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Background and Aims: Stroke is the leading cause of adult-onset disability. Although clinical factors influence stroke outcome, there is a significant variability among individuals that may be attributed to genetics and epigenetics, including DNA methylation (DNAm). We aimed to study the association between DNAm and stroke prognosis., Methods and Results: To that aim, we conducted a two-phase study (discovery-replication and meta-analysis) in Caucasian patients with ischemic stroke from two independent centers (BasicMar [discovery, N = 316] and St. Pau [replication, N = 92]). Functional outcome was assessed using the modified Rankin Scale (mRS) at three months after stroke, being poor outcome defined as mRS > 2. DNAm was determined using the 450K and EPIC BeadChips in whole-blood samples collected within the first 24 h. We searched for differentially methylated positions (DMPs) in 370,344 CpGs, and candidates below p-value < 10 -5 were subsequently tested in the replication cohort. We then meta-analyzed DMP results from both cohorts and used them to identify differentially methylated regions (DMRs). After doing the epigenome-wide association study, we found 29 DMPs at p-value < 10 -5 and one of them was replicated: cg24391982, annotated to thrombospondin-2 (THBS2) gene (p-value discovery  = 1.54·10 -6 ; p-value replication  = 9.17·10 -4 ; p-value meta-analysis  = 6.39·10 -9 ). Besides, four DMRs were identified in patients with poor outcome annotated to zinc finger protein 57 homolog (ZFP57), Arachidonate 12-Lipoxygenase 12S Type (ALOX12), ABI Family Member 3 (ABI3) and Allantoicase (ALLC) genes (p-value < 1·10 -9 in all cases)., Discussion: Patients with poor outcome showed a DMP at THBS2 and four DMRs annotated to ZFP57, ALOX12, ABI3 and ALLC genes. This suggests an association between stroke outcome and DNAm, which may help identify new stroke recovery mechanisms., (© 2024. The Author(s).)

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.

Ischemic stroke is associated with aging. It is possible to predict chronological age by measuring age-related changes in DNA methylation from multiple CpG sites across the genome, known as biological age. The difference between biological age and actual chronological age would indicate an individual's level of aging. Our aim was to determine the biological age of ischemic stroke patients and compare their aging with controls of the same chronological age. A total of 123 individuals, 41 controls and 82 patients with ischemic stroke were paired by chronological age, ranging from 39 to 82 years. Illumina HumanMethylation450 BeadChip array was used to measure DNA methylation in CpG sites in both groups, and biological age was estimated using methylation values of specific CpGs. Ischemic stroke patients were biologically an average 2.5 years older than healthy controls (p-value=0.010). Stratified by age tertiles, younger stroke patients (≤57 years old) were biologically older than controls (OR=1.19; 95%CI 1.00-1.41, p-value=0.046). The older groups showed no biological age differences between cases and controls, but were close to reaching the significance level. Ischemic stroke patients are biologically older than controls. Biological age should be considered as a potential new biomarker of stroke risk., Competing Interests: The authors declare that they have no competing interests.

Type 2 diabetes mellitus (DM) is an established risk factor for a wide range of vascular diseases, including ischemic stroke (IS). Glycated hemoglobin A1c (HbA1c), a marker for average blood glucose levels over the previous 12 weeks, is used as a measure of glycemic control and also as a diagnostic criterion for diabetes (HbA1c levels ≥ 6.5%). Epigenetic mechanisms, such as DNA methylation, may be associated with aging processes and with modulation of the risk of various pathologies, such as DM. Specifically, DNA methylation could be one of the mechanisms mediating the relation between DM and environmental exposures. Our goal was to identify new CpG methylation sites associated with DM. We performed a genome-wide methylation study in whole-blood DNA from an IS patient cohorts. Illumina HumanMethylation450 BeadChip array was used to measure DNA methylation in CpG sites. All statistical analyses were adjusted for sex, age, hyperlipidemia, body mass index (BMI), smoking habit and cell count. Findings were replicated in two independent cohorts, an IS cohort and a population-based cohort, using the same array. In the discovery phase (N = 355), we identified a CpG site, cg19693031 (located in the TXNIP gene) that was associated with DM (P = 1.17 × 10(-12)); this CpG was replicated in two independent cohorts (N = 167 and N = 645). Methylation of TXNIP was inversely and intensely associated with HbA1c levels (P = 7.3 × 10(-16)), specifically related to diabetic patients with poor control of glucose levels. We identified an association between the TXNIP gene and DM through epigenetic mechanisms, related to sustained hyperglycemia levels (HbA1c ≥ 7%)., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

In DNA methylation, methyl groups are covalently bound to CpG dinucleotides. However, the assumption that methyl groups are not lost during routine DNA extraction has not been empirically tested. To avoid nonbiological associations in DNA methylation studies, it is essential to account for potential batch effect bias in the assessment of this epigenetic mechanism. Our purpose was to determine if the DNA isolation method is an independent source of variability in methylation status. We quantified Global DNA Methylation (GDM) by luminometric methylation assay (LUMA), comparing the results from 3 different DNA isolation methods. In the controlled analysis (n = 9), GDM differed slightly for the same individual depending on extraction method. In the population analysis (n = 580) there were significant differences in GDM between the 3 DNA isolation methods (medians, 78.1%, 76.5% and 75.1%; p<0.001). A systematic review of published data from LUMA GDM studies that specify DNA extraction methods is concordant with our findings. DNA isolation method is a source of GDM variability measured with LUMA. To avoid possible bias, the method used should be reported and taken into account in future DNA methylation studies.