Genetic and Non-Genetic Risk Factors for Rotator Cuff Disease

1项目摘要/摘要： 2退行性肩袖疾病是导致肩部残疾和肩部损伤的最常见原因。 3导致比身体其他部位更长的中位数休假天数。肩袖手术率也是 4增加，导致医疗保健系统负担沉重。考虑到高成本和高发病率， 5有症状的肩袖疾病，重要的是准确识别高危亚组，以使 6.预防工作。这需要了解重要的风险因素以及创建和验证 7大型前瞻性研究中的预测模型。亚尼克博士的首要职业目标是发现新的见解 8研究肩袖疾病的病因和进展，可以直接为临床决策和 9预防途径。在目前的研究中，她假设遗传和职业因素 10对症状性肩袖疾病的发生有重要作用，这些因素 11结合已知的危险因素可以准确预测未来的疾病风险。具体地说，亚尼克博士提议 12项研究的目的是：1)确定遗传标记与有症状的肩袖疾病风险的关联， 13 2)阐明职业性上肢需求与 14)症状性肩袖疾病风险；3)建立症状性肩袖疾病预测模型 15个风险因素包括遗传和非遗传风险因素。为了实现这些目标，亚尼克博士将利用英国 16 Biobank，一个由500,182人组成的基于人群的大型预期队列，拥有广泛的数据 17个人口统计数据、行为、职业、医院诊断(包括3,500个症状性肩袖疾病 18个诊断)，以及800,000个遗传标记的完整的基因信息。亚尼克博士是唯一有资格 19从事这一领域的研究，因为她在流行病学方法方面接受了广泛的培训，并有经验 20利用各种数据资源解决独特的研究问题。然而，成功的执行 21.这项研究和对未来研究的有效规划将需要在以下领域进行额外培训： 22 1)肩袖病的病理生物学和临床护理，2)统计遗传学和遗传流行病学，3) 23.职业健康和职业暴露评估；4)专业技能； 24流行病学、研究交流和领导力。亚尼克博士的指导团队由杰伊·基纳博士领导， 25岁，高度致力于将她发展成为一名成功的独立调查员。她的研究领域有一个 26潜在影响的数量。肩袖疾病重要遗传标记的发现将 27允许更集中地观察具有更详细临床资料的队列中的遗传易感性的具体测量 28信息，而确定职业风险可导致确定可改变的危险行为。 29最后，结合了这些风险因素的预测模型可以被调整，以帮助识别处于高风险状态的个人。 30在不同的环境中有撕裂的风险，可以帮助预防工作和临床决策。

1 Project Summary/Abstract: 2 Degenerative rotator cuff disease is the most frequent cause of shoulder disability, and injuries of the shoulder 3 lead to higher median days away from work than any other body part. Rotator cuff surgery rates are also 4 increasing, leading to significant burdens on the healthcare system. Given the high costs and morbidity of 5 symptomatic rotator cuff disease, it will be important to identify high-risk subgroups accurately to enable 6 prevention efforts. This requires knowledge of important risk factors as well as the creation and validation of 7 predictive models in large, prospective studies. Dr. Yanik’s overarching career goal is to discover new insights 8 into the etiology and progression of rotator cuff disease that can directly inform clinical decision-making and 9 prevention approaches. For the present study, she hypothesizes that genetic and occupational factors 10 contribute significantly to the development of symptomatic rotator cuff disease, and that these factors 11 combined with known risk factors can accurately predict future disease risk. Specifically, Dr. Yanik’s proposed 12 research aims are to: 1) determine associations of genetic markers with symptomatic rotator cuff disease risk, 13 2) elucidate the magnitude of the association between occupational upper extremity demands and 14 symptomatic rotator cuff disease risk, and 3) develop a prediction model for symptomatic rotator cuff disease 15 risk including genetic and non-genetic risk factors. To accomplish these aims, Dr. Yanik will use the UK 16 Biobank, a large prospective, population-based cohort of 500,182 people with extensive data on 17 demographics, behaviors, occupations, hospital diagnoses (including >3,500 symptomatic rotator cuff disease 18 diagnoses), and complete genotype information for >800,000 genetic markers. Dr. Yanik is uniquely qualified 19 to pursue this line of research, as she has extensive training in epidemiologic methods and has experience 20 using a diverse array of data resources to address unique research questions. However, successful execution 21 of this research and effective planning for future research will require additional training in the following areas: 22 1) the pathobiology and clinical care of rotator cuff disease, 2) statistical genetics and genetic epidemiology, 3) 23 occupational health and occupational exposure assessment, and 4) professional skills in grantsmanship, 24 epidemiology, research communication, and leadership. Dr. Yanik’s mentoring team, led by Dr. Jay Keener, is 25 highly committed to her development as a successful independent investigator. Her line of research has a 26 number of potential implications. The discovery of important genetic markers for rotator cuff disease would 27 allow a more focused look at specific measures of genetic susceptibility in cohorts with more detailed clinical 28 information, while determining occupational risks could lead to the identification of modifiable risk behaviors. 29 Finally, prediction models incorporating these risk factors can be adapted to help identify individuals at high- 30 risk for tears in various settings and could aid both prevention efforts and clinical decision-making.