Chemokines in thyroid autoimmunity

Causal relationship between inflammatory cytokines and autoimmune thyroid disease: a bidirectional two-sample Mendelian randomization analysis

Background

Autoimmune thyroid disease (AITD) ranks among the most prevalent thyroid diseases, with inflammatory cytokines playing a decisive role in its pathophysiological process. However, the causal relationship between the inflammatory cytokines and AITD remains elusive.

Methods

A two-sample Mendelian randomization (MR) analysis was performed to elucidate the causal connection between AITD and 41 inflammatory cytokines. Genetic variations associated with inflammatory cytokines were sourced from the FinnGen biobank, whereas a comprehensive meta-analysis of genome-wide association studies (GWASs) yielded data on Graves' disease (GD) and Hashimoto thyroiditis. Regarding the MR analysis, the inverse variance-weighted, MR-Egger, and weighted median methods were utilized. Additionally, sensitivity analysis was conducted using MR-Egger regression, MR-pleiotropy residual sum, and outliers.

Results

Seven causal associations were identified between inflammatory cytokines and AITD. High levels of tumor necrosis factor-β and low levels of stem cell growth factor-β were indicative of a higher risk of GD. In contrast, high levels of interleukin-12p70 (IL-12p70), IL-13, and interferon-γ and low levels of monocyte chemotactic protein-1 (MCP-1) and TNF-α suggested a higher risk of HD. Moreover, 14 causal associations were detected between AITD and inflammatory cytokines. GD increases the levels of macrophage inflammatory protein-1β, MCP-1, monokine induced by interferon-γ (MIG), interferon γ-induced protein 10 (IP-10), stromal cell-derived factor-1α, platelet-derived growth factor BB, β-nerve growth factor, IL-2ra, IL-4, and IL-17 in blood, whereas HD increases the levels of MIG, IL-2ra, IP-10, and IL-16 levels.

Conclusion

Our bidirectional MR analysis revealed a causal relationship between inflammatory cytokines and AITD. These findings offer valuable insights into the pathophysiological mechanisms underlying AITD.

Exploring the bidirectional relationship between metabolic syndrome and thyroid autoimmunity: a Mendelian randomization study

Background

Observational studies have reported a possible association between metabolic syndrome (MetS) and thyroid autoimmunity. Nevertheless, the relationship between thyroid autoimmunity and MetS remains unclear. The objective of this research was to assess the causal impact of MetS on thyroid autoimmunity through the utilization of Mendelian randomization (MR) methodology.

Methods

We performed bidirectional MR to elucidate the causal relationship between MetS and their components and thyroid autoimmunity (positivity of TPOAb). Single nucleotide polymorphisms (SNPs) of MetS and its components were obtained from the publicly available genetic variation summary database. The Thyroidomics Consortium conducted a genome-wide association analysis, which provided summary-level data pertaining to thyroid autoimmunity. The study included several statistical methods, including the inverse variance weighting method (IVW), weighted median, simple mode, weight mode, and MR-Egger methods, to assess the causal link. In addition, to ensure the stability of the results, a sensitivity analysis was conducted.

Results

IVW showed that MetS reduced the risk of developing thyroid autoimmunity (OR = 0.717, 95% CI = 0.584 - 0.88, P = 1.48E-03). The investigation into the causative association between components of MetS and thyroid autoimmune revealed a statistically significant link between triglycerides levels and the presence of thyroid autoimmunity (IVW analysis, OR = 0.603, 95%CI = 0.45 -0.807, P = 6.82E-04). The reverse analysis did not reveal any causal relationship between thyroid autoimmunity and MetS, including its five components.

Conclusions

We have presented new genetic evidence demonstrating that MetS and its triglyceride components may serve as potential protective factors against thyroid autoimmunity.

CXCL9 mediating the effect of thyroid disorders on oral and oropharyngeal cancer risk: A mediation Mendelian randomization study

INTRODUCTION

The established association between thyroid disorders (TD) and its two main subtypes-hyperthyroidism and hypothyroidism-and the incidence of oral and oropharyngeal cancer (OCPC) has been substantiated. However, the direct causal relationship and potential intermediary mechanisms linking these conditions have not been clearly defined in prior studies.

MATERIAL & METHODS

This study employed univariate Mendelian randomization (MR) analysis to explore those relationship. Instrumental variables from genome-wide association study (GWAS) datasets for TD (n = 218,792), hyperthyroidism (n = 460,499), hypothyroidism (n = 213,990), and OCPC (n = 12,619), along with 41 intermediary inflammatory cytokines (n = 8293), were analyzed. Inverse variance weighting (IVW) method assessed the causal relationships, while summary MR analysis with pQTL datasets from decode and 91 inflammatory cytokines explored the cytokines' roles as biomarkers and therapeutic targets for OCPC. Multivariable MR (MVMR) analysis quantified the mediation effect of these cytokines in the TD-OCPC relationship.

RESULTS

UVMR analysis provided strong evidence for a causal relationship between TD (OR = 1.376, 95 % CI = 1.142-1.656, p = 0.001), hyperthyroidism (OR = 1.319, 95 % CI=1.129-1.541, p = 0.001), hypothyroidism (OR = 1.224, 95 % CI = 1.071-1.400, p = 0.003), and the risk of OCPC. CXCL9 was identified as a significant intermediary in mediating the risk of OCPC from TD and its two subtypes (OR = 1.218, 95 % CI = 1.016-1.461, P = 0.033), suggesting its potential as a predictive biomarker for OCPC. MVMR analysis further revealed that CXCL9 mediated 7.94 %, 14.4 %, and 18 % of the effects of TD, hyperthyroidism, and hypothyroidism on OCPC risk, respectively.

DISCUSSION

This study not only elucidated the potential causal relationships between TD including its two subtypes and OCPC risk, but also highlighted CXCL9 as a pivotal mediator in this association.

Costimulatory Molecule CD226 Regulates Atopic Dermatitis in a Mouse Model

This study investigated the role of CD226 in a 2,4-dinitrochlorobenzene (DNCB)-induced mouse model of atopic dermatitis. The results showed that the lack of CD226 (global and CD4+ T-cell specific) significantly increased ear thickness, reddening, swelling, and scaling of the skin as well as inflammatory cell and mast cell infiltration. RT-qPCR results demonstrated that the mRNA expressions of atopic dermatitis-related inflammatory cytokines and chemokines were markedly increased in the draining lymph nodes and lesioned ear skin tissues of global and CD4+ T-cell-specific CD226-deficient mice compared with that in control mice. In vitro assessment revealed that CD226 directly modulates TGFβ-mediated regulatory T (Treg) cell differentiation and proliferation. Notably, Treg cell-specific deletion of CD226 (Cd226fl/flFoxp3cre mice) resulted in more severe dermatitis and epidermal thickening than those observed in littermate mice upon DNCB treatment. Subsequent analysis showed that the infiltration of Treg cells in ear lesions and the number of Tregs in the spleen were significantly reduced in Cd226fl/flFoxp3cre mice after DNCB treatment. In addition, the lack of CD226 induced apoptosis of Treg cells through the activation of caspase 3. Therefore, these results suggest that CD226 has potential efficacy in atopic dermatitis, correlating with Treg cell inhibition.

Clinical and molecular impact of concurrent thyroid autoimmune disease and thyroid cancer: From the bench to bedside

The recent incorporation of immune checkpoint inhibitors targeting the PD-1 (programmed cell death receptor 1) and CTLA-4 (cytotoxic T lymphocyte antigen 4) pathways into the therapeutic armamentarium of cancer has increased the need to understand the correlation between the immune system, autoimmunity, and malignant neoplasms. Both autoimmune thyroid diseases and thyroid cancer are common clinical conditions. The molecular pathology of autoimmune thyroid diseases is characterized by the important impact of the PD-1/PD-L1 axis, an important inhibitory pathway involved in the regulation of T-cell responses. Insufficient inhibitory pathways may prone the thyroid tissue to a self-destructive immune response that leads to hypothyroidism. On the other hand, the PD-1/PD-L1 axis and other co-inhibitory pathways are the cornerstones of the immune escape mechanisms in thyroid cancer, which is a mechanism through which the immune response fails to recognize and eradicate thyroid tumor cells. This common mechanism raises the idea that thyroid autoimmunity and thyroid cancer may be opposite sides of the same coin, meaning that both conditions share similar molecular signatures. When associated with thyroid autoimmunity, thyroid cancer may have a less aggressive presentation, even though the molecular explanation of this clinical consequence is unclear. More studies are warranted to elucidate the molecular link between thyroid autoimmune disease and thyroid cancer. The prognostic impact that thyroid autoimmune disease, especially chronic lymphocytic thyroiditis, may exert on thyroid cancer raises important insights that can help physicians to better individualize the management of patients with thyroid cancer.

Identification and Preliminary Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Hashimoto's Thyroiditis by Comprehensive Analysis

Hashimoto's thyroiditis (HT) is an autoimmune disruption manifested by immune cell infiltration in thyroid tissue and the production of antibodies against thyroid-specific antigens, such as the thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TGAb). TPOAb and TGAb are commonly used in clinical tests; however, handy indicators of the diagnosis and progression of HT are still scarce. Extracellular proteins are glycosylated and are likely to enter body fluids and become readily available and detectable biomarkers. Our research aimed to discover extracellular biomarkers and potential treatment targets associated with HT through integrated bioinformatics analysis and clinical sample validations. A total of 19 extracellular protein-differentially expressed genes (EP-DEGs) were screened by the GSE138198 dataset from the Gene Expression Omnibus (GEO) database and protein annotation databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE, and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Six key EP-DEGs (CCL5, GZMK, CXCL9, CXCL10, CXCL11, and CXCL13) were further validated in the GSE29315 dataset and the diagnostic curves were evaluated, which all showed high diagnostic accuracy (AUC > 0.95) for HT. Immune profiling revealed the correlation of the six key EP-DEGs and the pivotal immune cells in HT, such as CD8+ T cells, dendritic cells, and Th2 cells. Further, we also confirmed the key EP-DEGs in clinical thyroid samples. Our study may provide bioinformatics and clinical evidence for revealing the pathogenesis of HT and improving the potential diagnosis biomarkers and therapeutic strategies for HT.

Association of maternal thyroid peroxidase antibody during pregnancy with placental morphology and inflammatory and oxidative stress responses

Background

Studies suggest that thyroid peroxidase antibody (TPOAb) positivity exposure during pregnancy may contribute to changes in placental morphology and pathophysiology. However, little is known about the association of maternal TPOAb during pregnancy with placental morphology and cytokines. This study focuses on the effect of repeated measurements of maternal TPOAb during pregnancy on the placental morphology and cytokines.

Methods

Based on Ma'anshan Birth Cohort (MABC) in China, maternal TPOAb levels were retrospectively detected in the first, second and third trimesters. Placental tissues were collected 30 minutes after childbirth, placental morphological indicators were obtained by immediate measurement and formula calculation, and cytokine mRNA expression was detected by real-time quantitative polymerase chain reaction (RT-qPCR) afterward. Generalized linear models and linear mixed models were analyzed for the relationships of maternal TPOAb in the first, second and third trimesters with placental indicators.

Results

Totally 2274 maternal-fetal pairs were included in the analysis of maternal TPOAb levels and placental morphology, and 2122 pairs were included in that of maternal TPOAb levels and placental cytokines. Maternal TPOAb levels in early pregnancy were negatively associated with placental length, thickness, volume, weight and disc eccentricity, while positively correlated with placental IL-6, TNF-α, CRP, CD68, MCP-1, IL-10, HO-1, HIF-1α and GRP78. In mid-pregnancy, maternal TPOAb levels were negatively correlated with placental length, width and area. In late pregnancy, maternal TPOAb levels were negatively correlated with placental length, area, volume and weight. Repeated measures analysis showed that maternal TPOAb positivity tended to increase placental TNF-α, CD68 and MCP-1 while decreasing placental length, width and area than TPOAb negativity. Repeated measures analysis showed that maternal TPOAb levels were positively correlated with placental IL-6, TNF-α, CD68, MCP-1, IL-10, HO-1, HIF-1α and GRP78, while negatively correlated with placental length, area, volume, weight, and disc eccentricity.

Conclusion

There may be trimester-specific associations between maternal TPOAb levels and placental morphology and inflammatory and oxidative stress responses. The effect of maternal TPOAb levels on placental morphology is present throughout pregnancy. Early pregnancy may be the critical period for the association between maternal TPOAb levels and placental inflammatory and oxidative stress responses.

A novel hybrid model to predict concomitant diseases for Hashimoto's thyroiditis

Hashimoto's thyroiditis is an autoimmune disorder characterized by the destruction of thyroid cells through immune-mediated mechanisms involving cells and antibodies. The condition can trigger disturbances in metabolism, leading to the development of other autoimmune diseases, known as concomitant diseases. Multiple concomitant diseases may coexist in a single individual, making it challenging to diagnose and manage them effectively. This study aims to propose a novel hybrid algorithm that classifies concomitant diseases associated with Hashimoto's thyroiditis based on sequences. The approach involves building distinct prediction models for each class and using the output of one model as input for the subsequent one, resulting in a dynamic decision-making process. Genes associated with concomitant diseases were collected alongside those related to Hashimoto's thyroiditis, and their sequences were obtained from the NCBI site in fasta format. The hybrid algorithm was evaluated against common machine learning algorithms and their various combinations. The experimental results demonstrate that the proposed hybrid model outperforms existing classification methods in terms of performance metrics. The significance of this study lies in its two distinctive aspects. Firstly, it presents a new benchmarking dataset that has not been previously developed in this field, using diverse methods. Secondly, it proposes a more effective and efficient solution that accounts for the dynamic nature of the dataset. The hybrid approach holds promise in investigating the genetic heterogeneity of complex diseases such as Hashimoto's thyroiditis and identifying new autoimmune disease genes. Additionally, the results of this study may aid in the development of genetic screening tools and laboratory experiments targeting Hashimoto's thyroiditis genetic risk factors. New software, models, and techniques for computing, including systems biology, machine learning, and artificial intelligence, are used in our study.