Evidence map›Paper›PMID 28329324›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2017

Age-Related Biomarkers in LLFS Families With Exceptional Cognitive Abilities.

Sandra Barral, Jatinder Singh, Erin Fagan, Stephanie Cosentino, Stacy L Andersen-Toomey, Mary K Wojczynski, Mary Feitosa, Candace M Kammerer, Nicole Schupf, Long Life Family Study

Open access · bronzeAbstract read
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Effect of Familial Longevity on Frailty and Sarcopenia: A Case-Control Study.International journal of environmental research and public health · 2023
    Observational
  4. Article
  5. NIA Long Life Family Study: Objectives, Design, and Heritability of Cross-Sectional and Longitudinal Phenotypes.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022
    Article
  6. Article
  7. Article
  8. 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

10 authors at 4 institutions in 1 country.

Sandra BarralG.H. Sergievsky Center, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, New York.
Jatinder SinghDepartments of Epidemiology and of Human Genetics, Center for Aging and Population Health University of Pittsburgh, Pennsylvania.
Erin FaganG.H. Sergievsky Center, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, New York.
Stephanie CosentinoG.H. Sergievsky Center, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, New York.
Stacy L Andersen-ToomeySection of Geriatrics, Department of Medicine, Boston Medical Center, Boston, University School of Medicine, Massachusetts.
Mary K WojczynskiDivision of Biostatistics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri.
Mary FeitosaDivision of Biostatistics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri.
Candace M KammererDepartments of Epidemiology and of Human Genetics, Center for Aging and Population Health University of Pittsburgh, Pennsylvania.
Nicole SchupfG.H. Sergievsky Center, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, New York.
Long Life Family Study
Columbia University Irving Medical Center · USCenter for Human Genetics · USWashington University in St. Louis · USBoston Medical Center · US

Funding

Long Life Family Study: Data Management and Coordinating CenterU01AG023746 · NIA · WASHINGTON UNIVERSITY · PI PROVINCE, MICHAEL A. · 2004 to 2018
$29.2M
TRAJECTORIES OF MORTALITY IN CAENORHABDITIS ELEGANSP01AG008761 · NIA · UNIVERSITY OF MINNESOTA TWIN CITIES · PI ROACH, DEBORAH A · 1990 to 2008
$17.5M
The Long Life Family StudyU01AG023755 · NIA · BOSTON MEDICAL CENTER · PI PERLS, THOMAS T · 2004 to 2018
$13.2M
Plasma beta-amyloid in long lived families: genetics and risk of ADU01AG023749 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI COSENTINO, STEPHANIE ANN, LEE, JOSEPH HYUNGWOO · 2004 to 2018
$13.0M
Multicenter Study on Exceptional Survival in Families: The Long Life Family StudyU01AG023744 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI NEWMAN, ANNE B., ZMUDA, JOSEPH M. · 2004 to 2018
$12.0M
Long Life Family Study: Duke Univ./Univ. of Southern Denmark Field CenterU01AG023712 · NIA · DUKE UNIVERSITY · PI CHRISTENSEN, KAARE · 2004 to 2018
$10.4M
NIA NIH HHS P01 AG008761NIA NIH HHS U01 AG023712NIA NIH HHS U01 AG023744NIA NIH HHS U01 AG023746NIA NIH HHS U01 AG023749NIA NIH HHS U01 AG023755
6 · The paper itself

Abstract

backgroundWe previously demonstrated familial aggregation of memory performance within the Long Life Family Study (LLFS), suggesting that exceptional cognition (EC) may contribute to their exceptional longevity. Here, we investigated whether LLFS families with EC may also exhibit more favorable profiles of other age-related biomarkers.

methodsNondemented offspring of the LLFS probands scoring 1.5 SD above the mean in a cognitive phenotype were classified as participants with EC. Families were categorized into EC (n = 28) and non-EC families (n = 433) based on having at least two EC offspring. Adjusted general estimating equations were used to investigate whether EC families had a better longevity and age-related biomarker profiles than non-EC families.

resultsEC families exhibited higher scores on familial longevity than non-EC families (average Family Longevity Selection Score of 12 ± 7 vs 9 ± 8, p = 2.5 × 10-14). EC families showed a better a metabolic profile (β = -0.63, SE = 0.23, p = .006) than non-EC families. The healthier metabolic profile is related to obesity in an age-dependent fashion. The prevalence of obesity in EC families is significantly lower compared with non-EC families (38% vs 51%, p = .015) among family members less than 80 years of age; however, among EC family members 80 years of age and older, the prevalence of obesity is higher (40% vs 38%, p = .011). EC families also showed better physical/pulmonary function than non-EC families (β = 0.51, SE = 0.25, p = .042).

conclusionsLong-live families with EC are characterized by a healthier metabolic profile which is related to the prevalence of obesity in the older family members. Our results suggest that familial exceptional longevity may be achieved through heterogeneous yet correlated pathways.

Indexed as

AgedAge FactorsBiomarkersCognitionFemaleHumansLongevityMaleMiddle AgedBiomarkersAge-related biomarkersExceptional cognitionExceptional longevity

Identifiers

PMID28329324
PMCPMC5861897
OpenAlexW2591618543

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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.