Genes Related to Human Aging from Microarray Studies in Mammals

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This dataset is a manually curated database of genetic associations of gene expression signatures of aging from a meta-analysis of microarray studies in mammals that reflect current knowledge of the genetics of human aging and longevity. This dataset comes from the GenAge (Genetic Aging) section of the Human Ageing Genomic Resources (HAGR) which is a repository containing information about the genetics of human aging. Information is obtained from modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses.

Complexity

This dataset of genes associated with longevity or aging in model organisms is essentially a list of genes with one or a few key references, a brief description of the phenotype or effects of genetic manipulations of the gene, human homologues of the gene, and a few external links. For a gene to be featured, its association with aging and/or longevity must be unambiguous, and hence most genes were selected based on genetic manipulations and not mere correlations, such as a gene’s upregulation with age, in which causality is impossible to determine.

Gene expression changes likely play important roles in aging and could serve as biomarkers of physiological decline and disease, yet age-related gene expression profiles tend to be noisy, making it difficult to identify key genes and processes. In this work, a meta-analysis of 27 age-related gene expression profiles from mice, rats, and humans was done. By analyzing the combined profiles from these studies, common molecular signatures of aging were identified: genes consistently over – or underexpressed with age in multiple mammalian tissues and species. In this study, it was found that age-related gene expression changes most notably involve an overexpression of genes related to inflammation and the lysosome as well as an underexpression of genes related to mitochondrial energy metabolism.

Genes associated with longevity or aging from model organisms can be useful as a reference and educational resource for researchers. This dataset also serves as the primary resource for deriving the list of genes that may be associated with human aging. Typically, the best genes from model organisms serve as the basis for deriving the dataset of putative human aging-related genes.

The human dataset in GenAge is a curated database of genes that may regulate human aging or that at least might be considerably associated with the human aging phenotype. It is a functional genomics database designed to provide up-to-date information in the context of aging and molecular genetics.

Because the focus is on the fundamental aging process, what some authors call senescence, and not just age-related pathologies, the human dataset features primarily genes related to biological aging rather than genes that only affect longevity by having an impact on overall health. This is an important point because longevity can be influenced by factors unrelated to aging, and the distinction is crucial, albeit often difficult. (For those interested in genes associated with human longevity, please refer to the LongevityMap). Likewise, a gene is differentially expressed during aging is not by itself proof that this gene is causally involved in the aging process. Nonetheless, for researchers studying transcriptional changes with age, also available are genes commonly differentially expressed during mammalian aging which were identified by performing a meta-analysis of aging microarray data.

Each gene in the human dataset was selected after an extensive review of the literature. They were identified genes associated with aging in model organisms as well as those that may directly modulate aging in mammals, including humans. Each gene was selected or excluded based on its association with aging in the different model systems, with priority being given to organisms biologically and evolutionary more closely related to humans. Because the focus is on the genetic basis of human aging, there was no in-depth description of aging in model systems but was rather incorporated in the information gathered from multiple models to gather clues about the genetics of human aging.

In each human gene entry, the main reason for inclusion in the database is given. The following criteria are used:

1. Evidence directly linking the gene product to aging in humans (human)
2. Evidence directly linking the gene product to aging in a mammalian model organism (mammal)
3. Evidence directly linking the gene product to aging in a non-mammalian model organism (model)
4. Evidence directly linking the gene product to aging in a cellular model system (cell)
5. Evidence linking the gene or its product to human longevity and/or multiple age-related phenotypes (human link)
6. Evidence directly linking the gene product to the regulation or control of genes previously linked to aging (upstream)
7. Evidence linking the gene product to a pathway or mechanism linked to aging (functional)
8. Evidence showing the gene product to act downstream of a pathway, mechanism, or other gene product linked to aging (downstream)
9. Indirect or inconclusive evidence linking the gene product to aging (putative)

GenAge has its limits but the aim is to include the most relevant information, but not all the data are available. The human dataset in GenAge can be helpful in more classical genetic studies of aging and longevity. For example, if a given chromosomal region is identified, it is possible to look up which genes are present in that region. Although GenAge is not a bibliographic database, the bibliographic references in the human dataset can be a useful resource.

**Notes**:
Values of individual experiments represent the log2 ratio of the expression signal old / young normalized to common ages, as described in the Methods.
n Genes = number of experiments with gene expression measurements.
n Overexpressed = number of experiments with a significant overexpression using p < 0.05 as statistical cutoff (individual experiments are marked with *).
n Underexpressed = number of experiments with a significant underexpression using p < 0.05 as statistical cutoff (individual experiments are marked with *).
p value and q value were calculated for the combined profiles of all experiments, as described in the Methods.

Date Created

1997

Last Modified

2014-12-26

Version

2014-12-26

Update Frequency

Irregular

Temporal Coverage

1997-2014

Spatial Coverage

N/A

Source

John Snow Labs => Human Ageing Genomic Resources

Source License URL

John Snow Labs Standard License

Source License Requirements

N/A

Source Citation

de Magalhães et al.de Magalhaes, J. P., Curado, J., Church, G. M. (2009) Meta-analysis of age-related gene expression profiles identifies common signatures of aging. Bioinformatics 25875-881.

Keywords

Senescence, Reverse Aging, Telomeres, Human Genomics, SNP, Genetic Variant, Genetic Association, Longevity, Aging

Other Titles

Genes Related to Human Senescence from Microarray Studies in Mammals, Telomeres and Human Aging from Microarray Studies in Mammals, Human Genomics from Microarray Studies in Mammals Genetic testing

Name Description Type Constraints
Entrez_Gene_IDGeneID is a unique identifier that is assigned to a gene record in Entrez Gene. Entry number with individual genes starting with single integer digits.integerrequired : 1 level : Nominal
Gene_NameThe recommended name used to officially represent a gene.string-
Gene_SymbolGene symbol of the gene associated with aging or gene studied. The official gene symbol approved by the HAGR.string-
Gene_Microarray_StudyType Stringrequired : 1
Human_BrainHuman brain aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Human_KidneyHuman kidney aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Human_Muscle_1Human muscle 1 aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Human_Muscle_2Human muscle 2 aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_BrainMouse brain aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_CochleaMouse cochlea aging microarray data obtained from one of the 27 publicly available studies in mice, rats, and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_EyeMouse eye aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_HeartMouse heart aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_HematopoieticMouse hematopoietic aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_HippocampusMouse hippocampus aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_KidneyMouse kidney aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_LiverMouse liver aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_LungMouse lung aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_MuscleMouse muscle aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_MyoblastMouse myoblast aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Mouse_NeocortexMouse neocortex aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_CardiacRat cardiac aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_ExtraocularRat extraocular aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_GliaRat glia aging microarray data obtained from one of the 27 publicly available studies in mice, rats, and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_Hippocampal_CA1_1Rat hippocampal CA1 1 aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_Hippocampal_CA1_2Rat hippocampal CA1 2 aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_HippocampusRat hippocampus aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_LaryngeRat larynge aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_MuscleRat muscle aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_OculomotorRat oculomotor aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_SpinalRat spinal aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Rat_StromalRat stromal aging microarray data obtained from one of the 27 publicly available studies in mice, rats and humans from GAN and GEO, used in the meta-analysis of age-related gene expression profiles performed in this studystring-
Genes_Sample_SizeGenes sample population used for the study; the number of experiments with gene expression measurements.integerrequired : 1 level : Ordinal
Overexpressed_Sample_SizeGenes overexpressed sample population used for the study; the number of experiments with a significant overexpression using p < 0.05 as a statistical cutoff (individual experiments are marked with *).integerlevel : Ordinal
Underexpressed_Sample_SizeGenes underexpressed sample population used for the study; the number of experiments with a significant underexpression using p < 0.05 as a statistical cutoff (individual experiments are marked with *).integerlevel : Ordinal
Probability_ValueThe probability or p-value of finding the observed, or more extreme, results when the null hypothesis of a study question is true. Calculated for the combined profiles of all experiments, as described in the Methods.stringrequired : 1
False_Discovery_Rate_ValueThe False Discovery Rate or q-value is the proportion of false positives you can expect to get from a test. Calculated for the combined profiles of all experiments, as described in the Methods.numberrequired : 1 level : Ratio
Entrez_Gene_IDGene_NameGene_SymbolGene_Microarray_StudyHuman_BrainHuman_KidneyHuman_Muscle_1Human_Muscle_2Mouse_BrainMouse_CochleaMouse_EyeMouse_HeartMouse_HematopoieticMouse_HippocampusMouse_KidneyMouse_LiverMouse_LungMouse_MuscleMouse_MyoblastMouse_NeocortexRat_CardiacRat_ExtraocularRat_GliaRat_Hippocampal_CA1_1Rat_Hippocampal_CA1_2Rat_HippocampusRat_LaryngeRat_MuscleRat_OculomotorRat_SpinalRat_StromalGenes_Sample_SizeOverexpressed_Sample_SizeUnderexpressed_Sample_SizeProbability_ValueFalse_Discovery_Rate_Value
436430Genes Underexpressed-0.4789*-0.3628*-0.4269*339.86111E-050.09046356
3696integrin, beta 8ITGB8Genes Overexpressed0.2640*0.4603*-0.15741.6031*-0.2456-0.2081630.0016657840.146529028
84025Genes Overexpressed-1.1042-0.2630.1719*0.67120.0337-0.58120.05591.9594*1.7842*0.51771030.0087198530.351561131
99104expressed sequence AI852064Mouse:AI852064Genes Underexpressed-0.5519*1.3770*-1.0181*3120.0062060980.407094508
295217SNAP-associated proteinRat:SnapapGenes Overexpressed0.25860.1755*0.2145*0.2030*0.0188530.0008619760.111562377
24145pannexin 1PANX1Genes Overexpressed0.2485-0.12350.08131.3307*0.0065-1.72010.12611.9016*2.3311*930.006314910.294403689
71073RIKEN cDNA 4933421O10 geneMouse:4933421O10RikGenes Overexpressed-3.9934*1.27911.0581*0.3958*4210.0115319990.430182157
299944hypothetical LOC299944Rat:RGD1304605Genes Underexpressed-0.3297*-0.1093-0.1911*-0.3184*-0.4572530.0009190370.233829414
57674ring finger protein 213RNF213Genes Overexpressed0.7514*0.3118*0.2191-0.02160.3825*0.4049*-0.4545740.0001308320.027452229
11214A kinase (PRKA) anchor protein 13AKAP13Genes Overexpressed0.0160.1899*0.42970.4926*1.0478*0.1101630.0016657840.143121376