Biophysical characterisation and profile of HLA-specific antibodies in transplantation

Abstract Following five decades of kidney transplantation, increasingly high risk immunological kidney transplantation (which previously was considered as sub-optimal) are carried out. The risk stratification with the current available assays have allowed safe transplantation in low risk non-sensitised patients and direct transplantation in high risk highly sensitised patients by removal of circulating donor specific antibodies (DSA) with reasonable outcomes. However, a large number of patients with chronic kidney disease and with low or intermediate antibody levels measured by current assay, the best way forward is uncertain resulting in denial of transplantation in some cases. Whilst in other cases, the solid phase Luminex assay may under or overestimate the risks of rejection and graft failure following direct kidney transplantation. Currently only IgG-class of DSA is considered immunologically important and routinely measured in clinical laboratories. Other bio-physiological characteristics such as class, sub-class and binding kinetics of DSA may be more specific for risk stratification of immunological risks. In this thesis, we studied effect of de novo IgM class of HLA-specific antibodies on outcome of kidney transplantation and characterised binding kinetics and strength of HLA-specific antibodies. De novo IgM or IgG HLA-specific responses alone were not associated with adverse outcomes following kidney transplantation. Presence of both IgM and IgG responses, however, was associated with poor graft function at 36 months. There was no temporal relationship of antibody response and episodes of rejections. De novo Donor specific responses were less frequent compared to non-specific responses. A shorter follow-up and use of modern triple immunosuppressant therapy (Tacrolimus, Mycophenolate and Steroid) may explain this. Binding kinetics measured by biosensor assay- surface plasmon resonance (SPR) on purified monoclonal HLA-specific antibodies showed binding kinetics and strength differed between HLA alleles despite same epitope and paratope interactions. There was a tendency towards higher affinity and faster association rate for HLA protein that was the initial immunizing antigen for the corresponding monoclonal HLA-specific antibodies. The dissociation constant (KD) of human monoclonal HLA-specific antibodies range between 10-8 to 10-10 M. Thermodynamic analysis showed higher Gibbs free energy released for interactions with higher binding strength. The binding strength of mixed monoclonal HLA-specific antibodies is generally average of the strength of individual monoclonal HLA-specific antibodies. Enriched polyclonal HLA-specific antibodies from clinical sample gave distinct binding response on bio-sensor based on SPR assay. Quantification of polyclonal HLA-specific antibodies using sandwich ELISA and SPR allowed quantitative measurement of binding kinetics and strengths. A range of binding strength was observed between patients and within same patient antibodies of different affinities was observed. Thus the antibodies could be grouped in four groups based on the strength of binding and this can serve as additional biomarker for risk stratifications

'A Better Way to Measure Choices' Discrete Choice Experiment and Conjoint Analysis Studies in Nephrology: A Literature Review

Discrete choice experiments (DCE) and conjoint analysis (CA) are increasingly used to address health policy issues. This is because the DCE and CA approaches have theoretical foundations in the characteristics theory of demand, which assumes goods, services, or healthcare provision, can be valued in terms of their characteristics (or attributes). As a result, such analysis is grounded in economic theory, lending theoretical validity to this approach. With DCEs, respondents are also assumed to act in a utility-maximising manner and make choices contingent upon the levels of attributes in DCE scenarios. Therefore, choice data can be analysed using econometric methods compatible with random utility theory (RUT) or random regret minimisation (RRM) theory. This means they have additional foundations in economic theory. In contrast, analyses described as CAs are sometimes compatible with RUT or RRM, but by definition they do not have to be. In this paper we review the CA/DCE evidence relating to nephrology. The CA/DCE approach is then compared with other approaches used to provide either quality of life information or preference information relating to nephrology. We conclude by providing an assessment of the value of undertaking CA or DCE analysis in nephrology, comparing the application of CA/DCEs in nephrology with other methodological approaches.</p

Defining clinically pathogenic HLA-specific antibodies - granular details in characteristics in pre and early time following HLA-antibody incompatible kidney transplantation

Antibodies against donor HLA determine access to solid organ transplantation and in many cases the outcome of transplantation, but graft failure is not an inevitable consequence of their presence. Much research has been performed with two main aims – which antibodies represent the highest risk factor prior to transplantation, and second to understand how donor specific HLA antibodies behave after transplantation, with a long-term aim of being able to manipulate their production. HLA antibody incompatible kidney transplantation is the best model for examining antibody responses and this review looks at methods for interrogating the antibodies using ‘traditional’ snapshot techniques such as cytoxicity testing, and newer dissection techniques such as antibody subclass, complement binding and activity and affinity. Integral to the understanding of the large datasets generated is sophisticated mathematical analysis using techniques such as decision tree analysis and unsupervised machine learning. This review examines key aspects of this work, performed by us and others

Behaviour of non-donor specific antibodies during rapid re-synthesis of donor specific HLA antibodies after antibody incompatible renal transplantation

Background: HLA directed antibodies play an important role in acute and chronic allograft rejection. During viral infection of a patient with HLA antibodies, the HLA antibody levels may rise even though there is no new immunization with antigen. However it is not known whether the converse occurs, and whether changes on non-donor specific antibodies are associated with any outcomes following HLA antibody incompatible renal transplantation. Methods: 55 patients, 31 women and 24 men, who underwent HLAi renal transplant in our center from September 2005 to September 2010 were included in the studies. We analysed the data using two different approaches, based on; i) DSA levels and ii) rejection episode post transplant. HLA antibody levels were measured during the early post transplant period and corresponding CMV, VZV and Anti-HBs IgG antibody levels and blood group IgG, IgM and IgA antibodies were quantified. Results: Despite a significant DSA antibody rise no significant non-donor specific HLA antibody, viral or blood group antibody rise was found. In rejection episode analyses, multiple logistic regression modelling showed that change in the DSA was significantly associated with rejection (p = 0.002), even when adjusted for other antibody levels. No other antibody levels were predictive of rejection. Increase in DSA from pre treatment to a post transplant peak of 1000 was equivalent to an increased chance of rejection with an odds ratio of 1.47 (1.08, 2.00). Conclusion: In spite of increases or decreases in the DSA levels, there were no changes in the viral or the blood group antibodies in these patients. Thus the DSA rise is specific in contrast to the viral, blood group or third party antibodies post transplantation. Increases in the DSA post transplant in comparison to pre-treatment are strongly associated with occurrence of rejection

A new data-driven model for post-transplant antibody dynamics in high risk kidney transplantation

The dynamics of donor specific human leukocyte antigen (HLA) antibodies during early stage after transplantation are of great clinical interest as they are considered to be associated with short and long term outcomes (graft function and rejection). However, the limited number of such detailed donor-specific antibody (DSA) time series currently available and their diverse patterns have made the task of modelling difficult. Focusing on one typical dynamic pattern with rapid falls and stable settling levels, a novel data-driven model in the form of a third order differential equation has been developed to describe such post-transplant dynamics in DSAs for the first time. A variational Bayesian inference method has been applied to select a model and learn its parameters for 39 time series from two groups of graft recipients, i.e. patients with and without acute antibody-mediated rejection (AMR) episodes. Linear and nonlinear dynamic models of different order were attempted to fit the time series, and the third order linear model provided the best description of the common features in both groups. Both deterministic and stochastic parameters are found to be significantly different in the AMR and no-AMR groups. Eigenvalues have been calculated for each fitting, and phase portraits have been plotted to show the trajectories of the system states for both groups. The results from our previous study with fewer cases have been further confirmed: the time series in the AMR group have significantly higher frequency of oscillations and faster dissipation rates, which may potentially lead to better laboratory measurement strategy and a better chance of understanding the underlying immunological mechanisms

Narrowing the gap in careers in clinical research and academia for healthcare professionals: A scoping review on the role of major funding bodies in the UK

Differential attainment (DA) exists in research and academia, where individuals with protected characteristics face barriers to progression at different stages from selection in training or career pathways through to obtaining funding and getting research published. The causes of DA are multifactorial, however more barriers are associated with an individual’s gender, race, ethnicity, sexual orientation, disability or other social and economic factors rather than academic factors related to research. DA is seen across medicine and healthcare therefore it is likely a manifestation of wider inequalities experienced by these individuals within society. This scoping review takes a first step at exploring DA through the lens of equality, diversity and inclusion in research and academia, specific to healthcare professionals in medicine, in the UK. Given the paucity of published data, benchmarking and investigation of the causes of DA and access in this area, this review seeks to identify what published reports exploring this issue reveal. There has been mixed success in the area of gender equality with the Athena Swan benchmarking exercise; however differences in outcomes exist within gender when other protected characteristics, such as ethnicity, are also explored. The DA observed among women despite the Athena Swan programme demonstrates other factors such as allyship, apprenticeship, sponsorship and mentoring which may be accessible to some individuals, but not others. Furthermore, ethnicity appears to be a barrier to accessing this form of support, and non-Black and Minority Ethnic (BAME) women appear to be more privileged to receiving this type of support. Without more research into the lived experiences of individuals from non-traditional backgrounds at the micro-level, as well as data across the career progression pathway over time at the macro-level, the problem of DA is unlikely to improve. If anything, lack of openness and transparency around such data at an organisational level, may exacerbate the sense of injustice within research and academia among individuals with protected characteristics, especially given that the perceived sense of DA is very real for them. The purpose of this paper is to start the conversation with stakeholders within research and academia, about DA and commence the process of reducing the gap using equality, diversity and inclusion as fundamental concepts for achieving a level playing field for all. This type of accountability is essential for developing trust and in the system. Such open conversations need to happen across every organisation, that is a stakeholder of research and academia in the UK.Peer reviewe

Does Gender or Religion Contribute to the Risk of COVID-19 in Hospital Doctors?

This webpage details and provides the research study conducted in the United Kingdom through online surveys focusing on the relationship between healthcare workplace prevention efforts, COVID-19 risks, religious identity, and gender. The research study focuses on healthcare workers, primarily hospital doctors and mental health doctors. A PDF of the entire study is available on the webpage

Subclass analysis of donor HLA-specific IgG in antibody-incompatible renal transplantation reveals a significant association of IgG4 with rejection and graft failure

Donor HLA-specific antibodies (DSAs) can cause rejection and graft loss after renal transplantation, but their levels measured by the current assays are not fully predictive of outcomes. We investigated whether IgG subclasses of DSA were associated with early rejection and graft failure. DSA levels were determined pretreatment, at the day of peak pan-IgG level and at 30 days post-transplantation in eighty HLA antibody-incompatible kidney transplant recipients using a modified microbead assay. Pretreatment IgG4 levels were predictive of acute antibody-mediated rejection (P = 0.003) in the first 30 days post-transplant. Pre-treatment presence of IgG4 DSA (P = 0.008) and day 30 IgG3 DSA (P = 0.03) was associated with poor graft survival. Multivariate regression analysis showed that in addition to pan-IgG levels, total IgG4 levels were an independent risk factor for early rejection when measured pretreatment, and the presence of pretreatment IgG4 DSA was also an independent risk factor for graft failure. Pretreatment IgG4 DSA levels correlated independently with higher risk of early rejection episodes and medium-term death-censored graft survival. Thus, pretreatment IgG4 DSA may be used as a biomarker to predict and risk stratify cases with higher levels of pan-IgG DSA in HLA antibody-incompatible transplantation. Further investigations are needed to confirm our results

Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation

Clinical datasets are commonly limited in size, thus restraining applications of Machine Learning (ML)techniques for predictive modelling in clinical research and organ transplantation. We explored thepotential of Decision Tree (DT) and Random Forest (RF) classification models, in the context of smalldataset of 80 samples, for outcome prediction in high-risk kidney transplantation. The DT and RF modelsidentified the key risk factors associated with acute rejection: the levels of the donor specific IgG anti-bodies, the levels of IgG4 subclass and the number of human leucocyte antigen mismatches betweenthe donor and recipient. Furthermore, the DT model determined dangerous levels of donor-specific IgGsubclass antibodies, thus demonstrating the potential of discovering new properties in the data whentraditional statistical tools are unable to capture them. The DT and RF classifiers developed in this workpredicted early transplant rejection with accuracy of 85%, thus offering an accurate decision supporttool for doctors tasked with predicting outcomes of kidney transplantation in advance of the clinicalintervention