Standardized description of rare diseases the natural course and treatment of metachromatic leukodystrophy

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1 Standardized description of rare diseases the natural course and treatment of metachromatic leukodystrophy Samuel Groeschel, Christiane Kehrer, Ingeborg Krägeloh-Mann Department of Paediatric Neurology and Developmental Medicine. University Children s Hospital. Tübingen, Germany. Corresponding author: Samuel Groeschel MD. Department of Paediatric Neurology and Developmental Medicine. University Children s Hospital. Hoppe-Seyler-Strasse Tübingen, Germany. Fax: / Samuel.Groeschel@med.uni-tuebingen.de Summary. Metachromatic leukodystrophy (MLD) is a rare neurometabolic disorder leading to demyelination and rapid neurological deterioration. As therapeutic options evolve, it seems essential to understand and quantify progression of the natural disease. In an ongoing nationwide study, we therefore established and validated standardized assessment tools and objectively described motor and cognitive function in children with MLD. Furthermore, we were able to systematically characterize the cerebral changes associated with MLD non-invasively using MRI. Both a visual MRI scoring system as well as a quantification of the demyelination load were established and applied in our large cohort. This allowed the identification of typical MRI changes in children with late-infantile and juvenile MLD and the quantification of demyelination and atrophy in the brain. These MRI parameters were correlated with the decline of neurological function in MLD underlining their potential as surrogate parameters for disease progression. In addition, the treatment effect of hematopoietic stem cell transplantation in children with lateinfantile and juvenile MLD was evaluated and compared to the natural history data. In conclusion, the standardized description of the natural disease course of MLD is essential in increasing our knowledge about this rare disease and thereby improving patient counselling. In addition, these data may serve as reference data for the evaluation of therapeutic interventions. Introduction Metachromatic leukodystrophy (MLD) is a rare lysosomal storage disorder caused by a deficiency of the catabolic enzyme arylsulfatase A, resulting in accumulation of sulfatides [1]. Sulfatide is an important component of myelin in the (central and peripheral) nervous system and its accumulation causes progressive demyelination as a pathological feature of MLD, leading to various neurological symptoms [2]. Depending on the onset of first symptoms, three clinical forms of the disease have been identified. Children with the late-infantile form have their disease onset during the first years of life and undergo a rapid neurological deterioration with loss of motor function as a key feature. In patients with the juvenile form, onset of the disease is later and rate of progression clearly slower; in the adult form with an onset after the age of 16 years, cognitive and psychiatric symptoms may predominate and may precede motor and neurological symptoms [3]. Currently, new therapeutic approaches are emerging, including gene therapy and enzyme replacement therapy [4 8]. Outside of these trials, however, the only available treatment option is Rev Neurol 2014; 58 (Congr 1): C1 C496 C84

2 haematopoetic stem cell transplantation (SCT), in which some success has been reported when treated early in the disease course, preferentially in the presymptomatic stage (for review see [9]). However, due to the low incidence of the disease (1 per 100,000 live births [10,11]), developing therapeutic strategies remains challenging. Natural history data are scarce making it difficult to evaluate treatment effects. In addition, disease specific standardized assessment is needed in order to reliably quantify disease progression. The aim of our work therefore was to establish and validate standardized assessment tools for the description of the natural disease course of MLD and in order to establish reference data for the evaluation of therapy. Methods Patients Children with biochemically proven MLD were recruited within Germany. Clinical and MRI data have systematically been collected since 2006 in the framework of the German and European leukodystrophy networks LEUKONET and LEUKOTREAT in order to establish a database with reference data. The study was funded by the German Federal Ministry of Education and Research and the European Commission (framework 7). The local ethics committee approved the study and parents gave written informed consent. Patients were assessed using standardized questionnaires, telephone interviews, and clinical examinations [12]. Gross motor function classification for MLD As the loss of gross motor function is a main clinical feature in MLD, a gross motor function classification system for MLD (GMFC-MLD) was developed and validated [13]. Patients gross motor function was categorized into 7 categories (Table I), from normal gross motor function (GMFC-MLD = 0) to loss of all gross motor function, including head control (GMFC-MLD = 6). Language and cognition Development and loss of language as well as cognitive parameters were assessed systematically in children with late-infantile and juvenile MLD [14]. In order to describe regression of language abilities, we analyzed age at loss of complete sentences, loss of two-word-sentences, loss of single meaningful words, first language decline, and complete loss of expressive language. Furthermore, in order to describe regression of cognitive abilities, we analyzed the age when the child presented with problems in concentration, behavioral problems, decline in skills for reading, writing and calculating, and loss of any communication. MR Severity Score For the visual analysis of MRI images a scoring system was established and validated for MLD [15], similar to the scoring system for adrenoleukodystrophy [16]. This scoring system assesses both demyelination and atrophy of brain regions and grades these changes from 0 (= no changes) to 34 (= all regions are affected) (Table II). Demyelination load As demyelination and atrophy are the most prominent features of cerebral changes in MLD, a volumetric analysis was done in order to quantify the volume of demyelination (i.e. the demyelination load [18]). Two methods were established: A semi-automated clustering method for a fast manual delineation of the demyelination load in axial T2-weighted images, called clusterize [19]. This software is available for download [20]. Rev Neurol 2014; 58 (Congr 1): C1 C496 C85

3 A fully automated and objective method for quantification of demyelination load and grey and white matter volume in MLD using both high-resolution T1-weighted and axial T2-weighted images [18] (Figure). Results Clinical course of MLD Both late-infantile and juvenile MLD began with gait disturbances and abnormal movement. Onset in the juvenile form was additionally characterized by problems in concentration, behavior and fine motor function [14]. In late-infantile MLD, all patients showed loss of all gross motor function until 3 years and 4 months of age. Patients with juvenile MLD showed a more variable and significantly longer motor decline. Having lost independent walking, subsequent decline of motor function was very rapid both in the late-infantile and juvenile form[12]. Language development was abnormal in half of the children with late-infantile MLD, who did not learn to speak in complete sentences after initially normal use of first words. They showed a rapid decline of language function with first language difficulties at the age of 2.5 years (median) and complete loss of expressive language within a few months (median age 32, range months). This was followed by total loss of communication at a median age of four years. In juvenile patients, language decline was more protracted and problems in concentration and behavior were followed by loss of cultural techniques around four years after disease onset [14]. Cerebral changes in MLD assessed by MRI The progression of MRI changes was clearly faster and more uniform in children with late-infantile MLD compared with the juvenile form, where change over disease duration was more variable [17]. High MRI scores were evident in the juvenile form already at the onset of first symptoms and even in the presymptomatic stage. Still, early (involving central white matter, corpus callosum) and late signs in MRI (involving pons, cerebellum, cerebral atrophy) were similar between the two forms. In late-infantile patients, MRI changes correlated highly with motor deterioration, this was less remarkable in the juvenile form. In the late-infantile patients, the demyelination load (corrected by the total WM volume) was found to increase after disease onset and correlated positively with motor deterioration (p<0.001) and disease duration (p<0.003) [18]. Furthermore, WM volumes of children with late-infantile MLD did not differ from healthy controls, although their growth curves appeared different. However, the GM volume of children with MLD was clearly below those of normally developing children (p<0.001) [18]. Validation of the volumetric methods against manual volume measurements yielded excellent interrater and intra-rater reliability [18,19]. Application of standardized assessment tools to therapy evaluation A girl with juvenile MLD 10 years after hematopoietic SCT was compared not only with the clinical and MRI course of her untreated sister, but also with a cohort of untreated patients [9]. The girl received SCT at the age of 5 years when first motor signs appeared. She was stable with respect to her clinical course over 10 years after SCT and gained cognitive abilities resulting in normal school education. MRI scores, MR spectroscopy changes and demyelination load showed improvement [9]. Only the demyelinating neuropathy showed some progression. Her gross motor function and MRI-scores were clearly better compared with her sister and the cohort of untreated patients [9]. Rev Neurol 2014; 58 (Congr 1): C1 C496 C86

4 In order to assess outcomes of a large cohort of juvenile patients after hematopoietic SCT in 3 German centers, 23 transplanted patients were analyzed and their motor and cognitive functions as well as MRI changes were compared to 25 untreated MLD patients [21]. Although survival rates after SCT did not differ from the non-treated group, neurological outcome and MRI scores were improved [21]. Patients transplanted in the presymptomatic and early symptomatic stage were more likely to show a stabilization of their disease course. MRI severity scores before SCT were significantly lower in patients who showed a stable disease after SCT than in those who deteriorated. Also, 65% of untreated patients progressed to GMFC-MLD level 5 (only head control possible) 10 years after disease onset, whereas none of the patients in the treatment group with a stabilization of their disease course lost their ability to sit independently (level 3 or better). Furthermore, 2 patients with the late-infantile form of MLD received SCT at the age of 9 months, before the onset of any symptoms [22]. Their diagnosis was done preclinically due to their affected siblings. The clinical course and MRI of both patients up to 3.5 and 5 years after SCT was compared to a large group of untreated patients with late-infantile MLD. Aided walking was possible until the age of 70 (patient 1) and 48 (patient 2) months, while untreated patients lost this significantly earlier (median age 29 months, 90-%-percentile 32.2 months). Crawling and headcontrol was lost at the age of 72 months in patient 1 and is still preserved in patient 2, clearly beyond the median age of the untreated group [12]. Patient 1 learned 2-word-sentences and is still able to speak single words, patient 2 speaks in short sentences, while untreated children lost complete speech before the age of 4 years. MRI showed no MLD-typical lesions in patient 1, but in patient 2, mild demyelination was seen at 39 months, clearly later than in untreated controls [22]. Discussion Standardized description of natural disease course Our data reflect the natural course of decline in motor function, language and cognition in children with late-infantile and juvenile MLD in a large cohort over a long observation period [12,14]. The course of motor disease was found to be more variable in juvenile MLD with respect to onset and dynamics. However, the motor decline after the loss of independent walking was similarly steep in both forms [12]. Furthermore, knowledge of first symptoms may lead to earlier diagnosis and subsequently to a better outcome following therapeutic intervention. These data can serve as a reference for individual treatment decisions and for evaluation of clinical outcome after treatment. In addition, by analyzing brain changes in MRI during disease progression, we were able not only to identify spatial and temporal patterns of cerebral changes and identify typical early and late signs during disease course [17], but we also gained new insight into the disease mechanism. Grey matter volume in patients with MLD was found to be reduced early during the disease course when compared with healthy controls [18]. This supports the notion that, besides demyelination, neuronal dysfunction caused by neuronal storage plays an additional role in the disease process of this leukodystrophy. New standardized assessment tools for MLD We have established and validated new assessment tools for the standardized description of natural disease course of MLD. The GMFC-MLD has been shown to be a reliable and easily applicable tool in the assessment of gross motor function [13] and has been proven useful in the description of the natural course of the disease [12] but also in order to show relationships of cerebral changes with loss of motor function [17,18]. Furthermore, it was successfully applied in the evaluation of therapy [7,9]. Rev Neurol 2014; 58 (Congr 1): C1 C496 C87

5 With the development of MRI parameters, the cerebral changes in MLD can be assessed and quantified non-invasively. The visual MR severity scoring system is an easily applicable and reliable tool in assessing and quantifying disease progression [15,17]. The demyelination load seems to be even a more sensitive parameter in depicting cerebral changes or responses to treatment [9]. The semi-automated clusterize-approach proved to be a fast and easily applicable tool in order to quantify the demyelination load [19]. Furthermore, with a fully automated and therefore more objective method, we were able to accurately quantify the demyelination load as well as grey and white matter volume in order to assess tissue atrophy during the disease course [18]. These volumetric tools might not only be useful in MLD but also in other white matter diseases. Evaluating hematopoietic stem cell transplantation (SCT) in MLD Using our standardized natural history data on MLD we were able to evaluate patients who received SCT more reliably. Previous studies often used only short observation periods and no larger control groups, weakening their conclusions (for review see [9]). Not only from our case report of a longterm follow-up after stem cell transplantation [9] but also from our larger multicenter evaluation, we conclude that SCT, early in the course of disease, can lead to stabilization of juvenile MLD with a course clearly different from the natural history [21]. SCT may prevent disease progression, if performed in sufficient time before loss of walking, which typically initiates rapid deterioration [12]. However, benefit and risk have to be carefully balanced considering the relevant transplantrelated mortality. SCT in patients with late-infantile MLD does not prevent deterioration in motor function as well as in speech and cognition but clearly has a protracting effect of the disease course [22]. Loss of motor function as well as loss of speech occurred clearly beyond the 90%-quantile when compared to natural course data, but children developed a significant impairment. Demyelination signs in MRI are mild or absent. Whether SCT is a treatment option in late-infantile MLD must be ethically discussed. Open questions and future directions In the light of new treatment approaches for MLD like enzyme replacement and gene therapy as well as the inconclusive results of hematopoietic SCT, it seems of great importance to establish and maintain clinical reference data, although it remains a challenge for a rare disease like MLD. Data quality and monitoring of data entry are essential, as well as ethical considerations. This often becomes a greater challenge when different countries or institutions are involved [23]. Regarding the decision for SCT, clear inclusion/exclusion criteria still need to be established. As MLD is a rare disease and different experiences regarding outcome after SCT are observed between different centers, more exchange and recommendation based on scientific evidence is clearly needed. One important step is the use of natural history data as presented here. Furthermore, the role of MRI in the treatment decision should be studied in more detail since MRI changes precede neurological symptoms in juvenile MLD and might be early markers for disease progression [17]. Also, the predictive value of different MRI parameters before SCT should be evaluated with respect to outcome after SCT. Furthermore, the relationship between MRI changes and motor/cognitive function in juvenile patients remains to be understood in more detail. This would allow more prognostic information for family counselling and help in any treatment decision. More specific and more sensitive MRI parameters are needed, like parameters from diffusion-weighted imaging [24] or other more myelin specific parameters [25], which are able to quantify microstructural changes in MLD, compared to the more unspecific T2-hyperintensity, which do not necessarily reflect demyelination. This has also important implications for the reversal of cerebral changes by therapeutic intervention. Rev Neurol 2014; 58 (Congr 1): C1 C496 C88

6 References 1. Gieselmann V. Metachromatic leukodystrophy: genetics, pathogenesis and therapeutic options. Acta Paediatr Suppl 2008; 97 (457): Gieselmann V, Krageloh-Mann I. Metachromatic leukodystrophy an update. Neuropediatrics 2010; 41 (1): Gieselmann V, Krägeloh-Mann I. Metachromatic leukodystrophy. In: The online metabolic and molecular bases of inherited disease. New York: McGraw-Hill; chapter Matzner U, Lullmann-Rauch R, Stroobants S, et al. Enzyme replacement improves ataxic gait and central nervous system histopathology in a mouse model of metachromatic leukodystrophy. Mol Ther 2009; 17 (4): Stroobants S, Gerlach D, Matthes F, et al. Intracerebroventricular enzyme infusion corrects central nervous system pathology and dysfunction in a mouse model of metachromatic leukodystrophy. Hum Mol Genet 2011; 20 (14): I Dali C, Hanson LG, Barton NW, et al. Brain N-acetylaspartate levels correlate with motor function in metachromatic leukodystrophy. Neurology 2010; 75 (21): Biffi A, Montini E, Lorioli L, et al. Lentiviral hematopoietic stem cell gene therapy benefits metachromatic leukodystrophy. Science 2013; 341 (6148). 8. Piguet F, Sondhi D, Piraud M, et al. Correction of brain oligodendrocytes by AAVrh.10 intracerebral gene therapy in metachromatic leukodystrophy mice. Hum Gene Ther 2012; 23 (8): Krägeloh-Mann I, Groeschel S, Kehrer C, et al. Juvenile metachromatic leukodystrophy 10 years post transplant compared with a non-transplanted cohort. Bone Marrow Transplant 2013; 48 (3): Heim P, Claussen M, Hoffmann B, et al. Leukodystrophy incidence in Germany. Am J Med Genet 1997; 71 (4): Poorthuis BJ, Wevers RA, Kleijer WJ, et al. The frequency of lysosomal storage diseases in The Netherlands. Hum Genet 1999; 105 (1-2): Kehrer C, Blumenstock G, Gieselmann V, Krageloh-Mann I. The natural course of gross motor deterioration in metachromatic leukodystrophy. Dev Med Child Neurol 2011; 53 (9): Kehrer C, Blumenstock G, Raabe C, Krageloh-Mann I. Development and reliability of a classification system for gross motor function in children with metachromatic leucodystrophy. Dev Med Child Neurol 2011; 53 (2): Kehrer C, Groeschel S, Kustermann-Kuhn B, et al. Language and cognition in children with metachromatic leukodystrophy: onset and natural course in a nationwide cohort. Orphanet J Rare Dis 2014; 9 (1): Eichler F, Grodd W, Grant E, et al. Metachromatic leukodystrophy: a scoring system for brain MR observations. AJNR Am J Neuroradiol 2009; 30 (10): Loes DJ, Hite S, Moser H, et al. Adrenoleukodystrophy: a scoring method for brain MR observations. AJNR Am J Neuroradiol 1994; 15 (9): Groeschel S, Kehrer C, Engel C, et al. Metachromatic leukodystrophy: natural course of cerebral MRI changes in relation to clinical course. J Inherit Metab Dis 2011; 34 (5): Groeschel S, I Dali C, Clas P, et al. Cerebral gray and white matter changes and clinical course in metachromatic leukodystrophy. Neurology 2012; 79 (16): Clas P, Groeschel S, Wilke M. A semi-automatic algorithm for determining the demyelination load in metachromatic leukodystrophy. Acad Radiol 2012; 19 (1): Experimental Pediatric Neuroimaging (software). Children s Hospital Tübingen. URL: Groeschel S, Bley A, Kühl J, et al. Hematopoietic stem cell transplantation in juvenile metachromatic leukodystrophy. Eur J Paediatr Neurol 2013; 17: S Kehrer C, Groeschel S, Doering M, Krägeloh-Mann I. 5-year follow-up in hematopoietic stem cell transplantation in 2 patients with late-infantile metachromatic leukodystrophy in Rev Neurol 2014; 58 (Congr 1): C1 C496 C89

7 comparison to an untreated cohort. Eur J Paediatr Neurol Soc 2013; 17: S1 S Duchange N, Darquy S, D Audiffret D, et al. Ethical management in the constitution of a European database for leukodystrophies rare diseases. Eur J Paediatr Neurol Soc Groeschel S, Scheffler K, Schultz T. Microstructural changes in metachromatic leukodystrophy assessed by DTI, FOD, and NODDI. Workshop Proc Int Soc Magn Reson Med Groeschel S, Schultz T, Hagberg G, et al. Assessing white matter microstructure in regions with different myelin architecture. Proc Int Soc Magn Reson Med Rev Neurol 2014; 58 (Congr 1): C1 C496 C90

8 Table I. Gross motor classification system for MLD [13]. Level 0 Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Walking without support with quality of performance normal for age. Walking without support, but with reduced quality of performance, i.e. instability when standing or walking. Walking with support. Walking without support not possible (fewer than 5 steps). Sitting without support and locomotion such as crawling or rolling. Walking with or without support not possible. a) Sitting without support, but no locomotion or b) Sitting without support not possible but locomotion such as crawling or rolling. No locomotion nor sitting without support but head control is possible. Loss of any locomotion as well as loss of any head and trunk control. Rev Neurol 2014; 58 (Congr 1): C1 C496 C91

9 Table II. MRI severity scoring system for MLD [15,17]. Brain areas Score Maximum per area Frontal WM 6 Periventricular Central U-Fibers Parieto-occipital WM 6 Periventricular Central U-Fibers Temporal WM 6 Periventricular Central U-Fibers Corpus callosum 4 Genu Splenium Projection fibers 6 Internal capsule posterior limb Internal capsule anterior limb midline pons Cerebral atrophy Thalamus Basal ganglia Cerebellum 2 White matter 0 1 Atrophy Total 34 Rev Neurol 2014; 58 (Congr 1): C1 C496 C92

10 Figure. Methodological approach for quantification of grey (GM) and white matter (WM), and demyelination load [18]. Rev Neurol 2014; 58 (Congr 1): C1 C496 C93