Anatomical categorization of isolated non-focal dystonia: novel and existing patterns using a data-driven approach

According to expert consensus, dystonia can be classified as focal, segmental, multifocal, and generalized, based on the affected body distribution. To provide an empirical and data-driven approach to categorizing these distributions, we used a data-driven clustering approach to compare frequency an...

Full description

Saved in:

Bibliographic Details
Published in:	Dystonia Vol. 2
Main Authors:	Younce, J R, Cascella, R H, Berman, B D, Jinnah, H A, Bellows, S, Feuerstein, J, Wagle Shukla, A, Mahajan, A, Chang, F C F, Duque, K R, Reich, S, Richardson, S Pirio, Deik, A, Stover, N, Luna, J M, Norris, S A
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media S.A 01-01-2023
Subjects:	clustering dystonia Dystonia Coalition non-focal segmental clustering Dystonia Coalition dystonia non-focal segmental
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	According to expert consensus, dystonia can be classified as focal, segmental, multifocal, and generalized, based on the affected body distribution. To provide an empirical and data-driven approach to categorizing these distributions, we used a data-driven clustering approach to compare frequency and co-occurrence rates of non-focal dystonia in pre-defined body regions using the Dystonia Coalition (DC) dataset. We analyzed 1,618 participants with isolated non-focal dystonia from the DC database. The analytic approach included construction of frequency tables, variable-wise analysis using hierarchical clustering and independent component analysis (ICA), and case-wise consensus hierarchical clustering to describe associations and clusters for dystonia affecting any combination of eighteen pre-defined body regions. Variable-wise hierarchical clustering demonstrated closest relationships between bilateral upper legs (distance = 0.40), upper and lower face (distance = 0.45), bilateral hands (distance = 0.53), and bilateral feet (distance = 0.53). ICA demonstrated clear grouping for the a) bilateral hands, b) neck, and c) upper and lower face. Case-wise consensus hierarchical clustering at k = 9 identified 3 major clusters. Major clusters consisted primarily of a) cervical dystonia with nearby regions, b) bilateral hand dystonia, and c) cranial dystonia. Our data-driven approach in a large dataset of isolated non-focal dystonia reinforces common segmental patterns in cranial and cervical regions. We observed unexpectedly strong associations between bilateral upper or lower limbs, which suggests that symmetric multifocal patterns may represent a previously underrecognized dystonia subtype.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 BB, HJ, SB, JF, AW, AM, FC, KD, SR, SP, AD, NS, and SAN: recruitment, subject assessments, data collection. JRY, RC, JL, and SAN: Statistical analysis design and execution. JRY, RC, and SAN: drafting of manuscript. All authors contributed to the article and approved the submitted version. Author contributions
ISSN:	2813-2106 2813-2106
DOI:	10.3389/dyst.2023.11305