A pilot exploration of multi-omics research of gut microbiome in major depressive disorders

The pathophysiology of major depressive disorder (MDD) remains obscure. Recently, the microbiota-gut-brain (MGB) axis’s role in MDD has an increasing attention. However, the specific mechanism of the multi-level effects of gut microbiota on host metabolism, immunity, and brain structure is unclear. Multi-omics approaches based on the analysis of different body fluids and tissues using a variety of analytical platforms have the potential to provide a deeper understanding of MGB axis disorders. Therefore, the data of metagenomics, metabolomic, inflammatory factors, and MRI scanning are collected from the two groups including 24 drug-naïve MDD patients and 26 healthy controls (HCs). Then, the correlation analysis is performed in all omics. The results confirmed that there are many markedly altered differences, such as elevated Actinobacteria abundance, plasma IL-1β concentration, lipid, vitamin, and carbohydrate metabolism disorder, and diminished grey matter volume (GMV) of inferior frontal gyrus (IFG) in the MDD patients. Notably, three kinds of discriminative bacteria, Ruminococcus bromii, Lactococcus chungangensis, and Streptococcus gallolyticus have an extensive correlation with metabolome, immunology, GMV, and clinical symptoms. All three microbiota are closely related to IL-1β and lipids (as an example, phosphoethanolamine (PEA)). Besides, Lactococcus chungangensis is negatively related to the GMV of left IFG. Overall, this study demonstrate that the effects of gut microbiome exert in MDD is multifactorial.

Age-associated network controllability changes in first episode drug-naïve schizophrenia

Background Recent neuroimaging studies revealed dysregulated neurodevelopmental, or/and neurodegenerative trajectories of both structural and functional connections in schizophrenia. However, how the alterations in the brain’s structural connectivity lead to dynamic function changes in schizophrenia with age remains poorly understood. Methods Combining structural magnetic resonance imaging and a network control theory approach, the white matter network controllability metric (average controllability) was mapped from age 16 to 60 years in 175 drug-naïve schizophrenia patients and 155 matched healthy controls. Results Compared with controls, the schizophrenia patients demonstrated the lack of age-related decrease on average controllability of default mode network (DMN), as well as the right precuneus (a hub region of DMN), suggesting abnormal maturational development process in schizophrenia. Interestingly, the schizophrenia patients demonstrated an accelerated age-related decline of average controllability in the subcortical network, supporting the neurodegenerative model. In addition, compared with controls, the lack of age-related increase on average controllability of the left inferior parietal gyrus in schizophrenia patients also suggested a different pathway of brain development. Conclusions By applying the control theory approach, the present study revealed age-related changes in the ability of white matter pathways to control functional activity states in schizophrenia. The findings supported both the developmental and degenerative hypotheses of schizophrenia, and suggested a particularly high vulnerability of the DMN and subcortical network possibly reflecting an illness-related early marker for the disorder.

Identifying a Whole-brain Connectome-based Model in Drug-naïve Parkinson’s Disease for Predicting Motor Impairment

Identifying a whole-brain connectome-based predictive model in drug-naïve patients with Parkinson’s disease and verifying its predictions on drug-managed patients would be useful in determining the intrinsic functional underpinnings of motor impairment and establishing general brain-behavior associations. In this study, we constructed a predictive model from the resting-state functional data of 47 drug-naïve patients by using a connectome-based approach. This model was subsequently validated in 115 drug-managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson’s Disease Rating Scale Part III scores. The predictive performance of model was evaluated using the correlation coefficient (rtrue) between predicted and observed scores. As a result, a connectome-based model for predicting individual motor impairment in drug-naïve patients was identified with significant performance (rtrue = 0.845, p < 0.001, ppermu = 0.002). Two patterns of connection were identified according to correlations between connection strength and the severity of motor impairment. The negative motor-impairment-related network contained more within-network connections in the motor, visual-related, and default mode networks, whereas the positive motor-impairment-related network was constructed mostly with between-network connections coupling the motor-visual, motor-limbic, and motor-basal ganglia networks. Finally, this predictive model constructed around drug-naïve patients was confirmed with significant predictive efficacy on drug-managed patients (r = 0.209, p = 0.025), suggesting a generalizability in Parkinson’s disease patients under long-term drug influence. In conclusion, this study identified a whole-brain connectome-based model that could predict the severity of motor impairment in Parkinson’s patients and furthers our understanding of the functional underpinnings of the disease.

Long-Range White Matter Microstructural Alterations in Drug-Naive Children with Attention Deficit Hyperactivity Disorder: A Tract-Based Spatial Statistics Study

Background Microstructural changes might underlie white matter (WM) pathology in attention deficit hyperactivity disorder (ADHD). To investigate WM alterations, particularly the changes in long-range fibers, in drug-naive children with ADHD, we conducted tract-based spatial statistics (TBSS) analysis on diffusion tensor imaging (DTI) data. Materials and Methods In this study, 57 children with ADHD and 41 healthy controls (HCs) were enrolled. None of the enrolled ADHD children received any medication before data collection. The difference in fractional anisotropy (FA), and in mean (MD), axial (AD), and radial diffusivity (RD) between both groups were calculated using TBSS. WM changes were then correlated with clinical symptoms, including the hyperactivity index score and the impulsivity score. Results Whole-skeleton analysis identified several long-range fibers of decreased FA and increased RD in the ADHD group as compared to the HC group. ADHD children demonstrated decreased FA in the right corpus callosum (CC) splenium, left inferior fronto-occipital fasciculus, and intersection of the anterior and posterior internal capsule. Moreover, higher RD was observed in the right CC splenium, superior longitudinal fasciculus, and posterior corona radiata. No regions of increased FA or reduced RD were observed, and no differences in MD or AD were noted. Conclusion Our results demonstrate that microstructural WM alterations and changes in the long-range WM connections are present in children with ADHD. We speculate that these changes may relate to the symptoms of hyperactivity and impulsivity.

Potential Associations of Mutations within the HIV-1 Env and Gag Genes Conferring Protease Inhibitor (PI) Drug Resistance

An increasing number of patients in Africa are experiencing virological failure on a second-line antiretroviral protease inhibitor (PI)-containing regimen, even without resistance-associated mutations in the protease region, suggesting a potential role of other genes in PI resistance. Here, we investigated the prevalence of mutations associated with Lopinavir/Ritonavir (LPV/r) failure in the Envelope gene and the possible coevolution with mutations within the Gag-protease (gag-PR) region. Env and Gag-PR sequences generated from 24 HIV-1 subtype C infected patients failing an LPV/r inclusive treatment regimen and 344 subtype C drug-naïve isolates downloaded from the Los Alamos Database were analyzed. Fisher’s exact test was used to determine the differences in mutation frequency. Bayesian network probability was applied to determine the relationship between mutations occurring within the env and gag-PR regions and LPV/r treatment. Thirty-five mutations in the env region had significantly higher frequencies in LPV/r-treated patients. A combination of Env and Gag-PR mutations was associated with a potential pathway to LPV/r resistance. While Env mutations were not directly associated with LPV/r resistance, they may exert pressure through the Gag and minor PR mutation pathways. Further investigations using site-directed mutagenesis are needed to determine the impact of Env mutations alone and in combination with Gag-PR mutations on viral fitness and LPV/r efficacy.

NLRP3 Influences Cognitive Function in Schizophrenia in Han Chinese

It has been proposed that immune abnormalities may be implicated with pathophysiology of schizophrenia. The nod-like receptor pyrin domain-contraining protein 3 (NLRP3) can trigger immune-inflammatory cascade reactions. In this study, we intended to identify the role of gene encoding NLRP3 (NLRP3) in susceptibility to schizophrenia and its clinical features. For the NLRP3 mRNA expression analysis, 53 drug-naïve patients with first-episode schizophrenia and 56 healthy controls were enrolled. For the genetic study, a total of 823 schizophrenia patients and 859 controls were recruited. Among them, 239 drug-naïve patients with first-episode schizophrenia were enrolled for clinical evaluation. There is no significant difference in NLRP3 mRNA levels between patients with schizophrenia and healthy controls (p = 0.07). We did not observe any significant differences in allele and genotype frequencies of rs10754558 polymorphism between the schizophrenia and control groups. We noticed significant differences in the scores of RBANS attention and total scores between the patients with different genotypes of rs10754558 polymorphism (p = 0.001 and p &lt; 0.01, respectively). Further eQTL analysis presented a significant association between the rs10754558 polymorphism and NLRP3 in frontal cortex (p = 0.0028, p = 0.028 after Bonferroni correction). Although our findings did not support NLRP3 confer susceptibility to schizophrenia, NLRP3 may be a risk factor for cognitive impairment, especially attention deficit in this disorder.

Is Gut Microbiota a Key Player in Epilepsy Onset? A Longitudinal Study in Drug-Naive Children

Microbiota alterations have been recently investigated in individuals with epilepsy and in other neurological diseases as environmental factors that play a role, by acting through the gut-brain axis, in the pathological process. Most studies focus on the contribution of bacterial communities in refractory epilepsy and suggest a beneficial role of ketogenic diet in modulating the gut microbiota and seizure occurrence. However, they do not evaluate whether epilepsy itself alters the gut microbiota in these patients or if the gut microbial communities could contribute as a seizure trigger. In this pilot study, we performed 16S rRNA sequencing and investigated the gut microbial communities of eight children at their seizure onset and after anti-seizure was started (one year follow-up) and we compared microbial data with seven healthy children, age- and sex-matched. In drug-naive subjects, we observed a microbial signature that shared several features with those reported in refractory epilepsy, such as an increased abundance in Akkermansia spp. and Proteobacteria and a decreased relative abundance in Faecalibacterium spp.We suggest that a bacterial-mediated proinflammatory milieu could contribute to seizure occurrence in children with new onset of epilepsy, as already reported for individuals with drug-resistant epilepsy, and that it could vary during treatment in those who are drug-responsive.