| 1. |
- Mishra, A., et al.
(författare)
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Stroke genetics informs drug discovery and risk prediction across ancestries
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 611
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Tidskriftsartikel (refereegranskat)abstract
- Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
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| 2. |
- Franceschini, N., et al.
(författare)
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GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes
- 2018
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans. © 2018, The Author(s).
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| 3. |
- Kaptoge, S., et al.
(författare)
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Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation
- 2023
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Ingår i: The Lancet Diabetes and Endocrinology. - : Elsevier. - 2213-8587 .- 2213-8595. ; 11:10, s. 731-742
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Tidskriftsartikel (refereegranskat)abstract
- Background: The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy. Methods: For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961–2007, median latest follow-up years 1980–2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU. Findings: For participants with diabetes, we observed a linear dose–response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43–2·97) when diagnosed at 30–39 years, 2·26 (2·08–2·45) at 40–49 years, 1·84 (1·72–1·97) at 50–59 years, 1·57 (1·47–1·67) at 60–69 years, and 1·39 (1·29–1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier. Interpretation: Every decade of earlier diagnosis of diabetes was associated with about 3–4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes. Funding: British Heart Foundation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.
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| 4. |
- Gregson, J., et al.
(författare)
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Cardiovascular Risk Factors Associated With Venous Thromboembolism
- 2019
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Ingår i: JAMA Cardiology. - : American Medical Association (AMA). - 0965-2590 .- 2380-6583 .- 2380-6591. ; 4:2, s. 163-173
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Tidskriftsartikel (refereegranskat)abstract
- IMPORTANCE It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). OBJECTIVE To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. DESIGN, SETTING, AND PARTICIPANTS This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. MAIN OUTCOMES AND MEASURES Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CND], 25131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). RESULTS Of the 731728 participants from the ERFC. 403 396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421537 participants from the UK Biobank, 233 699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. CONCLUSIONS AND RELEVANCE Older age, smoking, and adiposity were consistently associated with higher VTE risk.
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| 5. |
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| 6. |
- Pulit, SL, et al.
(författare)
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Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study.
- 2016
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Ingår i: The Lancet. Neurology. - 1474-4465. ; 15:2, s. 174-84
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Tidskriftsartikel (refereegranskat)abstract
- The discovery of disease-associated loci through genome-wide association studies (GWAS) is the leading genetic approach to the identification of novel biological pathways underlying diseases in humans. Until recently, GWAS in ischaemic stroke have been limited by small sample sizes and have yielded few loci associated with ischaemic stroke. We did a large-scale GWAS to identify additional susceptibility genes for stroke and its subtypes.To identify genetic loci associated with ischaemic stroke, we did a two-stage GWAS. In the first stage, we included 16 851 cases with state-of-the-art phenotyping data and 32 473 stroke-free controls. Cases were aged 16 to 104 years, recruited between 1989 and 2012, and subtypes of ischaemic stroke were recorded by centrally trained and certified investigators who used the web-based protocol, Causative Classification of Stroke (CCS). We constructed case-control strata by identifying samples that were genotyped on nearly identical arrays and were of similar genetic ancestral background. We cleaned and imputed data by use of dense imputation reference panels generated from whole-genome sequence data. We did genome-wide testing to identify stroke-associated loci within each stratum for each available phenotype, and we combined summary-level results using inverse variance-weighted fixed-effects meta-analysis. In the second stage, we did in-silico lookups of 1372 single nucleotide polymorphisms identified from the first stage GWAS in 20 941 cases and 364 736 unique stroke-free controls. The ischaemic stroke subtypes of these cases had previously been established with the Trial of Org 10 172 in Acute Stroke Treatment (TOAST) classification system, in accordance with local standards. Results from the two stages were then jointly analysed in a final meta-analysis.We identified a novel locus (G allele at rs12122341) at 1p13.2 near TSPAN2 that was associated with large artery atherosclerosis-related stroke (first stage odds ratio [OR] 1·21, 95% CI 1·13-1·30, p=4·50 × 10(-8); joint OR 1·19, 1·12-1·26, p=1·30 × 10(-9)). Our results also supported robust associations with ischaemic stroke for four other loci that have been reported in previous studies, including PITX2 (first stage OR 1·39, 1·29-1·49, p=3·26 × 10(-19); joint OR 1·37, 1·30-1·45, p=2·79 × 10(-32)) and ZFHX3 (first stage OR 1·19, 1·11-1·27, p=2·93 × 10(-7); joint OR 1·17, 1·11-1·23, p=2·29 × 10(-10)) for cardioembolic stroke, and HDAC9 (first stage OR 1·29, 1·18-1·42, p=3·50 × 10(-8); joint OR 1·24, 1·15-1·33, p=4·52 × 10(-9)) for large artery atherosclerosis stroke. The 12q24 locus near ALDH2, which has previously been associated with all ischaemic stroke but not with any specific subtype, exceeded genome-wide significance in the meta-analysis of small artery stroke (first stage OR 1·20, 1·12-1·28, p=6·82 × 10(-8); joint OR 1·17, 1·11-1·23, p=2·92 × 10(-9)). Other loci associated with stroke in previous studies, including NINJ2, were not confirmed.Our results suggest that all ischaemic stroke-related loci previously implicated by GWAS are subtype specific. We identified a novel gene associated with large artery atherosclerosis stroke susceptibility. Follow-up studies will be necessary to establish whether the locus near TSPAN2 can be a target for a novel therapeutic approach to stroke prevention. In view of the subtype-specificity of the associations detected, the rich phenotyping data available in the Stroke Genetics Network (SiGN) are likely to be crucial for further genetic discoveries related to ischaemic stroke.US National Institute of Neurological Disorders and Stroke, National Institutes of Health.
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| 7. |
- Di Angelantonio, E., et al.
(författare)
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Glycated Hemoglobin Measurement and Prediction of Cardiovascular Disease
- 2014
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Ingår i: Jama-Journal of the American Medical Association. - : American Medical Association (AMA). - 0098-7484 .- 1538-3598. ; 311:12, s. 1225-1233
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Tidskriftsartikel (refereegranskat)abstract
- IMPORTANCE The value of measuring levels of glycated hemoglobin (HbA(1c)) for the prediction of first cardiovascular events is uncertain. OBJECTIVE To determine whether adding information on HbA(1c) values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. DESIGN, SETTING, AND PARTICIPANTS Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. MAIN OUTCOMES AND MEASURES Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (>= 7.5%) risk. RESULTS During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA(1c) values and CVD risk. The association between HbA(1c) values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA(1c) was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA(1c) assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. CONCLUSIONS AND RELEVANCE In a study of individuals without known CVD or diabetes, additional assessment of HbA(1c) values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.
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| 8. |
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| 9. |
- Di Angelantonio, E., et al.
(författare)
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Association of Cardiometabolic Multimorbidity With Mortality
- 2015
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Ingår i: JAMA. - : American Medical Association (AMA). - 0098-7484 .- 1538-3598. ; 314:1, s. 52-60
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Tidskriftsartikel (refereegranskat)abstract
- IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing. OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy. RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.
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| 10. |
- Jaworek, T., et al.
(författare)
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Contribution of Common Genetic Variants to Risk of Early-Onset Ischemic Stroke
- 2022
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Ingår i: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 0028-3878 .- 1526-632X. ; 99:16, s. E1738-E1754
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Tidskriftsartikel (refereegranskat)abstract
- Background and Objectives Current genome-wide association studies of ischemic stroke have focused primarily on late-onset disease. As a complement to these studies, we sought to identify the contribution of common genetic variants to risk of early-onset ischemic stroke. Methods We performed a meta-analysis of genome-wide association studies of early-onset stroke (EOS), ages 18-59 years, using individual-level data or summary statistics in 16,730 cases and 599,237 nonstroke controls obtained across 48 different studies. We further compared effect sizes at associated loci between EOS and late-onset stroke (LOS) and compared polygenic risk scores (PRS) for venous thromboembolism (VTE) between EOS and LOS. Results We observed genome-wide significant associations of EOS with 2 variants in ABO, a known stroke locus. These variants tag blood subgroups O1 and A1, and the effect sizes of both variants were significantly larger in EOS compared with LOS. The odds ratio (OR) for rs529565, tagging O1, was 0.88 (95% confidence interval [CI]: 0.85-0.91) in EOS vs 0.96 (95% CI: 0.92-1.00) in LOS, and the OR for rs635634, tagging A1, was 1.16 (1.11-1.21) for EOS vs 1.05 (0.99-1.11) in LOS; p-values for interaction = 0.001 and 0.005, respectively. Using PRSs, we observed that greater genetic risk for VTE, another prothrombotic condition, was more strongly associated with EOS compared with LOS (p = 0.008). Discussion The ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with EOS than with LOS, supporting a stronger role of prothrombotic factors in EOS.
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