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INTRODUCTION
Celiac disease (CeD) is an autoimmune disorder character-
ized by inflammation primarily in the small intestine, caused by
abnormal immune response to gluten ingestion [1]. Although
CeD primarily manifests its symptoms within the gastrointestinal
region, the disease does not limit itself to digestive issues; it also
has significant effects on other systems of the body, including the
nervous system [2]. This broader impact can be partially illustrat-
ed through the concept of the gut-brain axis, a bidirectional com-
munication network linking the gut and the brain. This so-called
gut-brain axis follows the intricate interactions between the gut
and the brain, which connects the enteric and central neurological
systems through a complex communication network [3]. Recent
studies show that CeD’s neurological involvement lies primarily in
the gut-liver-brain axis and may related to gluten-mediated patho-
genesis, including antibody cross-reaction, deposition of immune-
complex, direct neurotoxicity, and in extreme cases, vitamins or
nutrients deficiency [4].
Neurological disorders associated with CeD encompass a broad
range of conditions, including but not limited to ataxia, cognitive
impairment, epilepsy, headache, and neuropathy [5]. Addition-
Celiac Disease Increases the Risk of Multiple Sclerosis: Evidence
from Mendelian Randomization and the Role of CCL19
Seongjin Lim1†, Junhua Wu2†, Yeon Woo Kim1, Sun Woo Lim1, Juhee Shin3, Hyo Jung Shin4,
Sang Ryong Kim5 and Dong Woon Kim1*
1Department of Oral Anatomy & Developmental Biology, Kyung Hee University College of Dentistry, Seoul 02447, Korea,
2Department of Neurology, Southwest Hospital, ird Military Medical University (Army Medical University),
Chongqing 400038, China, 3Center for Cognition and Sociality, Institute for Basic Science (IBS), Daejeon 34824,
4Department Biochemistry, Eulji University School of Medicine, Daejeon 34824, 5School of Life Sciences,
Kyungpook National University, Daegu 41566, Korea
https://doi.org/10.5607/en25009
pISSN 1226-2560 • eISSN 2093-8144
Original Article
Celiac disease (CeD) is an autoimmune disorder triggered by gluten, primarily affecting the small intestine but potentially impacting other systems,
including the nervous system through the gut-brain axis. This study employed Mendelian randomization (MR) to explore the causal relationships
between CeD and several neurological disorders, with a particular focus on multiple sclerosis (MS). Utilizing genetic data from the OpenGWAS
and Finngen databases, we applied various MR methods, including Inverse Variance Weighted (IVW), IVW-multiplicative random effects (MRE),
weighted median (WM), MR-Egger, and robust adjusted profile score (RAPS), to investigate these associations. The analysis revealed no signifi-
cant causal relationship between CeD and several other neurological disorders, but a significant positive association with MS was found (IVW
OR=1.1919, 95% CI: 1.0851~1.3092, p=0.0002). Further analysis indicated that the mediator CCL19 plays a significant role in the pathway from
CeD to MS, suggesting that CCL19 may be a key factor in the immune response linking these conditions. This mediation effect highlights the po-
tential mechanism through which CeD increases the risk of developing MS. These findings emphasize the complexity of the relationship between
CeD and MS, indicating the need for further research to understand these connections better and their clinical implications.
Key words: Celiac disease, Alzheimer’s disease, Gut-brain axis, Mendelian randomization, Gluten-free diet
Submitted February 27, 2025, Revised March 5, 2025,
Accepted March 6, 2025
*To whom correspondence should be addressed.
TEL: 82-2-961-9298, FAX: 82-2-961-9594
e-mail: visnu528@khu.ac.kr
†These authors contributed equally to this article.
Copyright © Experimental Neurobiology 2025.
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This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License
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Seongjin Lim, et al.
ally, bacterial metabolites produced by CeD progression can seep
into the bloodstream from the intestinal lumen and may enter the
brain, triggering localized neuroinflammatory reactions [6]. The
exact mechanisms underlying these associations remain contro-
versial, raising questions about whether these neurological disor-
ders are directly caused by CeD or if they arise from secondary
effects as in gluten-mediated pathogenesis.
To address these questions, Mendelian randomization (MR) pro-
vides a potent method for elucidating causal links by using genetic
differences linked to CeD as instrumental variables (IVs). MR
aims to minimize confounding factors and reverse causation, pro-
viding insights into whether CeD is a causal factor for neurological
disorders or if observed associations are due to other underlying
reasons [7]. By leveraging genetic variations that are actively linked
to CeD, MR can help distinguish between direct causal effects and
those resulting from correlated but separated processes. It serves
as a valuable tool, particularly in situations in which randomized
controlled trials are deemed impractical and observational studies
may yield biased results due to confounding or reverse causation
[8].
Therefore, we conduct to investigate the causal relationship
between CeD and various neurological disorders, including de-
mentia, Alzheimer’s disease (AD), Parkinson’s disease (PD), amyo-
trophic lateral sclerosis (ALS), status epilepticus (SE), stroke, and
multiple sclerosis (MS), using MR analysis. These disorders are
selected due to their significant neurological impacts and potential
links to systemic inflammation and autoimmune processes trig-
gered by CeD. By exploring these connections, we seek to clarify
how CeD may contribute to these disorders and thereby enhanc-
ing our understanding of the gut-brain axis and its implications
for both diagnosis and treatment strategies in CeD and related
neurological conditions.
MATERIALS AND METHODS
Mendelian randomization and assumptions
This study is based on a multiple two-directional two-sample
MR using single-nucleotide polymorphisms (SNPs) to evaluate the
potential relationship between CeD as exposure and various neu-
rological disorders as outcomes, using the latest data from GWAS
(Genome Wide Association Study) and Finngen. Three underlying
hypotheses underpin MR: first, that genetic exposure predictors
are highly correlated with the exposure of interest; second, that
genetic exposure predictors are unaffected by confounders in the
exposure-outcome relation; and third, that genetic predictors are
only related to the outcome by directly influencing the exposure of
interest (i.e., the exclusion-restriction assumption) [9].
Data source for exposure and outcome
The data for exposure CeD was obtained from the OpenGWAS
database (GWAS ID: ieu-a-1058). There were 24,269 samples and
38,037 single-nucleotide polymorphisms, of which 97% were part
of the European demographic (cases: 12,041; controls: 12,228)
[10]. The dataset for outcomes of various neurological disorders
were collectively acquired from Finngen database, which only
studies European population; the data include dementia (finngen_
R11_F5_DEMENTIA), AD (finngen_R11_G6_ALZHEIMER),
PD (finngen_R11_G6_PARKINSON), ALS (finngen_R11_G6_
ALS), SE (finngen_R11_G6_STATUSEPI), stroke (finngen_R11_
C_STROKE), and MS (finngen_R11_G6_MS). All genomic data
used for this research are the most up-to-date and have been made
publicly available online.
Statistical analysis
In this study, MR, performed by R (version4.4.1) through the
TwoSampleMR package, was employed to investigate the causal
relationship between CeD and various neurological disorders,
using genetic variations as instrumental variables (IV). Establish-
ing CeD as the exposure and neurological disorders as outcomes,
MR leverages genetic variants, primarily SNPs, as proxies to esti-
mate the causal effects. We selected SNPs that were independent
(R2<0.001) and had a strong association with the exposure factor
(p<5×10-8); then, to enhance the precision and integrity of the
analysis, any SNPs that were common to both the exposure (CeD)
and the outcomes (neurological disorders) were carefully identi-
fied and excluded to prevent potential confounding effects using
the PhenoScanner database V2 [11]. While 5×10^(-8) has become
the conventional genome-wide significance p-value threshold for
common-variant GWAS, since the dataset for CD had only few in-
dependent SNPs at genome-wide significance, SNPs with p-values
<5×10^(−6) and p-values <5×10^(−5) that have higher cut-offs
were chosen to ensure the relevance and validity of the IVs [12].
The primary method in this study was the inverse-variance
weighted (IVW) approach, assuming all IVs are valid and free
from pleiotropy, which provides strong causal estimates under
these conditions [13]. It provides a consistent estimate of the caus-
al effect of the exposure on the outcome by combining the Wald
ratio estimates of the causal effect obtained from different SNPs
using a meta-analysis approach [14]. To further enhance robust-
ness, complementary MR methods were used, including IVW-
multiplicative random effects (MRE), weighted median (WE), and
MR-Egger. The IVW(MRE) method accounts for heterogeneity
among IVs, improving reliability when assumptions are partially
violated. The weighted median method is robust even if up to 50%
of IVs are invalid [15], while MR-Egger not only does not rely on
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Celiac Disease and AD with MR Study
non-zero pleiotropy but detects and controls bias from directional
pleiotropy, offering unbiased estimates more efficiently [16, 17].
Further reliability of the study was assessed using the MR robust
adjusted profile score (MR-RAPS) method, which provides unbi-
ased estimates even with numerous weak instruments and valida-
tion to both systematic and idiosyncratic pleiotropy [18]. This
comprehensive analysis allowed us to rigorously test for causal
relationships, correct for biases, and confirm the reliability of the
findings, thereby enhancing the overall strength and reliability of
our results and highlighting valuable insights of the genetic links
between CeD and neurological disorders.
Mediation analysis
We conducted a mediation analysis to connect CeD with neu-
rological disorders through circulating inflammatory proteins.
After performing a bidirectional MR, we found positive associa-
tions between CeD and inflammation-related circulating proteins
[19]. Next, we investigated the correlations between 91 circulating
inflammatory proteins with the outcome factor MS. Media-
tion analysis is to determine whether the effect of the exposure
(CeD) on the outcome (MS) is direct or is mediated through the
mediator. This helps in understanding the pathway and potential
mechanisms. MR mediation analysis involves using genetic vari-
ants as instrumental variables to assess the causal effect of the
exposure on the mediator, and subsequently, the mediator on the
outcome. This is done to estimate the indirect effect (through the
mediator) and the direct effect (not through the mediator) [20]. If
a significant mediation effect is found, it suggests that part of the
effect of the exposure on the outcome is explained by the media-
tor. This can identify potential targets for intervention to prevent
or treat the outcome. We selected the circulating proteins that
showed positive associations for further analysis. These selected
proteins were then analyzed to determine their correlation with
exposure factor CeD when considered as outcome factors MS.
When intermediary substances were found to be correlated with
both exposure and outcome factors, we calculated the proportion
of the mediating effect attributable to each intermediary substance
using delta method [21]. We calculated the proportion of media-
tion using the delta method, which involves estimating the indirect
effect of CeD on MS through CCL19 and comparing it to the
total effect. Specifically, we utilized the formula: [ \text{Proportion
of Mediation}=\frac{\text{Beta1} \times \text{Beta2}}{\text{Beta
all}} ] where Beta1 represents the effect of CeD on the mediator
(CCL19), Beta2 represents the effect of the mediator on MS, and
Beta all is the total effect of CeD on MS.
RESULTS
CeD on MS
In order to investigate the potential causal relationship between
CeD and MS, a two-way MR analysis was conducted. A total of
23 SNPs were carefully chosen for this study, with some SNPs ex-
cluded due to their confounding effects to ensure more accurate
results. The results shown in Fig. 1A, together with the scatterplots
of SNP effect sizes for CeD and MS in Fig. 1B, offer detailed in-
sights: the IVW method reveals an OR of 1.1919 with a 95% CI of
1.0851 to 1.3092, and a p-value of 0.0002, making it abundantly
clear that there’s a significant positive association between CeD
and MS. The IVW(MRE) method echoes this conclusion with
identical results (OR=1.1919, 95% CI=1.0851~1.3092, p=0.0002).
The WM method also backs this up, with an OR of 1.0992 (95%
CI=1.0266~1.1769, p=0.0067), affirming the positive impact of
CeD on MS. The MR Egger method shows a slightly different out-
come, with an OR of 1.1730 (95% CI=1.0270~1.3399, p=0.0285).
Although the CIs are wider due to the method’s sensitivity to plei-
otropy, it still suggests a significant association. The RAPS method,
yielding an OR of 1.2189 (95% CI=1.0474~1.4184, p=0.105), fur-
ther reinforces the presence of a positive association. Despite the
methodological differences between MR Egger and RAPS, which
are inherently designed to be more cautious due to their sensitiv-
ity to specific biases and outliers, the overall message is consistent:
there is a positive causal link between CeD and MS.
The slight difference in the results from the MR Egger and RAPS
methods can be attributed to the unique characteristics and as-
sumptions underlying these approaches. The MR Egger method
is particularly sensitive to directional pleiotropy, where genetic
variants influence the outcome through pathways other than the
exposure, which may lead to more conservative estimates and
wider CIs. Similarly, the RAPS method is designed to be robust
against weak instruments and outliers, which can also lead to more
cautious estimates. These differences in methodology can result in
slightly lower significance levels, but they still support the overall
conclusion of a positive association between CeD and MS.
Considering the findings from all the applied methods, the re-
sults consistently indicate a significant causal relationship between
CeD and MS. The odds ratios across the board are substantially
above 1, with p-values that consistently reach statistical signifi-
cance and CIs that do not cross 1. These findings strongly suggest
that CeD significantly increases the risk of developing MS, raising
the possibility that CeD could be a contributing factor in the onset
of MS.
Next we, we used the MR method to analyze the connection
between 91 circulating inflammatory proteins with MS [19].
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Seongjin Lim, et al.
We identified that a total of potential circulating inflammatory
proteins were associated with CeD, with positively or negatively
correlated. We then analyzed the correlation between these cir-
culating inflammatory proteins as the outcome factor with MS as
the exposure factor. We also calculated the mediating effect ratios.
After completing these steps, we identified a CCL19 as potential
mediators that reduce the likelihood of MS. Standard error (se),
Upper CI and Lower CI was calculated; se=sqrt(Beta 1 ^2*se1^2+
Beta 2 ^2*se2^2), Upper CI=Beta mediation (Beta1*Beta2)+
1.96*se, Lower CI=Beta mediation (Beta1*Beta2)-1.96*se. Z score
is 23.838 suggested that the effect is statistically significant, mean-
ing it is unlikely to have occurred by chance (Tab le 1).
Table 1. Mediation analysis of CeD on MS through circulating inflammatory proteins
Exposure CeD ieu-a-1058
Beta (SE), p value
Exposure-outcome
(Beta all)
Mediator-outcome
(Beta 2)
Exposure-Mediator
(Beta 1)
Mediator CCL19 GCST90274765 0.169297 (0.040066), 2.39E-05 0.126806 (0.0593), 0.032487 0.057913 (0.015971), 0.000288
Outcome MS finngen_R11
_G6_MS
Beta mediation%=Beta1*Beta2/Beta all=4.17.
Upper CI 95%=Upper CI 95%/Beta all=0.13109. Lower CI 95%=Lower CI 95%/Beta all=-0.04433.
Fig 1.
Fig. 1. (A) Mendelian randomization (MR) analysis of the association between celiac disease (CeD) and multiple sclerosis (MS). The analysis incorpo-
rates various MR methods, including inverse variance weighted (IVW) for primary analysis, and sensitivity analyses using IVW-multiplicative random
effects (MRE), weighted median, MR-Egger, and robust adjusted profile score (RAPS). Results are presented as odds ratios (OR) with 95% confidence
intervals (CI) per log-odds increment in MS risk, indicating the strength and direction of the association. (B) Scatterplot illustrating the potential effects
of the targeted single nucleotide polymorphisms (SNPs) on CeD versus MS. Each line's slope in the scatterplot represents the estimated MR effect for a
given method: a positive slope suggests a positive correlation, indicating that CeD may increase MS risk, while a negative slope would suggest a negative
correlation.
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Celiac Disease and AD with MR Study
CeD on PD and ALS
CeD on Parkinson’s disease
For this two-way MR analysis, 43 SNPs were selected to explore
the causal relationship between CeD (CeD) and Parkinson’s
disease (PD). The findings from these methods are shown in
Fig. 2A, and the scatterplots of SNP effect sizes for CeD and PD
can be seen in Fig. 2C. The results portrayed the following: The
IVW method yielded an OR of 1.0134 (95% CI=0.9720~1.0564,
p=0.5320). This result suggests no significant causal effect of
CeD on PD, as the CI crosses 1 and the p-value is not statistically
significant. The IVW(MRE) method produced identical results
(OR=1.0134, 95% CI=0.9720~1.0564, p=0.5320), corroborating
the findings of the IVW method. The WM method resulted in an
OR of 1.0018 (95% CI=0.9597~1.0458, p=0.9349), indicating no
significant relationship between CeD and PD. Similarly, the MR-
Egger method yielded an OR of 0.9806 (95% CI=0.9297~1.0342,
p=0.4751), which also indicates no significant effect of CeD on
PD. Finally, the RAPS method provided an OR of 1.0188 (95%
CI=0.9753~1.0643, p=0.4031), further suggesting that there is no
significant association.
In summary, all MR methods used in this analysis, including
IVW, IVW-MRE, weighted median, MR Egger, and RAPS, con-
sistently indicate that there is no significant causal relationship
between CeD and PD. The odds ratios across all methods are near
Fig 2.
Fig. 2. (A, B) Mendelian randomization (MR) estimates between A celiac disease (CeD) and Parkinson’s disease (PD) and B celiac disease (CeD) and
amyotrophic lateral sclerosis (ALS). Primary analysis (IVW) and sensitivity analysis (IVW-MRE, weighted median, MR-Egger, and RAPS were utilized.
Data are displayed as odds ratio (OR) and 95% confidence interval (CI) per log-odds increment in PD/ALS risk. (C, D) Scatterplot of potential effects
of the targeted SNPs on C CeD vs PD and D CeD vs ALS. The slope of each line corresponds to the estimated MR effect for each method used. Positive
slope indicates a positive correlation, and negative slope indicates a negative correlation.
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Seongjin Lim, et al.
1, and none of the CIs exclude 1, reinforcing the conclusion that
CeD does not significantly affect the risk of developing PD.
CeD on amyotrophic lateral sclerosis
A total of 43 SNPs were employed to carry out the two-way
MR analysis between CeD as exposure and ALS as outcome. The
results are illustrated in Fig. 2B alongside the scatterplots of SNP
effect sizes for CeD and ALS in Fig. 2D. The IVW method resulted
in an OR of 0.9877 (95% CI=0.9064~1.0764, p=0.7784). The
IVW(MRE) method produced identical results (OR=0.9877, 95%
CI=0.9064~1.0764, p=0.7784), indicating no significant causal
relationship between CeD and ALS. The WM method provided
an OR of 0.9370 (95% CI=0.8355~1.0508, p=0.2660), and the MR-
Egger method gave an OR of 0.9868 (95% CI=0.8801~1.1065,
p=0.8213); both methods suggest no significant association be-
tween CeD and ALS. The RAPS method also showed consistent
results with an OR of 0.9870 (95% CI=0.8988~1.0838, p=0.7838).
In total, all MR methods consistently indicate that there is no
significant causal relationship between CeD and ALS. The odds
ratios across all methods are close to 1, and the CIs do not exclude
1, reinforcing the conclusion that CeD does not significantly influ-
ence the risk of developing ALS.
CeD on status epilepticus and stroke
CeD on status epilepticus
A total of 43 SNPs were selected for this two-way MR analysis,
which aimed to investigate the potential causal relationship be-
tween CeD and SE. The results outlined in Fig. 3A, combined with
the scatterplots of SNP effect sizes for CeD and SE shown in Fig.
3C, illustrate the findings comprehensively. The IVW method
produced an OR of 1.0098 with a 95% CI of 0.9540 to 1.0689 and
a non-significant p-value of 0.7359, indicating no significant asso-
ciation between CeD and SE. The IVW(MRE) method provided
nearly identical results (OR=1.0098, 95% CI=0.9590~1.0633,
p=0.7102), reinforcing the conclusion that there is no significant
causal relationship between CeD and SE. Similarly, the WM meth-
od showed an OR of 1.0230 (95% CI=0.9411~1.1120, p=0.5938),
and the MR Egger method resulted in an OR of 1.0455 (95%
CI=0.9701~1.1268, p=0.2505). Finally, while the RAPS method
yielded an OR of 0.9994 (95% CI=0.9422~1.0599, p=0.9829). All
these methods suggest no significant association.
Taking all the methods into account, the results consistently
indicate no significant causal relationship between CeD and SE.
Although several of the OR are slightly above 1, the p-values across
all methods are far from statistically significant, with CIs consis-
tently including 1. This suggests that CeD does not significantly
affect the risk of developing SE, and any observed associations are
likely due to chance rather than a true causal effect.
CeD on stroke
In the two-way MR analysis, 42 SNPs were selected with CeD
as the exposure and stroke as the outcome to investigate whether
having CeD could affect the risk of developing stroke. Certain
SNPs were excluded to minimize confounding effects and en-
hance the reliability of the results. The results detailed in Fig. 3B
and the corresponding scatterplots of SNP effect sizes for CeD and
Stroke in Fig. 3D provide a thorough analysis. The IVW method
reported an OR of 1.0159 (95% CI=1.0011~1.0310, p=0.0350),
suggesting a statistically significant but small association between
CeD and stroke. The IVW(MRE) method produced identical re-
sults (OR=1.0159, 95% CI=1.0011~1.0310, p=0.0350), supporting
the IVW findings. However, the significance of these results is bor-
derline, and the effect size is small, which might limit the clinical
relevance. The weighted median method yielded an OR of 1.0091
(95% CI=0.9909~1.0276, p=0.3293), indicating no significant
association. Similarly, the MR Egger method reported an OR of
1.0117 (95% CI=0.9922~1.0316, p=0.2476), which also suggests no
significant effect of CeD on stroke. Interestingly, the RAPS method
resulted in an OR of 1.0242 (95% CI=1.0083~1.0403, p=0.0027),
showing a statistically significant association. The RAPS method
is particularly robust against weak instruments and the influence
of outliers, making it more sensitive to subtle associations. Despite
the statistically significant result from the RAPS method, the small
effect size and the CI close to 1 suggest that the practical or clinical
significance of this finding may be limited.
In conclusion, while the majority of methods do not show a
significant causal relationship between CeD and stroke, the RAPS
method does detect a marginally significant association. However,
the effect size is small, and the CI is narrow, indicating that even
though the association is statistically significant, it may not trans-
late into a substantial impact on stroke risk for individuals with
CeD. Therefore, these findings should be interpreted with caution.
CeD on dementia and Alzheimer's disease
CeD on dementia
In the two-way MR analysis, 43 SNPs were obtained with CeD
as the exposure and dementia as the outcome to explore whether
having CeD could influence the risk of developing AD. The re-
sults of these methods reflected in Fig. 4A, and the scatterplots of
SNP effect sizes for CeD and dementia are shown in Fig. 4C. The
IVW method as well as the IVW(MRE) method yielded an OR
of 0.9881, with a 95% CI ranging from 0.9675 to 1.0091. Since the
CI includes 1 and the p-value of 0.2638 is higher than 0.05, these
methods suggest no significant causal effect of CeD on dementia.
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Celiac Disease and AD with MR Study
The WM method produced an OR of 0.9834 with a Cl of 0.9601
to 1.0072, which also indicates a lack of a significant causal rela-
tionship. Similarly, the MR-Egger method resulted in an OR of
0.9841 (95% CI=0.9570~1.0120, p=0.2671), and the RAPS method
produced an OR of 0.9908 (95% CI=0.9705~1.0116, p=0.3832),
both implying no effect of importance of CeD on dementia.
Overall, the results across all MR methods suggest that CeD
does not have a significant causal impact on the risk of developing
Dementia. The odds ratios are close to 1, and the CIs consistently
include 1, while the p-values are way above the threshold for sta-
tistical significance. This indicates that there is no strong evidence
to support a causal relationship between CeD and dementia based
on the genetic data analyzed in this study.
CeD on Alzheimer’s disease
This two-way MR analysis between CeD and AD utilized a total
of 23 SNPs that were selected after excluding those with confound-
ing effects from the initial pool. The outcomes of these methods
are illustrated in Fig. 4B, while the scatterplots of SNP effect sizes
for CeD and AD are depicted in Fig. 4D. The results showed the
following: The IVW method produced an OR of 0.9688 (95%
CI=0.9431~0.9952, p=0.0206). This result suggests a statistically
significant inverse relationship between CeD and AD, indicating
that CeD might slightly reduce the risk of developing AD. The
IVW(MRE) method provided identical results (OR=0.9688, 95%
CI=0.9431~0.9952, p=0.0206), reinforcing the findings of the
IVW method. The WM method showed an OR of 0.9600 (95%
Fig 3.
Fig. 3. (A, B) Mendelian randomization (MR) estimates between A celiac disease (CeD) and status epilepticus (SE) and B celiac disease and Stroke. Pri-
mary analysis (IVW) and sensitivity analysis (IVW-MRE, weighted median, MR-Egger, and RAPS) were utilized. Data are displayed as odds ratio (OR)
and 95% confidence interval (CI) per log-odds increment in SE/Stroke risk. (C, D) Scatterplot of potential effects of the targeted SNPs on C CeD vs SE
and D CeD vs Stroke. The slope of each line corresponds to the estimated MR effect for each method used. Positive slope indicates a positive correlation,
and negative slope indicates a negative correlation.
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Seongjin Lim, et al.
CI=0.9318~0.9891, p=0.0074). This method also indicates a signif-
icant protective effect of CeD against AD, as the CI does not cross
1 and the p-value is well below 0.05, supporting the conclusion
of the IVW method. Similarly, the RAPS method, with an OR of
0.9727 (95% CI=0.9463~0.9997, p=0.0474), suggests a borderline
significant inverse relationship between CeD and AD, aligning
with the trends observed in the IVW and WM methods.
On the other hand, the MR Egger method yielded an OR of
0.9857 (95% CI=0.9503~1.0223, p=0.4472). This result differs
from the other methods, as the CI crosses 1 and the p-value is not
statistically significant, indicating no strong evidence for a causal
effect. Although the MR Egger method is valuable for detecting
potential violations of the assumptions underlying instrumental
variables, it can produce biased causal estimates and elevated Type
1 error rates under certain conditions [22]. Specifically, the method
may be compromised by violating the assumption that the vari-
ance of the association between the IV and the exposure is small
enough to be negligible [23]. Presence of outlier variants can also
distort the results.
All in all, while the MR Egger method shows less significance
and recommends caution in terms of interpretation, the consis-
tent results from the IVW, IVW-MRE, WM, and RAPS methods
point toward a weak but statistically significant inverse association
between CeD and AD. These findings suggest that CeD might
Fig 4.
Fig. 4. (A, B) Mendelian randomization (MR) estimates between A celiac disease (CeD) and dementia Alzheimer’s disease (AD) and B celiac disease
(CeD) and Alzheimer’s disease (AD). Primary analysis (IVW) and sensitivity analysis (IVW-MRE, weighted median, MR-Egger, and RAPS) were utilized.
Data are displayed as odds ratio (OR) and 95% confidence interval (CI) per log-odds increment in dementia/AD risk. (C, D) Scatterplot of potential
effects of the targeted SNPs on C CeD vs dementia and D CeD vs AD. The slope of each line corresponds to the estimated MR effect for each method
used. Positive slope indicates a positive correlation, and negative slope indicates a negative correlation.
9
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Celiac Disease and AD with MR Study
slightly lower the risk of AD, with the general trend across most
methods indicating a potentially meaningful protective effect. De-
spite the limitations of the MR Egger method, the general results
remain significant, supporting the hypothesis that CeD may have
a modest protective role against AD.
Gluten free diet and Alzheimer’s disease
The relationship between CeD and AD suggests a potential link
between gluten ingestion and AD, including cases of non-celiac
gluten sensitivity (NCGS). This underscores the need to investigate
how gluten consumption—whether related to CeD or not—might
influence the risk of developing AD, highlighting the importance
of exploring gluten’s impact on cognitive health.
Research indicates that a gluten-free diet (GFD) significantly re-
duces inflammation markers in both the gut and brain of CeD pa-
tients, leading to decreased systemic inflammation and potentially
offering protection against neurodegenerative diseases like AD [5].
Elevated interleukin-6 (IL-6), a pro-inflammatory cytokine, is no-
tably high in untreated CeD patients consuming gluten, but levels
decrease after a year on a GFD [24]. Studies show that adherence
to a GFD not only lowers pro-inflammatory cytokines but also
improves cognitive function in CeD patients, suggesting effective
gluten management may safeguard against neurodegenerative dis-
eases [25].
Beyond CeD, it is crucial to examine gluten’s effects on cognitive
health in individuals without CeD, particularly those with NCGS.
NCGS involves adverse reactions to gluten without CeD or wheat
allergy and can manifest as various extra-intestinal symptoms, in-
cluding neurological issues [26]. Conditions like cerebellar ataxia
and peripheral neuropathy have been linked to NCGS, indicating
that gluten-related inflammation can affect the nervous system
even in those without CeD [27, 28]. This aligns with evidence
suggesting gluten sensitivity may lead to systemic inflammation
impacting brain health [29].
In individuals with NCGS, gluten ingestion has been associated
with neurological symptoms, and systemic inflammation may dis-
rupt brain function [30]. Mechanisms may include a compromised
blood-brain barrier (BBB) and heightened neuroinflammatory re-
sponses [31]. Increasing evidence suggests gluten may exacerbate
neuroinflammation, potentially accelerating cognitive decline [32].
Moreover, gluten-related neuropathies can negatively affect quality
of life and contribute to cognitive decline. However, a recent study
found no significant association between long-term gluten intake
and cognitive decline among U.S. women, indicating that gluten’s
impact on cognitive health might be influenced by overall diet and
individual health conditions [33].
In light of these findings, we conducted MR analyses to explore
the impact of a GFD on AD (GWAS ID: ukb-b-11189; cases: 1,376,
controls: 63,573) (Fig. 5). Our results indicate that a GFD does
not significantly affect AD risk, emphasizing the need for further
research to clarify this relationship. This suggests that connections
between gluten ingestion and AD may be influenced more by
environmental factors than the genetically mediated risk seen in
CeD. Understanding these mechanisms is vital for developing tar-
geted dietary strategies to manage cognitive health across diverse
populations.
DISCUSSION
CeD and MS
The findings from various Mendelian randomization (MR)
methods, including IVW, IVW(MRE), WM, and RAPS, indicate a
positive association between celiac disease (CeD) and an increased
risk of multiple sclerosis (MS). This suggests that individuals with
CeD may have a heightened risk of developing MS, implying that
immune dysregulation in CeD could contribute to MS susceptibil-
ity and offering insights into shared mechanisms underlying these
autoimmune disorders.
To understand the connection between CeD and MS, it’s essen-
tial to explore the immunopathogenic mechanisms linking these
conditions. In CeD, the immune response is triggered by gluten
ingestion, while MS involves an autoimmune attack against the
myelin sheath, leading to demyelination and neurological dys-
function [34]. Although the primary targets differ, both conditions
can induce widespread inflammation affecting various systems.
CeD primarily impacts the gastrointestinal tract, whereas MS
targets the CNS. The systemic inflammation characteristic of CeD
may extend its effects to the CNS, potentially contributing to MS
pathogenesis [35]. Gluten ingestion leads to pro-inflammatory
cytokine production, activating microglia—resident immune cells
in the CNS—which is central to neuroinflammation in MS [36].
Epidemiological studies suggest that individuals with CeD may
be at higher risk for MS. The coexistence of both conditions high-
lights shared pathogenic mechanisms, such as chronic inflamma-
tion and immune dysregulation [37]. Population-based studies
report a higher prevalence of CeD among MS patients compared
to the general population, implying that autoimmune processes
triggered by CeD might increase MS susceptibility [35, 38]. A
meta-analysis also found a significantly higher incidence of CeD
among MS patients, reinforcing the notion that CeD may predis-
pose individuals to MS through shared immunological pathways
or genetic factors [39].
However, the relationship between CeD and MS remains de-
bated, with conflicting results in some studies. These discrepancies
10 www.enjournal.org https://doi.org/10.5607/en25009
Seongjin Lim, et al.
may be attributed to several factors. Firstly, variability in cohort
sizes can significantly influence the ability to detect significant as-
sociations. Larger cohorts provide more reliable estimates, while
smaller studies may lack the power to identify associations. Sec-
ondly, genetic diversity among study populations can contribute
to differences in findings. Variations in genetic predispositions re-
lated to CeD and MS across populations could influence observed
associations. Next, inconsistencies in diagnostic criteria for CeD
and MS can lead to variability in study outcomes. Differences in
definitions and diagnostic practices may affect case and control
identification. Also, differences in environmental exposures, di-
etary habits, and healthcare access can impact the prevalence and
manifestation of CeD and MS, contributing to inconsistent results
across studies. Finally, variations in study design, such as prospec-
tive versus retrospective approaches, and differences in data col-
lection methods can result in divergent findings.
An important limitation of this study is its reliance on data
predominantly derived from European populations, where CeD
is more prevalent. This focus means that the findings may be
particularly relevant to European populations but might not be
directly applicable to populations with lower CeD prevalence or
different genetic and environmental backgrounds. Genetic pre-
dispositions related to CeD and MS could vary significantly in
non-European populations, potentially influencing the observed
associations. Furthermore, environmental factors, such as dietary
habits and healthcare access, which vary widely globally, might
contribute to differences in disease prevalence and manifestation.
Future research should aim to include diverse population groups
to enhance the generalizability of the findings and explore poten-
tial population-specific effects.
In this study, we investigated the association between CeD
and MS using MR analysis with data from a large-scale genomic
database. Considering the gut-brain axis, we hypothesized that
circulating proteins are likely mediators of the causal relationship
between CeD and MS. Consequently, we focused on inflam-
matory circulating proteins as potential mediators. Fortunately,
GWAS data from a genome-wide protein quantitative trait locus
(pQTL) study of 91 plasma proteins were available, enabling us to
Fig 5.
Fig. 5. (A) Mendelian randomization (MR) estimates between Gluten-free diet and Alzheimer’s disease (AD). Primary analysis (IVW) and sensitivity
analysis (IVW-MRE, weighted median, MR-Egger, and RAPS) were utilized. Data are displayed as odds ratio (OR) and 95% confidence interval (CI) per
log-odds increment in AD risk. (B) Scatterplot of potential effects of the targeted SNPs on gluten-free diet vs AD. The slope of each line corresponds to
the estimated MR effect for each method used. Positive slope indicates a positive correlation, and negative slope indicates a negative correlation.
11
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Celiac Disease and AD with MR Study
identify CCL19 as a potential mediator [19]. Moreover, Krumb-
holz and collegues reported that CCL19 is constitutively expressed
in the central nervous system and is significantly elevated in both
active and inactive multiple sclerosis lesions [40]. CCR7 ligands,
CCL19 and CCL21, are known to act as chemotactic and retentive
signals in lymphoid organs. However, it has recently been reported
that ectopic CCL19 and CCL21 are increased in the inflamed
intestine in Crohn's disease [41, 42]. Although studies on the ex-
pression of CCL19 in the intestinal epithelium in celiac disease
are insufficient, there is a report that gliadin fragments increase
the migration of dendritic cells [43]. Additionally, there is a report
that CCR7, a chemokine receptor of CCL19, expressed in some T
cells of celiac disease patients [44]. For this reason, it is presumed
that CCL19 is involved in the immune response to gluten in celiac
disease. However, the precise mechanisms by which CCL19 might
link CeD and MS remain unclear. The potential role of CCL19 in
mediating immune responses and its involvement in both gut and
CNS inflammation suggest avenues for further investigation.
CeD and Alzheimer’s disease
The findings from various MR methods, including IVW,
IVW(MRE), WM, and RAPS, suggest a modest inverse relation-
ship between CeD and AD, indicating that individuals with CeD
may have a slightly reduced risk of developing AD. Although the
MR Egger method did not show significant protective effects, the
overall trend supports the hypothesis that CeD may be associated
with decreased AD risk.
The gut-brain axis facilitates communication between the brain’s
immune system and the peripheral immune system, allowing
increased peripheral immune function to upregulate microglial
activity in the brain [45]. Activated microglia release pro-inflam-
matory cytokines, such as tumor necrosis factor-alpha (TNF-α)
and interleukin-1 beta (IL-1β), which can exacerbate neuronal
damage and contribute to neurodegenerative conditions[46]. The
inverse relationship between CeD and AD suggests that these in-
flammatory responses may not necessarily lead to increased AD
risk, indicating potential compensatory mechanisms that mitigate
the effects of systemic inflammation and microglial activation on
neurodegeneration.
Elevated inflammatory markers, like interleukin-6 (IL-6), are
characteristic of CeD and linked to systemic inflammation [47].
Despite elevated IL-6 levels—crucial for stimulating acute phase
responses—the inverse relationship between CeD and AD risk
suggests that systemic inflammation may not directly translate
into increased susceptibility to AD, highlighting the complexity of
these interactions.
Drawing from the relationships between CeD, AD, and MS, a
compelling hypothesis emerges: CeD may inversely influence the
risk of these neurodegenerative diseases. Specifically, while CeD
might reduce the risk of AD, it appears to increase susceptibility to
MS. This differential impact highlights the complexity of autoim-
mune responses triggered by gluten.
The observed inverse relationship parallels phenomena seen in
allergies and parasitic infections, where immune responses to one
condition can provide protection against another [48]. In the case
of AD, CeD may not directly influence risk through previously as-
sumed mechanisms, but the autoimmune processes regulated by a
GFD could promote neuroprotective pathways or alter the brain’s
immune environment. This suggests that while CeD might not
directly impact AD risk, GFD-regulated processes could still en-
hance neuroprotection. Conversely, in MS, the same autoimmune
mechanisms driven by CeD could exacerbate the disease. Systemic
inflammation resulting from CeD might worsen the autoimmune
attack on the myelin sheath, leading to accelerated demyelination.
Research indicates that disruptions in the intestinal barrier—a
hallmark of CeD—can contribute to systemic inflammation and
may influence the progression of autoimmune conditions like MS.
In response to the inquiry about why a GFD does not appear to
be associated with the prevention of AD, it is important to recog-
nize that our current understanding of the relationship between
diet, CeD, and neurodegenerative diseases like AD is still evolving.
At present, there is no clear evidence that a GFD has a protective
effect against the development of AD. This may be due to several
factors. Firstly, the pathophysiological mechanisms that link CeD
and AD are complex and not yet fully elucidated. While CeD is as-
sociated with systemic inflammation and immune responses, how
these processes intersect with the pathways leading to AD is not
well understood. Additionally, while a GFD is effective in manag-
ing CeD by preventing immune reactions triggered by gluten,
its impact on other unrelated neurodegenerative processes may
be limited. The development of AD involves a myriad of factors
including genetics, environmental influences, and lifestyle choices,
which may not be directly influenced by dietary gluten intake.
ACKNOWLEDGEMENTS
Acknowledgment is given to the participants and investigators
of the FinnGen study. Gratitude is also extended to the IEU Open-
GWAS project for generously sharing the summary-level data.
All authors are grateful for financial support from the National
Research Foundation of Korea funded by the Ministry of Science
and ICT, Republic of Korea (NRF-2022R1A2B5B02001886).
This research was supported by a grant of the Korea Dementia
Research Project through the Korea Dementia Research Center
12 www.enjournal.org https://doi.org/10.5607/en25009
Seongjin Lim, et al.
(KDRC), funded by the Ministry of Health & Welfare and Min-
istry of Science and ICT, Republic of Korea (grant number: RS-
2024-00335192). This work was supported by a grant from Kyung
Hee University in 2024 (20241072).
AUTHOR CONTRIBUTIONS
S. Lim contributed to conception, design, data acquisition and
analysis, and drafted manuscript; J. Wu contributed to design,
analysis, and drafted manuscript; Y.Y. Kim. & S.W. Lim contributed
to design, analysis, and drafted manuscript; J. Shin, & H.J. Shin. &
S.R. Kim. contributed to conception, design, interpretation, and
critically revised manuscript; D.W. Kim contributed to conception,
design, interpretation, and critically revised manuscript. All au-
thors have their final approval and agree to be accountable for all
aspects of work.
CONFLICT OF INTEREST
We declare no competing interests/conflicts.
CONSENT STATEMENT
This study utilized data from the GWAS and Finngen databases,
where informed consent was obtained from all human subjects
involved in the research. Therefore, consent was confirmed for the
use of this genetic data in the analysis.
DATA SHARING
All bona fide researchers can apply for and access the public
datasets from the UK Biobank, FinnGen project, and MEGAS-
TROKE consortium. The MRC-IEU and FinnGen websites pro-
vide download links for all the data used in this study.
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