Mikael Benson

Network properties of complex human disease genes identified through genome-wide association studies.

Background Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs), thereby eliminating discovery bias. Principal findings We derived a network of complex diseases (n = 54) and complex disease genes (n = 349) to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process. Conclusions This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.

Increased expression of aquaporin 3 in atopic eczema.

Background:  Dry skin in atopic eczema depends on increased water loss. The mechanisms behind this are poorly understood. The aim of this work was to identify genes that may contribute to water loss in eczema.

Modules, networks and systems medicine for understanding disease and aiding diagnosis

Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.

An assay to evaluate the long-term effects of inflammatory mediators on murine airway smooth muscle: evidence that TNFalpha up-regulates 5-HT(2A)-mediated contraction.

Asthma research is arguably limited by an absence of appropriate animal models to study the pharmacology of inflammatory mediators that affect airway hyperresponsiveness and remodelling. Here we assessed an assay based on mouse tracheal segments cultured for 1–32 days, and investigated contractile responses mediated by muscarinic and 5‐hydroxytryptamine (5‐HT) receptors following long‐term exposure to tumour necrosis factor‐alpha (TNFα). Following culture, in the absence of TNFα, maximum contractile responses to KCl and carbachol were similar, with an increase in response up to day two and a decrease to a stable level after 8 days. Maximal relaxations to isoprenaline were not affected by the culture procedure. The potency of KCl and isoprenaline increased throughout the study. DNA microarray data revealed that global gene expression changes were greater when tissues were introduced to culture than when they were maintained in culture. The morphology of smooth muscle cells was maintained throughout the culture period. 5‐HT induced a weak contraction in both fresh and cultured (up to 8 days) segments. Culture with TNFα produced a time‐ and concentration‐dependent increase in the maximal contraction to 5‐HT, evidently mediated by 5‐HT2A receptors, whereas, the potency for carbachol was reduced. In conclusion, the phenotype of airway smooth muscle remained largely intact during the culture period, even though minor changes were obtained during the first days of culture. The time‐dependent effect of TNFα indicates the importance of studying the long‐term effect of cytokines on the smooth muscle cells in relation to airway hyperresponsiveness and remodelling.

Rapid reprogramming of epigenetic and transcriptional profiles in mammalian culture systems

BackgroundThe DNA methylation profiles of mammalian cell lines differ from those of the primary tissues from which they were derived, exhibiting increasing divergence from the in vivo methylation profile with extended time in culture. Few studies have directly examined the initial epigenetic and transcriptional consequences of adaptation of primary mammalian cells to culture, and the potential mechanisms through which this epigenetic dysregulation occurs is unknown.ResultsWe demonstrate that adaptation of mouse embryonic fibroblasts to cell culture results in a rapid reprogramming of epigenetic and transcriptional states. We observed global 5-hydroxymethylcytosine (5hmC) erasure within three days of culture initiation. Loss of genic 5hmC was independent of global 5-methylcytosine (5mC) levels and could be partially rescued by addition of vitamin C. Significantly, 5hmC loss was not linked to concomitant changes in transcription. Discrete promoter-specific gains of 5mC were also observed within seven days of culture initiation. Against this background of global 5hmC loss we identified a handful of developmentally important genes that maintained their 5hmC profile in culture, including the imprinted loci Gnas and H19. Similar outcomes were identified in the adaption of CD4+ T cells to culture.ConclusionsWe report a dramatic and novel consequence of adaptation of mammalian cells to culture in which global loss of 5hmC occurs, suggesting rapid concomitant loss of methylcytosine dioxygenase activity. The observed epigenetic and transcriptional re-programming occurs much earlier than previously assumed, and has significant implications for the use of cell lines as faithful mimics of in vivo epigenetic and physiological processes.

Network properties of human disease genes with pleiotropic effects.

BackgroundThe ability of a gene to cause a disease is known to be associated with the topological position of its protein product in the molecular interaction network. Pleiotropy, in human genetic diseases, refers to the ability of different mutations within the same gene to cause different pathological effects. Here, we hypothesized that the ability of human disease genes to cause pleiotropic effects would be associated with their network properties.ResultsShared genes, with pleiotropic effects, were more central than specific genes that were associated with one disease, in the protein interaction network. Furthermore, shared genes associated with phenotypically divergent diseases (phenodiv genes) were more central than those associated with phenotypically similar diseases. Shared genes had a higher number of disease gene interactors compared to specific genes, implying higher likelihood of finding a novel disease gene in their network neighborhood. Shared genes had a relatively restricted tissue co-expression with interactors, contrary to specific genes. This could be a function of shared genes leading to pleiotropy. Essential and phenodiv genes had comparable connectivities and hence we investigated for differences in network attributes conferring lethality and pleiotropy, respectively. Essential and phenodiv genes were found to be intra-modular and inter-modular hubs with the former being highly co-expressed with their interactors contrary to the latter. Essential genes were predominantly nuclear proteins with transcriptional regulation activities while phenodiv genes were cytoplasmic proteins involved in signal transduction.ConclusionThe properties of a disease gene in molecular interaction network determine its role in manifesting different and divergent diseases.

Making sense of big data in health research: Towards an EU action plan

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of “big data” for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.

Bridging the gap between systems biology and medicine

Systems biology has matured considerably as a discipline over the last decade, yet some of the key challenges separating current research efforts in systems biology and clinically useful results are only now becoming apparent. As these gaps are better defined, the new discipline of systems medicine is emerging as a translational extension of systems biology. How is systems medicine defined? What are relevant ontologies for systems medicine? What are the key theoretic and methodologic challenges facing computational disease modeling? How are inaccurate and incomplete data, and uncertain biologic knowledge best synthesized in useful computational models? Does network analysis provide clinically useful insight? We discuss the outstanding difficulties in translating a rapidly growing body of data into knowledge usable at the bedside. Although core-specific challenges are best met by specialized groups, it appears fundamental that such efforts should be guided by a roadmap for systems medicine drafted by a coalition of scientists from the clinical, experimental, computational, and theoretic domains.

Interleukin 6 response to urinary tract infection in childhood.

This study analyzed the interleukin 6 (IL-6) response in 114 children with suspected urinary tract infection (UTI). Urine and serum samples were obtained at the time of enrollment. There were 90 children with UTI, 41 with and 49 without a temperature > or = 38.5 degrees C. The remaining 24 children did not have bacteriuria; 11 were febrile and 13 were not. The urinary IL-6 concentrations were higher in the children with UTI (mean, 129 units/ml) than in the children without bacteriuria (mean, 7 units/ml, P < 0.01). In contrast the serum IL-6 did not differ between children with or without UTI or between children with or without a temperature > or = 38.5 degrees C. The urinary IL-6 response was higher in children who were infected with P fimbriated Escherichia coli than in other children with UTI (P < 0.05). There was a correlation of urinary IL-6 with the degree of proteinuria, hematuria and urinary leukocyte counts (P < 0.001, P < 0.05, P < 0.05, respectively) but not with serum IL-6, CRP or temperature, and of serum IL-6 to C-reactive protein (P = 0.053) and renal concentrating capacity (P < 0.05). The results demonstrate that infections of the urinary tract activate an IL-6 response in children and that the magnitude of the IL-6 response is influenced by the properties of the infecting strain.

Expression of Toll-like receptor 9 in nose, peripheral blood and bone marrow during symptomatic allergic rhinitis.

BackgroundAllergic rhinitis is an inflammatory disease of the upper airway mucosa that also affects leukocytes in bone marrow and peripheral blood. Toll-like receptor 9 (TLR9) is a receptor for unmethylated CpG dinucleotides found in bacterial and viral DNA. The present study was designed to examine the expression of TLR9 in the nasal mucosa and in leukocytes derived from different cellular compartments during symptomatic allergic rhinitis.MethodsThe study was based on 32 patients with seasonal allergic rhinitis and 18 healthy subjects, serving as controls. Nasal biopsies were obtained before and after allergen challenge. Bone marrow, peripheral blood and nasal lavage fluid were sampled outside and during pollen season. The expression of TLR9 in tissues and cells was analyzed using immunohistochemistry and flow cytometry, respectively.ResultsTLR9 was found in several cell types in the nasal mucosa and in different leukocyte subpopulations derived from bone marrow, peripheral blood and nasal lavage fluid. The leukocyte expression was generally higher in bone marrow than in peripheral blood, and not affected by symptomatic allergic rhinitis.ConclusionThe widespread expression of TLR9 in the nasal mucosa along with its rich representation in leukocytes in different compartments, demonstrate the possibility for cells involved in allergic airway inflammation to directly interact with bacterial and viral DNA.