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Little is known about tissue specific changes that occur with aging in humans. Using the description of 33 million histological samples we extract thousands of age- and mortality-associated features from text narratives that we call The Human Pathome (pathoage.com). Notably, we can determine when pathological aging starts at the organism and tissue level, indicating a sexual dimorphism with females aging earlier but slower and males aging later but faster. We employ unsupervised topic-modelling to identify terms and themes that predict age and mortality. As a proof of principle, we cross reference these terms in PubMed to identify nintedanib as a potential aging intervention and show that nintedanib reduces markers of cellular senescence, reduces pro-fibrotic gene pathways in senescent cells and extends the lifespan of fruit flies. Our findings pave the way for expanded exploitation of population datasets towards discovery of novel aging interventions.

Post-translational modifications, such as lysine acetylation, regulate the activity of diverse proteins across many cellular compartments. Protein deacetylation in mitochondria is catalyzed by the enzymatic activity of the NAD+-dependent deacetylase sirtuin 3 (SIRT3), however it remains unclear whether corresponding mitochondrial acetyltransferases exist. We used a bioinformatics approach to search for mitochondrial proteins with an acetyltransferase catalytic domain, and identified a novel splice variant of ELP3 (mt-ELP3) of the elongator complex, which localizes to the mitochondrial matrix in mammalian cells. Unexpectedly, mt-ELP3 does not mediate mitochondrial protein acetylation but instead induces a post-transcriptional modification of mitochondrial-transfer RNAs (mt-tRNAs). Overexpression of mt-ELP3 leads to the protection of mt-tRNAs against the tRNA-specific RNase angiogenin, increases mitochondrial translation, and furthermore increases expression of OXPHOS complexes. This study thus identifies mt-ELP3 as a non-canonical mt-tRNA modifying enzyme.

Cellular senescence is an important factor in aging and many age-related diseases, but understanding its role in health is challenging due to the lack of exclusive or universal markers. Using neural networks, we predict senescence from the nuclear morphology of human fibroblasts with up to 95% accuracy, and investigate murine astrocytes, murine neurons, and fibroblasts with premature aging in culture. After generalizing our approach, the predictor recognizes higher rates of senescence in p21-positive and ethynyl-2’-deoxyuridine (EdU)-negative nuclei in tissues and shows an increasing rate of senescent cells with age in H&E-stained murine liver tissue and human dermal biopsies. Evaluating medical records reveals that higher rates of senescent cells correspond to decreased rates of malignant neoplasms and increased rates of osteoporosis, osteoarthritis, hypertension and cerebral infarction. In sum, we show that morphological alterations of the nucleus can serve as a deep learning predictor of senescence that is applicable across tissues and species and is associated with health outcomes in humans.

Cellular senescence is a critical component of aging and many age-related diseases, but understanding its role in human health is challenging in part due to the lack of exclusive or universal markers. Using neural networks, we achieve high accuracy in predicting senescence state and type from the nuclear morphology of DAPI-stained human fibroblasts, murine astrocytes, murine neurons, and fibroblasts derived from premature aging diseases in culture. After generalizing this approach, the predictor recognizes an increasing rate of senescent cells with age in H&E-stained murine liver tissue and human dermal biopsies, suggesting that alterations in nuclear morphology is a universal feature of senescence. Evaluating corresponding medical records reveals that individuals with a higher rate of senescent cells have a significantly decreased rate of malignant neoplasms, lending support for the protective role of senescence in limiting cancer development. Additionally, we find a positive association with lower significance for other conditions, including osteoporosis, osteoarthritis, hypertension, cerebral infarction, hyperlipidemia, and hypercholesteremia. In sum, we introduce a predictor of cellular senescence based on nuclear morphology that is applicable across tissues and species and is associated with health outcomes in humans.

A major stress response influenced by microRNAs (miRNAs) is senescence, a state of indefinite growth arrest triggered by sublethal cell damage. Here, through bioinformatic analysis and experimental validation, we identified miR-340-5p as a novel miRNA that foments cellular senescence. miR-340-5p was highly abundant in diverse senescence models, and miR-340-5p overexpression in proliferating cells rendered them senescent. Among the target mRNAs, miR-340-5p prominently reduced the levels of LBR mRNA, encoding lamin B receptor (LBR). Loss of LBR by ectopic overexpression of miR-340-5p derepressed heterochromatin in lamina-associated domains, promoting the expression of DNA repetitive elements characteristic of senescence. Importantly, overexpressing miR-340-5p enhanced cellular sensitivity to senolytic compounds, while antagonization of miR-340-5p reduced senescent cell markers and engendered resistance to senolytic-induced cell death. We propose that miR-340-5p can be exploited for removing senescent cells to restore tissue homeostasis and mitigate damage by senescent cells in pathologies of human aging.

Cellular senescence is a critical component of aging and many age-related diseases, but understanding its role in human health is challenging in part due to the lack of exclusive or universal markers. Using neural networks, we achieve high accuracy in predicting senescence state and type from the nuclear morphology of DAPI-stained human fibroblasts, murine astrocytes and fibroblasts derived from premature aging diseases in vitro. After generalizing this approach, the predictor recognizes an increasing rate of senescent cells with age in H&E-stained murine liver tissue and human dermal biopsies. Evaluating corresponding medical records reveals that individuals with increased senescent cells have a significantly decreased rate of malignant neoplasms, lending support for the protective role of senescence in limiting cancer development. In sum, we introduce a novel predictor of cellular senescence and apply it to diagnostic medical images, indicating cancer occurs more frequently for those with a lower rate of senescence.

Declining tissue nicotinamide adenine dinucleotide (NAD) levels are linked to ageing and its associated diseases. However, the mechanism for this decline is unclear. Here, we show that pro-inflammatory M1-like macrophages, but not naive or M2 macrophages, accumulate in metabolic tissues, including visceral white adipose tissue and liver, during ageing and acute responses to inflammation. These M1-like macrophages express high levels of the NAD-consuming enzyme CD38 and have enhanced CD38-dependent NADase activity, thereby reducing tissue NAD levels. We also find that senescent cells progressively accumulate in visceral white adipose tissue and liver during ageing and that inflammatory cytokines secreted by senescent cells (the senescence-associated secretory phenotype, SASP) induce macrophages to proliferate and express CD38. These results uncover a new causal link among resident tissue macrophages, cellular senescence and tissue NAD decline during ageing and offer novel therapeutic opportunities to maintain NAD levels during ageing.

SummaryDecline in tissue NAD levels during aging is linked to aging and its associated diseases. However, the mechanism for aging-associated NAD decline remains unclear. Here we report that pro-inflammatory M1-like macrophages, but not naïve or M2 macrophages, accumulate in metabolic tissues including visceral white adipose tissue and the liver during aging. Remarkably, these M1-like macrophages highly express the NAD consuming enzyme CD38 and have enhanced CD38-dependent NADase activity. We also find that senescent cells progressively accumulate in visceral white adipose tissue during aging and that inflammatory cytokines found in the supernatant from senescent cells (Senescence associated secretory proteins, SASP) induce macrophages to proliferate and to express CD38. These results highlight a new causal link between visceral tissue senescence and tissue NAD decline during aging and represent a novel therapeutic opportunity targeting maintenance of NAD levels during aging.

This paper builds a model of high-frequency equity returns by separately modeling the dynamics of trade-time returns and trade arrivals. Our main contributions are threefold. First, we characterize the distributional behavior of high-frequency asset returns both in ordinary clock time and in trade time. We show that when controlling for pre-scheduled market news events, trade-time returns of the highly liquid near-month E-mini S&P 500 futures contract are well characterized by a Gaussian distribution at very fine time scales. Second, we develop a structured and parsimonious model of clock-time returns by subordinating a trade-time Gaussian distribution with a trade arrival process that is associated with a modified Markov-Switching Multifractal Duration (MSMD) model. This model provides an excellent characterization of high-frequency inter-trade durations. Over-dispersion in this distribution of inter-trade durations leads to leptokurtosis and volatility clustering in clock-time returns, even when trade-time returns are Gaussian. Finally, we use our model to extrapolate the empirical relationship between trade rate and volatility in an effort to understand conditions of market failure. Our model suggests that the 1,200 km physical separation of financial markets in Chicago and New York/New Jersey provides a natural ceiling on systemic volatility and may contribute to market stability during periods of extremely heavy trading.