Age-related changes in the metabolic profiles of rat hippocampus, medial prefrontal cortex and striatum

Transcriptome-based biomarker prediction for Parkinson's disease using genome-scale metabolic modeling

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. Identification of PD biomarkers is crucial for early diagnosis and to develop target-based therapeutic agents. Integrative analysis of genome-scale metabolic models (GEMs) and omics data provides a computational approach for the prediction of metabolite biomarkers. Here, we applied the TIMBR (Transcriptionally Inferred Metabolic Biomarker Response) algorithm and two modified versions of TIMBR to investigate potential metabolite biomarkers for PD. To this end, we mapped thirteen post-mortem PD transcriptome datasets from the substantia nigra region onto Human-GEM. We considered a metabolite as a candidate biomarker if its production was predicted to be more efficient by a TIMBR-family algorithm in control or PD case for the majority of the datasets. Different metrics based on well-known PD-related metabolite alterations, PD-associated pathways, and a list of 25 high-confidence PD metabolite biomarkers compiled from the literature were used to compare the prediction performance of the three algorithms tested. The modified algorithm with the highest prediction power based on the metrics was called TAMBOOR, TrAnscriptome-based Metabolite Biomarkers by On-Off Reactions, which was introduced for the first time in this study. TAMBOOR performed better in terms of capturing well-known pathway alterations and metabolite secretion changes in PD. Therefore, our tool has a strong potential to be used for the prediction of novel diagnostic biomarkers for human diseases.

Spatial omics: An innovative frontier in aging research

Disentangling the impact of aging on health and disease has become critical as population aging progresses rapidly. Studying aging at the molecular level is complicated by the diverse aging profiles and dynamics. However, the examination of cellular states within aging tissues in situ is hampered by the lack of high-resolution spatial data. Emerging spatial omics technologies facilitate molecular and spatial analysis of tissues, providing direct access to precise information on various functional regions and serving as a favorable tool for unraveling the heterogeneity of aging. In this review, we summarize the recent advances in spatial omics application in multi-organ aging research, which has enhanced the understanding of aging mechanisms from multiple standpoints. We also discuss the main challenges in spatial omics research to date, the opportunities for further developing the technology, and the potential applications of spatial omics in aging and aging-related diseases.

Mechanism of lily bulb and Rehmannia decoction in the treatment of lipopolysaccharide-induced depression-like rats based on metabolomics study and network pharmacology

CONTEXT

Lily bulb and Rehmannia decoction (LBRD), consisting of Lilium henryi Baker (Liliaceae) and Rehmannia glutinosa (Gaertn) DC (Plantaginaceae), is a specialized traditional Chinese medicine formula for treating depression. However, the underlying mechanisms, especially the relationship between LBRD efficacy and metabolomics, remains unclear.

OBJECTIVE

This study was aimed to investigate the metabolic mechanism of LBRD in treating depression.

MATERIALS AND METHODS

Network pharmacology was conducted using SwissTargetPrediction, DisGeNET, DrugBank, Metascape, etc., to construct component-target-pathway networks. The depression-like model was induced by intraperitoneal injection with lipopolysaccharide (LPS) (0.3 mg/kg) for 14 consecutive days. After the administration of LBRD (90 g/kg) and fluoxetine (2 mg/kg) for 14 days, we assessed behaviour and the levels of neurotransmitter, inflammatory cytokine and circulating stress hormone. Prefrontal metabolites of rats were detected by using liquid chromatography-mass spectrometry metabolomics method.

RESULTS

The results of network pharmacology showed that LBRD mainly acted on neurotransmitter and second messenger pathways. Compared to the model group, LBRD significantly ameliorated depressive phenotypes and increased the level of 5-HT (13.4%) and GABA (24.8%), as well as decreased IL-1β (30.7%), IL-6 (32.8%) and TNF-α (26.6%). Followed by LBRD treatment, the main metabolites in prefrontal tissue were contributed to retrograde endocannabinoid signalling, glycerophospholipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, autophagy signal pathway, etc.

DISCUSSION AND CONCLUSIONS

LBRD were effective at increasing neurotransmitter, attenuating proinflammatory cytokine and regulating glycerophospholipid metabolism and glutamatergic synapse, thereby ameliorating depressive phenotypes. This research will offer reference for elucidating the metabolomic mechanism underlying novel antidepressant agents contained LBRD formula.

Multi-omics analysis reveals neuroinflammation, activated glial signaling, and dysregulated synaptic signaling and metabolism in the hippocampus of aged mice

Aging is an intricate biological event that occurs in both vertebrates and invertebrates. During the aging process, the brain, a vulnerable organ, undergoes structural and functional alterations, resulting in behavioral changes. The hippocampus has long been known to be critically associated with cognitive impairment, dementia, and Alzheimer’s disease during aging; however, the underlying mechanisms remain largely unknown. In this study, we hypothesized that altered metabolic and gene expression profiles promote the aging process in the hippocampus. Behavioral tests showed that exploration, locomotion, learning, and memory activities were reduced in aged mice. Metabolomics analysis identified 69 differentially abundant metabolites and showed that the abundance of amino acids, lipids, and microbiota-derived metabolites (MDMs) was significantly altered in hippocampal tissue of aged animals. Furthermore, transcriptomic analysis identified 376 differentially expressed genes in the aged hippocampus. A total of 35 differentially abundant metabolites and 119 differentially expressed genes, constituting the top 200 correlations, were employed for the co-expression network. The multi-omics analysis showed that pathways related to inflammation, microglial activation, synapse, cell death, cellular/tissue homeostasis, and metabolism were dysregulated in the aging hippocampus. Our data revealed that metabolic perturbations and gene expression alterations in the aged hippocampus were possibly linked to their behavioral changes in aged mice; we also provide evidence that altered MDMs might mediate the interaction between gut and brain during the aging process.

Age-Associated Molecular Changes in Human Hippocampus Subfields as Determined by Quantitative Proteomics

The hippocampus demonstrates age-associated changes in functions, neuronal circuitry, and plasticity during various developmental stages. On the contrary, there is a significant knowledge gap on age-associated proteomic alterations in the hippocampus subfields. Using tandem mass tag-based high-resolution mass spectrometry and quantitative proteomics, we report here age-associated changes in the human hippocampus at the subregional level. We used formalin-fixed paraffin-embedded hippocampal tissue sections from a total of 12 healthy individuals, with 3 individuals from each of the 4 different age groups, specifically, 1-10, 21-30, 31-40, and 81-90 years. We found that lysosome and oxidative phosphorylation were the pathways enriched in the 81- to 90-year age group. On the contrray, nervous system development, synaptic plasticity and transmission, messenger RNA (mRNA) splicing, and electron transport chain (ETC) complex-I activity were the enriched biological processes observed in the younger age groups. In a hippocampus subfield context, our topline findings on age-associated proteome changes include altered expression of proteins associated with adult neurogenesis with age in the dentate gyrus and increased expression of immune response-associated proteins with age in certain cornu ammonis sectors of the hippocampus. Signal peptide analysis predicted hippocampal proteins with secretory potential. While these new findings warrant replication in larger study samples, the current data contribute to (1) our understanding of the molecular basis of proteomic changes across various age groups in hippocampus subfields in healthy individuals, and (2) the design and interpretation of future research on the age-associated neurodegenerative disorders.

Effects of Sex, Age, and Apolipoprotein E Genotype on Brain Ceramides and Sphingosine-1-Phosphate in Alzheimer's Disease and Control Mice

Apolipoprotein ε4 (APOE)4 is a strong risk factor for the development of Alzheimer’s disease (AD) and aberrant sphingolipid levels have been implicated in AD. We tested the hypothesis that the APOE4 genotype affects brain sphingolipid levels in AD. Seven ceramides and sphingosine-1-phosphate (S1P) were quantified by LC-MSMS in hippocampus, cortex, cerebellum, and plasma of <3 months and >5 months old human APOE3 and APOE4-targeted replacement mice with or without the familial AD (FAD) background of both sexes (145 animals). APOE4 mice had higher Cer(d18:1/24:0) levels in the cortex (1.7-fold, p = 0.002) than APOE3 mice. Mice with AD background showed higher levels of Cer(d18:1/24:1) in the cortex than mice without (1.4-fold, p = 0.003). S1P levels were higher in all three brain regions of older mice than of young mice (1.7-1.8-fold, all p ≤ 0.001). In female mice, S1P levels in hippocampus (r = −0.54 [−0.70, −0.35], p < 0.001) and in cortex correlated with those in plasma (r = −0.53 [−0.71, −0.32], p < 0.001). Ceramide levels were lower in the hippocampus (3.7–10.7-fold, all p < 0.001), but higher in the cortex (2.3–12.8-fold, p < 0.001) of female than male mice. In cerebellum and plasma, sex effects on individual ceramides depended on acyl chain length (9.5-fold lower to 11.5-fold higher, p ≤ 0.001). In conclusion, sex is a stronger determinant of brain ceramide levels in mice than APOE genotype, AD background, or age. Whether these differences impact AD neuropathology in men and women remains to be investigated.

Toxic Substance-induced Hippocampal Neurodegeneration in Rodents as Model of Alzheimer’s Dementia

BACKGROUND: Alzheimer’s Dementia (AD) cases are increasing with the global elderly population. To study the part of the brain affected by AD, animal models for hippocampal degeneration are still necessary to better understand AD pathogenesis and develop treatment and prevention measures. AIM: This study was a systematic review of toxic substance-induced animal models of AD using the Morris Water Maze method in determining hippocampal-related memory impairment. Our aim was reviewing the methods of AD induction using toxic substances in laboratory rodents and evaluating the report of the AD biomarkers reported in the models. METHODS: Data were obtained from articles in the PubMed database, then compiled, categorized, and analyzed. Eighty studies published in the past 5 years were included for analysis. RESULTS AND DISCUSSION: The most widely used method was intracerebroventricular injection of amyloid-β _substances. However, some less technically challenging techniques using oral or intraperitoneal administration of other toxic substances also produce successful models. Instead of hippocampal neurodegeneration, many studies detected biomarkers of the AD pathological process while some reported inflammation, oxidative stress, neurotrophic factors, and changes of cholinergic activity. Female animals were underrepresented despite a high incidence of AD in women. CONCLUSION: Toxic substances may be used to develop AD animal models characterized with appropriate AD pathological markers. Characterization of methods with the most easy-handling techniques and more studies in female animal models should be encouraged.

Integration of Mass Spectrometry Imaging and Machine Learning Visualizes Region-Specific Age-Induced and Drug-Target Metabolic Perturbations in the Brain

Detailed metabolic imaging of specific brain regions in early aging may expose pathophysiological mechanisms and indicate effective neuropharmacological targets in the onset of cognitive decline. Comprehensive imaging of brain aging and drug-target effects is restricted using conventional methodology. We simultaneously visualized multiple metabolic alterations induced by normal aging in specific regions of mouse brains by integrating Fourier-transform ion cyclotron resonance mass spectrometry imaging and combined supervised and unsupervised machine learning models. We examined the interplay between aging and the response to tacrine-induced acetylcholinesterase inhibition, a well-characterized therapeutic treatment against dementia. The dipeptide carnosine (β-alanyl-l-histidine) and the vitamin α-tocopherol were significantly elevated by aging in different brain regions. l-Carnitine and acetylcholine metabolism were found to be major pathways affected by aging and tacrine administration in a brain region-specific manner, indicating altered mitochondrial function and neurotransmission. The highly interconnected hippocampus and retrosplenial cortex displayed different age-induced alterations in lipids and acylcarnitines, reflecting diverse region-specific metabolic effects. The subregional differences observed in the hippocampal formation of several lipid metabolites demonstrate the unique potential of the technique compared to standard mass spectrometry approaches. An age-induced increase of endogenous antioxidants, such as α-tocopherol, in the hippocampus was detected, suggesting an augmentation of neuroprotective mechanisms in early aging. Our comprehensive imaging approach visualized heterogeneous age-induced metabolic perturbations in mitochondrial function, neurotransmission, and lipid signaling, not always attenuated by acetylcholinesterase inhibition.

Proteomic Profile of Mouse Brain Aging Contributions to Mitochondrial Dysfunction, DNA Oxidative Damage, Loss of Neurotrophic Factor, and Synaptic and Ribosomal Proteins

The deleterious effects of aging on the brain remain to be fully elucidated. In the present study, proteomic changes of young (4-month) and aged (16-month) B6129SF2/J male mouse hippocampus and cerebral cortex were investigated by using nano liquid chromatography tandem mass spectrometry (NanoLC-ESI-MS/MS) combined with tandem mass tag (TMT) labeling technology. Compared with the young animals, 390 hippocampal proteins (121 increased and 269 decreased) and 258 cortical proteins (149 increased and 109 decreased) changed significantly in the aged mouse. Bioinformatic analysis indicated that these proteins are mainly involved in mitochondrial functions (FIS1, DRP1), oxidative stress (PRDX6, GSTP1, and GSTM1), synapses (SYT12, GLUR2), ribosome (RPL4, RPS3), cytoskeletal integrity, transcriptional regulation, and GTPase function. The mitochondrial fission-related proteins FIS1 and DRP1 were significantly increased in the hippocampus and cerebral cortex of the aged mice. Further results in the hippocampus showed that ATP content was significantly reduced in aged mice. A neurotrophin brain-derived neurotrophic factor (BNDF), a protein closely related with synaptic plasticity and memory, was also significantly decreased in the hippocampus of the aged mice, with the tendency of synaptic protein markers including complexin-2, synaptophysin, GLUR2, PSD95, NMDAR2A, and NMDAR1. More interestingly, 8-hydroxydeoxyguanosine (8-OHdG), a marker of DNA oxidative damage, increased as shown by immunofluorescence staining. In summary, we demonstrated that aging is associated with systemic changes involving mitochondrial dysfunction, energy reduction, oxidative stress, loss of neurotrophic factor, synaptic proteins, and ribosomal proteins, as well as molecular deficits involved in various physiological/pathological processes.

Quantitative proteomics to study aging in rabbit liver

Aging globally effects cellular and organismal metabolism across a range of mammalian species, including humans and rabbits. Rabbits (Oryctolagus cuniculus are an attractive model system of aging due to their genetic similarity with humans and their short lifespans. This model can be used to understand metabolic changes in aging especially in major organs such as liver where we detected pronounced variations in fat metabolism, mitochondrial dysfunction, and protein degradation. Such changes in the liver are consistent across several mammalian species however in rabbits the downstream effects of these changes have not yet been explored. We have applied proteomics to study changes in the liver proteins from young, middle, and old age rabbits using a multiplexing cPILOT strategy. This resulted in the identification of 2,586 liver proteins, among which 45 proteins had significant p < 0.05) changes with aging. Seven proteins were differentially-expressed at all ages and include fatty acid binding protein, aldehyde dehydrogenase, enoyl-CoA hydratase, 3-hydroxyacyl CoA dehydrogenase, apolipoprotein C3, peroxisomal sarcosine oxidase, adhesion G-protein coupled receptor, and glutamate ionotropic receptor kinate. Insights to how alterations in metabolism affect protein expression in liver have been gained and demonstrate the utility of rabbit as a model of aging.

Proteome profiling in the hippocampus, medial prefrontal cortex, and striatum of aging rat

Decrease in multiple functions occurs in the brain with aging, all of which can contribute to age-related cognitive and locomotor impairments. Brain atrophy specifically in hippocampus, medial prefrontal cortex (mPFC), and striatum, can contribute to this age-associated decline in function. Our recent metabolomics analysis showed age-related changes in these brain regions. To further understand the aging processes, analysis using a proteomics approach was carried out. This study was conducted to identify proteome profiles in the hippocampus, mPFC, and striatum of 14-, 18-, 23-, and 27-month-old rats. Proteomics analysis using ultrahigh performance liquid chromatography coupled with Q Exactive HF Orbitrap mass spectrometry identified 1074 proteins in the hippocampus, 871 proteins in the mPFC, and 241 proteins in the striatum. Of these proteins, 97 in the hippocampus, 25 in mPFC, and 5 in striatum were differentially expressed with age. The altered proteins were classified into three ontologies (cellular component, molecular function, and biological process) containing 44, 38, and 35 functional groups in the hippocampus, mPFC, and striatum, respectively. Most of these altered proteins participate in oxidative phosphorylation (e.g. cytochrome c oxidase and ATP synthase), glutathione metabolism (e.g. peroxiredoxins), or calcium signaling pathway (e.g. protein S100B and calmodulin). The most prominent changes were observed in the oldest animals. These results suggest that alterations in oxidative phosphorylation, glutathione metabolism, and calcium signaling pathway are involved in cognitive and locomotor impairments in aging.

Metabolomics study of the therapeutic mechanism of Schisandra chinensis lignans on aging rats induced by d-galactose

Objective

The aim of this study was to evaluate the antiaging effect of Schisandra chinensis lignans (SCL) by analyzing the characteristics in the serum of d-galactose (d-gal)-induced rats.

Methods

Forty male Wistar rats were randomly divided into control group, d-gal model group, low-dose SCL group (50 mg/kg/d), medium-dose SCL group (100 mg/kg/d), and high-dose SCL group (200 mg/kg/d). A serum metabolomics analysis method based on rapid resolution liquid chromatography coupled with quadruple-time-of-flight mass spectrometry was carried out to study the characteristics of d-gal-induced aging rats and evaluate the antiaging effects of SCL, and multivariate statistical analysis was performed for pattern recognition and characteristic metabolites identification. The relative levels of p19, p53, and p21 genes in the brain tissue were measured by quantitative real-time polymerase chain reaction for investigating the underlying mechanism.

Results

Metabolomics analysis showed that 15 biomarkers were identified and 13 of them recovered to the normal levels after the administration of SCL. Based on the pathway analysis, the antiaging mechanisms of SCL might be involved in the following metabolic pathways: energy, amino acid, lipid, and phospholipid metabolism. Furthermore, SCL significantly inhibited the mRNA expression level of p19, p53, and p21 in the brain of aging rats induced by d-gal.

Conclusion

These results suggest that SCL can delay rat aging induced by d-gal through multiple pathways.