ReviewNature reviews. Genetics2009
Detecting gene-gene interactions that underlie human diseases.
Review in Nature reviews. Genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 679 papers, 4 of them syntheses that pooled 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.
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
679 citing papers in PubMed, 4 syntheses or guidelines pooled it, 1,370 citations in OpenAlex.
- Impact of Gene Modifiers on Cystic Fibrosis Phenotypic Profiles: A Systematic Review.Human mutation · 2024Pooled it
- Machine learning for genetic prediction of psychiatric disorders: a systematic review.Molecular psychiatry · 2021Pooled it
- Detecting fitness epistasis in recently admixed populations with genome-wide data.BMC genomics · 2020Pooled it
- Detecting epistasis within chromatin regulatory circuitry reveals CAND2 as a novel susceptibility gene for obesity.International journal of obesity (2005) · 2019Pooled it
- An epistasis between dopaminergic and oxytocinergic systems confers risk of post-traumatic stress disorder in a traumatized Chinese cohort.Scientific reports · 2019Trial
- Association ofAnnals of medicine · 2026Article
- Interaction between smoking andMultiple sclerosis (Houndmills, Basingstoke, England) · 2026Article
- Epistasis and co-adaptation in bacterial genome evolution.Nature reviews. Genetics · 2026Review
- Novel Alzheimer's disease-associated variants and genetic interactions identified from UK biobank whole-exome sequencing data using IBI-DT.Scientific reports · 2026Article
- Article
- Genetic and immunological determinants of Pemphigus vulgaris: integrative analysis of HLA-DRB1 and FCGR2B variants.Immunogenetics · 2026Article
- Epistemic frontiers and the distinction between causality, information, and predictability in pattern recognition.Scientific reports · 2026Article
- A novel explainable deep-learning approach for network analysis of epistatic interactions.NAR genomics and bioinformatics · 2026Article
- The oligogenic inheritance test GCOD detects risk genes and their interactions in congenital heart defects.Genome research · 2026Article
- Phantom epistasis through the lens of genealogies.Genetics · 2026Article
- Pre-training genomic language model with variants for better modeling functional genomics.NPJ artificial intelligence · 2026Article
- Co-expression-wide association studies link genetically regulated interactions with complex traits.Nature communications · 2025Article
- Decoding the genomic symphony: unravelling brain disorders through data integration and machine learning.Molecular psychiatry · 2025Review
- Potential synthetic associations created by epistasis.Genome biology · 2025Article
- Article
619 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Following the identification of several disease-associated polymorphisms by genome-wide association (GWA) analysis, interest is now focusing on the detection of effects that, owing to their interaction with other genetic or environmental factors, might not be identified by using standard single-locus tests. In addition to increasing the power to detect associations, it is hoped that detecting interactions between loci will allow us to elucidate the biological and biochemical pathways that underpin disease. Here I provide a critical survey of the methods and related software packages currently used to detect the interactions between genetic loci that contribute to human genetic disease. I also discuss the difficulties in determining the biological relevance of statistical interactions.
Indexed as
Identifiers
What OpenQuestion holds
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.