Rare and common epilepsies converge on a shared gene regulatory network providing opportunities for novel antiepileptic drug discovery

Background The relationship between monogenic and polygenic forms of epilepsy is poorly understood, and the extent to which the genetic and acquired epilepsies share common pathways is unclear. Here, we use an integrated systems-level analysis of brain gene expression data to identify molecular networks disrupted in epilepsy. Results We identify a co-expression network of 320 genes (M30), which is significantly enriched for non-synonymous de novo mutations ascertained from patients with monogenic epilepsy, and for common variants associated with polygenic epilepsy. The genes in M30 network are expressed widely in the human brain under tight developmental control, and encode physically interacting proteins involved in synaptic processes. The most highly connected proteins within M30 network are preferentially disrupted by deleterious de novo mutations for monogenic epilepsy, in line with the centrality-lethality hypothesis. Analysis of M30 expression revealed consistent down-regulation in the epileptic brain in heterogeneous forms of epilepsy including human temporal lobe epilepsy, a mouse model of acquired temporal lobe epilepsy, and a mouse model of monogenic Dravet (SCN1A) disease. These results suggest functional disruption of M30 via gene mutation or altered expression as a convergent mechanism regulating susceptibility to epilepsy broadly. Using the large collection of drug-induced gene expression data from Connectivity Map, several drugs were predicted to preferentially restore the down-regulation of M30 in epilepsy toward health, most notably valproic acid, whose effect on M30 expression was replicated in neurons. Conclusions Taken together, our results suggest targeting the expression of M30 as a potential new therapeutic strategy in epilepsy

Author Correction: WWP2 regulates pathological cardiac fibrosis by modulating SMAD2 signaling.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease

Genetic determinants of cognition are poorly characterized, and their relationship to genes that confer risk for neurodevelopmental disease is unclear. Here we performed a systems-level analysis of genome-wide gene expression data to infer gene-regulatory networks conserved across species and brain regions. Two of these networks, M1 and M3, showed replicable enrichment for common genetic variants underlying healthy human cognitive abilities, including memory. Using exome sequence data from 6,871 trios, we found that M3 genes were also enriched for mutations ascertained from patients with neurodevelopmental disease generally, and intellectual disability and epileptic encephalopathy in particular. M3 consists of 150 genes whose expression is tightly developmentally regulated, but which are collectively poorly annotated for known functional pathways. These results illustrate how systems-level analyses can reveal previously unappreciated relationships between neurodevelopmental disease–associated genes in the developed human brain, and provide empirical support for a convergent gene-regulatory network influencing cognition and neurodevelopmental disease

Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus

Peer reviewe

Systems-level analysis of episodic memory performance and neuropsychiatric disease

Episodic memory refers to the ability to store and recall place and time related information. The hippocampus is essential to the encoding of new memories via long-term remodelling of neuronal synapses. However, the understanding of the genetic mechanisms of memory formation and how these genes relate to neuropsychiatric disease is incomplete. In this study, I integrate the information from genome-wide expression patterns from the human hippocampus with multiple genome-wide studies to identify hippocampal gene regulatory networks associated with memory and neuropsychiatric disease. I construct gene co-expression networks from human hippocampi, surgically resected from patients with temporal lobe epilepsy and show that some of these networks are conserved in healthy human brain. By integrating hippocampal gene expression with pre-operative memory performance scores I identify networks whose expression is significantly correlated with memory performance. I then show that the same networks are enriched for common genetic variants (SNP – single nucleotide polymorphisms) associated with verbal recall using data from two independent genome wide association studies (GWAS) of memory. In addition, I integrate hippocampal gene co-expression networks with common variants (SNP) and rare de-novo mutations (DNM) relating to neuropsychiatric disease. These analyses identify two candidate networks of genes co-expressed in the adult human hippocampus (M1 and M3) that may underlie variation in healthy human memory and reveal a convergent gene network for neuropsychiatric disease and memory. This information can be used as a starting point for in vitro and in vivo investigations to identify the genes regulating human memory performance in health and disease.Open Acces

Integrated systems-genetic analyses reveal a network target for delaying glioma progression

OBJECTIVETo identify a convergent, multitarget proliferation characteristic for astrocytoma transformation that could be targeted for therapy discovery.METHODS Using an integrated functional genomics approach, we prioritized networks associated with astrocytoma progression using the following criteria: differential co-expression between grade II and grade III IDH1-mutated and 1p/19q euploid astrocytomas, preferential enrichment for genetic risk to cancer, association with patient survival and sample-level genomic features. Drugs targeting the identified multitarget network characteristic for astrocytoma transformation were computationally predicted using drug transcriptional perturbation data and validated using primary human astrocytoma cells.RESULTS A single network, M2, consisting of 177 genes, was associated with glioma progression on the basis of the above criteria. Functionally, M2 encoded physically interacting proteins regulating cell cycle processes and analysis of genome-wide gene-regulatory interactions using mutual information and DNA-protein interactions revealed the known regulators of cell cycle processes FoxM1, B-Myb, and E2F2 as key regulators of M2. These results suggest functional disruption of M2 via gene mutation or altered expression as a convergent pathway regulating astrocytoma transformation. By considering M2 as a multitarget drug target regulating astrocytoma transformation, we identified several drugs that are predicted to restore M2 expression in anaplastic astrocytoma toward its low-grade profile and of these, we validated the known antiproliferative drug resveratrol as down-regulating multiple nodes of M2 including at nanomolar concentrations achievable in human cerebrospinal fluid by oral dosing.INTERPRETATION Our results identify M2 as a multitarget network characteristic for astrocytoma progression and encourage M2-based drug screening to identify new compounds for preventing glioma transformation.</p

Integrated systems-genetic analyses reveal a network target for delaying glioma progression

OBJECTIVETo identify a convergent, multitarget proliferation characteristic for astrocytoma transformation that could be targeted for therapy discovery.METHODS Using an integrated functional genomics approach, we prioritized networks associated with astrocytoma progression using the following criteria: differential co-expression between grade II and grade III IDH1-mutated and 1p/19q euploid astrocytomas, preferential enrichment for genetic risk to cancer, association with patient survival and sample-level genomic features. Drugs targeting the identified multitarget network characteristic for astrocytoma transformation were computationally predicted using drug transcriptional perturbation data and validated using primary human astrocytoma cells.RESULTS A single network, M2, consisting of 177 genes, was associated with glioma progression on the basis of the above criteria. Functionally, M2 encoded physically interacting proteins regulating cell cycle processes and analysis of genome-wide gene-regulatory interactions using mutual information and DNA-protein interactions revealed the known regulators of cell cycle processes FoxM1, B-Myb, and E2F2 as key regulators of M2. These results suggest functional disruption of M2 via gene mutation or altered expression as a convergent pathway regulating astrocytoma transformation. By considering M2 as a multitarget drug target regulating astrocytoma transformation, we identified several drugs that are predicted to restore M2 expression in anaplastic astrocytoma toward its low-grade profile and of these, we validated the known antiproliferative drug resveratrol as down-regulating multiple nodes of M2 including at nanomolar concentrations achievable in human cerebrospinal fluid by oral dosing.INTERPRETATION Our results identify M2 as a multitarget network characteristic for astrocytoma progression and encourage M2-based drug screening to identify new compounds for preventing glioma transformation.</p

Author Correction: WWP2 regulates pathological cardiac fibrosis by modulating SMAD2 signaling.

An amendment to this paper has been published and can be accessed via a link at the top of the paper