ReviewCurrent hypertension reports2000
Context-dependent genetic effects in hypertension.
Review in Current hypertension reports, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
13 citing papers in PubMed.
- SNPs-Panel Polymorphism Variations inBiomedicines · 2023Article
- An overview of population genetic data simulation.Journal of computational biology : a journal of computational molecular cell biology · 2012Review
- Overweight, air and noise pollution: Universal risk factors for pediatric pre-hypertension.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2011Article
- Identifying genetic interactions in genome-wide data using Bayesian networks.Genetic epidemiology · 2010Article
- Opportunities and limitations of genetic analysis of hypertensive rat strains.Journal of hypertension · 2009Review
- Genome-wide association of echocardiographic dimensions, brachial artery endothelial function and treadmill exercise responses in the Framingham Heart Study.BMC medical genetics · 2007Article
- Genetic Programming Neural Networks: A Powerful Bioinformatics Tool for Human Genetics.Applied soft computing · 2007Article
- GPNN: power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease.BMC bioinformatics · 2006Article
- Genetic variation and lipid metabolism: modulation by dietary factors.Current cardiology reports · 2005Review
- Routine Discovery of Complex Genetic Models using Genetic Algorithms.Applied soft computing · 2004Article
- Genetic polymorphisms of the beta-adrenergic system: association with essential hypertension and response to beta-blockade.The pharmacogenomics journal · 2004Article
- Lack of association between the G protein beta3 subunit gene and essential hypertension in Chinese: a case-control and a family-based study.Journal of molecular medicine (Berlin, Germany) · 2003Article
- Application of Genetic Algorithms to the Discovery of Complex Models for Simulation Studies in Human Genetics.Proceedings of the Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference · 2002Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is a growing frustration with the limitations and inconsistencies of single locus candidate gene association and linkage studies. This frustration is exacerbated by the knowledge that a large influx of genotypic and gene expression data is expected to emerge over the next 5 years, and we are not prepared for the type of multigenic conceptual framework that will be necessary to analyze that data. A review of the hypertension genetic literature reveals substantial evidence for the importance of both genetic and environmental contexts on the mapping between single locus polymorphisms and risk of disease. These trends indicate that the current reliance on simple single gene studies to elucidate the complex etiology of hypertension needs to undergo some kind of transformation. It is suggested that even a minor shift to a more systematic investigation of context-dependent effects will increase our understanding of the multidimensional genetic and environmental realities underneath current studies. This shift is also necessary if we are to gain a deeper understanding of the specific ways in which an individual's risk of hypertension is a consequence of the inter- actions among genes and environments.
Indexed as
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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.