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%).

Background and Purpose— White matter hyperintensity (WMH), or leukoaraiosis, is a radiologic finding generally assumed to reflect diseased small cerebral vasculature. WMH has significant functional impact through its relation to cognitive decline and risk of ischemic and hemorrhagic stroke. Accumulating evidence suggests that some manifestations of small-vessel disease such as intracerebral hemorrhage are associated with low levels of cholesterol. We sought to determine the relation between hyperlipidemia and WMH severity in patients with acute ischemic stroke (AIS). Methods— We analyzed 2 independent, hospital-based AIS cohorts. Demographic and clinical data were collected prospectively. WMH was measured using semiautomated volumetric image analysis and a semiquantitative visual grading scale. Univariate and multivariable regression analyses were used to assess the relation between WMH severity and study variables. Results— A total of 631 and 504 subjects in the first and second cohorts, respectively, were included. In univariate analyses, advancing age and hypertension were associated with severity of WMH ( P <0.001) in both cohorts. In the multivariable analysis, after controlling for age, sex, and significant risk factors in the univariate and age-adjusted analyses, patients with a history of hyperlipidemia had less severe WMH in both cohorts ( P <0.01). Conclusions— Results from 2 independent cohorts demonstrate that AIS patients with a history of hyperlipidemia have less severe WMH at the time of stroke. These data support the hypothesis that hyperlipidemia may play a relatively protective role in cerebral small-vessel disease.

Age and stroke severity are the main mortality predictors after ischemic stroke. However, chronological age and biological age are not exactly concordant. Age-related changes in DNA methylation in multiple CpG sites across the genome can be used to estimate biological age, which is influenced by lifestyle, environmental factors, and genetic variation. We analyzed the impact of biological age on 3-month mortality in ischemic stroke. We assessed 594 patients with acute ischemic stroke in a cohort from Hospital del Mar (Barcelona) and validated the results in an independent cohort. Demographic and clinical data, including chronological age, vascular risk factors, initial stroke severity (NIHSS score), recanalization treatment, and previous modified Rankin scale were registered. Biological age was estimated with an algorithm based on DNA methylation in 71 CpGs. Biological age was predictive of 3-month mortality (p = 0.041; OR = 1.05, 95% CI 1.00–1.10), independently of NIHSS score, chronological age, TOAST, vascular risk factors, and blood cell composition. Stratified by TOAST classification, biological age was associated with mortality only in large-artery atherosclerosis etiology (p = 0.004; OR = 1.14, 95% CI 1.04–1.25). As estimated by DNA methylation, biological age is an independent predictor of 3-month mortality in ischemic stroke regardless of chronological age, NIHSS, previous modified Rankin scale, and vascular risk factors.

Objective: To analyze the effect of age-related DNA methylation changes in multiple cytosine-phosphate-guanine (CpG) sites (biological age [b-age]) on patient outcomes at 3 months after an ischemic stroke. Methods: We included 511 patients with first-ever acute ischemic stroke assessed at Hospital del Mar (Barcelona, Spain) as the discovery cohort. Demographic and clinical data, including chronological age (c-age), vascular risk factors, initial stroke severity, recanalization treatment, and previous and 3-month modified Rankin Scale (p-mRS and 3-mRS, respectively) were registered. B-age was estimated with an algorithm, based on DNA methylation in 71 CpGs. Bivariate analysis determined variables associated with 3-mRS for inclusion in ordinal multivariate analysis. Results: After ordinal regressions for 3-month ischemic stroke outcome (3-mRS), b-age was associated with outcome (odds ratio 1.04 [95% confidence interval 1.01–1.07]), nullifying c-age. Stepwise regression kept b-age, basal NIH Stroke Scale, sex, p-mRS, and recanalization treatment as better explanatory variables, instead of c-age. These results were successfully replicated in an independent cohort. Conclusions: B-age, estimated by DNA methylation, is an independent predictor of ischemic stroke outcome regardless of chronological years.

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.

Background and Objectives To examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern–specific ways. Methods MR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3–6 months after stroke were obtained from the MRI–Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning–based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age², sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts. Results A total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location–specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location. Discussion Higher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions.