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Rare diseases are heterogeneous diseases characterized by various symptoms and signs. Due to the low prevalence of such conditions (less than 1 in 2000 people), medical expertise is limited, knowledge is poor and patients’ care provided by medical centers is inadequate. An accurate diagnosis is frequently challenging and ongoing research is also insufficient, thus complicating the understanding of the natural progression of the rarest disorders. This review aims at presenting the multimodal approach supported by the integration of multiple analyses and disciplines as a valuable solution to clarify complex genotype–phenotype correlations and promote an in-depth examination of rare disorders. Taking into account the literature from large-scale population studies and ongoing technological advancement, this review described some examples to show how a multi-skilled team can improve the complex diagnosis of rare diseases. In this regard, Facio-Scapulo-Humeral muscular Dystrophy (FSHD) represents a valuable example where a multimodal approach is essential for a more accurate and precise diagnosis, as well as for enhancing the management of patients and their families. Given their heterogeneity and complexity, rare diseases call for a distinctive multidisciplinary approach to enable diagnosis and clinical follow-up.

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.