The effects of epigenetic age and its acceleration on surface area, cortical thickness, and volume in young adults

A blood biomarker of the pace of aging is associated with brain structure: replication across three cohorts

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3380; total N individuals=2322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, greater burden of white matter microlesions, and thinner cortex. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Cellular senescence in brain aging and cognitive decline

Cellular senescence is a biological aging hallmark that plays a key role in the development of neurodegenerative diseases. Clinical trials are currently underway to evaluate the effectiveness of senotherapies for these diseases. However, the impact of senescence on brain aging and cognitive decline in the absence of neurodegeneration remains uncertain. Moreover, patient populations like cancer survivors, traumatic brain injury survivors, obese individuals, obstructive sleep apnea patients, and chronic kidney disease patients can suffer age-related brain changes like cognitive decline prematurely, suggesting that they may suffer accelerated senescence in the brain. Understanding the role of senescence in neurocognitive deficits linked to these conditions is crucial, especially considering the rapidly evolving field of senotherapeutics. Such treatments could help alleviate early brain aging in these patients, significantly reducing patient morbidity and healthcare costs. This review provides a translational perspective on how cellular senescence plays a role in brain aging and age-related cognitive decline. We also discuss important caveats surrounding mainstream senotherapies like senolytics and senomorphics, and present emerging evidence of hyperbaric oxygen therapy and immune-directed therapies as viable modalities for reducing senescent cell burden.

A blood biomarker of accelerated aging in the body associates with worse structural integrity in the brain: replication across three cohorts

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3,380; total N individuals=2,322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, and thinner cortex. In two datasets, faster DunedinPACE was associated with greater burden of white matter hyperintensities. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Evaluation of the pooled sample method in Infinium MethylationEPIC BeadChip array by comparison with individual samples

BACKGROUND

The pooled sample method is used in epigenomic research and expression analysis and is a cost-effective screening approach for small amounts of DNA. Evaluation of the pooled sample method in epigenomic studies is performed using the Illumina Infinium Methylation 450K BeadChip array; however, subsequent reports on the updated 850K array are lacking. A previous study demonstrated that the methylation levels obtained from individual samples were accurately replicated using pooled samples but did not address epigenome-wide association study (EWAS) statistics. The DNA quantification method, which is important for the homogeneous mixing of DNA in the pooled sample method, has since become fluorescence-based, and additional factors need to be considered including the resolution of batch effects of microarray chips and the heterogeneity of the cellular proportions from which the DNA samples are derived. In this study, four pooled samples were created from 44 individual samples, and EWAS statistics for differentially methylated positions (DMPs) and regions (DMRs) were conducted for individual samples and compared with the statistics obtained from the pooled samples.

RESULTS

The methylation levels could be reproduced fairly well in the pooled samples. This was the case for the entire dataset and when limited to the top 100 CpG sites, consistent with a previous study using the 450K BeadChip array. However, the statistical results of the EWAS for the DMP by individual samples were not replicated in pooled samples. Qualitative analyses highlighting methylation within an arbitrary candidate gene were replicable. Focusing on chr 20, the statistical results of EWAS for DMR from individual samples showed replicability in the pooled samples as long as they were limited to regions with a sufficient effect size.

CONCLUSIONS

The pooled sample method replicated the methylation values well and can be used for EWAS in DMR. This method is sample amount-effective and cost-effective and can be utilized for screening by carefully understanding the effective features and disadvantages of the pooled sample method and combining it with candidate gene analyses.

Decoding the role of transcriptomic clocks in the human prefrontal cortex

Aging is a complex process with interindividual variability, which can be measured by aging biological clocks. Aging clocks are machine-learning algorithms guided by biological information and associated with mortality risk and a wide range of health outcomes. One of these aging clocks are transcriptomic clocks, which uses gene expression data to predict biological age; however, their functional role is unknown. Here, we profiled two transcriptomic clocks (RNAAgeCalc and knowledge-based deep neural network clock) in a large dataset of human postmortem prefrontal cortex (PFC) samples. We identified that deep-learning transcriptomic clock outperforms RNAAgeCalc to predict transcriptomic age in the human PFC. We identified associations of transcriptomic clocks with psychiatric-related traits. Further, we applied system biology algorithms to identify common gene networks among both clocks and performed pathways enrichment analyses to assess its functionality and prioritize genes involved in the aging processes. Identified gene networks showed enrichment for diseases of signal transduction by growth factor receptors and second messenger pathways. We also observed enrichment of genome-wide signals of mental and physical health outcomes and identified genes previously associated with human brain aging. Our findings suggest a link between transcriptomic aging and health disorders, including psychiatric traits. Further, it reveals functional genes within the human PFC that may play an important role in aging and health risk.

Epigenetic clock analysis of blood samples in drug-naive first-episode schizophrenia patients

BACKGROUND

Schizophrenia (SCZ) is a severe and chronic psychiatric disorder with premature age-related physiological changes. However, numerous previous studies examined the epigenetic age acceleration in SCZ patients and yielded inconclusive results. In this study, we propose to explore the epigenetic age acceleration in drug-naive first-episode SCZ (FSCZ) patients and investigate whether epigenetic age acceleration is associated with antipsychotic treatment, psychotic symptoms, cognition, and subcortical volumes.

METHODS

We assessed the epigenetic age in 38 drug-naive FSCZ patients and 38 healthy controls by using three independent clocks, including Horvath, Hannum and Levine algorithms. The epigenetic age measurements in SCZ patients were repeated after receiving 8 weeks risperidone monotherapy.

RESULTS

Our findings showed significantly positive correlations between epigenetic ages assessed by three clocks and chronological age in both FSCZ patients and healthy controls. Compared with healthy controls, drug-naive FSCZ patients have a significant epigenetic age deceleration in Horvath clock (p = 0.01), but not in Hannum clock (p = 0.07) and Levine clock (p = 0.43). The epigenetic ages of Hannum clock (p = 0.002) and Levine clock (p = 0.01) were significantly accelerated in SCZ patients after 8-week risperidone treatment. However, no significant associations between epigenetic age acceleration and psychotic symptoms, cognitive function, as well as subcortical volumes were observed in FSCZ patients.

CONCLUSION

These results demonstrate that distinct epigenetic clocks are sensitive to different aspects of aging process. Further investigations with comprehensive epigenetic clock analyses and large samples are required to confirm our findings.

Epigenetic Regulation of Chondrocytes and Subchondral Bone in Osteoarthritis

The aim of this review is to provide an updated review of the epigenetic factors involved in the onset and development of osteoarthritis (OA). OA is a prevalent degenerative joint disease characterized by chronic inflammation, ectopic bone formation within the joint, and physical and proteolytic cartilage degradation which result in chronic pain and loss of mobility. At present, no disease-modifying therapeutics exist for the prevention or treatment of the disease. Research has identified several OA risk factors including mechanical stressors, physical activity, obesity, traumatic joint injury, genetic predisposition, and age. Recently, there has been increased interest in identifying epigenetic factors involved in the pathogenesis of OA. In this review, we detail several of these epigenetic modifications with known functions in the onset and progression of the disease. We also review current therapeutics targeting aberrant epigenetic regulation as potential options for preventive or therapeutic treatment.