biostudies-literatureDivaris KBundesministerium für Bildung und ForschungNIDCR NIH HHSNIEHS NIH HHSNIOSH CDC HHSNHGRI NIH HHSNational Institute of Dental and Craniofacial ResearchForskningsrådet om Hälsa, Arbetsliv och VälfärdNational Human Genome Research Institute1408-1416https://www.ebi.ac.uk/biostudies/studies/S-EPMC9516613biostudies-literatureUnknown101(11)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 (<i>N</i> = 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.Journal of dental researchPhenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium.PMC95166132017-061002017-00641R01DE014899X01HG009878X01HG00784R01 DE009551R01 OH00987801ZZ9603R01DE095512017-006442015-025972020-00930R01 DE016148U01DE025046U01 DE01890301ZZ0403R01 DE014899R01DE016148P30 ES01012601ZZ0103U01 DE025046R01 HG008978P30DE10126X01HG011437U01DE018903Sudo TLundberg PReis KMichaelsson KSun YQDivaris KJonsson DTamahara TAnttonen VMcNeil DWPalotie USchaefer ASPorteous DFuruichi YKocher TMagnusson PKESalminen AHoltfreter BShaffer JRHaworth SPussinen PJSuominen ALBeck JDLevy SMWeinberg SMMarazita MLJohansson INorth KEPapapanou PNfalsePhenotype 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 (<i>N</i> = 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.2022-01-01T00:00:00Z2022 Oct2025-04-25T21:25:14.469Z2025-04-06T08:43:30.404ZS-EPMC95166133600080010.1177/00220345221109775