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- Bergström, Göran, 1964, et al.
(author)
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Prevalence of Subclinical Coronary Artery Atherosclerosis in the General Population
- 2021
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In: Circulation. - Philadelphia : American Heart Association. - 0009-7322 .- 1524-4539. ; 144:12, s. 916-929
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Journal article (peer-reviewed)abstract
- Background: Early detection of coronary atherosclerosis using coronary computed tomography angiography (CCTA), in addition to coronary artery calcification (CAC) scoring, may help inform prevention strategies. We used CCTA to determine the prevalence, severity, and characteristics of coronary atherosclerosis and its association with CAC scores in a general population.Methods: We recruited 30 154 randomly invited individuals age 50 to 64 years to SCAPIS (the Swedish Cardiopulmonary Bioimage Study). The study includes individuals without known coronary heart disease (ie, no previous myocardial infarctions or cardiac procedures) and with high-quality results from CCTA and CAC imaging performed using dedicated dual-source CT scanners. Noncontrast images were scored for CAC. CCTA images were visually read and scored for coronary atherosclerosis per segment (defined as no atherosclerosis, 1% to 49% stenosis, or ≥50% stenosis). External validity of prevalence estimates was evaluated using inverse probability for participation weighting and Swedish register data.Results: In total, 25 182 individuals without known coronary heart disease were included (50.6% women). Any CCTA-detected atherosclerosis was found in 42.1%; any significant stenosis (≥50%) in 5.2%; left main, proximal left anterior descending artery, or 3-vessel disease in 1.9%; and any noncalcified plaques in 8.3% of this population. Onset of atherosclerosis was delayed on average by 10 years in women. Atherosclerosis was more prevalent in older individuals and predominantly found in the proximal left anterior descending artery. Prevalence of CCTA-detected atherosclerosis increased with increasing CAC scores. Among those with a CAC score >400, all had atherosclerosis and 45.7% had significant stenosis. In those with 0 CAC, 5.5% had atherosclerosis and 0.4% had significant stenosis. In participants with 0 CAC and intermediate 10-year risk of atherosclerotic cardiovascular disease according to the pooled cohort equation, 9.2% had CCTA-verified atherosclerosis. Prevalence estimates had excellent external validity and changed marginally when adjusted to the age-matched Swedish background population.Conclusions: Using CCTA in a large, random sample of the general population without established disease, we showed that silent coronary atherosclerosis is common in this population. High CAC scores convey a significant probability of substantial stenosis, and 0 CAC does not exclude atherosclerosis, particularly in those at higher baseline risk.
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- Bergström, Göran, et al.
(author)
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Prevalence of Subclinical Coronary Artery Atherosclerosis in the General Population
- 2021
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In: Circulation. - : Wolters Kluwer. - 0009-7322 .- 1524-4539. ; 144:12, s. 916-929
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Journal article (peer-reviewed)abstract
- Background: Early detection of coronary atherosclerosis using coronary computed tomography angiography (CCTA), in addition to coronary artery calcification (CAC) scoring, may help inform prevention strategies. We used CCTA to determine the prevalence, severity, and characteristics of coronary atherosclerosis and its association with CAC scores in a general population.Methods: We recruited 30 154 randomly invited individuals age 50 to 64 years to SCAPIS (the Swedish Cardiopulmonary Bioimage Study). The study includes individuals without known coronary heart disease (ie, no previous myocardial infarctions or cardiac procedures) and with high-quality results from CCTA and CAC imaging performed using dedicated dual-source CT scanners. Noncontrast images were scored for CAC. CCTA images were visually read and scored for coronary atherosclerosis per segment (defined as no atherosclerosis, 1% to 49% stenosis, or ≥50% stenosis). External validity of prevalence estimates was evaluated using inverse probability for participation weighting and Swedish register data.Results: In total, 25 182 individuals without known coronary heart disease were included (50.6% women). Any CCTA-detected atherosclerosis was found in 42.1%; any significant stenosis (≥50%) in 5.2%; left main, proximal left anterior descending artery, or 3-vessel disease in 1.9%; and any noncalcified plaques in 8.3% of this population. Onset of atherosclerosis was delayed on average by 10 years in women. Atherosclerosis was more prevalent in older individuals and predominantly found in the proximal left anterior descending artery. Prevalence of CCTA-detected atherosclerosis increased with increasing CAC scores. Among those with a CAC score >400, all had atherosclerosis and 45.7% had significant stenosis. In those with 0 CAC, 5.5% had atherosclerosis and 0.4% had significant stenosis. In participants with 0 CAC and intermediate 10-year risk of atherosclerotic cardiovascular disease according to the pooled cohort equation, 9.2% had CCTA-verified atherosclerosis. Prevalence estimates had excellent external validity and changed marginally when adjusted to the age-matched Swedish background population.Conclusions: Using CCTA in a large, random sample of the general population without established disease, we showed that silent coronary atherosclerosis is common in this population. High CAC scores convey a significant probability of substantial stenosis, and 0 CAC does not exclude atherosclerosis, particularly in those at higher baseline risk.
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- Bergström, Göran, et al.
(author)
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Self-report tool for identification of individuals with coronary atherosclerosis : the Swedish cardiopulmonary bioimage study
- 2024
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In: Journal of the American Heart Association. - : John Wiley & Sons. - 2047-9980. ; 13:14
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Journal article (peer-reviewed)abstract
- BACKGROUND: Coronary atherosclerosis detected by imaging is a marker of elevated cardiovascular risk. However, imaging involves large resources and exposure to radiation. The aim was, therefore, to test whether nonimaging data, specifically data that can be self-reported, could be used to identify individuals with moderate to severe coronary atherosclerosis.METHODS AND RESULTS: We used data from the population-based SCAPIS (Swedish CardioPulmonary BioImage Study) in individuals with coronary computed tomography angiography (n=25 182) and coronary artery calcification score (n=28 701), aged 50 to 64 years without previous ischemic heart disease. We developed a risk prediction tool using variables that could be assessed from home (self-report tool). For comparison, we also developed a tool using variables from laboratory tests, physical examinations, and self-report (clinical tool) and evaluated both models using receiver operating characteristic curve analysis, external validation, and benchmarked against factors in the pooled cohort equation. The self-report tool (n=14 variables) and the clinical tool (n=23 variables) showed high-to-excellent discriminative ability to identify a segment involvement score ≥4 (area under the curve 0.79 and 0.80, respectively) and significantly better than the pooled cohort equation (area under the curve 0.76, P<0.001). The tools showed a larger net benefit in clinical decision-making at relevant threshold probabilities. The self-report tool identified 65% of all individuals with a segment involvement score ≥4 in the top 30% of the highest-risk individuals. Tools developed for coronary artery calcification score ≥100 performed similarly.CONCLUSIONS: We have developed a self-report tool that effectively identifies individuals with moderate to severe coronary atherosclerosis. The self-report tool may serve as prescreening tool toward a cost-effective computed tomography-based screening program for high-risk individuals.
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- Bergström, Göran, et al.
(author)
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Self-Report Tool for Identification of Individuals With Coronary Atherosclerosis : The Swedish CardioPulmonary BioImage Study
- 2024
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In: Journal of the American Heart Association. - : American Heart Association. - 2047-9980. ; 13:14
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Journal article (peer-reviewed)abstract
- BACKGROUND: Coronary atherosclerosis detected by imaging is a marker of elevated cardiovascular risk. However, imaging involves large resources and exposure to radiation. The aim was, therefore, to test whether nonimaging data, specifically data that can be self-reported, could be used to identify individuals with moderate to severe coronary atherosclerosis. METHODS AND RESULTS: We used data from the population-based SCAPIS (Swedish CardioPulmonary BioImage Study) in individuals with coronary computed tomography angiography (n=25 182) and coronary artery calcification score (n=28 701), aged 50 to 64 years without previous ischemic heart disease. We developed a risk prediction tool using variables that could be assessed from home (self-report tool). For comparison, we also developed a tool using variables from laboratory tests, physical examinations, and self-report (clinical tool) and evaluated both models using receiver operating characteristic curve analysis, external validation, and benchmarked against factors in the pooled cohort equation. The self-report tool (n=14 variables) and the clinical tool (n=23 variables) showed high-to-excellent discriminative ability to identify a segment involvement score ≥4 (area under the curve 0.79 and 0.80, respectively) and significantly better than the pooled cohort equation (area under the curve 0.76, P<0.001). The tools showed a larger net benefit in clinical decision-making at relevant threshold probabilities. The self-report tool identified 65% of all individuals with a segment involvement score ≥4 in the top 30% of the highest-risk individuals. Tools developed for coronary artery calcification score ≥100 performed similarly. CONCLUSIONS: We have developed a self-report tool that effectively identifies individuals with moderate to severe coronary atherosclerosis. The self-report tool may serve as prescreening tool toward a cost-effective computed tomography-based screening program for high-risk individuals.
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- Carlsson, Axel C, et al.
(author)
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Growth differentiation factor 15 (GDF-15) is a potential biomarker of both diabetic kidney disease and future cardiovascular events in cohorts of individuals with type 2 diabetes : a proteomics approach
- 2020
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In: Upsala Journal of Medical Sciences. - : Uppsala Medical Society. - 0300-9734 .- 2000-1967. ; 25:1, s. 37-43
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Journal article (peer-reviewed)abstract
- Background: Diabetic kidney disease (DKD) is a leading risk factor for end-stage renal disease and is one of the most important risk factors for cardiovascular disease in patients with diabetes. It is possible that novel markers portraying the pathophysiological underpinning processes may be useful.Aim: To investigate the associations between 80 circulating proteins, measured by a proximity extension assay, and prevalent DKD and major adverse cardiovascular events (MACE) in type 2 diabetes.Methods: We randomly divided individuals with type 2 diabetes from three cohorts into a two-thirds discovery and one-third replication set (total n = 813, of whom 231 had DKD defined by estimated glomerular filtration rate <60 mg/mL/1.73 m2 and/or urinary albumin-creatinine ratio ≥3 g/mol). Proteins associated with DKD were also assessed as predictors for incident major adverse cardiovascular events (MACE) in persons with DKD at baseline.Results: Four proteins were positively associated with DKD in models adjusted for age, sex, cardiovascular risk factors, glucose control, and diabetes medication: kidney injury molecule-1 (KIM-1, odds ratio [OR] per standard deviation increment, 1.65, 95% confidence interval [CI] 1.27-2.14); growth differentiation factor 15 (GDF-15, OR 1.40, 95% CI 1.16-1.69); myoglobin (OR 1.57, 95% CI 1.30-1.91), and matrix metalloproteinase 10 (MMP-10, OR 1.43, 95% CI 1.17-1.74). In patients with DKD, GDF-15 was significantly associated with increased risk of MACE after adjustments for baseline age, sex, microalbuminuria, and kidney function and (59 MACE events during 7 years follow-up, hazard ratio per standard deviation increase 1.43 [95% CI 1.03-1.98]) but not after further adjustments for cardiovascular risk factors.Conclusion: Our proteomics approach confirms and extends previous associations of higher circulating levels of GDF-15 with both micro- and macrovascular disease in patients with type 2 diabetes. Our data encourage additional studies evaluating the clinical utility of our findings.
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- Lind, Lars, et al.
(author)
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Plasma Protein Profile of Carotid Artery Atherosclerosis and Atherosclerotic Outcomes : Meta-Analyses and Mendelian Randomization Analyses
- 2021
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In: Arteriosclerosis, Thrombosis and Vascular Biology. - : Lippincott Williams & Wilkins. - 1079-5642 .- 1524-4636. ; 41:5, s. 1777-1788
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Journal article (peer-reviewed)abstract
- OBJECTIVE: To identify causal pathophysiological mechanisms for atherosclerosis and incident cardiovascular events using protein measurements.APPROACH AND RESULTS: Carotid artery atherosclerosis was assessed by ultrasound, and 86 cardiovascular-related proteins were measured using the Olink CVD-I panel in 7 Swedish prospective studies (11 754 individuals). The proteins were analyzed in relation to intima-media thickness in the common carotid artery (IMT-CCA), plaque occurrence, and incident cardiovascular events (composite end point of myocardial infarction or ischemic stroke) using a discovery/replication approach in different studies. After adjustments for traditional cardiovascular risk factors, 11 proteins remained significantly associated with IMT-CCA in the replication stage, whereas 9 proteins were replicated for plaque occurrence and 17 proteins for incident cardiovascular events. NT-proBNP (N-terminal pro-B-type natriuretic peptide) and MMP (matrix metalloproteinase)-12 were associated with both IMT-CCA and incident events, but the overlap was considerably larger between plaque occurrence and incident events, including MMP-12, TIM-1 (T-cell immunoglobulin and mucin domain 1), GDF (growth/differentiation factor)-15, IL (interleukin)-6, U-PAR (urokinase plasminogen activator surface receptor), LOX-1 (lectin-like oxidized LDL [low-density lipoprotein] receptor 1), and TRAIL-R2 (TNF [tumor necrosis factor]-related apoptosis-inducing ligand receptor 2). Only MMP-12 was associated with IMT-CCA, plaque, and incident events with a positive and concordant direction of effect. However, a 2-sample Mendelian randomization analysis suggested that increased MMP-12 may be protective against ischemic stroke (P=5.5x10(-7)), which is in the opposite direction of the observational analyses.CONCLUSIONS: The present meta-analysis discovered several proteins related to carotid atherosclerosis that partly differed in their association with IMT-CCA, plaque, and incident atherosclerotic disease. Mendelian randomization analysis for the top finding, MMP-12, suggests that the increased levels of MMP-12 could be a consequence of atherosclerotic burden rather than the opposite chain of events.
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- Locke, Adam E, et al.
(author)
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Genetic studies of body mass index yield new insights for obesity biology.
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
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Journal article (peer-reviewed)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.
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- Nowak, Christoph, et al.
(author)
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Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes
- 2018
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In: Diabetologia. - : SPRINGER. - 0012-186X .- 1432-0428. ; 61:8, s. 1748-1757
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Journal article (peer-reviewed)abstract
- Aims/hypothesis Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes. Methods We combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multivariable-adjusted Cox regression was used in a discovery/replication design to identify biomarkers for incident MACE. We used gradient-boosted machine learning and lasso regularised Cox regression in a random 75% training subsample to assess whether adding proteins to risk factors included in the Swedish National Diabetes Register risk model would improve the prediction of MACE in the separate 25% test subsample. Results Of 1211 adults with type 2 diabetes (32% women), 211 experienced a MACE over a mean (+/- SD) of 6.4 +/- 2.3 years. We replicated associations (< 5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit alpha (IL-27a), kidney injury molecule (KIM)-1, fibroblast growth factor (FGF)-23, protein S100-A12, TNF receptor (TNFR)-1, TNFR-2 and TNF-related apoptosis-inducing ligand receptor (TRAIL-R)2. Addition of the 80-protein assay to established risk factors improved discrimination in the separate test sample from 0.686 (95% CI 0.682, 0.689) to 0.748 (95% CI 0.746, 0.751). A sparse model of 20 added proteins achieved a C statistic of 0.747 (95% CI 0.653, 0.842) in the test sample. Conclusions/interpretation We identified eight protein biomarkers, four of which are novel, for risk of MACE in community residents with type 2 diabetes, and found improved risk prediction by combining multiplex proteomics with an established risk model. Multiprotein arrays could be useful in identifying individuals with type 2 diabetes who are at highest risk of a cardiovascular event.
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