Complex disease genetics: present and future translational applications

A report on the British Atherosclerosis Society autumn meeting 'Genetics of Complex Diseases', Cambridge, UK, 17-18 September 2009

ChIP-on-chip analysis reveals angiopoietin 2 (Ang2, ANGPT2) as a novel target of steroidogenic factor-1 (SF-1, NR5A1) in the human adrenal gland

The nuclear receptor steroidogenic factor-1 (SF-1, NR5A1) is a key regulator of adrenal and gonadal biology. Disruption of SF-1 can lead to disorders of adrenal development, while increased SF-1 dosage has been associated with adrenocortical tumorigenesis. We aimed to identify a novel subset of SF-1 target genes in the adrenal by using chromatin immunoprecipitation (ChIP) microarrays (ChIP-on-chip) combined with systems analysis. SF-1 ChIP-on-chip was performed in NCI-H295R human adrenocortical cells using promoter tiling arrays, leading to the identification of 445 gene loci where SF-1-binding regions were located from 10 kb upstream to 3 kb downstream of a transcriptional start. Network analysis of genes identified as putative SF-1 targets revealed enrichment for angiogenic process networks. A 1.1-kb SF-1-binding region was identified in the angiopoietin 2 (Ang2, ANGPT2) promoter in a highly repetitive region, and SF-1-dependent activation was confirmed in luciferase assays. Angiogenesis is paramount in adrenal development and tumorigenesis, but until now a direct link between SF-1 and vascular remodeling has not been established. We have identified Ang2 as a potentially important novel target of SF-1 in the adrenal gland, indicating that regulation of angiogenesis might be an important additional mechanism by which SF-1 exerts its actions in the adrenal gland

Childhood Absence Epilepsy with Tonic-Clonic Seizures and Electroencephalogram 3–4-Hz Spike and Multispike–Slow Wave Complexes: Linkage to Chromosome 8q24

SummaryChildhood absence epilepsy (CAE), a common form of idiopathic generalized epilepsy, accounts for 5%–15% of childhood epilepsies. To map the chromosomal locus of persisting CAE, we studied the clinical and electroencephalographic traits of 78 members of a five-generation family from Bombay, India. The model-free affected–pedigree member method was used during initial screening with chromosome 6p, 8q, and 1p microsatellites, and only individuals with absence seizures and/or electroencephalogram 3–4-Hz spike– and multispike–slow wave complexes were considered to be affected. Significant P values of .00000–.02 for several markers on 8q were obtained. Two-point linkage analysis, assuming autosomal dominant inheritance with 50% penetrance, yielded a maximum LOD score (Zmax) of 3.6 for D8S502. No other locus in the genome achieved a significant Zmax. For five smaller multiplex families, summed Zmax was 2.4 for D8S537 and 1.7 for D8S1761. Haplotypes composed of the same 8q24 microsatellites segregated with affected members of the large family from India and with all five smaller families. Recombinations positioned the CAE gene in a 3.2-cM interval

Ibuprofen, a traditional drug that may impact the course of COVID-19 new effective formulation in nebulizable solution

The traditional formulation of ibuprofen is poorly soluble in water, so the administered dose must be 10 times higher than the dose required for a therapeutic effect. The development of a hydrosoluble form of ibuprofen can be a strategy to reach a high concentration in the lungs by using modern inhalation devices. Therefore, the development of an inhalable formulation with high bioavailability in the lungs was the leitmotiv of our investigation. The hypertonic ibuprofen solution to be nebulized (NIH) presents great relevant characteristics: bactericidal, virucidal, mucolytic and has a known anti-inflammatory property. Bactericidal and virucidal effects are related to the physico-chemical properties of Na-ibuprofenate as an amphipathic molecule. It has the capability to insert into the bilayer membranes destabilizing the structure, altering its biological properties and avoiding the duplication or infection. Our preliminary results indicate that the presence of this high ionic strength solution reduces 10 times the amount of ibuprofen necessary to kill bacteria, but also the time to kill 1x106 bacteria, from 4 h (in its absence) to only three minutes (in its presence). That was observed using Pseudomona aeruginosa, methicillin-resistant Staphylococcus aureus and Burkholderia cepacia. Also, ?in vitro´´ ibuprofen demonstrated virucidal activity against the so-called enveloped virus, a family that includes coronavirus strain (2019-nCoV). We observed too, the markedly reduced local inflammation in the airways after administering NIH lays on its ability to inhibit the enzyme cyclooxygenase and to markedly diminish reactive oxygen species (ROS). Other investigators also showed the importance of actin in the rapid spread of virus infection. Furthermore, reorganization of the actin filaments is a key step in lung inflammation induced by systemic inflammatory responses caused by SARS-CoV-2. These findings suggest that the interaction between actin proteins and S1 is involved in the 2019-nCoV infection and pathogenesis.Consequently, the possibility of interfering in this interaction could represent a valid hypothesis for the development of promising therapeutic and prevention strategies. In conclusion, we consider that treating people with COVID-19 with NIH may be beneficial and an opportunity to contribute for the current global health emergency.publishedVersionFil: García Canclini, Néstor. Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina. Instituto de Investigaciones en Ciencias de la Salud; Argentina.Fil: García Canclini, Néstor. Universidad Nacional de Córdoba. Facultad de Ciencias Médicas; Argentina.Fil: Porta, Daniela Josefina. Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina. Instituto de Investigaciones en Ciencias de la Salud; Argentina.Fil: Porta, Daniela Josefina. Universidad Nacional de Córdoba. Facultad de Ciencias Médicas; Argentina.Fil: Muñoz, Sonia Edith. Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina. Instituto de Investigaciones en Ciencias de la Salud; Argentina; Argentina.Fil: Muñoz, Sonia Edith. Universidad Nacional de Córdoba. Facultad de Ciencias Médicas; Argentina.Fil: Alasino, Roxana Valeria. Ministerio de Ciencia y Tecnología de Córdoba. Centro de Excelencia en Productos y Procesos de Córdoba; Argentina.Fil: Beltramo, Dante MiguelIcon. Ministerio de Ciencia y Tecnología de Córdoba. Centro de Excelencia en Productos y Procesos de Córdoba; Argentina

Identifying differential exon splicing using linear models and correlation coefficients

Background: With the availability of the Affymetrix exon arrays a number of tools have been developed to enable the analysis. These however can be expensive or have several pre-installation requirements. This led us to develop an analysis workflow for analysing differential splicing using freely available software packages that are already being widely used for gene expression analysis. The workflow uses the packages in the standard installation of R and Bioconductor (BiocLite) to identify differential splicing. We use the splice index method with the LIMMA framework. The main drawback with this approach is that it relies on accurate estimates of gene expression from the probe-level data. Methods such as RMA and PLIER may misestimate when a large proportion of exons are spliced. We therefore present the novel concept of a gene correlation coefficient calculated using only the probeset expression pattern within a gene. We show that genes with lower correlation coefficients are likely to be differentially spliced.Results: The LIMMA approach was used to identify several tissue-specific transcripts and splicing events that are supported by previous experimental studies. Filtering the data is necessary, particularly removing exons and genes that are not expressed in all samples and cross-hybridising probesets, in order to reduce the false positive rate. The LIMMA approach ranked genes containing single or few differentially spliced exons much higher than genes containing several differentially spliced exons. On the other hand we found the gene correlation coefficient approach better for identifying genes with a large number of differentially spliced exons.Conclusion: We show that LIMMA can be used to identify differential exon splicing from Affymetrix exon array data. Though further work would be necessary to develop the use of correlation coefficients into a complete analysis approach, the preliminary results demonstrate their usefulness for identifying differentially spliced genes. The two approaches work complementary as they can potentially identify different subsets of genes (single/few spliced exons vs. large transcript structure differences)

Intracluster correlation coefficients and coefficients of variation for perinatal outcomes from five cluster-randomised controlled trials in low and middle-income countries: results and methodological implications

Background: Public health interventions are increasingly evaluated using cluster-randomised trials in which groups rather than individuals are allocated randomly to treatment and control arms. Outcomes for individuals within the same cluster are often more correlated than outcomes for individuals in different clusters. This needs to be taken into account in sample size estimations for planned trials, but most estimates of intracluster correlation for perinatal health outcomes come from hospital-based studies and may therefore not reflect outcomes in the community. In this study we report estimates for perinatal health outcomes from community-based trials to help researchers plan future evaluations.Methods: We estimated the intracluster correlation and the coefficient of variation for a range of outcomes using data from five community-based cluster randomised controlled trials in three low-income countries: India, Bangladesh and Malawi. We also performed a simulation exercise to investigate the impact of cluster size and number of clusters on the reliability of estimates of the coefficient of variation for rare outcomes.Results: Estimates of intracluster correlation for mortality outcomes were lower than those for process outcomes, with narrower confidence intervals throughout for trials with larger numbers of clusters. Estimates of intracluster correlation for maternal mortality were particularly variable with large confidence intervals. Stratified randomisation had the effect of reducing estimates of intracluster correlation. The simulation exercise showed that estimates of intracluster correlation are much less reliable for rare outcomes such as maternal mortality. The size of the cluster had a greater impact than the number of clusters on the reliability of estimates for rare outcomes.Conclusions: The breadth of intracluster correlation estimates reported here in terms of outcomes and contexts will help researchers plan future community-based public health interventions around maternal and newborn health. Our study confirms previous work finding that estimates of intracluster correlation are associated with the prevalence of the outcome of interest, the nature of the outcome of interest ( mortality or behavioural) and the size and number of clusters. Estimates of intracluster correlation for maternal mortality need to be treated with caution and a range of estimates should be used in planning future trials

Predicting protein linkages in bacteria: Which method is best depends on task

<p>Abstract</p> <p>Background</p> <p>Applications of computational methods for predicting protein functional linkages are increasing. In recent years, several bacteria-specific methods for predicting linkages have been developed. The four major genomic context methods are: Gene cluster, Gene neighbor, Rosetta Stone, and Phylogenetic profiles. These methods have been shown to be powerful tools and this paper provides guidelines for when each method is appropriate by exploring different features of each method and potential improvements offered by their combination. We also review many previous treatments of these prediction methods, use the latest available annotations, and offer a number of new observations.</p> <p>Results</p> <p>Using <it>Escherichia coli </it>K12 and <it>Bacillus subtilis</it>, linkage predictions made by each of these methods were evaluated against three benchmarks: functional categories defined by COG and KEGG, known pathways listed in EcoCyc, and known operons listed in RegulonDB. Each evaluated method had strengths and weaknesses, with no one method dominating all aspects of predictive ability studied. For functional categories, as previous studies have shown, the Rosetta Stone method was individually best at detecting linkages and predicting functions among proteins with shared KEGG categories while the Phylogenetic profile method was best for linkage detection and function prediction among proteins with common COG functions. Differences in performance under COG versus KEGG may be attributable to the presence of paralogs. Better function prediction was observed when using a weighted combination of linkages based on reliability versus using a simple unweighted union of the linkage sets. For pathway reconstruction, 99 complete metabolic pathways in <it>E. coli </it>K12 (out of the 209 known, non-trivial pathways) and 193 pathways with 50% of their proteins were covered by linkages from at least one method. Gene neighbor was most effective individually on pathway reconstruction, with 48 complete pathways reconstructed. For operon prediction, Gene cluster predicted completely 59% of the known operons in <it>E. coli </it>K12 and 88% (333/418)in <it>B. subtilis</it>. Comparing two versions of the <it>E. coli </it>K12 operon database, many of the unannotated predictions in the earlier version were updated to true predictions in the later version. Using only linkages found by both Gene Cluster and Gene Neighbor improved the precision of operon predictions. Additionally, as previous studies have shown, combining features based on intergenic region and protein function improved the specificity of operon prediction.</p> <p>Conclusion</p> <p>A common problem for computational methods is the generation of a large number of false positives that might be caused by an incomplete source of validation. By comparing two versions of a database, we demonstrated the dramatic differences on reported results. We used several benchmarks on which we have shown the comparative effectiveness of each prediction method, as well as provided guidelines as to which method is most appropriate for a given prediction task.</p

Comparative analysis of genome-wide association studies signals for lipids, diabetes, and coronary heart disease: Cardiovascular Biomarker Genetics Collaboration

To evaluate the associations of emergent genome-wide-association study-derived coronary heart disease (CHD)-associated single nucleotide polymorphisms (SNPs) with established and emerging risk factors, and the association of genome-wide-association study-derived lipid-associated SNPs with other risk factors and CHD events

Cholesteryl Ester Transfer Protein (CETP) Polymorphisms Affect mRNA Splicing, HDL Levels, and Sex-Dependent Cardiovascular Risk

Polymorphisms in and around the Cholesteryl Ester Transfer Protein (CETP) gene have been associated with HDL levels, risk for coronary artery disease (CAD), and response to therapy. The mechanism of action of these polymorphisms has yet to be defined. We used mRNA allelic expression and splice isoform measurements in human liver tissues to identify the genetic variants affecting CETP levels. Allelic CETP mRNA expression ratios in 56 human livers were strongly associated with several variants 2.5–7 kb upstream of the transcription start site (e.g., rs247616 p = 6.4×10−5, allele frequency 33%). In addition, a common alternatively spliced CETP isoform lacking exon 9 (Δ9), has been shown to prevent CETP secretion in a dominant-negative manner. The Δ 9 expression ranged from 10 to 48% of total CETP mRNA in 94 livers. Increased formation of this isoform was exclusively associated with an exon 9 polymorphism rs5883-C>T (p = 6.8×10−10) and intron 8 polymorphism rs9930761-T>C (5.6×10−8) (in high linkage disequilibrium with allele frequencies 6–7%). rs9930761 changes a key splicing branch point nucleotide in intron 8, while rs5883 alters an exonic splicing enhancer sequence in exon 9