Metabolomic alterations in the blood plasma of older adults with mild cognitive impairment and Alzheimer's disease (from the Nakayama Study)

Alterations in the gut microbiome and metabolome in elderly patients with postoperative delirium: A prospective nested case-control study

OBJECTIVE

To elucidate the role of gut microbiota and their metabolites, including short-chain fatty acids (SCFAs) and targeted metabolomics, in the development of postoperative delirium (POD) in elderly patients.

DESIGN

Prospective nested case-control study.

SETTING

A Chinese tertiary hospital.

PARTICIPANTS

Elderly patients underwent elective orthopedic surgery.

METHODS

Participants were assessed for POD using the 3-min Diagnostic Confusion Assessment Method (3D-CAM). Biological samples, including feces and plasma, were collected. A 1:1 propensity score matching (PSM) was conducted to match POD cases with non-POD cases. 16S ribosomal RNA (rRNA) sequencing and metabolomics analyses were performed on the matched case series. Predictive models were developed using logistic regression analysis, incorporating bacterial genera and metabolites that exhibited significant differences between the two groups as predictors.

RESULTS

Among 234 patients who were followed up, 41 were diagnosed with POD. A total of 39 cases were matched for both the POD and control groups using PSM. No significant differences were found in the α-diversity and β-diversity of preoperative gut microbiota between the two groups. However, specific bacterial genera, including Romboutsia, Bacteroides faecalis, Blautia mucilaginosa, and Eggerthella lenta, exhibited significant differences. The risk of POD was associated with higher postoperative plasma levels of propionic acid, histidine, aspartate, and ornithine. Logistic regression and receiver operating characteristic curve analyses revealed that indicators derived from the gut microbiota and metabolites could predict POD, with an area under the curve of 0.8413 (95 % confidence interval (CI): 0.7393-0.9434).

CONCLUSION

This study identified four preoperative bacterial genera and four postoperative plasma metabolites associated with an increased risk of POD in elderly orthopedic patients, suggesting the potential of gut microbiota and metabolite profiles as biomarkers for improving risk prediction and guiding interventions.

Dysregulation of lipid metabolism, energy production, and oxidative stress in myalgic encephalomyelitis/chronic fatigue syndrome, Gulf War Syndrome and fibromyalgia

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Gulf War Syndrome (GWS), and Fibromyalgia (FM) are complex, chronic illnesses with overlapping clinical features. Symptoms that are reported across these conditions include post-exertional malaise (PEM), fatigue, and pain, yet the etiology of these illnesses remains largely unknown. Diagnosis is challenging in patients with these conditions as definitive biomarkers are lacking; patients are required to meet clinical criteria and often undergo lengthy testing to exclude other conditions, a process that is often prolonged, costly, and burdensome for patients. The identification of reliable validated biomarkers could facilitate earlier and more accurate diagnosis and drive the development of targeted pharmacological therapies that might address the underlying pathophysiology of these diseases. Major driving forces for biomarker identification are the advancing fields of metabolomics and proteomics that allow for comprehensive characterization of metabolites and proteins in biological specimens. Recent technological developments in these areas enable high-throughput analysis of thousands of metabolites and proteins from a variety of biological samples and model systems, that provides a powerful approach to unraveling the metabolic phenotypes associated with these complex diseases. Emerging evidence suggests that ME/CFS, GWS, and FM are all characterized by disturbances in metabolic pathways, particularly those related to energy production, lipid metabolism, and oxidative stress. Altered levels of key metabolites in these pathways have been reported in studies highlighting potential common biochemical abnormalities. The precise mechanisms driving altered metabolic pathways in ME/CFS, GWS, and FM remain to be elucidated; however, the elevated oxidative stress observed across these illnesses may contribute to symptoms and offer a potential target for therapeutic intervention. Investigating the mechanisms, and their role in the disease process, could provide insights into disease pathogenesis and reveal novel treatment targets. As such, comprehensive metabolomic and proteomic analyses are crucial for advancing the understanding of these conditions in-order to identify both common, and unique, metabolic alterations that could serve as diagnostic markers or therapeutic targets.

Alterations of amino acids in older adults with Alzheimer's Disease and Vascular Dementia

Metabolomics provide a promising tool for understanding dementia pathogenesis and identifying novel biomarkers. This study aimed to identify amino acid biomarkers for Alzheimer's Disease (AD) and Vascular Dementia (VD). By amino acid metabolomics, the concentrations of amino acids were determined in the serum of AD and VD patients as well as age-matched healthy controls. Several differences in the concentration of amino acids were observed in AD patients compared to both healthy controls and VD patients. However, no significant distinction was found between healthy controls and VD patients. Considering comorbidities, cystine levels were higher in AD than in VD among non-diabetic patients, but not in those with diabetes. Notably, creatine, spermidine, cystine, and tyrosine demonstrated favorable results in decision curve analyses and good discriminative performances, suggesting their potential for clinical application. These fundings give novel perspectives of serum amino acids for predicting metabolic pathways in AD and VD pathogenesis.

A Principal Component Analysis of Metabolome and Cognitive Decline Among Japanese Older Adults: Cross-sectional Analysis Using Tohoku Medical Megabank Cohort Study Data

BACKGROUND

Dementia is the leading cause of disability and imposes a significant burden on society. Previous studies have suggested an association between metabolites and cognitive decline. Although the metabolite composition differs between Western and Asian populations, studies targeting Asian populations remain scarce.

METHODS

This cross-sectional study used data from a cohort survey of community-dwelling older adults aged ≥60 years living in Miyagi, Japan, conducted by Tohoku Medical Megabank Organization between 2013 and 2016. Forty-three metabolite variables quantified using nuclear magnetic resonance spectroscopy were used as explanatory variables. Dependent variable was the presence of cognitive decline (≤23 points), assessed by the Mini-Mental State Examination. Principal component (PC) analysis was performed to reduce the dimensionality of metabolite variables, followed by logistic regression analysis to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for cognitive decline.

RESULTS

A total of 2,940 participants were included (men: 49.0%, mean age: 67.6 years). Among them, 1.9% showed cognitive decline. The first 12 PC components (PC1-PC12) accounted for 71.7% of the total variance. Multivariate analysis showed that PC1, which mainly represented essential amino acids, was associated with lower odds of cognitive decline (OR 0.89; 95% CI, 0.80-0.98). PC2, which mainly included ketone bodies, was associated with cognitive decline (OR 1.29; 95% CI, 1.11-1.51). PC3, which included amino acids, was associated with lower odds of cognitive decline (OR 0.81; 95% CI, 0.66-0.99).

CONCLUSION

Amino acids are protectively associated with cognitive decline, whereas ketone metabolites are associated with higher odds of cognitive decline.

Serum metabolome profiling in patients with mild cognitive impairment reveals sex differences in lipid metabolism

Alzheimer's disease (AD) affects more women than men. Although women live longer than men, it is not longevity alone, but other factors, including metabolic changes, that contribute to the higher risk of AD in women. Metabolic pathways have been implicated in AD progression, but studies to date examined targeted pathways, leaving many metabolites unmeasured. Sex is often a neglected biological variable, and most metabolomic studies were not designed to investigate sex differences in metabolomic profiles. Here, we performed untargeted metabolomic profiling of sera from male and female patients with mild cognitive impairment (MCI), a common precursor to AD, and matched controls. We discovered significant metabolic changes in individuals with MCI, and found several pathways that were strongly associated with sex. Peptide energy metabolism demonstrated sexual dimorphism. Lipid pathways exhibited the strongest differences between female and male MCI patients, including specific phosphatidylcholine lipids, lysophospholipids, long-chain fatty acids, and monoacylglycerols. 1-palmitoleoyl glycerol and 1-arachidonoyl glycerol were higher in female MCI subjects than in male MCI subjects with no differences between control males and females. Conversely, specific dicarboxylic fatty acids were lower in female MCI subjects than male MCI subjects. In cultured astrocytes, 1-arachidonoyl glycerol promoted phosphorylation of the transcriptional regulator sphingosine kinase 2, which was inhibited by the transient receptor potential vanilloid 1 receptor antagonists, as well as chromatin remodelling. Overall, we identified novel sex-specific metabolites in MCI patients that could serve as biomarkers of MCI in both sexes, help further define AD etiology, and reveal new potential prevention strategies for AD.

Serum metabolome profiling in patients with mild cognitive impairment reveals sex differences in lipid metabolism

Alzheimer's disease (AD) affects more women than men. Although women live longer than men, it is not longevity alone, but other factors, including metabolic changes, that contribute to the higher risk of AD in women. Metabolic pathways have been implicated in AD progression, but studies to date examined targeted pathways, leaving many metabolites unmeasured. Sex is often a neglected biological variable, and most metabolomic studies were not designed to investigate sex differences in metabolomic profiles. Here, we performed untargeted metabolomic profiling of sera from male and female patients with mild cognitive impairment (MCI), a common precursor to AD, and matched controls. We discovered significant metabolic changes in individuals with MCI, and found several pathways that were strongly associated with sex. Peptide energy metabolism demonstrated sexual dimorphism. Lipid pathways exhibited the strongest differences between female and male MCI patients, including specific phosphatidylcholine lipids, lysophospholipids, long-chain fatty acids, and monoacylglycerols. 1-palmitoleoyl glycerol and 1-arachidonoyl glycerol were higher in female MCI subjects than in male MCI subjects with no differences between control males and females. Conversely, specific dicarboxylic fatty acids were lower in female MCI subjects than male MCI subjects. In cultured astrocytes, 1-arachidonoyl glycerol promoted phosphorylation of the transcriptional regulator sphingosine kinase 2, which was inhibited by the transient receptor potential vanilloid 1 receptor antagonists, as well as chromatin remodelling. Overall, we identified novel sex-specific metabolites in MCI patients that could serve as biomarkers of MCI in both sexes, help further define AD etiology, and reveal new potential prevention strategies for AD.

Decreased plasma nicotinamide and altered NAD+ metabolism in glial cells surrounding Aβ plaques in a mouse model of Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease and a leading cause of senile dementia. Amyloid-β (Aβ) accumulation triggers chronic neuroinflammation, initiating AD pathogenesis. Recent clinical trials for anti-Aβ immunotherapy underscore that blood-based biomarkers have significant advantages and applicability over conventional diagnostics and are an unmet clinical need. To further advance ongoing clinical trials and identify novel therapeutic targets for AD, developing additional plasma biomarkers closely associated with pathogenic mechanisms downstream of Aβ accumulation is critically important. To identify plasma metabolites reflective of neuroinflammation caused by Aβ pathology, we performed untargeted metabolomic analyses of the plasma by capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS) and analyzed the potential roles of the identified metabolic changes in the brain neuroinflammatory response using the female App knock-in (AppNLGF) mouse model of Aβ amyloidosis. The CE-TOFMS analysis of plasma samples from female wild-type (WT) and AppNLGF mice revealed that plasma levels of nicotinamide, a nicotinamide adenine dinucleotide (NAD+) precursor, were decreased in AppNLGF mice, and altered metabolite profiles were enriched for nicotinate/nicotinamide metabolism. In AppNLGF mouse brains, NAD+ levels were unaltered, but mRNA levels of NAD+-synthesizing nicotinate phosphoribosyltransferase (Naprt) and NAD+-degrading Cd38 genes were increased. These enzymes were induced in reactive astrocytes and microglia surrounding Aβ plaques in the cortex and hippocampus of female AppNLGF mouse brains, suggesting neuroinflammation increases NAD+ metabolism. This study suggests plasma nicotinamide could be indicative of the neuroinflammatory response and that nicotinate and nicotinamide metabolism are potential therapeutic targets for AD, by targeting both neuroinflammation and neuroprotection.

A review on polyamines as promising next-generation neuroprotective and anti-aging therapy

Neurodegenerative disorders are diseases characterized by progressive degeneration of neurons and associated structures and are a major global issue growing more widespread as the global population's average age increases. Despite several investigations on their etiology, the specific cause of these disorders remains unknown. However, there are few symptomatic therapies to treat these disorders. Polyamines (PAs) (putrescine, spermidine, and spermine) are being studied for their role in neuroprotection, aging and cognitive impairment. They are ubiquitous polycations which have relatively higher concentrations in the brain and possess pleiotropic biochemical activities, including regulation of gene expression, ion channels, mitochondria Ca2+ transport, autophagy induction, programmed cell death, and many more. Their cellular content is tightly regulated, and substantial evidence indicates that their altered levels and metabolism are strongly implicated in aging, stress, cognitive dysfunction, and neurodegenerative disorders. In addition, dietary polyamine supplementation has been reported to induce anti-aging effects, anti-oxidant effects, and improve locomotor abnormalities, and cognitive dysfunction. Thus, restoring the polyamine level is considered a promising pharmacological strategy to counteract neurodegeneration. This review highlights PAs' physiological role and the molecular mechanism underpinning their proposed neuroprotective effect in aging and neurodegenerative disorders.

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults

Alzheimer's disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical Fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS) and nuclear magnetic resonance (NMR) metabolomics. The 2 metabolomics data sets were analyzed by Data Integration Analysis for Biomarker discovery using Latent approaches for Omics studies (DIABLO), to identify a minimum set of metabolites that could describe cognitive decline status. NMR or SFC-HRMS data alone cannot predict cognitive decline. However, among the 320 metabolites identified, a statistical method that integrated the 2 data sets enabled the identification of a minimal signature of 9 metabolites (3-hydroxybutyrate, citrate, succinate, acetone, methionine, glucose, serine, sphingomyelin d18:1/C26:0 and triglyceride C48:3) with a statistically significant ability to predict cognitive decline more than 3 years before decline. This metabolic fingerprint obtained during this exploratory study may help to predict amyloid-positive individuals who will develop cognitive decline. Due to the high prevalence of brain amyloid-positivity in older adults, identifying adults who will have cognitive decline will enable the development of personalized and early interventions.

Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer's disease: a cross-sectional metabolomic analysis

Background

In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis.

Methods

A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 ± 8.2 years), probable AD (n = 15; 76.1 ± 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 ± 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data.

Results

The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809-0.996; sensitivity = 0.90; specificity = 0.90).

Discussion

Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts.

A Metabolomics Analysis of a Novel Phenotype of Older Adults at Higher Risk of Dementia

Background

Older adults presenting with dual-decline in cognition and walking speed face a 6-fold higher risk for dementia compared with those showing no decline. We hypothesized that the metabolomics profile of dual-decliners would be unique even before they show signs of decline in cognition and gait speed.

Objective

The objective of this study was to determine if plasma metabolomics signatures can discriminate dual-decliners from no decliners, purely cognitive decliners, and purely motor decliners prior to decline.

Methods

A retrospective cross-sectional study using baseline plasma for untargeted metabolomics analyses to investigate early signals of later dual-decline status in study participants (n = 76) with convenient sampling. Dual-decline was operationalized as decline in gait speed (>10 cm/s) and cognition (>2 points decline in Montreal Cognitive Assessment score) on at least two consecutive 6-monthly assessments. The participants' decliner status was evaluated 3 years after the blood sample was collected. Pair-wise comparison of detected compounds was completed using principal components and hierarchical clustering analyses.

Results

Analyses did not detect any cluster separation in untargeted metabolomes across baseline groups. However, follow-up analyses of specific molecules detected 4 compounds (17-Hydroxy-12-(hydroxymethyl)-10-oxo-8 oxapentacyclomethyl hexopyranoside, Fleroxacin, Oleic acid, and 5xi-11,12-Dihydroxyabieta-8(14),9(11),12-trien-20-oic acid) were at significantly higher concentration among the dual-decliners compared to non-decliners. The pure cognitive decliner group had significantly lower concentration of six compounds (1,3-nonanediol acetate, 4-(2-carboxyethyl)-2-methoxyphenyl beta-D-glucopyranosiduronic acid, oleic acid, 2E-3-[4-(sulfo-oxy)phenyl] acrylic acid, palmitelaidic acid, and myristoleic acid) compared to the non-decliner group.

Conclusions

The unique metabolomics profile of dual-decliners warrants follow-up metabolomics analysis. Results may point to modifiable pathways.

Circulating arginine metabolites in Alzheimer's disease and vascular dementia: A systematic review and meta-analysis

BACKGROUND

Alterations in nitric oxide (NO) synthesis have been reported in Alzheimer's disease and vascular dementia. However, as the measurement of NO in biological samples is analytically challenging, alternative, stable circulatory biomarkers of NO synthesis may be useful to unravel new pathophysiological mechanisms and treatment targets in dementia.

METHODS

We conducted a systematic review and meta-analysis of the circulating concentrations of arginine metabolites linked to NO synthesis, arginine, citrulline, asymmetric (ADMA) and symmetric (SDMA) dimethylarginine, and ornithine, in Alzheimer's disease and vascular dementia. We searched for relevant studies in PubMed, Scopus, and Web of Science from inception to the 31st of May 2023. The JBI checklist and GRADE were used to assess the risk of bias and the certainty of evidence, respectively.

RESULTS

In 14 selected studies, there were no significant between-group differences in arginine and ornithine concentrations. By contrast, compared to controls, patients with dementia had significantly higher ADMA (standard mean difference, SMD=0.62, 95% CI 0.06-1.19, p = 0.029), SDMA (SMD=0.70, 95% CI 0.34-1.35, p<0.001), and citrulline concentrations (SMD=0.50, 95% CI 0.08-0.91, p = 0.018). In subgroup analysis, the effect size was significantly associated with treatment with cholinesterase inhibitors and/or antipsychotics for ADMA, and underlying disorder (Alzheimer's disease), study continent, and analytical method for citrulline.

CONCLUSION

Alterations in ADMA, SDMA, and citrulline, biomarkers of NO synthesis, may be useful to investigate the pathophysiology of different forms of dementia and identify novel therapeutic strategies. (PROSPERO registration number: CRD42023439528).

Analysis of factors related to cognitive impairment in a community-based, complete enumeration survey in Japan: the Nakayama study

BACKGROUND

The number of patients with cognitive disorders is rapidly increasing in the world, becoming not only a medical problem, but also a social problem. There have been many reports that various factors are associated with cognitive dysfunction, but the factors have not yet been fully identified. This was a community-based complete enumeration study which aimed to identify risk and protective factors for dementia.

METHODS

The first phase included all residents aged 65 years or older in a town in Japan. They completed many examinations, such as living conditions questionnaires, physical examination, Mini-Mental State Examination, and brain magnetic resonance imaging. The participants with suspected cognitive impairment underwent additional examinations for detailed evaluation in the second phase. Statistical analysis was performed to identify risk and protective factors for dementia after all participants were diagnosed.

RESULTS

There were 927 participants in the baseline evaluation; 611 (65.9%) were healthy, 165 (17.8%) had mild cognitive impairment (MCI), and 151 (16.3%) had dementia. The age-standardised prevalence of dementia was 9.5%. Statistical analyses for amnestic MCI and Alzheimer's disease showed that risk factors for cognitive decline were diabetes mellitus, low activities of daily living, and living alone, and that protective factors were history of exercise and drinking habit.

CONCLUSION

The present findings suggest that several lifestyle-related diseases and factors are associated with cognitive decline. These results support similar findings from previous studies and will be helpful for preventing dementia in the future.

Metabolic changes in the plasma of mild Alzheimer's disease patients treated with Hachimijiogan

Background: Alzheimer's disease (AD), the most prevalent form of dementia, is a debilitating, progressive neurodegeneration. Amino acids play a wide variety of physiological and pathophysiological roles in the nervous system, and their levels and disorders related to their synthesis have been related to cognitive impairment, the core feature of AD. Our previous multicenter trial showed that hachimijiogan (HJG), a traditional Japanese herbal medicine (Kampo), has an adjuvant effect for Acetylcholine estelase inhibitors (AChEIs) and that it delays the deterioration of the cognitive dysfunction of female patients with mild AD. However, there are aspects of the molecular mechanism(s) by which HJG improves cognitive dysfunction that remain unclear. Objectives: To elucidate through metabolomic analysis the mechanism(s) of HJG for mild AD based on changes in plasma metabolites. Methods: Sixty-seven patients with mild AD were randomly assigned to either an HJG group taking HJG extract 7.5 g/day in addition to AChEI or to a control group treated only with AChEI (HJG:33, Control:34). Blood samples were collected before, 3 months, and 6 months after the first drug administration. Comprehensive metabolomic analyses of plasma samples were done by optimized LC-MS/MS and GC-MS/MS methods. The web-based software MetaboAnalyst 5.0 was used for partial least square-discriminant analysis (PLS-DA) to visualize and compare the dynamics of changes in the concentrations of the identified metabolites. Results: The VIP (Variable Importance in Projection) score of the PLS-DA analysis of female participants revealed a significantly higher increase in plasma metabolite levels after HJG administration for 6 months than was seen in the control group. In univariate analysis, the aspartic acid level of female participants showed a significantly higher increase from baseline after HJG administration for 6 months when compared with the control group. Conclusion: Aspartic acid was a major contributor to the difference between the female HJG and control group participants of this study. Several metabolites were shown to be related to the mechanism of HJG effectiveness for mild AD.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Metabolomic Footprint of Disrupted Energetics and Amino Acid Metabolism in Neurodegenerative Diseases: Perspectives for Early Diagnosis and Monitoring of Therapy

The prevalence of neurodegenerative diseases (NDs) is increasing due to the aging population and improved longevity. They are characterized by a range of pathological hallmarks, including protein aggregation, mitochondrial dysfunction, and oxidative stress. The aim of this review is to summarize the alterations in brain energy and amino acid metabolism in Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD). Based on our findings, we proposed a group of selected metabolites related to disturbed energy or mitochondrial metabolism as potential indicators or predictors of disease. We also discussed the hidden challenges of metabolomics studies in NDs and proposed future directions in this field. We concluded that biochemical parameters of brain energy metabolism disruption (obtained with metabolomics) may have potential application as a diagnostic tool for the diagnosis, prediction, and monitoring of the effectiveness of therapies for NDs. However, more studies are needed to determine the sensitivity of the proposed candidates. We suggested that the most valuable biomarkers for NDs studies could be groups of metabolites combined with other neuroimaging or molecular techniques. To attain clinically applicable results, the integration of metabolomics with other “omic” techniques might be required.