Evidence map›Paper›PMID 30710575›Full record

ArticleMetabolism: clinical and experimental2019

A novel healthy metabolic phenotype developed among a cohort of families enriched for longevity.

Megan M Marron, Iva Miljkovic, Robert M Boudreau, Kaare Christensen, Mary F Feitosa, Joseph H Lee, Paola Sebastiani, Bharat Thyagarajan, Mary K Wojczynski, Joseph M Zmuda and 2 more

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in Metabolism: clinical and experimental, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. 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

12 authors at 5 institutions in 2 countries.

Megan M MarronDepartment of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Iva MiljkovicDepartment of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Robert M BoudreauDepartment of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Kaare ChristensenThe Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense, Denmark.
Mary F FeitosaDivision of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
Joseph H LeeTaub Institute for Research on Alzheimer's Disease and the Aging Brain, and Sergievsky Center, Columbia University Medical Center, New York, NY, USA.
Paola SebastianiDepartment of Biostatistics, Boston University, Boston, MA, USA.
Bharat ThyagarajanDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
Mary K WojczynskiDivision of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
Joseph M ZmudaDepartment of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Anne B NewmanDepartment of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Departments of Medicine and Clinical and Translational Science, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address: newmana@edc.pitt.edu.
Long Life Family Study
University of Pittsburgh · USBoston University · USColumbia University Irving Medical Center · USUniversity of Minnesota · USUniversity of Southern Denmark · DK

Funding

The Long Life Family StudyU19AG063893 · NIA · WASHINGTON UNIVERSITY · PI Stacy Andersen, KAARE CHRISTENSEN · 2019 to 2026
$125.4M
Long Life Family Study: Data Management and Coordinating CenterU01AG023746 · NIA · WASHINGTON UNIVERSITY · PI PROVINCE, MICHAEL A. · 2004 to 2018
$29.2M
Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategiesUH3AG064704 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI PERLS, THOMAS T, SEBASTIANI, PAOLA · 2022 to 2025
$14.7M
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
TRAINING IN THE EPIDEMIOLOGY OF AGINGT32AG000181 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI STROTMEYER, ELSA S. · 1989 to 2025
$6.2M
NIA NIH HHS T32 AG000181NIA NIH HHS U01 AG023712NIA NIH HHS U01 AG023744NIA NIH HHS U01 AG023746NIA NIH HHS U01 AG023749NIA NIH HHS U01 AG023755NIA NIH HHS U19 AG063893NIA NIH HHS UH3 AG064704
6 · The paper itself

Abstract

backgroundLong-lived individuals and their offspring have healthier metabolic characteristics than expected, such as more favorable levels of fasting glucose, insulin, and lipids than controls without longevity. Dysregulation in metabolic pathways has also shown to predict accelerated aging. Using information from the Long Life Family Study (LLFS), a multi-center study of two-generation families selected for exceptional longevity, we developed an indicator of healthy metabolism to determine whether metabolic health was more prevalent in a subset of LLFS families and whether it was heritable and associated with other metrics of healthy aging.

methodsA Latent Profile Analysis was applied to age- and gender-adjusted z-scores of fasting levels of glucose, insulin, triglycerides, and high-density lipoprotein cholesterol, body mass index, waist circumference, interleukin-6, and C-reactive protein. Families were defined as meeting the healthy metabolic phenotype if ≥2 and ≥50% of their offspring were classified into a latent subgroup with a profile of healthier metabolic markers than expected given age and gender relative to all LLFS offspring.

resultsThe log odds of being classified into the latent subgroup with a healthy profile of metabolic markers was heritable (h

conclusionsThe better cognition, pulmonary function, and physical performance among probands from families with the healthy metabolic phenotype may indicate that this subset of LLFS families have a more extreme longevity phenotype than other LLFS families since cognitive, physical, and pulmonary function are top mortality predictors for older adults. Future work is needed to determine if rare or protective alleles confer a healthy metabolic phenotype in this subset of LLFS families with exceptional metabolism.

Indexed as

Family HealthCognitionHealthy AgingHumansLongevityLungMetabolismPhenotypeCognitionHealthy agingLongevityMetabolism

Identifiers

PMID30710575
PMCPMC7099575
OpenAlexW2914790723

What OpenQuestion holds

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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.