Association of the RAGE G82S polymorphism with Alzheimer's disease.

Abstract

The receptor for advanced glycation end-products (RAGE) has been implicated in several pathophysiological processes relevant to Alzheimer's disease (AD), including transport and synaptotoxicity of AD-associated amyloid beta (Abeta) peptides. A recent Chinese study (Li et al. in J Neural Transm 117:97-104, 2010) suggested an association between the 82S allele of the functional single nucleotide polymorphism (SNP) G82S (rs2070600) in the RAGE-encoding gene AGER and risk of AD. The present study aimed to investigate associations between AGER, AD diagnosis, cognitive scores and cerebrospinal fluid AD biomarkers in a European cohort of 316 neurochemically verified AD cases and 579 controls. Aside from G82S, three additional tag SNPs were analyzed to cover the common genetic variation in AGER. The 82S allele was associated with increased risk of AD (P (c) = 0.04, OR = 2.0, 95% CI 1.2-3.4). There was no genetic interaction between AGER 82S and APOE epsilon4 in producing increased risk of AD (P = 0.4), and none of the AGER SNPs showed association with Abeta(42), T-tau, P-tau(181) or mini-mental state examination scores. The data speak for a weak, but significant effect of AGER on risk of AD.

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DEMENTIAS - ORIGINAL ARTICLE
Association of the RAGE G82S polymorphism
with Alzheimer’s disease
Jonny Daborg•Malin von Otter•Annica Sjo ¨lander•
Staffan Nilsson•Lennart Minthon•Deborah R. Gustafson•
Ingmar Skoog•Kaj Blennow•Henrik Zetterberg
Received: 14 April 2010/Accepted: 7 June 2010/Published online: 22 June 2010
? The Author(s) 2010. This article is published with open access at Springerlink.com
Abstract
products (RAGE) has been implicated in several patho-
physiological processes relevant to Alzheimer’s disease
(AD), including transport and synaptotoxicity of AD-
associated amyloid b (Ab) peptides. A recent Chinese
study (Li et al. in J Neural Transm 117:97–104, 2010)
suggested an association between the 82S allele of the
functional single nucleotide polymorphism (SNP) G82S
(rs2070600) in the RAGE-encoding gene AGER and risk of
AD. The present study aimed to investigate associations
between AGER, AD diagnosis, cognitive scores and cere-
brospinal fluid AD biomarkers in a European cohort of 316
neurochemically verified AD cases and 579 controls. Aside
The receptor for advanced glycation end-
from G82S, three additional tag SNPs were analyzed to
cover the common genetic variation in AGER. The 82S
allele was associated with increased risk of AD (Pc= 0.04,
OR = 2.0, 95% CI 1.2–3.4). There was no genetic inter-
action between AGER 82S and APOE e4 in producing
increased risk of AD (P = 0.4), and none of the AGER
SNPs showed association with Ab42, T-tau, P-tau181 or
mini-mental state examination scores. The data speak for a
weak, but significant effect of AGER on risk of AD.
Keywords
Advanced glycosylation end product-specific receptor ?
SNP ? Haplotype
Alzheimer’s disease ? RAGE ? AGER ?
Introduction
Alzheimer’s disease (AD) is the most frequent form of
dementia, accounting for 50–60% of all cases (Blennow
et al. 2006). It is a genetically heterogeneous disease with
both familial and sporadic forms. The familial forms of AD
are very rare, but the few cases that exist all carry muta-
tions that in some way affect the processing of the amyloid
precursor protein (APP) in a manner that accelerates the
formation of synaptotoxic amyloid b (Ab) (Blennow et al.
2006). Pathologically, AD is characterized by senile pla-
ques containing aggregates of Ab, and neurofibrillary tan-
gles consisting of hyperphosphorylated tau protein. These
pathological hallmarks generally debut in the hippocam-
pus, a brain structure that is necessary for explicit learning
(Salmon and Bondi 2009). Consistent with hippocampal
pathology, the main clinical feature in patients with AD is
anterograde amnesia, and as the disease progresses, the
patients also develop other cognitive symptoms (Salmon
and Bondi 2009). In line with these clinical findings,
J. Daborg and M. von Otter contributed equally to this work.
J. Daborg (&)
Department of Physiology,
Institute of Neuroscience and Physiology,
Sahlgrenska Academy at the University of Gothenburg,
432, 405 30 Gothenburg, Sweden
e-mail: jonny.daborg@physiol.gu.se
M. von Otter ? A. Sjo ¨lander ? D. R. Gustafson ? I. Skoog ?
K. Blennow ? H. Zetterberg
Department of Psychiatry and Neurochemistry,
Institute of Neuroscience and Physiology,
Sahlgrenska Academy at the University of Gothenburg,
Gothenburg, Sweden
S. Nilsson
Department of Mathematical Statistics,
Institute of Mathematical Sciences,
Chalmers University of Technology, Gothenburg, Sweden
L. Minthon
Clinical Memory Research Unit,
Department of Clinical Sciences in Malmo ¨,
Lund University, Lund, Sweden
123
J Neural Transm (2010) 117:861–867
DOI 10.1007/s00702-010-0437-0

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animal research has shown that long-term potentiation
(LTP), a process that is widely believed to constitute the
synaptic substrate for learning and memory (Martin et al.
2000), is inhibited by low-n oligomers of Ab (Shankar
et al. 2008; Townsend et al. 2006; Walsh et al. 2002;
Klyubin et al. 2008).
The mechanisms by which Ab inhibit LTP have been
elusive and several suggestions have been made (Lauren
et al. 2009; Li et al. 2009; Origlia et al. 2009; Townsend
et al. 2007). It has, for example, been suggested that the
LTP-inhibiting effect of Ab depend on the receptor for
advanced glycation end-products (RAGE) (Arancio et al.
2004; Origlia et al. 2008, 2009). In addition, this protein
has been implicated in several other aspects of AD
pathology, such as inflammation, oxidative stress and
transport of Ab across the blood–brain barrier (Deane et al.
2003; Schmidt et al. 2009; Yan et al. 1996). Together, these
findings make the gene encoding RAGE (AGER) an
interesting candidate gene for AD. Indeed, a recent Chinese
case–control study presented evidence for an association
between the G82S single nucleotide polymorphism (SNP)
in AGER and AD (Li et al. 2010).
The RAGEreceptoris a multi-ligand receptor,and one of
its ligands is Ab (Yan et al. 1996). Several intracellular
pathwaysareactivatedbyRAGE(Lueetal.2009),andaside
from inhibiting LTP, RAGE activation can stimulate the
expression of b-site APP-cleaving enzyme 1 (BACE1) (Cho
et al. 2009), an enzyme that is necessary for the production
of Ab. Accordingly, Ab might exert positive feedback on its
own production. Moreover, RAGE can induce its own
expression throughactivation of the transcription factor NF-
jB, and thereby initiate yet another potentially hazardous
positive feedback loop (Lue et al. 2009).
There is, however, another facet of RAGE; a soluble
form, which is formed by alternative splicing (Ding and
Keller 2005) or proteolytic cleavage by the proteinase
ADAM 10 (Raucci et al. 2008). Soluble RAGE (sRAGE)
contains the ligand-binding site, but does not have the
signaling properties of full-length RAGE (flRAGE). As a
result, it could act as a decoy receptor by competing with
flRAGE for ligands, and thus have protective properties.
Indeed, studies have shown that sRAGE can reduce the
accumulation of Ab in the brains of mice (Deane et al.
2003), and that it can inhibit Ab aggregation (Chaney et al.
2005). In addition, it has been shown that sRAGE is
present at lower levels in the blood and brain of AD
patients (Emanuele et al. 2005; Nozaki et al. 2007).
Whatever role is most important for the development of
AD, be it the sword or the shield, remains to be seen. Either
way these findings highlight AGER as a most interesting
candidate gene for AD.
Although several susceptibility genes for AD have been
identified, few have been confirmed in independent
populations (Bertram and Tanzi 2010). Thus, independent
evaluation of the finding by Li et al. (2010) is warranted.
A distinguishing feature of our study is that all AD cases
were neurochemically verified, i.e., had low cerebrospinal
fluid (CSF) levels of the 42 amino acid isoform of Ab
(Ab1–42) as a sign of brain amyloid pathology and high
levels of total tau (T-tau) as a sign of cortical axonal
degeneration (Blennow et al. 2010). This approach reduces
the risk of including patients with other dementing illnesses
in the AD group.
Subjects and methods
Subjects
The case–control material consisted of 316 AD cases and
579 controls (Table 1). All individuals were of Caucasian
origin. All diagnoses were set according to the National
Institute of Neurological and Communicative Disorders and
Stroke—Alzheimer’sDisease
Association (NINCDS-ADRDA) criteria (McKhann et al.
1984) after detailed clinical investigation including medical
history, physical, neurological and psychiatric examination,
screening laboratory tests, and computed tomography of the
brain. No patient had a family history of autosomal domi-
nant dementia. For all 316 cases, previously determined AD
CSF biomarker levels of T-tau and Ab1-42were available,
and for a subgroup of cases (n = 111) P-tau181levels were
andRelated Disorders
Table 1 Demographics for Alzheimer’s disease cases and controls
Parameter Alzheimer’sControls
P values
No. of subjects 316579
Age (Years)76 ± 12.973 ± 4.9
\0.001
Sex
Female197 (62.3) 416 (71.8)0.003
Male
APOE-e4
0
119 (37.7)163 (28.2)
81 (25.6)430 (74.3)
\0.001
1164 (51.9) 136 (23.5)
271 (22.5)13 (2.2)
MMSEa
20 ± 5.129 ± 0.7
\0.001
–T-tau (pg/mL)
P-tau181(pg/mL)b
Ab42(pg/mL)
815 ± 389–
106 ± 46––
256 ± 78––
Data presented as n (%) or mean ± SD deviations
P values were calculated with v2-test for categorical parameters and
Mann–Whitney U test for continuous parameters
a(nAD= 277, ncontr= 579)
b(nAD= 111)
862J. Daborg et al.
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available as well (Table 1). CSF biomarker concentrations
were determined using INNOTEST ELISAs (Innogenetics,
Ghent, Belgium) as described elsewhere (Blennow et al.
1995; Vanderstichele et al. 2000; Vanmechelen et al. 2000).
Clinical diagnoses were set without knowledge of the
results from the biochemical and genetic analyses and vice
versa. The ambition was to study a pure AD group and
minimize the risk of including other dementias in the AD
group. Therefore, we only included cases with a typical
AD CSF biomarker profile, i.e. Ab42\400 pg/mL and
T-tau[400 pg/mL (Hansson et al. 2006; Zetterberg et al.
2003). Controls did not have dementia and did not show any
signs of psychiatric illness, malignant disease or systematic
disorder. Mini-mental state examination (MMSE) scores
(Folstein et al. 1975) were available for most AD cases
(n = 277) and all controls (Table 1). Potential controls with
MMSE scores below 28 were excluded to minimize the risk
of including incipient AD cases. APOE e4 carrier status was
known for all cases and controls.
Tag SNP selection
Single nucleotide polymorphism genotyping data covering
AGER (gene ID: 177) for the European population CEU
(Utah residents with ancestry from northern and western
Europe) were downloaded from the HapMap Genome
Browser (Phases 1 and 2—full dataset) at the International
HaplotypeMappingProject
hapmap.org) (HapMap-Consortium 2003) and processed
in the Haploview software (Barrett et al. 2005). Tag SNPs
were assigned using the Tagger function (Barrett et al.
2005). A minor allele frequency of C5% and pairwise
tagging with a minimum r2of 0.80 were applied to capture
the common variations within the whole gene. The func-
tional SNP G82S (rs2070600) was included using the
‘‘force include’’ option. The complete common genetic
variation of AGER was tagged for by G82S and three
additional tag SNPs: rs1800684, rs3131300 and rs1035798
(Table 2).
website(http://www.
Genotyping
Tag SNPs were genotyped using genomic DNA extracted
from blood tissue. TaqMan?Pre-Designed SNP genotyp-
ing assays (Applied Biosystems, Foster City, CA, USA)
were used (Table 2) according to the TaqMan Allelic
Discrimination technology (Livak 1999) on the ABI
PRISM 7900HT Sequence Detection System (Applied
Biosystems, Foster City, CA, USA).
Statistical analyses
Statistical
AD cases and controls were performed with SYSTAT11
(SYSTAT Software GmbH, Erkrath, Germany) using
v2-test for categorical parameters and using Mann–Whit-
ney U test for continuous parameters. The effects of known
risk factors, e.g., sex and APOE e4 were taken into con-
sideration by identifying significantly relevant covariates
for each outcome variable (disease risk, MMSE and levels
of AD CSF biomarkers) using forward stepwise logistic/
linear regression.
The genetic association analyses were performed using
HelixTree 6.3 (Golden Helix, Bozeman, MT, USA;
available at: http://www.goldenhelix.com). All tag SNPs
wereanalysed fordeviation
equilibrium. Single marker associations were performed
using logistic or linear regression including relevant
covariates in an additive model (SNP coded as minor
allele count). Haplotype analysis was carried out using
stepwise forward logistic or linear haplotype regression
always keeping the identified covariates in the model.
Haplotype frequencies were estimated using the expec-
tation–maximization algorithm (Excoffier and Slatkin
1995) and only haplotypes with a frequency of C5%
were included in the analysis. Detailed description of the
haplotype analyses have been given elsewhere (von Otter
et al. 2010). Difference in OR according to APOE e4
status was tested by adding an interaction term between
analyses comparingthedemographics in
from Hardy–Weinberg
Table 2 Overview of the SNPs studied
SNPa: NFE2L2
Genome positionb: Chr: 2Alleles d[Dc
Gene locationSNP type TaqMan assay
rs180068432259972 A[T
T[C
G[A (82G[82S)
T[C
Exon 1Synonymous C___3293838_10
rs313130032259912Intron 1Non-coding
Gly?Ser
Non-coding
C__11409142_10
rs2070600 (G82S) 32259421Exon 3 C__15867521_20
rs1035798 32259200 Intron 3C___8848032_1_
aPresented are the genotyped SNPs arranged according to location on the gene
bGenome positions were obtained from the HapMap Genome Browser (Phases 1 and 2—full dataset) at the International Haplotype Mapping
Project web site (http://www.hapmap.org)
cAlleles are given according to the sense sequence of the gene
Association of the RAGE G82S polymorphism 863
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APOE e4 and AGER. Corrected P values (Pc) of B0.05
were considered statistically significant. To correct for
multiple testing, Bonferroni correction for the number of
studied SNPs was used in all single marker analyses
(n = 4) and permutation tests with 10,000 permutations
were performed in the haplotype analyses.
Ethics
The study was approved by the ethics committees at the
University of Gothenburg and the University of Lund in
Sweden. The cases (or their closest relatives) and the
controls gave informed consent to participate in the study,
which was conducted in accordance with the provisions of
the Helsinki Declaration.
Results
Demographics
Mean age and sex distribution differed between cases and
controls (Table 1). As expected, the APOE e4 allele was
strongly overrepresented in the AD group when com-
paredwith thecontrol group
covariates were sex and APOE e4 for the risk association,
and APOE e4 alone for analysis of association with Ab42
and MMSE.
(Table 1).Identified
SNP genotyping
All markers were in Hardy–Weinberg equilibrium and had
a genotyping call rate[98%.
Association analyses
A significant association between the 82S allele (encoding
amino acid Ser of the non-synonymous SNP rs2070600)
and risk of AD was observed [Pc= 0.04, OR = 2.0 (95%
CI 1.2–3.4) per allele, Table 3]. When stratifying for
APOE e4 status, the carriers showed a significant associa-
tion between the 82S allele and risk of AD [P = 0.01,
OR = 2.6 (95% CI 1.2–5.3], while the non-carriers showed
a weaker non-significant association [P = 0.37, OR = 1.5
(95% CI 0.6–3.6) per allele, Table 4]. This OR difference
was, however, not significant (P = 0.4) according to an
interaction test between G82S and APOE e4 status in the
logistic regression. None of the four studied SNPs showed
association with Ab42, T-tau, P-tau181or MMSE (data not
shown). Haplotype analysis revealed no additional associ-
ation with risk of AD or with any of the other studied
outcomes (data not shown).
Discussion
In the present European case–control study, we show that
the G82S SNP (rs2070600) in AGER, the gene encoding
RAGE, is associated with increased risk of AD (Pc= 0.04,
OR = 2.0, 95% CI 1.2–3.4, n = 893). This finding cor-
roborates the finding of Li et al. (2010), who showed that
the G82S SNP in AGER was associated with AD diagnosis
in a Chinese case–control study. They reported an OR of
approximately 1.5, which is slightly lower than reported
here. These results reinforce each other and suggest that
Table 3 SNP frequencies and associations with risk of Alzheimer’s
disease
SNPGenotype Alzheimer’s Controls
P value (Pc)
rs1800684 TT 8 (2.6)9 (1.6) 0.54
AT72 (23.5)150 (26.1)
AA 227 (73.9)416 (72.3)
rs3131300 CC6 (1.9)13 (2.2)0.93
CT92 (29.4)167 (28.9)
TT 215 (68.7)398 (68.9)
rs2070600 AA (82S/82S)1 (0.3)0 (0.0) 0.01 (0.04)
AG (82S/82G)42 (13.3)35 (6.1)
GG (82G/82G) 273 (86.4) 542 (93.9)
rs1035798 TT16 (5.1) 48 (8.3)0.17
CT 115 (36.4)224 (38.7)
CC 185 (58.5)307 (53.0)
Presented are n (%)
At least 98% of the genotypes were successfully obtained for all SNPs
as specified by the n numbers for the genotypes
Risk associations were calculated using logistic regression in an
additive model (SNP coded as minor allele count) with sex and APOE
e4 allele count as covariates
The Pcvalue represents the Bonferroni corrected P value for the
number of studied SNPs (n = 4)
Table 4 G82S genotype frequencies and associations after stratify-
ing by APOE e4 carrier status
Alzheimer’s Controls
P value
APOE e4 non-carriers
AA (82S/82S) 0 (0.0)0 (0.0)0.37
AG (82S/82G) 7 (8.6)25 (5.8)
GG (82G/82G)
APOE e4 carriers
AA (82S/82S)
74 (91.4)404 (94.2)
1 (0.4)0 (0.0)0.01
AG (82S/82G) 35 (14.9)10 (6.8)
GG (82G/82G) 199 (84.7) 138 (93.2)
Presented are n (%)
Risk associations were calculated using logistic regression in an
additive model (SNP coded as minor allele count) with sex as a
covariate
864J. Daborg et al.
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AGER indeed is a susceptibility gene for AD. The lack of
association of the synonymous SNP (rs1800684) is in line
with previously published data (Blomqvist et al. 2006;
Emahazion et al. 2001) while the other SNPs have not been
previously analysed regarding risk of AD.
In the study by Li et al. (2010) the risk association of
82S carriers with AD (OR = 1.6) was found significant
among the APOE e4 non-carriers, but slightly weaker
(OR = 1.4) and not significant among the smaller group of
APOE e4 carriers. When analyzing the difference in these
two ORs by adding an interaction term in a logistic
regression model, no significant deviation was found. The
G82S effect on risk of AD differed slightly according to
APOE e4 status in our study as well. However, we had a
significant effect (OR = 2.6) among the APOE e4 carriers,
but a weaker non-significant effect (OR = 1.5) in the
APOE e4 non-carrier group. The difference between our
two ORs was also not significant. Taken together, the two
studies indicate that the risk associated with G82S is
independent of APOE e4 status. The lack of association of
AGER SNPs with CSF biomarkers for neuropathological
changes in AD and MMSE scores may be considered
reasonable in the light of the small effect size of AGER
G82S on disease risk.
What biological effects of a single amino acid substi-
tution in RAGE may explain the association with AD?
First, RAGE may affect both production and accumulation
of Ab in the brain (Chaney et al. 2005; Cho et al. 2009;
Deane et al. 2003). Because the G82S SNP is located in an
exon that codes for the ligand-binding site, it is possible
that the observed effect is related to ligand binding. The
82S variant has been shown to increase the ligand-binding
affinity of the receptor (Hofmann et al. 2002; Osawa et al.
2007). This could potentially lead to an increased signal-
ing, which in turn, would accelerate APP processing
through BACE1 [since BACE1 has been shown to be
positively regulated by RAGE (Cho et al. 2009)], and
thereby increase Ab production. In addition, an increased
transport of circulating Ab into the brain would be
expected because RAGE has been shown to transport Ab
across the blood–brain barrier into the brain (Deane et al.
2003). It seems unlikely that this is how the 82S variant
increases the risk for AD though, since we found no
association between G82S genotype and Ab levels. The
82S variant may on the other hand be more effective in
mediating the LTP-inhibiting effect of Ab (Arancio et al.
2004; Origlia et al. 2008, 2009), a hypothesis that remains
to be tested.
It is not entirely obvious that a higher affinity for ligand
binding should lead to an increased risk for AD since
sRAGE should also be affected, and hence, have an
increased propensity to scavenge Ab, thus increased pro-
tective properties. Nevertheless, this is not the case and an
explanation could be that flRAGE is engaged in positive
feedback mechanisms, thereby enhancing its own produc-
tion, thus giving little room for sRAGE to exert its pro-
posed protective mechanisms. This notion is supported by
the finding that flRAGE expression is increased in AD
brains (Lue et al. 2001; Miller et al. 2008). In addition, it
has been shown that 82S carriers have roughly half as
much circulating sRAGE when compared with 82G carri-
ers (Jang et al. 2007; Li et al. 2010), implying that the
increased ligand affinity of the receptor leads to a dysreg-
ulation of RAGE isoforms. In this context, it is interesting
to note that we found no association between G82S
genotype and Ab levels in CSF, since it implies that the
protective properties of sRAGE observed in animal models
of AD may be of limited clinical relevance.
It was recently shown that AGER deletion leads to lower
levels of Ab in 6 months old mice carrying the familial
Arctic (Arc) and Swedish (Swe) AD mutations. Interest-
ingly, this was not the case for 12 months old animals, and
surprisingly neither the 6 months nor 12 months old
knockout animals performed better than the control Arc/
Swe animals in a Y-maze memory test (Vodopivec et al.
2009). This is in conflict with the results from Fang et al.
(2010) showing that deletion of the intracellular signaling
domain in RAGE (dominant negative, DN-RAGE) has a
protective effect on memory function. One explanation for
these contradicting results could be that the two studies
used different memory testing paradigms. Another expla-
nation could be that DN-RAGE still has the possibility to
form sRAGE. A third piece in this knockout puzzle is the
study by Takuma et al. (2009) which showed that deletion
of AGER reduced the amount of intracellular Ab, p38
MAPK phosphorylation and Ab-induced mitochondrial
dysfunction in cultured cortical neurons. To summarize, it
seems like deletion of AGER leads to reduction in Ab and
its related pathology. The results on Ab levels by Vodop-
ivec et al. might be due to the highly pathogenic Arc/Swe
mutations, and might also suggest that RAGE is mainly a
contributing factor in the disease process highlighting the
importance of RAGE in the acquisition of sporadic AD. If
this is the case, one would expect age at onset to be
affected. Unfortunately, this analysis was not possible to
perform in our material, but it would be a valuable addition
in future replication studies.
Aside from the importance of identifying genetic risk
factors, which might aid future therapeutic strategies, and
early diagnosis, gene association studies constitute a bridge
between experimental animal research aiming in under-
standing the mechanisms of disease, and clinical research
on the actual patients whom the experimentalists aim to
aid, thereby lending further support to the findings made in
animal models of the disease. This is of great importance
since a lot of effort is put into understanding the etiology of
Association of the RAGE G82S polymorphism 865
123

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different diseases. By showing associations between dis-
ease and a gene under intense study, we can confirm that
the clues found in experimental model systems are relevant
to the disease under study, and thus, should be further
pursued.
In conclusion, our data, together with the findings by Li
et al. speak for a weak, but significant effect of AGER on
risk of AD. Further studies on independent and larger
cohorts are highly desired, as is the exploration of a pos-
sible association of AGER G82S with age at onset of AD.
Acknowledgments
technical assistance and Prof. Eric Hanse for helpful comments on the
manuscript. This work was supported by Grants from the Swedish
Research Council, the Alzheimer’s Association (NIRG-08-90356),
the Royal Swedish Academy of Sciences, the Sahlgrenska University
Hospital, the Go ¨teborg Medical Society, Swedish Brain Power, Stif-
telsen fo ¨r Gamla Tja ¨narinnor, Gun och Bertil Stohnes stiftelse,
Handlanden Hjalmar Svensson Foundation, the A˚hle ´n Foundation,
Magn. Bergvall’s Foundation and the Alzheimer Foundation, Sweden.
Funding sources did not influence the design and conduct of the
study; collection, management, analyses, and interpretation of the
data; or preparation, review, or approval of the manuscript.
We thank Mrs Mona Seibt Palme ´r for excellent
Open Access
Creative Commons Attribution Noncommercial License which per-
mits any noncommercial use, distribution, and reproduction in any
medium, provided the original author(s) and source are credited.
This article is distributed under the terms of the
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