59 research outputs found

    ‘Everyone thought I was a very very bad person… no one want to know you like the nurses and doctors’:using focus groups to elicit the views of adults with learning disability who use challenging behaviour services

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    and Tables S1–S3. (PDF 3090 kb

    An epigenetic clock for gestational age at birth based on blood methylation data

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    Background: Gestational age is often used as a proxy for developmental maturity by clinicians and researchers alike. DNA methylation has previously been shown to be associated with age and has been used to accurately estimate chronological age in children and adults. In the current study, we examine whether DNA methylation in cord blood can be used to estimate gestational age at birth. Results: We find that gestational age can be accurately estimated from DNA methylation of neonatal cord blood and blood spot samples. We calculate a DNA methylation gestational age using 148 CpG sites selected through elastic net regression in six training datasets. We evaluate predictive accuracy in nine testing datasets and find that the accuracy of the DNA methylation gestational age is consistent with that of gestational age estimates based on established methods, such as ultrasound. We also find that an increased DNA methylation gestational age relative to clinical gestational age is associated with birthweight independent of gestational age, sex, and ancestry. Conclusions: DNA methylation can be used to accurately estimate gestational age at or near birth and may provide additional information relevant to developmental stage. Further studies of this predictor are warranted to determine its utility in clinical settings and for research purposes. When clinical estimates are available this measure may increase accuracy in the testing of hypotheses related to developmental age and other early life circumstances.Peer reviewe

    Genome-Wide Association Study of Genetic Variants in LPS-Stimulated IL-6, IL-8, IL-10, IL-1ra and TNF-α Cytokine Response in a Danish Cohort

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    <div><p>Background</p><p>Cytokine response plays a vital role in various human lipopolysaccharide (LPS) infectious and inflammatory diseases. This study aimed to find genetic variants that might affect the levels of LPS-induced interleukin (IL)-6, IL-8, IL-10, IL-1ra and tumor necrosis factor (TNF)-α cytokine production.</p><p>Methods</p><p>We performed an initial genome-wide association study using Affymetrix Human Mapping 500 K GeneChip® to screen 130 healthy individuals of Danish descent. The levels of IL-6, IL-8, IL-10, IL-1ra and TNF-α in 24-hour LPS-stimulated whole blood samples were compared within different genotypes. The 152 most significant SNPs were replicated using Illumina Golden Gate® GeneChip in an independent cohort of 186 Danish individuals. Next, 9 of the most statistical significant SNPs were replicated using PCR-based genotyping in an independent cohort of 400 Danish individuals. All results were analyzed in a combined study among the 716 Danish individuals.</p><p>Results</p><p>Only one marker of the 500 K Gene Chip in the discovery study showed a significant association with LPS-induced IL-1ra cytokine levels after Bonferroni correction (<i>P</i><10<sup>−7</sup>). However, this SNP was not associated with the IL-1ra cytokine levels in the replication dataset. No SNPs reached genome-wide significance for the five cytokine levels in the combined analysis of all three stages.</p><p>Conclusions</p><p>The associations between the genetic variants and the LPS-induced IL-6, IL-8, IL-10, IL-1ra and TNF-α cytokine levels were not significant in the meta-analysis. This present study does not support a strong genetic effect of LPS-stimulated cytokine production; however, the potential for type II errors should be considered.</p></div

    Forest plots of meta-analysis of each selected SNP on the cytokine production.

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    <p>The x-axis represents the estimated effect sizes in mean differences. The horizontal lines show the stage-specific estimated effect sizes and the corresponding 95% confidence intervals of the natural logarithmic mean differences. The solid vertical line at 0 means no difference in effect size.</p

    Sedation and unrest after an injection of BuTAC.

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    <p>Sedation and unrest were rated on a scale ranging from 0–6. Data are shown as medians +/- quartiles. +p<0.05 relative to vehicle, (n = 7).</p

    Effect of BuTAC on d-amphetamine-induced arousal.

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    <p>The behaviour was rated on a scale ranging from 0–6. Data are shown as medians +/- quartiles. +p<0.05 relative to vehicle. *p<0.05 relative to amphetamine, (n = 7).</p