The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Metabolomic Profiling for the Identification of Novel Biomarkers and Mechanisms Related to Common Cardiovascular Diseases: Form and Function
Open accessAbstract
C ardiovascular diseases (CVDs) are the leading cause of death worldwide, but their molecular etiology remains poorly understood, in part because they develop slowly as a result of a mixture of genetic and environmental factors.Given the complex nature of CVD, molecular profiling of processes more "proximal" to the disease than genetic markers may have great promise in revealing both "form" (novel biomarkers with clinical potential) and "function" (mechanisms of disease development) of CVD.CVD is often associated with conditions of perturbed energy homeostasis and metabolism, including obesity, insulin resistance, and diabetes.The strong relationship between CVD and certain circulating lipids such as cholesterol and triglycerides has been recognized for decades.However, beyond these well-established associations, there is a strong possibility that other links between metabolic dysregulation and CVD remain to be discovered, and as a corollary, that new metabolite signatures can be identified that enhance risk prediction models.Comprehensive metabolic profiling, or "metabolomics" is increasingly being applied to CVD, leading to recent discoveries with both form and function implications.Here we review recent progress in this rapidly expanding area.
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
Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization
Go, A. S., Chertow, G. M., Fan, D., McCulloch, C. E., & Hsu, C.-Y. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa041031 · Cited by 11,369
Newgard, C. B., An, J., Bain, J. R., Muehlbauer, M. J., Stevens, R. D., Lien, L. F., Haqq, A. M., Shah, S. H., Arlotto, M., Slentz, C. A., et al. (2009) · Cell Metabolism · doi:10.1016/j.cmet.2009.02.002 · Cited by 3,165
Self-citationA Common Variant on Chromosome 9p21 Affects the Risk of Myocardial Infarction
Helgadottir, A., Thorleifsson, G., Manolescu, A., Gretarsdottir, S., Blondal, T., Jonasdottir, A., Jonasdottir, A., Sigurdsson, A., Baker, A., Palsson, A., et al. (2007) · Science · doi:10.1126/science.1142842 · Cited by 1,594
Self-citationFrom noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus
Musunuru, K., Strong, A., Frank-Kamenetsky, M., Lee, N. E., Ahfeldt, T., Sachs, K. V., Li, X., Li, H., Kuperwasser, N., Ruda, V. M., et al. (2010) · Nature · doi:10.1038/nature09266 · Cited by 1,140
Interplay between lipids and branched-chain amino acids in development of insulin resistance
Newgard, C. B. (2012) · Cell Metabolism · doi:10.1016/j.cmet.2012.01.024 · Cited by 1,080
Self-citationHuman metabolic individuality in biomedical and pharmaceutical research
CARDIoGRAM, Suhre, K., Shin, S.-Y., Petersen, A.-K., Mohney, R. P., Meredith, D., Wägele, B., Altmaier, E., Deloukas, P., Erdmann, J., et al. (2011) · Nature · doi:10.1038/nature10354 · Cited by 1,017
Koves, T. R., Li, P., An, J., Akimoto, T., Slentz, D., Ilkayeva, O., Dohm, G. L., Yan, Z., Newgard, C. B., & Muoio, D. M. (2005) · Journal of Biological Chemistry · doi:10.1074/jbc.m507621200 · Cited by 464
Self-citationMetabolic signatures of exercise in human plasma
Lewis, G. D., Farrell, L., Wood, M. J., Martinovic, M., Arany, Z., Rowe, G. C., Souza, A., Cheng, S., McCabe, E. L., Yang, E., et al. (2010) · Science Translational Medicine · doi:10.1126/scitranslmed.3001006 · Cited by 432
Huffman, K. M., Shah, S. H., Stevens, R. D., Bain, J. R., Muehlbauer, M., Slentz, C. A., Tanner, C. J., Kuchibhatla, M., Houmard, J. A., Newgard, C. B., et al. (2009) · Diabetes Care · doi:10.2337/dc08-2075 · Cited by 410
Self-citationMuoio, D. M., Noland, R. C., Kovalik, J.-P., Seiler, S. E., Davies, M. N., DeBalsi, K. L., Ilkayeva, O. R., Stevens, R. D., Kheterpal, I., Zhang, J., et al. (2012) · Cell Metabolism · doi:10.1016/j.cmet.2012.04.005 · Cited by 372
Self-citation
Cited by
2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure
Yancy, C. W., Jessup, M., Bozkurt, B., Butler, J., Casey, D. E., Colvin, M. M., Drazner, M. H., Filippatos, G. S., Fonarow, G. C., Givertz, M. M., et al. (2017) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2017.04.025 · Cited by 3,418
Yancy, C. W., Jessup, M., Bozkurt, B., Butler, J., Casey, D. E., Colvin, M. M., Drazner, M. H., Filippatos, G. S., Fonarow, G. C., Givertz, M. M., et al. (2017) · Circulation · doi:10.1161/cir.0000000000000509 · Cited by 3,109
Livestock metabolomics and the livestock metabolome: A systematic review
Goldansaz, S. A., Guo, A. C., Sajed, T., Steele, M. A., Plastow, G. S., & Wishart, D. S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177675 · Cited by 379
Fischer, K., Kettunen, J., Würtz, P., Haller, T., Havulinna, A. S., Kangas, A. J., Soininen, P., Esko, T., Tammesoo, M.-L., Mägi, R., et al. (2014) · PLoS Medicine · doi:10.1371/journal.pmed.1001606 · Cited by 344
Wang, D. D., Toledo, E., Hruby, A., Rosner, B. A., Willett, W. C., Sun, Q., Razquin, C., Zheng, Y., Ruiz-Canela, M., Guasch-Ferré, M., et al. (2017) · Circulation · doi:10.1161/circulationaha.116.024261 · Cited by 327
Metadata
- Authors
- Shah, S. H., Kraus, W. E., & Newgard, C. B.
- Venue
- Circulation
- Published
- 2012-08-28
- Volume
- 126
- Issue
- 9
- Pages
- 1110-1120
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W1974438296
- Cited by
- 370
- References
- 14
- FWCI
- 7.09
- Type
- journal article
- Language
- en
- Open access
- bronze
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Metabolomic Profiling for the Identification of Novel Biomarkers and Mechanisms Related to Common Cardiovascular Diseases: Form and Function. https://app.cochat.ai/papers/10.1161/circulationaha.111.060368
- The paper
- Shah, S. H., Kraus, W. E., & Newgard, C. B. (2012). Metabolomic Profiling for the Identification of Novel Biomarkers and Mechanisms Related to Common Cardiovascular Diseases: Form and Function. Circulation. https://doi.org/10.1161/circulationaha.111.060368
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.
