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- Ding, Ming, et al.
(författare)
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Dairy consumption, systolic blood pressure, and risk of hypertension : Mendelian randomization study
- 2017
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Ingår i: The BMJ. - : BMJ Publishing Group Ltd. - 1756-1833 .- 0959-8138. ; 356
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE To examine whether previous observed inverse associations of dairy intake with systolic blood pressure and risk of hypertension were causal. DESIGN Mendelian randomization study using the single nucleotide polymorphism rs4988235 related to lactase persistence as an instrumental variable. SETTING CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium. PARTICIPANTS Data from 22 studies with 171 213 participants, and an additional 10 published prospective studies with 26 119 participants included in the observational analysis. MAIN OUTCOME MEASURES The instrumental variable estimation was conducted using the ratio of coefficients approach. Using metaanalysis, an additional eight published randomized clinical trials on the association of dairy consumption with systolic blood pressure were summarized. RESULTS Compared with the CC genotype (CC is associated with complete lactase deficiency), the CT/TT genotype (TT is associated with lactose persistence, and CT is associated with certain lactase deficiency) of LCT-13910 (lactase persistence gene) rs4988235 was associated with higher dairy consumption (0.23 (about 55 g/day), 95% confidence interval 0.17 to 0.29) serving/day; P<0.001) and was not associated with systolic blood pressure (0.31, 95% confidence interval -0.05 to 0.68 mm Hg; P=0.09) or risk of hypertension (odds ratio 1.01, 95% confidence interval 0.97 to 1.05; P=0.27). Using LCT-13910 rs4988235 as the instrumental variable, genetically determined dairy consumption was not associated with systolic blood pressure (beta=1.35, 95% confidence interval -0.28 to 2.97 mm Hg for each serving/day) or risk of hypertension (odds ratio 1.04, 0.88 to 1.24). Moreover, meta-analysis of the published clinical trials showed that higher dairy intake has no significant effect on change in systolic blood pressure for interventions over one month to 12 months (intervention compared with control groups: beta=-0.21, 95% confidence interval -0.98 to 0.57 mm Hg). In observational analysis, each serving/day increase in dairy consumption was associated with -0.11 (95% confidence interval -0.20 to -0.02 mm Hg; P=0.02) lower systolic blood pressure but not risk of hypertension (odds ratio 0.98, 0.97 to 1.00; P=0.11). CONCLUSION The weak inverse association between dairy intake and systolic blood pressure in observational studies was not supported by a comprehensive instrumental variable analysis and systematic review of existing clinical trials.
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| 2. |
- Johannesson, Magnus, et al.
(författare)
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Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies
- 2017
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Ingår i: PLoS Genetics. - : Public Library of Science. - 1553-7404 .- 1553-7390. ; 13:1, s. 1-23
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Tidskriftsartikel (refereegranskat)abstract
- Large-scale genome-wide association results are typically obtained from a fixed-effects meta-analysis of GWAS summary statistics from multiple studies spanning different regions and/or time periods. This approach averages the estimated effects of genetic variants across studies. In case genetic effects are heterogeneous across studies, the statistical power of a GWAS and the predictive accuracy of polygenic scores are attenuated, contributing to the so-called ‘missing heritability’. Here, we describe the online Meta-GWAS Accuracy and Power (MetaGAP) calculator (available at www.devlaming.eu) which quantifies this attenuation based on a novel multi-study framework. By means of simulation studies, we show that under a wide range of genetic architectures, the statistical power and predictive accuracy provided by this calculator are accurate. We compare the predictions from the MetaGAP calculator with actual results obtained in the GWAS literature. Specifically, we use genomic-relatedness-matrix restricted maximum likelihood to estimate the SNP heritability and cross-study genetic correlation of height, BMI, years of education, and self-rated health in three large samples. These estimates are used as input parameters for the MetaGAP calculator. Results from the calculator suggest that cross-study heterogeneity has led to attenuation of statistical power and predictive accuracy in recent large-scale GWAS efforts on these traits (e.g., for years of education, we estimate a relative loss of 51–62% in the number of genome-wide significant loci and a relative loss in polygenic score R2of 36–38%). Hence, cross-study heterogeneity contributes to the missing heritability.
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