ReviewPhysiological genomics2018
Emerging applications of genome-editing technology to examine functionality of GWAS-associated variants for complex traits.
Review in Physiological genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- A glance at the application of CRISPR/Cas9 gene-editing technology in cardiovascular diseases.Journal of cardiovascular and thoracic research · 2022Review
- Review
- Using CRISPR to understand and manipulate gene regulation.Development (Cambridge, England) · 2021Review
- Update on SLC6A14 in lung and gastrointestinal physiology and physiopathology: focus on cystic fibrosis.Cellular and molecular life sciences : CMLS · 2020Review
- Review
- Dysregulated Transcriptional Control in Prostate Cancer.International journal of molecular sciences · 2019Review
- Programmable Molecular Scissors: Applications of a New Tool for Genome Editing in Biotech.Molecular therapy. Nucleic acids · 2019Review
- Post-GWAS in prostate cancer: from genetic association to biological contribution.Nature reviews. Cancer · 2019Review
- A New Era of Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated Protein 9 Gene Editing Technology in Cardiovascular Diseases: Opportunities, Challenges, and Perspectives.Heart views : the official journal of the Gulf Heart AssociationReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Over the last decade, genome-wide association studies (GWAS) have propelled the discovery of thousands of loci associated with complex diseases. The focus is now turning toward the function of these association signals, determining the causal variant(s) among those in strong linkage disequilibrium, and identifying their underlying mechanisms, such as long-range gene regulation. Genome-editing techniques utilizing zinc-finger nucleases (ZFN), transcription activator-like effector nucleases (TALENs), and clustered regularly-interspaced short palindromic repeats with Cas9 nuclease (CRISPR-Cas9) are becoming the tools of choice to establish functionality for these variants, due to the ability to assess effects of single variants in vivo. This review will discuss examples of how these technologies have begun to aid functional analysis of GWAS loci for complex traits such as cardiovascular disease, Type 2 diabetes, cancer, obesity, and autoimmune disease. We focus on analysis of variants occurring within noncoding genomic regions, as these comprise the majority of GWAS variants, providing the greatest challenges to determining functionality, and compare editing strategies that provide different levels of evidence for variant functionality. The review describes molecular insights into some of these potentially causal variants and how these may relate to the pathology of the trait and look toward future directions for these technologies in post-GWAS analysis, such as base-editing.
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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.