Dataset Information

Achondroplasia and periodontal disease.

ABSTRACT: Achondroplasia is a non-lethal form of chondrodysplasia. It is a disturbance of endochondral bone formation which results in characteristic dwarfism. It is transmitted as an autosomal dominant trait, with complete penetrance. De novo mutations cause up to 90% of cases. The mutation rate is estimated to be 0.000014 per gamete per generation. It is a rare disorder with a prevalence of 1:10,000 to 1:50,000 births worldwide. A young female patient suffering from achondroplasia reported with oral manifestations showing features of periodontitis, hypoplasia of the mid-face, deep periodontal pockets, and mobility of teeth. This case report highlights this rare anomaly and its oral manifestations.

SUBMITTER: Chawla K

PROVIDER: S-EPMC3357025 | biostudies-other | 2012 Jan

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Achondroplasia and periodontal disease.

Chawla Kirti K Lamba Arundeep Kaur AK Faraz Farrukh F Tandon Shruti S

Journal of Indian Society of Periodontology 20120101 1

Achondroplasia is a non-lethal form of chondrodysplasia. It is a disturbance of endochondral bone formation which results in characteristic dwarfism. It is transmitted as an autosomal dominant trait, with complete penetrance. De novo mutations cause up to 90% of cases. The mutation rate is estimated to be 0.000014 per gamete per generation. It is a rare disorder with a prevalence of 1:10,000 to 1:50,000 births worldwide. A young female patient suffering from achondroplasia reported with oral man ...[more]

PMID: 22628982

Similar Datasets

Project description:BACKGROUND:Current periodontal disease taxonomies have limited utility for predicting disease progression and tooth loss; in fact, tooth loss itself can undermine precise person-level periodontal disease classifications. To overcome this limitation, the current group recently introduced a novel patient stratification system using latent class analyses of clinical parameters, including patterns of missing teeth. This investigation sought to determine the clinical utility of the Periodontal Profile Classes and Tooth Profile Classes (PPC/TPC) taxonomy for risk assessment, specifically for predicting periodontal disease progression and incident tooth loss. METHODS:The analytic sample comprised 4,682 adult participants of two prospective cohort studies (Dental Atherosclerosis Risk in Communities Study and Piedmont Dental Study) with information on periodontal disease progression and incident tooth loss. The PPC/TPC taxonomy includes seven distinct PPCs (person-level disease pattern and severity) and seven TPCs (tooth-level disease). Logistic regression modeling was used to estimate relative risks (RR) and 95% confidence intervals (CI) for the association of these latent classes with disease progression and incident tooth loss, adjusting for examination center, race, sex, age, diabetes, and smoking. To obtain personalized outcome propensities, risk estimates associated with each participant's PPC and TPC were combined into person-level composite risk scores (Index of Periodontal Risk [IPR]). RESULTS:Individuals in two PPCs (PPC-G: Severe Disease and PPC-D: Tooth Loss) had the highest tooth loss risk (RR = 3.6; 95% CI = 2.6 to 5.0 and RR = 3.8; 95% CI = 2.9 to 5.1, respectively). PPC-G also had the highest risk for periodontitis progression (RR = 5.7; 95% CI = 2.2 to 14.7). Personalized IPR scores were positively associated with both periodontitis progression and tooth loss. CONCLUSIONS:These findings, upon additional validation, suggest that the periodontal/tooth profile classes and the derived personalized propensity scores provide clinical periodontal definitions that reflect disease patterns in the population and offer a useful system for patient stratification that is predictive for disease progression and tooth loss.

Project description:The use of Next Generation Sequencing (NGS) techniques has generated a wide variety of blood microbiome data. Due to the large variation in bacterial DNA profiles between studies and the likely high concentrations of cell-free bacterial DNA in the blood, it is still not clear how such microbiome data relates to viable microbiota. For these reasons much remains to be understood about the true nature of any possible healthy blood microbiota and of bacteraemic events associated with disease. The gut, reproductive tracts, skin, and oral cavity are all likely sources of blood-borne bacteria. Oral bacteria, especially those associated with periodontal diseases, are also commonly associated with cardiovascular diseases such as infective endocarditis, and also have been linked to rheumatoid arthritis and Alzheimer's disease. Periodontal treatment, dental probing, and toothbrushing have been shown to cause transient bacteraemia and oral bacteria from the phyla Firmicutes (e.g. Streptococci) and Bacteroidetes (e.g. Porphyromonas) are found in cardiovascular lesions (CVD). Many studies of blood bacterial DNA content however, find Proteobacteria DNA to be the dominant microbiome component, suggesting a gut origin. Most studies of this type use total DNA extracted from either whole blood or blood fractions, such as buffy coat. Here, using a method that purifies DNA from intact bacterial cells only, we examined blood donated by those with active, severe periodontitis and periodontally healthy controls and show that 43-52% of bacterial species in blood are classified as oral. Firmicutes, consisting largely of members of the Streptococcus mitis group and Staphylococcus epidermidis, were predominant at 63.5% of all bacterial sequences detected in periodontal health and, little changed at 66.7% in periodontitis. Compared to studies using total DNA Proteobacteria were found here at relatively low levels in blood at 13.3% in periodontitis and 17.6% in health. This study reveals significant phylogenetic differences in blood bacterial population profiles when comparing periodontal health to periodontal disease cohorts.

Dataset Information

Achondroplasia and periodontal disease.

Publications

Achondroplasia and periodontal disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets