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.
Fibroblast growth factor 21 (FGF21) plays a key role in hepatic lipid metabolism and long-acting FGF21 analogues has emerged as a promising drug candidates for the treatment of non-alcoholic steatohepatitis (NASH). It remains to characterize this drug class in translational animal models that recapitulate the aetiology and hallmarks of the human disease. To this end, we evaluated the long-acting FGF21 analogue PF-05231023 in the GAN (Gubra Amylin NASH) diet-induced obese (DIO) and biopsy-confirmed mouse model of NASH. Male C57BL/6J mice were fed the GAN diet high in fat, fructose, and cholesterol for 34 weeks prior to study start. GAN DIO-NASH mice with biopsy-confirmed NAFLD Activity Score (NAS ≥5) and fibrosis (stage ≥F1) were biweekly administered with PF-05231023 (10 mg/kg, SC) or vehicle (SC) for 12 weeks. Vehicle-dosed chow-fed C57BL/6J mice served as healthy controls. Pre-to-post liver biopsy histopathological scoring was performed for within-subject evaluation of NAFLD Activity Score (NAS) and fibrosis stage. Terminal endpoints included quantitative liver histology and transcriptome signatures as well as blood and liver biochemistry. PF-05231023 significantly reduced body weight, hepatomegaly, plasma transaminases and plasma/liver lipids in GAN DIO-NASH mice. Notably, PF-05231023 reduced both NAS (≥2-point improvement) and fibrosis stage (1-point improvement). Improvements in NASH and fibrosis severity were supported by reduced quantitative histological markers of steatosis, inflammation and fibrogenesis as well as improvements in disease-associated liver transcriptome signatures. Conclusion: PF-05231023 reduces NASH and fibrosis severity in a translational biopsy-confirmed mouse model of NASH, supporting development of FGF21 analogues for the treatment of NASH.
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.
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.
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