ReviewFrontiers in genetics2015
Implications of pleiotropy: challenges and opportunities for mining Big Data in biomedicine.
Review in Frontiers in genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies.BMC bioinformatics · 2019Pooled it
- A Comprehensive Assessment of the Shared Genetic Architecture between Myopia and Open-Angle Glaucoma.Ophthalmology science · 2026Article
- Pleiotropic germline PTEN mutations influence gastrulation through dysregulated AKT activation.NPJ genomic medicine · 2026Article
- Pleiotropy, epistasis and the genetic architecture of quantitative traits.Nature reviews. Genetics · 2024Review
- A novel approach to risk exposure and epigenetics-the use of multidimensional context to gain insights into the early origins of cardiometabolic and neurocognitive health.BMC medicine · 2023Article
- Leveraging the local genetic structure for trans-ancestry association mapping.American journal of human genetics · 2022Article
- Comparison of adaptive multiple phenotype association tests using summary statistics in genome-wide association studies.Human molecular genetics · 2021Article
- Total genetic contribution assessment across the human genome.Nature communications · 2021Article
- Penalized partial least squares for pleiotropy.BMC bioinformatics · 2021Article
- Genome-to-phenome research in rats: progress and perspectives.International journal of biological sciences · 2021Review
- A powerful method for pleiotropic analysis under composite null hypothesis identifies novel shared loci between Type 2 Diabetes and Prostate Cancer.PLoS genetics · 2020Article
- Genome-wide association study reveals the genetic basis of fiber quality traits in upland cotton (Gossypium hirsutum L.).BMC plant biology · 2020Article
- Multi-Omics Analysis of Diabetic Nephropathy Reveals Potential New Mechanisms and Drug Targets.Frontiers in genetics · 2020Article
- Bivariate logistic Bayesian LASSO for detecting rare haplotype association with two correlated phenotypes.Genetic epidemiology · 2019Article
- Integrating natural history collections and comparative genomics to study the genetic architecture of convergent evolution.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Review
- Big Data Analytics in Medicine and Healthcare.Journal of integrative bioinformatics · 2018Article
- The ubiquity of pleiotropy in human disease.Human genetics · 2018Article
- Foreword: Big Data and Its Application in Health Disparities Research.Ethnicity & disease · 2017Article
- Estimating Marginal Healthcare Costs Using Genetic Variants as Instrumental Variables: Mendelian Randomization in Economic Evaluation.PharmacoEconomics · 2016Article
- From integrative genomics to systems genetics in the rat to link genotypes to phenotypes.Disease models & mechanisms · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Pleiotropy arises when a locus influences multiple traits. Rich GWAS findings of various traits in the past decade reveal many examples of this phenomenon, suggesting the wide existence of pleiotropic effects. What underlies this phenomenon is the biological connection among seemingly unrelated traits/diseases. Characterizing the molecular mechanisms of pleiotropy not only helps to explain the relationship between diseases, but may also contribute to novel insights concerning the pathological mechanism of each specific disease, leading to better disease prevention, diagnosis and treatment. However, most pleiotropic effects remain elusive because their functional roles have not been systematically examined. A systematic investigation requires availability of qualified measurements at multilayered biological processes (e.g., transcription and translation). The rise of Big Data in biomedicine, such as high-quality multi-omics data, biomedical imaging data and electronic medical records of patients, offers us an unprecedented opportunity to investigate pleiotropy. There will be a great need of computationally efficient and statistically rigorous methods for integrative analysis of these Big Data in biomedicine. In this review, we outline many opportunities and challenges in methodology developments for systematic analysis of pleiotropy, and highlight its implications on disease prevention, diagnosis and treatment.
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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.