DNA methylation profiling in Kabuki syndrome: reclassification of germline KMT2D VUS and sensitivity in validating postzygotic mosaicism

Abstract

Autosomal dominant Kabuki syndrome (KS) is a rare multiple congenital anomalies/neurodevelopmental disorder caused by heterozygous inactivating variants or structural rearrangements of the lysine-specific methyltransferase 2D (KMT2D) gene. While it is often recognizable due to a distinctive gestalt, the disorder is clinically variable, and a phenotypic scoring system has been introduced to help clinicians to reach a clinical diagnosis. The phenotype, however, can be less pronounced in some patients, including those carrying postzygotic mutations. The full spectrum of pathogenic variation in KMT2D has not fully been characterized, which may hamper the clinical classification of a portion of these variants. DNA methylation (DNAm) profiling has successfully been used as a tool to classify variants in genes associated with several neurodevelopmental disorders, including KS. In this work, we applied a KS-specific DNAm signature in a cohort of 13 individuals with KMT2D VUS and clinical features suggestive or overlapping with KS. We succeeded in correctly classifying all the tested individuals, confirming diagnosis for three subjects and rejecting the pathogenic role of 10 VUS in the context of KS. In the latter group, exome sequencing allowed to identify the genetic cause underlying the disorder in three subjects. By testing five individuals with postzygotic pathogenic KMT2D variants, we also provide evidence that DNAm profiling has power to recognize pathogenic variants at different levels of mosaicism, identifying 15% as the minimum threshold for which DNAm profiling can be applied as an informative diagnostic tool in KS mosaics.

Fig. 1. Comparison among different DNAm signatures for Kabuki syndrome.

MDS plots (top) and HC (bottom) obtained from beta-values of different KS-specific CpGs as identified by Butcher and colleagues [31] (a), Aref-Eshghi and colleagues [26] (b), and Oexle and colleagues [32] (c) are reported to compare DNAm profiling-based classification in our internal dataset composed by KS subjects (red) and a control cohort constituted by healthy individuals or subjects affected with other NDDs (light blue).

Fig. 2. Validation of Kabuki syndrome by means of independent datasets.

DNAm signature was tested for robustness using MDS (a) and HC (b) on two different internal cohorts (OPBG, magenta and blue/light blue), and an external dataset (RH, orange and green). Using the selected probes, an SVM-based ML classifier was trained to score all KS cases (red) and controls (light blue) with statistical confidence (c). Controls used as validation set are depicted in blue.

Fig. 3. DNAm profiling to test for classification rare KMT2D variants of unknown clinical significance.

MDS (a) and HC (b) analyses on episignature’s CpG site were performed on molecularly unsolved samples from independent datasets: 13 internal VUS (OPBG, green) and 1 external one (RH, black). Using the selected sites, an SVM-based ML classifier was trained to score all KS cases and controls with statistical confidence (c). KS individuals are in red, while controls are depicted in light blue.

Fig. 4. DNAm profiling properly classifies pathogenic variants occurring at different level of mosaicism.

MDS (a), HC (b), and SVM-based ML classifier (c) were used to assess genome-wide DNAm patterns of variable percentages of mosaic pathogenic variants in KMT2D (10 to 25%, depicted in orange). Two different molecularly confirmed KS individuals were also inspected ranging the variant allele frequency down to 20%, 10%, and 5% by dilution with blood-derived DNA obtained from age-matched healthy controls (D1 and D2, depicted in black and gray). KS individuals are in red, while controls are in light blue.