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Terveystieteiden tiedekunta
2017
Alzheimer's Disease-Related
Polymorphisms in Shunt-Responsive
Idiopathic Normal Pressure Hydrocephalus
Huovinen J
IOS Press
Tieteelliset aikakauslehtiartikkelit
© IOS Press and the authors
All rights reserved
http://dx.doi.org/10.3233/JAD-170583
https://erepo.uef.fi/handle/123456789/7918
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Alzheimer’s disease-related polymorphisms in shunt-responsive idiopathic normal pressure
hydrocephalus
Joel Huovinena, Seppo Helisalmib Jussi Paananenc, Tiina Laiteräa, Maria Kojoukhovaa, Anna
Sutelad, Ritva Vanninend, Marjo Laitinenb, Tuomas Rauramaae, Anne M Koivistob, Anne M Remesf,
Hilkka Soininenb, Mitja Kurkia,g, Annakaisa Haapasalob,e, Juha E Jääskeläinena, Mikko Hiltunenb,c,
Ville Leinonena
Institute of Clinical Medicine – Neurosurgery, University of Eastern Finland and Department of
a
Neurosurgery, Kuopio University Hospital, Kuopio, Finland
Institute of Clinical Medicine – Neurology, University of Eastern Finland and Department of
b
Neurology, Kuopio University Hospital, Kuopio, Finland
c
Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
Institute of Clinical Medicine – Pathology, University of Eastern Finland and Department of
d
Pathology, Kuopio University Hospital, Kuopio, Finland
Institute of Clinical Medicine – Radiology, University of Eastern Finland and Department of
e
Radiology, Kuopio University Hospital, Kuopio, Finland
f
Medical Research Center, Oulu University Hospital, Oulu, Finland and Research Unit of Clinical
Neuroscience, Neurology, University of Oulu, Oulu, Finland
g
Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General
Hospital, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard,
USA; Stanley Center for Psychiatric Research, Broad Institute for Harvard and MIT, USA
e
A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
Running title: AD genetics in iNPH
Corresponding author
Ville Leinonen MD, PhD
Department of Neurosurgery
Kuopio University Hospital
P.O.Box 100, FIN-70029 KYS, Finland
tel. +358-44-717 2303
fax. +358-17-173 916
e-mail: ville.leinonen@kuh.fi
www.uef.fi/nph
ABSTRACT
Background
Idiopathic normal pressure hydrocephalus (iNPH) is a late onset, surgically treated progressive
brain disease caused by impaired cerebrospinal fluid (CSF) dynamics and subsequent
ventriculomegaly. Comorbid Alzheimer’s disease (AD) seems to be frequent in iNPH. Here we aim
to evaluate the role of AD-related polymorphisms in iNPH.
Materials and methods
Overall 188 shunt-operated iNPH patients and 688 controls without diagnosed neurodegenerative
disease were included into analysis. Twenty-three single-nucleotide polymorphisms (SNPs
FRMD4A [rs7081208_A, rs2446581_A, rs17314229_T], CR1, BIN, CD2AP, CLU, MS4A6A,
MS4A4E, PICALM, ABCA7, CD33, INPP5D, HLA_DRB5, EPHA1, PTK2B, CELF1, SORL1,
FERMT2, SLC24A, DSG2, CASS4 and NME8) adjusted to APOE were analysed between groups
by using binary logistic regression analysis. Neuroradiological characteristics and AD-related
changes in the right frontal cortical brain biopsies were available for further analysis.
Results
Logistic regression analysis adjusted to age, gender and other SNPs indicated allelic variation of
NME8 between iNPH patients and non-demented controls (p = 0.014). The allelic variation of
NME8 was not related to the neuropathological changes in the brain biopsies of iNPH patients.
However, periventricular white matter changes (p = 0.017) were more frequent in the iNPH patients
with the AA-genotype, an identified risk factor of AD.
Conclusions
Our findings increase evidence that iNPH is characterized by genetic and pathophysiological
mechanisms independent from AD. Considering that NME8 plays a role in the ciliary function and
displays SNP-related diversity in white matter changes, the mechanisms of NME8 in iNPH and
other neurodegenerative processes are worth further studying.
Key Words: Idiopathic Normal Pressure Hydrocephalus, genetics, pathology, radiology,
Alzheimer’s disease
INTRODUCTION
Idiopathic normal pressure hydrocephalus (iNPH) is a progressive brain disease caused by
disturbance in the cerebrospinal fluid (CSF) dynamics resulting in ventriculomegaly and
compression-induced stress of periventricular parenchyma [1, 2]. Classical clinical characteristics
are impaired gait, cognitive decline and urinary incontinence [1]. The only treatment currently
available is a neurosurgically implanted CSF shunt, which usually alleviates symptoms in properlyselected patients [3-5]. However, the long-term benefit of operative treatment is only modest for a
number of patients due to comorbidities like Alzheimer’s disease (AD) [3-7].
Despite having history dating back to the 1960s, the molecular mechanisms of iNPH remain to be
discovered [1, 6-8]. Concomitant AD seems to be frequent in patients with iNPH [7, 8]. However,
the prevalence of APOEε4, the most common genetic risk factor of AD, in patients with iNPH and
age-adjusted controls seems to be similar [9]. Furthermore, there is no benefit in shunting patients
with solitary AD [10].
Familial occurrence of iNPH was first introduced by Portenoy et al. (1984) having discovered
siblings with typical neurological symptomatology, neuroradiologically confirmed ventriculomegaly
and favourable response to shunt surgery [11]. Since then a number of pedigrees with multiple
affected relatives have been documented [12-18]. According to our recent nation-wide study, the
potential familial occurrence of iNPH can be up to 16% [18]. Summing up these findings, there may
be inherited traits predisposing patients to suboptimal CSF dynamics and ultimately manifesting as
iNPH [18]. The first genetic finding associated with iNPH-related ventriculomegaly was the copy
number loss of SFMBT1, a gene that is expressed e.g. in choroid plexus, which is the primary site
of CSF formation [19, 20].
Synthesizing the idea of inheritability into molecular level, several hypotheses can be assessed.
The increased prevalence of AD-related pathology among iNPH patients may theoretically be
caused by inadequate β-amyloid clearance due to impaired CSF circulation [8]. Disproportional
subarachnoid spaces may indicate a selective block of CSF absorption and activation of potential
compensatory pathways of CSF flow, which may play a key role in the pathogenesis of iNPH [21-
22]. Considering ventriculomegaly in iNPH and other forms of hydrocephalus, the ependyma with
potentially altered gene expression could also play a role in iNPH [21-24]. Whether this
hypothetical dysfunction would be the primary cause or reactive to CSF flow disturbance is also
intriguing.
In this study, we examined 24 established AD-related single-nucleotide polymorphisms [25-27] in
patients with iNPH and healthy controls to further provide insights into the common molecular
mechanisms of AD and iNPH.
MATERIALS AND METHODS
Ethics statement
Kuopio University Hospital (KUH) Research Ethical Committee approved the study. All patients
gave an informed consent to the study. Patients with lower cognitive capacity were included with
the support of the next of kin but also always asking and respecting patient’s own will.
Study sample
This study included 188 iNPH patients from Kuopio University Hospital (KUH) catchment area
(Table 1). Patients were shunted during the years 1993-2009. Patients underwent a careful
preoperative assessment carried out by a neurologist. At least one triad symptom with
characteristic findings (Evans’ index > 0.3) in CT or MRI was required in order for the patient to be
included. Patients were further assessed in the Neurosurgical unit with additional diagnostic
procedures, including a 24-hour intracerebral pressure (ICP) monitoring with a perioperative right
frontal cortical biopsy [8, 9]. All iNPH patients were shunted and the shunt-response was
determined clinically after three months had passed from the shunt surgery by a neurosurgeon as
changes in gait, urinary incontinence and memory (no change, improvement, regression). The
control group of 688 subjects was gender-adjusted without any signs of cognitive decline in
neuropsychological examination [9].
Neuropathological samples
Frontal cortical biopsies were fixed in formalin overnight, embedded in paraffin and then sectioned
(7 m) and stained with hematoxylin-eosin and monoclonal antibodies against Aβ (6F/3D, M0872;
Dako; dilution 1:100; pre-treatment 80% formic acid 1 h) and hyperphosphorylated tau protein
(Hpτ, AT8, Br-3; Innogenetics; dilution 1:30) [6, 28]. Aβ and Hpτ were evaluated either present or
absent by a neuropathologist as described previously [28]. The Aβ percentage was quantified from
high-resolution images and reported as the area of immunostained Aβ in square millimetres [28].
Radiological analysis
The radiological data of the iNPH patients, collected since 1990 with both CT and MRI scanners
was evaluated in a subgroup analysis. The evaluation consisted of both visually-assessed and
measurement-based markers by using a Sectra-PACS platform (IDS7, version 15.1.20.2, Sectra
AB, Linköping, Sweden) [29]. Medial temporal lobe atrophy was evaluated by Scheltens protocol
[30] and white matter changes with Fazekas grading [31]. Disproportionality of sylvian and
suprasylvian subarachnoid spaces was graded from 0 to 2 (0 = none, 1 = mild, 2 = severe). With
respect to the control group, no comparable radiological data was available.
Genetic analyses
In addition to APOE, 23 AD-related single-nucleotide polymorphisms (FRMD4A, CR1, BIN,
CD2AP, CLU, MS4A6A, MS4A4E, PICALM, ABCA7, CD33, INPP5D, HLA_DRB5, NME8, EPHA1,
PTK2B, CELF1, SORL1, FERMT2, SLC24A, DSG2, CASS4) were examined between groups.
Polymorphisms and their association with AD have been previously discovered in GWAS-studies
with large samples [24-26]. DNA was extracted from venous blood samples. SNPs were genotyped
by using a Sequenom iPlex platform (Sequenom, Hamburg, Germany) [28]. With respect to SNPs
association analyses made in Hardy-Weinberg Equilibrium, a call rate of 90% was required for
inclusion.
Statistical analyses
Statistical analyses were made with an additive model by using a binary logistic regression
analysis with adjustments for age, sex and APOE. The following protocol was applied: a unilateral
analysis of all the SNPs and the final multivariate model with SNPs was selected according to the
unilateral analyses with p < 0.1. Analyses were performed with SPSS statistical software (version
22.0, SPSS Inc., Chicago, Illinois).
RESULTS
Results of the primary comparisons and the analysed loci are described in Table 2. The only
significant difference found was associated with the prevalence of NME8 rs2718058_G SNP
(AA/AG/GG), which was 51.1%, 42.4% and 6.5% in patients with iNPH and 56.0%, 36.6% and
7.4% amongst controls (p = 0.014, adjusted to all other SNPs, Table 2, non-significant after
Bonferroni correction for multiple testing).
The presence of the Aβ accumulation alone (p = 0.158) or with the hyperphosphorylated tau (p =
0.774) in the brain biopsies of iNPH patients or response rate to the shunt (p = 0.475) did not vary
between the NME8 alleles.
Periventricular white matter changes were more frequent amongst patients with the NME8 AAgenotype compared with the AG-genotype (p = 0.017, Table 3). No significant differences in the
prevalence of diabetes, hypertension or heart disease were detected between the genotypes
(Table 4).
DISCUSSION
Genetic insights into iNPH
The most interesting finding of this study was the significant allelic variation of NME8 in iNPH. Due
to the limited statistical power, the nominal p-value was used to select this gene for further
evaluation. Instead of correlating with the AD-related pathology in the frontal cortical brain biopsy,
the allelic variation of NME8 is associated with periventricular white matter changes and thus
seems to be related to iNPH independently of AD.
NME8, also known as TXNDC3, is located in 7p14.1 and encodes a thioredoxin –nucleoside
diphosphate kinase enzyme [27, 32]. Duriez et al. [33] discovered a nonsense mutation of NME8 in
the primary ciliary dyskinesia (PCD, type 6) manifesting as situs abnormalities, infertility, chronic
otosinopulmonary disease, digital clubbing (associated with bronchiectasis), and in some cases as
hydrocephalus. Dynein arm deficits as well as changes in the ciliary ultrastructure are molecular
changes discovered in patients with PCD [34].
Although it is unclear whether and to which extent NME8 is expressed in the human brain, the
potential ciliopathic features of iNPH are intriguing. The large-scale GWAS analyses of Lambert et
al. [27] discovered the association of NME8 rs2718058 SNP with AD (G vs. A; OR 0.93). Liu et al.
[35] further examined the relation of the allelic variation of SNPs to MRI-volumetry and CSFbiomarkers in patients with AD, MCI and controls. They discovered no significant correlation of any
genotype with CSF Aβ42 or phospho-tau levels [35]. However, the risk-genotype AA correlated
with occipital gyrus atrophy among those with AD. The AG-genotype, also overexpressed in our
sample set of iNPH patients, significantly correlated with milder hippocampal atrophy and elevated
periventricular glucose metabolism rates in FDG-PET-imaging [35]. In our sample set, the AAgenotype was associated with periventricular white matter degeneration but not with
temporomesial atrophy. Despite the different neuroradiological markers and scanners used in our
study, the allelic variation of NME8 seems to correlate with periventricular white matter changes.
This supports the link between the neurodegenerative mechanisms and the NME8 allelic variation.
The risk genotype (AA) correlated with AD in a large GWAS cohort and additionally seems to have
a tendency to correlate with central atrophy indicating that there may be overlapping
pathophysiologic mechanisms in iNPH and AD. Interestingly, vascular comorbidities related to
iNPH were not overexpressed among patients with the AA-genotype, suggesting that the genetic
variation may independently expose the patient to white matter lesions (WMLs) [36]. In addition to
AD, the plausible role of NME8 is worth further study in iNPH.
Overall, these findings together with the ciliopathic manifestations of NME8, as well as animal
models indicating the link between thioredoxin domain mutations and oxidative stress, suggest that
our findings may offer a novel perspective into the elusive pathophysiology of iNPH [37].
Suboptimal ependymal cilia function with plausible environmental factors may lead to a dysfunction
of the CSF circulation resulting as hydrocephalus [38].
Why this plausible pathway would manifest at senescence in those with iNPH is unclear. One
theory leaning on previous neurotraumatological studies is that the dysfunction of cilia is so minor
that additional stress factors are required to induce cilia loss or dysfunction, and that the decreased
CSF flow ultimately manifests as hydrocephalus [38]. Whether or not more evidence of neuronal
damage or ciliopathic features will be discovered, the therapeutic applications of neurotrophic
factors, such as the ciliary neurotrophic factor (CNTF), are worth further studying also in iNPH [39].
Therefore, our very preliminary findings motivate further study on the cilia structure and function in
iNPH.
Furthermore, the genes affecting cytoskeleton, basal lamina and cell polarity seem to play a role in
the hydrocephalic mouse model and the cilia itself may affect ependymal cell polarity [40].
Therefore, although not further evaluated in this study due to only non-significant tendencies,
FRMDA4, CASS4 and CD2AP may be worth taking into account in the further genetic studies of
iNPH with larger populations. Targeted genome-wide analyses on the pedigrees of interest offer
potential novel discoveries in the future [18]. Until now, the copy number loss of the SFMBT1-gene
was the only genetic factor somehow connected to iNPH and may also be worth further study in
different populations [19, 20].
The most notable weakness of this study is the modest sample size, considering that most of the
SNPs have been discovered in sample sizes of thousands. After the Bonferroni correction, allelic
variations of NME8 or any other polymorphism did not remain significant in the analyses (data not
shown). On the other hand, differences discovered in a moderate sample size may indicate that
some common genetic mechanisms may be more specific in iNPH than AD, explaining the partially
comorbid occurrence of these conditions [6]. Our sample is well-selected and mainly shuntresponsive (86.2%). The prevalence of the comorbid clinical AD is rather low (8.9%) considering
the mean age of 79.3 years. Ninety-nine out of the 188 patients with iNPH had neither β-amyloid
nor tau in the frontal cortical biopsy. In this selected subsample, the prevalence of the NME8 AGgenotype was even higher (44%, data not shown).
This study further suggests that iNPH has pathophysiological features (Fig 1) and genetic factors
independent of those associated with AD. In line with Pyykkö et al. [9] and Yang et al. [41], neither
the APOE epsilon 4 allele nor most of the later-discovered novel AD-loci [23-25] seem to have
notable variations in patients with shunt-operated iNPH. In conclusion, the potential link between
the NME8 polymorphism and iNPH requires further replication.
In conclusion, the modest allelic variation of NME8 should be interpreted cautiously due to the
limited sample size. However, the correlation of periventricular changes and the potential role in
the cilia function, cell polarization and cytoskeleton function support the biological link of NME8
with iNPH. Suboptimal reserves in these cellular processes along with environmental burden could
increase the vulnerability for iNPH to develop in the elderly.
ACKNOWLEDGMENTS
We would like to acknowledge Marita Parviainen, RN, for the maintenance of KUH NPH Registry
and Anniina Savolainen, MSc, for the revision of the English language. The study was partially
funded by Emil Aaltonen foundation, Academy of Finland, Kuopio University Hospital (VTR grant
V16001, 5252614), Sigrid Juselius Foundation, Cultural foundation of Northern Savo, VPH
Dementia Research Enabled by IT VPH-DARE@IT (no 601055), JPND-CO-FUND program (no
301220) and the Strategic Funding of the University of Eastern Finland.
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TABLE 1 Clinical characteristics and brain biopsy findings in 188 shunt-operated iNPH
patients
Variable
Frequency (%)
Gender (F/M)
109/79 (58% / 42%)
Mean age
79.3 (SD 7.5)
Shunt-response
162/185 (87.6%)
Concomitant clinical Alzheimer’s disease
13/146 (8.9%)
Neuropathological features
Aβ-/tauAβ+/tauAβ+/tau+
Aβ-/tau+
99 (52.9%)
57 (30.5%)
27 (14.4%)
4 (2.1%)
MMSE
22.3 (SD 5.1)
GENE
SNP
TABLE 2 Allelic variation of 23 SNPs in patients with iNPH and controls without known cognitive decline
Model
iNPH patients n (%)
Controls n (%)
Age,
gender
Age,
gender
APOE,
other
SNPs
p
p
rs7081208_A
0.632
FRMD4A
rs2446581_A
0.635
FRMD4A
rs17314229_T
0.059
CR1
rs3818361_T
0.347
FRMD4A
0.147
Odds ratio
(Model 2)
11
12
22
tot
11
12
22
tot
0.82
GG/GA/AA
123 (65.4%)
57 (30.3%)
8 (4.3%)
188
420 (63.8%)
211 (32.1%)
27 (4.1%)
658
1.06
GG/AG/AA
126 (67.0%)
58 (30.9%)
4 (2.1%)
188
467 (71.4%)
172 (26.3%)
15 (2.3%)
654
0.62
CC/CT/TT
164 (87.2%)
24 (12.8%)
0 (0%)
188
549 (82.8%)
104 (15.7%)
10 (1.5%)
663
1.15
CC/CT/TT
128 (68.1%)
51 (27.1%)
9 (4.8%)
188
438 (64.7%)
220 (32.5%)
19 (2.8%)
677
1.07
TT/TC/CC
115 (62.5%)
63 (34.2%)
6 (3.3%)
184
408 (60.4%)
226 (33.5%)
41 (6.1%)
675
0.73
GG/GC/CC
126 (67.0%)
55 (29.3%)
7 (3.7%)
188
431 (63.8%)
207 (30.6%)
38 (5.6%)
676
BIN
rs744373_C
0.702
CD2AP
rs9349407_C
0.098
CLU
rs11136000_T
0.787
0.93
CC/CT/TT
66 (35.9%)
85 (46.2%)
33 (17.9%)
184
227 (34.0%)
339 (50.7%)
102 (15.3%)
668
MS4A6A
rs610932_A
0.573
0.89
AA/AC/CC
96 (51.1%)
75 (39.9%)
17 (9.0%)
188
346 (54.7%)
274 (40.1%)
63 (9.2%)
683
MS4A4E
rs670139_C
0.786
1.15
AA/AC/CC
71 (37.8%)
85 (45.2%)
32 (17.0%)
188
268 (40.1%)
311 (46.5%)
90 (13.5%)
669
PICALM
rs3851179_A
0.733
1.05
GG/GA/AA
80 (42.6%)
88 (46.8%)
20 (10.6%)
188
293 (43.3%)
282 (41.7%)
101 (14.9%)
676
ABCA7
rs3764650_G
0.791
0.65
TT/TG/-
177 (94.1%)
11 (5.9%)
188
658 (97.1%)
20 (2.9%)
CD33
rs3865444_T
0.698
1.05
GG/GT/TT
76 (40.4%)
90 (47.9%)
22 (11.7%)
188
305 (45.1%)
287 (42.5%)
84 (12.4%)
676
INPP5D
rs35349669_C
0.757
1.00
TT/TC/CC
53 (28.8%)
92 (50.0%)
39 (21.2%)
184
174 (27.3%)
334 (52.4%)
129 (20.3%)
637
HLA_DRB5
rs9271192_C
0.309
0.87
AA/AC/CC
77 (41.8%)
84 (45.7%)
23 (12.5%)
184
242 (38.2%)
302 (47.7%)
89 (14.1%)
633
0.110
0.014
678
NME8
rs2718058_G
0.042
1.57
AA/AG/GG
94 (51.1%)
78 (42.4%)
12 (6.5%)
184
356 (56.0%)
233 (36.6%)
47 (7.4%)
636
EPHA1
rs11771145_A
0.883
0.93
GG/AG/AA
72 (39.1%)
83 (45.1%)
29 (15.8%)
184
219 (34.7%)
311 (49.2%)
102 (16.1%)
632
PTK2B
rs28834970_C
0.557
0.88
TT/CT/CC
72 (39.1%)
92 (50.0%)
20 (10.9%)
184
223 (36.6%)
313 (49.2%)
90 (14.2%)
636
7 (3.8%)
184
411 (64.5%)
196 (30.8%)
30 (4.7%)
637
184
604 (95.0%)
32 (5.0%)
CELF1
rs10838725_C
0.808
0.99
TT/CT/CC
116 (63.0%)
61 (33.2%)
SORL1
rs11218343_C
0.323
1.66
TT/CT/-
174 (94.6%)
10 (5.4%)
FERMT2
rs17125944_C
0.657
0.91
TT/CT/CC
151 (82.1%)
31 (16.8%)
2 (1.1%)
184
518 (81.2%)
111 (17.4%)
9 (1.4%)
638
SLC24A4
rs10498633_T
0.244
0.77
GG/TG/TT
133 (72.3%)
47 (25.5%)
4 (2.2%)
184
420 (65.9%)
198 (31.1%)
19 (3.0%)
637
DSG2
rs8093731_T
0.545
0.72
CC/TC/-
182 (98.9%)
2 (1.1%)
184
625 (98.0%)
13 (2.0%)
CASS4
rs7274581_C
0.096
0.39
TT/TC/CC
179 (97.3%)
5 (2.7%)
184
601 (94.5%)
34 (5.3%)
0.115
0 (0%)
636
638
1 (0.2%)
636
Table 3 Differences of neuroradiological characteristics and NME8 variation among patients with iNPH
Radiological variable
n
Periventricular white matter changes (Fazekas)
0-1
2-3
145
Deep white matter changes (Fazekas)
0-1
2-3
141
White matter changes in brainstem (Fazekas)
0
1-2
54
Pooled temporomesial atrophy (Scheltens)
0-1
2
3-4
70
Evans index
150
Disproportionality of the SA-spaces
No
Mild
Severe
146
Superior convexity subarachnoid spaces
Decreased
Normal
146
NME8 genotype
AA
AG
GG
30 (41.1 %)
43 (58.9 %)
41 (65.1 %)
22 (34.9 %)
5 (55.6 %)
4 (44.4 %)
0.017
35 (50.7 %)
34 (49.3 %)
44 (69.8 %)
19 (30.2 %)
5 (55.6 %)
4 (44.4 %)
0.088
19 (76.0 %)
6 (24.0 %)
24 (82.8 %)
5 (17.2 %)
7 (21.2 %)
18(54.5 %)
8 (24.2 %)
11(31.4 %)
11 (31.4 %)
13 (37.1 %)
0
2 (100 %)
0
0.175
0.389 (0.044)
0.376 (0.049)
0.384 (0.046)
0.735 (AA vs. GG)
0.647 (AG vs. GG)
8 (10.7 %)
24 (32.0 %)
43 (57.3 %)
6 (9.7 %)
20 (32.3 %)
36 (58.1 %)
3 (33.3 %)
5 (55.6 %)
1 (1.3 %)
0.071
59 (78.7 %)
16 (21.3 %)
44 (71.0 %)
18 (29.0 %)
5 (55.6 %)
4 (44.4 %)
0.255
p
0.736
TABLE 4 Vascular comorbidities and allelic variation of NME8 rs2718058_G
AA
AG
Hypertension
52/94 (55.3 %)
41/78 (52.6 %)
Diabetes mellitus
23/94 (24.5 %)
16/78 (20.5 %)
Coronary disease
20/94 (21.3 %)
8/78 (10.3 %)
Heart insufficiency
3/94 (3.2 %)
5/78 (6.4 %)
Atrial fibrillation
6/94 (6.4 %)
9/78 (11.5 %)
Hyperlipidemia
41/94 (43.6%)
25/53 (32.1%)
GG
8/12 (66.7 %)
3/12 (25 %)
1/12 (8.3 %)
2/12 (16.7 %)
0/12
4/12 (33.3%)
p
0.689
0.818
0.096
0.124
0.225
0.290
Figure 1
Genetic factors
affecting resilience
of ependymal ciliary
function, survival
and polarity
Familial iNPH
with higher
genetic
vulnerability?
Family history
Genetics
MRI (AVIM, DESH)
Ageing, vascular
burden,
deterioration of
ependymal function
and CSF circulation
PRECLINICAL
PHASE
CLINICAL PHASE
Clinical iNPH with
symptoms and
ventriculomegaly
Early diagnosis and
management.
Figure Legends
Figure 1. Hypothesised disease course of iNPH
AVIM: asymptomatic ventriculomegaly, DESH: disproportionality between sylvian and suprasylvien
subarachnoid spaces