Targeted Metabolomic Analysis in Alzheimer's Disease Plasma and Brain Tissue in Non-Hispanic Whites

The bile acid profile

As a large and structurally diverse family of small molecules, bile acids play a crucial role in regulating lipid, glucose, and energy metabolism. In the human body, bile acids share a similar chemical structure with many isomers, exhibit little difference in polarity, and possess various physiological activities. The types and contents of bile acids present in different diseases vary significantly. Therefore, comprehensive and accurate detection of the content of various types of bile acids in different biological samples can not only provide new insights into the pathogenesis of diseases but also facilitate the exploration of novel strategies for disease diagnosis, treatment, and prognosis. The detection of disease-induced changes in bile acid profiles has emerged as a prominent research focus in recent years. Concurrently, targeted metabolomics methods utilizing high-performance liquid chromatography-mass spectrometry (HPLC-MS) have progressively established themselves as the predominant technology for the separation and detection of bile acids. Bile acid profiles will increasingly play an important role in diagnosis and guidance in the future as the relationship between disease and changes in bile acid profiles becomes clearer. This highlights the growing diagnostic value of bile acid profiles and their potential to guide clinical decision-making. This review aims to explore the significance of bile acid profiles in clinical diagnosis from four perspectives: the synthesis and metabolism of bile acids, techniques for detecting bile acid profiles, changes in bile acid profiles associated with diseases, and the challenges and future prospects of applying bile acid profiles in clinical settings.

Longitudinal characterization of the muscle metabolome in dairy cows during the transition from lactation cessation to lactation resumption

Skeletal muscle is vital in maintaining metabolic homeostasis and adapting to the physiological needs of pregnancy and lactation. Despite advancements in understanding metabolic changes in dairy cows around calving and early lactation, there are still gaps in our knowledge, especially concerning muscle metabolism and the changes associated with drying off. This study aimed to characterize the skeletal muscle metabolome in the context of the dietary and metabolic changes occurring during the transition from the cessation of lactation to the resumption of lactation in dairy cows. Twelve Holstein dairy cows housed in tiestalls were dried off 6 wk before the expected calving date. Cows were individually fed ad libitum TMR composed of grass silage, corn silage, and concentrate during lactation and of corn silage, barley straw, and concentrate during the dry period. The metabolome was characterized in skeletal muscle samples (M. longissimus dorsi) collected on wk -7 (9 d before dry-off), -5 (6 d after dry-off), and wk -1, and wk 1 relative to calving. The targeted metabolomics approach was conducted using the MxP Quant 500 kit (Biocrates Life Sciences AG) with liquid chromatography, flow injection, and electrospray ionization triple quadrupole mass spectrometry. Statistical analysis on the muscle metabolite data was performed using MetaboAnalyst 5.0, which allowed us to conduct various multivariate analyses such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), informative heat map generation, and hierarchical clustering. The statistical analysis revealed a clear separation between pregnancy (wk -7, -5, and -1) and postcalving (wk 1). Starting 5 wk before calving and continuing through the first week thereafter, the concentration of 3-methylhistidine (3-MH) in the muscle increased. This coincided with an increase in the concentrations of 11 AA (Phe, His, Tyr, Trp, Arg, Asn, Leu, Ile, Gly, Ser, and Thr) in the first week after calving, whereas Gln decreased. l-Arginine pathway metabolites (homoarginine, ornithine, citrulline, and asymmetric dimethylarginine), betaine, and sarcosine followed a similar pattern, increasing from wk -7 to -5, but decreasing from wk -1 to 1. The transition from pregnancy to lactation was associated with an increase in concentrations of the long-chain acylcarnitine species C16, C16:1, C18, and C18:1 in the muscle, whereas the concentrations of phosphatidylcholine and sphingomyelin in the muscle remained stable. The significant changes observed in the metabolome mainly concerned the AA and AA-related metabolites, indicating muscle protein breakdown in the first week after calving. The metabolites produced by the l-Arg pathway might contribute to regulating skeletal muscle mass and function in periparturient dairy cows. The elevated concentrations of long-chain acylcarnitine species in the muscle in the first week after calving suggest incomplete fatty acid oxidation, likely due to insufficient metabolic adaptation in response to the fatty acid load around the time of calving.

Exploration of plasma biomarkers for Alzheimer's disease by targeted lipid metabolomics based on nuclear magnetic resonance (NMR) spectroscopy

Alzheimer's disease (AD) is the most common cause of dementia, but the disease lacks convenient and cost-effective alternative biomarkers currently. We utilized targeted lipid metabolomics based on nuclear magnetic resonance (NMR) spectroscopy to identify plasma biomarkers in AD patients. Our study was a cross-sectional study that enrolled 58 AD patients and 40 matched health controls (HCs). Firstly, we identified plasma lipid metabolites that were significantly different between the two groups based on P < 0.05 and variable importance in the projection (VIP) > 1. Then we examined the correlation between the lipid metabolites and cognitive function using partial correlation analysis and assessed the diagnostic ability of the lipid metabolites using receiver operating characteristic (ROC) curves. Seventeen lipoproteins showed significant differences between AD patients and HCs among 114 lipid metabolites. All 17 lipoproteins were subtypes of low-density lipoprotein (LDL). Among them, LDL-3 particle number, LDL-3 apolipoprotein-B, LDL-3 phospholipids, LDL free cholesterol and LDL phospholipids were significantly correlated with cognitive function. The ROC curves showed that LDL-2 triglycerides (TG) and LDL-3 TG could significantly distinguish AD patients from HCs, with the area under the curve (AUC) above 0.7. In addition, we explored a strategy of combined diagnosis that significantly improved the diagnostic efficacy for AD (AUC = 0.879). Our study provides insight into the lipoprotein alterations associated with AD and potential biomarkers for its diagnosis and cognitive function assessment.

Protein restriction slows the development and progression of pathology in a mouse model of Alzheimer's disease

Dietary protein is a critical regulator of metabolic health and aging. Low protein diets are associated with healthy aging in humans, and dietary protein restriction extends the lifespan and healthspan of mice. In this study, we examined the effect of protein restriction (PR) on metabolic health and the development and progression of Alzheimer's disease (AD) in the 3xTg mouse model of AD. Here, we show that PR promotes leanness and glycemic control in 3xTg mice, specifically rescuing the glucose intolerance of 3xTg females. PR induces sex-specific alterations in circulating and brain metabolites, downregulating sphingolipid subclasses in 3xTg females. PR also reduces AD pathology and mTORC1 activity, increases autophagy, and improves the cognition of 3xTg mice. Finally, PR improves the survival of 3xTg mice. Our results suggest that PR or pharmaceutical interventions that mimic the effects of this diet may hold promise as a treatment for AD.

Metabolomic and Physiological Effects of a Cardiorenal Protective Diet Intervention in African American Adults with Chronic Kidney Disease

Chronic kidney disease (CKD) impacts 14% of adults in the United States, and African American (AA) individuals are disproportionately affected, with more than 3 times higher risk of kidney failure as compared to White individuals. This study evaluated the effects of base-producing fruit and vegetables (FVs) on cardiorenal outcomes in AA persons with CKD and hypertension (HTN) in a low socioeconomic area. The "Cardiorenal Protective Diet" prospective randomized trial evaluated the effects of a 6-week, community-based FV intervention compared to a waitlist control (WL) in 91 AA adults (age = 58.3 ± 10.1 years, 66% female, 48% income ≤ USD 25K). Biometric and metabolomic variables were collected at baseline and 6 weeks post-intervention. The change in health outcomes for both groups was statistically insignificant (p > 0.05), though small reductions in albumin to creatinine ratio, body mass index, total cholesterol, and systolic blood pressure were observed in the FV group. Metabolomic profiling identified key markers (p < 0.05), including C3, C5, 1-Met-His, kynurenine, PC ae 38:5, and choline, indicating kidney function decline in the WL group. Overall, delivering a directed cardiorenal protective diet intervention improved cardiorenal outcomes in AA adults with CKD and HTN. Additionally, metabolomic profiling may serve as a prognostic technique for the early identification of biomarkers as indicators for worsening CKD and increased CVD risk.

A machine learning algorithm based on circulating metabolic biomarkers offers improved predictions of neurological diseases

BACKGROUND AND AIMS

A machine learning algorithm based on circulating metabolic biomarkers for the predictions of neurological diseases (NLDs) is lacking. To develop a machine learning algorithm to compare the performance of a metabolic biomarker-based model with that of a clinical model based on conventional risk factors for predicting three NLDs: dementia, Parkinson's disease (PD), and Alzheimer's disease (AD).

MATERIALS AND METHODS

The eXtreme Gradient Boosting (XGBoost) algorithm was used to construct a metabolic biomarker-based model (metabolic model), a clinical risk factor-based model (clinical model), and a combined model for the prediction of the three NLDs. Risk discrimination (c-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index values were determined for each model.

RESULTS

The results indicate that incorporation of metabolic biomarkers into the clinical model afforded a model with improved performance in the prediction of dementia, AD, and PD, as demonstrated by NRI values of 0.159 (0.039-0.279), 0.113 (0.005-0.176), and 0.201 (-0.021-0.423), respectively; and IDI values of 0.098 (0.073-0.122), 0.070 (0.049-0.090), and 0.085 (0.068-0.101), respectively.

CONCLUSION

The performance of the model based on circulating NMR spectroscopy-detected metabolic biomarkers was better than that of the clinical model in the prediction of dementia, AD, and PD.

Protein restriction slows the development and progression of Alzheimer's disease in mice

Dietary protein is a critical regulator of metabolic health and aging. Low protein diets are associated with healthy aging in humans, and many independent groups of researchers have shown that dietary protein restriction (PR) extends the lifespan and healthspan of mice. Here, we examined the effect of PR on metabolic health and the development and progression of Alzheimer's disease (AD) in the 3xTg mouse model of AD. We found that PR has metabolic benefits for 3xTg mice and non-transgenic controls of both sexes, promoting leanness and glycemic control in 3xTg mice and rescuing the glucose intolerance of 3xTg females. We found that PR induces sex-specific alterations in circulating metabolites and in the brain metabolome and lipidome, downregulating sphingolipid subclasses including ceramides, glucosylceramides, and sphingomyelins in 3xTg females. Consumption of a PR diet starting at 6 months of age reduced AD pathology in conjunction with reduced mTORC1 activity, increased autophagy, and had cognitive benefits for 3xTg mice. Finally, PR improved the survival of 3xTg mice. Our results demonstrate that PR slows the progression of AD at molecular and pathological levels, preserves cognition in this mouse model of AD, and suggests that PR or pharmaceutical interventions that mimic the effects of this diet may hold promise as a treatment for AD.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Microbiota-gut-brain axis and its therapeutic applications in neurodegenerative diseases

The human gastrointestinal tract is populated with a diverse microbial community. The vast genetic and metabolic potential of the gut microbiome underpins its ubiquity in nearly every aspect of human biology, including health maintenance, development, aging, and disease. The advent of new sequencing technologies and culture-independent methods has allowed researchers to move beyond correlative studies toward mechanistic explorations to shed light on microbiome-host interactions. Evidence has unveiled the bidirectional communication between the gut microbiome and the central nervous system, referred to as the "microbiota-gut-brain axis". The microbiota-gut-brain axis represents an important regulator of glial functions, making it an actionable target to ameliorate the development and progression of neurodegenerative diseases. In this review, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases. As the gut microbiome provides essential cues to microglia, astrocytes, and oligodendrocytes, we examine the communications between gut microbiota and these glial cells during healthy states and neurodegenerative diseases. Subsequently, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases using a metabolite-centric approach, while also examining the role of gut microbiota-related neurotransmitters and gut hormones. Next, we examine the potential of targeting the intestinal barrier, blood-brain barrier, meninges, and peripheral immune system to counteract glial dysfunction in neurodegeneration. Finally, we conclude by assessing the pre-clinical and clinical evidence of probiotics, prebiotics, and fecal microbiota transplantation in neurodegenerative diseases. A thorough comprehension of the microbiota-gut-brain axis will foster the development of effective therapeutic interventions for the management of neurodegenerative diseases.

In vivo neuroprotective capacity of a Dunaliella salina extract - comprehensive transcriptomics and metabolomics study

In this study, an exhaustive chemical characterization of a Dunaliella salina (DS) microalga extract obtained using supercritical fluids has been performed, and its neuroprotective capacity has been evaluated in vivo using an Alzheimer's disease (AD) transgenic model of Caenorhabditis elegans (strain CL4176). More than 350 compounds were annotated in the studied DS extract, with triacylglycerols, free fatty acids (FAs), carotenoids, apocarotenoids and glycerol being the most abundant. DS extract significantly protects C. elegans in a dose-dependent manner against Aβ-peptide paralysis toxicity, after 32 h, 53% of treated worms at 50 µg/mL were not paralyzed. This concentration was selected to further evaluate the transcriptomics and metabolomics changes after 26 h by using advanced analytical methodologies. The RNA-Seq data showed an alteration of 150 genes, mainly related to the stress and detoxification responses, and the retinol and lipid metabolism. The comprehensive metabolomics and lipidomics analyses allowed the identification of 793 intracellular metabolites, of which 69 were significantly altered compared to non-treated control animals. Among them, different unsaturated FAs, lysophosphatidylethanolamines, nucleosides, dipeptides and modified amino acids that have been previously reported as beneficial during AD progression, were assigned. These compounds could explain the neuroprotective capacity observed, thus, providing with new evidences of the protection mechanisms of this promising extract.

Lipid metabolism and oxidative stress in patients with Alzheimer's disease and amnestic mild cognitive impairment

Lipid metabolism and oxidative stress are key mechanisms in Alzheimer's disease (AD). The link between plasma lipid metabolites and oxidative stress in AD patients is poorly understood. This study was to identify markers that distinguish AD and amnestic mild cognitive impairment (aMCI) from NC, and to reveal potential links between lipid metabolites and oxidative stress. We performed non-targeted lipid metabolism analysis of plasma from patients with AD, aMCI, and NC using LC-MS/MS. The plasma malondialdehyde (MDA), glutathione peroxidase (GSH-Px), and superoxide dismutase (SOD) levels were assessed. We found significant differences in lipid metabolism between patients with AD and aMCI compared to those in NC. AD severity is associated with lipid metabolites, especially TG (18:0_16:0_18:0) + NH4, TG (18:0_16:0_16:0) + NH4, LPC(16:1e)-CH3, and PE (20:0_20:4)-H. SPH (d16:0) + H, SPH (d18:1) + H, and SPH (d18:0) + H were high-performance markers to distinguish AD and aMCI from NC. The AUC of three SPHs combined to predict AD was 0.990, with specificity and sensitivity as 0.949 and 1, respectively; the AUC of three SPHs combined to predict aMCI was 0.934, with specificity and sensitivity as 0.900, 0.981, respectively. Plasma MDA concentrations were higher in the AD group than in the NC group (p = 0.003), whereas plasma SOD levels were lower in the AD (p < 0.001) and aMCI (p = 0.045) groups than in NC, and GSH-Px activity were higher in the AD group than in the aMCI group (p = 0.007). In addition, lipid metabolites and oxidative stress are widely associated. In conclusion, this study distinguished serum lipid metabolism in AD, aMCI, and NC subjects, highlighting that the three SPHs can distinguish AD and aMCI from NC. Additionally, AD patients showed elevated oxidative stress, and there are complex interactions between lipid metabolites and oxidative stress.

Comparing Symmetric Dimethylarginine and Amyloid-β42 as Predictors of Alzheimer's Disease Development

Background

Physicians may soon be able to diagnose Alzheimer's disease (AD) in its early stages using fluid biomarkers like amyloid. However, it is acknowledged that additional biomarkers need to be characterized which would facilitate earlier monitoring of AD pathogenesis.

Objective

To determine if a potential novel inflammation biomarker for AD, symmetric dimethylarginine, has utility as a baseline serum biomarker for discriminating prodromal AD from cognitively unimpaired controls in comparison to cerebrospinal fluid amyloid-β42 (Aβ42).

Methods

Data including demographics, magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography scans, Mini-Mental State Examination and Functional Activities Questionnaire scores, and biomarker concentrations were obtained from the Alzheimer's Disease Neuroimaging Initiative for a total of 146 prodromal AD participants and 108 cognitively unimpaired controls.

Results

Aβ42 (p = 0.65) and symmetric dimethylarginine (p = 0.45) were unable to predict age-matched cognitively unimpaired controls and prodromal AD participants. Aβ42 was negatively associated with regional brain atrophy and hypometabolism as well as cognitive and functional decline in cognitively unimpaired control participants (p < 0.05) that generally decreased in time. There were no significant associations between Aβ42 and symmetric dimethylarginine with imaging or neurocognitive biomarkers in prodromal AD patients.

Conclusions

Correlations were smaller between Aβ42 and neuropathological biomarkers over time and were absent in prodromal AD participants, suggesting a plateau effect dependent on age and disease stage. Evidence supporting symmetric dimethylarginine as a novel biomarker for AD as a single measurement was not found.

Metabolic profiling of Alzheimer's disease: Untargeted metabolomics analysis of plasma samples

Alzheimer's disease (AD) is often not recognized or is diagnosed very late, which significantly reduces the effectiveness of available pharmacological treatments. Metabolomic analyzes have great potential for improving existing knowledge about the pathogenesis and etiology of AD and represent a novel approach towards discovering biomarkers that could be used for diagnosis, prognosis, and therapy monitoring. In this study, we applied the untargeted metabolomic approach to investigate the changes in biochemical pathways related to AD pathology. We used gas chromatography and liquid chromatography coupled to mass spectrometry (GC-MS and LC-MS, respectively) to identify metabolites whose levels have changed in subjects with AD diagnosis (N = 40) compared to healthy controls (N = 40) and individuals with mild cognitive impairment (MCI, N = 40). The GC-MS identified significant differences between groups in levels of metabolites belonging to the classes of benzene and substituted derivatives, carboxylic acids and derivatives, fatty acyls, hydroxy acids and derivatives, keto acids and derivatives, and organooxygen compounds. Most of the compounds identified by the LC-MS were various fatty acyls, glycerolipids and glycerophospholipids. All of these compounds were decreased in AD patients and in subjects with MCI compared to healthy controls. The results of the study indicate disturbed metabolism of lipids and amino acids and an imbalance of metabolites involved in energy metabolism in individuals diagnosed with AD, compared to healthy controls and MCI subjects.

Plasma metabolites of aromatic amino acids associate with clinical severity and gut microbiota of Parkinson's disease

Gut microbial proteolytic metabolism has been reportedly altered in Parkinson's disease (PD). However, the circulating aromatic amino acids (AAA) described in PD are inconsistent. Here we aimed to investigate plasma AAA profiles in a large cohort of PD patients, and examine their correlations with clinical severity and gut microbiota changes. We enrolled 500 participants including 250 PD patients and 250 neurologically normal controls. Plasma metabolites were measured using liquid chromatography mass spectrometry. Faecal samples were newly collected from 154 PD patients for microbiota shotgun metagenomic sequencing combined with data derived from 96 PD patients reported before. Data were collected regarding diet, medications, and motor and non-motor symptoms of PD. Compared to controls, PD patients had higher plasma AAA levels, including phenylacetylglutamine (PAGln), p-cresol sulfate (Pcs), p-cresol glucuronide (Pcg), and indoxyl sulfate (IS). Multivariable linear regression analyses, with adjustment for age, sex, and medications, revealed that the plasma levels of PAGln (coefficient 4.49, 95% CI 0.40-8.58, P = 0.032) and Pcg (coefficient 1.79, 95% CI 0.07-3.52, P = 0.042) positively correlated with motor symptom severity but not cognitive function. After correcting for abovementioned potential confounders, these AAA metabolites were also associated with the occurrence of constipation in PD patients (all P < 0.05). Furthermore, plasma levels of AAA metabolites were correlated with the abundance of specific gut microbiota species, including Bacteroides sp. CF01-10NS, Bacteroides vulgatus, and Clostridium sp. AF50-3. In conclusion, elevated plasma AAA metabolite levels correlated with disease characteristics in PD, suggesting that upregulated proteolytic metabolism may contribute to the pathophysiology of PD.

A Targeted Mass Spectrometry Approach to Identify Peripheral Changes in Metabolic Pathways of Patients with Alzheimer's Disease

Alzheimer's disease (AD), a neurodegenerative disorder, is the most common cause of dementia in the elderly population. Since its original description, there has been intense debate regarding the factors that trigger its pathology. It is becoming apparent that AD is more than a brain disease and harms the whole-body metabolism. We analyzed 630 polar and apolar metabolites in the blood of 20 patients with AD and 20 healthy individuals, to determine whether the composition of plasma metabolites could offer additional indicators to evaluate any alterations in the metabolic pathways related to the illness. Multivariate statistical analysis showed that there were at least 25 significantly dysregulated metabolites in patients with AD compared with the controls. Two membrane lipid components, glycerophospholipids and ceramide, were upregulated, whereas glutamic acid, other phospholipids, and sphingolipids were downregulated. The data were analyzed using metabolite set enrichment analysis and pathway analysis using the KEGG library. The results showed that at least five pathways involved in the metabolism of polar compounds were dysregulated in patients with AD. Conversely, the lipid pathways did not show significant alterations. These results support the possibility of using metabolome analysis to understand alterations in the metabolic pathways related to AD pathophysiology.

Targeted metabolomic analysis in Parkinson's disease brain frontal cortex and putamen with relation to cognitive impairment

We performed liquid chromatography tandem mass spectrometry analysis with the targeted metabolomic kit Biocrates MxP Quant 500, in human brain cortex (Brodmann area 9) and putamen, to reveal metabolic changes characteristic of Parkinson's disease (PD) and PD-related cognitive decline. This case-control study involved 101 subjects (33 PD without dementia, 32 PD with dementia (cortex only), 36 controls). We found changes associated with PD, cognitive status, levodopa levels, and disease progression. The affected pathways include neurotransmitters, bile acids, homocysteine metabolism, amino acids, TCA cycle, polyamines, β-alanine metabolism, fatty acids, acylcarnitines, ceramides, phosphatidylcholines, and several microbiome-derived metabolites. Previously reported levodopa-related homocysteine accumulation in cortex still best explains the dementia status in PD, which can be modified by dietary supplementation. Further investigation is needed to reveal the exact mechanisms behind this pathological change.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.

Metabolic and Transcriptomic Signatures of the Acute Psychological Stress Response in the Mouse Brain

Acute stress response triggers various physiological responses such as energy mobilization to meet metabolic demands. However, the underlying molecular changes in the brain remain largely obscure. Here, we used a brief water avoidance stress (WAS) to elicit an acute stress response in mice. By employing RNA-sequencing and metabolomics profiling, we investigated the acute stress-induced molecular changes in the mouse whole brain. The aberrant expression of 60 genes was detected in the brain tissues of WAS-exposed mice. Functional analyses showed that the aberrantly expressed genes were enriched in various processes such as superoxide metabolism. In our global metabolomic profiling, a total of 43 brain metabolites were significantly altered by acute WAS. Metabolic pathways upregulated from WAS-exposed brain tissues relative to control samples included lipolysis, eicosanoid biosynthesis, and endocannabinoid synthesis. Acute WAS also elevated the levels of branched-chain amino acids, 5-aminovalerates, 4-hydroxy-nonenal-glutathione as well as mannose, suggesting complex metabolic changes in the brain. The observed molecular events in the present study provide a valuable resource that can help us better understand how acute psychological stress impacts neural functions.

Metabolic and Transcriptomic Changes in the Mouse Brain in Response to Short-Term High-Fat Metabolic Stress

The chronic consumption of diets rich in saturated fats leads to obesity and associated metabolic disorders including diabetes and atherosclerosis. Intake of a high-fat diet (HFD) is also recognized to dysregulate neural functions such as cognition, mood, and behavior. However, the effects of short-term high-fat diets on the brain are elusive. Here, we investigated molecular changes in the mouse brain following an acute HFD for 10 days by employing RNA sequencing and metabolomics profiling. Aberrant expressions of 92 genes were detected in the brain tissues of acute HFD-exposed mice. The differentially expressed genes were enriched for various pathways and processes such as superoxide metabolism. In our global metabolomic profiling, a total of 59 metabolites were significantly altered by the acute HFD. Metabolic pathways upregulated from HFD-exposed brain tissues relative to control samples included oxidative stress, oxidized polyunsaturated fatty acids, amino acid metabolism (e.g., branched-chain amino acid catabolism, and lysine metabolism), and the gut microbiome. Acute HFD also elevated levels of N-acetylated amino acids, urea cycle metabolites, and uracil metabolites, further suggesting complex changes in nitrogen metabolism. The observed molecular events in the present study provide a valuable resource that can help us better understand how acute HFD stress impacts brain homeostasis.

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.

Insulin resistance in Alzheimer's disease: The genetics and metabolomics links

Alzheimer's disease (AD) is a neurodegenerative disease with significant socioeconomic burden worldwide. Although genetics and environmental factors play a role, AD is highly associated with insulin resistance (IR) disorders such as metabolic syndrome (MS), obesity, and type two diabetes mellitus (T2DM). These findings highlight a shared pathogenesis. The use of metabolomics as a downstream systems' biology (omics) approach can help to identify these shared metabolic traits and assist in the early identification of at-risk groups and potentially guide therapy. Targeting the shared AD-IR metabolic trait with lifestyle interventions and pharmacological treatments may offer promising AD therapeutic approach. In this narrative review, we reviewed the literature on the AD-IR pathogenic link, the shared genetics and metabolomics biomarkers between AD and IR disorders, as well as the lifestyle interventions and pharmacological treatments which target this pathogenic link.

Alterations in Peripheral Metabolites as Key Actors in Alzheimer's Disease

Growing evidence supports that Alzheimer's disease (AD) could be regarded as a metabolic disease, accompanying central and peripheral metabolic disturbance. Nowadays, exploring novel and potentially alternative hallmarks for AD is needed. Peripheral metabolites based on blood and gut may provide new biochemical insights about disease mechanisms. These metabolites can influence brain energy homeostasis, maintain gut mucosal integrity, and regulate the host immune system, which may further play a key role in modulating the cognitive function and behavior of AD. Recently, metabolomics has been used to identify key AD-related metabolic changes and define metabolic changes during AD disease trajectory. This review aims to summarize the key blood- and microbial-derived metabolites that are altered in AD and identify the potential metabolic biomarkers of AD, which will provide future targets for precision therapeutic modulation.

The potential of the gut microbiome for identifying Alzheimer's disease diagnostic biomarkers and future therapies

Being isolated from the peripheral system by the blood-brain barrier, the brain has long been considered a completely impervious tissue. However, recent findings show that the gut microbiome (GM) influences gastrointestinal and brain disorders such as Alzheimer's disease (AD). Despite several hypotheses, such as neuroinflammation, tau hyperphosphorylation, amyloid plaques, neurofibrillary tangles, and oxidative stress, being proposed to explain the origin and progression of AD, the pathogenesis remains incompletely understood. Epigenetic, molecular, and pathological studies suggest that GM influences AD development and have endeavored to find predictive, sensitive, non-invasive, and accurate biomarkers for early disease diagnosis and monitoring of progression. Given the growing interest in the involvement of GM in AD, current research endeavors to identify prospective gut biomarkers for both preclinical and clinical diagnoses, as well as targeted therapy techniques. Here, we discuss the most recent findings on gut changes in AD, microbiome-based biomarkers, prospective clinical diagnostic uses, and targeted therapy approaches. Furthermore, we addressed herbal components, which could provide a new venue for AD diagnostic and therapy research.

A Perspective: Challenges in Dementia Research

Although dementia is a common and devastating disease that has been studied intensely for more than 100 years, no effective disease modifying treatment has been found. At this impasse, new approaches are important. The purpose of this paper is to provide, in the context of current research, one clinician's perspective regarding important challenges in the field in the form of specific challenges. These challenges not only illustrate the scope of the problems inherent in finding treatments for dementia, but can also be specific targets to foster discussion, criticism and new research. One common theme is the need to transform research activities from small projects in individual laboratories/clinics to larger multinational projects, in which each clinician and researcher works as an integral part. This transformation will require collaboration between researchers, large corporations, regulatory/governmental authorities and the general population, as well as significant financial investments. However, the costs of transforming the approach are small in comparison with the cost of dementia.