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Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium

Divaris, K. ; Haworth, S. ; Shaffer, J. R. ; Anttonen, V. ; Beck, J. D. ; Furuichi, Y. ; Holtfreter, B. ; Jönsson, D. LU ; Kocher, T. and Levy, S. M. , et al. (2022) In Journal of Dental Research 101(11). p.1408-1416
Abstract

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... (More)

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.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
data sciences, dental caries, dentition, permanent, epidemiology, Genetics, genome-wide association study
in
Journal of Dental Research
volume
101
issue
11
pages
1408 - 1416
publisher
International & American Associations for Dental Research
external identifiers
  • pmid:36000800
  • scopus:85137232298
ISSN
0022-0345
DOI
10.1177/00220345221109775
language
English
LU publication?
yes
id
a8b5d806-8324-45fd-824f-bc5b1ab7fe20
date added to LUP
2022-11-17 15:26:48
date last changed
2024-05-16 11:20:36
@article{a8b5d806-8324-45fd-824f-bc5b1ab7fe20,
  abstract     = {{<p>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.</p>}},
  author       = {{Divaris, K. and Haworth, S. and Shaffer, J. R. and Anttonen, V. and Beck, J. D. and Furuichi, Y. and Holtfreter, B. and Jönsson, D. and Kocher, T. and Levy, S. M. and Magnusson, P. K.E. and McNeil, D. W. and Michaëlsson, K. and North, K. E. and Palotie, U. and Papapanou, P. N. and Pussinen, P. J. and Porteous, D. and Reis, K. and Salminen, A. and Schaefer, A. S. and Sudo, T. and Sun, Y. Q. and Suominen, A. L. and Tamahara, T. and Weinberg, S. M. and Lundberg, P. and Marazita, M. L. and Johansson, I.}},
  issn         = {{0022-0345}},
  keywords     = {{data sciences; dental caries; dentition, permanent; epidemiology; Genetics; genome-wide association study}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{1408--1416}},
  publisher    = {{International & American Associations for Dental Research}},
  series       = {{Journal of Dental Research}},
  title        = {{Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium}},
  url          = {{http://dx.doi.org/10.1177/00220345221109775}},
  doi          = {{10.1177/00220345221109775}},
  volume       = {{101}},
  year         = {{2022}},
}