Per Eriksson

Linköping University, Linköping, Östergötland, Sweden

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Publications (205)1302.82 Total impact

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    ABSTRACT: Background One aspect in which RNA sequencing is more valuable than microarray-based methods is the ability to examine the allelic imbalance of the expression of a gene. This process is often a complex task that entails quality control, alignment, and the counting of reads over heterozygous single-nucleotide polymorphisms. Allelic imbalance analysis is subject to technical biases, due to differences in the sequences of the measured alleles. Flexible bioinformatics tools are needed to ease the workflow while retaining as much RNA sequencing information as possible throughout the analysis to detect and address the possible biases. Results We present AllelicImblance, a software program that is designed to detect, manage, and visualize allelic imbalances comprehensively. The purpose of this software is to allow users to pose genetic questions in any RNA sequencing experiment quickly, enhancing the general utility of RNA sequencing. The visualization features can reveal notable, non-trivial allelic imbalance behavior over specific regions, such as exons. Conclusions The software provides a complete framework to perform allelic imbalance analyses of aligned RNA sequencing data, from detection to visualization, within the robust and versatile management class, ASEset. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0620-2) contains supplementary material, which is available to authorized users.
    BMC Bioinformatics 06/2015; 16(1). DOI:10.1186/s12859-015-0620-2 · 2.67 Impact Factor
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    ABSTRACT: Abdominal aortic aneurysm (AAA) is characterized by inflammation, loss of smooth muscle cells (SMCs), and degradation of the extracellular matrix in the vessel wall. Innate immune receptors such as Toll-like receptors (TLRs) were recently shown to regulate immunological processes leading to the formation and progression of atherosclerotic plaques as well as to other cardiovascular pathologies. Our aim was to investigate whether blockage of TLR signaling, under the control of TIR domain-containing adaptor protein including IFN-β (TRIF), could inhibit the inflammatory response and AAA development in mice. In human AAA, an increased TLR3 and TLR4 expression in association with macrophages and T lymphocytes was demonstrated with immunohistochemical analysis. Angiotensin (Ang) II-induced aneurysm formation was significantly reduced by 30% in ApoE(-/-)Trif(-/-) mice compared to ApoE(-/-) mice. Morphologically, AngII-infused ApoE(-/-)Trif(-/-) mice had a more intact cellular and extracellular matrix while ApoE(-/-) mice infused with AngII displayed an increased medial thickness associated with aortic dissection, thrombus formation, and a more disorganized vessel wall. Gene expression analysis of the abdominal aorta revealed a profound decrease of the inflammatory genes CD68 (P < 0.05), CD11b (P < 0.05), and TNF-α (P < 0.05) and the protease gene MMP-12 (P < 0.01) in ApoE(-/-)Trif(-/-) mice compared to ApoE(-/-) mice infused with AngII. Our results suggest that signaling through TRIF is important for the inflammatory response of AngII-induced AAA and that blockage of the TRIF pathway reduces vascular inflammation and protects against AAA formation. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
    Atherosclerosis 06/2015; 26(2). DOI:10.1016/j.atherosclerosis.2015.06.014 · 3.97 Impact Factor
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    ABSTRACT: Rituximab (RTX) is approved for remission induction in ANCA associated vasculitis (AAV). However, data on use of RTX in patients with severe renal disease is lacking. We conducted a retrospective multi-center study to evaluate the efficacy and safety of RTX with glucocorticoids (GC) with and without use of concomitant cyclophosphamide (CYC) for remission induction in patients presenting with e GFR less than 20 ml/min/1.73 m(2). We evaluated outcomes of remission at 6 months (6 M), renal recovery after acute dialysis at diagnosis, e-GFR rise at 6 M, patient and renal survival and adverse events. A total 37 patients met the inclusion criteria. The median age was 61 years. (55-73), 62 % were males, 78 % had new diagnosis and 59 % were MPO ANCA positive. The median (IQR) e-GFR at diagnosis was 13 ml/min/1.73 m(2) (7-16) and 15 required acute dialysis. Eleven (30 %) had alveolar hemorrhage. Twelve (32 %) received RTX with GC, 25 (68 %) received RTX with GC and CYC and seventeen (46 %) received plasma exchange. The median (IQR) follow up was 973 (200-1656) days. Thirty two of 33 patients (97 %) achieved remission at 6 M and 10 of 15 patients (67 %) requiring dialysis recovered renal function. The median prednisone dose at 6 M was 6 mg/day. The mean (SD) increase in e-GFR at 6 months was 14.5 (22) ml/min/m(2). Twelve patients developed ESRD during follow up. There were 3 deaths in the first 6 months. When stratified by use of concomitant CYC, there were no differences in baseline e GFR, use of plasmapheresis, RTX dosing regimen or median follow up days between the groups. No differences in remission, renal recovery ESRD or death were observed. This study of AAV patients with severe renal disease demonstrates that the outcomes appear equivalent when treated with RTX and GC with or without concomitant CYC.
    Journal of nephrology 05/2015; DOI:10.1007/s40620-015-0208-y · 2.00 Impact Factor
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    ABSTRACT: Antineutrophil cytoplasmic antibody associated vasculitis (AAV) has an unpredictable course and better biomarkers are needed. Micro-RNAs in body fluids are protected from degradation and might be used as biomarkers for diagnosis and prognosis, here we explore the potential in AAV. Plasma samples from two AAV cohorts (n=67 and 38) were compared with samples from healthy controls (n=27 and 45) and disease controls (n=20). A panel of 32 miRNAs was measured using a microfluidic quantitative real-time PCR system, and results were compared with clinical data. Seven individual miRNAs were differently expressed compared to controls in both cohorts; miR-29a, -34a, -142-3p and -383 were up-regulated and miR-20a, -92a and -221 were down-regulated. Cluster analysis as well as principal component analysis (PCA) indicated that patterns of miRNA expression differentiate AAV patients from healthy subjects as well as from renal transplant recipients. Loadings plots indicated similar contribution of the same miRNAs in both cohorts to the PCA. Renal engagement was important for miRNA expression but consistent correlations between estimated glomerular filtration rate and miRNA levels were not found. We found no significant correlation between treatment regimens and circulating miRNA levels. In this first study ever on circulating miRNA profiles in AAV, we find clear indication of their potential as biomarkers for diagnosis and classification, but more studies are needed to identify the best markers as well as the mechanisms responsible for variations.
    Clinical and experimental rheumatology 05/2015; 33(2 Suppl 89):64-71. · 2.97 Impact Factor
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    ABSTRACT: Autophagy has emerged as a cell survival mechanism critical for cellular homeostasis, which may play a protective role in atherosclerosis. ATG16L1, a protein essential for early stages of autophagy, has been implicated in the pathogenesis of Crohn's disease. However, it is unknown whether ATG16L1 is involved in atherosclerosis. Our aim was to analyze ATG16L1 expression in carotid atherosclerotic plaques in relation to markers of plaque vulnerability. Histological analysis of 143 endarterectomized human carotid atherosclerotic plaques revealed that ATG16L1 was expressed in areas surrounding the necrotic core and the shoulder regions. Double immunofluorescence labeling revealed that ATG16L1 was abundantly expressed in phagocytic cells (CD68), endothelial cells (CD31), and mast cells (tryptase) in human advanced plaques. ATG16L1 immunogold labeling was predominantly observed in endothelial cells and foamy smooth muscle cells of the plaques. ATG16L1 protein expression correlated with plaque content of proinflammatory cytokines and matrix metalloproteinases. Analysis of Atg16L1 at 2 distinct stages of the atherothrombotic process in a murine model of plaque vulnerability by incomplete ligation and cuff placement in carotid arteries of apolipoprotein-E-deficient mice revealed a strong colocalization of Atg16L1 and smooth muscle cells only in early atherosclerotic lesions. An increase in ATG16L1 expression and autophagy flux was observed during foam cell formation in human macrophages using oxidized-LDL. Taken together, this study shows that ATG16L1 protein expression is associated with foam cell formation and inflamed plaque phenotype and could contribute to the development of plaque vulnerability at earlier stages of the atherogenic process. © 2015 American Heart Association, Inc.
    Arteriosclerosis Thrombosis and Vascular Biology 03/2015; 35(5). DOI:10.1161/ATVBAHA.114.304840 · 5.53 Impact Factor
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    ABSTRACT: Venous thromboembolism (VTE), the third leading cause of cardiovascular mortality, is a complex thrombotic disorder with environmental and genetic determinants. Although several genetic variants have been found associated with VTE, they explain a minor proportion of VTE risk in cases. We undertook a meta-analysis of genome-wide association studies (GWASs) to identify additional VTE susceptibility genes. Twelve GWASs totaling 7,507 VTE case subjects and 52,632 control subjects formed our discovery stage where 6,751,884 SNPs were tested for association with VTE. Nine loci reached the genome-wide significance level of 5 × 10(-8) including six already known to associate with VTE (ABO, F2, F5, F11, FGG, and PROCR) and three unsuspected loci. SNPs mapping to these latter were selected for replication in three independent case-control studies totaling 3,009 VTE-affected individuals and 2,586 control subjects. This strategy led to the identification and replication of two VTE-associated loci, TSPAN15 and SLC44A2, with lead risk alleles associated with odds ratio for disease of 1.31 (p = 1.67 × 10(-16)) and 1.21 (p = 2.75 × 10(-15)), respectively. The lead SNP at the TSPAN15 locus is the intronic rs78707713 and the lead SLC44A2 SNP is the non-synonymous rs2288904 previously shown to associate with transfusion-related acute lung injury. We further showed that these two variants did not associate with known hemostatic plasma markers. TSPAN15 and SLC44A2 do not belong to conventional pathways for thrombosis and have not been associated to other cardiovascular diseases nor related quantitative biomarkers. Our findings uncovered unexpected actors of VTE etiology and pave the way for novel mechanistic concepts of VTE pathophysiology. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
    The American Journal of Human Genetics 03/2015; DOI:10.1016/j.ajhg.2015.01.019 · 10.99 Impact Factor
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    ABSTRACT: Patients with bicuspid aortic valve (BAV) have an increased risk of developing ascending aortic aneurysms. Transforming growth factor-β (TGFβ) is a crucial factor of vascular remodeling, the impaired signaling of which can alter the structure and composition of the extracellular matrix. In this study, we analyzed the activity of TGFβ in aneurysmal and nonaneurysmal ascending aorta from BAV patients, using tricuspid aortic valve (TAV) patients as a reference group. The response to exogenous TGFβ was analyzed with regard to gene expression in primary aortic smooth muscle cells that were isolated from 7 BAV and 5 TAV patients and in valve fibroblasts from 7 BAV and 8 TAV patients. The set of genes that were significantly changed by TGFβ (217 genes) was compared with gene expression profiles of the ascending aorta from BAV and TAV patients (139 arrays). By principle component analysis, based on the 217 genes, gene expression differed significantly in the intima/media region between aneurysmal BAV and TAV aortas, driven by the response in TAV patients. During aneurysm development the levels of phosphorylated SMADs and the availability of free TGFβ were lower in BAV patients compared with TAV. Confocal microscopy analysis showed a higher colocalization of latency associated peptide and latent TGFβ binding protein 3 in BAV aortas. Our findings suggest that TGFβ activation during aneurysm formation is muted in patients with BAV, possibly as a result of an increased TGFβ sequestration in the extracellular space. © 2015 American Heart Association, Inc.
    Arteriosclerosis Thrombosis and Vascular Biology 03/2015; 35(4). DOI:10.1161/ATVBAHA.114.304996 · 5.53 Impact Factor
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    ABSTRACT: Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis
    Nature 02/2015; 518(7538). DOI:10.1038/nature14177 · 42.35 Impact Factor
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    ABSTRACT: Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 x 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
    Nature 02/2015; 518(7538-7538):187-96. DOI:10.1038/nature14132 · 42.35 Impact Factor
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    ABSTRACT: -Observational studies report that secretory phospholipase A2 (sPLA2) activity is a marker for CHD risk, and activity measures are thought to represent the composite activity of sPLA2-IIA, -V and -X. The aim of this study was to use genetic variants of PLA2G10, encoding sPLA2-X, to investigate the contribution of sPLA2-X to the measure of sPLA2 activity, and coronary heart disease (CHD) risk traits and outcome. -Three PLA2G10 tagging SNPs (rs72546339, rs72546340, rs4003232) and a previously studied PLA2G10 cSNP rs4003228, R38C, were genotyped in a nested case: control cohort drawn from the prospective EPIC-Norfolk Study (2175 cases and 2175 controls). Meta-analysis of rs4003228 (R38C) and CHD was carried out using data from the Northwick Park Heart Study II and two published cohorts AtheroGene and SIPLAC, providing in total an additional 1884 cases and 3119 controls. EPIC-Norfolk subjects in the highest tertile of sPLA2 activity were older and had higher inflammatory markers compared to those in the lowest tertile for sPLA2 activity. None of the PLA2G10 tSNPs nor R38C, a functional variant, were significantly associated with sPLA2 activity, intermediate CHD risk traits or CHD risk. In meta-analysis the summary OR for R38C was OR=0.97 (95%CI 0.77-1.22). -PLA2G10 variants are not significantly associated with plasma sPLA2 activity or with CHD risk.
    Circulation Cardiovascular Genetics 01/2015; 8(2). DOI:10.1161/CIRCGENETICS.114.000633 · 5.34 Impact Factor
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    ABSTRACT: Rationale: In human genetic studies a single nucleotide polymorphism within the salt-inducible kinase 1 (SIK1) gene was associated with hypertension. Lower SIK1 activity in vascular smooth muscle cells (VSMCs) leads to decreased Na(+),K(+)-ATPase activity, which associates with increased vascular tone. Also, SIK1 participates in a negative feedback mechanism on the transforming growth factor-β1 (TGFβ1)signaling and down-regulation of SIK1 induces the expression of extracellular matrix remodeling genes. Objective: To evaluate whether reduced expression/activity of SIK1 alone or in combination with elevated salt intake could modify the structure and/or function of the vasculature, leading to higher blood pressure. Methods and Results: SIK1 knockout (sik1-/-) and wild-type (sik1(+/+)) mice were challenged to a normal- or chronic high-salt intake (1% NaCl). Under normal-salt conditions, the sik1(-/-) mice showed increased collagen deposition in the aorta but similar blood pressure compared to the sik1(+/+) mice. During high-salt intake, the sik1(+/+) mice exhibited an increase in SIK1 expression in the VSMCs layer of the aorta, whereas the sik1(-/-) mice exhibited up-regulated TGFβ1 signaling and increased expression of endothelin-1 and genes involved in VSMC contraction, higher systolic blood pressure and signs of cardiac hypertrophy. In vitro knockdown of SIK1 induced up-regulation of collagen in aortic adventitial fibroblasts, and enhanced the expression of contractile markers and of endothelin-1 in VSMCs. Conclusions: Vascular SIK1 activation might represent a novel mechanism involved in the prevention of high blood pressure development triggered by high-salt intake through the modulation of the contractile phenotype of VSMCs via TGFβ1-signaling inhibition.
    Circulation Research 01/2015; 116(4). DOI:10.1161/CIRCRESAHA.116.304529 · 11.09 Impact Factor
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    ABSTRACT: The objectives of this study were to compare incidence rates, renal and patient survival between lupus nephritis (LN) and anti-neutrophil cytoplasmic antibody-associated nephritis (AAN) during a 12-year period in two geographically defined populations in Sweden. In the health care districts surrounding the Skåne University Hospital in Lund [mean population ≥18 years (1997-2008), 188 400] and the University Hospital in Linköping [mean population ≥18 years (1997-2008), 328 900] all patients with biopsy-proven LN and AAN during the period 1997-2008 were included in the study if they (i) were residing within the study areas at the time of onset of nephritis, (ii) had a clinical diagnosis of either SLE or ANCA-associated vasculitis (AAV) and (iii) experienced a first flare of biopsy-proven nephritis during the study period. Eighty-two patients (Lund 44 + Linköping 38) with biopsy-proven AAN were identified and 27 patients with LN (Lund 13 + Linköping 14). The annual incidence rate per million inhabitants aged ≥18 years in both study areas was estimated to be 13.2 (95% CI 10.4-16.1) for AAN and 4.3 (95% CI 2.7-6.0) for LN, P < 0.001. The patients were followed until January 2013. During the follow-up time 38 patients died (AAN 36, LN 2; P = 0.001), and 20 patients went into end-stage renal disease (AAN 19 and LN 1), P = 0.020. In Sweden, AAN was three times more common than LN, and the outcome was considerably worse. SLE is often diagnosed before the onset of nephritis leading to earlier treatment, while AAN is still often diagnosed at a later stage. © The Author 2014. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
    Nephrology Dialysis Transplantation 12/2014; DOI:10.1093/ndt/gfu396 · 3.49 Impact Factor
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    ABSTRACT: Identification and treatment of abdominal aortic aneurysm (AAA) remain among the most prominent challenges in vascular medicine. MicroRNAs (miRNAs) are crucial regulators of cardiovascular pathology and represent intriguing targets to limit AAA expansion. Here we show, by using two established murine models of AAA disease along with human aortic tissue and plasma analysis, that miR-24 is a key regulator of vascular inflammation and AAA pathology. In vivo and in vitro studies reveal chitinase 3-like 1 (Chi3l1) to be a major target and effector under the control of miR-24, regulating cytokine synthesis in macrophages as well as their survival, promoting aortic smooth muscle cell migration and cytokine production, and stimulating adhesion molecule expression in vascular endothelial cells. We further show that modulation of miR-24 alters AAA progression in animal models, and that miR-24 and CHI3L1 represent novel plasma biomarkers of AAA disease progression in humans.
    Nature Communications 10/2014; 6. DOI:10.1038/ncomms6214 · 10.74 Impact Factor
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    ABSTRACT: Atherosclerosis is an inflammatory disease associated with the activation of complex innate immune Toll-like receptors and cytoplasmic nucleotide-binding oligomerization domain-containing protein (NOD)-like receptor (NLR) pathways. However, the function of most innate immune receptors in atherosclerosis remains unclear. Here we show that NOD2 is a crucial innate immune receptor influencing vascular inflammation and atherosclerosis severity. A 10-week stimulation with muramyl dipeptide (MDP), the NOD2 cognate ligand, showed aggravated atherosclerosis, as indicated by the augmented lesion burden, increased vascular inflammation and enlarged lipid-rich necrotic cores in Ldlr−/− mice. Myeloid-specific ablation of NOD2, but not its downstream kinase receptor-interacting serine/threonine-protein kinase 2, restrained the expansion of the lipid-rich necrotic core in Ldlr−/− chimeric mice. In vitro stimulation of macrophages with MDP enhanced the uptake of oxidized LDL and impaired cholesterol efflux in concordance with upregulation of scavenger receptor A1/2 and downregulation of ATP-binding cassette transporter A1. Ex vivo stimulation of human carotid plaques with MDP led to increased activation of inflammatory signaling pathways, and p38 MAPK and NF-κB-mediated release of pro-inflammatory cytokines. Altogether, this study suggests that NOD2 contributes to the expansion of the lipid-rich necrotic core and promotes vascular inflammation in hyperlipidemic mice.This article is protected by copyright. All rights reserved
    European Journal of Immunology 10/2014; 44(10). DOI:10.1002/eji.201444755 · 4.52 Impact Factor
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    ABSTRACT: Exploiting genotyping, DNA sequencing, imputation, and trans-ancestral mapping, we used Bayesian and frequentist approaches to model the IRF5-TNPO3 locus association, now implicated in two immunotherapies and seven autoimmune diseases. Specifically, in systemic lupus erythematosus (SLE) we resolved separate associations in the IRF5 promoter (all ancestries) and with an extended European haplotype. We captured 3,230 IRF5-TNPO3 high quality, common variants across five ethnicities in 8,395 SLE cases and 7,367 controls. The genetic effect from the IRF5 promoter can be explained by any one of four variants in 5.7 kb (p-valuemeta=6x10(-49); OR=1.38-1.97). The second genetic effect spanned an 85.5 kb, 24 variant haplotype that included the genes IRF5 and TNPO3 (p-valuesEU=10(-27)-10(-32), OR=1.7-1.81). Many variants at the IRF5 locus with previously assigned biological function are not members of either final credible set of potential causal variants identified herein. In addition to the known biologically functional variants, we demonstrated that the risk allele of rs4728142, a variant in the promoter among the lowest frequentist probability and highest Bayesian posterior probability, was correlated with IRF5 expression and differentially binds the transcription factor ZBTB3. Our analytical strategy provides a novel framework for future studies aimed at dissecting etiological genetic effects. Finally, both SLE elements of the statistical model appear to operate in Sjögren's syndrome and systemic sclerosis while only the IRF5-TNPO3 gene-spanning haplotype is associated in primary biliary cirrhosis, demonstrating the nuance of similarity and difference in autoimmune disease risk mechanisms at IRF5-TNPO3.
    Human Molecular Genetics 09/2014; DOI:10.1093/hmg/ddu455 · 6.68 Impact Factor
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    ABSTRACT: Differences in clinical presentation between patients with tricuspid aortic valves (TAVs) or bicuspid aortic valves (BAVs) and aortic valve disease are evident. Whether these differences can be attributed to differences in cardiovascular risks remains uncertain.
    Journal of Thoracic and Cardiovascular Surgery 08/2014; DOI:10.1016/j.jtcvs.2014.08.023 · 3.99 Impact Factor
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    ABSTRACT: Chronic obstructive pulmonary disease (COPD) independently associates with an increased risk of coronary artery disease (CAD), but it has not been fully investigated whether this co-morbidity involves shared pathophysiological mechanisms. To identify potential common pathways across the two diseases, we tested all recently published single nucleotide polymorphisms (SNPs) associated with human lung function (spirometry) for association with carotid intima-media thickness (cIMT) in 3,378 subjects with multiple CAD risk factors, and for association with CAD in a case-control study of 5,775 CAD cases and 7,265 controls. SNPs rs2865531, located in the CFDP1 gene, and rs9978142, located in the KCNE2 gene, were significantly associated with CAD. In addition, SNP rs9978142 and SNP rs3995090 located in the HTR4 gene, were associated with average and maximal cIMT measures. Genetic risk scores combining the most robustly spirometry-associated SNPs from the literature were modestly associated with CAD, (odds ratio (OR) (95% confidence interval (CI95) = 1.06 (1.03, 1.09); P-value = 1.5×10-4, per allele). In conclusion, our study suggests that some genetic loci implicated in determining human lung function also influence cIMT and susceptibility to CAD. The present results should help elucidate the molecular underpinnings of the co-morbidity observed across COPD and CAD.
    PLoS ONE 08/2014; 9(8):e104082. DOI:10.1371/journal.pone.0104082 · 3.53 Impact Factor
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    ABSTRACT: Michael V Holmes, assistant professor (joint first author)123, Caroline E Dale, research fellow (joint first author)4, Luisa Zuccolo, population health scientist fellow5, Richard J Silverwood, lecturer in medical statistics46, Yiran Guo, research associate78, Zheng Ye, investigator scientist9, David Prieto-Merino, lecturer in medical statistics4, Abbas Dehghan, assistant professor10, Stella Trompet, senior researcher11, Andrew Wong, senior study manager12, Alana Cavadino, statistician13, Dagmar Drogan, scientist14, Sandosh Padmanabhan, reader15, Shanshan Li, postdoctoral research fellow16, Ajay Yesupriya, health scientist17, Maarten Leusink, doctoral candidate18, Johan Sundstrom, senior epidemiologist19, Jaroslav A Hubacek, senior scientist20, Hynek Pikhart, senior lecturer21, Daniel I Swerdlow, clinician scientist1, Andrie G Panayiotou, lecturer in public health22, Svetlana A Borinskaya, leading researcher23, Chris Finan, bioinformatician1, Sonia Shah, postdoctoral research fellow24, Karoline B Kuchenbaecker, research associate in genetic epidemiology25, Tina Shah, postdoctoral research fellow1, Jorgen Engmann, data manager1, Lasse Folkersen, postdoctoral research fellow26, Per Eriksson, professor of cardiovascular medicine26, Fulvio Ricceri, epidemiologist, research fellow28, Olle Melander, professor27, Carlotta Sacerdote, medical epidemiologist28, Dale M Gamble, researcher29, Sruti Rayaprolu, researcher30, Owen A Ross, associate professor30, Stela McLachlan, data manager31, Olga Vikhireva, research associate21, Ivonne Sluijs, assistant professor32, Robert A Scott, senior investigator scientist9, Vera Adamkova, head of department33, Leon Flicker, professor of geriatric medicine34, Frank M van Bockxmeer, director of cardiovascular genetics laboratory35, Christine Power, professor of epidemiology and public health13, Pedro Marques-Vidal, associate professor of internal medicine36, Tom Meade, emeritus professor of epidemiology4, Michael G Marmot, director of UCL institute of Health Equity37, Jose M Ferro, professor of neurology3839, Sofia Paulos-Pinheiro, masters student4041, Steve E Humphries, professor of cardiovascular genetics at UCL42, Philippa J Talmud, professor of cardiovascular genetics42, Irene Mateo Leach, postdoctoral research fellow43, Niek Verweij, doctoral candidate43, Allan Linneberg, professor44, Tea Skaaby, doctoral candidate44, Pieter A Doevendans, chief cardiologist45, Maarten J Cramer, consultant cardiologist45, Pim van der Harst, cardiologist434647, Olaf H Klungel, associate professor of pharmacoepidemiologic methods18, Nicole F Dowling, epidemiologist17, Anna F Dominiczak, regius professor of medicine15, Meena Kumari, professor of biological and social epidemiology1, Andrew N Nicolaides, emeritus professor of vascular surgery, professor emeritus484950, Cornelia Weikert, scientist, group head14, Heiner Boeing, professor and head of department14, Shah Ebrahim, professor of public health4, Tom R Gaunt, senior lecturer in bioinformatics and molecular genetics5, Jackie F Price, clinical reader in epidemiology31, Lars Lannfelt, professor51, Anne Peasey, teaching fellow in social epidemiology21, Ruzena Kubinova, head of centre52, Andrzej Pajak, professor and head of department53, Sofia Malyutina, professor and head of laboratory5455, Mikhail I Voevoda, professor and director5456, Abdonas Tamosiunas, senior researcher57, Anke H Maitland-van der Zee, associate professor18, Paul E Norman, winthrop professor58, Graeme J Hankey, winthrop professor of neurology5960, Manuela M Bergmann, scientist14, Albert Hofman, professor of epidemiology10, Oscar H Franco, professor of preventative medicine10, Jackie Cooper, senior research fellow61, Jutta Palmen, senior research fellow42, Wilko Spiering, vascular medicine internist62, Pim A de Jong, radiologist63, Diana Kuh, professor of life course epidemiology and MRC unit director12, Rebecca Hardy, professor of epidemiology and medical statistics and MRC programme leader12, Andre G Uitterlinden, professor of complex genetics10, M Arfan Ikram, associate professor of neuroepidemiology10, Ian Ford, professor of biostatistics64, Elina Hyppönen, professor of nutritional and genetic epidemiology136566, Osvaldo P Almeida, director of research, professor and Winthrop chair of geriatric psychiatry346768, Nicholas J Wareham, professor and director of the MRC epidemiology unit9, Kay-Tee Khaw, professor of clinical gerontology69, Anders Hamsten, professor and team leader on behalf of IMPROVE study group*2670, Lise Lotte N Husemoen, senior research fellow44, Anne Tjønneland, research leader71, Janne S Tolstrup, research programme director72, Eric Rimm, associate professor of epidemiology and nutrition7374, Joline W J Beulens, assistant professor32, W M Monique Verschuren, deputy head75, N Charlotte Onland-Moret, assistant professor of genetic epidemiology32, Marten H Hofker, professor of molecular genetics76, S Goya Wannamethee, professor of epidemiology77, Peter H Whincup, professor of cardiovascular epidemiology78, Richard Morris, professor of medical statistics and epidemiology77, Astrid M Vicente, head of department407980, Hugh Watkins, professor of cardiovascular medicine and head of department8182, Martin Farrall, professor of cardiovascular genetics8182, J Wouter Jukema, professor of cardiology11, James Meschia, physician investigator29, L Adrienne Cupples, professor of biostatistics8384, Stephen J Sharp, senior statistician9, Myriam Fornage, professor of molecular medicine and human genetics85, Charles Kooperberg, full member86, Andrea Z LaCroix, professor of epidemiology86, James Y Dai, associate member of biostatistics86, Matthew B Lanktree, postdoctoral research fellow87, David S Siscovick, senior vice-president for research88, Eric Jorgenson, research scientist89, Bonnie Spring, professor of preventive medicine and director90, Josef Coresh, professor of epidemiology91, Yun R Li, medical and doctoral trainee7, Sarah G Buxbaum, assistant professor92, Pamela J Schreiner, professor93, R Curtis Ellison, professor of medicine and public health94, Michael Y Tsai, professor95, Sanjay R Patel, associate professor of medicine96104, Susan Redline, professor96, Andrew D Johnson, principal investigator84, Ron C Hoogeveen, assistant professor of medicine97, Hakon Hakonarson, associate professor of paediatrics and director of genomics7, Jerome I Rotter, director and professor98, Eric Boerwinkle, professor and director99, Paul I W de Bakker, professor of genetic epidemiology and bioinformatics32100, Mika Kivimaki, professor of social epidemiology21, Folkert W Asselbergs, consultant cardiologist4547101, Naveed Sattar, professor of metabolic medicine102, Debbie A Lawlor, professor of epidemiology5, John Whittaker, professor and vice president of statistical platforms and technologies at GSK4103, George Davey Smith, director of MRC integrative epidemiology unit5, Kenneth Mukamal, general internalist104, Bruce M Psaty, professor105106, James G Wilson, professor of physiology and biophysics107, Leslie A Lange, associate professor108, Ajna Hamidovic, assistant professor109, Aroon D Hingorani, professor of genetic epidemiology1, Børge G Nordestgaard, professor110111112, Martin Bobak, professor of epidemiology21, David A Leon, professor of epidemiology4, Claudia Langenberg, academic clinical lecturer9, Tom M Palmer, assistant professor in medical statistics113, Alex P Reiner, research professor86, Brendan J Keating, assistant professor in paediatrics and surgery27, Frank Dudbridge, professor of statistical genetics4, Juan P Casas, professor of epidemiology14 on behalf of The InterAct Consortium1Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK2Department of Surgery, Penn Transplant Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA3Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA4Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK5MRC Integrative Epidemiology Unit (IEU) at the Universty of Bristol, Oakfield House, Bristol BS8 2BN, UK6Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK7Center for Applied Genomics, Abramson Research Center, The Childrentextquoterights Hospital of Philadelphia, Philadelphia, USA8BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China9MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooketextquoterights Hospital, Cambridge, UK10Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands11Department of Cardiology, Leiden University Medical Center, the Netherlands12MRC Unit for Lifelong Health and Ageing at UCL, London, UK13Centre for Paediatric Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK14German Institute of Human Nutrition Potsdam-Rehbrücke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany15Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK16Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA17Office of Public Health Genomics, Office of Epidemiology, Surveillance, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA18Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands19Department of Medical Sciences, Uppsala University, Uppsala University Hospital, SE-751 85 Uppsala, Sweden20Center for Experimental Medicine, Institute for Clinical and Experimental Medicine, Videnska 1958/9, Prague 4, 14021, Czech Republic21Department of Epidemiology and Public Health, University College London, London, WC1E 6BT, UK22Cyprus International Institute for Environmental and Public Health in association with the Harvard School of Public Health, Cyprus University of Technology, 3603 Limassol, Cyprus23Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia24UCL Genetics Institute, Department of Genetics Environment and Evolution, London, WC1E 6BT, UK25Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK26Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden27Department of Clinical Sciences, Lund University, Malmö, Sweden28Unit of Cancer Epidemiology, San Giovanni Battista Hospital and Center for Cancer Prevention (CPO-Piemonte), 10129, Torino, Italy29Mayo Clinic Department of Neurology, Jacksonville, FL 32224, USA30Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA31Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK32Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands33Department of Preventive Cardiology, Institute for Clinical and Experimental Medicine, Prague 4, 14021, Czech Republic34Western Australian Centre for Health & Ageing, Centre for Medical Research, University of Western Australia, Perth, Australia35Department of Clinical Biochemistry, Royal Perth Hospital and School of Surgery, the University of Western Australia36Department of Internal Medicine, Internal Medicine, CHUV, Lausanne, Switzerland37UCL Institute of Health Equity, Department of Epidemiology & Public Health, London WC1E 7HB, UK38Instituto Medicina Molecular, Faculdade de Medicina Universidade de Lisboa, 1649-028 Lisbon, Portugal39Servico Neurologia, Hospital de Santa Maria, 1649-035 Lisbon, Portugal40Instituto Nacional de Saude Doutor Ricardo Jorge, 1649-016 Lisbon, Portugal41Faculdade Ciencias Universidade Lisboa, 1749-016 Lisbon, Portugal42Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK43Department of Cardiology, University Medical Center Groningen, Groningen, The Netherlands44Research Centre for Prevention and Health, Capital Region of Denmark, Glostrup University Hospital, Glostrup, Denmark45Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands46Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands47Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands48Vascular Screening and Diagnostic Centre, Ayios Dometios, Nicosia, Cyprus49Deparment of Vascular Surgery, Imperial College, London, SW7 2BX, UK50Cyprus Cardiovascular Disease Educational and Research trust, Nicosia, Cyprus51Department of Public Health & Caring Sciences, Uppsala University, Uppsala University Hospital, SE-75185 Uppsala, Sweden52Centre for Health Monitoring, National Institute of Public Health, 100 42 Prague, Czech Republic53Department of Epidemiology and Population Studies, Institute of Public Health, Jagiellonian University Medical College, 31-531 Krakow, Poland54Institute of Internal and Preventative Medicine, Siberian Branch of Russian Academy of Medical Sciences, Novosibirsk, Russia, 63008955Dept of Internal Medicine, Novosibirsk State Medical University, Novosibirsk, Russia, 63009156Faculty of Medicine, Novosibirsk State University, Novosibirsk, Russia, 63009057Department of Population Studies, Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas LT-50161, Lithuania58School of Surgery, University of Western Australia, Perth, Australia59Department of Neurology, Sir Charles Gairdner Hospital, Perth, Australia60School of Medicine and Pharmacology, The University of Western Australia, Nedlands, Perth, Australia61Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK WC1E 6JF62Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands63Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands64Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK65School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide SA 5000, Australia66South Australian Health and Medical Research Institute, Adelaide SA5000, Australia67School of Psychiatry & Clinical Neurosciences (M573), University of Western Australia, Perth 6009, Australia68Department of Psychiatry, Royal Perth Hospital, Perth, Australia69Department of Primary Care and Public Health and Primary Care, University of Cambridge, Cambridge, UK70Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden71Danish Cancer Society, Strandboulevarden, Copenhagen, Denmark72National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark73Department of Epidemiology and Department of Nutrition, Harvard School of Public Health, Boston, MA, USA74Channing Division of Network Medicine, Brigham and Womentextquoterights Hospital and Harvard Medical School, Boston, MA, USA75National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands76Dept Pathology and Medical Biology, Medical Biology division, Molecular Genetics, University Medical Center Groningen and Groningen University, Groningen, The Netherlands77Department of Primary Care & Population Health, UCL, London, UK78Population Health Research Institute, St Georgetextquoterights, University of London, London, UK79Instituto Gulbenkian Ciencia, P-2780-156 Oeiras, Portugal80Biofig - Center for Biodiversity, Functional and Integrative Genomics, Campus da FCUL, 1749-016 Lisboa, Portugal81Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK82Department of Cardiovascular Medicine, University of Oxford, Oxford, UK83Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA84National Heart, Lung, and Blood Institutetextquoterights The Framingham Heart Study, Framingham, Massachusetts, USA85Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Texas, USA86Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA87Department of Medicine, McMaster University, Hamilton, Ontario, Canada L8S4L888New York Academy of Medicine, New York, NY 10021, USA89Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA90Northwestern University, Feinberg School of Medicine, Department of Preventive Medicine, Chicago, IL, USA91Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA92School of Health Sciences, Jackson State University, Jackson, MS, USA93School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA94Preventive Medicine and Epidemiology, Evans Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA95Department of Laboratory Medicine and Pathology, University of Minnesota, USA96Division of Sleep and Circadian Disorders, Brigham and Womentextquoterights Hospital; Harvard Medical School, Boston USA97Baylor College of Medicine, Department of Medicine, Division of Atherosclerosis & Vascular Medicine, Houston, Texas 77030, USA98Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, Calif, USA99Division of Epidemiology, School of Public Health, University of Texas Health Science Center at Houston, Texas, USA100Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands101Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK102British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK103Genetics, R&D, GlaxoSmithKline, Stevenage, UK104Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA105Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA,USA106Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA107Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA108Department of Genetics, University of North Carolina School of Medicine at Chapel Hill, Chapel Hill, North Carolina 27514, USA109College of Pharmacy, The University of New Mexico, Albuquerque, NM, USA110The Copenhagen General Population Study, Herlev Hospital, Copenhagen, Denmark111Faculty of Health Sciences, Copenhagen University Hospital, University of Copenhagen,Copenhagen, Denmark112Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Denmark113Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UKCorrespondence to: J P Casas, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK 21 May 2014Abstract Objective To use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease. Design Mendelian randomisation meta-analysis of 56 epidemiological studies. Participants 261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers. Main outcome measures Odds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption. Results Carriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m2). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)). Conclusions Individuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health. Footnotes Members of the InterAct Consortium and IMPROVE study group are listed in the supplementary appendix. We thank Dr Kieran McCaul (Western Australian Centre for Health & Ageing, Centre for Medical Research, University of Western Australia, Perth, Western Australia, Australia) for help with analysis of the Health in Men Study (HIMS) cohort. Contributors: All coauthors satisfy the recommendations outlined in the ICMJE Recommendations 2013. All coauthors provided substantial contributions to the conception or design of the work or acquisition, analysis, or interpretation of data for the work, and helped with drafting the work or revising it critically for important intellectual content. All coauthors approve this version of the manuscript and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. MVH, CED, and JPC are guarantors for the study, had full access to all of the data in the study, and take responsibility for the integrity of the data and the accuracy of the data analysis. Funding of individuals Dr Michael V. Holmes is funded by a UK Medical Research Council (MRC) population health scientist fellowship (G0802432). Dr Abbas Dehghan is supported by NWO grant (veni, 916.12.154) and the EUR Fellowship. Dr James Meschia receives support from a Clinical Investigator grant from the Mayo Foundation for Medical Education and Research. Prof Mika Kivimaki was supported by the Medical Research Council; the British Heart Foundation; the Economic and Social Research Council; the National Heart Lung and Blood Institute (NHLBI: HL36310); and the National Institute on Aging (AG13196), US, NIH. Prof. Dr. J. W. Jukema is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Dr Owen Ross is funded by the James and Ester King Foundation and the Florida State Department of Health, the American Heart Association and the Myron and Jane Hanley Award in Stroke research. Prof Sir Michael Marmot is supported by a Medical Research Council Professorship. Dr Johan Sundstrom is supported by the Swedish Heart-Lung Foundation (grant 20041151), the Swedish Research Council (grant 2007-5942). Dr. Alex Reiner was supported by a contract HHSN268200900009C from the NIH National Heart Lung and Blood Institute. Dr James Y. Dai was supported by a R01 grant from the National Heart Lung and Blood Institute (HL 114901). Prof Hugh Watkins and Prof Martin Farrall are members of the Oxford British Heart Foundation (BHF) Centre of Research Excellence. Dr Daniel Swerdlow was supported by a MRC doctoral training award, and acknowledges support of the UCL MBPhD programme. Prof Frank Dudbridge is supported by a MRC grant (G1000718). Dr Jaroslav Hubacek was supported by MH CZ - DRO (quotedblbaseInstitute for Clinical and Experimental Medicine - IKEM, IN 00023001textquotedblleft). Dr Richard Silverwood is supported by the UK Economic and Social Research Council (NCRM Pathways node, ES/I025561/2). Professor Steve E. Humphries is supported by the British Heart Foundation (PG/2008/008). Prof Kuh, Prof Hardy and Dr Wong were supported by the Medical Research Council (MC_UU_12019/1). Dr Folkert W. Asselbergs is supported by National Institute of Health Research University College London Hospitals Biomedical Research Centre and Netherlands Heart Foundation (2014T001). Dr. Jorgenson is supported by the National Institute on Alcohol Abuse and Alcoholism (NIAAA: AA021223-01). Ajna Hamidovic was funded by MD Scientist Fellowship in Genetic Medicine (Northwestern Memorial Foundation) and the National Research Service Award F32DA024920 (NIH/NIDA; Ajna Hamidovic). Dr. Springtextquoterights work is supported by NIH HL075451. This work was supported in part by BHF Programme Grant RG/10/12/28456. Professors Lawlor and Davey Smith and Dr Zuccolo work in a research unit that receives funding from the UK Medical Research Council (MC_UU_12013/1 and MC_UU_12013/5). Dr. Buxbaumtextquoterights research is supported in part by P20MD006899 awarded by the National Institute on Minority Health and Health Disparities of the National Institutes of Health. Professors Aroon D. Hingorani and Juan P Casas are supported by the National Institute of Health Research University College London Hospitals Biomedical Research Centre. Funding of studies ALSPAC: We are extremely grateful to all of the families who took part in this study, the midwives for recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The research leading to the specific results from ALSPAC in this paper received funding from the Wellcome Trust (WT088806 and WT087997MA). The UK Medical Research Council and Wellcome Trust (092731), together with the University of Bristol, provide core support for the ALSPAC study. ARIC: The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL087641, R01HL59367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research; BWHHS: The British Womentextquoterights Heart and Health Study has been supported by funding from the British Heart Foundation (BHF) (grant PG/09/022) and the UK Department of Health Policy Research Programme (England) (grant 0090049). The BWHHS HumanCVD data were funded by the BHF (PG/07/131/24254); We thank all BWHHS participants, the general practitioners and their staff who have supported data collection since the study inception; BRHS: The British Regional Heart Study has been supported by programme grant funding from the British Heart Foundation (RG/08/013/25942); CARe: wishes to acknowledge the support of the National Heart, Lung and Blood Institute and the contributions of the research institutions, study investigators, field staff, and study participants in creating this resource for biomedical research (NHLBI contract number HHSN268200960009C); CARDIA: CARDIA is supported by contracts N01-HC-48047, N01-HC-48048, N01-HC-48049, N01-HC-48050 and N01-HC-95095 from the National Heart, Lung, and Blood Institute/National Institutes of Health; CFS: The Cleveland Family Study (CFS) was supported by grant HL46380 from the National Heart, Lung, and Blood Institute (NHLBI); CGPS: This study was supported by Herlev Hospital, Copenhagen University Hospital, The Copenhagen County Research Fund, and The Danish Medical Research Council; CHS: This research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01 HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC65226, and grant HL080295 from the National Heart, Lung, and Blood Institute (NHLBI), with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by AG023629 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at; Cyprus: The Cyprus Study has been supported by the Cyprus Cardiovascular Disease Educational and Research Trust (CCDERT) and Joint Cyprus Research Promotion Foundation, Ministry of Health and Cyprus Heart Foundation grant No 41/5PE as well as Research Promotion Foundation grants (PENEK 05/04 and YGEIA 04/06); EAS: The EAS was funded by the British Heart Foundation (Programme Grant RG/98002); ELSA: Samples from the English Longitudinal Study of Ageing (ELSA) DNA Repository (EDNAR), received support under a grant (AG1764406S1) awarded by the National Institute on Ageing (NIA). ELSA was developed by a team of researchers based at the National Centre for Social Research, University College London and the Institute of Fiscal Studies. The data were collected by the National Centre for Social Research.; EPIC InterAct: We thank all EPIC participants and staff for their contribution to the study. We thank staff from the Technical, Field Epidemiology and Data Functional Group Teams of the MRC Epidemiology Unit in Cambridge, UK, for carrying out sample preparation, DNA provision and quality control, genotyping and data-handling work. The InterAct study received funding from the European Union (Integrated Project LSHM-CT-2006-037197 in the Framework Programme 6 of the European Community); EPIC Netherlands: We thank Statistics Netherlands and Netherlands Cancer Registry (NKR) for follow-up data on cancer, cardiovascular disease, vital status and causes of death. Supported by the European Commission: Public Health and Consumer Protection Directorate 1993-2004; Research Directorate-General 2005; Dutch Ministry of Public Health, Welfare and Sports; Netherlands Cancer Registry; LK Research Funds; Dutch Prevention Funds; Dutch Zorg Onderzoek Nederland; and World Cancer Research Fund (The Netherlands) (to the European Prospective Investigation into Cancer and Nutrition-Netherlands study). The EPIC-NL study was funded by textquoteleftEurope against Cancertextquoteright Programme of the European Commission (SANCO), Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch Cancer Society; ZonMW the Netherlands Organisation for Health Research and Development, World Cancer Research Fund (WCRF) (The Netherlands). Genotyping was funded by IOP Genomics grant IGE05012 from Agentschap NL; EPIC Norfolk: We thank all study participants and the general practitioners and the EPIC-Norfolk study team for their helpful input. The EPIC-Norfolk study is supported by programme grants from the Medical Research Council and Cancer Research UK; EPIC Potsdam: The recruitment phase of the EPIC-Potsdam Study was supported by the Federal Ministry of Science, Germany (01 EA 9401), and the European Union (SOC 95201408 05F02). The follow-up was supported by the German Cancer Aid (70-2488-Ha I) and the European Community (SOC 98200769 05F02). The present study was supported by the Federal Ministry of Education and Research (0312750B). Mercodia provided the oxLDL kits free of charge. JS and AFHP were supported by German Research Federal Ministry (BMBF), JS was supported by a Heisenberg-Professorship (SP716/1-1) and clinical research groups of the German Research Foundation (DFG; KFO192/1 and 218/1). JS, AFHP and MM were also supported by a graduate school of the DFG (GK1208); EPIC Turin: The EPIC Turin study is funded by grants from the Associazione Italiana per le Ricerche sul Cancro, Italy and grants from the Compagnia di San Paolo, Turin, Italy; FHS: The Framingham Heart Study began in 1948 with the recruitment of an original cohort of 5,209 men and women (mean age 44 years; 55 percent women). In 1971 a second generation of study participants was enrolled; this cohort consisted of 5,124 children and spouses of children of the original cohort. The mean age of the offspring cohort was 37 years; 52 percent were women. A third generation cohort of 4,095 children of offspring cohort participants (mean age 40 years; 53 percent women) was enrolled beginning in 2002. At each clinic visit, a medical history was obtained with a focus on cardiovascular content, and participants underwent a physical examination including measurement of height and weight from which BMI was calculated; HAPIEE: This study was supported by Wellcome Trust textquoteleftDeterminants of Cardiovascular Diseases in Eastern Europe: A multi-centre cohort studytextquoteright [grants 064947/Z/01/Z; and 081081/Z/06/Z]; the MacArthur Foundation textquoteleftMacArthur Initiative on Social Upheaval and Healthtextquoteright [grant 712058]; the National Institute on Ageing textquoteleftHealth disparities and aging in societies in transition (the HAPIEE study)textquoteright [grant 1R01 AG23522]; and a project from the Ministry of Health, Czech Republic, for the development of the research organization No. 00023001 (IKEM, Prague, Czech Republic). We would like to thank researchers, interviewers and participants in Novosibirsk, Krakow, Kaunas, Hav'iv rov/Karviná, Jihlava, Úst'i nad Labem, Liberec, Hradec Králové, and Kromev r'iz.; HIMS: National Health and Medical Research Council (NHMRC) project grants 279408, 379600, 403963, 513823 and 634492; HPFS/NHS: We would like to thank Hardeep Ranu and Pati Soule from the DF/HCC Genotyping Core for genotyping and data management. This study was supported by research grants HL35464, CA55075, CA87969, AA11181, and HL34594 from the National Institute of Health, Bethesda; M.D; IMPROVE: This study was supported by the European Commission (Contract number: QLG1- CT- 2002- 00896), Ministero della Salute Ricerca Corrente, Italy, the Swedish Heart-Lung Foundation, the Swedish Research Council (projects 8691 and 0593), the Foundation for Strategic Research, the Stockholm County Council (project 562183), the Foundation for Strategic Research, the Academy of Finland (Grant $#$110413) and the British Heart Foundation (RG2008/014). None of the aforementioned funding organizations or sponsors has had a specific role in design or conduct of the study, collection, management, analysis, or interpretation of the data, or preparation, review, or approval of the manuscript; Inter99: The Inter99 study was supported by the Danish Medical Research Council, the Danish Centre for Evaluation and Health Technology Assessment, Copenhagen County, the Danish Heart Foundation, the Danish Pharmaceutical Association, the Health Insurance Foundation, the Augustinus Foundation, the Ib Henriksens foundation and the Beckett Foundation. The present study was further supported by the Danish Diabetes Association (grant No. 32, December 2005) and the Health Insurance Foundation (grant No. 2010 B 131); ISGS/SWISS: ISGS (Grant Number R01 42733) and SWISS (R01 NS39987) were funded by grants from the National Institute of Neurological Disorders and Stroke (US); Izhevsk: The Izhevsk Family Studies was funded by a UK Wellcome Trust programme grant (078557); MDC: This work was supported by the Swedish Medical Research Council; by the Swedish Heart and Lung Foundation; by the Medical Faculty of Lund University, Malmo University Hospital; by the Albert Pahlsson Research Foundation; by the Crafoord foundation; by the Ernhold Lundstroms Research Foundation, the Region Skane; by the Hulda and Conrad Mossfelt Foundation; by the King Gustaf V and Queen Victoria Foundation; by the Lennart Hanssons Memorial Fund; and by the Marianne and Marcus Wallenberg Foundation. Genotyping was supported by the British Heart Foundation (grant number CH/98001 to A.F.D., RG/07/005/23633 to A.F.D., S.P.); MESA: The Multi-Ethnic Study of Atherosclerosis Study (MESA) is a multicenter prospective cohort study initiated to study the development of subclinical cardiovascular disease. A total of 6814 women and men between the age of 45 and 84 year were recruited for the first examination between 2000 and 2002. Participants were recruited in six US cities (Baltimore, MD; Chicago, IL; Forsyth County, NC; Los Angeles County, CA; Northern Manhattan, NY; and St. Paul, MN). This study was approved by the institutional review boards of each study site, and written informed consent was obtained from all participants. This cohort was genotyped as part of the National Heart Lung and Blood Institutetextquoterights (NHLBI) Candidate Gene Association Resource (CARe) (Musunuru, K., Lettre, G., Young, T., Farlow, D.N., Pirruccello, J.P., Ejebe, K.G., Keating, B.J., Yang, Q., Chen, M.H., Lapchyk, N. et al. Candidate gene association resource (CARe): design, methods, and proof of concept. Circ. Cardiovasc. Genet, 3, 267-275.); MRC 1958BC: Dr Sue Ring and Dr Wendy McArdle (University of Bristol) and Mr Jon Johnson (Centre for Longitudinal Studies, Institute of Education, London) are thanked for help with data linkage. The study was supported by the Academy of Finland (12926) and the Medical Research Council (MRC G0601653 and SALVE/PrevMedsyn). The Medical Research Council funded the 2002-2004 clinical follow-up of the 1958 birth cohort (grant G0000934). This research used resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases, National Human Genome Research Institute, National Institute of Child Health and Human Development, and Juvenile Diabetes Research Foundation International (JDRF) and supported by U01 DK062418. This study makes use of data generated by the Wellcome Trust Case-Control Consortium. A full list of investigators who contributed to generation of the data is available from the Wellcome Trust Case-Control Consortium website( Funding for the project was provided by the Wellcome Trust under award 076113. Work at the Centre for Paediatric Epidemiology and Biostatistics benefits from funding support from the MRC in its capacity as the MRC Centre of Epidemiology for Child Health. Research at the University College London Institute of Child Health and Great Ormond Street Hospital for Children NHS Trust benefits from R&D funding received from the NHS Executive; MRC NSHD: Supported by Medical Research Council -- MC_UU_12019/1. We are very grateful to the members of this birth cohort for their continuing interest and participation in the study. We would like to acknowledge the Swallow group, UCL, who performed the DNA extractions; NHANES III: The findings and conclusions in this report are those of the author(s) and do not necessarily represent the views of the Centers for Disease Control and Prevention; NORDIL: This work was supported by the British Heart Foundation (grant number CH/98001 to A.F.D., RG/07/005/23633 to A.F.D., S.P.) and a Special Project, for genotyping of the Swedish extremes from the NORDIL and MDC cohorts; and by Pharmacia. We thank Professor Thomas Hedner (Department of Clinical Pharmacology, Sahlgrenska Academy, Gotheburg, Sweden) and Professor Sverre Kjeldsen (Ullevaal University Hospital, University of Oslo, Oslo, Norway), who are investigators of the NORDIL study. Professor Kjeldsen is also an investigator of the ASCOT trial; NPHS II: NPHS-II was supported by the British Medical Research Council, the US National Institutes of Health (grant NHLBI 33014), and Du Pont Pharma, Wilmington, Delaware; Portuguese stroke: Instituto Nacional de Saude Doutor Ricardo Jorge; PREVEND: PREVEND genetics is supported by the Dutch Kidney Foundation (Grant E033), The Netherlands organisation for health research and development (ZonMw grant 90.700.441), and the Dutch Inter University Cardiology Institute Netherlands (ICIN); PROCARDIS: PROCARDIS was supported by the EU FP7 Program (LSHM-CT-2007-037273), AstraZeneca, the British Heart Foundation, the Oxford BHF Centre of Research Excellence, the Wellcome Trust core award (090532/Z/09/Z), the Swedish Research Council, the Knut and Alice Wallenberg Foundation, the Swedish Heart-Lung Foundation, the Torsten and Ragnar Söderberg Foundation, the Strategic Cardiovascular Program of Karolinska Institutet and Stockholm County Council, the Foundation for Strategic Research and the Stockholm County Council (560283); PROSPER: The PROSPER study was supported by an investigator initiated grant obtained from Bristol-Myers Squibb and by grants from the Interuniversity Cardiology Institute of the Netherlands (ICIN) and the Durrer Center for Cardiogenetic Research both Institutes of the Netherlands Royal Academy of Arts and Sciences (KNAW), the Netherlands Heart Foundation, the Center for Medical Systems Biology (CMSB), a center of excellence approved by the Netherlands Genomics Initiative/Netherlands Organisation for Scientific Research (NWO), the Netherlands Consortium for Healthy Ageing (NCHA). The research leading to these results has received funding from the European Uniontextquoterights Seventh Framework Programme (FP7/2007-2013) under grant agreement ntextdegree HEALTH-F2-2009-223004 and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810); Rotterdam: The Rotterdam Study is supported by the Erasmus Medical Center and Erasmus University Rotterdam; the Netherlands Organization for Scientific Research (NWO); the Netherlands Organization for Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (RIDE); the Netherlands Heart Foundation; the Ministry of Education, Culture and Science; the Ministry of Health Welfare and Sports; the European Commission; and the Municipality of Rotterdam. Support for genotyping was provided by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) project nr. 050-060-810; SMART: SMART GENETICS was financially supported by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007); TPT: TPT was funded by the Medical Research Council, the British Heart Foundation, DuPont Pharma and Bayer Corporation; UCP: The UCP study was funded by Veni grant Organization for Scientific Research (NWO), Grant no. 2001.064 Netherlands Heart Foundation (NHS), and TI Pharma Grant T6-101 Mondriaan. The department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, has received unrestricted research funding from the Netherlands Organisation for Health Research and Development (ZonMW), the Dutch Health Care Insurance Board (CVZ), the Royal Dutch Pharmacists Association (KNMP), the private-public funded Top Institute Pharma (, includes co-funding from universities, government, and industry), the EU Innovative Medicines Initiative (IMI), EU 7th Framework Program (FP7), the Dutch Medicines Evaluation Board, the Dutch Ministry of Health and industry (including GlaxoSmithKline, Pfizer, and others); Whitehall II: The Whitehall II study and Mika Kivimaki were supported by the Medical Research Council; the British Heart Foundation; the Economic and Social Research Council; the National Heart Lung and Blood Institute (NHLBI: HL36310); and the National Institute on Aging (AG13196), US, NIH; WHI: The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. A listing of WHI investigators can be found at Statement of independence from funders: All researchers acted independently of study funders. The study funders played no role in study design and the collection, analysis, and interpretation of data and the writing of the article and the decision to submit it for publication. None of the funders influenced the data analysis or interpretation of results. The comments made in this paper are those of the authors and not necessarily those of any funders. Competing interests: All authors have completed the ICMJE uniform disclosure form at and declare: Prof Whittaker is 90% employed by GlaxoSmithKline and own shares in GlaxoSmithKline. All other coauthors report no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. Data sharing statement: No additional data available Transparency declaration: The lead authors, MVH, CED, and JPC (the manuscripttextquoterights guarantors) affirm that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
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    ABSTRACT: The relationship between aortic valve pathology and the aortic root and ascending aortic dimensions in cardiac surgery patients is unclear, and its clarification was the objective of this study. The severity of valve pathology, whether aortic valve stenosis (AS) or aortic valve regurgitation (AR), and the aortic dimensions (aortic root and ascending aorta) were prospectively evaluated with echocardiography in 500 consecutive patients with tricuspid aortic valve (TAV) or bicuspid aortic valve (BAV) who had undergone surgery due to aortic valve and/or ascending aortic disease. The distribution of valve pathology was similar in TAV and BAV patients when the aorta was non-dilated. However, when the aorta was dilated, AS was seen predominantly in BAV patients (n = 76) compared to TAV patients (n = 2). In TAV and BAV patients with non-dilated aortas, an increased severity of valve pathology was associated with smaller dimensions of the aortic root and the ascending aorta. In TAV and BAV patients with dilated aortas, an increase in the severity of AR was associated with a decreasing dimension of the ascending aorta but an increasing dimension of the aortic root. In BAV patients with aneurysm, the severity of AS was associated with a decreased dimension of the aortic root and the ascending aorta. Patients with AS and ascending aortic dilatation almost exclusively have a BAV. An increasing severity of valve pathology was related to decreasing dimensions of the aortic root and the ascending aorta, and the pattern was strikingly similar in TAV and BAV patients. The high frequency of ascending aortic dilatations in BAV patients cannot be explained by the valve pathology.
    The Journal of heart valve disease 07/2014; 23(4):463-72. · 0.73 Impact Factor
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    [Show abstract] [Hide abstract]
    ABSTRACT: Background-The study hypothesis was that thoracic aortic disease (TAD) is associated with a higher-than-expected prevalence of inguinal hernia. Such an association has been reported for abdominal aortic aneurysm (AAA) and hernia. Unlike AAA, TAD is not necessarily detectable with clinical examination or ultrasound, and there are no population-based screening programs for TAD. Therefore, conditions associated with TAD, such as inguinal hernia, are of particular clinical relevance. Methods and Results-The prevalence of inguinal hernia in subjects with TAD was determined from nation-wide register data and compared to a non-TAD group (patients with isolated aortic stenosis). Groups were balanced using propensity score matching. Multivariable statistical analysis (logistic regression) was performed to identify variables independently associated with hernia. Hernia prevalence was 110 of 750 (15%) in subjects with TAD versus 29 of 301 (9.6%) in non-TAD, P=0.03. This statistically significant difference remained after propensity score matching: 21 of 159 (13%) in TAD versus 14 of 159 (8.9%) in non-TAD, P<0.001. Variables independently associated with hernia in multivariable analysis were male sex (odds ratio [OR] with 95% confidence interval [95% CI]) 3.4 (2.1 to 5.4), P<0.001; increased age, OR 1.02/year (1.004 to 1.04), P=0.014; and TAD, OR 1.8 (1.1 to 2.8), P=0.015. Conclusions-The prevalence of inguinal hernia (15%) in TAD is higher than expected in a general population and higher in TAD, compared to non-TAD. TAD is independently associated with hernia in multivariable analysis. Presence or history of hernia may be of importance in detecting TAD, and the association warrants further study.
    Journal of the American Heart Association 06/2014; 3(4). DOI:10.1161/JAHA.114.001040 · 2.88 Impact Factor

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  • 2002–2015
    • Linköping University
      • • Department of Clinical and Experimental Medicine (IKE)
      • • Department of Medical and Health Sciences (IMH)
      • • Centre for Medical Image Science and Visualization
      • • Faculty of Health Sciences
      Linköping, Östergötland, Sweden
    • Karolinska Institutet
      • • Center for Molecular Medicine - CMM
      • • Department of Medicine, Solna
      Solna, Stockholm, Sweden
  • 2001–2015
    • Karolinska University Hospital
      • Center for Molecular Medicine (CMM)
      Tukholma, Stockholm, Sweden
  • 2013
    • University College London
      • Faculty of Population Health Sciences
      Londinium, England, United Kingdom
    • Örebro universitet
      • School of Health and Medical Sciences
      Örebro, OErebro, Sweden
  • 2012–2013
    • Mid Sweden University
      Härnösand, Västernorrland, Sweden
    • National Heart, Lung, and Blood Institute
      Maryland, United States
    • Wellcome Trust Sanger Institute
      Cambridge, England, United Kingdom
  • 2011
    • Akademiska Sjukhuset
      Uppsala, Uppsala, Sweden
  • 2010
    • Istituto Clinico Humanitas IRCCS
      • Department of Cardiac Surgery
      Rozzano, Lombardy, Italy
  • 2005
    • Södersjukhuset
      Tukholma, Stockholm, Sweden
    • The Jackson Laboratory
      Bar Harbor, Maine, United States
  • 2003–2005
    • University of Southampton
      Southampton, England, United Kingdom
    • University of Milan
      • Department of Pharmacological Sciences
      Milano, Lombardy, Italy
    • Helsinki University Central Hospital
      • Department of Medicine
      Helsinki, Province of Southern Finland, Finland
  • 2002–2005
    • University Hospital Linköping
      • • Department of Radiology
      • • Department of Rheumatology
      Linköping, Östergötland, Sweden
  • 2004
    • Chiang Mai University
      • Department of Surgery
      Amphoe Muang Chiang Mai, Chiang Mai, Thailand