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.
Naturally occurring missense variants of G protein–coupled receptors with loss of function have been linked to metabolic disease in case studies and in animal experiments. The glucagon receptor, one such G protein–coupled receptor, is involved in maintaining blood glucose and amino acid homeostasis; however, loss-of-function mutations of this receptor have not been systematically characterized. Here, we observed fewer glucagon receptor missense variants than expected, as well as lower allele diversity and fewer variants with trait associations as compared with other class B1 receptors. We performed molecular pharmacological phenotyping of 38 missense variants located in the receptor extracellular domain, at the glucagon interface, or with previously suggested clinical implications. These variants were characterized in terms of cAMP accumulation to assess glucagon-induced Gα s coupling, and of recruitment of β-arrestin-1/2. Fifteen variants were impaired in at least one of these downstream functions, with six variants affected in both cAMP accumulation and β-arrestin-1/2 recruitment. For the eight variants with decreased Gα s signaling (D63 ECD N, P86 ECD S, V96 ECD E, G125 ECD C, R225 3.30 H, R308 5.40 W, V368 6.59 M, and R378 7.35 C) binding experiments revealed preserved glucagon affinity, although with significantly reduced binding capacity. Finally, using the UK Biobank, we found that variants with wildtype-like Gα s signaling did not associate with metabolic phenotypes, whereas carriers of cAMP accumulation-impairing variants displayed a tendency toward increased risk of obesity and increased body mass and blood pressure. These observations are in line with the essential role of the glucagon system in metabolism and support that Gα s is the main signaling pathway effecting the physiological roles of the glucagon receptor.
Strong efforts have been placed on understanding the physiological roles and therapeutic potential of the proglucagon peptide hormones including glucagon, GLP-1 and GLP-2. However, little is known about the extent and magnitude of variability in the amino acid composition of the proglucagon precursor and its mature peptides. Here, we identified 184 unique missense variants in the human proglucagon gene GCG obtained from exome and whole-genome sequencing of more than 450,000 individuals across diverse sub-populations. This provides an unprecedented source of population-wide genetic variation data on missense mutations and insights into the evolutionary constraint spectrum of proglucagon-derived peptides. We show that the stereotypical peptides glucagon, GLP-1 and GLP-2 display fewer evolutionary alterations and are more likely to be functionally affected by genetic variation compared to the rest of the gene products. Elucidating the spectrum of genetic variations and estimating the impact of how a peptide variant may influence human physiology and pathophysiology through changes in ligand binding and/or receptor signalling, are vital and serve as the first important step in understanding variability in glucose homeostasis, amino acid metabolism, intestinal epithelial growth, bone strength, appetite regulation, and other key physiological parameters controlled by these hormones.
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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