Gut microbiota alterations might affect the development of Alzheimer's disease (AD) through microbiota-derived metabolites. For example, microbiota-derived Indoles via tryptophan metabolism prevented Aβ accumulation and Tau hyperphosphorylation, restored synaptic plasticity, and then promoted the cognitive and behavioral ability of APP/PS1 mice. The imbalanced compositions of Indoles-producing bacteria with tryptophan deficiency were found in male APP/PS1 mice, but the molecular mechanisms remained unclear. Our current study revealed that Indoles (including indole, indole-3-acetic acid and indole-3-propionic acid) upregulated the production of aryl hydrocarbon receptor (AhR), inhibited the activation of the NF-κB signal pathway as well as the formation of the NLRP3 inflammasome, reduced the release of inflammatory cytokines, including TNF-α, IL-6, IL-1β and IL-18, alleviating the inflammatory response of APP/PS1 mice. These findings demonstrated the roles of Indoles-producing bacteria in activating the AhR pathway to regulate neuroinflammation of AD through gut microbiota-derived Indoles, which implied a novel way for AD treatment.

Read the full review for this F1000Prime recommended article: Omega-3 fatty acids for major depressive disorder during pregnancy: results from a randomized, double-blind, placebo-controlled trial.

Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) can exert antidepressant, anti-inflammatory and neuroprotective properties, but the exact molecular mechanism underlying their effects is still not fully understood. We conducted both in vitro and clinical investigations to test which EPA or DHA metabolites are involved in these anti-inflammatory, neuroprotective and antidepressant effects. In vitro, we used the human hippocampal progenitor cell line HPC0A07/03C, and pre-treated cells with either EPA or DHA, followed by interleukin 1beta (IL1β), IL6 and interferon-alpha (IFN-α). Both EPA and DHA prevented the reduction in neurogenesis and the increase in apoptosis induced by these cytokines; moreover, these effects were mediated by the lipoxygenase (LOX) and cytochrome P450 (CYP450) EPA/DHA metabolites, 5-hydroxyeicosapentaenoic acid (HEPE), 4-hydroxydocosahexaenoic acid (HDHA), 18-HEPE, 20-HDHA, 17(18)-epoxyeicosatetraenoic acid (EpETE) and 19(20)-epoxydocosapentaenoic acid (EpDPA), detected here for the first time in human hippocampal neurones using mass spectrometry lipidomics of the supernatant. In fact, like EPA/DHA, co-treatment with these metabolites prevented cytokines-induced reduction in neurogenesis and apoptosis. Moreover, co-treatment with 17(18)-EpETE and 19(20)-EpDPA and the soluble epoxide hydroxylase (sEH) inhibitor, TPPU (which prevents their conversion into dihydroxyeicosatetraenoic acid (DiHETE)/ dihydroxydocosapentaenoic acid (DiHDPA) metabolites) further enhanced their neurogenic and anti-apoptotic effects. Interestingly, these findings were replicated in a sample of n = 22 patients with a DSM-IV Major Depressive Disorder, randomly assigned to treatment with either EPA (3.0 g/day) or DHA (1.4 g/day) for 12 weeks, with exactly the same LOX and CYP450 lipid metabolites increased in the plasma of these patients following treatment with their precursor, EPA or DHA, and some evidence that higher levels of these metabolites were correlated with less severe depressive symptoms. Overall, our study provides the first evidence for the relevance of LOX- and CYP450-derived EPA/DHA bioactive lipid metabolites as neuroprotective molecular targets for human hippocampal neurogenesis and depression, and highlights the importance of sEH inhibitors as potential therapeutic strategy for patients suffering from depressive symptoms.

ChatGPT has sparked extensive discussions within the healthcare community since its November 2022 release. However, potential applications in the field of psychiatry have received limited attention. Deep learning has proven beneficial to psychiatry, and GPT is a powerful deep learning‐based language model with immense potential for this field. Despite the convenience of ChatGPT, this advanced chatbot currently has limited practical applications in psychiatry. It may be used to support psychiatrists in routine tasks such as completing medical records, facilitating communications between clinicians and with patients, polishing academic writings and presentations, and programming and performing analyses for research. The current training and application of ChatGPT require using appropriate prompts to maximize appropriate outputs and minimize deleterious inaccuracies and phantom errors. Moreover, future GPT advances that incorporate empathy, emotion recognition, personality assessment, and detection of mental health warning signs are essential for its effective integration into psychiatric care. In the near future, developing a fully‐automated psychotherapy system trained for expert communication (such as psychotherapy verbatim) is conceivable by building on foundational GPT technology. This dream system should integrate practical ‘real world’ inputs and friendly AI user and patient interfaces via clinically validated algorithms, voice comprehension/generation modules, and emotion discrimination algorithms based on facial expressions and physiological inputs from wearable devices. In addition to the technology challenges, we believe it is critical to establish generally accepted ethical standards for applying ChatGPT‐related tools in all mental healthcare environments, including telemedicine and academic/training settings.