Gray Matter Atrophy to Explain Subclinical Oculomotor Deficit in Multiple Sclerosis

Abstract

Eye movement deficits are frequently noted in multiple sclerosis during bedside clinical examination, but subtle dysfunction may remain undetected and might only be identified with advanced approaches. While classical neurology provides insight into the complex functional anatomy of oculomotor functions, little is known about the structural background of this dysfunction in MS. Thirty four clinically stable, treated relapsing-remitting MS patients with mild disability and 34 healthy controls were included in our study. Group difference and correlation with clinical parameters were analyzed in case of the latency, peak-velocity, gain, dysconjugacy index, and performance during a saccade and anti-saccade task. High-resolution T1 weighted, T2 FLAIR, and double inversion recovery images were acquired on 3T to evaluate the correlation between behavioral and MRI parameters, such as T2 lesion and T1 black-hole burden, global brain, gray, and white matter atrophy. VBM style analysis was used to identify the focal gray matter atrophy responsible for oculomotor dysfunction. Significantly increased latency in the prosaccade task and significantly worse performance in the anti-saccade task were found in MS patients. The detailed examination of conjugated eye movements revealed five subclinical internuclear ophthalmoparesis cases. The peak velocity and latency of the anti-saccade movement correlated with the number of black holes, but none of the eye movement parameters were associated with the T2 lesion burden or location. Global gray matter volume correlated with saccade and anti-saccade latency, whereas white matter and total brain volume did not. Local gray matter atrophy in the left inferio-parietal lobule and temporo-occipital junction correlated with anti-saccade peak velocity. Our results show that neurodegeneration-like features of the MRI (black-hole, gray matter atrophy) are the best predictors of eye movement deficit in MS. Concurring with the clinico-radiological paradox, T2 lesion burden cannot explain the behavioral results. Importantly, anti-saccade peak velocity correlates with gray matter atrophy in the left parietal regions, which are frequently implicated in attention tasks.

Keywords: anti-saccade; atrophy; black hole; multiple sclerosis; prosaccade.

Figure 1

Mean and ±SEM of latency in different conditions of the left eye in the saccade task. Significant group difference is marked with an asterisk (*). The mean and standard error from the left-upper part of the figure were the following: 198(±5)ms vs. 221(±7)ms (abduction+long), 206(±5)ms vs. 224(±7)ms (adduction+long), 183(±4)ms vs. 197(±6)ms (abduction+short), 188(±5)ms vs. 200(±6)ms (adduction+short) for HC and MS, respectively.

Figure 2

Mean and ± SEM of peak velocity in different conditions of the left eye in the saccade task. Significant group* distance interaction is marked with an asterisk (*). The mean and standard error are the following from left to right: 379(±9)/s vs. 366(±8)/s (abduction+long), 266(±4)/s vs. 265(±4)/s (abduction+short), 389(±7)/s vs. 359(±12)/s (adduction+long), 269(±4)/s vs. 260(±7)/s (adduction+short) for HC and MS, respectively.

Figure 3

Mean and ± SEM of gain in different conditions of the left eye in the saccade task. Slight hypometria could be detected, however, this difference was not significant. Mean and standard error are the following from left to right: 0.935(±0.012) vs. 0.918(±0.11) (abduction+long), 0.929(±0.012) vs. 0.922(±0.011) (abduction+short), 0.926(±0.008) vs. 0.89(±0.011) (adduction+long), 0.938(±0.01) vs. (adduction+short) for HC and MS, respectively.

Figure 4

Mean ± SEM of anti-saccade performance in the two groups. Significant group difference is marked with an asterisk (*).

Figure 5

Z-scores of velocity dysconjugacy index individually, Subjects' value higher than the cut-off are labeled.

Figure 6

Antisaccade peak velocity of the left eye negatively correlated with black-hole count.

Figure 7

Results of VBM analysis. Marked voxels positively correlated with anti-saccade peak velocity. The error bar represents different Z-value after cluster based thresholding. Disease duration and age were used as cofounders.