Search

BackgroundAs a rare genetic disease, adrenomyeloneuropathy (AMN) is the most common adult phenotype of X-linked adrenoleukodystrophy (X-ALD). Mutations in the ABCD1 gene have been identified to cause AMN.MethodsWe applied clinical evaluation, laboratory tests, and neuroimaging on three patients with progressive spastic paraparesis. In genetic analysis, we investigated ABCD1 gene mutations by whole-exome sequencing and Sanger sequencing. Bioinformatics tools were used to predict the effects of identified ABCD1 mutations on the protein.ResultsAll three patients were men with adult-onset disease, mainly characterized by progressive spastic paraparesis. Among them, two patients had peripheral neuropathy and one patient had signs of adrenal insufficiency. All three patients showed cerebral involvement on brain MRI, while two patients were found with diffuse cord atrophy on spinal MRI. High-VLCFA levels in plasma, as well as C24:0/C22:0 and C26:0/C22:0 ratios, were found in all three patients. In addition, three different ABCD1 mutations were identified in three unrelated Chinese families, including one known mutation (c.1415_1416delAG) and two novel mutations (c.217C>T and c.160_170delACGCAGGAGGC). Based on the clinical assessment, radiographic, biochemical, and genetic testing, the final diagnosis was AMN in these patients with spastic paraparesis.ConclusionThis study reported three patients with AMN and identified two novel mutations in the ABCD1 in the Chinese population. Our finding emphasized that X-ALD is an important cause of adult-onset spastic paraplegia. Thus, neuroimaging, VLCFA testing, and especially the detection of the ABCD1 gene have important implications for the etiological diagnosis of adult patients with spastic paraplegia.

ObjectivesTo develop and validate a predictive nomogram for idiopathic rapid eye movement (REM) sleep behavior disorder (RBD) in a community population in Beijing, China.MethodsBased on the validated RBD questionnaire-Hong Kong (RBDQ-HK), we identified 78 individuals with possible RBD (pRBD) in 1,030 community residents from two communities in Beijing. The least absolute shrinkage and selection operator (LASSO) regression was applied to identify candidate features and develop the nomogram. Internal validation was performed using bootstrap resampling. The discrimination of the nomogram was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, and the predictive accuracy was assessed via a calibration curve. Decision curve analysis (DCA) was performed to evaluate the clinical value of the model.ResultsFrom 31 potential predictors, 7 variables were identified as the independent predictive factors and assembled into the nomogram: family history of Parkinson's disease (PD) or dementia [odds ratio (OR), 4.59; 95% confidence interval (CI), 1.35–14.45; p = 0.011], smoking (OR, 3.24; 95% CI, 1.84–5.81; p < 0.001), physical activity (≥4 times/week) (OR, 0.23; 95% CI, 0.12–0.42; p < 0.001), exposure to pesticides (OR, 3.73; 95%CI, 2.08–6.65; p < 0.001), constipation (OR, 6.25; 95% CI, 3.58–11.07; p < 0.001), depression (OR, 3.66; 95% CI, 1.96–6.75; p < 0.001), and daytime somnolence (OR, 3.28; 95% CI, 1.65–6.38; p = 0.001). The nomogram displayed good discrimination, with original AUC of 0.885 (95% CI, 0.845–0.925), while the bias-corrected concordance index (C-index) with 1,000 bootstraps was 0.876. The calibration curve and DCA indicated the high accuracy and clinical usefulness of the nomogram.ConclusionsThis study proposed an effective nomogram with potential application in the individualized prediction for pRBD.