Clinical prioritization of reported disease variants in asymptomatic individuals

无症状个体中报告的疾病变异的临床优先顺序

• 批准号: 8487872
• 负责人: Christopher Cassa
• 金额: $ 10.91万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8487872
• 关键词: Address; Affect; Algorithms; Ambulatory Care; Behavioral; Benign; Caring; Case Study; Classification; Clinical; Clinical Trials; Cohort Studies; Confidence Intervals; Data; Data Set; Databases; Development; Diagnostic; Disease; Disease Association; Environmental Risk Factor; Epidemiology; Equilibrium; Exclusion; Foundations; Frequencies; Future; Gene Frequency; Genetic; Genetic Risk; Genetic Variation; Genomics; Gold; Hereditary Disease; Hypertrophic Cardiomyopathy; Incidence; Individual; Laboratories; Link; Literature; Measures; Medical; Methodology; Methods; Minor; Morbidity - disease rate; Neurofibromatoses; Online Mendelian Inheritance In Man; Pathogenicity; Patients; Penetrance; Pharmaceutical Preparations; Physicians; Population; Population Genetics; Positioning Attribute; Prevalence; Primary Health Care; Probability; Process; Publications; Publishing; Rare Diseases; Relative (related person); Reporting; Research; Risk; Risk Estimate; Source; Structure; Sum; Surveys; Symptoms; Tail; Translating; Variant; base; burden of illness; case control; clinical application; clinical practice; clinical risk; clinically relevant; clinically significant; cohort; cost; disorder risk; epidemiologic data; genetic variant; genome sequencing; genome-wide; improved; meetings; novel; novel strategies; population based; public health relevance; research clinical testing; response; risk variant

DESCRIPTION (provided by applicant): Whole genome sequencing (WGS) has the potential to improve medical care, but much effort remains to translate sequence data into meaningful clinical interpretations. WGS interpretation must address both newly observed genetic variants that are likely to be harmful, as well as the review of over 150,000 variants that are already reported to be associated with disease from the medical and scientific literature. Many of these discoveries were made in small cohort and case studies, making it difficult to translate these into disease risks for asymptomatic individuals that carry these variants. Without accurate risk estimates for these associations, we may potentially expose healthy patients to false positive findings, leading to needless diagnostic workups and screenings that will substantially increase medical costs and patient morbidity. Central to WGS interpretation is the development of a standardized methodology to filter likely benign results, and to prioritize those variants that may be clinically significant and scientifically valid. While many of these previously identified variats are associated with Mendelian disorders that are individually rare, (e.g. hypertrophic cardiomyopathy and neurofibromatosis,) these disorders are collectively common, forming a long tail that confers disease risk for many individuals. Because each of these diseases is so rare, it is hard to envision a specialized interpretive approach to calculate risk for each disease so we propose a systematic approach that is broadly applicable across many rare diseases to assess variant disease risk. To meet this urgent need, we will develop a novel approach that estimates the penetrance of disease- associated variants using the prior probability of each disease, and the population frequencies of all of the known genetic variants for that disease for affected and unaffected individuals. This prior probability of disease is measured as the prevalence, or the proportion of individuals in a population affected with a disorder. Because the prevalence of a Mendelian disease is actually a combination of the penetrance and frequency of all of its genetic variation (as well as other behavioral and environmental factors) we propose to estimate these penetrance values using the disease prevalence and distribution of associated variation, for each disease. If there is only one variant associated with a disease, the total penetrance and population frequency for that disease should be closely correlated with disease prevalence, but if there are many disease-associated variants, each contributes less to the overall burden of diseases, adjusted by its frequency in the population. We will then use these penetrance estimates to establish genome-wide filtering cutoffs for likely benign variation and to prioritize observed WGS variation for review by clinical geneticists. We then propose to use these values to filter and rank the observed variation in individual WGS datasets in an existing clinical trial, and to compare these with existing clinical genetics interpretations.

描述（由申请人提供）：全基因组测序（WGS）具有改善医疗保健的潜力，但将序列数据转化为有意义的临床解释仍需付出大量努力。 WGS 解释必须解决新观察到的可能有害的遗传变异，以及对医学和科学文献中已报道与疾病相关的超过 150,000 个变异的审查。其中许多发现是在小规模队列研究和案例研究中取得的，因此很难将其转化为 携带这些变异的无症状个体的疾病风险。如果没有对这些关联进行准确的风险评估，我们可能会将健康患者暴露在假阳性结果中，从而导致不必要的诊断检查和筛查，从而大幅增加医疗成本和患者发病率。 WGS 解释的核心是开发标准化方法来过滤可能的良性结果，并优先考虑那些可能的变异 具有临床意义和科学有效性。虽然许多先前发现的变异与孟德尔疾病有关，这些疾病个体罕见（例如肥厚性心肌病和神经纤维瘤病），但这些疾病总体上很常见，形成一条长尾，给许多人带来疾病风险。由于每种疾病都非常罕见，因此很难设想一种专门的解释方法来计算每种疾病的风险，因此我们提出了一种广泛适用于许多罕见疾病的系统方法来评估变异疾病风险。 为了满足这一迫切需求，我们将开发一种新方法，使用每种疾病的先验概率以及受影响和未受影响个体的该疾病的所有已知遗传变异的群体频率来估计疾病相关变异的外显率。疾病的先验概率以患病率或人口中患有某种疾病的个体比例来衡量。由于孟德尔疾病的患病率实际上是其所有遗传变异（以及其他行为和环境因素）的外显率和频率的组合，因此我们建议使用疾病患病率和相关变异的分布来估计这些外显率值，例如每种疾病。如果只有一种变异与一种疾病相关，则该疾病的总外显率和人群频率应与疾病患病率密切相关，但如果有许多与疾病相关的变异，则每种变异对疾病总体负担的贡献较小，调整为其在人群中的出现频率。然后，我们将使用这些外显率估计来建立可能的良性变异的全基因组过滤截止值，并优先考虑观察到的 WGS 变异以供临床遗传学家审查。然后，我们建议使用这些值来过滤和排序现有临床试验中各个 WGS 数据集中观察到的变异，并将这些值与现有的临床遗传学解释进行比较。