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Brain morphometry of Dravet Syndrome
Alejandro Péreza,∗, Lorna García-Pentóna,Erick J. Canales-Rodríguezb,c, Garikoitz Lerma-Usabiagaa,Yasser Iturria-Medinad, Francisco J. Románe, Doug Davidsona,Yasser Alemán-Gómezf, Joana Achag, Manuel Carreirasa,g,h
a Basque Center on Cognition Brain and Language, BCBL, Donostia-San Sebastián, Spainb Centro de Investigación Biomédica en Red de Salud Mental (CIBERSam), 28007 Madrid, Spainc FIDMAG Germanes Hospitalàries, 08830, Sant Boi de Llobregat, Barcelona, Spaind Neuroimaging Department, Cuban Neuroscience Center, La Habana, Cubae Facultad de Psicología, Departamento de Psicología Biológica y de la Salud, Universidad Autónoma deMadrid, 28049 Madrid, Spainf Instituto de Investigación Sanitaria Gregorio Maranón, IiSGM, HGUGM, CIBERSAM, Madrid, Spaing Euskal Herriko Unibertsitatea/Universidad del País Vasco EHU/UPV, Bilbao, Spainh Ikerbasque, Basque Foundation for Science, Bilbao, Spain
Received 19 September 2013; received in revised form 6 June 2014; accepted 28 June 2014
Summary The aim of this study was to identify differential global and local brain structuralpatterns in Dravet Syndrome (DS) patients as compared with a control subject group, usingbrain morphometry techniques which provide a quantitative whole-brain structural analysis thatallows for specific patterns to be generalized across series of individuals. Nine patients withthe diagnosis of DS that tested positive for mutation in the SCN1A gene and nine well-matchedhealthy controls were investigated using voxel brain morphometry (VBM), cortical thicknessand cortical gyrification measurements. Global volume reductions of gray matter (GM) andwhite matter (WM) were related to DS. Local volume reductions corresponding to several whitematter regions in brainstem, cerebellum, corpus callosum, corticospinal tracts and associationfibers (left inferior fronto-occipital fasciculus and left uncinate fasciculus) were also found.
Furthermore, DS showed a reduced cortical folding in the right precentral gyrus. The presentfindings describe DS-related brain structure abnormalities probably linked to the expression ofthe SCN1A mutation.
Please cite this article in press as: Pérez, A., et al., Brain mhttp://dx.doi.org/10.1016/j.eplepsyres.2014.06.006
ravet Syndrome (DS), also termed severe myoclonicpilepsy of infancy (SMEI), is a rare form of epilepsyccurring in the first year of life (up to 15 months) in appar-ntly normal infants (Dravet, 1978; Dravet and Guerrini,011). It is characterized by the onset of recurrent febrilend/or afebrile hemiclonic or generalized seizures, or statuspilepticus, in a previously healthy infant, followed by theppearance of multiple seizure types generally resistant tonti-epileptic drugs, with developmental arrest or regres-ion (Dravet et al., 2005; Jansen et al., 2006; Wolff et al.,006). Of these cases, 60—80% are caused by SCN1A muta-ions (Brunklaus et al., 2012; Catarino et al., 2011; Depiennet al., 2009; Marini et al., 2009; Mullen and Scheffer, 2009).owadays, the term DS has been proposed to describe theroup of severe infantile onset epilepsies associated withutations in the SCN1A gene (Stenhouse et al., 2013). Evo-
ution is insidious, with a significant mortality of up to 15%y 20 years (Dravet et al., 2005). Neurological declines alsoccur in adulthood, with cognitive and motor deteriorationDravet et al., 2005).
Correct diagnosis, treatment and monitoring of DS haveade an impact at several levels: family, social and eco-
omic (Skluzacek et al., 2011), and there has been increasednterest in the prevalence of this syndrome (Brunklaus et al.,012; Verbeek et al., 2013), its cognitive outcome (Chieffot al., 2011a,b; Ragona et al., 2010, 2011), neuropatho-ogy (Catarino et al., 2011) and specially epileptogenesisCheah et al., 2012; Higurashi et al., 2013; Jiao et al.,013; Liu et al., 2013). However, while the perspective ofcreening for appropriate drugs to be used in therapies isromising, the brain structural and functional counterpartsf the common pathogenesis in DS have not been generallyescribed (Jansen et al., 2006; Moehring et al., 2013; Sieglert al., 2005; Striano et al., 2007). Functional and structuralraits related to the DS brain could provide extra criteriaor diagnosis, as well as biological indicators for monitoringhe progression of the condition, especially relevant in theollow-up of novel drug treatments.
Despite the fact that a common genetic etiology in DSi.e. SCN1A mutation) might confer a unique brain profiler convergent brain pattern, findings of brain structuralbnormalities across different DS studies (and patients) areot consistent (Dalla Bernardina et al., 1982; Dravet et al.,005; Ferrie et al., 1996; Gaily et al., 2013; Guerrini et al.,011; Jansen et al., 2006; Sakakibara et al., 2009; Sieglert al., 2005; Striano et al., 2007). Also, brain functionalatterns diverge across subjects (Moehring et al., 2013).owever, all the structural reports are from qualitativessessments of computer tomography or magnetic resonancemaging (MRI) data, performed by neuroimaging experts. Tour knowledge, no study so far has investigated DS brainbnormalities using a whole-brain quantitative neuroimag-ng approach, which is highly desirable (Guerrini et al.,011). Nowadays, neuroimaging analysis techniques quan-ifying structural brain properties have been developed andore fine-grained brain structural studies on DS can now
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e conducted. In fact, these approaches could detect thetructural brain abnormalities that appear normal on con-entional MRI (Kakeda and Korogi, 2010). This is the casef voxel-based and surface-based morphometry techniques
Stp(
PRESSA. Pérez et al.
see Greve, 2011 for an overview) like voxel-based mor-hometry (VBM; Ashburner and Friston, 2000) and FreeSurferDale et al., 1999; Fischl et al., 1999), respectively. Theormer allows for investigation of volume differences inrain anatomy, while the later allows, for example, forhe automated measurement of cortical thickness (Fischlnd Dale, 2000; Fischl et al., 2002) and cortical foldingSchaer et al., 2008). Through the quantitative estimationf gray matter (GM), white matter (WM) and cerebro-spinaluid (CSF), probable global differences in the brains of DSatients can be assessed. In addition, as the procedureslready mentioned imply a transformation of the individ-al brains to a common brain space, local differences in theeasurements/indexes can also be assessed and related to
pecific brain areas, according to a brain atlas.Here, we took advantage of these morphometric meth-
ds to search for common brain structural abnormalitiesn DS patients. We hypothesized the existence of com-on brain structural abnormalities in DS as assessed by
olumetry, which involves global volume reductions in theS brain because of underlying mechanisms such as Walle-ian degeneration, apoptotic cell death, inflammation andxcitotoxicity that take place in the condition (Guerrinit al., 2011) and lead to brain atrophy. Local volume reduc-ions may also be expected at structures linked to the coreymptoms of DS, i.e. neurological signs and psychomotorevelopmental delay, because it has been demonstratedhat seizure-induced changes may affect the brain selec-ively (Liu et al., 2003). Hypotheses about cortical thicknessatterns related to the DS brain are not so clear; for typi-al populations in general, cortical thickness decreases withge during development due to axonal pruning mechanismsShaw et al., 2008). It is therefore plausible that some areasould have abnormally greater cortical thickness in DS. With
espect to the cortical folding, quantified by the local gyri-cation index (lGI), abnormal indices have already beenssociated with MRI-negative epilepsy (Ronan et al., 2011).herefore, we expect a reduced lGI in the DS patients,uggestive of malformations of cortical development. Sum-arizing, here we try to identify differential global and localrain structural patterns in a DS patients group as comparedith a well-matched healthy control group, using volumet-
ic, voxel-based and surface-based analyses.
ethods
ubjects
selected sample of nine patients with DS (age mean:3.6, SD: 5.2), all members of the Spanish Dravet Founda-ion took part in the present study. They were diagnosedsing the criteria proposed in Dravet et al. (2005): patientsith seizure onset in the first year, intractable epileptic
eizures triggered by infections and increased temperature,ormal development in the first year and no evidence oftructural-metabolic etiology at seizure onset. In addition,ll had undertaken the genetic study and tested positive for
morphometry of Dravet Syndrome. Epilepsy Res. (2014),
CN1A mutation. Exclusion criteria included having a his-ory of brain trauma or other neurological disease. All theatients use several medications in their drug treatmentmean: 3 drugs) with topiramate, stiripentol, valproic acid
Table 1 Age in years and gender of the participants (F forfeminine and M for masculine).
HC group DS group
Age Gender Age Gender
20.4 F 20.7 F11 F 11 F9.5 F 9.4 F
11.4 F 11.9 F22.1 M 22.6 M10 M 10.5 M20.9 M 20.4 M13.6 M 13.7 M9.2 M 10 M
Taimmik
cprtouRfGcensJa
S
Cpsptotogdd1epiuedtGtlarab
tGgc
14.3 M 16 F6.4 F 6.9 M
and benzodiazepines being the most common. A matchedsample for age (age mean: 13.1, SD: 5.2) and sex, ofhealthy control subjects (HC) (see Table 1) was recruitedfrom the local community via poster and web-based adver-tisement. They were healthy people with no reportedhistory of neurological/mental illness and/or treatment withpsychotropic medication. All participants gave verbal andwritten informed consent prior to involvement, in accor-dance with the Declaration of Helsinki, and the researchprotocol was approved by the BCBL Ethics Committee.
Structural imaging
All subjects underwent structural MRI scanning in a singlesession, using the same 3.0 Tesla Magnetom Trio Tim scan-ner (Siemens AG, Erlangen, Germany), located at the BCBL inDonostia-San Sebastián. A high-resolution T1-weighted scanwas acquired with a 3D ultrafast gradient echo (MPRAGE)pulse sequence. Acquisition parameters used were: matrixsize 256 × 256; 160 contiguous axial slices; voxel reso-lution 1 × 1 × 1 mm3; TE/TR/TI = 2.97 ms/2300 ms/1100 ms,respectively; flip angle 9◦.
Voxel-based morphometry
Structural data were analyzed with an optimized voxel-based morphometry (VBM) analysis carried out using theStatistical Parametric Mapping (SPM) software package(SPM8, Wellcome Trust Centre for Neuroimaging, UK), whichallows for the detection of potential differences in the localgray and white matter volume between different groupsof participants. Data were manually reoriented, segmentedinto different tissue types GM and WM, and then normalizedto the same anatomical space. Segmentation was performedusing the New Segmentation tool by estimating the modelparameters for a maximum a posteriori solution alternatingamong classification, bias correction and registration stepsin the same generative model (Ashburner and Friston, 2005).
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The registration was carried out using the DARTEL tool,which involves a high-resolution diffeomorphic anatomicalregistration (Ashburner, 2007), using the Large DeformationDiffeomorphic Metric Mapping approach (Beg et al., 2005).
Mfoc
PRESS3
he resulting normalized images were averaged to create study-specific template, to which the native GM and WMmages were nonlinearly re-registered. These images wereodulated (to correct for local expansion or contraction) byultiplying by the Jacobian of the warp field. Each normal-
zed and modulated volume was smoothed with a Gaussianernel of 8-mm full-width at half-maximum (FWHM).
Group comparison between patients and controls wasarried out using a voxel-wise general linear model andermutation-based nonparametric testing. This was car-ied out via the Statistical nonParametric Mapping (SnPM)oolbox for SPM (Nichols and Holmes, 2002). The numberf permutations was set to 5000 and the intracranial vol-me (ICV) was included as a continuous nuisance regressor.egional differences were reported as significant at p < 0.05,ully corrected for multiple comparisons across space via theaussian Random Field theory, applying topological false dis-overy rate (FDR) correction (Genovese et al., 2002) with anxtent threshold of 50 voxels. Anatomical locations of sig-ificant regions were determined by reference to the MNItructural atlas integrated into MRIcron software and theohns Hopkins University (JHU) white-matter tractographytlas (Mori et al., 2005).
urface-based and volumetric analyses
ortical reconstruction and volumetric segmentation waserformed with the FreeSurfer (version 5.1) image analy-is suite (http://surfer.nmr.mgh.harvard.edu/). Briefly, thisrocessing includes motion correction, removal of non-brainissue, automated Talairach transformation, segmentationf the subcortical WM and deep GM volumetric structures,essellation of the GM and WM boundaries, automated topol-gy correction, and surface deformation following intensityradients to optimally place the GM/WM and GM/CSF bor-ers at the location where the greatest shift in intensityefines the transition to the other tissue class (Dale et al.,999; Fischl and Dale, 2000; Fischl et al., 2002; Segonnet al., 2004). A number of deformation procedures wereerformed in the data analysis pipeline, including surfacenflation and registration to a spherical atlas. This methodses both intensity and continuity information from thentire three-dimensional MR images in the segmentation andeformation algorithms to produce representations of cor-ical thickness, calculated as the closest distance from theM/WM boundary to the GM/CSF boundary at each vertex on
he tessellated surface. Moreover, from the resulting mapsocal measurements of gyrification (i.e., lGI) were computeds described in Schaer et al. (2008). These maps are notestricted to the voxel resolution of the original data andre thus capable of detecting sub-millimeter differencesetween groups.
Prior to the statistical analysis, the individual corticalhickness and lGI maps were smoothed in cortex using aaussian filter with (FWHM) of 10 mm. Finally, a vertex-wiseeneral linear model was applied. Statistical inference wasarried out with FreeSurfer tools based on non-parametric
orphometry of Dravet Syndrome. Epilepsy Res. (2014),
onte Carlo testing, using a cluster-wise correction methodor multiple comparisons with initial cluster-forming thresh-ld (p < 0.01). In this analysis, only those clusters with aorrected value of p < 0.05 were considered as significant.
onparametric Friedman’s tests were performed to com-are global GM, WM and CSF volumes between groupshile considering the VBM and FreeSurfer outputs together.his tested for volume effects after adjusting for possibleffects of the different morphometry techniques. The testsevealed a significant effect of Group on GM (�2(1) = 16.98,
= 3.77e−5) and WM (�2(1) = 19.1, p = 1.24e−5) but not onSF (�2(1) = 0.1, p = 0.75), indicating that the DS group havetatistically significant reductions of global volumes in GMnd WM as compared to the HC group. The DS group’s meanlobal volume reduction in GM is 8.67% according to VBM and4.82% according to FreeSurfer. Volume reduction in WM wasarger, with 20.71% according to VBM and 20.47% accordingo FreeSurfer.
orrelation of the total intracranial volume with age general linear model was fitted using robust regression toodel the ICV as function of age and group and their inter-
ction (i.e. allowing different slopes and intercepts for eachroup of subjects). The effects of age were statistically sig-ificantly different between groups (positive slope for theontrol group whilst apparently negative for the patientroup, p = 2.6e−3) (see Fig. 1). Specifically, the differencef ICV between groups was not yet statistically significantt the age of 8 years (p = 0.2), while it achieved statisticalignificance at the age of 9 years (p = 0.046).
ubcortical volumetry
ndividual t-tests were performed to compare the meanolumes of the subcortical structures provided by thereeSurfer segmentation (i.e., including thalamus, caudate,utamen, pallidum, brainstem, hippocampus, amygdala andccumbens) between DS and HC groups. This analysis allowsor the comparison of both native/raw volumes and normal-zed volumes corrected for the intracranial volume (ICV).orrection by multiple comparisons was controlled via theonferroni method.
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The tests comparing native volumes revealed statisticallyignificant differences (p < 0.05 corrected) between groupsn the brainstem (p = 4e−4) and in three bilateral structures:halamus (p = 2.4e−3), pallidum (p = 1e−4) and amygdala
bFoe
igure 2 WM regions showing significant volume reduction in the
NI space.
igure 1 Linear correlations between age and ICVFreeSurfer), for both groups.
p = 3.5e−3), all showing volume reduction for the DS group.n the other hand, no significant differences were obtained
n the analysis using normalized volumes.
oxel base morphometry
rey mattert a p < 0.05 corrected, no significant increases or reductions
n local GM volume were found in patients.
hite mattert a p < 0.05 corrected, no significant increases in local WMolume were found in DS patients but significant reductionsere observed in four areas. One of these was located in
he left inferior fronto-occipital fasciculus, covering the leftncinate fasciculus. The second significant area was cen-ered in the brainstem, bilaterally reaching the corticospinalracts. A third significant region was located in the cere-
morphometry of Dravet Syndrome. Epilepsy Res. (2014),
ellum and includes the right superior cerebellar peduncle.inally, a further anomalous region was located in the bodyf the corpus callosum (see Fig. 2 and Table 2 for a morextended report).
DS group. The background brain image is the brain template in
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Brain morphometry of Dravet Syndrome 5
Table 2 Brain areas showing significant reduced WM volume in the patients group at p < 0.05, topological FDR-corrected formultiple comparison across voxels.
Cluster Num. of voxels T Peak MNIcoordinates x
y z Locations
1 245 6.46 −32 41 −9 Left inferior fronto-occipitalfasciculus and left uncinatefasciculus
2 2242 5.7 10 −31 −13 Brainstem5.41 −3 −14 −20 Left corticospinal tract5.28 3 −35 −20 Right corticospinal tract
3 253 4.65 −3 −47 −29 Cerebellum5 −46 −28 Right superior cerebellar peduncle
4 83 3.62 9
Surface-based morphometry
Cortical thicknessAt a p < 0.05 corrected, there were no areas where DSpatients had significantly thinner or thicker cortex than HScontrols.
Cortical gyrificationAt a p < 0.05 corrected, no significant increases in lGIwere found in DS patients but significant reductions wereobserved in a cluster located in the right precentral gyrus(peak in MNI space [24.6, −10.2, 47.4]; p = 1e−4) (seeFig. 3).
Discussion
We found significant reductions in the global GM and WMvolumes of the DS patients. This result is in agreement withprevious studies (Jansen et al., 2006; Sakakibara et al.,2009; Striano et al., 2007). It could have been expectedthat decreased brain volume is compensated by increasedCSF volume, i.e. enlarged ventricles (Striano et al., 2007),but this was not the case. These global volume reductionswere more pronounced for WM. Similar findings have been
Figure 3 Brain areas showing significant decreased lGI in theDS group are shown in red. The background brain image is theright hemisphere inflated template.
ra(eAupcsIt2toas
debltpcmcd(cb
lsd(wifa(ese
1 28 Body of the corpus callosum
eported for temporal lobe epilepsy (Jing-Jing et al., 2013)nd are in line with the WM hyperintensities reported in DSDalla Bernardina et al., 1982; Dravet et al., 2005; Sieglert al., 2005) which is an indication of volume reduction.lthough it is impossible to know from the present data whatnderlying mechanism is responsible for such large WM atro-hy observed in DS patients, a potential mechanism involvedould be dysfunction in the myelination process as a result ofeizures occurring during maturation (Mitchell et al., 2003).nvolvement of other mechanisms such as neuronal hetero-opia (Sankar et al., 2008) or microdysgenesis (Thom et al.,000) could also be speculated, in addition to the exci-otoxic effects of spreading epileptogenic activity. On thether hand, we found a statistically significantly effect ofge on total intracranial volume among groups. This resultuggests a differential developmental trajectory in patients.
Volumetric VBM analysis at the local level revealed noifferences in GM volume but WM volume reductions in sev-ral regions of DS patients. One of these regions is sharedy association fibers of the inferior fronto-occipital fascicu-us (IFOF) that connects the frontal and occipital lobes andhe uncinate fasciculus, which connects the anterior tem-oral lobe (include hippocampal formation) to the orbitalortex left. Other regions involve the brainstem and itsajor white matter track of the superior cerebellar pedun-
le (right), which is the main efferent pathway from theentate nucleus of the cerebellum toward the thalamusOishi et al., 2011). Finally, there are WM regions of theerebellum and the body of corpus callosum, which connectsilateral motor regions.
Accounting for the possible relationship between theseocal findings and the core symptoms of the DS we coulday that, for example, IFOF has been implicated in top-own modulations of attention in visual and visuomotor tasksUrbanski et al., 2008) while the uncinate fasciculus withorking memory (Charlton et al., 2010). More specifically,
n temporal lobe epilepsy, structural compromise in bothasciculus (strongly left-lateralized) have been found associ-ted to disturbances in memory and language performance
orphometry of Dravet Syndrome. Epilepsy Res. (2014),
McDonald et al., 2008) and task-switching (Kucukboyacit al., 2012). Importantly, attention deficit is the most con-tant and precocious neuropsychological trait in DS (Chieffot al., 2011a; Dravet and Guerrini, 2011) while language
s impaired. In the case of the brainstem abnormalitiesound here, they are congruent with the multiple neuro-ogical signs that occur in DS, for example, pyramidal signsnd autonomic symptoms (Dravet and Guerrini, 2011). Inter-stingly, no significant alterations in the brainstem haveeen found before for DS (Guerrini et al., 2011), even usinguantitative analysis (Catarino et al., 2011) suggesting aigh sensitivity of the morphometric techniques to detectlterations in this structure. On the other hand, cerebel-ar atrophy has already been described in DS (Jansen et al.,006). The cerebellum is involved in fine movements, equi-ibrium, posture and motor learning (Fine et al., 2002). Alson some cognitive functions such as attention and languageTimmann and Daum, 2007). Thus, the findings here could beelated to the ataxia and walking disturbances common inS patients (Dravet and Guerrini, 2011) and to the fact thatost skills: motor, linguistic and visual abilities are deeply
ffected in DS patients (Cassé-Perrot et al., 2001; Wolfft al., 2006). Finally, the body of the corpus callosum, whichonnects bilateral motor regions, has been found abnormaln different types of epilepsies (Liu et al., 2011; Scanlont al., 2013). Volume reductions in this region could be sug-estive of a disconnection of the homologous motor areas.
It is important to note that the VBM analysis performedere was intended to find local differences that cannote explained by global differences, because the ICV wasncluded as a covariate into the statistical model. There-ore, the detected altered regions are not necessarily all theegions altered in the illness. Indeed, results of the globalolumetric analysis revealed large brain volume reductionsn the DS patients. These large reductions may be more likelyxplained by a ‘uniform’ pattern of atrophy in the wholerain than by a sparse pattern of small local affected areas.his hypothesis is reinforced when considering the resultsrom the subcortical volumetric analysis, which depictedignificant reductions in the raw volumes of several struc-ures, including the brainstem, thalamus, pallidum andmygdala, but not in their normalized volumes correctedy ICV.
The surface-based analyses revealed an area of abnor-al cortical folding (i.e., lGI) in the right precentral gyrus
f the DS patients. Interestingly, a study with Dravet micei.e. Scn1a+/− mice) showed affected neuronal networksn the prefrontal cortex associated to behavioral prob-ems that include: hyperactivity, stereotyped behaviors andocial interaction deficits (Han et al., 2012). These abnormalehaviors in mice parallel behavioral and cognitive impair-ents present in DS patients (Brunklaus et al., 2011; Chieffo
t al., 2011a; Nabbout et al., 2013; Ragona et al., 2011).his result suggests the existence of malformations of cor-ical development directly linked to comorbidities of DS.n the other hand, the absence of findings using the cor-ical thickness approach may be explained by a lack oftatistical power due to the small sample size. Another pos-ible hypothesis is that the local and global morphometrichanges occurring in the illness are not mainly related toortical thickness changes.
In the future, further studies to detect structural abnor-
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alities should be conducted with larger sample sizes andsing different image modalities, such as advanced diffu-ion tensor imaging analyses (Canales-Rodríguez et al., inress) and graph-based connectivity (Iturria-Medina et al.,
B
PRESSA. Pérez et al.
011) approaches to account more specifically for the majorxonal disturbances present in DS (Manninen et al., 2013)nd their implications at a network level. It remains to beeen whether the differences in severity of seizures and cog-itive and motor impairment correlate with the anatomicalatterns. A more comprehensive characterization of the dis-rder requires further studies based on longitudinal designs.dditional analyses could be implemented to probe the med-
cation effects on the GM and WM volumes.
onclusion
ore brain structural patterns associated to DS haveemained elusive despite the etiological homogeneity ofhis condition that makes the existence of such patternsery plausible. Here we applied automatic, voxel- andurface-based morphometry techniques to investigate thexistence of these patterns, specifically in terms of globalnd local volume/cortical thickness/gyrification differencesompared to healthy individuals. In general, the globaleductions in GM and WM described are gross, especiallyn WM; while local structural findings may be linked to theore neurological signs/symptoms in DS, which are the bestredictors of a mutation in the SCN1A gene (Fountain-Capalt al., 2011). The findings here describe DS-related braintructure abnormalities that maybe linked to the expressionf SCN1A mutation.
unding source
he study has been supported by private funding from thepanish Dravet Foundation, a non-profit organization whichad no role in the study design; the collection, analysis andnterpretation of data; in the writing of the report; and inhe decision to submit the article for publication.
We confirm that we have read the Journal’s position onssues involved in ethical publication and affirm that thiseport is consistent with those guidelines.
onflicts of interest statement
one of the authors has any conflict of interest to disclose.
cknowledgment
he authors thank Margaret Gillon Dowens for her helpfulomments and the reviewing of the manuscript.
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