The anti-inflammatory effects of itaconate and its derivatives in neurological disorders.

Almost 16 % of the global population is affected by neurological disorders, including neurodegenerative and cerebral neuroimmune diseases, triggered by acute or chronic inflammation. Neuroinflammation is recognized as a common pathogenic mechanism in a wide array of neurological conditions including Alzheimer's disease, Parkinson's disease, postoperative cognitive dysfunction, stroke, traumatic brain injury, and multiple sclerosis. Inflammatory process in the central nervous system (CNS) can lead to neuronal damage and neuronal apoptosis, consequently exacerbating these diseases. Itaconate, an immunomodulatory metabolite from the tricarboxylic acid cycle, suppresses neuroinflammation and modulates the CNS immune response. Emerging human studies suggest that itaconate levels in plasma and cerebrospinal fluid may serve as biomarkers associated with inflammatory responses in neurological disorders. Preclinical studies have shown that itaconate and its highly cell-permeable derivatives are promising candidates for preventing and treating neuroinflammation-related neurological disorders. The underlying mechanism may involve the regulation of immune cells in the CNS and neuroinflammation-related signaling pathways and molecules including Nrf2/KEAP1 signaling pathway, reactive oxygen species, and NLRP3 inflammasome. Here, we introduce the metabolism and function of itaconate and the synthesis and development of its derivatives. We summarize the potential impact and therapeutic potential of itaconate and its derivatives on brain immune cells and the associated signaling pathways and molecules, based on preclinical evidence via various neurological disorder models. We also discuss the challenges and potential solutions for clinical translation to promote further research on itaconate and its derivatives for neuroinflammation-related neurological disorders.

Preoperative cerebrospinal fluid biomarkers may be associated with postoperative delirium in patients undergoing knee/hip arthroplasty: the PNDABLE study.

BACKGROUND: In the global aging population, the incidence of postoperative delirium (POD) is increasing. Therefore, finding its effective predictive tools becomes crucial. We aimed to identify potential Cerebrospinal fluid (CSF)biomarkers for POD. METHODS: A total of 825 patients undergoing knee/hip arthroplasty under combined spinal-epidural anesthesia were selected. The patients were aged 40 to 90 years with American Society of Anesthesiologists physical status I~II. The Mini-Mental State Examination was completed 1 day before the operation. CSF was extracted after successful spinal-epidural combined puncture, and α-synuclein (α-syn), amyloid beta40 (Aß40), amyloid beta42 (Aß42), t-Tau, phosphorylated Tau (p-Tau), progranulin (PGRN) and soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in the CSF were measured by enzyme-linked immunosorbent assays (ELISA). The patient's operation time, anesthesia time, intraoperative blood loss and fluid input were also recorded. After the operation, the occurrence rate and severity of POD were determined by the Confusion Assessment Method and the Memorial Delirium Assessment Scale (MDAS), respectively. Patients were categorized into POD group and non-POD group. Logistic regression analysis was performed on the indicators with statistically significant differences, and the area under the ROC curve (AUC) was used to estimate the predictive accuracy of the biomarkers for POD. RESULTS: A total of 92 patients developed POD and the incidence of POD was 11.15%. The results of the multivariable logistic regression showed that CSF t-Tau (P = 0.004, OR = 1.006, 95%CI 1.002~1.009) and α-syn (P = 0.004, OR = 1.001, 95%CI 1.000~1.001) were positively associated with the occurrence rate of POD, while Aß42 (P < 0.001, OR = 0.989, 95%CI 0.986~0.993), CSF PGRN (P = 0.002, OR = 0.999, 95%CI 0.999~1.000), Aß42/ t-Tau (P < 0.001, OR = 0.181, 95%CI 0.102~0.319) and Aß42/p-Tau (P < 0.001, OR = 0.617, 95%CI 0.526~0.725) were inversely proportional to the occurrence of POD. ROC curve analysis indicated that Aß42/t-Tau (AUC = 0.823), CSF Aß42 (AUC = 0.813), Aß42/p-Tau (AUC = 0.810), α-syn (AUC = 0.644) and PGRN (AUC = 0.638) could predict the occurrence rate of POD. The combination of all these biomarkers showed a greater AUC(0.896) than using any of them alone. CONCLUSIONS: CSF Aß42, PGRN, α-syn, Aß42/t-Tau and Aß42/p-Tau might be associated with the occurrence rate of POD in patients undergoing knee/hip arthroplasty. TRIAL REGISTRATION: Clinical Registration No. ChiCTR2000033439.

Mutational and Transcriptional Characterization Establishes Prognostic Models for Resectable Lung Squamous Cell Carcinoma.

Background: The prognosis of non-small cell lung cancer (NSCLC) patients has been comprehensively studied. However, the prognosis of resectable (stage I-IIIA) lung squamous cell carcinoma (LUSC) has not been thoroughly investigated at genomic and transcriptional levels. Methods: Data of genomic alterations and transcriptional-level changes of 355 stage I-IIIA LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database, together with the clinicopathological information (training cohort). A validation cohort of 91 patients was retrospectively recruited. Data were analyzed and figures were plotted using the R software. Results: Training cohort was established with 355 patients. TP53 (78%), TTN (68%), CSMD3 (39%), MUT16 (36%) and RYR2 (36%) were genes with the highest mutational frequency. BRINP3, COL11A1, GRIN2B, MUC5B, NLRP3 and TENM3 exhibited significant higher mutational frequency in stage III (P < 0.05). Patients with stage III also exhibited significantly higher tumor mutational burden (TMB) than those with stage I (P < 0.01). The mutational status of 10 genes were found to have significant stratification on patient prognosis. TMB at threshold of 25 percentile (TMB = 2.39 muts/Mb) also significantly stratified the patient prognosis (P = 0.0003). Univariate and multivariate analyses revealed TTN, ADGRB3, MYH7 and MYH15 mutational status and TMB as independent risk factors. Further analysis of transcriptional profile revealed many significantly up- and down-regulated genes, and multivariate analysis found the transcriptional levels of seven genes as independent risk factors. Significant factors from the multivariate analyses were used to establish a Nomogram model to quantify the risk in prognosis of individual LUSC patients. The model was validated with a cohort containing 91 patients, which showed good predicting efficacy and consistency. Conclusion: The influencing factors of prognosis of stage I-III LUSC patients have been revealed. Risk factors including gender, T stage, cancer location, and the mutational and transcriptional status of several genes were used to establish a Nomogram model to assess the patient prognosis. Subsequent validation proved its effectiveness.

Compare the performance of multiple machine learning models in predicting tacrolimus concentration for infant patients with living donor liver transplantation.

BACKGROUND: This study aims to establish multiple ML models and compare their performance in predicting tacrolimus concentration for infant patients who received LDLT within 3 months after transplantation. METHODS: Retrospectively collected basic information and relevant biochemical indicators of included infant patients. CMIA was used to determine tacrolimus C0 . PCR was used to determine the donors' and recipients' CYP3A5 genotypes. Multivariate stepwise regression analysis and stepwise elimination covariates were used for covariates selection. Thirteen machine learning algorithms were applied for the development of prediction models. APE, the ratio of the APE ≤3 ng ml-1 and ideal rate (the proportion of the predicted value with a relative error of 30% or less) were used to evaluate the predictive performance of the model. RESULTS: A total of 163 infant patients were included in this study. In the case of the optimal combination of covariates, the Ridge model had the lowest APE, 2.01 (0.85, 3.35 ng ml-1 ). The highest ratio of the APE ≤3 ng ml-1 was the LAR model (71.77%). And the Ridge model showed the highest ideal rate (55.05%). For the Ridge model, GRWR was the most important predictor. CONCLUSIONS: Compared with other ML models, the Ridge model had good predictive performance and potential clinical application.

Subjective cognitive decline may mediate the occurrence of postoperative delirium by P-tau undergoing total hip replacement: The PNDABLE study.

Objective: We again investigated the relationship between subjective cognitive decline (SCD) and postoperative delirium (POD) with a larger sample queue. We also determined whether SCD could cause the occurrence of POD through cerebrospinal fluid (CSF) biomarkers. Methods: A prospective, observational cohort study was implemented in the Qingdao Municipal Hospital Affiliated with Qingdao University. This study recruited 1,471 qualified patients affiliated with the Perioperative Neurocognitive Disorder And Biomarker Lifestyle (PNDABLE) study scheduled for total hip replacement under combined spinal and epidural anesthesia from June 2020 to May 2022. The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were used to assess the cognitive level of the patients the day before surgery. Pittsburgh sleeps quality index (PSQI) scale was used to assess sleep status. Patients were divided into the SCD group and the non-SCD (NSCD) group based on the Subjective Cognitive Decline Scale (SCDS). CSF was collected after a successful spinal-epidural combined puncture, and amyloid-ß40 (Aß40), amyloid-ß42 (Aß42), total tau (T-tau), and phosphorylated tau (P-Tau) in CSF were analyzed by enzyme-linked immunosorbent assays. After the surgery, the incidence of POD was determined by the Confusion Assessment Scale (CAM), and Memorial Delirium Assessment Scale (MDAS) score was used to determine the severity of POD. Logistic regression and sensitivity analyses were performed to determine the relationship between CSF biomarkers, SCD, and POD. The mediating effect was used to analyze the function of specific CSF biomarkers in the relationship between SCD and POD. The risk factors of SCD were also separately verified by logistic regression and sensitivity analysis models. Results: The total incidence rate of POD was 19.60% (n = 225/1148), which was 29.3% (n = 120/409) in the SCD group and 14.2% (n = 105/739) in the NSCD group. We comprehensively considered the effect of covariates such as age, hypertension, and diabetes. Multivariate logistic regression analysis showed that SCD (OR = 1.467, 95%CI: 1.015-2.120, p = 0.042) and P-tau (OR = 1.046, 95%CI: 1.028-1.063, p < 0.001) were risk factors for POD. The sensitivity analysis results were consistent with the above results. Mediation analysis showed that the relationship between SCD and POD was partially mediated by P-tau, which accounted for 31.25% (P-tau, IE = 4.279 × 10-2, p < 0.001). For SCD, the results of logistic regression analysis models showed that age (OR = 1.035, 95% CI: 1.020-1.049, p < 0.001), higher preoperative PSQI score (OR = 1.047, 95%CI: 1.014-1.080, p = 0.005), and P-tau (OR = 1.015, 95%CI: 1.002-1.028, p = 0.021) were risk factors for SCD, and subsequent sensitivity analysis confirmed this result after adjustment for ASA grade, height, and weight. Conclusion: Patients with SCD are more likely to develop POD undergoing total hip replacement, and SCD can mediate the occurrence of POD via P-tau. Clinical trial registration: This study was registered at China Clinical Trial Registry (Chictr2000033439).

The effect of neostigmine on postoperative delirium after colon carcinoma surgery: a randomized, double-blind, controlled trial.

BACKGROUND: Postoperative delirium (POD) is a critical complication in patients accepting colon carcinoma surgery. Neostigmine, as a cholinesterase inhibitor, can enhance the transmission of cholinergic transmitters in synaptic space, and play an important role in maintaining the normal level of cognition, attention and consciousness. The objective of this study was to investigate the effect of neostigmine on POD and clinical prognosis. METHODS: A randomized, double-blind controlled trial was implemented in Qingdao Municipal Hospital Affiliated to Qingdao University. A total of 454 patients aged 40 to 90 years old accepted colon carcinoma surgery were enrolled between June 7, 2020, and June 7, 2021, with final follow-up on December 8, 2021. Patients were randomly assigned to two groups: the neostigmine group (group N) and the placebo group (group P), the patients in group N were injected with 0.04 mg/kg neostigmine and 0.02 mg/kg atropine intravenously. The primary endpoint was the incidence of POD, researchers evaluated the occurrence of POD by the Confusion Assessment Method (CAM) twice daily (at 10 a.m. and 2 p.m.) during the first 7 postoperative days, POD severity was assessed by the Memorial Delirium Assessment Scale (MDAS). The secondary endpoints were the extubating time, postanesthesia care unit (PACU) time, the incidence of various postoperative complications, length of hospital stays, and 6 months postoperative mortality. RESULTS: The incidence of POD was 20.20% (81/401), including 19.39% (38/196) in group N and 20.98% (43/205) in group P. There was no significant statistical significance in the incidence of POD between group N and group P (P > 0.05); Compared to group P, the extubating time and PACU time in group N were significantly reduced (P < 0.001), the incidence of postoperative pulmonary complications (POPCs) decreased significantly in group N (P < 0.05), while no significant differences were observed in postoperative hospital stay and mortality in 6 months between the two groups (P > 0.05). CONCLUSION: For patients accepted colon carcinoma surgery, neostigmine did not significantly reduce the incidence of POD, postoperative mortality and postoperative hospital stay, while it indeed reduced the extubating time, PACU time and the incidence of POPCs. TRIAL REGISTRATION: The randomized, double-blind, controlled trial was registered retrospectively at www.chictr.org.cn on 07/06/2020 (ChiCTR2000033639).

Potential Value of Serum Lipid in the Identication of Postoperative Delirium Undergoing Knee/Hip Arthroplasty: The Perioperative Neurocognitive Disorder and Biomarker Lifestyle Study.

Objective: We aimed to investigate the relationship between preoperative lipid level and postoperative delirium (POD) and explore whether lipid's effect on POD is mediated by POD core protein. Methods: A total of 635 patients who were planned to undergo knee/hip arthroplasty under combined spinal-epidural anesthesia, regardless of gender, were selected. The patients were aged 40-90 years with American Society of Anesthesiologists physical status I II. The Mini-Mental State Examination (MMSE) was completed 1 day before the operation. Five milliliter elbow venous blood was taken from the patients before anesthesia, and serum levels of total cholesterol (TG), triglyceride (TC), low-density lipoprotein (LDL-C), and high-density lipoprotein (HDL-C) were detected. Cerebrospinal fluid (CSF) was extracted after successful spinal-epidural combined puncture, and amyloid beta40 (Aß40), amyloid beta42 (Aß42), total Tau (t-Tau), and phosphorylated Tau (p-Tau) in the CSF were measured by enzyme-linked immunosorbent assays (ELISA). After the operation, the occurrence and severity of POD were assessed using the Confusion Assessment Method and the Memorial Delirium Assessment Scale (MDAS), respectively. Patients were categorized into POD group and NPOD group. Logistic regression was used to analyze the relationship between POD and TC, TG, LDL-C, and HDL-C, and the mediating effect was used to analyze the role of POD core proteins in the relationship between lipid and MDAS. We used the receiver operating characteristic (ROC) and the precision-recall curve (PRC) analysis to assess the ability of TC, TG, LDL-C, and HDL-C ability to predict POD. Finally, we performed a sensitivity analysis to assess the stability of the results. Results: A total of 562 patients were finally enrolled in this study, and 66 patients developed POD, with an incidence of 11.7%. Logistic regression analysis showed that high concentration of TC (OR = 3.148, 95%CI 1.858∼5.333, P < 0.001), TG (OR = 2.483, 95%CI 1.573∼3.918, P < 0.001), and LDL-C (OR = 2.469, 95%CI 1.310∼4.656, P = 0.005) in serum were risk factors for POD. A high concentration of HDL-C (OR = 0.258, 95%CI 0.112∼0.594, P = 0.001) was a protective factor for POD after adjusted for age, sex, education, and MMSE score. ROC curves showed that HDL-C have the highest sensitivity and specificity in predicting POD. For these four lipid markers, the PRC range from 0.602 to 0.731, respectively. The mediating analysis showed that POD core proteins could partially mediate the relationship between lipid and POD (effect value: 16.19∼91.04%). The results were barely changed in the sensitivity analysis, and the sensitivity analysis has shown that the results were stable. Conclusion: The increase of serum TG, TC, and LDL-C concentration is a risk factor for POD development, while high HDL-C concentration is a protective factor for POD, and the occurrence of POD is caused by hyperlipidemia may be caused by POD core proteins. Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [Chictr200033439].

Correlation between microRNA-320 and postoperative delirium in patients undergoing tibial fracture internal fixation surgery.

BACKGROUND: Although the incidence of postoperative delirium (POD) in the elderly after surgery are rising as individuals are living longer, the pathogenesis of POD remains poorly understood. It has been suggested that miRNA-320 may play a role in POD based on animal study and human study. METHODS: We first carried out an animal study, and designed and conducted a human study based on the result of animal study. The aged rats were randomly assigned to five groups: the control (C), anesthesia and surgery (AS), saline (NS), agomir-320 (AG), and antagomir-320 (AT) groups. Postoperative spatial learning and memory in rats were analyzed by the Morris water maze and the open field tests. The plasma levels of insulin-like growth factor-1 (IGF-1), amyloid precursor protein (APP) proteins, miRNA320 and IGF-1mRNA were measured by ELISA and qRT-PCR, respectively. A total of 240 Chinese Han patients over 65 years who underwent tibial fracture internal fixation were included in the PNDABLE study. POD cases and non-POD controls (1:1 matched) were selected by an anesthesiologist using Confusion Assessment Method. RESULTS: For Group AS, the escape latency was significantly longer and the ratio of time spent in the target quadrant was significantly reduced, APP and miR-320 were upregulated and IGF-1mRNA was downregulated compared with Group C. For Group AG, the escape latency was significantly longer and the ratio of time spent in the target quadrant was significantly reduced, APP and miR-320 were upregulated and IGF-1mRNA was downregulated compared with Group AS. For Group AT, the escape latency was significantly reduced and the ratio of time spent in the target quadrant was significantly longer, APP and miR-320 were downregulated and IGF-1mRNAwas upregulated compared with Group AS. Compared with NPOD patients, the expressions of plasma miR-320 and APP protein were increased and the expression of plasma IGF-1 mRNA was decreased in POD patients after surgery. CONCLUSIONS: MiRNA-320 might play a role in up-regulating the levels of IGF-1mRNA and APP protein, which offered a new target for POD treatment. TRIAL REGISTRATION: Correlation of perioperative neurocognitive disorders with lifestyle and biomarkers. ChiCTR2000033439 . Registered 1 June 2020.

The relationship between body mass index and postoperative delirium.

PURPOSE: We aimed to investigate the relevance of body mass index (BMI) to postoperative delirium (POD), and to test whether the influences of BMI on POD were mediated by cerebrospinal fluid (CSF) biomarkers. PATIENTS AND METHODS: Our study recruited 682 and 761 cognitively intact individuals from the perioperative neurocognitive disorder risk factor and prognosis (PNDRFAP) study and the perioperative neurocognitive disorder and biomarker lifestyle (PNDABLE) study, respectively. The incidence of POD was evaluated by using Confusion Assessment Method (CAM), and POD severity was measured by using the Memorial Delirium Assessment Scale (MDAS). Logistic regression was used to analyze the relationship between BMI and POD. The levels of Aß40, Aß42, T-tau, and P-tau in preoperative CSF were measured by enzyme-linked immune-sorbent assay (ELISA) in the PNDABLE study. Mediation analysis with 5000 bootstrapped iterations was used to explore the mediation effects. RESULTS: In the PNDRFAP study, the incidence of POD was 16.3%, with logistic regression analysis showing that BMI (odds ratio [OR] = 0.900, 95% confidence interval [CI] 0.823-0.985, p = .022) is a protective factor of POD. In the PNDABLE study, the incidence of POD was 18.7%, and regression analysis confirmed that BMI (OR = 0.832, 95% CI 0.761-0.910, p < .001) is a protective factor of POD, while T-tau (OR = 1.005, 95% CI 1.003-1.006, p < .001) and P-tau (OR = 1.037, 95% CI 1.024-1.050, p < .001) were risk factors of POD. Mediation analyses revealed that the association between BMI and POD was partially mediated by T-tau (proportion: 36%) and P-tau (proportion: 24%). CONCLUSION: Higher BMI mediated protective effects on POD through CSF biomarkers (T-tau and P-tau).

Differential hippocampal protein expression between normal mice and mice with the perioperative neurocognitive disorder: a proteomic analysis.

OBJECTIVES: To compare differential expression protein in hippocampal tissues from mice of perioperative neurocognitive disorder (PND) and normal control mice and to explore the possible mechanism of PND. METHODS: Mice were randomly divided into a PND group (n = 9) and a control group (n = 9).The mice in the PND group were treated with open tibial fracture with intramedullary fixation under isoflurane anesthesia, while the mice in the control group received pure oxygen without surgery. The cognitive functions of the two groups were examined using Morris water maze experiment, Open field test and Fear conditioning test. The protein expression of the hippocampus of mice was analyzed by high-performance liquid chromatography-mass spectrometry (HPLC-MS/MS). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to explore the principal functions of dysregulated proteins. RESULTS: A total of 21 proteins were differentially expressed between PND and control mice on days 1, 3, and 7 after the operation. These proteins were involved in many pathological processes, such as neuroinflammatory responses, mitochondrial oxidative stress, impaired synaptic plasticity, and neuronal cell apoptosis. Also, the dysregulated proteins were involved in MAPK, AMPK, and ErbB signaling pathways. CONCLUSION: The occurrence of PND could be attributed to multiple mechanisms.

Subjective Cognitive Decline May Be Associated With Post-operative Delirium in Patients Undergoing Total Hip Replacement: The PNDABLE Study.

Objective: Subjective cognitive decline (SCD) is associated with an increased risk of clinical cognitive disorders. Post-operative delirium (POD) is a common complication after total hip replacement. We aimed to investigate the relationship between SCD and POD in patients undergoing total hip replacement. Methods: Our study recruited 214 cognitively intact individuals from the Perioperative Neurocognitive Disorder And Biomarker Lifestyle (PNDABLE) study in the final analysis. SCD was diagnosed with Subjective Cognitive Decline Scale (SCDS), Mini-Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA). The incidence of POD was evaluated by using Confusion Assessment Method (CAM), and POD severity was measured by using the Memorial Delirium Assessment Scale (MDAS). Preoperative cerebrospinal fluid (CSF) Aß40, Aß42, T-tau, and P-tau levels were measured by enzyme-linked immune-sorbent assay (ELISA). Results: Overall, the incidence of POD was 26.64% (57/214), including 32.43% (36/111) in the SCD group and 20.39% (21/103) in the NC group. With the increase of age, the incidence of POD in all age groups increased (P < 0.05). Logistic regression analysis showed that after adjusting for SCD, Aß42, Aß40, P-tau, and T-tau, SCD (OR 2.32, CI 1.18-4.55, P = 0.01) and the increased CSF level of P-tau (OR 1.04, CI 1.01-1.06, P < 0.001) were risk factors for POD, while the level of aß42 (OR 0.99, CI 0.99-1.00, P < 0.001) was a protective factor for POD. Conclusion: SCD is one of the preoperative risk factors for POD. Clinical Trial Registration: This study was registered at China Clinical Trial Registry (Chictr200033439).

Potential Value of Cerebrospinal Fluid Progranulin in the Identification of Postoperative Delirium in Geriatrics Patients Undergoing Knee Replacement: The Perioperative Neurocognitive Disorder and Biomarker LifestylE Study.

Objective: The aim of this study was to investigate whether progranulin (PGRN) levels in cerebrospinal fluid (CSF) were associated with postoperative delirium (POD) in geriatric patients undergoing knee replacement. Method: A total of 600 Han Chinese patients aged 65-90 years and who underwent unilateral total knee arthroplasty were included in the Perioperative Neurocognitive Disorder And Biomarker LifestylE (PNDABLE) study from June 2020 to November 2020. All participants were assessed using the Confusion Assessment Method and the Memorial Delirium Assessment Scale on postoperative days 1-7 (or before discharge) by an anesthesiologist. CSF PGRN and CSF biomarkers of POD were measured by ELISA. We analyzed the risk and protective factors of POD using the multivariate logistic regression, and the associations between CSF PGRN and CSF biomarkers of POD using multiple linear regression. We also explored whether the influence of CSF PGRN on POD was mediated by POD core pathology in linear regression models. Results: Postoperative delirium incidence was 9.7% (53/545). There were significant differences in preoperative CSF PGRN between patients with POD and non-POD (NPOD). As for CSF biomarkers, CSF Aß40, T-tau, and P-tau were risk factors for POD, while CSF PGRN, Aß42, and Aß42/Aß40 were protective factors for POD, as shown by the multivariate logistic regression analysis. CSF PGRN was positively associated with CSF Aß42 and was negatively associated with CSF Aß40, T-tau, and P-tau in patients with POD. We found that the AUC was 0.795 (95% CI = 0.706, 0.867) for PGRN between POD and NPOD groups. We found the influence of CSF PGRN on POD was mediated by POD core pathology. The effect was considered partial mediation with the proportion of mediation varying from 44.92 to 62.07%. Conclusion: Cerebrospinal fluid PGRN may be a reasonably good prognostic factor for POD development. Overall, amyloid pathology and tau protein might partially mediate the influence of PGRN on POD. Clinical Trial Registration: www.clinicaltrials.gov, identifier ChiCTR2000033439.