Translation of mouse model to human gives insights into periodontitis etiology

To suggest candidate genes involved in periodontitis, we combined gene expression data of periodontal biopsies from Collaborative Cross (CC) mouse lines, with previous reported quantitative trait loci (QTL) in mouse and with human genome-wide association studies (GWAS) associated with periodontitis. Periodontal samples from two susceptible, two resistant and two lines that showed bone formation after periodontal infection were collected during infection and naïve status. Differential expressed genes (DEGs) were analyzed in a case-control and case-only design. After infection, eleven protein-coding genes were significantly stronger expressed in resistant CC lines compared to susceptible ones. Of these, the most upregulated genes were MMP20 (P = 0.001), RSPO4 (P = 0.032), CALB1 (P = 1.06×10-4), and AMTN (P = 0.05). In addition, human orthologous of candidate genes were tested for their association in a case-controls samples of aggressive (AgP) and chronic (CP) periodontitis (5,095 cases, 9,908 controls). In this analysis, variants at two loci, TTLL11/PTGS1 (rs9695213, P = 5.77×10-5) and RNASE2 (rs2771342, P = 2.84×10-5) suggested association with both AgP and CP. In the association analysis with AgP only, the most significant associations were located at the HLA loci HLA-DQH1 (rs9271850, P = 2.52×10-14) and HLA-DPA1 (rs17214512, P = 5.14×10-5). This study demonstrates the utility of the CC RIL populations as a suitable model to investigate the mechanism of periodontal disease

Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

Background: In mucosal barrier interfaces, flexible responses of gene expression to long-term environmental changes allow adaptation and fine-tuning for the balance of host defense and uncontrolled not-resolving inflammation. Epigenetic modifications of the chromatin confer plasticity to the genetic information and give insight into how tissues use the genetic information to adapt to environmental factors. The oral mucosa is particularly exposed to environmental stressors such as a variable microbiota. Likewise, persistent oral inflammation is the most important intrinsic risk factor for the oral inflammatory disease periodontitis and has strong potential to alter DNA-methylation patterns. The aim of the current study was to identify epigenetic changes of the oral masticatory mucosa in response to long-term inflammation that resulted in periodontitis. Methods and results: Genome-wide CpG methylation of both inflamed and clinically uninflamed solid gingival tissue biopsies of 60 periodontitis cases was analyzed using the Infinium MethylationEPIC BeadChip. We validated and performed cell-type deconvolution for infiltrated immune cells using the EpiDish algorithm. Effect sizes of DMPs in gingival epithelial and fibroblast cells were estimated and adjusted for confounding factors using our recently developed “intercept-method”. In the current EWAS, we identified various genes that showed significantly different methylation between periodontitis-inflamed and uninflamed oral mucosa in periodontitis patients. The strongest differences were observed for genes with roles in wound healing (ROBO2, PTP4A3), cell adhesion (LPXN) and innate immune response (CCL26, DNAJC1, BPI). Enrichment analyses implied a role of epigenetic changes for vesicle trafficking gene sets. Conclusions: Our results imply specific adaptations of the oral mucosa to a persistent inflammatory environment that involve wound repair, barrier integrity, and innate immune defense

Utasvédelem, utasbiztonság a mai széria autógyártásban

The authors wish to apologize for the following two errors in the original article: (i) the first name of a co-author, Huseyin Gencay Keceli, was omitted; (ii) the statement 'This research was financially supported by the Turkish Scientific and Research Council (TUBITAK) (Grant no: 114S543)' was omitted. These have both now been corrected online

Meta-analysis of genome-wide association studies of aggressive and chronic periodontitis identifies two novel risk loci

Periodontitis is one of the most common inflammatory diseases, with a prevalence of 11% worldwide for the severe forms and an estimated heritability of 50%. It is classified into the widespread moderate form chronic periodontitis (CP) and the rare early-onset and severe phenotype aggressive periodontitis (AgP). These different disease manifestations are thought to share risk alleles and predisposing environmental factors. To obtain novel insights into the shared genetic etiology and the underlying molecular mechanisms of both forms, we performed a two step-wise meta-analysis approach using genome-wide association studies of both phenotypes. Genotypes from imputed genome-wide association studies (GWAS) of AgP and CP comprising 5,095 cases and 9,908 controls of North-West European genetic background were included. Two loci were associated with periodontitis at a genome-wide significance level. They located within the pseudogene MTND1P5 on chromosome 8 (rs16870060-G, P = 3.69 × 10−9, OR = 1.36, 95% CI = [1.23–1.51]) and intronic of the long intergenic non-coding RNA LOC107984137 on chromosome 16, downstream of the gene SHISA9 (rs729876-T, P = 9.77 × 10−9, OR = 1.24, 95% CI = [1.15–1.34]). This study identified novel risk loci of periodontitis, adding to the genetic basis of AgP and CP

Association Between Telomere Length And Risk Of Cancer And Non-neoplastic Diseases: A Mendelian Randomization Study

IMPORTANCE The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. OBJECTIVE To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases. DATA SOURCES Genomewide association studies (GWAS) published up to January 15, 2015. STUDY SELECTION GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available. DATA EXTRACTION AND SYNTHESIS Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population. MAIN OUTCOMES AND MEASURES Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation. RESULTS Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [ 95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [ 95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [ 95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [ 95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [ 95% CI, 0.05-0.15]). CONCLUSIONS AND RELEVANCE It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases