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Alterations in intestinal bile acid transport provide a therapeutic target in patients with post-bariatric hypoglycaemia

Nature Metabolism volume 7, pages 792–807 (2025)Cite this article

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Abstract

While Roux-en-Y gastric bypass is an effective treatment for obesity and type 2 diabetes, up to one-third of patients develop post-bariatric hypoglycaemia (PBH). Individuals with PBH exhibit increased postprandial secretion of the intestinal hormone fibroblast growth factor 19 (FGF19, Fgf15 in mice). However, the underlying mechanisms contributing to PBH remain uncertain. Here we demonstrate that faecal and plasma bile acid (BA) profiles are significantly altered in postoperative individuals with PBH versus those without hypoglycaemia. Furthermore, altered BAs in PBH induce FGF19 secretion in intestinal cells in a manner dependent on the apical sodium-dependent BA transporter (ASBT). We demonstrate that ASBT inhibition reduces Fgf15 expression and increases postprandial glucose in hypoglycaemic mice. Our data suggest that dysregulation of luminal BA profiles and transport may contribute to PBH and provide proof of concept that ASBT inhibition could be developed as a new therapeutic strategy for PBH.

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Fig. 1: Post-op hypoglycaemia in humans is characterized by a shift in faecal and postprandial plasma BAs.
Fig. 2: Metabolic metrics of post-op RYGB in humans.
Fig. 3: BAs shifted in individuals with post-op hypoglycaemia induce FGF19 secretion and gene expression in vitro.
Fig. 4: ASBT is required for BAs to induce FGF19 secretion and gene expression in vitro.
Fig. 5: ASBT inhibition reduced BA accumulation in intestinal epithelial cells.
Fig. 6: Elobixibat treatment reduces postprandial systemic BA absorption and Fgf15 expression and protects against hypoglycaemia.
Fig. 7: Caecal BA profiling in chow-fed mice treated with elobixibat and subjected to an MMTT.
Fig. 8: Elobixibat treatment protects against hypoglycaemia in female mice.

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Data availability

All data generated or analysed during this study are included in this article and its Extended Data and Supplementary Information. Requests for additional information can be made to the corresponding authors. Source data are provided with this paper.

Code availability

No custom code or mathematical algorithms were used in this study.

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Acknowledgements

This study was supported by the National Institutes of Health awards R01 DK121995 (to M.-E.P), DK126855 (to E.G.S. and A.S.D.), K99 DK128503 (to S.N.C.) and P30 DK036836 (Diabetes Research Center, Joslin Diabetes Center) and an American Surgical Association Foundation Fellowship Award (to E.G.S.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We are grateful to the study participants and clinical research nursing staff.

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Authors and Affiliations

  1. Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA

    Snehal N. Chaudhari, Gabriel D’Agostino, Fei Ye & A. Sloan Devlin

  2. Department of Biochemistry, University of Wisconsin–Madison, Madison, WI, USA

    Snehal N. Chaudhari

  3. Laboratory for Surgical and Metabolic Research, Department of Surgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Yingjia Chen & Eric G. Sheu

  4. Department of Integrative Physiology and Metabolism, Research Division, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA

    Rafael Ferraz-Bannitz, Cameron Cummings, Amanda Sheehan, Pilar Casanova Querol, Berkcan Ozturk, Hanna Wang & Mary-Elizabeth Patti

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Contributions

Conceptualization and study design was carried out by S.N.C., E.G.S., A.S.D. and M.-E.P. Human samples were collected and banked by C.C., A.S. and M.-E.P. Human blood molecular analyses were performed by R.F.-B. and C.C. All in vitro experiments and BA analyses in in vitro and in vivo samples were performed by S.N.C. C4 analyses were performed by G.D.A. and F.Y. In vivo experiments and assays were performed by R.F.-B., P.C.Q., B.O., H.W. and Y.C. All authors edited and contributed to the critical review of the paper.

Corresponding authors

Correspondence to A. Sloan Devlin or Mary-Elizabeth Patti.

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Competing interests

A.S.D. is an ad hoc consultant for Axial Therapeutics. E.G.S. is a consultant for Vicarious Surgical, and received speaker fees at Cine-Med. S.N.C. is an ad hoc consultant for Metis Therapeutics. M.-E.P. serves on the data safety monitoring board for Fractyl, has received investigator-initiated research support from Dexcom and has served as a consultant for Eiger, Hanmi and MBX Pharmaceuticals. The other authors declare no competing interests.

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Nature Metabolism thanks Rohit Kohli, Antonio Moschetta and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Jean Nakhle and Ashley Castellanos-Jankiewicz, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 Consort diagram.

a. Consort diagram for participants providing stool samples from NCT04428866 (left) and NCT03385707 (right). b. Consort diagram for participants in NCT04428866 for which mixed meal tolerance test samples were analyzed.

Extended Data Fig. 2 Post-op hypoglycemia in human patients is characterized by a shift in fecal BAs.

Individual BAs whose levels were reduced in the feces of post-op hypoglycemic individuals but for which the difference between groups was not statistically significant (post-op non-hypoglycemic n = 15, post-op hypoglycemic n = 46; two-tailed Welch’s t test). Data not marked are not statistically significant (p > 0.05). All other significant BAs shown in Fig. 1. Patient characteristics and demographics detailed in Supplementary Table 1. All data are represented as mean ± SEM.

Source data

Extended Data Fig. 3 Post-op hypoglycemia in human patients is characterized by a shift in post-prandial plasma BAs.

Individual BAs whose levels were reduced in the plasma of post-op hypoglycemic individuals but for which the difference between groups was not statistically significant (post-op non-hypoglycemic n = 9, post-op hypoglycemic n = 10; two-tailed Welch’s t test for each time point). Data not marked are not statistically significant (p > 0.05). All other significant BAs shown in Fig. 2. Patient characteristics and demographics detailed in Supplementary Table 1. All data are represented as mean ± SEM.

Source data

Extended Data Fig. 4 BAs shifted in post-op hypoglycemia patients induce FGF19 secretion and gene expression in vitro with differential effects on SHP.

a. FGF19 secretion and expression induced by BA pools totaling physiological concentrations (post-op non-hypoglycemic 1 mM, post-op hypoglycemic 0.6 mM) in undifferentiated Caco-2 cells. Post-op hypoglycemic fecal BAs induced higher FGF19 secretion and expression compared to post-op non-hypoglycemic fecal BAs (DMSO, n = 3; BA pools n = 6; FGF19 expression, n = 6 in each group; One-way ANOVA with Dunnet’s multiple comparison test. b. Post-op hypoglycemic fecal BAs (1 mM) induced higher Fgf15 expression compared to post-op non-hypoglycemic fecal BAs (1 mM) in in ex vivo ileal segments from lean, chow-fed mice. (n = 8 in each group; one-way ANOVA with Dunnet’s multiple comparison test. c. Dose-response curves for human SHP activation measured by using a SHP-luciferase reporter expressed in Caco-2 cells. Values were normalized to DMSO. EC50 values for activating BAs (blue) are indicated within each panel. BAs showing inhibitory (red) or no activity (black) have no EC50 or IC50 values listed. d. Dose-response curves for human SHP inhibition measured with the addition of 10 µM CDCA, a SHP activator. BAs were tested in their ability to inhibit SHP reporter in Caco-2 cells. Values were normalized to the agonist CDCA. EC50 and IC50 values for BAs are indicated within each panel and also listed in Supplementary Table 2 (each dose-response curve data point contains \(\ge\)3 biological replicates). e. SHP luciferase reporter activation (left) and shp expression (right) induced by BA pools totaling 1 mM in Caco-2 cells. No statistically significant difference was observed in SHP activation or expression in cells treated with post-op hypoglycemic fecal BAs compared to post-op non-hypoglycemic fecal BAs (SHP activation, DMSO, n = 3; BA pools n = 6; shp expression, n = 6 in each group; One-way ANOVA with Dunnet’s multiple comparison test. All data has been reproduced at least twice, each time in biological triplicate). All statistically significant p values are indicated. Lines above graphs indicate the groups being compared with p values. ns=not significant. Data not marked are not statistically significant (p > 0.05). All data are represented as mean ± SEM.

Source data

Extended Data Fig. 5 Portal BA profiling in chow-fed male mice treated with elobixibat and subjected to an MMTT.

UPLC-MS analysis of portal BAs from mice treated with PBS or elobixibat (ASBTi), followed by an MMTT and sacrificed at 120 min post-meal (n = 8 in each group, two-tailed Welch’s t test). All statistically significant p values are indicated in each graph. Lines above graphs indicate the groups being compared with p values. ns = not significant. All data are represented as mean ± SEM.

Source data

Extended Data Fig. 6 Serum BA profiling in chow-fed male mice treated with elobixibat and subjected to an MMTT.

UPLC-MS analysis of serum BAs from mice treated with PBS or elobixibat (ASBTi), followed by an MMTT and sacrificed at 120 min post-meal (n = 8 in each group, two-tailed Welch’s t test). All statistically significant p values are indicated in each graph. Lines above graphs indicate the groups being compared with p values. ns = not significant. All data are represented as mean ± SEM.

Source data

Extended Data Fig. 7 Elobixibat treatment prior to MMTT increased glucose, but did not significantly alter insulin or GLP-1 levels.

a. Elobixibat treatment significantly increased post-prandial blood glucose at 30 min after MM gavage compared with PBS (n = 4 in each group, two-way ANOVA). b. Insulin levels during MMTT did not differ between groups (n = 4 in each group, two-way ANOVA. AUC adjacent). c. GLP1 levels during MMTT did not differ between groups (n = 4 in each group, two-way ANOVA. AUC adjacent). Data not marked are not statistically significant (p > 0.05). All data are represented as mean ± SEM.

Source data

Supplementary information

Source data

Source Data Fig. 1 (download XLSX )

FGF19 and BA levels.

Source Data Fig. 2 (download XLSX )

Glucose, GLP-1, insulin and C4 levels.

Source Data Fig. 3 (download XLSX )

BA and FGF19 levels.

Source Data Fig. 4 (download XLSX )

BA and FGF19 levels.

Source Data Fig. 5 (download XLSX )

BA and FGF19 levels.

Source Data Fig. 6 (download XLSX )

Glucose, BA and gene expression measurements.

Source Data Fig. 7 (download XLSX )

Caecal BA.

Source Data Fig. 8 (download XLSX )

Glucose levels.

Source Data Extended Data Fig. 2 (download XLSX )

Human faecal BA levels.

Source Data Extended Data Fig. 3 (download XLSX )

Human plasma BA levels.

Source Data Extended Data Fig. 4 (download XLSX )

FGF19 expression/secretion and Shp expression/activity.

Source Data Extended Data Fig. 5 (download XLSX )

Mouse portal vein BA levels.

Source Data Extended Data Fig. 6 (download XLSX )

Mouse serum BA levels.

Source Data Extended Data Fig. 7 (download XLSX )

Mouse serum glucose, insulin and GLP-1 levels.

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Chaudhari, S.N., Chen, Y., Ferraz-Bannitz, R. et al. Alterations in intestinal bile acid transport provide a therapeutic target in patients with post-bariatric hypoglycaemia. Nat Metab 7, 792–807 (2025). https://doi.org/10.1038/s42255-025-01262-5

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  • DOI: https://doi.org/10.1038/s42255-025-01262-5

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