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New research indicates that computer models can simulate the recovery of the immune system in patients undergoing hematopoietic stem cell transplant (HSCT).
The study suggests the possibility of using DNA sequencing and computer modeling to predict which HSCT recipients might suffer complications such as graft-versus-host-disease.
The research was published in Biology of Blood and Marrow Transplantation.
The study builds upon prior research, which showed that the immune system may be modeled as a dynamical system. Dynamical systems are mathematical objects used to model physical phenomena that change over time. These systems can be used to predict future states via observations of past and present states.
Researchers say the ability to predict immune system recovery after HSCT could potentially allow doctors to refine donor selection and better personalize post-transplant care to improve outcomes.
With this in mind, the team sequenced the DNA of 34 HSCT donor-recipient pairs and used the resulting information in a computer model to simulate how the recipient’s T-cell repertoire will recover following transplant.
“This study is the first to simulate the growth of the T-cell repertoire following transplantation using variables that aren’t accounted for in typical HLA donor-recipient matching,” said study author Amir Ahmed Toor, MD, of Virginia Commonwealth University in Richmond.
“Using a larger cohort of patients than in previous studies, we were able to mathematically predict the interactions of these variables, which led to simulations that appear to be very similar to clinically observed post-transplantation T-cell repertoire development.”
Previous research by Dr Toor and his colleagues revealed large variations between donor-recipient minor histocompatibility antigens that could potentially contribute to transplant complications not accounted for by HLA testing.
The models used in the computer simulations were driven by population growth formulas developed from past studies by Dr Toor and his colleagues that revealed distinct patterns of lymphocyte recovery in HSCT recipients.
Using matrix mathematics to develop the simulations, the researchers observed competition among T cells as the T-cell repertoire develops.
This competition leads to certain families of T cells becoming dominant and more numerous, which crowds out weaker T-cell families, causing them to develop later and in fewer numbers.
“We are attempting to account for the many variables that could impact T-cell repertoire development and, in turn, patient outcomes,” Dr Toor said.
“In future studies, we hope to explore the impact of organ-specific antigen expression. The knowledge gained from this research could potentially allow more accurate predictions of which organs could be most affected by graft-versus-host-disease.” 
Photo by Darren Baker
New research indicates that computer models can simulate the recovery of the immune system in patients undergoing hematopoietic stem cell transplant (HSCT).
The study suggests the possibility of using DNA sequencing and computer modeling to predict which HSCT recipients might suffer complications such as graft-versus-host-disease.
The research was published in Biology of Blood and Marrow Transplantation.
The study builds upon prior research, which showed that the immune system may be modeled as a dynamical system. Dynamical systems are mathematical objects used to model physical phenomena that change over time. These systems can be used to predict future states via observations of past and present states.
Researchers say the ability to predict immune system recovery after HSCT could potentially allow doctors to refine donor selection and better personalize post-transplant care to improve outcomes.
With this in mind, the team sequenced the DNA of 34 HSCT donor-recipient pairs and used the resulting information in a computer model to simulate how the recipient’s T-cell repertoire will recover following transplant.
“This study is the first to simulate the growth of the T-cell repertoire following transplantation using variables that aren’t accounted for in typical HLA donor-recipient matching,” said study author Amir Ahmed Toor, MD, of Virginia Commonwealth University in Richmond.
“Using a larger cohort of patients than in previous studies, we were able to mathematically predict the interactions of these variables, which led to simulations that appear to be very similar to clinically observed post-transplantation T-cell repertoire development.”
Previous research by Dr Toor and his colleagues revealed large variations between donor-recipient minor histocompatibility antigens that could potentially contribute to transplant complications not accounted for by HLA testing.
The models used in the computer simulations were driven by population growth formulas developed from past studies by Dr Toor and his colleagues that revealed distinct patterns of lymphocyte recovery in HSCT recipients.
Using matrix mathematics to develop the simulations, the researchers observed competition among T cells as the T-cell repertoire develops.
This competition leads to certain families of T cells becoming dominant and more numerous, which crowds out weaker T-cell families, causing them to develop later and in fewer numbers.
“We are attempting to account for the many variables that could impact T-cell repertoire development and, in turn, patient outcomes,” Dr Toor said.
“In future studies, we hope to explore the impact of organ-specific antigen expression. The knowledge gained from this research could potentially allow more accurate predictions of which organs could be most affected by graft-versus-host-disease.”
Photo by Darren Baker
New research indicates that computer models can simulate the recovery of the immune system in patients undergoing hematopoietic stem cell transplant (HSCT).
The study suggests the possibility of using DNA sequencing and computer modeling to predict which HSCT recipients might suffer complications such as graft-versus-host-disease.
The research was published in Biology of Blood and Marrow Transplantation.
The study builds upon prior research, which showed that the immune system may be modeled as a dynamical system. Dynamical systems are mathematical objects used to model physical phenomena that change over time. These systems can be used to predict future states via observations of past and present states.
Researchers say the ability to predict immune system recovery after HSCT could potentially allow doctors to refine donor selection and better personalize post-transplant care to improve outcomes.
With this in mind, the team sequenced the DNA of 34 HSCT donor-recipient pairs and used the resulting information in a computer model to simulate how the recipient’s T-cell repertoire will recover following transplant.
“This study is the first to simulate the growth of the T-cell repertoire following transplantation using variables that aren’t accounted for in typical HLA donor-recipient matching,” said study author Amir Ahmed Toor, MD, of Virginia Commonwealth University in Richmond.
“Using a larger cohort of patients than in previous studies, we were able to mathematically predict the interactions of these variables, which led to simulations that appear to be very similar to clinically observed post-transplantation T-cell repertoire development.”
Previous research by Dr Toor and his colleagues revealed large variations between donor-recipient minor histocompatibility antigens that could potentially contribute to transplant complications not accounted for by HLA testing.
The models used in the computer simulations were driven by population growth formulas developed from past studies by Dr Toor and his colleagues that revealed distinct patterns of lymphocyte recovery in HSCT recipients.
Using matrix mathematics to develop the simulations, the researchers observed competition among T cells as the T-cell repertoire develops.
This competition leads to certain families of T cells becoming dominant and more numerous, which crowds out weaker T-cell families, causing them to develop later and in fewer numbers.
“We are attempting to account for the many variables that could impact T-cell repertoire development and, in turn, patient outcomes,” Dr Toor said.
“In future studies, we hope to explore the impact of organ-specific antigen expression. The knowledge gained from this research could potentially allow more accurate predictions of which organs could be most affected by graft-versus-host-disease.”