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Introduction

A very good morning to you. This lesson discusses Morelli et al.’s study report (2020) in detail. GWAS could help explain oral diseases like dental caries in addition to periodontal disease, which may be linked causally or correlatively. Essentially, it will be an all-around consideration of oral health, including issues other than DNA, our environment, and our lifestyle. Looking at it broadly, such as understanding why some populations are more prone to dental problems than others. Genetics plays a pivotal role in determining how we understand our dental health, exposing complex links between genes and ora welfare. The increased understanding of the genetic basis of dental conditions will improve our preventative strategy and set the foundation for personalised and effective dental care, leading to better oral health for different races.

Aim

The study aims to investigate the genomics of periodontal disease and tooth morbidity, emphasizing the potential utility of whole genome sequencing data and genome-wide association studies (GWAS) in determining the genetic basis of periodontal disease and tooth-related disorders.

Research Question

What are the underlying genomic factors contributing to periodontal disease and tooth morbidity, and how can whole genome sequencing data and genome-wide association studies (GWAS) be leveraged to identify and understand the genetic basis of these conditions?

Methodology

The authors used comprehensive analysis to summarize genetic studies on tooth caries, periodontal disease, and associated characteristics. The writers provide a compelling summary of the subject's current status by condensing the major conclusions from each study. The review highlights important findings and sheds light on the current state of genetic research in oral health. Furthermore, it guides the direction of this field by outlining potential directions and areas for future research.

Results

GWAS in oral health has not only improved our knowledge of the genes involved in the occurrence of periodontal disease and tooth morbidity but also deepened our understanding of the molecular aspects supporting these diseases. LYZL2 and AJAP1 are two genes that were discovered to have strong associations with genome-wide signals corresponding to different forms of dental caries. Additionally, some other loci such as KPNA4, PKD2, SIBLING, MPPED2, ACTN2, TRAV4 and MMP16 have been associated with oral health-related traits but did not meet the strict genome-wide significance threshold.

The researchers have developed a composite “tooth morbidity” index for evaluating the impact of dental caries and periodontitis on dentition. Adding the total DT is the most important point enabling an oral health assessment. Tooth morbidity is also associated with several gene mutations, including that of MPP7, SPC25, and PMAIP1, indicating genes' impact on dental fitness. Determining the relative contributions of periodontitis versus carious lesions towards tooth loss remains problematic because different study samples and populations will have widely differing profiles about these variables. Investigating genetic markers and their relationship with tooth morbidity will help us tailor our dental care more effectively and understand oral health inequalities.

Discussion

Periodontal disease

The study marked a pivotal moment in periodontal research, introducing genome-wide association studies (GWAS) to explore the genetic underpinnings of aggressive periodontitis. Key associations, like rs1537415 in GLT6D1, were identified and replicated. Recent investigations on rs149133391 in TSNAX-DISC1 expanded our understanding, yet numerous loci lack genome-wide significance or replication. SIGLEC5 (rs12461706) emerged prominently in aggressive periodontitis, gaining additional support in a chronic periodontitis meta-analysis. TENM2 (ODZ2) and DEFA1A3 polymorphisms (rs2978951, rs2738058) also exhibited noteworthy associations.

Functional approaches, including exome sequencing and RNA profiling, complemented GWAS. Gene-centric analyses revealed associations with severe chronic periodontitis and high pathogen colonization. Despite progress, challenges persist. Modest sample sizes in GWAS remain a limitation, albeit partially mitigated by consortium efforts. The 2017 reclassification of periodontitis and potential biases related to tooth loss pose additional complexities. Heterogeneity across studies and distinct population-specific risk factors necessitate caution in drawing overarching conclusions.

Dental Caries

The initial GWAS in 2011 focused on childhood caries in the primary dentition, followed by investigations into permanent dentition caries. Subsequent studies on adult dental caries and early childhood caries yielded suggestive evidence but lacked significant genome-wide signals. Recent meta-analyses, especially one involving a consortium of half a million individuals, identified significant loci (e.g., ALLC, rs1594318, and NEDD9, rs7738851) associated with childhood caries. Dental caries patterns and subtypes, such as pit-and-fissure lesions, have provided noteworthy outcomes in GWAS. For instance, LYZL2 (rs399593) and AJAP1 (rs3896439) were associated with adult dental caries subtypes, and KPNA4 (rs17236529) showed significance for primary dentition pit-and-fissure caries lesions.

Despite progress, challenges persist, including variations in clinical phenotype ascertainment. Issues like tooth shedding in primary dentition and the impact of dental restorative work on disease burden complicate phenotype assessment. Additionally, discerning the causes of tooth loss remains challenging. While enriching the understanding of dental caries genetics, the recent consortium meta-analysis highlights the need for sizable, well-characterized cohorts with detailed phenotypic data for comprehensive investigations.

Tooth Morbidity

Tooth loss, affecting 79% of American adults aged 50 and older, is a prevalent oral health issue with significant functional, biological, and psychosocial consequences. Edentulism, whether partial or complete, not only impairs quality of life but also incurs substantial rehabilitation costs. Caries and periodontitis are major contributors to tooth loss, sharing a common etiological basis involving shifts in the oral microbiome and complex interactions with host immunity.

Addressing this gap, a genome-wide association study examined the joint effects of caries and periodontitis on tooth morbidity using a composite index (DMTFS) in a sample of approximately 4500 European-American participants from the Atherosclerosis Risk in Communities study. Four loci, including PMAIP1, SPC25, MC4R, and MPP7, exhibited genome-wide significant associations with tooth morbidity, and notably, PMAIP1/MC4R showed consistency in a meta-analysis of over half a million individuals from the Gene-Lifestyle Interactions and Dental Endpoints consortium.

Biologically informed complex traits

Using a principle components technique, the study creatively mixes biological and clinical data to create six complicated features related to periodontal disease. These characteristics display unique inflammatory and microbiological profiles, offering a framework based on biological principles. Genome-wide association studies linked Twelve new loci to particular periodontal complex characteristics. One of the most notable disadvantages is that because these features are specific to the Atherosclerosis Risk in community research, it can be difficult to replicate the signals for these traits across studies. Challenges also include differences in measurement techniques and the impact of tooth loss on the diagnosis of periodontitis. Notwithstanding its drawbacks, this method has benefits in directly connecting traits to biologic processes, which facilitates the identification of related genetic loci.

Precision periodontal traits

Researchers developed a new classification system using a novel latent class analysis approach to address the difficulties caused by tooth loss in periodontitis measurement. The improved patient classification was made possible by identifying seven unique periodontal and tooth profile classes using this unsupervised clustering technique. These classes show promise for precision oral health applications, as they can forecast the course of periodontitis and the loss of teeth. The periodontal profile class is still awaiting genome-wide association research. Still, in the meanwhile, the new classification provides clinically recognized phenotypes that help identify recession areas, missing teeth, and reduced periodontal support. Analyses akin to this one in dental caries have shown that disease burden and decay exhibit heritable patterns through principal component and factor analysis.

Construction of a Periodontitis Genetic Score

When a genome-smoking interaction term was considered, the heritable variance increased to 0.52, indicating considerable heritability for severe periodontitis in the research. Although applying the results of genome-wide association studies (GWAS) to predictive models for oral health presents difficulties, the team showed promise. With remarkable precision, scientists created predicted models based on 658 distinct genetic regions linked to severe periodontitis. The genetic risk score of -40 demonstrated a substantial correlation with the likelihood of developing severe periodontitis while not being verified. Notwithstanding its limitations, the work highlights the possibility for precise oral health risk assessment and disease management in the future when demonstrated genomic markers are combined.

Strengths and Limitations

The paper employs GWAS to conduct genomics of oral health. This study was reinforced by the formation of the Gene-Lifestyle Interactions and Dental Endpoints consortium, involving more than 500,000 persons. Due to the large sample, the results are more credible and statistically powerful. Hence, the paper underlines that precise genetic markers should be identified to allow the exploitation of precision dentistry at its full potential. These biomarkers facilitate superior methods of assessing oral health and the risk of contracting disease.

The study recognizes various limitations in line with these alterations. The definition of periodontal disease and its categorisation is diverse, which makes the results incomparable. The number of samples in the individual studies for periodontal GWAS is also smaller than those for other diseases. This may also result in difficulty tracking minute effects and rare gene variations. More importantly, it is difficult to establish precisely the part played by caries and gum illness in toothlessness. However, some studies reveal how the issue affects diverse populations and samples. Thus, though it is a step forward in determining the genetic bases for dental health, diseases, and subjects, more work is needed to understand the complex interplay thoroughly.”

Reference

Morelli, T., Agler, C. S., & Divaris, K. (2020). Genomics of periodontal disease and tooth morbidity. Periodontology 2000 , 82 (1), 143-156.

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