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Institution

University of Texas Health Science Center at Houston

EducationHouston, 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.


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Journal ArticleDOI
Hana Lango Allen1, Karol Estrada2, Guillaume Lettre3, Sonja I. Berndt4  +341 moreInstitutions (90)
14 Oct 2010-Nature
TL;DR: It is shown that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait, and indicates that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
Abstract: Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

1,768 citations

Journal ArticleDOI
17 Apr 1998-Cell
TL;DR: It is demonstrated that the nuclear receptor PPARγ is induced in human monocytes following exposure to oxLDL and is expressed at high levels in the foam cells of atherosclerotic lesions, and it is suggested that endogenous PParγ ligands may be important regulators of gene expression during atherogenesis.

1,717 citations

Journal ArticleDOI
TL;DR: This paper performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals.
Abstract: We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 - 10'8 and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.

1,705 citations

Journal ArticleDOI
04 Apr 2012-Nature
TL;DR: Results from de novo events and a large parallel case–control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors and support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold.
Abstract: Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

1,700 citations

Journal ArticleDOI
06 Jul 2012-Science
TL;DR: The findings suggest that most human variation is rare, not shared between populations, and that rare variants are likely to play a role in human health, and show that large sample sizes will be required to associate rare variants with complex traits.
Abstract: As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111× in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86% with a minor allele frequency less than 0.5%), previously unknown (82%), and population-specific (82%). On average, 2.3% of the 13,595 SNVs each person carried were predicted to affect protein function of ~313 genes per genome, and ~95.7% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.

1,680 citations


Authors

Showing all 27450 results

NameH-indexPapersCitations
Paul M. Ridker2331242245097
Eugene Braunwald2301711264576
Eric N. Olson206814144586
Hagop M. Kantarjian2043708210208
André G. Uitterlinden1991229156747
Gordon B. Mills1871273186451
Eric Boerwinkle1831321170971
Bruce M. Psaty1811205138244
Aaron R. Folsom1811118134044
Daniel R. Weinberger177879128450
Bharat B. Aggarwal175706116213
Richard A. Gibbs172889249708
Russel J. Reiter1691646121010
James F. Sallis169825144836
Steven N. Blair165879132929
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202342
2022231
20213,048
20202,807
20192,467
20182,224