| 1. |
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
- Burgess, S., et al.
(författare)
-
Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables
- 2010
-
Ingår i: Statistics in medicine. - : Wiley. - 1097-0258 .- 0277-6715. ; 29:12, s. 1298-311
-
Tidskriftsartikel (refereegranskat)abstract
- Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.
|
|
| 5. |
- Surendran, Praveen, et al.
(författare)
-
Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals
- 2020
-
Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 52:12, s. 1314-1332
-
Tidskriftsartikel (refereegranskat)abstract
- Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to similar to 1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency <= 0.01) variant BP associations (P < 5 x 10(-8)), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were similar to 8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
- Ahmad, Shafqat, et al.
(författare)
-
A novel interaction between the FLJ33534 locus and smoking in obesity: a genome-wide study of 14 131 Pakistani adults.
- 2016
-
Ingår i: International Journal of Obesity. - : Springer Science and Business Media LLC. - 1476-5497 .- 0307-0565. ; 40:1, s. 186-190
-
Tidskriftsartikel (refereegranskat)abstract
- BackgroundObesity 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.MethodsIn the PROMIS study, a cross-sectional study based in Pakistan, we calculated 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.ResultsThe GWHVA analyses yielded a genome-wide significance (P-value=3.1 × 10(-8)) association of the rs140133294 variant at FLJ33534 with BMI variance. 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. No interactions with physical activity were observed. 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.ConclusionIn summary, we have identified a novel interaction between smoking and variation at the FLJ33534 locus in relation to BMI in people from Pakistan.International Journal of Obesity accepted article preview online, 17 August 2015. doi:10.1038/ijo.2015.152.
|
|
| 10. |
|
|
