Evidence map›Paper›PMID 28181587›Full record

ArticleScientific reports2017

Using information of relatives in genomic prediction to apply effective stratified medicine.

S Hong Lee, W M Shalanee P Weerasinghe, Naomi R Wray, Michael E Goddard, Julius H J van der Werf

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–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

29 citing papers in PubMed.

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  8. Factors affecting accuracy of estimated effective number of chromosome segments for numerically small breeds.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2021
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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

5 authors.

S Hong LeeSchool of Environmental and Rural Science, University of New England, NSW 2351, Australia.
W M Shalanee P WeerasingheSchool of Environmental and Rural Science, University of New England, NSW 2351, Australia.
Naomi R WrayThe Centre of Neurogenetics and Statistical Genomics, Queensland Brain Institute, The University of Queensland, QLD 4072, Australia.
Michael E GoddardFaculty of Land and Food Resources, University of Melbourne, Melbourne, Australia.
Julius H J van der WerfSchool of Environmental and Rural Science, University of New England, NSW 2351, Australia.

Funding

SNP HEALTH ASSOCIATION RESOURCE (SHARE)N02HL64278 · NHLBI · PI CHIN, SIANG · 2007 to 2007
$9.2M
Lifespan Psychosocial Profiles and Biological Pathways to Bone StrengthR01AG033067 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CRANDALL, CAROLYN JANET, KARLAMANGLA, ARUN S · 2009 to 2012
$1.4M
SLEEP AND ENTRAINMENT OF SCN FUNCTIONR01HL064278 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI STROHL, KINGMAN PERKINS · 1999 to 2002
$871k
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N02HL64278NIA NIH HHS R01 AG033067
6 · The paper itself

Abstract

Genomic prediction shows promise for personalised medicine in which diagnosis and treatment are tailored to individuals based on their genetic profiles for complex diseases. We present a theoretical framework to demonstrate that prediction accuracy can be improved by targeting more informative individuals in the data set used to generate the predictors ("discovery sample") to include those with genetically close relationships with the subjects put forward for risk prediction. Increase of prediction accuracy from closer relationships is achieved under an additive model and does not rely on any family or interaction effects. Using theory, simulations and real data analyses, we show that the predictive accuracy or the area under the receiver operating characteristic curve (AUC) increased exponentially with decreasing effective size (N

Indexed as

FamilyComputer SimulationGenetic Diseases, InbornGenomicsHumansPrecision MedicineRisk AssessmentROC CurveStatistics as Topic

Identifiers

PMID28181587
PMCPMC5299615

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.