Integrative Analyses of Genes Associated with Hashimoto's Thyroiditis

Electrochemical protein biosensors for disease marker detection: progress and opportunities

The development of artificial intelligence-enabled medical health care has created both opportunities and challenges for next-generation biosensor technology. Proteins are extensively used as biological macromolecular markers in disease diagnosis and the analysis of therapeutic effects. Electrochemical protein biosensors have achieved desirable specificity by using the specific antibody-antigen binding principle in immunology. However, the active centers of protein biomarkers are surrounded by a peptide matrix, which hinders charge transfer and results in insufficient sensor sensitivity. Therefore, electrode-modified materials and transducer devices have been designed to increase the sensitivity and improve the practical application prospects of electrochemical protein sensors. In this review, we summarize recent reports of electrochemical biosensors for protein biomarker detection. We highlight the latest research on electrochemical protein biosensors for the detection of cancer, viral infectious diseases, inflammation, and other diseases. The corresponding sensitive materials, transducer structures, and detection principles associated with such biosensors are also addressed generally. Finally, we present an outlook on the use of electrochemical protein biosensors for disease marker detection for the next few years.

Exploring the diagnostic value of endothelial cell and angiogenesis-related genes in Hashimoto's thyroiditis based on transcriptomics and single cell RNA sequencing

(1) BACKGROUND: Hashimoto's thyroiditis (HT) can cause angiogenesis in the thyroid gland. However, the molecular mechanism of endothelial cells and angiogenesis related genes (ARGs) has not been extensively studied in HT. (2) METHODS: The HRA001684, GSE29315 and GSE163203 datasets were included in this study. Using single-cell analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, machine learning algorithms and expression analysis for exploration. And receiver operator characteristic (ROC) curves was draw. Gene set enrichment analysis (GSEA) was utilized to investigate the biological function of the biomarkers. Meanwhile, we investigated into the relationship between biomarkers and different types of immune cells. Additionally, the expression of biomarkers in the TCGA-TC dataset was examined and the mRNA-drug interaction network was constructed. (3) RESULTS: We found 14 cell subtypes were obtained in HT samples after single-cell analysis. A total of 5 biomarkers (CD52, CD74, CD79A, HLA-B and RGS1) were derived, and they had excellent diagnostic performance. Then, 27 drugs targeting biomarkers were predicted. The expression analysis showed that CD74 and HLA-B were significantly up-regulated in HT samples. (4) CONCLUSION: In this study, 5 biomarkers (CD52, CD74, CD79A, HLA-B and RGS1) were screened and their expressions in endothelial cells was compared to offer a new reference for the recognition and management of HT.

Prevalence of Selected Polymorphisms of Il7R, CD226, CAPSL, and CLEC16A Genes in Children and Adolescents with Autoimmune Thyroid Diseases

Hashimoto's thyroiditis (HT) and Graves' disease (GD) are common autoimmune endocrine disorders in children. Studies indicate that apart from environmental factors, genetic background significantly contributes to the development of these diseases. This study aimed to assess the prevalence of selected single-nucleotide polymorphisms (SNPs) of Il7R, CD226, CAPSL, and CLEC16A genes in children with autoimmune thyroid diseases. We analyzed SNPs at the locus rs3194051, rs6897932 of IL7R, rs763361 of CD226, rs1010601 of CAPSL, and rs725613 of CLEC16A gene in 56 HT patients, 124 GD patients, and 156 healthy children. We observed significant differences in alleles IL7R (rs6897932) between HT males and the control group (C > T, p = 0.028) and between all GD patients and healthy children (C > T, p = 0.035) as well as GD females and controls (C > T, p = 0.018). Moreover, the C/T genotype was less frequent in GD patients at rs6897932 locus and in HT males at rs1010601 locus. The presence of the T allele in the IL7R (rs6897932) locus appears to have a protective effect against HT in males and GD in all children. Similarly, the presence of the T allele in the CAPSL locus (rs1010601) seems to reduce the risk of HT development in all patients.

SNVstory: inferring genetic ancestry from genome sequencing data

BACKGROUND

Genetic ancestry, inferred from genomic data, is a quantifiable biological parameter. While much of the human genome is identical across populations, it is estimated that as much as 0.4% of the genome can differ due to ancestry. This variation is primarily characterized by single nucleotide variants (SNVs), which are often unique to specific genetic populations. Knowledge of a patient's genetic ancestry can inform clinical decisions, from genetic testing and health screenings to medication dosages, based on ancestral disease predispositions. Nevertheless, the current reliance on self-reported ancestry can introduce subjectivity and exacerbate health disparities. While genomic sequencing data enables objective determination of a patient's genetic ancestry, existing approaches are limited to ancestry inference at the continental level.

RESULTS

To address this challenge, and create an objective, measurable metric of genetic ancestry we present SNVstory, a method built upon three independent machine learning models for accurately inferring the sub-continental ancestry of individuals. We also introduce a novel method for simulating individual samples from aggregate allele frequencies from known populations. SNVstory includes a feature-importance scheme, unique among open-source ancestral tools, which allows the user to track the ancestral signal broadcast by a given gene or locus. We successfully evaluated SNVstory using a clinical exome sequencing dataset, comparing self-reported ethnicity and race to our inferred genetic ancestry, and demonstrate the capability of the algorithm to estimate ancestry from 36 different populations with high accuracy.

CONCLUSIONS

SNVstory represents a significant advance in methods to assign genetic ancestry, opening the door to ancestry-informed care. SNVstory, an open-source model, is packaged as a Docker container for enhanced reliability and interoperability. It can be accessed from https://github.com/nch-igm/snvstory .

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.

The whole blood DNA methylation of RAB8A and RAP1A in autoimmune thyroiditis: evidence and validation of iodine exposure in a population from different water iodine areas

Our study aimed to identify and verify G protein-related methylated genes in AIT patients, while also investigate those genes in AIT patients exposed to iodine in different water iodine areas. Different areas were classified by median water iodine (MWI) concentrations: Iodine-Fortified Areas (IFA, MWI<10µg/L), Iodine-Adequate Areas (IAA, 40≤MWI≤100 µg/L), and Iodine-Excessive Areas (IEA, MWI>100 µg/L). We studied 176 AIT cases and 176 controls, with 89, 40, and 47 pairs in IFA, IAA, and IEA, respectively. Using the Illumina Human Methylation 850k BeadChip, we identified candidate methylated genes. MethylTargetTM and QRT-PCR validated DNA methylation and mRNA expression. Results showed hypomethylation and high expression of RAB8A and RAP1A in all 176 AIT cases. RAB8A's CpG sites were mainly hypomethylated in IFA and IEA, while RAP1A's sites were primarily hypomethylated in IEA. This study underscores how water iodine exposure may influence RAB8A and RAP1A methylation in AIT.

Comprehensive analysis of hub biomarkers associated with immune and oxidative stress in Hashimoto's thyroiditis

Hashimoto's thyroiditis (HT) is a type of autoimmune disorder with a complex interplay between immune disorder and oxidative stress (OS). This research aimed to discover biomarkers and potential treatment targets associated with immune and OS dysregulation in HT through integrated bioinformatics analysis and clinical validations. Differential gene expression analysis of GSE138198 dataset from the GEO database identified 1490 differentially expressed genes (DEGs) in HT, including 883 upregulated and 607 downregulated genes. Weighted gene co-expression network analysis explored module genes associated with HT. Overlapping the differentially expressed module genes with immune-related and OS-related genes identified eight differentially expressed module genes associated with immune and OS (DEIOGs) in HT. Protein-protein interaction network analysis identified five hub genes (TNFAIP3, FOS, PTK2B, STAT1, and MMP9). We confirmed four hub genes (TNFAIP3, PTK2B, STAT1 and MMP9) in GSE29315 dataset and clinical thyroid samples, which showed high diagnostic accuracy (AUC >0.7) for HT. The expression of these four genes was positively correlated with serum thyroid peroxidase antibody, thyroglobulin antibody levels, and inflammatory infiltration scores in clinical thyroid samples. Immune profiling revealed distinct profiles in HT, such as B cells memory, monocytes and macrophages. Additionally, all hub genes were inversely associated with monocytes. Further, miRNA-mRNA network analysis was conducted, and a regulatory network comprising four hub genes, 238 miRNAs and 32 TFs was established. These findings suggest that immune cells play a crucial role in the development of HT, and the hub genes TNFAIP3, PTK2B, STAT1, and MMP9 may be key players in HT through immune- and OS-related signaling pathways. Our results may provide valuable insights into the pathogenesis and therapeutic monitoring of HT.

Impact of Vitamin D on Immunopathology of Hashimoto's Thyroiditis: From Theory to Practice

Hashimoto's thyroiditis (HT) is a common autoimmune disease affecting the thyroid gland, characterized by lymphocytic infiltration, damage to thyroid cells, and hypothyroidism, and often requires lifetime treatment with levothyroxine. The disease has a complex etiology, with genetic and environmental factors contributing to its development. Vitamin D deficiency has been linked to a higher prevalence of thyroid autoimmunity in certain populations, including children, adolescents, and obese individuals. Moreover, vitamin D supplementation has shown promise in reducing antithyroid antibody levels, improving thyroid function, and improving other markers of autoimmunity, such as cytokines, e.g., IP10, TNF-α, and IL-10, and the ratio of T-cell subsets, such as Th17 and Tr1. Studies suggest that by impacting various immunological mechanisms, vitamin D may help control autoimmunity and improve thyroid function and, potentially, clinical outcomes of HT patients. The article discusses the potential impact of vitamin D on various immune pathways in HT. Overall, current evidence supports the potential role of vitamin D in the prevention and management of HT, although further studies are needed to fully understand its mechanisms of action and potential therapeutic benefits.

Molecular Mechanisms in Autoimmune Thyroid Disease

The most common cause of acquired thyroid dysfunction is autoimmune thyroid disease, which is an organ-specific autoimmune disease with two presentation phenotypes: hyperthyroidism (Graves-Basedow disease) and hypothyroidism (Hashimoto’s thyroiditis). Hashimoto’s thyroiditis is distinguished by the presence of autoantibodies against thyroid peroxidase and thyroglobulin. Meanwhile, autoantibodies against the TSH receptor have been found in Graves-Basedow disease. Numerous susceptibility genes, as well as epigenetic and environmental factors, contribute to the pathogenesis of both diseases. This review summarizes the most common genetic, epigenetic, and environmental mechanisms involved in autoimmune thyroid disease.

Follicular Thyroid Adenoma and Follicular Thyroid Carcinoma-A Common or Distinct Background? Loss of Heterozygosity in Comprehensive Microarray Study

Pre- and postsurgical differentiation between follicular thyroid adenoma (FTA) and follicular thyroid cancer (FTC) represents a significant diagnostic challenge. Furthermore, it remains unclear whether they share a common or distinct background and what the mechanisms underlying follicular thyroid lesions malignancy are. The study aimed to compare FTA and FTC by the comprehensive microarray and to identify recurrent regions of loss of heterozygosity (LOH). We analyzed formalin-fixed paraffin-embedded (FFPE) samples acquired from 32 Caucasian patients diagnosed with FTA (16) and FTC (16). We used the OncoScan™ microarray assay (Affymetrix, USA), using highly multiplexed molecular inversion probes for single nucleotide polymorphism (SNP). The total number of LOH was higher in FTC compared with FTA (18 vs. 15). The most common LOH present in 21 cases, in both FTA (10 cases) and FTC (11 cases), was 16p12.1, which encompasses many cancer-related genes, such as TP53, and was followed by 3p21.31. The only LOH present exclusively in FTA patients (56% vs. 0%) was 11p11.2-p11.12. The alteration which tended to be detected more often in FTC (6 vs. 1 in FTA) was 12q24.11-q24.13 overlapping FOXN4, MYL2, PTPN11 genes. FTA and FTC may share a common genetic background, even though differentiating rearrangements may also be detected.

Bioinformatics and Connectivity Map Analysis Suggest Viral Infection as a Critical Causative Factor of Hashimoto's Thyroiditis

Hashimoto's thyroiditis (HT) is a common autoimmune disease, and its prevalence is rapidly increasing. Both genetic and environmental risk factors contribute to the development of HT. Recently, viral infection has been suggested to act as a trigger of HT by eliciting the host immune response and subsequent autoreactivity. We analyzed the features of HT through bioinformatics analysis so as to identify the markers of HT development. We accessed public microarray data of HT patients from the Gene Expression Omnibus (GEO) and obtained differentially expressed genes (DEGs) under HT. Gene Ontology (GO) and KEGG-pathway-enrichment analyses were performed for functional clustering of our protein-protein interaction (PPI) network. Utilizing ranked gene lists, we performed a Gene Set Enrichment Analysis (GSEA) by using the clusterprofiler R package. By comparing the expression signatures of the huge perturbation database with the queried rank-ordered gene list, a connectivity map (CMap) analysis was performed to screen potential therapeutic targets and agents. The gene expression profile of the HT group was in line with the general characteristics of HT. Biological processes related to the immune response and viral infection pathways were obtained for the upregulated DEGs. The GSEA results revealed activation of autoimmune-disease-related pathways and several viral-infection pathways. Autoimmune-disease and viral-infection pathways were highly interconnected by common genes, while the HLA genes, which are shared by both, were significantly upregulated. The CMap analysis suggested that perturbagens, including SRRM1, NLK, and CCDC92, have the potential to reverse the HT expression profile. Several lines of evidence suggested that viral infection and the host immune response are activated during HT. Viral infection is suspected to act as a key trigger of HT by causing autoimmunity. SRRM1, an alternative splicing factor which responds to viral activity, might serve as potential marker of HT.

CARD9 gene rs4077515 polymorphism is associated with the susceptibility of Hashimoto's thyroiditis and the development of thyroid cancer

AMIS: Hashimoto's thyroiditis (HT) is the most common type of autoimmune thyroiditis and is a risk factor for the occurrence of thyroid papillary carcinoma (PTC). The study aimed to explore the distribution of CARD9 rs4077515 polymorphism in HT and PTC patients, in order to evaluate its association with the occurrence and development of HT.

METHODS

150 HT patients and 120 PTC cases were included. Genotypes of CARD9 rs40775155 polymorphism were sequenced and counted.

RESULTS

A remarkable increase trend of rs4077515 AA genotype was found in HT cases in comparison with the control group, while GG genotype frequency exhibited a down trend. An excess of A allele was also detected in HT group. HT cases carrying AG and AA genotypes had high risk to receive hormonotherapy and needed a much larger dose. In comparison with HT cases, both AG and AA appeared more frequently in PTC patients, and are associated with the tumor size, LN metastasis and surgical margin. The AG (OR = 2.566, 95 % CI = 1.376-4.786) and AA (OR = 3.040, 95 % CI = 1.525-6.060) genotype carriers had a greater risk of developing PTC. The A allele of rs4077515 polymorphism was a risk allele for the onset of PTC among HT cases (OR = 1.775, 95 % CI = 1.260-2.502).

CONCLUSION

CARD9 rs4077515 polymorphism is likely to be a risk factor for HT in the Chinese Han population, it also contributes to the development of PTC for HT patients.