Systems biology in aging: linking the old and the young

The Systems Biology of Single-Cell Aging

Aging is a leading cause of human morbidity and mortality, but efforts to slow or reverse its effects are hampered by an incomplete understanding of its multi-faceted origins. Systems biology, the use of quantitative and computational methods to understand complex biological systems, offers a toolkit well suited to elucidating the root cause of aging. We describe the known components of the aging network and outline innovative techniques that open new avenues of investigation to the aging research community. We propose integration of the systems biology and aging fields, identifying areas of complementarity based on existing and impending technological capabilities.

Uncovering the mechanisms of Caenorhabditis elegans ageing from global quantification of the underlying landscape

Recent studies on Caenorhabditis elegans reveal that gene manipulations can extend its lifespan several fold. However, how the genes work together to determine longevity is still an open question. Here we construct a gene regulatory network for worm ageing and quantify its underlying potential and flux landscape. We found ageing and rejuvenation states can emerge as basins of attraction at certain gene expression levels. The system state can switch from one attractor to another driven by the intrinsic or external perturbations through genetics or the environment. Furthermore, we simulated gene silencing experiments and found that the silencing of longevity-promoting or lifespan-limiting genes leads to ageing or rejuvenation domination, respectively. This indicates that the difference in depths between ageing and the rejuvenation attractor is highly correlated with worm longevity. We further uncovered some key genes and regulations which have a strong influence on landscape basin stability. A dynamic landscape model is proposed to describe the whole process of ageing: the ageing attractor dominates when senescence progresses. We also uncovered the oscillation dynamics, and a similar behaviour was observed in the long-lived creature Turritopsis dohrnii Our landscape theory provides a global and physical approach to explore the underlying mechanisms of ageing.

Proteomics and metabolomics in ageing research: from biomarkers to systems biology

Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible 'biomarkers', which are predictors of one's biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying 'endophenotypes' in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity.

Anti-aging effect and gene expression profiling of dung beetle glycosaminoglycan in aged rats

BACKGROUND

This study aimed to evaluate the anti-aging effect of a newly prepared insect-derived compound, dung beetle glycosaminoglycan (GAG), given intraperitoneally to old SD rats as part of their diet for 1 month. Insect GAG administration was found to be related to a reduction in oxidative damage, hepato-cellular biomarker levels, protein carbonyl content, and malondialdehyde concentration. The anti-aging-related molecular genetic mechanisms of dung beetle GAG are not yet fully elucidated.

RESULTS

Catharsius molossus (a type of dung beetle) GAG (CaG) possessed anti-aging activities; it reduced the serum level of creatinine kinase, had aortic vasorelaxant activities and cardioprotective actions, and maintained a normal glucose level in treated rats. Microarray analysis was performed with a rat 30 K cDNA clone set array to identify the gene-expression profiles of 14-month-old SD rats treated with dung beetle glycosaminoglycan 5 mg/kg (CaG5) over a 1-month period, which was done to investigate its anti-aging effect as compared to that of either Bombus ignitus (a type of bumblebee) queen GAG 5 mg/kg (IQG5) or chondroitin sulfate 10 mg/kg. CaG5 and IQG5 had marked anti-inflammatory effects, bringing about inhibition of free fatty acid, uric acid, sGPT, IL-1 beta, and CK values. In addition, anticoagulant and antithrombotic effects were seen: the concentration of factor 1 (fibrinogen) was increased in CaG- treated rat plasma. The CaG5-treated rat group, compared to the control, displayed upregulation of 131 genes, including lipocalin 2 (Lbp) and a serine peptidase inhibitor, Kaszal type3 (Spink3), and 64 downregulated genes, including lysyl oxidase (Lox), serine dehydratase (sds), and retinol saturase (Retsat).

CONCLUSION

Our data suggest that dung beetle glycosaminoglycan may be a helpful treatment for aged rats, which indicates its potential as a therapeutic biomaterial for aging.

A synopsis on aging-Theories, mechanisms and future prospects

Answering the question as to why we age is tantamount to answering the question of what is life itself. There are countless theories as to why and how we age, but, until recently, the very definition of aging - senescence - was still uncertain. Here, we summarize the main views of the different models of senescence, with a special emphasis on the biochemical processes that accompany aging. Though inherently complex, aging is characterized by numerous changes that take place at different levels of the biological hierarchy. We therefore explore some of the most relevant changes that take place during aging and, finally, we overview the current status of emergent aging therapies and what the future holds for this field of research. From this multi-dimensional approach, it becomes clear that an integrative approach that couples aging research with systems biology, capable of providing novel insights into how and why we age, is necessary.

Deciphering hallmark processes of aging from interaction networks

BACKGROUND

Aging is broadly considered to be a dynamic process that accumulates unfavourable structural and functional changes in a time dependent fashion, leading to a progressive loss of physiological integrity of an organism, which eventually leads to age-related diseases and finally to death.

SCOPE OF REVIEW

The majority of aging-related studies are based on reductionist approaches, focusing on single genes/proteins or on individual pathways without considering possible interactions between them. Over the last few decades, several such genes/proteins were independently analysed and linked to a role that is affecting the longevity of an organism. However, an isolated analysis on genes and proteins largely fails to explain the mechanistic insight of a complex phenotype due to the involvement and integration of multiple factors.

MAJOR CONCLUSIONS

Technological advance makes it possible to generate high-throughput temporal and spatial data that provide an opportunity to use computer-based methods. These techniques allow us to go beyond reductionist approaches to analyse large-scale networks that provide deeper understanding of the processes that drive aging.

GENERAL SIGNIFICANCE

In this review, we focus on systems biology approaches, based on network inference methods to understand the dynamics of hallmark processes leading to aging phenotypes. We also describe computational methods for the interpretation and identification of important molecular hubs involved in the mechanistic linkage between aging related processes. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Survival and its predictors from age 75 to 85 in men and women belonging to cohorts with marked survival differences to age 75: a comparative study in three Nordic populations

BACKGROUND AND AIMS

While predictors of survival in older people have been examined in depth in a large number of studies, a literature search revealed no cross-national comparative prospective cohort studies on this issue. This study investigated survival and its predictors from age 75 to 85 among three local Nordic populations using survival data on national cohorts as background information.

METHODS

The data were derived from national registers and from samples of 75-year old living in Denmark, Sweden, and Finland. The subjects were invited to take part in interviews and examinations focusing on different domains of health, functional capacity, and physical and social activities.

RESULTS

The proportion of survivors to age 75 was markedly smaller among the Finnish men and women than Danish or Swedish subjects. In the local population no marked differences in survival from age 75 to 85 were observed between the groups of men, while women survived longer than men and longer in Göteborg than in Glostrup or Jyväskylä. Univariate models revealed 12 predictors of survival. In the multivariate models, the significant predictors among men related to physical fitness, whereas among women they pertained to social activities and morbidity.

CONCLUSIONS

Despite great differences in the proportions of survivors to age 75, and excepting the survival advantage of women, only minor differences were present in the subjects' further survival to age 85. In the univariate analyses, many of the factors predictive of survival from age 75 to 85 were the same in the examined populations, whereas in the multivariate analyses differences between the sexes emerged.

Aging and computational systems biology

Aging research is undergoing a paradigm shift, which has led to new and innovative methods of exploring this complex phenomenon. The systems biology approach endeavors to understand biological systems in a holistic manner, by taking account of intrinsic interactions, while also attempting to account for the impact of external inputs, such as diet. A key technique employed in systems biology is computational modeling, which involves mathematically describing and simulating the dynamics of biological systems. Although a large number of computational models have been developed in recent years, these models have focused on various discrete components of the aging process, and to date no model has succeeded in completely representing the full scope of aging. Combining existing models or developing new models may help to address this need and in so doing could help achieve an improved understanding of the intrinsic mechanisms which underpin aging.

Anti-aging Effect and Gene Expression Profiling of Aged Rats Treated with G. bimaculatus Extract

Extract from Gryllus bimaculatus crickets inhibits oxidation at the DNA level, with reduced production of 8-hydroxy-2'-deoxyguanosine (8-OHdG). Microarray analyses were performed with a rat 28K cDNA clone set array to identify the gene expression profiles of aged (10 months old) Wistar Kyoto rats treated for one month with 100 mg/kg G. bimaculatus ethanol extract to assess the effects. The extract produced a meaningful anti-edema effect, evident by the inhibition of creatinine phosphokinase activity. The weights of abdominal and ovarian adipose tissues were reduced and the proportion of unsaturated fatty acids in adipose tissues was increased in an extract dose-dependent manner. Compared with untreated control rats, rats treated with the extract displayed the upregulation of 1053 genes including Fas (tumor necrosis factor receptor superfamily, member 6), Amigo3 (adhesion molecule with an immunoglobulin-like domain), Reticulon 4, 3-hydroxy-3-methylglutaryl-coenzyme (Hmgcr; a reductase), related anti-fatigue (enzyme metabolism), and Rtn antioxidant, and the downregulation of 73 genes including Ugt2b (UDP glycosyltransferase 2 family), Early growth response 1, and Glycoprotein m6a. Data suggest that G. bimaculatus extract may have value in lessening the effects of aging, resulting in a differential gene expression pattern indicative of a marked stress response and lower expression of metabolic and biosynthetic genes.

Why is aging conserved and what can we do about it?

The field of aging research has progressed rapidly over the past few decades. Genetic modulators of aging rate that are conserved over a broad evolutionary distance have now been identified. Several physiological and environmental interventions have also been shown to influence the rate of aging in organisms ranging from yeast to mammals. Here we briefly review these conserved pathways and interventions and highlight some key unsolved challenges that remain. Although the molecular mechanisms by which these modifiers of aging act are only partially understood, interventions to slow aging are nearing clinical application, and it is likely that we will begin to reap the benefits of aging research prior to solving all of the mysteries that the biology of aging has to offer.

Old age is the single greatest risk factor for the leading causes of death in the developed world. Advances in aging research promise to alleviate the diseases of aging by targeting aging itself.

Mathematical modelling of metabolic regulation in aging

The underlying cellular mechanisms that characterize aging are complex and multifaceted. However, it is emerging that aging could be regulated by two distinct metabolic hubs. These hubs are the pathway defined by the mammalian target of rapamycin (mTOR) and that defined by the NAD+-dependent deacetylase enzyme, SIRT1. Recent experimental evidence suggests that there is crosstalk between these two important pathways; however, the mechanisms underpinning their interaction(s) remains poorly understood. In this review, we propose using computational modelling in tandem with experimentation to delineate the mechanism(s). We briefly discuss the main modelling frameworks that could be used to disentangle this relationship and present a reduced reaction pathway that could be modelled. We conclude by outlining the limitations of computational modelling and by discussing opportunities for future progress in this area.

Integromics network meta-analysis on cardiac aging offers robust multi-layer modular signatures and reveals micronome synergism

Background

The avalanche of integromics and panomics approaches shifted the deciphering of aging mechanisms from single molecular entities to communities of them. In this orientation, we explore the cardiac aging mechanisms – risk factor for multiple cardiovascular diseases - by capturing the micronome synergism and detecting longevity signatures in the form of communities (modules).

For this, we developed a meta-analysis scheme that integrates transcriptome expression data from multiple cardiac-specific independent studies in mouse and human along with proteome and micronome interaction data in the form of multiple independent weighted networks. Modularization of each weighted network produced modules, which in turn were further analyzed so as to define consensus modules across datasets that change substantially during lifespan. Also, we established a metric that determines - from the modular perspective - the synergism of microRNA-microRNA interactions as defined by significantly functionally associated targets.

Results

The meta-analysis provided 40 consensus integromics modules across mouse datasets and revealed microRNA relations with substantial collective action during aging. Three modules were reproducible, based on homology, when mapped against human-derived modules. The respective homologs mainly represent NADH dehydrogenases, ATP synthases, cytochrome oxidases, Ras GTPases and ribosomal proteins. Among various observations, we corroborate to the involvement of miR-34a (included in consensus modules) as proposed recently; yet we report that has no synergistic effect. Moving forward, we determined its age-related neighborhood in which HCN3, a known heart pacemaker channel, was included. Also, miR-125a-5p/-351, miR-200c/-429, miR-106b/-17, miR-363/-92b, miR-181b/-181d, miR-19a/-19b, let-7d/-7f, miR-18a/-18b, miR-128/-27b and miR-106a/-291a-3p pairs exhibited significant synergy and their association to aging and/or cardiovascular diseases is supported in many cases by a disease database and previous studies. On the contrary, we suggest that miR-22 has not substantial impact on heart longevity as proposed recently.

Conclusions

We revised several proteins and microRNAs recently implicated in cardiac aging and proposed for the first time modules as signatures. The integromics meta-analysis approach can serve as an efficient subvening signature tool for more-oriented better-designed experiments. It can also promote the combinational multi-target microRNA therapy of age-related cardiovascular diseases along the continuum from prevention to detection, diagnosis, treatment and outcome.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1256-3) contains supplementary material, which is available to authorized users.

Computationally Modeling Lipid Metabolism and Aging: A Mini-review

One of the greatest challenges in biology is to improve the understanding of the mechanisms which underpin aging and how these affect health. The need to better understand aging is amplified by demographic changes, which have caused a gradual increase in the global population of older people. Aging western populations have resulted in a rise in the prevalence of age-related pathologies. Of these diseases, cardiovascular disease is the most common underlying condition in older people. The dysregulation of lipid metabolism due to aging impinges significantly on cardiovascular health. However, the multifaceted nature of lipid metabolism and the complexities of its interaction with aging make it challenging to understand by conventional means. To address this challenge computational modeling, a key component of the systems biology paradigm is being used to study the dynamics of lipid metabolism. This mini-review briefly outlines the key regulators of lipid metabolism, their dysregulation, and how computational modeling is being used to gain an increased insight into this system.

CoCiter: an efficient tool to infer gene function by assessing the significance of literature co-citation

A routine approach to inferring functions for a gene set is by using function enrichment analysis based on GO, KEGG or other curated terms and pathways. However, such analysis requires the existence of overlapping genes between the query gene set and those annotated by GO/KEGG. Furthermore, GO/KEGG databases only maintain a very restricted vocabulary. Here, we have developed a tool called "CoCiter" based on literature co-citations to address the limitations in conventional function enrichment analysis. Co-citation analysis is widely used in ranking articles and predicting protein-protein interactions (PPIs). Our algorithm can further assess the co-citation significance of a gene set with any other user-defined gene sets, or with free terms. We show that compared with the traditional approaches, CoCiter is a more accurate and flexible function enrichment analysis method. CoCiter is freely available at www.picb.ac.cn/hanlab/cociter/.

Genome-scale studies of aging: challenges and opportunities

Whole-genome studies involving a phenotype of interest are increasingly prevalent, in part due to a dramatic increase in speed at which many high throughput technologies can be performed coupled to simultaneous decreases in cost. This type of genome-scale methodology has been applied to the phenotype of lifespan, as well as to whole-transcriptome changes during the aging process or in mutants affecting aging. The value of high throughput discovery-based science in this field is clearly evident, but will it yield a true systems-level understanding of the aging process? Here we review some of this work to date, focusing on recent findings and the unanswered puzzles to which they point. In this context, we also discuss recent technological advances and some of the likely future directions that they portend.