Characterizing disease-causing variants using personal genomes with large recurrent deletions

摘要 基因组精准医学领域的一个主要挑战是观察到基因型并不总是 预测孟德尔疾病的表型。这种表型变异被认为部分是由常见的 变体和具有微妙影响的变体，但此类修饰等位基因的潜在确定性作用尚未 在临床环境中经过严格或系统的研究。朝着破译密码的长期目标 人类单基因疾病不完全外显率和可变表达性的遗传基础，该提案 旨在研究患有复发性基因组疾病的患者，其中表现出相同的基因组重排 以不完全渗透的方式检测疾病表型。该拟议项目的总体目标是 使用具有复发性大基因组缺失的患者队列制定一种通用方法，该方法可以 识别和表征具有临床意义的疾病缓解变异。中心假设是患者 反复发生的大基因组缺失为识别疾病缓解提供了有效的基因组背景 等位基因可作为个体患者疾病结果的可靠预测因子。这个中心假设将是 通过定义两个基因组位点特定表型呈现的遗传决定因素进行测试：早期 糖尿病发病于 17q12，头部尺寸异常于 1q21.1。将聚集大规模患者资源 基于临床诊断提供的分子信息。招募的患者将在 通过全基因组测序进行分子水平。将进行表型-基因型相关分析 根据初步数据确定不同疾病修饰模型下的候选修饰等位基因 每个疾病位点。将使用患者进行选定的疾病缓解等位基因的功能验证 衍生的诱导多能干细胞。本研究的创新点在于集合了稀有的个人资料 来自临床诊断数据库的具有相同拷贝数变异的基因组，使人类受试者能够 “增强屏幕。”拟议的研究意义重大，因为它有望确定临床上重要的 反复缺失位点中的等位基因，其存在或缺失可用于精确诊断、咨询和 遗传性疾病患者的管理。本文使用的研究策略可以推广到 其他表型或基因组位点，发现的一般机制将直接适用于 了解人类疾病的不完全外显率和可变表达性。

Abstract A major challenge in the field of genomic precision medicine is the observation that genotype does not always predict phenotype in Mendelian disorders. This phenotype variation is thought to be caused in part by common variants and variants with subtle effects, but the potential deterministic roles of such modifier alleles have not been rigorously or systematically studied in clinical settings. Toward the long-term goal of deciphering the genetic basis of incomplete penetrance and variable expressivity in human monogenic diseases, this proposal aims to study patients with recurrent genomic disorders in whom identical genomic rearrangements manifest disease phenotypes in an incompletely penetrant manner. The overall objective of this proposed project is to formulate a generalizable approach using cohorts of patients with recurrent large genomic deletions that can identify and characterize clinically significant disease-modifying variants. The central hypothesis is that patients with recurrent large genomic deletions offer an effective genomic background to identify disease-modifying alleles that serve as reliable predictors of disease outcome in individual patients. This central hypothesis will be tested by defining the genetic determinants of specific phenotype presentations at two genomic loci: early onset diabetes at 17q12 and abnormal head size at 1q21.1. Large-scale patient resources will be gathered based on molecular information made available by clinical diagnostics. Recruited patients will be analyzed at the molecular level by whole genome sequencing. Phenotype–genotype correlation analysis will be performed to identify candidate modifier alleles under different disease-modifying models based on preliminary data from each disease locus. Functional validation of selected disease-modifying alleles will be performed using patient- derived induced pluripotent stem cells. The innovation of this study lies in the assembly of rare personal genomes with identical copy number variants from clinical diagnostic databases to enable a human subject “enhancer screen.” The proposed research is significant because it is expected to identify clinically important alleles in recurrent deletion loci whose presence or absence can be used for precise diagnosis, counseling and management for patients with genetic disorders. The research strategy utilized herein could be generalized to other phenotypes or genomic loci, and the general mechanisms discovered will be directly applicable to understanding incomplete penetrance and variable expressivity in human diseases.