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Updated: Jan 10, 2026

Generation of a Mouse Spontaneous Autoimmune Thyroiditis Model
Published on: March 17, 2023
Variation spectra in mild isolated hyperthyrotropinemia: pilot cohort and systematic review
Valentina Ricci1, María E Masnata1, María D Villanueva Gonzalez1
1Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE) CONICET - FEI - División de Endocrinología, Hospital de Niños Ricardo Gutiérrez (HNRG), Buenos Aires, Argentina.
Background:
Lower thyrotropin (TSH) cutoffs for Congenital Hypothyroidism (CH) during the neonatal period and childhood have led to increased detection of Mild Isolated Hyperthyrotropinemia (MIH) or Subclinical Hypothyroidism; however, genetic testing has been limited in this setting. We aimed to evaluate the contribution and molecular spectrum of genetic variants in MIH.
Methods:
Ten patients underwent targeted Next-Generation Sequencing (NGS). Data was analyzed for Single Nucleotide Variants (SNVs), short insertions/deletions, noncanonical splice site (NCSS) variants, and Copy Number Variants (CNVs) in 13 candidate genes associated with thyroid dyshormonogenesis and isolated thyroid hypoplasia. To provide an expanded view of the genes and variants associated with MIH, we performed a Systematic Review (SR) and variant reclassification.
Results:
Eight monoallelic SNVs affecting 4 genes were identified in 5 subjects. A potential digenic or pseudo-digenic inheritance was identified in 3 infants. One novel variant was found in the TG gene. Genetic diagnosis, established based on the inheritance pattern, zygosity, pathogenicity of the variant, and genotype-phenotype correlation, was highly suggested in 4 patients. Through SR, we created a valuable database resource of 122 unique reclassified SNVs comprising 173 patients.
Conclusion:
Results provide further evidence for the elucidation of the genetic etiology of MIH and expand the phenotypic and variant spectrum of CH. Future, more extensive prospective studies are needed to investigate the utility of NGS in guiding treatment decisions and predicting prognosis for MIH patients.
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