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Johansson, Åsa
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Publications (10 of 91) Show all publications
Ek, W. E., Ahsan, M., Rask-Andersen, M., Liang, L., Moffatt, M. F., Gyllensten, U. & Johansson, Å. (2017). Epigenome-wide DNA methylation study of IgE concentration in relation to self-reported allergies. Epigenomics, 9(4), 407-418.
Open this publication in new window or tab >>Epigenome-wide DNA methylation study of IgE concentration in relation to self-reported allergies
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2017 (English)In: Epigenomics, ISSN 1750-1911, Vol. 9, no 4, 407-418 p.Article in journal (Refereed) Published
Abstract [en]

AIM: Epigenetic mechanisms are critical for normal immune development and epigenetic alterations might therefore be possible contributors to immune diseases. To investigate if DNA methylation in whole blood is associated with total and allergen-specific IgE levels.

METHODS: We performed an epigenome-wide association study to investigate the association between DNA methylation and IgE level, allergen-specific IgE and self-reported immune diseases and allergies in 728 individuals.

RESULTS: We identified and replicated 15 CpG sites associated with IgE, mapping to biologically relevant genes, including ACOT7, ILR5A, KCNH2, PRG2 and EPX. A total of 331 loci were associated with allergen-specific IgE, but none of these CpG sites were associated with self-reported allergies and immune diseases.

CONCLUSION: This study shows that IgE levels are associated with DNA methylation levels at numerous CpG sites, which might provide new leads for investigating the links between IgE and allergic inflammation.

Keyword
DNA methylation, Fx5, IgE, Phadiatop, allergy, immune diseases
National Category
Medical Genetics
Identifiers
urn:nbn:se:uu:diva-318034 (URN)10.2217/epi-2016-0158 (DOI)000399344700006 ()28322575 (PubMedID)
Funder
Swedish Society of Medicine, 2011-2354 K2007-66X-20270-01-3Göran Gustafsson Foundation for promotion of scientific research at Uppala University and Royal Institute of TechnologySwedish Foundation for Strategic Research EU, European Research CouncilScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Available from: 2017-03-23 Created: 2017-03-23 Last updated: 2018-01-13Bibliographically approved
Rask-Andersen, M., Karlsson, T., Ek, W. E. & Johansson, Å. (2017). Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status.. PLoS Genetics, 13(9), Article ID e1006977.
Open this publication in new window or tab >>Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status.
2017 (English)In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 13, no 9, e1006977Article in journal (Refereed) Published
Abstract [en]

Previous genome-wide association studies (GWAS) have identified hundreds of genetic loci to be associated with body mass index (BMI) and risk of obesity. Genetic effects can differ between individuals depending on lifestyle or environmental factors due to gene-environment interactions. In this study, we examine gene-environment interactions in 362,496 unrelated participants with Caucasian ancestry from the UK Biobank resource. A total of 94 BMI-associated SNPs, selected from a previous GWAS on BMI, were used to construct weighted genetic scores for BMI (GSBMI). Linear regression modeling was used to estimate the effect of gene-environment interactions on BMI for 131 lifestyle factors related to: dietary habits, smoking and alcohol consumption, physical activity, socioeconomic status, mental health, sleeping patterns, as well as female-specific factors such as menopause and childbirth. In total, 15 lifestyle factors were observed to interact with GSBMI, of which alcohol intake frequency, usual walking pace, and Townsend deprivation index, a measure of socioeconomic status, were all highly significant (p = 1.45*10-29, p = 3.83*10-26, p = 4.66*10-11, respectively). Interestingly, the frequency of alcohol consumption, rather than the total weekly amount resulted in a significant interaction. The FTO locus was the strongest single locus interacting with any of the lifestyle factors. However, 13 significant interactions were also observed after omitting the FTO locus from the genetic score. Our analyses indicate that many lifestyle factors modify the genetic effects on BMI with some groups of individuals having more than double the effect of the genetic score. However, the underlying causal mechanisms of gene-environmental interactions are difficult to deduce from cross-sectional data alone and controlled experiments are required to fully characterise the causal factors.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-332047 (URN)10.1371/journal.pgen.1006977 (DOI)000411976100011 ()28873402 (PubMedID)
Funder
Swedish Research Council, 2015-03327Göran Gustafsson Foundation for Research in Natural Sciences and MedicineSwedish Society for Medical Research (SSMF)Åke Wiberg FoundationSwedish National Infrastructure for Computing (SNIC), b2016021
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2017-12-19Bibliographically approved
Warren, H. R., Evangelou, E., Cabrera, C. P., Gao, H., Ren, M., Mifsud, B., . . . Morris, A. P. (2017). Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nature Genetics, 49(3), 403-415.
Open this publication in new window or tab >>Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk
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2017 (English)In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 49, no 3, 403-415 p.Article in journal (Refereed) Published
Abstract [en]

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure-raising genetic variants on future cardiovascular disease risk.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-318933 (URN)10.1038/ng.3768 (DOI)000394917800014 ()28135244 (PubMedID)
Available from: 2017-04-10 Created: 2017-04-10 Last updated: 2017-11-29Bibliographically approved
Graff, M., Scott, R. A., Justice, A. E., Young, K. L., Feitosa, M. F., Barata, L., . . . Kilpeläinen, T. O. (2017). Genome-wide physical activity interactions in adiposity: A meta-analysis of 200,452 adults.. PLoS Genetics, 13(4), Article ID e1006528.
Open this publication in new window or tab >>Genome-wide physical activity interactions in adiposity: A meta-analysis of 200,452 adults.
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2017 (English)In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 13, no 4, e1006528Article in journal (Refereed) Published
Abstract [en]

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE, 2017
Keyword
BODY-MASS INDEX; REACTIVE PROTEIN-LEVELS; GENE-EXPRESSION; IDENTICAL-TWINS; ADIPOCYTE DIFFERENTIATION; ASSOCIATION METAANALYSIS; ACTIVITY QUESTIONNAIRES; FAT DISTRIBUTION; BINDING PROTEIN; FOOD-INTAKE
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-321624 (URN)10.1371/journal.pgen.1006528 (DOI)000402549200002 ()28448500 (PubMedID)
Available from: 2017-05-09 Created: 2017-05-09 Last updated: 2018-01-03Bibliographically approved
Folkersen, L., Fauman, E., Sabater-Lleal, M., Strawbridge, R. J., Frånberg, M., Sennblad, B., . . . Mälarstig, A. (2017). Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease. PLoS Genetics, 13(4), Article ID e1006706.
Open this publication in new window or tab >>Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease
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2017 (English)In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 13, no 4, e1006706Article in journal (Refereed) Published
Abstract [en]

Recent advances in highly multiplexed immunoassays have allowed systematic large-scale measurement of hundreds of plasma proteins in large cohort studies. In combination with genotyping, such studies offer the prospect to 1) identify mechanisms involved with regulation of protein expression in plasma, and 2) determine whether the plasma proteins are likely to be causally implicated in disease. We report here the results of genome-wide association (GWA) studies of 83 proteins considered relevant to cardiovascular disease (CVD), measured in 3,394 individuals with multiple CVD risk factors. We identified 79 genome-wide significant (p<5e-8) association signals, 55 of which replicated at P<0.0007 in separate validation studies (n = 2,639 individuals). Using automated text mining, manual curation, and network-based methods incorporating information on expression quantitative trait loci (eQTL), we propose plausible causal mechanisms for 25 trans-acting loci, including a potential post-translational regulation of stem cell factor by matrix metalloproteinase 9 and receptor-ligand pairs such as RANK-RANK ligand. Using public GWA study data, we further evaluate all 79 loci for their causal effect on coronary artery disease, and highlight several potentially causal associations. Overall, a majority of the plasma proteins studied showed evidence of regulation at the genetic level. Our results enable future studies of the causal architecture of human disease, which in turn should aid discovery of new drug targets.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE, 2017
Keyword
GENOME-WIDE ASSOCIATION; INTIMA-MEDIA THICKNESS; GENETIC-VARIANTS; MENDELIAN RANDOMIZATION; EXPRESSION; RISK; POPULATION; CELLS; GWAS; LIFE
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-319845 (URN)10.1371/journal.pgen.1006706 (DOI)000402549200023 ()28369058 (PubMedID)
Available from: 2017-04-10 Created: 2017-04-10 Last updated: 2018-01-03Bibliographically approved
Wain, L. V., Vaez, A., Jansen, R., Joehanes, R., van der Most, P. J., Erzurumluoglu, A. M., . . . Xiao, L. (2017). Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney. Hypertension, 70(3), E4-e19.
Open this publication in new window or tab >>Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney
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2017 (English)In: Hypertension, ISSN 0194-911X, E-ISSN 1524-4563, Vol. 70, no 3, E4-e19 p.Article in journal (Refereed) Published
Abstract [en]

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA. Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation.

Keyword
blood pressure, cardiovascular risk, complex traits, eSNP, GWAS, hypertension
National Category
Cardiac and Cardiovascular Systems
Identifiers
urn:nbn:se:uu:diva-334925 (URN)10.1161/HYPERTENSIONAHA.117.09438 (DOI)000407241500001 ()
Funder
NIH (National Institute of Health), R01-DK062370; ZIA-HG000024; R01D0042157-01A; MH081802; 1RC2 MH089951; 1RC2 MH089995Swedish Research Council, K2007-66X-20270-01-3; 2011-5252; 2012-2884; 2011-2354; 2015-03327EU, FP7, Seventh Framework Programme, FP7 313010EU, European Research CouncilSwedish Heart Lung Foundation, 20120197Torsten Söderbergs stiftelseKnut and Alice Wallenberg FoundationSwedish Research Council, 2012-1397; M-2005-1112; 2009-2298Swedish Diabetes Association, 2013-024Swedish Society for Medical Research (SSMF)
Available from: 2017-11-29 Created: 2017-11-29 Last updated: 2017-11-29Bibliographically approved
Ameur, A., Dahlberg, J., Olason, P., Vezzi, F., Karlsson, R., Martin, M., . . . Gyllensten, U. B. (2017). SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population. European Journal of Human Genetics, 25(11), 1253-1260.
Open this publication in new window or tab >>SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population
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2017 (English)In: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 25, no 11, 1253-1260 p.Article in journal (Refereed) Published
Abstract [en]

Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2017
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-337314 (URN)10.1038/ejhg.2017.130 (DOI)000412823800012 ()28832569 (PubMedID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg Foundation, 2014.0272Swedish Research CouncilSwedish National Infrastructure for Computing (SNIC), sens2016003EU, European Research Council, 282330
Available from: 2018-01-08 Created: 2018-01-08 Last updated: 2018-01-08Bibliographically approved
Ek, W. E., Tobi, E. W., Ahsan, M., Lampa, E., Ponzi, E., Kyrtopoulos, S. A., . . . Johansson, Å. (2017). Tea and coffee consumption in relation to DNA methylation in four European cohorts. Human Molecular Genetics, 26(16), pp. 3221-3231.
Open this publication in new window or tab >>Tea and coffee consumption in relation to DNA methylation in four European cohorts
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2017 (English)In: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 26, no 16, 3221-3231 p.Article in journal, News item (Refereed) Published
Abstract [en]

Lifestyle factors, such as food choices and exposure to chemicals, can alter DNA methylation and lead to changes in gene activity. Two such exposures with pharmacologically active components are coffee and tea consumption. Both coffee and tea have been suggested to play an important role in modulating disease-risk in humans by suppressing tumour progression, decreasing inflammation and influencing estrogen metabolism. These mechanisms may be mediated by changes in DNA methylation. To investigate if DNA methylation in blood is associated with coffee and tea consumption, we performed a genome-wide DNA methylation study for coffee and tea consumption in four European cohorts (N = 3,096). DNA methylation was measured from whole blood at 421,695 CpG sites distributed throughout the genome and analysed in men and women both separately and together in each cohort. Meta-analyses of the results and additional regional-level analyses were performed. After adjusting for multiple testing, the meta-analysis revealed that two individual CpG-sites, mapping to DNAJC16 and TTC17, were differentially methylated in relation to tea consumption in women. No individual sites were associated with men or with the sex-combined analysis for tea or coffee. The regional analysis revealed that 28 regions were differentially methylated in relation to tea consumption in women. These regions contained genes known to interact with estradiol metabolism and cancer. No significant regions were found in the sex-combined and male-only analysis for either tea or coffee consumption.

Place, publisher, year, edition, pages
Oxford University Press, 2017
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-332048 (URN)10.1093/hmg/ddx194 (DOI)000406794000017 ()28535255 (PubMedID)
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2017-11-23Bibliographically approved
Ahsan, M., Ek, W. E., Rask-Andersen, M., Karlsson, T., Lind-Thomsen, A., Enroth, S., . . . Johansson, Å. (2017). The relative contribution of DNA methylation and genetic variants on protein biomarkers for human diseases.. PLoS Genetics, 13(9), Article ID e1007005.
Open this publication in new window or tab >>The relative contribution of DNA methylation and genetic variants on protein biomarkers for human diseases.
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2017 (English)In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 13, no 9, e1007005Article in journal (Refereed) Published
Abstract [en]

Associations between epigenetic alterations and disease status have been identified for many diseases. However, there is no strong evidence that epigenetic alterations are directly causal for disease pathogenesis. In this study, we combined SNP and DNA methylation data with measurements of protein biomarkers for cancer, inflammation or cardiovascular disease, to investigate the relative contribution of genetic and epigenetic variation on biomarker levels. A total of 121 protein biomarkers were measured and analyzed in relation to DNA methylation at 470,000 genomic positions and to over 10 million SNPs. We performed epigenome-wide association study (EWAS) and genome-wide association study (GWAS) analyses, and integrated biomarker, DNA methylation and SNP data using between 698 and 1033 samples depending on data availability for the different analyses. We identified 124 and 45 loci (Bonferroni adjusted P < 0.05) with effect sizes up to 0.22 standard units' change per 1% change in DNA methylation levels and up to four standard units' change per copy of the effective allele in the EWAS and GWAS respectively. Most GWAS loci were cis-regulatory whereas most EWAS loci were located in trans. Eleven EWAS loci were associated with multiple biomarkers, including one in NLRC5 associated with CXCL11, CXCL9, IL-12, and IL-18 levels. All EWAS signals that overlapped with a GWAS locus were driven by underlying genetic variants and three EWAS signals were confounded by smoking. While some cis-regulatory SNPs for biomarkers appeared to have an effect also on DNA methylation levels, cis-regulatory SNPs for DNA methylation were not observed to affect biomarker levels. We present associations between protein biomarker and DNA methylation levels at numerous loci in the genome. The associations are likely to reflect the underlying pattern of genetic variants, specific environmental exposures, or represent secondary effects to the pathogenesis of disease.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-332046 (URN)10.1371/journal.pgen.1007005 (DOI)000411976100027 ()28915241 (PubMedID)
Funder
Swedish Research Council, K2007-66X-20270-01-3, 2011-2354, 2015-03327Swedish Foundation for Strategic Research Göran Gustafsson Foundation for Research in Natural Sciences and MedicineSwedish Society for Medical Research (SSMF)Åke Wiberg Foundation
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2017-12-19Bibliographically approved
Dahl, A., Iotchkova, V., Baud, A., Johansson, Å., Gyllensten, U., Soranzo, N., . . . Marchini, J. (2016). A multiple-phenotype imputation method for genetic studies. Nature Genetics, 48(4), 466-472.
Open this publication in new window or tab >>A multiple-phenotype imputation method for genetic studies
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2016 (English)In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 48, no 4, 466-472 p.Article in journal (Refereed) Published
Abstract [en]

Genetic association studies have yielded a wealth of biological discoveries. However, these studies have mostly analyzed one trait and one SNP at a time, thus failing to capture the underlying complexity of the data sets. Joint genotype-phenotype analyses of complex, high-dimensional data sets represent an important way to move beyond simple genome-wide association studies (GWAS) with great potential. The move to high-dimensional phenotypes will raise many new statistical problems. Here we address the central issue of missing phenotypes in studies with any level of relatedness between samples. We propose a multiple-phenotype mixed model and use a computationally efficient variational Bayesian algorithm to fit the model. On a variety of simulated and real data sets from a range of organisms and trait types, we show that our method outperforms existing state-of-the-art methods from the statistics and machine learning literature and can boost signals of association.

National Category
Medical Genetics
Identifiers
urn:nbn:se:uu:diva-293023 (URN)10.1038/ng.3513 (DOI)000372908800018 ()26901065 (PubMedID)
Funder
EU, European Research Council, 617306
Available from: 2016-05-11 Created: 2016-05-11 Last updated: 2018-01-10Bibliographically approved
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