R01HL159376
Project Grant
Overview
Grant Description
Predicting Progression of Chronic Kidney Disease in Sickle Cell Anemia Using Machine Learning Models (PREMIER) - Abstract
Sickle Cell Disease (SCD) is characterized by a vasculopathy affecting multiple end organs, with complications including Chronic Kidney Disease (CKD). Albuminuria, an early measure of glomerular injury, is common in SCD and predicts progressive kidney disease. Kidney function decline is faster in SCD patients than in the general African American population. The prevalence of rapid decline in SCD is 3-fold higher than in the general population. Furthermore, high-risk APOL1 variants are associated with an increased risk of albuminuria and progression of CKD in SCD. Kidney disease, regardless of severity, and rapid eGFR decline are associated with increased mortality in SCD.
As such, early identification of patients at risk for progression of CKD is important to address potentially modifiable risk factors, slow eGFR decline, and reduce mortality. Despite the high prevalence of CKD and its contribution to increased morbidity and mortality, available treatments for SCD-related kidney disease remain limited. Although Angiotensin Converting Enzyme Inhibitors (ACE-I), Angiotensin Receptor Blockers (ARBs), and Hydroxyurea decrease albuminuria in short-term studies, their benefits in preventing or slowing progressive loss of kidney function in SCD remain undefined.
We have recently reported that machine learning (ML) models can identify patients at high risk for rapid decline in kidney function. Further, higher hemoglobin concentration is also an independent predictor of decreased odds of rapid kidney function decline. With the contribution of intravascular hemolysis to the pathophysiology of SCD-related glomerulopathy, Voxelotor, a small molecule which modifies sickle hemoglobin oxygen affinity and improves sickle RBC survival, may decrease glomerular injury and slow the progression of CKD in individuals with SCD.
In this application, we propose the conduct of a prospective, multicenter study to build a ML-based predictive model for progression of CKD in adults with SCD. Furthermore, in individuals predicted to be at risk for rapid decline in kidney function, based on the presence of persistent albuminuria (urine ACR = 100 mg/g), we will evaluate the effect of Voxelotor on albuminuria, rapid decline in kidney function, and progression of CKD. With advances in the understanding of the pathophysiology of SCD and its complications, combined with an increasing number of approved drug therapies, early identification of patients at risk for progressive kidney disease and subsequent increased risk of death is necessary to modify known risk factors, initiate targeted therapies, and possibly increase life expectancy.
Further, with the known contribution of hemolytic anemia to the pathogenesis of SCD-related glomerulopathy and progressive kidney disease, drugs that decrease hemolysis are likely to be beneficial in preventing and/or slowing the progression of kidney disease in this patient population.
Sickle Cell Disease (SCD) is characterized by a vasculopathy affecting multiple end organs, with complications including Chronic Kidney Disease (CKD). Albuminuria, an early measure of glomerular injury, is common in SCD and predicts progressive kidney disease. Kidney function decline is faster in SCD patients than in the general African American population. The prevalence of rapid decline in SCD is 3-fold higher than in the general population. Furthermore, high-risk APOL1 variants are associated with an increased risk of albuminuria and progression of CKD in SCD. Kidney disease, regardless of severity, and rapid eGFR decline are associated with increased mortality in SCD.
As such, early identification of patients at risk for progression of CKD is important to address potentially modifiable risk factors, slow eGFR decline, and reduce mortality. Despite the high prevalence of CKD and its contribution to increased morbidity and mortality, available treatments for SCD-related kidney disease remain limited. Although Angiotensin Converting Enzyme Inhibitors (ACE-I), Angiotensin Receptor Blockers (ARBs), and Hydroxyurea decrease albuminuria in short-term studies, their benefits in preventing or slowing progressive loss of kidney function in SCD remain undefined.
We have recently reported that machine learning (ML) models can identify patients at high risk for rapid decline in kidney function. Further, higher hemoglobin concentration is also an independent predictor of decreased odds of rapid kidney function decline. With the contribution of intravascular hemolysis to the pathophysiology of SCD-related glomerulopathy, Voxelotor, a small molecule which modifies sickle hemoglobin oxygen affinity and improves sickle RBC survival, may decrease glomerular injury and slow the progression of CKD in individuals with SCD.
In this application, we propose the conduct of a prospective, multicenter study to build a ML-based predictive model for progression of CKD in adults with SCD. Furthermore, in individuals predicted to be at risk for rapid decline in kidney function, based on the presence of persistent albuminuria (urine ACR = 100 mg/g), we will evaluate the effect of Voxelotor on albuminuria, rapid decline in kidney function, and progression of CKD. With advances in the understanding of the pathophysiology of SCD and its complications, combined with an increasing number of approved drug therapies, early identification of patients at risk for progressive kidney disease and subsequent increased risk of death is necessary to modify known risk factors, initiate targeted therapies, and possibly increase life expectancy.
Further, with the known contribution of hemolytic anemia to the pathogenesis of SCD-related glomerulopathy and progressive kidney disease, drugs that decrease hemolysis are likely to be beneficial in preventing and/or slowing the progression of kidney disease in this patient population.
Awardee
Funding Goals
THE DIVISION OF BLOOD DISEASES AND RESOURCES SUPPORTS RESEARCH AND RESEARCH TRAINING ON THE PATHOPHYSIOLOGY, DIAGNOSIS, TREATMENT, AND PREVENTION OF NON-MALIGNANT BLOOD DISEASES, INCLUDING ANEMIAS, SICKLE CELL DISEASE, THALASSEMIA, LEUKOCYTE BIOLOGY, PRE-MALIGNANT PROCESSES SUCH AS MYELODYSPLASIA AND MYELOPROLIFERATIVE DISORDERS, HEMOPHILIA AND OTHER ABNORMALITIES OF HEMOSTASIS AND THROMBOSIS, AND IMMUNE DYSFUNCTION. FUNDING ENCOMPASSES A BROAD SPECTRUM OF HEMATOLOGIC INQUIRY, RANGING FROM STEM CELL BIOLOGY TO MEDICAL MANAGEMENT OF BLOOD DISEASES AND TO ASSURING THE ADEQUACY AND SAFETY OF THE NATION'S BLOOD SUPPLY. PROGRAMS ALSO SUPPORT THE DEVELOPMENT OF NOVEL CELL-BASED THERAPIES TO BRING THE EXPERTISE OF TRANSFUSION MEDICINE AND STEM CELL TECHNOLOGY TO THE REPAIR AND REGENERATION OF HUMAN TISSUES AND ORGANS. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO STIMULATE TECHNOLOGICAL INNOVATION, USE SMALL BUSINESS TO MEET FEDERAL RESEARCH AND DEVELOPMENT NEEDS, FOSTER AND ENCOURAGE PARTICIPATION IN INNOVATION AND ENTREPRENEURSHIP BY SOCIALLY AND ECONOMICALLY DISADVANTAGED PERSONS, AND INCREASE PRIVATE-SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT FUNDING. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE TECHNOLOGICAL INNOVATION, FOSTER TECHNOLOGY TRANSFER THROUGH COOPERATIVE R&D BETWEEN SMALL BUSINESSES AND RESEARCH INSTITUTIONS, AND INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL R&D.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Memphis,
Tennessee
381630001
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 353% from $705,287 to $3,193,450.
University Of Tennessee was awarded
Predictive Machine Learning Model CKD Progression in Sickle Cell Anemia
Project Grant R01HL159376
worth $3,193,450
from National Heart Lung and Blood Institute in September 2021 with work to be completed primarily in Memphis Tennessee United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.837 Cardiovascular Diseases Research.
The Project Grant was awarded through grant opportunity Research Project Grant (Parent R01 Clinical Trial Required).
Status
(Ongoing)
Last Modified 9/5/25
Period of Performance
9/10/21
Start Date
8/31/26
End Date
Funding Split
$3.2M
Federal Obligation
$0.0
Non-Federal Obligation
$3.2M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for R01HL159376
Transaction History
Modifications to R01HL159376
Additional Detail
Award ID FAIN
R01HL159376
SAI Number
R01HL159376-2017085235
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
75NH00 NIH National Heart, Lung, and Blood Institute
Funding Office
75NH00 NIH National Heart, Lung, and Blood Institute
Awardee UEI
X1M1PN3KG3E7
Awardee CAGE
1BW75
Performance District
TN-09
Senators
Marsha Blackburn
Bill Hagerty
Bill Hagerty
Budget Funding
Federal Account | Budget Subfunction | Object Class | Total | Percentage |
---|---|---|---|---|
National Heart, Lung, and Blood Institute, National Institutes of Health, Health and Human Services (075-0872) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,271,503 | 100% |
Modified: 9/5/25