Genome-wide Prediction of Dementia in Parkinson Disease

帕金森病痴呆的全基因组预测 进展，而不是易感性，是患者幸福的主要决定因素。痴呆症是最常见的 帕金森氏症患者疾病进展的衰弱表现。它对治疗质量产生负面影响 生活，增加了照顾者的负担，增加了医疗费用。现有的治疗方法不能阻止从最初的下降 运动症状到认知障碍。恶化的速度在不同的患者之间有很大的不同 人们对此知之甚少。已经找到了有限的证据来证明两者之间的联系 预后和易感变异。我们的初步研究为不同的基因组座位提供了令人信服的证据 是记忆丧失的预兆。 我们假设，新的预后基因将有力地预测患者患帕金森氏症的风险 痴呆症。以前的全基因组关联研究是时间静态的、横断面的、病例对照的 不能解决时间维度对理解进展至关重要的研究。系统地解码 帕金森氏症认知进展的遗传结构，这里我们将进行无偏见的、纵向的 全基因组生存研究，对来自北美和欧洲的19个队列进行深度归因。更多 超过6000名帕金森氏症患者和超过5万名认知评估 采用COX比例风险模型和混合随机固定效应模型进行分析。在目标1中，我们将发现 与进展为帕金森氏病痴呆相关的新基因座。在目标2中，我们将复制和验证 在一个独立的种群中转发遗传变异。在目标3中，我们将构建并测试一个多功能多基因 危险评分，以准确预测未来认知能力下降的风险。 本研究旨在阐明帕金森氏病痴呆的进展基因，改善临床 预测和改变临床试验设计。基因驱动因素将指向一种独特的认知生物学 下降，这可能会启发新的治疗方向。

Genome-wide Prediction of Dementia in Parkinson's Disease Progression, not susceptibility, is the major determinant of patients' well-being. Dementia is one of the most debilitating manifestations of disease progression in patients with Parkinson's. It negatively impacts quality of life, burdens caregivers and increases health costs. Existing therapies cannot prevent the decline from initial motor symptoms to cognitive impairment. The pace of deterioration varies dramatically between patients for reasons that are poorly understood. Limited evidence has been found for a proposed association between prognosis and susceptibility variants. Our initial studies provide compelling evidence for distinct genome loci predictive of memory loss. We hypothesize that novel prognosis loci will powerfully predict a patient's risk for developing Parkinson's disease dementia. Previous genome-wide association studies were time-static, cross-sectional, case-control studies that cannot address the time dimension critical for understanding progression. To systematically decode the genetic architecture of cognitive progression in Parkinson's, here we will perform an unbiased, longitudinal genome-wide survival study with deep imputation of nineteen cohorts from North America and Europe. More than six thousand patients with Parkinson’s disease and over fifty thousand cognitive assessments will be analyzed using Cox proportional hazards and mixed random and fixed effect models. In Aim 1, we will discover novel loci associated with progression to Parkinson's disease dementia. In Aim 2, we will replicate and verify forwarded genetic variants in an independent population. In Aim 3, we will build and test a versatile Polygenic Hazard Score to accurately forecast risk of future cognitive decline. This study is poised to elucidate progression loci for Parkinson’s disease dementia, improve clinical prognostication, and transform clinical trial design. The genetic drivers will point to a distinct biology of cognitive decline that could inspire new therapeutic directions.