An Integrative Systems Genetics Approach to Nephrotic Syndrome

描述(申请人提供)：肾病综合征(NS)是一种由肾小球通透性异常引起的大量蛋白尿的临床综合征。这种蛋白尿伴随着感染、静脉血栓栓塞症和进行性肾功能丧失的风险增加。发病率也是由用于治疗这种疾病的非特异性免疫抑制药物的副作用引起的。影响儿童的原发NS的主要组织学类型是微小病变病(MCD)和局灶节段性肾小球硬化(FSGS)。为有更高风险的人提供有针对性的个性化护理具有挑战性， 或目前受NS影响。应对这一挑战的一个策略是更充分地了解NS的基因组基础。该研究小组正在研究在肾活检时招募到两个前瞻性观察队列中的450名所有年龄段的NS患者的子集。研究人员将首先确定20个已知导致单基因形式的类固醇耐药肾病(SRNS)的基因在等位基因频谱上的变异率，这些基因的基因型-表型相关性之前已经被观察到。对于这些基因罕见变异(微小等位基因频率为0.5%)的患者，将确定其与临床结果的相关性，如起病年龄、蛋白尿缓解和肾功能下降。还将研究隐性SRNS基因中的杂合稀有变种或意义未知的稀有变种对SRNS结果的影响，以及较不罕见的变种(0.5-1%)的可能贡献。除了确定已知SRNS基因变异的临床影响外，还将利用表达数量性状基因座(EQTL)研究，寻找与NS相关的新基因或非编码、调节基因组元件。与传统的全基因组关联研究不同，这项eQTL研究的结果将是来自NS受试者肾脏活检的基因表达。使用基因表达作为中间的内表型提高了检测重大关联的能力，也将直接阐明否则无法检测到的生物途径。最后，研究人员将继续与他在计算遗传学领域的合作者合作，以 开发新的全基因组方法，以识别在强负选择下的基因，并预测在NS的测序或综合基因组研究中发现的变异的功能影响。这将通过整合来自不同的高质量比较基因组学、种群遗传学和疾病特定数据集的基因组和功能特征来实现。在整个项目中，申请者将通过这些分析和生物信息学编程、系统生物学和高级统计遗传学的正式课程获得进行综合基因组研究的专业知识。总之，将基因组变异与前瞻性收集的基因表达、组织学、生化和临床数据相结合，将最大限度地提高对NS发病机制的洞察能力，识别风险、治疗反应或疾病进展的新生物标记物，并指导有针对性的治疗开发策略。

DESCRIPTION (provided by applicant): Nephrotic syndrome (NS) is a clinical syndrome of massive proteinuria caused by abnormal glomerular permeability. This proteinuria is accompanied by increased risk of infection, venous thromboembolism, and progressive loss of renal function. Morbidity also results from side effects of nonspecific immunosuppression medications used to treat this disease. The major histologic classifications of primary NS affecting children are minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS). It is challenging to provide targeted, individualized care for people at increased risk of, or currently affected by, NS. One strategy to meet this challenge is to more fully understand the genomic underpinnings of NS. This research team is studying a subset of 450 patients of all ages with incident NS recruited into two prospective observational cohorts at the time of renal biopsy. The investigators will first determine the prevalence of variants across the allele frequency spectrum for 20 genes known to cause monogenic forms of steroid-resistant NS (SRNS) and for which genotype-phenotype correlations have been observed previously. The association with clinical outcomes such as age of onset, remission of proteinuria, and decline of renal function will be determined for patients with rare variants in these genes (minor allele frequency <0.5%). The impact on SRNS outcomes from heterozygous rare variants in recessive SRNS genes or rare variants of unknown significance will also be studied, as well as possible contributions from less rare variants (0.5-1%). In addition to characterizing the clinical impact o variants in known SRNS genes, the discovery of novel genes or non-coding, regulatory genomic elements associated with NS will also be sought using an expression quantitative trait loci (eQTL) study. As opposed to a traditional genome-wide association study, the outcome for this eQTL study will be gene expression from the kidney biopsies of NS subjects. Using gene expression as an intermediate endophenotype improves power to detect significant associations and will also directly illuminate biologic pathways that would not have been detected otherwise. Finally, the investigator will continue to work with his collaborators in computational genetics to develop novel, genome-wide methods to identify genes under strong negative selection and to predict the functional impact of variants discovered in sequencing or integrative genomics studies of NS. This will be achieved by integrating genomic and functional characteristics from diverse high quality comparative genomics, population genetics, and disease specific datasets. Throughout this project, the applicant will acquire expertise in conducting integrative genomics research through these analyses and via formal coursework in bioinformatics programming, systems biology, and advanced statistical genetics. Altogether, integrating genomic variants with prospectively collected gene expression, histologic, biochemical, and clinical data will maximize ability to derive mechanistic insight about NS pathogenesis, identify novel biomarkers of risk, therapeutic response, or disease progression, and guide targeted therapeutic development strategies.