Detecting MUC1 Variants in Patients Clinicopathologically Diagnosed With Having Autosomal Dominant Tubulointerstitial Kidney Disease

Introduction

Autosomal dominant tubulointerstitial kidney disease (ADTKD)-MUC1 is predominantly caused by frameshift mutations owing to a single-base insertion into the variable number tandem repeat (VNTR) region in MUC1. Because of the complexity of the variant hotspot, identification using short-read sequencers (SRSs) is challenging. Although recent studies have revealed the usefulness of long-read sequencers (LRSs), the prevalence of MUC1 variants in patients with clinically suspected ADTKD remains unknown. We aimed to clarify this prevalence and the genetic characteristics and clinical manifestations of ADTKD-MUC1 in a Japanese population using an SRS and an LRS.

Methods

From January 2015 to December 2019, genetic analysis was performed using an SRS in 48 patients with clinically suspected ADTKD. Additional analyses were conducted using an LRS in patients with negative SRS results.

Results

Short-read sequencing results revealed MUC1 variants in 1 patient harboring a cytosine insertion in the second repeat unit of the VNTR region; however, deeper VNTR regions could not be read by the SRS. Therefore, we conducted long-read sequencing analysis of 39 cases and detected MUC1 VNTR variants in 8 patients (in total, 9 patients from unrelated families). With the inclusion of family-affected patients (n ¼ 31), the median age at the development of end-stage kidney disease (ESKD) was 45 years (95% CI: 40–40 years).

Conclusion

In Japan, the detection rate of MUC1 variants in patients with clinically suspected ADTKD was 18.8%. More than 20% of patients with negative SRS results had MUC1 variants detected by an LRS.

Keywords

ADTKD; ADTKD-MUC1; long-read sequencing; MCKD; NGS; SMRT sequencing.

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ADTKD is a group of hereditary kidney diseases characterized by progressive tubulointerstitial fibrosis and tubular atrophy leading to ESKD. ADTKD can be divided into subtypes based on the underlying causative genetic defects, including abnormalities in UMOD, MUC1, REN, HNF1B, and SEC61A1. Given the nonspecificity of the common unifying characteristics of ADTKD, including bland urinary sediment abnormalities and mild to negative proteinuria, ADTKD is presumed to be highly underdiagnosed.

MUC1 is a transmembrane glycoprotein highly expressed in the apical membrane of the thick ascending limb of the loop of Henle, distal convoluted tubules, and collecting ducts. The most common genetic cause of ADTKD-MUC1 is a frameshift variant caused by the insertion of a single base into the VNTR polymorphism of MUC1 (OMIM 158340; 1q22) in exon 2.5 This mutation terminates the synthesis of the MUC1 protein after the VNTR region and creates a new shortened protein (MUC1fs) that lacks a C-terminal domain (Figure 1a). MUC1fs then accumulates in the cytoplasm owing to abnormal intracellular protein transport. The VNTR region exhibits substantial interindividual variation because it is composed of 60-nucleotide units that repeat 20 to 125 times, with each allele having unique repeats (Figure 1b). Therefore, detecting gene variants using SRSs has been challenging owing to the complexity of the variant hotspot.

Previous studies have used alternative methods, including mass spectrometry and probe extension as says, to detect causative variants; however, these methods are technically demanding. Recent studies have found the usefulness of LRSs, which use a single molecule real-time (SMRT) sequencing method to identify MUC1 VNTR variants. Nevertheless, MUC1 VNTR variants have not yet been characterized in the Japanese population. In addition, the prevalence of MUC1 variants in patients with clinically suspected ADTKD remains unknown. Therefore, the aim of this study was to clarify this prevalence, including the genetic characteristics and clinical manifestations, of ADTKD-MUC1 in the Japanese population. Here, we diagnosed 9 patients with ADTKD-MUC1 who had VNTR variants detected using either an SRS (n ¼ 1) or an LRS (n ¼ 8) among 48 clinically suspected ADTKD cases.

Methods

1. Participants

Between January 2015 and December 2019, we performed genetic analysis in 48 patients with clinically suspected ADTKD. The participants had renal dysfunction from unknown causes, with mild to negative urinary abnormalities. Patients were clinically diagnosed with having ADTKD if they had a positive family history of chronic kidney disease and/or hyperuricemia or if pathologic findings on kidney biopsy revealed either medullary cystic kidney disease (the previous term for ADTKD-MUC1 and ADTKD-UMOD), tubulointerstitial nephritis, or chronic interstitial damage. We excluded patients with renal malformations and/or extrarenal symptoms. DNA samples were first analyzed using an SRS. Further investigations were then performed in patients with negative SRS results (n ¼ 39) using an LRS. All samples and clinical information were obtained from Japanese referral hospitals. Genetic analyses were performed after obtaining written informed consent from patients and/or their guardians if the patient was a minor. This study was approved by the Institutional Review Board of the Kobe University School of Medicine (approval number 301).

2. Short-Read Sequencing

Genomic DNA was extracted from peripheral blood leukocytes using the QuickGene Mini 80 system (Wako Pure Chemical Industries, Ltd., Tokyo, Japan). For targeted sequencing using an SRS, samples were prepared using HaloPlex (Agilent Technologies, Santa Clara, CA) according to the manufacturer’s instructions. Paired-end sequencing was performed on the MiSeq platform (Illumina, San Diego, CA). HaloPlex was used for targeted sequencing of 128 genes (version 2, Supplementary Table S1), 172 genes (version 4, Supplementary Table S2), 159 genes (version 5, Supplementary Table S3), 164 genes (version 6, Supplementary Table S4), 181 genes (version 7, Supplementary Table S5), and 183 genes (version 8, Supplementary Table S6) associated with congenital anomalies of the kidney and urinary tract, cystic kidneys, ADTKD, and nephronophthisis. The HaloPlex version used for each patient is found in Supplementary Table S7. Reads were aligned to the reference human genome (GRCh37/Hg19) using SureCall 4.0, which is a desktop application combining algorithms for end-to-end next-generation sequencing data analysis from alignment to categorization of mutations (Agilent Technologies). We excluded called variants with minor allele frequencies >1% in publicly available human variation databases, such as the following: Human Genetic Variation Database (http:// www.genome.med.kyoto-u.ac.jp/SnpDB/), gnomAD (https://gnomad.broadinstitute.org/), and 1000 Genomes Project (1000G) databases (https://www. internationalgenome.org/data). Candidate variants were selected using the computational prediction software, SIFT (https://sift.bii.astar.edu.sg/), PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/), Mutation Taster (http://www.mutationtaster.org/), and CADD (https://cadd.gs.washington.edu/snv), and then classified as pathogenic, likely pathogenic, or uncertain significance, according to the guidelines of the American College of Medical Genetics and Genomics.9

3. Library Preparation and Long-Read Sequencing (SMRT Sequencing)

The amplicons were pooled in equimolar ratios and prepared for SMRTbell sequence libraries using a SMRTbell Express Template Prep Kit 2.0 (Pacific Biosciences, Menlo Park, CA) according to the manufacturer’s instructions. Subsequently, a sequence template was constructed by attaching the sequence primer version 2 and DNA polymerase to the adapters at both ends of the sequence library, and the template was loaded onto an SMRT cell. SMRT sequencing was performed using the PacBio Sequel II System with Sequel II Sequencing Kit 2.0. The sequenced data were analyzed with SMRT Link version 9.0.0, and highly accurate consensus sequences were obtained. Thereafter, sequence clustering was conducted using the analysis tool “pbaa,” which is suitable for analyzing repetitive sequences. Library preparation, sequencing, and bioinformatics analyses of SMRT sequencing were conducted by Takara Bio (Kusatsu, Shiga, Japan). The nucleotide sequence, number of reads, and allele frequency were compiled into an Excel file for each patient (data not revealed). For each identified sequence, we manually reconstructed the sequence every 60 base per line, as described by Kirby et al.5 (Figure 1b). Because of potential PCR errors in the complex VNTR sequence, multiple sequences were detected in each patient. The correct sequences were identified by comparing the LRS results with electropherograms of the amplicons obtained using a bioanalyzer (Supplementary Table S8). In most cases, the top 2 sequences with the highest number of reads were determined to be correct. In some cases, however, sequences with the third or lower most common number of reads were determined to be correct if their sizes were matched to the electrophoresis peaks detected by the bioanalyzer (SC449, SC511, SC534, SC560, SC566, SC593, SC616, and SC639) owing to the inefficiency of PCR amplification of long alleles when the size of the VNTR region of the 2 alleles was significantly different.

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Discussion

To best of our knowledge, this is the first report of a genetic analysis of MUC1 VNTR variants detected using a combination of SRS and LRS in a Japanese cohort. We identified MUC1 VNTR mutations in 9 patients from unrelated families. Furthermore, the detection rate of MUC1 variants among patients with clinically suspected ADTKD was 18.8%.

Owing to the complexity of the variant hotspot, detecting MUC1 VNTR variants by routine genetic analysis using an SRS is challenging, and other methods, such as the snapshot method or mass spectrometry, are typically required. Unfortunately, these methods are technically demanding and are only performed at a few laboratories worldwide.5,6 Wenzel et al.7 conducted SMRT sequencing and confirmed all diagnoses in European participants from 9 families with previously detected MUC1 VNTR variants using the snapshot method. Wang et al.8 also revealed the usefulness of SMRT sequencing for detecting MUC1 VNTR mutations in a large Chinese family. Nevertheless, owing to their study design, these 2 studies did not determine the detection rate of MUC1 VNTR variants in patients with clinically suspected ADTKD. In this study, we clarified that the diagnostic rate of MUC1 variants in patients with clinically suspected ADTKD was 18.8%, which may facilitate more accurate probabilities, especially during genetic counseling.

Data on the prevalence of ADTKD-MUC1 are limited, although previous studies have revealed a prevalence of 0.7 to 4 per million in the United States and Ireland.3,13 A study in England revealed an estimated prevalence of ADTKD-UMOD of 9 per million, suggesting ADTKD-UMOD is the most frequent nonpolycystic kidney disease.14 In our study, 9 patients had MUC1 variants, whereas 6 had UMOD variants, suggesting ADTKD-MUC1 could be 1 of the most common disease subtypes of ADTKD.

Despite the structural complexity of the MUC1 VNTR region, SRS could detect variants in 3 patients, all of whom had the same mutation: a cytosine inserted into 7 consecutive cytosines at the end of the 60-nucleotide unit in the second repeat of the VNTR. It was presumed that variants in the shallow part of the MUC1 VNTR (until the third repeat of the VNTR) would be detectable even though the DNA was fragmented (100– 200 base pair per read) as part of the sample preparation for SRS analysis. Yamamoto et al.15 identified another frameshift mutation located before the MUC1 VNTR region using an SRS (whole exome sequence). This mutation also generates an abnormally truncated protein in the same manner as would the mutation positioned within the VNTR.15 These results suggest that SRS analysis may be useful for detecting variants positioned before or within the shallow region of the VNTR.

In our study, 7 of the 9 patients with MUC1 VNTR variants had the same 60-nucleotide unit sequence harboring the inserted cytosine (Table 2). In previous studies in which long-read sequencing genetic analysis for MUC1 VNTR was performed, the same variant was detected in 9 families in a European cohort7 and a large Chinese family.8 In addition, this mutation has been detected using the snapshot method and was defined as “27dupC.”12 Olinger et al.16 reported that the prevalence of the 27dupC variant was 93.5% in 2 registries of ADTKD in Europe and the United States. By these findings, our data indicated that the 27dupC variant was the most common MUC1 mutation in a Japanese cohort.

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The number of VNTR repeats has been reported to be 20 to 253 ; however, in our study, the VNTR repeat number ranged from 30 to 82, with 80% of the alleles having 30 to 36 repeats. A previous study in Europe reported that the percentage of alleles with 30 to 36 repeats was 39%, which may be underpinned by the ethnic homogeneity of the Japanese population. The present study revealed that the median age at developing ESKD was 45 years (95% CI: 40–50 years) in patients with ADTKD-MUC1, including familial affected patients in a Japanese cohort (9 families, n ¼ 31). A previous study evaluated 147 individuals, including patients with MUC1 mutations and their affected family members, and revealed that the mean age at developing ESKD was 44.9  15.4 years.17 In contrast, recent research using different cohorts indicated that the median time of kidney survival in 104 patients with ADTKD-MUC1 was 36 years (interquartile range: 30–46 years), which may be explained by the exclusion of affected family members who did not undergo genetic analysis.16 In addition, interfamilial and intrafamilial variations have been reported in patients with MUC1 variants,8,17,18 although the existence of modifier genes or other factors remains unknown. In the same study period, we also detected mutations in HNF1B, a causative gene for ADTKD, in 19 patients. Nevertheless, patients with clinically suspected HNF1B mutations were excluded from our study at registration, because most of these patients were clinically distinguishable from those with ADTKD-MUC1 because of morphologic abnormalities in the renal urinary tract system and/or an autosomal-dominant familial history of early onset diabetes and/or hypomagnesemia, and we have previously reported on this patient population.19 Indeed, a Kidney Disease: Improving Global Outcomes consensus report and recent review of ADTKD suggested that the term ADTKD-HNF1B should only be reserved for those cases in which kidney tubulointerstitial fibrosis is the leading manifestation because only a few cases present with tubulointerstitial disease only.1,20 Childhood anemia, mild hypotension, and mild hyperkalemia are thought to be specific features of ADTKD-REN. Nevertheless, a recent international cohort study on clinical characteristics of 111 ADTKD-REN patients reported that approximately 70% of the patients presented to medical institutions for chronic kidney disease or gout.21 According to this report, childhood anemia was present in 75.8% of the patients but its severity was relatively mild; mean hemoglobin levels were 9.6, 10.1, and 10.5 g/dl for ages <10 years, 10 to <15 years, and 15 to <20 years, respectively.21 Although hypotension was not reported in the article, the severity of hyperkalemia was mild and the mean serum potassium level in patients who were not taking fludrocortisone was 4.8 mEq/l.21 Childhood anemia, hypotension, or hyperkalemia may often be overlooked, and they are not always specific to ADRKD-REN; thus, we did not exclude participants with these findings. ADTKD-SEC61A1 is much rare than other ADTKD subtypes, with 6 families reported as of date.22 Patients harboring SEC61A1 mutation present with specific features, such as intrauterine growth retardation, cleft palate, congenital anemia, neutropenia, and immunodeficiency.3,22 Although the clinical manifestations of ADTKD-REN have not been completely clarified owing to the small number of reported cases, patients presenting with these specific features can be clearly distinguished from those with ADTKD-MUC1.

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Recent studies on the molecular and cellular mechanisms of ADTKD-MUC1 have revealed that this condition is a toxic proteinopathy caused by the intracellular accumulation of misfolded MUC1 protein.11,23 Dvela-Levitt et al.24 reported the use of a small molecule, BRD4780, to reroute the secretory pathway to lysosomes, revealing MUC1fs were eliminated in knock-in mice and patient organoids and highlighting the therapeutic potential of BRD4780. Accordingly, an accurate diagnosis of MUC1 variants may be crucial for the development of effective therapeutic agents. Our study had several limitations. First, all of our study participants were Japanese, and our sample size was small owing to the short study duration. Given the retrospective nature of this study, we were also unable to obtain longitudinal clinical information, such as renal prognosis. Second, single-base insertions were observed even in alleles without mutations. Owing to high error rate, it was challenging to achieve high quality assembly to detect single-nucleotide variants or indels using an LRS. It was necessary to combine sequencing technologies to detect all the different types of genetic variations, which increases the cost and complexity of projects. Thus, PacBio devised a new sequencing system, named circular consensus sequencing. Circular consensus sequencing produces high-fidelity reads with 99.8% accuracy and an average length of 13.5 kilobase, which drastically reduces the sequencing error rate.25 This sequencing method was also applied in our study. Hence, considering improvements in the sequencing accuracy, single-base insertions were possibly caused by PCR error. Even though KOD Hot Start DNA polymerase was optimized for the amplification of the most difficult targets,26 other DNA polymerases, the fidelity of which is higher than that of KOD (e.g., Phusion), may contribute in reducing the PCR error rate.27 Recent studies have found an amplification-free protocol for targeted enrichment using the clustered regularly interspaced short palindromic repeats/Cas9 system.28,29 This new method would likely provide better results. Third, we have not validated an alternative method that could facilitate a diagnosis, such as immunostaining of kidney specimens or urine-derived cells. Kirby et al., 5 who first reported the causative mutation for ADTKD-MUC1, performed an immunohistochemical analysis of kidney samples from patients with MUC1 mutations. They reported that, although immunostaining in normal controls resulted in nonspecific staining, patients with MUC1 mutations exhibited a specific intracellular staining pattern in the loop of Henle, distal tubules, and collecting ducts.5 Similar immunostaining analyses of the mutant MUC1 protein have been reported.11,13,18,30 Yamamoto et al.15 detected mutant MUC1 protein in urine exosomes. Although the clinical manifestations of ADTKD-MUC1 are nonspecific, these nongenetic analyses may support the clinical diagnosis. Thus, it is necessary to verify the usefulness of these nongenetic analyses in conjunction with the results of our study. In conclusion, our study reveals that combination genetic analysis with SRS and LRS is useful for detecting MUC1 VNTR variants in a Japanese cohort and that the prevalence of ADTKD-MUC1 may be high in this population. Combination genetic analysis using SRS and LRS is likely to improve the diagnosis rate of ADTKD-MUC1 and may contribute to the development of optimal treatment approaches.

REFERENCES

1. Eckardt KU, Alper SL, Antignac C, et al. Autosomal dominant tubulointerstitial kidney disease: diagnosis, classification, and management—a KDIGO consensus report. Kidney Int. 2015;88:676–683. https://doi.org/10. 1038/ki.2015.28

2. Bolar NA, Golzio C, Zivná M, et al. Heterozygous loss-of-
function SEC61A1 mutations cause autosomal-dominant tubulo-interstitial and glomerulocystic kidney disease with anemia. Am J Hum Genet. 2016;99:174–187. https://doi.org/ 10.1016/j.ajhg.2016.05.028

3. Devuyst O, Olinger E, Weber S, et al. Autosomal dominant tubulointerstitial kidney disease. Nat Rev Dis Primers. 2019;5: 60. https://doi.org/10.1038/s41572-019-0109-9

4. Patton S, Gendler SJ, Spicer AP. The epithelial mucin, MUC1, of milk, mammary gland and other tissues. Biochim Biophys Acta. 1995;1241:407–423. https://doi.org/10.1016/0304-4157 (95)00014-3

5. Kirby A, Gnirke A, Jaffe DB, et al. Mutations causing medullary cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing. Nat Genet. 2013;45: 299–303. https://doi.org/10.1038/ng.2543

6. Ekici AB, Hackenbeck T, Morinière V, et al. Renal fibrosis is the common feature of autosomal dominant tubulointerstitial kidney diseases caused by mutations in mucin 1 or uromodulin. Kidney Int. 2014;86:589–599. https://doi.org/10.1038/ki. 2014.72

7. Wenzel A, Altmueller J, Ekici AB, et al. Single molecule real time sequencing in ADTKD-MUC1 allows complete assembly of the VNTR and exact positioning of causative mutations. Sci Rep. 2018;8:4170. https://doi.org/10.1038/s41598-018-22428-0

8. Wang GQ, Rui HL, Dong HR, et al. SMRT sequencing revealed to be an effective method for ADTKD-MUC1 diagnosis through follow-up analysis of a Chinese family. Sci Rep. 2020;10:8616. https://doi.org/10.1038/s41598-020-65491-2

9. Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–424. https://doi.org/10.1038/ gim.2015.30

10. Kanda Y. Investigation of the freely available easy-to-use software “EZR” for medical statistics. Bone Marrow Transplant. 2013;48:452–458. https://doi.org/10.1038/bmt.2012.244

11. Robinson JT, Thorvaldsdóttir H, Winckler W, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29:24–26. https://doi. org/10.1038/nbt.1754

12. Zivná M, Kidd K, P

ristoupilová A, et al. Noninvasive immunohistochemical diagnosis and novel MUC1 mutations causing autosomal dominant tubulointerstitial kidney disease [published correction appears in J Am Soc Nephrol. 2020;31: 892]. J Am Soc Nephrol. 2018;29:2418–2431. https://doi.org/ 10.1681/ASN.2018020180

13. Cormican S, Connaughton DM, Kennedy C, et al. Autosomal dominant tubulointerstitial kidney disease (ADTKD) in Ireland. Ren Fail. 2019;41:832–841. https://doi.org/10.1080/ 0886022X.2019.1655452

14. Gast C, Marinaki A, Arenas-Hernandez M, et al. Autosomal dominant tubulointerstitial kidney disease—UMOD is the most frequent non polycystic genetic kidney disease. BMC Nephrol. 2018;19:301. https://doi.org/10.1186/s12882-018- 1107-y

15. Yamamoto S, Kaimori J-Y, Yoshimura T, et al. Analysis of an ADTKD family with a novel frameshift mutation in MUC1 reveals characteristic features of mutant MUC1 protein. Nephrol Dial Transplant. 2017;32:2010–2017. https://doi.org/10. 1093/ndt/gfx083

16. Olinger E, Hofmann P, Kidd K, et al. Clinical and genetic spectra of autosomal dominant tubulointerstitial kidney disease due to mutations in UMOD and MUC1. Kidney Int. 2020;98:717–731. https://doi.org/10.1016/j.kint.2020.04.038

17. Bleyer AJ, Kmoch S, Antignac C, et al. Variable clinical presentation of a MUC1 mutation causing medullary cystic kidney disease type 1. Clin J Am Soc Nephrol. 2014;9:527– 535. https://doi.org/10.2215/CJN.06380613

18. Ayasreh N, Bullich G, Miquel R, et al. Autosomal dominant tubulointerstitial kidney disease: clinical presentation of patients with ADTKD-UMOD and ADTKD-MUC1. Am J Kidney Dis. 2018;72:411–418. https://doi.org/10.1053/j.ajkd.2018.03. 019

Eri Okada1,2 , Naoya Morisada1,3 , Tomoko Horinouchi1 , Hideki Fujii4 , Takayuki Tsuji5 , Masayoshi Miura6 , Hideyuki Katori7 , Masashi Kitagawa8 , Kunio Morozumi9 , Takanobu Toriyama10, Yuki Nakamura11, Ryuta Nishikomori12, Sadayuki Nagai1 , Atsushi Kondo1 , Yuya Aoto1 , Shinya Ishiko1 , Rini Rossanti1 , Nana Sakakibara1 , China Nagano1 , Tomohiko Yamamura1 , Shingo Ishimori1 , Joichi Usui2 , Kunihiro Yamagata2 , Kazumoto Iijima13,14, Toshiyuki Imasawa15 and Kandai Nozu1