Thyroid cancer is the most common endocrine malignancy, yet its biological underpinnings remain incompletely understood. We conducted a multi-ancestry genome-wide association study meta-analysis of thyroid cancer (16,167 cases and 2,430,374 controls), identifying 51 independent loci, including 21 novel signals. We analyzed the associations of thyroid cancer risk alleles with 151 other thyroid-cancer-related traits. These pleiotropic relationships reveal mechanistic clusters linked to thyroid function, oncogenic pathways, and mixed physiological function. Two thyroid-specific clusters associated with thyroid stimulating hormone, influencing thyroid growth and function and were enriched in thyroid tissues. Oncogenic clusters included DNA repair (ATM, CHEK2, TP53) and telomere maintenance (TERT) genes, implicating shared cancer mechanisms. Cluster-specific polygenic scores were associated with thyroid disease, cancer, and metabolic traits across ancestry groups, suggesting distinct genetic subtypes of thyroid cancer risk. These results demonstrate the utility of pleiotropy-based approaches in uncovering thyroid cancer mechanisms and advancing genetically informed risk stratification.

B.R.H. has received research funding from Veracyte to perform a study on transcriptomics of thyroid tumors.

This work was supported in part by the Intramural Research Program of the National Cancer Institute, US National Institutes of Health (NIH). This work was supported by a stipend from the PhD Program in Population Health Sciences at Harvard University.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This study protocol was approved by the Institutional Review Board of the Severance Hospital (approval number: 4-2011-0277).

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The meta-analysis GWAS summary statistics will be made publicly available prior to publication. Data sources for other publicly available GWAS summary statistics are available in Supplementary Table 4.