ArticleDialogues in clinical neuroscience2019
Use of the epigenetic toolbox to contextualize common variants associated with schizophrenia risk .
Article in Dialogues in clinical neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Epigenetics factors in schizophrenia: future directions for etiologic and therapeutic study approaches.Annals of general psychiatry · 2025Review
- Mapping miRNA Research in Schizophrenia: A Scientometric Review.International journal of molecular sciences · 2022Review
- Article
- Associations between the development of PTSD symptoms and longitudinal changes in the DNA methylome of deployed military servicemen: A comparison with polygenic risk scores.Comprehensive psychoneuroendocrinology · 2020Article
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2 authors.
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Abstract
Schizophrenia is a debilitating psychiatric disorder with a complex genetic architecture and limited understanding of its neuropathology, reflected by the lack of diagnostic measures and effective pharmacological treatments. Geneticists have recently identified more than 145 risk loci comprising hundreds of common variants of small effect sizes, most of which lie in noncoding genomic regions. This review will discuss how the epigenetic toolbox can be applied to contextualize genetic findings in schizophrenia. Progress in next-generation sequencing, along with increasing methodological complexity, has led to the compilation of genome-wide maps of DNA methylation, histone modifications, RNA expression, and more. Integration of chromatin conformation datasets is one of the latest efforts in deciphering schizophrenia risk, allowing the identification of genes in contact with regulatory variants across 100s of kilobases. Large-scale multiomics studies will facilitate the prioritization of putative causal risk variants and gene networks that contribute to schizophrenia etiology, informing clinical diagnostics and treatment downstream. .
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