Hereditary polyneuropathies (HPPs), including Charcot-Marie-Tooth disease (CMT), represent a genetically and clinically heterogeneous group of disorders. Overlapping phenotypes, genetics, and clinical heterogeneity, and more complex phenotypes mimicking CMT can complicate the diagnosis. This study evaluated the effectiveness of an algorithm-guided, broad genetic testing strategy in a tertiary neuromuscular center in Türkiye, where recessive disorders are relatively common. Sixty-seven patients from 63 families referred for suspected HPP (2018-2025) were clinically stratified by phenotype and electrophysiology, and a diagnostic workflow integrating PMP22 MLPA with clinical or whole-exome sequencing was applied. The overall molecular diagnostic yield was 73% (46/63). PMP22-related neuropathies accounted for 43.5% of all diagnosed cases, with a group-specific yield of 60%. Among the non-PMP22 CMT group, the predominant inheritance pattern was autosomal recessive (70%). Nine novel variants were identified. Two dual molecular diagnoses (PMP22/MCCC1; MPZ/CRYBB2) were established. Importantly, six patients initially labeled as "CMT-like" harbored non-CMT disorders, including CYP27A1-, BTD-, HEXB-, ZFYVE26-, C19ORF12-, and COA7-related diseases-several of which are treatable or actionable. In a population with high genetic heterogeneity and elevated consanguinity, reliance on narrow CMT-focused panels risks misdiagnosis and may miss therapeutic opportunities. An algorithm-driven approach integrating PMP22 CNV analysis with exome sequencing substantially improves diagnostic yield, reveals blended or digenic mechanisms, and helps distinguish non-CMT phenocopies. These findings underscore the importance of comprehensive genomic testing and careful phenotype-genotype correlation in the evaluation of hereditary polyneuropathies.
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