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Giulia Brigante Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Azienda USL, Modena, Italy

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Giorgia Spaggiari Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Azienda USL, Modena, Italy

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Daniele Santi Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Azienda USL, Modena, Italy

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Katia Cioni Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Azienda USL, Modena, Italy

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Valentina Gnarini Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Azienda USL, Modena, Italy

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Chiara Diazzi Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Azienda USL, Modena, Italy

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Elisa Pignatti Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Center of Genomic Research, University of Modena and Reggio Emilia

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Livio Casarini Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Center of Genomic Research, University of Modena and Reggio Emilia

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Marco Marino Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Center of Genomic Research, University of Modena and Reggio Emilia

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Frank Tüttelmann Institute of Human Genetics, University of Munster, Munster, Germany

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Cesare Carani Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Azienda USL, Modena, Italy

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Manuela Simoni Unit of Endocrinology and Metabolism, Department of Biomedical, Metabolic and Neural Sciences
Center of Genomic Research, University of Modena and Reggio Emilia
Azienda USL, Modena, Italy

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Background: Thyroidectomized patients need variable doses of levothyroxine (LT<sub>4</sub>) to obtain target thyroid-stimulating hormone (TSH) levels. Individual feedback set-points have been hypothesized and the influence of several genes in the regulation of the pituitary-thyroid axis has been demonstrated. Objectives: We hypothesized that genetic variants of the TRHR gene could be associated with a different hypothalamo-pituitary sensitivity to thyroid hormone feedback. Methods: We retrospectively analyzed 84 thyroidectomized patients with no residual thyroid function and undetectable thyroglobulin levels. Patients were evaluated under LT<sub>4</sub> resulting in TSH levels detectable but <0.5 μIU/ml. The two SNPs rs3134105 and rs3110040 were identified as informative markers of the TRHR gene. Genotyping was performed using high-resolution melting technology. Genotype distribution was compared between the patients and 99 euthyroid controls. Results: The selected SNPs were in linkage disequilibrium and only rs3134105 was further considered. A significant difference between the three possible genotypes for rs3134105 was found for TSH (p = 0.04) and free thyroxine (fT<sub>4</sub>)/TSH ratio (p = 0.02). Moreover, despite similar serum concentrations of free triiodothyronine (fT<sub>3</sub>) and fT<sub>4</sub>, carriers of at least one A allele of rs3134105 had significantly lower serum TSH levels (p = 0.01) as well as higher fT<sub>3</sub>/TSH (p = 0.01) and fT<sub>4</sub>/TSH ratios (p < 0.01). Conclusions: We demonstrated an association between serum TSH levels and discrete alleles of the TRHR gene in totally thyroidectomized patients under LT<sub>4</sub> therapy. Therefore, the TRHR gene seems to be a determinant of hypothalamo-pituitary sensitivity to LT<sub>4</sub>.

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Marco Marino Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Center for Genomic Research, Italy

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Maria Laura Monzani Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Azienda USL of Modena, Modena, Italy

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Giulia Brigante Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Azienda USL of Modena, Modena, Italy

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Katia Cioni Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Azienda USL of Modena, Modena, Italy

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Bruno Madeo Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Azienda USL of Modena, Modena, Italy

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Daniele Santi Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Azienda USL of Modena, Modena, Italy

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Antonino Maiorana Department of Diagnostic and Clinical Medicine and Public Health, University of Modena and Reggio Emilia, Italy

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Stefania Bettelli Department of Diagnostic and Clinical Medicine and Public Health, University of Modena and Reggio Emilia, Italy

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Valeria Moriondo Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Center for Genomic Research, Italy

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Elisa Pignatti Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Center for Genomic Research, Italy

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Lara Bonacini Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Azienda USL of Modena, Modena, Italy

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Cesare Carani Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy

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Vincenzo Rochira Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Azienda USL of Modena, Modena, Italy

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Manuela Simoni Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, Italy
Center for Genomic Research, Italy
Azienda USL of Modena, Modena, Italy

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Objective: The diagnostic accuracy of thyroid fine needle aspiration biopsy (FNAB) can be improved by the combination of cytological and molecular analysis. In this study, washing liquids of FNAB (wFNAB) were tested for the BRAF V600E mutation, using the sensitive and cost-effective technique called high-resolution melting (HRM). The aim was to demonstrate the feasibility of BRAF analysis in wFNAB and its diagnostic utility, combined with cytology. Design: Prospective cohort study. Methods: 481 patients, corresponding to 648 FNAB samples, were subjected to both cytological (on cells smeared onto a glass slide) and molecular analysis (on fluids obtained washing the FNAB needle with 1 ml of saline) of the same aspiration. BRAF V600E analysis was performed by HRM after methodological validation for application to wFNAB (technique sensitivity: 5.4%). Results: The cytological results of the FNAB were: 136 (21%) nondiagnostic (THY1); 415 (64%) benign (THY2); 80 (12.4%) indeterminate (THY3); 9 (1.4%) suspicious for malignancy (THY4); 8 (1.2%) diagnostic of malignancy (THY5). The BRAF V600E mutation was found in 5 THY2, 2 THY3, 6 THY4 and 6 THY5 samples. Papillary carcinoma diagnosis was histologically confirmed in all BRAF+ thyroidectomized patients. BRAF combined with cytology improved the diagnostic value compared to cytology alone in a subgroup of 74 operated patients. Conclusions: HRM was demonstrated to be a feasible method for BRAF analysis in wFNAB. Thanks to its sensitivity and cost-effectiveness, it might be routinely used on a large scale in clinical practice. In perspective, standby wFNAB samples could be analyzed a posteriori in case of indeterminate cytology and/or suspicious findings on ultrasound.

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Sara De Vincentis Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Unit of Endocrinology, Department of Medical Specialties, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy

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Simona Loiacono Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy

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Eleonora Zanni Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy

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Roberta Sueri Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy

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Maria Laura Monzani Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Unit of Endocrinology, Department of Medical Specialties, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy

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Daniele Santi Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Unit of Endocrinology, Department of Medical Specialties, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy

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Ilaria Muller Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
Department of Endocrinology, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy

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Francesco Di Marco School of Specialisation in Endocrinology, University of Milan, Milan, Italy

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Erica Crivicich School of Specialisation in Endocrinology, University of Milan, Milan, Italy

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Mirco Armenti School of Specialisation in Endocrinology, University of Milan, Milan, Italy

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Uberto Pagotto Department of Medical and Surgical Sciences, Alma Mater Studiorum - Bologna University, Bologna, Italy
Department of Endocrinology and Diabetes Care and Prevention Unit, IRCCS Sant’Orsola-Malpighi Polyclinic, Bologna, Italy

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Lorenzo Tucci Department of Medical and Surgical Sciences, Alma Mater Studiorum - Bologna University, Bologna, Italy
Department of Endocrinology and Diabetes Care and Prevention Unit, IRCCS Sant’Orsola-Malpighi Polyclinic, Bologna, Italy

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Carolina Cecchetti Department of Medical and Surgical Sciences, Alma Mater Studiorum - Bologna University, Bologna, Italy
Department of Endocrinology and Diabetes Care and Prevention Unit, IRCCS Sant’Orsola-Malpighi Polyclinic, Bologna, Italy

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Tommaso Trenti Department of Laboratory Medicine and Anatomy Pathology, Azienda USL Modena, Modena, Italy

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Valentina Pecoraro Department of Laboratory Medicine and Anatomy Pathology, Azienda USL Modena, Modena, Italy

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Giulia Canu Department of Laboratory Medicine and Anatomy Pathology, Azienda USL Modena, Modena, Italy

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Manuela Simoni Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Unit of Endocrinology, Department of Medical Specialties, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy

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Giulia Brigante Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Unit of Endocrinology, Department of Medical Specialties, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy

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Objective

Many cases of subacute thyroiditis (SAT) have been described related to SARS-CoV-2 infection, but no prospective data about follow-up are known. This prospective, longitudinal, 3-year, multicentre study aims to explore the clinical peculiarities and outcome of SAT in relation to SARS-CoV-2 infection, ascertained with antibody dosage.

Methods

All patients receiving SAT diagnosis from November 2020 to May 2022 were enrolled. Data on anamnesis, physical examination, blood tests (TSH, freeT4, freeT3, thyroglobulin, anti-thyroid antibodies, C-reactive protein, erythrocyte sedimentation rate, complete blood count), and thyroid ultrasound were collected. At baseline, the presence of IgG against the SARS-CoV-2 spike protein or nucleocapsid was investigated. Patients were evaluated after 1, 3, 6, and 12 months.

Results

Sixty-six subjects were enrolled. At baseline, 54 presented with pain, 36 (67%) for at least 15 days. Serum SARS-CoV-2 IgG measurements documented that 7 out of 52 subjects (13.5%) had infection before SAT diagnosis (COVID+). No significant differences between the COVID+ and COVID− groups were found at baseline, except for respiratory symptoms and fever, which were more common in COVID+ (P = 0.039 and P = 0.021, respectively). Among the 41 subjects who completed follow-up, COVID+ and COVID− did not differ for therapeutic approach to SAT or outcome, all having an improvement in neck pain, inflammation parameters, and ultrasound features.

Conclusion

This is the first prospective study investigating any difference both at diagnosis and at follow-up between SAT presentation in patients with previous SARS-CoV-2 infection and those without. Our data demonstrate that SARS-CoV-2 does not impact on SAT onset, evolution, and outcome.

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Giulia Brigante Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Unit of Endocrinology, Department of Medical Specialties, Azienda Ospedaliero-Universitaria, Modena, Italy

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Clara Lazzaretti Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy

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Elia Paradiso Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy

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Federico Nuzzo Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy

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Martina Sitti Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy

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Frank Tüttelmann Institute of Reproductive Genetics, University of Münster, Münster, Germany

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Gabriele Moretti Department of Biology, University of Pisa, Pisa, Italy

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Roberto Silvestri Department of Biology, University of Pisa, Pisa, Italy

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Federica Gemignani Department of Biology, University of Pisa, Pisa, Italy

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Asta Försti Hopp Children’s Cancer Center (KiTZ), Heidelberg, Germany
Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany

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Kari Hemminki Biomedical Center, Faculty of Medicine and Biomedical Center in Pilsen, Charles University in Prague, Pilsen, Czech Republic
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

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Rossella Elisei Department of Endocrinology, University Hospital, Pisa, Italy

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Cristina Romei Department of Endocrinology, University Hospital, Pisa, Italy

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Eric Adriano Zizzi PolitoBIO Med Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Italy

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Marco Agostino Deriu PolitoBIO Med Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Italy

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Manuela Simoni Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Unit of Endocrinology, Department of Medical Specialties, Azienda Ospedaliero-Universitaria, Modena, Italy
Center for Genomic Research, University of Modena and Reggio Emilia, Modena, Italy

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Stefano Landi Department of Biology, University of Pisa, Pisa, Italy

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Livio Casarini Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Center for Genomic Research, University of Modena and Reggio Emilia, Modena, Italy

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To identify a peculiar genetic combination predisposing to differentiated thyroid carcinoma (DTC), we selected a set of single nucleotide polymorphisms (SNPs) associated with DTC risk, considering polygenic risk score (PRS), Bayesian statistics and a machine learning (ML) classifier to describe cases and controls in three different datasets. Dataset 1 (649 DTC, 431 controls) has been previously genotyped in a genome-wide association study (GWAS) on Italian DTC. Dataset 2 (234 DTC, 101 controls) and dataset 3 (404 DTC, 392 controls) were genotyped. Associations of 171 SNPs reported to predispose to DTC in candidate studies were extracted from the GWAS of dataset 1, followed by replication of SNPs associated with DTC risk (P < 0.05) in dataset 2. The reliability of the identified SNPs was confirmed by PRS and Bayesian statistics after merging the three datasets. SNPs were used to describe the case/control state of individuals by ML classifier. Starting from 171 SNPs associated with DTC, 15 were positive in both datasets 1 and 2. Using these markers, PRS revealed that individuals in the fifth quintile had a seven-fold increased risk of DTC than those in the first. Bayesian inference confirmed that the selected 15 SNPs differentiate cases from controls. Results were corroborated by ML, finding a maximum AUC of about 0.7. A restricted selection of only 15 DTC-associated SNPs is able to describe the inner genetic structure of Italian individuals, and ML allows a fair prediction of case or control status based solely on the individual genetic background.

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