Common developmental genome deprogramming in schizophrenia - Role of Integrative Nuclear FGFR1 Signaling (INFS)

Abstract

The watershed-hypothesis of schizophrenia asserts that over 200 different mutations dysregulate distinct pathways that converge on an unspecified common mechanism(s) that controls disease ontogeny. Consistent with this hypothesis, our RNA-sequencing of neuron committed cells (NCCs) differentiated from established iPSCs of 4 schizophrenia patients and 4 control subjects uncovered a dysregulated transcriptome of 1349 mRNAs common to all patients. Data reveals a global dysregulation of developmental genome, deconstruction of coordinated mRNA networks, and the formation of aberrant, new coordinated mRNA networks indicating a concerted action of the responsible factor(s). Sequencing of miRNA transcriptomes demonstrated an overexpression of 16 miRNAs and deconstruction of interactive miRNA-mRNA networks in schizophrenia NCCs. ChiPseq revealed that the nuclear (n) form of FGFR1, a pan-ontogenic regulator, is overexpressed in schizophrenia NCCs and overtargets dysregulated mRNA and miRNA genes. The nFGFR1 targeted 54% of all human gene promoters and 84.4% of schizophrenia dysregulated genes. The upregulated genes reside within major developmental pathways that control neurogenesis and neuron formation, whereas downregulated genes are involved in oligodendrogenesis. Our results indicate (i) an early (preneuronal) genomic etiology of schizophrenia, (ii) dysregulated genes and new coordinated gene networks are common to unrelated cases of schizophrenia, (iii) gene dysregulations are accompanied by increased nFGFR1-genome interactions, and (iv) modeling of increased nFGFR1 by an overexpression of a nFGFR1 lead to up or downregulation of selected genes as observed in schizophrenia NCCs. Together our results designate nFGFR1 signaling as a potential common dysregulated mechanism in investigated patients and potential therapeutic target in schizophrenia.

Keywords: Developmental hypothesis; Fibroblast Growth Factor Receptor 1; Genome regulation; Schizophrenia; miRNA.

Figure 1

RNAseq of control and schizophrenia NCCs. A) Distribution of gene expression across 8 samples: 4 control and 4 schizophrenia NCC lines. 15,279 expressed genes (mRNAs) were detected in all 8 samples. 4470 expressed genes were detected in some but not all samples. 4582 annotated genes were not detected in any sample. B) Heatmap of 1349 genes that were dysregulated in all 4 schizophrenia NCCs samples (FC ≥ −/+1.5 and q value ≥ 0.05). Among these, 839 were upregulated and 510 were downregulated. Raw expression data were log transformed and then centered to the median of all 8 samples. Red indicates higher value than median, green indicates lower value than median. C–E) IPA analysis of dysregulated genes. The number on the right represents the total number of genes in the pathway. The bar height represents the percentage of genes in the pathway that were found to be dysregulated. Green represents downregulated genes. C) Neuronal pathways, D) developmental pathways, and E) pathways that are predominantly up- or downregulated.

Figure 2

A) Histogram of pairwise correlations. Correlation was performed using 4 control and 4 patient NCCs samples. A flat distribution of correlation is observed in controls, while in patients an increase in the number of positively and negatively correlated genes was observed. B) Top 200 nodes (genes whose expression is highly correlated with that of multiple other genes) in control and in patient NCCs were identified. Yellow represents upregulated genes, and blue represents downregulated genes. Grey lines link pairs of genes whose correlation is greater than 0.9. In the control set, two separate networks are observed and each contains both upregulated and downregulated genes. In the patient set the upregulated and downregulated genes form two separate networks.

Figure 3

A) NCCs from three control subjects and three patients were analyzed. Heatmap shows 16 dysregulated miRNA genes (all upregulated) in patient NCCs. Raw expression data were log transformed, and then centered to the median of all 6 samples. Red indicates higher value than median, green indicates, lower value than median. B) 16 dysregulated miRNAs (Green) target 440 dysregulated mRNA (Blue). Each gray line indicates a connection between an miRNA and an mRNA. C) In pairwise correlation of dysregulated miRNA genes a high correlation is observed in control NCCs (n=3), but not in patient NCCs (n=3). D) Modeled versus actual miRNA-mRNA correlations. Red line shows correlations for miRNAs predicted based on correlations of their target mRNAs as in (Huttenhower et al., 2009). Blue line shows measured correlations between miRNAs and their target mRNAs. In control NCCs the predicted and actual correlations are similar. In patients, the patterns of predicted and actual correlations differ markedly.

Figure 4

A) Distribution of nFGFR1 peaks throughout the genomes of NCCs from a female control (C4) and a female patient (P3). nFGFR1 binds to all chromosomes. The binding profiles are similar for both control and patient genomes. B) Distributions of nFGFR1 peaks in genomes of control and patient NCCss. In patients, a two-fold increase is observed in introns, distal intergenic regions, downstream (0–3kb), and distal promoters (1–3kb). C) Enrichment of nFGFR1 peaks in genomes of control and patient NCCs within the promoters and bidirectional promoters, and downstream of the TSS. No enrichment is observed in introns or intergenic regions.

Figure 5

A) nFGFR1 binds to 54% of all annotated human genes in control (C4) NCCs and to 63% in schizophrenia patient (P3) NCCs. B) nFGFR1 binds to 915 dysregulated genes under both conditions, and to an additional 203 genes in schizophrenia NCCs only. In total, nFGFR1 binds to 84% of the genes that are dysregulated in schizophrenia NCCs. Only 14 genes are targeted by nFGFR1 in control but not schizophrenia NCCs.

Figure 6

A) Conservation plot of sequences of FGFR1 peaks in NCCs from a female control (C4) and female patient (P3). The expected increase in conservation was observed near the center of the nFGFR1 peak. B) Strength of nFGFR1 binding across a modeled average gene in NCCs from female C4 (blue) and male P3 (red). C) UCSC genome browser views of nFGFR1 binding for Disc1, FZD1, and Sox3. Tag distribution of nFGFR1 – increased binding is observed in patient (P3) compared to control (C4).

Figure 7

Overexpression of constitutively active nuclear FGFR1(NLS/SP-) affects expression of selected schizophrenia dysregulated genes. Human ESCs were stimulated to differentiate into NPCs and transfected with constitutively active nuclear FGFR1(NLS/SP-) or control β-galactosidase (β-gal). Transfected NPCs were induced to commit to a neuronal lineage (NCCs) within 2 days of treatment, and specific mRNAs were analyzed by RT-qPCR. FGFR1(NLS/SP-) transfection upregulates TH, Wnt7B, and Neurod4 mRNAs and downregulates Olig2, Olig1, and NCAM mRNAs.

Figure 8

Disruption of INFS in schizophrenia. “Feed-Forward-and-Gate” signaling by INFS during development(Fang et al., 2005; Stachowiak et al., 2015). Neurogenic signals generated by diverse extracellular stimuli (S: neurotransmitters, hormones, growth factors, cell contact receptors) are propagated through signaling pathways (SiP; cAMP, Ca++/PKC, MAPK, etc.) to sequence-specific transcription factors (TF: CREB, AP1, NfkB, Smads, Klf4, Stat3, RXR/RAR, etc.). In parallel, newly synthesized nFGFR1 translocates into the nucleus and “feeds forward” (F-F) developmental signals directly to CREB binding protein (CBP), an essential transcriptional co-activator and gene-gating factor. The coupled activation of TFs and CBP by nFGFR1 allows genes to respond to developmental signals in a coordinated fashion. In addition, INFS reinforces or turns off the input signals via a feedback loop (Stachowiak et al., 2013a). * marks signaling pathways in which schizophrenia-linked genes have been found, including cAMP, G-protein, PKC, MAPK, NfkB, CREB, RXR, and Nurr1 pathways (Stachowiak et al., 2013a). In schizophrenia and other neurodevelopmental diseases, mutations of these individual genes, including “weak” copy variations, could deregulate this auto-regulated genomic circuit (red lines) and thus lead to broad molecular and developmental dysfunction.