Early recognition and diagnosis of multiple system atrophy: best practice and emerging concepts

ABSTRACT

Introduction: Multiple system atrophy (MSA) is a progressive degenerative disorder of the central and autonomic nervous systems characterized by parkinsonism, cerebellar ataxia, dysautonomia, and pyramidal signs. The confirmatory diagnosis is pathological, but clinical-diagnostic criteria have been developed to help clinicians. To date, the early diagnosis of MSA is challenging due to the lack of reliable diagnostic biomarkers.

Areas covered: The authors reappraised the main clinical, neurophysiological, imaging, genetic, and laboratory evidence to help in the early diagnosis of MSA in the clinical and in the research settings. They also addressed the practical clinical issues in the differential diagnosis between MSA and other parkinsonian and cerebellar syndromes. Finally, the authors summarized the unmet needs in the early diagnosis of MSA and proposed the next steps for future research efforts in this field.

Expert opinion: In the last decade, many advances have been achieved to help the correct MSA diagnosis since early stages. In the next future, the early diagnosis and correct classification of MSA, together with a better knowledge of the causative mechanisms of the disease, will hopefully allow the identification of suitable candidates to enroll in clinical trials and select the most appropriate disease-modifying strategies to slow down disease progression.

KEYWORDS:

• Multiple system atrophy
• atypical parkinsonian syndromes
• diagnosis
• neuroimaging
• biomarkers

Article highlights

• Clinical consensus criteria for MSA should be revised to improve the sensitivity and specificity of the early diagnosis. Correspondingly, ‘red flags’ and early dysautonomic features as OH and urinary symptoms are essential clues to increase the possibility of a correct diagnosis of MSA.

• Neurophysiological tests are helpful in detecting dysautonomia early in the disease course. In the research setting, technological advances will allow the measurement of neurophysiological phenomena as the startle reflex or the kinematic analysis of finger tapping during the clinical routine and not only in dedicated laboratories.

• The development of machine-learning-based algorithms for neuroimaging will allow diagnosing MSA with better approximation in the next few years. FDG-PET and MIBG SPECT are promising techniques for the correct diagnosis of MSA, but their broad diffusion is currently limited to their high cost.

• Genetic analyses on comprehensive, multi-centric, international, well-characterized, longitudinal cohorts should be performed to clarify the role of some putative genes in the pathogenesis of MSA. Similarly, fluid and tissue biomarker development is required to increase the diagnostic accuracy in the early disease stages in MSA patients.

Declaration of interest

L Marsili received honoraria from the International Association of Parkinsonism and Related Disorders (IAPRD) Society for social media and web support. C Colosimo has received grants from Abbvie, BIAL, Ipsen and Zambon unrelated to the present research. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or conflict with the subject matter or materials discussed in this manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgments

The authors thank the native English speaker who provided the language editing of the manuscript, and we respect her/his wishes to remain anonymous.

Additional information

Funding

This paper was not funded.