Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Basic Science Article
  • Published:

Hirschsprung’s disease may increase the incidence of inflammatory bowel disease through alterations in CA1

Abstract

Background

The role of Hirschsprung’s disease (HSCR) for the development of inflammatory bowel disease (IBD) and the common pathogenesis of the diseases remains unclear. The objective is to investigate the relationship between HSCR and IBD.

Methods

In our study, the Mendelian randomization approach was employed to analyze the causal relationships. A further search was conducted for differentially expressed genes (DEGs) between disease and control tissues in HSCR and IBD. Subsequently, the potential pathway mechanisms were subjected to an enrichment analysis. Furthermore, the molecular docking was employed to investigate the binding relationship between potential therapeutic targets and drugs.

Results

The results show HSCR have an increased risk of developing IBD (IVW: OR = 1.048, P < 0.05; weighted median: OR = 1.065, P < 0.05). A total of 111 DEGs were identified in IBD, while 471 DEGs were observed in HSCR. CA1 was identified as core gene and exhibited lower expression levels in IBD (P < 0.05). Concomitantly, CA1 exhibited reduced expression levels in inflamed tissues. And the TNF and IL17 signaling pathway were found closely related to CA1 expression.

Conclusion

In total, our study shows HSCR promote the occurrence of IBD and reveals pathogenesis. Our results suggest CA1 may provide novel insight for the treatment of HSCR complicated with IBD.

Impact

  • Individuals with HSCR are at a higher risk of developing IBD (IVW: OR = 1.048, P < 0.05; Weighted median: OR = 1.065, P < 0.05).

  • Patients with IBD exhibited lower expression levels of CA1 (P < 0.05). Furthermore, CA1 expression was found to be lower in inflamed tissues (P < 0.05).

  • CA1 may provide novel insight for the treatment of HSCR complicated with IBD.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Results of MR analysis.
Fig. 2: Results of variance analysis and enrichment analysis.
Fig. 3: Comparison of immunization between IBD and control samples.
Fig. 4: Results of variance analysis and enrichment analysis.
Fig. 5: Identification of CA1 as the core genes.
Fig. 6: Results of the analysis of the relationship between CA1 and immunity.
Fig. 7: Results of the molecular docking.

Similar content being viewed by others

Data availability

The raw data used in this study were obtained from publicly available data. Details of the specific data sources are described in the “MATERIALS AND METHODS” section. Relevant results are available in the supplementary material. The codes used in this analysis can be obtained by contacting the corresponding author.

References

  1. Rosen, M. J., Dhawan, A. & Saeed, S. A. Inflammatory Bowel Disease in Children and Adolescents. JAMA Pediatrics 169, 1053–1060 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Jeong, D. Y. et al. Induction and maintenance treatment of inflammatory bowel disease: A comprehensive review. Autoimmun. Rev. 18, 439–454 (2019).

    Article  PubMed  Google Scholar 

  3. Bousvaros, A. et al. Differentiating ulcerative colitis from Crohn disease in children and young adults: report of a working group of the North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition and the Crohn’s and Colitis Foundation of America. J. Pediatr. Gastroenterol. Nutr. 44, 653–674 (2007).

    Article  PubMed  Google Scholar 

  4. Khor, B., Gardet, A. & Xavier, R. J. Genetics and pathogenesis of inflammatory bowel disease. Nature 474, 307–317 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Panza, E. et al. Genetics of human enteric neuropathies. Prog. Neurobiol. 96, 176–189 (2012).

    Article  CAS  PubMed  Google Scholar 

  6. Montalva, L. et al. Hirschsprung disease. Nat. Rev. Dis. Prim. 9, 54 (2023).

    Article  PubMed  Google Scholar 

  7. Lee, H. C. Gene and TET1 association in Hirschsprung disease. Pediatr. Neonatol. 63, 327–328 (2022).

    Article  PubMed  Google Scholar 

  8. Goldstein, A. M., Thapar, N., Karunaratne, T. B. & De Giorgio, R. Clinical aspects of neurointestinal disease: Pathophysiology, diagnosis, and treatment. Dev. Biol. 417, 217–228 (2016).

    Article  CAS  PubMed  Google Scholar 

  9. Heuckeroth, R. O. Hirschsprung disease - integrating basic science and clinical medicine to improve outcomes. Nat. Rev. Gastroenterol. Hepatol. 15, 152–167 (2018).

    Article  PubMed  Google Scholar 

  10. Bernstein, C. N. et al. Increased Incidence of Inflammatory Bowel Disease After Hirschsprung Disease: A Population-based Cohort Study. J. Pediatr. 233, 98–104.e102 (2021).

    Article  PubMed  Google Scholar 

  11. Sutthatarn, P. et al. Hirschsprung-associated inflammatory bowel disease: A multicenter study from the APSA Hirschsprung disease interest group. J. Pediatr. Surg. 58, 856–861 (2023).

    Article  PubMed  Google Scholar 

  12. Löf Granström, A., Amin, L., Arnell, H. & Wester, T. Increased Risk of Inflammatory Bowel Disease in a Population-based Cohort Study of Patients With Hirschsprung Disease. J. Pediatr. Gastroenterol. Nutr. 66, 398–401 (2018).

    Article  PubMed  Google Scholar 

  13. Granström, A. L., Ludvigsson, J. F. & Wester, T. Clinical characteristics and validation of diagnosis in individuals with Hirschsprung disease and inflammatory bowel disease. J. Pediatr. Surg. 56, 1799–1802 (2021).

    Article  PubMed  Google Scholar 

  14. Birney, E. Mendelian Randomization. Cold Spring Harb. Perspect. Med. 12, https://doi.org/10.1101/cshperspect.a041302 (2022).

  15. Emdin, C. A., Khera, A. V. & Kathiresan, S. Mendelian Randomization. JAMA 318, 1925–1926 (2017).

    Article  PubMed  Google Scholar 

  16. Palmer, N. P. et al. Concordance between gene expression in peripheral whole blood and colonic tissue in children with inflammatory bowel disease. PLoS One 14, e0222952 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Li, K. et al. Molecular Comparison of Adult and Pediatric Ulcerative Colitis Indicates Broad Similarity of Molecular Pathways in Disease Tissue. J. Pediatr. Gastroenterol. Nutr. 67, 45–52 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. Keir, M. E. et al. Regulation and Role of αE Integrin and Gut Homing Integrins in Migration and Retention of Intestinal Lymphocytes during Inflammatory Bowel Disease. J. Immunol. 207, 2245–2254 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Elsworth, B. et al. The MRC IEU OpenGWAS data infrastructure. bioRxiv, https://doi.org/10.1101/2020.08.10.244293 (2020).

  20. Tang, C. S. et al. Fine mapping of the 9q31 Hirschsprung’s disease locus. Hum. Genet. 127, 675–683 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Garcia-Etxebarria, K. et al. Local genetic variation of inflammatory bowel disease in Basque population and its effect in risk prediction. Sci. Rep. 12, 3386 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kanehisa, M. & Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Newman, A. M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Bhattacharya, S. et al. ImmPort, toward repurposing of open access immunological assay data for translational and clinical research. Sci. Data 5, 180015 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma. 9, 559 (2008).

    Article  Google Scholar 

  29. Szklarczyk, D. et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607–d613 (2019).

    Article  CAS  PubMed  Google Scholar 

  30. Ru, Y. et al. The multiMiR R package and database: integration of microRNA-target interactions along with their disease and drug associations. Nucleic Acids Res. 42, e133 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Rauluseviciute, I. et al. JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles. Nucleic Acids Res. https://doi.org/10.1093/nar/gkad1059 (2023).

  32. Lamb, J. et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929–1935 (2006).

    Article  CAS  PubMed  Google Scholar 

  33. Wishart, D. S. et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 46, D1074–d1082 (2018).

    Article  CAS  PubMed  Google Scholar 

  34. Freshour, S. L. et al. Integration of the Drug-Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts. Nucleic Acids Res. 49, D1144–d1151 (2021).

    Article  CAS  PubMed  Google Scholar 

  35. Zdrazil, B. et al. The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods. Nucleic Acids Res., https://doi.org/10.1093/nar/gkad1004 (2023).

  36. Kim, S. et al. PubChem 2023 update. Nucleic Acids Res. 51, D1373–d1380 (2023).

    Article  PubMed  Google Scholar 

  37. Berman, H. M. et al. The Protein Data Bank. Nucleic Acids Res. 28, 235–242 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Morris, G. M. et al. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem. 30, 2785–2791 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Pontén, F., Jirström, K. & Uhlen, M. The Human Protein Atlas–a tool for pathology. J. Pathol. 216, 387–393 (2008).

    Article  PubMed  Google Scholar 

  40. Meng, C. et al. Gut microbiome and risk of ischaemic stroke: a comprehensive Mendelian randomization study. Eur. J. Prevent. Cardiol. 30, 613–620 (2023).

    Article  Google Scholar 

  41. Burgess, S., Scott, R. A., Timpson, N. J., Davey Smith, G. & Thompson, S. G. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur. J. Epidemiol. 30, 543–552 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Bowden, J., Davey Smith, G., Haycock, P. C. & Burgess, S. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet. Epidemiol. 40, 304–314 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Burgess, S., Butterworth, A. & Thompson, S. G. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet. Epidemiol. 37, 658–665 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Verbanck, M., Chen, C. Y., Neale, B. & Do, R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat. Genet. 50, 693–698 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Bowden, J., Davey Smith, G. & Burgess, S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44, 512–525 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Soret, R. et al. Glial Cell-Derived Neurotrophic Factor Induces Enteric Neurogenesis and Improves Colon Structure and Function in Mouse Models of Hirschsprung Disease. Gastroenterology 159, 1824–1838.e1817 (2020).

    Article  CAS  PubMed  Google Scholar 

  47. He, E. et al. The potential effects and mechanism of echinacoside powder in the treatment of Hirschsprung’s Disease. Math. Biosci. Eng. 20, 14222–14240 (2023).

    Article  PubMed  Google Scholar 

  48. Tomuschat, C., O’Donnell, A. M., Coyle, D. & Puri, P. Altered expression of IL36γ and IL36 receptor (IL1RL2) in the colon of patients with Hirschsprung’s disease. Pediatr. Surg. Int. 33, 181–186 (2017).

    Article  PubMed  Google Scholar 

  49. Tomuschat, C., O’Donnell, A. M., Coyle, D. & Puri, P. Increased Act1/IL-17R expression in Hirschsprung’s disease. Pediatr. Surg. Int. 32, 1201–1207 (2016).

    Article  PubMed  Google Scholar 

  50. Nakamura, H., Lim, T. & Puri, P. Inflammatory bowel disease in patients with Hirschsprung’s disease: a systematic review and meta-analysis. Pediatr. Surg. Int. 34, 149–154 (2018).

    Article  CAS  PubMed  Google Scholar 

  51. Saez, A., Herrero-Fernandez, B., Gomez-Bris, R., Sánchez-Martinez, H. & Gonzalez-Granado, J. M. Pathophysiology of Inflammatory Bowel Disease: Innate Immune System. Int. J. Mol. Sci. 24, https://doi.org/10.3390/ijms24021526 (2023).

  52. Verstockt, B. et al. Sphingosine 1-phosphate modulation and immune cell trafficking in inflammatory bowel disease. Nat. Rev. Gastroenterol. Hepatol. 19, 351–366 (2022).

    Article  CAS  PubMed  Google Scholar 

  53. Higashiyama, M. & Hokaria, R. New and Emerging Treatments for Inflammatory Bowel Disease. Digestion 104, 74–81 (2023).

    Article  CAS  PubMed  Google Scholar 

  54. Skrivankova, V. W. et al. Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement. JAMA 326, 1614–1621 (2021).

    Article  PubMed  Google Scholar 

  55. Davies, N. M., Holmes, M. V. & Davey Smith, G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ 362, k601 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Chen, X. et al. Intestinal proinflammatory macrophages induce a phenotypic switch in interstitial cells of Cajal. J. Clin. Invest. 130, 6443–6456 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Meir, M. et al. Intestinal Epithelial Barrier Maturation by Enteric Glial Cells Is GDNF-Dependent. Int. J. Mol. Sci. 22, https://doi.org/10.3390/ijms22041887 (2021).

  58. Schumacher, M. A. et al. ErbB4 signaling stimulates pro-inflammatory macrophage apoptosis and limits colonic inflammation. Cell Death Dis. 8, e2622 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Roberts, R. L. et al. Confirmation of association of IRGM and NCF4 with ileal Crohn’s disease in a population-based cohort. Genes Immun. 9, 561–565 (2008).

    Article  CAS  PubMed  Google Scholar 

  60. Rioux, J. D. et al. Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis. Nat. Genet. 39, 596–604 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Neurath, M. F. Cytokines in inflammatory bowel disease. Nat. Rev. Immunol. 14, 329–342 (2014).

    Article  CAS  PubMed  Google Scholar 

  62. Neurath, M. F. Targeting cytokines in inflammatory bowel disease. Sci. Transl. Med. 14, eabq4473 (2022).

    Article  CAS  PubMed  Google Scholar 

  63. Boland, B. S. et al. Heterogeneity and clonal relationships of adaptive immune cells in ulcerative colitis revealed by single-cell analyses. Sci. Immunol. 5, https://doi.org/10.1126/sciimmunol.abb4432 (2020).

  64. Geremia, A., Biancheri, P., Allan, P., Corazza, G. R. & Di Sabatino, A. Innate and adaptive immunity in inflammatory bowel disease. Autoimmun. Rev. 13, 3–10 (2014).

    Article  CAS  PubMed  Google Scholar 

  65. Boros, É. et al. Elevated Expression of AXL May Contribute to the Epithelial-to-Mesenchymal Transition in Inflammatory Bowel Disease Patients. Mediators Inflamm. 2018, 3241406 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Hang, S. et al. Bile acid metabolites control T(H)17 and T(reg) cell differentiation. Nature 576, 143–148 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Tange, K. et al. Oral administration of human carbonic anhydrase I suppresses colitis in a murine inflammatory bowel disease model. Sci. Rep. 12, 17983 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Minichová, L., Škultéty, Ľ. & Lakota, J. Autoimmune phenomena and spontaneous tumour regression. The role of carbonic anhydrase I. J. Cell. Mol. Med. 25, 5339–5340 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Schmitt, H., Neurath, M. F. & Atreya, R. Role of the IL23/IL17 Pathway in Crohn’s Disease. Front. Immunol. 12, 622934 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Cui, G., Fan, Q., Li, Z., Goll, R. & Florholmen, J. Evaluation of anti-TNF therapeutic response in patients with inflammatory bowel disease: Current and novel biomarkers. EBioMedicine 66, 103329 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge the public databases including GEO, IEU, GO, KEGG, GEPIA, STRING, JASPAR, Cmap, Drugbank, DGIdb, ChEMBL and HPA for their contributions to human medicine in which they share vast volumes of data. We are also grateful to the majority of researchers who are willing to publicly upload their experimental data. Thanks to the authors of the R package for their contribution to the advancement of Bioinformatics.

Funding

This work was supported in part by Tianjin Municipal Education Commission Research Plan Project (Natural Science) (2023YXZD12) and Tianjin University “Medicine+” Special Fund, Tianjin Natural Science Foundation (22JCZDJC00230).

Author information

Authors and Affiliations

Authors

Contributions

Research idea and design: Enyang He, Xiaohong Die and Hualei Cui. Data acquisition: Enyang He, Hailan Zhao and WeiZhao. Data analysis: Enyang He, Bowen Shi, Wenjin Sun, Miao Jia and Kaili Chang. Manuscript Writing: Enyang He,WeiFeng, Bowen Shi and Hongyv Jiang. Reviewing: Enyang He, Liang Dong and Hualei Cui.

Corresponding authors

Correspondence to Wei Feng or Hualei Cui.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval

The study was based on open-source data from multiple databases. Ethical approval has been provided for the patients involved in these databases. Therefore, there are no ethical issues with this article.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, E., Shi, B., Jia, M. et al. Hirschsprung’s disease may increase the incidence of inflammatory bowel disease through alterations in CA1. Pediatr Res 98, 1580–1590 (2025). https://doi.org/10.1038/s41390-025-03938-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41390-025-03938-w

Search

Quick links