Overall analytical strategy.

<p>In step I, 50 co-regulation modules were generated using meta-clustering of gene clusters identified by the “penalized K-medoids” method across 11 transcriptome MDD and matched controls studies. In step II, modules enriched from most of the selected GWAS studies related to MDD, neuropsychiatric disorder and traits, including systemic disease linked to psychiatric disorders were identified. In step III, the biological functions represented by genes included in each module were defined by pathway analysis from 2,334 gene sets of MSigDB (<a href="http://www.broadinstitute.org/gsea/msigdb" target="_blank">www.broadinstitute.org/gsea/msigdb</a>). In step IV, SNPs from the Catalog of GWAS were organized into three categories: cancer GWAS, human body indices GWAS and GWAS for common diseases and medial illnesses unrelated to MDD or other brain function. Three additional categories were defined as non-MDD-related negative control gene sets. (Note: In order to increase the performance of the heatmap in module #35, we first performed the hierarchical clustering with “complete” agglomeration method to aggregated samples with similar expression among all 88 genes, and the genes were sorted by the correlation from high to low of selected genes in the top.).</p

Consistent association of genes in module #35 with MDD-related gene categories.

<p>(<b>a</b>) Heatmap of log₁₀-transformed p-values from Fisher’s exact test for 50 modules obtained from MDD cases and matched controls and 8 MDD related GWAS and 3 negative controls. (<b>b</b>) Heatmap of log₁₀-transformed p-values from Fisher’s exact test for 50 modules obtained from controls and 8 MDD related GWAS and 3 negative controls. The green rectangle identifies module #35.</p

Histograms of the –log₁₀(p) of the Stouffer statistic from 50 modules of meta-analysis of 11 MDD studies and each single study.

<p>Module #35 with 88 genes (red arrow and double-cross) have largest –log₁₀ transformed p-value of Stouffer’s statistic 4.4. The other four blue arrows and double crosses indicated that these four modules in all single studies have more than 14 (15% of the 88 genes in module #35) overlapped with module #35. See detailed description in text.</p

Top 15 enriched pathways in module #35.

<p>Top 15 enriched pathways in module #35.</p

SMART: Statistical Metabolomics AnalysisAn R Tool

Metabolomics data provide unprecedented opportunities to decipher metabolic mechanisms by analyzing hundreds to thousands of metabolites. Data quality concerns and complex batch effects in metabolomics must be appropriately addressed through statistical analysis. This study developed an integrated analysis tool for metabolomics studies to streamline the complete analysis flow from initial data preprocessing to downstream association analysis. We developed Statistical Metabolomics AnalysisAn R Tool (SMART), which can analyze input files with different formats, visually represent various types of data features, implement peak alignment and annotation, conduct quality control for samples and peaks, explore batch effects, and perform association analysis. A pharmacometabolomics study of antihypertensive medication was conducted and data were analyzed using SMART. Neuromedin N was identified as a metabolite significantly associated with angiotensin-converting-enzyme inhibitors in our metabolome-wide association analysis (<i>p</i> = 1.56 × 10^–4 in an analysis of covariance (ANCOVA) with an adjustment for unknown latent groups and <i>p</i> = 1.02 × 10^–4 in an ANCOVA with an adjustment for hidden substructures). This endogenous neuropeptide is highly related to neurotensin and neuromedin U, which are involved in blood pressure regulation and smooth muscle contraction. The SMART software, a user guide, and example data can be downloaded from http://www.stat.sinica.edu.tw/hsinchou/metabolomics/SMART.htm

Description of cohorts in 11 MDD microarray platforms.

<p>ACC, anterior cingulate cortex; AMY, amygdala; DLPFC, dorsolateral prefrontal cortex, OFC, orbital ventral prefrontal cortex.</p

Functional groups of 88 gene in module #35<b>.</b>

<p>Annotations are based on Gene Ontology. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090980#pone-0090980-t003" target="_blank">Table 3</a> for a separate analysis of pathway enrichment.</p