Descriptive characteristics of study participants.

<p>A total sample size of N = 50 was included in the analysis. Descriptive data are presented in means (M) and standard deviations (SD). Absolute numbers of participants are given (N) and expressed as percentage (%).</p><p><b>Abbreviations:</b> means (<i>M</i>); standard deviation (<i>SD</i>), brain-derived neurotrophic factor (BDNF); Insomnia Severity Index (ISI); Perceived Stress Scale (PSS); restless legs syndrome (RLS), periodic limb movement (PLM).</p

Stress experience in subjects suffering from current insomnia.

<p>Correlation between insomnia severity score (indicated by the <i>Insomnia Severity Index</i> (ISI)) and stress perception (indicated by the <i>Perceived Stress Scale</i> (PSS)). Analysis showed a significant correlation between scores on the ISI and the PSS across the whole sample (<i>r_p</i> = 0.548, <i>p</i><0.001). * Denotes statistical significance at <i>p</i><0.05.</p

Correlation between serum BDNF levels and scores on the <i>Perceived Stress Scale</i> (PSS) by insomnia severity groups according to the <i>Insomnia Severity Index</i> (ISI).

<p>Analyses showed a significant correlation (partial correlation controlled for smoking) between BDNF and stress only in subjects with no insomnia (<i>r_p</i> = −0.511, p = 0.013) compared to subjects with sub threshold (<i>r_p</i> = 0.069, <i>p</i> = 0.814) or clinical insomnia (<i>r_p</i> = 0.199, <i>p</i> = 0.608). White squares represent subjects with no insomnia, black circles represent subjects with sub threshold and black triangles represent subjects with clinical insomnia. (Inset) Mean serum BDNF levels of the insomnia severity groups. Plotted means and standard errors estimated by ANCOVA with serum BDNF as dependent variable, insomnia severity group as independent variable and smoking as covariate. For all three insomnia severity groups the overall effect on serum BDNF was not significant (<i>F</i>(2) = 2.67; <i>p</i> = 0.080). Contrasts showed that serum BDNF levels in the group with no insomnia were significantly higher compared to the groups reporting sub threshold and clinical insomnia (<i>F</i>(1) = 5.33; <i>p</i> = 0.026); (no insomnia n = 24; sub threshold insomnia n = 16, clinical insomnia n = 10). * Denotes statistical significance at <i>p</i><0.05</p

Additional file 5: of PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

Figure S4. Software performance between datasets across number of PRS p-value thresholds to generate in a single run. Imputed HC = imputed posterior probabilities converted to “hard calls”, Array Data = observed genotypes. (PDF 5 kb

Additional file 1: of PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

Supplementary Methods and Data Analysis. Additional information on the MAVAN cohort. Genetic data quality control and supplementary data analyses are provided. (Additional file 4: Figure S3, Additional file 5: Figure S4). (PDF 142 kb

Additional file 3: of PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

Figure S2. PRSice v1.25, PRSice-2, and PRSoS performance across datasets. Bar plot shows the results of the performance test comparing running PRSice v1.25, PRSice-2, and PRSoS across the datasets. Processing time (y-axis) uses a log base 10 scale. Error bars indicate standard deviations. Numbers in boxed inserts indicate the size of the genotype data input. †Note that the file sizes used for the Imputed PP are same for PRSice v1.25 and PRSoS, thus illustrating the processing speed difference with same file size input. Genotype input formats are different across all three software for the other performance tests. Imputed PP = imputed posterior probabilities, Imputed HC = imputed posterior probabilities converted to “hard calls”, Array Data = observed genotypes. (PDF 34 kb

Additional file 2: of PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

Figure S1. PRSice v1.25 and PRSoS performance across the number of cores used to generate PRS and five thresholds using the Imputed Hard Call dataset. PRSice v1.25 could only run on 1 core. PRSoS performance was tested with 1, 4, 12, 20, and 24 cores on a Linux CentOS 7, 24-core Intel Xeon server. Error bars indicate standard deviations. (PDF 4 kb