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Child Kidney Dis > Volume 25(1); 2021 > Article
Kang and Lee: Clinical Genetic Testing in Children with Kidney Disease

Abstract

Chronic kidney disease, the presence of structural and functional abnormalities in the kidneys, is associated with a lower quality of life and increased morbidity and mortality in children. Genetic etiologies account for a substantial proportion of pediatric chronic kidney disease. With recent advances in genetic testing techniques, an increasing number of genetic causes of kidney disease continue to be found. Genetic testing is recommended in children with steroid-resistant nephrotic syndrome, congenital malformations of the kidney and urinary tract, cystic disease, or kidney disease with extrarenal manifestations. Diagnostic yields differ according to the category of clinical diagnosis and the choice of test. Here, we review the characteristics of genetic testing modalities and the implications of genetic testing in clinical genetic diagnostics.

Introduction

Chronic kidney disease (CKD) in children is defined as the presence of structural and functional abnormalities or a decline in glomerular filtration rate for more than 3 months, and can progress to end-stage renal disease (ESRD) [1]. The prognosis of CKD has improved remarkably with improved medical treatment, dialysis techniques, and transplantation. However, CKD is still associated with growth impairment, lower quality of life, cardiovascular morbidity, and increased risk of mortality in the pediatric population [2-4]. The main etiologies of pediatric CKD are congenital anomalies of the kidneys and urinary tract (CAKUT), steroid-resistant nephrotic syndrome (SRNS), chronic glomerulonephritis, and renal cystic ciliopathies, which account for more than 70% of pediatric CKD altogether [5-7].
A positive family history of kidney disease is reported in approximately 25 % of patients with kidney disease, suggesting the importance of genetics in kidney disease [8,9].With recent advances in genetic testing technologies, genetic testing has become a mainstay in clinical diagnostics and research. As a result, knowledge about genes associated with kidney and urological disorders continue to expand, and more than 600 genetic disorders have been identified in kidney disease [10,11]. Genetic kidney disease is more prevalent in pediatric patients than in adult patients, and is estimated to account for approximately 30% of pediatric chronic kidney disease [10].
From the perspective of this genetic heterogeneity, selection of appropriate genetic testing is not an easy decision, and is generally made based on the patients’ clinical impression, the diagnostic yield of a test, and its cost. In this review, we introduce various genetic testing methods and describe the characteristics of each modality to help pediatric nephrologists select the appropriate genetic testing method as part of the genetic diagnostic process in children with kidney disease.

Diagnostic genetic testing and diagnostic yield

The human genome contains approximately 20,000 genes, with approximately 1% to 2% being protein-encoding exonic regions, known as the exome. Another 26% form intronic regions between exons, and the remaining 72% to 73% of intragenic regions form noncoding regions [12]. Genetic variations range in size from single nucleotide variants (SNVs) that substitute a single base and small insertion/ deletion (INDEL) mutations that affects 2–1,000 bases, to large copy number variations (CNVs) that affect more than 1,000 bases.
Genetic tests available in clinical practice include karyotyping, chromosomal microarray (CMA), Sanger sequencing, targeted gene panel, whole exome sequencing (WES), and whole genome sequencing (WGS). Table 1 summarizes the characteristics of the different genomic diagnostic modalities used.
Karyotyping directly visualizes the entire set of 46 chromosomes during prometaphase or metaphase with a high sensitivity for aneuploidies, large deletions and duplications, and translocations. CMA is more sensitive for the detection of microdeletions or microduplications that are over 20–400 kilobases (Kb) in size, but cannot detect balanced translocations or inversions [13-15]. CMA in combination with karyotype is the test of choice when a structural variant is clinically suspected, as in developmental delay and multiple congenital anomalies. Recent studies have reported a high frequency of CNVs in CAKUT, involving 45 different genomic disorders at 37 independent loci, with six of these loci (1q12.1, 4p16.1–16.3, 16p11.2, 16p13.11, 17q12, 22q11.2) accounting for approximately 65% of cases with a genomic disorder [16]. Structural variants have been detected in approximately 10%–17% of children with CAKUT [17,18].
Sanger sequencing, a targeted dideoxy terminator sequencing, identifies small variants of less than 1 kb in specific genes or gene regions. It is simple with highly reliable results having a low error rate (0.001%–1%), and has been considered the gold standard for accurate genetic diagnosis [19]. Sanger sequencing is used for testing when a variation is clinically suspected at a specific locus.
Next-generation sequencing (NSG), also known as massive parallel sequencing, uses simultaneous sequencing of millions of small DNA fragments that can be reassembled into a full sequence using analytical tools. This approach is a powerful tool for identifying small variants in the whole exome, whole genome, or selected genes at a relatively low cost. It has emerged as a powerful tool for clinical genetic diagnosis [20].
The targeted gene panel covers a selected set of genes that are considered to be associated with a specific phenotype. It is a rapid and cost-effective test for a clearly distinct phenotype with several causative genes, such as nephronophthisis, Alport’s syndrome, SRNS, and focal segmental glomerulosclerosis (FSGS) (Table 2) [21-24]. The diagnostic yield depends on the clinical diagnosis and selection criteria. In recent reports, the causative mutations were found in 8%–20% of children with CAKUT, approximately 26% of children with SRNS, and up to 80% of patients with cystic kidney disease [10,25-28]. This targeted approach simplifies the interpretation of the results, minimizes potential false negative results caused by incomplete sequencing coverage, and reduces the opportunity for incidental findings. However, because the genes in a particular panel are selected, it is not possible to reanalyze the data panels when new or phenocopy genes are discovered. For example, isolated proteinuria or SRNS may be the only evident clinical sign of Alport syndrome, Dent disease, or Fabry disease at disease onset or even later. These genetic kidney diseases are often misclassified as SRNS, and the results of targeted genetic testing prove to be negative. These conditions are referred to as the phenocopies of hereditary SRNS [29,30].
WES and WGS are relatively unbiased genome-wide tests. WES covers protein-coding regions of the human genome, whereas WGS covers all genomic DNA, including protein-coding and noncoding regions. WES is less expensive, detects a reduced number of variants compared to WGS, and approximately 75% of variants are located within the exome. On the other hand, WGS is efficient for detecting structural variants and variants in splicing or regulatory regions [31,32]. WES and WGS allow for future reanalysis without the need for additional sequencing, as our knowledge on the function of a gene and analytic techniques improves with the discovery of a new causative gene [33].
In general, WES and WGS yield higher diagnostic results than targeted gene panels [34-37]. The diagnostic rate of genetic forms of kidney diseases was higher among patients with a positive family history of kidney disease, consanguinity, congenital forms of kidney disease or early age of onset, and extra-renal manifestations [30,35,38].
Nonetheless, NGS coverage is suboptimal in genes related to kidney disease, such as PKD1 and GREB1L [39,40]. In addition, tandem repeats, which are short repetitive nucleotide sequences, are difficult to sequence with short-read NSG technology.
The large amount of sequence variations and incidental findings raise the issue of interpretation in NGS. The American College of Medical Genetics and Genomics (ACMG) recommends that variants be classified into one of five categories: pathogenic, likely pathogenic, variant of uncertain significance (VUS), likely benign, and benign. The variant is assessed using various types of evidence, including population frequency, in silico prediction, functional study data, segregation data, de novo mutation, variant characterization, and prior occurrence [41]. The terms “pathogenic” or “benign” are used for variants of almost certainty, and “likely pathogenic” and “likely benign” for those of over 90% certainty. The variants that have insufficient evidence to be classified into the above categories are reported as VUS.
There are concerns regarding the interpretation of the indeterminate results reported as VUS. Without an understanding of the variation of the human genome, this result can be misinterpreted as significant. Importantly, recent reports indicate that many VUS cases can be reclassified as benign [42,43].
Regarding the possibility of incidental findings, ACMG lists 59 medically actionable genes, including those of cancer and cardiomyopathy, to be assessed in patients undergoing WES or WGS [44]. There are ethical issues around incidental findings, particularly in children, since the advantages of informing children or their family of incidental findings related to adult-onset diseases is unclear. The American Academy of Pediatrics recommends delaying testing for adult-onset disease until adulthood [45].

Clinical implications of genetic diagnosis

Genetic testing in patients with kidney disease has several clinical implications which can contribute to a definitive diagnosis. Establishing an accurate diagnosis is necessary for the effective management of kidney disease based on the pathophysiology of the disease. For example, avoidance of corticosteroid and CoQ10 supplementation can be considered in patients with SRNS caused by defects in genes of the CoQ10 biosynthesis pathway [46].
In addition, genetic diagnosis provides a better understanding of long-term prognosis and enables early evaluation, referrals, and follow-up of extrarenal manifestations of syndromic disease. CAKUT caused by HNF1B mutations or 17q12 microdeletion is related to hypomagnesemia, hyperuricemia, and maturity-onset diabetes of the young (MODY) type 5. Similarly, PAX2 , EYA1, and SALL1 have been associated with CAKUT and deafness, GATA3 with CAKUT and hypoparathyroidism, WT1 with nephrotic syndrome and increased risk of Wilms’ tumor and gonadoblastoma; and NPHP5 with nephronophthisis and retinitis pigmentosa, resulting in progressive blindness [47-52]. Thus, early detection of these conditions can lead to early treatment.
Genetic diagnosis enables avoidance of unnecessary or invasive diagnostic procedures such as kidney biopsy for the diagnosis of Alport’s syndrome in the proband or in at-risk relatives. Genetic diagnosis also enables precise genetic counseling, identification and testing of at-risk relatives, prediction of disease recurrence for future pregnancies, and preimplantation and prenatal diagnosis.

Genetic counseling

When genetic testing is required, appropriate genetic counseling, including documentation of consent from the patient, is essential before testing [53]. This discussion includes an explanation on the basic principles of heredity, genetic disease, and testing modality; the benefits, risks and limitations of testing; expected testing results; types of incidental/secondary findings; and cost of testing. Patients should be informed of the possibility of incidentally finding medically actionable genes.
Genetic counseling should be provided after testing. The test results should be interpreted, and the inheritance pattern and risk of recurrence need to be discussed. In addition, the availability of management and prevention modalities, the need for further testing, and the implications for the family should be discussed. Moreover, emotional and social support and patient support groups or reference resources should be provided.

Diagnostic approach and interpretation of genetic testing

The most appropriate genetic testing modality should be determined according to the clinical diagnosis. The Fig. 1 shows the diagnostic approach for genetic testing of kidney disease, modified from the suggested algorithm for kidney disease of unknown etiology by Hay et al. [15]. When genetic testing results are positive, we should check whether the genetic diagnosis is consistent with the patient’s clinical manifestations. The strategy of re-evaluation of patients after genetic testing, i.e., reverse phenotyping, increases the diagnostic yield and enables the identification of subtle and previously unrecognized clinical signs [29,54].
If the genetic diagnosis is compatible with the clinical diagnosis, appropriate genetic counseling should be performed with patients and at-risk relatives. If the genetic test result is incompatible with clinical manifestations, we should review the clinical and molecular data, and discuss it with molecular diagnosticians or clinical geneticists.
There should be high suspicion for genetic diagnoses despite negative genetic testing results, considering the limitations of genetic testing modalities. For example, WES has blind spots and cannot detect deep intronic splicing variants, large deletions, or duplications. Additionally, somatic mosaic mutations that are not detected in DNA extracted from peripheral leukocytes may be present.

Conclusion

The role of genetic testing in the diagnosis of kidney disease has increased in recent years. It is important for pediatric nephrologists to know when and how to apply genetic testing modalities. Genetic testing is recommended in children with SRNS, in those suspected hereditary forms of kidney disease such as CAKUT or cystic disease, and in those with extrarenal manifestations [55,56]. Genetic testing alone, without a detailed phenotype, rarely yields a confirmative diagnosis. Therefore, careful, precise, and comprehensive assessment by clinicians is essential, encompassing patient history, family history, physical examination, biochemical and serologic testing, radiologic testing, and pathology, if indicated.

Notes

Funding
This research was supported in part by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (NRF-2018M3A9H1078335).
Conflict of interest
No potential conflict of interest relevant to this article was reported.

References

1. Andrassy KM. Comments on 'KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease'. Kidney Int. 2013;84: 622-3.
crossref
2. Mong Hiep TT, Ismaili K, Collart F, Van Damme-Lombaerts R, Godefroid N, Ghuysen MS, et al. Clinical characteristics and outcomes of children with stage 3-5 chronic kidney disease. Pediatr Nephrol. 2010;25: 935-40.
crossref pmid
3. Weaver DJ, Mitsnefes M. Cardiovascular Disease in Children and Adolescents With Chronic Kidney Disease. Semin Nephrol. 2018;38: 559-69.
crossref pmid
4. Ruidiaz-Gómez KS, Higuita-Gutiérrez LF. Impact of chronic kidney disease on health-related quality of life in the pediatric population: meta-analysis. J Pediatr (Rio J). 2020;S0021-7557(20)302436.
crossref
5. Vivante A, Hildebrandt F. Exploring the genetic basis of earlyonset chronic kidney disease. Nat Rev Nephrol. 2016;12: 133-46.
crossref pmid pmc
6. Harambat J, van Stralen KJ, Kim JJ, Tizard EJ. Epidemiology of chronic kidney disease in children. Pediatr Nephrol. 2012;27: 363-73.
crossref pmid
7. Smith JM, Stablein DM, Munoz R, Hebert D, McDonald RA. Contributions of the Transplant Registry: The 2006 Annual Report of the North American Pediatric Renal Trials and Collaborative Studies (NAPRTCS). Pediatr Transplant. 2007;11: 366-73.
crossref pmid
8. McClellan WM, Satko SG, Gladstone E, Krisher JO, Narva AS, Freedman BI. Individuals with a family history of ESRD are a highrisk population for CKD: implications for targeted surveillance and intervention activities. Am J Kidney Dis. 2009;53: S100-6.
crossref pmid
9. Connaughton DM, Bukhari S, Conlon P, Cassidy E, O'Toole M, Mohamad M, et al. The Irish Kidney Gene Project--Prevalence of Family History in Patients with Kidney Disease in Ireland. Nephron. 2015;130: 293-301.
crossref
10. Connaughton DM, Hildebrandt F. Personalized medicine in chronic kidney disease by detection of monogenic mutations. Nephrology Dialysis Transplantation. 2019;35: 390-7.
crossref pmc
11. Rasouly HM, Groopman EE, Heyman-Kantor R, Fasel DA, Mitrotti A, Westland R, et al. The Burden of Candidate Pathogenic Variants for Kidney and Genitourinary Disorders Emerging From Exome Sequencing. Ann Intern Med. 2019;170: 11-21.
crossref pmid
12. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, et al. The Sequence of the Human Genome. Science. 2001;291: 1304-51.
crossref pmid
13. Stankiewicz P, Lupski JR. Structural variation in the human genome and its role in disease. Annu Rev Med. 2010;61: 437-55.
crossref pmid
14. Miller DT, Adam MP, Aradhya S, Biesecker LG, Brothman AR, Carter NP, et al. Consensus statement: chromosomal microarray is a firsttier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet. 2010;86: 749-64.
crossref
15. Hays T, Groopman EE, Gharavi AG. Genetic testing for kidney disease of unknown etiology. Kidney Int. 2020;98: 590-600.
crossref pmid
16. Verbitsky M, Westland R, Perez A, Kiryluk K, Liu Q, Krithivasan P, et al. The copy number variation landscape of congenital anomalies of the kidney and urinary tract. Nat Genet. 2019;51: 117-27.
pmid
17. Sanna-Cherchi S, Kiryluk K, Burgess KE, Bodria M, Sampson MG, Hadley D, et al. Copy-number disorders are a common cause of congenital kidney malformations. Am J Hum Genet. 2012;91: 987-97.
crossref pmid pmc
18. Caruana G, Wong MN, Walker A, Heloury Y, Webb N, Johnstone L, et al. Copy-number variation associated with congenital anomalies of the kidney and urinary tract. Pediatr Nephrol. 2015;30: 487-95.
crossref pmid
19. Wang XV, Blades N, Ding J, Sultana R, Parmigiani G. Estimation of sequencing error rates in short reads. BMC Bioinformatics. 2012;13: 185.
crossref pmid pmc
20. Goodwin S, McPherson JD, McCombie WR. Coming of age: ten years of next-generation sequencing technologies. Nature Reviews Genetics. 2016;17: 333-51.
crossref pmid
21. Artuso R, Fallerini C, Dosa L, Scionti F, Clementi M, Garosi G, et al. Advances in Alport syndrome diagnosis using next-generation sequencing. Eur J Hum Genet. 2012;20: 50-7.
crossref
22. McCarthy HJ, Bierzynska A, Wherlock M, Ognjanovic M, Kerecuk L, Hegde S, et al. Simultaneous sequencing of 24 genes associated with steroid-resistant nephrotic syndrome. Clin J Am Soc Nephrol. 2013;8: 637-48.
crossref pmid pmc
23. Otto EA, Ramaswami G, Janssen S, Chaki M, Allen SJ, Zhou W, et al. Mutation analysis of 18 nephronophthisis associated ciliopathy disease genes using a DNA pooling and next generation sequencing strategy. J Med Genet. 2011;48: 105-16.
crossref pmid
24. Murray SL, Fennelly NK, Doyle B, Lynch SA, Conlon PJ. Integration of genetic and histopathology data in interpretation of kidney disease. Nephrol Dial Transplant. 2020;35: 1113-32.
crossref pmid
25. Ahn YH, Lee C, Kim NKD, Park E, Kang HG, Ha I-S, et al. Targeted Exome Sequencing Provided Comprehensive Genetic Diagnosis of Congenital Anomalies of the Kidney and Urinary Tract. Journal of Clinical Medicine. 2020;9: 751.
crossref pmc
26. Sen ES, Dean P, Yarram-Smith L, Bierzynska A, Woodward G, Buxton C, et al. Clinical genetic testing using a custom-designed steroid-resistant nephrotic syndrome gene panel: analysis and recommendations. J Med Genet. 2017;54: 795-804.
crossref pmid
27. Park E, Lee C, Kim NKD, Ahn YH, Park YS, Lee JH, et al. Genetic Study in Korean Pediatric Patients with Steroid-Resistant Nephrotic Syndrome or Focal Segmental Glomerulosclerosis. Journal of Clinical Medicine. 2020;9: 2013.
crossref pmc
28. Bullich G, Domingo-Gallego A, Vargas I, Ruiz P, Lorente-Grandoso L, Furlano M, et al. A kidney-disease gene panel allows a comprehensive genetic diagnosis of cystic and glomerular inherited kidney diseases. Kidney Int. 2018;94: 363-71.
pmid
29. Landini S, Mazzinghi B, Becherucci F, Allinovi M, Provenzano A, Palazzo V, et al. Reverse Phenotyping after Whole-Exome Sequencing in Steroid-Resistant Nephrotic Syndrome. Clin J Am Soc Nephrol. 2020;15: 89-100.
crossref pmid
30. Warejko JK, Tan W, Daga A, Schapiro D, Lawson JA, Shril S, et al. Whole Exome Sequencing of Patients with Steroid-Resistant Nephrotic Syndrome. Clin J Am Soc Nephrol. 2018;13: 53-62.
pmid
31. Zhou B, Ho SS, Zhang X, Pattni R, Haraksingh RR, Urban AE. Wholeg-enome sequencing analysis of CNV using low-coverage and paired-end strategies is efficient and outperforms array-based CNV analysis. J Med Genet. 2018;55: 735-43.
crossref pmid
32. Meienberg J, Bruggmann R, Oexle K, Matyas G. Clinical sequencing: is WGS the better WES? Hum Genet. 2016;135: 359-62.
crossref pmid pmc
33. Baker SW, Murrell JR, Nesbitt AI, Pechter KB, Balciuniene J, Zhao X, et al. Automated Clinical Exome Reanalysis Reveals Novel Diagnoses. J Mol Diagn. 2019;21: 38-48.
crossref pmid
34. Rao J, Liu X, Mao J, Tang X, Shen Q, Li G, et al. Genetic spectrum of renal disease for 1001 Chinese children based on a multicenter registration system. Clin Genet. 2019;96: 402-10.
pmid
35. Mann N, Braun DA, Amann K, Tan W, Shril S, Connaughton DM, et al. Whole-Exome Sequencing Enables a Precision Medicine Approach for Kidney Transplant Recipients. J Am Soc Nephrol. 2019;30: 201-15.
crossref pmid pmc
36. Groopman EE, Marasa M, Cameron-Christie S, Petrovski S, Aggarwal VS, Milo-Rasouly H, et al. Diagnostic Utility of Exome Sequencing for Kidney Disease. N Engl J Med. 2019;380: 142-51.
crossref pmid
37. Lionel AC, Costain G, Monfared N, Walker S, Reuter MS, Hosseini SM, et al. Improved diagnostic yield compared with targeted gene sequencing panels suggests a role for whole-genome sequencing as a first-tier genetic test. Genet Med. 2018;20: 435-43.
crossref pmid
38. Sadowski CE, Lovric S, Ashraf S, Pabst WL, Gee HY, Kohl S, et al. A single-gene cause in 29.5% of cases of steroid-resistant nephrotic syndrome. J Am Soc Nephrol. 2015;26: 1279-89.
crossref pmid
39. Ali H, Al-Mulla F, Hussain N, Naim M, Asbeutah AM, AlSahow A, et al. PKD1 Duplicated regions limit clinical Utility of Whole Exome Sequencing for Genetic Diagnosis of Autosomal Dominant Polycystic Kidney Disease. Scientific Reports. 2019;9: 4141.
crossref pmid pmc
40. Kingsmore SF, Cakici JA, Clark MM, Gaughran M, Feddock M, Batalov S, et al. A Randomized, Controlled Trial of the Analytic and Diagnostic Performance of Singleton and Trio, Rapid Genome and Exome Sequencing in Ill Infants. Am J Hum Genet. 2019;105: 719-33.
pmid pmc
41. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in medicine : official journal of the American College of Medical Genetics. 2015;17: 405-24.
crossref pmid pmc
42. Deignan JL, Chung WK, Kearney HM, Monaghan KG, Rehder CW, Chao EC. Points to consider in the reevaluation and reanalysis of genomic test results: a statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2019;21: 1267-70.
crossref pmid pmc
43. SoRelle JA, Thodeson DM, Arnold S, Gotway G, Park JY. Clinical Utility of Reinterpreting Previously Reported Genomic Epilepsy Test Results for Pediatric Patients. JAMA Pediatr. 2019;173: e182302.
crossref pmid
44. Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, et al. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2017;19: 249-55.
crossref pmid
45. Ethical and policy issues in genetic testing and screening of children. Pediatrics. 2013;131: 620-2.
pmid
46. Tan W, Airik R. Primary coenzyme Q10 nephropathy, a potentially treatable form of steroid-resistant nephrotic syndrome. Pediatr Nephrol. 2021;doi: 10.1007/s00467-020-04914-8.
crossref
47. Madariaga L, García-Castaño A, Ariceta G, Martínez-Salazar R, Aguayo A, Castaño L. Variable phenotype in HNF1B mutations: extrarenal manifestations distinguish affected individuals from the population with congenital anomalies of the kidney and urinary tract. Clin Kidney J. 2019;12: 373-9.
crossref pmid
48. Sanyanusin P, McNoe LA, Sullivan MJ, Weaver RG, Eccles MR. Mutation of PAX2 in two siblings with renal-coloboma syndrome. Hum Mol Genet. 1995;4: 2183-4.
crossref pmid
49. Ruf RG, Xu PX, Silvius D, Otto EA, Beekmann F, Muerb UT, et al. SIX1 mutations cause branchio-oto-renal syndrome by disruption of EYA1-SIX1-DNA complexes. Proc Natl Acad Sci U S A. 2004;101: 8090-5.
crossref pmid pmc
50. Kohlhase J, Wischermann A, Reichenbach H, Froster U, Engel W. Mutations in the SALL1 putative transcription factor gene cause Townes-Brocks syndrome. Nat Genet. 1998;18: 81-3.
crossref pmid
51. Van Esch H, Groenen P, Nesbit MA, Schuffenhauer S, Lichtner P, Vanderlinden G, et al. GATA3 haplo-insufficiency causes human HDR syndrome. Nature. 2000;406: 419-22.
crossref pmid
52. Chernin G, Vega-Warner V, Schoeb DS, Heeringa SF, Ovunc B, Saisawat P, et al. Genotype/phenotype correlation in nephrotic syndrome caused by WT1 mutations. Clin J Am Soc Nephrol. 2010;5: 1655-62.
crossref pmid pmc
53. ACMG Board of Directors. Points to consider for informed consent for genome/exome sequencing. Genet Med. 2013;15: 748-9.
pmid
54. Connaughton DM, Kennedy C, Shril S, Mann N, Murray SL, Williams PA, et al. Monogenic causes of chronic kidney disease in adults. Kidney Int. 2019;95: 914-28.
crossref pmid pmc
55. Cheong HI. Genetic tests in children with steroid-resistant nephrotic syndrome. Kidney Res Clin Pract. 2020;39: 7-16.
crossref pmid pmc
56. Aymé S, Bockenhauer D, Day S, Devuyst O, Guay-Woodford LM, Ingelfinger JR, et al. Common Elements in Rare Kidney Diseases: Conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int. 2017;92: 796-808.
pmid pmc

Fig. 1.
Approach to genetic testing in children with kidney disease, which is modified from the suggested algorithm for kidney disease of unknown etiology by Hay et al.[15]. CAKUT, congenital anomalies of the kidney and urinary tract; CMA, chromosomal microarray; SNRS, steroid-resistant nephrotic syndrome; VUS, variants of unknown significance; WES, whole exome sequencing.
ckd-25-1-14f1.jpg
Table 1.
Summary of genetic testing modalities
Target and resolution Detects Advantages Disadvantage
Karyotyping Genome Aneuploidies, chromosomal Low cost Low resolution
≥10Mb abnormalities Detects balanced translocations
Chromosomal microarray Genome Small chromosomal rearrangements/CNVs High resolution for CNVs Limited ability to detect inversions and balanced translocations
≥200 kb–400 kb Detects regions of homozygosity in SNP based array CNVs in repetitive regions and pseudogenes
Sanger sequencing Specific gene SNVs/small INDELs (<1 kb) Targeted, rapid and simple interpretation Low throughput
Single base High accuracy (error rate 0.001–1%) Labor intensive
Massive parellel sequencing (Second generation sequencing, NGS)
 Targeted gene panel Specific gene of interest for the clinical phenotype SNVs/small INDELs (<1 kb) Targeted high throughput Unable to identify genes not on panel
Reduced analysis time Limited potential for reanalysis
Single base Minimize potential detection of secondary and incidental findings
 Exome sequencing Coding regions of the genome (exome) SNV/small INDELs (<1 kb) Covers entire coding regions of genome Coverage per base is generally lower than with targeted panels
Single base Useful for reanalysis Misses noncoding variants
Low limited detection in CG-rich and repetitive regions
Potential detection of undesired secondary and incidental findings
 Genome sequencing Coding and noncoding regions of the genome SNV/small INDELs (<1 kb), CNV Identification of deep splicing and intronic variants High costs
Single base Identification of structural variants Generates large amount of data
Useful for reanalysis Potential detection of undesired secondary and incidental findings

CNV, copy number variation; INDEL, insertion/deletion; SNV, single nucleotide variant.

Table 2.
Summary of major genetic causes of inherited kidney diseases
Clinical diagnosis Genomic regions or genes Diagnostic yield
Congenital anomalies of kidney and urologic tract 1q12.1, 4p16.1-16.3, 16p11.2, 16p13.11, 17q12, 22q11.2 8–20%
ACE, AGT, AGTR1, BICC1, BMP4, BMP7, CDC5L, CDKN1C, CHD1L, CHD7, CHRM3, EYA1, FGFR1, FGFR2, GATA3, GDF11, GDNF, GFRA1, GLI3, GPC3, GREM1, HNF1B,HPSE2, JAG1, KAL1, NOTCH2, OFD1, PAX2, PAX8, RET, ROBO2, SALL1, SIX1, SIX5, SOX17, SOX9, UPK3A, WNT4, WT1
Cystic kidney disease 36–80%
Autosomal dominant polycystic kidney disease PKD1, PKD2, GANAB, DNAJB11
Autosomal recessive polycystic kidney disease PKHD1, DZIP1L
Nephronophthisis-related ciliopathies NPHP1-NPHP6, TMEM67, ANKS6, TTC21B, GLIS2, CEP164, INVS, MAPKB1, NEK8, CEP83, WDR19, ZNF423
Joubert syndrome INPP5E, TMEM216, CC2D2A, AHI1, CEP41, RPGRIP1L
Bardet–Biedl syndrome BBS1-BBS12, NPHP6, CEP290, MKS1, SDCCAG8, SEPT7
Senior–Løken syndrome NPHP1, NPHP4, CEP290, IQCB1, SDCCAG8, WDR19
Autosomal dominant tubulointerstitial kidney disease UMOD, MUC1, REN, HNF1B,SEC61A1 34–45%
Alport syndrome COL4A3, COL4A4 and COL4A5 ~80%
Steroid resistant nephrotic syndrome/Focal segmental glomerulosclerosis 6.3–100%
Non-syndromic PLCE1, KANK2, KANK4, TRPC6, NPHS1, NPHS2, CD2AP, MYO1E, MAGI2, XPO5, NUP85, NUP93, NUP205, NUP160, PTPRO, MP2, COQ8B, TTC21B, AVIL, INF2, ACTN4, ARHGAP24, ANLN, CRB2, ARHGDIA, FAT1, NXF5, TBC1D8B
Syndromic WT1, PAX2, EYA1, LMX1B, SMARCAL1, LMNA, WDR73, SCARB2, COL4A3, COL4A4, COL4A5, ITGB4, LAMB2, MYH9, CUBN, SGPL1, PODXL, NUP107, NUP133, MT-TL1, MT-TL2, MT-TY, COQ2, COQ6

Modified from Murray et al. and Connaughton et al. [10,24].

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