The Role Of Genetic Testing in The Diagnostic Workfow Of Pediatric Patients With Kidney Diseases: The Experience Of A Single Institution
Oct 18, 2023
Abstract Purpose Inherited kidney diseases are among the leading causes of kidney failure in children, resulting in increased mortality, high healthcare costs, and the need for organ transplantation. Next-generation sequencing technologies can help in the diagnosis of rare monogenic conditions, allowing for optimized medical management and therapeutic choices.
Methods Clinical exome sequencing (CES) was performed on a cohort of 191 pediatric patients from a single institution, followed by Sanger sequencing to confirm identified variants and for family segregation studies. Results All patients had a clinical diagnosis of kidney disease: the main disease categories were glomerular diseases (32.5%), ciliopathies (20.4%), CAKUT (17.8%), nephrolithiasis (11.5%) and tubular disease (10.5%). 7.3% of patients presented with other conditions. A conclusive genetic test, based on CES and Sanger validation, was obtained in 37.1% of patients. The highest detection rate was obtained for ciliopathies (74.4%), followed by nephrolithiasis (45.5%), and tubular diseases (45%), while most glomerular diseases and CAKUT remained undiagnosed. Conclusions Results indicate that genetic testing consistently used in the diagnostic workflow of children with chronic kidney disease can (i) confirm clinical diagnosis, (ii) provide an early diagnosis in the case of inherited conditions, (iii) and the genetic cause of previously unrecognized diseases and (iv) tailor transplantation programs.
Keywords Clinical exome sequencing, Next-generation sequencing, Kidney diseases, Genetic testing, Pediatric cohort
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Introduction
Pediatric nephropathies comprise widely different disease entities in terms of clinical presentation, evolution, and therapeutic options [1–4]. Approximately 30% of children with chronic kidney disease (CKD) suffer from a monogenic condition, a percentage increasing when considering children with end-stage renal disease (ESRD) [5, 6]. Many of these children remain undiagnosed at the time of transplantation [4, 6, 7]. Reaching a diagnosis for these patients not only implies the end of a diagnostic odyssey, but presents several advantages for prognosis, management, and treatment
Pioneering studies have consistently shown that the implementation of next-generation sequencing (NGS) techniques has significantly improved the diagnostic yield in patients with inherited kidney diseases (IKD) [8]. More recently, the widespread use of NGS has made the available genetic diagnosis in a reasonable time and at affordable costs, raising the question of whether and when it should be integrated in the routine diagnostic workflow [5].
Genetic diagnosis in children is of utmost importance for different aspects. The first is that it may be relevant in the clinical approach to the disease, the typical example being that of nephrotic syndromes where the identification of structural variants in podocyte-related genes argues against immunosuppressive therapies that would otherwise be routinely used over a period of several months [9]. The second is that it may be highly relevant for the child’s family and for the identification of other members who are carrying the variant possibly transmissible to future generations. Once a pathogenic variant is identified in a proband, cascade testing of family members and genetic counseling in variant carriers represent standard practice in clinical genetics [5]. The third is that knowing the pathogenic variant is essential in the transplantation context where the donor may be a relative. Indeed, it is critical to rule out the presence of the same variant(s) in the organ donor, as well as it is critical to identify all family members potentially in need of a transplant. The fourth is that some diseases present a high risk of relapse after the organ transplantation, such as focal segmental glomerulosclerosis [10] or their outcome may be improved by a more tailored choice of the transplant to be performed, such as in the case of primary hyperoxaluria where a combined kidney-liver transplant may result in a better outcome [11]. Finally, having a clear disease diagnosis may be useful for the patient to take part in clinical trials and to benefit from novel treatment options [12, 13].
At the end of 2018, in a collaboration between pediatric nephrologists and geneticists, we started performing genetic tests for monogenic conditions potentially leading to ESRD and hence transplantation. Our hospital is the biggest in Northwest Italy, draining from an area of about 5 million people. We selected a “one size fits all” kind of analysis, with the sequencing of the clinical exome, i.e., approximately 6700 genes that are associated with monogenic conditions, focusing analysis on gene panels tailored to the clinical suspicion and therefore limiting incidental findings and reducing time for sequence analysis.
Overall, by applying this pipeline, we obtained a diagnostic yield in line with published data, with some heterogeneity among the different clinical suspicion, as expected. The results obtained confirm the relevance of including routine genetic testing and counseling in the diagnostic workflow of pediatric patients affected by nephropathies. Indeed, the identification of causative variants is critical for their clinical management, and potentially for optimal live-donor selection.
Materials and methods
Patients recruitment
The study was based on a diagnostic cohort of 191 consecutive pediatric patients (age at recruitment < 18 years old), recruited by the Pediatric Nephrology, Dialysis, and Transplantation Units at the Regina Margherita Children’s Hospital and referred to the Immunogenetics and Transplant Biology Service for genetic analysis. All patients included in the study provided a written informed consent signed by both parents, whenever possible.
Sample preparation, sequencing, and bioinformatics analyses
Nucleic acid extraction from peripheral blood, analysis of DNA quality, library preparation, and sequencing were performed as previously reported [14]. Raw data obtained from sequencing were converted in FASTQ files and then aligned with Enrichment 3.1.0 or DRAGEN Enrichment tools (Illumina) and mapped on TruSightOne Expanded v2.0 manifest using Homo Sapiens UCSC GRCh37 genome as a reference to obtain single nucleotide variants, copy number variants (CNV) and structural variants of files. For copy number identification, a baseline made of sequencing data from 5 different patients, all negative for CNV (as per array comparative genomic hybridization data) was used. This approach allows to detection of CNV even in sexual chromosomes since the reference group was made both of female and male individuals and the gender of the subject to be analyzed was always specified during the alignment phase. Variant calling and prioritization were made following defined criteria. Reads alignment and exons coverage of gene of interest were checked and displayed by Integrative Genomics ViewerIGV, freely available from the UC San Diego—University of California and the Broad Institute of MIT and Harvard University—Boston (https://software.broadinstitute.org/ software/igv/). Variants to be included in the final genetic report were classified according to the American College of Medical Genetics and Genomics (ACMG) criteria.
Generation of in silico gene‑disease list
Genes to be considered for variant identification and prioritization were defined based on the clinical suspicions. In silico gene lists were generated matching (i) data from different databases, correlating genotype to phenotype (OMIM, PanelApp England, ClinGen, Malacards), and (ii) data from the literature. The available gene lists are updated once a year based on novel evidence of gene-disease association.
Sanger sequencing and multiplex ligation‑dependent probe amplification (MLPA)
Sanger sequencing and/or MLPA analyses were performed to validate variants identified by NGS and for family segregation studies. Briefly, DNA was extracted starting from a second independent aliquot of the proband peripheral blood and from the parents. The DNA regions of interest were amplified by PCR using specific experimental conditions. The purity and specificity of the amplified regions were checked by 0.8 or 1.5% agarose gel. Amplified PCR products were then Sanger sequenced using the same primers. For PKD1 variants, validation was performed using a long-range PCR followed by a nested PCR to avoid any inference from the pseudogenes.
Results
Definition of criteria for the return of genetic analysis results
We previously reported on the design and set-up of a “kidney” gene panel that comprises>400 genes all involved in different forms of kidney diseases [14]. For this study, we implemented analysis with subpanels focused on the specific clinical category of suspicion (e.g., CAKUT, glomerulopathy, tubulopathy, etc.) and prioritized a specific group of genes for analysis. This approach limited the number of analyzed genes, simplifying analyses, and reducing the number of incidental findings. Only when, at the end of the analytical field with relevant panel(s), the genetic result was negative and (i) the clinical phenotype not clearly indicated or (ii) overlapping different disease categories, genetic analysis was extended to the so-called “kidney full-list or kidneyome”, a super-panel comprising all the genes included in the subpanels.
As a first step, we defined a set of criteria for the interpretation of NGS results. After performing clinical exome sequencing (CES) and data alignment, a pipeline of analysis was determined to filter in the relevant variants. Specifically, based on clinical suspicion, identified variants were filtered based on in silico gene lists, specific for the different disease macro-categories. Synonymous variants not impacting the splicing mechanism or intronic variants not mapping within the splicing region were excluded, keeping in consideration only the nonsynonymous, nonsense, frameshift, and splicing-affecting variants. Ten, only rare variants (frequency less than 1% in the population) and variants with an allele frequency in the patient of at least 0.2 and coverage of at least 20 reads were included. The remaining variants were annotated and further curated based on (i) mode of inheritance, (ii) nucleotide conservation, (iii) protein impact, exploiting different databases to check the scores, and (iv) literature, if any. At this point, filtered-in variants were listed in a so-called “technical report”. The technical report was interpreted by a medical geneticist to produce the final genetic report for the patient and his/her family. During the genetic consult, family segregation studies were proposed to (i) confirm the variants in the proband, and (ii) to include/exclude non-causative variants based on their segregation in the family (Fig. 1).
By adopting these criteria, we were able to define three different categories of genetic reports. First, a “conclusive report” that included pathogenic (C5) and likely pathogenic (C4) variants. Reports of variants of unknown significance (C3) were considered conclusive only if fully compatible with the clinical picture and if family segregation studies confrmed their possible role. Second, an “uncertain report” that included C3 variants identified by CES that are not yet or could not be validated in the context of family segregation studies or C4/C5 variants that were not fully in line with the clinical phenotype. Third, an “inconclusive report” that included (i) a negative CES analysis, meaning that no variants were identified by NGS; (ii) single variants in recessive genes; and (iii) C3 variants not in line with the clinical phenotype, identified when the analysis was extended to all kidney disease-related genes (Fig. 1).
Main features of the recruited cohort
This study describes a cohort of 191 pediatric patients (0–18 years of age) who were consecutively referred by the Pediatric Nephrology Unit for genetic analysis from November 2018 to May 2022, with an average of 50 new patients enrolled each year. Criteria for genetic testing were (i) nephropathy associated with a positive family history of kidney disease or (ii) clinical suspicion of a monogenic condition or (iii) need to rule out a monogenic condition (as in the case of nephrotic syndromes, where distinguishing monogenic versus non-monogenic diseases is clinically meaningful for prognosis and treatment).
The cohort was divided on the basis of the clinical suspicion, considering 6 different disease macro-categories: congenital abnormalities of the kidney and urinary tract (CAKUT; n=34), ciliopathies (n=39), glomerulopathy (n=62), nephrolithiasis (n=22), tauopathies (n=20) and other diseases that included also syndromic phenotypes (n=14). Except for CAKUT and tubulopathies that showed an equal distribution between females and males, in all the other categories, there was a prevalence of male subjects (Fig. 2a). When looking at the age of recruitment, no significantly different distribution was highlighted among the different groups, with mean age ranging from 6.7 to 10 years old in “Other diseases” and glomerulopathies, respectively. However, when looking at the median age, CAKUT diseases showed the lowest value (4.6 years old), in keeping with a congenital phenotype. From the ethnicity point of view, independent of the disease macro-category considered, most patients were European, followed by African, with only a few patients being Asian, Latin-American or crossbred (Fig. 2b). Among the cohort, only 8 patients had consanguineous parents.
Fig. 1 Genetic data analysis pipeline and criteria for variant inclusion. Schematic representation of the analytical pipeline adopted for variant identification and prioritization, including all the filtering-in and filtering-out criteria. The resulting variants were included in the final genetic report. Whenever possible, variant(s) validation and family segregation studies were performed. Genetic reports were classified as conclusive, uncertain, or inconclusive based on the indicated criteria. Based on this classification the diagnostic rate of our next-generation sequencing (NGS) workflow was calculated. 1 KG: 1000 genomes database; Alt fr: altered frequency; C3: variant of unknown significance; C4: likely pathogenic variant; C5: pathogenic variant; AR: autosomal recessive
Finally, when taking into account family history for kidney diseases considering male and female subjects separately, heterogeneity in distribution between positive and negative cases was evident considering the different disease categories. Overall, most of the recruited cohort and independently of the gender was not characterized by a positive family history, as shown for CAKUT, glomerulopathies, tauopathies and other kidney disorders. However, in ciliopathies and nephrolithiasis, a signifcant proportion of cases presented with a positive family history with a different distribution between females and males (13 cases out of 22 for ciliopathies, and 5 out of 12 for nephrolithiasis; Fig. 2c).
From the clinical standpoint, the cohort was quite heterogenous with different primary diseases included (Fig. 2d). Among them, the most recurrent clinical suspicions were polycystic kidney disease (n=27), CAKUT (n=25), nephrotic syndrome (n=19), focal segmental glomerulosclerosis (FSGS; n=14) and Alport syndrome (n=13; Fig. 2d).
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