Increased brain age in adults with Prader-Willi syndrome

In this study, a machine learning approach was used to predict brain age based on grey matter (GM) and white matter (WM) maps derived from structural neuroimaging data using T1-weighted magnetic resonance imaging (MRI) scans. Brain-predicted age difference (brain-PAD) scores, calculated as the difference between chronological age and brain-predicted age, are designed to reflect deviations from healthy brain aging, with higher brain-PAD scores indicating premature aging.Two separate adult cohorts underwent brain-predicted age calculation. The main cohort consisted of PWS (n = 20; age mean 23.1 years, range 19.8–27.7; 70.0% male; body mass index (BMI) mean 30.1 kg/m2, 21.5–47.7; n = 19 paternal chromosome 15q11–13 deletion) and age- and sex-matched controls (n = 40; age 22.9 years, 19.6–29.0; 65.0% male; BMI 24.1 kg/m2, 19.2–34.2) adults (BMI PWS vs. control P = .002). Brain-PAD was significantly greater in PWS than controls (effect size mean ± SEM +7.24 ± 2.20 years [95% CI 2.83, 11.63], P = .002). Brain-PAD remained significantly greater in PWS than controls when restricting analysis to a sub-cohort matched for BMI consisting of n = 15 with PWS with BMI range 21.5–33.7 kg/m2, and n = 29 controls with BMI 21.7–34.2 kg/m2 (effect size +5.51 ± 2.56 years [95% CI 3.44, 10.38], P = .037). In the PWS group, brain-PAD scores were not associated with intelligence quotient (IQ), use of hormonal and psychotrop...
Source: NeuroImage: Clinical - Category: Radiology Source Type: research