Heatmaps of module eigengene (MEs) correlations with traits of interest from PITT sample (GS5 SCZ risk preserved co-expression network).

SCZ risk genomic scores GS1-SCZ (pGWASGWAS GWAS thresholds). Last four columns: correlations of MEs and cell type proportions to quality check the removal of variance explained by cell type proportion. Virtually no ME had correlations with cell type proportions, which confirms the efficient cell type deconvolution for neurons, astrocytes and endothelia. (TIF)</p

Gene overlap of modules that concentrate genetic risk of SCZ risk in co-expression networks of <i>preserved</i> GS3-SCZ-GS5-SCZ and GS3-GS5 height from LIBD dataset and the independent replication sample (PITT sample).

Gene overlap of modules that concentrate genetic risk of SCZ risk in co-expression networks of preserved GS3-SCZ-GS5-SCZ and GS3-GS5 height from LIBD dataset and the independent replication sample (PITT sample).</p

PGC3 prioritized genes overlap in modules of preserved SCZ GS-SCZ and GS-Ht; LIBD sample.

PGC3 prioritized genes overlap in modules of preserved SCZ GS-SCZ and GS-Ht; LIBD sample.</p

Methodological pipeline to create artifact co-expression networks and background from input adjusted to preserve or remove shuffled GS SCZ and height scores.

Methodological pipeline to create artifact co-expression networks and background from input adjusted to preserve or remove shuffled GS SCZ and height scores.</p

Proportions of fragmented original vs. shuffled preserved GS3 height in the background.

Proportions of fragmented original vs. shuffled preserved GS3 height in the background.</p

PGC3 prioritized genes enrichment in modules of preserved SCZ GS-SCZ and GS-Ht; LIBD sample.

PGC3 prioritized genes enrichment in modules of preserved SCZ GS-SCZ and GS-Ht; LIBD sample.</p

GS-SCZ, GS-Ht <i>preserved</i> modules correlated with genomic scores and significant enrichment in PGC3 priority genes in LBD and PITT samples.

GS-SCZ, GS-Ht preserved modules correlated with genomic scores and significant enrichment in PGC3 priority genes in LBD and PITT samples.</p

Goodness-of-fit measures of CIBERSORT deconvolution of pseudobulk RNA-Seq data (i.e., correlation coefficients and Root Mean Square Error- RMSE) show a better performance for a model based on brain scRNA-Seq signature- Velmeshev 2019 (higher correlation coefficients and lower RMSE).

The algorithm fails though to estimate microglia and endothelia. (TIF)</p

Distribution of SCZ genetic risk and height heritability in modules of preserved genomic scores effects (GS5 height).

Columns are organized by enrichment of heritability for two traits or just one; directionality of enrichment (enrichment: significant LD score >1; depletion: significant LD scorepreserved genomics scores modules in the background (yes = fragmented; no = not fragmented); significance of enrichment in biological pathways; significance of enrichment in PGC3 loci genes. Criteria for concordant concentration of genetic burden for SCZ risk (green cells = 1 in the table) represented by significant enrichment for trait heritability, significant MEs correlations with genomic scores, directionality- MEs negatively correlated with GS-SCZ associated with neuronal functionality pathways, MEs positively correlated with GS-SCZ associated with general cellular functions; fragmentation in background; significant enrichment in PGC3 loci genes. Legend: modules in green cells annotated with * are fulfilling all criteria and have the highest concentration of genetic risk for SCZ (i.e., brown for GS5 height preserved network). Modules annotated with ** or in tan colored cells do not fulfill all criteria for SCZ genetic risk convergence. (TIF)</p

Functional profiling of GS-SCZ <i>preserved</i> modules with cumulative evidence for genomic risk effect on co-expression.

Transcription, translation and metabolic ontologies are enriched in gene sets originated from modules with MEs positively correlated with GS-SCZs SCZ; nervous system development and functionality ontologies are enriched in gene sets originated from modules with MEs negatively correlated with GS-SCZs SCZ (highlighted by red rectangles). Legend: BG_GS3-SCZ_ / BG_GS5-SCZ_x = fragments from SCZ risk GS3-SCZ or GS5-SCZ preserved modules overlapped with background (BG) modules.</p