A strategy to incorporate prior knowledge into correlation network cutoff selection

Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization

MIgGGly (mouse IgG glycosylation analysis) - a high-throughput method for studying Fc-linked IgG N-glycosylation in mice with nanoUPLC-ESI-MS

Immunoglobulin G (IgG) N-glycosylation is crucial for its effector functions. It is a complex trait, and large sample sets are needed to discover multiple genetic factors that underlie it. While in humans such high-throughput studies of IgG N-glycans became usual, only one has been carried out in mice. Here we describe and validate a method for the relative quantification of IgG Fc-linked N-glycans in a subclassspecific manner using nano-reverse phase liquid chromatography coupled with mass-spectrometry (nanoRP-LC-MS) applied to murine IgG. High-throughput data processing is ensured by the LaCyTools software. We have shown that IgG isolation procedure is the main source of technical variation in the current protocol. The major glycoforms were quantified reliably with coefficients of variation below 6% for all the analytes with relative abundances above 5%. We have applied our method to a sample set of 3 inbred strains: BALB/c, C57BL/6 and C3H and observed differences in subclass-specific and strainspecific N-glycosylation of IgG, suggesting a significant genetic component in the regulation of Fclinked IgG N-glycosylation

Public preferences and priorities for end-of-life care in Kenya:a population-based street survey

BACKGROUND: End-of-life care needs are great in Africa due to the burden of disease. This study aimed to explore public preferences and priorities for end-of-life care in Nairobi, Kenya. METHODS: Population-based street survey of Kenyans aged ≥18; researchers approached every 10th person, alternating men and women. Structured interviews investigated quality vs. quantity of life, care priorities, preferences for information, decision-making, place of death (most and least favourite) and focus of care in a hypothetical scenario of serious illness with <1 year to live. Descriptive analysis examined variations. RESULTS: 201 individuals were interviewed (100 women) representing 17 tribes (n = 90 44.8%, Kikuyu). 56.7% (n = 114) said they would always like to be told if they had limited time left. The majority (n = 121, 61.4%) preferred quality of life over quantity i.e. extending life (n = 47, 23.9%). Keeping a positive attitude and ensuring relatives/friends were not worried were prioritised above having pain/discomfort relieved. The three most concerning problems were pain (45.8%), family burden (34.8%) and personal psychological distress (29.8%). Home was both the most (51.1% n = 98) and least (23.7% n = 44) preferred place of death. CONCLUSION: This first population-based survey on preferences and priorities for end-of-life care in Africa revealed that psycho-social domains were of greatest importance to the public, but also identified variations that require further exploration. If citizens’ preferences and priorities are to be met, the development of end-of-life care services to deliver preferences in Kenya should ensure an holistic model of palliative care responsive to individual preferences across care settings including at home

Glycoproteomic Analysis of Antibodies

Antibody glycosylation has been shown to change with various processes. This review presents mass spectrometric approaches for antibody glycosylation analysis at the level of released glycans, glycopeptides, and intact protein. With regard to IgG fragment crystallizable glycosylation, mass spectrometry has shown its potential for subclass-specific, high-throughput analysis. In contrast, because of the vast heterogeneity of peptide moieties, fragment antigen binding glycosylation analysis of polyclonal IgG relies entirely on glycan release. Next to IgG, IgA has gained some attention, and studies of its O- and N-glycosylation have revealed disease-associated glycosylation changes. Glycoproteomic analyses of IgM and IgE are lagging behind but should complete our picture of glycosylation's influence on antibody function. Molecular & Cellular Proteomics 12: 10.1074/mcp.R112.026005, 856-865, 2013

Association between Galactosylation of Immunoglobulin G and Improvement of Rheumatoid Arthritis during Pregnancy Is Independent of Sialylation

Rheumatoid arthritis (RA) is known to improve during pregnancy and to flare after delivery. Changes in the glycosylation of immunoglobulin G (IgG)'s fragment crystallizable (Fc) have been suggested to play a role herein. Recent animal studies indicate that not galactosylation but mainly sialylation is important in this respect. We aim to find new associations between IgG-Fc N-glycosylation and improvement of RA during pregnancy and the flare after delivery. Sera of RA patients (n = 251 pregnancies) and healthy controls (n = 32), all participating in a prospective cohort study on RA and pregnancy (PARA study), were collected before conception, during pregnancy, and after delivery. Using a recently developed fast and robust nanoRP-HPLC-sheath-flow-ESI-MS method the glycosylation of IgG Fc-glycopeptides was measured in a subclass specific manner, with relative standard deviations of <4% for the 8 most abundant IgG Fc glycopeptides during the entire measurement period of over 3 weeks. In patients and controls, several glycosylation changes were observed during pregnancy. In depth analysis of the association of these glycosylation changes with disease activity revealed that galactosylation, independent of sialylation, is associated with improvement of RA during pregnancy. Functional studies in human cell systems should be performed to obtain more insight into this matter

Determination of N-linked Glycosylation in Viral Glycoproteins by Negative Ion Mass Spectrometry and Ion Mobility

Glycan analysis of virion-derived glycoproteins is challenging due to the difficulties in glycoprotein isolation and low sample abundance. Here, we describe how ion mobility mass spectrometry can be used to obtain spectra from virion samples. We also describe how negative ion fragmentation of glycans can be used to probe structural features of virion glycans