Identifying novel clinical, genetic and proteomic risk factors for sickle cell nephropathy.

摘要 镰状细胞病（SCD）肾病或SCDN，定义为存在蛋白尿或低肾小球 滤过率（GFR）影响高达30%的成人SCD患者。我们已经证明，SCD患者的GFR下降 患者几乎是没有SCD的非洲裔美国人的两倍。SCDN可进展为终末期肾病 疾病;两者都是SCD早期死亡的潜在危险因素。这种关联可能部分归因于 SCDN与其他内皮病变，特别是肺动脉高压的相关性。SCDN 目前的治疗选择仅限于用于其它肾脏疾病，如糖尿病肾病， 并且不是特别有效。因此，早期识别高危患者并开发有效的治疗方法 专门针对SCDN的病理生理学至关重要。遗传因素，尤其是APOL 1， 对SCDN的敏感性。然而，APOL 1不足以解释所有SCDN风险，提示其他临床和 存在遗传风险因素。NHLBI的TOPMed计划是一个非凡的机会， SCD的个性化医疗发现，包括SCDN。我们的队列（OMG-SCD）与其他 TOPMed SCD队列，总计>4100个样本，具有全基因组序列结果和丰富的临床数据，包括 肾脏相关表型。我们的OMG-SCD队列储存了血浆样本，以前用于生成 代谢组学和初步蛋白质组学数据，并确定与GFR快速下降相关的两种代谢物 8种蛋白质，包括胱抑素C和补体因子D，估计GFR低于90 mL/min/1.73 M2.产生额外的蛋白质组数据将促进生物标志物的发现和潜在的生物学特性。 SCDN的机制。具体而言，我们建议：（1）确定新的临床和遗传危险因素的SCDN; (2)确定SCDN的蛋白质组学生物标志物;和（3）建立风险模型以将患有和 没有肾病。我们将利用大型的、特征良好的TOPM SCD队列来揭示 SCDN的分子基础，SCD中最大的临床挑战之一，由于严重的风险， 发病率和死亡率。我们的工作准备产生SCDN风险因素（遗传基因座， 生物标志物），指向因果生物学机制，从而促进风险分层的临床研究，以进一步 在这一患者群体中发展精准医疗方法。

ABSTRACT Sickle cell disease (SCD) nephropathy or SCDN, as defined by the presence of proteinuria or low glomerular filtration rate (GFR), affects up to 30% of adult SCD patients. We have shown that GFR decline among SCD patients is nearly double that among African Americans without SCD. SCDN can progress to end-stage renal disease; both are potent risk factors for early mortality in SCD. This association may be partly attributable to the correlation of SCDN with other endotheliopathic conditions, especially pulmonary hypertension. SCDN therapeutic options are currently limited to those used for other renal diseases, such as diabetic nephropathy, and are not particularly efficacious. Thus, identifying at-risk patients early and developing effective therapeutics targeted specifically to the pathophysiology of SCDN is critical. Genetic factors, most notably APOL1, influence susceptibility to SCDN. However, APOL1 is insufficient to explain all SCDN risk, suggesting other clinical and genetic risk factors exist. NHLBI’s TOPMed program is an extraordinary opportunity to make significant discoveries in personalized medicine for SCD, including SCDN. Our cohort (OMG-SCD), together with other TOPMed SCD cohorts, total >4100 samples with whole genome sequence results and rich clinical data, including kidney-related phenotypes. Our OMG-SCD cohort has stored plasma samples, used previously to generate metabolomics and preliminary proteomics data and identify two metabolites associated with rapid GFR decline and eight proteins, including cystatin-C and complement factor D, with estimated GFR below 90 mL/min/1.73 m2. Generation of additional proteomic data would facilitate biomarker discovery and underlying biologic mechanisms of SCDN. Specifically, we propose to: (1) Identify novel clinical and genetic risk factors for SCDN; (2) Identify proteomic biomarkers for SCDN; and (3) Establish risk models to classify SCD patients with and without nephropathy. We will harness the large, well-characterized TOPMed SCD cohorts to uncover the molecular underpinnings of SCDN, one of the greatest clinical challenges in SCD, due to the profound risk for morbidity and mortality. Our work is poised to yield significant discoveries of SCDN risk factors (genetic loci, biomarkers), point toward causal biologic mechanisms, and thus facilitate risk-stratified clinical studies to further the development of precision medicine approaches in this patient population.