Brian J Bennett

CSU Mentor, Long Beach, California, United States

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Publications (31)259.73 Total impact

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    ABSTRACT: Intestinal microbial community structure is driven by host genetics in addition to environmental factors such as diet. In comparison with environmental influences, the effect of host genetics on intestinal microbiota, and how host-driven differences alter host metabolism is unclear. Additionally, the interaction between host genetics and diet, and the impact on the intestinal microbiome and possible down-stream effect on host metabolism is not fully understood, but represents another aspects of inter-individual variation in disease risk. The objectives of this study were to investigate how diet and genetic background shape microbial communities, and how these diet- and genetic-driven microbial differences relate to cardiometabolic phenotypes. To determine these effects, we used the 8 progenitor strains of the collaborative cross/diversity outbred mapping panels (C57BL/6J, A/J, NOD/ShiLtJ, NZO/HILtJ, WSB/EiJ, CAST/EiJ, PWK/PhJ, and 129S1/SvImJ). 16s rRNA profiling of enteric microbial communities in addition to the assessment of phenotypes central to cardiometabolic health was conducted under baseline nutritional conditions and in response to diets varying in atherogenic nutrient (fat, cholesterol, cholic acid) composition. These studies revealed strain-driven differences in enteric microbial communities which were retained with dietary intervention. Diet-strain interactions were seen for a core group of cardiometabolic-related microbial taxa. In conclusion, these studies highlight diet and genetically regulated cardiometabolic-related microbial taxa. Furthermore, we demonstrate the progenitor model is useful for nutrigenomic-based studies and screens seeking to investigate the interaction between genetic background and the phenotypic and microbial response to diet.
    Mammalian genome : official journal of the International Mammalian Genome Society. 08/2014;
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    ABSTRACT: Atherosclerosis, the underlying cause of cardiovascular disease, results from both genetic and environmental factors.
    BMC Medical Genomics 08/2014; 7(1):51. · 3.47 Impact Factor
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    ABSTRACT: It is important to understand whether eating eggs, which are a major source of dietary choline, results in increased exposure to trimethylamine-N-oxide (TMAO) that is purported to be a risk factor for developing heart disease.OBJECTIVE: We determined whether humans eating eggs generate TMAO and, if so, whether there is an associated increase in a marker for inflammation [ie, high-sensitivity C-reactive protein (hsCRP)] or increased oxidation of low-density lipoprotein (LDL).DESIGN: In a longitudinal, double-blind, randomized dietary intervention, 6 volunteers were fed breakfast doses of 0, 1, 2, 4, or 6 egg yolks. Diets were otherwise controlled on the day before and day of each egg dose with a standardized low-choline menu. Plasma TMAO at timed intervals (immediately before and 1, 2, 4, 8, and 24 h after each dose), 24-h urine TMAO, predose and 24-h postdose serum hsCRP, and plasma oxidized LDL were measured. Volunteers received all 5 doses with each dose separated by >2-wk washout periods.RESULTS: The consumption of eggs was associated with increased plasma and urine TMAO concentrations (P < 0.01), with ∼14% of the total choline in eggs having been converted to TMAO. There was considerable variation between individuals in the TMAO response. There was no difference in hsCRP or oxidized LDL concentrations after egg doses.Conclusions: The consumption of ≥2 eggs results in an increased formation of TMAO. Choline is an essential nutrient that is required for normal human liver and muscle functions and important for normal fetal development. Additional study is needed to both confirm the association between TMAO and atherosclerosis and identify factors, microbiota and genetic, that influence the generation of TMAO before policy and medical recommendations are made that suggest reduced dietary choline intake. This trial was registered at clinicaltrials.gov as A12-1066-001.
    American Journal of Clinical Nutrition 06/2014; · 6.50 Impact Factor
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    ABSTRACT: We profiled and analyzed 283 metabolites representing eight major classes of molecules including Lipids, Carbohydrates, Amino Acids, Peptides, Xenobiotics, Vitamins and Cofactors, Energy Metabolism, and Nucleotides in mouse liver of 104 inbred and recombinant inbred strains. We find that metabolites exhibit a wide range of variation, as has been previously observed with metabolites in blood serum. Using genome-wide association analysis, we mapped 40% of the quantified metabolites to at least one locus in the genome and for 75% of the loci mapped we identified at least one candidate gene by local expression QTL analysis of the transcripts. Moreover, we validated 2 of 3 of the significant loci examined by adenoviral overexpression of the genes in mice. In our GWAS results, we find that at significant loci the peak markers explained on average between 20 and 40% of variation in the metabolites. Moreover, 39% of loci found to be regulating liver metabolites in mice were also found in human GWAS results for serum metabolites, providing support for similarity in genetic regulation of metabolites between mice and human. We also integrated the metabolomic data with transcriptomic and clinical phenotypic data to evaluate the extent of co-variation across various biological scales.
    Molecular Systems Biology 05/2014; 10(5). · 11.34 Impact Factor
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    ABSTRACT: Elevated levels of plasma trimethylamine N-oxide (TMAO), the product of gut microbiome and hepatic-mediated metabolism of dietary choline and l-carnitine, have recently been identified as a novel risk factor for the development of atherosclerosis in mice and humans. The goal of this study was to identify the genetic factors associated with plasma TMAO levels. We used comparative genome-wide association study approaches to discover loci for plasma TMAO levels in mice and humans. A genome-wide association study in the hybrid mouse diversity panel identified a locus for TMAO levels on chromosome 3 (P=2.37×10(-6)) that colocalized with a highly significant (P=1.07×10(-20)) cis-expression quantitative trait locus for solute carrier family 30 member 7. This zinc transporter could thus represent ≥1 positional candidate gene responsible for the association signal at this locus in mice. A genome-wide association study for plasma TMAO levels in 1973 humans identified 2 loci with suggestive evidence of association (P=3.0×10(-7)) on chromosomes 1q23.3 and 2p12. However, genotyping of the lead variants at these loci in 1892 additional subjects failed to replicate their association with plasma TMAO levels. The results of these limited observational studies indicate that, at least in humans, genes play a marginal role in determining TMAO levels and that any genetic effects are relatively weak and complex. Variation in diet or the repertoire of gut microbiota may be more important determinants of plasma TMAO levels in mice and humans, which should be investigated in future studies.
    Arteriosclerosis Thrombosis and Vascular Biology 03/2014; · 6.34 Impact Factor
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    ABSTRACT: Both dietary fat and carbohydrates (Carbs) may play important roles in the development of insulin resistance. The main goal of this study was to further define the roles for fat and dietary carbs in insulin resistance. C57BL/6 mice were fed normal chow diet (CD) or HFD containing 0.1-25.5% carbs for 5 weeks, followed by evaluations of calorie consumption, body weight and fat gains, insulin sensitivity, intratissue insulin signaling, ectopic fat, and oxidative stress in liver and skeletal muscle. The role of hepatic gluconeogenesis in the HFD-induced insulin resistance was determined in mice. The role of fat in insulin resistance was also examined in cultured cells. HFD with little carbs (0.1%) induced severe insulin resistance. Addition of 5% carbs to HFD dramatically elevated insulin resistance and 10% carbs in HFD was sufficient to induce a maximal level of insulin resistance. HFD with little carbs induced ectopic fat accumulation and oxidative stress in liver and skeletal muscle and addition of carbs to HFD dramatically enhanced ectopic fat and oxidative stress. HFD increased hepatic expression of key gluconeogenic genes and the increase was most dramatic by HFD with little carbs, and inhibition of hepatic gluconeogenesis prevented the HFD-induced insulin resistance. In cultured cells, development of insulin resistance induced by a pathological level of insulin was prevented in the absence of fat. Together, fat is essential for development of insulin resistance and dietary carb is not necessary for HFD-induced insulin resistance due to the presence of hepatic gluconeogenesis but a very small amount of it can promote HFD-induced insulin resistance to a maximal level.
    PLoS ONE 01/2014; 9(7):e100875. · 3.73 Impact Factor
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    ABSTRACT: Genetic variations in blood cell parameters can impact clinical traits. We report here the mapping of blood cell traits in a panel of 100 inbred strains of mice of the Hybrid Mouse Diversity Panel (HMDP) using genome-wide association (GWA). We replicated a locus previously identified in using linkage analysis in several genetic crosses for mean corpuscular volume (MCV) and a number of other red blood cell traits on distal chromosome 7. Our peak for SNP association to MCV occurred in a linkage disequilibrium (LD) block spanning from 109.38 to 111.75 Mb that includes Hbb-b1, the likely causal gene. Altogether, we identified five loci controlling red blood cell traits (on chromosomes 1, 7, 11, 12, and 16), and four of these correspond to loci for red blood cell traits reported in a recent human GWA study. For white blood cells, including granulocytes, monocytes, and lymphocytes, a total of six significant loci were identified on chromosomes 1, 6, 8, 11, 12, and 15. An average of ten candidate genes were found at each locus and those were prioritized by examining functional variants in the HMDP such as missense and expression variants. These results provide intermediate phenotypes and candidate loci for genetic studies of atherosclerosis and cancer as well as inflammatory and immune disorders in mice.
    Mammalian Genome 02/2013; · 2.42 Impact Factor
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    ABSTRACT: Circulating trimethylamine-N-oxide (TMAO) levels are strongly associated with atherosclerosis. We now examine genetic, dietary, and hormonal factors regulating TMAO levels. We demonstrate that two flavin mono-oxygenase family members, FMO1 and FMO3, oxidize trimethylamine (TMA), derived from gut flora metabolism of choline, to TMAO. Further, we show that FMO3 exhibits 10-fold higher specific activity than FMO1. FMO3 overexpression in mice significantly increases plasma TMAO levels while silencing FMO3 decreases TMAO levels. In both humans and mice, hepatic FMO3 expression is reduced in males compared to females. In mice, this reduction in FMO3 expression is due primarily to downregulation by androgens. FMO3 expression is induced by dietary bile acids by a mechanism that involves the farnesoid X receptor (FXR), a bile acid-activated nuclear receptor. Analysis of natural genetic variation among inbred strains of mice indicates that FMO3 and TMAO are significantly correlated, and TMAO levels explain 11% of the variation in atherosclerosis.
    Cell metabolism 01/2013; 17(1):49-60. · 17.35 Impact Factor
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    ABSTRACT: Obesity is a highly heritable disease driven by complex interactions between genetic and environmental factors. Human genome-wide association studies (GWAS) have identified a number of loci contributing to obesity; however, a major limitation of these studies is the inability to assess environmental interactions common to obesity. Using a systems genetics approach, we measured obesity traits, global gene expression, and gut microbiota composition in response to a high-fat/high-sucrose (HF/HS) diet of more than 100 inbred strains of mice. Here we show that HF/HS feeding promotes robust, strain-specific changes in obesity that are not accounted for by food intake and provide evidence for a genetically determined set point for obesity. GWAS analysis identified 11 genome-wide significant loci associated with obesity traits, several of which overlap with loci identified in human studies. We also show strong relationships between genotype and gut microbiota plasticity during HF/HS feeding and identify gut microbial phylotypes associated with obesity.
    Cell metabolism 01/2013; 17(1):141-52. · 17.35 Impact Factor
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    ABSTRACT: Background: Network construction and analysis algorithms provide scientists with the ability to sift through high-throughput biological outputs, such as transcription microarrays, for small groups of genes (modules) that are relevant for further research. Most of these algorithms ignore the important role of non-linear interactions in the data, and the ability for genes to operate in multiple functional groups at once, despite clear evidence for both of these phenomena in observed biological systems. Results: We have created a novel co-expression network analysis algorithm that incorporates both of these principles by combining the information-theoretic association measure of the maximal information coefficient (MIC) with an Interaction Component Model. We evaluate the performance of this approach on two datasets collected from a large panel of mice, one from macrophages and the other from liver by comparing the two measures based on a measure of module entropy, Gene Ontology (GO) enrichment, and scale-free topology (SFT) fit. Our algorithm outperforms a widely used co-expression analysis method, weighted gene co-expression network analysis (WGCNA), in the macrophage data, while returning comparable results in the liver dataset when using these criteria. We demonstrate that the macrophage data has more non-linear interactions than the liver dataset, which may explain the increased performance of our method, termed Maximal Information Component Analysis (MICA) in that case. Conclusions: In making our network algorithm more accurately reflect known biological principles, we are able to generate modules with improved relevance, particularly in networks with confounding factors such as gene by environment interactions.
    Frontiers in Genetics 01/2013; 4:28.
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    ABSTRACT: The osteoblast-lineage consists of cells at various stages of maturation that are essential for skeletal development, growth, and maintenance. Over the past decade, many of the signaling cascades that regulate this lineage have been elucidated; however, little is known of the networks that coordinate, modulate, and transmit these signals. Here, we identify a gene network specific to the osteoblast-lineage through the reconstruction of a bone co-expression network using microarray profiles collected on 96 Hybrid Mouse Diversity Panel (HMDP) inbred strains. Of the 21 modules that comprised the bone network, module 9 (M9) contained genes that were highly correlated with prototypical osteoblast maker genes and were more highly expressed in osteoblasts relative to other bone cells. In addition, the M9 contained many of the key genes that define the osteoblast-lineage, which together suggested that it was specific to this lineage. To use the M9 to identify novel osteoblast genes and highlight its biological relevance, we knocked-down the expression of its two most connected "hub" genes, Maged1 and Pard6g. Their perturbation altered both osteoblast proliferation and differentiation. Furthermore, we demonstrated the mice deficient in Maged1 had decreased bone mineral density (BMD). It was also discovered that a local expression quantitative trait locus (eQTL) regulating the Wnt signaling antagonist Sfrp1 was a key driver of the M9. We also show that the M9 is associated with BMD in the HMDP and is enriched for genes implicated in the regulation of human BMD through genome-wide association studies. In conclusion, we have identified a physiologically relevant gene network and used it to discover novel genes and regulatory mechanisms involved in the function of osteoblast-lineage cells. Our results highlight the power of harnessing natural genetic variation to generate co-expression networks that can be used to gain insight into the function of specific cell-types.
    PLoS Genetics 12/2012; 8(12):e1003150. · 8.52 Impact Factor
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    ABSTRACT: Many common diseases have an important inflammatory component mediated in part by macrophages. Here we used a systems genetics strategy to examine the role of common genetic variation in macrophage responses to inflammatory stimuli. We examined genome-wide transcript levels in macrophages from 92 strains of the Hybrid Mouse Diversity Panel. We exposed macrophages to control media, bacterial lipopolysaccharide (LPS), or oxidized phospholipids. We performed association mapping under each condition and identified several thousand expression quantitative trait loci (eQTL), gene-by-environment interactions, and eQTL "hot spots" that specifically control LPS responses. We used siRNA knockdown of candidate genes to validate an eQTL hot spot in chromosome 8 and identified the gene 2310061C15Rik as a regulator of inflammatory responses in macrophages. We have created a public database where the data presented here can be used as a resource for understanding many common inflammatory traits that are modeled in the mouse and for the dissection of regulatory relationships between genes.
    Cell 10/2012; 151(3):658-70. · 31.96 Impact Factor
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    ABSTRACT: We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5 % of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches.
    Mammalian Genome 08/2012; 23(9-10):680-92. · 2.42 Impact Factor
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    ABSTRACT: The purpose of this study was to fine map previously identified quantitative trait loci affecting atherosclerosis in mice using association analysis. We recently showed that high-resolution association analysis using common inbred strains of mice is feasible if corrected for population structure. To use this approach for atherosclerosis, which requires a sensitizing mutation, we bred human apolipoprotein B-100 transgenic mice with 22 different inbred strains to produce F1 heterozygotes. Mice carrying the dominant transgene were tested for association with high-density single nucleotide polymorphism maps. Here, we focus on high-resolution mapping of the previously described atherosclerosis 30 locus on chromosome 1. Compared with the previous linkage analysis, association improved the resolution of the atherosclerosis 30 locus by more than an order of magnitude. Using expression quantitative trait locus analysis, we identified one of the genes in the region, desmin, as a strong candidate. Our high-resolution mapping approach accurately identifies and fine maps known atherosclerosis quantitative trait loci. These results suggest that high-resolution genome-wide association analysis for atherosclerosis is feasible in mice.
    Arteriosclerosis Thrombosis and Vascular Biology 06/2012; 32(8):1790-8. · 6.34 Impact Factor
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    ABSTRACT: Objective:A better understanding of the processes influencing energy expenditure could provide new therapeutic strategies for reducing obesity. As the metabolic activity of the brown adipose tissue (BAT) and skeletal muscle is an important determinant of overall energy expenditure and adiposity, we investigated the role of genes that could influence cellular bioenergetics in these two tissues.Design:We screened for genes that are induced in both the BAT and skeletal muscle during acute adaptive thermogenesis in the mouse by microarray. We used C57BL/6J mice as well as the primary and immortalized brown adipocytes and C2C12 myocytes to validate the microarray data. Further characterization included gene expression, mitochondrial density, cellular respiration and substrate utilization. We also used a Hybrid Mouse Diversity Panel to assess in vivo effects on obesity and body fat content.Results:We identified the transcription factor Zbtb16 (also known as Plzf and Zfp14) as being induced in both the BAT and skeletal muscle during acute adaptive thermogenesis. Zbtb16 overexpression in brown adipocytes led to the induction of components of the thermogenic program, including genes involved in fatty acid oxidation, glycolysis and mitochondrial function. Enhanced Zbtb16 expression also increased mitochondrial number, as well as the respiratory capacity and uncoupling. These effects were accompanied by decreased triglyceride content and increased carbohydrate utilization in brown adipocytes. Natural variation in Zbtb16 mRNA levels in multiple tissues across a panel of >100 mouse strains was inversely correlated with body weight and body fat content.Conclusion:Our results implicate Zbtb16 as a novel determinant of substrate utilization in brown adipocytes and of adiposity in vivo.
    Nutrition & Diabetes 01/2012; 2:e46.
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    ABSTRACT: The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.
    PLoS Genetics 06/2011; 7(6):e1001393. · 8.52 Impact Factor
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    ABSTRACT: Metabolomics studies hold promise for the discovery of pathways linked to disease processes. Cardiovascular disease (CVD) represents the leading cause of death and morbidity worldwide. Here we used a metabolomics approach to generate unbiased small-molecule metabolic profiles in plasma that predict risk for CVD. Three metabolites of the dietary lipid phosphatidylcholine--choline, trimethylamine N-oxide (TMAO) and betaine--were identified and then shown to predict risk for CVD in an independent large clinical cohort. Dietary supplementation of mice with choline, TMAO or betaine promoted upregulation of multiple macrophage scavenger receptors linked to atherosclerosis, and supplementation with choline or TMAO promoted atherosclerosis. Studies using germ-free mice confirmed a critical role for dietary choline and gut flora in TMAO production, augmented macrophage cholesterol accumulation and foam cell formation. Suppression of intestinal microflora in atherosclerosis-prone mice inhibited dietary-choline-enhanced atherosclerosis. Genetic variations controlling expression of flavin monooxygenases, an enzymatic source of TMAO, segregated with atherosclerosis in hyperlipidaemic mice. Discovery of a relationship between gut-flora-dependent metabolism of dietary phosphatidylcholine and CVD pathogenesis provides opportunities for the development of new diagnostic tests and therapeutic approaches for atherosclerotic heart disease.
    Nature 04/2011; 472(7341):57-63. · 38.60 Impact Factor
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    ABSTRACT: Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis were used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal, and femoral BMD revealed four significant associations (-log10P>5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12, and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism through which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cells of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.
    PLoS Genetics 04/2011; 7(4):e1002038. · 8.52 Impact Factor
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    ABSTRACT: Our understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution. A total of 27 behavioral quantitative trait loci were mapped with a false discovery rate of 5%. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and also genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. In addition, we surveyed the architecture of brain transcript regulation and demonstrated preservation of gene co-expression modules in hippocampus and striatum, while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance were strongly associated with fear phenotypes. Application of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior.
    BMC Systems Biology 03/2011; 5:43. · 2.98 Impact Factor
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    ABSTRACT: The bone morphogenetic proteins (BMPs), a family of morphogens, have been implicated as mediators of calcification and inflammation in the vascular wall. To investigate the effect of altered expression of matrix Gla protein (MGP), an inhibitor of BMP, on vascular disease. We used MGP transgenic or MGP-deficient mice bred to apolipoprotein E mice, a model of atherosclerosis. MGP overexpression reduced vascular BMP activity, atherosclerotic lesion size, intimal and medial calcification, and inflammation. It also reduced expression of the activin-like kinase receptor 1 and the vascular endothelial growth factor, part of a BMP-activated pathway that regulates angiogenesis and may enhance lesion formation and calcification. Conversely, MGP deficiency increased BMP activity, which may explain the diffuse calcification of vascular medial cells in MGP deficient aortas and the increase in expression of activin-like kinase receptor 1 and vascular endothelial growth factor. Unexpectedly, atherosclerotic lesion formation was decreased in MGP-deficient mice, which may be explained by a dramatic reduction in expression of endothelial adhesion molecules limiting monocyte infiltration of the artery wall. Our results indicate that BMP signaling is a key regulator of vascular disease, requiring careful control to maintain normal vascular homeostasis.
    Circulation Research 08/2010; 107(4):485-94. · 11.86 Impact Factor

Publication Stats

1k Citations
259.73 Total Impact Points

Institutions

  • 2013
    • CSU Mentor
      Long Beach, California, United States
    • University of North Carolina at Pembroke
      North Carolina, United States
  • 2012–2013
    • University of North Carolina at Chapel Hill
      • Department of Genetics
      North Carolina, United States
  • 2007–2013
    • University of California, Los Angeles
      • Department of Medicine
      Los Angeles, California, United States
  • 2011
    • University of Virginia
      Charlottesville, Virginia, United States
  • 2002–2006
    • University of Washington Seattle
      • Department of Pathology
      Seattle, WA, United States