Mental Depressive Disorder (MDD) is a serious mental disease with high morbidity and suicide rate. To the present, there is still a lack of reliable and reproducible biomarkers for diagnosis and treatment. Findings of genetic, epigenetic, proteome, metabolome and neuroimaging can help to explore relevant biomarker. Moreover, some new testing techniques and analysis methods will contribute to progress in this important area including single-cell sequencing, multi-omics analysis and machine learning-based algorithms to construct models for diagnosis and prediction of treatment response. More research in this area is needed to identify promising biomarkers.
The goal of this research topic is to highlight objective diagnostic and/or prognostic biomarkers, especially genetic, epigenetic, proteome, metabolome and neuroimaging findings. This can be used to assist diagnosis, provide prognostic value, or explore biological targets for treatment intervention. Research based on multi-omics analysis and machine learning algorithms are especially welcome.
We invite submissions including but not limited to original research articles, reviews and meta-analyses to provide new evidence on the following:
• Risk and protective factors of MDD including demographics and biosignatures.
• Diagnostic and prognostic biomarkers of MDD related to genetic, epigenetic, proteome, metabolome, gut microbiota and neuroimaging findings.
• Predictors of treatment response and adverse reactions for antidepressants, ECT and neuromodulation.
• Biomarkers of cognitive impairment, suicide and rhythm disturbances in patients with MDD.
• Animal research to explore the neurobiological mechanisms of depression and candidate antidepressant targets.
Mental Depressive Disorder (MDD) is a serious mental disease with high morbidity and suicide rate. To the present, there is still a lack of reliable and reproducible biomarkers for diagnosis and treatment. Findings of genetic, epigenetic, proteome, metabolome and neuroimaging can help to explore relevant biomarker. Moreover, some new testing techniques and analysis methods will contribute to progress in this important area including single-cell sequencing, multi-omics analysis and machine learning-based algorithms to construct models for diagnosis and prediction of treatment response. More research in this area is needed to identify promising biomarkers.
The goal of this research topic is to highlight objective diagnostic and/or prognostic biomarkers, especially genetic, epigenetic, proteome, metabolome and neuroimaging findings. This can be used to assist diagnosis, provide prognostic value, or explore biological targets for treatment intervention. Research based on multi-omics analysis and machine learning algorithms are especially welcome.
We invite submissions including but not limited to original research articles, reviews and meta-analyses to provide new evidence on the following:
• Risk and protective factors of MDD including demographics and biosignatures.
• Diagnostic and prognostic biomarkers of MDD related to genetic, epigenetic, proteome, metabolome, gut microbiota and neuroimaging findings.
• Predictors of treatment response and adverse reactions for antidepressants, ECT and neuromodulation.
• Biomarkers of cognitive impairment, suicide and rhythm disturbances in patients with MDD.
• Animal research to explore the neurobiological mechanisms of depression and candidate antidepressant targets.