Cognitive decline in aging is a multifaceted process influenced by genetic, environmental, and epigenetic factors. Unlike genetic mutations, epigenetic modifications regulate gene activity dynamically and reversibly, making them attractive targets for therapeutic intervention [1]. This letter uniquely integrates evidence across the spectrum of epigenetic modifications and their implications for cognitive aging. Additionally, we provide useful insights into how artificial intelligence is transforming this field by enabling more precise and personalized approaches. Our analysis indicates that combination approaches targeting multiple epigenetic pathways simultaneously may yield superior outcomes compared to single-target interventions.
Epigenetic changes, such as DNA methylation, histone modifications, and non-coding RNAs, regulate gene activity without altering the DNA sequence. DNA methylation is a crucial epigenetic modification that regulates gene expression by adding methyl groups to cytosine residues, often leading to gene silencing. Studies have demonstrated that hypermethylation of genes involved in synaptic plasticity and memory, such as brain-derived neurotrophic factor (BDNF) and reelin, correlates with cognitive impairment in aging individuals [2]. Furthermore, Histones undergo various modifications, including acetylation (addition of acetyl groups that loosens DNA packaging, enabling gene expression), methylation, and phosphorylation, which influence chromatin structure and gene accessibility. Age-associated reductions in histone acetylation, mediated by increased histone deacetylase (HDAC) activity, are linked to cognitive decline [3]. HDAC inhibitors (HDACi), such as vorinostat and sodium butyrate, have shown promise in preclinical studies for enhancing memory function by restoring histone acetylation levels [4]. Recent studies have introduced selective HDAC2 inhibitors, like JRM-28, that show promise in improving memory and synaptic plasticity while reducing side effects, paving the way for new treatments for neurodegenerative diseases [5]. Moreover, Non-coding RNAs, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), regulate post-transcriptional gene expression. Specific miRNAs are involved in modulating neuroinflammation and synaptic plasticity, indicating their potential as therapeutic targets for cognitive aging. For instance, miR-132 and miR-124 have emerged as critical regulators of synaptic function, with age-related decreases correlating with cognitive deficits in human studies [6, 7].
Lifestyle interventions, including regular exercise and polyphenol-rich diets, regulate epigenetic mechanisms, improving neural resilience. For instance, moderate-intensity exercise increases BDNF via histone acetylation [8]. A meta-analysis consistently showed cognitive enhancement [9]. Polyphenol-rich diets, such as those including green tea and curcumin, modulate DNA methylation patterns, enhance neural resilience, and support synaptic plasticity while reducing neuroinflammation [10]. Table 1 summarizes interventions below. The mechanisms of synaptic plasticity, neuroinflammation, and neuronal survival rate are present in Table 2.

Recent advancements in AI-driven approaches are revolutionizing epigenetic research in cognitive aging. Deep learning models, such as in Deep-PGD, identify methylation patterns in the prefrontal cortex predictive of HDAC inhibitor responsiveness [16]. Neural networks integrate multi-omics data (epigenomics, transcriptomics, and proteomics) for personalized cognitive therapies. Machine learning models in distinguishing aging-related epigenetic shifts from Alzheimer's alterations [17]. These innovations promise earlier intervention and enhanced therapeutic precision.
Epigenetic mechanisms play a crucial role in cognitive aging, offering novel targets for therapeutic intervention. Unlike previous reviews that examined isolated mechanisms, our analysis integrates findings across multiple epigenetic pathways and highlights their collective impact on cognitive function. While lifestyle modifications and pharmacological approaches show promise, further research is needed to improve specificity and clinical applicability. AI-driven epigenetics is emerging as a powerful tool for optimizing personalized treatments, potentially revolutionizing cognitive health interventions in aging populations. Our synthesis suggests that combination approaches targeting multiple epigenetic pathways simultaneously, guided by AI-based precision medicine, represent the most promising future direction in this field.