RESUMEN
BACKGROUND: Semaphorins and plexins are ligands and cell surface receptors that regulate multiple neurodevelopmental processes such as axonal growth and guidance. PLXNA3 is a plexin gene located on the X chromosome that encodes the most widely expressed plexin receptor in fetal brain, plexin-A3. Plexin-A3 knockout mice demonstrate its role in semaphorin signaling in vivo. The clinical manifestations of semaphorin/plexin neurodevelopmental disorders have been less widely explored. This study describes the neurological and neurodevelopmental phenotypes of boys with maternally inherited hemizygous PLXNA3 variants. METHODS: Data-sharing through GeneDx and GeneMatcher allowed identification of individuals with autism or intellectual disabilities (autism/ID) and hemizygous PLXNA3 variants in collaboration with their physicians and genetic counselors, who completed questionnaires about their patients. In silico analyses predicted pathogenicity for each PLXNA3 variant. RESULTS: We assessed 14 boys (mean age, 10.7 [range 2 to 25] years) with maternally inherited hemizygous PLXNA3 variants and autism/ID ranging from mild to severe. Other findings included fine motor dyspraxia (92%), attention-deficit/hyperactivity traits, and aggressive behaviors (63%). Six patients (43%) had seizures. Thirteen boys (93%) with PLXNA3 variants showed novel or very low allele frequencies and probable damaging/disease-causing pathogenicity in one or more predictors. We found a genotype-phenotype correlation between PLXNA3 cytoplasmic domain variants (exons 22 to 32) and more severe neurodevelopmental disorder phenotypes (P < 0.05). CONCLUSIONS: We report 14 boys with maternally inherited, hemizygous PLXNA3 variants and a range of neurodevelopmental disorders suggesting a novel X-linked intellectual disability syndrome. Greater understanding of PLXNA3 variant pathogenicity in humans will require additional clinical, computational, and experimental validation.
Asunto(s)
Trastorno del Espectro Autista/genética , Moléculas de Adhesión Celular/fisiología , Discapacidad Intelectual/genética , Proteínas del Tejido Nervioso/fisiología , Receptores de Superficie Celular/genética , Semaforinas/fisiología , Adolescente , Adulto , Trastorno del Espectro Autista/fisiopatología , Niño , Preescolar , Estudios de Asociación Genética , Humanos , Discapacidad Intelectual/fisiopatología , Masculino , Transducción de Señal/fisiología , Adulto JovenRESUMEN
BACKGROUND: Understanding risk factors associated with prolonged opioid use to help mitigate abuse and develop presurgical screening programs to identify at-risk patients is paramount. The purpose of this study was to develop and validate a clinical risk assessment tool to preoperatively predict prolonged opioid use after shoulder surgery. METHODS: A total of 561 patients who underwent shoulder surgery within a tertiary health care system were identified, and opioid prescription data were retrospectively collected from the Connecticut Prescription Monitoring and Reporting System. The inclusion criteria were patients aged 18 years or older, and the exclusion criteria were patients not registered in the Connecticut Prescription Monitoring and Reporting System. Quantities of opioids prescribed were documented. Demographic characteristics, surgery type, medications, and medical comorbidities were identified by chart abstraction. Logistic regression was used to calculate odds ratios of patients using opioids longer than 6 weeks, and multivariate analysis was performed on 10 identified patient factors. A concordance index was used to calculate the discriminatory ability of a nomogram to predict prolonged opioid use. RESULTS: Multivariate analysis demonstrated that opioid use prior to surgery, insurance type, procedure type, body mass index, smoking status, and psychiatric disorders were responsible for prolonged opioid use. The prediction accuracy of this model was good, with a calculated concordance index of 0.766 (95% confidence interval, 0.736-0.820). CONCLUSIONS: We present a preoperative predictive calculator to help identify at-risk patients and quantify their risk of prolonged opioid use after shoulder surgery. This is a valuable clinical decision-making tool to identify patients benefitting from referral to pain management specialists and to possibly reduce the risk of opioid abuse and addiction.