Since the end of December 2019, the Chinese city of Wuhan has reported a novel pneumonia caused by coronavirus disease 2019 (COVID-19), which is spreading domestically and internationally.¹ The virus has been named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this report, we will refer to the disease, COVID-19. According to data released by the National Health Commission of China, the number of confirmed cases in mainland China has increased to 80 151 as of March 2, 2020,² and confirmed cases have been reported in more than a dozen other countries. Moreover, person-to-person transmission has been recorded outside mainland China.³ On January 30, 2020, the World Health Organization held an emergency meeting and declared the global COVID-19 outbreak a public health emergency of international concern.⁴

Non-suicidal self-injury (NSSI) in adolescents is a significant mental health problem around the world. Here, we performed a meta-analysis to systematically delineate the risk factors for NSSI. We searched Medline, Embase, Web of Science and Cochrane for relevant articles and abstracts published prior to 12 November 2021. Pooled odds ratios (ORs) and 95% confident intervals (CIs) were used to assess various risk factors, and publication bias was assessed by Egger's test, the trim and fill method and meta-regression. This study is registered with PROSPERO, CRD42021265885. A total of 25 articles were eventually included in the analysis. Eighty risk factors were identified and classified into 7 categories: mental disorders (ORs, 1·89; 95% CI, 1·60–2·24), bullying (ORs, 1·98; 95% CI, 1·32–2·95), low health literacy (ORs, 2·20; 95% CI, 1·63–2·96), problem behaviours (ORs, 2·36; 95% CI, 2·00–2·77), adverse childhood experiences (ORs, 2·49; 95% CI, 1·85–3.34), physical symptoms (ORs, 2·85; 95% CI, 1·36–5·97) and the female gender (ORs, 2·89; 95% CI, 2·43–3·43). The range of heterogeneity (I²) was from 20·3% to 99·2%. This meta-analysis found that mental disorders, low health literacy, adverse childhood experiences, bullying, problem behaviours, the female gender and physical symptoms appear to be risk factors for NSSI.

Gut microbiota plays an important role in the bidirectional communication between the gut and the central nervous system. Mounting evidence suggests that gut microbiota can influence the brain function via neuroimmune and neuroendocrine pathways as well as the nervous system. Advances in gene sequencing techniques further facilitate investigating the underlying relationship between gut microbiota and psychiatric disorders. In recent years, researchers have preliminarily explored the gut microbiota in patients with mood disorders. The current review aims to summarize the published human studies of gut microbiota in mood disorders. The findings showed that microbial diversity and taxonomic compositions were significantly changed compared with healthy individuals. Most of these findings revealed that short-chain fatty acids-producing bacterial genera were decreased, while pro-inflammatory genera and those involved in lipid metabolism were increased in patients with depressive episodes. Interestingly, the abundance of Actinobacteria, Enterobacteriaceae was increased and Faecalibacterium was decreased consistently in patients with either bipolar disorder or major depressive disorder. Some studies further indicated that specific bacteria were associated with clinical characteristics, inflammatory profiles, metabolic markers, and pharmacological treatment. These studies present preliminary evidence of the important role of gut microbiota in mood disorders, through the brain-gut-microbiota axis, which emerges as a promising target for disease diagnosis and therapeutic interventions in the future.

Discriminating depressive episodes of bipolar disorder (BD) from major depressive disorder (MDD) is a major clinical challenge. Recently, gut microbiome alterations are implicated in these two mood disorders; however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, using 16S ribosomal RNA (rRNA) gene sequencing, the microbial compositions of 165 subjects with MDD are compared with 217 BD, and 217 healthy controls (HCs). It is found that the microbial compositions are different between the three groups. Compared to HCs, MDD is characterized by altered covarying operational taxonomic units (OTUs) assigned to the Bacteroidaceae family, and BD shows disturbed covarying OTUs belonging to Lachnospiraceae, Prevotellaceae, and Ruminococcaceae families. Furthermore, a signature of 26 OTUs is identified that can distinguish patients with MDD from those with BD or HCs, with area under the curve (AUC) values ranging from 0.961 to 0.986 in discovery sets, and 0.702 to 0.741 in validation sets. Moreover, 4 of 26 microbial markers correlate with disease severity in MDD or BD. Together, distinct gut microbial compositions are identified in MDD compared to BD and HCs, and a novel marker panel is provided for distinguishing MDD from BD based on gut microbiome signatures.

中文概要