TY - JOUR
T1 - Urine Biomarkers of Kidney Tubule Health and Incident CKD Stage 3 in Women Living With HIV
T2 - A Repeated Measures Study
AU - Ascher, Simon B.
AU - Scherzer, Rebecca
AU - Estrella, Michelle M.
AU - Jotwani, Vasantha K.
AU - Shigenaga, Judy
AU - Spaulding, Kimberly A.
AU - Ng, Derek K.
AU - Gustafson, Deborah
AU - Spence, Amanda B.
AU - Sharma, Anjali
AU - Cohen, Mardge H.
AU - Parikh, Chirag R.
AU - Ix, Joachim H.
AU - Shlipak, Michael G.
N1 - Funding Information:
The primary funding source for this study was an R01 award from the National Institute of Aging to MGS and RS (NIA, R01AG034853-08). The funders had no role in the study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication.
Funding Information:
Simon B. Ascher, MD, MPH, Rebecca Scherzer, PhD, Michelle M. Estrella, MD, MHS, Vasantha K. Jotwani, MD, Judy Shigenaga, BS, Kimberly A. Spaulding, MS, Derek K. Ng, PhD, Deborah Gustafson, MS, PhD, Amanda B. Spence, MD, Anjali Sharma, MD, MS, Mardge H. Cohen, MD, Chirag R. Parikh, MD, PhD, Joachim H. Ix, MD, MAS, and Michael G. Shlipak, MD, MPH, Research idea and study design: SBA, MGS, RS, MME; data acquisition: JS, KAS, DKN, DG, ABS, AS, MHC; data analysis/interpretation: SBA, RS, MME, VKJ, CRP, JHI, MGS; statistical analyses: RS; supervision or mentorship: MGS. Each author contributed important intellectual content during manuscript drafting or revision, accepts personal accountability for the author's own contributions, and agrees to ensure that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. The primary funding source for this study was an R01 award from the National Institute of Aging to MGS and RS (NIA, R01AG034853-08). The funders had no role in the study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication. Dr Shlipak is a scientific advisor and holds stock options in TAI Diagnostics and has received personal compensation from Cricket Health, Inc. The remaining authors declare that they have no relevant financial interests. Data in this manuscript were collected by the WIHS, now the MACS/WIHS Combined Cohort Study (MWCCS). The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). MWCCS (Principal Investigators): Atlanta Center for Reproductive Science (CRS; Ighovwerha Ofotokun, Anandi Sheth, and Gina Wingood), U01-HL146241; Baltimore CRS (Todd Brown and Joseph Margolick), U01-HL146201; Bronx CRS (Kathryn Anastos and Anjali Sharma), U01-HL146204; Brooklyn CRS (Deborah Gustafson and Tracey Wilson), U01-HL146202; Data Analysis and Coordination Center (Gypsyamber D'Souza, Stephen Gange, and Elizabeth Golub), U01-HL146193; Chicago-Cook County CRS (Mardge Cohen and Audrey French), U01-HL146245; Chicago-Northwestern CRS (Steven Wolinsky), U01-HL146240; Connie Wofsy Women's HIV Study, Northern California CRS (Bradley Aouizerat and Phyllis Tien), U01-HL146242; Los Angeles CRS (Roger Detels), U01-HL146333; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01-HL146205; Miami CRS (Maria Alcaide, Margaret Fischl, and Deborah Jones), U01-HL146203; Pittsburgh CRS (Jeremy Martinson and Charles Rinaldo), U01-HL146208; UAB-MS CRS (Mirjam-Colette Kempf and Deborah Konkle-Parker), U01-HL146192; UNC CRS (Adaora Adimora), U01-HL146194. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute, with additional co-funding from the Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Human Genome Research Institute, National Institute on Aging, National Institute of Dental & Craniofacial Research, National Institute of Allergy and Infectious Diseases, National Institute of Neurological Disorders and Stroke, National Institute of Mental Health, National Institute on Drug Abuse, National Institute of Nursing Research, National Cancer Institute, National Institute on Alcohol Abuse and Alcoholism, National Institute on Deafness and Other Communication Disorders, and National Institute of Diabetes and Digestive and Kidney Diseases. MWCCS data collection is also supported by UL1-TR000004 (UCSF CTSA), P30-AI-050409 (Atlanta CFAR), P30-AI-050410 (UNC CFAR), and P30-AI-027767 (UAB CFAR). Received October 28, 2020. Evaluated by 2 external peer reviewers, with direct editorial input by the Statistical Editor and the Editor-in-Chief. Accepted in revised form January 31, 2021.
Funding Information:
Data in this manuscript were collected by the WIHS, now the MACS/WIHS Combined Cohort Study (MWCCS). The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). MWCCS (Principal Investigators): Atlanta Center for Reproductive Science (CRS; Ighovwerha Ofotokun, Anandi Sheth, and Gina Wingood), U01-HL146241; Baltimore CRS (Todd Brown and Joseph Margolick), U01-HL146201; Bronx CRS (Kathryn Anastos and Anjali Sharma), U01-HL146204; Brooklyn CRS (Deborah Gustafson and Tracey Wilson), U01-HL146202; Data Analysis and Coordination Center (Gypsyamber D’Souza, Stephen Gange, and Elizabeth Golub), U01-HL146193; Chicago-Cook County CRS (Mardge Cohen and Audrey French), U01-HL146245; Chicago-Northwestern CRS (Steven Wolinsky), U01-HL146240; Connie Wofsy Women’s HIV Study, Northern California CRS (Bradley Aouizerat and Phyllis Tien), U01-HL146242; Los Angeles CRS (Roger Detels), U01-HL146333; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01-HL146205; Miami CRS (Maria Alcaide, Margaret Fischl, and Deborah Jones), U01-HL146203; Pittsburgh CRS (Jeremy Martinson and Charles Rinaldo), U01-HL146208; UAB-MS CRS (Mirjam-Colette Kempf and Deborah Konkle-Parker), U01-HL146192; UNC CRS (Adaora Adimora), U01-HL146194. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute, with additional co-funding from the Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Human Genome Research Institute, National Institute on Aging, National Institute of Dental & Craniofacial Research, National Institute of Allergy and Infectious Diseases, National Institute of Neurological Disorders and Stroke, National Institute of Mental Health, National Institute on Drug Abuse, National Institute of Nursing Research, National Cancer Institute, National Institute on Alcohol Abuse and Alcoholism, National Institute on Deafness and Other Communication Disorders, and National Institute of Diabetes and Digestive and Kidney Diseases. MWCCS data collection is also supported by UL1-TR000004 (UCSF CTSA), P30-AI-050409 (Atlanta CFAR), P30-AI-050410 (UNC CFAR), and P30-AI-027767 (UAB CFAR).
Publisher Copyright:
© 2021 The Authors
PY - 2021/5/1
Y1 - 2021/5/1
N2 - Rationale & Objective: Single measurements of urinary biomarkers reflecting kidney tubule health are associated with chronic kidney disease (CKD) risk in HIV infection, but the prognostic value of repeat measurements over time is unknown. Study Design: Cohort study. Setting & Participants: 647 women living with HIV infection enrolled in the Women's Interagency Health Study. Exposures: 14 urinary biomarkers of kidney tubule health measured at 2 visits over a 3-year period. Outcome: Incident CKD, defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 at two 6-month visits and an average eGFR decline ≥ 3% per year. Analytical Approach: We used multivariable generalized estimating equations adjusting for CKD risk factors to evaluate baseline, time-updated, and change-over-time biomarker associations with incident CKD. We compared CKD discrimination between models with and without a parsimoniously selected set of biomarkers. Results: During a median 7 years of follow-up, 9.7% (63/647) developed CKD. In multivariable-adjusted analyses, 3 of 14 baseline biomarkers associated with incident CKD. In contrast, 10 of 14 time-updated biomarkers and 9 of 14 biomarkers modeled as change over time associated with incident CKD. Urinary epidermal growth factor (EGF), α1-microglobulin (A1M), and albumin were selected using penalized regression methods. In the time-updated model, lower urinary EGF (risk ratio [RR] per 2-fold higher time-updated biomarker levels, 0.69; 95% CI, 0.58-0.81), higher urinary A1M (RR, 1.47; 95% CI, 1.25-1.73), and higher urinary albumin excretion (RR, 1.21; 95% CI, 1.03-1.42) were jointly associated with increased risk for CKD. Compared with a base model (C statistic, 0.75), CKD discrimination improved after adding urinary EGF, A1M, and albumin values across baseline (C = 0.81), time-updated (C = 0.83), and change-over-time (C = 0.83) models (P < 0.01 for all). Limitations: Observational design, incident CKD definition limited to eGFR. Conclusions: Repeat urinary biomarker measurements for kidney tubule health have stronger associations with incident CKD compared with baseline measurements and moderately improve CKD discrimination in women living with HIV infection.
AB - Rationale & Objective: Single measurements of urinary biomarkers reflecting kidney tubule health are associated with chronic kidney disease (CKD) risk in HIV infection, but the prognostic value of repeat measurements over time is unknown. Study Design: Cohort study. Setting & Participants: 647 women living with HIV infection enrolled in the Women's Interagency Health Study. Exposures: 14 urinary biomarkers of kidney tubule health measured at 2 visits over a 3-year period. Outcome: Incident CKD, defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 at two 6-month visits and an average eGFR decline ≥ 3% per year. Analytical Approach: We used multivariable generalized estimating equations adjusting for CKD risk factors to evaluate baseline, time-updated, and change-over-time biomarker associations with incident CKD. We compared CKD discrimination between models with and without a parsimoniously selected set of biomarkers. Results: During a median 7 years of follow-up, 9.7% (63/647) developed CKD. In multivariable-adjusted analyses, 3 of 14 baseline biomarkers associated with incident CKD. In contrast, 10 of 14 time-updated biomarkers and 9 of 14 biomarkers modeled as change over time associated with incident CKD. Urinary epidermal growth factor (EGF), α1-microglobulin (A1M), and albumin were selected using penalized regression methods. In the time-updated model, lower urinary EGF (risk ratio [RR] per 2-fold higher time-updated biomarker levels, 0.69; 95% CI, 0.58-0.81), higher urinary A1M (RR, 1.47; 95% CI, 1.25-1.73), and higher urinary albumin excretion (RR, 1.21; 95% CI, 1.03-1.42) were jointly associated with increased risk for CKD. Compared with a base model (C statistic, 0.75), CKD discrimination improved after adding urinary EGF, A1M, and albumin values across baseline (C = 0.81), time-updated (C = 0.83), and change-over-time (C = 0.83) models (P < 0.01 for all). Limitations: Observational design, incident CKD definition limited to eGFR. Conclusions: Repeat urinary biomarker measurements for kidney tubule health have stronger associations with incident CKD compared with baseline measurements and moderately improve CKD discrimination in women living with HIV infection.
KW - Chronic kidney disease
KW - HIV
KW - albuminuria
KW - epidermal growth factor
KW - α-1 microglobulin
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U2 - 10.1016/j.xkme.2021.01.012
DO - 10.1016/j.xkme.2021.01.012
M3 - Article
AN - SCOPUS:85106270094
SN - 2590-0595
VL - 3
SP - 395-404.e1
JO - Kidney Medicine
JF - Kidney Medicine
IS - 3
ER -
