Abstract Epigenetic “clocks” based on DNA methylation (DNAme) have emerged as the most robust and widely employed aging biomarkers, but conventional methods for applying them are expensive and laborious. Here, we develop T agmentation-based Indexing for M ethylation Seq uencing (TIME-Seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-Seq, we applied multi-tissue and tissue-specific epigenetic clocks to over 1,600 mouse DNA samples. We also discovered a novel approach for age prediction from shallow sequencing (e.g., 10,000 reads) by adapting scAge for bulk measurements. In benchmarking experiments, TIME-Seq performed favorably against prevailing methods and could quantify the effects of interventions thought to accelerate, slow, and reverse aging in mice. Finally, we built and validated a highly accurate human blood clock from 1,056 demographically representative individuals. Our methods increase the scalability and reduce the cost of epigenetic age predictions by more than 100-fold, enabling accurate aging biomarkers to be applied in more large-scale animal and human studies.
Here we show a method of directing the edges of the connectomes, prepared from diffusion tensor imaging (DTI) datasets from the human brain. Before the present work, no high-definition directed braingraphs (or connectomes) were published, because the tractography methods in use are not capable of assigning directions to the neural tracts discovered. Previous work on the functional connectomes applied low-resolution functional MRI-detected statistical causality for the assignment of directions of connectomes of typically several dozens of vertices. Our method is based on the phenomenon of the Consensus Connectome Dynamics (CCD), described earlier by our research group. In this contribution, we apply the method to the 423 braingraphs, each with 1015 vertices, computed from the public release of the Human Connectome Project, and we also made the directed connectomes publicly available at the site \url{this http URL}. We also show the robustness of our edge directing method in four independently chosen connectome datasets: we have found that 86\% of the edges, which were present in all four datasets, get the very same directions in all datasets; therefore the direction method is robust, it does not depend on the particular choice of the dataset. We think that our present contribution opens up new possibilities in the analysis of the high-definition human connectome: from now on we can work with a robust assignment of directions of the connections of the human brain.
Abstract Heterochronic parabiosis is a powerful rejuvenation model in aging research. Due to limitations in the duration of blood sharing and/or physical attachment, it is currently unclear if parabiosis retards the molecular signatures of aging or affects healthspan/lifespan in the mouse. Here, we describe a long-term heterochronic parabiosis model, which appears to slow down the aging process. We observed a “deceleration” of biological age based on molecular aging biomarkers estimated with DNA methylation clock and RNA-seq signature analysis. The slowing of biological aging was accompanied by systemic amelioration of aging phenotypes. Consistent with these findings, we found that aged mice, which underwent heterochronic parabiosis, had an increased healthspan and lifespan. Overall, our study re-introduces a prolonged parabiosis and detachment model as a novel rejuvenation therapy, suggesting that a systemic reset of biological age in old organisms can be achieved through the exposure to young environment.
Abstract Mobility of transposable elements (TEs) frequently leads to insertional mutations in functional DNA regions. In the potentially immortal germline, TEs are effectively suppressed by the Piwi-piRNA pathway. However, in the genomes of ageing somatic cells lacking the effects of the pathway, TEs become increasingly mobile during the adult lifespan, and their activity is associated with genomic instability. Whether the progressively increasing mobilization of TEs is a cause or a consequence of ageing remains a fundamental problem in biology. Here we show that in the nematode Caenorhabditis elegans , the downregulation of active TE families extends lifespan. Ectopic activation of Piwi proteins in the soma also promotes longevity. Furthermore, DNA N 6 -adenine methylation at TE stretches gradually rises with age, and this epigenetic modification elevates their transcription as the animal ages. These results indicate that TEs represent a novel genetic determinant of ageing, and that N 6 -adenine methylation plays a pivotal role in ageing control.
Here we show a method of directing the edges of the connectomes, prepared from diffusion tensor imaging (DTI) datasets from the human brain. Before the present work, no high-definition directed braingraphs (or connectomes) were published, because the tractography methods in use are not capable of assigning directions to the neural tracts discovered. Previous work on the functional connectomes applied low-resolution functional MRI-detected statistical causality for the assignment of directions of connectomes of typically several dozens of vertices. Our method is based on the phenomenon of the "Consensus Connectome Dynamics" (CCD), described earlier by our research group. In this contribution, we apply the method to the 423 braingraphs, each with 1015 vertices, computed from the public release of the Human Connectome Project, and we also made the directed connectomes publicly available at the site \url{http://braingraph.org}. We also show the robustness of our edge directing method in four independently chosen connectome datasets: we have found that 86\% of the edges, which were present in all four datasets, get the very same directions in all datasets; therefore the direction method is robust, it does not depend on the particular choice of the dataset. We think that our present contribution opens up new possibilities in the analysis of the high-definition human connectome: from now on we can work with a robust assignment of directions of the connections of the human brain.
Abstract Aging is classically conceptualized as an ever-increasing trajectory of damage accumulation and loss of function, leading to increases in morbidity and mortality. However, recent in vitro studies have raised the possibility of age reversal. Here, we report that biological age is fluid and exhibits rapid changes in both directions. By applying advanced epigenetic aging clocks, we find that the biological age of young mice is increased by heterochronic parabiosis and restored following surgical detachment of animals. We also identify transient changes in biological age during major surgery, pregnancy, and severe COVID-19 in humans and/or mice. Together, these data show that biological age undergoes a rapid increase in response to diverse forms of stress, which is reversed following recovery from stress. Our study uncovers a new layer of aging dynamics that should be considered in future studies. Elevation of biological age by stress may be a quantifiable and actionable target for future interventions.
Abstract Local recurrences (LR) can occur within residual breast tissue, chest wall, skin, or newly formed scar tissue. Artificial intelligence (AI) technologies can extract a wide range of tumor features from large datasets helping in oncological decision-making. Recently, machine learning (ML) models have been developed to predict breast cancer recurrence or distant metastasis (DM). However, there is still a lack of models that consider the localization of LR as a tumor feature. To address this gap, here, we analysed data from 154 patients including pathological, clinical, and follow-up data (with an average follow-up of 133.16 months) on both primary tumors (PT) and recurrences. By using ML methods we predicted the localization of LR and the occurrence of DM after LR. The performance (ROC AUC) of the best ML models was 0.75, and 0.69 for predicting LR in breast parenchyma, and surgical scar tissue, respectively, and 0.74 for predicting DM after LR. We identified recurrence localization, and the time elapsed between the detection of primary breast carcinoma and the recurrence, and adjuvant chemotherapy as the most important features associated with further DM. We conclude that combining traditional prognostic factors with ML may provide important tools in the risk assessment of patients with breast LR.
Abstract Adult aging is characterized by a progressive deterioration of biological functions at physiological, cellular and molecular levels, but its damaging effects on the transcriptome are not well characterized. Here, by analyzing splicing patterns in ∼1,000 human subjects sampled across multiple tissues, we found that splicing fidelity declines with age. Most prominently, genuine introns fail to be spliced out, manifesting as a broad surge in intron retention, and this is exacerbated by the increase in diverse spurious exon-exon junctions with age. Both of these effects are prominently detected in the majority of human tissues. Collectively, they result in the progressive deterioration of the active transcriptome, wherein functional mRNAs are increasingly diluted with non-functional splicing isoforms. We discuss the concept of “splicing damage” and formulate methods to quantify it. Using these tools, we show that splicing damage increases both with age and with the incidence of diseases. Altogether, this work uncovers transcriptome damage as a critical molecular indicator of human aging and healthspan.
