Institution
University of Texas Health Science Center at Houston
Education•Houston, Texas, United States•
About: University of Texas Health Science Center at Houston is a education organization based out in Houston, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 27309 authors who have published 42520 publications receiving 2151596 citations. The organization is also known as: UTHealth & The UT Health Science Center at Houston.
Topics: Population, Poison control, Cancer, Stroke, Health care
Papers published on a yearly basis
Papers
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TL;DR: Treated mice developed a considerably greater number of polyps in the colon but not in the small intestine, indicating that PPARγ activation may provide a molecular link between a high-fat diet and increased risk of colorectal cancer.
Abstract: A high-fat diet increases the risk of colon, breast and prostate cancer. The molecular mechanism by which dietary lipids promote tumorigenesis is unknown. Their effects may be mediated at least in part by the peroxisome proliferator-activated receptors (PPARs). These ligand-activated nuclear receptors modulate gene expression in response to fatty acids, lipid-derived metabolites and antidiabetic drugs. To explore the role of the PPARs in diet-induced carcinogenesis, we treated mice predisposed to intestinal neoplasia with a synthetic PPARgamma ligand. Reflecting the pattern of expression of PPARgamma in the gastrointestinal tract, treated mice developed a considerably greater number of polyps in the colon but not in the small intestine, indicating that PPARgamma activation may provide a molecular link between a high-fat diet and increased risk of colorectal cancer.
581 citations
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University of Pennsylvania1, University College London2, University of Warwick3, University of Bristol4, McMaster University5, Glenfield Hospital6, University of London7, University of Glasgow8, Utrecht University9, University of Amsterdam10, University of Edinburgh11, University of Leeds12, University of North Carolina at Chapel Hill13, Baylor College of Medicine14, University of Vermont15, University of Texas Health Science Center at Houston16, Harvard University17, University of Washington18, University of Minnesota19, Stanford University20, University of Groningen21, Lund University22, University of Ulm23, University of Oxford24, University of Mississippi25, University of Virginia26, Fred Hutchinson Cancer Research Center27
TL;DR: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.
Abstract: AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.
579 citations
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TL;DR: This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype, providing insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelia phenotypes.
Abstract: Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.
579 citations
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Johns Hopkins University1, University of Washington2, Erasmus University Rotterdam3, National Institutes of Health4, Boston University5, University of Iceland6, University of Texas Health Science Center at Houston7, Geneva College8, Cedars-Sinai Medical Center9, Tufts University10, Harvard University11, University of California, San Francisco12
TL;DR: These findings provide new insights into CKD pathogenesis and underscore the importance of common genetic variants influencing renal function and disease.
Abstract: Caroline Fox and colleagues report results of a genome-wide association study to identify common variants associated with indices of renal function. They show that variants at UMOD, a gene previously implicated in rare monogenic forms of kidney disease, are associated with risk of chronic kidney disease in the general population.
578 citations
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TL;DR: A genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry finds a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
Abstract: Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
576 citations
Authors
Showing all 27450 results
Name | H-index | Papers | Citations |
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Paul M. Ridker | 233 | 1242 | 245097 |
Eugene Braunwald | 230 | 1711 | 264576 |
Eric N. Olson | 206 | 814 | 144586 |
Hagop M. Kantarjian | 204 | 3708 | 210208 |
André G. Uitterlinden | 199 | 1229 | 156747 |
Gordon B. Mills | 187 | 1273 | 186451 |
Eric Boerwinkle | 183 | 1321 | 170971 |
Bruce M. Psaty | 181 | 1205 | 138244 |
Aaron R. Folsom | 181 | 1118 | 134044 |
Daniel R. Weinberger | 177 | 879 | 128450 |
Bharat B. Aggarwal | 175 | 706 | 116213 |
Richard A. Gibbs | 172 | 889 | 249708 |
Russel J. Reiter | 169 | 1646 | 121010 |
James F. Sallis | 169 | 825 | 144836 |
Steven N. Blair | 165 | 879 | 132929 |