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. 2025 Aug 7;16(1):7290.
doi: 10.1038/s41467-025-62319-3.

Exome analysis links kidney malformations to developmental disorders and reveals causal genes

Hila Milo Rasouly #  1   2 Sarath Babu Krishna Murthy #  3 Natalie Vena  4   3 Gundula Povysil  5   6 Andrew Beenken  4 Miguel Verbitsky  4 Shirlee Shril  7 Iris Lekkerkerker  8 Sandy Yang  3 Atlas Khan  4 David Fasel  3 Janewit Wongboonsin  9   10 Jeremiah Martino  4   11 Juntao Ke  4 Naama Elefant  3   5 Nikita Tomar  3 Ofek Harnof  3 Sergey Kisselev  4 Shiraz Bheda  3 Sivan Reytan-Miron  4 Tze Y Lim  4   12 Anna Jamry-Dziurla  13 Francesca Lugani  14 Jun Y Zhang  4 Maddalena Marasa  4   15 Victoria Kolupaeva  4   3 Emily E Groopman  4   16 Gina Jin  4 Iman Ghavami  4 Kelsey O Stevens  4 Arielle C Coughlin  4   17 Byum Hee Kil  4 Debanjana Chatterjee  4 Drew Bradbury  4 Jason Zheng  4 Karla Mehl  4 Maria Morban  4 Rachel Reingold  4   18 Stacy Piva  4 Xueru Mu  4 Adele Mittrori  4   19 Agnieszka Szmigielska  20 Aleksandra Gliwińska  21 Andrea Ranghino  22   23 Andrew S Bomback  4 Andrzej Badenski  21 Anna Latos-Bielenska  13 Valentina Capone  24 Anna Materna-Kiryluk  13 Antonio Amoroso  25   26 Claudia Izzi  27 Claudio La Scola  28   29 David Jonathan Cohen  4 Domenico Santoro  30 Dorota Drozdz  31 Enrico Fiaccadori  32 Fangming Lin  33 Francesco Scolari  34 Francesco Tondolo  35 Gaetano La Manna  35   36 Gerald B Appel  4 Gian Marco Ghiggeri  14 Gianluigi Zaza  37 Giovanni Montini  24   38 Giuseppe Masnata  39 Grażyna Krzemien  20 Isabella Pisani  31 Jai Radhakrishnan  4 Katarzyna Zachwieja  30 Loreto Gesualdo  19 Luigi Biancone  40   41 Davide Meneghesso  42 Malgorzata Mizerska-Wasiak  20 Marcin Tkaczyk  43 Marcin Zaniew  44 Maria K Borszewska-Kornacka  45 Maria Szczepanska  21 Marijan Saraga  46 Maya K Rao  4 Monica Bodria  47 Monika Miklaszewska  30 Natalie S Uy  48 Olga Baraldi  35   49 Omar Bjanid  21 Pasquale Esposito  50   51 Pasquale Zamboli  52 Pierluigi Marzuillo  53 Pietro A Canetta  4 Przemyslaw Sikora  54 Rik Westland  55 Russell J Crew  4 Shumyle Alam  56 Stefano Guarino  53 Susanna Negrisolo  57   58 Thomas Hays  59 Shrikant Mane  60 Valeria Grandinetti  34 Velibor Tasic  61 Vladimir J Lozanovski  61   62 Yasar Caliskan  63 David Goldstein  5   64 Richard P Lifton  65 Iuliana Ionita-Laza  66   67 Krzysztof Kiryluk  4 Albertien M van Eerde  8 Friedhelm Hildebrandt  7 Simone Sanna-Cherchi  4 Ali G Gharavi  68   69
Affiliations

Exome analysis links kidney malformations to developmental disorders and reveals causal genes

Hila Milo Rasouly et al. Nat Commun. .

Abstract

Congenital anomalies of the kidneys and urinary tract (CAKUT) are developmental disorders that commonly cause pediatric chronic kidney disease and mortality. We examine here rare coding variants in 248 CAKUT trios and 1742 singleton CAKUT cases and compare them to 22,258 controls. Diagnostic and candidate diagnostic variants are detected in 14.1% of cases. We find a significant enrichment of rare damaging variants in constrained genes expressed during kidney development and in genes associated with other developmental disorders, suggesting phenotype expansion. Consistent with these data, 18% of CAKUT patients with diagnostic variants have neurodevelopmental or cardiac phenotypes. We identify 40 candidate genes, including CELSR1, SSBP2, XPO1, NR6A1, and ARID3A. Two are confirmed as CAKUT genes: ARID3A and NR6A1. This study suggests that many yet-unidentified syndromes would be discoverable with larger cohorts and cross-phenotype analysis, leading to clarification of the genetic and phenotypic spectrum of developmental disorders.

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Conflict of interest statement

Competing interests: A.G.G. has served on advisory boards for Natera through a service agreement with Columbia University. A.G.G. has served on advisory boards for Actio Biosciences, Novartis, Vera, Vertex, and Travere. The remaining authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Diagnostic analysis in 1990 individuals.
a Percentages of cases with diagnostic findings (green) and a candidate diagnosis (dark blue: VUS-high in a known gene, P/LP in a candidate gene or candidate structural variant) and those without a diagnostic or candidate variant (black). b Number of cases with an LP/P variant diagnostic or candidate finding (cases with two variants were counted once, with the variant most likely associated with their form of CAKUT) per gene and CAKUT (red: cystic kidney disease, black: renal hypoplasia and light blue: renal agenesis). c number of cases with a diagnostic or candidate structural variant per genomic area and CAKUT (red: cystic kidney disease, black: renal hypoplasia and light blue: renal agenesis). d Proportion of cases with diagnostic/candidate findings based on clinical characteristics (green: diagnostic findings and dark blue: candidate diagnosis). Diagnostic rate comparisons were performed using two-sided chi-square tests: (i) Bilateral vs. unilateral CAKUT: 20% vs. 7% (Chi-square p-value = 1.8 × 10−7; n = 1249). (ii) Females vs. males: 11% vs. 9% (Chi-square p-value = 3.8 × 10−3; n = 1710). (iii) Extra-renal anomalies vs. isolated CAKUT: 12% vs. 9% (Chi-square p-value = 0.02; n = 1710). (iv) Kidney phenotype: 13% (cystic dysplastic), 7% (agenesis), 12% (hypodysplasia) (Chi-square p-value = 1.9 × 10−3; n = 1710). Asterisks (*) indicate statistical significance. No adjustments for multiple comparisons were applied.
Fig. 2
Fig. 2. Gene-burden and gene-set enrichment analyses.
a The gene-burden analysis was performed by extracting the number of cases and controls with and without a qualifying variant (QV) per gene. The exact two-sided Cochran–Mantel–Haenszel (CMH) test was used to test for enrichment of qualifying variants in cases vs controls, while controlling for cluster. Quantile–Quantile probability plot of the p-values generated by the gene-burden analysis focused on qualifying variants (LoF and predicted deleterious missense). Red indicates case-enriched p-values. The green lines represent the 95% confidence interval. Empiric confidence interval distributions created by permutations (n = 1000). b List of the ten most significant genes.
Fig. 3
Fig. 3. Gene-set enrichment analyses and distribution of the number of qualifying variants per individual.
a Forest plot depicting the gene-set analysis using six gene sets based on three gene burden analyses. b Number of cases (black) and controls (Ctrl: gray) with 0, 1, 2, or at least 3 qualifying variants (LoF and predicted deleterious missense variants in constrained genes). Statistical significance of the difference between cases and controls was assessed using a two-sided Wilcoxon rank sum test. A significant difference was observed (OR = 1.1, p-value = 1.2 × 10−28). c Number of cases with extra-renal phenotypes (dark gray) and cases without known extra-renal phenotypes (light gray) with 0, 1, 2, or at least 3 qualifying variants (LoF and predicted deleterious missense variants in constrained genes). Statistical significance of the difference between cases with and without known extra-renal phenotypes was assessed using a two-sided Wilcoxon rank sum test (OR = 1.1; p-value = 3.03 × 10−2). No adjustment for multiple comparisons was applied. CHD congenital heart disorder, ID/ASD intellectual delay and autism spectrum disorder, LoF loss-of-function variants, mis missense variants, NPCs nephron progenitor cells, OR odds ratio, syn synonymous variants. Predicted deleterious missense variants: subRVI domain score percentile < 50% and predicted damaging based on at least 2 of the following criteria: (1) REVEL > 0.5; (2) PrimateAI > 0.8; (3) AlphaMissense score > 0.6; and (4) CADD score > 25. Constrained genes had pLI ≥ 0.9 and LoeF < 0.35 and/or misZ > 3.09.
Fig. 4
Fig. 4. Missense variants in NR6A1.
a Four independent Columbia CAKUT cases with predicted deleterious missense variants in NR6A1. b Family carrying the p.Arg92Trp (R92W) variant in NR6A1. (I: 1 pelvic and small kidney, II: 1 renal agenesis and Eye coloboma, III: 3 renal agenesis and eye coloboma, and IV: 2 renal agenesis and unknown genetic status). c Crystal structure of mouse NR6A1 and location of the three amino acids in which missense variants were identified in the four cases. d Modeling the potential impact of two of the three missense variants on the protein structure (R92W and R116C are modeled on the NR6A1 crystal structure PDB ID: 5KRB), the potential structural consequences of R66H could not be determined from the published NR6A1 structure.

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