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.

  • Article
  • Published:

Potential drug targets for gastroesophageal reflux disease and Barrett’s esophagus identified through Mendelian randomization analysis

Abstract

Gastroesophageal reflux disease (GERD) is a prevalent chronic ailment, and present therapeutic approaches are not always effective. This study aimed to find new drug targets for GERD and Barrett’s esophagus (BE). We obtained genetic instruments for GERD, BE, and 2004 plasma proteins from recently published genome-wide association studies (GWAS), and Mendelian randomization (MR) was employed to explore potential drug targets. We further winnowed down MR-prioritized proteins through replication, reverse causality testing, colocalization analysis, phenotype scanning, and Phenome-wide MR. Furthermore, we constructed a protein-protein interaction network, unveiling potential associations among candidate proteins. Simultaneously, we acquired mRNA expression quantitative trait loci (eQTL) data from another GWAS encompassing four different tissues to identify additional drug targets. Meanwhile, we searched drug databases to evaluate these targets. Under Bonferroni correction (P < 4.8 × 10−5), we identified 11 plasma proteins significantly associated with GERD. Among these, 7 are protective proteins (MSP, GPX1, ERBB3, BT3A3, ANTR2, CCM2, and DECR2), while 4 are detrimental proteins (TMEM106B, DUSP13, C1-INH, and LINGO1). Ultimately, C1-INH and DECR2 successfully passed the screening process and exhibited similar directional causal effects on BE. Further analysis of eQTLs highlighted 4 potential drug targets, including EDEM3, PBX3, MEIS1-AS3, and NME7. The search of drug databases further supported our conclusions. Our study indicated that the plasma proteins C1-INH and DECR2, along with 4 genes (EDEM3, PBX3, MEIS1-AS3, and NME7), may represent potential drug targets for GERD and BE, warranting further investigation.

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

Access options

Buy this article

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Katzka DA, Kahrilas PJ. Advances in the diagnosis and management of gastroesophageal reflux disease. BMJ. 2020;371:m3786.

    Article  PubMed  Google Scholar 

  2. Richter JE, Rubenstein JH. Presentation and Epidemiology of Gastroesophageal Reflux Disease. Gastroenterology. 2018;154:267–76.

    Article  PubMed  Google Scholar 

  3. Eusebi LH, Ratnakumaran R, Yuan Y, Solaymani-Dodaran M, Bazzoli F, Ford AC. Global prevalence of, and risk factors for, gastro-oesophageal reflux symptoms: a meta-analysis. Gut. 2018;67:430–40.

    Article  PubMed  Google Scholar 

  4. Peery AF, Dellon ES, Lund J, Crockett SD, McGowan CE, Bulsiewicz WJ, et al. Burden of gastrointestinal disease in the United States: 2012 update. Gastroenterology. 2012;143:1179–87.e3.

    Article  PubMed  Google Scholar 

  5. Maret-Ouda J, Markar SR, Lagergren J. Gastroesophageal reflux disease: a review. JAMA. 2020;324:2536–47.

    Article  CAS  PubMed  Google Scholar 

  6. Zheng Z, Shang Y, Wang N, Liu X, Xin C, Yan X, et al. Current advancement on the dynamic mechanism of gastroesophageal reflux disease. Int J Biol Sci. 2021;17:4154–64.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Yadlapati R, DeLay K. Proton Pump Inhibitor-Refractory Gastroesophageal Reflux Disease. Med Clin North Am. 2019;103:15–27.

    Article  PubMed  Google Scholar 

  8. Nelson MR, Tipney H, Painter JL, Shen J, Nicoletti P, Shen Y, et al. The support of human genetic evidence for approved drug indications. Nat Genet. 2015;47:856–60.

    Article  CAS  PubMed  Google Scholar 

  9. Reay WR, Cairns MJ. Advancing the use of genome-wide association studies for drug repurposing. Nat Rev Genet. 2021;22:658–71.

    Article  CAS  PubMed  Google Scholar 

  10. Ochoa D, Karim M, Ghoussaini M, Hulcoop DG, McDonagh EM, Dunham I. Human genetics evidence supports two-thirds of the 2021 FDA-approved drugs. Nat Rev Drug Discov. 2022;21:551.

    Article  CAS  PubMed  Google Scholar 

  11. Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27:1133–63.

    Article  MathSciNet  PubMed  Google Scholar 

  12. Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018;7:e34408.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Ning Z, Huang Y, Lu H, Zhou Y, Tu T, Ouyang F, et al. Novel Drug Targets for Atrial Fibrillation Identified Through Mendelian Randomization Analysis of the Blood Proteome. Cardiovasc Drugs Ther. 2023. https://doi.org/10.1007/s10557-023-07467-8.

  14. Lin J, Zhou J, Liu Z, Zeng R, Wang L, Li F, et al. Identification of potential drug targets for varicose veins: a Mendelian randomization analysis. Front Cardiovasc Med. 2023;10:1126208.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Gu X, Dou M, Su W, Jiang Z, Duan Q, Cao B, et al. Identifying novel proteins underlying schizophrenia via integrating pQTLs of the plasma, CSF, and brain with GWAS summary data. BMC Med. 2022;20:474.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ong JS, An J, Han X, Law MH, Nandakumar P, Me Research t. et al. Multitrait genetic association analysis identifies 50 new risk loci for gastro-oesophageal reflux, seven new loci for Barrett’s oesophagus and provides insights into clinical heterogeneity in reflux diagnosis. Gut. 2022;71:1053–61.

    Article  PubMed  Google Scholar 

  17. Zhang J, Dutta D, Kottgen A, Tin A, Schlosser P, Grams ME, et al. Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies. Nat Genet. 2022;54:593–602.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ferkingstad E, Sulem P, Atlason BA, Sveinbjornsson G, Magnusson MI, Styrmisdottir EL, et al. Large-scale integration of the plasma proteome with genetics and disease. Nat Genet. 2021;53:1712–21.

    Article  CAS  PubMed  Google Scholar 

  19. Pierce BL, Ahsan H, Vanderweele TJ. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol. 2011;40:740–52.

    Article  PubMed  Google Scholar 

  20. Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362:k601.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Swerdlow DI, Kuchenbaecker KB, Shah S, Sofat R, Holmes MV, White J, et al. Selecting instruments for Mendelian randomization in the wake of genome-wide association studies. Int J Epidemiol. 2016;45:1600–16.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Deng YT, Ou YN, Wu BS, Yang YX, Jiang Y, Huang YY, et al. Identifying causal genes for depression via integration of the proteome and transcriptome from brain and blood. Mol Psychiatry. 2022;27:2849–57.

    Article  CAS  PubMed  Google Scholar 

  23. Lin J, Zhou J, Xu Y. Potential drug targets for multiple sclerosis identified through Mendelian randomization analysis. Brain. 2023;146:3364–72.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23:R89–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Hemani G, Tilling K, Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017;13:e1007081.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Giambartolomei C, Vukcevic D, Schadt EE, Franke L, Hingorani AD, Wallace C, et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 2014;10:e1004383.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Chen L, Peters JE, Prins B, Persyn E, Traylor M, Surendran P, et al. Systematic Mendelian randomization using the human plasma proteome to discover potential therapeutic targets for stroke. Nat Commun. 2022;13:6143.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kamat MA, Blackshaw JA, Young R, Surendran P, Burgess S, Danesh J, et al. PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019;35:4851–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Chong M, Sjaarda J, Pigeyre M, Mohammadi-Shemirani P, Lali R, Shoamanesh A, et al. Novel Drug Targets for Ischemic Stroke Identified Through Mendelian Randomization Analysis of the Blood Proteome. Circulation. 2019;140:819–30.

    Article  CAS  PubMed  Google Scholar 

  30. Elsworth B, Lyon M, Alexander T, Liu Y, Matthews P, Hallett J, et al. The MRC IEU OpenGWAS data infrastructure. bioRxiv. 2020.08.10.244293.

  31. Finan C, Gaulton A, Kruger FA, Lumbers RT, Shah T, Engmann J, et al. The druggable genome and support for target identification and validation in drug development. Sci Transl Med. 2017;9:eaag1166.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Zhou Y, Zhang Y, Lian X, Li F, Wang C, Zhu F, et al. Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents. Nucleic Acids Res. 2022;50:D1398–D407.

    Article  CAS  PubMed  Google Scholar 

  33. Mostafavi S, Ray D, Warde-Farley D, Grouios C, Morris Q. GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function. Genome Biol. 2008;9:S4.

    Article  PubMed  PubMed Central  Google Scholar 

  34. McGowan LM, Davey Smith G, Gaunt TR, Richardson TG. Integrating Mendelian randomization and multiple-trait colocalization to uncover cell-specific inflammatory drivers of autoimmune and atopic disease. Hum Mol Genet. 2019;28:3293–300.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Zheng J, Haberland V, Baird D, Walker V, Haycock PC, Hurle MR, et al. Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases. Nat Genet. 2020;52:1122–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Lutz SM, Wu AC, Hokanson JE, Vansteelandt S, Lange C. Caution against examining the role of reverse causality in Mendelian Randomization. Genet Epidemiol. 2021;45:445–54.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Zhang Y, Xie J, Wen S, Cao P, Xiao W, Zhu J, et al. Evaluating the causal effect of circulating proteome on the risk of osteoarthritis-related traits. Ann Rheum Dis. 2023;82:1606–17.

  38. Tack J, Pandolfino JE. Pathophysiology of Gastroesophageal Reflux Disease. Gastroenterology. 2018;154:277–88.

    Article  CAS  PubMed  Google Scholar 

  39. Mittal R, Vaezi MF. Esophageal Motility Disorders and Gastroesophageal Reflux Disease. N. Engl J Med. 2020;383:1961–72.

    Article  CAS  PubMed  Google Scholar 

  40. Wouters D, Wagenaar-Bos I, van Ham M, Zeerleder S. C1 inhibitor: just a serine protease inhibitor? New and old considerations on therapeutic applications of C1 inhibitor. Expert Opin Biol Ther. 2008;8:1225–40.

    Article  CAS  PubMed  Google Scholar 

  41. Morgan EL. Modulation of the immune response by anaphylatoxins. Complement. 1986;3:128–36.

    Article  CAS  PubMed  Google Scholar 

  42. Caballero T. Treatment of Hereditary Angioedema. J Investig Allergol Clin Immunol. 2021;31:1–16.

    Article  CAS  PubMed  Google Scholar 

  43. Kavanagh KL, Jornvall H, Persson B, Oppermann U. Medium- and short-chain dehydrogenase/reductase gene and protein families: the SDR superfamily: functional and structural diversity within a family of metabolic and regulatory enzymes. Cell Mol Life Sci. 2008;65:3895–906.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Wanders RJ, Waterham HR. Biochemistry of mammalian peroxisomes revisited. Annu Rev Biochem. 2006;75:295–332.

    Article  CAS  PubMed  Google Scholar 

  45. Kenchaiah S, Evans JC, Levy D, Wilson PW, Benjamin EJ, Larson MG, et al. Obesity and the risk of heart failure. N. Engl J Med. 2002;347:305–13.

    Article  PubMed  Google Scholar 

  46. Estruch R, Ros E. The role of the Mediterranean diet on weight loss and obesity-related diseases. Rev Endocr Metab Disord. 2020;21:315–27.

    Article  PubMed  Google Scholar 

  47. Singh S, Sharma AN, Murad MH, Buttar NS, El-Serag HB, Katzka DA, et al. Central adiposity is associated with increased risk of esophageal inflammation, metaplasia, and adenocarcinoma: a systematic review and meta-analysis. Clin Gastroenterol Hepatol. 2013;11:1399–412.e7.

    Article  PubMed  Google Scholar 

  48. Yu S, Ito S, Wada I, Hosokawa N. ER-resident protein 46 (ERp46) triggers the mannose-trimming activity of ER degradation-enhancing alpha-mannosidase-like protein 3 (EDEM3). J Biol Chem. 2018;293:10663–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Xu YX, Peloso GM, Nagai TH, Mizoguchi T, Deik A, Bullock K, et al. EDEM3 Modulates Plasma Triglyceride Level through Its Regulation of LRP1 Expression. iScience. 2020;23:100973.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  50. Bilitou A, Watson J, Gartner A, Ohnuma S. The NM23 family in development. Mol Cell Biochem. 2009;329:17–33.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the authors for providing GWAS data and making the GWAS summary data publicly available. We acknowledge the participants and investigators of the ARIC cohort, deCODE cohort, IEU Open GWAS, The Genotype-Tissue Expression Consortium and the study of Ong et al.

Funding

This work was funded by the National Natural Science Foundation of China [grantnumbers82070333]; and the Zhejiang Provincial Natural Science Foundation [grantnumbersLY21H020011].

Author information

Authors and Affiliations

Authors

Contributions

Yun-Lu Lin, Tao Yao, and Jia-Feng Lin designed the study and drafted the article; Ying-Wei Wang and Zhi-Xiang Zhou conducted data acquisition, and Ze-Chao Hong, Yu Shen, and Yu Yan performed data analysis and manuscript revision. All authors contributed to the article and approved the submitted version.

Corresponding authors

Correspondence to Yue-Chun Li or Jia-Feng Lin.

Ethics declarations

Competing interests

The authors declare no competing interests.

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

Lin, YL., Yao, T., Wang, YW. et al. Potential drug targets for gastroesophageal reflux disease and Barrett’s esophagus identified through Mendelian randomization analysis. J Hum Genet (2024). https://doi.org/10.1038/s10038-024-01234-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s10038-024-01234-9

Search

Quick links