ArticleBiogerontology2018
A network-based meta-analysis for characterizing the genetic landscape of human aging.
Article in Biogerontology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Cross-Species and Human Inter-Tissue Network Analysis of Genes Implicated in Longevity and Aging Reveal Strong Support for Nutrient Sensing.Frontiers in genetics · 2021Article
- The quest to slow ageing through drug discovery.Nature reviews. Drug discovery · 2020Review
- Article
- DNA methylation QTL analysis identifies new regulators of human longevity.Human molecular genetics · 2020Article
- Article
- Genetic and epigenetic regulation of human aging and longevity.Biochimica et biophysica acta. Molecular basis of disease · 2019Review
- Identifying Potential Ageing-Modulating Drugs In Silico.Trends in endocrinology and metabolism: TEM · 2019Review
- Computational Drug Screening Identifies Compounds Targeting Renal Age-associated Molecular Profiles.Computational and structural biotechnology journal · 2019Article
- Using the drug-protein interactome to identify anti-ageing compounds for humans.PLoS computational biology · 2019Article
- Impact of Growth Hormone-Related Mutations on Mammalian Aging.Frontiers in genetics · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Great amounts of omics data are generated in aging research, but their diverse and partly complementary nature requires integrative analysis approaches for investigating aging processes and connections to age-related diseases. To establish a broader picture of the genetic and epigenetic landscape of human aging we performed a large-scale meta-analysis of 6600 human genes by combining 35 datasets that cover aging hallmarks, longevity, changes in DNA methylation and gene expression, and different age-related diseases. To identify biological relationships between aging-associated genes we incorporated them into a protein interaction network and characterized their network neighborhoods. In particular, we computed a comprehensive landscape of more than 1000 human aging clusters, network regions where genes are highly connected and where gene products commonly participate in similar processes. In addition to clusters that capture known aging processes such as nutrient-sensing and mTOR signaling, we present a number of clusters with a putative functional role in linking different aging processes as promising candidates for follow-up studies. To enable their detailed exploration, all datasets and aging clusters are made freely available via an interactive website ( https://gemex.eurac.edu/bioinf/age/ ).
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What OpenQuestion holds
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.