Meaning behind measurement : self-comparisons affect responses to health related quality of life questionnaires

Purpose The subjective nature of quality of life is particularly pertinent to the domain of health-related quality of life (HRQOL) research. The extent to which participants’ responses are affected by subjective information and personal reference frames is unknown. This study investigated how an elderly population living with a chronic metabolic bone disorder evaluated self-reported quality of life. Methods Participants (n = 1,331) in a multi-centre randomised controlled trial for the treatment of Paget’s disease completed annual HRQOL questionnaires, including the SF-36, EQ-5D and HAQ. Supplementary questions were added to reveal implicit reference frames used when making HRQOL evaluations. Twenty-one participants (11 male, 10 female, aged 59–91 years) were interviewed retrospectively about their responses to the supplementary questions, using cognitive interviewing techniques and semi-structured topic guides. Results The interviews revealed that participants used complex and interconnected reference frames to promote response shift when making quality of life evaluations. The choice of reference frame often reflected external factors unrelated to individual health. Many participants also stated that they were unclear whether to report general or disease-related HRQOL. Conclusions It is important, especially in clinical trials, to provide instructions clarifying whether ‘quality of life’ refers to disease-related HRQOL. Information on selfcomparison reference frames is necessary for the interpretation of responses to questions about HRQOL.The Chief Scientist Office of the Scottish Government Health Directorates, The PRISM funding bodies (the Arthritis Research Campaign, the National Association for the Relief of Paget’s disease and the Alliance for Better Bone Health)Peer reviewedAuthor final versio

Cellular expression, trafficking, and function of two isoforms of human ULBP5/RAET1G

Background: The activating immunoreceptor NKG2D is expressed on Natural Killer (NK) cells and subsets of T cells. NKG2D contributes to anti-tumour and anti-viral immune responses in vitro and in vivo. The ligands for NKG2D in humans are diverse proteins of the MIC and ULBP/RAET families that are upregulated on the surface of virally infected cells and tumours. Two splicing variants of ULBP5/RAET1G have been cloned previously, but not extensively characterised. Methodology/Principal Findings: We pursue a number of approaches to characterise the expression, trafficking, and function of the two isoforms of ULBP5/RAET1G. We show that both transcripts are frequently expressed in cell lines derived from epithelial cancers, and in primary breast cancers. The full-length transcript, RAET1G1, is predicted to encode a molecule with transmembrane and cytoplasmic domains that are unique amongst NKG2D ligands. Using specific anti-RAET1G1 antiserum to stain tissue microarrays we show that RAET1G1 expression is highly restricted in normal tissues. RAET1G1 was expressed at a low level in normal gastrointestinal epithelial cells in a similar pattern to MICA. Both RAET1G1 and MICA showed increased expression in the gut of patients with celiac disease. In contrast to healthy tissues the RAET1G1 antiserum stained a wide variety or different primary tumour sections. Both endogenously expressed and transfected RAET1G1 was mainly found inside the cell, with a minority of the protein reaching the cell surface. Conversely the truncated splicing variant of RAET1G2 was shown to encode a soluble molecule that could be secreted from cells. Secreted RAET1G2 was shown to downregulate NKG2D receptor expression on NK cells and hence may represent a novel tumour immune evasion strategy. Conclusions/Significance: We demonstrate that the expression patterns of ULBP5RAET1G are very similar to the well-characterised NKG2D ligand, MICA. However the two isoforms of ULBP5/RAET1G have very different cellular localisations that are likely to reflect unique functionality

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

Effect of Differential N-linked and O-linked Mannosylation on Recognition of Fungal Antigens by Dendritic Cells

BACKGROUND. An experimental approach for improving vaccine efficacy involves targeting antigens to mannose receptors (MRs) on dendritic cells (DCs) and other professional antigen presenting cells. Previously, we demonstrated that mannosylated Pichia pastoris-derived recombinant proteins exhibited increased immunogenicity compared to proteins lacking mannosylation. In order to gain insight into the mechanisms responsible for this observation, the present study examined the cellular uptake of the mannosylated and deglycosylated recombinant proteins. METHODOLOGY/PRINCIPAL FINDINGS. Utilizing transfected cell lines, roles for the macrophage mannose receptor (MMR, CD206) and DC-SIGN (CD209) in the recognition of the mannosylated, but not deglycosylated, antigens were demonstrated. The uptake of mannosylated antigens into murine bone marrow-derived DCs (BMDCs) was inhibited by yeast mannans (YMs), suggesting a mannose-specific C-type lectin receptor-dependent process, while the uptake of deglycosylated antigens remained unaffected. In particular, antigens with both N-linked and extensive O-linked mannosylation showed the highest binding and uptake by BMDCs. Finally, confocal microscopy studies revealed that both mannosylated and deglycosylated P. pastoris-derived recombinant proteins localized in MHC class II+ compartments within BMDCs. CONCLUSIONS/SIGNIFICANCE. Taken together with our previous results, these data suggest that increased uptake by mannose-specific C-type lectin receptors is the major mechanism responsible for the enhanced antigenicity seen with mannosylated proteins. These findings have important implications for vaccine design and contribute to our understanding of how glycosylation affects the immune response to eukaryotic pathogens.National Institutes of Health (RO1 AI25780, RO1 AI37532

Gene Expression Patterns of Oxidative Phosphorylation Complex I Subunits Are Organized in Clusters

After the radiation of eukaryotes, the NUO operon, controlling the transcription of the NADH dehydrogenase complex of the oxidative phosphorylation system (OXPHOS complex I), was broken down and genes encoding this protein complex were dispersed across the nuclear genome. Seven genes, however, were retained in the genome of the mitochondrion, the ancient symbiote of eukaryotes. This division, in combination with the three-fold increase in subunit number from bacteria (N = ∼14) to man (N = 45), renders the transcription regulation of OXPHOS complex I a challenge. Recently bioinformatics analysis of the promoter regions of all OXPHOS genes in mammals supported patterns of co-regulation, suggesting that natural selection favored a mechanism facilitating the transcriptional regulatory control of genes encoding subunits of these large protein complexes. Here, using real time PCR of mitochondrial (mtDNA)- and nuclear DNA (nDNA)-encoded transcripts in a panel of 13 different human tissues, we show that the expression pattern of OXPHOS complex I genes is regulated in several clusters. Firstly, all mtDNA-encoded complex I subunits (N = 7) share a similar expression pattern, distinct from all tested nDNA-encoded subunits (N = 10). Secondly, two sub-clusters of nDNA-encoded transcripts with significantly different expression patterns were observed. Thirdly, the expression patterns of two nDNA-encoded genes, NDUFA4 and NDUFA5, notably diverged from the rest of the nDNA-encoded subunits, suggesting a certain degree of tissue specificity. Finally, the expression pattern of the mtDNA-encoded ND4L gene diverged from the rest of the tested mtDNA-encoded transcripts that are regulated by the same promoter, consistent with post-transcriptional regulation. These findings suggest, for the first time, that the regulation of complex I subunits expression in humans is complex rather than reflecting global co-regulation

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

<p>Abstract</p> <p>Background</p> <p>The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions.</p> <p>Results</p> <p>In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification.</p> <p>Conclusion</p> <p>High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.</p

Mammalian Genes Preferentially Co-Retained in Radiation Hybrid Panels Tend to Avoid Coexpression

Coexpression has been frequently used to explore modules of functionally related genes in eukaryotic genomes. However, we found that genetically interacting mammalian genes identified through radiation hybrid (RH) genotypes tend not to be coexpressed across tissues. This pattern remained unchanged after controlling for potential confounding factors, including chromosomal linkage, chromosomal distance, and gene duplication. Because >99.9% of the genetically interacting genes were identified according to the higher co-retention frequencies, our observation implies that coexpression is not necessarily an indication of the need for the co-presence of two genes in the genome, which is a prerequisite for cofunctionality of their coding proteins in the cell. Therefore, coexpression information must be applied cautiously to the exploration of the functional relatedness of genes in a genome

Acute kidney disease and renal recovery : consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of > 90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD