Distribution of the 5-HTTLPR genotype.

<p>Distribution of the 5-HTTLPR genotype.</p

Demographic data of the nurse groups by work stress.

<p>Demographic data of the nurse groups by work stress.</p

Methylation in the promoter of <i>SLC6A4</i> at five CpG sites in high (grey) and low (white) work stress environments.

<p>Coordinates for each residue are 28 563 120 (CpG5), 28 563 109 (CpG4), 28 563 107 (CpG3), 28 563 102 (CpG2), and 28 563 090 (CpG1) as per GRCh37 build (NCBI Reference Sequence: NC_000017.10). Differences between work stress environments were significant as per t-test (p = 7.10E–06, p = 2.50E–05, p = 0.000292, p = 4.37E–06, and p = 0.000289 respectively). Standard errors are indicated.</p

Representation of the <i>SLC6A4</i> gene promoter region for bisulfite sequencing analysis.

<p>Analyzed CpG sites are bolded and numbered from 1 through 5. Coordinates are based on the GRCh37 build (NCBI Reference Sequence: NC_000017.10).</p

Analysis strategy.

<p>The flow of statistical analysis and the amount of entities (genes/transcripts) after each step are illustrated. a) The 15101 entities that passed the filtering by flags and reannotation included 1292 up-regulated (red) and 1039 down-regulated (green) transcripts with at least 1.2-fold change from baseline (BL) to sleep restriction (SR) in sleep-restricted subjects ( = cases). * The pathway analysis was run for these genes. b) The 2331 entities were analyzed with 2-way ANOVA using the case/control status and the three timepoints as analysis axes. Changes with ANOVA interaction <i>P</i> value <0.05 were observed in 227 up-regulated and 83 down-regulated transcripts. c) Altogether 310 entities were further analyzed with 1-way repeated measures ANOVA considering the three timepoints. The 43 entities showing changes also in the control group were excluded from the analysis. The 133 genes with 1-way ANOVA <i>P</i> value <0.05 for the cases but not for the controls were then analyzed using a <i>t</i> test between the timepoints BL and SR. 62 genes were up-regulated and 55 down-regulated (P<0.05).</p

Expression changes after partial sleep restriction.

<p>The 310 entities (genes/transcripts) with interaction <i>P</i> value (<i>P</i><0.05) in 2-way ANOVA, sorted by average fold change from baseline (BL) to sleep restriction (SR) (with the up-regulated (red) on top, followed by the down-regulated (green). Each lane represents one individual (sleep deprived subjects, N = 9; controls, N = 4), and colour codes represent the fold change from BL to SR (BL  = 1).</p

Down-regulated genes after experimental sleep restriction.

<p>The expression changes of the 25 most down-regulated genes/transcripts after experimental sleep restriction period (SR) compared to baseline values (BL). Pointwise <i>P</i> values and fold changes (SR expression / BL expression) between these two timepoints are shown for each transcript.</p

Genome Wide Analysis of Narcolepsy in China Implicates Novel Immune Loci and Reveals Changes in Association Prior to Versus After the 2009 H1N1 Influenza Pandemic

<div><p>Previous studies in narcolepsy, an autoimmune disorder affecting hypocretin (orexin) neurons and recently associated with H1N1 influenza, have demonstrated significant associations with five loci. Using a well-characterized Chinese cohort, we refined known associations in TRA@ and P2RY11-DNMT1 and identified new associations in the TCR beta (TRB@; rs9648789 max P = 3.7×10⁻⁹ OR 0.77), ZNF365 (rs10995245 max P = 1.2×10⁻¹¹ OR 1.23), and IL10RB-IFNAR1 loci (rs2252931 max P = 2.2×10⁻⁹ OR 0.75). Variants in the Human Leukocyte Antigen (HLA)- DQ region were associated with age of onset (rs7744020 P = 7.9×10⁻⁹ beta −1.9 years) and varied significantly among cases with onset after the 2009 H1N1 influenza pandemic compared to previous years (rs9271117 P = 7.8×10⁻¹⁰ OR 0.57). These reflected an association of DQB1*03:01 with earlier onset and decreased DQB1*06:02 homozygosity following 2009. Our results illustrate how genetic association can change in the presence of new environmental challenges and suggest that the monitoring of genetic architecture over time may help reveal the appearance of novel triggers for autoimmune diseases.</p></div

Analysis of predisposing and protective HLA allelic combinations in Chinese individuals that carry DQB1*06:02.

<p>The comparison used only DQA1*01:02-DQB1*06:02 positive individuals (1183 cases, 438 controls) thus p values are well-below those reported in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003880#pgen-1003880-t002" target="_blank">Table 2</a> (see text).</p><p>The analysis was done sequentially first analyzing DQB1*06:02 homozygotes, then DQB1*03:01 carriers, then individuals with DQA1*01:02 with non-DQB1*06:02 at the other allele, and finally DQA1*01-nonDQA1*01:02 carriers.</p

Regional analysis of genome-wide significant loci.

<p>Combined association scores were computed using Mantel Haenszel X² test, following imputation of genotypes surrounding replicated SNPs in Chinese and European samples. The top scoring SNP for each region is marked with a purple diamond. Strength of LD is not indicated, as results represent data from two ethnic groups. The X-axis scale shows chromosomal position (Mb) from human genome reference sequence (hg19). The left Y-axis shows the negative base ten logarithm of the p-value, with genome-wide significance threshold (P<5×10⁻⁸) marked by dashed blue line. The right Y-axis shows recombination rate (cM/Mb) as a blue line. Genes in the regions are annotated at the bottom as blue bars. A: T cell receptor alpha on chromosome 14; B. T cell receptor beta on chromosome 7; C. P2RY11-DNMT1 on chromosome 19; D. ZNF365 on chromosome 10; E. IL10RB-INFAR1 region on chromosome 21.</p