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Beduleva L, Sidorov A, Fomina K, Terentiev A, Menshikov I, Shklyaeva N, Ivanov P, Varaksin V. Experimental rat models for Hashimoto's thyroiditis. J Endocrinol Invest 2024; 47:1205-1214. [PMID: 38010598 DOI: 10.1007/s40618-023-02240-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 11/04/2023] [Indexed: 11/29/2023]
Abstract
PURPOSE Hashimoto's thyroiditis (HT) is an autoimmune thyroid disease characterized by T lymphocyte-mediated destruction of thyroid follicles. To study the pathogenesis of HT and the efficacy of new substances for its treatment, an easily obtained and adequate to the human disease experimental model is needed. The aim of our study was to find out whether it is possible to induce experimental autoimmune thyroiditis (EAT) similar to Hashimoto's thyroiditis by injecting with thyroglobulin (Tg) without using agents that enhance its thyroiditogenicity and without taking into account the genetic sensitivity of animals. METHODS Wistar rats were immunized with freshly isolated rat Tg or porcine Tg. In 8 weeks, histological studies of the thyroid and parathyroid glands were performed. Thyroid function and total serum calcium level were also evaluated. RESULTS Immunization with both rat and porcine freshly isolated Tg caused T lymphocytic infiltration of the thyroid gland, thyroid follicle atrophy and degradation in Wistar rats. EAT caused by porcine Tg was characterized by greater severity than EAT induced with rat Tg. In 55% of rats with porcine Tg-induced EAT, oxyphilic metaplasia was detected in the parathyroid glands. In addition, low total serum calcium was observed in these rats. CONCLUSION Two rat models of autoimmune thyroiditis were obtained. EAT caused in Wistar rats by immunization with rat Tg is similar to Hashimoto's thyroiditis. EAT induced with porcine Tg was accompanied by oxyphil cell metaplasia in the parathyroids and hypocalcemia.
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Affiliation(s)
- L Beduleva
- Laboratory of Molecular and Cell Immunology, Department of Immunology and Cell Biology, Udmurt State University, 1 Universitetskaya St., Izhevsk, Russian Federation, 426034.
- Laboratory of Biocompatible Materials, Udmurt Federal Research Center UB RAS, 34 T. Baramzinoy St., Izhevsk, Russian Federation, 426067.
| | - A Sidorov
- Laboratory of Molecular and Cell Immunology, Department of Immunology and Cell Biology, Udmurt State University, 1 Universitetskaya St., Izhevsk, Russian Federation, 426034
- Laboratory of Biocompatible Materials, Udmurt Federal Research Center UB RAS, 34 T. Baramzinoy St., Izhevsk, Russian Federation, 426067
| | - K Fomina
- Laboratory of Molecular and Cell Immunology, Department of Immunology and Cell Biology, Udmurt State University, 1 Universitetskaya St., Izhevsk, Russian Federation, 426034
- Laboratory of Biocompatible Materials, Udmurt Federal Research Center UB RAS, 34 T. Baramzinoy St., Izhevsk, Russian Federation, 426067
| | - A Terentiev
- Laboratory of Molecular and Cell Immunology, Department of Immunology and Cell Biology, Udmurt State University, 1 Universitetskaya St., Izhevsk, Russian Federation, 426034
- Laboratory of Biocompatible Materials, Udmurt Federal Research Center UB RAS, 34 T. Baramzinoy St., Izhevsk, Russian Federation, 426067
| | - I Menshikov
- Laboratory of Molecular and Cell Immunology, Department of Immunology and Cell Biology, Udmurt State University, 1 Universitetskaya St., Izhevsk, Russian Federation, 426034
- Laboratory of Biocompatible Materials, Udmurt Federal Research Center UB RAS, 34 T. Baramzinoy St., Izhevsk, Russian Federation, 426067
| | - N Shklyaeva
- Laboratory of Molecular and Cell Immunology, Department of Immunology and Cell Biology, Udmurt State University, 1 Universitetskaya St., Izhevsk, Russian Federation, 426034
| | - P Ivanov
- Laboratory of Molecular and Cell Immunology, Department of Immunology and Cell Biology, Udmurt State University, 1 Universitetskaya St., Izhevsk, Russian Federation, 426034
| | - V Varaksin
- Laboratory of Biocompatible Materials, Udmurt Federal Research Center UB RAS, 34 T. Baramzinoy St., Izhevsk, Russian Federation, 426067
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Zeng Y, Suo C, Yao S, Lu D, Larsson H, D'Onofrio BM, Lichtenstein P, Fang F, Valdimarsdóttir UA, Song H. Genetic Associations Between Stress-Related Disorders and Autoimmune Disease. Am J Psychiatry 2023; 180:294-304. [PMID: 37002690 DOI: 10.1176/appi.ajp.20220364] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
Abstract
Objective: Emerging evidence supports a bidirectional phenotypic association between stress-related disorders and autoimmune disease. However, the biological underpinnings remain unclear. Here, the authors examined whether and how shared genetics contribute to the observed phenotypic associations. Methods: Based on data from 4,123,631 individuals identified from Swedish nationwide registers, familial coaggregation of stress-related disorders (any disorder or posttraumatic stress disorder [PTSD]) and autoimmune disease were initially estimated in seven cohorts with different degrees of kinship. Polygenic risk score (PRS) analyses were then performed with individual-level genotyping data from 376,871 participants in the UK Biobank study. Finally, genetic correlation analyses and enrichment analyses were performed with genome-wide association study (GWAS) summary statistics. Results: Familial coaggregation analyses revealed decreasing odds of concurrence of stress-related disorders and autoimmune disease with descending kinship or genetic relatedness between pairs of relatives; adjusted odds ratios were 1.51 (95% CI=1.09–2.07), 1.28 (95% CI=0.97–1.68), 1.16 (95% CI=1.14–1.18), and 1.01 (95% CI=0.98–1.03) for monozygotic twins, dizygotic twins, full siblings, and half cousins, respectively. Statistically significant positive associations were observed between PRSs of stress-related disorders and autoimmune disease, as well as between PRSs of autoimmune disease and stress-related disorders. GWAS summary statistics revealed a genetic correlation of 0.26 (95% CI=0.14–0.38) between these two phenotypes and identified 10 common genes and five shared functional modules, including one module related to G-protein–coupled receptor pathways. Similar analyses performed for PTSD and specific autoimmune diseases (e.g., autoimmune thyroid disease) largely recapitulated the results of the main analyses. Conclusions: This study demonstrated familial coaggregation, genetic correlation, and common biological pathways between stress-related disorders and autoimmune disease.
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Affiliation(s)
- Yu Zeng
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Chen Suo
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Shuyang Yao
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Donghao Lu
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Henrik Larsson
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Brian M D'Onofrio
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Paul Lichtenstein
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Fang Fang
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Unnur A Valdimarsdóttir
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
| | - Huan Song
- West China Biomedical Big Data Center, West China Hospital (Zeng, Lu, Fang, Song), and Med-X Center for Informatics (Zeng, Song), Sichuan University, Chengdu, China; Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai (Suo); Department of Medical Epidemiology and Biostatistics (Yao, Larsson, D'Onofrio, Lichtenstein) and Institute of Environmental Medicine (Lu, Fang, Valdimarsdóttir), Karolinska Institutet, Stockholm; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Lu, Valdimarsdóttir); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson); Department of Psychological and Brain Sciences, Indiana University, Bloomington (D'Onofrio); Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík (Valdimarsdóttir, Song)
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