The Genetic Epidemiology of Rotator Cuff Tears: The cuffGEN Study

项目摘要 2015年，美国因肩痛就诊的门诊医生达1260万人次。肩袖 撕裂是肩痛和残疾的主要原因之一，2006年有272 148例手术。 退行性非创伤性肩袖撕裂的病因尚不清楚。来自家族聚集性研究的数据 提供令人信服的初步证据表明遗传易感性肩袖撕裂。然而，在这方面， 大规模全基因组关联研究（GWAS）使用经成像验证的肩袖撕裂病例， 缺乏控制，寻找致病的遗传变异和致病基因仍然难以捉摸。 肩袖肌肉的脂肪浸润（FI）程度对于治疗决策至关重要，因为 FI分级与更差的结果相关。大约40%到50%的肩袖撕裂患者 菲FI背后的遗传病因尚未得到评估，肥胖与肥胖之间的关系是否与肥胖有关？ FI的因果关系尚不清楚。康复和袖带撕裂手术后的患者报告结局也 变量有支持性证据表明遗传变异在预测治疗结果中的作用， 还没有得到很好的研究。 我们的研究团队正在招募一个12个地点，NIH和PCORI资助的临床试验，700名患者随机 关节镜手术与物理治疗的非创伤性肩袖撕裂（称为关节镜肩袖） （ARC）。这提供了一个独特的机会，可以利用我们现有的基础设施， 一项关于袖带撕裂遗传学的影像学验证病例对照研究。我们制定了标准化的 使用电子健康记录（EHR）数据确定图像验证病例和控制的方法。通过 将这些标准化方法应用于范德比尔特（BioVU）和凯泽（Kaiser）的EHR相关生物库 Permanente（GERA），每个都有大约100，000个基因型个体，并通过与 来自犹他州和斯坦福大学的研究人员是仅有的两个袖带撕裂GWAS的领导者， 召集了最大的财团（cuffGEN）来研究肩袖疾病的遗传学。我们将执行 独一无二的GWAS调查，包括5，000个成像的分类良好的发现和复制样本， 经验证的肩袖撕裂病例和5,000例经成像验证的对照。这项精心设计的研究将确定 遗传变异与袖带撕裂、FI和术后患者报告的最佳结局之间的相关性 或康复治疗。我们将优先考虑基因发现， 脂肪和肌肉使用参考数据库与GWAS结果。通过孟德尔随机化， 研究将澄清肥胖和FI之间是否存在因果关系。这项拟议中的研究允许NIH基金 利用现有的基础设施，没有这些基础设施，这项大型遗传研究将很困难。 评估干预准备和康复进展的遗传分析是NIH的优先事项， 建议的研究将交付。关于袖带撕裂遗传易感性、FI和最佳治疗的数据 结果将有助于识别高风险个体，并根据 个人的基因图谱。

PROJECT SUMMARY Shoulder pain accounted for 12.6 million ambulatory physician visits in 2015 in the United States. Rotator cuff tears are one of the leading causes of shoulder pain and disability and accounted for 272,148 surgeries in 2006. The etiology of degenerative atraumatic rotator cuff tears is unknown. Data from familial aggregation studies provide convincing preliminary evidence suggesting genetic predisposition to rotator cuff tears. However, large-scale genome-wide association studies (GWAS) using imaging-verified rotator cuff tear cases and controls are lacking, and the search for causal genetic variants and causal genes remains elusive. The degree of fatty infiltration (FI) of rotator cuff muscles is critical for treatment decision-making since higher grades of FI are associated with worse outcomes. About 40 to 50% of patients with rotator cuff tears develop FI. The genetic etiology behind FI has not yet been assessed, and whether the relationship between obesity and FI is causal remains unclear. Patient-reported outcomes after rehabilitation and surgery for cuff tear are also variable. There is supportive evidence for the role of genetic variants in predicting treatment outcomes, but this has not been well-studied. Our research team is recruiting for a 12-site, NIH- and PCORI-funded, clinical trial of 700 patients randomized to arthroscopic surgery versus physical therapy for atraumatic cuff tears called Arthroscopic Rotator Cuff (ARC). This provides a unique opportunity to leverage our existing infrastructure and recruit 2,500 patients in an imaging-verified, case-control study on the genetics of cuff tears. We have developed standardized approaches to ascertain image-verified cases and controls using electronic health record (EHR) data. By applying these standardized approaches to EHR-linked biorepositories at Vanderbilt (BioVU) and Kaiser Permanente (GERA), each with approximately 100,000 genotyped individuals, and by collaborating with investigators from Utah and Stanford who are leaders in the only two existing GWAS of cuff tear, we have convened the largest consortium (cuffGEN) to study the genetics of rotator cuff disorders. We will perform one-of-a-kind GWAS investigations with well-classified discovery and replication samples of 5,000 imaging- verified rotator cuff tear cases and 5,000 imaging-verified controls. This well-designed study will identify associations between genetic variants and cuff tears, FI, and optimal patient-reported outcomes after surgery or rehabilitative treatments. We will prioritize gene discovery by incorporating gene-expression data from adipose and muscle using reference databases with GWAS results. Through Mendelian randomization, our study will clarify if there is a causal relationship between obesity and FI. The proposed study allows NIH funds to leverage existing infrastructure without which this large genetic study would be difficult. Genetic profiling to assess intervention readiness and rehabilitation progress are NIH priorities which the proposed study will deliver upon. Data on genetic predisposition to cuff tear, FI, and optimal treatment outcomes will help in identifying high-risk individuals and developing optimal interventions based on an individual's genetic profile.