Background: Parkinson’s disease (PD) is a prevalent neurological disease in the elderly with increasing morbidity and mortality. Despite enormous efforts, rapid and accurate diagnosis of PD is still compromised. Metabolomics defines the final readout of genome-environment interactions through the analysis of the entire metabolic profile in biological matrices. Recently, unbiased metabolic profiling of human sample has been initiated to identify novel PD metabolic biomarkers and dysfunctional metabolic pathways, however, it remains a challenge to define reliable biomarker(s) for clinical use.Methods: We presented a comprehensive metabolic evaluation for identifying crucial metabolic disturbances in PD using liquid chromatography-high resolution mass spectrometry-based metabolomics approach. Plasma samples from 3 independent cohorts (n = 460, 223 PD, 169 healthy controls (HCs) and 68 PD-unrelated neurological disease controls) were collected for the characterization of metabolic changes resulted from PD, antiparkinsonian treatment and potential interferences of other diseases. Unbiased multivariate and univariate analyses were performed to determine the most promising metabolic signatures from all metabolomic datasets. Multiple linear regressions were applied to investigate the associations of metabolites with age, duration time and stage of PD. The combinational biomarker model established by binary logistic regression analysis was validated by 3 cohorts.Results: A list of metabolites including amino acids, acylcarnitines, organic acids, steroids, amides, and lipids from human plasma of 3 cohorts were identified. Compared with HC, we observed significant reductions of fatty acids (FFAs) and caffeine metabolites, elevations of bile acids and microbiota-derived deleterious metabolites, and alterations in steroid hormones in drug-naïve PD. Additionally, we found that L-dopa treatment could affect plasma metabolome involved in phenylalanine and tyrosine metabolism and alleviate the elevations of bile acids in PD. Finally, a metabolite panel of 4 biomarker candidates, including FFA 10:0, FFA 12:0, indolelactic acid and phenylacetyl-glutamine was identified based on comprehensive discovery and validation workflow. This panel showed favorable discriminating power for PD.Conclusions: This study may help improve our understanding of PD etiopathogenesis and facilitate target screening for therapeutic intervention. The metabolite panel identified in this study may provide novel approach for the clinical diagnosis of PD in the future.

Traumatic brain injury (TBI) occurs in response to an acute insult to the head and is recognized as a major risk factor for Alzheimer’s disease (AD). Indeed, recent studies have suggested a pathological overlap between TBI and AD, with both conditions exhibiting amyloid-beta (Aβ) deposits, tauopathy, and neuroinflammation. Additional studies involving animal models of AD indicate that some AD-related genotypic determinants may be critical factors enhancing temporal and phenotypic symptoms of TBI. Thus in the present study, we examined sub-acute effects of moderate TBI delivered by a gas-driven shock tube device in Aβ depositing Tg2576 mice. Three days later, significant increases in b-amyloid deposition, glycogen synthase-3 (GSK-3) activation, phospho-tau, and pro-inflammatory cytokines were observed. Importantly, peripheral treatment with the naturally occurring flavonoid, luteolin, significantly abolished these accelerated pathologies. This study lays the groundwork for a safe and natural compound that could prevent or treat TBI with minimal or no deleterious side effects in combat personnel and others at risk or who have experienced TBI.

Alzheimer's disease (AD) is the most common neurodegenerative disease mainly caused by abnormal tau phosphorylation, amyloid β (Aβ) deposition and neuroinflammation. As an important environmental factor, hypoxia has been reported to aggravate AD via exacerbating Aβ and tau pathologies. However, the link between hypoxia and neuroinflammation, especially the changes of pro-inflammatory M1 or anti-inflammation M2 microglia phenotypes in AD, is still far from being clearly investigated. Here, we evaluated the activation of microglia in the brains of APPswe/PS1dE9 transgenic (Tg) mice and their wild type (Wt) littermates, after a single episode of acute hypoxia (24 hours) exposure. We found that acute hypoxia facilitated the activation of M1 microglia in both Tg and Wt mice as evidenced by the elevated M1 markers including cluster of differentiation 86 (CD86), tumor necrosis factor (TNF)-α, interleukin-6 (IL-6), C-C motif chemokine ligand 2 (CCL2) and CCL3. In addition, the markers of M2 microglia phenotype (Arg-1, CD206, IL-4 and IL-10) were decreased after acute hypoxia exposure, suggesting an attenuated M2 phenotype of microglia. Moreover, the activation of microglial and the release of cytokines and chemokines were associated with Nuclear factor-κB (NF-κB) induction through toll-like receptor 4 (TLR4). In summary, our findings revealed that acute hypoxia facilitated the activation of M1 microglia and attenuated the activation of M2 microglia in a transgenic AD mouse model, indicating the pathological role of hypoxia in the neuroinflammation of AD.