Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraint-based modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) γ, CCAAT/enhancer binding protein (CEBP) α, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-3-phosphate acyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic condition

Cell type-selective disease-association of genes under high regulatory load

We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3′ UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks. In summary, epigenetic mapping of active enhancers presents a promising and unbiased approach for identification of novel disease genes in a cell type-selective manne

The multifocal pattern electroretinogram in glaucoma

AbstractBackground: The pattern ERG can be used to detect early glaucomatous change, because the response of cells in the inner retina from (typically) 20°–40° of area is reduced before perimetric abnormality is certain. The multifocal pattern electroretinogram (mfPERG) allows analysis of many local regions within this area. The aim of this study was to investigate whether in patients with presumed glaucoma the mfPERG permits diagnosis and discrimination from normals.Methods: Measurements on 25 age-related normal eyes were compared to those on 23 eyes with different stages of glaucoma. A RETIScan system was used to generate a stimulus pattern of 19 hexagons, each consisting of six triangles. The triangles pattern-reversed black to white at 75 Hz. Those 19 hexagons were grouped into three stimulus regions: a central field, a middle, and a peripheral ring. The complete array subtended 48° at the eye. The hexagons alternated between black and white, in a temporal pattern that followed a corrected binary m-sequence (length 512, 10 cycles with 39 s each). The amplitudes and latencies of positive responses at approximately 50 ms (P-50) and negative responses at approximately 95 ms (N-95) were analyzed.Results: In patients with glaucoma the P-50 and N-95 components of the mfPERG were significantly reduced for the central area and both outer rings compared to normal volunteers (p<0.001, Mann–Whitney-U). The most distinct reduction was observed for N-95 and the central ring. Changes in latencies were not conclusive. The reduction of the components increased with the stage of glaucoma. A predictive model for detecting early glaucomatous changes was designed based on P-50–N-95 with 88% sensitivity and 76% specificity.Conclusion: In glaucoma a marked reduction of components, especially centrally is observed in the mfPERG. This hints to an early involvement of central ganglion cells and may be useful for future functional tests

Cell type-selective disease-association of genes under high regulatory load

We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3'UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks. In summary, epigenetic mapping of active enhancers presents a promising and unbiased approach for identification of novel disease genes in a cell type-selective manner

Sub-nanosecond Analysis of Complex Velocities

Author Institution: National Security Technologies, LLCSlides presented at the 3nd Annual Photonic Doppler Velocimetry (PDV) Conference and Workshop held at Sandia National Laboratories, Albuquerque, New Mexico, September 3-4, 2008