Pro-saccades predict decline in attention over 18 months in newly diagnosed Parkinson’s disease Samuel Stuart, Lisa Alcock, Jeremy Nell, Rachael A Lawson, Rosie Morris, Alison J Yarnall, David Burn and Lynn Rochester Institute of Neuroscience/Newcastle University Institute of Ageing, Newcastle University http://research.ncl.ac.uk/bam |
@BAM_Research
Introduction
Results
• Cognitive impairments, such as attentional decline and fluctuation, are common in PD and impact saccadic eye-movements [1].
•
• Accuracy, control and speed of saccades have been linked to cognitive processes, primarily attention [2].
•
• Saccades may therefore be an important and useful non-invasive biomarker for cognitive decline or dementia in PD. Aims: 1)To investigate pro-saccades in a newly diagnosed cohort of Parkinson’s disease (PD) compared to healthy older adult controls at baseline 2)To examine whether baseline pro-saccades can predict attentional decline over 18 months better than traditional computerised testing in PD and controls
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was true for controls (Table 2).
Change in Fluctuating Attention (CV)
Controls Mean (SD)
PD Mean (SD)
P
Latency (ms)
245.2 (62.4)
259.2 (64.6)
.161
Duration (ms)
54.4 (7.3)
52.3 (7.1)
.067
Amplitude (°)
10.8 (2.0)
10.0 (2.2)
.019*
Peak Velocity (°/sec)
403.6 (98.8)
405.5 (114.2)
.909
Average Velocity (°/sec)
204.8 (48.2)
196.7 (51.9)
.310
0.4 Series1 0.3 Linear (Series1) 0.2 0.1 0 -0.1 -0.2 0
10 20 30 40 50 Baseline Pro-saccade Duration (CV)
Table 2 Predictors of Change in Fluctuating Attention in controls (n=71) R2
R2
β
P
ANOVA ANOVA
Baseline FA
.252
.244
-.514
.000
F
p
5.556
.001
Baseline Saccade Duration CV (ms)
References [1] Antoniades, C.A., Demeyere, N., Kennard, C., Humphreys, G.W. and Hu, M.T. (2015) 'Antisaccades and executive dysfunction in early drugnaive Parkinson's disease: The discovery study', Movement Disorders, 30(6), pp. 843-847.
Series1 0.3 Linear (Series1) 0.2 0.1
[2] Ballanger, B. (2009) 'Top-down control of saccades as part of a generalized model of proactive inhibitory control', J Neurophysiol, 102(5), pp. 2578-80.
0 -0.1 -0.2 0
10 20 30 40 50 Baseline Pro-saccade Duration (CV)
60
Fig 3 Correlation between Change in Fluctuating Attention over 18months and Baseline Prosaccade duration in Parkinson’s disease
Table 3 Predictors of Change in Fluctuating Attention in Parkinson’s disease (n=97) Predictor
R2
R2
β
P
ANOVA ANOVA
Change Baseline FA
F
p
.058
.001
-.034 .760
1.113
.359
.134
.086
.282
2.781
.022
Baseline Saccade
.068
[Controlled for Age, Sex, NART]
C
• Saccadometry is a quick, non-invasive and inexpensive tool for saccadic measurement that can be used within clinical settings.
0.4
60
Fig 2 Correlation between Change in Fluctuating Attention over 18months and Baseline Pro-saccade duration in controls
Change
B
• Therefore, saccades are a feasible biomarker of attentional decline in PD, which may be useful for early cognitive impairment diagnosis and intervention.
Table 1 Pro-saccade characteristics at baseline (diagnosis) in controls and Parkinson's
Predictor
A
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• Pro-saccades are impaired in PD compared to controls Pro-saccades were significantly impaired in PD compared to controls at baseline (e.g. at baseline. amplitude; p=.019, Table 1). Increased FA over 18 months was associated with more variable pro-saccade duration (CV) • Baseline pro-saccade duration (CV) rather than baseline at baseline in PD (r=.30, p=.003) and controls (r=.24, p=.046). FA (measured with a computerised battery) was a Pro-saccade duration (CV) was then entered into a regression model and was an significant predictor of change in FA (increased independent predictor of change in FA (CV) in PD (Table 3), but not controls. variability) over 18 months in PD, but not in controls. Conversely, baseline FA was unable to predict change in FA in PD, whereas the opposite
Methods • Pro-saccades were recorded using a saccadometer (Ober consulting) in 97 newly diagnosed people with PD and 71 healthy older adult controls at baseline, as part of the ICICLE-PD and ICICLE-GAIT studies. • Pro-saccade characteristics included latency, duration, amplitude, average and peak velocity. • Attention (power of attention and fluctuating attention (FA)) were assessed using a computerised battery (Cognitive Drug Research battery). • Independent t-tests compared pro-saccade characteristics in PD and controls. • Coefficient of variation (CV) was calculated as standard deviation divided by mean. • Scatterplots and linear multiple regression (controlling for age, sex, education and change in levodopa) assessed predictive value of baseline pro-saccades in relation to change in FA over 18months.
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Conclusion
Change in Fluctuating Attention (CV)
• Saccadic deficits have also been linked to poor mobility and may impact falls risk [3].
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.012
.250
.042
1.208
.316
.006
Duration CV (ms) [Controlled for Age, Sex, NART, Change in LED from baseline to 18months]
[3] Stuart, S., Lord, S., Hill, E. and Rochester, L. (2016) 'Gait in Parkinson’s disease: A visuo-cognitive challenge', Neuroscience & Biobehavioral Reviews, 62, pp. 76-88.
Acknowledgements ICICLE-GAIT is supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Unit based at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. ICICLE-PD is supported by Parkinson's UK. The research was also supported by NIHR Newcastle CRF Infrastructure funding. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
Fig 1 Saccadometer [A = Front view, B = Side view, C = Hand-held recording device]
Presented at International Congress of Parkinson’s disease and Movement Disorders, Vancouver, BC, Canada. June 4-8, 2017
