Childhood Oral Infections Associate with Adulthood Metabolic Syndrome: A Longitudinal Cohort Study

Chronic oral infection/inflammation is cross-sectionally associated with metabolic syndrome (MetS) in adults, but there are few longitudinal studies and studies on childhood oral infections and adult MetS risk. We investigated whether childhood clinical parameters indicative of oral infection/inflammation were associated with adulthood MetS and its components. A total of 755 children aged 6, 9, and 12 y underwent a clinical oral examination in 1980 as part of the Cardiovascular Risk in Young Finns Study. Oral health measures included bleeding on probing (BOP), periodontal probing pocket depth, caries, fillings, and visible plaque. Metabolic parameters were determined at baseline and during follow-up. MetS was diagnosed (n = 588, 77.9%) in the adulthood at 21 y (in 2001), 27 y (in 2007), and 31 y (in 2011) after the oral assessment, when the participants were 27 to 43 y old. Regression analyses were adjusted for childhood age, sex, body mass index, and family income, as well as adulthood smoking and education level. In adulthood, MetS was diagnosed in 11.9% (2001), 18.7% (2007), and 20.7% (2011) of participants at the 3 follow-ups. Childhood caries and fillings were associated with increased risk of adult MetS (risk ratio [95% CI], 1.25 [0.90 to 2.45] and 1.27 [1.02 to 1.99]) and with increased systolic blood pressure (1.78 [1.01 to 4.26] and 2.48 [1.11 to 4.12]) and waist circumference (2.25 [1.02 to 4.99] and 1.56 [1.01 to 3.25]), whereas BOP and visible plaque were associated with plasma glucose (1.97 [1.08 to 3.60] and 1.88 [1.00 to 3.53]). Severity of BOP (P = 0.015) and caries (P = 0.005) and teeth with plaque (P = 0.027) were associated with number of MetS components. No such trends were seen with probing pocket depth. Childhood oral infection/inflammation was associated with adverse metabolic parameters and MetS in adulthood

Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium

Genetic risk factors play important roles in the etiology of oral, dental, and craniofacial diseases. Identifying the relevant risk loci and understanding their molecular biology could highlight new prevention and management avenues. Our current understanding of oral health genomics suggests that dental caries and periodontitis are polygenic diseases, and very large sample sizes and informative phenotypic measures are required to discover signals and adequately map associations across the human genome. In this article, we introduce the second wave of the Gene-Lifestyle Interactions and Dental Endpoints consortium (GLIDE2) and discuss relevant data analytics challenges, opportunities, and applications. In this phase, the consortium comprises a diverse, multiethnic sample of over 700,000 participants from 21 studies contributing clinical data on dental caries experience and periodontitis. We outline the methodological challenges of combining data from heterogeneous populations, as well as the data reduction problem in resolving detailed clinical examination records into tractable phenotypes, and describe a strategy that addresses this. Specifically, we propose a 3-tiered phenotyping approach aimed at leveraging both the large sample size in the consortium and the detailed clinical information available in some studies, wherein binary, severity-encompassing, and ?precision,? data-driven clinical traits are employed. As an illustration of the use of data-driven traits across multiple cohorts, we present an application of dental caries experience data harmonization in 8 participating studies (N = 55,143) using previously developed permanent dentition tooth surface?level dental caries pattern traits. We demonstrate that these clinical patterns are transferable across multiple cohorts, have similar relative contributions within each study, and thus are prime targets for genetic interrogation in the expanded and diverse multiethnic sample of GLIDE2. We anticipate that results from GLIDE2 will decisively advance the knowledge base of mechanisms at play in oral, dental, and craniofacial health and disease and further catalyze international collaboration and data and resource sharing in genomics research

Matrix metalloproteinase (MMP)-8 and tissue inhibitor of MMP-1 (TIMP-1) gene polymorphisms in generalized aggressive periodontitis: Gingival crevicular fluid MMP-8 and TIMP-1 levels and outcome of periodontal therapy

PubMed ID: 24283658Background: The aim of the present study is to investigate matrix metalloproteinase (MMP)-8 and tissue inhibitor of MMP-1 (TIMP-1) gene polymorphisms in generalized aggressive periodontitis (GAgP) and to assess the effects of MMP-8 and TIMP-1 genotypes on the outcomes of non-surgical periodontal therapy. Methods: Genomic DNA was obtained from peripheral blood of 100 patients with GAgP and 167 periodontally healthy controls. MMP-8 +17 C/G, -799 C/T, -381 A/G and TIMP-1 372 T/C, *429 T/G polymorphisms were determined by polymerase chain reaction-restriction fragment length polymorphism. Patients with GAgP received non-surgical periodontal therapy and were followed for 6 months. Clinical periodontal parameters and gingival crevicular fluid (GCF) samples were collected at baseline and at follow-up visits. GCF biomarkers were analyzed by immunofluorescence assay and enzyme-linked immunosorbent assay. Results: Distribution of the MMP-8-799 C/T genotypes was significantly different between the GAgP and control groups (P <0.005). TIMP-1 372 T/C and *429 T/G genotypes in males were also significantly different between study groups (P <0.004). GCF MMP-8 levels decreased until 3 months after non-surgical therapy compared with baseline in T and G alleles, as well as G and C allele carriers (P <0.0125), whereas no significant decreased was observed in non-carriers (P >0.0125). Conclusion: On the basis of the present findings, it can be suggested that MMP-8-799 C/T and TIMP-1 372 T/C, *429 T/G gene polymorphisms in males may be associated with the susceptibility to GAgP in the Turkish population

Model documentation for the European Forest Information Scenario model (EFISCEN 3.1.3)

EFISCEN is a forest resource projection model, used to gain insight into the future development of European forests. It has been used widely to study issues such as sustainable management regimes, wood production possibilities, nature oriented management, climate change impacts, natural disturbances and carbon balance issues. This report describes the history of EFISCEN and the current state of the model, version 3.1.3. It contains a user guide as well as a description of past validations and an uncertainty analysi