ArticleAmerican journal of epidemiology2011
Impact of phenotype definition on genome-wide association signals: empirical evaluation in human immunodeficiency virus type 1 infection.
Article in American journal of epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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.
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Who cites it
12 citing papers in PubMed.
- Review
- Similarity and diversity of genetic architecture for complex traits between East Asian and European populations.BMC genomics · 2023Article
- Detecting Genotype-Population Interaction Effects by Ancestry Principal Components.Frontiers in genetics · 2020Article
- Systematic detection of positive selection in the human-pathogen interactome and lasting effects on infectious disease susceptibility.PloS one · 2018Article
- Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies.PLoS genetics · 2017Article
- Article
- Meta-analysis methods for genome-wide association studies and beyond.Nature reviews. Genetics · 2013Review
- The impact of phenotypic and genetic heterogeneity on results of genome wide association studies of complex diseases.PloS one · 2013Article
- Correction of phenotype misclassification based on high-discrimination genetic predictive risk models.Epidemiology (Cambridge, Mass.) · 2012Article
- HIV-1 dynamics: a reappraisal of host and viral factors, as well as methodological issues.Viruses · 2012Review
- Host genes important to HIV replication and evolution.Cold Spring Harbor perspectives in medicine · 2012Review
- Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Discussion on improving the power of genome-wide association studies to identify candidate variants and genes is generally centered on issues of maximizing sample size; less attention is given to the role of phenotype definition and ascertainment. The authors used genome-wide data from patients infected with human immunodeficiency virus type 1 (HIV-1) to assess whether differences in type of population (622 seroconverters vs. 636 seroprevalent subjects) or the number of measurements available for defining the phenotype resulted in differences in the effect sizes of associations between single nucleotide polymorphisms and the phenotype, HIV-1 viral load at set point. The effect estimate for the top 100 single nucleotide polymorphisms was 0.092 (95% confidence interval: 0.074, 0.110) log(10) viral load (log(10) copies of HIV-1 per mL of blood) greater in seroconverters than in seroprevalent subjects. The difference was even larger when the authors focused on chromosome 6 variants (0.153 log(10) viral load) or on variants that achieved genome-wide significance (0.232 log(10) viral load). The estimates of the genetic effects tended to be slightly larger when more viral load measurements were available, particularly among seroconverters and for variants that achieved genome-wide significance. Differences in phenotype definition and ascertainment may affect the estimated magnitude of genetic effects and should be considered in optimizing power for discovering new associations.
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