Proteomic Analysis of Preoperative CSF Reveals Risk Biomarkers of Postoperative Delirium

Discovery of Delirium Biomarkers through Minimally Invasive Serum Molecular Fingerprinting

Delirium presents a significant clinical challenge, primarily due to its profound impact on patient outcomes and the limitations of the current diagnostic methods, which are largely subjective. During the COVID-19 pandemic, this challenge was intensified as the frequency of delirium assessments decreased in Intensive Care Units (ICUs), even as the prevalence of delirium among critically ill patients increased. The present study evaluated how the serum molecular fingerprint, as acquired by Fourier-Transform InfraRed (FTIR) spectroscopy, can enable the development of predictive models for delirium. A preliminary univariate analysis of serum FTIR spectra indicated significantly different bands between 26 ICU patients with delirium and 26 patients without, all of whom were admitted with COVID-19. However, these bands resulted in a poorly performing Naïve-Bayes predictive model. Considering the use of a Fast-Correlation-Based Filter for feature selection, it was possible to define a new set of spectral bands with a wider coverage of molecular functional groups. These bands ensured an excellent Naïve-Bayes predictive model, with an AUC, a sensitivity, and a specificity all exceeding 0.92. These spectral bands, acquired through a minimally invasive analysis and obtained rapidly, economically, and in a high-throughput mode, therefore offer significant potential for managing delirium in critically ill patients.

Association of reduced cerebrospinal fluid NPTX2 levels with postoperative delirium in patients undergoing knee/hip replacement: a prospective cohort study

BACKGROUND

Postoperative delirium (POD) is a common complication with poor prognosis in the elderly, but its mechanism has not been fully elucidated. There is evidence that the changes in synaptic activity in the brain are closely related to the occurrence of POD. And neuronal pentraxin 2 (NPTX2) can regulate synaptic activity in vivo.

AIMS

This study aims to explore whether decreased NPTX2 levels affects POD and whether the cerebrospinal fluid (CSF) biomarkers of POD mediate this association.

METHODS

In this prospective cohort study, we interviewed patients with knee/hip replacement 1 day before surgery to collect patient information and assess their cognitive function. CSF was extracted for measuring the CSF levels of NPTX2 and other POD biomarkers on the day of surgery. And postoperative follow-up visits were performed 1-7 days after surgery.

RESULTS

Finally, 560 patients were included in the study. The patients were divided into POD group and NPOD (non-POD) group. The POD group had a median age of 80 years, a female proportion of 45%, a median BMI of 24.1 kg/m2, and a median years of education of 9 years. The Mann-Whitney U test showed that CSF NPTX2 levels were significantly lower in POD group, compared with the NPOD group (P < 0.05). Univariate binary logistic regression analysis showed that reduced CSF levels of NPTX2 protected against POD (crude OR = 0.994, 95% CI 0.993-0.995, P < 0.001). The receiver-operating characteristic (ROC) curve indicated that CSF NPTX2 level had high predictive value for POD. Mediation analyses showed that CSF T-tau (mediating proportion = 21%) and P-tau (mediating proportion = 29%) had significant mediating effects on the association between CSF NPTX2 and POD.

CONCLUSION

CSF NPTX2 levels were associated with the occurrence of POD. Low CSF NPTX2 levels may be an independent protective factor for POD. CSF T-tau and P-tau could mediate the association between CSF NPTX2 and POD occurrence.

CLINICAL TRIAL REGISTRATION

The trial registration number (TRN): ChiCTR2200064740, Date of Registration: 2022-10-15.

Machine learning for prediction of delirium in patients with extensive burns after surgery

AIMS

Machine learning-based identification of key variables and prediction of postoperative delirium in patients with extensive burns.

METHODS

Five hundred and eighteen patients with extensive burns who underwent surgery were included and randomly divided into a training set, a validation set, and a testing set. Multifactorial logistic regression analysis was used to screen for significant variables. Nine prediction models were constructed in the training and validation sets (80% of dataset). The testing set (20% of dataset) was used to further evaluate the model. The area under the receiver operating curve (AUROC) was used to compare model performance. SHapley Additive exPlanations (SHAP) was used to interpret the best one and to externally validate it in another large tertiary hospital.

RESULTS

Seven variables were used in the development of nine prediction models: physical restraint, diabetes, sex, preoperative hemoglobin, acute physiological and chronic health assessment, time in the Burn Intensive Care Unit and total body surface area. Random Forest (RF) outperformed the other eight models in terms of predictive performance (ROC:84.00%) When external validation was performed, RF performed well (accuracy: 77.12%, sensitivity: 67.74% and specificity: 80.46%).

CONCLUSION

The first machine learning-based delirium prediction model for patients with extensive burns was successfully developed and validated. High-risk patients for delirium can be effectively identified and targeted interventions can be made to reduce the incidence of delirium.

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.

Aptamer-Based Proteomics Measuring Preoperative Cerebrospinal Fluid Protein Alterations Associated with Postoperative Delirium

Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to a lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with the development of postoperative delirium in older surgical patients. We employed a nested case-control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort, and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p < 0.05). Due to the limited sample size, these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, and principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identified 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.

Intraoperative plasma proteomic changes in cardiac surgery: In search of biomarkers of post-operative delirium

PURPOSE

Delirium presents a significant healthcare burden. It complicates post-operative care in up to 50% of cardiac surgical patients with worse outcomes, longer hospital stays and higher cost of care. Moreover, the nature of delirium following cardiac surgery with cardiopulmonary bypass (CPB) remains unclear, the underlying pathobiology is poorly understood, status quo diagnostic methods are subjective, and diagnostic biomarkers are currently lacking.

OBJECTIVE

To identify diagnostic biomarkers of delirium and for insights into possible neuronal pathomechanisms.

EXPERIMENTAL DESIGN

Comparative proteomic analyses were performed on plasma samples from a nested matched cohort of patients who underwent cardiac surgery. Validation by targeted proteomics was performed in an independent set of samples. Biomarkers were assessed for biological functions and diagnostic accuracy.

RESULTS

Forty-seven percent of subjects demonstrated delirium. Of 3803 proteins identified from patient samples by multiplexed quantitative proteomics, 16 were identified as signatures of exposure to CPB, and 11 biomarkers distinguished delirium cases from non-cases (AuROC = 93%). Notable among these biomarkers are C-reactive protein, serum amyloid A-1 and cathepsin-B.

CONCLUSIONS AND CLINICAL RELEVANCE

The interplay of systemic and central inflammatory markers sheds new light on delirium pathogenesis. This work suggests that accurate identification of cases may be achievable using panels of biomarkers.

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.

Preclinical and translational models for delirium: Recommendations for future research from the NIDUS delirium network

Delirium is a common, morbid, and costly syndrome that is closely linked to Alzheimer's disease (AD) and AD-related dementias (ADRD) as a risk factor and outcome. Human studies of delirium have advanced our knowledge of delirium incidence and prevalence, risk factors, biomarkers, outcomes, prevention, and management. However, understanding of delirium neurobiology remains limited. Preclinical and translational models for delirium, while challenging to develop, could advance our knowledge of delirium neurobiology and inform the development of new prevention and treatment approaches. We discuss the use of preclinical and translational animal models in delirium, focusing on (1) a review of current animal models, (2) challenges and strategies for replicating elements of human delirium in animals, and (3) the utility of biofluid, neurophysiology, and neuroimaging translational markers in animals. We conclude with recommendations for the development and validation of preclinical and translational models for delirium, with the goal of advancing awareness in this important field.

Preoperative serum ribose concentrations may be associated with postoperative delirium in older patients with a hip fracture

BACKGROUND

Postoperative delirium (POD) is a common postoperative neurocognitive complication, especially in older patients. However, satisfactory biomarkers for predicting individual risks of POD have not been confirmed. D-ribose involvement in protein glycation and aggregation plays a pivotal role in age-related neurodegenerative disorders such as Alzheimer's disease.

OBJECTIVES

This study aimed to determine whether serum D-ribose concentrations contribute to the early diagnosis of POD. We also discuss the probable mechanisms underlying the development of POD.

METHODS

110 older patients with hip fracture who had undergone internal fixation or hip replacement under general anesthesia and had completed our assessments were selected. Preoperative venous blood (4 ml) was collected before the induction of anesthesia. Postoperative venous blood was obtained at 07:00 and 20:00 h on postoperative day 1 and at 20:00 h on postoperative day 2. On the first 2 postoperative days, the patients were assessed twice daily (at 8:00 and 20:00 h on each day) using the Confusion Assessment Method-Chinese Revision.

RESULTS

15 patients were finally diagnosed with POD. We also included 15 patients without POD who were matched with the recruited patients with POD (1:1) on the basis of age, sex, body mass index and the Mini-Mental State Examination score. Serum ribose concentrations were measured by high-performance liquid chromatography. The demographic characteristics of the groups were matched. Preoperative serum ribose concentrations were significantly higher in patients with POD than in those without POD (p < 0.05) and were also an independent risk factor for POD. Moreover, when the preoperative serum ribose concentration doubled, the risk of POD increased by 1.672 times.

CONCLUSIONS

These results indicate that the serum D-ribose concentration may be a potential predictive molecular biomarker for POD, and provide useful information for further pathological mechanism studies.

Proteomics for the Discovery of Clinical Delirium Biomarkers: A Systematic Review of Major Studies

Delirium represents a significant health care burden, diagnosed in more than 2 million elderly Americans each year. In the surgical population, delirium remains the most common complication among elderly patients, and is associated with longer hospital stays, higher costs of care, increased mortality, and functional impairment. The pathomechanism of disease is poorly understood, with current diagnostic approaches somewhat subjective and arbitrary, and definitive diagnostic biomarkers are currently lacking. Despite the recent interest in delirium research, biomarker discovery for it remains new. Most attempts to discover biomarkers are targeted studies that seek to assess the involvement of one or more members of a focused panel of candidates in delirium. For a more unbiased, system-biology view, we searched literature from Medical Literature Analysis and Retrieval System Online (MEDLINE), Cochrane Central, Web of Science, SCOPUS, and Dimensions between 2016 and 2021 for untargeted proteomic discovery studies for biomarkers of delirium conducted on human geriatric subjects. Two reviewers conducted an independent review of all search results and resolved discordance by consensus. From an overall search of 1172 publications, 8 peer-reviewed studies met our defined inclusion criteria. The 370 unique perioperative biomarkers identified in these reports are enriched in pathways involving activation of the immune system, inflammatory response, and the coagulation cascade. The most frequently identified biomarker was interleukin-6 (IL-6). By reviewing the distribution of protein biomarker candidates from these studies, we conclude that a panel of proteins, rather than a single biomarker, would allow for discriminating delirium cases from noncases. The paucity of hypothesis-generating studies in the peer-reviewed literature also suggests that a system-biology view of delirium pathomechanisms has yet to fully emerge.

Detection Analysis of Perioperative Plasma and CSF Reveals Risk Biomarkers of Postoperative Delirium of Parkinson's Disease Patients Undergoing Deep Brain Stimulation of the Subthalamic Nuclei

Objective

This study aimed to explore possible biomarkers of postoperative delirium (POD) of Parkinson's disease (PD) patients received deep brain stimulation (DBS) of the subthalamic nuclei.

Materials and methods

This nested case control study analyzed perioperative plasma and cerebral spinal fluid (CSF) of patients (n = 40) who developed POD undergone DBS surgery (n = 10) and those who did not (n = 30). Blood sample was collected before surgery and on the first day postoperative, CSF sample was collected at the beginning of the operation. POD was assessed by the Confusion Assessment Method (CAM) twice a day between 7:00 am and 7:00 pm after the surgery until discharge. Plasma and CSF sample from the two groups were analyzed to investigate possible biomarkers for POD in PD patients.

Results

There was no difference between POD and Non-POD groups on the concentration of Interleukin 6 and Tumor Necrosis Factor-α in CSF, preoperative plasma and postoperative plasma. There was no difference between POD and Non-POD groups on the concentration of S100 calcium-binding protein β protein (S100β) and Neurofilament light chain (NFL) in preoperative plasma and postoperative plasma. The concentration of C-reactive protein (CRP), NFL and S100β were significant higher in POD group than non-POD group in CSF. The concentration of CRP was significantly higher in POD group than non-POD group in preoperative plasma and postoperative plasma. CSF concentration of S100β might be a potential biomarker for POD via the receiver operating characteristic curve analysis and the area under the curve value of 0.973.

Conclusion

For PD patients received DBS surgery, CSF S100β might be a marker for aiding detection of high-risk patients with delirium. This requires further confirmation in clinical trials.

Research progress on risk factors of delirium in burn patients: A narrative review

Delirium, an acute brain dysfunction, is a common and serious complication in burn patients. The occurrence of delirium increases the difficulty of patient treatment, is associated with various adverse outcomes, and increases the burden on the patient's family. Many scholars have studied the factors that cause delirium, but the causes, pathogenesis, and treatment of delirium in burn patients have not been fully revealed. There is no effective pharmacological treatment for delirium, but active preventive measures can effectively reduce the incidence of delirium in burn patients. Therefore, it is necessary to study the relevant factors affecting the occurrence of delirium in burn patients. This study was conducted on December 20, 2021 by searching the PubMed database for a narrative review of published studies. The search strategy included keywords related to "burns," "delirium," and "risk factors." We reviewed the characteristics of delirium occurrence in burn patients and various delirium assessment tools, and summarized the risk factors for the development of delirium in burn patients in terms of personal, clinical, and environmental factors, and we found that although many risk factors act on the development of delirium in burn patients, some of them, such as clinical and environmental factors, are modifiable, suggesting that we can estimate the exposure of burn patients to risk factors by assessing their likelihood of delirium occurring and to make targeted interventions that provide a theoretical basis for the prevention and treatment of burn delirium.

Identification of Serum Biomarkers Associated With Emergence Agitation After General Anesthesia in Adult Patients: A Metabolomics Analysis

Background

Emergence agitation (EA) is a conscious disturbance after general anesthesia in adult patients that can lead to severe respiratory or circulatory complications and serious physical injury to patients and caregivers. However, the pathophysiological mechanisms underlying EA remain unclear. The present study aimed to identify serum metabolites with significant alterations in EA patients after general anesthesia and enable inferences on their associations with EA.

Methods

EA patients were identified by Richmond Agitation-Sedation Scale (RASS) ≥ + 2 among a cohort of adult patients who received elective surgery under general anesthesia in Peking University Third Hospital between 01 June 2020 and 30 December 2020. We further selected sex-, age-, and surgery type-matched non-EA control patients at a 1:1.5 ratio. Postoperative serum samples were collected from both groups of patients. An untargeted metabolic method was used to identify differences in serum metabolomic profiles between the EA patients and the non-EA patients.

Results

A total of 19 EA patients and 32 matched non-EA patients were included in the study. After screening and mapping with a database, 12 metabolites showed significant postoperative alterations in EA patients compared with non-EA patients, and were mainly involved in lipid, fatty acid and amino acid metabolism pathways. Receiver operating characteristic curve analyses indicated that vanillic acid, candoxatril, tiglylglycine, 5-methoxysalicylic acid, decanoylcarnitine, and 24-epibrassinolide may be involved in EA pathogenesis after general anesthesia.

Conclusion

In this study, we found differences in the serum levels of vanillic acid, candoxatril, tiglylglycine, 5-methoxysalicylic acid, decanoylcarnitine, and 24-epibrassinolide involved in fatty acid metabolism, lipid metabolism, and amino acid metabolism pathways in EA patients compared with non-EA patients, which may demonstrate an EA pathogenesis-associated molecular pattern and contribute toward better understanding of EA occurrence.

Potential Serum Biomarkers for Postoperative Neurocognitive Disorders Based on Proteomic Analysis of Cognitive-Related Brain Regions

Postoperative neurocognitive disorders (po-NCD), including postoperative delirium (POD) and delayed neurocognitive recovery (dNCR), are common in geriatric surgical patients. However, the ideal diagnostic biomarkers to predict individual risks of po-NCDs have not been identified. In this study, proteomic analysis was used to detect dysregulated proteins in three cognitive-related brain regions, the hippocampus, prefrontal cortex, and temporal lobe, of aged dNCR rats. The common affected proteins in these three brain regions were further verified by real-time polymerase chain reaction and western blotting. Furthermore, serum samples from aged rats with dNCR and elderly hip fracture patients with POD were also assessed with enzyme linked immunosorbent assays to investigate the biomarker potential of these dysregulated proteins. The increased expression levels of haptoglobin, caseinolytic protease (ClpP), and alpha-2 macroglobulin (A2M) as well as decreased expression levels of 14-3-3β/α and biliverdin reductase-A (BVR-A) were validated by proteomic analysis in the hippocampus, prefrontal cortex, and temporal lobe of aged dNCR rats. The increased expression of haptoglobin and decreased expression of 14-3-3β/α were further demonstrated in the three brain regions by western blotting. Moreover, increased levels of S100A6 and BVR-A in the hippocampus, S100A6 in the prefrontal cortex, and A2M in the temporal lobe were also observed. More intriguingly, both decreased serum 14-3-3β/α and increased A2M in geriatric POD patients as well as decreased serum ClpP in aged dNCR rats were verified. These results not only indicate potential diagnostic biomarkers for po-NCD but also provide directions for further pathological investigations.

Clinical Trial Registration:www.ClinicalTrials.gov, identifier [ChiCTR1900027393].

Cerebrospinal Fluid Proteome Changes in Older Non-Cardiac Surgical Patients with Postoperative Cognitive Dysfunction

Background:

Postoperative cognitive dysfunction (POCD), a syndrome of cognitive deficits occurring 1–12 months after surgery primarily in older patients, is associated with poor postoperative outcomes. POCD is hypothesized to result from neuroinflammation; however, the pathways involved remain unclear. Unbiased proteomic analyses have been used to identify neuroinflammatory pathways in multiple neurologic diseases and syndromes but have not yet been applied to POCD.

Objective:

To utilize unbiased mass spectrometry-based proteomics to identify potential neuroinflammatory pathways underlying POCD.

Methods:

Unbiased LC-MS/MS proteomics was performed on immunodepleted cerebrospinal fluid (CSF) samples obtained before, 24 hours after, and 6 weeks after major non-cardiac surgery in older adults who did (n = 8) or did not develop POCD (n = 6). Linear mixed models were used to select peptides and proteins with intensity differences for pathway analysis.

Results:

Mass spectrometry quantified 8,258 peptides from 1,222 proteins in > 50%of patient samples at all three time points. Twelve peptides from 11 proteins showed differences in expression over time between patients with versus without

POCD (q < 0.05), including proteins previously implicated in neurodegenerative disease pathophysiology. Additionally, 283 peptides from 182 proteins were identified with trend-level differences (q < 0.25) in expression over time between these groups. Among these, pathway analysis revealed that 50 were from 17 proteins mapping to complement and coagulation pathways (q = 2.44^*10^–13).

Conclusion:

These data demonstrate the feasibility of performing unbiased mass spectrometry on perioperative CSF samples to identify pathways associated with POCD. Additionally, they provide hypothesis-generating evidence for CSF complement and coagulation pathway changes in patients with POCD.