The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Little Fish, Big Data: Zebrafish as a Model for Cardiovascular and Metabolic Disease
Open accessAbstract
The burden of cardiovascular and metabolic diseases worldwide is staggering. The emergence of systems approaches in biology promises new therapies, faster and cheaper diagnostics, and personalized medicine. However, a profound understanding of pathogenic mechanisms at the cellular and molecular levels remains a fundamental requirement for discovery and therapeutics. Animal models of human disease are cornerstones of drug discovery as they allow identification of novel pharmacological targets by linking gene function with pathogenesis. The zebrafish model has been used for decades to study development and pathophysiology. More than ever, the specific strengths of the zebrafish model make it a prime partner in an age of discovery transformed by big-data approaches to genomics and disease. Zebrafish share a largely conserved physiology and anatomy with mammals. They allow a wide range of genetic manipulations, including the latest genome engineering approaches. They can be bred and studied with remarkable speed, enabling a range of large-scale phenotypic screens. Finally, zebrafish demonstrate an impressive regenerative capacity scientists hope to unlock in humans. Here, we provide a comprehensive guide on applications of zebrafish to investigate cardiovascular and metabolic diseases. We delineate advantages and limitations of zebrafish models of human disease and summarize their most significant contributions to understanding disease progression to date.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Lozano, R., Naghavi, M., Foreman, K., Lim, S., Shibuya, K., Aboyans, V., Abraham, J., Adair, T., Aggarwal, R., Ahn, S. Y., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61728-0 · Cited by 14,070
Murray, C. J. L., Vos, T., Lozano, R., Naghavi, M., Flaxman, A. D., Michaud, C., Ezzati, M., Shibuya, K., Salomon, J. A., Abdalla, S., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61689-4 · Cited by 8,888
Vos, T., Flaxman, A. D., Naghavi, M., Lozano, R., Michaud, C., Ezzati, M., Shibuya, K., Salomon, J. A., Abdalla, S., Aboyans, V., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61729-2 · Cited by 8,291
The new frontier of genome engineering with CRISPR-Cas9
Doudna, J. A., & Charpentier, E. (2014) · Science · doi:10.1126/science.1258096 · Cited by 7,062
O'Leary, N. A., Wright, M. W., Brister, J. R., Ciufo, S., Haddad, D., McVeigh, R., Rajput, B., Robbertse, B., Smith-White, B., Ako-Adjei, D., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1189 · Cited by 6,357
Leptin and the regulation of body weight in mammals
Friedman, J. M., & Halaas, J. L. (1998) · Nature · doi:10.1038/27376 · Cited by 5,405
The zebrafish reference genome sequence and its relationship to the human genome.
Howe, K., Clark, M. D., Torroja, C. F., Torrance, J., Berthelot, C., Muffato, M., Collins, J. E., Humphray, S., McLaren, K., Matthews, L., et al. (2013) · Nature · doi:10.1038/nature12111 · Cited by 5,100
CRISPR-Cas systems for editing, regulating and targeting genomes
Sander, J. D., & Joung, J. K. (2014) · Nature Biotechnology · doi:10.1038/nbt.2842 · Cited by 3,153
Raise standards for preclinical cancer research
Begley, C. G., & Ellis, L. M. (2012) · Nature · doi:10.1038/483531a · Cited by 2,979
Transient Regenerative Potential of the Neonatal Mouse Heart
Porrello, E. R., Mahmoud, A. I., Simpson, E., Hill, J. A., Richardson, J. A., Olson, E. N., & Sadek, H. A. (2011) · Science · doi:10.1126/science.1200708 · Cited by 2,545
Human Fatty Liver Disease: Old Questions and New Insights
Cohen, J. C., Horton, J. D., & Hobbs, H. H. (2011) · Science · doi:10.1126/science.1204265 · Cited by 2,089
Sirtuins as regulators of metabolism and healthspan
Houtkooper, R. H., Pirinen, E., & Auwerx, J. (2012) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3293 · Cited by 2,008
RNA-guided genetic silencing systems in bacteria and archaea
Wiedenheft, B., Sternberg, S. H., & Doudna, J. A. (2012) · Nature · doi:10.1038/nature10886 · Cited by 1,851
How were new medicines discovered?
Swinney, D. C., & Anthony, J. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3480 · Cited by 1,812
Haeussler, M., Schönig, K., Eckert, H., Eschstruth, A., Mianné, J., Renaud, J.-B., Schneider-Maunoury, S., Shkumatava, A., Teboul, L., Kent, J., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1012-2 · Cited by 1,756
New genetic loci link adipose and insulin biology to body fat distribution
The ADIPOGen Consortium, Shungin, D., The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The GEFOS Consortium, The GENIE Consortium, The, G. L. G. C., The, I. C. B. P., The International Endogene Consortium, Study, T. L. C., et al. (2015) · Nature · doi:10.1038/nature14132 · Cited by 1,580
Can Animal Models of Disease Reliably Inform Human Studies?
van der Worp, H. B., Howells, D. W., Sena, E. S., Porritt, M. J., Rewell, S., O'Collins, V., & Macleod, M. R. (2010) · PLoS Medicine · doi:10.1371/journal.pmed.1000245 · Cited by 1,354
Zebrafish heart regeneration occurs by cardiomyocyte dedifferentiation and proliferation
Jopling, C., Sleep, E., Raya, M., Martí, M., Raya, A., & Belmonte, J. C. I. (2010) · Nature · doi:10.1038/nature08899 · Cited by 1,333
Cas9 as a versatile tool for engineering biology
Mali, P., Esvelt, K. M., & Church, G. M. (2013) · Nature Methods · doi:10.1038/nmeth.2649 · Cited by 1,197
Sudden death associated with short-QT syndrome linked to mutations in HERG
Brugada, R., Hong, K., Dumaine, R., Cordeiro, J., Gaita, F., Borggrefe, M., Menendez, T. M., Brugada, J., Pollevick, G. D., Wolpert, C., et al. (2004) · Circulation · doi:10.1161/01.cir.0000109482.92774.3a · Cited by 847
mTORC1 controls the adaptive transition of quiescent stem cells from G0 to GAlert
Rodgers, J. T., King, K. Y., Brett, J. O., Cromie, M. J., Charville, G. W., Maguire, K. K., Brunson, C., Mastey, N., Liu, L., Tsai, C.-R., et al. (2014) · Nature · doi:10.1038/nature13255 · Cited by 776
Whole-organism lineage tracing by combinatorial and cumulative genome editing
McKenna, A., Findlay, G. M., Gagnon, J. A., Horwitz, M. S., Schier, A. F., & Shendure, J. (2016) · Science · doi:10.1126/science.aaf7907 · Cited by 766
A novel TALE nuclease scaffold enables high genome editing activity in combination with low toxicity
Mussolino, C., Morbitzer, R., Lütge, F., Dannemann, N., Lahaye, T., & Cathomen, T. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr597 · Cited by 714
Anderson, K. V., Jürgens, G., & Nüsslein-Volhard, C. (1985) · Cell · doi:10.1016/0092-8674(85)90274-0 · Cited by 691
Adipocyte inflammation is essential for healthy adipose tissue expansion and remodeling
Wernstedt Asterholm, I., Tao, C., Morley, T. S., Wang, Q. A., Delgado-Lopez, F., Wang, Z. V., & Scherer, P. E. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.05.005 · Cited by 668
SIRT1 Controls Endothelial Angiogenic Functions During Vascular Growth
Potente, M., Ghaeni, L., Baldessari, D., Mostoslavsky, R., Rossig, L., Dequiedt, F., Haendeler, J., Mione, M., Dejana, E., Alt, F. W., et al. (2007) · Genes & Development · doi:10.1101/gad.435107 · Cited by 608
Yang, X. W., Model, P., & Heintz, N. (1997) · Nature Biotechnology · doi:10.1038/nbt0997-859 · Cited by 544
The discovery of first-in-class drugs: origins and evolution
Eder, J., Sedrani, R., & Wiesmann, C. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4336 · Cited by 514
Zebrafish pigmentation mutations and the processes of neural crest development
Kelsh, R. N., Brand, M., Jiang, Y.-J., Heisenberg, C.-P., Lin, S., Haffter, P., Odenthal, J., Mullins, M. C., Eeden, F. J. M. V., Furutani-Seiki, M., et al. (1996) · Development · doi:10.1242/dev.123.1.369 · Cited by 455
Cellular dynamics in the muscle satellite cell niche
Bentzinger, C. F., Wang, Y. X., Dumont, N. A., & Rudnicki, M. A. (2013) · The EMBO Reports · doi:10.1038/embor.2013.182 · Cited by 398
Recurrent turnover of senescent cells during regeneration of a complex structure
Yun, M. H., Davaapil, H., & Brockes, J. P. (2015) · eLife · doi:10.7554/elife.05505 · Cited by 385
Phenothiazines induce PP2A-mediated apoptosis in T cell acute lymphoblastic leukemia
Gutierrez, A., Pan, L., Groen, R. W. J., Baleydier, F., Kentsis, A., Marineau, J., Grebliunaite, R., Kozakewich, E., Reed, C., Pflumio, F., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci65093 · Cited by 220
The QT Interval International GWAS Consortium (QT-IGC), Lundby, A., Rossin, E. J., Steffensen, A. B., Acha, M. R., Newton-Cheh, C., Pfeufer, A., Lynch, S. N., Olesen, S.-P., Brunak, S., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2997 · Cited by 71
Cited by
Sex determination, gonadal sex differentiation, and plasticity in vertebrate species
Nagahama, Y., Chakraborty, T., Paul-Prasanth, B., Ohta, K., & Nakamura, M. (2021) · Physiological Reviews · doi:10.1152/physrev.00044.2019 · Cited by 346
Gut, P., Matilainen, S., Meyer, J. G., Pällijeff, P., Richard, J., Carroll, C. J., Euro, L., Jackson, C. B., Isohanni, P., Minassian, B. A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19743-4 · Cited by 83
Self-citationPre-clinical Models of Metastasis in Pancreatic Cancer
Miquel, M., Zhang, S., & Pilarsky, C. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.748631 · Cited by 53
Xiao, Y., Hu, L., Duan, J., Che, H., Wang, W., Yuan, Y., Xu, J., Chen, D., & Zhao, S. (2024) · Environmental Pollution · doi:10.1016/j.envpol.2024.124022 · Cited by 49
Metadata
- Authors
- Gut, P., Reischauer, S., Stainier, D. Y. R., & Arnaout, R.
- Venue
- Physiological Reviews
- Publisher
- American Physiological Society
- Published
- 2017-07-01
- Volume
- 97
- Issue
- 3
- Pages
- 889-938
- ISSN
- 0031-9333 (ISSN-L)
- 1522-1210
- OpenAlex
- W2611783013
- Cited by
- 333
- References
- 33
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.