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Estimating Nephron Number from Biopsies: Impact on Clinical Studies
Journal of the American Society of Nephrology  (IF10.121),  Pub Date : 2022-01-01, DOI: 10.1681/asn.2021070998
Darya Morozov, Neda Parvin, Mark Conaway, Gavin Oxley, Edwin J. Baldelomar, Aleksandra Cwiek, Kim deRonde, Scott C. Beeman, Jennifer R. Charlton, Kevin M. Bennett

Background

Accumulating evidence supports an association between nephron number and susceptibility to kidney disease. However, it is not yet possible to directly measure nephron number in a clinical setting. Recent clinical studies have used glomerular density from a single biopsy and whole kidney cortical volume from imaging to estimate nephron number and single nephron glomerular filtration rate. However, the accuracy of these estimates from individual subjects is unknown. Furthermore, it is not clear how sample size or biopsy location may influence these estimates. These questions are critical to study design, and to the potential translation of these tools to estimate nephron number in individual subjects.

Methods

We measured the variability in estimated nephron number derived from needle or virtual biopsies and cortical volume in human kidneys declined for transplantation. We performed multiple needle biopsies in the same kidney, and examined the three-dimensional spatial distribution of nephron density by magnetic resonance imaging. We determined the accuracy of a single-kidney biopsy to predict the mean nephron number estimated from multiple biopsies from the same kidney.

Results

A single needle biopsy had a 15% chance and virtual biopsy had a 60% chance of being within 20% of the whole-kidney nephron number. Single needle biopsies could be used to detect differences in nephron number between large cohorts of several hundred subjects.

Conclusions

The number of subjects required to accurately detect differences in nephron number between populations can be predicted on the basis of natural intrakidney variability in glomerular density. A single biopsy is insufficient to accurately predict nephron number in individual subjects.