GenAge: a genomic and proteomic network map of human ageing

Magalhães, João Pedro de; Toussaint, Olivier

doi:10.1016/j.febslet.2004.07.006

Cited by 124 publications

(106 citation statements)

References 21 publications

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“…Next, we classified M. lignano transcripts according to their homology to human genes present in the GenAge database of aging‐related genes (De Magalhães & Toussaint, 2004) and to the genome maintenance genes (Macrae et al., 2015), and overlapped the distribution of these gene categories with the identified temporal groups. Remarkably, the Down‐Up‐Up category is 1.38‐fold enriched ( p = 4.293e‐08) for aging‐related genes, and 1.51‐fold enriched ( p = 6.961e‐05) for genome maintenance genes (Table 1).…”

Section: Resultsmentioning

confidence: 99%

Resilience to aging in the regeneration‐capable flatworm Macrostomum lignano

et al. 2018

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SummaryAnimals show a large variability of lifespan, ranging from short‐lived as Caenorhabditis elegans to immortal as Hydra. A fascinating case is flatworms, in which reversal of aging by regeneration is proposed, yet conclusive evidence for this rejuvenation‐by‐regeneration hypothesis is lacking. We tested this hypothesis by inducing regeneration in the sexual free‐living flatworm Macrostomum lignano. We studied survival, fertility, morphology, and gene expression as a function of age. Here, we report that after regeneration, genes expressed in the germline are upregulated at all ages, but no signs of rejuvenation are observed. Instead, the animal appears to be substantially longer lived than previously appreciated, and genes expressed in stem cells are upregulated with age, while germline genes are downregulated. Remarkably, several genes with known beneficial effects on lifespan when overexpressed in mice and C. elegans are naturally upregulated with age in M. lignano, suggesting that molecular mechanism for offsetting negative consequences of aging has evolved in this animal. We therefore propose that M. lignano represents a novel powerful model for molecular studies of aging attenuation, and the identified aging gene expression patterns provide a valuable resource for further exploration of anti‐aging strategies.

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Section: Resultsmentioning

confidence: 99%

Resilience to aging in the regeneration‐capable flatworm Macrostomum lignano

et al. 2018

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“…Out of 53 genes that returned a p-value less than the arbitrary cut-off of 0.02, we found three that were represented in 253 aging-related genes from the curated GenAge database [12]. Using a hypergeometric distribution with 253 known genes involved in aging and the number of genes in the human genome conservatively estimated at 20,000 [13], we find that retrieving 3 aging-related genes out of 53 is statistically significant at p = 0.023.…”

Section: Discussionmentioning

confidence: 99%

Novel Integration of Hospital Electronic Medical Records and Gene Expression Measurements to Identify Genetic Markers of Maturation

Chen

Weber²,

Constantinou³

et al. 2007

Biocomputing 2008

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Traditionally, the elucidation of genes involved in maturation and aging has been studied in a temporal fashion by examining gene expression at different time points in an organism's life as well as by knocking out, knocking in, and mutating genes thought to be involved. Here, we propose an in silico method to combine clinical electronic medical record (EMR) data and gene expression measurements in the context of disease to identify genes that may be involved in the process of human maturation and aging. First we show that absolute lymphocyte count may serve as a biomarker for maturation by using statistical methods to compare trends among different clinical laboratory tests in response to an increase in age. We then propose using the rate of decay for absolute lymphocyte count across 12 diseases as a proxy for differences in aging. We correlate the differing rates with gene expression across the same diseases to find maturation/aging related genes. Among the 53 genes with strongest correlations between expression profile and change in rate of decay, we found genes previously implicated in the process of aging, including MGMT (DNA repair), TERF2 (telomere stability), POLD1 (DNA replication and repair), and POLG (mtDNA replication).

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“…Van Leeuwen et al (2002) proposed a model to describe the food consumption, body growth and survival of laboratory rodents, which predicted well the observed differences in body weight and longevity in function of the food intake rate. De Magalhães & Toussaint (2004) developed a proteomic network map of human ageing, suggesting a relationship between the genetics of development and ageing. Furthermore, Xue and co-workers have recently derived a modular network of protein-protein interactions in fruitflies and humans, and then identified those modules that are responsible for the progression of ageing (Xue et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Dynamic energy budget approaches for modelling organismal ageing

Leeuwen

Vera

Wolkenhauer

2010

Phil. Trans. R. Soc. B

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Ageing is a complex multifactorial process involving a progressive physiological decline that, ultimately, leads to the death of an organism. It involves multiple changes in many components that play fundamental roles under healthy and pathological conditions. Simultaneously, every organism undergoes accumulative 'wear and tear' during its lifespan, which confounds the effects of the ageing process. The scenario is complicated even further by the presence of both age-dependent and age-independent competing causes of death. Various manipulations have been shown to interfere with the ageing process. Calorie restriction, for example, has been reported to increase the lifespan of a wide range of organisms, which suggests a strong relation between energy metabolism and ageing. Such a link is also supported within the main theories for ageing: the free radical hypothesis, for instance, links oxidative damage production directly to energy metabolism. The Dynamic Energy Budgets (DEB) theory, which characterizes the uptake and use of energy by living organisms, therefore constitutes a useful tool for gaining insight into the ageing process. Here we compare the existing DEB-based modelling approaches and, then, discuss how new biological evidence could be incorporated within a DEB framework.

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GenAge: a genomic and proteomic network map of human ageing

Cited by 124 publications

References 21 publications

Resilience to aging in the regeneration‐capable flatworm Macrostomum lignano

Resilience to aging in the regeneration‐capable flatworm Macrostomum lignano

Novel Integration of Hospital Electronic Medical Records and Gene Expression Measurements to Identify Genetic Markers of Maturation

Dynamic energy budget approaches for modelling organismal ageing

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