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

Finding Achievable Features and Constraint Conflicts for Inconsistent Metamodels

Determining the consistency of a metamodel is a task of generating a metamodel instance that not only meets structural constraints but also constraints written in Object Constraint Language (OCL). Those constraints can be conflicting, resulting in inconsistencies. When this happens, the existing techniques and tools have no knowledge about which constraints are achievable and which ones cause the conflicts. In this paper, we present an approach to finding achievable metamodel features and constraint conflicts for inconsistent metamodels. This approach allows users to rank individual metamodel features and works by reducing it to a weighted maximum satisfiability modulo theories (MaxSMT). This reduction allows us to utilise SMT solvers to tackle multiple ranked constraints and at the same time locate conflicts among them. We have prototyped this approach, incorporated it into an existing modelling tool, and evaluated it against a benchmark. The preliminary results show that our approach is promising and scalable