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UNIVERSITY OF HELSINKI
FACULTY OF MEDICINE
Graph theoretical analyses
Graph theoretical properties of the structural brain networks were
investigated both globally (betweenness centrality, clustering
coefficient, characteristic path length, global efficiency, small-
worldness, degree, and strength) and locally (betweenness
centrality, local efficiency, and strength) (Bullmore and Sporns,
We found global abnormalities in the structural connectome of
patients with CLN3. Characteristic path length (p=0.003) was
significantly increased in CLN3. In addition, small-worldness
(p=0.009), global efficiency (p=0.02), clustering coefficient
(p=0.02), strength (p=0.02) and degree (p=0.02) were decreased,
but did not endure a Bonferroni correction for multiple
The local analyses showed that betweenness centrality was
decreased in the right thalamus (p=0.007) and increased in the
posterior part of the right midcingulate cortex (p=0.003) in CLN3.
In addition, local efficiency was decreased in seventeen nodes
(p<0.01), and strength was decreased in nine nodes (p<0.01).
However, none of the local results endured a Bonferroni correction
for multiple comparisons.
Juvenile neuronal ceroid lipofuscinosis (CLN3) is a
neurodegenerative lysosomal storage disease with an incidence of
7.0 in 100,000 births in Scandinavia (Uvebrant and Hagberg,
1997). The disease is caused by the recessive inheritance of
mutations in CLN3 gene located on chromosome 16p12 encoding
a membrane protein CLN3 (Lerner et al., 1995). It manifests with
loss of vision, seizures, and loss of cognitive and motor functions,
and leads to premature death typically in the second or third
decade of life (Jalanko and Braulke, 2009).
Previous MRI studies
Previous studies have reported cerebral and cerebellar atrophy,
progressive hippocampal atrophy, thalamic signal intensity
alterations, and decreased white matter volume in the corona
radiata (Autti et al., 2007; Tokola et al., 2014). In addition, global
and widespread local microstructural alterations have been found
using diffusion MRI (Roine et al., 2018).
We acquired diffusion MRI and T1-weighted data with Philips
Achieva 3T machine from 14 patients with CLN3 (aged 9.6±3.4
years), of which 12 were imaged again two years later (aged
11.4±3.2 years), and 14 age-matched controls (aged 11.2±2.3
Acquisition and preprocessing
Diffusion MRI data were acquired in 32 orientations with b=1000
s/mm2 and a 2 mm isotropic voxel size. T1-weighted data were
acquired with a 1 mm isotropic voxel size. Diffusion MRI data were
corrected for subject motion (Leemans and Jones, 2009), eddy
current induced distortions, and nonlinearly registered to the T1-
weighted data to correct for echo planar imaging distortions
(Irfanoglu et al., 2012).
Although conventional MRI is usually visually normal under the
age of ten, we found decreased integration of the structural
connectome in CLN3 by using diffusion MRI. In addition, the
centrality of the thalamus was decreased, which is supported by
the previous MRI findings related to thalamic signal intensity
Decreased structural brain network integration in
juvenile neuronal ceroid lipofuscinosis
Roine U.1, Roine T.1,2, Tokola A.1, Balk M.1, Mannerkoski M.3, Åberg L.4, Lönnqvist T.5, Autti T.1
1HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, Finland, 2Turku
Brain and Mind Center, University of Turku, Finland, 3Child Psychiatry, University of Helsinki and Helsinki
University Hospital, Helsinki, Finland, 4Department of Psychiatry, University of Helsinki and Helsinki University
Hospital, Finland, 5Department of Child Neurology, University of Helsinki and Helsinki University Hospital, Finland
Figure 1. A) Whole-brain constrained spherical deconvolution
(CSD)-based tractography was performed with ExploreDTI by
using up to 4th order spherical harmonics (Tournier et al., 2007;
Leemans et al., 2009; Jeurissen et al., 2011). CSD can track
through regions with complex (e.g. crossing) fiber configurations,
present in most of the white matter (Jeurissen et al., 2013). B)
Cortical parcellation was performed in FreeSurfer by using the
Destrieux atlas (Destrieux et al., 2009) combined with the
subcortical structures from FSL’s FIRST (Patenaude et al., 2011).
C) The 164 gray matter areas become the nodes, and the edges
are weighted by the number of fibers connecting a pair of gray
A B C
Reconstruction of structural brain networks
Figure 2. The structural
connectome in CLN3. The
size of the nodes illustrates
the size of the gray matter
area, and the colour of the
nodes shows whether
there are differences in
The size of the edges is
proportional to the number
of fiber tracts connecting
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Proc Intl Soc Mag Reson Med 17, 3537; Leemans and Jones (2009). Magn Reson Med, 61(6), 1336-1349; Lerner et al. (1995). Cell, 82(6), 949-957;
Patenaude et al. (2011). NeuroImage, 56(3), 907-922; Roine et al., (2018). Am J Neuroradiol, DOI:10.3174/ajnr.A5687; Tokola et al. (2014). Pediatr
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The structural connectome in CLN3
This work was supported by the Noah’s Hope/Hope 4 Bridget (NH/H4B), Thisbe and Noah Scott Foundation, and the Batten Disease Support and Research Association, Emil Aaltonen
Foundation, Pehr Oscar Klingendahl Fund, and Arvo and Lea Ylppö Foundation.