Integrated Transcriptome Analyses Revealed Key Target Genes in Mouse Models of Autism.
Mouse brain data converge on fifteen genes that may steer future autism studies and treatments.
01Research in Context
What this study did
Duan et al. (2020) merged mouse brain data from several autism models. They ran the numbers to see which genes keep popping up.
The team looked for shared genes across models, not just one strain. They wanted a short list of prime suspects.
What they found
Fifteen genes showed up again and again. Names you might see in future papers include SDC4, GRIN2A, and GABRA2.
These genes sit at synapses and in cell-signaling paths. The authors flag them as top targets for next-step studies.
How this fits with other research
Furukawa et al. (2023) extends this hunt to germ cells. They also used mice but found chromatin and ubiquitin genes, not the synaptic set. Same method, different tissue, fresh angle.
Szoko et al. (2017) warns that proteome work in autism has been small and shaky. Their review reminds us that gene lists from RNA still need protein-level checks.
Griesi-Oliveira et al. (2013) used baby-teeth stem cells instead of brain. Both studies pull transcriptomes for autism clues, showing you can hunt genes without brain biopsies.
Why it matters
You now have a vetted short list of genes to watch. If a parent asks about future bio-markers, you can say researchers are tracking fewer than two dozen strong leads. Keep an eye on GRIN2A and GABRA2; they may show up in medication trials or genetic panels that feed into your behavior plans.
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02At a glance
03Original abstract
Genetic mutations are the major pathogenic factor of Autism Spectrum Disorder (ASD). In recent years, more and more ASD risk genes have been revealed, among which there are a group of transcriptional regulators. Considering the similarity of the core clinical phenotypes, it is possible that these different factors may regulate the expression levels of certain key targets. Identification of these targets could facilitate the understanding of the etiology and developing of novel diagnostic and therapeutic methods. Therefore, we performed integrated transcriptome analyses of RNA-Seq and microarray data in multiple ASD mouse models and identified a number of common downstream genes in various brain regions, many of which are related to the structure and function of the synapse components or drug addiction. We then established protein-protein interaction networks of the overlapped targets and isolated the hub genes by 11 algorithms based on the topological structure of the networks, including Sdc4, Vegfa, and Cp in the Cortex-Adult subgroup, Gria1 in the Cortex-Juvenile subgroup, and Kdr, S1pr1, Ubc, Grm2, Grin2b, Nrxn1, Pdyn, Grin3a, Itgam, Grin2a, Gabra2, and Camk4 in the Hippocampus-Adult subgroup, many of which have been associated with ASD in previous studies. Finally, we cross compared our results with human brain transcriptional data sets and verified several key candidates, which may play important role in the pathology process of ASD, including SDC4, CP, S1PR1, UBC, PDYN, GRIN2A, GABRA2, and CAMK4. In summary, by integrated bioinformatics analysis, we have identified a series of potentially important molecules for future ASD research. Autism Res 2020, 13: 352-368. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Abnormal transcriptional regulation accounts for a significant portion of Autism Spectrum Disorder. In this study, we performed transcriptome analyses of mouse models to identify common downstream targets of transcriptional regulators involved in ASD. We identified several recurrent target genes that are close related to the common pathological process of ASD, including SDC4, CP, S1PR1, UBC, PDYN, GRM2, NRXN1, GRIN3A, ITGAM, GRIN2A, GABRA2, and CAMK4. These results provide potentially important targets for understanding the molecular mechanism of ASD.
Autism research : official journal of the International Society for Autism Research, 2020 · doi:10.1002/aur.2240