Consortium-based genome-wide meta-analysis for childhood dental caries traits

ASSOCIATION STUDIES ARTICLE Consortium-based genome-wide meta-analysis for childhood dental caries traits Simon Haworth 1, * ,† , Dmitry Shungin 2,3,† , Justin T. van der Tas 4 , Strahinja Vucic 4 , Carolina Medina-Gomez 5,6,7 , Victor Yakimov 8 , Bjarke Feenstra 8 , John R. Shaffer 9,10 , Myoung Keun Lee 10 , Marie Standl 11 , Elisabeth Thiering 11,12 , Carol Wang 13 , Klaus Bønnelykke 14 , Johannes Waage 14 , Leon Eyrich Jessen 14 , Pia Elisabeth Nørrisgaard 14 , Raimo Joro 15 , Ilkka Seppa¨la¨ 16 , Olli Raitakari 17,18 , Tom Dudding 1 , Olja Grgic 4,5 , Edwin Ongkosuwito 5 , Anu Vierola 15 , Aino-Maija Eloranta 15 , Nicola X. West 19 , Steven J. Thomas 19 , Daniel W. McNeil 20 , Steven M. Levy 21 , Rebecca Slayton 22 , Ellen A. Nohr 23 , Terho Lehtima¨ki 16 , Timo Lakka 15,24,25 , Hans Bisgaard 14 , Craig Pennell 13 , Jan Ku¨ hnisch 26 , Mary L. Marazita 9,10 , Mads Melbye 8,27,28 , Frank Geller 8 , Fernando Rivadeneira 5,6,7 , Eppo B. Wolvius 4 , Paul W. Franks 29,30,31 , Ingegerd Johansson 2 and Nicholas J. Timpson 1 1 Medical Research Council Integrative Epidemiology Unit at Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK, 2 Department of Odontology, Umea˚ University, Umea˚ 901 87, Sweden, 3 Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA, 4 Department of Oral and Maxillofacial Surgery, Special Dental Care and Orthodontics, 5 The Generation R Study Group, 6 Department of Internal Medicine, 7 Department of Epidemiology, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam 3015 CN, The Netherlands, 8 Department of Epidemiology Research, Statens Serum Institut, Copenhagen DK-2300, Denmark, 9 Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA, 10 Center for Craniofacial and Dental Genetics, Department of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA, 11 Institute of Epidemiology I, Helmholtz Zentrum Mu¨ nchen - German Research Center for Environmental Health, Neuherberg D-85764, Germany, 12 Division of Metabolic and Nutritional Medicine, Dr von Hauner Children’s Hospital, University of Munich Medical Center, Munich 80337, Germany, 13 Division of Obstetrics and Gynaecology, The University of Western Australia, Perth WA 6009, Australia, 14 COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofe Hospital, University of Copenhagen, Copenhagen 2730, Denmark, 15 Institute of Biomedicine, School of Medicine, University of Eastern Finland † The authors wish it to be known that, in their opinion, the first 2 authors should be regarded as joint First Authors. Received: March 1, 2018. Revised: May 29, 2018. Accepted: June 14, 2018 V CThe Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. 3113 doi: 10.1093/hmg/ddy237 Advance Access Publication Date: 20 June 2018 Association Studies Article Human Molecular Genetics, 2018, Vol. 27, No. 17 3113–3127 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018 Kuopio Campus, 70211 Kuopio, Finland, 16 Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere - Faculty of Medicine and Life Sciences, University of Tampere, Tampere 33520, Finland, 17 Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland, 18 Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland, 19 Bristol Dental School, University of Bristol, Bristol BS1 2LY, UK, 20 Department of Psychology, Eberly College of Arts and Sciences, West Virginia University, Morgantown, WA 26506-6286, USA, 21 Department of Preventive and Community Dentistry, College of Dentistry, University of Iowa, Cedar Rapids, IA 52242-1010, USA, 22 Department of Pediatric Dentistry (Retired), School of Dentistry, University of Washington, Seattle, WA 98195, USA, 23 Research Unit for Gynaecology and Obstetrics, Department of Clinical Research, University of Southern Denmark, Odense 5000, Denmark, 24 Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio 70210, Finland, 25 Kuopio Research Institute of Exercise Medicine, Kuopio 70100, Finland, 26 Department of Conservative Dentistry and Periodontology, University Hospital, Ludwig-Maximilians-Universita¨tMu¨ nchen, Munich 80336, Germany, 27 Department of Clinical Medicine, University of Copenhagen, Copenhagen 2200, Denmark, 28 Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, 29 Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmo¨ 202 13, Sweden, 30 Department of Public Health and Clinical Medicine, Umea˚ University, Umea˚ 901 85, Sweden and 31 Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA *To whom correspondence should be addressed at: MRC Integrative Epidemiology Unit, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK. Tel: þ44 (0) 1173310083; Fax: þ44 (0) 1179287325; Email: [email protected] Abstract Prior studies suggest dental caries traits in children and adolescents are partially heritable, but there has been no large-scale consortium genome-wide association study (GWAS) to date. We therefore performed GWAS for caries in participants aged 2.5–18.0 years from nine contributing centres. Phenotype definitions were created for the presence or absence of treated or untreated caries, stratified by primary and permanent dentition. All studies tested for association between caries and genotype dosage and the results were combined using fixed-effects meta-analysis. Analysis included up to 19 003 individuals (7530 affected) for primary teeth and 13 353 individuals (5875 affected) for permanent teeth. Evidence for association with caries status was observed at rs1594318-C for primary teeth [intronic within ALLC, odds ratio (OR) 0.85, effect allele frequency (EAF) 0.60, P4.13e-8] and rs7738851-A (intronic within NEDD9, OR 1.28, EAF 0.85, P1.63e-8) for permanent teeth. Consortiumwide estimated heritability of caries was low [h 2 of 1% (95% CI: 0%: 7%) and 6% (95% CI 0%: 13%) for primary and permanent dentitions, respectively] compared with corresponding within-study estimates [h 2 of 28% (95% CI: 9%: 48%) and 17% (95% CI: 2%: 31%)] or previously published estimates. This study was designed to identify common genetic variants with modest effects which are consistent across different populations. We found few single variants associated with caries status under these assumptions. Phenotypic heterogeneity between cohorts and limited statistical power will have contributed; these findings could also reflect complexity not captured by our study design, such as genetic effects which are conditional on environmental exposure. Introduction Dental caries remains a prevalent public health problem in both children and adults. Untreated dental caries was estimated to affect 621 million children worldwide in 2010, with little change in prevalence or incidence between 1990 and 2010 (1). This problem is not unique to lower income countries; around 50% of children have evidence of caries by age 5 in industrialized nations (2–4). Dental caries results from reduced mineral saturation of fluids surrounding teeth, driven by ecological shifts in the oral microbiome (5). Many different factors predispose toward dental caries, of which high sugar consumption, poor oral hygiene and low socio-economic status are the most notorious (6–8). Over the last decades there has been increasing appreciation for the role of genetic influences in dental caries. The importance of genetic susceptibility for dental caries experience was demonstrated in an animal model over 50 years ago, a finding since substantiated in twin studies in humans (9–11). Of particular relevance to caries traits in children and adolescents, Bretz et al. (10) analysed longitudinal rates of change in caries status in children, and found that caries progression and severity were highly heritable in the primary and permanent dentition. It has also been suggested that heritability for dental caries does not depend entirely on genetic predisposition to sweet food consumption (12). Despite evidence of a genetic contribution to caries susceptibility, few specific genetic loci have been identified. Shaffer et al. (13) performed the first GWAS for dental caries in 2011, studying the primary dentition of 1305 children. They found evidence for association at novel and previously studied candidate genes (ACTN2, MTR, EDARADD, MPPED2 and LPO), but 3114 |Human Molecular Genetics, 2018, Vol. 27, No. 17 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018 no individual single-nucleotide polymorphisms (SNPs) exceeded the genome-wide significance threshold (P5.0e-08), possibly as a consequence of the modest sample size (13). The first GWAS for dental caries in the permanent dentition in adults was performed at a similar time by Wang et al. (14). They included 7443 adults from five different cohorts and identified several suggestive loci (P-value 10e-05) for dental caries (RPS6KA2,PTK2B,RHOU,FZD1,ADMTS3 and ISL1), different loci from those mentioned above for the primary dentition and again with no single variants reaching genome-wide significance. The next wave of GWAS of caries suggested association at a range of different loci. Two GWAS used separate phenotype definitions for pit-and-fissure and smooth tooth surfaces and identified different loci associated with dental caries susceptibility in both primary and permanent dentition (15,16). The GWAS in primary dentition used a sample of approximately 1000 children and found evidence for association at loci reported in previous studies, including MPPED2,RPS6KA2 and AJAP1 (13–16). The largest GWAS for dental caries in permanent dentition was performed in a Hispanic and Latino sample of 11754 adults (17). This study identified unique genetic loci (NAMPT and BMP7) compared with previous GWAS in individuals of European ancestry. To date, it is unclear whether the variability in nominated loci reflects true variability in the genetic architecture of dental caries across different populations, age periods and sub-phenotypic definitions, or merely represent chance differences between studies given the modest power in the studies performed to date. Dental caries is a complex and multifactorial disease, caused by a complex interplay between environmental, behavioural and genetic factors. Until now there has been a lack of largescale studies of dental caries traits in children and the genetic basis of these traits remains poorly characterized. This investigation set out to examine the hypothesis that common genetic variants influence dental caries with modest effects on susceptibility. We anticipated that (a) caries in both primary and permanent teeth would be heritable in children and adolescents aged 2.5–18 years and (b) common genetic variants are likely to only have small effects on the susceptibility of a complex disease such as dental caries. Therefore, the aim of this largescale, consortium-based GWAS is to examine novel genetic loci associated with dental caries in primary and permanent dentition in children and adolescents. Results Single variant results Meta-analysis of caries in primary teeth in individuals of European ancestry included 17 037 individuals (6922 affected) from 22 results files representing all nine coordinating centres. After final quality control (QC), this meta-analysis included 8 640 819 variants, with mild deflation (genomic inflation factor, k¼0.994) (Supplementary Material, Fig. S1). Meta-analysis of caries in primary teeth which included individuals of multiple ethnicities in the Generation R (GENR) study included 19 003 individuals (7530 affected) from 22 results files representing all 9 coordinating centres. There were 8 699 928 variants after final QC, with mild deflation in summary statistics (k¼0.986) (Supplementary Material, Fig. S2). Analysis of caries status in permanent teeth included 13 353 individuals (5875 affected) from 14 results files representing 7 coordinating centres. The sample size was smaller for permanent teeth as two coordinating centres did not have phenotype data for permanent teeth (RAINE and GENR), whilst the COPSAC group only had data for participants in the earlier birth cohort (COPSAC 2000). There were 8 734 121 variants after final QC, with mild deflation in summary statistics (k¼0.999) (Supplementary Material, Fig. S3). The strongest evidence for association with caries in primary teeth was seen at rs1594318 [odds ratio (OR) 0.85 for C allele, EAF 0.60, P¼4.13e-08] in the European ancestry metaanalysis (Figs 1, 2 and 3,Table 1). This variant is intronic within ALLC on 2p25, a locus which has not previously been reported for dental caries traits. In the meta-analysis combining individuals of all ancestries this variant no longer reached genomewide significance, although suggestive evidence persisted at rs1594318 (OR 0.868 for C allele EAF 0.60, P¼3.78e-07) and other intronic variants within ALLC in high linkage disequilibrium (LD) (Fig. 3). For the permanent dentition the strongest statistical evidence for association was seen between caries status and rs7738851 (OR 1.28 for A allele, EAF 0.85, P¼1.63e-08) (Figs 1, 2 and 4,Table 1). This variant is intronic within NEDD9 on 6p24. Estimated heritability Using participant level data in ALSPAC heritability was estimated at 0.28 (95% CI 0.09: 0.48) and 0.17 (95% CI 0.02: 0.31) for primary and permanent teeth, respectively. Using summary statistics at the meta-analysis level produced point estimates near zero heritability, with wide confidence intervals (Table 2). Cross-phenotype comparisons Genome-wide mean chi-squared was too low to undertake genome-wide genetic correlation using the linkage disequilibrium score regression (LDSR) method for caries in either primary or permanent teeth. Hypothesis-free phenome-wide lookup for rs1594318 included 885 GWAS where either rs1594318 or a proxy with r 2 >0.8 was present. None of these traits showed evidence of association with rs1594318 at a Bonferroni-corrected alpha of 0.05. Lookup of rs7738851 and its proxies was performed against 662 traits, where similarly no traits reached a Bonferronicorrected threshold. Hypothesis-driven lookup in adult caries traits revealed no strong evidence for persistent genetic effects into adulthood (Table 3). Gene prioritization, gene set enrichment and association with predicted gene transcription Gene-based tests identified association between caries status in the primary dentition and a region of 7q35 containing TCAF1, OR2F2 and OR2F1 (P¼1.91e-06, 1.58e-06 and 1.29e-06, respectively). There were insufficient independently associated loci to perform gene set enrichment analysis using DEPICT for either of the principal meta-analyses. Association with predicted gene transcription was tested but no genes met the threshold for association after accounting for multiple testing. The single greatest evidence for association was seen between increased predicted transcription of CDK5RAP3 and increased liability for permanent caries (P¼3.94e-05). CDK5RAP3 is known to interact with PAK4 and p14 ARF , with a potential role in oncogenesis (18,19). Discussion Dental caries in children and adolescents has not been studied to date using a large-scale, consortium-based genome-wide 3115| Human Molecular Genetics, 2018, Vol. 27, No. 17 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018 meta-analysis approach. Based on previous knowledge of the heritability of caries in young populations and from our understanding of other complex diseases, we anticipated that common genetic variants would be associated with dental caries risk with consistent effects across different cohorts. We found evidence for association between rs1594318 and caries in primary teeth. This variant showed weaker evidence for association in the multi-ethnic meta-analysis, potentially relating to Figure 1. Manhattan plots for each principal meta-analysis. (A) Caries in primary teeth (European ancestry), nsamples ¼17 036, nvariants ¼8 640 819, k¼0.9944. Variants within 500Kb of rs1594318 are highlighted in green. (B) Caries in primary teeth (multi-ethnic analysis), nsamples ¼19 003, nvariants ¼8 699 928, k¼0.9861. (C) Caries in permanent teeth (European ancestry), nsamples ¼13 353, nvariants ¼8 734 121, k¼0.9991. Variants within 500Kb of rs7738851 are highlighted in green. 3116 |Human Molecular Genetics, 2018, Vol. 27, No. 17 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018 different allele frequencies across the different ethnic groups included in analysis. Frequency of the G allele is reported to vary between 0.24 in Asian populations and 0.42 in populations of European ancestry based on 1KGP allele frequencies. ALLC (Allantoicase) codes the enzyme allantoicase, which is involved in purine metabolism and whose enzymatic activity is believed to have been lost during vertebrate evolution. Mouse studies suggest that this loss of activity relates to low expression levels and low substrate affinity rather than total non-functionality (20). Although there is some evidence that ALLC polymorphisms are associated with response to asthma treatment (21), there is limited understanding of the implications of variation in ALLC for human health, and it is possible that rs1594318 tags functionality elsewhere in the same locus. For permanent teeth, we found evidence for association between caries status and rs7738851, an intronic variant with NEDD9 (neural precursor cell-expressed, developmentally down-regulard gene 9). NEDD9 is reported to mediate integrininitiated signal transduction pathways and is conserved from gnathostomes into mammals (22,23). NEDD9 appears to play a number of functional roles in disease and normal development, including regulation of neuronal differentiation, development and migration (22,24–28). One such function involves regulation of neural crest cell migration (26). Disruption of neural crest signalling is known to lead to enamel and dentin defectsinanimalmodels(29,30) and might provide a mechanism for variation at rs7738851 to influence dental caries susceptibility. Traditionally, risk assessment for dental caries in childhood has concentrated on dietary behaviours and other modifiable risk factors (31), with little focus on tooth quality. Although our understanding of the genetic risk factors for dental caries is incomplete, authors have noted that the evidence from previous genetic association studies tends to support a role for innate tooth structure and quality in risk of caries (32,33). If validated by future studies, the association with rs7738851 would provide further evidence for this argument, and may in the future enhance risk assessment in clinical practice. Figure 2. Regional association plots. (A) Regional association plot for rs1594318 and caries in primary teeth (European ancestry meta-analysis). (B) Regional association plot for rs7738851 and caries in permanent teeth. 3117| Human Molecular Genetics, 2018, Vol. 27, No. 17 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018 The lookup of lead associated variants against adult caries traits provided no strong evidence for persistent association in adulthood. This might imply genetic effects which are specific to the near-eruption timepoint. An alternative explanation is that the variants identified in the present study represent false positive signals as the statistical evidence presented is not irrefutable and there is no formal replication stage in our study; yet, we see good consistency of effects across studies. The meta-analysis heritability estimates were lower than anticipated from either previous within-study heritability estimates (34) or the new within-study heritability estimates obtained for this analysis. There are several possible explanations for this phenomenon. First, the methods used in the present analysis are SNP based which consistently underestimate heritability of complex traits relative to twin and family studies (35). Second, meta-analysis heritability represents the heritability of genetic effects which are consistent across populations. In the event of genuine differences in genetic architecture of dental caries across strata of age, geography, environmental exposure or subtly different phenotypic meanings, the metaheritability estimate is not the same conceptually as the weighted average of heritability within each study. More intuitively, genetic influences might be important within populations with relatively similar environments but not determine much of the overall differences in risk when comparing groups of people in markedly different environments. This view is consistent with existing literature from family based and candidate gene association studies suggesting the genetic Figure 3. Forest plot for rs1594318 and caries in primary teeth. Effect sizes are expressed on a log OR scale, grouped by geographical location. The summary estimate is from the fixed-effect meta-analysis of participants of European ancestry. 3118 |Human Molecular Genetics, 2018, Vol. 27, No. 17 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018 architecture of dental caries is complex with multiple interactions. For example, gene–sex interactions are reported which change in magnitude between the primary and permanent dentition (36), genetic variants may have heterogeneous effects on the primary and permanent dentition (37) and environmental exposures such as fluoride may interact with genetic effects (38). Finally, the aetiological relevance of specific microbiome groups appears to vary between different populations (39), suggesting genetic effects acting through the oral microbiome might also vary between populations. Unfortunately, this study lacks statistical power to perform meta-analyses stratified on these exposures, so does not resolve this particular question. In line with any consortium-based approach, the need to harmonize analysis across different collections led to some compromises. The phenotypic definitions used in this study do not contain information on disease extent or severity. Loss of information in creating these definitions may have contributed to the low statistical power of analysis. Our motivation for using simple definitions was based on the facts that (a) case-control status simply represents a threshold level of an underlying continuum of disease risk, (b) simple binary classifications facilitate comparison of studies with different assessment protocols and population risks and (c) simple classifications have been used successfully in a range of complex phenotypes. Between participating centres there are differences in characteristics such as age at participation, phenotypic assessment and differences in the environment (such as nutrition, oral hygiene and the oral microbiome) which might influence dental Figure 4. Forest plot for rs7738851 and caries in permanent teeth. Effect sizes are expressed on a log OR scale, grouped by geographical location. The summary estimate is from fixed-effect meta-analysis. 3119| Human Molecular Genetics, 2018, Vol. 27, No. 17 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018 caries or its treatment, as reflected in the wide range of caries prevalence between different study centres. Varying phenotypic characteristics do not necessarily result in heterogeneous genetic effects, as this variability may be uncorrelated with genetic effects. There was little evidence for heterogeneity in the top associated loci reported, however, the test for heterogeneity in genetic effects (I 2 ) is limited by the small number of participating studies in meta-analysis (40) and wide confidence intervals for within-study genetic effect estimates. Given these limitations, it is possible that heterogeneity contributed to low study power and prevented more comprehensive single variant findings. In the ALSPAC study we made extensive use of questionnaire derived data. This will systematically under-report true Table 1. Lead associated single variants Phenotype Variant Position Effect allele Other allele EAF Beta (SE) Odds ratio P-value NI 2 P-value for heterogeneity Annotation Caries in primary teeth (European ancestry analysis) rs1594318 chr2: 3733944 C G 0.60 0.165 (0.030) 0.848 4.13e-08 16 994 0.0 0.69 Intronic, ALLC Caries in primary teeth (multiethnic analysis) a rs1594318 chr2: 3733944 C G 0.60 0.142 (0.028) 0.868 3.78e-07 18 960 0.0 0.61 Intronic, ALLC Caries in primary teeth(multi-ethnic analysis) a rs872877 chr2: 3735826 A G 0.59 0.142 (0.028) 0.868 4.18e-07 18 958 17.5 0.68 Intronic, ALLC Caries in permanent teeth rs7738851 chr6: 11241788 A T 0.85 0.248 (0.044) 1.28 1.63e-08 13 353 13.3 0.20 Intronic, NEDD9 a No single variants were associated with dental caries status at the genome-wide level in the multi-ethnic analysis of primary teeth, however two variants are discussed in Results section and are included here for reference. Table 2. Within-sample and meta-analysis heritability estimates Phenotype Method Estimated h 2 (95% CI) N Caries in primary teeth GCTA GREML 0.28 (0.09: 0.48) 7230 LDSR All participants 0.01 (0.00: 0.06) 19 003 European ancestry only 0.01 (0.00: 0.07) 17 036 Caries in permanent teeth GCTA GREML 0.17 (0.02: 0.31) 6657 LDSR 0.06 (0.00: 0.12) 13 353 Table 3 Lookup of lead associated variants Variant Discovery trait Risk increasing allele (discovery) Cross trait lookup P-value Effect per caries risk increasing allele (se) N rs1594318 Caries in primary teeth (European ancestry meta-analysis) G Adult caries traits DMFS (standard deviation of residuals of caries-affected surfaces) 0.87 0.0015 (0.0092) 26 790 Number of teeth (inverse normal transformed residuals) 0.60 0.0051 (0.0098) 27 947 Standardized DFS (inverse normal transformed residuals) 0.033 0.0195 (0.0091) 26 532 Hypothesis free (No traits meeting threshold for multiple testing) rs7738851 Caries in permanent teeth A Adult caries traits DMFS (standard deviation of residuals of caries-affected surfaces) 0.57 0.007 (0.011) 26 791 Number of teeth (inverse normal transformed residuals) 0.63 0.0064 (0.013) 27 949 Standardized DFS (inverse normal transformed residuals) 0.65 0.0054 (0.012) 26 531 Hypothesis free (No traits meeting threshold for multiple testing) Adult caries traits were defined as follows. DMFS—a count of the number of decayed, missing or filled tooth surfaces. This count was residualized after regression on age and age-squared and standard deviations of residuals calculated. Number of teeth—a count of the number of teeth in the mouth. This count was residualized after regression on age and age-squared and residuals underwent inverse normal transformation. Standardized DFS. The number of decayed and filled surfaces was divided by the total number of tooth surfaces in the mouth. This ratio was residualized after regression on age and age-squared and residuals underwent inverse normal transformation. 3120 |Human Molecular Genetics, 2018, Vol. 27, No. 17 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018 caries exposure compared with other studies as children or their parents are unlikely to be aware of untreated dental caries which would be evident to a trained assessor. We have explored some of these issues previously and shown that self-report measures at scale can be used to make meaningful inference about dental health in childhood (41). We believe that misclassification and under-reporting in questionnaire data would tend to bias genetic effect estimates and heritability toward the null. Despite this we show evidence for heritability using these definitions and effect sizes at lead variants are comparable with effect sizes obtained using clinically assessed data (Figs 3 and 4). As our power calculations showed, the sample size was sufficient to detect the identified variants associated at a genome wide significant level with caries in the primary teeth (rs1594318) and in permanent teeth (rs872877), where we observed relatively large effect sizes. For smaller effect sizes we were underpowered to identify association, and did not detect any variants with effect sizes (expressed as per-allele increased odds) smaller than 15% or 17% in the primary and permanent teeth, respectively. Caries is highly influenced by environmental factors and it is likely that its susceptibility is polygenic in nature (32) with individual genetic variants conferring small effect sizes, as seen in other comparable complex traits (42). Furthermore, some of the included studies had major differences in their caries prevalence, likely acting as a proxy for features affecting risk of caries. This may have introduced heterogeneity and reduced power to detect association, as discussed further below. One area of interest in the literature is the ability of genetics to guide personalized decisions on risk screening or identifying treatment modalities, and this is also true in dentistry. The genetic variants identified in this study are unlikely to be useful on their own in this context, given the modest effect sizes and low total heritability observed in our meta-analysis. We would suggest clinicians should continue to consider environment and aggregate genetic effects (e.g. knowledge of disease patterns of close relatives) rather than specific genetic variants at this moment in time. Nevertheless, the findings of our study contribute to a better understanding of the genetic and biological mechanisms underlying caries susceptibility. Materials and Methods Study samples We performed genome-wide association (GWA) analysis for dental caries case/control status in a consortium including nine coordinating centres. Study procedures differed between these centres. We use the term ‘clinical dental assessment’ to mean that a child was examined in person, whether this was in a dental clinic or a study centre. We use the term ‘examiner’ to refer to a dental professional, and use the term ‘assessor’ to refer to an individual with training who is not a dental professional, for example a trained research nurse. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a longitudinal birth cohort which recruited pregnant women living near Bristol, UK with an estimated delivery date between 1991 and 1992. Follow-up has included clinical assessment and questionnaires and is ongoing (43). A subset of children attended clinics including clinical dental assessment by a trained assessor at age 31, 43 and 61 months of age. Parents were asked to complete questionnaires about their children’s health regularly, including comprehensive questions at a mean age of 5.4 and 6.4 years. Parents and children were asked to complete questionnaires about oral health at a mean age of 7.5, 10.7 and 17.8 years. Please note that the study website contains details of all the data that are available through a fully searchable data dictionary (www.bristol.ac.uk/alspac/researchers/access; date last accessed June 2018). Both clinical and questionnaire derived data were included in this analysis, with priority given to clinical data were available (Supplementary Material, Table S3). The Copenhagen Prospective Studies on Asthma in Childhood includes two population-based longitudinal birth cohorts in Eastern Denmark. COPSAC2000 recruited pregnant women with a history of asthma between 1998 and 2001 (44). Children who developed wheeze in early life were considered for enrolment in a nested randomized trial for asthma prevention. COPSAC2010 recruited pregnant women between 2008 and 2010 and was not selected on asthma status. Both COPSAC2000 and COPSAC2010 studies included regular clinical follow-up. Within Denmark clinical dental assessment is routinely offered to children and adolescents until the age of 18 years and summary data from these examinations are stored in a national register. These data were obtained via index linkage for participants of COPSAC2000 and COPSAC2010 and used to perform joint analysis across both cohorts. The Danish National Birth Cohort (DNBC) is a longitudinal birth cohort which recruited women in mid-pregnancy from 1996 onwards (45). For this analysis, index linkage was performed to obtain childhood dental records for mothers participating in DNBC. As with the COPSAC studies, these data were originally obtained by a qualified dentist and included surface level dental charting. The Generation R study (GENR) recruited women in early pregnancy with expected delivery dates between 2002 and 2006 living in the city of Rotterdam, the Netherlands. The cohort is multi-ethnic with representation from several non-European ethnic groups. Follow-up has included clinical assessment visits and questionnaires and is ongoing (46). Intra-oral photography was performed as a part of their study protocol, with surface level charting produced by a dental examiner (a specialist in paediatric dentistry) (47). Analysis in GENR included (a) a multiethnic association study including all individuals with genetic and phenotypic data (48) and (b) analysis including only individuals of European ancestry. The GENEVA consortium is a group of studies which undertake coordinated analysis across several phenotypes (49). Within GENEVA, the Center for Oral Health Research in rural Appalachia, West Virginia and Pennsylvania, USA (COHRA), the Iowa Fluoride Study in Iowa, USA (IFS) and the Iowa Head Start (IHS) study participated in analysis of dental traits in children (15). COHRA recruited families with at least one child aged between 1 and 18 years of age, with dental examination performed at baseline (50). IFS recruited mothers and new-born infants in Iowa between 1992 and 1995 with a focus on longitudinal fluoride exposures and dental and bone health outcomes. Clinical dental examination in IFS was performed by trained assessors aged 5, 9, 13 and 17 years (51). IHS recruited children participating in an early childhood education program which included a one-time clinical dental examination (13). The ‘German Infant study on the influence of Nutrition Intervention plus air pollution and genetics on allergy development’ (GINIplus) is a multi-centre prospective birth cohort study which has an observational and interventional arm which conducted a nutritional intervention during the first 4 months of life. The study recruited new born infants with and without family history of allergy in the Munich and Wesel areas, Germany between 1995 and 1998 (52,53) .The ‘Lifestyle-related 3121| Human Molecular Genetics, 2018, Vol. 27, No. 17 Downloaded from https://academic.oup.com/hmg/article-abstract/27/17/3113/5040780 by Tampere University and University Hospital user on 27 September 2018