Association analysis between mitogen-activated protein/extracellular signal-regulated kinase (MEK) gene polymorphisms and depressive disorder in the Han Chinese population

A Systematic Review of Candidate Genes for Major Depression

Background and Objectives: The aim of this systematic review was to analyse which candidate genes were examined in genetic association studies and their association with major depressive disorder (MDD). Materials and Methods: We searched PUBMED for relevant studies published between 1 July 2012 and 31 March 2019, using combinations of keywords: “major depressive disorder” OR “major depression” AND “gene candidate”, “major depressive disorder” OR “major depression” AND “polymorphism”. Synthesis focused on assessing the likelihood of bias and investigating factors that may explain differences between the results of studies. For selected gene list after literature overview, functional enrichment analysis and gene ontology term enrichment analysis were conducted. Results: 141 studies were included in the qualitative review of gene association studies focusing on MDD. 86 studies declared significant results (p < 0.05) for 172 SNPs in 85 genes. The 13 SNPs associations were confirmed by at least two studies. The 18 genetic polymorphism associations were confirmed in both the previous and this systematic analysis by at least one study. The majority of the studies (68.79 %) did not use or describe power analysis, which may have had an impact over the significance of their results. Almost a third of studies (N = 54) were conducted in Chinese Han population. Conclusion: Unfortunately, there is still insufficient data on the links between genes and depression. Despite the reported genetic associations, most studies were lacking in statistical power analysis, research samples were small, and most gene polymorphisms have been confirmed in only one study. Further genetic research with larger research samples is needed to discern whether the relationship is random or causal. Summations: This systematic review had summarized all reported genetic associations and has highlighted the genetic associations that have been replicated. Limitations: Unfortunately, most gene polymorphisms have been confirmed only once, so further studies are warranted for replicating these genetic associations. In addition, most studies included a small number of MDD cases that could be indicative for false positive. Considering that polymorphism loci and associations with MDD is also vastly dependent on interpersonal variation, extensive studies of gene interaction pathways could provide more answers to the complexity of MDD.

Construction of gene-classifier and co-expression network analysis of genes in association with major depressive disorder

Because the pathogenesis of major depressive disorder (MDD) is still unclear and the accurate diagnosis remains unavailable, we aimed to analyze its molecular mechanisms and develop a gene classifier to improve diagnostic accuracy. We extracted differentially expressed genes from two datasets, GSE45642 (from brain tissue samples) and GSE98793 (from blood samples), and found three key modules to have a significant correlation with MDD traits by weighted gene coexpression network analysis. Hub genes were identified from the key modules according to the connectivity degree in the network and subjected to least absolute shrinkage and selection operator regression analysis. A total of eighty-five hub genes were selected to construct the gene classifier, which had considerable ability to recognize MDD patients in the training set and test set. In addition, the relationship between the key MDD modules and brain tissues indicated that the anterior cingulate should be a notable region in the study of MDD pathogenesis. The results of Gene Ontology (GO) and pathway enrichment analyses reiterate the relationship between depression and immunity. Therefore we identified MDD hub genes in the InnateDB database, and found 14 genes involved in both MDD and the inflammatory response.

Combination of high-resolution accurate mass spectrometry and network pharmacology provides a new method for the chemical constituents' study and target prediction in vivo of Garcinia multiflora

Garcinia multiflora is a kind of evergreen tree which is widely distributed in the south of China. However, few researches focused on the constituents in different parts of G. multiflora as well as their potential targets and pathways in vivo. To clarify the chemical constituents of G. multiflora rapidly and predict the potential targets as well as pathways in vivo that this plant may have effects on, a feasible and accurate strategy was developed to identify the chemical constituents in fruits, leaves, and branches of G. multiflora by ultra-high performance liquid chromatography with Q-Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry. Network pharmacology was then employed and a "compounds-targets-diseases" network was established. Sixty-one compounds including polycyclic polyprenylated acylphloroglucinols, xanthones, and flavonoids were finally identified in different parts of G. multiflora, and the contents of seven constituents were quantified, respectively. On the basis of the network pharmacology analysis results, compounds in this plant were speculated to have potential pharmacodynamic effect on cancer, inflammatory, respiratory diseases, cardiovascular diseases, and metabolic diseases. This research will provide a new method for the advanced study on the pharmacodynamic materials basis of G. multiflora, and offer valuable evidences for medicinal purpose of this plant.

Synapse-to-Nucleus Signaling in Neurodegenerative and Neuropsychiatric Disorders

Synapse-to-nucleus signaling is critical for converting signals received at synapses into transcriptional programs essential for cognition, memory, and emotion. This neuronal mechanism usually involves activity-dependent translocation of synaptonuclear factors from synapses to the nucleus resulting in regulation of transcriptional programs underlying synaptic plasticity. Acting as synapse-to-nucleus messengers, amyloid precursor protein intracellular domain associated-1 protein, cAMP response element binding protein (CREB)-regulated transcription coactivator-1, Jacob, nuclear factor kappa-light-chain-enhancer of activated B cells, RING finger protein 10, and SH3 and multiple ankyrin repeat domains 3 play essential roles in synapse remodeling and plasticity, which are considered the cellular basis of memory. Other synaptic proteins, such as extracellular signal-regulated kinase, calcium/calmodulin-dependent protein kinase II gamma, and CREB2, translocate from dendrites or cytosol to the nucleus upon synaptic activity, suggesting that they could contribute to synapse-to-nucleus signaling. Notably, some synaptonuclear factors converge on the transcription factor CREB, indicating that CREB signaling is a key hub mediating integration of synaptic signals into transcriptional programs required for neuronal function and plasticity. Although major efforts have been focused on identification and regulatory mechanisms of synaptonuclear factors, the relevance of synapse-to-nucleus communication in brain physiology and pathology is still unclear. Recent evidence, however, indicates that synaptonuclear factors are implicated in neuropsychiatric, neurodevelopmental, and neurodegenerative disorders, suggesting that uncoupling synaptic activity from nuclear signaling may prompt synapse pathology, contributing to a broad spectrum of brain disorders. This review summarizes current knowledge of synapse-to-nucleus signaling in neuron survival, synaptic function and plasticity, and memory. Finally, we discuss how altered synapse-to-nucleus signaling may lead to memory and emotional disturbances, which is relevant for clinical and therapeutic strategies in neurodegenerative and neuropsychiatric diseases.

Approaching to the Essence of Major Depressive Disorder

Major Depressive Disorder (MDD) is a serious neuropsychic disease. It destroys person’s family relationship and social connections seriously. Latest WHO investigation disclosed nearly 4.4% of the population worldwide (approximately 322 million people) were being affected by MDD extensively [1]. While in China, Dong M, et al. reported the occurrence rate of suicide attempt during hospitalization and after the onset of MDD were 17.3% (95% CI: 12.4-23.7%) and 42.1% (95% CI: 26.1-60.0%) respectively [2]. Another research made by Grupta S, et al. announced MDD in urban China might be under-diagnosed and untreated [3].