No abstract

Obstructive sleep apnea (OSA) occurs at a high prevalence in patients with Down syndrome (DS). A polysomnogram, which is often cumbersome and challenging, remains the gold standard method of diagnosing OSA. OSA in patients with DS is often attributed to skeletal and soft-tissue structural alterations that are characteristic of the DS phenotype; as such, we hypothesized that assessing anthropometric facial measurements may be predictive of OSA in patients with DS. We used the 3dMDface sterophotography system to capture and create 3D facial images, and we subsequently identified facial landmarks using a single, experienced investigator and utilizing proprietary software to calculate inter-landmark distances and angles. We compared our findings with similar data for neurotypically developing participants. We further compared the findings in participants with DS with and without OSA. Participants with DS had maxillomandibular hypoplasia with smaller ear, nose, and eye measurements compared to neurotypically developing peers. We found no statistically significant differences in 3D photogrammetric measurements between participants with DS with or without OSA.

No abstract

Study Objectives The study aim was to compare urinary biomarkers in individuals with Down syndrome (DS) with and without obstructive sleep apnea (OSA) to those of age- and sex-matched neurotypically developing healthy controls (HC). We further investigated whether we could predict OSA in individuals with DS using these biomarkers. Methods Urine samples were collected from 58 individuals with DS the night before or the morning after their scheduled overnight polysomnogram or both, of whom 47 could be age- and sex-matched to a sample of 43 HC. Concentrations of 12 neurotransmitters were determined by enzyme-linked immunosorbent assay. Log-transformed creatinine-corrected assay levels were normalized. Normalized z-scores were compared between individuals with DS vs. HC, between individuals with DS with vs. without OSA, and to derive composite models to predict OSA. Results Most night-sampled urinary biomarkers were elevated among individuals with DS relative to matched HC. No urinary biomarker levels differed between individuals with DS with vs. without OSA. A combination of four urinary biomarkers predicted AHI > 1 with a positive predictive value of 90% and a negative predictive value of 68%. Conclusions Having DS, even in the absence of concurrent OSA, is associated with a different urinary biomarker profile when compared to HC. Therefore, while urinary biomarkers may be predictive of OSA in the general pediatric population, a different approach is needed in interpreting urinary biomarker assays in individuals with DS. Certain biomarkers also seem promising to be predictive of OSA in individuals with DS.