Erratum: Perturbed Microbial Ecology in Myasthenia Gravis: Evidence from the Gut Microbiome and Fecal Metabolome.

[This corrects the article DOI: 10.1002/advs.201901441.].

Perturbed Microbial Ecology in Myasthenia Gravis: Evidence from the Gut Microbiome and Fecal Metabolome.

Myasthenia gravis (MG) is a devastating acquired autoimmune disease. Emerging evidence indicates that the gut microbiome plays a key role in maintaining immune system homeostasis. This work reports that MG is characterized by decreased α-phylogenetic diversity, and significantly disturbed gut microbiome and fecal metabolome. The altered gut microbial composition is associated with fecal metabolome changes, with 38.75% of altered bacterial operational taxonomic units showing significant correlations with a range of metabolite biomarkers. Some microbes are particularly linked with MG severity. Moreover, a combination of microbial makers and their correlated metabolites enable discriminating MG from healthy controls (HCs) with 100% accuracy. To investigate whether disturbed gut mcirobiome might contribute to the onset of MG, germ-free (GF) mice are initially colonized with MG microbiota (MMb) or healthy microbiota (HMb), and then immunized in a classic mouse model of MG. The MMb mice demonstrate substantially impaired locomotion ability compared with the HMb mice. This effect could be reversed by cocolonizing GF mice with both MMb and HMb. The MMb mice also exhibit similar disturbances of fecal metabolic pathways as found in MG. Together these data demonstrate disturbances in microbiome composition and activity that are likely to be relevant to the pathogenesis of MG.

Metabonomics reveals peripheral and central short-chain fatty acid and amino acid dysfunction in a naturally occurring depressive model of macaques.

PURPOSE: Depression is a complex psychiatric disorder. Various depressive rodent models are usually constructed based on different pathogenesis hypotheses. MATERIALS AND METHODS: Herein, using our previously established naturally occurring depressive (NOD) model in a non-human primate (cynomolgus monkey, Macaca fascularis), we performed metabolomics analysis of cerebrospinal fluid (CSF) from NOD female macaques (N=10) and age-and gender-matched healthy controls (HCs) (N=12). Multivariate statistical analysis was used to identify the differentially expressed metabolites between the two groups. Ingenuity Pathways Analysis and MetaboAnalyst were applied for predicted pathways and biological functions analysis. RESULTS: Totally, 37 metabolites responsible for discriminating the two groups were identified. The NOD macaques were mainly characterized by perturbations of fatty acid biosynthesis, ABC transport system, and amino acid metabolism (eg, aspartate, glycine, serine, and threonine metabolism). Interestingly, we found that eight altered CSF metabolites belonging to short-chain fatty acids and amino acids were also observed in the serum of NOD macaques (N=13 per group). CONCLUSION: Our findings suggest that peripheral and central short-chain fatty acids and amino acids are implicated in the onset of depression.

Absence of gut microbiota during early life affects anxiolytic Behaviors and monoamine neurotransmitters system in the hippocampal of mice.

The gut microbiome is composed of an enormous number of microorganisms, generally regarded as commensal bacteria. Resident gut bacteria are an important contributor to health and significant evidence suggests that the presence of healthy and diverse gut microbiota is important for normal cognitive and emotional processing. Here we measured the expression of monoamine neurotransmitter-related genes in the hippocampus of germ-free (GF) mice and specific-pathogen-free (SPF) mice to explore the effect of gut microbiota on hippocampal monoamine functioning. In total, 19 differential expressed genes (Htr7, Htr1f, Htr3b, Drd3, Ddc, Maob, Tdo2, Fos, Creb1, Akt1, Gsk3a, Pik3ca, Pla2g5, Cyp2d22, Grk6, Ephb1, Slc18a1, Nr4a1, Gdnf) that could discriminate between the two groups were identified. Interestingly, GF mice displayed anxiolytic-like behavior compared to SPF mice, which were not reversed by colonization with gut microbiota from SPF mice. Besides, colonization of adolescent GF mice by gut microbiota was not sufficient to reverse the altered gene expression associated with their GF status. Taking these findings together, the absence of commensal microbiota during early life markedly affects hippocampal monoamine gene-regulation, which was associated with anxiolytic behaviors and monoamine neurological signs.

Diagnosis of major depressive disorder based on changes in multiple plasma neurotransmitters: a targeted metabolomics study.

Major depressive disorder (MDD) is a debilitating psychiatric illness. However, there is currently no objective laboratory-based diagnostic tests for this disorder. Although, perturbations in multiple neurotransmitter systems have been implicated in MDD, the biochemical changes underlying the disorder remain unclear, and a comprehensive global evaluation of neurotransmitters in MDD has not yet been performed. Here, using a GC-MS coupled with LC-MS/MS-based targeted metabolomics approach, we simultaneously quantified the levels of 19 plasma metabolites involved in GABAergic, catecholaminergic, and serotonergic neurotransmitter systems in 50 first-episode, antidepressant drug-naïve MDD subjects and 50 healthy controls to identify potential metabolite biomarkers for MDD (training set). Moreover, an independent sample cohort comprising 49 MDD patients, 30 bipolar disorder (BD) patients and 40 healthy controls (testing set) was further used to validate diagnostic generalizability and specificity of these candidate biomarkers. Among the 19 plasma neurotransmitter metabolites examined, nine were significantly changed in MDD subjects. These metabolites were mainly involved in GABAergic, catecholaminergic and serotonergic systems. The GABAergic and catecholaminergic had better diagnostic value than serotonergic pathway. A panel of four candidate plasma metabolite biomarkers (GABA, dopamine, tyramine, kynurenine) could distinguish MDD subjects from health controls with an AUC of 0.968 and 0.953 in the training and testing set, respectively. Furthermore, this panel distinguished MDD subjects from BD subjects with high accuracy. This study is the first to globally evaluate multiple neurotransmitters in MDD plasma. The altered plasma neurotransmitter metabolite profile has potential differential diagnostic value for MDD.

Dietary cholesterol intake and stroke risk: a meta-analysis.

Background/Objectives: The association between dietary cholesterol and stroke risk has remained controversial over the past two decades. The aim of this meta-analysis was to assess the relationship between dietary cholesterol and stroke risk. Results: Seven prospective studies including 269,777 non-overlapping individuals (4,604 strokes) were included. The combined RR of stroke for higher cholesterol intake (> 300 mg/day) was 0.98 (95% CI, 0.90-1.07), and the combined RR of stroke for higher cholesterol intake (> 300 mg/day) in females (age of ≥ 60 years or body mass index of ≥ 24 kg/m2) was 1.18 (95% CI, 1.02-1.36). Materials and Methods: The PubMed, Medline, Embase, Web of Knowledge, and Google Scholar databases were searched. Relevant studies were identified by searching these online databases through September 2017. The relative risk (RR) and 95% confidence interval (CI) were used to investigate the strength of the association. Conclusions: Higher cholesterol intake has no association with the overall stroke risk. Age and body mass index affect the relationship between dietary cholesterol intake and stroke risk. However, the association between higher dietary cholesterol and stroke risk in males remains unclear.