Association between infection of different strains of Porphyromonas gingivalis and Actinobacillus actinomycetemcomitans in subgingival plaque and clinical parameters in chronic periodontitis

Objective: The aim of this study was to investigate subgingival infection frequencies of Porphyromonas gingivalis and Actinobacillus actinomycetemcomitans strains with genetic variation in Chinese chronic periodontitis (CP) patients and to evaluate its correlation with clinical parameters. Methods: Two multiplex polymerase chain reaction (PCR) assays were developed to detect the 16SrDNA, collagenase (prtC) and fimbria (fimA) genes of P. gingivalis and the 16SrDNA, leukotoxin (lktA) and fimbria-associated protein (fap) genes of A. actinomycetemcomitans in 60 sulcus samples from 30 periodontal healthy subjects and in 122 subgingival plaque samples from 61 patients with CP. The PCR products were further T-A cloned and sent for nucleotide sequence analysis. Results: The 16SrDNA, prtC and fimA genes of P. gingivalis were detected in 92.6%, 85.2% and 80.3% of the subgingival plaque samples respectively, while the 16SrDNA, lktA and fap genes of A. actinomycetemcomitans were in 84.4%, 75.4% and 50.0% respectively. Nucleotide sequence analysis showed 98.62%~100% homology of the PCR products in these genes with the reported sequences. P. gingivalis strains with prtC+/fimA+ and A. actinomycetemcomitans with lktA+ were predominant in deep pockets (>6 mm) or in sites with attachment loss ≥5 mm than in shallow pockets (3~4 mm) or in sites with attachment loss ≤2 mm (P<0.05). P. gingivalis strains with prtC+/fimA+ also showed higher frequency in gingival index (GI)=3 than in GI=1 group (P<0.05). Conclusion: Infection of P. gingivalis with prtC+/fimA+ and A. actinomycetemcomitans with lktA+ correlates with periodontal destruction of CP in Chinese. Nonetheless P. gingivalis fimA, prtC genes and A. actinomycetemcomitans lktA gene are closely associated with periodontal destruction, while A. actinomycetemcomitans fap gene is not

Identification of symbol digit modality test score extremes in Huntington's disease

Studying individuals with extreme phenotypes could facilitate the understanding of disease modification by genetic or environmental factors. Our aim was to identify Huntington's disease (HD) patients with extreme symbol digit modality test (SDMT) scores. We first examined in HD the contribution of cognitive measures of the Unified Huntington's Disease Rating Scale (UHDRS) in predicting clinical endpoints. The language-independent SDMT was used to identify patients performing very well or very poorly relative to their CAG and age cohort. We used data from REGISTRY and COHORT observational study participants (5,603 HD participants with CAG repeats above 39 with 13,868 visits) and of 1,006 healthy volunteers (with 2,241 visits), included to identify natural aging and education effects on cognitive measures. Separate Cox proportional hazards models with CAG, age at study entry, education, sex, UHDRS total motor score and cognitive (SDMT, verbal fluency, Stroop tests) scores as covariates were used to predict clinical endpoints. Quantile regression for longitudinal language-independent SDMT data was used for boundary (2.5% and 97.5% quantiles) estimation and extreme score analyses stratified by age, education, and CAG repeat length. Ten percent of HD participants had an extreme SDMT phenotype for at least one visit. In contrast, only about 3% of participants were consistent SDMT extremes at two or more visits. The thresholds for the one-visit and two-visit extremes can be used to classify existing and new individuals. The identification of these phenotype extremes can be useful in the search for disease modifiers.Neurological Motor Disorder