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Corsetti J.P.,University of Rochester | Ryan D.,University of Rochester | Rainwater D.L.,Southwest Foundation for Biomedical Research | Moss A.J.,University of Rochester | And 2 more authors.
Arteriosclerosis, Thrombosis, and Vascular Biology | Year: 2010

Objective: To investigate the roles of inflammation and a cholesteryl ester transfer protein (CETP) polymorphism potentially related to recent findings demonstrating coronary risk with increasing high-density lipoprotein cholesterol (HDL-C) level. Methods and results: A novel graphical exploratory data analysis tool allowed the examination of coronary risk in postinfarction patients relating to HDL-C and C-reactive protein levels. Results demonstrated a high-risk subgroup, defined by high HDL-C and C-reactive protein levels, exhibiting larger HDL particles and lower lipoprotein-associated phospholipaseA2 levels than lower-risk patients. Subgroup CETP-associated risk was probed using a functional CETP polymorphism (TaqIB, rs708272). In the high-risk subgroup, multivariable modeling revealed greater risk for B2 allele carriers (less CETP activity) versus B1 homozygotes (hazard ratio, 2.41; 95% CI, 1.04 to 5.60; P=0.04). Within the high-risk subgroup, B2 allele carriers had higher serum amyloid A levels than B1 homozygotes. Evidence also demonstrates that CETP genotypic differences in HDL subfraction distributions regarding non-HDL-C and lipoprotein-associated phospholipaseA2 may potentially relate to impaired HDL remodeling. Conclusion: Postinfarction patients with high HDL-C and C-reactive protein levels demonstrate increased risk for recurrent events. Future studies should aim at characterizing altered HDL particles from such patients and at elucidating the mechanistic details related to inflammation and HDL particle remodeling. Such patients should be considered in drug trials involving an increase in HDL-C level. © 2010 American Heart Association, Inc. Source


Hlusko L.J.,University of California at Berkeley | Sage R.D.,University of California at Berkeley | Mahaney M.C.,Southwest Foundation for Biomedical Research
Journal of Experimental Zoology Part B: Molecular and Developmental Evolution | Year: 2011

The concept of modularity provides a useful tool for exploring the relationship between genotype and phenotype. Here, we use quantitative genetics to identify modularity within the mammalian dentition, connecting the genetics of organogenesis to the genetics of population-level variation for a phenotype well represented in the fossil record. We estimated the correlations between dental traits owing to the shared additive effects of genes (pleiotropy) and compared the pleiotropic relationships among homologous traits in two evolutionary distant taxa-mice and baboons. We find that in both mice and baboons, who shared a common ancestor >65 Ma, incisor size variation is genetically independent of molar size variation. Furthermore, baboon premolars show independent genetic variation from incisors, suggesting that a modular genetic architecture separates incisors from these posterior teeth as well. Such genetic independence between modules provides an explanation for the extensive diversity of incisor size variation seen throughout mammalian evolution-variation uncorrelated with equivalent levels of postcanine tooth size variation. The modularity identified here is supported by the odontogenic homeobox code proposed for the patterning of the rodent dentition. The baboon postcanine pattern of incomplete pleiotropy is also consistent with predictions from the morphogenetic field model. Copyright © 2010 Wiley-Liss, Inc., A Wiley Company. Source


Hageman R.S.,The Jackson Laboratory | Leduc M.S.,Southwest Foundation for Biomedical Research | Korstanje R.,The Jackson Laboratory | Paigen B.,The Jackson Laboratory | Churchill G.A.,The Jackson Laboratory
Genetics | Year: 2011

Complex genetic interactions lie at the foundation of many diseases. Understanding the nature of these interactions is critical to developing rational intervention strategies. In mammalian systems hypothesis testing in vivo is expensive, time consuming, and often restricted to a few physiological endpoints. Thus, computational methods that generate causal hypotheses can help to prioritize targets for experimental intervention. We propose a Bayesian statistical method to infer networks of causal relationships among genotypes and phenotypes using expression quantitative trait loci (eQTL) data from genetically randomized populations. Causal relationships between network variables are described with hierarchical regression models. Prior distributions on the network structure enforce graph sparsity and have the potential to encode prior biological knowledge about the network. An efficient Monte Carlo method is used to search across the model space and sample highly probable networks. The result is an ensemble of networks that provide a measure of confidence in the estimated network topology. These networks can be used to make predictions of system-wide response to perturbations. We applied our method to kidney gene expression data from an MRL/MpJ × SM/J intercross population and predicted a previously uncharacterized feedback loop in the local renin-angiotensin system. © 2011 by the Genetics Society of America. Source


Kochunov P.,University of Maryland, Baltimore | Kochunov P.,Southwest Foundation for Biomedical Research | Rogers W.,University of Maryland, Baltimore | Mangin J.-F.,CEA Saclay Nuclear Research Center | Lancaster J.,University of Maryland, Baltimore
Neuroinformatics | Year: 2012

Sharing of analysis techniques and tools is among the main driving forces of modern neuroscience. We describe a library of tools developed to quantify global and regional differences in cortical anatomy in high resolution structural MR images. This library is distributed as a plug-in application for popular structural analysis software, BrainVisa (BV). It contains tools to measure global and regional gyrification, gray matter thickness and sulcal and gyral white matter spans. We provide a description of each tool and examples for several case studies to demonstrate their use. These examples show how the BV library was used to study cortical folding process during antenatal development and recapitulation of this process during cerebral aging. Further, the BV library was used to perform translation research in humans and nonhuman primates on the genetics of cerebral gyrification. This library, including source code and self-contained binaries for popular computer platforms, is available from the NIH-Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) resource (http://www.nitrc.org/ projects/brainvisa-ext). © Springer Science+Business Media, LLC 2011. Source


Oler J.A.,University of Wisconsin - Madison | Fox A.S.,University of Wisconsin - Madison | Shelton S.E.,University of Wisconsin - Madison | Rogers J.,Baylor College of Medicine | And 7 more authors.
Nature | Year: 2010

Anxious temperament (AT) in human and non-human primates is a trait-like phenotype evident early in life that is characterized by increased behavioural and physiological reactivity to mildly threatening stimuli. Studies in children demonstrate that AT is an important risk factor for the later development of anxiety disorders, depression and comorbid substance abuse. Despite its importance as an early predictor of psychopathology, little is known about the factors that predispose vulnerable children to develop AT and the brain systems that underlie its expression. To characterize the neural circuitry associated with AT and the extent to which the function of this circuit is heritable, we studied a large sample of rhesus monkeys phenotyped for AT. Using 238 young monkeys from a multigenerational single-family pedigree, we simultaneously assessed brain metabolic activity and AT while monkeys were exposed to the relevant ethological condition that elicits the phenotype. High-resolution 18 F-labelled deoxyglucose positron-emission tomography (FDG-PET) was selected as the imaging modality because it provides semi-quantitative indices of absolute glucose metabolic rate, allows for simultaneous measurement of behaviour and brain activity, and has a time course suited for assessing temperament- associated sustained brain responses. Here we demonstrate that the central nucleus region of the amygdala and the anterior hippocampus are key components of the neural circuit predictive of AT. We also show significant heritability of the AT phenotype by using quantitative genetic analysis. Additionally, using voxelwise analyses, we reveal significant heritability of metabolic activity in AT-associated hippocampal regions. However, activity in the amygdala region predictive of AT is not significantly heritable. Furthermore, the heritabilities of the hippocampal and amygdala regions significantly differ from each other. Even though these structures are closely linked, the results suggest differential influences of genes and environment on how these brain regions mediate AT and the ongoing risk of developing anxiety and depression. © 2010 Macmillan Publishers Limited. All rights reserved. Source

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