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Based on epidemiologic and embryologic patterns, nonsyndromic orofacial clefts– the most common craniofacial birth defects in humans– are commonly categorized into cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP), which are traditionally considered to be etiologically distinct. However, some evidence of shared genetic risk in IRF6 , GRHL3 and ARHGAP29 regions exists; only FOXE1 has been recognized as significantly associated with both CL/P and CP in genome-wide association studies (GWAS). We used a new statistical approach, PLACO (pleiotropic analysis under composite null), on a combined multi-ethnic GWAS of 2,771 CL/P and 611 CP case-parent trios. At the genome-wide significance threshold of 5 × 10 −8 , PLACO identified 1 locus in 1q32.2 ( IRF6 ) that appears to increase risk for one OFC subgroup but decrease risk for the other. At a suggestive significance threshold of 10 −6 , we found 5 more loci with compelling candidate genes having opposite effects on CL/P and CP: 1p36.13 ( PAX7 ), 3q29 ( DLG1 ), 4p13 ( LIMCH1 ), 4q21.1 ( SHROOM3 ) and 17q22 ( NOG ). Additionally, we replicated the recognized shared locus 9q22.33 ( FOXE1 ), and identified 2 loci in 19p13.12 ( RAB8A ) and 20q12 ( MAFB ) that appear to influence risk of both CL/P and CP in the same direction. We found locus-specific effects may vary by racial/ethnic group at these regions of genetic overlap, and failed to find evidence of sex-specific differences. We confirmed shared etiology of the two OFC subtypes comprising CL/P, and additionally found suggestive evidence of differences in their pathogenesis at 2 loci of genetic overlap. Our novel findings include 6 new loci of genetic overlap between CL/P and CP; 3 new loci between pairwise OFC subtypes; and 4 loci not previously implicated in OFCs. Our in-silico validation showed PLACO is robust to subtype-specific effects, and can achieve massive power gains over existing approaches for identifying genetic overlap between disease subtypes. In summary, we found suggestive evidence for new genetic regions and confirmed some recognized OFC genes either exerting shared risk or with opposite effects on risk to OFC subtypes.

Dental caries and periodontitis account for a vast burden of morbidity and healthcare spending, yet their genetic basis remains largely uncharacterized. Here, we identify self-reported dental disease proxies which have similar underlying genetic contributions to clinical disease measures and then combine these in a genome-wide association study meta-analysis, identifying 47 novel and conditionally-independent risk loci for dental caries. We show that the heritability of dental caries is enriched for conserved genomic regions and partially overlapping with a range of complex traits including smoking, education, personality traits and metabolic measures. Using cardio-metabolic traits as an example in Mendelian randomization analysis, we estimate causal relationships and provide evidence suggesting that the processes contributing to dental caries may have undesirable downstream effects on health. Dental caries and periodontitis are among the most common medical conditions. Here, the authors report a GWAS for measures of oral health that reveals 47 risk loci for caries, find genetic correlation with 31 other complex traits and use Mendelian randomization analyses to explore potential causal relationships.

Numerous lines of evidence point to a genetic basis for facial morphology in humans, yet little is known about how specific genetic variants relate to the phenotypic expression of many common facial features. We conducted genome-wide association meta-analyses of 20 quantitative facial measurements derived from the 3D surface images of 3118 healthy individuals of European ancestry belonging to two US cohorts. Analyses were performed on just under one million genotyped SNPs (Illumina OmniExpress+Exome v1.2 array) imputed to the 1000 Genomes reference panel (Phase 3). We observed genome-wide significant associations (p < 5 x 10-8) for cranial base width at 14q21.1 and 20q12, intercanthal width at 1p13.3 and Xq13.2, nasal width at 20p11.22, nasal ala length at 14q11.2, and upper facial depth at 11q22.1. Several genes in the associated regions are known to play roles in craniofacial development or in syndromes affecting the face: MAFB, PAX9, MIPOL1, ALX3, HDAC8, and PAX1. We also tested genotype-phenotype associations reported in two previous genome-wide studies and found evidence of replication for nasal ala length and SNPs in CACNA2D3 and PRDM16. These results provide further evidence that common variants in regions harboring genes of known craniofacial function contribute to normal variation in human facial features. Improved understanding of the genes associated with facial morphology in healthy individuals can provide insights into the pathways and mechanisms controlling normal and abnormal facial morphogenesis.

Genome-wide association scans of complex multipartite traits like the human face typically use preselected phenotypic measures. Here we report a data-driven approach to phenotyping facial shape at multiple levels of organization, allowing for an open-ended description of facial variation while preserving statistical power. In a sample of 2,329 persons of European ancestry, we identified 38 loci, 15 of which replicated in an independent European sample ( n  = 1,719). Four loci were completely new. For the others, additional support ( n  = 9) or pleiotropic effects ( n  = 2) were found in the literature, but the results reported here were further refined. All 15 replicated loci highlighted distinctive patterns of global-to-local genetic effects on facial shape and showed enrichment for active chromatin elements in human cranial neural crest cells, suggesting an early developmental origin of the facial variation captured. These results have implications for studies of facial genetics and other complex morphological traits. The authors report a data-driven approach to phenotyping 3D facial shape. They apply their methodology to 2,329 individuals of European ancestry and identify 38 loci that associate with specific facial morphologies, some of which overlap with neural-crest-specific regulatory regions.

Non-syndromic cleft lip with palate (NSCLP) is the most serious sub-phenotype of non-syndromic orofacial clefts (NSOFC), which are the most common craniofacial birth defects in humans. Here we conduct a GWAS of NSCLP with multiple independent replications, totalling 7,404 NSOFC cases and 16,059 controls from several ethnicities, to identify new NSCLP risk loci, and explore the genetic heterogeneity between sub-phenotypes of NSOFC. We identify 41 SNPs within 26 loci that achieve genome-wide significance, 14 of which are novel ( RAD54B , TMEM19 , KRT18 , WNT9B , GSC / DICER1 , PTCH1 , RPS26 , OFCC1/TFAP2A , TAF1B , FGF10 , MSX1 , LINC00640 , FGFR1 and SPRY1 ). These 26 loci collectively account for 10.94% of the heritability for NSCLP in Chinese population. We find evidence of genetic heterogeneity between the sub-phenotypes of NSOFC and among different populations. This study substantially increases the number of genetic susceptibility loci for NSCLP and provides important insights into the genetic aetiology of this common craniofacial malformation. Non-syndromic cleft lip with palate is a common birth defect of unknown aetiology. Here, the authors discover 14 new genes associated with this condition, and show genetic heterogeneity in this and other non-syndromic orofacial clefting disorders.

The NIH Consensus Development Program released a statement in 2001 (http://consensus.nih.gov/2001/2001DentalCaries115html.htm) and listed six major clinical caries research directions. One of these directions was the need for genetic studies to identify genes and genetic markers of diagnostic, prognostic and therapeutic value. This last decade has seen a steep increase in studies investigating the presence of genetic factors influencing individual susceptibility to caries. This review revisits recent caries human genetic studies and provides a perspective for future studies in order to fulfil their promise of revolutionizing our understanding of and the standard of care for the most prevalent bacteria-mediated non-contagious disease in the world.

There is increasing evidence that genetic risk variants for non-syndromic cleft lip/palate (nsCL/P) are also associated with normal-range variation in facial morphology. However, previous analyses are mostly limited to candidate SNPs and findings have not been consistently replicated. Here, we used polygenic risk scores (PRS) to test for genetic overlap between nsCL/P and seven biologically relevant facial phenotypes. Where evidence was found of genetic overlap, we used bidirectional Mendelian randomization (MR) to test the hypothesis that genetic liability to nsCL/P is causally related to implicated facial phenotypes. Across 5,804 individuals of European ancestry from two studies, we found strong evidence, using PRS, of genetic overlap between nsCL/P and philtrum width; a 1 S.D. increase in nsCL/P PRS was associated with a 0.10 mm decrease in philtrum width (95% C.I. 0.054, 0.146; P = 2x10-5). Follow-up MR analyses supported a causal relationship; genetic variants for nsCL/P homogeneously cause decreased philtrum width. In addition to the primary analysis, we also identified two novel risk loci for philtrum width at 5q22.2 and 7p15.2 in our Genome-wide Association Study (GWAS) of 6,136 individuals. Our results support a liability threshold model of inheritance for nsCL/P, related to abnormalities in development of the philtrum.

Several studies have now shown evidence of association between common genetic variants and quantitative facial traits in humans. The reported associations generally involve simple univariate measures and likely represent only a small fraction of the genetic loci influencing facial morphology. In this study, we applied factor analysis to a set of 276 facial linear distances derived from 3D facial surface images of 2187 unrelated individuals of European ancestry. We retained 23 facial factors, which we then tested for genetic associations using a genome-wide panel of 10,677,593 single nucleotide polymorphisms (SNPs). In total, we identified genome-wide significant (p < 5 × 10-8) associations in three regions, including two that are novel: one involving measures of midface height at 6q26 within an intron of PARK2 (lead SNP rs9456748; p = 4.99 × 10-8) and another involving measures of central upper lip height at 9p22 within FREM1 (lead SNP rs72713618; p = 2.02 × 10-8). In both cases, the genetic association was stronger with the composite facial factor phenotype than with any of the individual linear distances that comprise those factors. While the biological role of PARK2 in the craniofacial complex is currently unclear, there is evidence from both mouse models and Mendelian syndromes that FREM1 may influence facial variation. These results highlight the potential value of data-driven multivariate phenotyping for genetic studies of human facial morphology.

As the biomedical data ecosystem increasingly embraces the findable, accessible, interoperable, and reusable (FAIR) data principles to publish multimodal datasets to the cloud, opportunities for cloud-based research continue to expand. Besides the potential for accelerated and diverse biomedical discovery that comes from a harmonized data ecosystem, the cloud also presents a shift away from the standard practice of duplicating data to computational clusters or local computers for analysis. However, despite these benefits, researcher migration to the cloud has lagged, in part due to insufficient educational resources to train biomedical scientists on cloud infrastructure. There exists a conceptual lack especially around the crafting of custom analytic pipelines that require software not pre-installed by cloud analysis platforms. We here present three fundamental concepts necessary for custom pipeline creation in the cloud. These overarching concepts are workflow and cloud provider agnostic, extending the utility of this education to serve as a foundation for any computational analysis running any dataset in any biomedical cloud platform. We illustrate these concepts using one of our own custom analyses, a study using the case-parent trio design to detect sex-specific genetic effects on orofacial cleft (OFC) risk, which we crafted in the biomedical cloud analysis platform CAVATICA.

Orofacial clefts include cleft lip (CL), cleft palate (CP), and cleft lip and palate (CLP), which combined represent the largest group of craniofacial malformations in humans with an overall prevalence of one per 1,000 live births. Each of these birth defects shows strong familial aggregation, suggesting a major genetic component to their etiology. Genetic studies of orofacial clefts extend back centuries, but it has proven difficult to define any single etiologic mechanism because many genes appear to influence risk. Both linkage and association studies have identified several genes influencing risk, but these differ across families and across populations. Genome-wide association studies have identified almost two dozen different genes achieving genome-wide significance, and there are broad classes of ‘causal genes’ for orofacial clefts: a few genes strongly associated with risk and possibly directly responsible for Mendelian syndromes which include orofacial clefts as a key phenotypic feature of the syndrome, and multiple genes with modest individual effects on risk but capable of disrupting normal craniofacial development under the right circumstances (which may include exposure to environmental risk factors). Genomic sequencing studies are now underway which will no doubt reveal additional genes/regions where variants (sequence and structural) can play a role in controlling risk to orofacial clefts. The real challenge to medicine and public health is twofold: to identify specific genes and other etiologic factors in families with affected members and then to devise effective interventions for these different biological mechanisms controlling risk to complex and heterogeneous birth defects such as orofacial clefts.