Altered Chromosomal Positioning, Compaction, and Gene Expression with a Lamin A/C Gene Mutation

Lamins A and C, encoded by the LMNA gene, are filamentous proteins that form the core scaffold of the nuclear lamina. Dominant LMNA gene mutations cause multiple human diseases including cardiac and skeletal myopathies. The nuclear lamina is thought to regulate gene expression by its direct interaction with chromatin. LMNA gene mutations may mediate disease by disrupting normal gene expression.To investigate the hypothesis that mutant lamin A/C changes the lamina's ability to interact with chromatin, we studied gene misexpression resulting from the cardiomyopathic LMNA E161K mutation and correlated this with changes in chromosome positioning. We identified clusters of misexpressed genes and examined the nuclear positioning of two such genomic clusters, each harboring genes relevant to striated muscle disease including LMO7 and MBNL2. Both gene clusters were found to be more centrally positioned in LMNA-mutant nuclei. Additionally, these loci were less compacted. In LMNA mutant heart and fibroblasts, we found that chromosome 13 had a disproportionately high fraction of misexpressed genes. Using three-dimensional fluorescence in situ hybridization we found that the entire territory of chromosome 13 was displaced towards the center of the nucleus in LMNA mutant fibroblasts. Additional cardiomyopathic LMNA gene mutations were also shown to have abnormal positioning of chromosome 13, although in the opposite direction.These data support a model in which LMNA mutations perturb the intranuclear positioning and compaction of chromosomal domains and provide a mechanism by which gene expression may be altered

The CO-Regulation Database (CORD): A Tool to Identify Coordinately Expressed Genes

<div><p>Background</p><p>Meta-analysis of gene expression array databases has the potential to reveal information about gene function. The identification of gene-gene interactions may be inferred from gene expression information but such meta-analysis is often limited to a single microarray platform. To address this limitation, we developed a gene-centered approach to analyze differential expression across thousands of gene expression experiments and created the CO-Regulation Database (CORD) to determine which genes are correlated with a queried gene.</p><p>Results</p><p>Using the GEO and ArrayExpress database, we analyzed over 120,000 group by group experiments from gene microarrays to determine the correlating genes for over 30,000 different genes or hypothesized genes. CORD output data is presented for sample queries with focus on genes with well-known interaction networks including p16 (<i>CDKN2A</i>), vimentin (<i>VIM)</i>, MyoD (<i>MYOD1</i>). <i>CDKN2A</i>, <i>VIM</i>, and <i>MYOD1</i> all displayed gene correlations consistent with known interacting genes.</p><p>Conclusions</p><p>We developed a facile, web-enabled program to determine gene-gene correlations across different gene expression microarray platforms. Using well-characterized genes, we illustrate how CORD's identification of co-expressed genes contributes to a better understanding a gene's potential function. The website is found at <a href="http://cord-db.org" target="_blank">http://cord-db.org</a>.</p></div

Documenting Penicillin Allergy: The Impact of Inconsistency

Background: Allergy documentation is frequently inconsistent and incomplete. The impact of this variability on subsequent treatment is not well described. Objective: To determine how allergy documentation affects subsequent antibiotic choice. Design: Retrospective, cohort study. Participants: 232,616 adult patients seen by 199 primary care providers (PCPs) between January 1, 2009 and January 1, 2014 at an academic medical system. Main Measures: Inter-physician variation in beta-lactam allergy documentation; antibiotic treatment following beta-lactam allergy documentation. Key Results: 15.6% of patients had a reported beta-lactam allergy. Of those patients, 39.8% had a specific allergen identified and 22.7% had allergic reaction characteristics documented. Variation between PCPs was greater than would be expected by chance (all p Conclusions: Provider documentation of beta-lactam allergy is highly variable, and details of the allergy are infrequently documented. Classification of a patient as beta-lactam allergic and incomplete documentation regarding the details of the allergy lead to beta-lactam avoidance and use of other antimicrobial agents, behaviors that may adversely impact care quality and cost.</p

CORD results for <i>MYOD1</i>.

<p><b>A</b>) The differentiation of muscle stem cells (satellite cells) to myoblasts and ultimately to skeletal muscle is under the control of muscle regulatory factors including the transcription factor MyoD. CORD output for <i>MYOD1</i> demonstrates co- expression of other muscle regulatory factors like myogenin (<i>MYOG</i>) and many genes implicated in muscle differentiation. <b>B</b>) The MyoD1 correlated genes were over representative for several KEGG pathways relating to muscle such as “Cardiac muscle contraction” and “Dilated cardiomyopathy.”</p

Top 20 Genes Co-expressed with vimentin (<i>VIM</i>) identified by CORD.

<p>Top 20 Genes Co-expressed with vimentin (<i>VIM</i>) identified by CORD.</p

CORD results for <i>VIM</i>.

<p><b>A</b>) The epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial transitions are important oncogenic pathways where vimentin (<i>VIM</i>) plays a central role. Twelve of the top 20 most correlated <i>VIM</i> genes affect the EMT transition. <b>B</b>) The EMT transitions depend heavily on cell adhesion. The <i>VIM</i>-correlated genes were over representative for several KEGG pathways in cell adhesion and cancer pathways such as “ECM-receptor interaction”, “Focal adhesion”, and “Pathways in cancer.”</p

Documenting Penicillin Allergy: The Impact of Inconsistency.

BACKGROUND:Allergy documentation is frequently inconsistent and incomplete. The impact of this variability on subsequent treatment is not well described. OBJECTIVE:To determine how allergy documentation affects subsequent antibiotic choice. DESIGN:Retrospective, cohort study. PARTICIPANTS:232,616 adult patients seen by 199 primary care providers (PCPs) between January 1, 2009 and January 1, 2014 at an academic medical system. MAIN MEASURES:Inter-physician variation in beta-lactam allergy documentation; antibiotic treatment following beta-lactam allergy documentation. KEY RESULTS:15.6% of patients had a reported beta-lactam allergy. Of those patients, 39.8% had a specific allergen identified and 22.7% had allergic reaction characteristics documented. Variation between PCPs was greater than would be expected by chance (all p<0.001) in the percentage of their patients with a documented beta-lactam allergy (7.9% to 24.8%), identification of a specific allergen (e.g. amoxicillin as opposed to "penicillins") (24.0% to 58.2%) and documentation of the reaction characteristics (5.4% to 51.9%). After beta-lactam allergy documentation, patients were less likely to receive penicillins (Relative Risk [RR] 0.16 [95% Confidence Interval: 0.15-0.17]) and cephalosporins (RR 0.28 [95% CI 0.27-0.30]) and more likely to receive fluoroquinolones (RR 1.5 [95% CI 1.5-1.6]), clindamycin (RR 3.8 [95% CI 3.6-4.0]) and vancomycin (RR 5.0 [95% CI 4.3-5.8]). Among patients with beta-lactam allergy, rechallenge was more likely when a specific allergen was identified (RR 1.6 [95% CI 1.5-1.8]) and when reaction characteristics were documented (RR 2.0 [95% CI 1.8-2.2]). CONCLUSIONS:Provider documentation of beta-lactam allergy is highly variable, and details of the allergy are infrequently documented. Classification of a patient as beta-lactam allergic and incomplete documentation regarding the details of the allergy lead to beta-lactam avoidance and use of other antimicrobial agents, behaviors that may adversely impact care quality and cost

CORD results for <i>CDKN2A</i>.

<p><b>A</b>) <i>CDKN2A</i> encoding p16 plays a significant role in the cell cycle by regulating the initiation of DNA replication. A simplified diagram shows select genes that play a major role in the cell cycle. CORD identifies many genes known to play major roles in the cell cycle by determining genes co-regulated with <i>CDKN2A</i> (bolded text.) <b>B</b>) The <i>CDKN2A</i>-correlated genes were over representative for several KEGG pathways in cancer and the cell cycle including “DNA replication”, “p53 signaling”, and “cell cycle.”</p

Determination of co-regulated genes.

<p><b>A</b>) The list of co-regulated genes was determined for each gene using the Individual and Grouped Factor Method. The two gene lists were then compared to one another by determining the % overlap (similarity) of the lists for the top 10 to top 1000 most correlated genes. The % overlap reached a plateau at 47%. <b>B</b>) The first derivative of the % overlap vs. the gene list size shows that on average, after comparing the top 400 genes the lists are no longer similar. <b>C, D</b>) This analysis was repeated for randomly generated gene lists and showed no change in the rate of % overlap vs. gene list size. <b>E</b>) To determine how using the Individual or Grouped Factor method effected gene-gene correlation co-efficients, we analyzed the ratio of the correlation co-efficient for each gene-gene pair. A histogram of this data shows that on average, the Grouped Factor method yielded higher correlation co-efficients.</p