Cortical sensorimotor alterations classify clinical phenotype and putative genotype of spasmodic dysphonia

Abstract

Background and purpose: Spasmodic dysphonia (SD), or laryngeal dystonia, is a task-specific isolated focal dystonia of unknown causes and pathophysiology. Although functional and structural abnormalities have been described in this disorder, the influence of its different clinical phenotypes and genotypes remains scant, making it difficult to explain SD pathophysiology and to identify potential biomarkers.

Methods: We used a combination of independent component analysis and linear discriminant analysis of resting-state functional magnetic resonance imaging data to investigate brain organization in different SD phenotypes (abductor versus adductor type) and putative genotypes (familial versus sporadic cases) and to characterize neural markers for genotype/phenotype categorization.

Results: We found abnormal functional connectivity within sensorimotor and frontoparietal networks in patients with SD compared with healthy individuals as well as phenotype- and genotype-distinct alterations of these networks, involving primary somatosensory, premotor and parietal cortices. The linear discriminant analysis achieved 71% accuracy classifying SD and healthy individuals using connectivity measures in the left inferior parietal and sensorimotor cortices. When categorizing between different forms of SD, the combination of measures from the left inferior parietal, premotor and right sensorimotor cortices achieved 81% discriminatory power between familial and sporadic SD cases, whereas the combination of measures from the right superior parietal, primary somatosensory and premotor cortices led to 71% accuracy in the classification of adductor and abductor SD forms.

Conclusions: Our findings present the first effort to identify and categorize isolated focal dystonia based on its brain functional connectivity profile, which may have a potential impact on the future development of biomarkers for this rare disorder.

Keywords: dystonia; imaging marker; resting-state networks.

© 2016 EAN.

Figures

Figure 1. Sensorimotor functional network alteration assessed using independent component analysis (ICA)

Panel (A) shows the sensorimotor network extracted across all SD patients and controls. Voxel-based inferential statistics were used to compare (B-I) all SD patients vs. healthy controls, (B-II) sporadic vs. familial SD patients, and (B-III) ADSD vs. ABSD patients. Statistical maps are superimposed on a series of axial slices of the standard brain in Talairach-Tournoux space. The color bars represent Z scores for independent components and t scores for group statistical comparisons (p ≤ 0.01, FWE-corrected). AB – abductor SD patients; AD – adductor SD patients; FM – familial SD patients; HV – healthy control volunteers; PT – patients; SD – spasmodic dysphonia; SP – sporadic SD patients.

Figure 2. Frontoparietal functional network alteration assessed using independent component analysis (ICA)

Panel (A) shows the frontoparietal network extracted across all SD patients and controls. Voxel-based inferential statistics were used to compare (B-I) all SD patients vs. healthy volunteers, and (B-II) sporadic vs. familial SD patients. Statistical maps are superimposed on a series of axial slices of the standard brain in Talairach-Tournoux space. The color bars represent Z scores for independent components and t scores for group statistical comparisons (p ≤ 0.01, FWE-corrected). FM – familial SD patients; HV – healthy control volunteers; PT – patients; SD – spasmodic dysphonia; SP – sporadic SD patients.

Figure 3. Results of the linear discriminant analysis of (I) SD patients vs healthy volunteers, (II) sporadic vs familial SD patients, and (III) ADSD vs ABSD patients

The scatter plots show the individual combinations of the mean values of the Z score within (I) the left sensorimotor and the left inferior parietal cortices in patients (gray circles for correct classification and gray triangles for misclassification of patients) and healthy volunteers (empty circles for correct classification and empty triangles for misclassified helthy volunteers); (II) the left inferior parietal lobule, right somatosensory, and left sensorimotor cortices in sporadic SD (empty circles for correct classification and empty triangles for misclassification of sporadic patients) and familial SD (gray circles for correct classification and gray triangles for misclassification of familial patients); (III) the right superior parietal lobule, somatosensory and premotor cortices in ABSD (gray circles for correct classification and gray triangles for ABSD patients misclassified) and ADSD (empty circles for correct classification and empty triangles for misclassified ADSD) patients. The red line (I) and red planes (II and III) represent the decision boundary of the classification. The corresponding values are provided in Table 3. AB – abductor SD patients; AD – adductor SD patients; FM – familial SD patients; HV – healthy control volunteers; PT – patients; SP – sporadic SD patients.