Cerebrospinal Fluid Spermidine, Glutamine and Putrescine Predict Postoperative Delirium Following Elective Orthopaedic Surgery

Analysis of cerebrospinal fluid metabolites affected by WenDanTang based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry

WenDanTang (WDT) is a Chinese herbal formula used to treat various diseases, including neurodegenerative diseases. However, the neuroprotective metabolic pathways and the components involved in this process are not fully understood. In this study, we examined the neuroprotective metabolic pathways of WDT in rat brains using cerebrospinal fluid metabolomics and ultra-high-performance liquid chromatography-high-resolution mass spectrometry. Twelve rats were randomly divided into a WDT (administrated with WDT solution) and a control group. The ultra-high-performance liquid chromatography technique was used to explore the components of the WDT solution and cerebrospinal fluid, and secondary mass spectra of cerebrospinal fluid were used to identify possible brain-incorporating components after WDT. The results of the differential metabolism analysis showed that eight metabolites were typically altered (all p < 0.05). By comparing the secondary mass spectra of the cerebrospinal fluid of rats and WDT solution, two possible brain-incorporating components of WDT, stachydrine and α-methoxyphenylacetic acid, were identified. The data also suggested that WDT affects nucleotide metabolism, glutathione metabolism, and B-vitamin metabolic pathways, the central differential metabolic pathways. These data suggest that WDT protects neurons through its active components, such as stachydrine, and regulates biochemical metabolism to affect the brain's energy metabolism and antioxidant capacity.

From Recognition to Remedy: The Significance of Biomarkers in Neurodegenerative Disease Pathology

With the inexorable aging of the global populace, neurodegenerative diseases (NDs) like Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) pose escalating challenges, which are underscored by their socioeconomic repercussions. A pivotal aspect in addressing these challenges lies in the elucidation and application of biomarkers for timely diagnosis, vigilant monitoring, and effective treatment modalities. This review delineates the quintessence of biomarkers in the realm of NDs, elucidating various classifications and their indispensable roles. Particularly, the quest for novel biomarkers in AD, transcending traditional markers in PD, and the frontier of biomarker research in ALS are scrutinized. Emergent susceptibility and trait markers herald a new era of personalized medicine, promising enhanced treatment initiation especially in cases of SOD1-ALS. The discourse extends to diagnostic and state markers, revolutionizing early detection and monitoring, alongside progression markers that unveil the trajectory of NDs, propelling forward the potential for tailored interventions. The synergy between burgeoning technologies and innovative techniques like -omics, histologic assessments, and imaging is spotlighted, underscoring their pivotal roles in biomarker discovery. Reflecting on the progress hitherto, the review underscores the exigent need for multidisciplinary collaborations to surmount the challenges ahead, accelerate biomarker discovery, and herald a new epoch of understanding and managing NDs. Through a panoramic lens, this article endeavors to provide a comprehensive insight into the burgeoning field of biomarkers in NDs, spotlighting the promise they hold in transforming the diagnostic landscape, enhancing disease management, and illuminating the pathway toward efficacious therapeutic interventions.

Application of Multiple Omics to Understand Postoperative Delirium Pathophysiology in Humans

Delirium, an acute change in cognition, is common, morbid, and costly, particularly among hospitalized older adults. Despite growing knowledge of its epidemiology, far less is known about delirium pathophysiology. Initial work understanding delirium pathogenesis has focused on assaying single or a limited subset of molecules or genetic loci. Recent technological advances at the forefront of biomarker and drug target discovery have facilitated application of multiple "omics" approaches aimed to provide a more complete understanding of complex disease processes such as delirium. At its basic level, "omics" involves comparison of genes (genomics, epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), or lipids (lipidomics) in biological fluids or tissues obtained from patients who have a certain condition (i.e., delirium) and those who do not. Multi-omics analyses of these various types of molecules combined with machine learning and systems biology enable the discovery of biomarkers, biological pathways, and predictors of delirium, thus elucidating its pathophysiology. This review provides an overview of the most recent omics techniques, their current impact on identifying delirium biomarkers, and future potential in enhancing our understanding of delirium pathogenesis. We summarize challenges in identification of specific biomarkers of delirium and, more importantly, in discovering the mechanisms underlying delirium pathophysiology. Based on mounting evidence, we highlight a heightened inflammatory response as one common pathway in delirium risk and progression, and we suggest other promising biological mechanisms that have recently emerged. Advanced multiple omics approaches coupled with bioinformatics methodologies have great promise to yield important discoveries that will advance delirium research.

Biomarkers of delirium risk in older adults: a systematic review and meta-analysis

Delirium is a neuropsychiatric syndrome associated with increased morbidity and mortality in older patients. The aim of this study was to review predictive biomarkers of delirium in older patients to gain insights into the pathophysiology of this syndrome and provide guidance for future studies. Two authors independently and systematically searched MEDLINE, Embase, Cochrane Library, Web of Science and Scopus databases up to August 2021. A total of 32 studies were included. Only 6 studies were eligible for the meta-analysis, pooled results showed a significant increase in some serum biomarkers (C-reactive protein [CRP], tumour necrosis factor alpha [TNF-α] and interleukin-6 [IL-6]) among patients with delirium (odds ratio = 1.88, 95% CI 1.01 to 1.637; I2 = 76.75%). Although current evidence does not favour the use of any particular biomarker, serum CRP, TNF-α, and IL-6 were the most consistent biomarkers of delirium in older patients.

Bioinformatics insights into the genes and pathways on severe COVID-19 pathology in patients with comorbidities

Background: Coronavirus disease (COVID-19) infection is known for its severe clinical pathogenesis among individuals with pre-existing comorbidities. However, the molecular basis of this observation remains elusive. Thus, this study aimed to map key genes and pathway alterations in patients with COVID-19 and comorbidities using robust systems biology approaches. Methods: The publicly available genome-wide transcriptomic datasets from 120 COVID-19 patients, 281 patients suffering from different comorbidities (like cardiovascular diseases, atherosclerosis, diabetes, and obesity), and 252 patients with different infectious diseases of the lung (respiratory syncytial virus, influenza, and MERS) were studied using a range of systems biology approaches like differential gene expression, gene ontology (GO), pathway enrichment, functional similarity, mouse phenotypic analysis and drug target identification. Results: By cross-mapping the differentially expressed genes (DEGs) across different datasets, we mapped 274 shared genes to severe symptoms of COVID-19 patients or with comorbidities alone. GO terms and functional pathway analysis highlighted genes in dysregulated pathways of immune response, interleukin signaling, FCGR activation, regulation of cytokines, chemokines secretion, and leukocyte migration. Using network topology parameters, phenotype associations, and functional similarity analysis with ACE2 and TMPRSS2-two key receptors for this virus-we identified 17 genes with high connectivity (CXCL10, IDO1, LEPR, MME, PTAFR, PTGS2, MAOB, PDE4B, PLA2G2A, COL5A1, ICAM1, SERPINE1, ABCB1, IL1R1, ITGAL, NCAM1 and PRKD1) potentially contributing to the clinical severity of COVID-19 infection in patients with comorbidities. These genes are predicted to be tractable and/or with many existing approved inhibitors, modulators, and enzymes as drugs. Conclusion: By systemic implementation of computational methods, this study identified potential candidate genes and pathways likely to confer disease severity in COVID-19 patients with pre-existing comorbidities. Our findings pave the way to develop targeted repurposed therapies in COVID-19 patients.

The inter-relationship between delirium and dementia: the importance of delirium prevention

Delirium and dementia are two frequent causes of cognitive impairment among older adults and have a distinct, complex and interconnected relationship. Delirium is an acute confusional state characterized by inattention, cognitive dysfunction and an altered level of consciousness, whereas dementia is an insidious, chronic and progressive loss of a previously acquired cognitive ability. People with dementia have a higher risk of developing delirium than the general population, and the occurrence of delirium is an independent risk factor for subsequent development of dementia. Furthermore, delirium in individuals with dementia can accelerate the trajectory of the underlying cognitive decline. Delirium prevention strategies can reduce the incidence of delirium and associated adverse outcomes, including falls and functional decline. Therefore, delirium might represent a modifiable risk factor for dementia, and interventions that prevent or minimize delirium might also reduce or prevent long-term cognitive impairment. Additionally, understanding the pathophysiology of delirium and the connection between delirium and dementia might ultimately lead to additional treatments for both conditions. In this Review, we explore mechanisms that might be common to both delirium and dementia by reviewing evidence on shared biomarkers, and we discuss the importance of delirium recognition and prevention in people with dementia.

In this Review, Fong and Inouye explore mechanisms that might be common to both delirium and dementia. They present delirium as a possible modifiable risk factor for dementia and discuss the importance of delirium prevention strategies in reducing this risk.

Delirium and dementia are frequent causes of cognitive impairment among older adults and have a distinct, complex and interconnected relationship.

Delirium prevention strategies have been shown to reduce not only the incidence of delirium but also the incidence of adverse outcomes associated with delirium such as falls and functional decline.

Adverse outcomes associated with delirium, such as the onset of dementia symptoms in individuals with preclinical dementia, and/or the acceleration of cognitive decline in individuals with dementia might also be delayed by the implementation of delirium prevention strategies.

Evidence regarding the association of systemic inflammatory and neuroinflammatory biomarkers with delirium is variable, possibly as a result of co-occurring dementia pathology or disruption of the blood–brain barrier.

Alzheimer disease pathology, even prior to the onset of symptoms, might have an effect on delirium risk, with potential mechanisms including neuroinflammation and gene–protein interactions with the APOE ε4 allele.

Novel strategies, including proteomics, multi-omics, neuroimaging, transcranial magnetic stimulation and EEG, are beginning to reveal how changes in cerebral blood flow, spectral power and connectivity can be associated with delirium; further work is needed to expand these findings to patients with delirium superimposed upon dementia.

The Influence of Orthopedic Surgery on Circulating Metabolite Levels, and their Associations with the Incidence of Postoperative Delirium

The mechanisms underlying the occurrence of postoperative delirium development are unclear and measurement of plasma metabolites may improve understanding of its causes. Participants (n = 54) matched for age and gender were sampled from an observational cohort study investigating postoperative delirium. Participants were ≥65 years without a diagnosis of dementia and presented for primary elective hip or knee arthroplasty. Plasma samples collected pre- and postoperatively were grouped as either control (n = 26, aged: 75.8 ± 5.2) or delirium (n = 28, aged: 76.2 ± 5.7). Widespread changes in plasma metabolite levels occurred following surgery. The only metabolites significantly differing between corresponding control and delirium samples were ornithine and spermine. In delirium cases, ornithine was 17.6% higher preoperatively, and spermine was 12.0% higher postoperatively. Changes were not associated with various perioperative factors. In binary logistic regression modeling, these two metabolites did not confer a significantly increased risk of delirium. These findings support the hypothesis that disturbed polyamine metabolism is an underlying factor in delirium that warrants further investigation.

High Resolution Magic Angle Spinning Proton NMR Study of Alzheimer's Disease with Mouse Models

Alzheimer's disease (AD) is a crippling condition that affects millions of elderly adults each year, yet there remains a serious need for improved methods of diagnosis. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease; however, studies of human brain tissue metabolomics are challenging, due to sample limitations and ethical considerations. Comprehensive comparisons of imaging measurements in animal models to identify similarities and differences between aging- and AD-associated metabolic changes should thus be tested and validated for future human non-invasive studies. In this paper, we present the results of our highresolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) studies of AD and wild-type (WT) mouse models, based on animal age, brain regions, including cortex vs. hippocampus, and disease status. Our findings suggest the ability of HRMAS NMR to differentiate between AD and WT mice using brain metabolomics, which potentially can be implemented in in vivo evaluations.

The neuropsychological profile of delirium vulnerability: A systematic review and meta-analysis

Delirium is a common neurocognitive disorder in hospitalised older adults with substantial negative consequences. Impaired global cognition is a well-established delirium risk factor. However, poor performance on attention tests and higher intra-subject variability may be more sensitive delirium risk factors, given the disorder is characterised by a fluctuating course and attentional deficits. We systematically searched databases (Embase, PsycINFO, MEDLINE) and 44 studies satisfied inclusion criteria. Random-effects meta-analysis models showed poor performance in all cognitive domains except perception was significantly associated with incident delirium. Largest effects were for orientation (g=-1.20) and construction and motor performance (g=-0.60). These effects were no longer significant in the subgroup without pre-existing cognitive impairment, where executive functions and verbal functions and language skills were associated with incident delirium. A small, non-significant association between intra-subject variability and incident delirium was found (g=0.42). Cognitive domain specific tests may be quicker and more sensitive predictors of incident delirium. This pattern of neuropsychological findings supports the proposition that vulnerability for delirium manifests as a dysfunction of whole-brain information integration.

Phenotypes and subphenotypes of delirium: a review of current categorisations and suggestions for progression

Delirium is a clinical syndrome occurring in heterogeneous patient populations. It affects 45-87% of critical care patients and is often associated with adverse outcomes including acquired dementia, institutionalisation, and death. Despite an exponential increase in delirium research in recent years, the pathophysiological mechanisms resulting in the clinical presentation of delirium are still hypotheses. Efforts have been made to categorise the delirium spectrum into clinically meaningful subgroups (subphenotypes), using psychomotor subtypes such as hypoactive, hyperactive, and mixed, for example, and also inflammatory and non-inflammatory delirium. Delirium remains, however, a constellation of symptoms resulting from a variety of risk factors and precipitants with currently no successful targeted pharmacological treatment. Identifying specific clinical and biological subphenotypes will greatly improve understanding of the relationship between the clinical symptoms and the putative pathways and thus risk factors, precipitants, natural history, and biological mechanism. This will facilitate risk factor mitigation, identification of potential methods for interventional studies, and informed patient and family counselling. Here, we review evidence to date and propose a framework to identify subphenotypes. Endotype identification may be done by clustering symptoms with their biological mechanism, which will facilitate research of targeted treatments. In order to achieve identification of delirium subphenotypes, the following steps must be taken: (1) robust records of symptoms must be kept at a clinical level. (2) Global collaboration must facilitate large, heterogeneous research cohorts. (3) Patients must be clustered for identification, validation, and mapping of subphenotype stability.

Metabolomics and computational analysis of the role of monoamine oxidase activity in delirium and SARS-COV-2 infection

Delirium is an acute change in attention and cognition occurring in ~ 65% of severe SARS-CoV-2 cases. It is also common following surgery and an indicator of brain vulnerability and risk for the development of dementia. In this work we analyzed the underlying role of metabolism in delirium-susceptibility in the postoperative setting using metabolomic profiling of cerebrospinal fluid and blood taken from the same patients prior to planned orthopaedic surgery. Distance correlation analysis and Random Forest (RF) feature selection were used to determine changes in metabolic networks. We found significant concentration differences in several amino acids, acylcarnitines and polyamines linking delirium-prone patients to known factors in Alzheimer's disease such as monoamine oxidase B (MAOB) protein. Subsequent computational structural comparison between MAOB and angiotensin converting enzyme 2 as well as protein-protein docking analysis showed that there potentially is strong binding of SARS-CoV-2 spike protein to MAOB. The possibility that SARS-CoV-2 influences MAOB activity leading to the observed neurological and platelet-based complications of SARS-CoV-2 infection requires further investigation.

Targeted metabolomics analysis of postoperative delirium

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered "valine, leucine, and isoleucine biosynthesis" at PREOP and "citrate cycle" at POD2 as the most significantly enriched pathways (false discovery rate < 0.05). Perturbations in energy metabolism and amino acid synthesis pathways may be associated with postoperative delirium and suggest potential mechanisms for delirium pathogenesis. Our results could lead to the development of a metabolomic delirium predictor.

Effect of unsaturated fatty acids on glycation product formation pathways (Ⅰ) the role of oleic acid

Research on advanced glycation end-products (AGEs) and their formation pathways in food processing has gradually increased because AGEs are associated with human health, especially with involvement of lipids. In this study, radicals and glycation products were detected via electron spin resonance (ESR) and ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) respectively. The correlation of important intermediates was used to explain the effect of oleic acid (OA) on the glycation products and pathways. The results indicated OA participation decreased the content of stable radicals and glycosyl compounds in Maillard Reaction (MR). The oxidation of OA produced active radicals, and electron transfer caused lysine to transform radical form. These radicals participated in the formation of fructosyllysine (FL) with glucose (Glc) via the MR. The participation of OA is acted as inhibiting the way of Glc autoxidation and promoting the glycation pathway from FL to 3-deoxyglucosone (3-DG) to fluorescent-AGEs. Orthogonal projection to latent structures discriminant analysis results indicated that 3-DG, D-glucosone and methylglyoxal are key products in discriminating the glycation reaction.

Intensive Care Unit Delirium in Surgical Patients Is Associated with Upregulation in Tryptophan Metabolism

INTRODUCTION

In intensive care unit (ICU) patients, delirium is frequent, occurs early in ICU admission, and is associated with poor outcomes. Risk models based on clinical factors have shown variable performance in terms of predictive ability. Identification of a candidate biomarker that associates with delirium may lead to a better understanding of disease mechanism, validation biomarker studies, and the ability to develop targeted interventions for prevention and treatment of delirium. This study analyzed metabolite concentrations early in the course of ICU admission to assess the association with delirium onset.

METHODS

Within 24 hours of ICU admission, blood samples for global and targeted metabolomics analyses in adult surgical ICU patients were collected prospectively. Metabolites were determined using mass spectrometry/ultra-high-pressure liquid chromatography and analyzed in patients with delirium and a group of controls matched on age, sex, and admission Sequential Organ Function Assessment (SOFA) score.

RESULTS

Patients in the study (65 per group) were a mean age of 59 years, had a median SOFA score of 6, and were most commonly admitted to the ICU following major trauma. In the delirium group, median onset of delirium was 3 (interquartile range 1-6) days, and the most common delirium subtype was mixed (56%). Kynurenic acid was significantly increased, and tryptophan concentration was significantly decreased in the delirium group (p=0.04). The ratio of kynurenine-to-tryptophan concentration was significantly higher in the delirium group (p=0.005).

CONCLUSIONS

Evidence of upregulation was found in the tryptophan metabolic pathway in delirious patients because tryptophan concentrations were lower, tryptophan metabolites were higher, and the kynurenine-to-tryptophan ratio was increased. These findings suggest a role of increased inflammation and accumulation of neurotoxic metabolites in the pathogenesis of ICU delirium. Future studies should target this pathway to validate metabolites in the tryptophan pathway as risk biomarkers in patients with ICU delirium.

The Differences of Serum Metabolites Between Patients With Early-Stage Alzheimer's Disease and Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is regarded as a transition phase between normal aging and Alzheimer's disease (AD). Identification of novel and non-invasive biomarkers that can distinguish AD at an early stage from MCI is warranted for therapeutic and support planning. The goal of this study was to identify the differences of serum metabolomic profiles between MCI and early-stage AD, which could be potential non-invasive biomarkers for early diagnosis of AD.

Methods: The subjects enrolled in the study were classified into two diagnostic groups: MCI (n = 40) and early-stage AD (n = 40). Targeted metabolomics analysis of serum samples was performed using the Biocrates Absolute-IDQ P180 kit. Targeted metabolic data were analyzed by TargetLynx, and MetIDQ software was applied to integrate the metabolites by automated calculation of metabolite concentrations.

Results: The datasets of targeted metabolite analysis were analyzed by the orthogonal-projection-to-latent-structure–discriminant-analysis (OPLS-DA) model. The OPLS-DA score plots demonstrated considerable separation between the MCI and early-stage AD patients. The levels of pimelylcarnitine, putrescine, SM (OH) C24:1, and SM C24:0 were significantly lower, whereas the levels of acetylornithine, methionine sulfoxide, and PC ae C44:3 were significantly higher in early-stage AD patients as compared with MCI patients. Receiver operating characteristic curve analysis of a combination of three lipid metabolites [SM (OH) C24:1, SM C24:0, and PC ae C44:3] showed an acceptable discrimination between the early-stage AD and MCI patients (area under the curve = 0.788).

Conclusions: Our results characterized the differences of serum metabolic profiles between MCI and early-stage AD patients. The positive findings from this study indicate that the minimally invasive method of blood sampling may help to identify patients with AD at an early stage from those with MCI.