Integrating D4Z4 methylation analysis into clinical practice: improvement of FSHD molecular diagnosis through distinct thresholds for 4qA/4qA and 4qA/4qB patients

Abstract

Background: Facioscapulohumeral dystrophy (FSHD) is a myopathy characterized by the loss of repressive epigenetic features affecting the D4Z4 locus (4q35). The assessment of DNA methylation at two regions (DUX4-PAS and DR1) of D4Z4 locus proved to be an effective method to detect epigenetic signatures compatible with FSHD. The present study aims at validating the employment of this method into clinical practice and improving the protocol by refining the classification thresholds of 4qA/4qA patients. To this purpose, 218 subjects with clinical suspicion of FSHD collected in 2022-2023 were analyzed. Each participant underwent in parallel the traditional FSHD molecular testing (D4Z4 sizing) and the proposed methylation assay. The results provided by both analyses were compared to evaluate the concordance and calculate the performance metrics of the methylation test.

Results: Among the 218 subjects, the 4q variant type distribution was 54% 4qA/4qA, 43% 4qA/4qB and 3% 4qB/4qB. The methylation analysis was performed only on carriers of at least one 4qA allele. After refining the classification threshold, the test reached the following performance metrics: sensitivity = 0.90, specificity = 1.00 and accuracy = 0.93. These results confirmed the effectiveness of the methylation assay in identifying patients with genetic signature compatible with FSHD1 and FSHD2 based on their DUX4-PAS and DR1 profile, respectively. The methylation data were also evaluated with respect to the clinical information.

Conclusions: The study confirmed the ability of the method to accurately identify methylation profiles compatible with FSHD genetic signatures considering the 4q genotype. Moreover, the test allows the detection of hypomethylated profiles in asymptomatic patients, suggesting its potential application in identifying preclinical conditions in patients with positive family history and FSHD genetic signatures. Furthermore, the present work emphasizes the importance of interpreting methylation profiles considering the patients' clinical data.

Keywords: D4Z4; DNA methylation; Epigenetic biomarker; FSHD; FSHD diagnosis; FSHD signature; Neuromuscular diseases.

Fig. 1

Methylation analysis workflow. The protocol employed for 4q subtelomeric variant typing and the assessment of methylation levels at DUX4-PAS and DR1 regions of D4Z4 locus (AFLP = amplification fragments length polymorphisms). Figure adapted from Megalizzi et al. [22] (Created with BioRender.com)

Fig. 2

Scatter Plot highlighting the distribution of methylation values of 4qA/4qA subjects for the refinement of DUX4-PAS threshold. Group 1 shows the CN subjects, whereas the Group 2 contains the NCN subjects. Methylation levels are grouped according to the status (y-axis) and visualized into different colors: blue for CN (Group 1) and red for NCN (Group 2). The data are displayed as a collection of shapes plotted with respect to methylation values on x-axis (A for CpG6; B for CpG3). Rounds, crosses, and triangles represent the RU number of the subjects whose methylation levels are plotted. The dashed lines indicate the threshold identified for each CpG site (yellow-highlighted), chosen according to methylation levels of the CN subject displaying the lowest value within each CpG (Created with OrangeDataMining.com)

Fig. 3

Confusion matrix employed to calculate the performance metrics of the ML model. The confusion matrix shows the number of concordant positive (CP), non-concordant-positive (NCP), concordant negative (CN), and non-concordant-negative (NCN). The number of predictions considered for assessing the metrics is indicated at the bottom of each confusion matrix. The performance metrics were calculated with respect to the overall cohort (A, D) as well as by splitting for 4qA/4qA patients (C, F) and 4qA/4qB ones (B, E). Moreover, sensitivity (sens.), specificity (spec.) and accuracy (acc.) are showed for each box (Created with BioRender.com)

Fig. 4

Flowchart summarizing the results obtained by the employment of D4Z4 methylation assay in the study cohort of 218 patients. CP = concordant-positive; NCN = non-concordant-negative; CN = concordant-negative

Fig. 5

Decisional workflow showing the thresholds of CpGs methylation levels for FSHD prediction and considering the 4q genotype. (Created with BioRender.com)