Anti-SARS-CoV-2 Immune Responses in Patients Receiving an Allogeneic Stem Cell or Organ Transplant.
Djordje AtanackovicTim LuetkensStephanie V AvilaNancy M HardyForat LutfiGabriela Sanchez-PetittoErica Vander MauseNicole GlynnHeather D MannuelHanan AlkhaldiKim HankeyJohn W BaddleySaurabh DahiyaAaron P RapoportPublished in: Vaccines (2021)
Patients after autologous (autoSCT) and allogeneic stem cell transplantation (alloSCT) are at an increased risk of COVID-19-related morbidity and mortality, compounded by an immune system weakened by the underlying malignancy and prior treatments. Allogeneic transplantation, including stem cell and solid organ transplants, requires intensive immunosuppressive prophylaxis, which may further undermine the development of a protective vaccine-induced anti-viral immunity. Herein, we report on short- and long-term antiviral immune responses in two peri-stem cell transplant recipients and a third patient who received a COVID-19 vaccination after kidney transplantation. Our data indicate that: (1) patients post-alloSCT may be able to mount an anti-COVID-19 immune response; however, a sufficient time interval between transplant and exposure may be of critical importance; (2) alloSCT recipients with preexisting anti-SARS-CoV-2 immunity are at risk for losing protective humoral immunity following transplantation, particularly if the stem-cell donor lacks antiviral immunity, e.g., vaccine-derived immunity; and (3) some post-transplant patients are completely unable to build an immune response to a COVID-19 vaccine, perhaps based on the prophylactic suppression of T cell immunity.
Keyphrases
- sars cov
- immune response
- stem cell transplantation
- stem cells
- coronavirus disease
- end stage renal disease
- ejection fraction
- newly diagnosed
- bone marrow
- respiratory syndrome coronavirus
- chronic kidney disease
- prognostic factors
- patient reported outcomes
- inflammatory response
- low dose
- machine learning
- case report
- cell therapy
- oxidative stress
- deep learning
- patient reported
- electronic health record
- big data
- drug induced
- artificial intelligence