Structural white matter networks in myotonic dystrophy type 1.

Maud Van Dorst,Roy P.C Kessels,Joost Raaphorst,Anil M Tuladhar,Darren G Monckton,Kees Okkersen,Baziel G.M Van Engelen,Frederick J.A Meijer

doi:10.1016/j.nicl.2018.101615

Abstract

The myriad of neuropsychiatric manifestations reported in myotonic dystrophy type 1 may have its origin in alterations of complex brain network interactions at the structural level. In this study, we tested the hypothesis that altered white matter microstructural integrity and network organisation were present in a cohort of individuals with DM1 compared to unaffected controls, which was expected to be associated with CNS related disease manifestations of DM1. We performed a cross-sectional neuropsychological assessment and brain MRI in 25 myotonic dystrophy type 1 (DM1) patients and 26 age, sex and educational level matched unaffected controls. Patients were recruited from the Dutch cohort of the OPTIMISTIC study, a concluded trial which had included ambulant, genetically confirmed DM1 patients who were severely fatigued. We applied graph theoretical analysis on structural networks derived from diffusion tensor imaging (DTI) data and deterministic tractography to determine global and local network properties and performed group-wise comparisons. Furthermore, we analysed the following variables from structural MRI imaging: semi-quantitative white matter hyperintensity load andwhite matter tract integrity using tract-based spatial statistics (TBSS). Structural white matter networks in DM1 were characterised by reduced global efficiency, local efficiency and strength, while the network density was compatible to controls. Other findings included increased white matter hyperintensity load, and diffuse alterations of white matter microstructure in projection, association and commissural fibres. DTI and network measures were associated (partial correlations coefficients ranging from 0.46 to 0.55) with attention (d2 Test), motor skill (Purdue Pegboard test) and visual-constructional ability and memory (copy subtest of the Rey-Osterrieth Complex Figure Test). DTI and network measures were not associated with clinical measures of fatigue (checklist individual strength, fatigue subscale) or apathy (apathy evaluation scale – clinician version). In conclusion, our study supports the view of brain involvement in DM1 as a complex network disorder, characterised by white matter network alterations that may have relevant neuropsychological correlations. This work was supported by the European Community's Seventh Framework Programme (FP7/2007–2013; grant agreement n° 305,697) and the Marigold Foundation.

Highlights

Myotonic dystrophy type 1 (DM1) is an hereditary chronic progressive multisystem disorder with autosomal dominant inheritance. (Bird, 1993) Clinical features of central nervous system (CNS) involvement in DM1 include cognitive deficits, psychiatric and behaviour disturbances such as apathy, fatigue, and excessive daytime sleepiness
We tested the hypothesis that altered white matter microstructural integrity and network organisation were present in a cohort of individuals with DM1 compared to unaffected controls, which was expected to be associated with CNS related disease manifestations of DM1
These CNS symptoms are critical determinants of quality of life in DM1, and some may be amenable to treatment. (Antonini et al, 2006; Gagnon et al, 2008; Laberge et al, 2013; Okkersen et al, 2018) The broad spectrum of clinical CNS involvement in DM1 is corroborated by a variety of structural brain imaging abnormalities that are widely dispersed throughout the brain, with apparently little anatomical specificity.(Cabada et al, 2017; Okkersen et al, 2017b; Sugiyama et al, 2017) In particular, white matter involvement encompasses a combination increased white matter hyperintensity load and decreased microstructural integrity of white matter based on diffusion tensor imaging (DTI) studies.(Minnerop et al, 2011; Zanigni et al, 2016)

Summary

Introduction

Myotonic dystrophy type 1 (DM1) is an hereditary chronic progressive multisystem disorder with autosomal dominant inheritance. (Bird, 1993) Clinical features of central nervous system (CNS) involvement in DM1 include cognitive deficits, psychiatric and behaviour disturbances such as apathy, fatigue, and excessive daytime sleepiness. (Bird, 1993) Clinical features of central nervous system (CNS) involvement in DM1 include cognitive deficits, psychiatric and behaviour disturbances such as apathy, fatigue, and excessive daytime sleepiness. (Antonini et al, 2006; Gagnon et al, 2008; Laberge et al, 2013; Okkersen et al, 2018) The broad spectrum of clinical CNS involvement in DM1 is corroborated by a variety of structural brain imaging abnormalities that are widely dispersed throughout the brain, with apparently little anatomical specificity.(Cabada et al, 2017; Okkersen et al, 2017b; Sugiyama et al, 2017) In particular, white matter involvement encompasses a combination increased white matter hyperintensity load and decreased microstructural integrity of white matter based on diffusion tensor imaging (DTI) studies.(Minnerop et al, 2011; Zanigni et al, 2016). Given the exceptionally large clinical variability of the disease, in which the genetic defect exerts heterogeneous downstream effects in virtually all cells of many different tissue types, these diverse and widely dispersed structural imaging changes may come as no surprise. (Harper, 2001) Despite the many structural imaging changes, attempts at correlation with neuropsychological performance and other CNS features have given inconsistent results.(Cabada et al, 2017; Minnerop et al, 2011) Partly, this is explained by the variability of the disease in combination with limited sample sizes.(Okkersen et al, 2017a) cognitive and behavioural functions are not strictly anatomically localised in particular brain regions, but have their origin in complex network interactions.(Bressler and Menon, 2010; Wang et al, 2015) In this respect, structural network analysis of white matter changes may improve understanding of brain dysfunction in complex neurological disorders with diffuse structural alterations, such as DM1.(Stam, 2014) Structural connectivity of a network, consisting of brain regions (nodes) and connecting white matter tracts (edges), can be obtained using analysis of DTI followed by tractography.(Yan et al, 2011; Zalesky et al, 2011) Graph theory, a branch of modern network theory, can subsequently be used to characterise the properties of the network organisation.(Bullmore and Sporns, 2009) Previous research in diseases that, like DM1, have prominent white matter involvement (i.e., cerebral small-vessel disease) showed that white matter network alterations were an independent predictor of cognitive dysfunction and a more sensitive measure than traditional magnetic resonance imaging (MRI) measures.(Lawrence et al, 2014; Tuladhar et al, 2016) In this study, we tested the hypothesis that altered white matter microstructural integrity and network organisation was present in a cohort of individuals with DM1 compared to unaffected controls, which was expected to be associated with CNS related disease manifestations of DM1

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