ReviewAging cell2015
Integration of 'omics' data in aging research: from biomarkers to systems biology.
Review in Aging cell, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
71 citing papers in PubMed.
- Multiomics Approaches for Bacteriophage-Based Biocontrol Applications: A Review of Metabolomics, Transcriptomics, and Proteomics.BioMed research international · 2026Review
- Genetic, Socioecological, and Health Research on Extreme Longevity in Semisupercentenarians and Supercentenarians: A Scoping Review.Journal of aging research · 2026Article
- Python-Based Interactive Notebooks for Teaching AI and Data Science to Undergraduate Students in the Life Sciences.Methods in molecular biology (Clifton, N.J.) · 2026Article
- A multi-omics molecular landscape of 30 tissues in aging female rhesus macaques.Nature methods · 2025Article
- Plasma proteomic Alzheimer's risk score: Biological age clock and pseudotime trajectory.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Molecular Aspects of Geriatric Pharmacotherapy.Cells · 2025Review
- Article
- Plasma microRNA signatures of aging and their links to health outcomes and mortality: findings from a population-based cohort study.Genome medicine · 2025Article
- Biological age prediction using a DNN model based on pathways of steroidogenesis.Science advances · 2025Article
- ESPClust: unsupervised identification of modifiers for the effect size profile in omics association studies.Bioinformatics (Oxford, England) · 2025Article
- Multiomics of Aging and Aging-Related Diseases.International journal of molecular sciences · 2024Review
- Association Between Phenotypic Age and the Risk of Mortality in Patients With Heart Failure: A Retrospective Cohort Study.Clinical cardiology · 2024Article
- Biomarkers of Aging and Relevant Evaluation Techniques: A Comprehensive Review.Aging and disease · 2024Review
- A Review: Multi-Omics Approach to Studying the Association between Ionizing Radiation Effects on Biological Aging.Biology · 2024Review
- The Gompertz Law emerges naturally from the inter-dependencies between sub-components in complex organisms.Scientific reports · 2024Article
- How is Big Data reshaping preclinical aging research?Lab animal · 2023Review
- The Association of Epigenetic Age Acceleration and Multimorbidity at Age 90 in the Women's Health Initiative.The journals of gerontology. Series A, Biological sciences and medical sciences · 2023Article
- Efficient representations of binarized health deficit data: the frailty index and beyond.GeroScience · 2023Article
- Aging Hallmarks and the Role of Oxidative Stress.Antioxidants (Basel, Switzerland) · 2023Review
- Stimulation of RAS-dependent ROS signaling extends longevity by modulating a developmental program of global gene expression.Science advances · 2022Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Age is the strongest risk factor for many diseases including neurodegenerative disorders, coronary heart disease, type 2 diabetes and cancer. Due to increasing life expectancy and low birth rates, the incidence of age-related diseases is increasing in industrialized countries. Therefore, understanding the relationship between diseases and aging and facilitating healthy aging are major goals in medical research. In the last decades, the dimension of biological data has drastically increased with high-throughput technologies now measuring thousands of (epi) genetic, expression and metabolic variables. The most common and so far successful approach to the analysis of these data is the so-called reductionist approach. It consists of separately testing each variable for association with the phenotype of interest such as age or age-related disease. However, a large portion of the observed phenotypic variance remains unexplained and a comprehensive understanding of most complex phenotypes is lacking. Systems biology aims to integrate data from different experiments to gain an understanding of the system as a whole rather than focusing on individual factors. It thus allows deeper insights into the mechanisms of complex traits, which are caused by the joint influence of several, interacting changes in the biological system. In this review, we look at the current progress of applying omics technologies to identify biomarkers of aging. We then survey existing systems biology approaches that allow for an integration of different types of data and highlight the need for further developments in this area to improve epidemiologic investigations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.