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PREDICT-PD:一种前瞻性识别帕金森病风险指标的在线方法。

PREDICT-PD: An online approach to prospectively identify risk indicators of Parkinson's disease.

作者信息

Noyce Alastair J, R'Bibo Lea, Peress Luisa, Bestwick Jonathan P, Adams-Carr Kerala L, Mencacci Niccolo E, Hawkes Christopher H, Masters Joseph M, Wood Nicholas, Hardy John, Giovannoni Gavin, Lees Andrew J, Schrag Anette

机构信息

University College London Institute of Neurology, University College London, London, UK.

Barts and the London School of Medicine and Dentistry, Queen Mary University, London, UK.

出版信息

Mov Disord. 2017 Feb;32(2):219-226. doi: 10.1002/mds.26898. Epub 2017 Jan 16.

Abstract

BACKGROUND

A number of early features can precede the diagnosis of Parkinson's disease (PD).

OBJECTIVE

To test an online, evidence-based algorithm to identify risk indicators of PD in the UK population.

METHODS

Participants aged 60 to 80 years without PD completed an online survey and keyboard-tapping task annually over 3 years, and underwent smell tests and genotyping for glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 (LRRK2) mutations. Risk scores were calculated based on the results of a systematic review of risk factors and early features of PD, and individuals were grouped into higher (above 15th centile), medium, and lower risk groups (below 85th centile). Previously defined indicators of increased risk of PD ("intermediate markers"), including smell loss, rapid eye movement-sleep behavior disorder, and finger-tapping speed, and incident PD were used as outcomes. The correlation of risk scores with intermediate markers and movement of individuals between risk groups was assessed each year and prospectively. Exploratory Cox regression analyses with incident PD as the dependent variable were performed.

RESULTS

A total of 1323 participants were recruited at baseline and >79% completed assessments each year. Annual risk scores were correlated with intermediate markers of PD each year and baseline scores were correlated with intermediate markers during follow-up (all P values < 0.001). Incident PD diagnoses during follow-up were significantly associated with baseline risk score (hazard ratio = 4.39, P = .045). GBA variants or G2019S LRRK2 mutations were found in 47 participants, and the predictive power for incident PD was improved by the addition of genetic variants to risk scores.

CONCLUSIONS

The online PREDICT-PD algorithm is a unique and simple method to identify indicators of PD risk. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

摘要

背景

帕金森病(PD)诊断之前会出现一些早期特征。

目的

测试一种基于证据的在线算法,以识别英国人群中PD的风险指标。

方法

年龄在60至80岁且无PD的参与者在3年中每年完成一项在线调查和按键任务,并接受嗅觉测试以及针对葡萄糖脑苷脂酶(GBA)和富含亮氨酸重复激酶2(LRRK2)突变的基因分型。基于对PD风险因素和早期特征的系统评价结果计算风险评分,并将个体分为高风险组(高于第15百分位数)、中风险组和低风险组(低于第85百分位数)。将先前定义的PD风险增加指标(“中间标志物”),包括嗅觉减退、快速眼动睡眠行为障碍和手指敲击速度,以及新发PD作为研究结果。每年并前瞻性地评估风险评分与中间标志物的相关性以及个体在风险组之间的变动情况。以新发PD作为因变量进行探索性Cox回归分析。

结果

共有1323名参与者在基线时被招募,每年>79%的参与者完成评估。每年的风险评分与每年的PD中间标志物相关,基线评分与随访期间的中间标志物相关(所有P值<0.001)。随访期间的新发PD诊断与基线风险评分显著相关(风险比=4.39,P=0.045)。在47名参与者中发现了GBA变异或G2019S LRRK2突变,将基因变异添加到风险评分中可提高对新发PD的预测能力。

结论

在线PREDICT-PD算法是一种独特且简单的识别PD风险指标的方法。©2017作者。《运动障碍》由Wiley Periodicals, Inc.代表国际帕金森和运动障碍协会出版。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23a5/5324558/bb77e4173168/MDS-32-219-g001.jpg

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