ReviewAmerican journal of human genetics2009
Epistasis and its implications for personal genetics.
Review in American journal of human genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 200 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
200 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-analytic framework for detection of genetic interactions.Genetic epidemiology · 2016Pooled it
- An assessment of gene-by-gene interactions as a tool to unfold missing heritability in dyslexia.Human genetics · 2015Trial
- Determination of genotype combinations that can predict the outcome of the treatment of alcohol dependence using the 5-HT(3) antagonist ondansetron.The American journal of psychiatry · 2013Trial
- Revisiting retinal and macular degeneration in the genomics era.Nature reviews. Genetics · 2026Review
- Inference of fitness landscapes with heterogeneous patterns of epistasis across sites.bioRxiv : the preprint server for biology · 2026Article
- Novel Alzheimer's disease-associated variants and genetic interactions identified from UK biobank whole-exome sequencing data using IBI-DT.Scientific reports · 2026Article
- Association of Polymorphisms of Inflammatory-Relevant Genes with Cancer Risk.Current issues in molecular biology · 2026Article
- Inference and Visualization of Complex Genotype-Phenotype Maps.Molecular biology and evolution · 2026Article
- Epistatic contributions to human traits via transcription factor mechanisms.medRxiv : the preprint server for health sciences · 2025Article
- Inference and visualization of complex genotype-phenotype maps withbioRxiv : the preprint server for biology · 2025Article
- Learning sequence-function relationships with scalable, interpretable Gaussian processes.bioRxiv : the preprint server for biology · 2025Article
- Spotlight on amino acid changing mutations in the JAK-STAT pathway: from disease-specific mutation to general mutation databases.Scientific reports · 2025Article
- Modeling gene interactions in polygenic prediction via geometric deep learning.Genome research · 2025Article
- DNA-based prediction of external ear morphology in the Chinese population: an exploratory study.PeerJ · 2025Article
- Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens.Human genomics · 2024Review
- Distinct network patterns emerge from Cartesian and XOR epistasis models: a comparative network science analysis.BioData mining · 2024Article
- Multiome-wide Association Studies: Novel Approaches for Understanding Diseases.Genomics, proteomics & bioinformatics · 2024Review
- Combinatorial transcriptomic and genetic dissection of insulin/IGF-1 signaling-regulated longevity in Caenorhabditis elegans.Aging cell · 2024Article
- Distinct Network Patterns Emerge from Cartesian and XOR Epistasis Models: A Comparative Network Science Analysis.Research square · 2024Article
- Poor statistical power in population-based association study of gene interaction.BMC medical genomics · 2024Article
140 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity.
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Registered trials
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.