Non‐HLA genomics: does it have a role in predicting haematopoietic stem cell transplantation outcome?

Abstract

Haematopoietic stem cell transplantation (HSCT) remains the only cure for many haematological neoplasms; however, the mortality rate remains high, at around 30-80%. Complications after HSCT include relapse, graft-versus-host disease, graft rejection and infection. High-resolution HLA matching has improved survival in HSCT over recent years; however, GVHD still remains a serious complication. Single nucleotide polymorphisms (SNPS) within genes that are involved with an individual's capability to mount an immune response to infectious pathogens, residual leukaemia, alloantigens or genes involved in drug metabolism have been studied for their association with HSCT outcome. Indeed, over the last 15 years, several groups, including ourselves, have demonstrated that non-HLA gene polymorphisms can be predictive of HSCT outcome. Can genetic characteristics of the patient and donor be used in the future to tailor HSCT protocols and determine GVHD prophylaxis? This review summarizes some of the recent SNP association studies in HSCT and highlights some of the disparities therein, discussing the integral problems of performing genetic association studies on diseases with complex outcomes using heterogeneous cohorts. The review will comment on recent genomewide association studies (GWAS) and discuss their relevance in this field, and it will also comment on recent meta-analysis combining GWAS studies with other studies such as gene expression micro array data in the field of autoimmune disease and solid organ transplantation. It will mention possible novel candidate gene polymorphisms, for example SNPS in microRNAs. In addition, it will discuss some of the inherent problems associated with gene association studies including the GRIPs (genetic risk prediction studies) recommendations. In summary, this review will assess the usefulness of non-HLA genomic studies in HSCT with regard to predicting outcome and modifying therapy.

Alloreactivity: the Janus-face of hematopoietic stem cell transplantation

“…There are indications for such constellations. [31][32][33] Environmental factors might as well influence presence or absence of graftversus-host disease; the microbiome of the gut has long been in focus and regained most recent interest. 33,34 If successful, a 'no graft-versus-host disease' constellation might favor an early low cost transplant with no need for immunosuppression post grafting, and save costs and suffering.…”

Not All Stem Cells Are Equally Great: Donor Single-Nucleotide Polymorphisms (SNP) May Matter More Than Previously Thought

“…Similar to autologous bone marrow storage, cord blood bank also provides an opportunity, after long-term storage, for autologous cord transplantation. 27,28 In most cases, however, allogeneic donors can be the choice only available. The most important factor affecting the outcome of allogeneic transplantation is the quality of the HLA match between donor and recipient and therefore patients subject to allogeneic HSCT will have to find a HLA-matching donor.…”

“…The current mortality rate of HSCT, unfortunately, stands rather high at 30-80% although up-todated high-resolution HLA genotyping and matching techniques have improved the survival to a significant extent. 27,28 Despite stringent procedures to secure the best HLA matching between donors and recipients, life-threatening complications continue to occur in some cases after HSCT. Common complications post HSCT are relapse, GVHD, graft rejection and viral infection.…”

A novel predictive approach for GVHD after allogeneic SCT based on clinical variables and cytokine gene polymorphisms

“…4 It is well established that the most important risk factor for the development of GVHD is the degree of HLA matching between the recipient and the donor, 5,6 although a significant proportion of patients undergoing transplantation with HLA-identical grafts develop aGVHD 1 and/or cGHVD. 7 Consequently, other non-HLA factors contribute to the development of this complication. Major clinical factors associated with GVHD include patient age, sex of donor/recipient, 8 stem-cell source, 9 GVHD prophylaxis, underlying disease, conditioning regimen, 10 and, for cGVHD, a history of aGVHD.…”

“…Kim et al 22,23 built a risk model incorporating SNPs and clinical markers to stratify patients and more accurately predict the risk of GVHD in specific organs, Paczesny et al 24 developed protein panels that provide meaningful information to confirm the diagnosis of GVHD in patients at the onset of clinical symptoms of GVHD and provide useful data for prognosis. 25 After genotyping a panel of polymorphisms in cytokine genes that had been previously associated with aGVHD or cGVHD, 7,18,26 we applied a complex estimation method, the least absolute shrinkage and selection operator (LASSO) procedure, 27 which is able to group optimal predictors from a large set of potential clinical and genetic predictor variables, improving their clinical utility.…”