Network correlates of disease severity in multiple system atrophy

K. L. Poston, C. C. Tang, T. Eckert, V. Dhawan, S. Frucht, J. P. Vonsattel, S. Fahn, D. Eidelberg

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

Objective: Multiple system atrophy (MSA), the most common of the atypical parkinsonian disorders, is characterized by the presence of an abnormal spatial covariance pattern in resting state metabolic brain images from patients with this disease. Nonetheless, the potential utility of this pattern as a MSA biomarker is contingent upon its specificity for this disorder and its relationship to clinical disability in individual patients. Methods: We used [18F]fluorodeoxyglucose PET to study 33 patients with MSA, 20 age- and severity-matched patients with idiopathic Parkinson disease (PD), and 15 healthy volunteers. For each subject, we computed the expression of the previously characterized metabolic covariance patterns for MSA and PD (termed MSARP and PDRP, respectively) on a prospective single-case basis. The resulting network values for the individual patients were correlated with clinical motor ratings and disease duration. Results: In the MSA group, disease-related pattern (MSARP) values were elevated relative to the control and PD groups (p < 0.001 for both comparisons). In this group, MSARP values correlated with clinical ratings of motor disability (r - 0.57, p - 0.0008) and with disease duration (r = -0.376, p = 0.03). By contrast, MSARP expression in the PD group did not differ from control values (p = 1.0). In this group, motor ratings correlated with PDRP (r = 0.60, p = 0.006) but not with MSARP values (p = 0.88). Conclusions: MSA is associated with elevated expression of a specific disease-related metabolic pattern. Moreover, differences in the expression of this pattern in patients with MSA correlate with clinical disability. The findings suggest that the MSARP may be a useful biomarker in trials of new therapies for this disorder.

Original languageEnglish
Pages (from-to)1237-1244
Number of pages8
JournalNeurology
Volume78
Issue number16
DOIs
StatePublished - 17 Apr 2012

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