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- Mishra, A., et al.
(author)
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Stroke genetics informs drug discovery and risk prediction across ancestries
- 2022
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 611, s. 115-123
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Journal article (peer-reviewed)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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- Pulit, S. L., et al.
(author)
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Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes
- 2018
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In: Neurology-Genetics. - : Ovid Technologies (Wolters Kluwer Health). - 2376-7839. ; 4:6
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Journal article (peer-reviewed)abstract
- Objective We sought to assess whether genetic risk factors for atrial fibrillation (AF) can explain cardioembolic stroke risk. We evaluated genetic correlations between a previous genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors. We observed a strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson r = 0.77 and 0.76, respectively, across SNPs with p < 4.4 x 10(-4) in the previous AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio [OR] per SD = 1.40, p = 1.45 x 10(-48)), explaining similar to 20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per SD = 1.07,p = 0.004), but no other primary stroke subtypes (all p > 0.1). Genetic risk of AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.
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3. |
- Marini, S., et al.
(author)
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Association of Apolipoprotein E With Intracerebral Hemorrhage Risk by Race/Ethnicity A Meta-analysis
- 2019
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In: Jama Neurology. - : American Medical Association (AMA). - 2168-6149 .- 2168-6157. ; 76:4, s. 480-491
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Journal article (peer-reviewed)abstract
- IMPORTANCE Genetic studies of intracerebral hemorrhage (ICH) have focused mainly on white participants, but genetic risk may vary or could be concealed by differing nongenetic coexposures in nonwhite populations. Transethnic analysis of risk may clarify the role of genetics in ICH risk across populations. OBJECTIVE To evaluate associations between established differences in ICH risk by race/ethnicity and the variability in the risks of apolipoprotein E (APOE) epsilon 4 alleles, the most potent genetic risk factor for ICH. DESIGN, SETTING, AND PARTICIPANTS This case-control study of primary ICH meta-analyzed the association of APOE allele status on ICH risk, applying a 2-stage clustering approach based on race/ethnicity and stratified by a contributing study. A propensity score analysis was used to model the association of APOE with the burden of hypertension across race/ethnic groups. Primary ICH cases and controls were collected from 3 hospital- and population-based studies in the United States and 8 in European sites in the International Stroke Genetic Consortium. Participants were enrolled from January 1, 1999, to December 31, 2017. Participants with secondary causes of ICH were excluded from enrollment. Controls were regionally matched within each participating study. MAIN OUTCOMES AND MEASURES Clinical variables were systematically obtained from structured interviews within each site. APOE genotype was centrally determined for all studies. RESULTS In total, 13 124 participants (7153 [54.5%] male with a median [interquartile range] age of 66 [56-76] years) were included. In white participants, APOE epsilon 2 (odds ratio [OR], 1.49; 95% CI, 1.24-1.80; P < .001) and APOE epsilon 4 (OR, 1.51; 95% CI, 1.23-1.85; P < .001) were associated with lobar ICH risk; however, within self-identified Hispanic and black participants, no associations were found. After propensity score matching for hypertension burden, APOE epsilon 4 was associated with lobar ICH risk among Hispanic (OR, 1.14; 95% CI, 1.03-1.28; P = .01) but not in black (OR, 1.02; 95% CI, 0.98-1.07; P = .25) participants. APOE epsilon 2 and epsilon 4 did not show an association with nonlobar ICH risk in any race/ethnicity. CONCLUSIONS AND RELEVANCE APOE epsilon 4 and epsilon 2 alleles appear to affect lobar ICH risk variably by race/ethnicity, associations that are confirmed in white individuals but can be shown in Hispanic individuals only when the excess burden of hypertension is propensity score-matched; further studies are needed to explore the interactions between APOE alleles and environmental exposures that vary by race/ethnicity in representative populations at risk for ICH.
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5. |
- Franceschini, N., et al.
(author)
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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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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1
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Journal article (peer-reviewed)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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6. |
- Wang, Z., et al.
(author)
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Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention
- 2022
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 54:9, s. 1332-1344
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Journal article (peer-reviewed)abstract
- Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention. Multi-ancestry meta-analyses of genome-wide association studies for self-reported physical activity during leisure time, leisure screen time, sedentary commuting and sedentary behavior at work identify 99 loci associated with at least one of these traits.
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7. |
- Lumbers, R. T., et al.
(author)
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The genomics of heart failure: design and rationale of the HERMES consortium
- 2021
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In: Esc Heart Failure. - : Wiley. - 2055-5822. ; 8:6, s. 5531-5541
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Journal article (peer-reviewed)abstract
- Aims The HERMES (HEart failure Molecular Epidemiology for Therapeutic targets) consortium aims to identify the genomic and molecular basis of heart failure. Methods and results The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of >1.10 for common variants (allele frequency > 0.05) and >1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 x 10(-8) under an additive genetic model. Conclusions HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.
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8. |
- Jaworek, T., et al.
(author)
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Contribution of Common Genetic Variants to Risk of Early-Onset Ischemic Stroke
- 2022
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In: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 0028-3878 .- 1526-632X. ; 99:16
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Journal article (peer-reviewed)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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9. |
- Romagnoni, A, et al.
(author)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Journal article (peer-reviewed)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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10. |
- Pulit, SL, et al.
(author)
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Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study.
- 2016
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In: The Lancet. Neurology. - 1474-4465. ; 15:2, s. 174-84
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Journal article (peer-reviewed)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 16851 cases with state-of-the-art phenotyping data and 32473 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 20941 cases and 364736 unique stroke-free controls. The ischaemic stroke subtypes of these cases had previously been established with the Trial of Org 10172 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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