Intestinal microbiota composition of children with glycogen storage Type I patients.


Journal

European journal of clinical nutrition
ISSN: 1476-5640
Titre abrégé: Eur J Clin Nutr
Pays: England
ID NLM: 8804070

Informations de publication

Date de publication:
24 Feb 2024
Historique:
received: 17 05 2023
accepted: 07 02 2024
revised: 26 01 2024
medline: 25 2 2024
pubmed: 25 2 2024
entrez: 24 2 2024
Statut: aheadofprint

Résumé

Dietary therapy of glycogen storage disease I (GSD I) is based on frequent feeding, with a high intake of complex carbohydrates (supplied by uncooked cornstarch), restriction of sugars, and a lower amount of lipids. There is limited information about the dietary regimen in patients with GSD, which might affect the intestinal luminal pH and microbiota composition. The aim of this study to investigate the intestinal microbiota composition in patients with GSD receiving diet treatment. Twelve patients who were followed up with GSD I after the diagnosis receiving diet therapy and 11 healthy children have been enrolled. Intestinal microbiota composition was evaluated by 16 s rRNA gene sequencing. A significant difference was found for beta-diversity between the GSD group and controls. A significantly lower abundance of Firmicutes and higher abundance of Actinobacteria was found in GSD group compared to the controls. Akkermansia, Pseudoalteromonas, Uruburella, and Castellaniella were dominant in the GSD patients at the genus level, while Faecalibacterium, Bacterioides, Gemmiger, Parabacteroides in the control group. At species level, Faecalibacterium prausnitzii decreased, and Akkermansia muciniphila were dominant in children with GSD. There is a substantial change in the composition of the gut microbiota, reduction of F. prausnitzii and an increase of A. muciniphila in children with GSD receiving consumption of uncooked cornstarch. Alterations of the intestinal microbiota might be related with the disease itself or dietary restrictions in patients with GSD, however, in certain condition, dysbiosis can negatively affect the course and make it difficult to control the disease.

Identifiants

pubmed: 38402355
doi: 10.1038/s41430-024-01412-0
pii: 10.1038/s41430-024-01412-0
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Gazi Üniversitesi (Gazi University)
ID : TGA-2021-7036

Informations de copyright

© 2024. The Author(s).

Références

Rake JP, Visser G, Labrune P, Leonard JV, Ullrich K, Smit GP. Glycogen storage disease type I: diagnosis, management, clinical course and outcome. Results of the European study on glycogen storage disease Type I (ESGSD I). Eur J Pediatr. 2002;161:S20–34. https://doi.org/10.1007/s00431-002-0999-4 .
doi: 10.1007/s00431-002-0999-4 pubmed: 12373567
Bhattacharya K. Dietary dilemmas in the management of glycogen storage disease Type I. J Inherit Metab Dis. 2011;34:621–9. https://doi.org/10.1007/s10545-011-9322-8 .
doi: 10.1007/s10545-011-9322-8 pubmed: 21491105
Kishnani PS, Austin SL, Abdenur JE, Arn P, Bali DS, Boney A, et al. Diagnosis and management of glycogen storage disease Type I: a practice guideline of the American college of medical genetics and genomics. Genet Med. 2014;16:e1. https://doi.org/10.1038/gim.2014.128 .
doi: 10.1038/gim.2014.128 pubmed: 25356975
Wolfsdorf JI, Crigler JF Jr. Effect of continuous glucose therapy begun in infancy on the long-term clinical course of patients with Type I glycogen storage disease. J Pediatr Gastroenterol Nutr. 1999;29:136–43. https://doi.org/10.1097/00005176-199908000-00008 .
doi: 10.1097/00005176-199908000-00008 pubmed: 10435649
Weinstein DA, Somers MJ, Wolfsdorf JI. Decreased urinary citrate excretion in Type 1a glycogen storage disease. J Pediatr. 2001;138:378–82. https://doi.org/10.1067/mpd.2001.111322 .
doi: 10.1067/mpd.2001.111322 pubmed: 11241046
Shah KK, O’Dell SD. Effect of dietary interventions in the maintenance of normoglycaemia in glycogen storage disease Type 1a: a systematic review and meta-analysis. J Hum Nutr Diet. 2013;26:329–39. https://doi.org/10.1111/jhn.12030 .
doi: 10.1111/jhn.12030 pubmed: 23294025
Bhattacharya K, Orton RC, Qi X, Mundy H, Morley DW, Champion MP. et al. A novel starch for the treatment of glycogen storage diseases. J Inherit Metab Dis. 2007;30:350–7. https://doi.org/10.1007/s10545-007-0479-0 .
doi: 10.1007/s10545-007-0479-0 pubmed: 17514432
Correia CE, Bhattacharya K, Lee PJ, Shuster JJ, Theriaque DW, Shankar MN. et al. Use of modified cornstarch therapy to extend fasting in glycogen storage disease Types Ia and Ib. Am J Clin Nutr. 2008;88:1272–6. https://doi.org/10.3945/ajcn.2008.26352 .
doi: 10.3945/ajcn.2008.26352 pubmed: 18996862
Dahlberg KR, Ferrecchia IA, Dambska-Williams M, Resler TE, Ross KM, Butler GL, et al. Cornstarch requirements of the adult glycogen storage disease Ia population: a retrospective review. J Inherit Metab Dis. 2020;43:269–78. https://doi.org/10.1002/jimd.12160 .
doi: 10.1002/jimd.12160 pubmed: 31415093
Ceccarani C, Bassanini G, Montanari C, Casiraghi MC, Ottaviano E, Morace G, et al. Proteobacteria overgrowth and butyrate-producing taxa depletion in the gut microbiota of glycogen storage disease Type 1 patients. Metabolites. 2020;10:133. https://doi.org/10.3390/metabo10040133 .
doi: 10.3390/metabo10040133 pubmed: 32235604 pmcid: 7240959
Colonetti K, de Carvalho EL, Rangel DL, Pinto PM, Roesch LFW, Pinheiro FC. et al. Are the bacteria and their metabolites contributing for gut inflammation on GSD-Ia patients?. Metabolites. 2022;12:873. https://doi.org/10.3390/metabo12090873 .
doi: 10.3390/metabo12090873 pubmed: 36144277 pmcid: 9504798
Agakisiyeva G, Yildirim D, Hizarcioglu-Gulsen H, Gumus E, Karhan AN, Karabulut E. et al. Nutritional characteristics of patients with functional constipation aged 4 years and older. Minerva Pediatr (Torino). 2022;74:468–76. https://doi.org/10.23736/S2724-5276.20.05978-2 .
doi: 10.23736/S2724-5276.20.05978-2 pubmed: 32960005
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7. https://doi.org/10.1038/s41587-019-0209-9 .
doi: 10.1038/s41587-019-0209-9 pubmed: 31341288 pmcid: 7015180
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3. https://doi.org/10.1038/nmeth.3869 .
doi: 10.1038/nmeth.3869 pubmed: 27214047 pmcid: 4927377
Schloss PD. Amplicon sequence variants artificially split bacterial genomes into separate clusters. mSphere. 2021;6:e0019121. https://doi.org/10.1128/mSphere.00191-21 .
doi: 10.1128/mSphere.00191-21 pubmed: 34287003
Werner JJ, Koren O, Hugenholtz P, DeSantis TZ, Walters WA, Caporaso JG. et al. Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys. ISME J. 2012;6:94–103. https://doi.org/10.1038/ismej.2011.82 .
doi: 10.1038/ismej.2011.82 pubmed: 21716311
McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One. 2013;8:e61217. https://doi.org/10.1371/journal.pone.0061217 .
doi: 10.1371/journal.pone.0061217 pubmed: 23630581 pmcid: 3632530
R Core Team. R: A language and environment for statistical computing. 2017. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ .
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. https://doi.org/10.1186/s13059-014-0550-8 .
doi: 10.1186/s13059-014-0550-8 pubmed: 25516281 pmcid: 4302049
Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12:R60. https://doi.org/10.1186/gb-2011-12-6-r60 .
doi: 10.1186/gb-2011-12-6-r60 pubmed: 21702898 pmcid: 3218848
Parada Venegas D, De la Fuente MK, Landskron G, González MJ, Quera R, Dijkstra G, et al. Corrigendum: short chain fatty acids (SCFAs)-mediated gut epithelial and immune regulation and its relevance for inflammatory bowel diseases. Front Immunol. 2019;10:1486. https://doi.org/10.3389/fimmu.2019.01486 .
doi: 10.3389/fimmu.2019.01486 pubmed: 31316522 pmcid: 6611342
Louis P, Flint HJ. Formation of propionate and butyrate by the human colonic microbiota. Environ Microbiol. 2017;19:29–41. https://doi.org/10.1111/1462-2920.13589 .
doi: 10.1111/1462-2920.13589 pubmed: 27928878
Clemente JC, Ursell LK, Parfrey LW, Knight R. The impact of the gut microbiota on human health: an integrative view. Cell. 2012;148:1258–70. https://doi.org/10.1016/j.cell.2012.01.035 .
doi: 10.1016/j.cell.2012.01.035 pubmed: 22424233 pmcid: 5050011
Suskun C, Kilic O, Yilmaz Ciftdogan D, Guven S, Karbuz A, Ozkaya Parlakay A, et al. Intestinal microbiota composition of children with infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and multisystem inflammatory syndrome (MIS-C). Eur J Pediatr. 2022;181:3175–91. https://doi.org/10.1007/s00431-022-04494-9 .
doi: 10.1007/s00431-022-04494-9 pubmed: 35585256 pmcid: 9117086
Shin NR, Whon TW, Bae JW. Proteobacteria: microbial signature of dysbiosis in gut microbiota. Trends Biotechnol. 2015;33:496–503. https://doi.org/10.1016/j.tibtech.2015.06.011 .
doi: 10.1016/j.tibtech.2015.06.011 pubmed: 26210164
Cani PD, de Vos WM. Next-generation beneficial microbes: the case of Akkermansia muciniphila. Front Microbiol. 2017;8:1765. https://doi.org/10.3389/fmicb.2017.01765 .
doi: 10.3389/fmicb.2017.01765 pubmed: 29018410 pmcid: 5614963
Derrien M, Belzer C, de Vos WM. Akkermansia muciniphila and its role in regulating host functions. Micro Pathog. 2017;106:171–81. https://doi.org/10.1016/j.micpath.2016.02.005 .
doi: 10.1016/j.micpath.2016.02.005
Ottman N, Geerlings SY, Aalvink S, de Vos WM, Belzer C. Action and function of Akkermansia muciniphila in microbiome ecology, health and disease. Best Pr Res Clin Gastroenterol. 2017;31:637–42. https://doi.org/10.1016/j.bpg.2017.10.001 .
doi: 10.1016/j.bpg.2017.10.001
Crouch LI, Liberato MV, Urbanowicz PA, Baslé A, Lamb CA, Stewart CJ, et al. Prominent members of the human gut microbiota express endo-acting O-glycanases to initiate mucin breakdown. Nat Commun. 2020;11:4017. https://doi.org/10.1038/s41467-020-17847-5 .
doi: 10.1038/s41467-020-17847-5 pubmed: 32782292 pmcid: 7419316
Verhoog S, Taneri PE, Roa Díaz ZM, Marques-Vidal P, Troup JP, Bally L, et al. Dietary factors and modulation of bacteria strains of akkermansia muciniphila and faecalibacterium prausnitzii: a systematic review. Nutrients. 2019;11:1565. https://doi.org/10.3390/nu11071565 .
doi: 10.3390/nu11071565 pubmed: 31336737 pmcid: 6683038
Yan J, Sheng L, Li H. Akkermansia muciniphila: is it the Holy Grail for ameliorating metabolic diseases? Gut Microbes. 2021;13:1984104. https://doi.org/10.1080/19490976.2021.1984104 .
doi: 10.1080/19490976.2021.1984104 pubmed: 34674606 pmcid: 8726741
Dao MC, Everard A, Aron-Wisnewsky J, Sokolovska N, Prifti E, Verger EO, et al. Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut. 2016;65:426–36. https://doi.org/10.1136/gutjnl-2014-308778 .
doi: 10.1136/gutjnl-2014-308778 pubmed: 26100928
Medina-Vera I, Sanchez-Tapia M, Noriega-López L, Granados-Portillo O, Guevara-Cruz M, Flores-López A, et al. A dietary intervention with functional foods reduces metabolic endotoxaemia and attenuates biochemical abnormalities by modifying faecal microbiota in people with Type 2 diabetes. Diabetes Metab. 2019;45:122–31. https://doi.org/10.1016/j.diabet.2018.09.004 .
doi: 10.1016/j.diabet.2018.09.004 pubmed: 30266575

Auteurs

Sabire Gokalp (S)

Gazi University Faculty of Medicine, Department of Pediatric Nutrition and Metabolism, Ankara, Turkey. sabire32@hotmail.com.

Ener Cagri Dinleyici (EC)

Eskisehir Osmangazi University Faculty of Medicine, Department of Pediatrics, Eskisehir, Turkey.

Cansu Muluk (C)

Gazi University Faculty of Medicine, Department of Pediatrics, Ankara, Turkey.

Asli Inci (A)

Gazi University Faculty of Medicine, Department of Pediatric Nutrition and Metabolism, Ankara, Turkey.

Emine Aktas (E)

Gazi University Faculty of Medicine, Department of Pediatric Nutrition and Metabolism, Ankara, Turkey.

Ilyas Okur (I)

Gazi University Faculty of Medicine, Department of Pediatric Nutrition and Metabolism, Ankara, Turkey.

Fatih Ezgu (F)

Gazi University Faculty of Medicine, Department of Pediatric Nutrition and Metabolism, Ankara, Turkey.

Leyla Tumer (L)

Gazi University Faculty of Medicine, Department of Pediatric Nutrition and Metabolism, Ankara, Turkey.

Classifications MeSH