Distinct proteomic profiles in prefrontal subareas of elderly major depressive disorder and bipolar disorder patients

Omics Approaches to Investigate the Pathogenesis of Suicide

Suicide is the second leading cause of death in U.S. adolescents and young adults and is generally associated with a psychiatric disorder. Suicidal behavior has a complex etiology and pathogenesis. Moderate heritability suggests genetic causes. Associations between childhood and recent life adversity indicate contributions from epigenetic factors. Genomic contributions to suicide pathogenesis remain largely unknown. This article is based on a workshop held to design strategies to identify molecular drivers of suicide neurobiology that would be putative new treatment targets. The panel determined that while bulk tissue studies provide comprehensive information, single-nucleus approaches that identify cell type-specific changes are needed. While single-nuclei techniques lack information on cytoplasm, processes, spines, and synapses, spatial multiomic technologies on intact tissue detect cell alterations specific to brain tissue layers and subregions. Because suicide has genetic and environmental drivers, multiomic approaches that combine cell type-specific epigenome, transcriptome, and proteome provide a more complete picture of pathogenesis. To determine the direction of effect of suicide risk gene variants on RNA and protein expression and how these interact with epigenetic marks, single-nuclei and spatial multiomics quantitative trait loci maps should be integrated with whole-genome sequencing and genome-wide association databases. The workshop concluded with a recommendation for the formation of an international suicide biology consortium that will bring together brain banks and investigators with expertise in cutting-edge omics technologies to delineate the biology of suicide and identify novel potential treatment targets to be tested in cellular and animal models for drug and biomarker discovery to guide suicide prevention.

ProMENDA: an updated resource for proteomic and metabolomic characterization in depression

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

Olink proteomics analysis uncovers inflammatory proteins in patients with different states of bipolar disorder

STUDY DESIGN

A prospective study.

BACKGROUND

This study aims to investigate the relationship between different states of bipolar disorder (BD) and plasma inflammatory proteins, which may be used as their biomarkers.

MATERIALS AND METHODS

We totally collected admission plasma from 16 healthy subjects and 32 BD patients, including 16 patients with BD manic episodes (BD-M) and 16 patients with BD depressive episodes (BD-D). Ten samples in each group were analyzed by proximity extension assays of 92 inflammation-related proteins, and all samples were verified by ELISA. Receiver-operating characteristic (ROC) curve analysis was performed to identify the diagnostic ability and cut-off values of potential biomarkers.

RESULTS

Our findings showed that BD patients had significantly higher levels of IL6, MCP-1, TGF-α, IL8, and IL10-RB in comparison with healthy subjects, and their cut-off values were 0.531 pg/ml, 0.531 pg/ml, 0.469 pg/ml, 0.406 pg/ml, and 0.406 pg/ml, respectively. The levels of IL6, MCP-1, TGF-α, and IL8 in BD-M patients were significantly greater than in healthy individuals, and their cut-off values were 0.813 pg/ml, 0.688 pg/ml, 0.438 pg/ml, and 0.625 pg/ml, respectively. Moreover, we found cut-off values of 0.500 pg/mL and 0.688 ng/mL for TGF-α and β-NGF, respectively, even though the levels in the BD-D group were much higher than in the control group. Furthermore, BD-M patients had significantly higher levels of IL6, FGF-19, IFN-γ, and IL-17C in comparison with BD-D patients. Likewise, 0.687 pg/ml, 0.500 pg/ml, 0.438 pg/ml, and 0.375 pg/ml were their cut-off values, respectively. Our findings also showed that the combination of these proteins had the highest diagnostic accuracy.

CONCLUSIONS

Our findings showed that plasma inflammatory proteins were related to BD and its subtypes, which may be utilized as potential biomarkers of different stages of BD. Furthermore, we also found their cut-off values and their combinations to have the highest diagnostic accuracy, providing clinicians with a new method to rapidly differentiate BD and its subtypes and manage early targeted interventions.

A novel Mediterranean diet-inspired supplement ameliorates cognitive, microbial, and metabolic deficits in a mouse model of low-grade inflammation

The Mediterranean diet (MD) and its bioactive constituents have been advocated for their neuroprotective properties along with their capacity to affect gut microbiota speciation and metabolism. Mediated through the gut brain axis, this modulation of the microbiota may partly contribute to the neuroprotective properties of the MD. To explore this potential interaction, we evaluated the neuroprotective properties of a novel bioactive blend (Neurosyn240) resembling the Mediterranean diet in a rodent model of chronic low-grade inflammation. Behavioral tests of cognition, brain proteomic analysis, 16S rRNA sequencing, and 1H NMR metabolomic analyses were employed to develop an understanding of the gut-brain axis interactions involved. Recognition memory, as assessed by the novel object recognition task (NOR), decreased in response to LPS insult and was restored with Neurosyn240 supplementation. Although the open field task performance did not reach significance, it correlated with NOR performance indicating an element of anxiety related to this cognitive change. Behavioral changes associated with Neurosyn240 were accompanied by a shift in the microbiota composition which included the restoration of the Firmicutes: Bacteroidota ratio and an increase in Muribaculum, Rikenellaceae Alloprevotella, and most notably Akkermansia which significantly correlated with NOR performance. Akkermansia also correlated with the metabolites 5-aminovalerate, threonine, valine, uridine monophosphate, and adenosine monophosphate, which in turn significantly correlated with NOR performance. The proteomic profile within the brain was dramatically influenced by both interventions, with KEGG analysis highlighting oxidative phosphorylation and neurodegenerative disease-related pathways to be modulated. Intriguingly, a subset of these proteomic changes simultaneously correlated with Akkermansia abundance and predominantly related to oxidative phosphorylation, perhaps alluding to a protective gut-brain axis interaction. Collectively, our results suggest that the bioactive blend Neurosyn240 conferred cognitive and microbiota resilience in response to the deleterious effects of low-grade inflammation.

Biomarkers in psychiatric disorders

Psychiatric disorders represent a significant socioeconomic and healthcare burden worldwide. Of these, schizophrenia, bipolar disorder, major depressive disorder and anxiety are among the most prevalent. Unfortunately, diagnosis remains problematic and largely complicated by the lack of disease specific biomarkers. Accordingly, much research has focused on elucidating these conditions to more fully understand underlying pathophysiology and potentially identify biomarkers, especially those of early stage disease. In this chapter, we review current status of this endeavor as well as the potential development of novel biomarkers for clinical applications and future research study.

Network analysis of plasma proteomes in affective disorders

The conventional differentiation of affective disorders into major depressive disorder (MDD) and bipolar disorder (BD) has insufficient biological evidence. Utilizing multiple proteins quantified in plasma may provide critical insight into these limitations. In this study, the plasma proteomes of 299 patients with MDD or BD (aged 19-65 years old) were quantified using multiple reaction monitoring. Based on 420 protein expression levels, a weighted correlation network analysis was performed. Significant clinical traits with protein modules were determined using correlation analysis. Top hub proteins were determined using intermodular connectivity, and significant functional pathways were identified. Weighted correlation network analysis revealed six protein modules. The eigenprotein of a protein module with 68 proteins, including complement components as hub proteins, was associated with the total Childhood Trauma Questionnaire score (r = -0.15, p = 0.009). Another eigenprotein of a protein module of 100 proteins, including apolipoproteins as hub proteins, was associated with the overeating item of the Symptom Checklist-90-Revised (r = 0.16, p = 0.006). Functional analysis revealed immune responses and lipid metabolism as significant pathways for each module, respectively. No significant protein module was associated with the differentiation between MDD and BD. In conclusion, childhood trauma and overeating symptoms were significantly associated with plasma protein networks and should be considered important endophenotypes in affective disorders.

Combined fractional anisotropy and subcortical volumetric deficits in patients with mild-to-moderate depression: Evidence from the treatment of antidepressant traditional Chinese medicine

Numerous neuroimaging studies have demonstrated that diverse brain structural plasticity could occur in a human brain during a depressive episode. However, there is a lack of knowledge regarding the underlying mechanisms of mild-to-moderate depression (MMD), especially the changes of brain structural characteristics after treatment with the Shuganjieyu capsule (SG), a kind of traditional Chinese medicine that has been recommended for the specialized treatment of MMD. In this study, we investigated the structural brain plasticity in MMD that have been undergoing 8 weeks of SG treatment compared with age- and sex-matched healthy controls (HCs) and assessed the relationship between these brain structural alternations and clinical symptoms in MMD. At the baseline, we found that: (1) fractional anisotropy (FA) values in patients with MMD were found to be significantly increased in the regions of anterior limb of internal capsule (ALIC) [MNI coordinates: Peak (x/y/z) = 102, 126, 77; MMD FA_peak (Mean ± SD) = 0.621 ± 0.043; HCs FA_peak (Mean ± SD) = 0.524 ± 0.052; MMD > HCs, t = 9.625, p < 0.001] and posterior limb of internal capsule (PLIC) [MNI coordinates: Peak (x/y/z) = 109, 117, 87; MMD FA_peak (Mean ± SD) = 0.694 ± 0.042; HCs FA_peak (Mean ± SD) = 0.581 ± 0.041; MMD > HCs, t = 12.90, p < 0.001], and FA values were significantly positively correlated with HAMD scores in patients with MMD. (2) Patients with MMD showed smaller gray matter volume (GMV) of the dorsolateral prefrontal cortex (DLPFC), frontal cortex, occipital cortex, and precuneus, and the GMV of DLPFC was negatively correlated with HAMD scores. After SG treatment, we found that (1) the HAMD scores decreased; (2) FA values were significantly decreased in the regions of the ALIC and PLIC compared to those at baseline and TBSS revealed no significant differences in FA values between patients with MMD and HCs. (3) The structural characteristics of DLPFC in patients with MMD obtained at the 8th week were improved, e.g., no significant differences in GMV of DLPFC between the two groups. Taken together, our results provided neuroimaging evidence suggesting that SG is an effective treatment for patients with MMD. Moreover, alterations of GMV after 8 weeks of SG treatment indicated a potential modulation mechanism in brain structural plasticity within the DLPFC in patients with MMD.