Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium

Genetic risk factors play important roles in the etiology of oral, dental, and craniofacial diseases. Identifying the relevant risk loci and understanding their molecular biology could highlight new prevention and management avenues. Our current understanding of oral health genomics suggests that dental caries and periodontitis are polygenic diseases, and very large sample sizes and informative phenotypic measures are required to discover signals and adequately map associations across the human genome. In this article, we introduce the second wave of the Gene-Lifestyle Interactions and Dental Endpoints consortium (GLIDE2) and discuss relevant data analytics challenges, opportunities, and applications. In this phase, the consortium comprises a diverse, multiethnic sample of over 700,000 participants from 21 studies contributing clinical data on dental caries experience and periodontitis. We outline the methodological challenges of combining data from heterogeneous populations, as well as the data reduction problem in resolving detailed clinical examination records into tractable phenotypes, and describe a strategy that addresses this. Specifically, we propose a 3-tiered phenotyping approach aimed at leveraging both the large sample size in the consortium and the detailed clinical information available in some studies, wherein binary, severity-encompassing, and "precision," data-driven clinical traits are employed. As an illustration of the use of data-driven traits across multiple cohorts, we present an application of dental caries experience data harmonization in 8 participating studies (N = 55,143) using previously developed permanent dentition tooth surface-level dental caries pattern traits. We demonstrate that these clinical patterns are transferable across multiple cohorts, have similar relative contributions within each study, and thus are prime targets for genetic interrogation in the expanded and diverse multiethnic sample of GLIDE2. We anticipate that results from GLIDE2 will decisively advance the knowledge base of mechanisms at play in oral, dental, and craniofacial health and disease and further catalyze international collaboration and data and resource sharing in genomics research.Peer reviewe

Evidence of a causal effect of genetic tendency to gain muscle mass on uterine leiomyomata

Uterine leiomyomata (UL) are the most common tumours of the female genital tract and the primary cause of surgical removal of the uterus. Genetic factors contribute to UL susceptibility. To add understanding to the heritable genetic risk factors, we conduct a genome-wide association study (GWAS) of UL in up to 426,558 European women from FinnGen and a previous UL meta-GWAS. In addition to the 50 known UL loci, we identify 22 loci that have not been associated with UL in prior studies. UL-associated loci harbour genes enriched for development, growth, and cellular senescence. Of particular interest are the smooth muscle cell differentiation and proliferation-regulating genes functioning on the myocardin-cyclin dependent kinase inhibitor 1A pathway. Our results further suggest that genetic predisposition to increased fat-free mass may be causally related to higher UL risk, underscoring the involvement of altered muscle tissue biology in UL pathophysiology. Overall, our findings add to the understanding of the genetic pathways underlying UL, which may aid in developing novel therapeutics.Peer reviewe