Unraveling the genetic susceptibility of [IBS]: integrative genome-wide analyses in 845 492 individuals: a diagnostic study, 2024, Huang et al

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Unraveling the genetic susceptibility of irritable bowel syndrome: integrative genome-wide analyses in 845 492 individuals: a diagnostic study

Huang, Wentao; Zhang, Lijun; Ma, Yuying; Yu, Shiyi; Lyu, Yanlin; Tong, Shuangshuang; Wang, Jiaxuan; Jiang, Rui; Meng, Meijun; Wu, Yanjun; Luo, Ruibang; Qiu, Xinqi; Sha, Weihong; Chen, Hao

Background
Irritable bowel syndrome (IBS) significantly impacts individuals due to its prevalence and negative effect on quality of life. Current genome-wide association studies (GWAS) have only identified a small number of crucial single nucleotide polymorphisms (SNPs), not fully elucidating IBS’s pathogenesis.

Objective
To identify genomic loci at which common genetic variation influences IBS susceptibility.

Methods
Combining independent cohorts that in total comprise 65 840 cases of IBS and 788 652 controls, the authors performed a meta-analysis of genome-wide association studies (GWAS) of IBS. The authors also carried out gene mapping and pathway enrichment to gain insights into the underlying genes and pathways through which the associated loci contribute to disease susceptibility.

Furthermore, the authors performed transcriptome analysis to deepen their understanding. IBS risk models were developed by combining clinical/lifestyle risk factors with polygenic risk scores (PRS) derived from the GWAS meta-analysis. The authors detect the phenotype association for IBS utilizing PRS-based phenome-wide association (PheWAS) analyses, linkage disequilibrium score regression, and Mendelian randomization.

Results
The GWAS meta-analysis identified 10 IBS risk loci, seven of which were novel (rs12755507, rs34209273, rs34365748, rs67427799, rs2587363, rs13321176, rs1546559). Multiple methods identified nine promising IBS candidate gene ( PRRC2A, COP1, CADM2, LRP1B, SUGT1, MED12L, P2RY14, PHF2, SHISA6 ) at 10 GWAS loci.

Transcriptome validation also revealed differential expression of these genes. Phenome-wide associations between PRS-IBS and nine traits (neuroticism, diaphragmatic hernia, asthma, diverticulosis, cholelithiasis, depression, insomnia, COPD, and BMI) were identified.

The six diseases (asthma, diaphragmatic hernia, diverticulosis, insomnia major depressive disorder and neuroticism) were found to show genetic association with IBS and only major depressive disorder and neuroticism were found to show causality with IBS.

Conclusion
The authors identified seven novel risk loci for IBS and highlighted the substantial influence on genetic risk harbored. The authors’ findings offer novel insights into etiology and phenotypic association of IBS and lay the foundation for therapeutic targets and interventional strategies.

Web | DOI | PMC | PDF | International Journal of Surgery | Open Access
 
The researchers looked at expression of SHISA6 in a different cohort:

We selected bulk sequencing data from the GEO dataset (GSE36701), which includes data from 18 constipation-predominant IBS subjects (IBS-C), 27 diarrhea-predominant IBS subjects (IBS-D), 21 individuals with Campylobacter jejuni infection, and 40 healthy volunteers (HV)29. Then, we visualized the results of the differential analysis using R with the “ggplot2” (https://ggplot2.tidyverse.org) and “ggpubr” (https://rpkgs.datanovia.com/ggpubr/) packages.
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Additionally, transcriptome validation provided further evidence supporting the functional relevance of our identified genes (Supplementary Figure S1, Supplemental Digital Content 3, http://links.lww.com/JS9/D338).
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The plot is very blurry, so it's hard to make out what that number is, but I assume it's a p-value, and I think the exponent is -10.
1777131901077.png
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8 out of 9 of their GWAS candidate genes seem to show significant differential expression in the other cohort:
1777132049296.png

That looks like a lot more dots than the number of participants they described in the methods section. I looked at the dataset page, GSE36701, where it shows that there is data for 221 samples, which seems like it could be the number of dots in that plot. But I think this is multiple samples per individual. For example, there are four samples listed for the healthy control with subject identifier SD52930.

If they tested multiple samples per individual, the low p-value for this gene and most of the other genes in the expression tests below is likely artificially low due to pseudoreplication.

Though this is separate from the GWAS results, which may be more reliable.
 
This shows the effect sizes for the SNPs in the individual cohorts used in the meta-analysis. I highlighted the SHISA6 lead SNP, 17-11325637-G-C / rs1546559.
1777138516309.png
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It's somewhat significant in UK BioBank (p=9.62e-6), not significant in FinnGen (p=0.13), and no data for this SNP in Genetic Epidemiology Research on Aging (GERA) cohort. Highly significant when combining the cohorts (p=1.53e-9).

The effect direction is negative for both UKB and FinnGen.

The negative effect direction for the C allele is consistent with DecodeME:
1777139245424.png
 
For SHISA6, the lead SNP for IBS in this study is actually the same as the lead SNP for ME/CFS in DecodeME, so I think there's a very good chance it's the same causal variant.

Zoomed in plot for DecodeME:
1777140524999.png

42.6% of the DecodeME cohort reported IBS, so it makes sense that there are some genetic similarities.
 
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This makes me wonder if in the future, it might be good to do a larger GWAS that includes both ME/CFS and IBS cases, as this might help pinpoint the common factors that make people susceptible to both conditions, with the benefit of larger sample size as well.

Same thing for ME/CFS and chronic pain, considering the high comorbidity of pain in ME/CFS, and the genetic similarities that were noted.

Maybe all three at once.
 
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