Literature DB >> 19211293

Multiple step pattern as a biomarker in Parkinson disease.

Tanya Blekher1, Marjorie Weaver, Jason Rupp, William C Nichols, Siu L Hui, Jacqueline Gray, Robert D Yee, Joanne Wojcieszek, Tatiana Foroud.   

Abstract

OBJECTIVE: To evaluate quantitative measures of saccades as possible biomarkers in early stages of Parkinson disease (PD) and in a population at-risk for PD.
METHODS: The study sample (n=68) included mildly to moderately affected PD patients, their unaffected siblings, and control individuals. All participants completed a clinical evaluation by a movement disorder neurologist. Genotyping of the G2019S mutation in the LRRK2 gene was performed in the PD patients and their unaffected siblings. A high resolution, video-based eye tracking system was employed to record eye positions during a battery of visually guided, anti-saccadic (AS), and two memory-guided (MG) tasks. Saccade measures (latency, velocity, gain, error rate, and multiple step pattern) were quantified.
RESULTS: PD patients and a subgroup of their unaffected siblings had an abnormally high incidence of multiple step patterns (MSP) and reduced gain of saccades as compared with controls. The abnormalities were most pronounced in the more challenging version of the MG task. For this task, the MSP measure demonstrated good sensitivity (87%) and excellent specificity (96%) in the ability to discriminate PD patients from controls. PD patients and their siblings also made more errors in the AS task.
CONCLUSIONS: Abnormalities in eye movement measures appear to be sensitive and specific measures in PD patients as well as a subset of those at-risk for PD. The inclusion of quantitative laboratory testing of saccadic movements may increase the sensitivity of the neurological examination to identify individuals who are at greater risk for PD.

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Year:  2009        PMID: 19211293      PMCID: PMC2872983          DOI: 10.1016/j.parkreldis.2009.01.002

Source DB:  PubMed          Journal:  Parkinsonism Relat Disord        ISSN: 1353-8020            Impact factor:   4.891


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