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Systematic Screening of Autosomal Dominant Tubulointerstitial Kidney Disease–MUC1 27dupC Pathogenic Variant through Exome Sequencing

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Key Points MUC1 is associated with autosomal dominant tubulointerstitial kidney disease, a genetic disorder progressing to kidney failure.Variations in this gene are not easily diagnosed by conventional methods due to the MUC1 architecture, which contains a variable number of tandem repeats.Using dedicated bioinformatics tools, we systematically detected the presence of 27dupC most common MUC1 pathogenic variant from exome sequencing data. Background The MUC1 gene is associated with autosomal dominant tubulointerstitial kidney disease (ADTKD), leading to CKD. Current methods of sequencing, such as exome sequencing, rarely detect MUC1 pathogenic variants because of the variable number of tandem repeats (VNTR) in MUC1 exon2. We demonstrated that combining fast read filtering with a sensitive VNTR genotyping strategy enables systematic screening of 27dupC pathogenic MUC1 variant from exome data. Methods We initially validated our bioinformatics pipeline in a proof-of-concept cohort incorporating exome data from 33 participants with a known MUC1 pathogenic variant identified by Snapshot PCR and confirmed by 54 MUC1-negative individuals for negative control. We then retrospectively analyzed exome sequencing data from January 2019 to October 2023 from 3512 adult participants with nephropathy of unknown origin. Finally, we prospectively validated our pipeline in 825 additional participants enrolled from November 2023. Results SharkVNTyper accurately identified MUC1 variants in 32 of 33 participants and excluded its presence in all the 54 negative controls in the proof-of-concept cohort (sensitivity of 97%, specificity of 100%). Integration of the Shark tool with VNTyper significantly reduced running time from 6–12 hours to 5–10 minutes per sample, allowing both retrospective and prospective analyses. In the retrospective cohort, SharkVNTyper identified 23 additional positive participants who were not suspected clinically and had been missed in the initial exome analysis; 18 of these participants were confirmed as carrying the MUC1 27dupC mutation by low-throughput Snapshot PCR. In the prospective cohort of 825 participants with CKD, systematic screening discovered 13 positive participants, with 12 confirmed by PCR. Overall, of 63 participants (1.4% of 4653) with molecularly confirmed ADTKD-MUC1, comprehensive diagnoses and descriptions of the disease were available for 24 participants. The median age of kidney failure was 50 years, 38% exhibited bilateral multiple kidney cysts, 8% had early-onset gout, and 58% had arterial hypertension. Conclusions SharkVNTyper enabled the analysis of highly repeated regions, such as the MUC1 VNTR, and facilitated the systematic screening of ADTKD-MUC1 from exome data, fostering 27dupC variation identification. Podcast This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/JASN/2024_11_15_KTS_November2024.mp3
Title: Systematic Screening of Autosomal Dominant Tubulointerstitial Kidney Disease–MUC1 27dupC Pathogenic Variant through Exome Sequencing
Description:
Key Points MUC1 is associated with autosomal dominant tubulointerstitial kidney disease, a genetic disorder progressing to kidney failure.
Variations in this gene are not easily diagnosed by conventional methods due to the MUC1 architecture, which contains a variable number of tandem repeats.
Using dedicated bioinformatics tools, we systematically detected the presence of 27dupC most common MUC1 pathogenic variant from exome sequencing data.
Background The MUC1 gene is associated with autosomal dominant tubulointerstitial kidney disease (ADTKD), leading to CKD.
Current methods of sequencing, such as exome sequencing, rarely detect MUC1 pathogenic variants because of the variable number of tandem repeats (VNTR) in MUC1 exon2.
We demonstrated that combining fast read filtering with a sensitive VNTR genotyping strategy enables systematic screening of 27dupC pathogenic MUC1 variant from exome data.
Methods We initially validated our bioinformatics pipeline in a proof-of-concept cohort incorporating exome data from 33 participants with a known MUC1 pathogenic variant identified by Snapshot PCR and confirmed by 54 MUC1-negative individuals for negative control.
We then retrospectively analyzed exome sequencing data from January 2019 to October 2023 from 3512 adult participants with nephropathy of unknown origin.
Finally, we prospectively validated our pipeline in 825 additional participants enrolled from November 2023.
Results SharkVNTyper accurately identified MUC1 variants in 32 of 33 participants and excluded its presence in all the 54 negative controls in the proof-of-concept cohort (sensitivity of 97%, specificity of 100%).
Integration of the Shark tool with VNTyper significantly reduced running time from 6–12 hours to 5–10 minutes per sample, allowing both retrospective and prospective analyses.
In the retrospective cohort, SharkVNTyper identified 23 additional positive participants who were not suspected clinically and had been missed in the initial exome analysis; 18 of these participants were confirmed as carrying the MUC1 27dupC mutation by low-throughput Snapshot PCR.
In the prospective cohort of 825 participants with CKD, systematic screening discovered 13 positive participants, with 12 confirmed by PCR.
Overall, of 63 participants (1.
4% of 4653) with molecularly confirmed ADTKD-MUC1, comprehensive diagnoses and descriptions of the disease were available for 24 participants.
The median age of kidney failure was 50 years, 38% exhibited bilateral multiple kidney cysts, 8% had early-onset gout, and 58% had arterial hypertension.
Conclusions SharkVNTyper enabled the analysis of highly repeated regions, such as the MUC1 VNTR, and facilitated the systematic screening of ADTKD-MUC1 from exome data, fostering 27dupC variation identification.
Podcast This article contains a podcast at https://dts.
podtrac.
com/redirect.
mp3/www.
asn-online.
org/media/podcast/JASN/2024_11_15_KTS_November2024.
mp3.

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