Genome-wide association study and polygenic risk prediction of hypothyroidism.
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Rand Søren A, Ahlberg Gustav, Tragante Vinicius, Monfort Laia M, Zheng Chaoqun, Feldt-Rasmussen Ulla, Klose Marianne C, Teder-Laving Maris, Metspalu Andres, Poulsen Henrik E, Ellervik Christina, Nygaard Birte, Erikstrup Christian, Bruun Mie T, A Jensen Bitten, Ullum Henrik, Brunak Søren, DBDS Genomic Consortium, Estonian Biobank Research Team, 23andMe Research Team, Schwinn Michael, Ostrowski Sisse R, Pedersen Ole B, Sørensen Erik, Jonsdottir Ingileif, Gudbjartsson Daniel F, Thorleifsson Gudmar, Holm Hilma, Saevarsdottir Saedis, Stefansson Kari, Salling Olesen Morten, Bundgaard Henning, Ghouse Jonas
Аннотация
We performed a genome-wide meta-analysis of hypothyroidism (113,393 cases and 1,065,268 controls), free thyroxine (191,449 individuals) and thyroid-stimulating hormone (482,873 individuals). We identified 350 loci associated with hypothyroidism, including 179 not previously reported, 29 of which were linked through thyroid-stimulating hormone. We found that many hypothyroidism risk loci regulate blood cell counts and the circulating inflammasome, and through multiple gene-mapping strategies, we prioritized 259 putative causal genes enriched in immune-related functions. We developed a polygenic risk score (PRS) based on more than 115,000 hypothyroidism cases to address diagnostic challenges in individuals with or at risk of thyroid hormone deficiency. We show that the highest predictive accuracy for hypothyroidism was achieved when combining the PRS with thyroid hormones and thyroid-peroxidase autoantibodies, and that the PRS was able to stratify risk of progression among individuals with subclinical hypothyroidism. These findings demonstrate the potential for a hypothyroidism PRS to support the prediction of disease progression and onset in thyroid hormone deficiency.