DNA methylation is a well-studied epigenetic modification in mammals. Changes in the methylation pattern can be associated with various disease states, including psychopathologies. Suicide is a global public health problem, with Slovenia being ranked as one of leading European countries regarding suicide rate. Therefore, we strive to identify biomarkers that would be suitable for clinical use in psychiatry; one possibility could be the use of DNA methylation as a biomarker. Zinc finger 714 (ZNF714) is a protein belonging to a large group of DNA binding proteins, zinc fingers. We have identified ZNF714 as a new candidate gene in a pilot study of a global methylation pattern. Our sample included blood and tissue of four different brain areas (hippocampus, insula, amygdala and Brodmann area 46. Using next-generation targeted bisulfite sequencing we obtained methylation information of a CpG island, residing in the promoter region of ZNF714. We observed significantly decreased levels of methylation in suicide victims in all four brain regions and blood, with highly comparable methylation pattern between all brain regions and blood. When analysing gene expression, in hippocampus there was a significantly higher expression of ZNF714 in suicide victims. With suicidal behaviour and other mental disorders being highly prevalent, the need for additional diagnostics and treatment is grave. ZNF714 could therefore serve as a possible blood biomarker of suicidal behaviour.
COBISS.SI-ID: 41029379
In psychiatry, compared to other medical fields, the identification of biological markers that would complement current clinical interview, and enable more objective and faster clinical diagnosis, implement accurate monitoring of treatment response and remission, is grave. Current technological development enables analyses of various biological marks in high throughput scale at reasonable costs, and therefore 'omic' studies are entering the psychiatry research. However, big data demands a whole new plethora of skills in data processing, before clinically useful information can be extracted. So far the classical approach to data analysis did not really contribute to identification of biomarkers in psychiatry, but the extensive amounts of data might get to a higher level, if artificial intelligence in the shape of machine learning algorithms would be applied. Not many studies on machine learning in psychiatry have been published, but we can already see from that handful of studies that the potential to build a screening portfolio of biomarkers for different psychopathologies, including suicide, exists.
COBISS.SI-ID: 46033411
Background: Given that approximately 70% of miRNAs in the body are neuronal, we critically assessed current studies on miRNAs and suicidal behavior. Materials & Methods: To further define the role of miRNAs in suicide, we searched for studies on extracellular vesicles (exosomes) because miRNAs are particularly enriched in exosomes. miRNAs also have important physiological roles, and they can cross the blood-brain barrier and participate in cell-to-cell communication with both nearby and distant cells. Results & Conclusion: This critical assessment suggests that several miRNAs can be closely related to neurophysiology, suicidal behavior, and psychiatric disorders. However, clear overlap is poor due to either different methodologies applied or to molecular differences between suicidal behaviors and studied psychiatric disorders.
COBISS.SI-ID: 44314627