Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. 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 analysis3, 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 approach4, 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 ancestry5. 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.
Background and Purpose: MMP (matrix metalloproteinase) levels have been widely associated with ischemic stroke risk and poststroke outcome. However, their role as a risk factor or as a subeffect because of ischemia is uncertain. Methods: We performed a literature search of genome-wide studies that evaluate serum/plasma levels of MMPs. We used a 2-sample Mendelian randomization approach to evaluate the causality of MMP levels on ischemic stroke risk or poststroke outcome, using 2 cohorts: MEGASTROKE (n=440 328) and GODs (n=1791). Results: Genome-wide association studies of MMP-1, MMP-8, and MMP-12 plasma/serum levels were evaluated. A significant association, which was also robust in the sensitivity analysis, was found with all ischemic strokes: MMP-12 (odds ratio=0.90 [95% CI, 0.86–0.94]; q value=7.43×10 − 5 ), and with subtypes of stroke, large-artery atherosclerosis: MMP-1 (odds ratio=0.95 [95% CI, 0.92–0.98]; q value=0.01) and MMP-12 (odds ratio=0.71 [95% CI, 0.65–0.77]; q value=5.11×10 − 14 ); small-vessel occlusion: MMP-8 (odds ratio=1.24 [95% CI, 1.06–1.45]; q value=0.03). No associations were found in relation to stroke outcome. Conclusions: Our study suggests a causal link between lower serum levels of MMP-12 and the risk of ischemic stroke, lower serum levels of MMP-1 and MMP-12 and the risk of large-artery stroke and higher serum levels of MMP-8 and the risk of lacunar stroke.
Small vessel strokes (SVS) and intracerebral haemorrhages (ICH) are acute outcomes of cerebral small vessel disease (SVD). Genetic studies combining both phenotypes have identified three loci associated with both traits. However, the genetic cis-regulation at the protein level associated with SVD has not been studied before. We performed a proteome-wide association study (PWAS) using FUSION to integrate a genome-wide association study (GWAS) and brain proteomic data to discover the common mechanisms regulating both SVS and ICH. Dorsolateral prefrontal cortex (dPFC) brain proteomes from the ROS/MAP study (N = 376 subjects and 1443 proteins) and the summary statistics for the SVS GWAS from the MEGASTROKE study (N = 237,511) and multi-trait analysis of GWAS (MTAG)-ICH–SVS from Chung et al. (N = 240,269) were selected. We performed PWAS and then a co-localization analysis with COLOC. The significant and nominal results were validated using a replication dPFC proteome (N = 152). The replicated results (q-value < 0.05) were further investigated for the causality relationship using summary data-based Mendelian randomization (SMR). One protein (ICA1L) was significantly associated with SVS (z-score = −4.42 and p-value = 9.6 × 10−6) and non-lobar ICH (z-score = −4.8 and p-value = 1.58 × 10−6) in the discovery PWAS, with a high co-localization posterior probability of 4. In the validation PWAS, ICA1L remained significantly associated with both traits. The SMR results for ICA1L indicated a causal association of protein expression levels in the brain with SVS (p-value = 3.66 × 10−5) and non-lobar ICH (p-value = 1.81 × 10−5). Our results show that the association of ICA1L with SVS and non-lobar ICH is conditioned by the cis-regulation of its protein levels in the brain.
Background: Stroke onset in women occurs later in life compared with men. The underlying mechanisms of these differences have not been established. Epigenetic clocks, based on DNA methylation (DNAm) profiles, are the most accurate biological age estimate. Epigenetic age acceleration (EAA) measures indicate whether an individual is biologically younger or older than expected. Our aim was to analyze whether sexual dichotomy at age of stroke onset is conditioned by EAA. METHODS: We used 2 DNAm datasets from whole blood samples of case-control genetic studies of ischemic stroke (IS), a discovery cohort of 374 IS patients (N women=163, N men=211), from GRECOS (Genotyping Recurrence Risk of Stroke) and SEDMAN (Dabigatran Study in the Early Phase of Stroke, New Neuroimaging Markers and Biomarkers) studies and a replication cohort of 981 IS patients (N women=411, N men=570) from BASICMAR register. We compared chronological age, 2 DNAm-based biomarkers of aging and intrinsic and extrinsic epigenetic age acceleration EAA (IEAA and extrinsic EAA, respectively), in IS as well as in individual IS etiologic subtypes. Horvath and Hannum epigenetic clocks were used to assess the aging rate. A proteomic study using the SOMAScan multiplex assay was performed on 26 samples analyzing 1305 proteins. Results: Women present lower Hannum-extrinsic EAA values, whereas men have higher Hannum-extrinsic EAA values (women=−0.64, men=1.24, P =1.34×10 -2 ); the same tendency was observed in the second cohort (women=−0.57, men=0.79, P =0.02). These differences seemed to be specific to cardioembolic and undetermined stroke subtypes. Additionally, 42 blood protein levels were associated with Hannum-extrinsic EAA ( P <0.05), belonging to the immune effector process ( P =1.54×10 -6 ) and platelet degranulation ( P <8.74×10 -6 ) pathways. Conclusions: This study shows that sex-specific underlying biological mechanisms associated with stroke onset could be due to differences in biological age acceleration between men and women.
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