Evidence map›Paper›PMID 30150289›Full record

ArticleGenetics2018

Accurate Genomic Prediction of Human Height.

Louis Lello, Steven G Avery, Laurent Tellier, Ana I Vazquez, Gustavo de Los Campos, Stephen D H Hsu

Erratum issuedAbstract read
In one paragraph

Article in Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing 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

77 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Forensic genetics in the omics era.Nature reviews. Genetics · 2026
    Review
  5. Article
  6. Article
  7. Consent and its discontents: the case of UK Biobank.Medicine, health care, and philosophy · 2025
    Article
  8. Article
  9. [Application of HIrisPlex-S System in Forensic DNA Phenotyping].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025
    Article
  10. Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Observational
  19. Article
  20. Article

17 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Louis LelloDepartment of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824.
Steven G AveryDepartment of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824.
Laurent TellierDepartment of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824.
Ana I VazquezDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan 48824.
Gustavo de Los CamposDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan 48824.ORCID 0000-0001-5692-7129
Stephen D H HsuDepartment of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824 hsu@msu.edu.

Funding

Statistical Tools for Whole-Genome Prediction of Complex Traits and DiseasesR01GM101219 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DE LOS CAMPOS, GUSTAVO · 2012 to 2017
$1.6M
Factors Affecting Prediction Accuracy of Complex Human Traits and DiseasesR01GM099992 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DE LOS CAMPOS, GUSTAVO · 2012 to 2015
$1.0M
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NIGMS NIH HHS R01 GM099992NIGMS NIH HHS R01 GM101219
6 · The paper itself

Abstract

We construct genomic predictors for heritable but extremely complex human quantitative traits (height, heel bone density, and educational attainment) using modern methods in high dimensional statistics (

Indexed as

Models, GeneticBody HeightGenome, HumanHumansMultifactorial InheritancePolymorphism, Single NucleotideQuantitative Trait, Heritablecomplex traitsgenomic predictionGenPredGWASheritabilityinvestigationpenalized regression

Identifiers

PMID30150289
PMCPMC6216598

What OpenQuestion holds

Textmetadata
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.