Graves' disease (GD) is the commonest cause of hyperthyroidism, characterised by anti-thyrotropin receptor autoantibodies (TRAb) persistently stimulating the thyroid gland. Around 30-50% GD patients also develop Graves' orbitopathy (GO), an orbital inflammation causing disfigurement and visual problems; moderate-to-severe forms represent 5% of GO cases and are associated with high risk of sight loss. Some risk factors for GO have been identified (i.e. smoking, stress, high TRAb titres, severe hyperthyroidism) and predictive models for disease development and response to treatment have been attempted, but are still missing/incomplete. The GD/GO pathogenesis is multifactorial and not fully understood, including a complex interplay between genetic predisposition and environmental factors. A loss of immune tolerance has been observed; in particular an imbalance between T Helper 17 (Th17) and T Regulatory (Treg). The gut microbiota modulates the differentiation of immature T cells in the gut-associated-lymphoid-tissue and microbiota alterations seem involved in autoimmune diseases, including GD/GO. Indeed, a dysbiosis of the gut microbiota may alter the Treg/T17 balance and thus impact on immune homeostasis.
The international EU-FP7 funded study "Investigation of Novel biomarkers and Definition of the role of the microbiome In Graves' Orbitopathy" (INDIGO) represented one of the first investigations about the role of gut microbiota in GD and GO diseases (https://cordis.europa.eu/project/id/612116), spanning across eight centres of four European countries: United Kingdom (Cardiff, Merthyr Tydfil, Newcastle upon Tyne and Moorfields), Italy (Milan and Pisa), Belgium (Brussels) and Germany (Essen). The INDIGO consortium provided the human gut microbiome analysis by 16S rRNA sequencing, performed on faecal samples of 105 patients (59 GD, 46 GO) and 41 controls enrolled between October 2014 and June 2016. It was discovered an increase of Actinobacteria phylum in both GD and GO compared with controls, and a selective enrichment of Roseburia spp. in moderate-severe GO compared with both GD and controls.
The first objective of this MISS.GO study is to validate with advanced metagenomics techniques (Shotgun sequencing) the INDIGO study's gut microbiome findings, whose samples were stored in a biobank of UO1 (UNIMI). The Shotgun sequencing allows a deeper taxonomic investigation down to species level, while 16s rRNA sequencing is limited to genus level. Furthermore it increases the chances to detect low abundant species, not possible with 16S rRNA sequencing, and extends the microbiome analysis to yeasts, fungi and a variety of other microorganisms in addition to Bacteria and Archea, to which 16s rRNA sequencing is restricted. Furthermore, this study integrates the metabolomics analysis performed on stored plasma of INDIGO's patients.
The MISS.GO study also includes a prospective phase were 59 subjects (33 GO, 9 GD and 17 controls) were recruited in the Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico of Milan, Italy, to deliver an in depth analysis of the relationship between microbiota and immune system, since:
1. Advanced Shotgun sequencing is also applied to nasal swabs, in addition to faecal samples. The role of nasal microbiota, and its relationship with gut microbiota, will be explored for the first time in GD and GO patients;
2. Metagenomics data are integrated with metabolomics and proteomics analysis performed on plasma, faecal and nasal samples;
3. Such advanced microbiota's analyses are also integrated with paired immunophenotyping of lymphocytes resident within the organs targeted by autoimmunity in GD and GO patients (thyroid and lymph node) accessed by fine-needle aspiration (FNA), to study the bidirectional modulation between microbiota and immune system.
The final goal of MISS.GO study, thanks to such integrated analysis of fecal and nasal metagenomics, metabolomics and metaproteomics, together with paired tissue-resident immunophenotyping, is to improve the current knowledge of GD and GO pathogenesis, aiming to identify prognostic GD and GO markers, predictive factors for GO development, and key microbiota and immune signatures that can be exploited for prevention, mitigation and therapeutic strategies.