| 1. |
- Ahmad, Shafqat, et al.
(författare)
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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
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Ingår i: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 9:7, s. 1003607-1003607
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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.
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| 2. |
- Ahmad, Shafqat, et al.
(författare)
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Gene x physical activity interactions in obesity : combined analysis of 111,421 individuals of European ancestry
- 2013
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Ingår i: PLOS Genetics. - : Public Library of Science. - 1553-7390 .- 1553-7404. ; 9:7, s. e1003607-
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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.
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| 3. |
- Berndt, Sonja I., et al.
(författare)
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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
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Tidskriftsartikel (refereegranskat)abstract
- Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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| 4. |
- Do, Ron, et al.
(författare)
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Common variants associated with plasma triglycerides and risk for coronary artery disease
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:11, s. 1345-
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Tidskriftsartikel (refereegranskat)abstract
- Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 x 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
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| 5. |
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| 6. |
- Ganna, Andrea, 1985-, et al.
(författare)
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Genetic determinants of mortality : Can findings from genome-wide association studies explain variation in human mortality?
- 2013
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Ingår i: Human Genetics. - : Springer Science and Business Media LLC. - 0340-6717 .- 1432-1203. ; 132:5, s. 553-561
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Tidskriftsartikel (refereegranskat)abstract
- Twin studies have estimated the heritability of longevity to be approximately 20-30 %. Genome-wide association studies (GWAS) have revealed a large number of determinants of morbidity, but so far, no new polymorphisms have been discovered to be associated with longevity per se in GWAS. We aim to determine whether the genetic architecture of mortality can be explained by single nucleotide polymorphisms (SNPs) associated with common traits and diseases related to mortality. By extensive quality control of published GWAS we created a genetic score from 707 common SNPs associated with 125 diseases or risk factors related with overall mortality. We prospectively studied the association of the genetic score with: (1) time-to-death; (2) incidence of the first of nine major diseases (coronary heart disease, stroke, heart failure, diabetes, dementia, lung, breast, colon and prostate cancers) in two population-based cohorts of Dutch and Swedish individuals (N = 15,039; age range 47-99 years). During a median follow-up of 6.3 years (max 22.2 years), we observed 4,318 deaths and 2,132 incident disease events. The genetic score was significantly associated with time-to-death [hazard ratio (HR) per added risk allele = 1.003, P value = 0.006; HR 4th vs. 1st quartile = 1.103]. The association between the genetic score and incidence of major diseases was stronger (HR per added risk allele = 1.004, P value = 0.002; HR 4th vs. 1st quartile = 1.160). Associations were stronger for individuals dying at older ages. Our findings are compatible with the view of mortality as a complex and highly polygenetic trait, not easily explainable by common genetic variants related to diseases and physiological traits.
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| 7. |
- Ganna, Andrea, et al.
(författare)
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Multilocus Genetic Risk Scores for Coronary Heart Disease Prediction
- 2013
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Ingår i: Arteriosclerosis, Thrombosis and Vascular Biology. - : Lippincott Williams & Wilkins. - 1079-5642 .- 1524-4636. ; 33:9, s. 2267-2272
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Tidskriftsartikel (refereegranskat)abstract
- Objective-Current guidelines do not support the use of genetic profiles in risk assessment of coronary heart disease (CHD). However, new single nucleotide polymorphisms associated with CHD and intermediate cardiovascular traits have recently been discovered. We aimed to compare several multilocus genetic risk score (MGRS) in terms of association with CHD and to evaluate clinical use. Approach and Results-We investigated 6 Swedish prospective cohort studies with 10 612 participants free of CHD at baseline. We developed 1 overall MGRS based on 395 single nucleotide polymorphisms reported as being associated with cardiovascular traits, 1 CHD-specific MGRS, including 46 single nucleotide polymorphisms, and 6 trait-specific MGRS for each established CHD risk factors. Both the overall and the CHD-specific MGRS were significantly associated with CHD risk (781 incident events; hazard ratios for fourth versus first quartile, 1.54 and 1.52; P<0.001) and improved risk classification beyond established risk factors (net reclassification improvement, 4.2% and 4.9%; P=0.006 and 0.017). Discrimination improvement was modest (C-index improvement, 0.004). A polygene MGRS performed worse than the CHD-specific MGRS. We estimate that 1 additional CHD event for every 318 people screened at intermediate risk could be saved by measuring the CHD-specific genetic score in addition to the established risk factors. Conclusions-Our results indicate that genetic information could be of some clinical value for prediction of CHD, although further studies are needed to address aspects, such as feasibility, ethics, and cost efficiency of genetic profiling in the primary prevention setting.
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| 8. |
- Ganna, Andrea, et al.
(författare)
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Utilizing Twins as Controls for Non-Twin Case-Materials in Genome Wide Association Studies
- 2013
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:12, s. e83101-
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Tidskriftsartikel (refereegranskat)abstract
- Twin registries around the globe have collected DNA samples from large numbers of monozygotic and dizygotic twins. The twin sample collections are frequently used as controls in disease-specific studies together with non-twins. This approach is unbiased under the hypothesis that twins and singletons are comparable in terms of allele frequencies; i.e. there are no genetic variants associated with being a twin per se. To test this hypothesis we performed a genome-wide association study comparing the allele frequency of 572,352 single nucleotide polymorphisms (SNPs) in 1,413 monozygotic (MZ) and 5,451 dizygotic (DZ) twins with 3,720 healthy singletons. Twins and singletons have been genotyped using the same platform. SNPs showing association with being a twin at P-value < 1 × 10-5 were selected for replication analysis in 1,492 twins (463 MZ and 1,029 DZ) and 1,880 singletons from Finland. No SNPs reached genome-wide significance (P-value < 5 × 10-8) in the main analysis combining MZ and DZ twins. In a secondary analysis including only DZ twins two SNPs (rs2033541 close to ADAMTSL1 and rs4149283 close to ABCA1) were genome-wide significant after meta-analysis with the Finnish population. The estimated proportion of variance on the liability scale explained by all SNPs was 0.08 (P-value=0.003) when MZ and DZ were considered together and smaller for MZ (0.06, P-value=0.10) compared to DZ (0.09, P-value=0.003) when analyzed separately. In conclusion, twins and singletons can be used in genetic studies together with general population samples without introducing large bias. Further research is needed to explore genetic variances associated with DZ twinning.
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| 9. |
- Hruby, Adela, et al.
(författare)
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Higher Magnesium Intake Is Associated with Lower Fasting Glucose and Insulin, with No Evidence of Interaction with Select Genetic Loci, in a Meta-Analysis of 15 CHARGE Consortium Studies
- 2013
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Ingår i: Journal of Nutrition. - : Elsevier BV. - 0022-3166 .- 1541-6100. ; 143:3, s. 345-353
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Tidskriftsartikel (refereegranskat)abstract
- Favorable associations between magnesium intake and glycemic traits, such as fasting glucose and insulin, are observed in observational and clinical studies, but whether genetic variation affects these associations is largely unknown. We hypothesized that single nucleotide polymorphisms (SNPs) associated with either glycemic traits or magnesium metabolism affect the association between magnesium intake and fasting glucose and insulin. Fifteen studies from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided data from up to 52,684 participants of European descent without known diabetes. In fixed-effects meta-analyses, we quantified 1) cross-sectional associations of dietary magnesium intake with fasting glucose (mmol/L) and insulin (In-pmol/L) and 2) interactions between magnesium intake and SNPs related to fasting glucose (16 SNPs), insulin (2 SNPs), or magnesium (8 SNPs) on fasting glucose and insulin. After adjustment for age, sex, energy intake, BMI, and behavioral risk factors, magnesium (per 50-mg/d increment) was inversely associated with fasting glucose [beta = -0.009 mmol/L (95% CI: -0.013, -0.005), P< 0.0001] and insulin (-0.020 In-pmo/L (95% CI: -0.024, -0.017), P< 0.0001]. No magnesium-related SNP or interaction between any SNP and magnesium reached significance after correction for multiple testing. However, rs2274924 in magnesium transporter-encoding TRPM6 showed a nominal association (uncorrected P= 0.03) with glucose, and rs11558471 in SLC30A8and rs3740393 near CNNM2showed a nominal interaction (uncorrected, both P = 0.02) with magnesium on glucose. Consistent with other studies, a higher magnesium intake was associated with lower fasting glucose and insulin. Nominal evidence of TRPM6 influence and magnesium interaction with select loci suggests that further investigation is warranted. J. Nutr. 143: 345-353, 2013.
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| 10. |
- Hu, Yi-Juan, et al.
(författare)
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Meta-analysis of Gene-Level Associations for Rare Variants Based on Single-Variant Statistics
- 2013
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 93:2, s. 236-248
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Tidskriftsartikel (refereegranskat)abstract
- Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recoVered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
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