The diagnosis of sleep-wake disorders (SWDs) is challenging because of the existence of only few accurate biomarkers and the frequent coexistence of multiple SWDs and/or other comorbidities. The aim of this study was to assess in a large cohort of well-characterized SWD patients the potential of a data-driven approach for the identification of SWDs. We included 6958 patients from the Bernese Sleep Registry and 300 variables/biomarkers including questionnaires, results of polysomnography/vigilance tests, and final clinical diagnoses. A pipeline, based on machine learning, was created to extract and cluster the clinical data. Our analysis was performed on three cohorts: patients with central disorders of hypersomnolence (CDHs), a full cohort of patients with SWDs, and a clean cohort without coexisting SWDs. A first analysis focused on the cohort of patients with CDHs and revealed four patient clusters: two clusters for narcolepsy type 1 (NT1) but not for narcolepsy type 2 or idiopathic hypersomnia. In the full cohort of SWDs, nine clusters were found: four contained patients with obstructive and central sleep apnea syndrome, one with NT1, and four with intermixed SWDs. In the cohort of patients without coexisting SWDs, an additional cluster of patients with chronic insomnia disorder was identified. This study confirms the existence of clear clusters of NT1 in CDHs, but mainly intermixed groups in the full spectrum of SWDs, with the exception of sleep apnea syndromes and NT1. New biomarkers are needed for better phenotyping and diagnosis of SWDs.

Delays in diagnosing rare genetic disorders often arise due to limited awareness and systemic challenges in primary care. This case highlights the importance of a holistic approach to patient care, encompassing timely detection and comprehensive evaluation of clinical features. We report the case of a 21-year-old Ecuadorian male with facial and hand dysmorphias, cardiomegaly, pulmonary hypertension, and patent ductus arteriosus (PDA). Whole-exome sequencing, performed using the Illumina NextSeq platform. We extensively analyzed over 100 genes linked to congenital structural heart diseases. The genetic findings provided a definitive diagnosis of Craniofacial-Deafness-Hand Syndrome, an extremely rare autosomal dominant condition, but found no variants that explain the patient's cardiac phenotype. We identified a novel pathogenic missense variant in the PAX3 gene (c.A91C, p. T31P). This case underscores the necessity of integrating genetic testing into routine clinical practice to enhance diagnostic precision for rare diseases. It also highlights the need for multidisciplinary collaboration and a holistic care model to improve patient outcomes. The unique association of Craniofacial-Deafness-Hand Syndrome with cardiovascular anomalies due to a PAX3 variation provides valuable insights into the genetic underpinnings of this rare condition.