Abstract: TH-OR64
Race, Genetic Ancestry, and GFR Estimation: Findings from the CRIC Study
Session Information
- Preventing Progression and Reassessing Race in GFR Estimation
November 04, 2021 | Location: Simulive, Virtual Only
Abstract Time: 04:30 PM - 06:00 PM
Category: CKD (Non-Dialysis)
- 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Hsu, Chi-yuan, University of California San Francisco, San Francisco, California, United States
- Yang, Wei, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
- Parikh, Rishi V., Kaiser Permanente Northern California, Oakland, California, United States
- Anderson, Amanda Hyre, Tulane University, New Orleans, Louisiana, United States
- Chen, Teresa K., Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
- Cohen, Debbie L., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
- He, Jiang, Tulane University, New Orleans, Louisiana, United States
- Mohanty, Madhumita J., Wayne State University, Detroit, Michigan, United States
- Lash, James P., University of Illinois at Chicago, Chicago, Illinois, United States
- Mills, Katherine T., Tulane University, New Orleans, Louisiana, United States
- Muiru, Anthony N., University of California San Francisco, San Francisco, California, United States
- Parsa, Afshin, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States
- Saunders, Milda Renne, The University of Chicago Medicine, Chicago, Illinois, United States
- Shafi, Tariq, The University of Mississippi Medical Center, Jackson, Mississippi, United States
- Townsend, Raymond R., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
- Waikar, Sushrut S., Boston University School of Medicine, Boston, Massachusetts, United States
- Wang, Jianqiao, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
- Wolf, Myles, Duke University, Durham, North Carolina, United States
- Tan, Thida C., Kaiser Permanente Northern California, Oakland, California, United States
- Feldman, Harold I., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
- Go, Alan S., Kaiser Permanente Northern California, Oakland, California, United States
Group or Team Name
- CRIC
Background
Inclusion of race in GFR estimating equations is undesirable. Prior studies have not examined replacing race with genetic ancestry.
Methods
We studied 1248 Chronic Renal Insufficiency Cohort (CRIC) Study participants with urinary 125I-iothalamate clearance GFR (iGFR) measurements and complete data on self-reported race, genetic ancestry, serum creatinine (SCr) & cystatin C. Genotyping was conducted using the Illumina HumanOmni1-Quad v1.0 microarray. The cohort was split into development (2/3) and validation (1/3) samples. Using linear regression, we derived GFR estimating equations for iGFR using SCr or cystatin C, age, sex, and self-reported race or African ancestry. The derived equations were then applied to the validation sample. Equation performance was assessed using root mean squared error (RMSE), adjusted R2, bias (iGFR - eGFR), and proportion of eGFR within 10% (P10) and 30% (P30) of iGFR.
Results
539 participants were female and 458 self-identified as Black. Mean±SD age was 55.9±12.1 yr, iGFR 48±20 ml/min/1.73m2, median [IQR] SCr was 1.5 [1.3-2.0] mg/dL, cystatin C 1.35 [1.09-1.71] mg/L. Median % African ancestry was 82.6% [74.5-88.3%] among those who self-identified as Black and 0.2% [0.1-2.0%] in those who did not.
When using SCr to estimate GFR, incorporating vs omitting self-reported race yielded better performing estimates (Table). Incorporating genetic ancestry provided estimates of GFR similar to those incorporating self-reported race. Incorporation of race or ancestry was unnecessary when estimating GFR using cystatin C. A GFR estimating equation using cystatin C, age and sex performed comparably to an equation using SCr, age, sex, and race or ancestry.
Conclusion
Switching from SCr to cystatin C to estimate GFR yields comparably valid without needing to include either race or genetic ancestry.
| Model for iGFR | RMSE | Adjusted R2 | Median (IQR) Bias, mL/min/1.73m2 (iGFR - eGFR) | P30 | P10 | % Higher iGFR (95% CI) | |||||
| Black | Non-Black | Black | Non-Black | Black | Non-Black | ||||||
| SCr, age, sex | 11.39 | 0.667 | 3.99 (-1.90, 10.13) | -0.91 (-7.17, 6.05) | 86 | 81 | 31 | 34 | |||
| SCr, age, sex, race | 11.22 | 0.677 | 1.11 (-4.48, 6.73) | 1.01 (-5.16, 7.81) | 86 | 82 | 42 | 37 | 13.6 (9.9 to 17.3)% if Black vs. non-Black race | ||
| SCr, age, sex, % African ancestry | 11.21 | 0.678 | 1.33 (-4.98, 6.18) | 1.07 (-5.30, 7.78) | 86 | 83 | 42 | 37 | 1.6 (1.2 to 2.1)% per 10% higher African ancestry | ||
| Cystatin C, age, sex | 10.76 | 0.704 | 0.33 (-4.50, 6.53) | 0.29 (-4.69, 6.91) | 85 | 83 | 41 | 39 | |||
| Cystatin C, age, sex, race | 10.76 | 0.703 | 0.85 (-3.98, 6.92) | 0.03 (-4.99, 6.71) | 85 | 83 | 42 | 39 | -1.6 (-4.7% to 1.4)% if Black vs. non-Black race | ||
| Cystatin C, age, sex, % African ancestry | 10.75 | 0.704 | 0.90 (-4.05, 6.74) | 0.04 (-4.97, 6.72) | 85 | 83 | 42 | 39 | -0.2 (-0.6% to 0.2)% per 10% higher African ancestry | ||
Funding
- NIDDK Support