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Sökning: WFRF:(Beulens J. W. J.) > (2020-2023)

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1.
  • Ramdas, S., et al. (författare)
  • A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
  • 2022
  • Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 109:8, s. 1366-1387
  • Tidskriftsartikel (refereegranskat)abstract
    • A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
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2.
  • Kanoni, Stavroula, et al. (författare)
  • Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
  • 2022
  • Ingår i: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N=1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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5.
  • Hageman, S., et al. (författare)
  • SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe
  • 2021
  • Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 42:25, s. 2439-2454
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims The aim of this study was to develop, validate, and illustrate an updated prediction model (SCORE2) to estimate 10-year fatal and non-fatal cardiovascular disease (CVD) risk in individuals without previous CVD or diabetes aged 40-69 years in Europe. Methods and results We derived risk prediction models using individual-participant data from 45 cohorts in 13 countries (677 684 individuals, 30 121 CVD events). We used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol. We defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions. Region-specific incidence was estimated using CVD mortality and incidence data on 10 776 466 individuals. For external validation, we analysed data from 25 additional cohorts in 15 European countries (1 133 181 individuals, 43 492 CVD events). After applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65-0.68) to 0.81 (0.76-0.86). Predicted CVD risk varied several-fold across European regions. For example, the estimated 10-year CVD risk for a 50-year-old smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low- risk countries to 14.0% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries. Conclusion SCORE2-a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations-enhances the identification of individuals at higher risk of developing CVD across Europe.
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6.
  • Bar, N., et al. (författare)
  • A reference map of potential determinants for the human serum metabolome
  • 2020
  • Ingår i: Nature. - : Nature Research. - 0028-0836 .- 1476-4687. ; 588:7836, s. 135-140
  • Tidskriftsartikel (refereegranskat)abstract
    • The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites—in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites. 
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7.
  • Tschiderer, L., et al. (författare)
  • Association of Intima-Media Thickness Measured at the Common Carotid Artery With Incident Carotid Plaque: Individual Participant Data Meta-Analysis of 20 Prospective Studies
  • 2023
  • Ingår i: Journal of the American Heart Association (JAHA). - 2047-9980. ; 12:12
  • Tidskriftsartikel (refereegranskat)abstract
    • BackgroundThe association between common carotid artery intima-media thickness (CCA-IMT) and incident carotid plaque has not been characterized fully. We therefore aimed to precisely quantify the relationship between CCA-IMT and carotid plaque development. Methods and ResultsWe undertook an individual participant data meta-analysis of 20 prospective studies from the Proof-ATHERO (Prospective Studies of Atherosclerosis) consortium that recorded baseline CCA-IMT and incident carotid plaque involving 21 494 individuals without a history of cardiovascular disease and without preexisting carotid plaque at baseline. Mean baseline age was 56 years (SD, 9 years), 55% were women, and mean baseline CCA-IMT was 0.71 mm (SD, 0.17 mm). Over a median follow-up of 5.9 years (5th-95th percentile, 1.9-19.0 years), 8278 individuals developed first-ever carotid plaque. We combined study-specific odds ratios (ORs) for incident carotid plaque using random-effects meta-analysis. Baseline CCA-IMT was approximately log-linearly associated with the odds of developing carotid plaque. The age-, sex-, and trial arm-adjusted OR for carotid plaque per SD higher baseline CCA-IMT was 1.40 (95% CI, 1.31-1.50; I-2=63.9%). The corresponding OR that was further adjusted for ethnicity, smoking, diabetes, body mass index, systolic blood pressure, low- and high-density lipoprotein cholesterol, and lipid-lowering and antihypertensive medication was 1.34 (95% CI, 1.24-1.45; I-2=59.4%; 14 studies; 16 297 participants; 6381 incident plaques). We observed no significant effect modification across clinically relevant subgroups. Sensitivity analysis restricted to studies defining plaque as focal thickening yielded a comparable OR (1.38 [95% CI, 1.29-1.47]; I-2=57.1%; 14 studies; 17 352 participants; 6991 incident plaques). ConclusionsOur large-scale individual participant data meta-analysis demonstrated that CCA-IMT is associated with the long-term risk of developing first-ever carotid plaque, independent of traditional cardiovascular risk factors.
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8.
  • Tschiderer, L., et al. (författare)
  • The Prospective Studies of Atherosclerosis (Proof-ATHERO) Consortium: Design and Rationale
  • 2020
  • Ingår i: Gerontology. - : S. Karger AG. - 0304-324X .- 1423-0003. ; 66:5, s. 447-459
  • Tidskriftsartikel (refereegranskat)abstract
    • Atherosclerosis - the pathophysiological mechanism shared by most cardiovascular diseases - can be directly or indirectly assessed by a variety of clinical tests including measurement of carotid intima-media thickness, carotid plaque, ankle-brachial index, pulse wave velocity, and coronary artery calcium. The Prospective Studies of Atherosclerosis (Proof-ATHERO) consortium (https://clinicalepi.i-med.ac.at/research/proof-athero/) collates de-identified individual-participant data of studies with information on atherosclerosis measures, risk factors for cardiovascular disease, and incidence of cardiovascular diseases. It currently comprises 74 studies that involve 106,846 participants from 25 countries and over 40 cities. In summary, 21 studies recruited participants from the general population (n = 67,784), 16 from high-risk populations (n = 22,677), and 37 as part of clinical trials (n = 16,385). Baseline years of contributing studies range from April 1980 to July 2014; the latest follow-up was until June 2019. Mean age at baseline was 59 years (standard deviation: 10) and 50% were female. Over a total of 830,619 person-years of follow-up, 17,270 incident cardiovascular events (including coronary heart disease and stroke) and 13,270 deaths were recorded, corresponding to cumulative incidences of 2.1% and 1.6% per annum, respectively. The consortium is coordinated by the Clinical Epidemiology Team at the Medical University of Innsbruck, Austria. Contributing studies undergo a detailed data cleaning and harmonisation procedure before being incorporated in the Proof-ATHERO central database. Statistical analyses are being conducted according to pre-defined analysis plans and use established methods for individual-participant data meta-analysis. Capitalising on its large sample size, the multi-institutional collaborative Proof-ATHERO consortium aims to better characterise, understand, and predict the development of atherosclerosis and its clinical consequences. (c) 2020 S. Karger AG, Basel
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9.
  • Koivula, Robert W., et al. (författare)
  • The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes : an IMI DIRECT study
  • 2020
  • Ingår i: Diabetologia. - : Springer Nature. - 0012-186X .- 1432-0428. ; 63:4, s. 744-756
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims/hypothesis: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.
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10.
  • Obura, M., et al. (författare)
  • Clinical profiles of post-load glucose subgroups and their association with glycaemic traits over time : An IMI-DIRECT study
  • 2021
  • Ingår i: Diabetic Medicine. - : Wiley. - 0742-3071 .- 1464-5491. ; 38:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Aim: To examine the hypothesis that, based on their glucose curves during a seven-point oral glucose tolerance test, people at elevated type 2 diabetes risk can be divided into subgroups with different clinical profiles at baseline and different degrees of subsequent glycaemic deterioration. Methods: We included 2126 participants at elevated type 2 diabetes risk from the Diabetes Research on Patient Stratification (IMI-DIRECT) study. Latent class trajectory analysis was used to identify subgroups from a seven-point oral glucose tolerance test at baseline and follow-up. Linear models quantified the associations between the subgroups with glycaemic traits at baseline and 18 months. Results: At baseline, we identified four glucose curve subgroups, labelled in order of increasing peak levels as 1–4. Participants in Subgroups 2–4, were more likely to have higher insulin resistance (homeostatic model assessment) and a lower Matsuda index, than those in Subgroup 1. Overall, participants in Subgroups 3 and 4, had higher glycaemic trait values, with the exception of the Matsuda and insulinogenic indices. At 18 months, change in homeostatic model assessment of insulin resistance was higher in Subgroup 4 (β = 0.36, 95% CI 0.13–0.58), Subgroup 3 (β = 0.30; 95% CI 0.10–0.50) and Subgroup 2 (β = 0.18; 95% CI 0.04–0.32), compared to Subgroup 1. The same was observed for C-peptide and insulin. Five subgroups were identified at follow-up, and the majority of participants remained in the same subgroup or progressed to higher peak subgroups after 18 months. Conclusions: Using data from a frequently sampled oral glucose tolerance test, glucose curve patterns associated with different clinical characteristics and different rates of subsequent glycaemic deterioration can be identified.
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