Literature DB >> 32031351

Sources of bias in genomics research of oral and dental traits.

C S Agler1, K Divaris1.   

Abstract

Evidence regarding the genomic basis of oral/dental traits and diseases is a fundamental pillar of the emerging notion of precision health. During the last decade, technological advances have improved the feasibility and affordability of conducting genome-wide association studies (GWAS) and studying the associations of emanating data with both common and rare oral conditions. Most evidence thus far emanates from GWAS of dental caries and periodontal disease that have tested the associations of several million single nucleotide polymorphisms (SNPs) with typically binary, health vs. disease phenotypes. GWAS offer advantages over the previous candidate-gene studies, mainly owing to their agnostic (i.e., unbiased, or hypothesis-free) nature. Nevertheless, GWAS are prone to virtually all sources of random and systematic error. Here, we review common sources of bias in genomics research with focus on GWAS including: type I and II errors, population stratification and heterogeneity, selection bias, adjustment for heritable covariates, appropriate reference panels for imputation, and gene annotation. We argue that valid and precise phenotype measurement is a key requirement, as GWAS sample sizes and thus statistical power increase. Finally, we stress that the lack of diversity of populations with phenotypes and genotypes is a major limitation for the generalizability and ultimate translation of the emerging genomics evidence-base into oral health promotion for all. Copyright
© 2020 Dennis Barber Ltd.

Entities:  

Keywords:  bias; dental caries; genetic epidemiology; genome-wide association studies; periodontitis

Mesh:

Year:  2020        PMID: 32031351      PMCID: PMC7316399          DOI: 10.1922/CDH_SpecialIssue_Divaris05

Source DB:  PubMed          Journal:  Community Dent Health        ISSN: 0265-539X            Impact factor:   1.349


  25 in total

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Review 3.  Curses--winner's and otherwise--in genetic epidemiology.

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Review 4.  Prioritizing GWAS results: A review of statistical methods and recommendations for their application.

Authors:  Rita M Cantor; Kenneth Lange; Janet S Sinsheimer
Journal:  Am J Hum Genet       Date:  2010-01       Impact factor: 11.025

Review 5.  Meta-analysis of genetic association studies: methodologies, between-study heterogeneity and winner's curse.

Authors:  Hirofumi Nakaoka; Ituro Inoue
Journal:  J Hum Genet       Date:  2009-10-23       Impact factor: 3.172

6.  Adjusting for heritable covariates can bias effect estimates in genome-wide association studies.

Authors:  Hugues Aschard; Bjarni J Vilhjálmsson; Amit D Joshi; Alkes L Price; Peter Kraft
Journal:  Am J Hum Genet       Date:  2015-01-29       Impact factor: 11.025

7.  Genomics is failing on diversity.

Authors:  Alice B Popejoy; Stephanie M Fullerton
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8.  Distinguishing true from false positives in genomic studies: p values.

Authors:  Linda Broer; Christina M Lill; Maaike Schuur; Najaf Amin; Johannes T Roehr; Lars Bertram; John P A Ioannidis; Cornelia M van Duijn
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9.  Fundamentals of Precision Medicine.

Authors:  Kimon Divaris
Journal:  Compend Contin Educ Dent       Date:  2017-09

10.  Quantifying and correcting for the winner's curse in genetic association studies.

Authors:  Rui Xiao; Michael Boehnke
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  2 in total

1.  Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium.

Authors:  K Divaris; S Haworth; J R Shaffer; V Anttonen; J D Beck; Y Furuichi; B Holtfreter; D Jönsson; T Kocher; S M Levy; P K E Magnusson; D W McNeil; K Michaëlsson; K E North; U Palotie; P N Papapanou; P J Pussinen; D Porteous; K Reis; A Salminen; A S Schaefer; T Sudo; Y Q Sun; A L Suominen; T Tamahara; S M Weinberg; P Lundberg; M L Marazita; I Johansson
Journal:  J Dent Res       Date:  2022-08-24       Impact factor: 8.924

2.  Cohort Profile: ZOE 2.0-A Community-Based Genetic Epidemiologic Study of Early Childhood Oral Health.

Authors:  Kimon Divaris; Gary D Slade; Andrea G Ferreira Zandona; John S Preisser; Jeannie Ginnis; Miguel A Simancas-Pallares; Cary S Agler; Poojan Shrestha; Deepti S Karhade; Apoena de Aguiar Ribeiro; Hunyong Cho; Yu Gu; Beau D Meyer; Ashwini R Joshi; M Andrea Azcarate-Peril; Patricia V Basta; Di Wu; Kari E North
Journal:  Int J Environ Res Public Health       Date:  2020-11-01       Impact factor: 3.390

  2 in total

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