Autori: Rik Westland1,2, Priya Krithivashan1, David Fasel1, Adele Mitrotti1, Emily Groopman1, Gabriel Makar1, Monica Bodria3, Landino Allegri4, Marijan Saraga5, Joanna van Wijk2, Krzysztof Kiryluk1, Ali Gharavi1, Velibor Tasic6, Francesco Scolari7, Gianmarco Ghiggheri3, Simone Sanna-Cherchi1
Affiliazioni: 1. Division of Nephrology, Columbia University College of Physicians and Surgeons, New York City, USA; 2. Department of Pediatrics, VU University Medical Center, Amsterdam, The Netherlands; 3. Division of Pediatric Nephrology, G. Gaslini Institute, Genoa, Italy; 4. Università di Parma, Ospedale Maggiore, Parma, Italy; 5. Department of Pediatrics, Clinical Hospital Split, Croatia; 6. Department of Pediatrics, University Children’s Hospital, Medical Faculty Skopje, Macedonia. 7. Division of Nephrology and Dialysis, University of Brescia and Montichiari Hospital, Brescia, Italy;
Introduction
Congenital ureteral malformations range in severity from transient hydronephrosis during pregnancy to defects that cause chronic kidney disease from birth such as ureteropelvic junction obstruction, congenital megaureter and impervious ureter. Although a clear genetic component underlies congenital ureteral malformations, the molecular basis of these malformations remains to be elucidated. By using a whole exome sequencing approach, we aim to identify novel genes that are implicated in congenital ureteral malformations.
Methods
We performed whole-exome sequencing in 259 cases with various congenital ureteral malformation phenotypes assembled from nephrology centers across Europe and the United States. Whole exome was done by using the Agilent V4 sequencing (majority of cases) and Roche exome (minority of cases) kits. For case-control comparison, we selected a dataset of 7,589 healthy controls and family members that were whole exome or whole genome sequenced at the Columbia Institute for Genomic Medicine for other genetic studies than congenital malformations or renal disease (internal controls). In addition, we used the dataset from the Exome Aggregation consortium (ExAC) Database, which contains whole exome sequencing data of 60,706 individuals, as external controls. After quality control using PLINK and KING, we performed a case-control comparison (“collapsing”) analysis to identify ultrarare deleterious loss-of-function and missense variants (i.e. completely absent in our internal and external control datasets) that are enriched in cases versus controls.
Results
After quality control and correction for platform differences between cases and controls, the genomic inflation factor (λ) was 1.25. This factor is used for genomic control. In addition, the top 15 genes that are enriched in cases versus controls are presented in Table 1. Qualifying variants in the top gene TARSL2 were found in 6/259 cases and 15/7,589 controls, which is close to reaching exome-wide significance (OR 12.0, 95% CI 3.77-32.96; corrected P = 5.45×10-5) (Table 2). TARSL2 encodes a threonyl-tRNA synthetase that has not previously been associated to human disease but is expressed in the developing ureter and bladder in GUDMAP, highlighting its potential as a candidate gene for congenital ureteral malformations.
Conclusion
Our whole exome collapsing analysis study in cases with congenital ureteral malformations provide a framework to define the genomic basis of this pleiotropic genetic disease. Our approach can be used for gene discovery studies as well as in the development of a precision medicine strategy that allows clinicians to discriminate transient ureteral malformations from severe defects. As such, precision medicine may lead to a better outcome for children with congenital ureteral malformations.
Table 1. Top 15 genes from the whole exome sequencing collapsing analysis. P-values are corrected for genomic inflation.
| Rank | Gene Name | Qualified Case (n=259) | Qualified Ctrl (n=7,589) | Enriched Direction | Corrected P-value | Genomically controlled
P-value |
| 1 | TARSL2′ | 6 | 15 | case | 4.36E-05 | 5.45E-05 |
| 2 | ‘FPGS’ | 4 | 5 | case | 1.28E-04 | 1.60E-04 |
| 3 | ‘P2RY13’ | 4 | 5 | case | 1.28E-04 | 1.60E-04 |
| 4 | ‘MLH1’ | 4 | 8 | case | 4.65E-04 | 5.82E-04 |
| 5 | ‘ITIH2’ | 5 | 16 | case | 4.96E-04 | 6.21E-04 |
| 6 | ‘PUS10’ | 4 | 9 | case | 6.55E-04 | 8.19E-04 |
| 7 | ‘CCNF’ | 4 | 9 | case | 6.55E-04 | 8.19E-04 |
| 8 | ‘DDX50’ | 4 | 9 | case | 6.55E-04 | 8.19E-04 |
| 9 | ‘CDS2’ | 3 | 3 | case | 6.60E-04 | 8.25E-04 |
| 10 | ‘OSBPL5’ | 4 | 10 | case | 8.93E-04 | 1.12E-03 |
| 11 | ‘ALPL’ | 4 | 10 | case | 8.93E-04 | 1.12E-03 |
| 12 | ‘NRG1’ | 5 | 19 | case | 9.56E-04 | 1.20E-03 |
| 13 | ‘TRAPPC8’ | 5 | 19 | case | 9.56E-04 | 1.20E-03 |
| 14 | ‘ARGLU1’ | 2 | 0 | case | 0.0011 | 1.38E-03 |
| 15 | ‘BOLA1’ | 2 | 0 | case | 0.0011 | 1.38E-03 |
Table 2. Qualifying variants in TARSL2 in cases.
| Variant | Consequence | Genotype | CADD | Case | Gender | Ureteral phenotype | Side | Additional CAKUT | Extrarenal malformations |
| 15-102194823-T-A | p.R791W | het | 25.6 | 1 | Male | UPJO | Right | N | N |
| 15-102224312-T-C | p.Q539R | het | 26.9 | 2 | Female | Congenital hydronephrosis | Right | N | N |
| 15-102226223-T-C | p.N455D | het | 26.4 | 3 | Male | UVJO | Left | N | N |
| 15-102245943-T-G | p.K313T | het | 22.5 | 4 | Male | UVJO | Bilateral | N | N |
| 15-102261398-A-C | p.V166G | het | 16.63 | 5 | Male | UPJO | Left | N | N |
| 15-102202003-TATC-T | p.D661- | het | 23.1 | 6 | Male | UVJO | Left | Renal hypodysplasia | N |
Overview of deleterious variants found in cases, that were absent in our internal and external control dataset. CADD = combined annotation dependent depletion score; CAKUT = congenital anomalies of the kidney and urinary tract; het = heterozygous; UPJO = ureteropelvic junction obstruction; UVJO = ureterovesical junction obstruction.
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