Introduction: Inherited kidney disease (IKD) is the second most common cause of prevalent kidney failure on kidney replacement therapy in Europe. However, it remains underdiagnosed, in part, because of suboptimal genetic test resolution. The genetic diagnosis of autosomal dominant tubulointerstitial kidney disease (ADTKD) caused by MUC1 gene variants (ADTKD- MUC1 ) is technically challenging. Methods: We implemented a customized library for short-read high-throughput sequencing (SR-HTS) with specific bioinformatic approaches to enhance the genetic diagnosis of ADTKD- MUC1 . Specific analysis of the variable number tandem repeat (VNTR)- MUC1 region was performed in 550 patients with suspected IKD lacking an identifiable genetic cause using customized SR-HTS. We used a combination of techniques to confirm the genetic variant detected by SR-HTS. Results: Overall, 28 patients (5% [25/550]) had ADTKD- MUC1 with DupC (almost 90% [25/28] of MUC1 variants) or DupA (10%) MUC1 pathogenic frameshift variants. More than half of these cases required specialized bioinformatics analysis to detect the variants. These variants were validated using Sanger, SNaPshot, or long-read sequencing (LRS) according to the location and mutation type. Conclusion: This study presents an applicable solution of a customized SR-HTS approach for the systematic screening of MUC1 gene variants, with particular emphasis on the detection of frameshift alterations within the VNTR region that generate pathogenic MUC1 neoproteins associated with ADTKD- MUC1 . Integrating this strategy into routine diagnostic workflows increased the overall diagnostic yield while reducing the technical complexity associated with the sequential application of multiple methodologies.
