Towards Personalized TSH Reference Ranges: A Genetic and Population-Based Approach in Three Independent Cohorts.

Background: Serum thyroid-stimulating hormone (TSH) measurement is the diagnostic cornerstone for primary thyroid dysfunction. There is high inter-individual but limited intra-individual variation in TSH concentrations, largely due to genetic factors. The currently used wide population-based reference intervals may lead to inappropriate management decisions. Methods: A polygenic score (PGS) including 59 genetic variants was used to calculate genetically determined TSH reference ranges in a thyroid disease-free cohort (n = 6,834). Its effect on reclassification of diagnoses was investigated when compared to using population-based reference ranges. Next, results were validated in a second independent population-based thyroid disease-free cohort (n = 3,800). Potential clinical implications were assessed in a third independent population-based cohort including individuals without thyroid disease (n = 26,321) as well as individuals on levothyroxine (LT4) treatment (n = 1,132). Results: PGS was a much stronger predictor of individual TSH concentrations than FT4 (total variance in TSH concentrations explained 9.2-11.1% vs. 2.4-2.7%, respectively) or any other nongenetic factor (total variance in TSH concentrations explained 0.2-1.8%). Genetically determined TSH reference ranges differed significantly between PGS quartiles in all cohorts, while the differences in FT4 concentrations were absent or only minor. Up to 24.7-30.1% of individuals, previously classified as having subclinical hypo- and hyperthyroidism when using population-based TSH reference ranges, were reclassified as euthyroid when genetically determined TSH reference ranges were applied. Individuals in the higher PGS quartiles had a higher probability of being prescribed LT4 treatment compared to individuals from the lower PGS quartiles (3.3% in Q1 vs. 5.2% in Q4, P_{for trend} =1.7 × 10^-8). Conclusions: Individual genetic profiles have the potential to personalize TSH reference ranges, with large effects on reclassification of diagnosis and LT4 prescriptions. As the currently used PGS can only predict approximately 10% of inter-individual variation in TSH concentrations, it should be further improved when more genetic variants determining TSH concentrations are identified in future studies.