# NIH grant: Non-invasive assessment of kidney histology for acute tubular injury and interstitial fibrosis and tubular atrophy (1R01DK145838-01A1) — retained record

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source: [us-gov-api](https://highsignal.app/data/us-gov-api) (us-gov-api:nih-reporter)  published 2026-08-21 00:00 ingested 2026-08-24 06:47

[original source ↗](https://reporter.nih.gov/project-details/1R01DK145838-01A1)

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NIH grant 1R01DK145838-01A1: Non-invasive assessment of kidney histology for acute tubular injury and interstitial fibrosis and tubular atrophy
Institute: {'code': 'DK', 'abbreviation': 'NIDDK', 'name': 'National Institute of Diabetes and Digestive and Kidney Diseases', 'admin_org_id': '12500020', 'admin_funding_url': ''}. PI: Steven  Menez. Award: $798088.
Start: 2026-08-21T00:00:00.
ABSTRACT
Kidney biopsy remains a cornerstone in the evaluation of kidney disease, offering critical insights into the
presence and severity of acute tubular injury (ATI) and interstitial fibrosis and tubular atrophy (IFTA). An
accurate understanding of these histological features is essential not only for diagnosis but also for accurate
risk stratification and prognostication. However, the use of kidney biopsy is often constrained by various
factors, including patient-related issues like thrombocytopenia and broader systemic barriers such as limited
access to care. The overarching goal of this research is to develop and validate predictive models for
identifying and assessing the severity of ATI and IFTA on kidney biopsy. To develop this non-invasive
approach, we will first leverage the Novel Approaches in the Investigation of Kidney Disease (NAIKID) Study,
an ongoing prospective cohort study at Johns Hopkins. This study collects blood, urine, kidney tissue, and
detailed clinical data from patients undergoing clinically indicated native kidney biopsies, and establishing a
comprehensive kidney biorepository. In this project, we will analyze data from the first 700 participants of the
NAIKID Study, measuring blood and urine biomarkers previously associated with adverse kidney outcomes. By
integrating these biomarkers with key clinical variables, we aim to construct robust predictive models for ATI
and IFTA, using kidney biopsy as the gold standard. Subsequently, we will validate these models across three
sites, Johns Hopkins, Mount Sinai, and Yale, capitalizing on existing kidney biorepositories at both external
sites. Successful completion of this research will transform the field by reducing reliance on invasive biopsy
procedures, paving the way for innovative clinical trial designs, and advancing precision medicine in kidney
disease.
```



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