Project Details
Description
The major types of pathological rejection after heart transplantation are acute cellular rejection (ACR) and anti-body-mediated rejection (AMR). Despite the known risk factors for ACR, it is not possible to predict which patients will develop ACR and at what time point after transplant. Therefore, all transplant programs perform rejection monitoring by routine endomyocardial biopsy (EMB) after transplant.
The immune response to an allograft is an ongoing dialogue between the innate and adaptive immune system. Activation of the innate immune system in the early phase post-transplant is largely, a non-specific response to tissue damage. Cells of the innate immune system express invariant pathogen associated pattern recognition receptors that enable them to detect not only repeating structural units expressed by pathogens but also markers of tissue injury or damage associated molecular patterns, which results in upregulating transcription of genes, and production of micro-RNAs. Cell differentiation and function of immune cells is thought to be dependent on epigenetic mechanisms, however the impact of DNA methylation profiles on transplant acceptance and rejection as well as on other post-transplant complications is unknown.
Observational studies from the early 90ths reported that HLA-A, B, or DR mismatching significantly reduced 3-year graft survival. However, a study conducted by Bućin et al. in kidney transplantation demonstrated a beneficial effect on long-term graft survival of HLA-A incompatibility in HLA-B, DR mismatched transplants. These results might indicate the existence of a down-regulative immune response to incompatible HLA-B and HLA-DR antigens, induced by tolerance-promoting allogeneic markers within the HLA-A class I region.
The use of next-generation sequencing (NGS) technologies for whole-genome analysis may provide further knowledge of the HLA genes or other regions of the genome which could be related to the regulation of the immune response, thereby resolving HLA-genotyping issues and contributing to the prediction of cardiac allograft rejection. Such as the role of regulatory T cells (Treg) (Treg; CD4þFOXP3þ) in the induction and maintenance of tolerance in organ trans-plantation has been demonstrated in several experimental models of transplantation.
Variation in the sequence of DNA between transplant recipients and their donor may be an explanation for the differences in the chances of progression transplant failure. Due to the wide variability of HLA alleles and the high degree of polymorphism that has been identified through current DNA-based genotyping methods, genome sequencing approaches may be highly desirable to allow further investigation of the genes involved in graft-related immune responses, thereby contributing to the prediction of cardiac allograft rejection and improving long-term graft and patient survival.
Question to investigate
- Identify genes/variants in genes contribute to progressive transplant failure and early transplant damage
- Analyse the Human Genome Profile’s impact on graft failure, early and late mortality after heart transplantation using Deep learning algorithms
- Analyse the recipients impact on donor Genome Profile’s over time
The immune response to an allograft is an ongoing dialogue between the innate and adaptive immune system. Activation of the innate immune system in the early phase post-transplant is largely, a non-specific response to tissue damage. Cells of the innate immune system express invariant pathogen associated pattern recognition receptors that enable them to detect not only repeating structural units expressed by pathogens but also markers of tissue injury or damage associated molecular patterns, which results in upregulating transcription of genes, and production of micro-RNAs. Cell differentiation and function of immune cells is thought to be dependent on epigenetic mechanisms, however the impact of DNA methylation profiles on transplant acceptance and rejection as well as on other post-transplant complications is unknown.
Observational studies from the early 90ths reported that HLA-A, B, or DR mismatching significantly reduced 3-year graft survival. However, a study conducted by Bućin et al. in kidney transplantation demonstrated a beneficial effect on long-term graft survival of HLA-A incompatibility in HLA-B, DR mismatched transplants. These results might indicate the existence of a down-regulative immune response to incompatible HLA-B and HLA-DR antigens, induced by tolerance-promoting allogeneic markers within the HLA-A class I region.
The use of next-generation sequencing (NGS) technologies for whole-genome analysis may provide further knowledge of the HLA genes or other regions of the genome which could be related to the regulation of the immune response, thereby resolving HLA-genotyping issues and contributing to the prediction of cardiac allograft rejection. Such as the role of regulatory T cells (Treg) (Treg; CD4þFOXP3þ) in the induction and maintenance of tolerance in organ trans-plantation has been demonstrated in several experimental models of transplantation.
Variation in the sequence of DNA between transplant recipients and their donor may be an explanation for the differences in the chances of progression transplant failure. Due to the wide variability of HLA alleles and the high degree of polymorphism that has been identified through current DNA-based genotyping methods, genome sequencing approaches may be highly desirable to allow further investigation of the genes involved in graft-related immune responses, thereby contributing to the prediction of cardiac allograft rejection and improving long-term graft and patient survival.
Question to investigate
- Identify genes/variants in genes contribute to progressive transplant failure and early transplant damage
- Analyse the Human Genome Profile’s impact on graft failure, early and late mortality after heart transplantation using Deep learning algorithms
- Analyse the recipients impact on donor Genome Profile’s over time
Popular science description
Internationella material visar att 12 % av hjärttransplanterade patienter inte överlever det första postoperativa året. En viktig orsak till mortalitet är avstötning av transplanterat organ utlöst av immunologiska skillnader mellan vävnader från olika individer. Retrospektiva studier har visat att en god matchning avseende centrala immunologiska karaktäristika kan resultera i färre avstötningsreaktioner, färre infektioner samt en förbättrad överlevnad. Det är dock många faktorer som ska vägas in för att uppnå en god matchning. Genom att samla stora mängder data har vår forskningsgrupp utvecklat matematiska datoriserade modeller, som gör det möjligt att undersöka hur flera olika faktorer tillsammans bidrar till en god matchning. Syftet med detta projekt är att även kunna lägga till hur arvsmassan hos en individ påverkar hur det donerade organet accepteras av kroppens vävnader. Genom att studera genetisk variabilitet mellan donator och recipient hos individer som drabbas av tidig avstötning, och jämföra med variabilitet hos individer som inte drabbas av tidig avstötning, bör lämpliga DNA-sekvenser användbara för prediktion av gynnsam matchning kunna identifieras. Kunskap om arvsmassan kan läggas till övriga faktorer och med hjälp av datoriserade modeller kan matchning förbättras och överlevnaden förbättras. På sikt har vi även förhoppningar om att analys av arvsmassa från sönderfallande celler i blodet ska kunna ersätta eller komplettera diagnostik av avstötningsepisoder hos en transplanterad individ. På liknande vis bör effekten av immunsupprimerande behandling kunna följas. Detta kan underlätta för individen och för samhället i stort.
Short title | HeartTX and Genome |
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Acronym | HTXG |
Status | Not started |
UKÄ subject classification
- Cardiac and Cardiovascular Systems
- Medical Biotechnology
- Medical Genetics
- Surgery