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Article

Mutation Analysis of Autosomal-Dominant Polycystic Kidney Disease Patients

by
Yasuo Suzuki
1,2,
Kan Katayama
1,*,
Ryosuke Saiki
1,
Yosuke Hirabayashi
1,
Tomohiro Murata
1,
Eiji Ishikawa
3,
Masaaki Ito
1 and
Kaoru Dohi
1
1
Department of Cardiology and Nephrology, Mie University Graduate School of Medicine, Tsu 514-8507, Japan
2
Department of Kidney center, Suzuka Kaisei Hospital, Suzuka 513-8505, Japan
3
Department of Nephrology, Saiseikai Matsusaka General Hospital, Matsusaka 515-0003, Japan
*
Author to whom correspondence should be addressed.
Genes 2023, 14(2), 443; https://doi.org/10.3390/genes14020443
Submission received: 26 December 2022 / Revised: 7 February 2023 / Accepted: 7 February 2023 / Published: 9 February 2023
(This article belongs to the Special Issue Nephrogenetics and Kidney Genomics—the Future Is Now?)
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Abstract

:
Autosomal-dominant polycystic kidney disease (ADPKD) is characterized by bilateral kidney cysts that ultimately lead to end-stage kidney disease. While the major causative genes of ADPKD are PKD1 and PKD2, other genes are also thought to be involved. Fifty ADPKD patients were analyzed by exome sequencing or multiplex ligation-dependent probe amplification (MLPA), followed by long polymerase chain reaction and Sanger sequencing. Variants in PKD1 or PKD2 or GANAB were detected in 35 patients (70%). Exome sequencing identified 24, 7, and 1 variants in PKD1, PKD2, and GANAB, respectively, in 30 patients. MLPA analyses identified large deletions in PKD1 in three patients and PKD2 in two patients. We searched 90 cyst-associated genes in 15 patients who were negative by exome sequencing and MLPA analyses, and identified 17 rare variants. Four of them were considered “likely pathogenic” or “pathogenic” variants according to the American College of Medical Genetics and Genomics guidelines. Of the 11 patients without a family history, four, two, and four variants were found in PKD1, PKD2, and other genes, respectively, while no causative gene was identified in one patient. While the pathogenicity of each variant in these genes should be carefully assessed, a comprehensive genetic analysis may be useful in cases of atypical ADPKD.

1. Introduction

Autosomal-dominant polycystic kidney disease (ADPKD) is characterized by progressive enlargement of bilateral kidney cysts, which ultimately leads to end-stage kidney disease [1]. Extrarenal manifestations include liver cysts, valvular heart disease (VHD), and brain aneurysm [2]. The prevalences of liver cysts, VHD, and brain aneurysm in ADPKD patients are reported to be approximately 83%, 25%, and 10%, respectively [3,4,5].
While the main causative genes of ADPKD are PKD1 and PKD2, GANAB is also known as PKD3 [6]. The genetic analysis of PKD1 is complicated in comparison to PKD2 or GANAB because there are six PKD1 pseudogenes, from PKD1P1 to PKD1P6, as well as PKD1 on chromosome 16 [7]. Long polymerase chain reaction (PCR) was used in previous genetic studies to differentiate true PKD1 from the six PKD1 pseudogenes [8,9,10,11,12,13].
Exome sequencing is a powerful tool to identify causative genes for chronic kidney disease (CKD); 31% of the genetically diagnosed cases are due to PKD1 and PKD2 mutations [14]. Although the causative genes of ADPKD are mainly PKD1 and PKD2, many genes are associated with cystic kidney diseases, including nephronophthisis or autosomal-dominant tubulointerstitial kidney disease (ADTKD). Therefore, exome sequencing is superior to Sanger sequencing for performing a comprehensive analysis. A multiplex ligation-dependent probe amplification (MLPA) analysis of PKD1 or PKD2 is also useful for detecting large deletions or insertions [15,16].
Therefore, we have analyzed 50 ADPKD cases by exome sequencing or multiplex ligation-dependent probe amplification (MLPA), followed by long PCR and Sanger sequencing.

2. Materials and Methods

2.1. Patients

Patients who were being treated in the outpatient ward between March 2020 and June 2022 were enrolled in the present study. The inclusion criteria were as follows: age >20 years and >5 kidney cysts in each kidney according to abdominal computed tomography (CT) or magnetic resonance imaging (MRI). The exclusion criteria were as follows: <20 years of age, ≤5 five kidney cysts in each kidney according to abdominal CT or MRI, or lack of informed consent. After obtaining written informed consent from 50 patients, blood samples were collected. Hypertension was defined as blood pressure >130/80 mmHg or taking an anti-hypertensive drug. Total kidney volume (TKV) was calculated with 3D construction or an ellipsoid equation using the length, width, and depth of the kidneys.

2.2. Exome Sequencing

Genomic DNA was extracted from blood samples of the 50 patients using a Blood Genomic DNA Extraction Mini Kit (FAVORGEN, Vienna, Austria). The DNA concentration was measured with a Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA). The Ion AmpliSeq Exome RDY Library (Thermo Fisher Scientific) was prepared according to the manufacturer’s instructions. The library concentration was examined with a QuantStudio 3D digital PCR system (Thermo Fisher Scientific). Templates were prepared with an Ion PI Hi-Q Chef Kit (Thermo Fisher Scientific) and sequenced with an Ion Proton System (Thermo Fisher Scientific). Variants in the 93 genes (AHI1, ALG8, ANKS6, ARL13B, ARL6, ARMC9, ASS1, B9D1, B9D2, BBIP1, BBS1, BS2, BBS4, BBS5, BBS7, BBS9, BBS10, BBS12, C5orf42, C8orf37, CC2D2A, CCDC28B, CEP41, CEP83, CEP104 CEP120, CEP164, CEP290, CSPP1, DCDC2, DNAJB11, DZIP1L, GANAB, GLIS2, HNF1B, IFT27, IFT43, IFT74, IFT122, IFT140, IFT172, INPP5E, INVS, IQCB1, KIAA0556, KIAA0586, KIF14, KIF7, LRP5, MAPKBP1, MKKS, MKS1, MUC1, NEK8, NOTCH2, NPHP1, NPHP3, NPHP4, OFD1, PDE6D, PIBF1, PKD1, PKD2, PKHD1, PRKCSH, REN, RPGRIP1L, SDCCAG8, SEC61A1, SEC61B, SEC63, SLC41A1, SUFU, TCTN1, TCTN2, TCTN3, TMEM67, TMEM107, TMEM138, TMEM216, TMEM231, TMEM237, TRAF3IP1, TRIM32, TSC2, TTC21B, TTC8, UMOD, WDPCP, WDR19, WDR35, XPNPEP3, and ZNF423) [17,18,19,20,21,22,23,24,25,26,27,28] were examined.

2.3. Multiplex Ligation-Dependent Probe Amplification (MLPA) Analyses

MLPA analyses were performed with a SALSA MLPA kit P351 PKD1 or SALSA MLPA kit P352 PKD1-PKD2 (MRC Holland, Amsterdam, The Netherlands) to detect deletions or duplications in the PKD1 or PKD2 gene, respectively. The results were analyzed with Coffalyser.Net (MRC Holland, Amsterdam, the Netherlands).

2.4. Sanger Sequencing

Long polymerase chain reaction (PCR) was performed with KOD FX Neo (Toyobo, Tokyo, Japan) according to the manufacturer’s instructions. The reaction volume was 25 μL, which included 12.5 μL of 2×PCR buffer for KOD FX Neo, 5 μL of 2 mM dNTP mix, 2 μL (30–50 ng) of template DNA, 0.75 μL of 10 μM forward primer, 0.75 μL of 10 μM reverse primer, 0.5 μL of KOD FX Neo, and 3.5 μL of PCR-grade water. The PCR conditions were as follows: pre-denaturation at 94 °C for 2 min, 5 cycles of denaturation at 98 °C for 10 s and extension at 74 °C for 30 s per kilobase (kb), 5 cycles of denaturation at 98 °C for 10 s and extension at 72 °C for 30 s per kb, 5 cycles of denaturation at 98 °C for 10 s and extension at 70 °C for 30 s per kb, 25 cycles of denaturation at 98 °C for 10 s and extension at 68 °C for 30 s per kb, and extension at 68 °C for 7 min. Long PCR primers and sequencing primers for PKD1 are shown in Table S1 [29]. Normal PCR was performed with HotStarTaq DNA Polymerase (Qiagen, Hilden, Germany). The PCR conditions were as follows: 96 °C for 15 min, 35 cycles of denaturation at 96°C for 45 s, annealing at 57 °C for 45 s, and elongation at 72 °C for 1 min and 72 °C for 15 min. PCR primers for PKD2 and GANAB are shown in Table S2. Sanger sequencing was performed with an Applied Biosystems 3130 Genetic Analyzer (Applied Biosystems, Waltham, MA, USA). The sequence results were analyzed with the BioEdit software program and compared using the Ensembl database.

2.5. Pathogenicity Evaluation

The pathogenicity of the identified variants was evaluated according to the American College of Medical Genetics and Genomics (ACMG) guidelines [30]. Previous reports of each variant were examined in the ClinVar database [31] and Leiden Open Variation Database (LOVD) [32]. The minor allele frequency (MAF) of each variant was searched in the Genome Aggregation Database (gnomAD) and 3.5KJPNv2 database, and rare minor allele frequency (MAF) was defined as <1% [33]. The pathogenicity of variants was assessed in silico with software programs such as Polymorphism Phenotyping v2 (PolyPhen-2) and Sorting Intolerant From Tolerant (SIFT).

3. Results

3.1. Background Data

Fifty patients were analyzed (Table 1). The mean age of the 50 patients was 56 ± 13 years, and 18 patients (36%) were male. A family history of ADPKD was observed in 39 patients (78%), and the number of other affected members is shown in Table 1. Microhematuria was observed in nine patients (18%). The median protein/creatinine ratio was 0.13 (0.07–0.39) g/g·Cr, and the protein/creatinine ratio was >0.5 g/g·Cr in nine patients (18%). The mean estimated glomerular filtration rate (eGFR) was 48.7 ± 27.3 mL/min/1.73 m2. The median TKV was 1266 (877–1716) ml. Twenty-six patients (52%) received tolvaptan at an average dose of 57 ± 31 mg. The Mayo classifications of the patients were as follows: class IA (n = 6), class IB (n = 6), class IC (n = 11), class ID (n = 4), and class II (n = 18) [34]. Five patients were unclassified because four patients were diagnosed with stage 5 CKD and one had an eGFR of >100 mL/min/1.73 m2.

3.2. Mutation Analyses of Patients with Autosomal-Dominant Polycystic Kidney Disease

Exome Sequencing

Exome sequencing was performed in 50 patients, and variants in PKD1, PKD2, or GANAB were detected in 30 patients (60%) (Table 2). Among the 30 patients, there were 24 variants in PKD1, 7 variants in PKD2, and 1 variant in GANAB; patients 1 and 10 had two variants in PKD1. Nineteen of the thirty-two variants were considered to be “likely pathogenic” or “pathogenic” according to the ACMG guidelines (Table S3). Twenty-two of the thirty-two variants were unreported in the ClinVar or LOVD databases and were considered to be novel. To confirm variants in PKD1, long PCR followed by sequencing was performed (except for PKD1 c.12671C>A in patient 1, c.12386T>A in patient 5, and c.11441_11459dup in patient 32, which were confirmed by Sanger sequencing). The 24 variants in PKD1 were classified as follows: missense (n = 10), insertion frameshift (n = 4), deletion (n = 3 (2 were frameshifts)), near splice-site (n = 3), and nonsense (n = 4). Sanger sequencing was performed to confirm variants in PKD2 or GANAB. The seven variants in PKD2 were classified as follows: splice-site (n = 3), deletion frameshift (n = 2), missense (n = 1), and nonsense (n = 1). The variant in GANAB was a missense variant.

3.3. MLPA Analyses

MLPA analyses of PKD1 or PKD2 were performed in 20 patients who did not have any variants in PKD1, PKD2, or GANAB in exome sequencing and in 10 patients who had unreported missense variants (patients 5, 11, 20, 26, 30, 45, and 47) or intronic variants (patients 15, 17, and 18). Five novel large deletions in patients 4, 8, 14, 29, and 44 were identified (Figure 1A). In patients 8 and 44, the deletion of exons 31–34 of PKD1 was observed, and Sanger sequencing identified a 1694-bp deletion between intron 30 and intron 34 in PKD1, leading to the deletion of exons 31–34 of PKD1 (Figure 1B). The deletion of exons 2–6 in PKD1 was observed in patient 29, and Sanger sequencing identified an 8354-bp deletion and an insertion of ATC between intron 1 and exon 7 in PKD1, leading to the deletion of exons 2–7 of PKD1 (Figure 1B). The deletion of all exons of PKD2 was observed in patients 4 and 14, and Sanger sequencing identified a 723424-bp deletion between intron 3 in NUDT9 and intron 1 in ABCG2 in patient 14 (Figure 1B), while a breakpoint could not be confirmed in patient 4.

3.4. The Exome Analysis of Cyst-Associated Genes

Rare variants with MAF <1% in the 90 genes were examined in 15 patients who showed negative results in exome sequencing and MLPA analyses. The results were confirmed by Sanger sequencing and are summarized in Table 3. The PCR primers are shown in Table S4. In all, 19 variants were identified in 13 patients. While 17 were heterozygous, OFD1 c.1215A>C in patient 7 was hemizygous, and PKHD1 c.9629C>G in patient 28 was homozygous. Four of the nineteen variants were considered to be “pathogenic” or “likely pathogenic” according to the ACMG guidelines (Table S5). Seven of the nineteen variants were unreported in the ClinVar or LOVD databases and were considered to be novel. Rare pathogenic variants in other genes were examined in 15 patients (Table S6). There were no rare pathogenic variants in other genes in patients 28, 38, or 39.
Then, rare pathogenic variants in other genes in 11 patients (pt 1, 5, 11, 15, 17, 18, 20, 26, 30, 45, 47) with variants of uncertain significance in PKD1, PKD2, or GANAB were examined in exome sequencing (Table S7). There were no rare pathogenic variants in other genes in patient 26.

3.5. Comorbidity Evaluation

The prevalences of liver cysts, VHD, and brain aneurysm are summarized in Table 4. Liver cysts were observed in 43 patients (86%), among whom 7 had severe liver cysts. Six of the seven patients with severe liver cysts were female. The causative genes of severe liver cysts were five variants in PKD1, one variant in GANAB, and one variant in PKHD1. Hypertension was observed in 40 patients (80%). The median value of brain natriuretic peptide (BNP) was 23.8 [13.1–38.2] pg/mL, and 30 patients (60%) had a value of >18.4 pg/mL. The mean ejection fraction (EF) in an ultrasound cardiography examination was 68.9 ± 6.6%, and 48 patients (96%) had a value of >50%. Mild regurgitation was observed at the aortic valve (n = 7), mitral valve (n = 23), tricuspid valve (n = 28), and pulmonary valve (n = 20). Moderate regurgitation was observed in the aortic valve (n = 5) and tricuspid valve (n = 1). Severe tricuspid valve regurgitation was observed in one patient. The mean E/A and E/e’ ratios were 1.0 ± 0.4 and 9.1 ± 2.9, respectively. Septal e’ < 7 cm/s, septal E/e’ > 15, tricuspid regurgitant velocity (TRV) > 2.8 m/s, and left atrial volume index (LAVI) >34 mL/m2 were observed in 21, 3, 0, and 2 patients, respectively. Patients 19 and 35 fulfilled two of the four criteria for heart failure with preserved ejection fraction (HFpEF), with increased BNP levels [35]. The causative genes of VHD were as follows: PKD1 (n = 19), PKD2 (n = 8), GANAB (n = 1), and other genes (n = 9); the causative gene was unknown in two patients. Brain aneurysms were observed in eight patients (16%), all of whom were female. The causative genes of brain aneurysm were three variants in PKD1, two variants in PKD2, and three variants in other genes. Thirty-seven patients had a low (score 0–3) Predicting Renal Outcome in Polycystic Kidney Disease (PROPKD) score, while thirteen had an intermediate (score 4–6) PROPKD score (Table 4 and Table S8) [36].
Eighteen patients had a type II Mayo classification (Table 1); among these patients eight had “likely pathogenic” or “pathogenic” variants, including four PKD1/PKD2 deletions and four other variants such as DNAJB11, NEK8, PKHD1, or WDR19. Transverse and coronal CT images of the eight patients are shown in Figure 2. The kidney images of patients 8, 14, 29, and 44 were similar (Figure 2A). There were no apparent liver cysts in patients 35 and 46 (Figure 2B). The kidney cysts in patient 35 were mostly seen in the kidney medulla. The kidney cysts and TKV in patient 38 were small. The kidney cysts in patient 41 had calcification. Each of the kidney cysts in patient 46 was relatively small.

3.6. Change in eGFR and TKV without and with Tolvaptan

Because tolvaptan was administered to 26 patients (52%), the change in eGFR and TKV was examined in patients who were followed up for more than one year (Table 5). Sixteen patients were managed without tolvaptan, and twenty-four were managed with tolvaptan. The mean eGFR changes per year in patients managed without and with tolvaptan were −2.6 ± 1.6 and −3.1 ± 2.6 mL/min/1.73 m2, respectively. The mean initial TKV values in patients managed without and with tolvaptan were 1059 ± 615 and 1429 ± 631 mL, respectively. The mean TKV changes per year in patients managed without and with tolvaptan were 3.8 ± 7.0% and 5.0 ± 5.5%, respectively.

4. Discussion

We demonstrated 32 variants in PKD1, PKD2, or GANAB in 30 of 50 patients (60%) in the exome analyses; 19 of these variants (59%) were considered to be “likely pathogenic” or “pathogenic” according to the ACMG guidelines, and 22 variants (69%) were considered to be novel. We also identified five novel large deletions in 5 of 20 patients (25%) in MLPA analyses. Additional exome analyses of 90 cyst-associated genes were conducted for 15 patients who showed negative results in exome sequencing and MLPA analyses; these identified 19 variants, of which 4 (21%) were considered to be “pathogenic” or “likely pathogenic” according to the ACMG guidelines, and 7 variants (37%) were considered to be novel. Overall, “likely pathogenic” or “pathogenic” variants were identified in 28 patients; these were identified by PKD1/PKD2 exome analyses in 19 patients; MLPA analyses in 5 patients; and exome sequencing of 90 genes in 4 patients. Other patients had variants of uncertain significance, which did not indicate a definite diagnosis until further proof was obtained.
Of the 50 patients in the present study, the causative genes were PKD1 in 25 patients (50%), PKD2 in 9 patients (18%), and GANAB in 1 patient (2%). Variants in other cyst-associated genes that were identified in 13 of 50 patients (26%) were variable, including BBS12, CEP164, DNAJB11, GLIS2, IFT140, KIF7, NEK8, OFD1, SLC41A1, TMEM67, WDPCP, WDR19, and ZNF423 in 1 patient, NPHP3 in 2 patients, and PKHD1 in 4 patients. No causative genes were identified in 2 of the 50 patients (4%). While rare pathogenic variants in other genes were examined in 15 patients who showed negative results in exome sequencing or MLPA analyses, their functional roles in ADPKD were undetermined. Rare pathogenic variants in other genes were also examined in 11 patients with variants of uncertain significance in PKD1, PKD2, or GANAB in a similar way, and while the functional roles in ADPKD were undetermined for most of these variants, the roles of CPLANE1 in patient 18 and AHI1 in patient 47, both of which were cilia-associated genes, might be involved in the development of ADPKD to some degree.
Of the 39 patients with a family history of ADPKD, the causative genes were PKD1 in 21 patients, PKD2 in 7 patients, GANAB in 1 patient, other genes in 9 patients, and unknown in 1 patient. On the other hand, the causative genes of the 11 patients without an apparent family history of ADPKD were variable, including 4 variants in PKD1 (missense (n = 2), nonsense (n = 1), large deletion mutation (n = 1)), 2 variants in PKD2 (frameshift deletion (n = 1), splice-site deletion mutation (n = 1)), 1 missense variant in OFD1, 1 missense variant in WDPCP, 1 missense variant in CEP164, 1 nonsense variant in PKHD1, and 1 unknown.
Liver cysts were observed in 43 patients (86%), and 7 of the 43 patients had severe liver cysts. The causative genes of the severe cysts were PKD1 (nonsense (n = 2), large deletion (n = 1), frameshift insertion (n = 1), in-frame deletion (n = 1)), GANAB (missense (n = 1)), and PKHD1 (missense (n = 1)). The causative genes in seven patients (14%) without liver cysts were PKD1 (missense (n = 2), in-frame deletion (n = 1)), OFD1 (missense (n = 1)), PKHD1 (nonsense (n = 1)), WDPCP (missense (n = 1)), and WDR19 (splice-site (n = 1)); genes other than PKD1 or PKD2 or GANAB were observed in four of seven patients (59%).
The high prevalence of hypertension in the present study (80%) might reflect the activation of the renin-angiotensin system or the sympathetic nervous system in ADPKD patients [37]. Thirty patients (60%) had increased serum BNP levels, which was compatible with studies reporting that serum BNP levels were increased in patients with CKD [38,39]. Two patients (4%) fulfilled two of the four criteria for HFpEF with an EF of >50% and an elevated serum BNP level. The causative genes in the two patients were ZNF423 (missense variant) in patient 19 and GLIS2 (missense), PKHD1 (missense), or WDR19 (splice-site) in patient 35. VHD was observed in 39 patients (78%), and the causative genes were PKD1 (missense (n = 6), in-frame deletion (n = 2), frameshift deletion (n = 1), large deletion (n = 3), frameshift insertion (n = 3), near splice-site (n = 3), nonsense (n = 2)), PKD2 (missense (n = 1), frameshift deletion (n = 2), large deletion (n = 1), splice-site (n = 3), nonsense (n = 1)), GANAB (missense (n = 1)), other genes in 10 patients, and unknown in 2 patients. The causative genes in 11 patients (22%) without VHD were PKD1 (missense (n = 3), frameshift insertion (n = 2), nonsense (n = 1)), PKD2 (large deletion), PKHD1 (missense, nonsense), CEP164 (missense), KIF7 (missense), and TMEM67 (missense).
Brain aneurysm was observed in eight patients (16%), and the causative genes were PKD1 (missense (n = 2), nonsense (n = 1)), PKD2 (missense (n = 1), splice-site (n = 1)), ZNF423 (missense), GLIS2 (missense) or PKHD1 (missense) or WDR19 (splice-site), and CEP164 (missense).
Tolvaptan is frequently used in the treatment of ADPKD due to its effectiveness [40]. Patients with a TKV of >750 mL and with a growth rate of >5% are suitable for tolvaptan treatment. The goal of tolvaptan treatment is to slow the progression of kidney cysts, which can slow the progression of CKD in this disease. The present study showed a decline in eGFR of −3.1 mL/min/1.73 m2 per year and a 5.0% TKV change per year, which might be acceptable according to previous research [40]. Careful follow-up of the patients receiving tolvaptan treatment should be continued.
The present study was associated with the following limitations. In the present study, no variants were identified in patient 25 or 39. Patient 25 had stage 5 CKD, and his kidney cysts may have been related to hemodialysis treatment. Patient 39 had a relatively small TKV for her age, and the causative gene may be unknown. While two variants in PKD1 were found in patient 1 and patient 10, respectively, we could not examine whether these acted as in cis or in trans variants, as blood samples could not be obtained from parents or siblings. While DNAJB11 is a known disease-causing gene of ADPKD [25], and kidney cysts can develop in patients who are heterozygous for a pathogenic variant in PKHD1, more evidence is required to determine whether heterozygous NEK8 and WDR19 pathogenic variants can mimic the ADPKD phenotype. Rare pathogenic variants in other genes were not validated in Sanger sequencing. We did not examine variants in the introns of 93 genes in the present study.

5. Conclusions

While the pathogenicity of each variant in cyst-associated genes should be carefully assessed, a comprehensive genetic analysis may be useful for atypical ADPKD cases.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes14020443/s1, Table S1: PKD1 primers; Table S2: PKD2 and GANAB primers; Table S3: Evaluation of the pathogenicity of the 29 variants in PKD1, PKD2, and GANAB; Table S4: Other primers; Table S5: Evaluation of the pathogenicity of the 17 variants in 90 genes; Table S6: Rare pathogenic variants in other genes in 15 patients after evaluation of 90 cyst-associated genes; Table S7: Rare pathogenic variants in other genes in 11 patients with variants of uncertain significance in PKD1, PKD2, or GANAB; Table S8: PROPKD score.

Author Contributions

Conceptualization of the study: Y.S. and K.K.; data curation and analysis: Y.S., K.K., R.S., Y.H., T.M. and E.I.; writing—original draft, Y.S. and K.K.; writing—critical review and editing, R.S., Y.H., T.M., E.I., M.I. and K.D.; supervision: K.K., M.I. and K.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Board of Mie University Graduate School of Medicine (IRB approval number H2019-113) and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed Consent Statement

Informed consent was obtained from all individual participants included in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to ethical restrictions.

Acknowledgments

We thank Yuko Koizumi for her excellent technical help.

Conflicts of Interest

Masaaki Ito received honoraria for lectures from Daiichi Sankyo Co., Ltd. Kaoru Dohi received honoraria for lectures from Otsuka Pharmaceutical Co., Ltd., Novartis Pharma K.K., Daiichi Sankyo Co., Ltd., Nippon Boehringer Ingelheim Co., Ltd., Bayer Yakuhin, Ltd., Kowa Co., Ltd., and AstraZeneca K.K. Kaoru Dohi received research funding from Shinogi & Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Takeda Pharmaceutical Company, Novartis Pharma K.K., Otsuka Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Ono Pharmaceutical Co., Ltd., Kowa Co., Ltd., and Abbott Medical Japan LLC. All other authors declare no competing interests in association with the present study.

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Genes 14 00443 g001 550
Figure 1. MLPA analyses. (A) Five large deletions in patients 4, 8, 14, 29, and 44 were identified. (B) Sanger sequencing identified deletions of exons 31–34 of PKD1 in patients 8 and 44, a deletion of Iexons 2–7 of PKD1 in patient 29, and a deletion between intron 3 in NUDT9 and intron 1 in ABCG2 in patient 14, while a breakpoint could not be confirmed in patient 4. Pt, patient.
Figure 1. MLPA analyses. (A) Five large deletions in patients 4, 8, 14, 29, and 44 were identified. (B) Sanger sequencing identified deletions of exons 31–34 of PKD1 in patients 8 and 44, a deletion of Iexons 2–7 of PKD1 in patient 29, and a deletion between intron 3 in NUDT9 and intron 1 in ABCG2 in patient 14, while a breakpoint could not be confirmed in patient 4. Pt, patient.
Genes 14 00443 g001
Genes 14 00443 g002 550
Figure 2. Transverse and coronal CT images of eight patients with “likely pathogenic” or “pathogenic” variants and Mayo type II classifications. (A) The kidney images in patients 8, 14, 29, and 44 were similar. (B) The kidney cysts in patient 35 were mostly seen in the kidney medulla, without apparent liver cysts. The kidney cysts and TKV in patient 38 were small. The kidney cysts in patient 41 had calcification. Each of the kidney cysts in patient 46 was relatively small without apparent liver cysts.
Figure 2. Transverse and coronal CT images of eight patients with “likely pathogenic” or “pathogenic” variants and Mayo type II classifications. (A) The kidney images in patients 8, 14, 29, and 44 were similar. (B) The kidney cysts in patient 35 were mostly seen in the kidney medulla, without apparent liver cysts. The kidney cysts and TKV in patient 38 were small. The kidney cysts in patient 41 had calcification. Each of the kidney cysts in patient 46 was relatively small without apparent liver cysts.
Genes 14 00443 g002
Table
Table 1. Clinical characteristics of the study subjects.
Table 1. Clinical characteristics of the study subjects.
PtAgeSexFamily HistoryMicrohematuriaProteinuria (g/g·Cr)eGFR (mL/min/1.73m2)TKV (mL)Tolvaptan (mg)Mayo (Class)
Pt 135M100.0886.998690IC
Pt 265F200.0928.297360IB
Pt 384M1005.213840NA
Pt 461F200315240NA
Pt 547F31+0.1358.6106430IC
Pt 670M02+0.7413.425490NA
Pt 778M01+0.0959.58590II
Pt 851F200.6720.287445II
Pt 954F200.3541.92425120IC
Pt 1053M200.2545.1290360ID
Pt 1160F22+0.4746.8134615IB
Pt 1236F200.1789.613630ID
Pt 1351M200.0435.623320II
Pt 1452M200.8431.81961120II
Pt 1545F200.4823.2207975IC
Pt 1660F200.3927.8175245IC
Pt 1770F100.1318.15447.5IA
Pt 1843F10068.7116860IC
Pt 1979F1(+/−)0.54565030II
Pt 2059M000.0855.9160830IC
Pt 2164F400.0725130945IB
Pt 2251F10040.2155975IC
Pt 2347M001.6318.1272722.5ID
Pt 2448F01+0.1754.3384145ID
Pt 2571M0NANA829080NA
Pt 2675F400.14376920IA
Pt 2755M000.1245.3160860IC
Pt 2858F10070.45860II
Pt 2938M00074.51544120II
Pt 3032F200.12144.52690NA
Pt 3141F200.2598.93960IA
Pt 3239F200.3946.188660IC
Pt 3358F1(+/−)0.2266.45180IA
Pt 3448F200.0579.23120IA
Pt 3569F10078.7208960II
Pt 3654F20071.93770IA
Pt 3777M02+1.4922.214080II
Pt 3870F2(+/−)0.05474020II
Pt 3956F300.0940.76780II
Pt 4058M100.5822.9160360IC
Pt 4167F101.462.49080II
Pt 4254M100.9821.1111037.5IB
Pt 4351M100.1164.920880II
Pt 4435F100.0990.496515II
Pt 4579F100.0643.810940IB
Pt 4648M000.3137.189160II
Pt 4753M200.0762.112220IB
Pt 4865F100.1849.814410II
Pt 4969F300.1844.517680II
Pt 5045F000.2250.788560II
eGFR, estimated glomerular filtration rate; F, female; M, male; NA, not available; Pt, patient; TKV, total kidney volume.
Table
Table 2. Summary of exome sequencing.
Table 2. Summary of exome sequencing.
PtGeneVariantsAmino Acid ChangeACMGClinVarLOVDdbSNPgnomAD3.5KJPNv2PolyPhen-2 (Score)SIFT (Score)
Pt 1PKD1c.7302_7313delGCGGGGCGTGCTp.Gly2436_Arg2439delUSUnreportedUnreportedNANANANANA
Pt 1PKD1c.12671C>Ap.Thr4224AsnUSUnreportedUnreportedrs2006858830.00002170.000180.725APF (0.03)
Pt 2PKD2c.965G>Ap.Arg322GlnLPLPP2, LP1rs1458775970.000003982NA1APF (0.00)
Pt 3PKD1c.1831C>Tp.Arg611TrpLPP1, LP2, US3P1, LP1rs1555458413NANA1APF (0.00)
Pt 5PKD1c.12386T>Ap.Met4129LysUSUnreportedUnreportedrs7506299500.0000319NA1APF (0.00)
Pt 6PKD2c.362delGp.Gly121AlafsTer11PUnreportedUnreportedNANANANANA
Pt 9PKD1c.11459_11460insATGACAGCGGGGGCTACGTp.Gln3821TerPUnreportedUnreportedNANANANANA
Pt 10PKD1c.9559_9561delGACp.Asp3187delLPUnreportedLPNANANANANA
Pt 10PKD1c.7825A>Gp.Ile2609ValUSUnreportedUnreportedrs7677097560.000025820.001070.566T (0.15)
Pt 11PKD1c.6290G>Tp.Gly2097ValUSUnreportedUnreportedNANANA1APF (0.00)
Pt 12PKD1c.6561G>Ap.Trp2187TerPUnreportedUnreportedNANANANANA
Pt 15PKD1c.3161+5G>Ap.?USUSUnreportedNANANANANA
Pt 16PKD1c.10859_10860insAp.Arg3621AlafsTer6PUnreportedUnreportedNANANANANA
Pt 17PKD1c.10822-3C>Gp.?USUnreportedUnreportedNANANANANA
Pt 18PKD1c.3161+5G>Ap.?USUSUnreportedNANANANANA
Pt 20PKD1c.12734G>Cp.Ser4245ThrUSUnreportedUnreportedNANANA0.47APF (0.00)
Pt 21PKD1c.4796_4797insAp.Tyr1599TerPUnreportedUnreportedNANANANANA
Pt 22PKD1c.4306C>Tp.Arg1436TerPPPrs1567200516NANANANA
Pt 23PKD1c.5830G>Tp.Gly1944TerPPUnreportedrs2000014710.000157NANANA
Pt 24PKD1c.6643C>Tp.Arg2215TrpLPP1, LP2, US1LPrs7527937570.000008359NA0.999APF (0.02)
Pt 26GANABc.203A>Gp.Gln68ArgUSUnreportedUnreportedrs1500625070.0002510.004710.001T (0.23)
Pt 27PKD2c.709+1_709+4delGTAAp.?PUnreportedUnreportedNANANANANA
Pt 30PKD1c.6421G>Tp.Val2141PheUSUnreportedUnreportedNANANA1APF (0.01)
Pt 31PKD1c.6882_6883delCAp.Ser2295PhefsTer124PUnreportedPNANANANANA
Pt 32PKD1c.11441_11459dupp.Gln3821TerPUnreportedUnreportedNANANANANA
Pt 33PKD2c.2224C>Tp.Arg742TerPPPrs1219180400.00003185NANANA
Pt 34PKD2c.1549-1G>Cp.?PUnreportedUnreportedrs1720121027NANANANA
Pt 36PKD2c.1717-1G>Cp.?PUnreportedUnreportedNANANANANA
Pt 40PKD2c.2195_2205delGAGGAGGCAAGp.Gly732ValfsTer4PUnreportedUnreportedNANANANANA
Pt 42PKD1c.4796_4797insAp.Tyr1599TerPUnreportedUnreportedNANANANANA
Pt 45PKD1c.7825A>Gp.Ile2609ValUSUnreportedUnreportedrs7677097560.000025820.001070.566T (0.15)
Pt 47PKD1c.9806G>Ap.Arg3269GlnUSUnreportedUnreportedrs5504676900.000005862NA1APF (0.03)
ACMG, American College of Medical Genetics and Genomics; APF, affect protein function; dbSNP, Single Nucleotide Polymorphism Database; del, deletion; gnomAD, Genome Aggregation Database; LOVD, Leiden Open Variation Database; LP, likely pathogenic; NA, not available; P, pathogenic; PolyPhen-2, Polymorphism Phenotyping v2; Pt, patient; SIFT, Sorting Intolerant From Tolerant; T, tolerated; US, uncertain significance.
Table
Table 3. Exome analyses of cyst-associated genes.
Table 3. Exome analyses of cyst-associated genes.
PtGeneVariantsAmino Acid ChangeACMGClinVarLOVDdbSNPgnomAD3.5KJPNv2PolyPhen-2 (Score)SIFT (Score)
Pt 7BBS12c.775A>Gp.Thr259AlaUSUSUnreportedrs7465650720.000019890.00370T (0.61)
Pt 7OFD1c.1215A>Cp.Glu405AspUSUnreportedUnreportedrs7721291290.000005478NA0.675NA
Pt 13IFT140c.2317C>Tp.Arg773TrpUSUnreportedUSrs2022363030.000023860.000180.999NA
Pt 13NPHP3c.2986G>Ap.Val996MetUSUSUSrs1508675340.0001310.008410.537T (0.52)
Pt 19ZNF423c.955G>Ap.Ala319ThrUSUSUSrs1999197030.00009351NA0.981T (0.19)
Pt 28PKHD1c.9629C>Gp.Ser3210CysUSConflictingUnreportedrs1410812950.00017350.064621T (0.11)
Pt 28TMEM67c.1243G>Ap.Val415MetUSUnreportedUnreportedNANANA0.986NA
Pt 35GLIS2c.1403C>Tp.Thr468MetUSConflictingUnreportedrs1382852540.00011370.017490.999APF (0.00)
Pt 35PKHD1c.1481G>Ap.Arg494GlnUSUnreportedUnreportedrs1510704710.00005661NA0.996APF (0.05)
Pt 35WDR19c.3262-2A>Gp.?PLPUnreportedrs75329115100.00036NANA
Pt 37WDPCPc.151C>Tp.His51TyrUSUSUnreportedrs7796899370.000020110.00280.949NA
Pt 38DNAJB11c.672delTp.Phe224LeufsTer39LPUnreportedUnreportedNANANANANA
Pt 41NEK8c.1864delGp.Asp622MetfsTer5LPUnreportedUnreportedNANANANANA
Pt 43NPHP3c.2986G>Ap.Val996MetUSUSUSrs1508675340.0001310.008410.537T (0.52)
Pt 43SLC41A1c.509A>Gp.Lys170ArgUSUnreportedUnreportedNANANA0.014T (0.80)
Pt 46PKHD1c.865C>Tp.Gln289TerPPUnreportedNANANANANA
Pt 48PKHD1c.9629C>Gp.Ser3210CysUSConflictingUnreportedrs1410812950.00017350.064621T (0.11)
Pt 49KIF7c.2476C>Tp.Arg826TrpUSUSUnreportedrs1397112380.00010310.000841APF (0.00)
Pt 50CEP164c.3557T>Cp.Leu1186ProUSUnreportedUnreportedNANANA1NA
ACMG, American College of Medical Genetics and Genomics; APF, affect protein function; dbSNP, Single Nucleotide Polymorphism Database; del, deletion; gnomAD, Genome Aggregation Database; LOVD, Leiden Open Variation Database; LP, likely pathogenic; NA, not available; P, pathogenic; PolyPhen-2, Polymorphism Phenotyping v2; Pt, patient; SIFT, Sorting Intolerant From Tolerant; T, tolerated; US, uncertain significance.
Table
Table 4. Comorbidity evaluation.
Table 4. Comorbidity evaluation.
PtHTBNP (pg/mL)EF (%)ARMRTRPRSeptal e’ (cm/s)Septal E/e’TRV (m/s)LAVI (mL/m2)Liver CystsBrain MRAPROPKD (Score)
Pt 1(+)5.862(−)(−)Mi(−)6.9 7.8 2.2 NA(−)normal5
Pt 2(+)6.169TTTMi5.7 9.6 2.0 60(+)rt. VA AN0
Pt 3(+)44051(−)T(−)(−)5.1 12.4 NANA(+)normal3
Pt 4(+)48.465(−)TT(−)4.8 12.0 2.0 NA(+)normal0
Pt 5(+)2165(−)TTT6.9 8.4 0.7 21.0 (+)lt. ICA AN2
Pt 6(+)12070.1(−)(−)(−)Mi7.7 7.9 NANA(+)normal1
Pt 7(+)42.175.6(−)MiMiMiNANANANA(−)normal1
Pt 8(+)27.770.8MoMiMiMi6.6 8.7 NANA(++)normal4
Pt 9(+)7.368(−)TTT5.4 8.7 1.4 23(+)lt. MCA occlusion4
Pt 10(+)15.267.5(−)(−)MiMi6.6 8.4 NANA(++)normal3
Pt 11(+)14.376.5(−)MiMi(−)6.2 7.9 NANA(+)lt. ICA AN2
Pt 12(+)669(−)TTT4.3 7.6 NA16.2 (++)lt. MCA AN6
Pt 13(−)23.869.7(−)(−)MiT8.2 7.4 NA27.2 (+)normal1
Pt 14(+)27.670.1(−)MiMiMi7.7 9.5 NANA(+)rt. A1 perforator dilatation1
Pt 15(+)52.172.2(−)MiMi(−)12.1 5.3 NANA(+)lt. IC−PC dilatation2
Pt 16(+)20.264.6(−)MiMiMi6.2 10.1 NANA(+)normal4
Pt 17(+)84.162.1(−)MiMi(−)8.6 7.5 NANA(+)normal2
Pt 18(+)2070.4(−)MiMiMi7.1 6.9 NANA(+)lt. ICA dilatation2
Pt 19(+)105.663.8MiMiMiMi5.2 19.3 NANA(+)lt. MCA AN0
Pt 20(+)10.378.5(−)(−)(−)(−)7.1 9.4 NANA(+)normal3
Pt 21(+)26.575.6(−)(−)MiMi9.1 4.8 NANA(+)normal4
Pt 22(+)23.279.4(−)MiMiMi9.7 9.7 NANA(++)normal4
Pt 23(+)2225.559.4Mo(−)(−)MiNANANANA(+)normal5
Pt 24(+)20.766.7Mo(−)(−)Mi7.5 9.0 NANA(+)normal2
Pt 25(+)3760.5MoT(−)(−)6.8 5.5 NANA(+)normal1
Pt 26(+)133.673.1MiMiMiMi5.2 9.3 NANA(++)normal0
Pt 27(+)11.172.8MiMiMoMi8.6 8.6 NANA(+)normal1
Pt 28(−)6.374.9(−)(−)(−)(−)8.1 6.2 NANA(+)lt. M1 stenosis0
Pt 29(+)6.273.2(−)MiMi(−)5.4 8.1 NANA(+)normal5
Pt 30(−)39.376.8(−)(−)Mi(−)14.7 6.5 2.1 NA(−)normal2
Pt 31(−)33.969.9(−)MiMiMi9.9 8.9 2.0 NA(+)normal4
Pt 32(−)15.362.4(−)(−)(−)(−)7.8 6.6 NANA(++)normal4
Pt 33(−)4368.9MiTTT8.0 7.0 NA27.2 (+)normal0
Pt 34(−)12.277TMiT(−)9.5 6.2 NA19(+)Acom AN0
Pt 35(+)113.665MiMiTT3.5 15.5 NA32(−)rt. MCA AN0
Pt 36(−)35.473TMiMi(−)7.9 9.9 2.4 45(+)normal0
Pt 37(+)36.973T(−)MiT5.2 9.6 2.4 13(−)normal1
Pt 38(+)NA76.8Mi(−)(−)(−)NANANANA(+)Acom perforator dilatation0
Pt 39(+)32.965.1(−)(−)Mi(−)8.5 8.5 2.2 NA(+)normal0
Pt 40(+)1170TTMi(−)6.4 9.5 2.2 24(+)normal1
Pt 41(+)13.977.6(−)MiMiMi8.210.92.3NA(+)normal0
Pt 42(+)24.250(−)MiMi(−)8.8 6.5 NANA(+)normal5
Pt 43(+)5.462.2(−)MiMi(−)6.3 13.1 NANA(+)normal1
Pt 44(−)5.872.5MiMiMi(−)9.9 6.5 1.6 NA(+)normal4
Pt 45(−)5378.1MoMiSMi7.1 13.3 NANA(−)lt. PCA stenosis, rt. M1 stenosis0
Pt 46(+)1769TTTT7.3 15.9 2.3 27(−)normal1
Pt 47(+)NA73.5(−)(−)MiMiNANANANA(+)normal3
Pt 48(+)24.471(−)MiMiMi6.7 6.9 1.9 NA(++)normal0
Pt 49(+)3260.5(−)(−)T(−)4.8 10.8 NANA(+)normal0
Pt 50(+)23.763(−)(−)(−)(−)12.3 7.7 NANA(+)rt. MCA AN0
Acom, anterior communicating artery; AN, aneurysm; AR, aortic valve regurgitation, BNP, brain natriuretic peptide; EF, ejection fraction; HT, hypertension; ICA, internal carotid artery; IC-PC, internal carotid-posterior communicating artery; LAVI, left atrial volume index; lt, left; MCA, middle cerebral artery; Mi, mild; Mo, moderate; MR, mitral valve regurgitation; MRA, magnetic resonance angiography; NA, not available; PCA, posterior cerebral artery; PR, pulmonic valve regurgitation; PROPKD, Predicting Renal Outcome in Polycystic Kidney Disease; rt, right; S, severe; T, trivial; TR, tricuspid valve regurgitation; TRV, tricuspid regurgitant velocity; VA, vertebral artery.
Table
Table 5. Changes in eGFR and TKV in patients managed without and with tolvaptan.
Table 5. Changes in eGFR and TKV in patients managed without and with tolvaptan.
PtTolvaptaneGFR Change per Year (mL/min/1.73 m2)Initial TKVTKV Change per Year (%)
Pt 6(−)−4.3 21923.8
Pt 7(−)−0.1 8101.9
Pt 12(−)−6.0 133125.6
Pt 13(−)−1.0 21301.7
Pt 19(−)−2.1 526−0.3
Pt 26(−)−1.6 7133.1
Pt 28(−)−1.4 601−0.6
Pt 31(−)−3.9 396−2.3
Pt 37(−)−0.7 1576−2.2
Pt 38(−)−2.5 4152.2
Pt 39(−)−2.2 2932.5
Pt 41(−)−3.6 8112.8
Pt 43(−)−2.8 169512.7
Pt 45(−)−4.4 8678.5
Pt 47(−)−2.6 10043.4
Pt 48(−)−2.0 1580−1.5
Pt 1(+)−9.9 9869.1
Pt 5(+)2.4 1064−4.9
Pt 8(+)−2.0 8013.8
Pt 9(+)−2.4 20239.9
Pt 10(+)−2.4 26907.4
Pt 11(+)−1.9 13202.0
Pt 14(+)−3.1 107817.6
Pt 15(+)−4.7 168713.0
Pt 16(+)−2.8 18373.0
Pt 17(+)−2.7 1010−2.6
Pt 18(+)−4.6 10465.6
Pt 20(+)−2.0 16112.6
Pt 21(+)−1.6 13441.0
Pt 22(+)−3.5 14293.6
Pt 23(+)−3.1 24879.1
Pt 24(+)−4.3 32197.4
Pt 27(+)−0.4 13513.5
Pt 29(+)−5.0 13409.5
Pt 32(+)−3.4 8484.2
Pt 35(+)−1.6 14126.0
Pt 42(+)−9.3 111011.8
Pt 44(+)0.2 7003.2
Pt 46(+)−3.9 891−2.5
Pt 50(+)−2.4 1021−4.0
eGFR, estimated glomerular filtration rate; Pt, patient; TKV, total kidney volume.
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Suzuki, Y.; Katayama, K.; Saiki, R.; Hirabayashi, Y.; Murata, T.; Ishikawa, E.; Ito, M.; Dohi, K. Mutation Analysis of Autosomal-Dominant Polycystic Kidney Disease Patients. Genes 2023, 14, 443. https://doi.org/10.3390/genes14020443

AMA Style

Suzuki Y, Katayama K, Saiki R, Hirabayashi Y, Murata T, Ishikawa E, Ito M, Dohi K. Mutation Analysis of Autosomal-Dominant Polycystic Kidney Disease Patients. Genes. 2023; 14(2):443. https://doi.org/10.3390/genes14020443

Chicago/Turabian Style

Suzuki, Yasuo, Kan Katayama, Ryosuke Saiki, Yosuke Hirabayashi, Tomohiro Murata, Eiji Ishikawa, Masaaki Ito, and Kaoru Dohi. 2023. "Mutation Analysis of Autosomal-Dominant Polycystic Kidney Disease Patients" Genes 14, no. 2: 443. https://doi.org/10.3390/genes14020443

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