4.8 Article

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

Journal

GUT
Volume 71, Issue 6, Pages 1053-+

Publisher

BMJ PUBLISHING GROUP
DOI: 10.1136/gutjnl-2020-323906

Keywords

-

Funding

  1. US National Cancer Institute at the National Institutes of Health [R01CA136725]
  2. National Health and Medical Research Council (NHMRC) Fellowships
  3. NHMRC Investigator Grant [1173390]
  4. University of Queensland Research Training Scholarship
  5. QIMR Berghofer PhD Top Up Scholarship
  6. NHMRC [1123248]
  7. Australian NHMRC [APP1063061, R01CA57947-03]
  8. National Cancer Institute
  9. Swedish Cancer Society [4559-B01-01XAA, 4758-B02-01XAB]
  10. US NIH [R01DK63616, R01CA59636]
  11. California Tobacco Related Research Program [3RT-0122, 10RT-0251]
  12. University of Texas MD Anderson Cancer Center (UTMDACC)
  13. NIH [R01CA100264, P30CA016672, R01CA133996]
  14. UTMDACC NIH SPORE in Melanoma [2P50CA093459]
  15. Marit Peterson Fund for Melanoma Research [HHSN268200782096C]
  16. National Institute of Neurological Disorders and Stroke (NINDS) dbGaP database from the CIDR
  17. National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
  18. NIDDK
  19. Wellcome Trust medical charity, Medical Research Council (UK), Department of Health (UK)
  20. Scottish Government
  21. Northwest Regional Development Agency
  22. Welsh Assembly Government
  23. British Heart Foundation
  24. Diabetes UK
  25. [25331]
  26. National Health and Medical Research Council of Australia [1123248, 1173390] Funding Source: NHMRC

Ask authors/readers for more resources

Researchers identified numerous novel risk loci for GERD and BE using a multitrait GWAS model, providing strong evidence for a genetic basis of disease heterogeneity in GERD. They showed that GERD loci associated with obesity are better predictors of BE/EA compared to those associated with depressive symptoms.
Objective Gastro-oesophageal reflux disease (GERD) has heterogeneous aetiology primarily attributable to its symptom-based definitions. GERD genome-wide association studies (GWASs) have shown strong genetic overlaps with established risk factors such as obesity and depression. We hypothesised that the shared genetic architecture between GERD and these risk factors can be leveraged to (1) identify new GERD and Barrett's oesophagus (BE) risk loci and (2) explore potentially heterogeneous pathways leading to GERD and oesophageal complications. Design We applied multitrait GWAS models combining GERD (78 707 cases; 288 734 controls) and genetically correlated traits including education attainment, depression and body mass index. We also used multitrait analysis to identify BE risk loci. Top hits were replicated in 23andMe (462 753 GERD cases, 24 099 BE cases, 1 484 025 controls). We additionally dissected the GERD loci into obesity-driven and depression-driven subgroups. These subgroups were investigated to determine how they relate to tissue-specific gene expression and to risk of serious oesophageal disease (BE and/or oesophageal adenocarcinoma, EA). Results We identified 88 loci associated with GERD, with 59 replicating in 23andMe after multiple testing corrections. Our BE analysis identified seven novel loci. Additionally we showed that only the obesity-driven GERD loci (but not the depression-driven loci) were associated with genes enriched in oesophageal tissues and successfully predicted BE/EA. Conclusion Our multitrait model identified many novel risk loci for GERD and BE. We present strong evidence for a genetic underpinning of disease heterogeneity in GERD and show that GERD loci associated with depressive symptoms are not strong predictors of BE/EA relative to obesity-driven GERD loci.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available