Evidence map›Paper›PMID 14975075›Full record

ArticleBMC genetics2003

Quantitative trait linkage analysis of longitudinal change in body weight.

Astrid Golla, Konstantin Strauch, Johannes Dietter, Max P Baur

Open access · diamondAbstract read
In one paragraph

Article in BMC genetics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 31% 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

2 citing papers in PubMed, 8 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

4 authors at 2 institutions in 1 country.

Astrid GollaInstitut für Medizinische Biometrie, Informatik und Epidemiologie, Sigmund-Freud-Strasse 25, 53105 Bonn, Universität Bonn, Bonn, Germany. astrid.golla@uni-bonn.de
Konstantin Strauch
Johannes Dietter
Max P Baur
Institut für Medizinische Biometrie, Informatik und Epidemiologie · DEUniversity of Bonn · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the great strengths of the Framingham Heart Study data, provided for the Genetic Analysis Workshop 13, is the long-term survey of phenotypic data. We used this unique data to create new phenotypes representing the pattern of longitudinal change of the provided phenotypes, especially systolic blood pressure and body weight. We performed a linear regression of body weight and systolic blood pressure on age and took the slopes as new phenotypes for quantitative trait linkage analysis using the SOLAR package. There was no evidence for heritability of systolic blood pressure change. Heritability was estimated as 0.15 for adult life "body weight change", measured as the regression slope, and "body weight gain" (including only individuals with a positive regression slope), and as 0.22 for body weight "change up to 50" (regression slope of weight on age up to an age of 50). With multipoint analysis, two regions on the long arm of chromosome 8 showed the highest LOD scores of 1.6 at 152 cM for "body weight change" and of >1.9 around location 102 cM for "body weight gain" and "change up to 50". The latter two LOD scores almost reach the threshold for suggestive linkage. We conclude that the chromosome 8 region may harbor a gene acting on long-term body weight regulation, thereby contributing to the development of the metabolic syndrome.

Indexed as

AdultAdult ChildrenBody WeightCardiovascular DiseasesChromosomes, Human, Pair 8Cohort StudiesFemaleGenetic LinkageGenetic MarkersHumansLod ScoreLongitudinal StudiesMalePhenotypeQuantitative Trait LociWeight GainGenetic Markers

Identifiers

PMID14975075
PMCPMC1866508
OpenAlexW2042087762

What OpenQuestion holds

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LicenceCC BY
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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.