Genome-wide association studies (GWASs) of isolated cleft lip with or without cleft palate (CL/P) occurring without other birth defects have identified multiple loci with evidence of etiologic mutations (Birnbaum et al. 2009; Grant et al. 2009; Beaty et al. 2010; Beaty et al. 2013; Mangold et al. 2010; Camargo et al. 2012; Ludwig et al., 2012; Sun et al. 2015; Wolf et al. 2015). Key loci include (in genomic order) PAX7 (1p36), ABCA4-ARHGAP29 (1p22.1), IRF6 (1q32), THADA (2p21), DCAF4L2 (8q21.3), 8q24, GADD45G (9q22.1), KIAA1598-VAX1 (10q25.3), SPRY2 (13q31.3), TPM1 (15q22.2), NTN1 (17p13.1), NOG1 (17q22), and MAFB (20q12). More recent and larger GWASs have found evidence for these loci and additional ones such as FOXE1 (9q22.3; Leslie, Carlson, et al. 2016; Leslie et al. 2017; Yu et al. 2017). Candidate gene studies first suggested some of these genes/loci for CL/P, such as IRF6 and FOXE1, but also others, such as MSX1, FGFR2, and CRISPLD2 (Chiquet et al. 2007; Leslie and Marazita 2013). Interestingly, except perhaps for FOXE1 (Moreno et al. 2009; Leslie et al. 2017), there is little evidence that the loci for CL/P are related to cleft palate only (CPO) especially at GWAS significance levels.

Despite the convincing evidence for many loci, there are several limitations in prior assessments of their effects. Previous studies have almost exclusively focused on clinic-based rather than population-based samples. Genetic risk estimates from clinic-based samples may have limited generalizability because of potential ascertainment bias (Kukull and Ganguli 2012). In contrast, population-based samples provide more reliable and generalizable estimates for quantifying the epidemiologic and clinical relevance of these top loci. Prior studies have had modest sample sizes that may lack power to accurately estimate separate effects on cleft lip only (CLO) versus cleft lip with palate (CLP) and meaningfully examine potential differences between these 2 phenotypes, and most examined CL/P as 1 phenotype. Small sample sizes have been a challenge for examining genetic effects on CPO, a less common trait with a higher proportion of syndromic cases. Another limitation is focusing on fetal gene effects with little attention to additional underlying genetic mechanisms, such as maternal gene (MG) and parent-of-origin (PoO) effects. MG effects influence fetal intra-uterine environment conditional on fetal genes. PoO effects indicate differential effects in fetal genes depending on whether they were inherited from the mother or the father. Two studies of MG and PoO effects based on GWAS data (Shi et al. 2012; Garg et al. 2014) found nonsignificant effects. However, their study samples were relatively modest for a meaningful assessment of such effects. Finally, GWASs have focused on isolated orofacial clefting (OFC), and little is known about whether these loci are relevant for nonisolated OFC occurring with other birth defects or syndromes.

In this study, we estimated the effects of the main OFC loci in GWASs and top candidate gene studies published before February 2016 on risks of isolated CLO, CLP, and CPO examined as separate phenotypes in the largest consortium to date of population-based samples of European descent. We examined fetal, MG, and PoO effects, and we estimated effects on non-isolated OFC separately for CL/P and CPO. We used individual-level data pooled across 5 population-based samples, accounting for study differences through stratified estimation, to study a total of 31 single-nucleotide polymorphisms (SNPs) within 17 genes/loci (Appendix Table 1). Our work provides the most definitive assessment to date of the importance of these loci for each of the 3 isolated OFC phenotypes in populations of European descent, including risk estimates that may be meaningful for clinical counseling and etiologic research. Furthermore, we provide novel evidence on the relevance of these loci for nonisolated OFC.

Our study employs data from a unique international consortium of 5 OFC population-based case-control studies: the Norway Facial Clefts Study, the Norwegian Mother and Child Cohort, the Utah Child and Family Health Study, the Iowa Case-Control Study, and the US National Birth Defects Prevention Study. Cases and controls for each study were identified through national or state-based registries that provide population-based surveillance of OFC. Mothers and children were enrolled and provided DNA specimens. The controls across all studies included children without oral clefts or other major birth defects who were randomly selected from the same birth year and regions as the cases (Reefhuis et al. 2015; Kummet et al. 2016; Kutbi 2017). Subject enrollment and data collection in each study were approved by the appropriate institutional review boards. Descriptions of these studies and genotyping methods are in the online Appendix.

In the main analysis, we limited our sample to children born with isolated oral clefts (excluding cases with syndromes or other major birth defects). Because of differences in minor allele frequencies and possibly genetic effects by ancestry, we limited the sample from the US studies to self-reported non-Hispanic whites. Most participants in the Norway studies were Caucasians (studies required eligible participants to be native speakers of Norwegian). In additional analyses, we examined effects of SNPs significantly related to isolated clefts on risk of nonisolated clefts.

The total analytic sample included 1,875 cases with isolated clefts, including 1,311 mother-child dyads with genetic data on both mothers and children. The sample included 459 cases with nonisolated clefts, of whom 267 had mother-child dyad data, and 3,749 controls, including 2,481 mother-child dyads with genetic data. Appendix Table 2 shows the sample distribution by case-control group, cleft type, and genetic data availability for each study.

Using the largest sample to date of individuals of European descent, we investigated 31 SNPs within 17 top loci for OFC from previous GWASs and candidate gene studies. Our initial screening of fetal alleles with Bonferroni adjustment for isolated CLO, CLP, and CPO found significant associations for 14 SNPs in 12 loci; most associations were consistent with a dose-response allelic effect. Most SNPs had remarkably similar effects between isolated CLO and CLP. Potential exceptions were ABCA4-ARHGAP29 and THADA, which were significantly associated with isolated CLP but not CLO. In contrast, TPM1 and NOG1 had stronger associations with isolated CLO than CLP. There was no evidence of significant associations with isolated CPO except for NOG1 (rs227731), which had opposite effects on CPO and CLO—reduction (increase) in CPO (CLO) risk with the minor allele. Our study is the first to report differential effects of ABCA4-ARHGAP29 on CLP and CLO and opposite NOG1 effects on CLO and CPO, including the significant reduction in CPO risk. The lack of significant associations of other loci with isolated CPO is consistent with prior studies (Beaty et al. 2011; Böhmer et al. 2013; Leslie et al. 2017; Ludwig et al. 2017) and studies of familial recurrence suggesting a distinct etiology for CPO in many, if not most, cases (Sivertsen et al. 2008; Grosen et al. 2010). Among all examined loci, 8q24 (rs987525) had the strongest effects on isolated CLO and CLP. There was little evidence of prominent MG or PoO effects consistent with previous studies (Shi et al. 2012; Garg et al. 2014) and findings of similar mother-offspring and father-offspring OFC recurrences (Sivertsen et al. 2008; Grosen et al. 2010), suggesting that such effects do not play a major role in the etiologic mechanisms of almost all the examined loci. A detailed discussion of key loci findings is in the online Appendix. We did not find significant associations for CLO or CLP with MSX1, FGFR2, CRISPLD2, NTN1, and MYH9, suggesting that prior findings for these loci are perhaps not generalizable to population-based samples and are possibly more specific to selective clinic-based samples.

Our comparison of locus effects between isolated and non-isolated CL/P revealed remarkable similarity in direction and magnitude between the 2 cleft groups for most loci. The strongest evidence was observed for 8q24 (rs987525), which had similar significant effects (at P < 0.05) on nonisolated CL/P in both single and double minor allele doses, despite the much smaller sample size. Other loci had significant associations (at P < 0.05) in double minor allele forms (PAX7, THADA, TPM1, and NOG) or single minor allele dose (KIAA1598-VAX1). This finding suggests that these loci are modifiers of cleft risk in both isolated and nonisolated forms and that combining isolated and nonisolated CLO and CLP may be considered in initial GWAS analyses to increase power for identifying such variants. Such analyses would complement analyses specific to isolated forms. Furthermore, it indicates that genetic pathways and possibly even the same etiologic variants converge to contribute risk for CL/P under syndromic and nonsyndromic genetic backgrounds. This reduction in heterogeneity facilitates the design of studies to disentangle the contribution of such variants to OFC etiology. However, it is possible that loci effects on OFC risk within the nonisolated group may vary by etiology of the noncleft malformations, for example, between cases with known syndromes and those of unknown etiologies. Examining this potential heterogeneity in future work is important for understanding the contribution of these loci to nonisolated OFC risk. In conclusion, this study represents the largest population-based examination of top loci suggested for isolated OFC to date. We provide further evidence of the notion of different genetic etiologies between isolated CL/P and CPO and similar genetic etiologies between CLO and CLP for most top loci identified to date. The similarity in effects of most loci between CLO and CLP supports pooling these phenotypes in preliminary GWAS analyses to maximize power. We provide novel evidence of remarkable similarity in effects of top loci between isolated and nonisolated forms of CL/P, suggesting that nonisolated forms may be included in initial GWAS analyses to maximize power and that studying syndromic forms can continue to inform our understanding of molecular mechanisms underlying the nonsyndromic forms. We consistently observed dose-response allelic effects for most loci, allowing for more accurate estimation of genetic effects and providing additional evidence on the likelihood that the effects have a biological basis.

The strengths of our study include a pooled analysis of individual-level data from large population-based samples allowing for precise estimation of loci effects on risk and reducing ascertainment bias. One potential caveat is incomplete accounting for population stratification since we do not have GWAS data to fully capture ancestry. However, this is unlikely to meaningfully affect our results since the majority of our sample is of Caucasian ancestry. While it is possible that some variants may vary in allelic distribution or risk associations across different ancestries among self-reported whites, we did not find significant heterogeneity in association across the 5 study populations we examined. Furthermore, some of the dyad-case samples with isolated OFC from the Utah and Norway studies were included in a previous GWAS (Beaty et al. 2010). However, these cases were previously analyzed with a model of allelic transmission within triads with OFC and not with the combined dyad and case-control design as we did here. Therefore, there is little overlap with previous work that included these samples.

Our results can be considered the most reliable estimates to date of the effects of these top loci on risks of isolated OFC in a population of European descent. These estimates can be used to generate polygenic risk scores to predict risks of CLO or CLP in other smaller data sets with data on the top significant SNPs. Furthermore, they may be informative for predicting risk of oral clefts in cases for whom screening is being considered such as individuals with a family history of clefts. Our analysis focused on the effects of each SNP on its own. Obviously, individuals can have combinations of risk alleles across these SNPs that are associated with different cleft risks, and investigating these combinations in future studies is meaningful to better understand and quantify risk heterogeneity. Also, estimating the effects of causal variants (not only GWAS lead SNPs) and new loci as they are identified, such as GRHL3 for CPO (Leslie, Liu, et al. 2016), is needed for more accurate risk prediction.