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1.
J Dent Res ; 100(6): 615-622, 2021 06.
Article in English | MEDLINE | ID: mdl-33423574

ABSTRACT

Dental caries is characterized by a dysbiotic shift at the biofilm-tooth surface interface, yet comprehensive biochemical characterizations of the biofilm are scant. We used metabolomics to identify biochemical features of the supragingival biofilm associated with early childhood caries (ECC) prevalence and severity. The study's analytical sample comprised 289 children ages 3 to 5 (51% with ECC) who attended public preschools in North Carolina and were enrolled in a community-based cross-sectional study of early childhood oral health. Clinical examinations were conducted by calibrated examiners in community locations using International Caries Detection and Classification System (ICDAS) criteria. Supragingival plaque collected from the facial/buccal surfaces of all primary teeth in the upper-left quadrant was analyzed using ultra-performance liquid chromatography-tandem mass spectrometry. Associations between individual metabolites and 18 clinical traits (based on different ECC definitions and sets of tooth surfaces) were quantified using Brownian distance correlations (dCor) and linear regression modeling of log2-transformed values, applying a false discovery rate multiple testing correction. A tree-based pipeline optimization tool (TPOT)-machine learning process was used to identify the best-fitting ECC classification metabolite model. There were 503 named metabolites identified, including microbial, host, and exogenous biochemicals. Most significant ECC-metabolite associations were positive (i.e., upregulations/enrichments). The localized ECC case definition (ICDAS ≥1 caries experience within the surfaces from which plaque was collected) had the strongest correlation with the metabolome (dCor P = 8 × 10-3). Sixteen metabolites were significantly associated with ECC after multiple testing correction, including fucose (P = 3.0 × 10-6) and N-acetylneuraminate (p = 6.8 × 10-6) with higher ECC prevalence, as well as catechin (P = 4.7 × 10-6) and epicatechin (P = 2.9 × 10-6) with lower. Catechin, epicatechin, imidazole propionate, fucose, 9,10-DiHOME, and N-acetylneuraminate were among the top 15 metabolites in terms of ECC classification importance in the automated TPOT model. These supragingival biofilm metabolite findings provide novel insights in ECC biology and can serve as the basis for the development of measures of disease activity or risk assessment.


Subject(s)
Dental Caries , Child , Child, Preschool , Cross-Sectional Studies , Dental Caries/diagnosis , Dental Caries/epidemiology , Dental Caries Susceptibility , Humans , Metabolomics , North Carolina/epidemiology , Prevalence
2.
Int J Obes (Lond) ; 40(9): 1346-52, 2016 09.
Article in English | MEDLINE | ID: mdl-27121252

ABSTRACT

BACKGROUND: Recent cross-sectional genome-wide scans have reported associations of 97 independent loci with body mass index (BMI). In 3541 middle-aged adult participants from the GLACIER Study, we tested whether these loci are associated with 10-year changes in BMI and other cardiometabolic traits (fasting and 2-h glucose, triglycerides, total cholesterol, and systolic and diastolic blood pressures). METHODS: A BMI-specific genetic risk score (GRS) was calculated by summing the BMI-associated effect alleles at each locus. Trait-specific cardiometabolic GRSs comprised only the loci that show nominal association (P⩽0.10) with the respective trait in the original cross-sectional study. In longitudinal genetic association analyses, the second visit trait measure (assessed ~10 years after baseline) was used as the dependent variable and the models were adjusted for the baseline measure of the outcome trait, age, age(2), fasting time (for glucose and lipid traits), sex, follow-up time and population substructure. RESULTS: The BMI-specific GRS was associated with increased BMI at follow-up (ß=0.014 kg m(-2) per allele per 10-year follow-up, s.e.=0.006, P=0.019) as were three loci (PARK2 rs13191362, P=0.005; C6orf106 rs205262, P=0.043; and C9orf93 rs4740619, P=0.01). Although not withstanding Bonferroni correction, a handful of single-nucleotide polymorphisms was nominally associated with changes in blood pressure, glucose and lipid levels. CONCLUSIONS: Collectively, established BMI-associated loci convey modest but statistically significant time-dependent associations with long-term changes in BMI, suggesting a role for effect modification by factors that change with time in this population.


Subject(s)
Body Mass Index , Genetic Predisposition to Disease/genetics , Genome-Wide Association Study , Obesity/complications , Obesity/genetics , Polymorphism, Single Nucleotide/genetics , Blood Pressure , Cholesterol/blood , Cross-Sectional Studies , Fasting , Female , Genetic Predisposition to Disease/epidemiology , Genetic Variation , Genotype , Glucose/metabolism , Humans , Male , Middle Aged , Obesity/blood , Obesity/epidemiology , Phenotype , Prospective Studies , Triglycerides/blood
3.
Int J Obes (Lond) ; 40(1): 186-90, 2016 Jan.
Article in English | MEDLINE | ID: mdl-26278006

ABSTRACT

BACKGROUND: Obesity is a complex disease caused by the interplay of genetic and lifestyle factors, but identification of gene-lifestyle interactions in obesity has remained challenging. Few large-scale studies have reported use of genome-wide approaches to investigate gene-lifestyle interactions in obesity. METHODS: In the Pakistan Risk of Myocardial Infraction Study, a cross-sectional study based in Pakistan, we calculated body mass index (BMI) variance estimates (square of the residual of inverse-normal transformed BMI z-score) in 14 131 participants and conducted genome-wide heterogeneity of variance analyses (GWHVA) for this outcome. All analyses were adjusted for age, age(2), sex and genetic ancestry. RESULTS: The GWHVA analyses identified an intronic variant, rs140133294, in the FLJ33544 gene in association with BMI variance (P-value=3.1 × 10(-8)). In explicit tests of gene × lifestyle interaction, smoking was found to significantly modify the effect of rs140133294 on BMI (Pinteraction=0.0005), whereby the minor allele (T) was associated with lower BMI in current smokers, while positively associated with BMI in never smokers. Analyses of ENCODE data at the FLJ33534 locus revealed features indicative of open chromatin and high confidence DNA-binding motifs for several transcription factors, providing suggestive biological support for a mechanism of interaction. CONCLUSIONS: In summary, we have identified a novel interaction between smoking and variation at the FLJ33534 locus in relation to BMI in people from Pakistan.


Subject(s)
Genome-Wide Association Study , Obesity/genetics , Smoking/genetics , Adult , Asian People/genetics , Body Mass Index , Cross-Sectional Studies , Female , Genetic Predisposition to Disease , Humans , Life Style , Male , Obesity/complications , Obesity/epidemiology , Pakistan/epidemiology , Polymorphism, Single Nucleotide , Receptors, Nicotinic , Smoking/epidemiology
4.
Int J Obes (Lond) ; 35(3): 416-26, 2011 Mar.
Article in English | MEDLINE | ID: mdl-20661252

ABSTRACT

OBJECTIVE: The aim of this study was to examine the association of body mass index (BMI) and weight gain with eating at restaurants and similar establishments or eating at work among 10 European countries of the European Prospective Investigation into Cancer and Nutrition (EPIC) study. SUBJECTS: This study included a representative sample of 24,310 randomly selected EPIC participants. METHODS: Single 24-h dietary recalls with information on the place of consumption were collected using standardized procedures between 1995 and 2000. Eating at restaurants was defined to include all eating and drinking occasions at restaurants, cafeterias, bars and fast food outlets. Eating at work included all eating and drinking occasions at the workplace. Associations between eating at restaurants or eating at work and BMI or annual weight changes were assessed using sex-specific linear mixed-effects models, controlling for potential confounders. RESULTS: In southern Europe energy intake at restaurants was higher than intake at work, whereas in northern Europe eating at work appeared to contribute more to the mean daily intake than eating at restaurants. Cross-sectionally, eating at restaurants was found to be positively associated with BMI only among men (ß=+0.24, P=0.003). Essentially no association was found between BMI and eating at work among both genders. In a prospective analysis among men, eating at restaurants was found to be positively, albeit nonsignificantly, associated with weight gain (ß=+0.05, P=0.368). No association was detected between energy intake at restaurants and weight changes, controlling for total energy intake. CONCLUSION: Among men, eating at restaurants and similar establishments was associated with higher BMI and possibly weight gain.


Subject(s)
Body Weight/physiology , Eating , Energy Intake , Obesity/epidemiology , Adult , Aged , Anthropometry , Body Mass Index , Cross-Sectional Studies , Europe/epidemiology , Female , Humans , Male , Middle Aged , Prospective Studies , Restaurants , Risk Factors , Sex Factors , Weight Gain/physiology , Workplace/statistics & numerical data
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