Novel genetic risk variants for pediatric celiac disease
Department of Pharmacy, School of Health Sciences, University of Patras,
University Campus, Rion
Novel genetic risk variants for pediatric celiac disease
Angeliki Balasopoulou 0
Angeliki Panagiotara 0
Brock A. Peters
Effrosyni Mendrinou 0
Apostolos Stratopoulos 0
Aigli Ioanna Legaki 0
Vasiliki Stathakopoulou 0
Aristoniki Tsolia 0
Nikolaos Govaris 0
Sofia Govari 0
Zoi Zagoriti 0
Konstantinos Poulas 0
Bassam R. Ali
George P. Patrinos 0
Theodora Katsila 0
0 Department of Pharmacy, School of Health Sciences, University of Patras, University Campus , Rion, 265 04 Patras , Greece
Background: Celiac disease is a complex chronic immune-mediated disorder of the small intestine. Today, the pathobiology of the disease is unclear, perplexing differential diagnosis, patient stratification, and decision-making in the clinic. Methods: Herein, we adopted a next-generation sequencing approach in a celiac disease trio of Greek descent to identify all genomic variants with the potential of celiac disease predisposition. Results: Analysis revealed six genomic variants of prime interest: SLC9A4 c.1919G>A, KIAA1109 c.2933T>C and c. 4268_4269delCCinsTA, HoxB6 c.668C>A, HoxD12 c.418G>A, and NCK2 c.745_746delAAinsG, from which NCK2 c. 745_746delAAinsG is novel. Data validation in pediatric celiac disease patients of Greek (n = 109) and Serbian (n = 73) descent and their healthy counterparts (n = 111 and n = 32, respectively) indicated that HoxD12 c. 418G>A is more prevalent in celiac disease patients in the Serbian population (P < 0.01), while NCK2 c.745_ 746delAAinsG is less prevalent in celiac disease patients rather than healthy individuals of Greek descent (P = 0. 03). SLC9A4 c.1919G>A and KIAA1109 c.2933T>C and c.4268_4269delCCinsTA were more abundant in patients; nevertheless, they failed to show statistical significance. Conclusions: The next-generation sequencing-based family genomics approach described herein may serve as a paradigm towards the identification of novel functional variants with the aim of understanding complex disease pathobiology.
Celiac disease; Genomic variants; Family genomics; Next-generation sequencing; Disease predisposition
Celiac disease is a complex chronic immune-mediated
disorder of the small intestine. Today, the pathobiology of the
disease is unclear, perplexing differential diagnosis, patient
stratification, and decision-making in the clinic. Genetics
has been reported to play a key role. The HLA-DQ2 gene is
identified in up to 95 % of celiac disease patients, while
most of the remaining patients have the HLA-DQ8 gene.
Notwithstanding, the Chinese and Japanese populations
(devoid of HLA-DQ2) are not expected to develop the
disease, yet this is not true for the individuals with the
HLA-DQ8 gene. Celiac disease is also associated with an
extended ancestral haplotype that is defined by class I and
II HLAs (A, B, DR, DQ). Notably, HLA-DQ2 and/or
HLADQ8 expression is necessary but not sufficient for disease
development. Thus, other genes are anticipated to be
involved. Indeed, genome-wide association studies (GWAS)
have revealed 26 non-HLA genetic loci-associated celiac
disease and other autoimmune or chronic immune
© The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
disorders (diabetes mellitus type I, rheumatoid arthritis) [1,
2]. In 2008 to 2011, several new celiac disease risk loci have
been identified [3–5], bringing the number of known loci
(including the HLA one) to 40 and indicating genes and
gene regulatory elements of paramount importance. In
2015, five new genetic loci were identified, being
independent of HLA-DQA1 and HLA-DQB1 and associated with
celiac disease predisposition .
Although a genetic component has been described,
disease occurrence has been also associated with
environmental factors and gut microbiome. In all cases,
gluten has been identified as the environmental trigger
of the disease, leading to the stimulation of
glutenspecific T cells. Differential diagnosis is still a major
issue. Although a gold standard diagnostic approach
has been defined (endoscopy with biopsy of the small
intestine coupled to positive disease serology), several
pathological conditions have been reported sharing
similar mucosal transformations with celiac disease as
well as other autoimmune disorders (thyroid disease,
Addison disease, autoimmune liver disease, Sjögren
syndrome) that occur ten times more frequently in
celiac disease patients often masking celiac disease
symptoms. Disease management options are restricted
to a gluten-free lifestyle, which ultimately fails to
protect patients from disease symptoms due to its
chronic nature. Can we delineate individual variability
towards differential diagnosis? Can we highlight the
disease mechanisms in question to assist disease
So far, findings account for 49 % of the genetic basis of
the disease. As in other immune-mediated diseases,
genetic predisposition to celiac disease remains unresolved as
we still need to explain the remaining major fraction of
heritability, including rare as well as additional common
risk variants. Causal variants and genes still need to be
identified and/or more finely localized. In this context, the
Immunochip Consortium was developed to explore
comprehensive datasets containing common, low-frequency,
and rare variants in related diseases (autoimmune thyroid
disease, ankylosing spondylitis, Crohn disease, celiac
disease, IgA deficiency, multiple sclerosis, primary biliary
cirrhosis, psoriasis, rheumatoid arthritis, systemic lupus
erythematosus, type 1 diabetes mellitus, and ulcerative
As expected, the advent of technology and, in
particular, next-generation sequencing has provided
unprecedented opportunities to delineate disease pathobiology
as well as inter-individual differences [8, 9]. Herein, we
propose a multi-step next-generation sequencing-based
family genomics approach, piloted in a celiac disease trio
of Greek descent to identify novel genomic variants of
functional significance with the aim of understanding
Case selection, DNA isolation, and whole-genome
A seven-member Greek family has been recruited
(informed consents have been obtained), and a trio analysis
(III-1, III-2, IV-3) has been performed using the celiac
disease model (Additional file 1: Figure S1). A family-based
design was employed rather than a population-based
design, as the former is generally considered to be robust
against population admixture and stratification and may
yield both within- and between-family information .
Genomic DNA isolation was performed from saliva using
the Oragene collection kit (DNA Genotek, Ontario,
Canada) (Serbian cohort) and peripheral blood using an
automated system (MagNA Pure Compact, Roche, Basel,
Switzerland) (Greek cohort). Whole-genome sequencing
was performed using Complete Genomics’ (CA, USA)
DNA nanoarray platform . DNA sequencing coverage
was 110×. Only high-quality call variants were included in
the analysis (>93 %). Genomes were aligned with the hg19
Bioinformatics and in silico analyses
Next-generation sequencing data (Complete Genomics
Inc., CA) were analyzed using Ingenuity Variant Analysis
version 3.1.2 (Ingenuity® Systems, www.ingenuity.com).
This is a well-established software that identifies
associations between phenotypes, defined by the user by
classification of the tested individuals, and variants in the
sequenced genome. Upon classification of the family
members by phenotype (celiac vs. normal), a number of
variants were listed; the output was filtered into a
smaller variant list upon classification of the family
members by those being celiac patients vs. those who
were healthy and known not to be celiac disease
subjects. The genetic model used for this comparison was of
an autosomal dominant model, since it traces the genetic
inheritance from mother (III-2) to daughter (IV-3) in a
highly penetrant form. A total of 263 genes followed an
autosomal dominant pattern, and 227 variants were
identified in the genetic model. Out of these, 6 genes
and 7 variants were identified in the
biological/phenotype pattern of celiac disease, due to either the past
association of the genes considered or via the biological
significance as determined by the IVA software.
Due to the large amount of variants which are
normally present in the genome, even when excluding
intronic sequences, several filtering steps are used in data
analysis to include only the genes which are likely to be
causative in the final output connected with just the
disease of interest, in this case—celiac disease. All variants
were filtered according to the analysis required, using
custom scripts and Complete Genomics Analysis Tools
(CGA™ Tools). The filtering cascade utilized in the
present data analysis is as follows:
1. Confidence: Only variants with call quality at least 20.0 in cases or at least 20.0 in controls (i.e., 99 % call accuracy) were included.
2. Common variants: All variants observed to have an
allele frequency ≥3.0 % of the genomes in the 1000
genomes project OR ≥3.0 % of the public Complete
Genomics genomes OR ≥3.0 % of the NHLBI ESP
exomes were excluded.
3. Predicted deleterious: Only variants that are
experimentally observed to be associated with a
phenotype (Pathogenic, Possibly Pathogenic,
Unknown Significance OR established gain of
function in the literature OR gene fusions OR
inferred activating mutations by Ingenuity OR
predicted gain of function by BSIFT OR in a
microRNA binding site OR Frameshift, in-frame
indel, or stop codon change OR Missense and not
predicted to be innocuous by SIFT OR disrupt splice
site up to 2.0 bases into intron OR deleterious to a
microRNA OR structural variant) were kept.
4. Genetic analysis: Only variants with the following
genotype characteristics were kept: associated with
gain of function OR heterozygous_alt OR
haploinsufficient OR heterozygous OR homozygous
OR heterozygous_amb OR compound_heterozygous
OR hemizygous AND occur in at least 2 of the case
samples at the gene level in the Case samples AND
not which are associated with gain of function OR
heterozygous_alt OR haploinsufficient OR
heterozygous OR homozygous OR
heterozygous_amb OR compound_heterozygous OR
hemizygous AND occur in at least 1 of the control
samples at the variant level in the control samples.
5. Biological context: Only variants that are within 1 hop (direct targets) of upstream regulators or downstream regulatory targets of such genes and that are known or predicted to affect celiac disease.
Variants of interest were annotated with Annovar in
Galaxy  and compared with NCBI dbSNP build
mmary.cgi), 69 reference genomes from Complete
69Genomes/), and GWAS (http://www.genome.gov/
gwastudies) to determine their novelty or otherwise.
To obtain a list of variants of potential functional
significance, we employed protein variation effect
analyzer (PROVEAN) v1.1.3 (PROVEAN human
genome variants tool) that provides both scale-invariant
feature transform (SIFT)  and PROVEAN 
predictions for a given list of human genome variants
as well as accessory information (dbSNP rs IDs, gene
description, PFAM domain, GO terms, etc.). PROVEAN is
able to make predictions for any type of protein sequence
alteration, including single or multiple amino acid
substitutions, deletions, and insertions . Additionally, Variant
Effect Predictor  and RegulomeDB  were employed
to allow further data interrogation.
Downstream molecular analysis
Selected variants were subsequently validated in pediatric
celiac disease patients of Greek (n = 109)  and Serbian
(n = 73)  descent and their healthy counterparts (n =
111 and n = 32, respectively). The diagnosis of celiac disease
was based on the criteria of the European Society for
Paediatric Gastroenterology, Hepatology and Nutrition
(ESPGHAN) . For children diagnosed prior to 1990, the
“Interlaken criteria” were applied. The Ethics Committee of
University Children’s Hospital, University of Belgrade, and
the Review Board of “Aghia Sophia” Children’s Hospital
have approved the study.
Amplification was carried out according to the
KAPA2G Fast HotStart protocol (KAPABIOSYSTEMS,
MA, USA); detailed information per SNP amplification
conditions is available upon request. For SLC9A4
c.1919G>A, an allele-specific polymerase chain reaction
(PCR) assay was developed (two alternative reverse
primers hybridizing exclusively either to the wild-type
or the mutant allele). For NCK2 c.745_746delAAinsG,
PCR products were subjected to XcmI (New England
Biolabs, MA, USA) restriction endonuclease analysis at
37 °C for 1.15 h and subsequent enzyme deactivation
(65 °C, 20 min). Restriction fragments were visualized
by 3 % agarose gel electrophoresis following ethidium
bromide or Midori Green staining. For HoxD12
c.418G>A, HoxB6 c.668C>A, and KIAA1109 c.2933T>C
and c.4268_4269delCCinsTA, a PCR-based
conventional Sanger resequencing approach was employed.
Capillary electrophoresis was performed on the ABI
Prism 3130xl DNA Analyzer (Applied Biosystems).
Sanger sequencing was also employed to ensure
PCRRFLP and allele-specific PCR method verification.
Herein, a thorough statistical review and analysis has been
attempted, having always in mind that we used the celiac
disease model (trio analysis) as a reason to conduct a
more refined approach in searching/genotyping the
resulted variants in a selective population of celiac disease of
Greek and Serbian descent. We tested for deviations from
HWE using the chi-square goodness of fit test and
principal component analysis. Considering that the χ2
approximation can be poor when there are low genotype counts,
a Fisher exact test (R genetics package) was also used, as it
does not rely on the χ2 approximation . Tests were
Fig. 1 Distribution of newly identified risk variants in Greek and Serbian populations. a HoxD12 c.418G>A is more abundant in pediatric celiac
disease patients of Greek and Serbian descent, reaching statistical significance (**P < 0.01) in the Serbian population. b NCK2 c.745_746delAAinsG
is more abundant in healthy individuals of Greek and Serbian descent, reaching statistical significance (*P = 0.03) in the Greek population
performed as two-tailed, and differences were considered
statistically significant when P < 0.05. Focusing on
casecontrol phenotypes, we tested the null hypothesis of no
association between rows and columns of the 2 × 3 matrix
that contains the counts of the three genotypes (the two
homozygotes and the heterozygote) among cases and
controls. Again, a Fisher exact test was preferred (to evaluate
genotype and allele frequencies), as it is computationally
more demanding, but it is easily implemented in R. We
also performed the Armitage test (Monte Carlo method; it
obtains results that are closer to an exact test, since the
classical Cochran-Armitage trend test is based on
Results and discussion
Whole-genome sequencing analysis of trio reveals newly
identified genetic risk variants for pediatric celiac disease
Our multi-step next-generation sequencing-based family
genomics approach revealed six genomic variants of
prime interest: SLC9A4 c.1919G>A, HoxD12 c.418G>A,
KIAA1109 c.2933T>C and c.4268_4269delCCinsTA, HoxB6
c.668C>A, and NCK2 c.745_746delAAinsG. Susceptibility
to celiac disease (CELIAC6) and to autoimmunity (AIS5)
has been previously mapped to the 4q27 region, within a
linkage disequilibrium block encompassing KIAA1109,
TENR, IL2, and IL21 genes . So far, the most significant
linkage outside the HLA region refers to rs13119723 (P =
2.0 × 10−7 in the KIAA1109 gene on chromosome 4q27).
Zhernakova and coworkers  hypothesized that the
KIAA1109/TENR/IL2/IL21 susceptibility region reported by
van Heel and coworkers  might represent a general risk
locus for multiple autoimmune diseases. Even though
several CELIAC6 genomic variants have been reported [1, 2, 4,
21], this is the first time such a disease association is
revealed for KIAA1109 c.2933T>C and
c.4268_4269delCCinsTA. SLC9A4 c.1919G>A, HoxD12 c.418G>A, HoxB6
c.668C>A, and NCK2 c.745_746delAAinsG are also
reported for the first time as celiac disease risk variants
NCK2 c.745_746delAAinsG has not been annotated in
either dbSNP or the 1000 Genomes Project/exome
variant server data, and hence, it may be considered to be
novel. NCK2 codes for Human Nck2 (hNck2), a
380residue adapter protein consisting of three SH3 domains
and one SH2 domain. Nck2 plays a pivotal role in
connecting and integrating signaling networks constituted
by transmembrane receptors, such as ephrinB and
effectors critical for cytoskeletal dynamics and remodeling
[22–25]. A transient Nck2/PINCH-1 association process
has been also reported that may trigger rapid focal
adhesion turnover during integrin signaling, mediating cell
shape change and migration [26, 27]. We showed that
the novel variant identified herein results in a single
amino acid change (p.K249E), being this exact amino
acid that is reported of fundamental importance during
the abovementioned Nck2 SH3 domain protein-protein
interactions (Fig. 2a) [22, 26, 27]. p.K249E could severely
alter this network of polar interactions and affect the
interaction between the two proteins (Fig. 2b). In 2014,
Nadalutti et al.  observed that celiac patient IgA
antibodies disturb the extracellular protein cross-linking
function of transglutaminase 2, thus altering
cellextracellular matrix interactions and thereby affecting
endothelial cell adhesion, polarization, and motility.
In silico analyses
To ascertain whether the variants of interest have
functional significance, in silico analysis was performed using
Fig. 2 a View of the SH3-3/LIM4 binding interface as previously shown by NMR spectroscopy . The Nck2 DH3 domain interface is shown in
gray and the PINCH-1 LIM4 domain in green. K249 interacts with E233 and is part of a network connecting R192 of LIM4 and N250 of SH3. b
Structural model of the mutant p.K249E and the potential effect in the interactions between SH3 and LIM4
Table 1 In silico analyses outcome of the six variants of prime interest identified in the family trio
Reference residue Alternative residue
Variant effect predictor
Consequence Impact PolyPhen LoFtool
Table 2 Genotyping data of celiac disease pediatric patients of Greek and Serbian descent and healthy individuals
TT GG GT AA GG AG 0 100 0 0 96 4
Healthy individuals of Greek descent
Patients of Greek descent
Healthy individuals of Serbian descent 0
Patients of Serbian descent
In both Greek and Serbian patients, SLC9A4 c.1919G>A and KIAA1109 c.2933T>C and c.4268_4269delCCinsTA were more abundant in patients; nevertheless, they
failed to show statistical significance, possibly due to a small sample size
the SIFT and PROVEAN algorithms [13, 14], as well as
Variant Effect Predictor  and Regulome DB . As
summarized in Table 1, analyses yielded that all variants
share an effect to protein structure, which in the case of
NCK2 c.745_746delAAinsG is considered to be
damaging. Regulome DB questioned a possible role of the
variants of interest in terms of transcription factor
binding sites, chromatin states, eQTLs, differentially
methylated regions, validated functional SNPs and DNase
sensitivity. All variants had minimum or no impact
(Additional file 2: Table S1).
Replication analyses were carried out in two cohorts to
account for population differences. We found that
NCK2 c.745_746delAAinsG is a novel variant that is
more abundant in healthy individuals, reaching statistical
significance (P = 0.03) in the Greek population.
Moreover, HoxD12 c.418G>A, a frameshift variant, was more
abundant in pediatric celiac disease patients, reaching
statistical significance (P < 0.01) in the Serbian
population. When celiac disease risk assessment is considered,
it is important to note that apart from genotype data,
records related to family history along with gender and
country of residence should not be disregarded . In
both Greek and Serbian patients, SLC9A4 c.1919G>A
and KIAA1109 c.2933T>C and c.4268_4269delCCinsTA
were more abundant in patients; nevertheless, they failed
to show statistical significance, possibly due to small
sample sizes. All the studied variants satisfied the
Hardy-Weinberg equilibrium. All variants were verified
as non-frequent ones in agreement with PROVEAN’s
scoring scheme, separating disease-associated variants
from common ones . Genotype frequencies (%) are
summarized in Fig. 1 and Table 2.
In relation to disease diagnosis and prognosis, data
interpretation requires an understanding of the variation in
risk-associated variants. In celiac disease, in particular,
this knowledge is still largely lacking. As whole-genome
and/or whole-exome sequencing approaches begin to be
employed in clinical care, the understanding of detected
sequence variations on diagnosis (and prognosis) is still
not a trivial undertaking. We envisage that the clinical
implementation of next-generation sequencing will play
a crucial role in delineating inter-individual variability
and identification of novel variants towards improved
therapeutic modalities. Herein, we propose a multi-step
next-generation sequencing-based family genomics
approach, similar to our previous conducted cancer
genomics study , but piloted towards a complex genetic
disease, such as celiac disease, to analyze a family trio of
Greek descent to identify novel genomic variants of
functional significance with the aim of understanding
complex disease pathobiology. Recently, we have
outlined the paradigm of pharmacometabolomics-aided
pharmacogenomics in autoimmune diseases to address
the interplay of genomic and environmental influences
with information technologies to facilitate data analysis
as well as sense- and decision-making on the basis of
synergy between artificial and human intelligence. We
propose that better-informed, rapid, and cost-effective
“omics” studies need the implementation of holistic and
multidisciplinary approaches .
Additional file 1: A seven-member Greek family has been recruited
(informed consents have been obtained), and a trio analysis (III-1,
III2, IV-3) has been performed using the celiac disease model. (PNG
Additional file 2: Regulome DB questioned a possible role of the
variants of interest in terms of transcription factor binding sites,
chromatin states, eQTLs, differentially methylated regions, validated
functional SNPs and DNase sensitivity. All variants had minimum or no
impact. (XLSX 3.62 mb)
Availability of data and materials
The datasets during and/or analyzed during the current study are available
from the corresponding author on request.
TK and GPP conceived and designed the study. AB, AP, BS, GN, AJ, EM, AS,
AIL, VS, AT, NG, SG, ZZ, MK, MK, KS, and TK carried out the PCR-based
conventional Sanger resequencing approach. BAP and RD supervised the
nextgeneration sequencing analyses. TK carried out the in silico analyses. BRA,
NC, ER, JB, KP, GC, BZ, NR, RD, SP, TK, and GPP drafted the manuscript. All
authors read and approved the final manuscript.
The authors declare the following competing interests: BAP and RD are
employees of the Complete Genomics Inc. (Mountain View, CA, USA).
Consent for publication
Ethics approval and consent to participate
A family trio of Greek descent was recruited for this study (informed
consents have been obtained). The Ethics Committee of University Children’s
Hospital, University of Belgrade, and the Review Board of “Aghia Sophia”
Children’s Hospital have approved the study.
1. Burton PR , et al. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls . Nature . 2007 ; 447 ( 7145 ): 661 - 78 .
2. Zhernakova A , et al. Meta-analysis of genome-wide association studies in celiac disease and rheumatoid arthritis identifies fourteen non-HLA shared loci . PLoS Genet . 2011 ; 7 ( 2 ): e1002004 .
3. Hunt KA , et al. Novel celiac disease genetic determinants related to the immune response . Nat Genet . 2008 ; 40 ( 4 ): 395 - 402 .
4. Romanos J , et al. Six new coeliac disease loci replicated in an Italian population confirm association with coeliac disease . J Med Genet . 2009 ; 46 ( 1 ): 60 - 3 .
5. Trynka G , et al. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease . Nat Genet . 2011 ; 43 ( 12 ): 1193 - 201 .
6. Gutierrez-Achury J , et al. Fine-mapping in the MHC region accounts for 18 % additional genetic risk for celiac disease . Nat Genet . 2015 ; 47 ( 6 ): 577 - 8 .
7. Cortes A , Brown MA . Promise and pitfalls of the Immunochip . Arthritis Res Ther . 2011 ; 13 ( 1 ): 1 .
8. Boyle AP , et al. Annotation of functional variation in personal genomes using RegulomeDB . Genome Res . 2012 ; 22 ( 9 ): 1790 - 7 .
9. Mizzi C , et al. Personalized pharmacogenomics profiling using wholegenome sequencing . Pharmacogenomics . 2014 ; 15 ( 9 ): 1223 - 34 .
10. Laird NM , Lange C. Family-based designs in the age of large-scale geneassociation studies . Nat Rev Genet . 2006 ; 7 ( 5 ): 385 - 94 .
11. Drmanac R , et al. Human genome sequencing using unchained base reads on self-assembling DNA nanoarrays . Science . 2010 ; 327 ( 5961 ): 78 - 81 .
12. Hiltemann S , et al. CGtag: complete genomics toolkit and annotation in a cloud-based Galaxy . GigaScience . 2014 ; 3 : 1 .
13. Kumar P , Henikoff S , Ng PC. Predicting the effects of coding nonsynonymous variants on protein function using the SIFT algorithm . Nat Protoc . 2009 ; 4 ( 8 ): 1073 - 81 .
14. Choi Y , et al. Predicting the functional effect of amino acid substitutions and indels . PLoS One . 2012 ; 7 ( 10 ): e46688 .
15. Boycott KM , et al. Rare-disease genetics in the era of next-generation sequencing: discovery to translation . Nat Rev Genet . 2013 ; 14 ( 10 ): 681 - 91 .
16. McLaren W , et al. Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor . Bioinformatics . 2010 ; 26 ( 16 ): 2069 - 70 .
17. Krini M , et al. HLA class II high-resolution genotyping in Greek children with celiac disease and impact on disease susceptibility . Pediatr Res . 2012 ; 72 ( 6 ): 625 - 30 .
18. Stanković B , et al. HLA genotyping in pediatric celiac disease patients . Bosn J Basic Med Sci . 2014 ; 14 ( 3 ): 171 .
19. Walker-Smith J , et al. Revised criteria for diagnosis of coeliac disease . Report of working group of ESPGAN. Arch Dis Child . 1990 ; 65 : 909 - 11 .
20. Balding DJ . A tutorial on statistical methods for population association studies . Nat Rev Genet . 2006 ; 7 ( 10 ): 781 - 91 .
21. van Heel DA , et al. A genome-wide association study for celiac disease identifies risk variants in the region harboring IL2 and IL21 . Nat Genet . 2007 ; 39 ( 7 ): 827 - 9 .
22. Liu J , et al. Structural insight into the binding diversity between the human Nck2 SH3 domains and proline-rich proteins . Biochemistry . 2006 ; 45 ( 23 ): 7171 - 84 .
23. Mayer BJ . SH3 domains: complexity in moderation . J Cell Sci . 2001 ; 114 ( 7 ): 1253 - 63 .
24. Koytiger G , et al. Phosphotyrosine signaling proteins that drive oncogenesis tend to be highly interconnected . Mol Cell Proteomics . 2013 ; 12 ( 5 ): 1204 - 13 .
25. Ran X , Song J. Structural insight into the binding diversity between the Tyrphosphorylated human ephrinBs and Nck2 SH2 domain . J Biol Chem . 2005 ; 280 ( 19 ): 19205 - 12 .
26. Vaynberg J , et al. Structure of an ultraweak protein-protein complex and its crucial role in regulation of cell morphology and motility . Mol Cell . 2005 ; 17 ( 4 ): 513 - 23 .
27. Velyvis A , et al. Structural and functional insights into PINCH LIM4 domainmediated integrin signaling . Nat Struct Mol Biol . 2003 ; 10 ( 7 ): 558 - 64 .
28. Nadalutti CA , et al. Celiac disease patient IgA antibodies induce endothelial adhesion and cell polarization defects via extracellular transglutaminase 2 . Cell Mol Life Sci . 2014 ; 71 ( 7 ): 1315 - 26 .
29. Liu E , et al. Risk of pediatric celiac disease according to HLA haplotype and country . N Engl J Med . 2014 ; 371 ( 1 ): 42 - 9 .
30. Karageorgos I , et al. Identification of cancer predisposition variants in apparently healthy individuals using a next-generation sequencing-based family genomics approach . Hum Genomics . 2015 ; 9 ( 1 ): 1 .
31. Katsila T , et al. Pharmacometabolomics-aided pharmacogenomics in autoimmune disease . EBioMedicine . 2016 ; 5 : 40 - 5 .