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Comparative assessment of gut microbial composition and function in patients with Graves’ disease and Graves’ orbitopathy

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Abstract

Background

A previous study indicated that gut microbiota changed notably in Graves’ orbitopathy (GO) patients as compared to controls. However, the characteristics of intestinal bacteria in Graves’ disease (GD) and GO are unclear.

Objective

The present study aimed to identify specific intestinal bacteria of GD and GO, respectively.

Methods

The gut microbial communities of the fecal samples of 30 GD patients without GO, 33 GO subjects, and 32 healthy subjects were analyzed and compared by 16S rRNA gene sequencing.

Results

At the phylum level, the proportion of Deinococcus-Thermus and Chloroflexi was decreased significantly in GO patients as compared to GD. At the genus level, the proportion of Subdoligranulum and Bilophila was increased while that of Blautia, Anaerostipes, Dorea, Butyricicoccus, Romboutsia, Fusicatenibacter, unidentified_ Lachnospiraceae, unidentified_Clostridiales, Collineslla, Intestinibacter, and Phascolarctobacterium was decreased in the GO group as compared to the GD group. Random forest analysis was used for the identification of specific intestinal microbiota, and Deinococcus-Thermus, Cyanobacteria and Chloroflexi were ranked in the top ten according to their contributions to sample classification. Moreover, compared to the control, there were multiple gut bacterial enrichment metabolic pathways in GO and GD patients, including nucleotide metabolism, enzyme family, and energy metabolism. Compared to GO, the only enrichment metabolic pathway found in GD was the viral protein family.

Conclusions

This study highlighted the significant differences in the intestinal microbiota and predictive functions of GD with GO, thereby providing new insights into the role of the gut bacteria that might contribute to the development of GO in GD patients.

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Abbreviations

GO:

Graves’ orbitopathy

GD:

Graves’ disease

HT:

Hashimoto Thyroiditis

TRAb:

Thyrotropin receptor antibody

IBD:

Inflammatory bowel disease

SLE:

Systemic lupus erythematosus

RA:

Rheumatoid arthritis

AITD:

Autoimmune thyroid diseases

TPOAb:

Thyroperoxidase antibody

TGAb:

Antithyroglobulin antibody

OTU:

Operational taxonomy units

KEGG:

Kyoto Encyclopedia of Genes and Genomes

PCoA:

Principal coordinate analysis

LDA:

Linear discriminant analysis

LEfSe:

LDA effect size

MDG:

Mean Decrease Gini

References

  1. Ehlers M, Schott M, Allelein S (2019) Graves' disease in clinical perspective. Front Biosci (Landmark Ed) 24:35–47

    Article  Google Scholar 

  2. Smith TJ (2017) TSHR as a therapeutic target in Graves' disease. Expert Opin Ther Targets 21(4):427–432. https://doi.org/10.1080/14728222.2017.1288215

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Bahn RS (2010) Graves' ophthalmopathy. N Engl J Med 362(8):726–738. https://doi.org/10.1056/NEJMra0905750

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Drui D, Du Pasquier FL, Vignal Clermont C, Daumerie C (2018) Graves' orbitopathy: Diagnosis and treatment. Ann Endocrinol (Paris). https://doi.org/10.1016/j.ando.2018.08.005

    Article  Google Scholar 

  5. Wiersinga WM (2017) Advances in treatment of active, moderate-to-severe Graves' ophthalmopathy. Lancet Diabetes Endocrinol 5(2):134–142. https://doi.org/10.1016/S2213-8587(16)30046-8

    Article  CAS  PubMed  Google Scholar 

  6. Kataoka K (2016) The intestinal microbiota and its role in human health and disease. J Med Invest 63(1–2):27–37. https://doi.org/10.2152/jmi.63.27

    Article  PubMed  Google Scholar 

  7. Partida-Rodriguez O, Serrano-Vazquez A, Nieves-Ramirez ME, Moran P, Rojas L, Portillo T, Gonzalez E, Hernandez E, Finlay BB, Ximenez C (2017) Human intestinal microbiota: interaction between parasites and the host immune response. Arch Med Res 48(8):690–700. https://doi.org/10.1016/j.arcmed.2017.11.015

    Article  PubMed  Google Scholar 

  8. Virili C, Centanni M (2015) Does microbiota composition affect thyroid homeostasis? Endocrine 49(3):583–587. https://doi.org/10.1007/s12020-014-0509-2

    Article  CAS  PubMed  Google Scholar 

  9. Virili C, Fallahi P, Antonelli A, Benvenga S, Centanni M (2018) Gut microbiota and Hashimoto's thyroiditis. Rev Endocr Metab Disord 19(4):293–300. https://doi.org/10.1007/s11154-018-9467-y

    Article  PubMed  Google Scholar 

  10. Ishaq HM, Mohammad IS, Shahzad M, Ma C, Raza MA, Wu X, Guo H, Shi P, Xu J (2018) Molecular alteration analysis of human gut microbial composition in Graves' disease patients. Int J Biol Sci 14(11):1558–1570. https://doi.org/10.7150/ijbs.24151

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Zhao F, Feng J, Li J, Zhao L, Liu Y, Chen H, Jin Y, Zhu B, Wei Y (2018) Alterations of the gut microbiota in Hashimoto's thyroiditis patients. Thyroid 28(2):175–186. https://doi.org/10.1089/thy.2017.0395

    Article  CAS  PubMed  Google Scholar 

  12. Shi TT, Xin Z, Hua L, Zhao RX, Yang YL, Wang H, Zhang S, Liu W, Xie RR (2019) Alterations in the intestinal microbiota of patients with severe and active Graves' orbitopathy: a cross-sectional study. J Endocrinol Invest 42(8):967–978. https://doi.org/10.1007/s40618-019-1010-9

    Article  CAS  PubMed  Google Scholar 

  13. Bartalena L, Baldeschi L, Boboridis K, Eckstein A, Kahaly GJ, Marcocci C, Perros P, Salvi M, Wiersinga WM; European Group on Graves O (2016) The 2016 European Thyroid Association/European Group on Graves' Orbitopathy Guidelines for the management of Graves' orbitopathy. Eur Thyroid J 5(1):9–26. https://doi.org/10.1159/000443828

  14. Ji DY, Park SH, Park SJ, Kim KH, Ku CR, Shin DY, Yoon JS, Lee DY, Lee EJ (2018) Comparative assessment of Graves' disease and main extrathyroidal manifestation, Graves' ophthalmopathy, by non-targeted metabolite profiling of blood and orbital tissue. Sci Rep 8(1):9262. https://doi.org/10.1038/s41598-018-27600-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Allali I, Arnold JW, Roach J, Cadenas MB, Butz N, Hassan HM, Koci M, Ballou A, Mendoza M, Ali R, Azcarate-Peril MA (2017) A comparison of sequencing platforms and bioinformatics pipelines for compositional analysis of the gut microbiome. BMC Microbiol 17(1):194. https://doi.org/10.1186/s12866-017-1101-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Han Z, Li K, Shahzad M, Zhang H, Luo H, Qiu G, Lan Y, Wang X, Mehmood K, Li J (2017) Analysis of the intestinal microbial community in healthy and diarrheal perinatal yaks by high-throughput sequencing. Microb Pathog 111:60–70. https://doi.org/10.1016/j.micpath.2017.08.025

    Article  CAS  PubMed  Google Scholar 

  17. Piotrowska A, Gosiewski T, Bulanda M, Brzychczy-Wloch M (2016) Using of the 16S rDNA sequencing for identification of Lactobacillus species. Med Dosw Mikrobiol 68(1):5–11

    PubMed  Google Scholar 

  18. Zhou L, Ni Z, Cheng W, Yu J, Sun S, Zhai D, Yu C, Cai Z (2020) Characteristic gut microbiota and predicted metabolic functions in women with PCOS. Endocr Connect 9(1):63–73. https://doi.org/10.1530/EC-19-0522

    Article  CAS  PubMed  Google Scholar 

  19. Loke MF, Chua EG, Gan HM, Thulasi K, Wanyiri JW, Thevambiga I, Goh KL, Wong WF, Vadivelu J (2018) Metabolomics and 16S rRNA sequencing of human colorectal cancers and adjacent mucosa. PLoS ONE 13(12):e0208584. https://doi.org/10.1371/journal.pone.0208584

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ritari J, Salojarvi J, Lahti L, de Vos WM (2015) Improved taxonomic assignment of human intestinal 16S rRNA sequences by a dedicated reference database. BMC Genomics 16:1056. https://doi.org/10.1186/s12864-015-2265-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Zhou L, Li X, Ahmed A, Wu D, Liu L, Qiu J, Yan Y, Jin M, Xin Y (2014) Gut microbe analysis between hyperthyroid and healthy individuals. Curr Microbiol 69(5):675–680. https://doi.org/10.1007/s00284-014-0640-6

    Article  CAS  PubMed  Google Scholar 

  22. Griffiths E, Gupta RS (2007) Identification of signature proteins that are distinctive of the Deinococcus-Thermus phylum. Int Microbiol 10(3):201–208

    CAS  PubMed  Google Scholar 

  23. Kim CY, Lee HJ, Chae MK, Byun JW, Lee EJ, Yoon JS (2015) Therapeutic effect of resveratrol on oxidative stress in Graves' orbitopathy orbital fibroblasts. Invest Ophthalmol Vis Sci 56(11):6352–6361. https://doi.org/10.1167/iovs.15-16870

    Article  CAS  PubMed  Google Scholar 

  24. Abusleme L, Dupuy AK, Dutzan N, Silva N, Burleson JA, Strausbaugh LD, Gamonal J, Diaz PI (2013) The subgingival microbiome in health and periodontitis and its relationship with community biomass and inflammation. ISME J 7(5):1016–1025. https://doi.org/10.1038/ismej.2012.174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lu W, Feng Y, Jing F, Han Y, Lyu N, Liu F, Li J, Song X, Xie J, Qiu Z, Zhu T, Routy B, Routy JP, Li T, Zhu B (2018) Association between gut microbiota and CD4 recovery in HIV-1 infected patients. Front Microbiol 9:1451. https://doi.org/10.3389/fmicb.2018.01451

    Article  PubMed  PubMed Central  Google Scholar 

  26. Rivera-Pinto J, Egozcue JJ, Pawlowsky-Glahn V, Paredes R, Noguera-Julian M, Calle ML (2018) Balances: a new perspective for microbiome analysis. mSystems 3(4). https://doi.org/10.1128/mSystems.00053-18

  27. Canani RB, Costanzo MD, Leone L, Pedata M, Meli R, Calignano A (2011) Potential beneficial effects of butyrate in intestinal and extraintestinal diseases. World J Gastroenterol 17(12):1519–1528. https://doi.org/10.3748/wjg.v17.i12.1519

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Di Segni A, Braun T, BenShoshan M, Farage Barhom S, Glick Saar E, Cesarkas K, Squires JE, Keller N, Haberman Y (2018) Guided protocol for fecal microbial characterization by 16S rRNA-amplicon sequencing. J Vis Exp (133). https://doi.org/10.3791/56845

  29. Asshauer KP, Wemheuer B, Daniel R, Meinicke P (2015) Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics 31(17):2882–2884. https://doi.org/10.1093/bioinformatics/btv287

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ashton JJ, Colquhoun CM, Cleary DW, Coelho T, Haggarty R, Mulder I, Batra A, Afzal NA, Beattie RM, Scott KP, Ennis S (2017) 16S sequencing and functional analysis of the fecal microbiome during treatment of newly diagnosed pediatric inflammatory bowel disease. Medicine (Baltimore) 96(26):e7347. https://doi.org/10.1097/MD.0000000000007347

    Article  CAS  Google Scholar 

  31. Struja T, Kutz A, Fischli S, Meier C, Mueller B, Recher M, Schuetz P (2017) Is Graves' disease a primary immunodeficiency? New immunological perspectives on an endocrine disease. BMC Med 15(1):174. https://doi.org/10.1186/s12916-017-0939-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Yamashita S, Izumi M, Morita S, Hirayu H, Tanabe T, Taura M, Sato K, Morimoto I, Okamoto S, Nagataki S (1982) Plasma cAMP and cGMP concentrations in outpatients with Graves' disease and chronic thyroiditis. Nihon Naibunpi Gakkai Zasshi 58(12):1498–1504. https://doi.org/10.1507/endocrine1927.58.12_1498

    Article  CAS  PubMed  Google Scholar 

  33. Yagura T, Nagata I, Kuma K, Uchino H (1985) Increased cyclic nucleotide phosphodiesterase (PDE) and calmodulin activities in soluble fraction of Graves' thyroid: analysis of increase in Ca+2 dependence of PDE activities. J Clin Endocrinol Metab 60(6):1180–1186. https://doi.org/10.1210/jcem-60-6-1180

    Article  CAS  PubMed  Google Scholar 

  34. Wang X, Xu K, Chen S, Li Y, Li M (2018) Role of interleukin-37 in inflammatory and autoimmune diseases. Iran J Immunol 15(3):165–174. https://doi.org/10.22034/IJI.2018.39386

    Article  PubMed  Google Scholar 

  35. Cheng CW, Yang SF, Wang YH, Fang WF, Lin YC, Tang KT, Lin JD (2019) Associations of secreted phosphoprotein 1 and B lymphocyte kinase gene polymorphisms with autoimmune thyroid disease. Eur J Clin Invest 49(3):e13065. https://doi.org/10.1111/eci.13065

    Article  CAS  PubMed  Google Scholar 

  36. Jaspan JB, Luo H, Ahmed B, Tenenbaum S, Voss T, Sander DM, Bollinger K, Baquet T, Garry RF (1995) Evidence for a retroviral trigger in Graves' disease. Autoimmunity 20(2):135–142. https://doi.org/10.3109/08916939509001938

    Article  CAS  PubMed  Google Scholar 

  37. Leite JL, Bufalo NE, Santos RB, Romaldini JH, Ward LS (2010) Herpesvirus type 7 infection may play an important role in individuals with a genetic profile of susceptibility to Graves' disease. Eur J Endocrinol 162(2):315–321. https://doi.org/10.1530/EJE-09-0719

    Article  CAS  PubMed  Google Scholar 

  38. Tozzoli R, Barzilai O, Ram M, Villalta D, Bizzaro N, Sherer Y, Shoenfeld Y (2008) Infections and autoimmune thyroid diseases: parallel detection of antibodies against pathogens with proteomic technology. Autoimmun Rev 8(2):112–115. https://doi.org/10.1016/j.autrev.2008.07.013

    Article  CAS  PubMed  Google Scholar 

  39. Kuang M, Wang S, Wu M, Ning G, Yao Z, Li L (2010) Expression of IFNalpha-inducible genes and modulation of HLA-DR and thyroid stimulating hormone receptors in Graves' disease. Mol Cell Endocrinol 319(1–2):23–29. https://doi.org/10.1016/j.mce.2009.12.006

    Article  CAS  PubMed  Google Scholar 

  40. Merrill SJ, Mu Y (2015) Thyroid autoimmunity as a window to autoimmunity: an explanation for sex differences in the prevalence of thyroid autoimmunity. J Theor Biol 375:95–100. https://doi.org/10.1016/j.jtbi.2014.12.015

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors thank all the participants and staff involved in the study.

Funding

This work was supported by the Beijing Municipal Hospital Research and Development Program (PX2016063), the Expert Promotion Program of Beijing Health Systems (2015-3-017) to Zhong Xin, and the Foundation of Beijing Tongren Hospital (2015-YJJ-ZZL-006) to Ting-Ting Shi.

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Authors and Affiliations

  1. Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, 1 Dong Jiao Min Xiang, Beijing, 100730, China

    T.-T. Shi, Z. Xin, R.-X. Zhao, Y.-L. Yang, R.-R. Xie, H.-Y. Liu & J.-K. Yang

  2. Department of Mathematics, School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China

    L. Hua

  3. Department of Emergency, Beijing Tongren Hospital, Capital Medical University, Beijing, China

    H. Wang

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  1. T.-T. Shi
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Correspondence to Z. Xin or L. Hua.

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The study was approved by the Ethics Committee of Beijing Tongren Hospital, Capital Medical University. All procedures were performed in the study in accordance with the 1964 Helsinki declaration and its later amendments.

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Informed written consents were obtained from all participants included in this study.

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Shi, TT., Xin, Z., Hua, L. et al. Comparative assessment of gut microbial composition and function in patients with Graves’ disease and Graves’ orbitopathy. J Endocrinol Invest 44, 297–310 (2021). https://doi.org/10.1007/s40618-020-01298-2

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