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Donertas, H. M.

Publications and source records attributed to Donertas, H. M..

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Using the drug-protein interactome to identify anti-ageing compounds for humans

Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established its association with ageing at multiple levels of biological actions including pathways, functions and protein interactions. Finally, combining all the data, we calculated a comprehensive ranked list of drugs that predicted tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans.\n\nAuthor SummaryHuman life expectancy is continuing to increase worldwide, as a result of successive improvements in living conditions and medical care. Although this trend is to be celebrated, advancing age is the major risk factor for multiple impairments and chronic diseases. As a result, the later years of life are often spent in poor health and lowered quality of life. However, these effects of ageing are not inevitable, because very long-lived people often suffer rather little ill-health at the end of their lives. Furthermore, laboratory experiments have shown that animals fed with specific drugs can live longer and with fewer age-related diseases than their untreated companions. We therefore need to identify drugs with anti-ageing properties for humans. We have therefore used computers to search for drugs that affect components and processes known to be important in human ageing. This approach worked, because it was able to re-discover several drugs known to increase lifespan in animal models, plus some new ones, including one that we tested experimentally and validated in this study. These drugs are now a high priority for animal testing and for exploring effects on human ageing.

bioinformatics

Gene Expression-Based Drug Repurposing to Target Ageing

Ageing is the largest risk factor for a variety of non-communicable diseases. Model organism studies have shown that genetic and chemical perturbations can extend both life- and health-span. Ageing is a complex process, with parallel and interacting mechanisms contributing to its aetiology, posing a challenge for the discovery of new pharmacological candidates to ameliorate its effects. In this study, instead of a target-centric approach, we adopt a systems level drug repurposing methodology to discover drugs that could combat ageing in human brain. Using multiple gene expression datasets from brain tissue, taken from patients of different ages, we first identified the expression changes that characterise ageing. Then, we compared these changes in gene expression with drug perturbed expression profiles in the Connectivity Map. We thus identified 24 drugs with significantly associated changes. Some of these drugs may function as anti-ageing drugs by reversing the detrimental changes that occur during ageing, others by mimicking the cellular defense mechanisms. The drugs that we identified included significant number of already identified pro-longevity drugs, indicating that the method can discover de novo drugs that meliorate ageing. The approach has the advantages that, by using data from human brain ageing data it focuses on processes relevant in human ageing and that it is unbiased, making it possible to discover new targets for ageing studies.

systems biology

Mutation accumulation differentially impacts ageing in mammalian tissues

Medawars mutation accumulation (MA) hypothesis explains ageing by the declining force of natural selection with age: slightly deleterious germline mutations that are functional in old age are not effectively eliminated by selection and therefore lead to ageing-related phenotypes. Although widely cited, empirical support for the MA hypothesis, particularly molecular evidence, has remained limited. Here we test one of its predictions, that genes relatively highly expressed in old adults vs. young adults should be under weaker purifying selection than those relatively highly expressed in young adults. To do so, we combine 23 RNA-sequencing and 35 microarray gene expression datasets (including 9 tissues from 5 mammalian species) with protein and regulatory sequence conservation estimates across mammals. We identify age-related decrease in transcriptome conservation (ADICT) in four tissues, brain, liver, lung, and artery, but not in other tissues, most notably muscle and heart. ADICT is driven both by decreased expression of highly conserved genes and up-regulation of poorly conserved genes during ageing, in line with the MA hypothesis. Lowly conserved and up-regulated genes in ADICT-associated tissues have overlapping functional properties, particularly involving apoptosis and inflammation, with no evidence for a history of positive selection. Our results suggest that tissues vary in how evolution has shaped their ageing patterns. We find that in some tissues, genes up-regulated during ageing, possibly in response to accumulating cellular and histological damage, are under weaker purifying selection than other genes. We propose that accumulation of slightly deleterious substitutions in these genes may underlie their suboptimal regulation and activity during ageing, shaping senescent phenotypes such as inflammaging.

evolutionary biology