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start [2017/06/22 18:42] bioadmin [表3 致病变异分级标准] |
start [2017/06/24 17:24] (当前版本) bioadmin [6.4 药物基因组学] |
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| 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/]]). | 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)或相对风险用于衡量基因型(即存在于基因组中的变异)和表型(即所患疾病/结果)之间的关联，适用于任何孟德尔疾病或复杂疾病。本指南只涉及其在孟德尔疾病中的使用。相对风险与OR不同，但概率较小时相对风险近似等于OR。OR值为1.0意味着该变异与疾病风险不相关，大于1.0意味着变异与疾病风险正相关，小于1.0意味着变异与疾病风险负相关。一般情况下，具有孟德尔中等效应的变异，其OR值为3或者更大，高度外显的变异具有非常高的OR值，例如，APOE基因E4/E4纯合子与E3/E3纯合子相比，OR值为13(https://www.tgen.org/ home/education-outreach/past-summer-interns/2012-summer-interns/erika-kollitz.aspx#.VOSi3C7G_vY)。OR值的置信区间(confidence interval，CI)也是一个重要的衡量工具。如果CI中包括1.0(如OR=2.5，CI=0.9~7.4)，则关联的可信度很小。在上面APOE的例子中，CI为10~16。在线可获得简单的OR值计算器（http://www.hutchon.net/ConfidOR.htm/and http://easycalculation.com/statistics/odds-ratio.php/）。 | + | 比值比(OR)或相对风险用于衡量基因型(即存在于基因组中的变异)和表型(即所患疾病/结果)之间的关联，适用于任何孟德尔疾病或复杂疾病。本指南只涉及其在孟德尔疾病中的使用。相对风险与OR不同，但概率较小时相对风险近似等于OR。OR值为1.0意味着该变异与疾病风险不相关，大于1.0意味着变异与疾病风险正相关，小于1.0意味着变异与疾病风险负相关。一般情况下，具有孟德尔中等效应的变异，其OR值为3或者更大，高度外显的变异具有非常高的OR值，例如，APOE基因E4/E4纯合子与E3/E3纯合子相比，OR值为13(https://www.tgen.org/home/education-outreach/past-summer-interns/2012-summer-interns/erika-kollitz.aspx#.VOSi3C7G_vY)。OR值的置信区间(confidence interval，CI)也是一个重要的衡量工具。如果CI中包括1.0(如OR=2.5，CI=0.9~7.4)，则关联的可信度很小。在上面APOE的例子中，CI为10~16。在线可获得简单的OR值计算器（http://www.hutchon.net/ConfidOR.htm/and http://easycalculation.com/statistics/odds-ratio.php/）。 |
| ==== 4.6 PM1 热点突变和/或关键的、得到确认的功能域 ==== | ==== 4.6 PM1 热点突变和/或关键的、得到确认的功能域 ==== | ||
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| 线粒体变异的命名法与核基因的标准命名法不同，使用基因名和m.编号(如m.8993T>C)和p.编号，而不是标准的c.编号(见命名法)。目前公认的参考序列是人类线粒体DNA修订版剑桥参考序列: 基因库序列NC_012920 gi: 251831106(http://www.mitomap.org/MITOMAP/HumanMitoSeq)。 | 线粒体变异的命名法与核基因的标准命名法不同，使用基因名和m.编号(如m.8993T>C)和p.编号，而不是标准的c.编号(见命名法)。目前公认的参考序列是人类线粒体DNA修订版剑桥参考序列: 基因库序列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. | + | 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. |
| - | 如果已通过检测对异质性水平进行确定，应该对异质性或同质性，以及变异异质性的评估进行报道。不同组织类型的异质性百分比因检测样本的不同而有所改变, 因此，低异质性水平也必须结合所检测组织进行解读，且它们可能仅在受累及的组织中才是有意义的，如肌肉组织。超过275个与疾病相关的线粒体DNA变异已被记录(http://mitomap.org/bin/view.pl/ MITOMAP/WebHome)。MitoMap是线粒体变异及单倍型相关信息的主要来源。其他资源，如频率信息(http://www.mtdb.igp.uu.se/)、二级结构、序列和线粒体转运RNA的比对(http://mamittrna.u-strasbg.fr/)、线粒体单倍群(http://www.phylotree.org/)[35]和其他信息(http://www.mtdnacommunity.org/default.aspx)，可能在解读线粒体变异时是有用的。 | + | 如果已通过检测对异质性水平进行确定，应该对异质性或同质性，以及变异异质性的评估进行报道。不同组织类型的异质性百分比因检测样本的不同而有所改变, 因此，低异质性水平也必须结合所检测组织进行解读，且它们可能仅在受累及的组织中才是有意义的，如肌肉组织。超过275个与疾病相关的线粒体DNA变异已被记录(http://mitomap.org/bin/view.pl/MITOMAP/WebHome)。MitoMap是线粒体变异及单倍型相关信息的主要来源。其他资源，如频率信息(http://www.mtdb.igp.uu.se/)、二级结构、序列和线粒体转运RNA的比对(http://mamittrna.u-strasbg.fr/)、线粒体单倍群(http://www.phylotree.org/)和其他信息(http://www.mtdnacommunity.org/default.aspx)，可能在解读线粒体变异时是有用的。 |
| 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. | 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. | ||
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| ==== 6.4 药物基因组学 ==== | ==== 6.4 药物基因组学 ==== | ||
| - | 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. | + | 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. |
| 确认基因变异在药物代谢中的作用具有挑战性，部分原因在于其表型只有在接触药物后才得以显现。不过，临床上现已报告了各种与药物疗效和副作用风险相关的基因变异，且其数量仍然在不断增加。相关基因的汇总及其有临床意义的变异可查询药物基因组学知识库网站(http://www.pharmgkb.org/)。有关细胞色素P450基因家族等位基因及其命名可查询网站http://www.cypalleles.ki.se/。尽管解读药物基因组变异已超出了本文的范围，还是对与解读及报告药物基因组结果相关的挑战和鉴别进行了讨论。 | 确认基因变异在药物代谢中的作用具有挑战性，部分原因在于其表型只有在接触药物后才得以显现。不过，临床上现已报告了各种与药物疗效和副作用风险相关的基因变异，且其数量仍然在不断增加。相关基因的汇总及其有临床意义的变异可查询药物基因组学知识库网站(http://www.pharmgkb.org/)。有关细胞色素P450基因家族等位基因及其命名可查询网站http://www.cypalleles.ki.se/。尽管解读药物基因组变异已超出了本文的范围，还是对与解读及报告药物基因组结果相关的挑战和鉴别进行了讨论。 | ||
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| ===== 图1 ===== | ===== 图1 ===== | ||
| {{:figure1.png|}} | {{:figure1.png|}} | ||
| - | {{:图1.png|}} | + | {{:图1-1.jpg|}} |
| ===== 表1 人群数据库，疾病特异性数据库和序列数据库 ===== | ===== 表1 人群数据库，疾病特异性数据库和序列数据库 ===== | ||
| {{:table1.png|}} | {{:table1.png|}} | ||
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| {{:table4.png|}} | {{:table4.png|}} | ||
| ^良性影响的证据^ 分类 ^ | ^良性影响的证据^ 分类 ^ | ||
| - | |独立证据| BA1：ESP数据库、千人数据库、EAC数据库中等位基因频率>5%的变异| | + | |独立证据| BA1：ESP数据库、千人数据库、ExAC数据库中等位基因频率>5%的变异。| |
| - | |强|BS1：等位基因频率大于疾病发病率| | + | |强|BS1：等位基因频率大于疾病发病率。| |
| |:::|BS2：对于早期完全外显的疾病，在健康成年人中发现该变异（隐性遗传病发现纯合、显性遗传病发现杂合，或者X连锁半合子）。| | |:::|BS2：对于早期完全外显的疾病，在健康成年人中发现该变异（隐性遗传病发现纯合、显性遗传病发现杂合，或者X连锁半合子）。| | ||
| |:::|BS3： 在体内外实验中确认对蛋白质功能和剪接没有影响的变异。| | |:::|BS3： 在体内外实验中确认对蛋白质功能和剪接没有影响的变异。| | ||
| - | |:::|BS4：在一个家系成员中缺乏共分离| | + | |:::|BS4：在一个家系成员中缺乏共分离。| |
| - | |:::|注意事项：这部分需要考虑复杂疾病和外显率问题| | + | |:::|注：这部分需要考虑复杂疾病和外显率问题。| |
| |支持证据|BP1：已知一个疾病的致病原因是由于某基因的截短变异，在此基因中所发现的错义变异。| | |支持证据|BP1：已知一个疾病的致病原因是由于某基因的截短变异，在此基因中所发现的错义变异。| | ||
| |:::|BP2：在显性遗传病中又发现了另一条染色体上同一基因的一个已知致病变异，或者是任意遗传模式遗传病中又发现了同一条染色体上同一基因的一个已知致病变异。| | |:::|BP2：在显性遗传病中又发现了另一条染色体上同一基因的一个已知致病变异，或者是任意遗传模式遗传病中又发现了同一条染色体上同一基因的一个已知致病变异。| | ||
| |:::|BP3：功能未知重复区域内的缺失/插入，同时没有导致基因编码框改变。| | |:::|BP3：功能未知重复区域内的缺失/插入，同时没有导致基因编码框改变。| | ||
| - | |:::|BP4：种统计方法预测出该变异会对基因或基因产物无影响，包括保守性预测、进化预测、剪接位点影响等。注意事项：由于做预测时许多生物信息算法使用相同或非常相似的输入，每个算法不应该算作一个独立的标准。BP4在一个任何变异的评估中只能使用一次。| | + | |:::|BP4：多种统计方法预测出该变异会对基因或基因产物无影响，包括保守性预测、进化预测、剪接位点影响等。注：由于做预测时许多生物信息算法使用相同或非常相似的输入，每个算法不应该算作一个独立的标准。BP4在一个任何变异的评估中只能使用一次。| |
| |:::|BP5：在已经有另一分子致病原因的病例中发现的变异。| | |:::|BP5：在已经有另一分子致病原因的病例中发现的变异。| | ||
| |:::|BP6：有可靠信誉来源的报告认为该变异为良性的，但证据尚不足以支持进行实验室独立评估。| | |:::|BP6：有可靠信誉来源的报告认为该变异为良性的，但证据尚不足以支持进行实验室独立评估。| | ||
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| ===== 表5 遗传变异分类联合标准规则 ===== | ===== 表5 遗传变异分类联合标准规则 ===== | ||
| {{:table5.png?400 |}} | {{:table5.png?400 |}} | ||
| - | ^ 致病 | (i) 1个非常强（PVS1）和| | + | ^ 致病的 | (i) 1个非常强（PVS1）和| |
| ^ ::: | (a) ≥1个强（PS1-PS4）或 | | ^ ::: | (a) ≥1个强（PS1-PS4）或 | | ||
| ^ ::: | (b) ≥2个中等（PM1-PM6）或 | | ^ ::: | (b) ≥2个中等（PM1-PM6）或 | | ||
| 行 495: | 行 495: | ||
| ^ ::: | (b) 2个中等（PM1-PM6）和≥2个支持（PP1-PP5）或 | | ^ ::: | (b) 2个中等（PM1-PM6）和≥2个支持（PP1-PP5）或 | | ||
| ^ ::: | %%(c)%% 1个中等（PM1-PM6）和≥4个支持（PP1-PP5） | | ^ ::: | %%(c)%% 1个中等（PM1-PM6）和≥4个支持（PP1-PP5） | | ||
| - | ^ 可能致病 | (i) 1个非常强（PVS1）和1个中等（PM1-PM6）或 | | + | ^ 可能致病的 | (i) 1个非常强（PVS1）和1个中等（PM1-PM6）或 | |
| ^ ::: | (ii) 1个强（PS1-PS4）和1-2个中等（PM1-PM6）或 | | ^ ::: | (ii) 1个强（PS1-PS4）和1-2个中等（PM1-PM6）或 | | ||
| ^ ::: | (iii) 1个强（PS1-PS4）和≥2个支持（PP1-PP5）或 | | ^ ::: | (iii) 1个强（PS1-PS4）和≥2个支持（PP1-PP5）或 | | ||
| 行 501: | 行 501: | ||
| ^ ::: | (v) 2个中等（PM1-PM6）和≥2个支持（PP1-PP5）或 | | ^ ::: | (v) 2个中等（PM1-PM6）和≥2个支持（PP1-PP5）或 | | ||
| ^ ::: | (vi) 1个中等（PM1-PM6）和≥4个支持（PP1-PP5） | | ^ ::: | (vi) 1个中等（PM1-PM6）和≥4个支持（PP1-PP5） | | ||
| - | ^ 良性 | (i) 1个独立（BA1）或 | | + | ^ 良性的 | (i) 1个独立（BA1）或 | |
| ^ ::: | (ii) ≥2个强（BS1-BS4） | | ^ ::: | (ii) ≥2个强（BS1-BS4） | | ||
| - | ^ 可能良性 | (i) 1个强（BS1-BS4）和1个支持（BP1-BP7）或 | | + | ^ 可能良性的 | (i) 1个强（BS1-BS4）和1个支持（BP1-BP7）或 | |
| ^ ::: | (ii) ≥2个支持（BP1-BP7） | | ^ ::: | (ii) ≥2个支持（BP1-BP7） | | ||
| - | ^ 意义不明 | (i) 不满足上述标准或 | | + | ^ 意义不明确的 | (i) 不满足上述标准或 | |
| ^ ::: | (ii) 良性和致病标准相互矛盾 | | ^ ::: | (ii) 良性和致病标准相互矛盾 | | ||
| ===== 表6 评估人群中变异频率来策划变异分类 ===== | ===== 表6 评估人群中变异频率来策划变异分类 ===== | ||
| {{:table6.png |}} | {{:table6.png |}} | ||
| + | {{:表7-1.jpg|}} | ||
| + | {{:表7-3.jpg|}} | ||