Autoimmune thyroid diseases (AITD) such as Graves’ disease (GD) or Hashimoto’s thyroiditis (HT) are organ-specific diseases that involve complex interactions between distinct components of thyroid tissue. Here, we use spatial transcriptomics to explore the molecular architecture, heterogeneity and location of different cells present in the thyroid tissue, including thyroid follicular cells (TFCs), stromal cells such as fibroblasts, endothelial cells, and thyroid infiltrating lymphocytes. We identify damaged antigen-presenting TFCs with upregulated CD74 and MIF expression in thyroid samples from AITD patients. Furthermore, we discern two main fibroblast subpopulations in the connective tissue including ADIRF⁺ myofibroblasts, mainly enriched in GD, and inflammatory fibroblasts, enriched in HT patients. We also demonstrate an increase of fenestrated PLVAP⁺ vessels in AITD, especially in GD. Our data unveil stromal and thyroid epithelial cell subpopulations that could play a role in the pathogenesis of AITD.

Although predictors of response to first-generation somatostatin receptor ligands (fg-SRLs), and to a lesser extent to pasireotide, have been studied in acromegaly for many years, their use is still not recommended in clinical guidelines. Is there insufficient evidence to use them? Numerous biomarkers including various clinical, functional, radiological and molecular markers have been identified. The first ones are applicable pre-surgery, while the molecular predictors are utilized for patients not cured after surgery. In this regard, factors predicting a good response to fg-SRLs are specifically: low basal GH, a low GH nadir in the acute octreotide test, T2 MRI hypointensity, a densely granulated pattern, high immunohistochemistry staining for somatostatin receptor 2 (SSTR2), and E-cadherin. However, there is still a lack of consensus regarding which of these biomarkers is more useful or how to integrate them into clinical practice. With classical statistical methods, it is complex to define reliable and generalizable cut-off values for a single biomarker. The potential solution to the limitations of traditional methods involves combining systems biology with artificial intelligence, which is currently providing answers to such long-standing questions that may eventually be finally included into the clinical guidelines and make personalized medicine a reality. The aim of this review is to describe the current knowledge of the main fg-SRLs and pasireotide response predictors, discuss their current usefulness, and point to future directions in the research of this field.

Introduction: A small percentage of patients will develop a severe form of COVID-19 caused by SARS-CoV-2 infection. Thus, it is important to predict the potential outcomes identifying early markers of poor prognosis. In this context, we evaluated the association of SARS-CoV-2 infection with lipid abnormalities and their role in prognosis. Methods: Single-center, retrospective, observational study of COVID-19 patients admitted from March to October 2020. Clinical and laboratory data, comorbidities, and treatments for COVID-19 were evaluated. Main outcomes including intensive care unit (ICU) admission and mortality were analyzed with a multivariable Cox proportional hazards regression model. Results: We selected 1489 from a total of 2038 consecutive patients with confirmed COVID-19, who had a complete lipid profile before ICU admission. During the follow-up performed in 1109 patients, we observed a decrease in T-c, HDL-c, and LDL-c in 28.6%, 42.9%, and 30.4% of patients, respectively, and an increase in TG in 76.8%. The decrease of both T-c and HDL- c was correlated with a decrease in albumin levels (r = 0.39 and r = 0.37, respectively). Kaplan–Meier survival curves found an increased ICU admission in patients with lower T-c (HR 0.55, CI 0.36–0.86), HDL-c (HR 0.61, CI 0.45–0.84), and LDL-c (HR 0.85, CI 0.74–0.97). Higher values of T-c (HR 0.45, CI 0.36–0.57), HDL-c (HR 0.66, CI 0.54–0.81), and LDL-c (HR 0.86, CI 0.78–0.94) showed a protective effect on mortality. Conclusions: Abnormalities in lipid profile are a frequent complication of SARS-CoV-2 infection and might be related to morbidity and mortality. Funding: Proyectos de Investigación en Salud (FIS) and cofinanced by FEDER.

Purpose: Peripheral helper T (Tph) cells have an important role in the induction of humoral immune responses and autoantibody production. Accordingly, it is feasible that this lymphocyte subset has a relevant role in the pathogenesis of autoimmune thyroid diseases (AITD). In this study we aim to analyze the levels and function of Tph cells in blood samples from patients with AITD. Methods: We performed an observational study with cases and controls. Blood samples were obtained from nineteen patients with Hashimoto’s thyroiditis (HT), twenty-four with Graves’ disease (GD), and fifteen healthy controls. In addition, the levels of follicular T helper (Tfh) cells and Tph cells, the release of interleukin-21 (IL-21) by these lymphocytes and the number of plasmablasts were analyzed by multi-parametric flow cytometry analyses. Results: Increased percentages of Tfh and Tph lymphocytes were detected in patients with HT and GD. Furthermore, an enhanced synthesis of the cytokine IL-21 by these cells was observed. Accordingly, we detected significant higher percentages of plasmablasts in patients with GD, and these values tended to be also higher in HT patients. Moreover, significant positive associations were observed between the levels of Tfh or Tph and the number of plasmablast or anti-TSHR Ab titers in patients with AITD. Conclusion: Our data suggest that Tph lymphocytes may have a relevant role in the pathogenesis of AITD.

Background: Type 2 diabetes mellitus (T2DM) is usually accompanied by a low-grade inflammatory phenomenon, which participates in the pathogenesis of different complications of this condition. The inflammatory response is under the regulation of different mechanisms, including T regulatory (Treg) lymphocytes. However, the possible role of type 1 T regulatory (Tr1) cells in T2DM has not been explored so far. Aim: To carry out a quantitative analysis of Tr1 lymphocytes and other immune cell subsets in patients with T2DM and correlate these results with clinical findings and treatments. Materials and methods: Sixty patients with T2DM and twenty-three healthy controls were included in the study. Biochemical and anthropometric variables were evaluated, and Tr1 lymphocytes (CD4⁺CD49⁺LAG-3⁺IL-10⁺) and other cell subsets (Th17, Th22 and Foxp3 + Treg cells) were analyzed in peripheral blood samples by multiparametric flow cytometry. Results: Significant increased levels of Tr1 cells were detected in patients with severe and mild disease, compared to healthy controls. In addition, CD4⁺IL-10⁺ lymphocytes were also increased in patients with T2DM. In contrast, similar levels of Foxp3⁺ Treg cells, Th17 and Th22 lymphocytes were observed in patients and controls. Likewise, no significant associations were detected between Tr1 cell levels and different clinical and laboratory parameters. However, those patients receiving glucagon-like peptide-1 receptor agonists (GLP-1-RA) showed similar levels of Tr1 cells than healthy controls, and significant lower numbers than untreated patients. Conclusion: We observed an increase in Tr1 and CD4⁺IL10⁺ lymphocyte levels in T2DM. Moreover, GLP1-RA treatment was significantly associated with normalization of the Tr1 levels. This highlights another potential immune dysfunction in patients with T2DM, which could participate in the pathogenesis of this condition.