Evidence map›Paper›PMID 25063753›Full record

ArticleAging2014

The dynamic exome: acquired variants as individuals age.

Jasmin H Bavarva, Hongseok Tae, Lauren McIver, Enusha Karunasena, Harold R Garner

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 24% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. The MUC6/AP2A2 Locus and Its Relevance to Alzheimer's Disease: A Review.Journal of neuropathology and experimental neurology · 2020
    Review
  3. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Jasmin H BavarvaVirginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.
Hongseok Tae
Lauren McIver
Enusha Karunasena
Harold R Garner
Virginia Tech · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A singular genome used for inference into population-based studies is a standard method in genomics. Recent studies show that spontaneous genomic variants can propagate into new generations and these changes can contribute to individual cell aging with environmental and evolutionary elements contributing to cumulative genomic variation. However, the contribution of aging to genomic changes in tissue samples remains uncharacterized. Here, we report the impact of aging on individual human exomes and their implications. We found the human genome to be dynamic, acquiring a varying number of mutations with age (5,000 to 50,000 in 9 to 16 years). This equates to a variation rate of 9.6x10(-7) to 8.4x10(-6) bp(-1) year(-1) for nonsynonymous single nucleotide variants and 2.0x10(-4) to 1.0x10(-3) locus(-1) year(-1) for microsatellite loci in these individuals. These mutations span across 3,000 to 13,000 genes, which commonly showed association with Wnt signaling and Gonadotropin releasing hormone receptor pathways, and indicated for individuals a specific and significant enrichment for increased risk for diabetes, kidney failure, cancer, Rheumatoid arthritis, and Alzheimer's disease--conditions usually associated with aging. The results suggest that "age" is an important variable while analyzing an individual human genome to extract individual-specific clinically significant information necessary for personalized genomics.

Indexed as

AdolescentAdultAgingExomeGenome, HumanHumansMiddle AgedMutationPolymorphism, Single Nucleotide

Identifiers

PMID25063753
PMCPMC4100812
OpenAlexW2182007586

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.