ReviewHuman genomics2009
Use of pathway information in molecular epidemiology.
Review in Human genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed.
- Praxis-BGM: clustering of omics data using semi-supervised transfer learning for Gaussian mixture models via natural-gradient variational inference.Bioinformatics (Oxford, England) · 2026Article
- Fecal sample biobanking for breast cancer research focused on the gut microbiome.medRxiv : the preprint server for health sciences · 2025Article
- Bayesian matrix completion for hypothesis testing.Journal of the Royal Statistical Society. Series C, Applied statistics · 2023Article
- Generalized infinite factorization models.Biometrika · 2022Article
- A Hierarchical Approach Using Marginal Summary Statistics for Multiple Intermediates in a Mendelian Randomization or Transcriptome Analysis.American journal of epidemiology · 2021Article
- Association of Fish Consumption and Mercury Exposure During Pregnancy With Metabolic Health and Inflammatory Biomarkers in Children.JAMA network open · 2020Article
- A Novel Unsupervised Algorithm for Biological Process-based Analysis on Cancer.Scientific reports · 2017Article
- Untangling the role of one-carbon metabolism in colorectal cancer risk: a comprehensive Bayesian network analysis.Scientific reports · 2017Article
- Using mathematical models to understand metabolism, genes, and disease.BMC biology · 2015Article
- A Candidate-Pathway Approach to Identify Gene-Environment Interactions: Analyses of Colon Cancer Risk and Survival.Journal of the National Cancer Institute · 2015Article
- Multiple comparisons in genetic association studies: a hierarchical modeling approach.Statistical applications in genetics and molecular biology · 2014Article
- Two-phase and family-based designs for next-generation sequencing studies.Frontiers in genetics · 2013Review
- A scalable, knowledge-based analysis framework for genetic association studies.BMC bioinformatics · 2013Article
- Biomarkers for smoking cessation.Clinical pharmacology and therapeutics · 2013Review
- Pathway-based personalized analysis of cancer.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- Chapter 15: disease gene prioritization.PLoS computational biology · 2013Article
- Importance of different types of prior knowledge in selecting genome-wide findings for follow-up.Genetic epidemiology · 2013Article
- Genome-wide gene-environment interaction analysis for asbestos exposure in lung cancer susceptibility.Carcinogenesis · 2012Article
- Multiple apical plasma membrane constituents are associated with susceptibility to meconium ileus in individuals with cystic fibrosis.Nature genetics · 2012Article
- Joint analysis for integrating two related studies of different data types and different study designs using hierarchical modeling approaches.Human heredity · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Candidate gene studies are generally motivated by some form of pathway reasoning in the selection of genes to be studied, but seldom has the logic of the approach been carried through to the analysis. Marginal effects of polymorphisms in the selected genes, and occasionally pairwise gene–gene or gene–environment interactions,are often presented, but a unified approach to modelling the entire pathway has been lacking. In this review, a variety of approaches to this problem is considered, focusing on hypothesis-driven rather than purely exploratory methods. Empirical modelling strategies are based on hierarchical models that allow prior knowledge about the structure of the pathway and the various reactions to be included as ‘prior covariates’. By contrast, mechanistic models aim to describe the reactions through a system of differential equations with rate parameters that can vary between individuals, based on their genotypes. Some ways of combining the two approaches are suggested and Bayesian model averaging methods for dealing with uncertainty about the true model form in either framework is discussed. Biomarker measurements can be incorporated into such analyses, and two-phase sampling designs stratified on some combination of disease, genes and exposures can be an efficient way of obtaining data that would be too expensive or difficult to obtain on a full candidate gene sample. The review concludes with some thoughts about potential uses of pathways in genome-wide association studies.
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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.