Skip to main content

Shared and unique common genetic determinants between pediatric and adult celiac disease



Based on age of presentation, celiac disease (CD) is categorised as pediatric CD and adult CD. It however remains unclear if these are genetically and/or phenotypically distinct disorders or just different spectrum of the same disease. We therefore explored the common genetic components underlying pediatric and adult CD in a well characterized north Indian cohort.


A retrospective analysis of children (n = 531) and adult (n = 871) patients with CD between January 2001 and December 2010 was done. The database included basic demographic characteristics, clinical presentations, associated diseases and complications, if any. The genotype dataset was acquired for children (n = 217) and adult CD patients (n = 340) and controls (n = 736) using Immunochip. Association analysis was performed using logistic regression model to identify susceptibility genetic variants.


The predominant form of CD was classical CD in both pediatric and adult CD groups. There was remarkable similarity between pediatric and adult CD except for quantitative differences between the two groups such as female preponderance, non-classical presentation, co-occurrence of other autoimmune diseases being more common amongst adult CD. Notably, same HLA-DQ2 and –DQ8 haplotypes were established as the major risk factors in both types of CD. In addition, a few suggestively associated (p < 5 × 10−4) non-HLA markers were identified of which only ANK3 (rs4948256-A; rs10994257-T) was found to be shared and explain risk for ~45 % of CD patients with HLA allele.


Overall phenotypic similarity between pediatric and adult CD groups can be explained by contribution of same HLA risk alleles. Different non-HLA genes/loci with minor risk seem to play crucial role in disease onset and extra intestinal manifestation of CD. None of the non-HLA risk variants reached genome-wide significance, however most of them were shown to have functional implication to disease pathogenesis. Functional relevance of our findings needs to be investigated to address clinical heterogeneity of CD.


This present study is the first comparative study based on common genetic markers to suggest that CD in pediatric age group and in adults are the spectrum of the same disease with novel and shared genetic risk determinants. Follow-up fine mapping studies with larger study cohorts are warranted for further genetic investigation.


Celiac disease (CD) is a chronic systemic inflammatory condition of autoimmune origin as a result of permanent intolerance to gluten in genetically predisposed individuals [1, 2]. CD was thought initially to be a disease of children and was treated mainly by pediatricians. Over past two decades, it was realized that CD also occurs in adults [3, 4]. Such observations led to the concept of pediatric CD and adult onset CD and it’s sub-clasification based on the age at disease diagnosis [5, 6]. Pediatric CD develops in early years of life with introduction of gluten containing cereals in their diets and presents mostly with classical features of CD such as chronic diarrhoea, abdominal distension, failure to thrive and deficiencies of nutrients. On the other hand, adult CD presents later in life and has both classic manifestations and non-classical manifestation such as fatigue, anaemia, bone disease, idiopathic seizures, cryptogenic liver disease and various autoimmune diseases [7, 8].

The past two decades have witnessed considerable efforts to unravel the pathogenesis of CD including genetic risk determinants [9, 10]. HLA-DQ2 and -DQ8 haplotypes have been the most consistently reported genetic markers conferring ~40 % risk for CD development [11, 12]. More recently, an additional 39 loci have been identified by genome-wide association studies (GWAS) and Immunochip based genetic analysis [13]. These additional loci are estimated to confer an additional ~15 % genetic risk to them and explained ~55 % of the CD cases [12]. While all these genetic and clinical studies have brought extremely important information, they however have not delineated phenotypic and genetic characteristics based on the age at the onset leaving significant gaps in our understanding of these two distinct categories. We therefore explored the genetic landscape of a well characterized cohort of pediatric CD and adult CD.

Our observations are suggestive of novel as well as moderately shared genetic determinants underlying these two distinct celiac disease groups.


Study cohort

Database registry system for patients with CD being maintained at the Gastroenterology Department, Dayanand Medical College and Hospital since 1995, was used in this study. A patient registry database containing detailed baseline and follow up clinical and laboratory characteristics of all the patients with confirmed diagnosis of CD.

A retrospective database analysis of all the patients (n = 1402) with CD between January 2001 and December 2010 was done. The diagnosis of CD was established as per modified ESPGHAN criteria [14, 15]. Approval for this study was obtained from Institutional Ethics Committee (IEC) of University of Delhi South Campus, New Delhi and Drug Trial Ethics Committee (DTEC), Dayanand Medical College and Hospital, Ludhiana. An informed and written consent was obtained from all the participants. The baseline demographic characteristics such as age at the diagnosis, gender of the participants, and duration of the symptoms prior to diagnosis of CD was retrived from the database. Patients ≥18 years of age at diagnosis were identified as adult CD while patients <18 years were identified as having pediatric CD. Recruitment of pediatric CD patients were guided by “Convention on the Rights of the Child” adopted by the United Nations General Assembly (1989) and Indian Association of Pediatric Policy Statement on Age of Children for Pediatric Care (1999). Patients presenting symptoms such as chronic diarrhea, malabsorption and failure to thrive were classified as Classical CD and those presenting as extra intestinal manifestations such as short stature, fatigue, iron deficiency anaemia, osteoporosis, delayed puberty, infertility, cryptogenic chronic liver disease, idiopathic seizure and dyspepsia not responding to PPI were classified as non-classical CD. Subjects detected to have CD on screening of high-risk group such as family members of index patient, type I diabetes mellitus, cryptogenic liver disease, infertility, thyroiditis were classified as “Screen detected’ [15].

Relevant laboratory data including baseline haemoglobin and anti-tTG antibody levels were recorded. All the patients had undergone gastroduodenoscopic examination and their duodenal biopsies obtained. The grade of villous atrophy was classified as per modified Marsh criteria [16, 17]. All study subjects were from the north part of India and had been residents of the state of Punjab, a State in Northern part of India, for more than three generations.

Genetic analysis

Of the 1402 CD patients, 557 patients (n = 217 pediatric CD and n = 340 adult CD) were available for genetic analysis and their DNA was genotyped on the Illumina immunochip genotyping platform [13]. Unrelated healthy blood donors (n = 736) from the same locality and community having anti-tTG antibody value within normal range were recruited as controls. They were also genotyped on the Illumina immunochip genotyping platform. The controls were common for both the adults and pediatric patients with CD.

DNA from peripheral whole blood was extracted using conventional phenol-chloroform method at University of Delhi, South Campus, New Delhi, India. Samples were hybridized on the Immunochip platform at the genotyping facility, University Medical Centre Groningen, The Netherlands, as a part of the Celiac Disease Consortium (CDC). Immunochip is a custom made platform with ~186 known immune loci densely covered with 196524 polymorphic variants described before [13, 18]. Total sample set was divided into two groups namely i) Pediatric CD (n = 217); and ii) Adult CD (n = 340). All the quality control steps, as described elsewhere [13, 18] were performed separately on these two groups. Additionally, all markers with minor allele frequency (MAF) <0.10 were removed. After stringent QC, datasets for Pediatric CD and Adult CD were analysed separately for test of association. Principal component analysis (PCA) was performed using markers in linkage equilibrium (LD < 0.10) to elucidate the underlying genetic stratification present in the study cohort. Principal components 1 to 4 were included as covariates to correct for population stratification and genomic inflation. Since, multiple markers were tested for association in this study (similar to genome-wide association studies), to avoid false positives, Bonferroni correction was applied. Accordingly, significance level was kept at p ≤5 × 10−7 level and suggestive association at p-values between 5 × 10−7 and 5 × 10−4. Genetic heterogeneity of odds ratio obtained in test of association (described above) between Pediatric CD and Adult CD were tested using Breslow-Day statistics. Identified variants were further analysed in silico for their functional significance by evaluating their expression effects (cis-eQTL) on neighbouring genes. Genome-wide whole blood expression data was used, given in Blood eQTL browser [19] to identify cis-eQTL effect of the variants. Further, we used GRAIL (Gene Relationships Across Implicated Loci) [20] to understand the possible relationships of the genes identified in our study with already known genes at 39 non-HLA CD loci [13].

Data availability

Genotyping data for the entire north Indian cohort are available through the European Genome-Phenome Archive ( with the accession number EGAS00001000849. The summary statistics can be obtained by contacting the authors directly.


Clinical characteristics

Of 1402 patients with CD in our database, 531 (37.8 %) were pediatric CD and 871 (62.2 %) were adult CD. The mean age at the diagnosis in pediatric CD and adult CD was 10.08 ± 4.6 years (females 45.4 %) and 35.34 ± 11.83 years (females 60.3 %). The duration of symptoms before the diagnosis of CD was comparable in adult CD in comparison to that in pediatric CD (3.31 years versus 2.2 years; p = NS). While the predominant mode of presentation in both pediatric and adult CD was classical CD; the proportion of patients with classical CD was higher in pediatric CD in comparison of that in adult CD (75.5 % vs 69.6 %; p = 0.009). The non-classical presentation was statistically higher in adult CD in comparison to that in pediatric CD (20.3 % vs 25.2 %; p = 0.02).

Iron deficiency anemia and hypothyroidism were more commonly reported in adult CD (Table 1). Complications such as celiac crisis, refractory sprue and associated malignancy were seen in the adult group. The various malignancies reported included oesophageal, colon, stomach and small bowel sarcoma (one each). Dermatitis herpetiformis was seen in 3 adult CD cases while none was observed in pediatric CD. Associated autoimmune disorders, investigations, titre of anti-tTG antibody in pediatric and adult CD are summarized in Table 1.

Table 1 Demographic and clinical characteristics of pediatric and adult celiac disease

Genetic analysis

After stringent quality control of the immunochip based genotype data, a total of 27 pediatric CD, 33 adult CD and 6 controls were removed. Following removal of poorly clustered markers due to poor hybridization, 172,242 markers were considered for further analysis. Of them, 88,776 and 88,793 markers in Pediatric CD and Adult CD groups passed the QC steps. The genomic control inflation factor of association test statistics (λGC) was observed to be very limited in the two groups analysed in the study (λGC = 1.11 for pediatric CD; and λGC = 1.01 for adult CD) (Additional file 1: Figure S1a and b). Notably, Pediatric CD and Adult CD had 90 % and 95 % power, respectively to detect association of a variant having minor allele frequency (MAF) >0.20 and odds ratio (OR) >1.50.

Test of association

HLA locus emerged as the most significantly associated marker both in pediatric and adult CD patients (Tables 2 and 3; Additional file 1: Figure S2a and b). The strongest signal was at rs2854275, G > T, which is localized in the last intron of HLA-DQB1and which is in very strong LD (r2 = 0.95, D’ = 1) with European top HLA marker rs2187668 from HLA-DQA1, was common in both pediatric CD (p = 4.28 × 10−29) and adult CD (p = 5.82 × 10−35). A frequency of 14.9 % at rs2854275-T allele in healthy individuals versus 49.7 % in adult CD and 50 % in pediatric CD patients was noteworthy. Furthermore, while conditioned on rs2854275, we did not observe any other genome-wide significant HLA marker in either pediatric or adult CD groups. Association status of five known SNPs (rs2395182, rs7775228, rs4713586, rs2187668 and rs7454108) tagging HLA-DQ haplotypes [21] were checked in pediatric CD and adult CD. Comparable allelic association status for risk alleles (Table 4) and distribution of different-HLA-DQ haplotypes (Table 5) were observed between these two groups. We observed that similar proportion of CD patients in both these groups (87.30 % in Pediatric CD and 86.97 % in Adult CD) had at least one of the two risk haplotypes HLA-DQ2.5 or -DQ8, which was also comparable that reported in the European populations [2224].

Table 2 Top association signals identified in Pediatric CD and their association status in Adult CD among north Indians patients
Table 3 Top association signals identified in Adult CD group and their association status in Pediatric CD among north Indians
Table 4 Comparative association status of known tag SNPs (Monsur et al., [21], Romanos et al., [11] and [12]) for DQ haplotypes
Table 5 Comparative distribution of HLA-DQ haplotypes in pediatric CD and adult CD groups

On the other hand, 12 distinct non-HLA risk variants were observed to be suggestively associated (p <5 × 10−4) with pediatric CD and 19 variants with adult CD with only ANK3 gene being common to both groups (Tables 2 and 3). Though most of these are suggestive associations for CD, a few of them are known risk loci for other immune disorders (Additional file 2: Table S1). Except for ANK3 [ankyrin 3], ARHGAP39 [Rho GTPase activating protein 39], LILRA3 [leukocyte immunoglobulin-like receptor, superfamily A (without TM domain), member 3] and CSGALNACT1 (chondroitin sulfate N-acetylgalactosaminyltransferase 1] other Pediatric CD specific loci were not replicated (p ≤ 0.05) in Adult CD. Similarly, only four Adult CD specific loci, namely VAV2 [vav 2 guanine nucleotide exchange factor], FAM181B [family with sequence similarity 181, member B], non-genic region at 5p15.33, ANK3 [ankyrin 3] and ITLN2 [intelectin 2] were replicated in pediatric CD. Further ~58 % Pediatric CD specific variants were heterogeneous (p_BD < 0.05) compared to ~26 % among adult CD specific variants (Additional file 2: Table S2). cis-eQTL analysis revealed five variants in the Pediatric CD group and six in the Adult CD group to be functionally relevant (Additional file 2: Table S3). GRAIL analysis revealed three loci, two from Pediatric CD and one from Adult CD to be significantly connected with the known 39 non-HLA CD loci (Additional file 2: Table S4).


Celiac disease is one of the complex disorder where the major non-genetic factor namely gluten has been very well established. Further, two distinct groups of affected individuals based on age at onset of the disease have also been noted. The major limitation to date has however been the lack of information in the similarities and differences, if any, in the genetic susceptibility of the two groups. Analysis of clinical characteristics in this study cohort has demonstrated that while classic CD is the predominant manifestation in both pediatric and adult CD, non-classical manifestations are also commonly present in both the groups, iron deficiency anaemia being the most frequent (Table 1). An association has been reported between other autoimmune disorders and adult CD as approximately 30 % of adult patients with CD had one or more associated autoimmune disorders in comparison to approximately 3 % in the general population [2527]. This may happen due to late diagnosis of CD and longer duration of exposure to gluten in adults [25]. On the other hand, early institution of gluten-free diet in children patients may act as a protective factor against development of another autoimmune disease in pediatric CD [28].

It is noteworthy that already reported HLA-DQ haplotypes emerged as the major genetic risk factor in both pediatric and adult CD groups (Table 4) and confers equal risk to both of these groups (Table 5). In addition ANK3, an integral membrane protein controlling cytoskeleton, cell motility, proliferation and intestinal contraction, was the only other novel non-HLA marker which was associated with both pediatric and adult CD groups (Tables 2 and 3). Along with top HLA marker (rs2854275-T), risk variants from ANK3 (rs4948256-A among pediatric and rs10994257-T among adults) explains ~45 % of the CD cases. This finding reiterates our previous observation in a trans-ethnic study, where ANK3 was identified in the same combined CD cohort [18]. It is worthwhile to mention that ANK3 has been shown to be associated with bipolar disorder and schizophrenia [2932]. Interestingly, a co-occurrence of bipolar disorder and schizophrenia has been observed in patients with CD [3335]. Furthermore, approximately 10 % of patients with CD have some form of neurological disorders such as seizures, cognitive impairment, migraine or other psychiatric illness [33, 34] However, role if any, of ANK3 in occurrence of neurological and psychological disorder in patients with CD warrant further investigations. Contrary to two (HLA-DQ and ANK3) shared genes, most of the other associated genes in both pediatric and adult CD are notably different from each other. Though these genes seem functionally related and are present in similar pathways including cell signalling, cell cycle regulation, inflammatory responses and cellular metabolism (Additional file 2: Table S1). The degree of risk for associated allelic variants with pediatric CD is significantly different (higher degree of odds ratio heterogeneity) from the allelic variants in the adult CD groups (Additional file 2: Table S2). This may signify that these genes with minor risk contributions are specific to each of these two groups and might work in a network with known susceptible genes for the onset of different clinical phenotypes. In the absence of literature on the detailed function of these novel genes, their exact role in age specific CD pathogenesis remains to be understood.

Of 39 known non-HLA CD loci [13], THEMIS, a gene involved in T-cell development was observed to be associated with only adult CD group. Cis-eQTL evaluation of the suggestive risk variants that we observed in the study, indicated highly significant functional relevance of 11 (35.5 %) risk variants which were seen to alter the level of gene expression at these loci (Additional file 2: Table S3). Further, pathway and genetic interaction analysis identified LILRA3, CCL16 and VAV2 which are known to be involved in inflammatory process and are functionally related to the known 39 non-HLA CD loci (Additional file 2: Table S4). This novel comparative study identified suggestive loci in each of these groups but needs follow-up replication. In silico evidences of their effects on gene expression and involvement in integrated pathways in disease pathogenesis support their probable contribution. Therefore, additional investigations across ethnic groups and also functional validation are warranted.


Pediatric and adult CD seem to be a continuum of the disease entity with same HLA-DQ haplotypes and ANK3 being major genetic risk determinants. However, different sets of minor risk conferring genetic loci with promising functional involvement but which are present in a common network with other genes may determine the quantitative disease heterogeneity between them. These, preliminary findings warranted replication and fine mapping to confirm risk alleles.


CD, Celiac disease; CDC, Celiac disease consortium; eQTL, expression quantitative trait loci; ESPGHAN, The European Society for Paediatric Gastroenterology Hepatology and Nutrition; GRAIL, Gene Relationship Across Implicated Loci; GWAS, genome-wide association study; LD, linkage disequilibrium; MAF, minor allele frequency; OR, odds ratio; PCA, principal component analysis; PPI, proton-pump inhibitors; tTG, tissue transglutaminase


  1. Fasano A, Catassi C. Clinical practice. Celiac disease. New Engl J Med. 2012;367:2419–26.

    Article  CAS  PubMed  Google Scholar 

  2. Harris LA, Park JY, Voltaggio L, Lam-Himlin D. Celiac disease: clinical, endoscopic, and histopathologic review. Gastrointest Endosc. 2012;76(3):625–40.

    Article  PubMed  Google Scholar 

  3. Sabatino AD, Corazza GR. Coeliac disease. Lancet. 2009;373(9673):1480–93.

    Article  PubMed  Google Scholar 

  4. Gupta R, Reddy DN, Makharia GK, Sood A, Ramakrishna BS, Yachha SK, et al. Indian task force for celiac disease: current status. World J Gastroenterol. 2009;15(48):6028–33.

    Article  PubMed  PubMed Central  Google Scholar 

  5. John TJ. IAP policy on age of children for pediatriccare. Indian Pediatr. 1999;36(5):461–3.

    CAS  PubMed  Google Scholar 

  6. United Nations. General Assembly. Convention on the Rights of the Child, 20 November 1989. Annu Rev Popul Law. 1989;95:485–501.

    Google Scholar 

  7. Fasano A. Clinical presentation of celiac disease in the paediatric population. Gastroenterology. 2005;128(4 Suppl 1):S68–73.

    Article  PubMed  Google Scholar 

  8. Dewar DH, Ciclitira PJ. Clinical features and diagnosis of celiac disease. Gastroenterology. 2005;128(4 Suppl 1):S19–24.

    Article  PubMed  Google Scholar 

  9. Trynka G, Wijmenga C, van Heel DA. A genetic perspective on coeliac disease. Trends Mol Med. 2010;16(11):537–50.

    Article  CAS  PubMed  Google Scholar 

  10. Kumar V, Wijmenga C, Withoff S. From genome-wide association studies to disease mechanisms: celiac disease as a model for autoimmune disease. SeminImmunopathol. 2012;34(4):567–80.

    CAS  Google Scholar 

  11. Romanos J, van Diemen CC, Nolte IM, Trynka G, Zhernakova A, Fu J, et al. Analysis of HLA and non-HLA alleles can identify individuals at high risk for celiac disease. Gastroenterology. 2009;137(3):834–40. 840 e1-3.

    Article  CAS  PubMed  Google Scholar 

  12. Romanos J, Rosen A, Kumar V, Trynka G, Franke L, Szperl A, et al. Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants. Gut. 2014;63(3):415–22.

    Article  PubMed  Google Scholar 

  13. Trynka G, Hunt KA, Bockett NA, Romanos J, Mistry V, Szperl A, et al. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease. Nat Genet. 2011;43(12):1193–201.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Revised criteria for diagnosis of coeliac disease. Report of Working Group of European Society of Paediatric Gastroenterology and Nutrition. Arch Dis Child. 1990; 65(8):909–11.

  15. Husby S, Koletzko S, Korponay-Szabo IR, Mearin ML, Phillips A, Shamir R, et al. European Society for paediatric Gastroenterology, Hepatology, and Nutrition guidelines for the diagnosis of coeliac disease. J Pediatr Gastroenterol Nutr. 2012;54(1):136–60.

    Article  CAS  PubMed  Google Scholar 

  16. Vander LW, de Ru A, van der Wal Y, Kooy YM, Benckhuijsen W, Mearin ML, et al. Specificity of tissue transglutaminase explains cereal toxicity in celiac disease. J Exp Med. 2002;195(5):643–9.

    Article  Google Scholar 

  17. Malamut G, Afchain P, Verkarre V, Lecomte T, Amiot A, Damotte D, et al. Presentation and longterm follow-up of refractory celiac disease: comparison of type I and type II. Gastroenterology. 2009;136(1):81–90.

    Article  PubMed  Google Scholar 

  18. Senapati S, Gutierrez-Achury J, Sood A, Midha V, Szperl A, Romanos J, et al. Evaluation of European celiac disease risk variants in a north Indian population. Eur J Hum Genet. 2015;23(4):530–5.

    Article  CAS  PubMed  Google Scholar 

  19. Westra HJ, Peters MJ, Esko T, Yaghootkar H, Schurmann C, Kettunen J, et al. Systematic identification of transeQTLs as putative drivers of known disease associations. Nat Genet. 2013;45(10):1238–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Rayachuduri S, Plenge RM, Rossin EJ, Ng AC, Purcell SM, Sklar P, et al. Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions. PLoS Genet. 2009;5(6), e1000534.

    Article  Google Scholar 

  21. Monsur AJ, de Bakker PI, Zhernakova A, Pinto D, Verduijn W, Romanos J, et al. Effective detection of human leukocyte antigen risk alleles in celiac disease using tag single nucleotide polymorphisms. PLoS One. 2008;3(5), e2270.

    Article  Google Scholar 

  22. Karell K, Louka AS, Moodie SJ, Ascher H, Clot F, Greco L, et al. HLA types in celiac disease patients not carrying the DQA1*05-DQB1*02 (DQ2) heterodimer: results from the European Genetics Group on Celiac Disease. Hum Immunol. 2003;64(4):469–77.

    Article  CAS  PubMed  Google Scholar 

  23. Lundin KE, Scott H, Hansen T, Paulsen G, Halstensen TS, Fausa O, et al. Gliadin-specific, HLA-DQ(alpha 1*0501, beta 1*0201) restricted T cells isolated from the small intestinal mucosa of celiac disease patients. J Exp Med. 1993;178(1):187–96.

    Article  CAS  PubMed  Google Scholar 

  24. Lundin KE, Scott H, Fausa O, Thorsby E, Sollid LM. T cells from the small intestinal mucosa of a DR4, DQ7/DR4, DQ8 celiac disease patient preferentially recognize gliadin when presented by DQ8. Hum Immunol. 1994;41(4):285–91.

    Article  CAS  PubMed  Google Scholar 

  25. NIH Consensus Development Conference on Celiac Disease. NIH Consens State Sci Statements. 2004; 21(1):1–23.

  26. Ventura A, Magazzu G, Greco L. Duration of exposure to gluten and risk for autoimmune disorders in patients with celiac disease. Gastroenterology. 1999;117:297–303.

    Article  CAS  PubMed  Google Scholar 

  27. Grainge MJ, West J, Solaymani-Dodaran M, Card TR, Logan RF. The long-term risk of malignancy following a diagnosis of coeliac disease or dermatitis herpetiformis: a cohort study. Aliment Pharmacol Ther. 2012;35(6):730–9.

    Article  CAS  PubMed  Google Scholar 

  28. Murray JA, Watson T, Clearman B, Mitros F. Effect of a gluten-free diet on gastrointestinal symptoms in celiac disease. Am J Clin Nutr. 2004;79(4):669–73.

    CAS  PubMed  Google Scholar 

  29. Chen DT, Jiang X, Akula N, Shugart YY, Wendland JR, Steele CJ, et al. Genome-wide association study meta-analysis of European and Asian-ancestry samples identifies three novel loci associated with bipolar disorder. Mol Psychiatry. 2013;18(2):195–205.

    Article  CAS  PubMed  Google Scholar 

  30. Bergen SE, O’Dushlaine CT, Ripke S, Lee PH, Ruderfer DM, Akterin S, et al. Genome-wide association study in a Swedish population yields support for greater CNV and MHC involvement in schizophrenia compared with bipolar disorder. Mol Psychiatry. 2012;17(9):880–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Ferreira MA, O’Donovan MC, Meng YA, Jones IR, Ruderfer DM, Jones L, et al. Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet. 2008;40(9):1056–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Athanasiu L, Mattinqsdal M, Kahler AK, Brown A, Gustafsson O, Agartz I, et al. Gene variants associated with schizophrenia in a Norwegian genome-wide study are replicated in a large European cohort. J Psychiatr Res. 2010;44(12):748–53.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Dickerson F, Stallings C, Origoni A, Vaughan C, Khushalani S, Alaedini A, et al. Markers of gluten sensitivity and celiac disease in bipolar disorder. Bipolar Disord. 2011;13(1):52–8.

    Article  CAS  PubMed  Google Scholar 

  34. Genuis SJ, Lobo RA. Gluten sensitivity presenting as a neuropsychiatric disorder. Gastroenterol Res Pract. 2014;2014:293206.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Singh MM, Kay SR. Wheat gluten as a pathogenic factor in schizophrenia”. Science. 1976;191(4225):401–2.

    Article  CAS  PubMed  Google Scholar 

Download references


We gratefully acknowledge Ms. Anjali Dabral and Ms. Shalini Sharma for preparation of DNA samples and maintenance of the resource in the lab. We specially thank Prof. Cisca Wijmenga for providing Immunochip and genotyping facilities at Department of Genetics, University Medical Center Groningen, The Netherlands through the Celiac Disease Consortium (CDC), The Netherlands.


The genetic component of this study was funded by the Dutch Government (BSIK03009 to Cisca Wijmenga) and the Netherlands Organisation for Scientific Research (NWO, grant 918.66.620 to Cisca Wijmenga). University of Delhi R&D grant (2012–2013) to BKT. BKT received JC Bose fellowship from Department of Science and Technology, New Delhi, India. Sabyasachi Senapati is supported by a Senior Research Fellowship from the Council for Scientific and Industrial Research (CSIR), New Delhi, India.

Authors’ Contributions

BKT and S. Senapati conceived the study. CD participants were recruited by AS, VM. Diagnosis and clinical phenotyping were done by AS, VM, NS, S. Sharma and LK. Statistical analyses were done by S. Senapati. S. Senapati and BKT contributed towards writing the manuscript. All authors reviewed and approved the final manuscript.

Competing interest

The authors declare that they have no competing interests.

Author information

Authors and Affiliations


Corresponding author

Correspondence to B. K. Thelma.

Additional files

Additional file 1:

Figure S1. QQ plots showing level of genomic inflation in (a) Paediatric CD and (b) Adult CD groups in north Indian population. Inflation was measured using 3016 independent, neutral-reported variants present on the array (derived from reading and math skills GWAS therefore unlikely to be confounded by the immune signal). FigureS2. Manhattan plots showing association signals in (a) Paediatric CD and (b) Adult CD in north Indian population. (DOCX 254 kb)

Additional file 2:

Table S1. Functional profiles of the top non-HLA association signals identified in Paediatric CD and Adult CD among north Indians. Table S2. Test of heterogeneity (Breslow-Day test) for associated SNPs in PaediatricCD and AdultCD groups. Table S3. cis-eQTL evaluation of associated SNPs. Table S4. GRAIL analysis revealed seven genes with significant (p <0.05) interaction with 39 known non-HLA coeliac disease loci. These seven genes are from four loci identified in this study. (DOCX 26 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, 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 ( applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Senapati, S., Sood, A., Midha, V. et al. Shared and unique common genetic determinants between pediatric and adult celiac disease. BMC Med Genomics 9, 44 (2016).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: