A European focus on proteomics

A report on the First International Symposium of the Austrian Proteomics Platform, Seefeld, Austria, 26-29 January 2004.     

Idiopathic chronic sleep onset insomnia in attention-deficit/hyperactivity disorder: a circadian rhythm sleep disorder

To investigate whether ADHD-related sleep-onset insomnia (SOI) is a circadian rhythm disorder, we compared actigraphic sleep estimates, the circadian rest-activity rhythm, and dim light melatonin onset (DLMO) in ADHD children having chronic idiopathic SOI with that in ADHD children without sleep problems. Participants were 87 psychotropic-medication-na?ve children, aged 6 to 12 yrs, with rigorously diagnosed ADHD and SOI (ADHD-SOI) and 33 children with ADHD without SOI (ADHD-noSOI) referred from community mental health institutions and pediatric departments of non-academic hospitals in The Netherlands. Measurements were 1 wk, 24 h actigraphy recordings and salivary DLMO. The mean (+/-SD) sleep onset time was 21:38 +/- 0:54 h in ADHD-SOI, which was significantly (p < 0.001) later than that of 20:49 +/- 0:49 h in ADHD-noSOI. DLMO was significantly later in ADHD-SOI (20:32 +/- 0:55 h), compared with ADHD-noSOI (19:47 +/- 0:49 h; p < 0.001). Wake-up time in ADHD-SOI was later than in ADHD-noSOI (p = 0.002). There were no significant between-group differences in sleep maintenance, as estimated by number of wake bouts and activity level in the least active 5 h period, or inter- and intradaily rhythm variability. We conclude that children with ADHD and chronic idiopathic sleep-onset insomnia show a delayed sleep phase and delayed DLMO, compared with ADHD children without SOI.     

Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models

Background  

With the explosion of microarray studies, an enormous amount of data is being produced. Systematic integration of gene expression data from different sources increases statistical power of detecting differentially expressed genes and allows assessment of heterogeneity. The challenge, however, is in designing and implementing efficient analytic methodologies for combination of data generated by different research groups.