Monogenic Etiologies of Kidney Cysts in the Pediatric Population

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Abstract

Key Points

• In a cohort of children, 79% of families with kidney cysts had a monogenic diagnosis.

• Resolved cases were more likely to have a family history of kidney cysts and unresolved cases more often had unilateral cysts.

• Broad genetic testing revealed genetic diversity and informed prognosis and clinical management in childhood kidney cysts.

Background

Pediatric kidney cysts may indicate an underlying genetic disorder, yet the full spectrum of causes remains incompletely defined. With advances in genetic testing enabling broader evaluation, this study assessed the diagnostic utility of comprehensive genetic testing in a broad pediatric cohort with kidney cysts and characterized the underlying etiological diversity.

Methods

This observational cohort study included patients younger than 18 years enrolled between January 2020 and June 2024 at a single tertiary center. Genetic testing used targeted multigene or custom curated exome/genome sequencing panels, with segregation analysis when available. Eligible participants had at least two cysts without family history, one cyst with positive family history, or enlarged echogenic kidneys on prenatal ultrasound; those with congenital anomalies of the kidney and urinary tract associated with cysts were excluded. Clinical presentation was categorized as symptomatic, incidental, prenatal, or family screening. Primary outcomes were diagnostic yield and distribution of pathogenic variants.

Results

Among 109 patients (median age 7.6 years, 53% female), genetic testing identified a definitive diagnosis in 81 of 100 tested patients (81%) from 72 families (79%; 14 disorders). PKD1 variants were most common (45%), while PKD2 accounted for 7%. Other causes included HNF1B or 17q12 deletions (13%), minor autosomal dominant polycystic kidney disease genes (11%; GANAB, NEK8, IFT140), monoallelic PKHD1 (3%), and biallelic PKHD1 (8%), while syndromic ciliopathy genes accounted for 5%. A positive family history of cystic kidney disease was more common among patients with a genetic diagnosis (54% versus 11%; P = 0.008). Patients without an identified genetic diagnosis more often had unilateral cysts (26% versus 4%; P = 0.53). Diagnosis by clinical symptoms was the most genetically diverse category.

Conclusions

Comprehensive genetic testing in pediatric kidney cysts achieved high diagnostic yield in a selected cohort and identified diverse causes beyond major autosomal dominant polycystic kidney disease/autosomal recessive polycystic kidney disease genes, supporting early evaluation to improve diagnostic accuracy, inform prognosis, and guide management, even in the absence of family history.

Introduction

Cystic kidney diseases in children represent a heterogeneous group of disorders with significant implications for long-term kidney health. These conditions, including nonsyndromic polycystic kidney diseases (PKD) and related ciliopathies, are estimated to account for 6%–10% of early-onset CKD.¹ As imaging technologies such as prenatal ultrasound (US) and pediatric abdominal US become more widespread, kidney cysts are being identified with greater frequency in pediatric patients.^2,3 While simple kidney cysts are relatively common and typically benign in adults, their presence in children, particularly when detected early, and even if unilateral or in the absence of family history, can raise clinical concern for an underlying genetic disorder.^4,5 Even a single cyst can raise concern, presenting a diagnostic challenge for pediatricians in balancing appropriate evaluation with minimizing anxiety. Although autosomal recessive polycystic kidney disease (ARPKD) is the classic pediatric form, the full genetic spectrum of childhood cystic kidney disease remains unclear.

ARPKD is caused by biallelic pathogenic variants in PKHD1, which encodes fibrocystin, a ciliary protein essential for organ development and function.^6,7 Although traditionally considered an adult-onset disease, autosomal dominant polycystic kidney disease (ADPKD) related to monoallelic PKD1 or PKD2 pathogenic variants is increasingly recognized in childhood, with studies showing early cyst development in affected individuals.^8–10 In rare cases, children with biallelic PKD1 variants, including one hypomorphic allele, can present with very early-onset ADPKD (ADPKD_VEO), often complicated by hypertension, proteinuria, and progressive CKD.¹¹ HNF1B is essential for kidney development, and pathogenic variants, including large deletions including the gene (17q12 deletion syndrome; 17q12del), can cause a cystic kidney phenotype through dysregulation of cystogenesis-related genes.^12,13 Disruption of ciliary signaling not only drives cyst formation in the kidneys but may also affect the liver, pancreas, heart, eye, and brain, leading to systemic complications, such as hepatic fibrosis, congenital cardiac anomalies, and neurodevelopmental delay.^14,15

Recent studies have expanded the genetic landscape of cystic kidney disease, with biallelic variants in CYS1 and DZIP1L reported in ARPKD-like presentations,^16,17 and monoallelic variants in NEK8 linked to childhood PKD, including severe early-onset forms resembling ADPKD_VEO or ARPKD.^18,19 In adults, monoallelic pathogenic variants in GANAB, ALG5, ALG8, ALG9, DNAJB11, and IFT140 have been recently identified, typically associated with a mild ADPKD phenotype.^18,20–24 A large population-based study found that more than 8% of adults with an ADPKD-like phenotype did not involve PKD1 or PKD2, indicating broader genetic contributions, but the relevance in children is unclear.²⁵ Despite advances in genomic technologies, few studies have systematically evaluated the full genetic landscape of pediatric kidney cysts using next-generation sequencing (NGS), especially in pediatric populations.^26–30 Pediatric presentations are often complicated by nonspecific or subtle imaging findings, limited family histories, or overlap with congenital anomalies of the kidney and urinary tract (CAKUT), making clinical diagnosis and management particularly complex. Broader access to genetic testing may allow earlier and more accurate diagnoses, refine surveillance recommendations, and improve genetic counseling, even in cases where cysts are discovered incidentally or in the absence of family history.

In this observational cohort study, we assessed the diagnostic utility of NGS-based testing in children with one or more kidney cysts. By characterizing the genetic spectrum and associated clinical features, we aim to provide data that supports early, comprehensive evaluation in pediatric practice and informs targeted management strategies.

Methods

Study Design and Data Collection

This observational cohort study was conducted at the Mayo Clinic Children's Cystic Kidney Disease Center, which was established in January 2020, and included patients enrolled from January 2020 to June 2024. The study included children younger than 18 years who met one of the following criteria: (1) at least two kidney cysts identified on imaging studies, regardless of laterality, in the absence of a family history of PKD; (2) one or more kidney cysts identified on imaging studies in the presence of a positive family history; or (3) enlarged echogenic kidneys detected on prenatal screening US. Patients with CAKUT, including multicystic dysplastic kidney, kidney dysplasia, obstructive uropathy, or vesicoureteral reflux-associated cysts, were excluded to avoid inclusion of phenocopies that mimic PKD. The exclusion was based on clinical judgment and imaging interpretation by a pediatric nephrologist with expertise in cystic and genetic kidney disease. Written informed consent was obtained from all eligible patients and/or their legal representatives. This study was approved by the Institutional Review Board Committees at Mayo Clinic, Rochester, Minnesota. Participants did not receive any stipend or financial compensation for their involvement. Although the study was prospective in recruitment, data collection was retrospective in nature. After enrollment, relevant medical records, including data before January 2020 and up to January 2025, were reviewed, and clinical, laboratory, and imaging data were abstracted from the electronic medical record. Kidney function was estimated using the CKD in Children U25 equation,³¹ and hypertension was defined according to 2017 American Academy of Pediatrics criteria.³²

Genetic Testing and Analysis

Clinical genetic testing was performed using targeted NGS capture panels or exome or genome backbone sequencing with analysis limited to a slice of nephrology or PKD/ciliopathy genes. Research testing used a targeted NGS panel capturing PKD and ciliopathy genes. Variants were classified according to American College of Medical Genetics and Genomics guidelines.³³ Research-based genetic testing was offered to those who declined clinical testing or were not fully resolved from the clinical testing. Clinical testing was performed in two external commercial Clinical Laboratory Improvement Amendments-certified laboratories with different tests offered during the course of this study with selection on the basis of the most comprehensive available test and patient insurance. For patients who underwent both clinical and research testing, the results were categorized under the method generating the presented genetic results. Patients with previously completed positive genetic testing before enrollment had those results reported without additional testing. Research genetic testing was performed at the Mayo Clinic PKD Center, not a Clinical Laboratory Improvement Amendments-certified laboratory. For patients with negative clinical or research panel testing, long-range PCR and Sanger sequencing of PKD1 and PKD2 regions with poor NGS coverage were performed. Detailed descriptions of sequencing platforms, variant filtering, and interpretation protocols are provided in Supplemental Methods. In addition, patients who had negative clinical testing were offered a referral to the Clinical Genomics department for additional comprehensive genetic testing. Genes identified in the cohort and their accession numbers used for sequencing are provided (Supplemental Table 1).

Imaging and Statistical Analysis

Imaging was reviewed for height-adjusted total kidney volume and cyst number, using published automated segmentation methods^34,35 and kidney length reference charts.³⁶ Most of the initial imaging data were collected clinically before enrollment, and magnetic resonance imaging (MRI) and computed tomography (CT) examinations were not performed according to a standardized cystic kidney imaging protocol. Follow up MRI and CT imaging were obtained as part of routine clinical care when clinically indicated. No CT studies were performed for research purposes. Research MRI studies were limited to patients aged 9 years and older able to tolerate MRI without sedation and were performed under separate research consent. Statistical hypothesis testing in Table 1 accounted for familial clustering using random effects (generalized linear mixed effects models for binary and continuous variables) or permutation testing (for multilevel factors). Additional methodological details are provided in the Supplemental File.

Table 1.

Baseline characteristics of the study population

Variable	Whole Cohort (N=109)	Tested Patients (N=100)	Genetically Resolved (N=81)	Genetically Unresolved (N=19)	P Valuea
Female patients, n (%)	58 (53%)	54 (54%)	44 (54%)	10 (53%)	0.89b
Age at diagnosisc (yr), median (Q1–Q3)	7.64 (0–14)	7.44 (0–13)	6.91 (0–12)	9.68 (2.5–14.5)	0.93d
Race, n (%)					0.23e,f
Asian	3 (3%)	2 (2%)	2 (3%)	0
Black or African American	1 (0.9%)	1 (1%)	0	1 (5%)
Other/not reported	6 (6%)	6 (6%)	6 (7%)	0
White	99 (91%)	91 (91%)	73 (90%)	18 (95%)
Ethnicity, n (%)					0.85b
Hispanic or Latino	2 (2%)	2 (2%)	1 (1%)	1 (5%)
Not Hispanic or Latino	104 (95%)	96 (96%)	79 (98%)	17 (90%)
Unknown	3 (3%)	2 (2%)	1 (1%)	1 (5%)
Family history of PKD, n (%)					0.008b,g
Yes	52 (48%)	46 (46%)	44 (54%)	2 (11%)
No	54 (50%)	51 (51%)	34 (42%)	17 (90%)
Unknown	3 (3%)	3 (3%)	3 (4%)	0
Presentation type, n (%)					0.31b
Clinical symptoms	34 (31%)	31 (31%)	25 (31%)	6 (32%)
Incidental	38 (35%)	34 (34%)	25 (31%)	9 (47%)
Family screening	13 (12%)	12 (12%)	12 (15%)	0
Prenatal US detection	24 (22%)	23 (23%)	19 (24%)	4 (21%)
eGFR (ml/min per 1.73 m 2 ) at time of diagnosisc					0.46d
Mean (SD)	92.84 (26.1)	93.21 (26.7)	92.23 (28.6)	97.56 (17.8)
<60, n (%)	10 (9%)	10 (10%)	9 (11%)	1 (5%)
Hypertension, n (%)					0.97b
Yes	33 (30%)	32 (32%)	26 (32%)	6 (32%)
No	76 (70%)	68 (68%)	55 (68%)	13 (68%)
Proteinuria, n (%)					0.22b
Yes	8 (7%)	8 (8%)	5 (7%)	3 (16%)
No	60 (55%)	57 (57%)	48 (60%)	9 (47%)
N/A	41 (38%)	35 (35%)	28 (35%)	7 (37%)
Kidney cyst laterality					0.53b
Unilateral	9 (8%)	8 (8%)	3 (4%)	5 (26%)
Bilateral	100 (92%)	92 (92%)	76 (96%)	14 (74%)

US, ultrasound.

^aP = value comparing genetically resolved versus unresolved cases.

^bGeneralized linear mixed effects model.

^cInitial presentation/detection of cystic kidney disease.

^dLinear mixed effects model.

^ePermutation test.

^fComparison of White race versus all others, excluding not reported.

^gSignificant.

Results

Characteristics of the Study Cohort

Between January 2020 and June 2024, all children evaluated at our center for cystic kidney disease were screened for eligibility. Of these, 109 patients from 99 families met inclusion criteria and constituted the study denominator. The cohort showed wide variability, from isolated unilateral cysts to severe bilateral disease progressing to kidney failure, with both syndromic and nonsyndromic cases represented (Supplemental Table 2).

Of the 99 families, genetic testing was possible in 91, which included 100 affected individuals. Clinical genetic testing was performed in 55 patients, while 45 patients underwent research-only genetic testing. Nine patients from eight families did not undergo genetic testing because of family preference and/or loss to follow-up. A definitive genetic diagnosis, defined by the presence of a pathogenic or likely pathogenic variant(s), was determined in 72 families (79%; Figure 1). The median age at diagnosis was 7.6 years (interquartile range, 0–14 years), 53% were female, 91% were of White race, and 48% had a positive family history of kidney cysts (Table 1). Genetically resolved and unresolved patients had similar demographic characteristics; however, a positive family history of cystic kidney disease was significantly more common in the resolved group (44 of 81 [54%] versus 2 of 19 [11%]; P = 0.008). In addition, unilateral kidney cysts tended to be more common in the unresolved group although this did not reach statistical significance (26% versus 4%; P = 0.53; Table 1). There were no significant differences between the two groups in kidney function, hypertension, or degree of proteinuria.

Figure 1.

Flow chart for genetic analysis of the cohort. This flow diagram outlines the steps used to evaluate the clinical and genetic results of the study cohort, which includes 109 patients from 99 families. Genetic testing was performed on 100 patients from 91 families, and pathogenic or likely pathogenic variant(s) were identified in 81 patients from 72 families, resulting in a diagnostic yield of 79% of families. VUS, variant of unknown significance.

Categorization on the basis of initial presentation (n=109) included family screening (n=13, 12%), prenatal detection (n=24, 22%), clinical symptoms (n=34, 31%), and incidental findings (n=38, 35%; Supplemental Figure 1). Most incidental cases were detected during evaluations for unrelated abdominal concerns or musculoskeletal pain (Supplemental Figure 2A). By contrast, symptomatic cases were often diagnosed through targeted abdominal screening or presented with features suggestive of cystic kidney disease, such as hematuria, hypertension, impaired kidney function, polyuria/polydipsia, or cyst-related pain (Supplemental Figure 2B).

Genetic Findings

In the 72 families positive from genetic testing (Figure 2A), monoallelic variants were found in 62 (86%) and biallelic variants in 10 (14%). The most common genes were PKD1 (45%), HNF1B/17q12del (13%), PKD2 (7%), and minor ADPKD-associated genes (11%), including IFT140 (4%), NEK8 (4%), and GANAB (3%). Additional genes included TSC2 (4%), TSC2/PKD1 contiguous gene deletion (TSC2/PKD1; 3%), monoallelic PKHD1 (3%), and ZMYM2 (1%). Recessive or suspected recessive cases involving biallelic variants in PKHD1 (ARPKD) accounted for 8%, while syndromic ciliopathies were responsible for 5% of resolved families, including NPHP1 (4%) and TMEM67 (1%). Gene frequencies among genetically resolved patients (n=81) are shown in Supplemental Figure 3.

Figure 2.

Disease-causing genes and representation in the presentation groups. (A) Disease-causing genes and their frequency in genetically resolved families (n=72). Monoallelic variants were identified in PKD1, PKD2, IFT140, NEK8, GANAB, PKHD1, TSC2, TSC2/PKD1, HNF1B, and ZMYM2 and biallelic variants in PKHD1, NPHP1, and TMEM67 (represented by protruding slices). The number of families for each disease and percentage of the total is shown. (B) Initial presentation of resolved cases and distribution of causative genes across presentation categories. Clinical symptoms accounted for 31% of resolved cases, with causative genes including PKD1, NPHP1, PKHD1 (monoallelic and biallelic), TSC2, GANAB, TSC2/PKD1, HNF1B, NEK8, ZMYM2, and TMEM67. Incidental findings accounted for 31%, with genes including PKD1, PKD2, IFT140, GANAB, biallelic PKHD1, and NEK8. Prenatal detection accounted for 23%, with genes including PKD1, 17q12del, HNF1B, biallelic PKHD1, TSC2/PKD1, and NEK8. Family screening accounted for 15%, with only PKD1 and PKD2 identified.

Genotype–Phenotype Correlations

Genetic diagnostic yield was highest among those identified through family screening and prenatal detection (100% and 83%, respectively), followed by symptomatic presentations (81%) and incidental findings (74%), but the difference between family screening and incidental findings was not statistically significant (P = 0.09; Supplemental Figure 4). The symptomatic group exhibited the greatest genetic heterogeneity with eleven different diseases. By contrast, only PKD1 or PKD2 variants were identified in the family screening subgroup. HNF1B/17q12 deletions were enriched in the prenatal group, while IFT140 was exclusively found in cases diagnosed incidentally (Figure 2B).

Initial eGFR assessments at time of diagnosis (initial presentation/detection of cystic kidney disease) revealed reduced kidney function (eGFR <60 ml/min per 1.73 m²) associated with cases with HNF1B/17q12del, NPHP1, NEK8, biallelic PKHD1, or PKD1. Only one patient with PKD1 exhibited glomerular hyperfiltration (eGFR >140 ml/min per 1.73 m²; Supplemental Figure 5). Seven patients (9%) developed kidney failure by the end of the observation period: biallelic PKHD1 (n=2, ages 3 and 4 years), NEK8 (n=2, ages 6 and 8 years), HNF1B/17q12del (n=2, ages 1 and 14 years), and TMEM67 (n=1, age 16 years). The initial ages at kidney cyst detection are shown in Figure 3. Patients with prenatal presentations (n=24) and those diagnosed before age 1 (n=7) were plotted as age 0. The most common disease-causing genes in prenatal and early infancy included PKD1, HNF1B/17q12del, TSC2/PKD1 contiguous gene deletion biallelic PKHD1, NEK8, TSC2, and NPHP1. Notably, 6 of 27 genetically unresolved cases (22%) presented before age 1, suggesting some early-onset cystic disease may involve unidentified or novel genetic causes or result from nongenetic etiologies, such as environmental factors or developmental anomalies.

Figure 3.

Age at initial presentation of kidney cysts (N=109). The x axis shows the age at first kidney cyst presentation, and the y axis indicates the number of patients. Each stacked bar represents patients presenting at that age, subdivided by diagnostic outcome: resolved with biallelic variant(s), resolved with monoallelic variant(s), unresolved (no definitive genetic diagnosis), or no sample available. Prenatally detected cases (n=24) and <1 year reflect diagnoses after birth but before first birthday (n=7). The inset summarizes the gene findings among intrauterine and <1-year presentations.

Extrarenal manifestations were observed in 28% of genetically resolved patients (23 of 81). Syndromic features were associated with TSC2, TSC2/PKD1 contiguous gene deletion, NPHP1, ZMYM2, TMEM67, and 17q12del (Figure 4, A and B). More than half of patients (46 of 81) experienced additional renal complications beyond the presence of cysts, excluding those directly related to CKD, proteinuria, or albuminuria. These additional complications included hypertension (associated with PKD1, PKD2, NEK8, biallelic PKHD1, TSC2/PKD1, TSC2, TMEM67, and ZMYM2), nephrolithiasis (particularly associated with PKD1, GANAB, and monoallelic PKHD1), recurrent urinary tract infections, gross hematuria, kidney cyst rupture, and polyuria (Supplemental Figure 6).

Figure 4.

Prevalence, spectrum of extrarenal manifestations relative to disease etiology in resolved pediatric cases (N=81). Of 81 patients, 23 (28%) had extrarenal manifestations. Genes without extrarenal findings (PKD2, GANAB, monoallelic PKHD1, IFT140, NEK8 and HNF1B) were excluded. Two sunburst plots were generated: (A) Genotype-first plot: Inner circle shows causal genes, and outer circle shows corresponding phenotypes. Larger slices indicate more patients with that phenotype, while empty slices represent patients without additional manifestations. (B) Phenotype-first plot: Inner circle shows phenotypes, and outer circle shows corresponding causal genes. Slice size reflects the number of patients per phenotype (inner circle) and the genetic contributions to each phenotype (outer circle). PKD1: intracranial vascular anomalies (anterior cerebral artery fenestration, arachnoid cysts, ruptured aneurysm); hepatobiliary disease (congenital hepatic fibrosis, hepatic fibrosis, liver cysts). 17q12 deletion: cardiovascular malformations (aortic root dilatation, atrial septal defect). NPHP1: ocular abnormalities (rod-cone dystrophy, nystagmus, ocular motor apraxia). TSC2/PKD1: CNS lesions (SEGA, subependymal nodules, bilateral cortical tubers); cutaneous lesions (hypopigmented macules, hemangiomas). TSC2: cognitive/developmental abnormalities (autism, developmental delay, intellectual disability); CNS lesions (frontal cortical malformations, subependymal nodules); cutaneous lesions (hypopigmented macules, facial angiofibromas). ZMYM2: cognitive/developmental abnormalities (learning disability, delayed milestones, developmental delay); neuromuscular findings (hypotonia, muscle weakness); abnormal facial features. TMEM67: hepatobiliary disease (liver cirrhosis, chronic ascites, portal HTN, chronic liver disease). Other in the inner circle of Figure 4B represents MODY 5 associated with 17q12 deletion and abnormal facial features associated with ZMYM2. CDH, congenital diaphragmatic hernia; CHF, congenital hepatic fibrosis; CNS, central nervous system; HTN, hypertension; MODY 5, maturity-onset diabetes of the young type 5; PDA, patent ductus arteriosus; SEGA, subependymal giant cell astrocytoma.

For height-adjusted total kidney volume analyses, patients with PKD1 and PKD2 variants were evaluated for the Leuven Imaging Classification Pediatric ADPKD Model¹⁰ (Figure 5A). PKD1 patients exhibited a wide range of kidney sizes, with several showing markedly enlarged kidneys on initial imaging, while PKD2 patients generally demonstrated milder enlargement. Most PKD1 or PKD2 patients showed stable imaging trajectories. Among patients with non-PKD1 and non-PKD2 variants, some genes seemed to be associated with greater kidney enlargement, particularly TSC2/PKD1, biallelic PKHD1, and NEK8 (Figure 5B).

Figure 5.

HtTKV in pediatric patients with PKD1, PKD2 pathogenic/likely pathogenic variants, and other genetic variants, on the basis of CT or MRI. (A) HtTKV in PKD1 and PKD2 patients was calculated using automated kidney segmentation models and classified according to the LIC. To ensure comparability with the US-derived LIC framework, MRI-derived TKV values were converted to 3D US–equivalent TKV using a validated conversion equation before htTKV calculation and classification. Among 39 patients with PKD1, htTKV data were available for 30 individuals (open circles). Several had markedly enlarged kidneys on first imaging. All six patients with PKD2 had available data and generally exhibited milder enlargement (filled diamonds). The connecting lines link multiple data points from the same individual. (B) htTKV in non-PKD1 and non-PKD2 patients. Among 39 patients, htTKV was available for 19 cases. Although no standardized imaging classification exists for these genotypes, certain diseases were associated with greater enlargement, particularly TSC2/PKD1, biallelic PKHD1, and NEK8. The relatively low htTKV observed in one TMEM67 patient reflected the presence of a solitary kidney. CT, computed tomography; htTKV, height-adjusted total kidney volume; LIC, Leuven Imaging Classification; MRI, magnetic resonance imaging; TKV, total kidney volume; US, ultrasound.

Kidney length measurements were obtained from US images for patients without cross-sectional imaging (Supplemental Figure 7, A and B). Several patients with PKD1 variants, biallelic PKHD1, HNF1B, and NEK8 variants, exhibited kidney lengths above age-based percentile thresholds. By contrast, smaller kidney size (less than fifth percentile) was observed in two patients, NPHP1 and 17q12del. One HNF1B patient had just a solitary left kidney below the fifth percentile.

The approximate number of kidney cysts was assessed in 68 patients using contrast-enhanced CT (CCT) and MRI, on the basis of the earliest available imaging, and grouped into five categories (<10, 10–25, 25–50, 51–99, >99 cysts; Supplemental Figure 8). PKD1 and PKD2 variants were observed across the entire range of cyst burdens, highlighting the variability of cystic involvement in the pediatric population. By contrast, patients with minor ADPKD genes, GANAB and IFT140, and monoallelic PKHD1, tended to have fewer cysts, while NEK8 was associated with a high cyst number.

Given concerns regarding ionizing radiation exposure in children, CT imaging was used sparingly in this cohort. Twenty-nine patients underwent CT imaging (CCT or non–contrast-enhanced CT). Most CT examinations were performed before study enrollment and for clinical indications including evaluation of acute abdominal pain, nephrolithiasis, or nonrenal conditions, such as scoliosis or musculoskeletal abnormalities. After enrollment, CT use was limited to selected patients in whom noncontrast CT was clinically indicated for assessment of kidney stone burden and surgical planning.

Representative Cases

To illustrate the clinical and genetic heterogeneity of pediatric cystic kidney disease, we selected five representative cases (Figure 6), demonstrating novel or emerging genetic findings and non-PKD1/PKD2 etiologies. These cases were chosen to highlight scenarios in which broader genetic testing might have direct implications for diagnosis, prognosis, and genetic counseling in pediatric practice. (A-B) case 1: A 10-year-old girl without a family history of kidney cysts presented with chronic back pain, dysuria, and incidental cyst detection on CCT. Imaging at age 16 years showed numerous cortical cysts bilaterally and research genetic testing revealed a large monoallelic IFT140 deletion. (C-D) case 2: A 13-year-old boy presented to the emergency department with gross hematuria after trauma during a football game. Cross-sectional imaging of the abdomen showed bilateral kidney cysts, including hemorrhagic cysts. Research genetic testing revealed a truncating monoallelic GANAB variant. (E-F) case 3: A 2-year-old boy with early-onset CKD and malignant hypertension had severe PKD and required a kidney transplant at age 6 years. Genetic testing identified a nontruncating monoallelic NEK8 variant. (G-H) Case 4: A 10-year-old girl presented to the emergency department with flank pain and gross hematuria. Imaging studies showed nephrolithiasis and bilateral kidney cysts. Clinical genetic testing showed a single PKHD1 pathogenic variant. (I-J) case 5: A 9-year-old adopted boy with neurodevelopmental disorders and systemic features had a ZMYM2 nonsense variant identified. A kidney US showed two midpole kidney cysts. Research genetic testing for cystic kidney diseases revealed no additional pathogenic variants.

Figure 6.

Cases illustrating variable kidney cyst burden and new genetic findings among pediatric patients. Each box represents a family with a distinct PKD causing gene variant. Family number (M#) and the associated gene and transcript and protein changes are shown alongside representative imaging, with age at imaging.

Discussion

In this observational pediatric cohort with one or more kidney cysts, a monogenic cause was common and genetically diverse, identified in 79% of families who underwent genetic testing. Using a phenotype-first approach, comprehensive kidney genetic testing yielded a high diagnostic rate, particularly in children with bilateral cysts and family history, although many without a family history or with incidentally detected cysts also had a positive diagnosis. For clinicians, these findings carry important clinical implications; there is a high likelihood that detected kidney cysts in a pediatric participant will have a monogenic cause. Our results align with and expand on prior work by Obeidova et al. reporting a 71% diagnostic yield with frequent diagnostic reclassification and the study of the CAG Biobank by Watson et al. that reported a diagnostic yield of 80%.^26,28 Bracciamà et al. described a 76% yield in children with CAKUT and cystic kidneys, emphasizing prenatal and early-onset presentations^,.²⁹ By contrast, Kocaaga et al. in a smaller PKD cohort of 28 children, found no PKHD1 variants, highlighting the broader genetic spectrum identified in our study.²⁷ Notably, while these prior studies were retrospective, our study used an observational cohort design with prospective enrollment and predefined inclusion criteria, enabling a clearer assessment of the genetic causes of kidney cysts in children.

Although ARPKD remains a leading cause of severe, early-onset symptomatic cystic kidney disease in infancy, in this group and children presenting later in childhood with milder but clinically apparent disease were more frequently found to have dominant (monoallelic) PKD-related etiologies in this cohort. Given the broad phenotypic range in our cohort, predictably, PKD1 was the most common finding in ADPKD (45%), followed by PKD2. Notably, NEK8, a known cause of childhood kidney failure, was identified in three families, including cases beyond the common p.Arg45Trp variant,^18,19 while no biallelic PKD1 cases were identified.³⁷ Unexpected was the finding that minor ADPKD genes (GANAB, IFT140, and NEK8) represented 11% of the cohort. GANAB and IFT140 are increasingly recognized as milder, often atypical forms of cystic kidney disease in adults with generally favorable outcomes,^23,24,38 but pediatric presentations have so far been rare.^10,39 Therefore, clinicians should be aware that these genes can be significant, sometimes with atypical features of ADPKD, in young children. Also of note, HNF1B or 17q12del was more frequently in our cohort than biallelic PKHD1, indicating the importance of dosage of this transcription factor to cystogenesis.⁴⁰ ZMYM2 is associated with neurodevelopmental-craniofacial syndrome with variable renal and cardiac abnormalities, in which reported renal findings typically resemble CAKUT rather than cystic disease, although renal cysts have been observed in Zmym2-null mouse models.⁴¹ Given the absence of prior human reports of renal cysts and the lack of confirmed de novo status in our case, we have classified this variant as likely pathogenic and it represents a plausible cystic renal phenotype warranting further study.⁴¹ These findings underscore the importance of broad genetic testing, rather than limiting evaluation to classical childhood PKD genes, in pediatrics with kidney cysts. Similar conclusions came from a recent ARPKD phenocopy study by Halawi et al. who highlighted the diversity of detected genes, with implications for prognosis.⁴² This closely parallels several cases in our cohort that were initially suspected to have ARPKD but were genetically reclassified, including PKD1-related ADPKD_VEO, NEK8 cases, and a patient with TMEM67 who presented with renal and hepatobiliary features resembling ARPKD.

When stratifying genetic findings by diagnostic group, diagnostic yield was highest among those identified through family screening and prenatal detection, followed by symptomatic and incidental cases. Disease-associated gene variants also varied by subgroup; among familial cases, only PKD1 and PKD2 were identified. The variable penetrance of the minor ADPKD genes means that the family history often seems negative,²⁴ and de novo events are common for HNF1B/17q12del and NEK8.^18,43 HNF1B/17q12del were enriched in prenatal presentations; and IFT140 was only found in cases with incidentally discovered cysts. Our conclusions reflect other studies showing genotype–phenotype clustering across ADPKD, ARPKD, and syndromic genes and highlight the value of integrating clinical context into interpretation of genetic results.^29,44 The inclusion of high-quality imaging data allowed genotype/imaging correlations, adding another dimension and highlighted imaging features that may identify patients at greater risk of progression. For instance, children with markedly enlarged kidneys with rapid increases in kidney volume from longitudinal observations, warrant closer surveillance and possibly earlier intervention. Our study indicates that integration of imaging biomarkers with genetic data could further enhance prognostication in pediatric cystic kidney disease.

A definitive genetic diagnosis can directly influence clinical management by prompting earlier and more frequent BP monitoring, avoidance of nephrotoxic exposures, surveillance for extrarenal manifestations, and targeted family counseling including cascade testing. In this cohort, genetic findings did not alter immediate medical therapy but informed risk stratification, prognosis, family counseling, and anticipatory guidance regarding disease progression, transplant risk, and potential future therapeutic considerations, particularly for high-risk genotypes, such as NEK8. Recognition of gene-specific extrarenal phenotypes can further guide monitoring, as in HNF1B-associated diabetes and hypomagnesemia and TMEM67-related hepatic and syndromic features. Conversely, the presence of certain extrarenal manifestations may provide diagnostic clues to the underlying genotype, underscoring the reciprocal value of integrating clinical phenotype with genetic testing. For pediatric practices, our findings emphasize the broader genetic spectrum of PKD genes in children and the importance of considering a genetic diagnosis even in the absence of family history. Given the frequent overlap with syndromic features and the prognostic implications of certain genes, broad gene panels or exome/genome sequencing are recommended rather than sequential testing of one or a small number of genes. While routine testing in asymptomatic at-risk children is not currently recommended, early clinical monitoring for manifestations such as hypertension remains critical. Our findings align with the recent Kidney Disease: Improving Global Outcomes recommendations, which suggest genetic testing for children with early-onset or atypical presentations, equivocal imaging findings, or no known family history.⁴⁵ Early identification of a genetic diagnosis may become increasingly important as gene-based therapies evolve, and clinical trials expand in pediatric populations. However, these potential benefits must be weighed against possible harms, including anxiety for families, uncertainty with variants of unknown significance, and social or insurability implications of labeling a child with a genetic disease.⁴⁶

This study has limitations. As a referral-based cohort from a tertiary medical center, selection bias may have influenced the spectrum of phenotypes and genotypes observed. In addition, the study population was predominantly White race (91%), which limits generalizability to other ancestral populations and warrants further evaluation in more diverse cohorts. Genetic testing methods varied per patient, including clinical and research-based panels and exome/genome sequencing backbone panels, potentially contributing to heterogeneity in diagnostic yield. In addition, not all genes and variants classified as pathogenic or likely pathogenic have established long-term prognostic data in pediatric populations. Because children with CAKUT were excluded to focus on cystic phenotypes, some monogenic cases, presumably patients with an ARPKD-like phenotype, may have been missed, although genetic testing is still recommended in such presentations with a distinct gene set. Imaging-based severity assessment was limited because the Leuven Imaging Classification applied to pediatric patients with PKD1 or PKD2 variants remains preliminary and unvalidated for other PKD-related genotypes. In addition, kidney cyst counts are not validated disease severity measures in pediatric PKD and were therefore reported only descriptively. Despite these limitations, this study provides strong evidence that broad genetic testing is clinically valuable in children with kidney cysts. For pediatricians, integrating genetic evaluation into the assessment of cystic kidney findings, particularly when bilateral, early-onset, or associated with extrarenal features, can improve diagnostic accuracy and guide care planning. A comprehensive, phenotype-driven approach may support more precise and timely management for affected children and families.

Broad genetic testing in this carefully selected cohort achieved a high diagnostic yield, identified causes beyond the classical ADPKD and ARPKD genes, and supports early testing to refine diagnoses, prognoses, and clinical management, including in sporadic or isolated cases. However, we highlight the need to balance the benefits of an early genetic diagnosis against potential challenges, such as uncertainty with variants of unknown significance, family anxiety, and insurability concerns.

Supplementary Material

cjasn-21-0984-s001.pdf ^{(1.8MB, pdf)}

cjasn-21-0984-s002.pdf ^{(2.3MB, pdf)}

Disclosures

Disclosure forms, as provided by each author, are available with the online version of the article at http://links.lww.com/CJN/C667.

Author Contributions

Conceptualization: Elif G. Bozkurt, Fouad T. Chebib, Neera K. Dahl, Christian Hanna, Peter C. Harris, David J. Sas, Mohamad Sheikh Najeeb, Whitney S. Thompson, Vicente E. Torres.

Data curation: Tracy A. Baker, Elif G. Bozkurt, Fouad T. Chebib, Carl H. Cramer, Conrad Cruz, Neera K. Dahl, Christian Hanna, Jennifer L. Kemppainen, Timothy L. Kline, Anne M. Kouri, David J. Sas, Mohamad Sheikh Najeeb, Byron H. Smith, Cheryl L. Tran, Hana Yang.

Formal analysis: Elif G. Bozkurt, Conrad Cruz, Adriana V. Gregory, Christian Hanna, Muhammed Khalifa, Timothy L. Kline, Mohamad Sheikh Najeeb, Byron H. Smith, Whitney S. Thompson, Vicente E. Torres, Hana Yang.

Funding acquisition: Christian Hanna, Peter C. Harris.

Investigation: Elif G. Bozkurt, Carl H. Cramer, Conrad Cruz, Christian Hanna, Jennifer L. Kemppainen, Anne M. Kouri, David J. Sas, Vicente E. Torres, Cheryl L. Tran, Hana Yang.

Methodology: Elif G. Bozkurt, Fouad T. Chebib, Neera K. Dahl, Adriana V. Gregory, Christian Hanna, Peter C. Harris, Muhammed Khalifa, Timothy L. Kline, Byron H. Smith, Vicente E. Torres, Hana Yang.

Project administration: Tracy A. Baker.

Resources: Tracy A. Baker, Fouad T. Chebib, Neera K. Dahl, Jennifer L. Kemppainen, Anne M. Kouri, David J. Sas, Vicente E. Torres, Cheryl L. Tran.

Software: Elif G. Bozkurt, Conrad Cruz, Adriana V. Gregory, Jennifer L. Kemppainen, Muhammed Khalifa, Mohamad Sheikh Najeeb, Hana Yang.

Supervision: Fouad T. Chebib, Neera K. Dahl, Adriana V. Gregory, Christian Hanna, Peter C. Harris, Timothy L. Kline, Byron H. Smith, Vicente E. Torres.

Validation: Fouad T. Chebib, Neera K. Dahl, Adriana V. Gregory, Christian Hanna, Peter C. Harris, Timothy L. Kline, Byron H. Smith, Whitney S. Thompson, Vicente E. Torres, Hana Yang.

Visualization: Elif G. Bozkurt, Fouad T. Chebib, Carl H. Cramer, Neera K. Dahl, Adriana V. Gregory, Christian Hanna, Peter C. Harris, Jennifer L. Kemppainen, David J. Sas, Mohamad Sheikh Najeeb, Whitney S. Thompson, Vicente E. Torres, Cheryl L. Tran, Hana Yang.

Writing – original draft: Elif G. Bozkurt, Christian Hanna, Mohamad Sheikh Najeeb, Byron H. Smith.

Writing – review & editing: Tracy A. Baker, Elif G. Bozkurt, Fouad T. Chebib, Carl H. Cramer, Conrad Cruz, Neera K. Dahl, Adriana V. Gregory, Christian Hanna, Peter C. Harris, Jennifer L. Kemppainen, Muhammed Khalifa, Timothy L. Kline, Anne M. Kouri, David J. Sas, Whitney S. Thompson, Vicente E. Torres, Cheryl L. Tran, Hana Yang.

Funding

P.C. Harris: National Institute of Diabetes and Digestive and Kidney Diseases (DK058816, DK059597), Zell Family Foundation. C. Hanna: National Institute of Diabetes and Digestive and Kidney Diseases (DK114786).

Declarative Statements

This study includes clinical experimentation and received Institutional Review Board or Ethics Committee approval. All patients provided written informed consent. This study includes clinical experimentation and complies with the Declaration of Helsinki.

Data Availability Statements

Original data generated for the study will be made available upon reasonable request to the corresponding author. Data Type: Raw Data/Source Data. Reason for Restricted Access: The data supporting the findings of this study are available within the article and Supplemental Data files. Additional information for reproducing the results described in the article is available upon reasonable request and subject to a data use agreement. Variant data will be deposited into ClinVar upon publication. Access is restricted to minimize reidentification risk. To request the data, please contact Christian Hanna or Peter Harris.

Supplemental Material

This article contains the following supplemental material online at http://links.lww.com/CJN/C668.

Supplemental Methods.

Supplemental References.

Supplemental Table 1. Genes identified in the cohort along with the accession numbers used for genetic sequencing.

Supplemental Table 2. Details of the clinical phenotype and genetics in all individuals enrolled into the study.

Supplemental Figure 1. Distribution of initial presentations of the whole cohort.

Supplemental Figure 2. Detailed initial presentations of incidental and symptomatic cases.

Supplemental Figure 3. Disease-causing genes and their frequency in genetically resolved patients.

Supplemental Figure 4. Genetic diagnostic yield of each initial presentation.

Supplemental Figure 5. Initial available creatinine eGFR values of cohort.

Supplemental Figure 6. Prevalence and spectrum of renal manifestations.

Supplemental Figure 7. US-based kidney length measurements.

Supplemental Figure 8. Cyst number classification.