| 1. |
- Sennblad, Bengt, et al.
(författare)
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Genome- wide association study with additional genetic and post-transcriptional analyses reveals novel regulators of plasma factor XI levels
- 2017
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 26:3, s. 637-649
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Tidskriftsartikel (refereegranskat)abstract
- Coagulation factor XI (FXI) has become increasingly interesting for its role in pathogenesis of thrombosis. While elevated plasma levels of FXI have been associated with venous thromboembolism and ischemic stroke, its deficiency is associated with mild bleeding. We aimed to determine novel genetic and post-transcriptional plasma FXI regulators. We performed a genome-wide association study (GWAS) for plasma FXI levels, using novel data imputed to the 1000 Genomes reference panel. Individual GWAS analyses, including a total of 16,169 European individuals from the ARIC, GHS, MARTHA and PROCARDIS studies, were meta-analysed and further replicated in 2,045 individuals from the F5L family, GAIT2 and MEGA studies. Additional association with activated partial thromboplastin time (aPTT) was tested for the top SNPs. In addition, a study on the effect of miRNA on FXI regulation was performed using in silico prediction tools and in vitro luciferase assays. Three loci showed robust, replicating association with circulating FXI levels: KNG1 (rs710446, P-value = 2.07 x 10(-302)), F11 (rs4253417, P-value = 2.86 x 10(-193)), and a novel association in GCKR (rs780094, P-value = 3.56 x 10(-09)), here for the first time implicated in FXI regulation. The two first SNPs (rs710446 and rs4253417) also associated with aPTT. Conditional and haplotype analyses demonstrated a complex association signal, with additional novel SNPs modulating plasma FXI levels in both the F11 and KNG1 loci. Finally, eight miRNAs were predicted to bind F11 mRNA. Over-expression of either miR-145 or miR-181 significantly reduced the luciferase activity in cells transfected with a plasmid containing FXI-3'UTR. These results should open the door to new therapeutic targets for thrombosis prevention.
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| 2. |
- Frånberg, Mattias, 1985-, et al.
(författare)
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Fast and general tests of genetic interaction for genome-wide association studies
- 2017
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Ingår i: PloS Computational Biology. - : PUBLIC LIBRARY SCIENCE. - 1553-734X .- 1553-7358. ; 13:6
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Tidskriftsartikel (refereegranskat)abstract
- A complex disease has, by definition, multiple genetic causes. In theory, these causes could be identified individually, but their identification will likely benefit from informed use of anticipated interactions between causes. In addition, characterizing and understanding interactions must be considered key to revealing the etiology of any complex disease. Large-scale collaborative efforts are now paving the way for comprehensive studies of interaction. As a consequence, there is a need for methods with a computational efficiency sufficient for modern data sets as well as for improvements of statistical accuracy and power. Another issue is that, currently, the relation between different methods for interaction inference is in many cases not transparent, complicating the comparison and interpretation of results between different interaction studies. In this paper we present computationally efficient tests of interaction for the complete family of generalized linear models (GLMs). The tests can be applied for inference of single or multiple interaction parameters, but we show, by simulation, that jointly testing the full set of interaction parameters yields superior power and control of false positive rate. Based on these tests we also describe how to combine results from multiple independent studies of interaction in a meta-analysis. We investigate the impact of several assumptions commonly made when modeling interactions. We also show that, across the important class of models with a full set of interaction parameters, jointly testing the interaction parameters yields identical results. Further, we apply our method to genetic data for cardiovascular disease. This allowed us to identify a putative interaction involved in Lp(a) plasma levels between two 'tag' variants in the LPA locus (p = 2.42 . 10(-09)) as well as replicate the interaction (p = 6.97 . 10(-07)). Finally, our meta-analysis method is used in a small (N = 16,181) study of interactions in myocardial infarction.
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| 3. |
- Evangelou, Evangelos, et al.
(författare)
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Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.
- 2018
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 50:10, s. 1412-1425
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Tidskriftsartikel (refereegranskat)abstract
- High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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| 4. |
- Frånberg, Mattias, 1985-, et al.
(författare)
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Discovering Genetic Interactions in Large-Scale Association Studies by Stage-wise Likelihood Ratio Tests
- 2015
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 11:9
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Tidskriftsartikel (refereegranskat)abstract
- Despite the success of genome-wide association studies in medical genetics, the underlying genetics of many complex diseases remains enigmatic. One plausible reason for this could be the failure to account for the presence of genetic interactions in current analyses. Exhaustive investigations of interactions are typically infeasible because the vast number of possible interactions impose hard statistical and computational challenges. There is, therefore, a need for computationally efficient methods that build on models appropriately capturing interaction. We introduce a new methodology where we augment the interaction hypothesis with a set of simpler hypotheses that are tested, in order of their complexity, against a saturated alternative hypothesis representing interaction. This sequential testing provides an efficient way to reduce the number of non-interacting variant pairs before the final interaction test. We devise two different methods, one that relies on a priori estimated numbers of marginally associated variants to correct for multiple tests, and a second that does this adaptively. We show that our methodology in general has an improved statistical power in comparison to seven other methods, and, using the idea of closed testing, that it controls the family-wise error rate. We apply our methodology to genetic data from the PRO-CARDIS coronary artery disease case/control cohort and discover three distinct interactions. While analyses on simulated data suggest that the statistical power may suffice for an exhaustive search of all variant pairs in ideal cases, we explore strategies for a priori selecting subsets of variant pairs to test. Our new methodology facilitates identification of new disease-relevant interactions from existing and future genome-wide association data, which may involve genes with previously unknown association to the disease. Moreover, it enables construction of interaction networks that provide a systems biology view of complex diseases, serving as a basis for more comprehensive understanding of disease pathophysiology and its clinical consequences.
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| 5. |
- Joshi, Peter K, et al.
(författare)
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Directional dominance on stature and cognition in diverse human populations
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 523:7561, s. 459-462
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Tidskriftsartikel (refereegranskat)abstract
- Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
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| 6. |
- Persson, Jonas, et al.
(författare)
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Sex-Specific Effects of Adiponectin on Carotid Intima-Media Thickness and Incident Cardiovascular Disease
- 2015
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Ingår i: Journal of the American Heart Association. - : WILEY-BLACKWELL. - 2047-9980 .- 2047-9980. ; 4:8
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Tidskriftsartikel (refereegranskat)abstract
- Background-Plasma adiponectin levels have previously been inversely associated with carotid intima-media thickness (IMT), a marker of subclinical atherosclerosis. In this study, we used a sex-stratified Mendelian randomization approach to investigate whether adiponectin has a causal protective influence on IMT. Methods and Results-Baseline plasma adiponectin concentrationwas tested for association with baseline IMT, IMT progression over 30 months, and occurrence of cardiovascular events within 3 years in 3430 participants (women, n=1777; men, n=1653) with high cardiovascular risk but no prevalent disease. Plasma adiponectin levels were inversely associated with baseline mean bifurcation IMT after adjustment for established risk factors (beta=-0.018, P<0.001) in men but not in women (beta=-0.006, P=0.185; P for interaction=0.061). Adiponectin levels were inversely associated with progression of mean common carotid IMT in men (beta=-0.0022, P=0.047), whereas no association was seen in women (0.0007, P=0.475; P for interaction=0.018). Moreover, we observed that adiponectin levels were inversely associated with coronary events in women (hazard ratio 0.57, 95% CI 0.37 to 0.87) but not in men (hazard ratio 0.82,95% CI0.54 to 1.25). Agenescore of adiponectin-raisingalleles in6loci, reported recently inalarge multi-ethnic metaanalysis, was inversely associated with baseline mean bifurcation IMT in men (beta=-0.0008, P=0.004) but not in women (beta=-0.0003, P=0.522; P for interaction=0.007). Conclusions-This report provides some evidence for adiponectin protecting against atherosclerosis, with effects being confined to men; however, compared with established cardiovascular risk factors, the effect of plasma adiponectin was modest. Further investigation involving mechanistic studies is warranted.
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| 7. |
- Wessel, Jennifer, et al.
(författare)
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Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility
- 2015
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF = 1.4%) with lower FG (beta = -0.09 +/- 0.01 mmol l(-1), P = 3.4 x 10(-12)), T2D risk (OR[95% CI] = 0.86[0.76-0.96], P = 0.010), early insulin secretion (beta = -0.07 +/- 0.035 pmol(insulin) mmol(glucose)(-1), P = 0.048), but higher 2-h glucose (beta = 0.16 +/- 0.05 mmol l(-1), P = 4.3 x 10(-4)). We identify a gene-based association with FG at G6PC2 (p(SKAT) = 6.8 x 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF = 20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (beta = 0.02 +/- 0.004 mmol l(-1), P = 1.3 x 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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| 8. |
- de Vries, Paul S., et al.
(författare)
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Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study
- 2017
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5x10(-8) is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5x10(-8)), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.
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| 9. |
- Frånberg, Mattias, 1985-
(författare)
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Statistical methods for detecting gene-gene and gene-environment interactions in genome-wide association studies
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Despite considerable effort to elucidate the genetic architecture of multi-factorial traits and diseases, there remains a gap between the estimated heritability (e.g., from twin studies) and the heritability explained by discovered genetic variants. The existence of interactions between different genes, and between genes and the environment, has frequently been hypothesized as a likely cause of this discrepancy. However, the statistical inference of interactions is plagued by limited sample sizes, high computational requirements, and incomplete knowledge of how the measurement scale and parameterization affect the analysis.This thesis addresses the major statistical, computational, and modeling issues that hamper large-scale interaction studies today. Furthermore, it investigates whether gene-gene and gene-environment interactions are significantly involved in the development of diseases linked to atherosclerosis. Firstly, I develop two statistical methods that can be used to study of gene-gene interactions: the first is tailored for limited sample size situations, and the second enables multiple analyses to be combined into large meta-analyses. I perform comprehensive simulation studies to determine that these methods have higher or equal statistical power than contemporary methods, scale-invariance is required to guard against false positives, and that saturated parameterizations perform well in terms of statistical power. In two studies, I apply the two proposed methods to case/control data from myocardial infarction and associated phenotypes. In both studies, we identify putative interactions for myocardial infarction but are unable to replicate the interactions in a separate cohort. In the second study, however, we identify and replicate a putative interaction involved in Lp(a) plasma levels between two variants rs3103353 and rs9458157. Secondly, I develop a multivariate statistical method that simultaneously estimates the effects of genetic variants, environmental variables, and their interactions. I show by extensive simulations that this method achieves statistical power close to the optimal oracle method. We use this method to study the involvement of gene-environment interactions in intima-media thickness, a phenotype relevant for coronary artery disease. We identify a putative interaction between a genetic variant in the KCTD8 gene and alcohol use, thus suggesting an influence on intima-media thickness. The methods developed to support the analyses in this thesis as well as a selection of other prominent methods in the field is implemented in a software package called besiq.In conclusion, this thesis presents statistical methods, and the associated software, that allows large-scale studies of gene-gene and gene-environment interactions to be effortlessly undertaken.
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| 10. |
- Gaulton, Kyle J, et al.
(författare)
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Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.
- 2015
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 47:12, s. 1415-1415
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Tidskriftsartikel (refereegranskat)abstract
- We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
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