A donor-specific epigenetic classifier for acute graft-versus-host disease severity in hematopoietic stem cell transplantation

Donor whole blood DNA methylation is not a strong predictor of acute graft versus host disease in unrelated donor allogeneic haematopoietic cell transplantation

Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies, however it can also result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier to reduce incidence of aGVHD by improving donor selection. Genome-wide DNA methylation was assessed in a discovery cohort of 288 HCT donors selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD. We applied a machine learning algorithm to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91. To test this classifier, we used an independent validation cohort (n = 288) selected using the same criteria as the discovery cohort. Attempts to validate the classifier failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort. Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use.

[Unrelated donor selection for allogeneic hematopoietic stem cell transplantation: Guidelines from the Francophone Society of Bone Marrow Transplantation and Cellular Therapy (SFGM-TC)]

The selection of a donor is an essential element in allogeneic hematopoietic stem cell transplantation. In the absence of an HLA-matched related donor, the selection of an unrelated donor is considered, and is currently the most common type of allogenic donor used in practice. Many criteria are considered for the selection when multiple donors are available, particularly in case of partial match. The aim of this workshop is to assist in the selection of an unrelated donor, in keeping with recent data from the literature.

Surfing the Big Data Wave: Omics Data Challenges in Transplantation

In both research and care, patients, caregivers, and researchers are facing a leap forward in the quantity of data that are available for analysis and interpretation, marking the daunting "big data era." In the biomedical field, this quantitative shift refers mostly to the -omics that permit measuring and analyzing biological features of the same type as a whole. Omics studies have greatly impacted transplantation research and highlighted their potential to better understand transplant outcomes. Some studies have emphasized the contribution of omics in developing personalized therapies to avoid graft loss. However, integrating omics data remains challenging in terms of analytical processes. These data come from multiple sources. Consequently, they may contain biases and systematic errors that can be mistaken for relevant biological information. Normalization methods and batch effects have been developed to tackle issues related to data quality and homogeneity. In addition, imputation methods handle data missingness. Importantly, the transplantation field represents a unique analytical context as the biological statistical unit is the donor-recipient pair, which brings additional complexity to the omics analyses. Strategies such as combined risk scores between 2 genomes taking into account genetic ancestry are emerging to better understand graft mechanisms and refine biological interpretations. The future omics will be based on integrative biology, considering the analysis of the system as a whole and no longer the study of a single characteristic. In this review, we summarize omics studies advances in transplantation and address the most challenging analytical issues regarding these approaches.

Personal Genome Project UK (PGP-UK): a research and citizen science hybrid project in support of personalized medicine

BACKGROUND

Molecular analyses such as whole-genome sequencing have become routine and are expected to be transformational for future healthcare and lifestyle decisions. Population-wide implementation of such analyses is, however, not without challenges, and multiple studies are ongoing to identify what these are and explore how they can be addressed.

METHODS

Defined as a research project, the Personal Genome Project UK (PGP-UK) is part of the global PGP network and focuses on open data sharing and citizen science to advance and accelerate personalized genomics and medicine.

RESULTS

Here we report our findings on using an open consent recruitment protocol, active participant involvement, open access release of personal genome, methylome and transcriptome data and associated analyses, including 47 new variants predicted to affect gene function and innovative reports based on the analysis of genetic and epigenetic variants. For this pilot study, we recruited 10 participants willing to actively engage as citizen scientists with the project. In addition, we introduce Genome Donation as a novel mechanism for openly sharing previously restricted data and discuss the first three donations received. Lastly, we present GenoME, a free, open-source educational app suitable for the lay public to allow exploration of personal genomes.

CONCLUSIONS

Our findings demonstrate that citizen science-based approaches like PGP-UK have an important role to play in the public awareness, acceptance and implementation of genomics and personalized medicine.

Oral health in geroscience: animal models and the aging oral cavity

Age is the single greatest risk factor for many diseases, including oral diseases. Despite this, a majority of preclinical oral health research has not adequately considered the importance of aging in research aimed at the mechanistic understanding of oral disease. Here, we have attempted to provide insights from animal studies in the geroscience field and apply them in the context of oral health research. In particular, we discuss the relationship between the biology of aging and mechanisms of oral disease. We also present a framework for defining and utilizing age-appropriate rodents and present experimental design considerations, such as the number of age-points used and the importance of genetic background. While focused primarily on rodent models, alternative animal models that may be particularly useful for studies of oral health during aging, such as companion dogs and marmoset monkeys, are also discussed. We hope that such information will aid in the design of future preclinical studies of geriatric dental health, thus allowing more reliability for translation of such studies to age-associated oral disease in people.

Transplant genetics and genomics

Ever since the discovery of the major histocompatibility complex, scientific and clinical understanding in the field of transplantation has been advanced through genetic and genomic studies. Candidate-gene approaches and recent genome-wide association studies (GWAS) have enabled a deeper understanding of the complex interplay of the donor-recipient interactions that lead to transplant tolerance or rejection. Genetic analysis in transplantation, when linked to demographic and clinical outcomes, has the potential to drive personalized medicine by enabling individualized risk stratification and immunosuppression through the identification of variants associated with immune-mediated complications, post-transplant disease or alterations in drug-metabolizing genes.