Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

A dynamic network approach for the study of human phenotypes

The use of networks to integrate different genetic, proteomic, and metabolic datasets has been proposed as a viable path toward elucidating the origins of specific diseases. Here we introduce a new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN). We present evidence that the structure of the PDN is relevant to the understanding of illness progression by showing that (1) patients develop diseases close in the network to those they already have; (2) the progression of disease along the links of the network is different for patients of different genders and ethnicities; (3) patients diagnosed with diseases which are more highly connected in the PDN tend to die sooner than those affected by less connected diseases; and (4) diseases that tend to be preceded by others in the PDN tend to be more connected than diseases that precede other illnesses, and are associated with higher degrees of mortality. Our findings show that disease progression can be represented and studied using network methods, offering the potential to enhance our understanding of the origin and evolution of human diseases. The dataset introduced here, released concurrently with this publication, represents the largest relational phenotypic resource publicly available to the research community.Comment: 28 pages (double space), 6 figure

E-selectin S128R polymorphism and severe coronary artery disease in Arabs

BACKGROUND: The E-selectin p. S128R (g. A561C) polymorphism has been associated with the presence of angiographic coronary artery disease (CAD) in some populations, but no data is currently available on its association with CAD in Arabs. METHODS: In the present study, we determined the potential relevance of the E-selectin S128R polymorphism for severe CAD and its associated risk factors among Arabs. We genotyped Saudi Arabs for this polymorphism by PCR, followed by restriction enzyme digestion. RESULTS: The polymorphism was determined in 556 angiographically confirmed severe CAD patients and 237 control subjects with no CAD as established angiographically (CON). Frequencies of the S/S, S/R and R/R genotypes were found as 81.1%, 16.6% and 2.3% in CAD patients and 87.8%, 11.8%, and 0.4% in CON subjects, respectively. The frequency of the mutant 128R allele was higher among CAD patients compared to CON group (11% vs. 6%; odds ratio = 1.76; 95% CI 1.14 – 2.72; p = .007), thus indicating a significant association of the 128R allele with CAD among our population. However, the stepwise logistic regression for the 128R allele and different CAD risk factors showed no significant association. CONCLUSION: Among the Saudi population, The E-selectin p. S128R (g. A561C) polymorphism was associated with angiographic CAD in Univariate analysis, but lost its association in multivariate analysis

Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice

The millions of common DNA variations that occur in the human population, or among inbred strains of mice and rats, perturb the expression (transcript levels) of a large fraction of the genes expressed in a particular tissue. The hundreds or thousands of common cis-acting variations that occur in the population may in turn affect the expression of thousands of other genes by affecting transcription factors, signaling molecules, RNA processing, and other processes that act in trans. The levels of transcripts are conveniently quantitated using expression arrays, and the cis- and trans-acting loci can be mapped using quantitative trait locus (QTL) analysis, in the same manner as loci for physiologic or clinical traits. Thousands of such expression QTL (eQTL) have been mapped in various crosses in mice, as well as other experimental organisms, and less detailed maps have been produced in studies of cells from human pedigrees. Such an integrative genetics approach (sometimes referred to as “genetical genomics”) is proving useful for identifying genes and pathways that contribute to complex clinical traits. The coincidence of clinical trait QTL and eQTL can help in the prioritization of positional candidate genes. More importantly, mathematical modeling of correlations between levels of transcripts and clinical traits in genetic crosses can allow prediction of causal interactions and the identification of “key driver” genes. An important objective of such studies will be to model biological networks in physiologic processes. When combined with high-density single nucleotide polymorphism (SNP) mapping, it should be feasible to identify genes that contribute to transcript levels using association analysis in outbred populations. In this review we discuss the basic concepts and applications of this integrative genomic approach to cardiovascular and metabolic diseases

Network-Based Approach for Modeling and Analyzing Coronary Angiography

Significant intra-observer and inter-observer variability in the interpretation of coronary angiograms are reported. This variability is in part due to the common practices that rely on performing visual inspections by specialists (e.g., the thickness of coronaries). Quantitative Coronary Angiography (QCA) approaches are emerging to minimize observer's error and furthermore perform predictions and analysis on angiography images. However, QCA approaches suffer from the same problem as they mainly rely on performing visual inspections by utilizing image processing techniques. In this work, we propose an approach to model and analyze the entire cardiovascular tree as a complex network derived from coronary angiography images. This approach enables to analyze the graph structure of coronary arteries. We conduct the assessments of network integration, degree distribution, and controllability on a healthy and a diseased coronary angiogram. Through our discussion and assessments, we propose modeling the cardiovascular system as a complex network is an essential phase to fully automate the interpretation of coronary angiographic images. We show how network science can provide a new perspective to look at coronary angiograms

Quantitative 3-Dimensional Imaging of Murine Neointimal and Atherosclerotic Lesions by Optical Projection Tomography

Traditional methods for the analysis of vascular lesion formation are labour intensive to perform - restricting study to ‘snapshots’ within each vessel. This study was undertaken to determine the suitability of optical projection tomographic (OPT) imaging for the 3-dimensional representation and quantification of intimal lesions in mouse arteries. = 0.85), confirming both the accuracy of this methodology and its non-destructive nature. It was also possible to record volumetric measurements of lesion and lumen and these were highly reproducible between scans (coefficient of variation = 5.36%, 11.39% and 4.79% for wire- and ligation-injury and atherosclerosis, respectively).These data demonstrate the eminent suitability of OPT for imaging of atherosclerotic and neointimal lesion formation, providing a much needed means for the routine 3-dimensional analysis of vascular morphology in studies of this type

The importance of plasma apolipoprotein E concentration in addition to its common polymorphism on inter-individual variation in lipid levels: results from Apo Europe

The ApoEurope group, collaborating centres, and their associated investigators: Portugal: Unidade de Química Clínica, Instituto Nacional de Saúde, Lisboa: Maria do Carmo Martins, Maria Odete Rodrigues, Maria Isabel Albergaria, Maria Liseta AlpendreInterindividual variation in the concentration of plasma lipids which are associated with coronary artery disease (CAD) risk is determined by a combination of genetic and environmental factors. This study investigates the effects of apoE genotype and plasma concentration on cholesterol and triglycerides (TG) levels in subjects from five countries: Finland, France, Northern Ireland, Portugal, and Spain. Age and sex significantly influenced serum cholesterol, TG and apoE concentrations. The age effect differs in males and females. The allele frequencies of the apoE gene, one of the most widely studied CAD susceptibility genes, were determined: the epsilon2 allele frequency and the apoE concentration showed a north-south increasing gradient while the epsilon4 allele frequency showed the reverse. ApoE plays an important role in lipid metabolism. Total cholesterol and TG concentrations were significantly dependent on apoE genotype in both sexes. These differences in lipids between genotypes were more pronounced when plasma apoE concentrations were taken into account