Hippocampal and cortical tissue-specific epigenetic clocks indicate an increased epigenetic age in a mouse model for Alzheimer's disease

Advancing personalized medicine in neurodegenerative diseases: The role of epigenetics and pharmacoepigenomics in pharmacotherapy

About 80 % of brain disorders have a genetic basis. The pathogenesis of most neurodegenerative diseases is associated with a myriad of genetic defects, epigenetic alterations (DNA methylation, histone/chromatin remodeling, miRNA dysregulation), and environmental factors. The emergence of new sequencing technologies and tools to study the epigenome has led to identifying predictive biomarkers for earlier diagnosis, opening up the possibility of prophylactical interventions. As a result, advances in pharmacogenetics and pharmacoepigenomics now allow for personalized treatments based on the profile of each patient and the specific genetic and epigenetic mechanisms involved. This Review highlights the complexity of neurodegenerative diseases and the variability in patient responses to pharmacotherapy, emphasizing the influence of genetic polymorphisms on the pharmacokinetics and pharmacodynamics of drugs used to treat those conditions. We specifically discuss the potential modulatory effect of several genetic polymorphisms associated with an increased risk of developing different neurodegenerative diseases. We explore genetic and genomic technologies and the potential of analyzing individual-specific drug metabolism to predict and influence drug response and associated clinical outcomes. We also provide insights into the mechanism of action of the drugs under investigation and their potential impact on disease-modifying pathways. Finally, the Review underscores the great potential of this field to enhance the effectiveness and safety of drug treatments through personalized medicine.

Epigenetics in Alzheimer's Disease: A Critical Overview

Epigenetic modifications have been implicated in a number of complex diseases as well as being a hallmark of organismal aging. Several reports have indicated an involvement of these changes in Alzheimer's disease (AD) risk and progression, most likely contributing to the dysregulation of AD-related gene expression measured by DNA methylation studies. Given that DNA methylation is tissue-specific and that AD is a brain disorder, the limitation of these studies is the ability to identify clinically useful biomarkers in a proxy tissue, reflective of the tissue of interest, that would be less invasive, more cost-effective, and easily obtainable. The age-related DNA methylation changes have also been used to develop different generations of epigenetic clocks devoted to measuring the aging in different tissues that sometimes suggests an age acceleration in AD patients. This review critically discusses epigenetic changes and aging measures as potential biomarkers for AD detection, prognosis, and progression. Given that epigenetic alterations are chemically reversible, treatments aiming at reversing these modifications will be also discussed as promising therapeutic strategies for AD.

In vivo cyclic overexpression of Yamanaka factors restricted to neurons reverses age-associated phenotypes and enhances memory performance

In recent years, there has been success in partially reprogramming peripheral organ cells using cyclic Yamanaka transcription factor (YF) expression, resulting in the reversal of age-related pathologies. In the case of the brain, the effects of partial reprogramming are scarcely known, and only some of its effects have been observed through the widespread expression of YF. This study is the first to exclusively partially reprogram a specific subpopulation of neurons in the cerebral cortex of aged mice. The in vivo model demonstrate that YF expression in postmitotic neurons does not dedifferentiate them, and it avoids deleterious effects observed with YF expression in other cell types. Additionally, our study demonstrates that only cyclic, not continuous, expression of YF result in a noteworthy enhancement of cognitive function in adult mice. This enhancement is closely tied to increased neuronal activation in regions related to memory processes, reversed aging-related epigenetic markers and to increased plasticity, induced by the reorganization of the extracellular matrix. These findings support the therapeutic potential of targeted partial reprogramming of neurons in addressing age-associated phenotypes and neurodegenerative diseases correlated with aging.

Increased hippocampal epigenetic age in the Ts65Dn mouse model of Down Syndrome

Down syndrome (DS) is a segmental progeroid genetic disorder associated with multi-systemic precocious aging phenotypes, which are particularly evident in the immune and nervous systems. Accordingly, people with DS show an increased biological age as measured by epigenetic clocks. The Ts65Dn trisomic mouse, which harbors extra-numerary copies of chromosome 21 (Hsa21)-syntenic regions, was shown to recapitulate several progeroid features of DS, but no biomarkers of age have been applied to it so far. In this pilot study, we used a mouse-specific epigenetic clock to measure the epigenetic age of hippocampi from Ts65Dn and euploid mice at 20 weeks. Ts65Dn mice showed an increased epigenetic age in comparison with controls, and the observed changes in DNA methylation partially recapitulated those observed in hippocampi from people with DS. Collectively, our results support the use of the Ts65Dn model to decipher the molecular mechanisms underlying the progeroid DS phenotypes.

DNA methylation clocks for clawed frogs reveal evolutionary conservation of epigenetic aging

To address how conserved DNA methylation-based epigenetic aging is in diverse branches of the tree of life, we generated DNA methylation data from African clawed frogs (Xenopus laevis) and Western clawed frogs (Xenopus tropicalis) and built multiple epigenetic clocks. Dual species clocks were developed that apply to both humans and frogs (human-clawed frog clocks), supporting that epigenetic aging processes are evolutionary conserved outside mammals. Highly conserved positively age-related CpGs are located in neural-developmental genes such as uncx, tfap2d as well as nr4a2 implicated in age-associated disease. We conclude that signatures of epigenetic aging are evolutionary conserved between frogs and mammals and that the associated genes relate to neural processes, altogether opening opportunities to employ Xenopus as a model organism to study aging.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

Clinical relevance of animal models in aging-related dementia research

Alzheimer's disease (AD) and other, less prevalent dementias are complex age-related disorders that exhibit multiple etiologies. Over the past decades, animal models have provided pathomechanistic insight and evaluated countless therapeutics; however, their value is increasingly being questioned due to the long history of drug failures. In this Perspective, we dispute this criticism. First, the utility of the models is limited by their design, as neither the etiology of AD nor whether interventions should occur at a cellular or network level is fully understood. Second, we highlight unmet challenges shared between animals and humans, including impeded drug transport across the blood-brain barrier, limiting effective treatment development. Third, alternative human-derived models also suffer from the limitations mentioned above and can only act as complementary resources. Finally, age being the strongest AD risk factor should be better incorporated into the experimental design, with computational modeling expected to enhance the value of animal models.

Nanocomplexes of doxorubicin and DNA fragments for efficient and safe cancer chemotherapy

Cancer-targeted therapy by a chemotherapeutic agent formulated in a nanoscale platform has been challenged by complex and inefficient manufacturing, low drug loading, difficult characterization, and marginally improved therapeutic efficacy. This study investigated facile-to-produce nanocomplexes of doxorubicin (DOX), a widely used cancer drug, and clinically approved DNA fragments that are extracted from a natural source. DOX was found to self-assemble DNA fragments into relatively monodispersed nanocomplexes with a diameter of ∼70 nm at 14.3% (w/w) drug loading by simple and scalable mixing. The resulting DOX/DNA nanocomplexes showed sustained DOX release, unlike overly stable Doxil®, cellular uptake via multiple endocytosis pathways, and high hematological and immunological compatibility. DOX/DNA nanocomplexes eradicated EL4 T lymphoma cells in a time-dependent manner, eventually surpassing free DOX. Extended circulation of DOX/DNA nanocomplexes, while avoiding off-target accumulation in the lung and being cleared from the liver, resulted in rapid accumulation in tumor and lowered cardio toxicity. Finally, tumor growth of EL4-challenged C57BL/6 mice (syngeneic model) and OPM2-challenged NSG mice (human xenograft model) were efficiently inhibited by DOX/DNA nanocomplexes with enhanced overall survival, in comparison with free DOX and Doxil®, especially upon repeated administrations. DOX/DNA nanocomplexes are a promising chemotherapeutics delivery platform for their ease of manufacturing, high biocompatibility, desired drug release and accumulation, efficient tumor eradication with improved safety, and further engineering versatility for extended therapeutic applications.

Assessing brain and biological aging trajectories associated with Alzheimer’s disease

The development of effective treatments to prevent and slow Alzheimer’s disease (AD) pathogenesis is needed in order to tackle the steady increase in the global prevalence of AD. This challenge is complicated by the need to identify key health shifts that precede the onset of AD and cognitive decline as these represent windows of opportunity for intervening and preventing disease. Such shifts may be captured through the measurement of biomarkers that reflect the health of the individual, in particular those that reflect brain age and biological age. Brain age biomarkers provide a composite view of the health of the brain based on neuroanatomical analyses, while biological age biomarkers, which encompass the epigenetic clock, provide a measurement of the overall health state of an individual based on DNA methylation analysis. Acceleration of brain and biological ages is associated with changes in cognitive function, as well as neuropathological markers of AD. In this mini-review, we discuss brain age and biological age research in the context of cognitive decline and AD. While more research is needed, studies show that brain and biological aging trajectories are variable across individuals and that such trajectories are non-linear at older ages. Longitudinal monitoring of these biomarkers may be valuable for enabling earlier identification of divergent pathological trajectories toward AD and providing insight into points for intervention.

Gene-environment interactions in Alzheimer disease: the emerging role of epigenetics

With the exception of a few monogenic forms, Alzheimer disease (AD) has a complex aetiology that is likely to involve multiple susceptibility genes and environmental factors. The role of environmental factors is difficult to determine and, until a few years ago, the molecular mechanisms underlying gene-environment (G × E) interactions in AD were largely unknown. Here, we review evidence that has emerged over the past two decades to explain how environmental factors, such as diet, lifestyle, alcohol, smoking and pollutants, might interact with the human genome. In particular, we discuss how various environmental AD risk factors can induce epigenetic modifications of key AD-related genes and pathways and consider how epigenetic mechanisms could contribute to the effects of oxidative stress on AD onset. Studies on early-life exposures are helping to uncover critical time windows of sensitivity to epigenetic influences from environmental factors, thereby laying the foundations for future primary preventative approaches. We conclude that epigenetic modifications need to be considered when assessing G × E interactions in AD.

Premature aging is associated with higher levels of 8-oxoguanine and increased DNA damage in the Polg mutator mouse

Mitochondrial dysfunction plays an important role in the aging process. However, the mechanism by which this dysfunction causes aging is not fully understood. The accumulation of mutations in the mitochondrial genome (or "mtDNA") has been proposed as a contributor. One compelling piece of evidence in support of this hypothesis comes from the Polg^D257A/D257A mutator mouse (Polg^mut/mut ). These mice express an error-prone mitochondrial DNA polymerase that results in the accumulation of mtDNA mutations, accelerated aging, and premature death. In this paper, we have used the Polg^mut/mut model to investigate whether the age-related biological effects observed in these mice are triggered by oxidative damage to the DNA that compromises the integrity of the genome. Our results show that mutator mouse has significantly higher levels of 8-oxoguanine (8-oxoGua) that are correlated with increased nuclear DNA (nDNA) strand breakage and oxidative nDNA damage, shorter average telomere length, and reduced mtDNA integrity. Based on these results, we propose a model whereby the increased level of reactive oxygen species (ROS) associated with the accumulation of mtDNA mutations in Polg^mut/mut mice results in higher levels of 8-oxoGua, which in turn lead to compromised DNA integrity and accelerated aging via increased DNA fragmentation and telomere shortening. These results suggest that mitochondrial play a central role in aging and may guide future research to develop potential therapeutics for mitigating aging process.

Aging the brain: multi-region methylation principal component based clock in the context of Alzheimer's disease

Alzheimer's disease (AD) risk increases exponentially with age and is associated with multiple molecular hallmarks of aging, one of which is epigenetic alterations. Epigenetic age predictors based on 5' cytosine methylation (DNAm), or epigenetic clocks, have previously suggested that epigenetic age acceleration may occur in AD brain tissue. Epigenetic clocks are promising tools for the quantification of biological aging, yet we hypothesize that investigation of brain aging in AD will be assisted by the development of brain-specific epigenetic clocks. Therefore, we generated a novel age predictor termed PCBrainAge that was trained solely in cortical samples. This predictor utilizes a combination of principal components analysis and regularized regression, which reduces technical noise and greatly improves test-retest reliability. To characterize the scope of PCBrainAge's utility, we generated DNAm data from multiple brain regions in a sample from the Religious Orders Study and Rush Memory and Aging Project. PCBrainAge captures meaningful heterogeneity of aging: Its acceleration demonstrates stronger associations with clinical AD dementia, pathologic AD, and APOE ε4 carrier status compared to extant epigenetic age predictors. It further does so across multiple cortical and subcortical regions. Overall, PCBrainAge's increased reliability and specificity makes it a particularly promising tool for investigating heterogeneity in brain aging, as well as epigenetic alterations underlying AD risk and resilience.

HIV Tat and cocaine interactively alter genome-wide DNA methylation and gene expression and exacerbate learning and memory impairments

Cocaine use is a major comorbidity of HIV-associated neurocognitive disorder (HAND). In this study, we show that cocaine exposure worsens the learning and memory of doxycycline-inducible and brain-specific HIV Tat transgenic mice (iTat) and results in 14,838 hypermethylated CpG-related differentially methylated regions (DMRs) and 15,800 hypomethylated CpG-related DMRs, which are linked to 52 down- and 127 upregulated genes, respectively, in the hippocampus of iTat mice. These genes are mostly enriched at the neuronal function-, cell morphology-, and synapse formation-related extracellular matrix (ECM) receptor-ligand interaction pathway and mostly impacted in microglia. The accompanying neuropathological changes include swollen dendritic spines, increased synaptophysin expression, and diminished glial activation. We also find that sex (female) and age additively worsen the behavioral and pathological changes. These findings together indicate that chronic cocaine and long-term Tat expression interactively contribute to HAND, likely involving changes of DNA methylation and ECM receptor-ligand interactions.

Characterization of cerebrospinal fluid DNA methylation age during the acute recovery period following aneurysmal subarachnoid hemorrhage

Background

Biological aging may occur at different rates than chronological aging due to genetic, social, and environmental factors. DNA methylation (DNAm) age is thought to be a reliable measure of accelerated biological aging which has been linked to an array of poor health outcomes. Given the importance of chronological age in recovery following aneurysmal subarachnoid hemorrhage (aSAH), a type of stroke, DNAm age may also be an important biomarker of outcomes, further improving predictive models. Cerebrospinal fluid (CSF) is a unique tissue representing the local central nervous system environment post-aSAH. However, the validity of CSF DNAm age is unknown, and it is unclear which epigenetic clock is ideal to compute CSF DNAm age, particularly given changes in cell type heterogeneity (CTH) during the acute recovery period. Further, the stability of DNAm age post-aSAH, specifically, has not been examined and may improve our understanding of patient recovery post-aSAH. Therefore, the purpose of this study was to characterize CSF DNAm age over 14 days post-aSAH using four epigenetic clocks.

Results

Genome-wide DNAm data were available for two tissues: (1) CSF for N = 273 participants with serial sampling over 14 days post-aSAH (N = 850 samples) and (2) blood for a subset of n = 72 participants at one time point post-aSAH. DNAm age was calculated using the Horvath, Hannum, Levine, and “Improved Precision” (Zhang) epigenetic clocks. “Age acceleration” was computed as the residuals of DNAm age regressed on chronological age both with and without correcting for CTH. Using scatterplots, Pearson correlations, and group-based trajectory analysis, we examined the relationships between CSF DNAm age and chronological age, the concordance between DNAm ages calculated from CSF versus blood, and the stability (i.e., trajectories) of CSF DNAm age acceleration over time during recovery from aSAH. We observed moderate to strong correlations between CSF DNAm age and chronological age (R = 0.66 [Levine] to R = 0.97 [Zhang]), moderate to strong correlations between DNAm age in CSF versus blood (R = 0.69 [Levine] to R = 0.98 [Zhang]), and stable CSF age acceleration trajectories over 14 days post-aSAH in the Horvath and Zhang clocks (unadjusted for CTH), as well as the Hannum clock (adjusted for CTH).

Conclusions

CSF DNAm age was generally stable post-aSAH. Although correlated, CSF DNAm age differs from blood DNAm age in the Horvath, Hannum, and Levine clocks, but not in the Zhang clock. Taken together, our results suggest that, of the clocks examined here, the Zhang clock is the most robust to CTH and is recommended for use in complex tissues such as CSF.

Impact of large granular lymphocyte leukemia on blood DNA methylation and epigenetic clock modeling in Fischer 344 rats

Age-dependent differences in methylation at specific cytosine-guanosine sites (CpGs) have been used in "epigenetic clock" formulas to predict age. Deviations of epigenetic age from chronological age are informative of health status and are associated with adverse health outcomes, including mortality. In most cases, epigenetic clocks are performed on methylation from DNA extracted from circulating blood cells. However, the effect of neoplastic cells in the circulation on estimation and interpretation of epigenetic clocks is not well understood. Here, we explored this using Fischer 344 (F344) rats, a strain that often develops large granular lymphocyte leukemia (LGL). We found clear histological markers of LGL pathology in the spleens and livers of 27 out of 61 rats aged 17-27 months. We assessed DNA methylation by reduced representation bisulfite sequencing with coverage of 3 million cytosine residues. Although LGL broadly increased DNA methylation variability, it did not change epigenetic aging. Despite this, inclusion of rats with LGL in clock training sets significantly altered predictor selection probability at 83 of 121 commonly utilized CpGs. Furthermore, models trained on rat samples that included individuals with LGL had greater absolute age error than those trained exclusively on LGL-free rats (39% increase; p<0.0001). We conclude that the epigenetic signals for aging and LGL are distinct, such that LGL assessment is not necessary for valid measures of epigenetic age in F344 rats. The precision and architecture of constructed epigenetic clock formulas, however, can be influenced by the presence of neoplastic hematopoietic cells in training set populations.

Aging biomarkers and the brain

Quantifying biological aging is critical for understanding why aging is the primary driver of morbidity and mortality and for assessing novel therapies to counter pathological aging. In the past decade, many biomarkers relevant to brain aging have been developed using various data types and modeling techniques. Aging involves numerous interconnected processes, and thus many complementary biomarkers are needed, each capturing a different slice of aging biology. Here we present a hierarchical framework highlighting how these biomarkers are related to each other and the underlying biological processes. We review those measures most studied in the context of brain aging: epigenetic clocks, proteomic clocks, and neuroimaging age predictors. Many studies have linked these biomarkers to cognition, mental health, brain structure, and pathology during aging. We also delve into the challenges and complexities in interpreting these biomarkers and suggest areas for further innovation. Ultimately, a robust mechanistic understanding of these biomarkers will be needed to effectively intervene in the aging process to prevent and treat age-related disease.