We investigated the cumulative role of genes on caries scores in PFS and SMS and found that caries experience for both surface types was moderately to highly heritable, with proportional caries scores exhibiting higher heritability than dfs and DMFS scores. In addition to significant heritability, we showed that the genetic correlation between PFS and SMS caries scores was very high, indicating similar genetic effects acting on both surface types. Indeed, estimates for genetic correlation were not statistically different from 1.0 for DMFS, dfs + DMFS, proportion dfs, proportion DMFS, and proportion dfs + DMFS. In contrast, the genetic correlation between PFS and SMS for the dfs caries score was 0.76, indicating that approximately 58% (i.e. rhoG2 = 0.762) of the heritability of these two traits was explained by common genetic effects and approximately 42% by trait-specific genetic effects (p < 0.001). Trait-specific genetic effects may include genes that differentially impact dfs for PFS and SMS in magnitude and/or direction. We caution that while genetic correlation was not statistically different from 1.0 for all other caries scores, our results indicated a lack of evidence for surface type-specific genetic effects, rather than evidence for a lack of surface type-specific genetic effects. In other words, true surface type-specific genetic effects may have gone undetected, but if so, they were likely small in comparison to common genetic effects.
Overall, the results of this report were consistent with a previous study in this sample on tooth-level caries scores (i.e. d1ft, D1MFT, and d1ft + D1MFT in primary, permanent, and total dentitions, respectively) [Wang et al., 2010
]. However, for all dentition types (i.e. primary, permanent, and total), heritability of both PFS and SMS were reduced compared to tooth-level caries scores. One explanation for the reduced heritability observed for PFS and SMS caries scores is that genetic factors may similarly affect caries risk for both surface types; therefore limiting analysis to one surface type may be less informative for the genetics of caries experience than simultaneous analysis of caries risk across both surface types. This notion is consistent with the high genetic correlation between PFS and SMS caries scores reported in this study.
While the current study did not seek to identify any specific genes affecting caries risk, it did show that PFS and SMS caries scores are heritable, and therefore may be useful phenotypes for future genetic association studies. The genetics of dental caries is thought to be very complex, with many biological mechanisms affecting cariogenesis and operating over long periods of time. Such mechanisms may include genes related to dietary choices (such as taste [Wendell et al., 2010
] and olfactory receptors), immune response to pathogens [Bergandi et al., 2007
], tooth enamel composition [Slayton et al., 2005
], tooth morphology, saliva composition and flow rate, oral health behaviors, transmission of cariogenic bacteria among hosts [Law et al., 2007
], and others. Genes acting through these and other avenues, some likely interacting with environmental factors, may each contribute only slightly to overall caries risk, and therefore teasing out the complex interplay of genetic and environmental risk factors represents a necessary challenge for better understanding of the multifactorial nature of dental caries.
Several limitations of the study warrant discussion. In particular, DMFS and dfs + DMFS caries scores for PFS and SMS were correlated, in part, due to the M surface classification. By convention, teeth missing due to decay contributed all surfaces to DMFS scores even though the actual carious lesion may have been limited to one surface type. Bias due to the M classification may have led to inflated estimation of the genetic correlation between PFS and SMS. In fact, the phenotypic correlation between PFS and SMS for the M component of DMFS was far greater than for D, F, or sound teeth (results not shown). However censoring the DMFS caries scores by removing the contribution of the M classification is also not ideal. Instead we suggest cautious interpretation of our genetic correlations given the known bias due to phenotype definitions. Likewise, restoration of approximal lesions is often performed via a two-surface filling, which results in the adjacent occlusal surface being counted toward PFS caries scores despite not necessarily having been decayed. This may have caused inflated PFS caries scores. Again, such bias may lead to inflated estimation of genetic correlation.
Another limitation of this study was that all tooth surfaces were dichotomized as either PFS or SMS, which may not fully reflect the complex hierarchy of surface-specific cariological risk factors. The epidemiology of surface-specific caries incidence suggests differences in caries susceptibility (and therefore suggests differences in caries risk factors) among PFS and among SMS [Batchelor and Sheiham, 2004
; Psoter et al., 2009
]. Future development of improved systems for categorizing and analyzing tooth surfaces may assist in discovering the surface-level factors leading to disease. For example, further subdivisions of surface types such as approximal versus buccal/lingual SMS, mandibular vs. maxillary, etc., may also be important for assessing the differential effects of environmental and genetic risk factors. Additionally, risk modification by age and, in particular, the duration of time that surfaces were present (i.e. at risk) is difficult to model for primary, permanent, and combined dentitions. Moreover, differences in environmental factors, such as fluoride varnish and sealants, were not modeled in these analyses, but may have differentially impacted caries scores among study participants leading to noise in the phenotype assessments. Indeed, other studies have shown important differential effects of fluoride exposure, dietary habits, socioeconomic status, and age on PFS and SMS caries [Maupome et al., 2001
; Jiang et al., 2005
; Warren et al., 2006
Lastly, our method of data collection – visual inspection with dental explorer – is itself limited in that it is not the gold standard method for clinical caries assessment and may lead to deflated caries scores. However, assessment of data quality in our sample [Polk et al., 2008
; Wendell et al., 2010
] has shown that our method produces reliable and reproducible data of sufficient quality for pursuing the goals of this study. Moreover, our methods of data analysis are very robust. In general, measurement error or bias, model misspecification, and/or any unknown factors introducing noise into the phenotype would not lead to false positive findings (because measurement issues would not affect data proportional to biological relatedness among participants), but would instead bias these analyses toward the null hypothesis. Therefore, despite these limitations, the analyses are likely conservative and the general conclusions from this study are robust.
This study benefits from many strengths, including a large sample from an understudied, high-risk population. Our household-based recruitment yielded a rich sample comprised of a variety of relative types, which greatly improved our estimation of heritability and genetic correlation compared to studies limited to one or few relative types (i.e. studies of siblings, parent-offspring trios, etc.). This is because extended relatives (especially relatives residing in separate households such as half-siblings, cousins, etc.) are less likely to share familial nongenetic factors that could lead to overestimation. Our study was adequately powered, and all significant p values far exceeded the significance thresholds for Bonferroni adjustment for multiple comparisons. Additionally, we assessed the effect of nonnormality of our trait distributions by repeating analysis using exactly normal transformed phenotypes. Heritability and genetic correlation estimates were nearly identical, suggesting that deviations of caries scores from normality did not adversely affect our modeling framework.
The major conclusion from this study was that caries scores were heritable and that the majority of genes affecting caries risk were common to both PFS and SMS. While some surface type-specific genetic effects may exist, especially for dfs scores in primary dentition, the high genetic correlations suggest that combining PFS and SMS in future efforts to identify genes involved in caries risk may be beneficial complement to studying PFS and SMS separately. Additionally, this study highlighted the need for better caries phenotypes and/or modeling approaches that more accurately capture the complexity of the distribution of caries risk across the dentition. Additional work is currently needed to identify the environmental and genetic factors that differentially affect caries risk across surface types, and to devise better categorization methods that sensibly group tooth surfaces based on common risk profiles. This study is one of few attempts at defining new traits and genetic models which may assist in finding the specific genes implicated in caries etiology, and lead to improved understanding, and prevention, of the factors leading to disease.