Grants Awarded

Principal Investigator:
Kim Nichols
St. Jude Children’s Hospital,
Memphis,Tennesse,USA

Date of Award:
December 2024

Amount of Award:
$50,000

Layperson Summary:

Normally, when the immune system of a healthy person is faced with a challenge, such as a virus or a cancer cell, the immune system becomes activated and destroys these target cells. The immune system then returns to its normal quiescent state. People with familial hemophagocytic lymphohistiocytosis (fHLH) are born with mutations that interrupt the function of genes needed for the immune system to destroy certain target cells. As a result, these cells persist, and the immune system remains activated.

This excessive activation of the immune system causes damage to organs and may lead to death if patients do not receive prompt treatment. The only cure for fHLH is a bone marrow transplant, in which the dysfunctional immune system is replaced by the immune system of a healthy donor. While many people with fHLH have been cured with bone marrow transplants, this procedure can also carry serious risks. Therefore, it is important to know with certainty that a person has fHLH before proceeding with a transplant. Unfortunately, the gene mutations that cause fHLH are often challenging to distinguish from other genetic changes that occur in healthy individuals and are not associated with fHLH, making it difficult to know who requires a transplant and who does not. Currently, the only way to determine with certainty whether a person has fHLH is to use a specialized cell-based test that is costly, time consuming, and only available in a small number of clinical laboratories. As a result, this test is largely inaccessible to people in resource-limited settings. To address this problem, we generated a computer-based tool to predict which gene mutations cause fHLH and which do not. In this proposal, we will verify the accuracy of our computer­ based predictions by comparing our predictions to data produced by the cell-based test. We will then make all of our predictions available via a web interface that is accessible worldwide. We anticipate that this work will aid physicians in resource-limited settings in diagnosing fHLH and determining the need for bone marrow transplant, which will in turn improve survival rates for people with this disease.