Integrated Analysis Reveals Altered Lipid and Glucose Metabolism and Identifies NOTCH2 as a Biomarker for Parkinson's Disease Related Depression

Investigating causal associations of gut microbiota and blood metabolites on stroke and its subtypes: A Mendelian randomization study

BACKGROUND

The causal relationships between gut microbiota, blood metabolites, and stroke and its subtypes remain unclear. This study aims to uncover the causal associations using Mendelian randomization.

METHODS

We initially identify Single-Nucleotide Polymorphisms (SNPs) correlated with gut microbiota and blood metabolites as instrumental variables (IVs) from the summary statistics in Genome-Wide Association Study (GWAS) to evaluate their potential causal associations with stroke and its subtypes. We proceed with a two-step Mendelian randomization analysis aiming to determine whether blood metabolites mediate the relationships between gut microbiota and stroke or its subtypes.

RESULTS

We identified the genetic predictions of 12, 11, and 10 particular gut microbiota were associated with stroke, ischemic stroke, and intracerebral hemorrhage respectively. Inverse variance weighted (IVW) analysis disclosed Alistipes (OR [95%CI]: 1.11[1.00,1.23]), Streptococcus (OR [95%CI]: 1.17[1.05,1.30]), and Porphyromonadaceae (OR [95%CI]: 2.41[1.09,5.31]) as the primary causal effects on stroke, ischemic stroke, and ICH, respectively. We determined that 8, 11, and 1 blood metabolites were causally related to stroke, ischemic stroke, and ICH, respectively. Among these metabolites, Citrate (OR [95%CI]: 2.39[1.32,4.34]) and Beta-hydroxyisovalerate (OR [95%CI]: 2.54[1.62,3.97]) had the foremost causal effect on stroke and ischemic stroke, respectively, whereas Glutaroyl carnitine evidenced a causal effect on ICH. Furthermore, our study revealed that Tetradecanedioate marginally mediated the causal effects of Paraprevotella on stroke and ischemic stroke.

CONCLUSIONS

This study established a causal link between gut microbiota, plasma metabolites, and stroke. It revealed a marginal pathway, shedding new light on the intricate interactions among gut microbes, blood metabolites, stroke, and their underlying mechanisms.

Glucose metabolism impairment in major depressive disorder

Major depressive disorder (MDD) is a common mental disorder with chronic tendencies that seriously affect regular work, life, and study. However, its exact pathogenesis remains unclear. Patients with MDD experience systemic and localized impairments in glucose metabolism throughout the disease course, disrupting various processes such as glucose uptake, glycoprotein transport, glycolysis, the tricarboxylic acid cycle (TCA), and oxidative phosphorylation (OXPHOS). These impairments may result from mechanisms including insulin resistance, hyperglycemia-induced damage, oxidative stress, astrocyte abnormalities, and mitochondrial dysfunction, leading to insufficient energy supply, altered synaptic plasticity, neuronal cell death, and functional and structural damage to reward networks. These mechanical changes contribute to the pathogenesis of MDD and severely interfere with the prognosis. Herein, we summarized the impairment of glucose metabolism and its pathophysiological mechanisms in patients with MDD. In addition, we briefly discussed potential pharmacological interventions for glucose metabolism to alleviate MDD, including glucagon-like peptide-1 receptor agonists, metformin, topical insulin, liraglutide, and pioglitazone, to encourage the development of new therapeutics.

Plasma metabolomics profiles indicate sex differences of lipid metabolism in patients with Parkinson's disease

The effect of sexual dimorphism on the metabolism of patients with Parkinson's disease has not been clarified. A group of patients with Parkinson's disease and healthy controls were recruited, and their clinical characteristics and plasma were collected. Untargeted liquid chromatography-mass spectrometry-based plasma metabolomics profiling was performed. Differentially expressed metabolites between patients and healthy controls were respectively identified in the male and female participants and metabolite set enrichment analyses were further employed. A total of 75 patients with Parkinson's disease (37 males and 38 females) and 31 healthy controls (16 males and 15 females) were enrolled while no significant differences can be discovered in clinical characteristics. The constructed male-specific metabolic model from orthogonal partial least squares-discriminant analysis can't well recognize female patients and the female-specific model also can't accurately identify male patients. There were 55 differentially expressed metabolites in the male participants, and fatty acids and conjugates and eicosanoids were the significantly enriched metabolite sets. Meanwhile, 86 metabolites were differentially expressed in the female participants while fatty acids and conjugates and glycerophosphocholines were enriched. Only 17 metabolites were simultaneously changed in both male and female patients. Significant sex differences of lipid metabolism were found in patients with Parkinson's disease.

Integrating digital gait data with metabolomics and clinical data to predict outcomes in Parkinson's disease

Parkinson's disease (PD) presents diverse symptoms and comorbidities, complicating its diagnosis and management. The primary objective of this cross-sectional, monocentric study was to assess digital gait sensor data's utility for monitoring and diagnosis of motor and gait impairment in PD. As a secondary objective, for the more challenging tasks of detecting comorbidities, non-motor outcomes, and disease progression subgroups, we evaluated for the first time the integration of digital markers with metabolomics and clinical data. Using shoe-attached digital sensors, we collected gait measurements from 162 patients and 129 controls in a single visit. Machine learning models showed significant diagnostic power, with AUC scores of 83-92% for PD vs. control and up to 75% for motor severity classification. Integrating gait data with metabolomics and clinical data improved predictions for challenging-to-detect comorbidities such as hallucinations. Overall, this approach using digital biomarkers and multimodal data integration can assist in objective disease monitoring, diagnosis, and comorbidity detection.

How close are we to a breakthrough? The hunt for blood biomarkers in Parkinson's disease diagnosis

Parkinson's disease (PD), being the second largest neurodegenerative disease, poses challenges in early detection, resulting in a lack of timely treatment options to effectively manage the disease. By the time clinical diagnosis becomes possible, more than 60% of dopamine neurons in the substantia nigra (SN) of patients have already degenerated. Therefore, early diagnosis or identification of warning signs is crucial for the prompt and timely beginning of the treatment. However, conducting invasive or complex diagnostic procedures on asymptomatic patients can be challenging, making routine blood tests a more feasible approach in such cases. Numerous studies have been conducted over an extended period to search for effective diagnostic biomarkers in blood samples. However, thus far, no highly effective biomarkers have been confirmed. Besides classical proteins like α-synuclein (α-syn), phosphorylated α-syn and oligomeric α-syn, other molecules involved in disease progression should also be given equal attention. In this review, we will not only discuss proposed biomarkers that are currently under investigation but also delve into the mechanisms underlying the disease, focusing on processes such as α-syn misfolding, intercellular transmission and the crossing of the blood-brain barrier (BBB). Our aim is to provide an updated overview of molecules based on these processes that may potentially serve as blood biomarkers.

Proteomic and metabolomic analyses illustrate the mechanisms of expression of the O6 -methylguanine-DNA methyltransferase gene in glioblastoma

AIM

Glioblastoma (GBM) has been reported to be the most common high-grade primary malignant brain tumor in clinical practice and has a poor prognosis. O6 -methylguanine-DNA methyltransferase (MGMT) promoter methylation has been related to prolonged overall survival (OS) in GBM patients after temozolomide treatment.

METHODS

Proteomics and metabolomics were combined to explore the dysregulated metabolites and possible protein expression alterations in white matter (control group), MGMT promoter unmethylated GBM (GBM group) or MGMT promoter methylation positive GBM (MGMT group).

RESULTS

In total, 2745 upregulated and 969 downregulated proteins were identified in the GBM group compared to the control group, and 131 upregulated and 299 downregulated proteins were identified in the MGMT group compared to the GBM group. Furthermore, 131 upregulated and 299 downregulated metabolites were identified in the GBM group compared to the control group, and 187 upregulated and 147 downregulated metabolites were identified in the MGMT group compared to the GBM group. The results showed that 94 upregulated and 19 downregulated proteins and 20 upregulated and 16 downregulated metabolites in the MGMT group were associated with DNA repair. KEGG pathway enrichment analysis illustrated that the dysregulated proteins and metabolites were involved in multiple metabolic pathways, including the synthesis and degradation of ketone bodies, amino sugar and nucleotide sugar metabolism. Moreover, integrated metabolomics and proteomics analysis was performed, and six key proteins were identified in the MGMT group and GBM group. Three key pathways were recognized as potential biomarkers for recognizing MGMT promoter unmethylated GBM and MGMT promoter methylation positive GBM from GBM patient samples, with areas under the curve of 0.7895, 0.7326 and 0.7026, respectively.

CONCLUSION

This study provides novel mechanisms to understand methylation in GBM and identifies some biomarkers for the prognosis of two different GBM types, MGMT promoter unmethylated or methylated GBM, by using metabolomics and proteomics analyses.

Exploring the interplay between metabolomics and genetics in Parkinson's disease: Insights from ongoing research and future avenues

Parkinson's disease (PD) is a widespread neurodegenerative disorder, whose complex aetiology remains under construction. While rare variants have been associated with the monogenic PD form, most PD cases are influenced by multiple genetic and environmental aspects. Nonetheless, the pathophysiological pathways and molecular networks involved in monogenic/idiopathic PD overlap, and genetic variants are decisive in elucidating the convergent underlying mechanisms of PD. In this scenario, metabolomics has furnished a dynamic and systematic picture of the synergy between the genetic background and environmental influences that impact PD, making it a valuable tool for investigating PD-related metabolic dysfunctions. In this review, we performed a brief overview of metabolomics current research in PD, focusing on significant metabolic alterations observed in idiopathic PD from different biofluids and strata and exploring how they relate to genetic factors associated with monogenic PD. Dysregulated amino acid metabolism, lipid metabolism, and oxidative stress are the critical metabolic pathways implicated in both genetic and idiopathic PD. By merging metabolomics and genetics data, it is possible to distinguish metabolic signatures of specific genetic backgrounds and to pinpoint subgroups of PD patients who could derive personalized therapeutic benefits. This approach holds great promise for advancing PD research and developing innovative, cost-effective treatments.

Sex- and age-specific prevalence and risk factors of depressive symptoms in Parkinson's disease

Although depressive symptoms are common in PD, few studies investigated sex and age differences in depressive symptoms. Our study aimed to explore the sex and age differences in the clinical correlates of depressive symptoms in patients with PD. 210 PD patients aged 50-80 were recruited. Levels of glucose and lipid profiles were measured. The Hamilton Depression Rating Scale-17 (HAMD-17), the Montreal Cognitive Assessment (MoCA) and the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS-III) assessed depressive symptom, cognition and motor function, respectively. Male depressive PD participants had higher fasting plasma glucose (FPG) levels. Regarding the 50-59 years group, depressive patients had higher TG levels. Moreover, there were sex and age differences in the factors associated with severity of depressive symptoms. In male PD patients, FPG was an independent contributor to HAMD-17 (Beta = 0.412, t = 4.118, p < 0.001), and UPDRS-III score was still associated with HAMD-17 in female patients after controlling for confounding factors (Beta = 0.304, t = 2.961, p = 0.004). Regarding the different age groups, UPDRS-III (Beta = 0.426, t = 2.986, p = 0.005) and TG (Beta = 0.366, t = 2.561, p = 0.015) were independent contributors to HAMD-17 in PD patients aged 50-59. Furthermore, non-depressive PD patients demonstrated better performance with respect to visuospatial/executive function among the 70-80 years group. These findings suggest that sex and age are crucial non-specific factors to consider when assessing the relationship between glycolipid metabolism, PD-specific factors and depression.

Brain-wide transcriptome-based metabolic alterations in Parkinson's disease: human inter-region and human-experimental model correlations

Alterations in brain metabolism are closely associated with the molecular hallmarks of Parkinson's disease (PD). A clear understanding of the main metabolic perturbations in PD is therefore important. Here, we retrospectively analysed the expression of metabolic genes from 34 PD-control post-mortem human brain transcriptome data comparisons from literature, spanning multiple brain regions. We found high metabolic correlations between the Substantia nigra (SN)- and cerebral cortex-derived tissues. Moreover, three clusters of PD patient cohorts were identified based on perturbed metabolic processes in the SN - each characterised by perturbations in (a) bile acid metabolism (b) omega-3 fatty acid metabolism, and (c) lipoic acid and androgen metabolism - metabolic themes not comprehensively addressed in PD. These perturbations were supported by concurrence between transcriptome and proteome changes in the expression patterns for CBR1, ECI2, BDH2, CYP27A1, ALDH1B1, ALDH9A1, ADH5, ALDH7A1, L1CAM, and PLXNB3 genes, providing a valuable resource for drug targeting and diagnosis. Also, we analysed 58 PD-control transcriptome data comparisons from in vivo/in vitro disease models and identified experimental PD models with significant correlations to matched human brain regions. Collectively, our findings suggest metabolic alterations in several brain regions, heterogeneity in metabolic alterations between study cohorts for the SN tissues and the need to optimize current experimental models to advance research on metabolic aspects of PD.

Short-term arecoline exposure affected the systemic health state of mice, in which gut microbes played an important role

Arecoline is a critical bioactive component in areca nuts with toxicity and pharmacological activities. However, its effects on body health remain unclear. Here, we investigated the effects of arecoline on physiologic and biochemical parameters in mouse serum, liver, brain, and intestine. The effect of arecoline on gut microbiota was investigated based on shotgun metagenomic sequencing. The results showed that arecoline promoted lipid metabolism in mice, manifested as significantly reduced serum TC and TG and liver TC levels and a reduction in abdominal fat accumulation. Arecoline intake significantly modulated the neurotransmitters 5-HT and NE levels in the brain. Notably, arecoline intervention significantly increased serum IL-6 and LPS levels, leading to inflammation in the body. High-dose arecoline significantly reduced liver GSH levels and increased MDA levels, which led to oxidative stress in the liver. Arecoline intake promoted the release of intestinal IL-6 and IL-1β, causing intestinal injury. In addition, we observed a significant response of gut microbiota to arecoline intake, reflecting significant changes in diversity and function of the gut microbes. Further mechanistic exploration suggested that arecoline intake can regulate gut microbes and ultimately affect the host's health. This study provided technical help for the pharmacochemical application and toxicity control of arecoline.

Interactions between cadmium, lead, mercury, and arsenic and depression: A molecular mechanism involved

BACKGROUND

We aimed to assess the interactions between mixed heavy metals, genes, and miRNAs implicated in depression development and to design and create miRNA sponges.

METHODS

The key data-mining approaches in this study were the Comparative Toxicogenomics Database (CTD), MIENTURNET, GeneMania, Metascape, Webgestalt, miRNAsong, and Cytoscape software.

RESULTS

A mixture of cadmium, lead, mercury, and arsenic was related to the development of depression. Even though the genes acquired from the heavy metals of depression studied were different, the "selenium micronutrient network", "vitamin B12 and folate metabolism", and "positive regulation of peptidyl-serine phosphorylation" pathways were highlighted. The heavy metal mixture altered the genes SOD1, IL6, PTGS2, PON1, BDNF, and ALB, highlighting the role of oxidative stress, pro-inflammatory cytokines, paraoxonase activity, neurotrophic factors, and antioxidants related to depression, as well as the possibility of targeting these genes in prospective depressive treatment. Chr1q31.1, five transcription factors (NR4A3, NR1H4, ATF3, CREB3L3, and NR1I3), the "endoplasmic reticulum lumen," "blood microparticle," and "myelin sheath", were found to be important chromosomal locations, transcription factors, and cellular parts linked to depression and affected by mixed heavy metals. Furthermore, we developed a network-based approach to detect significant genes, miRNA, pathways, and illnesses related to depression development. We also observed eight important miRNAs related to depression induced by mixed heavy metals (hsa-miR-16-5p, hsa-miR-132-3p, hsa-miR-1-3p, hsa-miR-204-5p, hsa-miR-206, hsa-miR-124-3p, hsa-miR-146a-5p, and hsa-miR-26a-5p). In addition, we created and evaluated miRNA sponge sequences for these miRNAs in silico.

LIMITATIONS

A toxicogenomic design in silico was used.

CONCLUSIONS

Our findings highlight the importance of oxidative stress, notably SOD1 and the selenium micronutrient network, in depression caused by heavy metal mixtures and provide additional insights into common molecular pathways implicated in depression pathogenesis.

Coordinated modification in expression levels of HSPA1A/B, DGKH, and NOTCH2 in Parkinson's patients' blood and substantia nigra as a diagnostic sign: the transcriptomes' relationship

BACKGROUND

Diagnosis of Parkinson's disease (PD) is associated with a vast number of challenges. This study aimed to assess the overlap of PD patients' transcriptomes in the substantia nigra (SN) with peripheral blood mononuclear cells (PBMCs) to discover potential biomarkers for diagnosis.

METHODS

GEO data were used to select genes with significant changes in expression level in the SN region and eligible studies. Also, transcriptome data related to blood of PD patients with other neurodegenerative diseases (ND) was considered. Differential expression genes between PD and control were evaluated in the SN and blood, and RT-qPCR was applied to validate the findings.

RESULTS

At the expression level, no significant similarity in long non-coding RNA was found between the patients' SN and blood. While in silico results revealed 16 common mRNAs in SN and blood with significant expression levels. Among all overexpressed mRNAs, HSPA1A/B expression level had the highest expression difference between control and PD samples. Moreover, DGKH had the highest score of down-regulated genes in both blood and SN. The NOTCH pathway had the highest score pathway among up-regulated pathways, and the expression levels of NOTCH2, H4C8, and H2BC21 associated with this pathway had the most ability to separate the control and PD populations. Furthermore, RT-qPCR results revealed that HSPA1A/B, NOTCH2, and H4C8 were overexpressed in PD PBMCs, while DGKH expression levels were lower compared to controls.

CONCLUSION

Our findings indicate that expression levels of HSPA1A/B, DGKH, and NOTCH2 could be applied as candidate biomarkers to diagnose PD patients in the SN region and PBMCs.

Regulators of proteostasis are translationally repressed in fibroblasts from patients with sporadic and LRRK2-G2019S Parkinson's disease

Deficits in protein synthesis are associated with Parkinson's disease (PD). However, it is not known which proteins are affected or if there are synthesis differences between patients with sporadic and Leucine-Rich Repeat Kinase 2 (LRRK2) G2019S PD, the most common monogenic form. Here we used bio-orthogonal non-canonical amino acid tagging for global analysis of newly translated proteins in fibroblasts from sporadic and LRKK2-G2019S patients. Quantitative proteomic analysis revealed that several nascent proteins were reduced in PD samples compared to healthy without any significant change in mRNA levels. Using targeted proteomics, we validated which of these proteins remained dysregulated at the static proteome level and found that regulators of endo-lysosomal sorting, mRNA processing and components of the translation machinery remained low. These proteins included autophagy-related protein 9A (ATG9A) and translational stability regulator YTH N6-ethyladenosine RNA binding protein 3 (YTHDF3). Notably, 77% of the affected proteins in sporadic patients were also repressed in LRRK2-G2019S patients (False discovery rate (FDR) < 0.05) in both sporadic and LRRK2-G2019S samples. This analysis of nascent proteomes from PD patient skin cells reveals that regulators of proteostasis are repressed in both sporadic and LRRK2-G2019S PD.

Tryptophan-5-HT pathway disorder was uncovered in the olfactory bulb of a depression mice model by metabolomic analysis

Major depression (MD) is a severe mental illness that creates a heavy social burden, and the potential molecular mechanisms remain largely unknown. Lots of research demonstrate that the olfactory bulb is associated with MD. Recently, gas chromatography-mass spectrometry-based metabolomic studies on depressive rats indicated that metabolisms of purine and lipids were disordered in the olfactory bulb. With various physicochemical properties and extensive concentration ranges, a single analytical technique could not completely cover all metabolites, hence it is necessary to adopt another metabolomic technique to seek new biomarkers or molecular mechanisms for depression. Therefore, we adopted a liquid chromatography-mass spectrometry metabonomic technique in the chronic mild stress (CMS) model to investigate significant metabolic changes in the olfactory bulb of the mice. We discovered and identified 16 differential metabolites in the olfactory bulb of the CMS treatments. Metabolic pathway analysis by MetaboAnalyst 5.0 was generated according to the differential metabolites, which indicated that the tryptophan metabolism pathway was the core pathogenesis in the olfactory bulb of the CMS depression model. Further, the expressions of tryptophan hydroxylase (TpH) and aromatic amino acid decarboxylase (AAAD) were detected by western blotting and immunofluorescence staining. The expression of TpH was increased after CMS treatment, and the level of AAAD was unaltered. These results revealed that abnormal metabolism of the tryptophan pathway in the olfactory bulb mediated the occurrence of MD.

Cognition, motor symptoms, and glycolipid metabolism in Parkinson's disease with depressive symptoms

Depressive symptoms and abnormal glycolipid metabolisms are common in patients with Parkinson's disease (PD), but their relationship has not been fully reported. It is not clear whether glycolipid impairments lead to poor cognitive and motor function, and aggravate depressive symptoms. Therefore, we aimed to explore the relationships between glycolipid variables, cognition, motor and depressive symptoms in PD patients cross-sectionally. Two hundred ten PD patients were recruited. Glycolipid parameters and Uric acid (UA) were measured. Depressive symptoms, cognitive function and motor symptoms were assessed using the Hamilton Depression Rating Scale-17 (HAMD-17), the Montreal Cognitive Assessment (MOCA) and the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part-III (UPDRS-III). Depressive PD patients had significantly worse motor symptoms and higher levels of fasting plasma glucose (FPG) than those in non-depressive patients (F = 24.145, P < 0.001). Further, logistic regression analysis indicated that UPDRS-III (OR = 1.039, 95% CI 1.019-1.057, P = 0.044), FPG (OR = 1.447, 95% CI 1.050-1.994, P = 0.024) were independently associated with depression. In PD patients without depression, UA (β = - 0.068, t = - 2.913, P = 0.005) and cholesterol (CHOL) (β = - 3.941, t = - 2.518, P = 0.014) were independent predictors of the UPDRS-III score; in addition, UPDRS-III score was negatively associated with MOCA score (β = - 0.092, t = - 2.791, P = 0.007). FPG levels and motor symptoms were related to depressive symptoms in PD patients. Further, in non-depressive PD patients, UA and CHOL showed putative biomarkers of motor symptoms.

A co-expression network based molecular characterization of genes responsive for Braak stages in Parkinson's disease

The progression of Parkinson's disease (PD) is defined by six Braak stages. We used transcriptome data from PD patients with Braak stage information to understand underlying molecular mechanisms for the progress of the disease. We created networks of genes with decreased/increased co-expression from control group to Braak 5-6 stages. These networks are significantly associated with PD related mechanisms such as mitochondrial dysfunction and synaptic signaling among others. Applying Weighted Gene Correlation Network Analysis (WGCNA) algorithm to the co-expression networks led to more specific modules enriched with neurodegeneration related disease pathways, seizure, abnormality of coordination, and hypotonia. Furthermore, we showed that one of the co-expression networks is clustered into three major communities with dedicated molecular functions: (i) tubulin folding pathway, gap junction related mechanisms, neuronal system (ii) synaptic vesicle, intracellular vesicle, proteasome complex, PD genes (iii) energy metabolism, mitochondrial mechanisms, oxidative phosphorylation, TCA cycle, PD genes. The co-expression relations we identified in this study as crucial players in the disease progression cover several known PD-associated genes and genes whose products are known to physically interact with alpha-synuclein protein.

Glycolipid Metabolism and Metagenomic Analysis of the Therapeutic Effect of a Phenolics-Rich Extract from Noni Fruit on Type 2 Diabetic Mice

The phenolics of noni fruit possess antihyperglycemic activity; however, the molecular mechanisms remain unclear. To understand the potential effects it has on type 2 diabetes (T2D), the glycolipid metabolism and gut microbiota regulation of phenolic-rich extracts from noni fruit (NFEs) were investigated. The results indicated that NFE could remarkably ameliorate hyperglycemia, insulin resistance, oxidative stress, and glycolipid metabolism via the adenosine 5'-monophosphate-activated protein kinase (AMPK) pathway in T2D mice. Furthermore, metagenomic sequencing results revealed that NFE intervention modulated the gut microbiota composition in T2D mice, characterized by increased abundance of unclassified_o_Bacteroidales, Alistipes, Prevotella, Lactobacillus, and Akkermansia and decreased abundance of Oscillibacter, Desulfovibrio, and significantly decreased the pathways related to carbohydrate metabolism, translation, amino acid metabolism, and nucleotide metabolism. Taken together, the results provided new evidence that the hypoglycemic and hypolipidemic activities of NFE in T2D were likely attributed to the activation of the liver AMPK pathway and modulation of gut microbiota.

Exploring the potential mechanism of Rhodomyrtus tomentosa (Ait.) Hassk fruit phenolic rich extract on ameliorating nonalcoholic fatty liver disease by integration of transcriptomics and metabolomics profiling

Nonalcoholic fatty liver disease (NAFLD), as the commonest form of chronic liver disease, is accompanied by liver oxidative stress and inflammatory responses. Rhodomyrtus tomentosa (Ait.) Hassk fruit phenolic rich extract (RTE) possesses multiple pharmacological effects in management of chronic diseases. In this study, the liver-protective effect of RTE on mice with high-fat-diet (HFD)-induced NAFLD was investigated for the first time, and the underlying molecular mechanism was explored via integration of transcriptomics and metabolomics. The results showed that RTE mitigated liver damage, which was evidenced by declined inflammatory cell infiltration in liver, decreased liver function markers, oxidative stress indexes, lipid profile levels and inflammatory cytokines levels. The differential metabolites by metabonomics illustrated supplementation of RTE affected metabolomics pathways including tryptophan metabolism, alanine, aspartate and glutamate metabolism, D-glutamine and D-glutamate metabolism, cysteine and methionine metabolism, arginine and proline metabolism, which are all involved in oxidative stress and inflammation. Furthermore, the five differential expression genes (DEGs) through liver transcriptomics were screened and recognized, namely Tnfrsf21, Ifit1, Inhbb, Mapk15 and Gadd45g, which revealed that HFD induced Cytokine-cytokine receptor interaction pathway, NF-κB signaling pathway NOD-like receptor pathway, TNF signaling pathway. Integrated analysis of transcriptomics and metabolomics confirmed the supplementation of RTE had significantly regulatory effects on the metabolic pathways involved in inflammatory responses. Additionally, RT-PCR and western blot authenticated RTE intervention regulated the mRNA levels of liver genes involved in inflammation response and inhibited the liver endotoxin-TLR4-NF-κB pathway triggered by HFD, thus alleviating NAFLD. Our findings strongly support the possibility that RTE can be regarded as a potential therapeutic method for obesity-associated NAFLD.

Lower Blood Lipid Level Is Associated with the Occurrence of Parkinson's Disease: A Meta-Analysis and Systematic Review

BACKGROUND

The changes of blood lipid levels in patients with Parkinson's disease (PD) and its clinical relevance remain unclear. We aimed to evaluate the potential association of blood lipid and the occurrence of PD, to provide evidence to the clinical treatment and nursing care of PD.

METHODS

We searched PubMed, Medline, Web of Science, Cochrane Library, Wanfang Database, Weipu Database, and China National Knowledge Infrastructure for studies related to the blood lipid levels and PD until November 30, 2021. Two researchers independently screened the literature and extricated the data including the levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of included studies. RevMan5.3 and Stata 12.0 software were used for statistical processing and analysis.

RESULTS

A total of 15 cohort studies with 9740 participants involving 2032 PD patients and 7708 controls were included. Meta-analysis indicated that TC (SMD = -0.29, 95% CI -0.55∼-0.03, P=0.04), TG (SMD = -16.83, 95% CI -20.71∼-12.95, P < 0.001), HDL-C (SMD = -0.14, 95% CI -0.26∼-0.02, P < 0.001) and LDL-C (SMD = -0.26, 95% CI -0.50∼-0.01, P=0.04) level in the PD patients was significantly lower than that of health controls. Sensitivity analysis indicated that the results were stable. No significant publication bias was found between the synthesized outcomes.

CONCLUSIONS

Lower blood TC, TG, HDL-C, and LDL-C level are associated with the occurrence of PD. Limited by sample size and study population, further high-quality, large-sample clinical trials in different areas are needed to further determine the relationship between blood lipids and PD in the future.

Oral, Nasal, and Gut Microbiota in Parkinson's Disease

Parkinson's disease (PD) is the second most frequently diagnosed neurodegenerative disease. The purpose of this study was to investigate the link between microbiota composition in important mucosal interfaces (oral, nasal, and intestinal) and PD. Sequencing was undertaken of the V4-V5 region of the 16S ribosomal RNA (rRNA) gene of the microbiome from the oral cavity, nasal cavity, and gut of 91 PD patients and 91 healthy controls. Significant differences were found in microbiota composition in the oral cavity and gut, but not the nasal cavity, between PD patients and healthy controls after adjusting for age, gender, and body mass index (BMI). More genera in the oral cavity were significantly positively correlated with clinical characteristics, such as the HAMA and HAMD rating scales. The taxa c_Clostridia, o_Clostridiales, and f_Ruminococcaceae in the gut microbiota were associated with weight and MMSE score. Furthermore, as a result of dysbiosis, there was an enrichment of ion channel-, oxidative phosphorylation-, and carbohydrate metabolism-related pathways in the oral cavity and glycolysis/gluconeogenesis- and propanoate metabolism-related pathways in the intestine. Changes in these pathways can influence metabolism and inflammation, thereby contributing to PD pathogenesis. In addition, several subnetworks containing differentially abundant microbiota in the oral cavity and gut samples from PD patients may regulate microbial composition and function in PD. Overall, our results indicate that oral and gut dysbiosis may affect PD progression and provide a basis for understanding the pathogenesis of PD and identifying potential therapeutic targets for the treatment of this disease.

Current advances in metabolomic studies on non-motor psychiatric manifestations of Parkinson's disease (Review)

Life expectancy has increased worldwide and, along with it, a greater prevalence of age-dependent disorders, chronic illnesses and comorbidities can be observed. In 2019, in both Europe and the Americas, dementias ranked 3rd among the top 10 causes of death. Parkinson's disease (PD) is the second most frequent type of neurodegenerative disease. In the last decades, globally, the number of people suffering from PD has more than doubled to over 6 million. Of all the neurological disorders, PD increased with the fastest rate. This troubling trend highlights the stringent need for accurate diagnostic biomarkers, especially in the early stages of the disease and to evaluate treatment response. To gain a broad and complex understanding of the recent advances in the '-omics' research fields, electronic databases such as PubMed, Google Academic, and Science Direct were searched for publications regarding metabolomic studies on PD to identify specific biomarkers for PD, and especially PD with associated psychiatric symptomatology. Discoveries in the fields of metagenomics, transcriptomics and proteomics, may lead to an improved comprehension of the metabolic pathways involved in disease etiology and progression and contribute to the discovery of novel therapeutic targets for effective treatment options.

The disturbance of lipid metabolism is correlated with neuropsychiatric symptoms in patients with Parkinson's disease

OBJECTIVE

We aimed to identify the detailed relationships between serum lipid levels and neuropsychiatric symptoms in patients with Parkinson's disease (PD).

METHODS

Consecutive PD patients and healthy controls were recruited and demographic data were collected. The disease stages of PD patients were assessed using Hoehn-Yahr scale while neuropsychiatric symptoms were determined using Hamilton depression rating scale (HAMD), Hamilton anxiety rating scale (HAMA), and mini-mental state examination scale. Fast serum samples were obtained and the serum levels of lipids were identified. Linear regression analyses and correlation analyses were performed to explore the relationships between serum lipid levels and neuropsychiatric symptoms.

RESULTS

The serum levels of triglyceride had significantly decreased while the levels of HDL-c and lipoprotein a had increased in PD patients. Linear regression analyses confirmed that the levels of triglyceride were mainly correlated with age and HAMA score, the levels of HDL-c were correlated with disease duration and gender, and the levels of lipoprotein a were correlated with HAMD score. Correlation analyses further confirmed that the levels of triglyceride were negatively correlated with HAMA score when the levels of lipoprotein a were negatively correlated with HAMD score.

CONCLUSIONS

Lipid metabolism is significantly correlated with neuropsychiatric disorders in PD patients.

Lipid metabolic dysregulation is involved in Parkinson's disease dementia

Dementia is very common in the late stage of patient with Parkinson's disease (PD). We aim to explore its underlying pathogenesis and identify candidate biomarkers using untargeted metabolomics analysis. Consecutive PD patients and healthy controls were recruited. Clinical data were assessed and patients were categorized into Parkinson's disease without dementia (PDND) and Parkinson's disease dementia (PDD). Fast plasma samples were obtained and untargeted liquid chromatography-mass spectrometry-based metabolomics analysis was performed. Based on the identified differentially-expressed metabolites from the metabolomics analysis, multivariate linear regression analyses and receiver operating characteristic (ROC) curves were further employed. According to the clinical data, the mean ages of PDND and PDD patients were significantly higher than those of healthy controls. The incidence of hypercholesterolemia was decreased in PDD patients. PDD patients also had lower levels of triglyceride, low-density lipoprotein cholesterol, and apolipoprotein B. There were 24 and 57 differentially expressed metabolites in PDD patients when compared with the healthy controls and PDND patients from the metabolomics analysis. Eleven lipid metabolites were simultaneously decreased between these two groups, and can be further subcategorized into fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and prenol lipids. The plasma levels of the eleven metabolites were positively correlated with MMSE score and can be candidate biomarkers for PDD patients with areas under the curve ranging from 0.724 to 0.806 based on the ROC curves. Plasma lipoproteins are significantly lower in PDD patients. A panel of eleven lipid metabolites were also decreased and can be candidate biomarkers for the diagnosis of PDD patients. Lipid metabolic dysregulation is involved in the pathogenesis of Parkinson's disease dementia.

C-coordinated O-carboxymethyl chitosan Cu(II) complex exerts antifungal activity by disrupting the cell membrane integrity of Phytophthora capsici Leonian

Damage to the cell membrane is an effective method to prevent drug resistance in plant fungal diseases. Here, we proposed a negative remodeling model of the cell membrane structure induced by the C-coordinated O-carboxymethyl chitosan Cu (II) complex (O-CSLn-Cu). FITC-labeled O-CSLn-Cu (FITC-O-CSLn-Cu) was first synthesized via a nucleophilic substitution reaction and confirmed by FT-IR. FITC-labeled O-CSLn-Cu could pass through the fungal cell membrane, as detected by confocal laser scanning microscopy (CLSM) coupled with fluorescein isothiocyanate (FITC)-fluorescence. O-CSLn-Cu treatment led to apparent morphological changes in the membranes of P. capsici Leonian and giant unilamellar vesicles (GUVs) by transmission electron microscopy (TEM). Then, we performed component analysis of the cell membrane from the P. capsici Leonian affected by O-CSLn-Cu with a particular interest in membrane physicochemical properties. Many unsaturated fatty acids (UFAs) and key enzymes promoting UFA synthesis of the cell membrane were downregulated. Similarly, a large number of membrane proteins responsible for substance transport and biochemical reactions were downregulated. Furthermore, O-CSLn-Cu treatments increased plasma membrane permeability with significant leakage of intercellular electrolytes, soluble proteins and sugars, and lipid peroxidation with decreasing membrane fluidity. Finally, aquaporin 10 was proven to be a potential molecular target sensitive to antimicrobial agents according to composition analysis of membrane structure and immunohistochemistry.

Advances of Mechanisms-Related Metabolomics in Parkinson's Disease

Parkinson's disease (PD) is a multifactorial disorder characterized by progressively debilitating dopaminergic neurodegeneration in the substantia nigra and the striatum, along with various metabolic dysfunctions and molecular abnormalities. Metabolomics is an emerging study and has been demonstrated to play important roles in describing complex human diseases by integrating endogenous and exogenous sources of alterations. Recently, an increasing amount of research has shown that metabolomics profiling holds great promise in providing unique insights into molecular pathogenesis and could be helpful in identifying candidate biomarkers for clinical detection and therapies of PD. In this review, we briefly summarize recent findings and analyze the application of molecular metabolomics in familial and sporadic PD from genetic mutations, mitochondrial dysfunction, and dysbacteriosis. We also review metabolic biomarkers to assess the functional stage and improve therapeutic strategies to postpone or hinder the disease progression.

Metabolomics profiling reveals altered lipid metabolism and identifies a panel of lipid metabolites as biomarkers for Parkinson's disease related anxiety disorder

OBJECTIVES

Anxiety disorder is a common non-motor symptom in patient with Parkinson's disease (PD). We aimed to explore its pathogenesis and identify plasma biomarkers using untargeted metabolomics analysis.

METHODS

Consecutive PD patients and healthy controls were recruited. Clinical data were assessed and patients with Parkinson's disease related anxiety disorder (PDA) were recognized. Fast plasma samples were obtained and untargeted liquid chromatography-mass spectrometry-based metabolomics analysis was performed. Based on the differentially expressed metabolites from the above metabolomics analysis, correlation analyses and receiver operating characteristic curves (ROC) were further employed.

RESULTS

According to the clinical data, PDA patients had lower plasma levels of total cholesterol, triglyceride, low-density lipoprotein cholesterol, and apolipoprotein B. There were thirty-nine differentially expressed metabolites in PDA patients when compared with the other two groups from the metabolomics analysis, respectively. Fourteen lipid metabolites were simultaneously altered between these two groups, and all of them were significantly decreased. They can be further subcategorized into fatty acyls, glycerolipids, sterol lipids, sphingolipids, and prenol lipids. The plasma levels of thirteen metabolites were negatively correlated with HAMA scores except 10-oxo-nonadecanoic acid. Based on the ROC curves, the fourteen lipid metabolites can be diagnostic biomarkers for PDA patients separately and the areas under the curve of the fourteen lipid metabolites ranged from 0.681 to 0.798.

CONCLUSIONS

Significantly lower plasma lipoproteins can be found in PDA patients. A panel of fourteen lipid metabolites were also significantly decreased and can be clinical biomarkers for the diagnosis of PDA patients.

Proteomic Workflows for High-Quality Quantitative Proteome and Post-Translational Modification Analysis of Clinically Relevant Samples from Formalin-Fixed Paraffin-Embedded Archives

Well-characterized archival formalin-fixed paraffin-embedded (FFPE) tissues are of much value for prospective biomarker discovery studies, and protocols that offer high throughput and good reproducibility are essential in proteomics. Therefore, we implemented efficient paraffin removal and protein extraction from FFPE tissues followed by an optimized two-enzyme digestion using suspension trapping (S-Trap). The protocol was then combined with TMTpro 16plex labeling and applied to lung adenocarcinoma patient samples. In total, 9585 proteins were identified, and proteins related to the clinical outcome were detected. Because acetylation is known to play a major role in cancer development, a fast on-trap acetylation protocol was developed for studying endogenous lysine acetylation, which allows identification and localization of the lysine acetylation together with quantitative comparison between samples. We demonstrated that FFPE tissues are equivalent to frozen tissues to study the degree of acetylation between patients. In summary, we present a reproducible sample preparation workflow optimized for FFPE tissues that resolves known proteomic-related challenges. We demonstrate compatibility of the S-Trap with isobaric labeling and for the first time, we prove that it is feasible to study endogenous lysine acetylation stoichiometry in FFPE tissues, contributing to better utility of the existing global tissue archives. The MS proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers PXD020157, PXD021986, and PXD021964.

Dopaminergic System Alteration in Anxiety and Compulsive Disorders: A Systematic Review of Neuroimaging Studies

Objective: The dopaminergic system is involved in many psychiatric disorders as a GABAergic, serotonergic, and glutamatergic system. A systematic review and meta-analysis was performed to elucidate the alteration of the dopaminergic system in anxiety and compulsive disorders.

Methods: The databases of Pubmed, Embase, and ScienceDirect were searched and articles reporting the involvement of the dopaminergic system in patients with anxiety disorder and obsessive compulsive disorder (OCD) were recognized. The key research data were extracted from the included articles and standardized mean differences were calculated using meta-analyses if there were more than two studies with obtainable data. Sensitivity analyses were further performed to detect the stability of results, and the qualities of all the included studies were assessed using the Newcastle Ottawa scale.

Results: Finally, we identified 8 and 11 studies associated with anxiety disorder and OCD for further analysis, respectively. Most consistently, the striatal dopamine D₂ receptor (D₂R) of OCD patients had decreased while no significant correlation was found between striatal D2R and disease severity. The striatal dopamine transporter (DAT) had not been significantly altered in both the anxiety disorder and OCD patients. The heterogeneity values from the meta-analyses were extremely high while those results remained stable after sensitivity analyses. Inconsistent data were found in the striatal D₂R of patients with anxiety disorder. Limited data had suggested that dopamine synthesis increased in most regions of the cerebral cortex and cerebellum in OCD patients.

Conclusions: The most convincing finding was that the D₂ receptor decreased in patients with obsessive compulsive disorder. The dopamine transporter may have no relationship with anxiety and compulsive disorder.

Increased Notch2/NF-κB Signaling May Mediate the Depression Susceptibility: Evidence from Chronic Social Defeat Stress Mice and WKY Rats

The susceptibility to depression has been attributed to the chronic stress and genetic factors but still fails to identify definite biomarkers. The present study aimed to investigate the role of disrupted Notch signaling in the medial prefrontal cortex of the chronic social defeat stress (CSDS) mice and Wistar Kyoto (WKY) rats. RNA-sequencing and quantitative real-time PCR analyses evidenced the involvement of Notch signaling pathway in depression. Western blotting reported an increased level of Notch2 and NF-κB and a decreased level of Hes1 and Bcl2/Bax ratio both in the susceptible mice when compared with the control or resilient ones and in the depression WKY rats when compared with the Wistar or non-depression WKY groups. Further analysis showed that the above-mentioned changes were significantly correlated with the depression-like behaviors and that the elicited Notch2 strongly correlated with the upregulated NF-κB, not with the downregulated Hes1 or Bcl2/Bax ratio. In conclusion, the increased Notch2/NF-κB signaling in the medial prefrontal cortex may mediate depression susceptibility, providing a potential diagnostic biomarker or therapeutic target for treating major depressive disorder.

Integrated Metabolomics and Proteomics Analysis Reveals Plasma Lipid Metabolic Disturbance in Patients With Parkinson's Disease

Parkinson’s disease (PD) is a common neurodegenerative disease in the elderly with a pathogenesis that remains unclear. We aimed to explore its pathogenesis through plasma integrated metabolomics and proteomics analysis. The clinical data of consecutively recruited PD patients and healthy controls were assessed. Fasting plasma samples were obtained and analyzed using metabolomics and proteomics methods. After that, differentially expressed metabolites and proteins were identified for further bioinformatics analysis. No significant difference was found in the clinical data between these two groups. Eighty-three metabolites were differentially expressed in PD patients identified by metabolomics analysis. These metabolites were predominately lipid and lipid-like molecules (63%), among which 25% were sphingolipids. The sphingolipid metabolism pathway was enriched and tended to be activated in the following KEGG pathway analysis. According to the proteomics analysis, forty proteins were identified to be differentially expressed, seven of which were apolipoproteins. Furthermore, five of the six top ranking Gene Ontology terms from cellular components and eleven of the other fourteen Gene Ontology terms from biological processes were directly associated with lipid metabolism. In KEGG pathway analysis, the five enriched pathways were also significantly related with lipid metabolism (p < 0.05). Overall, Parkinson’s disease is associated with plasma lipid metabolic disturbance, including an activated sphingolipid metabolism and decreased apolipoproteins.

Mitochondrial clearance and maturation of autophagosomes are compromised in LRRK2 G2019S familial Parkinson's disease patient fibroblasts

This study utilized human fibroblasts as a preclinical discovery and diagnostic platform for identification of cell biological signatures specific for the LRRK2 G2019S mutation producing Parkinson's disease (PD). Using live cell imaging with a pH-sensitive Rosella biosensor probe reflecting lysosomal breakdown of mitochondria, mitophagy rates were found to be decreased in fibroblasts carrying the LRRK2 G2019S mutation compared to cells isolated from healthy subject (HS) controls. The mutant LRRK2 increased kinase activity was reduced by pharmacological inhibition and targeted antisense oligonucleotide treatment, which normalized mitophagy rates in the G2019S cells and also increased mitophagy levels in HS cells. Detailed mechanistic analysis showed a reduction of mature autophagosomes in LRRK2 G2019S fibroblasts, which was rescued by LRRK2 specific kinase inhibition. These findings demonstrate an important role for LRRK2 protein in regulation of mitochondrial clearance by the lysosomes, which is hampered in PD with the G2019S mutation. The current results are relevant for cell phenotypic diagnostic approaches and potentially for stratification of PD patients for targeted therapy.

Dl-3-n-butylphthalide attenuates mouse behavioral deficits to chronic social defeat stress by regulating energy metabolism via AKT/CREB signaling pathway

Major depressive disorder (MDD) is a severe mental disorder associated with high rates of morbidity and mortality. Current first-line pharmacotherapies for MDD are based on enhancement of monoaminergic neurotransmission, but these antidepressants are still insufficient and produce significant side-effects. Consequently, the development of novel antidepressants and therapeutic targets is desired. Dl-3-n-butylphthalide (NBP) is a compound with proven efficacy in treating ischemic stroke, yet its therapeutic effects and mechanisms for depression remain unexplored. The aim of this study was to investigate the effect of NBP in a chronic social defeat stress model of depression and its underlying molecular mechanisms. Here, we examined depression-related behavior and performed a targeted metabolomics analysis. Real-time quantitative polymerase chain reaction and western blotting were used to examine key genes and proteins involved in energy metabolism and the AKT/cAMP response element-binding protein (CREB) signaling pathway. Our results reveal NBP attenuates stress-induced social deficits, anxiety-like behavior and despair behavior, and alters metabolite levels of glycolysis and tricarboxylic acid (TCA) cycle components. NBP affected gene expression of key enzymes of the TCA cycle, as well as protein expression of p-AKT and p-CREB. Our findings provide the first evidence showing that NBP can attenuate stress-induced behavioral deficits by modulating energy metabolism by regulating activation of the AKT/CREB signaling pathway.

The metabolome identity: basis for discovery of biomarkers in neurodegeneration

Neurodegenerative disorders are often associated with cellular dysfunction caused by underlying protein-misfolding signalling. Numerous neuropathologies are diagnosed at late stage symptomatic changes which occur in response to these molecular malfunctions and treatment is often too late or restricted only to the slowing of further cell death. Important new strategies to identify early biomarkers with predictive value to intervene with disease progression at stages where cell dysfunction has not progressed irreversibly is of paramount importance. Thus, the identification of these markers presents an essential opportunity to identify and target disease pathways. This review highlights some important metabolic alterations detected in neurodegeneration caused by misfolded prion protein and discusses common toxicity pathways identified across different neurodegenerative diseases. Thus, having established some commonalities between various degenerative conditions, detectable metabolic changes may be of extreme value as an early diagnostic biomarker in disease.