Epigenetics and stroke risk – beyond the static DNA code
Bibliographic record
Abstract
Charles C Matouk,1 Paul J Turgeon,2 Philip A Marsden2,31Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA; 2Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; 3Keenan Research Centre and Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, CanadaAbstract: Advances in high-throughput genome sequencing and genome-wide association studies indicate that only a fraction of estimated variability in stroke risk can be explained by genetic variation in protein-coding genes alone. Epigenetics is defined as chromatin-based mechanisms important in the regulation of gene expression that do not involve changes in the DNA sequence per se. Epigenetics represents an alternative explanation for how traditional risk factors confer increased stroke risk, provide a newer paradigm to explain heritability not explained by genetic variation, and provide insight into the link between how the environment of a cell can interact with the static DNA code. The nuclear-based mechanisms that contribute to epigenetic gene regulation can be separated into three distinct but highly interrelated processes: DNA methylation and hydroxymethylation; histone density and posttranslational modifications; and RNA-based mechanisms. Together, they offer a newer perspective on transcriptional control paradigms in blood vessels and provide a molecular basis for understanding how the environment impacts the genome to modify stroke susceptibility. This alternative view for transcriptional regulation allows a reassessment of the cis/trans model and even helps explain some of the limitations of current approaches to genetic-based screens. For instance, how does the environment exert chronic effects on gene expression in blood vessels after weeks or years? When a vascular cell divides, how is this information transmitted to daughter cells? This review provides an introduction to epigenetic concepts and a conceptual framework for understanding the shortcomings of an approach to stroke research that focuses solely on the static DNA code. Additionally, it will discuss classical and emerging mechanisms of epigenetic gene regulation that are especially relevant to large-vessel ischemic stroke.Keywords: DNA methylation, endothelial nitric oxide synthase, histone posttranslational modifications, long noncoding RNA, ANRIL, heritability
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".