Hypothyroidism is a prevalent endocrine disorder characterized by insufficient thyroid hormone (T3T4) production. Thyroglobulin (Tg) serves as the prohormone for T3 and T4 production, with many variants of uncertain clinical significance due to genetic diversity in the Tg gene. We leveraged the large-scale All of Us biobank to investigate the disease association of prevalent yet undercharacterized Tg variants. We related variant presence to thyroid-stimulating hormone levels and levothyroxine (LT4) usage as proxies for thyroid function. This identified R152H, Q870H, A993T, P1012L, and P1494L variants linked to increased LT4 usage and decreased thyroid function, while the R320C variant was associated with decreased thyroid function. Molecular characterization in Fisher rat thyroid cells revealed decreased secretion efficiency of R152H, Q870H, and R320C variants. Affinity purification-mass spectrometry demonstrated that secretion-deficient variants showed higher engagement with the protein homeostasis network, indicating protein quality control defects as the pathophysiology mechanism. In contrast, secretion-competent A993T and P1494L variants showed elevated interactions with degradation and antigen-presentation pathways, suggesting an alternative pathophysiology possibly linked to Hashimoto's disease, an autoimmune condition with overproduction of autoantibodies that target thyroid proteins. In support, participants carrying the A993T or P1494L variants had elevated anti-TPO antibody levels. We estimate ~150,000 US individuals currently taking levothyroxine could benefit from precision medicine targeting these variants, with ~100,000 carrying Q870H. Our findings highlight the power of combining large public biobank data with molecular characterization to understand Tg genotype-to-phenotype relationships. Q870H represents a candidate for molecular therapies to restore secretion, offering precision medicine beyond LT4 replacement therapy.
Public Cohort Analysis Identifies Thyroglobulin Variants as Hypothyroidism Risk Factors.
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作者:Hermanson Jake N, Hudson Andrew D, Plate Lars
| 期刊: | bioRxiv | 影响因子: | 0.000 |
| 时间: | 2025 | 起止号: | 2025 Nov 24 |
| doi: | 10.1101/2025.11.21.689591 | ||
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