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Neurogastroenterology
Original research
Cross-definition GWAS of IBS in 2.8 million individuals reveals cardiometabolic and triglyceride-linked mechanisms
Objective To identify genetic risk factors and actionable mechanisms for future clinical translation in IBS.
Design We conducted a genome-wide association study (GWAS) meta-analysis of IBS in 2 775 539 individuals from 22 biobanks. IBS genetics was studied across multiple ancestries, different case definitions and symptom-related subtypes. Heritability and genetic correlations with other traits were estimated, and Mendelian randomisation was used to test causal relationships. GWAS data were functionally annotated and fine-mapped to prioritise tissues, cell types, pathways, candidate genes, specific mechanisms and druggable targets.
Results Significant heritability was only detected in individuals of European ancestry, with near-identical genetic architecture across case definitions. Genetic correlations with GI, psychiatric and cardiometabolic traits were observed, including causal relationships with triglyceride (TG) levels. Functional annotation of IBS risk loci highlighted cell types and pathways relevant to brain, enteric neuro-glial and cardiometabolic domains, as well as actionable targets like GCKR, a regulator of TG metabolism. Druggability analyses converged on cardiometabolic mechanisms, including TG modulation. IBS polygenic risk scores were derived and showed a significant association with case status in an independent case-control dataset, supporting further evaluation in external population-based and clinically ascertained cohorts.
Conclusions This study provides the most comprehensive assessment of IBS genetics to date, demonstrating reproducible polygenic inheritance. We link IBS risk to convergent neurogastrointestinal and novel cardiometabolic mechanisms, highlight specific biological pathways and actionable mechanisms and outline translational opportunities emerging from integrated computational analyses.
Neurogastroenterology
Original research
Cross-definition GWAS of IBS in 2.8 million individuals reveals cardiometabolic and triglyceride-linked mechanisms
- Biagio Di Lorenzo1,
- Leticia Camargo Tavares2,3,4,5,
- http://orcid.org/0000-0002-1593-2885Cristian Díaz-Muñoz6,
- Francisco Heredia-Fernández6,
- Isotta Bozzarelli1,
- Cristina Esteban Blanco6,
- Zhe Wang7,8,
- Roelof A J Smit8,9,
- Ruth J F Loos8,9,
- Jibril Hirbo10,11,
- Nancy J Cox10,11,
- Peter Straub10,11,
- Marie-Julie Favé12,13,
- Philip Awadalla14,15,
- Nikita Pozdeyev16,17,18,19,
- Christopher R Gignoux16,18,19,20,
- Colorado Center for Personalized Medicine,
- Daniel F Gudbjartsson21,22,
- Gudmar Thorleifsson21,
- Ingileif Jonsdottir21,23,
- Kari Stefansson21,23,
- http://orcid.org/0000-0002-6529-3161Erik Abner24,
- Priit Palta24,
- Estonian Biobank Research Team,
- Alexander T Williams25,
- Kayesha Coley25,26,
- Gerald Sze25,26,
- Catherine John25,26,
- Anne Richmond27,
- Daniel McCartney27,
- Caroline Hayward27,
- Ashley J Mulford28,
- Alan R Sanders28,29,
- Raitis Peculis30,
- Vita Rovite30,
- Marija Simona Dombrovska30,
- Mario Capasso31,32,
- Valeria Lo Faro33,34,
- Trishla Sinha35,
- Esteban Alexander Lopera Maya35,
- Alexandra Zhernakova35,
- Lifelines Cohort,
- Ying Wang36,37,38,
- Alicia Martin36,37,38,
- Brett Vanderwerff39,
- Sebastian Zöllner39,40,
- Brian R Ferolito41,42,43,
- Alexander C Pereira41,42,43,
- John Michael Gaziano41,42,43,
- Kelly Cho41,42,43,
- Lanna Caruth44,
- Lindsay Guare44,
- Colleen M Kripke45,
- Daniel J Rader46,
- Shefali S Verma47,
- Anurag Verma45,
- Penn Medicine BioBank,
- Chadi Saad48,
- Hamdi Mbarek48,
- Pei-Yu Chao49,
- Tzu-Ting Chen50,
- Yen-Feng Lin50,
- Yen-Chen Anne Feng49,51,
- http://orcid.org/0009-0007-4043-3387Prasanna K Challa4,5,
- http://orcid.org/0000-0002-7956-6941Hamed Khalili4,5,43,52,
- Aristomo Andries53,
- http://orcid.org/0000-0001-6005-0729Eivind Ness-Jensen54,55,56,
- Ben Michael Brumpton53,54,57,
- http://orcid.org/0000-0001-5092-0831Madhusudan Grover58,
- FinnGen,
- Susanna Lemmelä59,60,
- Serena Sanna33,35,
- Ferdinando Bonfiglio31,32,
- http://orcid.org/0000-0003-2743-5197Mauro D’Amato1,6,61
- Correspondence to Professor Mauro D’Amato; damato@lum.it
Abstract
Background Irritable bowel syndrome (IBS) is a complex disorder of gut-brain interaction, with heterogeneous symptoms, no available biomarkers and limited pathogenetic insight.Objective To identify genetic risk factors and actionable mechanisms for future clinical translation in IBS.
Design We conducted a genome-wide association study (GWAS) meta-analysis of IBS in 2 775 539 individuals from 22 biobanks. IBS genetics was studied across multiple ancestries, different case definitions and symptom-related subtypes. Heritability and genetic correlations with other traits were estimated, and Mendelian randomisation was used to test causal relationships. GWAS data were functionally annotated and fine-mapped to prioritise tissues, cell types, pathways, candidate genes, specific mechanisms and druggable targets.
Results Significant heritability was only detected in individuals of European ancestry, with near-identical genetic architecture across case definitions. Genetic correlations with GI, psychiatric and cardiometabolic traits were observed, including causal relationships with triglyceride (TG) levels. Functional annotation of IBS risk loci highlighted cell types and pathways relevant to brain, enteric neuro-glial and cardiometabolic domains, as well as actionable targets like GCKR, a regulator of TG metabolism. Druggability analyses converged on cardiometabolic mechanisms, including TG modulation. IBS polygenic risk scores were derived and showed a significant association with case status in an independent case-control dataset, supporting further evaluation in external population-based and clinically ascertained cohorts.
Conclusions This study provides the most comprehensive assessment of IBS genetics to date, demonstrating reproducible polygenic inheritance. We link IBS risk to convergent neurogastrointestinal and novel cardiometabolic mechanisms, highlight specific biological pathways and actionable mechanisms and outline translational opportunities emerging from integrated computational analyses.