Genome-wide association study of periodontal pathogen colonization.

Pathological shifts of the human microbiome are characteristic of many diseases, including chronic periodontitis. To date, there is limited evidence on host genetic risk loci associated with periodontal pathogen colonization. We conducted a genome-wide association (GWA) study among 1,020 white participants of the Atherosclerosis Risk in Communities Study, whose periodontal diagnosis ranged from healthy to severe chronic periodontitis, and for whom "checkerboard" DNA-DNA hybridization quantification of 8 periodontal pathogens was performed. We examined 3 traits: "high red" and "high orange" bacterial complexes, and "high" Aggregatibacter actinomycetemcomitans (Aa) colonization. Genotyping was performed on the Affymetrix 6.0 platform. Imputation to 2.5 million markers was based on HapMap II-CEU, and a multiple-test correction was applied (genome-wide threshold of p < 5 × 10(-8)). We detected no genome-wide significant signals. However, 13 loci, including KCNK1, FBXO38, UHRF2, IL33, RUNX2, TRPS1, CAMTA1, and VAMP3, provided suggestive evidence (p < 5 × 10(-6)) of association. All associations reported for "red" and "orange" complex microbiota, but not for Aa, had the same effect direction in a second sample of 123 African-American participants. None of these polymorphisms was associated with periodontitis diagnosis. Investigations replicating these findings may lead to an improved understanding of the complex nature of host-microbiome interactions that characterizes states of health and disease.

The combined influence of genetic factors and sedentary activity on body mass changes from adolescence to young adulthood: the National Longitudinal Adolescent Health Study.

BACKGROUND: an increase in sedentary activities is likely a major contributor to the rise in obesity over the last three decades. Little research has examined interactions between genetic variants and sedentary activity on obesity phenotypes. High levels of sedentary activity during adolescence may interact with genetic factors to influence body mass changes between adolescence and young adulthood, a high risk period for weight gain. METHODS: in the National Longitudinal Study of Adolescent Health, siblings and twin pairs (16.5 ± 1.7 years) were followed into young adulthood (22.4 ± 1.8 years). Self-reported screen time (TV, video, and computer use in h/week) and body mass index (kg/m(2) ), calculated from measured height and weight at adolescence and at young adulthood, were available for 3795 participants. We employed a variance component approach to estimate the interaction between genotype and screen time for body mass changes. Additive genotype-by-screen time interactions were assessed using likelihood-ratio tests. Models were adjusted for race, age, sex, and age-by-sex interaction. RESULTS: the genetic variation in body mass changes was significantly larger in individuals with low ( δ(G) = 27.59 ± 1.58) compared with high (δ(G) = 18.76 ± 2.59) levels of screen time (p < 0.003) during adolescence. CONCLUSIONS: Our findings demonstrate that sedentary activities during adolescence may interact with genetic factors to influence body mass changes between adolescence and young adulthood. Accounting for obesity-related behaviours may improve current understanding of the genetic variation in body mass changes.

Genome-wide linkage scan for plasma high density lipoprotein cholesterol, apolipoprotein A-1 and triglyceride variation among American Indian populations: the Strong Heart Family Study.

BACKGROUND: Recent studies have identified chromosomal regions linked to variation in high density lipoprotein cholesterol (HDL-C), apolipoprotein A-1 (apo A-1) and triglyceride (TG), although results have been inconsistent and previous studies of American Indian populations are limited. OBJECTIVE: In an attempt to localise quantitative trait loci (QTLs) influencing HDL-C, apo A-1 and TG, we conducted genome-wide linkage scans of subjects of the Strong Heart Family Study. METHODS: We implemented analyses in 3484 men and women aged 18 years or older, at three study centres. RESULTS: With adjustment for age, sex and centre, we detected a QTL influencing both HDL-C (logarithm of odds (LOD) = 4.4, genome-wide p = 0.001) and apo A-1 (LOD = 3.2, genome-wide p = 0.020) nearest marker D6S289 at 6p23 in the Arizona sample. Another QTL influencing apo A-1 was found nearest marker D9S287 at 9q22.2 (LOD = 3.0, genome-wide p = 0.033) in the North and South Dakotas. We detected a QTL influencing TG nearest marker D15S153 at 15q22.31 (LOD = 4.5 in the overall sample and LOD = 3.8 in the Dakotas sample, genome-wide p = 0.0044) and when additionally adjusted for waist, current smoking, current alcohol, current oestrogen, lipid treatment, impaired fasting glucose, and diabetes, nearest marker D10S217 at 10q26.2 (LOD = 3.7, genome-wide p = 0.0058) in the Arizona population. CONCLUSIONS: The replication of QTLs in regions of the genome that harbour well known candidate genes suggest that chromosomes 6p, 9q and 15q warrant further investigation with fine mapping for causative polymorphisms in American Indians.

Longitudinal relationships between occupational and domestic physical activity patterns and body weight in China.

OBJECTIVES: To examine the longitudinal relationship between occupational and domestic sources of physical activity and body weight in a sample of Chinese adults. METHODS: Population-based longitudinal observational study of Chinese adults (4697 women and 4708 men) aged 18-55 from the 1991, 1993, 1997, and 2000 waves of the China Health and Nutrition Survey. Measured height and weight and detailed self-reported energy expenditure from multiple occupational and domestic sources were assessed over a 9-year period. Longitudinal relationships were modeled using linear random effects models. RESULTS: Increased occupational physical activity resulted in overall lower body weight for both men and women (beta-coefficients (95% confidence interval (CI)) for high levels: -0.46 (-0.76, -0.15) for men, -0.36 (-0.62, -0.10) for women, and increased domestic physical activity resulted in overall lower body weight in men (beta-coefficient (95% CI): -0.40 (-0.62, -0.18)). CONCLUSIONS: Physical activity that occurs in the occupational and domestic sectors is often overlooked; yet our research suggests they have important effects on body weight in Chinese adults. As China continues to urbanize, energy expenditure from these sources is decreasing, and our results point out the need to explore these types of physical activity more broadly across the world as potential sources of weight gain.