Evidence map›Paper›PMID 10486337›Full record

ArticleAmerican journal of human genetics1999

Genes, demography, and life span: the contribution of demographic data in genetic studies on aging and longevity.

A I Yashin, G De Benedictis, J W Vaupel, Q Tan, K F Andreev, I A Iachine, M Bonafe, M DeLuca, S Valensin, L Carotenuto and 1 more

Abstract read
In one paragraph

Article in American journal of human genetics, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

45 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

11 authors.

A I YashinMax Planck Institute for Demographic Research, Rostock, Germany. yashin@demogr.mpg.de
G De Benedictis
J W Vaupel
Q Tan
K F Andreev
I A Iachine
M Bonafe
M DeLuca
S Valensin
L Carotenuto
C Franceschi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In population studies on aging, the data on genetic markers are often collected for individuals from different age groups. The purpose of such studies is to identify, by comparison of the frequencies of selected genotypes, "longevity" or "frailty" genes in the oldest and in younger groups of individuals. To address questions about more-complicated aspects of genetic influence on longevity, additional information must be used. In this article, we show that the use of demographic information, together with data on genetic markers, allows us to calculate hazard rates, relative risks, and survival functions for respective genes or genotypes. New methods of combining genetic and demographic information are discussed. These methods are tested on simulated data and then are applied to the analysis of data on genetic markers for two haplogroups of human mtDNA. The approaches suggested in this article provide a powerful tool for analyzing the influence of candidate genes on longevity and survival. We also show how factors such as changes in the initial frequencies of candidate genes in subsequent cohorts, or secular trends in cohort mortality, may influence the results of an analysis.

Indexed as

DemographyAgingComputer SimulationCross-Sectional StudiesDNA, MitochondrialGene FrequencyGenotypeHaplotypesHumansItalyLikelihood FunctionsLongevityLongitudinal StudiesModels, GeneticSensitivity and SpecificitySurvival RateDNA, Mitochondrial

Identifiers

PMID10486337
PMCPMC1288251

What OpenQuestion holds

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Registered trials

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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.