Special Issue "Systems Biology of Aging"

A special issue of Biology (ISSN 2079-7737).

Deadline for manuscript submissions: closed (31 October 2017).

Special Issue Editors

Assoc. Prof. Dr. Andres Kriete
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Guest Editor
School of Biomedical Engineering, Science and Health Systems. Drexel University, Philadelphia, PA 19104, USA
Interests: systems biology, biology of aging, control theory, evolutionary tradeoffs, bioimaging
Prof. Dr. Hans Kestler
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Co-Guest Editor
Institute of Medical Systems Biology, Ulm University, 89069 Ulm, Germany
Interests: systems biology of aging; machine learning; high-dimensional statistics

Special Issue Information

Dear Colleagues,

This multidisciplinary volume focuses on experimental, theoretical and computational systems concepts applied to the biology of aging. Systems biology provides a deeper understanding of the overall complexity of molecular mechanisms underlying aging of cells, organisms, populations and age-related diseases. Novel experimental approaches, conceptual frameworks and integration of datasets generated from “omics” technologies are facilitators in the generation of systems level models. This includes, but is not limited, to molecular pathways involved in metabolism, signaling and stress responses, protein-protein interaction networks and genetic regulation. We invite for research articles, short communications and reviews addressing:

  • Aging pathways and networks
  • Experimental systems-level studies and designs
  • Genome-wide association studies
  • Novel conceptual frameworks
  • Data integration, standards and meta-analyses
  • Computational and statistical modeling
  • Semantic information integration
  • Network evolution.

Assoc. Prof. Dr. Andres Kriete
Prof. Dr. Hans Kestler
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Aging pathways
  • Experimental system models
  • Network evolution
  • Data integration and modeling

Published Papers (5 papers)

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Research

Open AccessArticle
Integrated Systems Approach Reveals Sphingolipid Metabolism Pathway Dysregulation in Association with Late-Onset Alzheimer’s Disease
Biology 2018, 7(1), 16; https://doi.org/10.3390/biology7010016 - 09 Feb 2018
Cited by 1
Abstract
Late-onset Alzheimer’s disease (LOAD) and age are significantly correlated such that one-third of Americans beyond 85 years of age are afflicted. We have designed and implemented a pilot study that combines systems biology approaches with traditional next-generation sequencing (NGS) analysis techniques to identify [...] Read more.
Late-onset Alzheimer’s disease (LOAD) and age are significantly correlated such that one-third of Americans beyond 85 years of age are afflicted. We have designed and implemented a pilot study that combines systems biology approaches with traditional next-generation sequencing (NGS) analysis techniques to identify relevant regulatory pathways, infer functional relationships and confirm the dysregulation of these biological pathways in LOAD. Our study design is a most comprehensive systems approach combining co-expression network modeling derived from RNA-seq data, rigorous quality control (QC) standards, functional ontology, and expression quantitative trait loci (eQTL) derived from whole exome (WES) single nucleotide variant (SNV) genotype data. Our initial results reveal several statistically significant, biologically relevant genes involved in sphingolipid metabolism. To validate these findings, we performed a gene set enrichment analysis (GSEA). The GSEA revealed the sphingolipid metabolism pathway and regulation of autophagy in association with LOAD cases. In the execution of this study, we have successfully tested an integrative approach to identify both novel and known LOAD drivers in order to develop a broader and more detailed picture of the highly complex transcriptional and regulatory landscape of age-related dementia. Full article
(This article belongs to the Special Issue Systems Biology of Aging)
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Open AccessArticle
Interaction Analysis of Longevity Interventions Using Survival Curves
Biology 2018, 7(1), 6; https://doi.org/10.3390/biology7010006 - 06 Jan 2018
Cited by 1
Abstract
A long-standing problem in ageing research is to understand how different factors contributing to longevity should be expected to act in combination under the assumption that they are independent. Standard interaction analysis compares the extension of mean lifespan achieved by a combination of [...] Read more.
A long-standing problem in ageing research is to understand how different factors contributing to longevity should be expected to act in combination under the assumption that they are independent. Standard interaction analysis compares the extension of mean lifespan achieved by a combination of interventions to the prediction under an additive or multiplicative null model, but neither model is fundamentally justified. Moreover, the target of longevity interventions is not mean life span but the entire survival curve. Here we formulate a mathematical approach for predicting the survival curve resulting from a combination of two independent interventions based on the survival curves of the individual treatments, and quantify interaction between interventions as the deviation from this prediction. We test the method on a published data set comprising survival curves for all combinations of four different longevity interventions in Caenorhabditis elegans. We find that interactions are generally weak even when the standard analysis indicates otherwise. Full article
(This article belongs to the Special Issue Systems Biology of Aging)
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Open AccessFeature PaperArticle
Age-Dependence and Aging-Dependence: Neuronal Loss and Lifespan in a C. elegans Model of Parkinson’s Disease
Biology 2018, 7(1), 1; https://doi.org/10.3390/biology7010001 - 23 Dec 2017
Cited by 5
Abstract
It is often assumed, but not established, that the major neurodegenerative diseases, such as Parkinson’s disease, are not just age-dependent (their incidence changes with time) but actually aging-dependent (their incidence is coupled to the process that determines lifespan). To determine a dependence on [...] Read more.
It is often assumed, but not established, that the major neurodegenerative diseases, such as Parkinson’s disease, are not just age-dependent (their incidence changes with time) but actually aging-dependent (their incidence is coupled to the process that determines lifespan). To determine a dependence on the aging process requires the joint probability distribution of disease onset and lifespan. For human Parkinson’s disease, such a joint distribution is not available, because the disease cuts lifespan short. To acquire a joint distribution, we resorted to an established C. elegans model of Parkinson’s disease in which the loss of dopaminergic neurons is not fatal. We find that lifespan is not correlated with the loss of individual neurons. Therefore, neuronal loss is age-dependent and aging-independent. We also find that a lifespan-extending intervention into insulin/IGF1 signaling accelerates the loss of specific dopaminergic neurons, while leaving death and neuronal loss times uncorrelated. This suggests that distinct and compartmentalized instances of the same genetically encoded insulin/IGF1 signaling machinery act independently to control neurodegeneration and lifespan in C. elegans. Although the human context might well be different, our study calls attention to the need to maintain a rigorous distinction between age-dependence and aging-dependence. Full article
(This article belongs to the Special Issue Systems Biology of Aging)
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Open AccessArticle
Stability of Signaling Pathways during Aging—A Boolean Network Approach
Biology 2017, 6(4), 46; https://doi.org/10.3390/biology6040046 - 18 Dec 2017
Cited by 5
Abstract
Biological pathways are thought to be robust against a variety of internal and external perturbations. Fail-safe mechanisms allow for compensation of perturbations to maintain the characteristic function of a pathway. Pathways can undergo changes during aging, which may lead to changes in their [...] Read more.
Biological pathways are thought to be robust against a variety of internal and external perturbations. Fail-safe mechanisms allow for compensation of perturbations to maintain the characteristic function of a pathway. Pathways can undergo changes during aging, which may lead to changes in their stability. Less stable or less robust pathways may be consequential to or increase the susceptibility of the development of diseases. Among others, NF- κ B signaling is a crucial pathway in the process of aging. The NF- κ B system is involved in the immune response and dealing with various internal and external stresses. Boolean networks as models of biological pathways allow for simulation of signaling behavior. They can help to identify which proposed mechanisms are biologically representative and which ones function but do not mirror physical processes—for instance, changes of signaling pathways during the aging process. Boolean networks can be inferred from time-series of gene expression data. This allows us to get insights into the changes of behavior of pathways such as NF- κ B signaling in aged organisms in comparison to young ones. Full article
(This article belongs to the Special Issue Systems Biology of Aging)
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Open AccessArticle
Simulation of Cellular Energy Restriction in Quiescence (ERiQ)—A Theoretical Model for Aging
Biology 2017, 6(4), 44; https://doi.org/10.3390/biology6040044 - 12 Dec 2017
Cited by 1
Abstract
Cellular responses to energy stress involve activation of pro-survival signaling nodes, compensation in regulatory pathways and adaptations in organelle function. Specifically, energy restriction in quiescent cells (ERiQ) through energetic perturbations causes adaptive changes in response to reduced ATP, NAD+ and NADP levels in [...] Read more.
Cellular responses to energy stress involve activation of pro-survival signaling nodes, compensation in regulatory pathways and adaptations in organelle function. Specifically, energy restriction in quiescent cells (ERiQ) through energetic perturbations causes adaptive changes in response to reduced ATP, NAD+ and NADP levels in a regulatory network spanned by AKT, NF-κB, p53 and mTOR. Based on the experimental ERiQ platform, we have constructed a minimalistic theoretical model consisting of feedback motifs that enable investigation of stress-signaling pathways. The computer simulations reveal responses to acute energetic perturbations, promoting cellular survival and recovery to homeostasis. We speculated that the very same stress mechanisms are activated during aging in post-mitotic cells. To test this hypothesis, we modified the model to be deficient in protein damage clearance and demonstrate the formation of energy stress. Contrasting the network’s pro-survival role in acute energetic challenges, conflicting responses in aging disrupt mitochondrial maintenance and contribute to a lockstep progression of decline when chronically activated. The model was analyzed by a local sensitivity analysis with respect to lifespan and makes predictions consistent with inhibitory and gain-of-function experiments in aging. Full article
(This article belongs to the Special Issue Systems Biology of Aging)
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