New insights into the hypothalamic-pituitary-thyroid axis: a transcriptome- and proteome-wide association study.

Introduction: Thyroid hormones have systemic effects on the human body and play a key role in the development and function of virtually all tissues. They are regulated via the hypothalamic-pituitary-thyroid (HPT) axis and have a heritable component. Using genetic information, we applied tissue-specific transcriptome-wide association studies (TWAS) and plasma proteome-wide association studies (PWAS) to elucidate gene products related to thyrotropin (TSH) and free thyroxine (FT4) levels. Results: TWAS identified 297 and 113 transcripts associated with TSH and FT4 levels, respectively (25 shared), including transcripts not identified by genome-wide association studies (GWAS) of these traits, demonstrating the increased power of this approach. Testing for genetic colocalization revealed a shared genetic basis of 158 transcripts with TSH and 45 transcripts with FT4, including independent, FT4-associated genetic signals within the CAPZB locus that were differentially associated with CAPZB expression in different tissues. PWAS identified 18 and ten proteins associated with TSH and FT4, respectively (HEXIM1 and QSOX2 with both). Among these, the cognate genes of five TSH- and 7 FT4-associated proteins mapped outside significant GWAS loci. Colocalization was observed for five plasma proteins each with TSH and FT4. There were ten TSH and one FT4-related gene(s) significant in both TWAS and PWAS. Of these, ANXA5 expression and plasma annexin A5 levels were inversely associated with TSH (PWAS: P = 1.18 × 10-13, TWAS: P = 7.61 × 10-12 (whole blood), P = 6.40 × 10-13 (hypothalamus), P = 1.57 × 10-15 (pituitary), P = 4.27 × 10-15 (thyroid)), supported by colocalizations. Conclusion: Our analyses revealed new thyroid function-associated genes and prioritized candidates in known GWAS loci, contributing to a better understanding of transcriptional regulation and protein levels relevant to thyroid function.

The role of thyroid function in borderline personality disorder and schizophrenia: a Mendelian Randomisation study.

BACKGROUND: Genome-wide association studies have reported a genetic overlap between borderline personality disorder (BPD) and schizophrenia (SCZ). Epidemiologically, the direction and causality of the association between thyroid function and risk of BPD and SCZ are unclear. We aim to test whether genetically predicted variations in TSH and FT4 levels or hypothyroidism are associated with the risk of BPD and SCZ. METHODS: We employed Mendelian Randomisation (MR) analyses using genetic instruments associated with TSH and FT4 levels as well as hypothyroidism to examine the effects of genetically predicted thyroid function on BPD and SCZ risk. Bidirectional MR analyses were employed to investigate a potential reverse causal association. RESULTS: Genetically predicted higher FT4 was not associated with the risk of BPD (OR: 1.18; P = 0.60, IVW) or the risk of SCZ (OR: 0.93; P = 0.19, IVW). Genetically predicted higher TSH was not associated with the risk of BPD (OR: 1.11; P = 0.51, IVW) or SCZ (OR: 0.98, P = 0.55, IVW). Genetically predicted hypothyroidism was not associated with BPD or SCZ. We found no evidence for a reverse causal effect between BPD or SCZ on thyroid function. CONCLUSIONS: We report evidence for a null association between genetically predicted FT4, TSH or hypothyroidism with BPD or SCZ risk. There was no evidence for reverse causality.

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, Pfor 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.

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications.

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.