| 41. |
- Nettleton, Jennifer A, et al.
(författare)
-
Gene x dietary pattern interactions in obesity : analysis of up to 68 317 adults of European ancestry
- 2015
-
Ingår i: Human Molecular Genetics. - : Oxford University Press. - 0964-6906 .- 1460-2083. ; 24:16, s. 4728-4738
-
Tidskriftsartikel (refereegranskat)abstract
- Obesity is highly heritable. Genetic variants showing robust associationswith obesity traits have been identified through genome wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphismswere genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjustedWHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjustedWHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.
|
|
| 42. |
- Nettleton, Jennifer A., et al.
(författare)
-
Meta-Analysis Investigating Associations Between Healthy Diet and Fasting Glucose and Insulin Levels and Modification by Loci Associated With Glucose Homeostasis in Data From 15 Cohorts
- 2013
-
Ingår i: American Journal of Epidemiology. - : Oxford University Press (OUP). - 0002-9262 .- 1476-6256. ; 177:2, s. 103-115
-
Forskningsöversikt (refereegranskat)abstract
- Whether loci that influence fasting glucose (FG) and fasting insulin (FI) levels, as identified by genome-wide association studies, modify associations of diet with FG or FI is unknown. We utilized data from 15 US and European cohort studies comprising 51,289 persons without diabetes to test whether genotype and diet interact to influence FG or FI concentration. We constructed a diet score using study-specific quartile rankings for intakes of whole grains, fish, fruits, vegetables, and nuts/seeds (favorable) and red/processed meats, sweets, sugared beverages, and fried potatoes (unfavorable). We used linear regression within studies, followed by inverse-variance-weighted meta-analysis, to quantify 1) associations of diet score with FG and FI levels and 2) interactions of diet score with 16 FG-associated loci and 2 FI-associated loci. Diet score (per unit increase) was inversely associated with FG ( 0.004 mmol/L, 95 confidence interval: 0.005, 0.003) and FI ( 0.008 ln-pmol/L, 95 confidence interval: 0.009, 0.007) levels after adjustment for demographic factors, lifestyle, and body mass index. Genotype variation at the studied loci did not modify these associations. Healthier diets were associated with lower FG and FI concentrations regardless of genotype at previously replicated FG- and FI-associated loci. Studies focusing on genomic regions that do not yield highly statistically significant associations from main-effect genome-wide association studies may be more fruitful in identifying diet-gene interactions.
|
|
| 43. |
|
|
| 44. |
|
|
| 45. |
- Saleheen, Danish, et al.
(författare)
-
Loss of Cardioprotective Effects at the ADAMTS7 Locus as a Result of Gene-Smoking Interactions
- 2017
-
Ingår i: Circulation. - 0009-7322 .- 1524-4539. ; 135:24, s. 2336-2353
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Common diseases such as coronary heart disease (CHD) are complex in etiology. The interaction of genetic susceptibility with lifestyle factors may play a prominent role. However, gene-lifestyle interactions for CHD have been difficult to identify. Here, we investigate interaction of smoking behavior, a potent lifestyle factor, with genotypes that have been shown to associate with CHD risk.METHODS: We analyzed data on 60 919 CHD cases and 80 243 controls from 29 studies for gene-smoking interactions for genetic variants at 45 loci previously reported to be associated with CHD risk. We also studied 5 loci associated with smoking behavior. Study-specific gene-smoking interaction effects were calculated and pooled using fixed-effects meta-analyses. Interaction analyses were declared to be significant at a P value of < 1.0x10-3 (Bonferroni correction for 50 tests).RESULTS: We identified novel gene-smoking interaction for a variant upstream of the ADAMTS7 gene. Every T allele of rs7178051 was associated with lower CHD risk by 12% in never-smokers (P= 1.3x10(-16)) in comparison with 5% in ever-smokers (P= 2.5x10-4), translating to a 60% loss of CHD protection conferred by this allelic variation in people who smoked tobacco (interaction P value= 8.7x10-5). The protective T allele at rs7178051 was also associated with reduced ADAMTS7 expression in human aortic endothelial cells and lymphoblastoid cell lines. Exposure of human coronary artery smooth muscle cells to cigarette smoke extract led to induction of ADAMTS7.CONCLUSIONS: Allelic variation at rs7178051 that associates with reduced ADAMTS7 expression confers stronger CHD protection in never-smokers than in ever-smokers. Increased vascular ADAMTS7 expression may contribute to the loss of CHD protection in smokers.
|
|
| 46. |
|
|
| 47. |
- Ahmad, Shafqat, et al.
(författare)
-
Gene × physical activity interactions in obesity: combined analysis of 111,421 individuals of European ancestry. : combined analysis of 111,421 individuals of European ancestry
- 2013
-
Ingår i: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 9:7, s. 1003607-1003607
-
Tidskriftsartikel (refereegranskat)abstract
- Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age(2), sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.
|
|
| 48. |
- Ahmad, Shafqat, et al.
(författare)
-
Gene x physical activity interactions in obesity : combined analysis of 111,421 individuals of European ancestry
- 2013
-
Ingår i: PLOS Genetics. - : Public Library of Science. - 1553-7390 .- 1553-7404. ; 9:7, s. e1003607-
-
Tidskriftsartikel (refereegranskat)abstract
- Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age(2), sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS x physical activity interaction effect estimate (P-interaction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, P-interaction = 0.014 vs. n = 71,611, P-interaction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (P-interaction = 0.003) and the SEC16B rs10913469 (P-interaction = 0.025) variants showed evidence of SNP x physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.
|
|
| 49. |
- Campbell, William, et al.
(författare)
-
Prediction impact curve is a new measure integrating intervention effects in the evaluation of risk models
- 2016
-
Ingår i: Journal of Clinical Epidemiology. - : Elsevier BV. - 0895-4356 .- 1878-5921. ; 69, s. 89-95
-
Tidskriftsartikel (refereegranskat)abstract
- Objective: We propose a new measure of assessing the performance of risk models, the area under the prediction impact curve (auPIC), which quantifies the performance of risk models in terms of their average health impact in the population. Study Design and Setting: Using simulated data, we explain how the prediction impact curve (PIC) estimates the percentage of events prevented when a risk model is used to assign high-risk individuals to an intervention. We apply the PIC to the Atherosclerosis Risk in Communities (ARIC) Study to illustrate its application toward prevention of coronary heart disease. Results: We estimated that if the ARIC cohort received statins at baseline, 5% of events would be prevented when the risk model was evaluated at a cutoff threshold of 20% predicted risk compared to 1% when individuals were assigned to the intervention without the use of a model. By calculating the auPIC, we estimated that an average of 15% of events would be prevented when considering performance across the entire interval. Conclusion: We conclude that the PIC is a clinically meaningful measure for quantifying the expected health impact of risk models that supplements existing measures of model performance.
|
|
| 50. |
|
|
