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Quantitative podocyte parameters predict human native kidney and allograft half-lives
Abhijit S. Naik, … , Yi Li, Roger C. Wiggins
Abhijit S. Naik, … , Yi Li, Roger C. Wiggins
Published May 19, 2016
Citation Information: JCI Insight. 2016;1(7):e86943. https://doi.org/10.1172/jci.insight.86943.
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Clinical Medicine Aging Nephrology

Quantitative podocyte parameters predict human native kidney and allograft half-lives

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Abstract

BACKGROUND. Kidney function decreases with age. A potential mechanistic explanation for kidney and allograft half-life has evolved through the realization that linear reduction in glomerular podocyte density could drive progressive glomerulosclerosis to impact both native kidney and allograft half-lives.

METHODS. Predictions from podometrics (quantitation of podocyte parameters) were tested using independent pathologic, functional, and outcome data for native kidneys and allografts derived from published reports and large registries.

RESULTS. With age, native kidneys exponentially develop glomerulosclerosis, reduced renal function, and end-stage kidney disease, projecting a finite average kidney life span. The slope of allograft failure rate versus age parallels that of reduction in podocyte density versus age. Quantitative modeling projects allograft half-life at any donor age, and rate of podocyte detachment parallels the observed allograft loss rate.

CONCLUSION. Native kidneys are designed to have a limited average life span of about 100–140 years. Allografts undergo an accelerated aging-like process that accounts for their unexpectedly short half-life (about 15 years), the observation that older donor age is associated with shorter allograft half-life, and the fact that long-term allograft survival has not substantially improved. Podometrics provides potential readouts for these processes, thereby offering new approaches for monitoring and intervention.

FUNDING: National Institutes of Health.

Authors

Abhijit S. Naik, Farsad Afshinnia, Diane Cibrik, Jeffrey B. Hodgin, Fan Wu, Min Zhang, Masao Kikuchi, Larysa Wickman, Milagros Samaniego, Markus Bitzer, Jocelyn E. Wiggins, Akinlolu Ojo, Yi Li, Roger C. Wiggins

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Figure 5

Simulation of allograft time to ESKD versus donor age derived from podometric data and comparison to observed transplant outcomes data versus age.

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Simulation of allograft time to ESKD versus donor age derived from podom...
(A) Method and assumptions. The normal reduction in podocyte density by age is illustrated by the diagonal solid line as previously reported (17). Open circles represent hypothetical kidney donation ages at 20, 40, and 60 years. At implantation both the kidney and glomerulus rapidly increase in size by 20% (19). Podocytes cannot divide and therefore have to undergo rapid compensatory hypertrophy, resulting in reduced podocyte density, as shown by the dotted line at each donor age. Following implantation, allografts continue to lose podocytes at an increased rate on average 6-fold above the native kidney control rate (19). This increased rate of podocyte detachment will result in an accelerated rate (steeper slope compared with native kidneys) of further reduction in podocyte density (dashed lines). At a podocyte density value below 50 per 106 μm3, global sclerosis will supervene and kidneys will be at end-stage kidney disease (ESKD). The predicted time to ESKD can therefore be estimated for any putative donor age, as shown by the arrowheads. The observed mean value for time to ESKD for deceased donor kidney transplants at each of the three donor ages is shown at right as derived from the OPTN/UNOS database as of September 5, 2014. (B) Comparison of projected to observed kidney transplant half-life by age. Each data point (n = 89) from the previously reported aging study (17) was used to estimate the projected time to ESKD that would have occurred were that kidney to have been transplanted according to the above criteria. The regression line ± 95% confidence limit is shown. The closed triangles show aggregated half-lives by age for deceased donors as derived from the OPTN/UNOS database as of September 5, 2014. The slope of the linear regression line derived from podometric data (solid line) is steeper than the observed OPTN/UNOS data, although this difference is not statistically significant (P = 0.42; general linear model).

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