Artificial intelligence and 3D printing technology in orthodontics: future and scope

New digital technologies, like in other fields, have revolutionized the health care field and orthodontic practice in the 21st century. They can assist the health care professionals in working more efficiently by saving time and improving patient care. Recent advances in artificial intelligence (AI) and 3D printing technology are useful for improving diagnosis and treatment planning, creating algorithms and manufacturing customized orthodontic appliances. AI accomplishes the task of human beings with the help of machines and technology. In orthodontics, AI-based models have been used for diagnosis, treatment planning, clinical decision-making and prognosis prediction. It minimizes the required workforce and speeds up the diagnosis and treatment procedure. In addition, the 3D printing technology is used to fabricate study models, clear aligner models, surgical guides for inserting mini-implants, clear aligners, lingual appliances, wires components for removable appliances and occlusal splints. This paper is a review of the future and scope of AI and 3D printing technology in orthodontics

Genetic and environmental factors involved in the development of oral malformations such as cleft lip/palate in non-syndromic patients and open bite malocclusion

Among the most common malformations observed in the oral cavity are cleft lip/palate and malocclusions, being this last one considered by the World Health Organization, the third public health problem. Malocclusions include the anterior open bite, a change in the vertical plane, that can be of two types: dental anterior open bite and skeletal anterior open bite. Cleft lip and cleft palate are the most common congenital malformations at birth. These malformations result from a failure in the normal craniofacial development process, which requires the coordination of a complex series of events. From the embryological point of view, the cleft lip/palate is a consequence of the failure of the first superior branchial arch to complete fusion with the frontonasal process during pregnancy. All these malformations result from the interaction of both genetic and environmental factors. Among the environmental factors involved in the development of malocclusions are deleterious habits, mouth breathing and trauma. Several genes involved in the development of facial bones, muscles and teeth are also responsible for the development of malocclusions. In the same way, clefts development is a multifactorial trait where multiple genes are involved as well as environmental factor like alcohol consumption, tobacco, exposure to pesticides or toxic solvents, in a complex interaction. All these factors may jeopardize the normal functioning of the stomatognathic system and the consequent quality of life of the patient. The purpose of this study was to review the literature concerning the genetic and environmental aspects involved in the development of these malformations.info:eu-repo/semantics/publishedVersio

Identification and comparison of imputed and genotyped variants for genome-wide association study of orofacial cleft case-parent trios

Background: Orofacial clefts (OFCs) – cleft lip with/without cleft palate (CL/P) and cleft palate (CP) – are the most common craniofacial malformations among newborns. Both CL/P and CP show strong familial aggregation resulting in high estimated heritability. Previously identified genetic risk factors account for about a quarter of the estimated total heritability of risk to OFCs, indicating additional genetic risk loci remain to be identified. The aim of this thesis is to update imputed genotypes generated from a genome-wide marker panel and use both observed and imputed genetic variants to identify the genetic risk factors for OFCs in a case-parent trio study of OFC. Methods: We imputed genotypes on case-parent trios from the Genes and Environment Association (GENEVA) consortium using the Michigan Imputation Server, and then conducted genome-wide association analysis to identify genetic variants associated with risk of CL/P and CP separately. For each cleft subtype, we performed genotypic transmission disequilibrium test (gTDT) using the trio R package on common single nucleotide polymorphic (SNP) markers (i.e. those with a minor allele frequency [MAF] ≥ 5%) in all the trios together, and then stratified by ethnicity (Asian and European sub-groups). Results: We identified two genes not previously reported as associated with risk to CL/P - 18q12 (TTR) and 4q22 (GRID2). The most significant SNP in the region of TTR (rs1375445) reached genome-wide significance in the combined set of all trios (p = 4.33 x 10-8) with RR=1.35 [95%CI: (1.21, 1.51)], despite not achieving this level of significance in either the European sub-group (p = 2.94 x 10-5) or Asian sub-group (p = 5.52 x 10-5) separately. However, the most significant SNP of GRID2 (rs1471079) reached genome-wide significance only in the Asian sub-group (p = 1.82 x 10-7) with estimated RR = 0.70 [95%CI: (0.60, 0.80)]. Both of these imputed SNPs have high imputation accuracy (rs1375445 R2 = 0.96; rs1471079 R2 = 0.97). Additionally, for CL/P, we replicated significant association of 8 regions identified in previous studies of these case-parent trios, including 8q24 (recognized as a gene desert), 1q32 (IRF6), 20q12 (MAFB), 17p13 (NTN1) and 1p22 (ABCA4). The most significant SNPs in six of these regions were imputed. The most significant SNP (rs17242358) in the 8q24 region showed genome-wide significance (p = 1.75 x 10-16) in the combined set of all trios. This imputed SNP showed over-transmission of A allele (over G allele) with estimated RR = 2.09 [95%CI: (1.76, 2.49)]. This imputed SNP achieved quite different levels of significance in the European (p = 7.11 x 10-14) and Asian sub-groups (p = 7.3 x 10-4) primarily because the MAF differed across the two sub-groups (MAF = 23% in Europeans and 2% in Asians). We did not detect any genome-wide significant locus for the OFC subtype CP. Conclusions: Our findings confirm the complex genetic architecture and the heterogeneity of genes influencing risk to OFCs. We replicated most previously reported genetic risk factors for these GENEVA case-parent trios. We also identified two new genetic risk factors for CL/P that require further investigation. Stratification by racial groups helped detect OFC risk loci specific to certain groups. In addition, imputation helped improve the statistical power to detect genetic risk factors for OFC

Machine Learning Models for Genetic Risk Assessment of Infants with Non-syndromic Orofacial Cleft

The isolated type of orofacial cleft, termed non-syndromic cleft lip with or without cleft palate (NSCL/P), is the second most common birth defect in China, with Asians having the highest incidence in the world. NSCL/P involves multiple genes and complex interactions between genetic and environmental factors, imposing difficulty for the genetic assessment of the unborn fetus carrying multiple NSCL/P-susceptible variants. Although genome-wide association studies (GWAS) have uncovered dozens of single nucleotide polymorphism (SNP) loci in different ethnic populations, the genetic diagnostic effectiveness of these SNPs requires further experimental validation in Chinese populations before a diagnostic panel or a predictive model covering multiple SNPs can be built. In this study, we collected blood samples from control and NSCL/P infants in Han and Uyghur Chinese populations to validate the diagnostic effectiveness of 43 candidate SNPs previously detected using GWAS. We then built predictive models with the validated SNPs using different machine learning algorithms and evaluated their prediction performance. Our results showed that logistic regression had the best performance for risk assessment according to the area under curve. Notably, defective variants in MTHFR and RBP4, two genes involved in folic acid and vitamin A biosynthesis, were found to have high contributions to NSCL/P incidence based on feature importance evaluation with logistic regression. This is consistent with the notion that folic acid and vitamin A are both essential nutritional supplements for pregnant women to reduce the risk of conceiving an NSCL/P baby. Moreover, we observed a lower predictive power in Uyghur than in Han cases, likely due to differences in genetic background between these two ethnic populations. Thus, our study highlights the urgency to generate the HapMap for Uyghur population and perform resequencing-based screening of Uyghur-specific NSCL/P markers. Keywords: Orofacial cleft, Genetic risk, Folic acid, Vitamin A, Nutritional interventio

Evaluating proposed phenotypic predictors of recurrence risk in unaffected individuals with a family history of isolated cleft lip with or without cleft palate

Cleft lip ± cleft palate (CL/P) is a common birth defect and public health concern, with significant, long-term health impacts, which require many healthcare resources and increase costs of care. The majority (>70%) of cases are isolated and non-syndromic (NSCL/P). Single-gene syndromes, chromosome anomalies, or teratogens account for the remainder. There is a strong genetic component in NSCL/P; individuals with a positive family history are more likely to have an affected child. The complex, multifactorial nature of NSCL/P complicates recurrence risk assessment. Currently, genetic counseling for NSCL/P is based on empiric recurrence risk figures from large cohort studies. Thus, risk assessment cannot be personalized. Developing predictive models based on established risk factors could refine estimates. Several subtle phenotypic differences have been identified among unaffected relatives of an individual with NSCL/P, compared to individuals with no family history. Phenotypes consistently associated with NSCL/P may be useful as markers of recurrence risk. The present study investigated the effect of seven such traits, on the odds of participants’ case versus control family status. Three models were built using logistic regression. Model 1 included orbicularis oris muscle defects and velopharyngeal dysfunction, and achieved an area under the receiver operating curve (AUC) of 0.63. Model 2 included maximum facial and intercanthal width, upper and lower facial height, and midface depth measurements, and achieved an AUC of 0.64. Model 3 included all variables from Models 1 and 2, and achieved an AUC of 0.72. AUC values below 0.7 indicate poor model discrimination. Models 1 and 2 had poor predictive performance, while Model 3 had fair performance. The public health significance of this work is that it adds to the body of research on risk factors and recurrence risk assessment in NSCL/P. It also works towards creating risk models. Reliable risk models allow for the identification of high-risk individuals, therefore making it possible to design and/or implement primary and secondary prevention interventions