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Candidate gene resequencing to identify rare, pedigree-specific variants influencing healthy aging phenotypes in the long life family study

Overview of attention for article published in BMC Geriatrics, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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1 news outlet
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1 X user
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1 Facebook page

Citations

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18 Dimensions

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54 Mendeley
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Title
Candidate gene resequencing to identify rare, pedigree-specific variants influencing healthy aging phenotypes in the long life family study
Published in
BMC Geriatrics, April 2016
DOI 10.1186/s12877-016-0253-y
Pubmed ID
Authors

Todd E. Druley, Lihua Wang, Shiow J. Lin, Joseph H. Lee, Qunyuan Zhang, E. Warwick Daw, Haley J. Abel, Sara E. Chasnoff, Enrique I. Ramos, Benjamin T. Levinson, Bharat Thyagarajan, Anne B. Newman, Kaare Christensen, Richard Mayeux, Michael A. Province

Abstract

The Long Life Family Study (LLFS) is an international study to identify the genetic components of various healthy aging phenotypes. We hypothesized that pedigree-specific rare variants at longevity-associated genes could have a similar functional impact on healthy phenotypes. We performed custom hybridization capture sequencing to identify the functional variants in 464 candidate genes for longevity or the major diseases of aging in 615 pedigrees (4,953 individuals) from the LLFS, using a multiplexed, custom hybridization capture. Variants were analyzed individually or as a group across an entire gene for association to aging phenotypes using family based tests. We found significant associations to three genes and nine single variants. Most notably, we found a novel variant significantly associated with exceptional survival in the 3' UTR OBFC1 in 13 individuals from six pedigrees. OBFC1 (chromosome 10) is involved in telomere maintenance, and falls within a linkage peak recently reported from an analysis of telomere length in LLFS families. Two different algorithms for single gene associations identified three genes with an enrichment of variation that was significantly associated with three phenotypes (GSK3B with the Healthy Aging Index, NOTCH1 with diastolic blood pressure and TP53 with serum HDL). Sequencing analysis of family-based associations for age-related phenotypes can identify rare or novel variants.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 4%
Spain 1 2%
Unknown 51 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 22%
Other 6 11%
Student > Ph. D. Student 6 11%
Professor > Associate Professor 6 11%
Student > Doctoral Student 5 9%
Other 12 22%
Unknown 7 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 20%
Agricultural and Biological Sciences 9 17%
Medicine and Dentistry 8 15%
Computer Science 5 9%
Nursing and Health Professions 3 6%
Other 7 13%
Unknown 11 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 April 2016.
All research outputs
#3,210,587
of 23,323,574 outputs
Outputs from BMC Geriatrics
#821
of 3,313 outputs
Outputs of similar age
#53,197
of 302,073 outputs
Outputs of similar age from BMC Geriatrics
#12
of 48 outputs
Altmetric has tracked 23,323,574 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,313 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one has gotten more attention than average, scoring higher than 74% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 302,073 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.