Leslie Ingram-Drake

Elucidating the role of gonadal hormones in sexually dimorphic gene coexpression networks.

We previously used high-density expression arrays to interrogate a genetic cross between strains C3H/HeJ and C57BL/6J and observed thousands of differences in gene expression between sexes. We now report analyses of the molecular basis of these sex differences and of the effects of sex on gene expression networks. We analyzed liver gene expression of hormone-treated gonadectomized mice as well as XX male and XY female mice. Differences in gene expression resulted in large part from acute effects of gonadal hormones acting in adulthood, and the effects of sex chromosomes, apart from hormones, were modest. We also determined whether there are sex differences in the organization of gene expression networks in adipose, liver, skeletal muscle, and brain tissue. Although coexpression networks of highly correlated genes were largely conserved between sexes, some exhibited striking sex dependence. We observed strong body fat and lipid correlations with sex-specific modules in adipose and liver as well as a sexually dimorphic network enriched for genes affected by gonadal hormones. Finally, our analyses identified chromosomal loci regulating sexually dimorphic networks. This study indicates that gonadal hormones play a strong role in sex differences in gene expression. In addition, it results in the identification of sex-specific gene coexpression networks related to genetic and metabolic traits.

Identification of Abcc6 as the major causal gene for dystrophic cardiac calcification in mice through integrative genomics

The genetic factors contributing to the complex disorder of myocardial calcification are largely unknown. Using a mouse model, we fine-mapped the major locus (Dyscalc1) contributing to the dystrophic cardiac calcification (DCC) to an 840-kb interval containing 38 genes. We then identified the causal gene by using an approach integrating genetic segregation and expression array analyses to identify, on a global scale, cis-acting DNA variations that perturb gene expression. By studying two intercrosses, in which the DCC trait segregates, a single candidate gene (encoding the ATP-binding cassette transporter ABCC6) was identified. Transgenic complementation confirmed Abcc6 as the underlying causal gene for Dyscalc1. We demonstrate that in the cross, the expression of Abcc6 is highly correlated with the local mineralization regulatory system and the BMP2-Wnt signaling pathway known to be involved in the systemic regulation of calcification, suggesting potential pathways for the action of Abcc6 in DCC. Our results demonstrate the power of the integrative genomics in discovering causal genes and pathways underlying complex traits.

Genomic analysis of metabolic pathway gene expression in mice

BackgroundA segregating population of (C57BL/6J × DBA/2J)F2 intercross mice was studied for obesity-related traits and for global gene expression in liver. Quantitative trait locus analyses were applied to the subcutaneous fat-mass trait and all gene-expression data. These data were then used to identify gene sets that are differentially perturbed in lean and obese mice.ResultsWe integrated global gene-expression data with phenotypic and genetic segregation analyses to evaluate metabolic pathways associated with obesity. Using two approaches we identified 13 metabolic pathways whose genes are coordinately regulated in association with obesity. Four genomic regions on chromosomes 3, 6, 16, and 19 were found to control the coordinated expression of these pathways. Using criteria that included trait correlation, differential gene expression, and linkage to genomic regions, we identified novel genes potentially associated with the identified pathways.ConclusionThis study demonstrates that genetic and gene-expression data can be integrated to identify pathways associated with clinical traits and their underlying genetic determinants.

Systems Genetics Analysis of Gene-by-Environment Interactions in Human Cells

Gene by environment (GxE) interactions are clearly important in many human diseases, but they have proven to be difficult to study on a molecular level. We report genetic analysis of thousands of transcript abundance traits in human primary endothelial cell (EC) lines in response to proinflammatory oxidized phospholipids implicated in cardiovascular disease. Of the 59 most regulated transcripts, approximately one-third showed evidence of GxE interactions. The interactions resulted primarily from effects of distal-, trans-acting loci, but a striking example of a local-GxE interaction was also observed for FGD6. Some of the distal interactions were validated by siRNA knockdown experiments, including a locus involved in the regulation of multiple transcripts involved in the ER stress pathway. Our findings add to the understanding of the overall architecture of complex human traits and are consistent with the possibility that GxE interactions are responsible, in part, for the failure of association studies to more fully explain common disease variation.

Identification of Pathways for Atherosclerosis in Mice: Integration of Quantitative Trait Locus Analysis and Global Gene Expression Data

We report a combined genetic and genomic analysis of atherosclerosis in a cross between the strains C3H/HeJ and C57BL/6J on a hyperlipidemic apolipoprotein E–null background. We incorporated sex and sex-by-genotype interactions into our model selection procedure to identify 10 quantitative trait loci for lesion size, revealing a level of complexity greater than previously thought. Of the known risk factors for atherosclerosis, plasma triglyceride levels and plasma glucose to insulin ratios were particularly strongly, but negatively, associated with lesion size. We performed expression array analysis for 23 574 transcripts of the livers and adipose tissues of all 334 F2 mice and identified more than 10 000 expression quantitative trait loci that either mapped to the gene encoding the transcript, implying cis regulation, or to a separate locus, implying trans-regulation. The gene expression data allowed us to identify candidate genes that mapped to the atherosclerosis quantitative trait loci and for which the expression was regulated in cis. Genes highly correlated with lesions were enriched in certain known pathways involved in lesion development, including cholesterol metabolism, mitochondrial oxidative phosphorylation, and inflammation. Thus, global gene expression in peripheral tissues can reflect the systemic perturbations that contribute to atherosclerosis.

Expression Quantitative Trait Loci: Replication, Tissue- and Sex-Specificity in Mice

By treating the transcript abundance as a quantitative trait, gene expression can be mapped to local or distant genomic regions relative to the gene encoding the transcript. Local expression quantitative trait loci (eQTL) generally act in cis (that is, control the expression of only the contiguous structural gene), whereas distal eQTL act in trans. Distal eQTL are more difficult to identify with certainty due to the fact that significant thresholds are very high since all regions of the genome must be tested, and confounding factors such as batch effects can produce false positives. Here, we compare findings from two large genetic crosses between mouse strains C3H/HeJ and C57BL/6J to evaluate the reliability of distal eQTL detection, including “hotspots” influencing the expression of multiple genes in trans. We found that >63% of local eQTL and >18% of distal eQTL were replicable at a threshold of LOD > 4.3 between crosses and 76% of local and >24% of distal eQTL at a threshold of LOD > 6. Additionally, at LOD > 4.3 four tissues studied (adipose, brain, liver, and muscle) exhibited >50% preservation of local eQTL and >17% preservation of distal eQTL. We observed replicated distal eQTL hotspots between the crosses on chromosomes 9 and 17. Finally, >69% of local eQTL and >10% of distal eQTL were preserved in most tissues between sexes. We conclude that most local eQTL are highly replicable between mouse crosses, tissues, and sex as compared to distal eQTL, which exhibited modest replicability.

Copy number variation influences gene expression and metabolic traits in mice

Copy number variants (CNVs) are genomic segments which are duplicated or deleted among different individuals. CNVs have been implicated in both Mendelian and complex traits, including immune and behavioral disorders, but the study of the mechanisms by which CNVs influence gene expression and clinical phenotypes in humans is complicated by the limited access to tissues and by population heterogeneity. We now report studies of the effect of 19 CNVs on gene expression and metabolic traits in a mouse intercross between strains C57BL/6J and C3H/HeJ. We found that 83% of genes predicted to occur within CNVs were differentially expressed. The expression of most CNV genes was correlated with copy number, but we also observed evidence that gene expression was altered in genes flanking CNVs, suggesting that CNVs may contain regulatory elements for these genes. Several CNVs mapped to hotspots, genomic regions influencing expression of tens or hundreds of genes. Several metabolic traits including cholesterol, triglycerides, glucose and body weight mapped to three CNVs in the genome, in mouse chromosomes 1, 4 and 17. Predicted CNV genes, such as Itlna, Defcr-1, Trim12 and Trim34 were highly correlated with these traits. Our results suggest that CNVs have a significant impact on gene expression and that CNVs may be playing a role in the mechanisms underlying metabolic traits in mice.

An integrative genetics approach to identify candidate genes regulating BMD: combining linkage, gene expression, and association.

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine‐map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine‐mapping and candidate gene identification.

Economic Benefits of Intensive Insulin Therapy in Critically Ill Patients: The Targeted Insulin Therapy to Improve Hospital Outcomes (TRIUMPH) Project

OBJECTIVE—The purpose of this study was to analyze the economic outcomes of a clinical program implemented to achieve strict glycemic control with intensive insulin therapy in patients admitted to the intensive care unit (ICU). RESEARCH DESIGN AND METHODS—A difference-in-differences (quasi-experimental) study design was used to examine the associations of an intensive insulin therapy intervention with changes in hospital length of stay (ICU and total), costs (ICU and total), and mortality. Hospital administrative data were obtained for 6,719 adult patients admitted between 2003 and 2005 to one of five intervention or four comparison ICUs in a large academic medical center. Linear regression models with log transformations and appropriate retransformations were used to estimate length of stay (LOS) and costs; logistic regressions were used to estimate mortality. RESULTS—After adjustment for observable patient characteristics and secular time trends, the intervention was consistently associated with lower average glucose levels and a trend toward shorter LOS, lower costs, and lower mortality. However, associations with resource use and outcomes were statistically significant in only ICU LOS, with an average reduction of 1.19 days of ICU care per admission. Other associations, although large in magnitude and in the hypothesized directions, were not estimated with sufficient precision to rule out other net effects. The associations with ICU days and costs were larger in magnitude than total days and costs. CONCLUSIONS—A clinical team focused on hyperglycemia management for ICU patients can be a valuable investment with significant economic benefits for hospitals.

Economic Benefits of Intensive Insulin Therapy in Critically Ill Patients: The TRIUMPH Project

OBJECTIVE—The purpose of this study was to analyze the economic outcomes of a clinical program implemented to achieve strict glycemic control with intensive insulin therapy in patients admitted to the intensive care unit (ICU). RESEARCH DESIGN AND METHODS—A difference-in-differences (quasi-experimental) study design was used to examine the associations of an intensive insulin therapy intervention with changes in hospital length of stay (ICU and total), costs (ICU and total), and mortality. Hospital administrative data were obtained for 6,719 adult patients admitted between 2003 and 2005 to one of five intervention or four comparison ICUs in a large academic medical center. Linear regression models with log transformations and appropriate retransformations were used to estimate length of stay (LOS) and costs; logistic regressions were used to estimate mortality. RESULTS—After adjustment for observable patient characteristics and secular time trends, the intervention was consistently associated with lower average glucose levels and a trend toward shorter LOS, lower costs, and lower mortality. However, associations with resource use and outcomes were statistically significant in only ICU LOS, with an average reduction of 1.19 days of ICU care per admission. Other associations, although large in magnitude and in the hypothesized directions, were not estimated with sufficient precision to rule out other net effects. The associations with ICU days and costs were larger in magnitude than total days and costs. CONCLUSIONS—A clinical team focused on hyperglycemia management for ICU patients can be a valuable investment with significant economic benefits for hospitals.