The influence of epigenetic biological age on key complications and outcomes in aneurysmal subarachnoid haemorrhage.

BACKGROUND: We aimed to investigate the association between DNA-methylation biological age (B-age) calculated as age acceleration (ageAcc) and key aneurysmal subarachnoid haemorrhage (aSAH) complications such as vasospasm, delayed cerebral ischaemia (DCI), poor outcome, and mortality. METHODS: We conducted a prospective study involving 277 patients with aSAH. B-age was determined in whole blood samples using five epigenetic clocks: Hannum's, Horvath's, Levine's and both versions of Zhang's clocks. Age acceleration was calculated as the residual obtained from regressing out the effect of C-age on the mismatch between C-age and B-age. We then tested the association between ageAcc and vasospasm, DCI and 12-month poor outcome (mRS 3-5) and mortality using linear regression models adjusted for confounders. RESULTS: Average C-age was 55.0 years, with 66.8% being female. Vasospasm occurred in 143 cases (51.6%), DCI in 70 (25.3%) and poor outcomes in 99 (35.7%), with a mortality rate of 20.6%. Lower ageAcc was linked to vasospasm in Horvath's and Levine's clocks, whereas increased ageAcc was associated with 12-month mortality in Hannum's clock. No significant differences in ageAcc were found for DCI or poor outcome at 12 months with other clocks. CONCLUSIONS: Our study indicates that B-age is independently associated with vasospasm and 12-month mortality in patients with aSAH. These findings underscore the potential role of epigenetics in understanding the pathophysiology of aSAH-related complications and outcomes.

The Role of Epigenetics in Brain Aneurysm and Subarachnoid Hemorrhage: A Comprehensive Review.

This comprehensive review explores the emerging field of epigenetics in intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (aSAH). Despite recent advancements, the high mortality of aSAH needs an understanding of its underlying pathophysiology, where epigenetics plays a crucial role. This review synthesizes the current knowledge, focusing on three primary epigenetic mechanisms: DNA methylation, non-coding RNA (ncRNA), and histone modification in IA and aSAH. While DNA methylation studies are relatively limited, they suggest a significant role in the pathogenesis and prognosis of IA and aSAH, highlighting differentially methylated positions in genes presumably involved in these pathologies. However, methodological limitations, including small sample sizes and a lack of diverse population studies, temper these results. The role of ncRNAs, particularly miRNAs, has been more extensively studied, but there are still few studies focused on histone modifications. Despite methodological challenges and inconsistent findings, these studies underscore the involvement of miRNAs in key pathophysiological processes, including vascular smooth muscle regulation and the inflammatory response. This review emphasizes methodological challenges in epigenetic research, advocating for large-scale epigenome-wide association studies integrating genetic and environmental factors, along with longitudinal studies. Such research could unravel the complex mechanisms behind IA and aSAH, guiding the development of targeted therapeutic approaches.

Factors associated with migraine aura mimicking stroke in code stroke.

INTRODUCTION: Migraine with aura (MA) is a frequent stroke simulator that can lead to erroneous diagnosis and subsequent unnecessary acute or secondary prevention treatments. We analyzed clinical and laboratory data of migraine with aura and ischemic stroke patients to detect differences that could help in the diagnosis. METHODS: Retrospective analysis of a consecutive register of code strokes between January 2005 and June 2020. Diagnosis of ischemic stroke or MA was collected. Multivariable logistic regression analyses were performed to test associations between clinical and blood data with ischemic stroke. RESULTS: Of 3140 code strokes, 2424 (77.2%) were ischemic strokes and 34 (1.1%) were MA. Migraine cases were younger, more frequently females and with lower prevalence of vascular risk factors. Initial NIHSS was lower in MA cases, but no differences were seen in fibrinolysis rate (30%). Blood test showed lower levels of glucose, D-dimer, and fibrinogen in MA cases. Multivariable model showed and independent association for ischemic stroke with age [OR, (95%CI): 1.09, (1.07-1.12, p < 0.001], male sex [OR, (95%CI): 4.47, (3.80-5.13), p < 0.001], initial NIHSS [OR, (95%CI): 1.21, (1.07-1.34), p < 0.01], and fibrinogen levels [OR, (95%CI): 1.01, (1.00-1.01), p < 0.05]. A model including sex male OR: 3.55 [2.882; 4.598], p < 0.001, and cutoff points (age > 65, OR: 7.953 [7.256; 8.649], p < 0.001, NIHSS > 6, OR: 3.740 [2.882; 4.598], p < 0.01, and fibrinogen > 400 mg/dL, OR: 2.988 [2.290; 3.686], p < 0.01) showed a good global discrimination capability AUC = 0.89 (95%CI: 0.88-0.94). CONCLUSIONS: In code stroke, a model including age, sex, NIHSS, and fibrinogen showed a good discrimination capability to differentiate between MA and Ischemic stroke. Whether these variables can be implemented in a diagnostic rule should be tested in future studies.

Machine Learning Approximations to Predict Epigenetic Age Acceleration in Stroke Patients.

Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk factors (VRF). The aim of this study is to estimate the contribution of these easily measurable factors to Age-A in patients with cerebrovascular disease (CVD), using different machine learning (ML) approximations, and try to find a more accessible model able to predict Age-A. We studied a CVD cohort of 952 patients with information about VRF, lifestyle habits, and target organ damage. We estimated Age-A using Hannum's epigenetic clock, and trained six different models to predict Age-A: a conventional linear regression model, four ML models (elastic net regression (EN), K-Nearest neighbors, random forest, and support vector machine models), and one deep learning approximation (multilayer perceptron (MLP) model). The best-performing models were EN and MLP; although, the predictive capability was modest (R2 0.358 and 0.378, respectively). In conclusion, our results support the influence of these factors on Age-A; although, they were not enough to explain most of its variability.

Blood DNA Methylation Analysis Reveals a Distinctive Epigenetic Signature of Vasospasm in Aneurysmal Subarachnoid Hemorrhage.

Vasospasm is a potentially preventable cause of poor prognosis in patients with aneurysmal subarachnoid hemorrhage (aSAH). Epigenetics might provide insight on its molecular mechanisms. We aimed to analyze the association between differential DNA methylation (DNAm) and development of vasospasm. We conducted an epigenome-wide association study in 282 patients with aSAH admitted to our hospital. DNAm was assessed with the EPIC Illumina chip (> 850 K CpG sites) in whole-blood samples collected at hospital admission. We identified differentially methylated positions (DMPs) at the CpG level using Cox regression models adjusted for potential confounders, and then we used the DMP results to find differentially methylated regions (DMRs) and enriched biological pathways. A total of 145 patients (51%) experienced vasospasm. In the DMP analysis, we identified 31 CpGs associated with vasospasm at p-value < 10-5. One of them (cg26189827) was significant at the genome-wide level (p-value < 10-8), being hypermethylated in patients with vasospasm and annotated to SUGCT gene, mainly expressed in arteries. Region analysis revealed 13 DMRs, some of them annotated to interesting genes such as POU5F1, HLA-DPA1, RUFY1, and CYP1A1. Functional enrichment analysis showed the involvement of biological processes related to immunity, inflammatory response, oxidative stress, endothelial nitric oxide, and apoptosis. Our findings show, for the first time, a distinctive epigenetic signature of vasospasm in aSAH, establishing novel links with essential biological pathways, including inflammation, immune responses, and oxidative stress. Although further validation is required, our results provide a foundation for future research into the complex pathophysiology of vasospasm.

DNA methylation and stroke prognosis: an epigenome-wide association study.

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-valuediscovery = 1.54·10-6; p-valuereplication = 9.17·10-4; p-valuemeta-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.

Epigenetic Clock Explains White Matter Hyperintensity Burden Irrespective of Chronological Age.

In this manuscript we studied the relationship between WMH and biological age (B-age) in patients with acute stroke. We included in this study 247 patients with acute stroke recruited at Hospital del Mar having both epigenetic (DNA methylation) and magnetic resonance imaging data. WMH were measured using a semi-automated method. B-age was calculated using two widely used methods: the Hannum and Horvath formulas. We used multiple linear regression models to interrogate the role of B-age on WMH volume after adjusting for chronological age (C-age) and other covariables. Average C-age of the sample was 68.4 (±11.8) and we observed a relatively high median WMH volume (median = 8.8 cm3, Q1-Q3 = 4.05-18.8). After adjusting for potential confounders, we observed a significant effect of B-ageHannum on WMH volume (ßHannum = 0.023, p-value = 0.029) independently of C-age, which remained significant (ßC-age = 0.021, p-value = 0.036). Finally, we performed a mediation analysis, which allowed us to discover that 42.7% of the effect of C-age on WMH is mediated by B-ageHannum. On the other hand, B-ageHoarvath showed no significant associations with WMH after being adjusted for C-age. In conclusion, we show for the first time that biological age, measured through DNA methylation, contributes substantially to explain WMH volumetric burden irrespective of chronological age.

Long-term vascular events after subarachnoid hemorrhage.

BACKGROUND: Spontaneous subarachnoid hemorrhage (SAH) long-term risk is not well known. Our aims are: describing long-term vascular event (VE) incidence rates in SAH survivors; describing VE: ischemic and/or hemorrhagic; identifying independent association of factors related to VE; and analyzing the usefulness of factors to increase predictive ability. METHODS: A prospective cohort study of consecutive patients admitted to Hospital del Mar with a diagnosis of SAH (n = 566) between January 2007 and January 2020 was carried out. They were followed up until January 2021. The study endpoint was a new VE in the follow-up. We calculated both incidence rates and cumulative rates at 5 years. Cox regression survival models including vascular risk factors with and without specific data of SAH disease were developed. We analyzed ROC curves of all multivariate models. RESULTS: The analyzed cohort included 423 non-fatal SAH cases. Total patient-years were 2468.16 years. The average follow-up was 70.03 ± 43.14; range: 1-180 months. There were 49 VE detected in 47 patients, as 2 of them had more than 1 VE. Incidence rate was 0.020 events_per_patient/year, cumulative incidence at 5 years was 11.11%. The more frequent VE that we found were cerebrovascular (28/49), mainly ischemic (21/28). Disability after SAH and the presence of multiple aneurysms were independently associated with a VE risk and improved the predictive capacity of multivariate models (AUC 0.679 vs 0.764; p = 0.0062). CONCLUSIONS: We reported a low vascular risk after SAH. We have shown the usefulness of SAH factors to identify patients with a higher risk of VE.