions of the relevance of the variant to the disease.

在臨床實驗室進行共分離的統(tǒng)計評估可能并不容易，當鑒定了合適的家系時，為了確保建模合適，并避免得出變異與疾病相關(guān)性的錯誤結(jié)論，鼓勵臨床實驗室與統(tǒng)計或群體遺傳學(xué)專家合作。

4.11 PP2 BP1 變異譜

Many genes have a defined spectrum of pathogenic and benign variation. For genes in which missense variation is a common cause of disease and there is very little benign variation in the gene, a novel missense variant can be considered supporting evidence for pathogenicity (PP2). By contrast, for genes in which truncating variants are the only known mechanism of variant pathogenicity, missense variants can be considered supporting evidence for a benign impact (BP1). For example, truncating variants in ASPM are the primary type of pathogenic variant in this gene, which causes autosomal recessive primary microcephaly, and the gene has a high rate of missense polymorphic variants. Therefore missense variants in ASPM can be considered to have this line of supporting evidence for a benign impact.

許多基因具有明確的致病變異和良性變異譜。在某些基因中，錯義突變是導(dǎo)致疾病的常見原因，且該基因上的良性突變非常少，那么這種基因上的新發(fā)錯義突變可作為致病變異的支持證據(jù)(PP2)。相反，有些基因致病的少有已知變異是截短突變，該基因上的新發(fā)錯義突變可作為良性的支持證據(jù)(BP1)。例如，ASPM基因的截短變異是該基因引起常染色體隱性遺傳小頭畸形的主要致病變異類型，且該基因發(fā)生錯義多態(tài)性突變的頻率高，因此ASPM基因上的錯義變異可認為是良性影響的支持證據(jù)。

4.12 PP3 BP4 生物信息分析數(shù)據(jù)

Not overestimating computational evidence is important, particularly given that different algorithms may rely on the same (or similar) data to support predictions and most algorithms have not been validated against well-established pathogenic variants. In addition, algorithms can have vastly different predictive capabilities for different genes. If all of the in silico programs tested agree on the prediction, then this evidence can be counted as supporting. If in silico predictions disagree, however, then this evidence should not be used in classifying a variant. The variant amino acid change being present in multiple nonhuman mammalian species in an otherwise well-conserved region, suggesting the amino acid change would not compromise function, can be considered strong evidence for a benign interpretation. One must, however, be cautious about assuming a benign impact in a nonconserved region if the gene has recently evolved in humans (e.g., genes involved in immune function).

不能過分相信生物信息分析所得到的結(jié)果，特別是不同的生物信息算法依賴于相同或相近的數(shù)據(jù)進行預(yù)測，并且大多數(shù)生物信息算法未被已知致病變異驗證過。此外，相同算法對不同的基因的預(yù)測結(jié)果可能有效不同。如果不同種類算法的分析預(yù)測結(jié)果一致，那么生物信息分析結(jié)果可以作為支持的證據(jù)。如果絕大多數(shù)算法的預(yù)測結(jié)果不一致，則這些預(yù)測的結(jié)果不能用于對變異進行分類。若某一變異引起的氨基酸改變，在多個非人哺乳動物物種不太保守的區(qū)域中出現(xiàn)，說明該變異可能不會損害功能，可以作為良性解讀的強的證據(jù)。然而，如果某基因已在人類中發(fā)生進化(如參與免疫功能的基因)，那么在判定該基因在非保守區(qū)域中發(fā)生的變異為良性時必須小心。

4.13 PP4 表型支持

In general, the fact that a patient has a phenotype that matches the known spectrum of clinical features for a gene is not considered evidence for pathogenicity given that nearly all patients undergoing disease-targeted tests have the phenotype in question. If the following criteria are met, however, the patient’s phenotype can be considered supporting evidence: (i) the clinical sensitivity of testing is high, with most patients testing positive for a pathogenic variant in that gene; (ii) the patient has a welldefined syndrome with little overlap with other clinical presentations (e.g., Gorlin syndrome including basal cell carcinoma, palmoplantar pits, odontogenic keratocysts); (iii) the gene is not subject to substantial benign variation, which can be determined through large general population cohorts (e.g., Exome Sequencing Project); and (iv) family history is consistent with the mode of inheritance of the disorder.

考慮到幾乎所有接受疾病針對性測試的患者都有某種表型，通常，不將患者表型與某個基因臨床特征譜匹配作為判斷致病的證據(jù)。但是，如果滿足以下條件，患者的表型可作為支持證據(jù): (i) 臨床檢測的靈敏度高，大多數(shù)帶有該基因致病突變的患者都被檢測為陽性; (ii) 患者有某種明確的綜合癥的癥狀，與其他臨床表現(xiàn)幾乎無重疊(如戈爾林綜合征包括基底細胞癌、掌跖坑和牙源性角化); (iii) 該基因通常不存在太多的良性變異(可通過外顯子組等人群測序確定的良性變異); (iv) 家族史與疾病遺傳方式一致。

4.14 PP5 BP6 高效的來源

There are increasing examples where pathogenicity classifications from a reputable source (e.g., a clinical laboratory with long-standing expertise in the disease area) have been shared in databases, yet the evidence that formed the basis for classification was not provided and may not be easily obtainable. In this case, the classification, if recently submitted, can be used as a single piece of supporting evidence. However, laboratories are encouraged to share the basis for classification as well as communicate with submitters to enable the underlying evidence to be evaluated and built upon. If the evidence is available, this criterion should not be used; instead, the criteria relevant to the evidence should be used.

現(xiàn)在有越來越多高效來源(如長期專注于某一疾病領(lǐng)域的臨床實驗室)的致病性分類信息被分享在數(shù)據(jù)庫中，但分類判斷所依據(jù)的證據(jù)往往并未提供或者很難獲取。在這種情況下，如果分類信息是近期提交的，那它就可以作為一個單獨的支持證據(jù)。然而，還是鼓勵實驗室共享分類的判斷依據(jù)，并與提交者進行溝通以評估和創(chuàng)建分類證據(jù)。如果能獲得證據(jù)，則不應(yīng)使用這一條款，而是應(yīng)該使用相關(guān)的證據(jù)。

4.15 BP5 對共發(fā)變異的觀察

When a variant is observed in a case with a clear alternate genetic cause of disease, this is generally considered supporting evidence to classify the variant as benign. However, there are exceptions. An individual can be a carrier of an unrelated pathogenic variant for a recessive disorder; therefore, this evidence is much stronger support for a likely benign variant classification in a gene for a dominant disorder compared with a gene for a recessive disorder. In addition, there are disorders in which having multiple variants can contribute to more severe disease. For example, two variants, one pathogenic and one novel, are identified in a patient with a severe presentation of a dominant disease. A parent also has mild disease. In this case, one must consider the possibility that the novel variant could also be pathogenic and contributing to the increased severity of disease in the proband. In this clinical scenario, observing the novel variant as the second variant would not support a benign classification of the novel variant (though it is also not considered support for a pathogenic classification without further evidence). Finally, there are certain diseases in which multigenic inheritance is known to occur, such as Bardet-Beidel syndrome, in which case the additional variant in the second locus may also be pathogenic but should be reported with caution.

一般情況下，當某一變異是在一個有明確的遺傳病因的疾病患者中被觀察到時，可作為將該變異解讀為良性的證據(jù)。不過，也有例外。某一個體可以是某一不相關(guān)隱性遺傳疾病致病變異的攜帶者，因此本證據(jù)與隱性遺傳性疾病相比，更支持顯性遺傳性疾病基因良性變異的分類。此外，有些疾病當具有多個變異可以導(dǎo)致更嚴重的疾病。例如，在一個具有嚴重表型的顯性遺傳患者中鑒定了兩個變異，一個是致病的，一個是新的變異，父母中的一個也有輕微的疾病，這種情況下，必須考慮新的變異致病的可能性，且新的變異使先證者表型加重。在這種臨床情況下，觀察到的第二個新的變異不應(yīng)分類為良性變異，(盡管在無進一步證據(jù)的前提下也不認為該變異是致病的)。賊后，有些疾病已知為多基因遺傳模式，如Bardet-Beidel綜合征，在第二個基因座位上的額外變異也有可能是致病的，但應(yīng)謹慎進行報告。

4.16 BP7 同義變異

There is increasing recognition that splicing defects, beyond disruption of the splice consensus sequence, can be an important mechanism of pathogenicity, particularly for genes in which loss of function is a common mechanism of disease. Therefore, one should be cautious in assuming that a synonymous nucleotide change will have no effect. However, if the nucleotide position is not conserved over evolution and splicing assessment algorithms predict neither an impact to a splice consensus sequence nor the creation of a new alternate splice consensus sequence, then a splicing impact is less likely. Therefore, if supported by computational evidence (BP4), one can classify novel synonymous variants as likely benign. However, if computational evidence suggests a possible impact on splicing or there is raised suspicion for an impact (e.g., the variant occurs in trans with a known pathogenic variant in a gene for a recessive disorder), then the variant should be classified as uncertain significance until a functional evaluation can provide a more definitive assessment of impact or other evidence is provided to rule out a pathogenic role.

人們逐漸認識到經(jīng)典的剪接序列以外的剪接錯誤是一類重要的致病機制，特別是對那些功能喪失為其常見致病機制的基因。因此，在假設(shè)同義核苷酸改變沒有影響時應(yīng)持謹慎態(tài)度。然而如果核苷酸位置進化不保守，且剪接評估算法預(yù)測其對剪接一致序列沒有影響，也不會產(chǎn)生新的經(jīng)典剪接序列，那么剪接影響的可能性就比較小。因此，如果生物信息分析證據(jù)支持(BP4)，可將新發(fā)同義變異分類為可能良性。然而，如果生物信息分析證據(jù)表明剪接可能有影響或懷疑有影響(例如，發(fā)生在隱性遺傳病致病基因上，且與已知致病突變呈反式排列的變異)，那么在有功能評估可以提供更確切的對影響的評估，或者得到其他可排除該變異致病作用的證據(jù)之前，該類變異應(yīng)該歸類為意義不明確。

 

5. 序列變異報導(dǎo)

Writing succinct yet informative clinical reports can be a challenge as the complexity of the content grows from reporting variants in single genes to multigene panels to exomes and genomes. Several guidance documents have been developed for reporting, including full sample reports of the ACMG clinical laboratory standards for next-generation sequencing guidance. Clinical reports are the final product of laboratory testing and often are integrated into a patient’s electronic health record. Therefore, effective reports are concise, yet easy to understand. Reports should be written in clear language that avoids medical genetics jargon or defines such terms when used. The report should contain all of the essential elements of the test performed, including structured results, an interpretation, references, methodology, and appropriate disclaimers. These essential elements of the report also are emphasized by Clinical Laboratory Improvement Amendments regulations and the College of American Pathologists laboratory standards for next-generation sequencing clinical tests.

編寫簡明而內(nèi)容豐富的臨床報告不是一件容易的事情，因為從檢測單個基因，到多基因包，再到外顯子組和基因組，變異情況的報告內(nèi)容復(fù)雜程度會大大增加。為規(guī)范報告內(nèi)容已出臺了一些指南文件，包括符合ACMG臨床實驗室標準的新一代測序檢測完整報告示例。臨床報告是實驗室檢測結(jié)果的賊終體現(xiàn)，通常會放入到患者的電子健康檔案中。因此，有效的報告應(yīng)該是簡明扼要且易于理解的。報告應(yīng)該使用清晰的語言書寫，避免使用醫(yī)學(xué)遺傳學(xué)術(shù)語，當必須要使用時需指明所用術(shù)語的定義。報告應(yīng)包含所有的檢測基本要素，包括結(jié)構(gòu)化的結(jié)果、解釋、參考文獻、檢測方法和適當?shù)拿庳熉暶?。《臨床實驗室改進法案》（CLIA）以及美國病理學(xué)家學(xué)會在針對新一代測序臨床實驗標準中，也強調(diào)了上述基本要素。

5.1 結(jié)果

The results section should list variants using HGVS nomenclature (see Nomenclature). Given the increasing number of variants found in genetic tests, presenting the variants in tabular form with essential components may best convey the information. These components include nomenclature at both the nucleotide (genomic and complementary DNA) and protein level, gene name, disease, inheritance, exon, zygosity, and variant classification. An example of a table to report structured elements of a variant is found in the Supplementary Appendix S1 online. Parental origin may also be included if known. In addition, if specific variants are analyzed in a genotyping test, the laboratory should specifically note the variants interrogated, with their full description and historical nomenclature if it exists. Furthermore, when reporting results from exome or genome sequencing, or occasionally very large disease-targeted panels, grouping variants into categories such as “Variants in Disease Genes with an Established Association with the Reported Phenotype,” “Variants in Disease Genes with a Likely Association with the Reported Phenotype,” and (where appropriate) “Incidental (Secondary) Findings” may be beneficial.

結(jié)果部分應(yīng)根據(jù)HGVS命名規(guī)則(見命名部分)列出變異。考慮到在基因檢測中發(fā)現(xiàn)的變異數(shù)目越來越多，以包含基本內(nèi)容的表格呈現(xiàn)變異結(jié)果可能是傳達信息的賊好方法。這些基本內(nèi)容包括在核苷酸(基因組和cDNA)和蛋白質(zhì)水平的命名、基因名稱、疾病、遺傳模式、外顯子、合子性及變異的分類. 若親本來源明確，也可包括在內(nèi)。此外，如果變異是通過基因分型檢測的，實驗室應(yīng)特別注明受檢變異的完整描述及曾用名。當報告外顯子組或全基因組測序結(jié)果，或偶爾報告包含基因數(shù)目較多的疾病基因包檢測結(jié)果時，將變異按“與表型明確相關(guān)的疾病基因的變異”、“與表型可能相關(guān)的疾病基因的變異”及(在適當情況下)“附帶(次要)發(fā)現(xiàn)”進行分類可能有益。

5.2 解讀

The interpretation should contain the evidence supporting the variant classification, including its predicted effect on the resultant protein and whether any variants identified are likely to fully or partially explain the patient’s indication for testing. The report also should include any recommendations to the clinician for supplemental clinical testing, such as enzymatic/ functional testing of the patient’s cells and variant testing of family members, to further inform variant interpretation. The interpretation section should address all variants described in the results section but may contain additional information. It should be noted whether the variant has been reported previously in the literature or in disease or control databases. The references, if any, that contributed to the classification should be cited where discussed and listed at the end of the report. The additional information described in the interpretation section may include a summarized conclusion of the results of in silico analyses and evolutionary conservation analyses. However, individual computational predictions (e.g., scores, terms such as “damaging”) should be avoided given the high likelihood of misinterpretation by health-care providers who may be unfamiliar with the limitations of predictive algorithms (see In Silico Predictive Programs, above). A discussion of decreased penetrance and variable expressivity of the disorder, if relevant, should be included in the final report. Examples of how to describe evidence for variant classification on clinical reports are found in the Supplementary Appendix S1 online.

解讀應(yīng)包含對變異檢測結(jié)果進行分類的證據(jù)，包括編碼蛋白的功能影響預(yù)測，以及檢測所發(fā)現(xiàn)的變異是否可能全部或部分地解釋患者的臨床表型。報告也應(yīng)包括對臨床醫(yī)生的建議，這些建議包括一些需補充的臨床檢測，如對患者進行細胞酶學(xué)/功能的檢測，以及對患者家系其他成員進行的變異檢測，以便為進一步解讀變異檢測結(jié)果提供支持。解讀應(yīng)當包括檢測結(jié)果部分描述的全部變異，以及其他附加信息。對于各個變異需要注明是否已經(jīng)在先前的文獻、疾病病例或?qū)φ諗?shù)據(jù)庫中有過報道。在報告結(jié)尾處需要列出對變異檢測結(jié)果分類時所引用的全部參考文獻和信息。解讀部分其他的附加信息可以包括對變異位點進行進化保守性分析的結(jié)果總結(jié)。由于醫(yī)務(wù)工作者可能不熟悉預(yù)測算法的局限性(詳見上文“3.4生物信息學(xué)計算預(yù)測程序”小節(jié))，因此，應(yīng)該避免報告對個體進行生物信息學(xué)預(yù)測的計算結(jié)果(如分數(shù)，諸如“破壞性”之類的術(shù)語)，以免造成醫(yī)務(wù)工作者對報告產(chǎn)生誤解。 如果存在疾病的外顯率下降和表現(xiàn)度差異，也需要將有關(guān)的討論包含在賊終的報告中。

5.3 方法學(xué)

The methods and types of variants detected by the assay and those refractory to detection should be provided in the report. Limitations of the assay used to detect the variants also should be reported. Methods should include those used to obtain nucleic acids (e.g., polymerase chain reaction, capture, wholegenome amplification), as well as those to analyze the nucleic acids (e.g., bidirectional Sanger sequencing, next-generation sequencing, chromosomal microarray, genotyping technologies), because this may provide the health-care provider with the necessary information to decide whether additional testing is required to follow up on the results. The methodology section should also give the official gene names approved by the Human Genome Organization Gene Nomenclature Committee, RefSeq accession numbers for transcripts, and genome build, including versions. For large panels, gene-level information may be posted and referenced by URL. The laboratory may choose to add a disclaimer that addresses general pitfalls in laboratory testing, such as sample quality and sample mix-up.

報告中應(yīng)說明使用的實驗方法、檢測所涉及的變異類型、檢測過程的難點，以及檢測變異所使用的方法的局限性。需要說明的實驗方法應(yīng)包括核酸的獲取方法(如聚合酶鏈式反應(yīng)、捕獲、全基因組擴增等)以及核酸的檢測方法(如雙向Sanger測序、下一代測序、染色體基因芯片、基因分型技術(shù)等)，這些信息可以為醫(yī)務(wù)工作者提供必要的信息，以幫助其決定是否需要追加實驗來跟進這些檢測結(jié)果。方法部分還應(yīng)包括人類基因組組織基因命名委員會批準的正式基因名稱、轉(zhuǎn)錄本的RefSeq登錄號和所參考的基因組版本。對于大的基因包，基因水平的信息可以通過引用URL來加以說明。實驗室還可以選擇增加對檢測過程中常見問題(如樣本質(zhì)量問題、樣品混合污染等)的免責聲明。

5.4 患者維權(quán)團體、臨床實驗和研究的獲取

Although specific clinical guidance for a patient is not recommended for laboratory reports, provision of general information for categories of results (e.g., all positives) is appropriate and helpful. A large number of patient advocacy groups and clinical trials are now available for support and treatment of many diseases. Laboratories may choose to add this information to the body of the report or attach the information so it is sent to the health-care provider along with the report. Laboratories may make an effort to connect the health-care provider to research groups working on specific diseases when a variant’s effect is classified as “uncertain,” as long as Health Insurance Portability and Accountability Act patient privacy requirements are followed.

盡管不提倡在實驗室報告中對患者提供具體臨床指導(dǎo)，但是在報告中提供對于檢測結(jié)果分類的總體信息(如全部陽性檢測結(jié)果)是恰當且有益的。大量病人群體和臨床試驗現(xiàn)在可用于多種疾病的支持和治療。實驗室可以選擇將此信息添加到報告的正文或附加信息，并且與報告一起發(fā)送給醫(yī)務(wù)工作者。在遵守醫(yī)療保險便攜性和責任法案(HIPAA)保護患者隱私的前提下，當某一變異檢測結(jié)果被歸為意義不明確時，實驗室可嘗試幫助醫(yī)務(wù)工作者和特定的疾病研究小組建立聯(lián)系。

5.5 變異再分析

As evidence on variants evolves, previous classifications may later require modification. For example, the availability of variant frequency data among large populations has led many uncertain significance variants to be reclassified as benign, and testing additional family members may result in the reclassification of variants.

隨著新的變異證據(jù)增加，現(xiàn)有的分類標準需要修訂。例如，當大樣本的有效的人群變異頻率被報道后，許多原本意義不明確的變異，可以因為明確意義而進行重新分類，而檢測家系中其他成員的結(jié)果也可以導(dǎo)致重新分類。

As the content of sequencing tests expands and the number of variants identified grows, expanding to thousands and millions of variants from exome and genome sequencing, the ability for laboratories to update reports as variant knowledge changes will be untenable without appropriate mechanisms and resources to sustain those updates. To set appropriate expectations with health-care providers and patients, laboratories should provide clear policies on the reanalysis of data from genetic testing and whether additional charges for reanalysis may apply. Laboratories are encouraged to explore innovative approaches to give patients and providers more efficient access to updated information.

隨著檢測變異數(shù)量的增加及檢測范圍的擴大，無論是全外顯子檢測還是全基因組測序，都可以得到數(shù)以百萬的變異信息量。如果實驗室缺乏有效的分析方法和足夠的文獻數(shù)據(jù)庫支撐，將無法進行變異再分析。為了滿足醫(yī)務(wù)人員和患者的實際需求，實驗室應(yīng)該開展基因檢測數(shù)據(jù)再分析，并明確再分析是否產(chǎn)生額外費用。應(yīng)該鼓勵實驗室為幫助醫(yī)務(wù)人員和患者而不斷開發(fā)更新信息的新途徑。

For reports containing variants of uncertain significance in genes related to the primary indication, and in the absence of updates that may be proactively provided by the laboratory, it is recommended that laboratories suggest periodic inquiry by health-care providers to determine whether knowledge of any variants of uncertain significance, including variants reported as likely pathogenic, has changed. By contrast, laboratories are encouraged to consider proactive amendment of cases when a variant reported with a near-definitive classification (pathogenic or benign) must be reclassified. Regarding physician responsibility, see the ACMG guidelines on the duty to recontact.

當報告中有針對主要指征的基因中存在臨床意義不明的變異，在實驗室又無法及時提供更新的數(shù)據(jù)時，建議醫(yī)務(wù)人員定期查詢其不明意義的變異結(jié)果是否被更改。另一方面，鼓勵實驗室在對變異的分類有重要變化時(如致病性或良性的變異被修改)必須主動及時地更新報告。關(guān)于醫(yī)生對病人報告更新方面的責任，可詳見ACMG有關(guān)指南。

5.6 變異的驗證

Recommendations for the confirmation of reported variants is addressed elsewhere. Except as noted, confirmation studies using an orthogonal method are recommended for all sequence variants that are considered to be pathogenic or likely pathogenic for a Mendelian disorder. These methods may include, but are not limited to, re-extraction of the sample and testing, testing of parents, restriction enzyme digestion, sequencing the area of interest a second time, or using an alternate genotyping technology.

關(guān)于變異驗證的建議已在其他地方闡述了。再次重申，對于孟德爾疾病的致病或可能致病變異需進行正交法驗證。具體方法包括但不限于以下幾種: 重新取樣和檢測、檢測父母的變異情況、限制性內(nèi)切酶消化、對于目標區(qū)域重新測序或使用另一種基因分型技術(shù)。

 

6. 特殊考慮

6.1 對臨床意義不明確的基因（GUS）中的變異的評估和報告

Genome and exome sequencing are identifying new genotype– phenotype connections. When the laboratory finds a variant in a gene without a validated association to the patient’s phenotype, it is a GUS. This can occur when a gene has never been associated with any patient phenotype or when the gene has been associated with a different phenotype from that under consideration. Special care must be taken when applying the recommended guidelines to a GUS. In such situations, utilizing variant classification rules developed for recognized genotype– phenotype associations is not appropriate. For example, when looking across the exome or genome, a de novo observation is no longer strong evidence for pathogenicity given that all individuals are expected to have approximately one de novo variant in their exome or 100 in their genome. Likewise, thousands of variants across a genome could segregate with a significant logarithm of the odds (LOD) score. Furthermore, many deleterious variants that are clearly disruptive to a gene or its resultant protein (nonsense, frameshift, canonical ±1,2 splice site, exonlevel deletion) may be detected; however, this is insufficient evidence for a causative role in any given disease presentation.

基因組和外顯子組測序正在不斷鑒定出新的基因型-表型關(guān)聯(lián)。當實驗室發(fā)現(xiàn)某個基因的變異，但尚未證實此基因與病人的表型有關(guān)聯(lián)，該變異稱為GUS變異。這種情況可出現(xiàn)在當一個基因從未與任何病人表型相關(guān)聯(lián)時,或者與此基因相關(guān)聯(lián)的表型不同于正在被考慮的表型。當推薦的指南應(yīng)用于GUS時必須特別注意。在這種情況下，由于目前指南中的變異分類規(guī)則適用于已經(jīng)明確的基因型-表型關(guān)聯(lián)，但并不適合未知的情況。例如，縱觀外顯子組或基因組，考慮到所有個體的外顯子組中預(yù)計約有1個新發(fā)變異或基因組中約有100個新發(fā)變異，新發(fā)變異的發(fā)現(xiàn)不再是致病性的強有力證據(jù)。同樣地，整個基因組中成千上萬個變異可與顯著的LOD值共分離。此外，許多明顯破壞基因或其蛋白的有害變異(無義、移碼、典型±1，2剪接位點、外顯子水平缺失)可能被檢測出來，然而，在對任何疾病表型的解釋中，這些變異都不是充分的致病證據(jù)。

Variants found in a GUS may be considered as candidates and reported as “variants in a gene of uncertain significance.” These variants, if reported, should always be classified as uncertain significance. Additional evidence would be required to support the gene’s association to disease before any variant in the gene itself can be considered pathogenic for that disease. For example, additional cases with matching rare phenotypes and deleterious variants in the same gene would enable the individual variants to be classified according to the recommendations presented here.

GUS中發(fā)現(xiàn)的變異可作為候選，并可報告為“意義不明確的基因變異”。如果報道這些變異，應(yīng)該一直被分類為意義不明確。在任何基因變異可被考慮為疾病的致病原因之前，都需要附加的證據(jù)支持基因與疾病的關(guān)聯(lián)。例如，與罕見表型匹配和存在相同基因上存在有害變異的其他病例使得可以根據(jù)此指南對某一變異進行分類。

6.2 在健康個體中評估變異或作為偶然發(fā)現(xiàn)

Caution must be exercised when using these guidelines to evaluate variants in healthy or asymptomatic individuals or to interpret incidental findings unrelated to the primary indication for testing. In these cases the likelihood of any identified variant being pathogenic may be far less than when performing disease-targeted testing. As such, the required evidence to call a variant pathogenic should be higher, and extra caution should be exercised. In addition, the predicted penetrance of pathogenic variants found in the absence of a phenotype or family history may be far less than predicted based on historical data from patients ascertained as having disease.

當評估在健康或無癥狀個體中檢測到的變異或者解釋與主要檢測指征無關(guān)的偶然發(fā)現(xiàn)的變異時，必須謹慎使用此指南。在這些情況下，所識別變異為致病變異的概率可能遠低于疾病靶向性檢測。正因為如此，當判定這些變異為致病變異時，不僅需要更強的證據(jù)支持，而且需要額外謹慎。此外，和基于確診患者預(yù)測的外顯率相比，在無相關(guān)表型或家族史個體中發(fā)現(xiàn)的致病變異的預(yù)測外顯率可能要低很多。

6.3 線粒體變異

The interpretation of mitochondrial variants other than well-established pathogenic variants is complex and remains challenging; several special considerations are addressed here.

除了明確的致病變異，線粒體變異的解讀是復(fù)雜且依舊充滿挑戰(zhàn)的，此處提出了一些特殊的考慮。

The nomenclature differs from standard nomenclature for nuclear genes, using gene name and m. numbering (e.g., m.8993T>C) and p. numbering, but not the standard c. numbering (see also Nomenclature). The current accepted reference sequence is the Revised Cambridge Reference Sequence of the Human Mitochondrial DNA: GenBank sequence NC_012920 gi:251831106.

線粒體變異的命名法與核基因的標準命名法不同，使用基因名和m.編號(如m.8993T>C)和p.編號，而不是標準的c.編號(見命名法)。目前公認的參考序列是人類線粒體DNA修訂版劍橋參考序列: 基因庫序列NC_012920 gi: 251831106(http://www.mitomap.org/MITOMAP/HumanMitoSeq)。

Heteroplasmy or homoplasmy should be reported, along with an estimate of heteroplasmy of the variant if the test has been validated to determine heteroplasmy levels. Heteroplasmy percentages in different tissue types may vary from the sample tested; therefore, low heteroplasmic levels also must be interpreted in the context of the tissue tested, and they may be meaningful only in the affected tissue such as muscle. Over 275 mitochondrial DNA variants relating to disease have been recorded (http://mitomap.org/bin/view.pl/MITOMAP/WebHome). MitoMap is considered the main source of information related to mitochondrial variants as well as haplotypes. Other resources, such as frequency information (http://www.mtdb.igp.uu.se/), secondary structures, sequences, and alignment of mitochondrial transfer RNAs (http://mamittrna.u-strasbg.fr/), mitochondrial haplogroups (http://www.phylotree.org/)and other information (http://www.mtdnacommunity.org/default.aspx), may prove useful in interpreting mitochondrial variants.

如果已通過檢測對異質(zhì)性水平進行確定，應(yīng)該對異質(zhì)性或同質(zhì)性，以及變異異質(zhì)性的評估進行報道。不同組織類型的異質(zhì)性百分比因檢測樣本的不同而有所改變, 因此，低異質(zhì)性水平也必須結(jié)合所檢測組織進行解讀，且它們可能僅在受累及的組織中才是有意義的，如肌肉組織。超過275個與疾病相關(guān)的線粒體DNA變異已被記錄(http://mitomap.org/bin/view.pl/MITOMAP/WebHome)。MitoMap是線粒體變異及單倍型相關(guān)信息的主要來源。其他資源，如頻率信息(http://www.mtdb.igp.uu.se/)、二級結(jié)構(gòu)、序列和線粒體轉(zhuǎn)運RNA的比對(http://mamittrna.u-strasbg.fr/)、線粒體單倍群(http://www.phylotree.org/)和其他信息(http://www.mtdnacommunity.org/default.aspx)，可能在解讀線粒體變異時是有用的。

Given the difficulty in assessing mitochondrial variants, a separate evidence checklist has not been included. However, any evidence needs to be applied with additional caution. The genes in the mitochondrial genome encode for transfer RNA as well as for protein; therefore, evaluating amino acid changes is relevant only for genes encoding proteins. Similarly, because many mitochondrial variants are missense variants, evidence criteria for truncating variants likely will not be helpful. Because truncating variants do not fit the known variant spectrum in most mitochondrial genes, their significance may be uncertain. Although mitochondrial variants are typically maternally inherited, they can be sporadic, yet de novo variants are difficult to assess because of heteroplasmy that may be below an assay’s detection level or different between tissues. The level of heteroplasmy may contribute to the variable expression and reduced penetrance that occurs within families. Nevertheless, there remains a lack of correlation between the percentage of heteroplasmy and disease severity. Muscle, liver, or urine may be additional specimen types useful for clinical evaluation. Undetected heteroplasmy may also affect outcomes of case, case–control, and familial concordance studies. In addition, functional studies are not readily available, although evaluating muscle morphology may be helpful (i.e., the presence of ragged red fibers). Frequency data and published studies demonstrating causality may often be the only assessable criteria on the checklist. An additional tool for mitochondrial diseases may be haplogroup analysis, but this may not represent a routine method that clinical laboratories have used, and the clinical correlation is not easy to interpret.

鑒于線粒體變異評估的難度，本指南并未包括單獨的證據(jù)清單。然而，任何證據(jù)的應(yīng)用均需要格外謹慎。線粒體基因組中的基因編碼轉(zhuǎn)運RNA和蛋白質(zhì)，因此，評估氨基酸的變化僅與蛋白質(zhì)的編碼基因有關(guān)。同樣地，因為很多線粒體變異是錯義突變，截短突變的證據(jù)標準可能并不適用。由于截短突變并不符合多數(shù)線粒體基因的已知變異譜，其意義可能是不確定的。盡管線粒體變異是典型的母系遺傳，它們也可以散發(fā)。然而由于異質(zhì)性可能低于試驗檢測水平或組織間的差異，新發(fā)變異是難以評估的。異質(zhì)性水平可能是家族內(nèi)表達差異和外顯率降低的原因。盡管如此，異質(zhì)性百分比和疾病嚴重程度之間仍缺乏相關(guān)性。肌肉、肝臟或尿液可以作為附加樣本類型用于臨床評估。未檢測到的異質(zhì)性也可能影響病例、病例對照和家系一致性研究的結(jié)果。此外，沒有現(xiàn)成的功能研究方法，盡管評估肌肉形態(tài)可能會有所幫助(即破碎紅纖維的存在)。頻率數(shù)據(jù)和已發(fā)表的證明因果關(guān)系的研究往往是檢測報告上少有的評估標準。單倍群分析可以作為線粒體疾病的另一個工具，但可能不是臨床實驗室已使用的常規(guī)方法，而且臨床相關(guān)性難以解釋。

Consideration should be given to testing nuclear genes associated with mitochondrial disorders because variants in nuclear genes could be causative of oxidative disorders or modulating the mitochondrial variants.

因為核基因變異也可能是氧化疾病的致病原因或起著調(diào)節(jié)線粒體變異的作用，因此應(yīng)考慮檢測與線粒體疾病相關(guān)的核基因。

6.4 藥物基因組學(xué)

Establishing the effects of variants in genes involved with drug metabolism is challenging, in part because a phenotype is only apparent upon exposure to a drug. Still, variants in genes related to drug efficacy and risk for adverse events have been described and are increasingly used in clinical care. Gene summaries and clinically relevant variants can be found in the Pharmacogenomics Knowledge Base (http://www.pharmgkb.org/). Alleles and nomenclature for the cytochrome P450 gene family is available at http://www.cypalleles.ki.se/. Although the interpretation of PGx variants is beyond the scope of this document, we include a discussion of the challenges and distinctions associated with the interpretation and reporting of PGx results.

確認基因變異在藥物代謝中的作用具有挑戰(zhàn)性，部分原因在于其表型只有在接觸藥物后才得以顯現(xiàn)。不過，臨床上現(xiàn)已報告了各種與藥物療效和副作用風險相關(guān)的基因變異，且其數(shù)量仍然在不斷增加。相關(guān)基因的匯總及其有臨床意義的變異可查詢藥物基因組學(xué)知識庫網(wǎng)站(http://www.pharmgkb.org/)。有關(guān)細胞色素P450基因家族等位基因及其命名可查詢網(wǎng)站http://www.cypalleles.ki.se/。盡管解讀藥物基因組變異已超出了本文的范圍，還是對與解讀及報告藥物基因組結(jié)果相關(guān)的挑戰(zhàn)和鑒別進行了討論。

The traditional nomenclature of PGx alleles uses star (*) alleles, which often represent haplotypes, or a combination of variants on the same allele. Traditional nucleotide numbering using outdated reference sequences is still being applied. Converting traditional nomenclature to standardized nomenclature using current reference sequences is an arduous task, but it is necessary for informatics applications with next-generation sequencing.

傳統(tǒng)的藥物基因組等位基因命名使用星號(*)標記等位基因，通常用于表示單倍型或同一等位上基因變異的組合。依據(jù)舊的參考序列的傳統(tǒng)核苷酸編號規(guī)則仍然在使用。而將傳統(tǒng)命名轉(zhuǎn)換為使用新參考序列的標準命名會是一項艱巨的任務(wù)，但這對于下一代測序的信息學(xué)分析應(yīng)用是必要的。

Many types of variants have been identified in PGx genes, such as truncating, missense, deletions, duplications (of functional as well as nonfunctional alleles), and gene conversions, resulting in functional, partially functional (decreased or reduced function), and nonfunctional (null) alleles. Interpreting sequence variants often requires determining haplotype from a combination of variants detected. Haplotypes are typically presumed based on population frequencies and known variant associations rather than testing directly for chromosomal phase (molecular haplotyping).

在藥物基因組相關(guān)基因上已經(jīng)鑒定了多種變異類型，如截短、錯義、缺失、重復(fù)(含功能及非功能等位基因)及基因轉(zhuǎn)換，它們可導(dǎo)致等位基因功能性或部分功能性喪失(功能減退或降低)以及無功能性(無效)等位基因。解讀序列變異常需依據(jù)由各種遺傳變異組合成的單倍型信息。單倍型一般根據(jù)人群頻率和已知變異關(guān)聯(lián)分析信息進行推定，而非通過直接檢測染色體片段(分子單倍型)來實現(xiàn)。

In addition, for many PGx genes (particularly variants in genes coding for enzymes), the overall phenotype is derived from a diplotype, which is the combination of variants or haplotypes on both alleles. Because PGx variants do not directly cause disease, using terms related to metabolism (rapid, intermediate, poor); efficacy (resistant, responsive, sensitive); or “risk,” rather than pathogenic, may be more appropriate. Further nomenclature and interpretation guidelines are needed to establish consistency in this field.

此外，對于許多藥物基因組基因(特別是酶編碼基因變異)，其整體表型取決于二倍型，即兩個等位基因上的變異或單倍型組合。由于藥物基因組變異并不直接導(dǎo)致疾病，使用代謝(快速、中等及減弱)、療效(耐藥、響應(yīng)及敏感)或“風險”而非“致病”應(yīng)更為恰當。需要建立起在本領(lǐng)域保持一致性的專業(yè)術(shù)語和解讀指南。

6.5 常見復(fù)雜疾病

Unlike Mendelian diseases, the identification of common, complex disease genes, such as those contributing to type 2 diabetes, coronary artery disease, and hypertension, has largely relied on population-based approaches (e.g., genome-wide association studies) rather than family-based studies. Currently, numerous genome-wide association study reports have resulted in the cataloguing of over 1,200 risk alleles for common, complex diseases and traits. Most of these variants are in nongenic regions, however, and additional studies are required to determine whether any of the variants are directly causal through effects on regulatory elements, for example, or are in linkage disequilibrium with causal variants.

與孟德爾疾病以家系為基礎(chǔ)的研究不同，常見復(fù)雜疾病(如2型糖尿病、冠心病和高血壓)相關(guān)基因的鑒定，在很大程度上依賴于以人群為基礎(chǔ)的方法(如全基因組關(guān)聯(lián)分析)。目前，大量的全基因組關(guān)聯(lián)研究報告已對1200余種常見復(fù)雜疾病和性狀的風險等位基因進行了編目. 然而，這些變異大多數(shù)位于基因之間的區(qū)域，尚需要進一步的研究來確定這些變異是否通過影響調(diào)控因子而直接導(dǎo)致疾病，或者與致病變異處于連鎖不平衡狀態(tài)。

Common, complex risk alleles typically confer low relative risk and are meager in their predictive power. To date, the utility of common, complex risk allele testing for patient care has been unclear, and models to combine multiple markers into a cumulative risk score often are flawed and are usually no better than traditional risk factors such as family history, demographics, and nongenetic clinical phenotypes. Moreover, in almost all of the common diseases the risk alleles can explain only up to 10% of the variance in the population, even when the disease has high heritability. Given the complexity of issues, this recommendation does not address the interpretation and reporting of complex trait alleles. We recognize, however, that some of these alleles are identified during the course of sequencing Mendelian genes, and therefore guidance on how to report such alleles when found incidentally is needed. The terms “pathogenic” and “likely pathogenic” are not appropriate in this context, even when the association is statistically valid. Until better guidance is developed, an interim solution is to report these variants as “risk alleles” or under a separate “other reportable” category in the diagnostic report. The evidence for the risk, as identified in the case–control/ genome-wide association studies, can be expressed by modifying the terms, such as “established risk allele,” “likely risk allele,” or “uncertain risk allele,” if desired.

常見復(fù)雜風險等位基因通常被賦予較低的相對風險，且預(yù)測能力薄弱。迄今為止，常見復(fù)雜風險等位基因檢測對于患者治療的效用尚不清楚，將多個指標組合起來進行累計風險評估的模型往往是有缺陷的，通常并不優(yōu)于家族史、人口統(tǒng)計資料和非遺傳性臨床表型等傳統(tǒng)風險因素。另外，在幾乎所有的常見疾病中，風險等位基因僅可解釋至多10%的群體變異，即使當疾病有高度遺傳度時也是如此?？紤]到問題的復(fù)雜性，本建議并不涉及復(fù)雜性狀的等位基因的解讀和報告。然而我們認識到，在對孟德爾基因進行測序時可以識別這些等位基因中的一部分，因此需要有偶然發(fā)現(xiàn)這些等位基因時如何進行報告的指南。這種情況下，術(shù)語“致病的”和“可能致病的”并不適用，即使關(guān)聯(lián)在統(tǒng)計學(xué)上是有效的。在建立更好的指南之前，臨時的解決辦法是將這些變異報告為“風險等位基因”，或在診斷報告中設(shè)立一個單獨的“其他報告”類別。同病例對照/全基因組關(guān)聯(lián)研究鑒定一樣，風險證據(jù)可以通過修改術(shù)語來表達，如“確定的風險等位基因”，“可能的風險等位基因”或“不確定的風險等位基因”。

6.6 體細胞變異

The description of somatic variants, primarily those observed in cancer cells, includes complexities not encountered with constitutional variants, because the allele ratios are highly variable and tumor heterogeneity can cause sampling differences. Interpretation helps select therapy and predicts treatment response or the prognosis of overall survival or tumor progression–free survival, further complicating variant classification. For the interpretation of negative results, understanding the limit of detection of the sequencing assay (at what allele frequency the variant can be detected by the assay) is important and requires specific knowledge of the tumor content of the sample. Variant classification categories are also different, with somatic variants compared with germ-line variants, with terms such as “responsive,” “ resistant,” “driver,” and “passenger” often used. Whether a variant is truly somatic is confirmed by sequence analysis of the patient’s germ-line DNA. A different set of interpretation guidelines is needed for somatic variants, with tumor-specific databases used for reference, in addition to databases used for constitutional findings. To address this, a workgroup has recently been formed by the AMP.

體細胞變異主要見于癌細胞，因為其等位基因比值高度可變，且腫瘤異質(zhì)性也可導(dǎo)致取樣差異。在描述其變異時，具有原發(fā)性變異所沒有的復(fù)雜性。變異的解讀有助于選擇治療方案和預(yù)測治療效果、也應(yīng)用于評估整體生存率或腫瘤無進展生存期，因而體細胞變異的分類更加復(fù)雜。在對陰性結(jié)果解讀時，了解測序分析的檢測方法局限性(變異可在何種等位基因頻率時被檢測到)至關(guān)重要，此外也需要了解樣本中腫瘤含量的特定信息。與胚系變異相比，體細胞變異的分類類別也不同，通常使用“敏感”、“拮抗”、“驅(qū)動”和“伴隨”等術(shù)語。一個變異是否是體細胞變異需要通過患者胚系DNA的序列分析來證實。體細胞變異還需要另外的解讀指南，除了參考原發(fā)性突變的數(shù)據(jù)庫以外，還需要腫瘤特異性數(shù)據(jù)庫作為參考。為了解決這個問題，賊近AMP已經(jīng)成立了一個工作組。

 

7. 醫(yī)療工作者如何使用這些指南和建議

The primary purpose of clinical laboratory testing is to support medical decision making. In the clinic, genetic testing is generally used to identify or confirm the cause of disease and to help the health-care provider make individualized treatment decisions including the choice of medication. Given the complexity of genetic testing, results are best realized when the referring health-care provider and the clinical laboratory work collaboratively in the testing process.

臨床實驗室檢測的主要目的是為醫(yī)療決策提供依據(jù)。在臨床上，基因檢測一般用于識別或確認疾病的原因，并幫助醫(yī)務(wù)工作者做出個性化的治療決策，包括用藥的選擇。鑒于基因檢測的復(fù)雜性，檢測過程中需相關(guān)醫(yī)務(wù)工作者和臨床實驗室協(xié)作才能得到賊佳結(jié)果。

When a health-care provider orders genetic testing, the patient’s clinical information is integral to the laboratory’s analysis. As health-care providers increasingly utilize genomic (exome or genome) sequencing, the need for detailed clinical information to aid in interpretation assumes increasing importance. For example, when a laboratory finds a rare or novel variant in a genomic sequencing sample, the director cannot assume it is relevant to a patient just because it is rare, novel, or de novo. The laboratory must evaluate the variant and the gene in the context of the patient’s and family’s history, physical examinations, and previous laboratory tests to distinguish between variants that cause the patient’s disorder and those that are incidental (secondary) findings or benign. Indeed, accurate and complete clinical information is so essential for the interpretation of genome-level DNA sequence findings that the laboratory can reasonably refuse to proceed with the testing if such information is not provided with the test sample.

當醫(yī)務(wù)工作者提出基因檢測需求時，需將患者的臨床信息提供給實驗室。由于醫(yī)務(wù)工作者越來越多地使用基因組(全外顯子組或全基因組)測序，而詳細的臨床信息有助于對檢測結(jié)果的解讀，因此向?qū)嶒炇姨峁┡R床信息就變得越來越重要。例如，當一個實驗室在基因組測序樣品中發(fā)現(xiàn)一個罕見或新發(fā)的變異時，實驗室負責人不能僅因為該變異是罕見的、新發(fā)現(xiàn)的或者新發(fā)的來確定它的致病性。該實驗室必須通過患者的病史、家族史、體格檢查和前期實驗室檢查對變異和基因進行評估，進而區(qū)分致病變異和其他偶然(次要)發(fā)現(xiàn)或良性變異。事實上，正確和完整的臨床信息對于基因組水平DNA序列檢測結(jié)果的解讀是不可或缺的，若待測樣品不能提供此類信息，實驗室可以合理拒絕繼續(xù)進行檢測。

For tests that cover a broad range of phenotypes (large panels, exome and genome sequencing) the laboratory may find candidate causative variants. Further follow-up with the health-care provider and patient may uncover additional evidence to support a variant. These additional phenotypes may be subclinical, requiring additional clinical evaluation to detect (e.g., temporal bone abnormalities detected by computed tomography in a hearing-impaired patient with an uncertain variant in SLC26A4, the gene associated with Pendred syndrome). In addition, testing other family members to establish when a variant is de novo, when a variant cosegregates with disease in the family, and when a variant is in trans with a pathogenic variant in the same recessive disease-causing gene is valuable. Filtering out or discounting the vast majority of variants for dominant diseases when they can be observed in healthy relatives is possible, making the interpretation much more efficient and conclusive. To this end, it is strongly recommended that every effort be made to include parental samples along with that of the proband, so-called “trio” testing (mother, father, affected child), in the setting of exome and genome sequencing, particularly for suspected recessive or de novo causes. Obviously this will be easier to achieve for pediatric patients than for affected adults. In the absence of one or both parents, the inclusion of affected and unaffected siblings can be of value.

利用如高通量的靶向測序、全外顯子組和全基因組測序等覆蓋廣泛表型的方法進行檢測，實驗室可能會發(fā)現(xiàn)候選的致病變異。對醫(yī)務(wù)工作者和患者后續(xù)的隨訪可能會發(fā)現(xiàn)更多的證據(jù)來支持某一變異的致病性。這些補充的表型信息可能是亞臨床癥狀，需要進一步完善相關(guān)的臨床檢測(例如，一個在SLC26A4基因(與Pendred綜合征相關(guān)的基因)上有不確定變異的聽力受損患者，需要進行CT檢查判斷其有無顳骨異常)。此外，當發(fā)現(xiàn)一個變異可能是新發(fā)變異，或者當一個變異在家系中與表型共分離，或者在隱性遺傳致病基因中一個變異與另一個致病變異處于反式位置時，必須在其他家系成員中進行驗證。在顯性遺傳性疾病的情況下，在健康親屬中觀察到的絕大部分變異可以被過濾或刪減，這樣可使解讀更加有效和正確。為此，強烈建議在開展外顯子組或基因組測序時，盡力做到“核心家系”檢測(即母親、父親、患病兒童)，尤其是對懷疑有隱性遺傳或新發(fā)變異的患者。與成人患者相比，這顯然在兒科患者中更易實現(xiàn)。在沒有父母一方或雙方時，納入患病和正常的兄弟姐妹也是有意義的。

Many genetic variants can result in a range of phenotypic expression (variable expressivity), and the chance of disease developing may not be 100% (reduced penetrance), further underscoring the importance of providing comprehensive clinical data to the clinical laboratory to aid in variant interpretation. Ideally, it is recommended that clinical data be deposited into, and shared via, centralized repositories as allowable by Health Insurance Portability and Accountability Act and institutional review board regulations. Importantly, referring health-care providers can further assist clinical laboratories by recruiting DNA from family members in scenarios where their participation will be required to interpret results, (e.g., when evaluating cosegregation with disease using affected family members, genotyping parents to assess for de novo occurrence and determining the phase of variants in recessive disorders using first-degree relatives).

許多遺傳變異會導(dǎo)致一系列表型(不同程度的表現(xiàn)度)，疾病發(fā)生的機率也可能不是100%(外顯率降低)，這些均進一步強調(diào)了向臨床實驗室提供全面的臨床數(shù)據(jù)來幫助解讀變異的重要性。在理想的情況下，建議應(yīng)依據(jù)醫(yī)療保險可攜性和責任法案(HIPAA)和機構(gòu)審查委員會條例，將臨床數(shù)據(jù)存入并通過集中存儲庫共享。重要的是，當家庭成員的信息對于解讀結(jié)果是必需的時候，相關(guān)醫(yī)務(wù)工作者可以進一步幫助臨床實驗室收集家庭成員的DNA(例如，當評估家系患者與疾病共分離時，父母的基因型分析可用來評估新發(fā)變異的發(fā)生，一級親屬可用來確定隱性遺傳疾病變異的同線或異線性)。

A key issue for health-care providers is how to use the evidence provided by genetic testing in medical management decisions. Variant analysis is, at present, imperfect, and the variant category reported does not imply 100% certainty. In general, a variant classified as pathogenic using the proposed classification scheme has met criteria informed by empirical data such that a health-care provider can use the molecular testing information in clinical decision making. Efforts should be made to avoid using this as the sole evidence of Mendelian disease; it should be used in conjunction with other clinical information when possible. Typically, a variant classified as likely pathogenic has sufficient evidence that a health-care provider can use the molecular testing information in clinical decision making when combined with other evidence of the disease in question. For example, in the prenatal setting an ultrasound may show a key confirmatory finding; in postnatal cases, other data such as enzyme assays, physical findings, or imaging studies may conclusively support decision making. However, it is recommended that all possible follow-up testing, as described above, be pursued to generate additional evidence related to a likely pathogenic variant because this may permit the variant to be reclassified as pathogenic. A variant of uncertain significance should not be used in clinical decision making. Efforts to resolve the classification of the variant as pathogenic or benign should be undertaken. While this effort to reclassify the variant is underway, additional monitoring of the patient for the disorder in question may be prudent. A variant considered likely benign has sufficient evidence that a health-care provider can conclude that it is not the cause of the patient’s disorder when combined with other information, for example, if the variant does not segregate in an affected family member and complex inheritance patterns are unlikely. A variant considered benign has sufficient evidence that a health-care provider can conclude that it is not the cause of the patient’s disorder.

醫(yī)務(wù)工作者如何使用基因檢測提供的證據(jù)來進行醫(yī)療管理決策是一個關(guān)鍵問題。目前變異分析是不完善的，報道的變異分類也并不是100%確定的。一般來說，根據(jù)推薦的分類方法劃分為致病性的變異符合經(jīng)驗數(shù)據(jù)形成的標準，所以醫(yī)務(wù)工作者可以在臨床決策時采用分子檢測信息。應(yīng)盡力避免使用此類信息作為孟德爾疾病的少有證據(jù)，在可能的情況下應(yīng)與其他臨床資料相結(jié)合。通常情況下，一個有足夠的證據(jù)被劃分為可能致病的變異，當與可疑疾病的其他證據(jù)相結(jié)合時，醫(yī)務(wù)工作者可以使用分子檢測信息進行臨床決策的制定。例如，產(chǎn)前超聲可能顯示關(guān)鍵的證據(jù)，對于產(chǎn)后的病例，其他數(shù)據(jù)，如酶檢測、體格檢查，或影像學(xué)研究可能賊終支持臨床決策。然而，推薦進行所有如上所述的可能的后續(xù)檢測，追蹤可能致病變異相關(guān)的附加證據(jù)的產(chǎn)生，因為這有可能將可能的致病性變異重新歸類為致病變異。意義不明確的變異不宜應(yīng)用于臨床決策。應(yīng)努力將變異分類為致病性或良性。當變異的重新分類正在進行中時，對可疑致病的患者進行額外的監(jiān)測應(yīng)審慎。一個有足夠證據(jù)被考慮為可能良性的變異，醫(yī)務(wù)工作者可以結(jié)合其他信息，推斷此變異不是該患者致病的原因, 例如，變異并不與家族中的某位患病成員共分離，而且也不太可能是復(fù)雜遺傳模式。一個有足夠證據(jù)被考慮為良性的變異，醫(yī)務(wù)工作者可以得出此變異不是該患者致病原因的結(jié)論。

How the genetic testing evidence is used is also dependent on the clinical context and indication for testing. In a prenatal diagnostic case where a family is considering irrevocable decisions such as fetal treatment or pregnancy termination, the weight of evidence from the report and other sources such as fetal ultrasound needs to be considered before action is taken. When a genetic test result is the only evidence in a prenatal setting, variants considered likely pathogenic must be explained carefully to families. It is therefore critical for referring healthcare providers to communicate with the clinical laboratory to gain an understanding of how variants are classified to assist in patient counseling and management.

基因檢測的證據(jù)如何使用也依賴于臨床背景和檢測指征。在產(chǎn)前診斷的病例中，如果該家庭正在考慮的決定將導(dǎo)致不可逆的后果時，如宮內(nèi)治療或終止妊娠等，需要在采取行動之前慎重考慮報告中證據(jù)的份量和胎兒超聲等其他信息。當基因檢測結(jié)果是產(chǎn)前檢查的少有證據(jù)時，需要向受檢家庭慎重解釋可能致病的變異。關(guān)鍵是相關(guān)的醫(yī)務(wù)工作者應(yīng)與臨床實驗室深入溝通，以了解所檢測到的變異是如何被分類的，以期為患者提供正確的遺傳咨詢和臨床決策。

 

8 參考文獻（略）

圖1

 

表1 人群數(shù)據(jù)庫，疾病特異性數(shù)據(jù)庫和序列數(shù)據(jù)庫

人群數(shù)據(jù)庫
Exome Aggregation Consortium http://exac.broadinstitute.org/	本數(shù)據(jù)庫中的變異信息是通過對61486個獨立個體進行全外顯子測序獲得。同時也是多種特殊疾病和群體遺傳學(xué)研究中的一部分。庫中不包括兒科疾病患者及其相關(guān)人群。
Exome Variant Server http://evs.gs.washington.edu/EVS	本數(shù)據(jù)庫中的變異信息是通過對幾個歐洲和非洲裔大規(guī)模人群的全外顯子測序獲得。當缺乏變異信息時, 默認該數(shù)據(jù)已覆蓋。
1000 Genomes Project http://browser.1000genomes.org	本數(shù)據(jù)庫中的變異信息是通過對26個種群進行低覆蓋度的全基因組測序和高覆蓋度的靶序列測序獲得。本庫所提供的信息比Exome Variant Server更具多樣性，但也包含有低質(zhì)量的數(shù)據(jù)，有些群體中還包含有關(guān)聯(lián)性個體在內(nèi)。
dbSNP http://www.ncbi.nlm.nih.gov/snp	本數(shù)據(jù)庫由多種來源獲得的短片段遺傳變異(通常≤50 bp)信息組成。庫中可能缺乏溯源性研究的細節(jié)，也可能包含致病性突變在內(nèi)。
dbVar http://www.ncbi.nlm.nih.gov/dbvar	本數(shù)據(jù)庫由多種來源獲得的基因結(jié)構(gòu)變異(通常>50 bp)信息組成。
疾病數(shù)據(jù)庫
ClinVar http://www.ncbi.nlm.nih.gov/clinvar	對變異與表型和臨床表型之間的關(guān)聯(lián)進行確定的數(shù)據(jù)庫。
OMIM http://www.omim.org	本數(shù)據(jù)庫所含人類基因和相關(guān)遺傳背景，同時具有疾病相關(guān)基因遺傳變異的代表性樣本收錄與遺傳疾病典型相關(guān)的樣本變異信息。
Human Gene Mutation Database http://www.hgmd.org	本數(shù)據(jù)庫中的變異注釋有文獻發(fā)表。庫中大部分內(nèi)容需付費訂閱。
其他特殊數(shù)據(jù)庫
Human Genome Variation Society http://www.hgvs.org/dblist/dblist.html	本數(shù)據(jù)庫由人類基因組變異協(xié)會(HGVS)開發(fā)，提供數(shù)千種專門針對人群中的特殊變異進行的注釋。數(shù)據(jù)庫很大一部分是基于Leiden Open Variation Database system建立。
Leiden Open Variation Database http://www.lovd.nl
DECIPHER http://decipher.sanger.ac.uk	使用Ensemble基因組瀏覽器，將基因芯片數(shù)據(jù)和臨床表型進行關(guān)聯(lián)，便于臨床醫(yī)生和研究人員使用的細胞分子遺傳學(xué)數(shù)據(jù)庫。
序列數(shù)據(jù)庫
NCBI Genomehttp://www.ncbi.nlm.nih.gov/genome	人類全基因組參考序列的來源。
RefSeqGenehttp://www.ncbi.nlm.nih.gov/refseq/rsg	醫(yī)學(xué)相關(guān)基因參考序列。
Locus Reference Genomic (LRG) http://www.lrg-sequence.org
MitoMap http://www.mitomap.org/MITOMAP/HumanMitoSeq	對“劍橋版-人類線粒體DNA參考序列”進行修訂后形成。

 

表2 生物信息分析工具

 

分類	名稱	網(wǎng)站	依據(jù)
錯義預(yù)測	Consurf	http://consurftest.tau.ac.il	進化保守性
	FATHMM	http://fathmm.biocompute.org.uk	進化保守性
	MutationAsses	http://mutationassessor.org	進化保守性
	PANTHER	http://www.pantherdb.org/tools/csnpScoreForm.jsp	進化保守性
	PhD-SNP	http://snps.biofold.org/phd-snp/phd-snp.html	進化保守性
	SIFT	http://sift.jcvi.org	進化保守性
	SNP&GO	http://snps-and-go.biocomp.unibo.it/snps-and-go	蛋白結(jié)構(gòu)/功能
	Align GVGD	http://agvgd.iarc.fr/agvgd_input.php	蛋白結(jié)構(gòu)/功能和進化保守性
	MAPP	http://mendel.stanford.edu/SidowLab/downloads/MAPP/index.html	蛋白結(jié)構(gòu)/功能和進化保守性
	MutationTaster	http://www.mutationtaster.org	蛋白結(jié)構(gòu)/功能和進化保守性
	MutPred	http://mutpred.mutdb.org	蛋白結(jié)構(gòu)/功能和進化保守性
	PolyPhen-2	http://genetics.bwh.harvard.edu/pph2	蛋白結(jié)構(gòu)/功能和進化保守性
	PROVEAN	http://provean.jcvi.org/index.php	變異序列和蛋白序列同源性之間的相似性比對和測量
	nsSNPAnalyzer	http://snpanalyzer.uthsc.edu	多序列比對和蛋白結(jié)構(gòu)分析
	Condel	http://bg.upf.edu/fannsdb/	綜合SIFT、PolyPhen-2和MutationAssessor進行綜合預(yù)測
	CADD	http://cadd.gs.washington.edu	對于來自模擬變異的等位基因進行不同的注釋
剪切位點預(yù)測	GeneSplicer	http://www.cbcb.umd.edu/software/GeneSplicer/gene_spl.shtml	馬爾可夫模型
	Human Splicing Finder	http://www.umd.be/HSF/	位置依賴的邏輯
	MaxEntScan	http://genes.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html	賊大熵原則
	NetGene2	http://www.cbs.dtu.dk/services/NetGene2	神經(jīng)網(wǎng)絡(luò)
	NNSplice	http://www.fruitfly.org/seq_tools/splice.html	神經(jīng)網(wǎng)絡(luò)
	FSPLICE	http://www.softberry.com/berry.phtml?topic=fsplice&group=programs&subgroup=gfind	基于權(quán)重矩陣模型進行種特異性預(yù)測
核酸保守性預(yù)測	GERP	http://mendel.stanford.edu/sidowlab/downloads/gerp/index.html	基因組進化速率分析
	PhastCons	http://compgen.bscb.cornell.edu/phast/	保守打分及鑒定保守元件
	PhyloP	http://compgen.bscb.cornell.edu/phast/
		http://compgen.bscb.cornell.edu/phast/help-pages/phyloP.txt	比對和分子進化樹：在家系特異或者所有分支中，計算保守或者加速的P值

 

表3 致病變異分級標準

 

致病性證據(jù)	分類
非常強	PVS1：當一個疾病的致病機制為功能喪失（LOF）時，無功能變異（無義突變、移碼突變、經(jīng)典±1或2的剪接突變、起始密碼子變異、單個或多個外顯子缺失）注：1. 該基因的LOF是否是導(dǎo)致該疾病的明確致病機制（如GFAP、MYH7）2. 3’端末端的功能缺失變異需謹慎解讀3.需注意外顯子選擇性缺失是否影響到蛋白質(zhì)的完整性4.考慮一個基因存在多種轉(zhuǎn)錄本的情況。
強	PS1：與先前已確定為致病性的變異有相同的氨基酸改變。例如：同一密碼子，G>C或G>T改變均可導(dǎo)致纈氨酸→亮氨酸的改變。注意剪切影響的改變。
	PS2：患者的新發(fā)變異，且無家族史（經(jīng)雙親驗證）。 注：僅僅確認父母還不夠，還需注意捐卵、采用健康女性合法提供的基因健康卵子、胚胎移植的差錯等情況。
	PS3：體內(nèi)、體外功能實驗已明確會導(dǎo)致基因功能受損的變異。 注：功能實驗需要驗證是有效的，且具有重復(fù)性與穩(wěn)定性。
	PS4：變異出現(xiàn)在患病群體中的頻率顯著高于對照群體。注 1：可選擇使用相對風險值或者OR值來評估，建議位點OR大于5.0且置信區(qū)間不包括1.0的可列入此項。（詳細見指南正文）。2：極罕見的變異在病例對照研究可能無統(tǒng)計學(xué)意義，原先在多個具有相同表型的患者中觀察到該變異且在對照中未觀察到可作為中等水平證據(jù)。
中等	PM1：位于熱點突變區(qū)域，和/或位于已知無良性變異的關(guān)鍵功能域（如酶的活性位點）。
	PM2：ESP數(shù)據(jù)庫、千人數(shù)據(jù)庫、EXAC數(shù)據(jù)庫中正常對照人群中未發(fā)現(xiàn)的變異（或隱性遺傳病中極低頻位點）（表6） 注： 高通量測序得到的插入/缺失人群數(shù)據(jù)質(zhì)量較差
	PM3：在隱性遺傳病中，在反式位置上檢測到致病變異。 注：這種情況必須通過患者父母或后代驗證。
	PM4：非重復(fù)區(qū)框內(nèi)插入/缺失或終止密碼子喪失導(dǎo)致的蛋白質(zhì)長度變化。
	PM5：新的錯義突變導(dǎo)致氨基酸變化，此變異之前未曾報道，但是在同一位點，導(dǎo)致另外一種氨基酸的變異已經(jīng)確認是致病性的，如：現(xiàn)在觀察到的是Arg156Cys，而Arg156His是已知致病的。注意剪切影響的改變。
	PM6： 未經(jīng)父母樣本驗證的新發(fā)變異。
支持證據(jù)	PP1：突變與疾病在家系中共分離（在家系多個患者中檢測到此變異） 注：如果有更多的證據(jù)，可作為更強的證據(jù)。
	PP2： 對某個基因來說，如果這個基因的錯義變異是造成某種疾病的原因，并且這個基因中良性變異所占的比例很小，在這樣的基因中所發(fā)現(xiàn)的新的錯義變異。
	PP3：多種統(tǒng)計方法預(yù)測出該變異會對基因或基因產(chǎn)物造成有害的影響，包括保守性預(yù)測、進化預(yù)測、剪接位點影響等。注：由于做預(yù)測時許多生物信息算法使用相同或非常相似的輸入，每個算法不應(yīng)該算作一個獨立的標準。PP3在一個任何變異的評估中只能使用一次。
	PP4：變異攜帶者的表型或家族史高度符合某種單基因遺傳疾病。
	PP5：有高效信譽來源的報告認為該變異為致病的，但證據(jù)尚不足以支持進行實驗室獨立評估。

 

表4 良性變異分類標準

 

良性影響的證據(jù)	分類
獨立證據(jù)	BA1：ESP數(shù)據(jù)庫、千人數(shù)據(jù)庫、ExAC數(shù)據(jù)庫中等位基因頻率>5%的變異。
強	BS1：等位基因頻率大于疾病發(fā)病率。
	BS2：對于早期有效外顯的疾病，在健康成年人中發(fā)現(xiàn)該變異（隱性遺傳病發(fā)現(xiàn)純合、顯性遺傳病發(fā)現(xiàn)雜合，或者X連鎖半合子）。
	BS3： 在體內(nèi)外實驗中確認對蛋白質(zhì)功能和剪接沒有影響的變異。
	BS4：在一個家系成員中缺乏共分離。
	注：這部分需要考慮復(fù)雜疾病和外顯率問題。
支持證據(jù)	BP1：已知一個疾病的致病原因是由于某基因的截短變異，在此基因中所發(fā)現(xiàn)的錯義變異。
	BP2：在顯性遺傳病中又發(fā)現(xiàn)了另一條染色體上同一基因的一個已知致病變異，或者是任意遺傳模式遺傳病中又發(fā)現(xiàn)了同一條染色體上同一基因的一個已知致病變異。
	BP3：功能未知重復(fù)區(qū)域內(nèi)的缺失/插入，同時沒有導(dǎo)致基因編碼框改變。
	BP4：多種統(tǒng)計方法預(yù)測出該變異會對基因或基因產(chǎn)物無影響，包括保守性預(yù)測、進化預(yù)測、剪接位點影響等。注：由于做預(yù)測時許多生物信息算法使用相同或非常相似的輸入，每個算法不應(yīng)該算作一個獨立的標準。BP4在一個任何變異的評估中只能使用一次。
	BP5：在已經(jīng)有另一分子致病原因的病例中發(fā)現(xiàn)的變異。
	BP6：有高效信譽來源的報告認為該變異為良性的，但證據(jù)尚不足以支持進行實驗室獨立評估。
	BP7：同義變異且預(yù)測不影響剪接。

 

表5 遺傳變異分類聯(lián)合標準規(guī)則

致病的	(i) 1個非常強（PVS1）和
	(a) ≥1個強（PS1-PS4）或
	(b) ≥2個中等（PM1-PM6）或
	(c) 1個中等（PM1-PM6）和1個支持（PP1-PP5）或
	(d) ≥2個支持（PP1-PP5）
	(ii) ≥2 個強（PS1-PS4）或
	(iii) 1個強（PS1）和
	(a) ≥3個中等（PM1-PM6）或
	(b) 2個中等（PM1-PM6）和≥2個支持（PP1-PP5）或
	(c) 1個中等（PM1-PM6）和≥4個支持（PP1-PP5）
可能致病的	(i) 1個非常強（PVS1）和1個中等（PM1-PM6）或
	(ii) 1個強（PS1-PS4）和1-2個中等（PM1-PM6）或
	(iii) 1個強（PS1-PS4）和≥2個支持（PP1-PP5）或
	(iv) ≥3個中等（PM1-PM6）或
	(v) 2個中等（PM1-PM6）和≥2個支持（PP1-PP5）或
	(vi) 1個中等（PM1-PM6）和≥4個支持（PP1-PP5）
良性的	(i) 1個獨立（BA1）或
	(ii) ≥2個強（BS1-BS4）
可能良性的	(i) 1個強（BS1-BS4）和1個支持（BP1-BP7）或
	(ii) ≥2個支持（BP1-BP7）
意義不明確的	(i) 不滿足上述標準或
	(ii) 良性和致病標準相互矛盾

 

表6 評估人群中變異頻率來策劃變異分類

 

 

(責任編輯：佳學(xué)基因)