Sucrase-isomaltase 15Phe IBS risk variant in relation to dietary carbohydrates and faecal microbiota composition

Louise Thingholm, Malte Rühlemann, Jun Wang, Matthias Hübenthal, Wolfgang Lieb, Matthias Laudes, Andre Franke, Mauro D'Amato, Louise Thingholm, Malte Rühlemann, Jun Wang, Matthias Hübenthal, Wolfgang Lieb, Matthias Laudes, Andre Franke, Mauro D'Amato

No abstract available

Keywords: carbohydrates; enteric bacterial microflora; genetics; irritable bowel syndrome.

Conflict of interest statement

Competing interests: MDA has received unrestricted research grants from QOL Medical.

Figures

Figure 1
Figure 1
Sucrase-isomaltase (SI) 15Phe-driven IBS risk effects are stronger in low-starch consumers. The prevalence of IBS (%) across quartiles of starch intake (g/day) is reported, together with respective counts and number of individuals in each quartile group (Q1–Q4).
Figure 2
Figure 2
15Phe genotype influences Blautia faecal abundance. (Left) Genotype-stratified correlation between starch intake and Blautia faecal microbiota abundance (each circle represents an individual). A trend was identified when comparing the two sucrase-isomaltase (SI) 15Phe genotype groups for their starch-bacteria correlations (age/sex/body mass index (BMI)/total energy (TE)-adjusted generalised linear model (GLM) with negative-binomial distribution, and interaction term for genotype and starch intake), in that increasing starch intake corresponds to higher Blautia abundance in 15Phe carriers compared with non-carriers (uncorrected P=0.054). (Right) Blautia faecal microbiota abundance in the two SI genotype groups stratified according to IBS status was significantly increased in IBS cases carrying the 15Phe variant (P=0.00041, beta=0.80), while there was no significant association in non-carriers (P=0.31, beta=0.33). Association analysis was performed using GLM age/sex/BMI/TE adjusted (glm.nb in stats/R). Plots were made using ggplot in ggplot2/R with stat_smooth and method=lm (left panel), and square root transformation of Blautia relative abundance (right panel).

References

    1. Henström M, Diekmann L, Bonfiglio F, et al. . Functional variants in the sucrase-isomaltase gene associate with increased risk of irritable bowel syndrome. Gut 2018;67:263–70. 10.1136/gutjnl-2016-312456
    1. Krawczak M, Nikolaus S, von Eberstein H, et al. . PopGen: population-based recruitment of patients and controls for the analysis of complex genotype-phenotype relationships. Community Genet 2006;9:55–61. 10.1159/000090694
    1. Müller N, Schulte DM, Türk K, et al. . IL-6 blockade by monoclonal antibodies inhibits apolipoprotein (a) expression and lipoprotein (a) synthesis in humans. J Lipid Res 2015;56:1034–42. 10.1194/jlr.P052209
    1. Wang J, Thingholm LB, Skiecevičienė J, et al. . Genome-wide association analysis identifies variation in vitamin D receptor and other host factors influencing the gut microbiota. Nat Genet 2016;48:1396–406. 10.1038/ng.3695
    1. Yi Wang UN, Wright S, Warton DI. mvabund: an R package for model-based analysis of multivariate data. Methods Ecol Evol 2012:471–4.
    1. Vieira-Silva S, Falony G, Darzi Y, et al. . Species-function relationships shape ecological properties of the human gut microbiome. Nat Microbiol 2016;1:16088 10.1038/nmicrobiol.2016.88
    1. Labus JS, Hollister EB, Jacobs J, et al. . Differences in gut microbial composition correlate with regional brain volumes in irritable bowel syndrome. Microbiome 2017;5:49 10.1186/s40168-017-0260-z
    1. Rajilić-Stojanović M, Biagi E, Heilig HG, et al. . Global and deep molecular analysis of microbiota signatures in fecal samples from patients with irritable bowel syndrome. Gastroenterology 2011;141:1792–801. 10.1053/j.gastro.2011.07.043
    1. Rajilić-Stojanović M, Jonkers DM, Salonen A, et al. . Intestinal microbiota and diet in IBS: causes, consequences, or epiphenomena? Am J Gastroenterol 2015;110:278–87. 10.1038/ajg.2014.427

Source: PubMed

Patrocinadores y Colaboradores

Condiciones médicas

Intervenciones de drogas

3
Suscribir