Evidence map›Paper›PMID 12592605›Full record

ArticleAmerican journal of human genetics2003

Improving the prediction of complex diseases by testing for multiple disease-susceptibility genes.

Quanhe Yang, Muin J Khoury, Lorenzo Botto, J M Friedman, W Dana Flanders

Erratum issuedAbstract read
In one paragraph

Article in American journal of human genetics, 2003. 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 50 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 4 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

50 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Multigene panels in prostate cancer risk assessment: a systematic review.Genetics in medicine : official journal of the American College of Medical Genetics · 2016
    Pooled it
  2. Guideline
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Article
  7. Article
  8. Genetic Bases of Complex Traits: From Quantitative Trait Loci to Prediction.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Summarizing polygenic risks for complex diseases in a clinical whole-genome report.Genetics in medicine : official journal of the American College of Medical Genetics · 2015
    Article
  14. Risk Classification with an Adaptive Naive Bayes Kernel Machine Model.Journal of the American Statistical Association · 2015
    Article
  15. Article
  16. Article
  17. Predictive genetic testing for complex diseases: a public health perspective.QJM : monthly journal of the Association of Physicians · 2014
    Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Quanhe YangNational Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. qyang@cdc.gov
Muin J Khoury
Lorenzo Botto
J M Friedman
W Dana Flanders

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies have argued that genetic testing will provide limited information for predicting the probability of common diseases, because of the incomplete penetrance of genotypes and the low magnitude of associated risks for the general population. Such studies, however, have usually examined the effect of one gene at time. We argue that disease prediction for common multifactorial diseases is greatly improved by considering multiple predisposing genetic and environmental factors concurrently, provided that the model correctly reflects the underlying disease etiology. We show how likelihood ratios can be used to combine information from several genetic tests to compute the probability of developing a multifactorial disease. To show how concurrent use of multiple genetic tests improves the prediction of a multifactorial disease, we compute likelihood ratios by logistic regression with simulated case-control data for a hypothetical disease influenced by multiple genetic and environmental risk factors. As a practical example, we also apply this approach to venous thrombosis, a multifactorial disease influenced by multiple genetic and nongenetic risk factors. Under reasonable conditions, the concurrent use of multiple genetic tests markedly improves prediction of disease. For example, the concurrent use of a panel of three genetic tests (factor V Leiden, prothrombin variant G20210A, and protein C deficiency) increases the positive predictive value of testing for venous thrombosis at least eightfold. Multiplex genetic testing has the potential to improve the clinical validity of predictive testing for common multifactorial diseases.

Indexed as

Genetic Diseases, InbornGenetic Predisposition to DiseaseGenotypeHumansLikelihood FunctionsModels, GeneticModels, StatisticalProbabilityRisk FactorsThrombophiliaVenous Thrombosis

Identifiers

PMID12592605
PMCPMC1180239

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.