Explore the Role of Frailty as a Contributor to the Association Between AT(N) Profiles and Cognition in Alzheimer's Disease.

Background: The relationship between Alzheimer's disease (AD)-related pathology and cognition was not exactly consistent. Objective: To explore whether the association between AD pathology and cognition can be moderated by frailty. Methods: We included 1711 participants from the Alzheimer's Disease Neuroimaging Initiative database. Levels of cerebrospinal fluid amyloid-ß, p-tau, and t-tau were identified for AD-related pathology based on the amyloid-ß/tau/neurodegeneration (AT[N]) framework. Frailty was measured using a modified Frailty Index-11 (mFI-11). Regression and interaction models were utilized to assess the relationship among frailty, AT(N) profiles, and cognition. Moderation models analyzed the correlation between AT(N) profiles and cognition across three frailty levels. All analyses were corrected for age, sex, education, and APOEɛ4 status. Results: In this study, frailty (odds ratio [OR] = 1.71, p < 0.001) and AT(N) profiles (OR = 2.00, p < 0.001) were independently associated with cognitive status. The model fit was improved when frailty was added to the model examining the relationship between AT(N) profiles and cognition (p < 0.001). There was a significant interaction between frailty and AT(N) profiles in relation to cognitive status (OR = 1.12, pinteraction = 0.028). Comparable results were obtained when Mini-Mental State Examination scores were utilized as the measure of cognitive performance. The association between AT(N) profiles and cognition was stronger with the levels of frailty. Conclusions: Frailty may diminish patients' resilience to AD pathology and accelerate cognitive decline resulting from abnormal AD-related pathology. In summary, frailty contributes to elucidating the relationship between AD-related pathology and cognitive impairment.

Clinical trajectories preceding incident dementia up to 15 years before diagnosis: a large prospective cohort study.

BACKGROUND: Dementia has a long prodromal stage with various pathophysiological manifestations; however, the progression of pre-diagnostic changes remains unclear. We aimed to determine the evolutional trajectories of multiple-domain clinical assessments and health conditions up to 15 years before the diagnosis of dementia. METHODS: Data was extracted from the UK-Biobank, a longitudinal cohort that recruited over 500,000 participants from March 2006 to October 2010. Each demented subject was matched with 10 healthy controls. We performed logistic regressions on 400 predictors covering a comprehensive range of clinical assessments or health conditions. Their evolutional trajectories were quantified using adjusted odds ratios (ORs) and FDR-corrected p-values under consecutive timeframes preceding the diagnosis of dementia. FINDINGS: During a median follow-up of 13.7 [Interquartile range, IQR 12.9-14.2] years until July 2022, 7620 subjects were diagnosed with dementia. In general, upon approaching the diagnosis, demented subjects witnessed worse functional assessments and a higher prevalence of health conditions. Associations up to 15 years preceding the diagnosis comprised declined physical strength (hand grip strength, OR 0.65 [0.63-0.67]), lung dysfunction (peak expiratory flow, OR 0.78 [0.76-0.81]) and kidney dysfunction (cystatin C, OR 1.13 [1.11-1.16]), comorbidities of coronary heart disease (OR 1.78 [1.67-1.91]), stroke (OR 2.34 [2.1-1.37]), diabetes (OR 2.03 [1.89-2.18]) and a series of mental disorders. Cognitive functions in multiple tests also demonstrate decline over a decade before the diagnosis. Inadequate activity (3-5 year, overall time of activity, OR 0.82 [0.73-0.92]), drowsiness (3-5 year, sleep duration, OR 1.13 [1.04-1.24]) and weight loss (0-5 year, weight, OR 0.9 [0.83-0.98]) only exhibited associations within five years before the diagnosis. In addition, serum biomarkers of enriched endocrine, dysregulations of ketones, deficiency of brand-chain amino acids and polyunsaturated fatty acids were found in a similar prodromal time window and can be witnessed as the last pre-symptomatic conditions before the diagnosis. INTERPRETATION: Our findings present a comprehensive temporal-diagnostic landscape preceding incident dementia, which could improve selection for preventive and early disease-modifying treatment trials.

Selective degradation of PL2L60 by metabolic stresses­induced autophagy suppresses multi­cancer growth.

It has been reported that PL2L60 proteins, a product of PIWIL2 gene which might be activated by an intragenic promoter, could mediate a common pathway specifically for tumorigenesis. In the present study, it was further identified by using western blot assay that the PL2L60 proteins could be degraded in cancer cells through a mechanism of selective autophagy in response to oxidative stress. The PL2L60 was downregulated in various types of cancer cells under the hypoxic condition independently of HIF­1α, resulting in apoptosis of cancer cells. Inhibition of autophagy by small interfering RNA targeting of either Beclin­1 (BECN1) or Atg5 resulted in restoration of PL2L60 expression in hypoxic cancer cell. The hypoxic degradation of PL2L60 was also blocked by the attenuation of the autophagosome membrane protein Atg8/microtubule­associated protein 1 light chain 3 (LC3) or autophagy cargo protein p62 expression. Surprisingly, Immunofluorescence analysis demonstrated that LC3 could be directly bound to PL2L60 and was required for the transport of PL2L60 from the nucleus to the cytoplasm for lysosomal flux under basal or activated autophagy in cancer cells. Moreover, flow cytometric analysis displayed that knocking down of PL2L60 mRNA but not PIWIL2 mRNA effectively inhibited cancer cell proliferation and promoted apoptosis of cancer cells. The similar results were obtained from in vivo tumorigenic experiment, in which PL2L60 downregulation in necroptosis areas was confirmed by immunohistochemistry. These results suggested that various cancer could be suppressed by promoting autophagy. The present study revealed a key role of autophagic degradation of PL2L60 in hypoxia­induced cancer cell death, which could be used as a novel therapeutic target of cancer.

Total Tau Protein Mediates the Association of Ischemic Cerebrovascular Disease with Cognitive Decline.

Background: Patients with transient ischemic attack (TIA) or ischemic stroke demonstrate an increased risk of cognitive dysfunction. Accumulating evidence indicates that ischemic cerebrovascular disease (ICVD) may interact with the amyloid/tau/neurodegeneration (AT[N]) biomarkers to promote dementia. However, the precise pathological mechanisms remain to be fully characterized. Objective: To elucidate the interrelationships among ICVD, ATN biomarkers in cerebrospinal fluid (CSF), and cognition. Methods: A total of 2524 participants were recruited from the CABLE study. ICVD referred to TIA/ischemic stroke. Cognitive performance was assessed by China Modified Mini-Mental State Examination (CM-MMSE) and Montreal Cognitive Assessment-b (MoCA-b). Multivariate linear regression analyses were performed to evaluate the associations of ICVD with CSF ATN biomarkers and cognition. Causal mediation analyses were used to identify whether the association was mediated by ATN biomarkers. Results: ICVD was associated with higher total-tau (t-tau) (p = 2.828×10-2) and poorer cognition (CM-MMSE: p = 1.539×10-5, MoCA-b: p = 4.552×10-6). Additionally, no discernible correlation surfaced between ICVD and amyloid-ß (Aß) 42 (p = 6.910×10-1) or phosphorylated tau (p-tau) (p = 4.324×10-1). The influence of ICVD on cognitive function was partially mediated by CSF t-tau (CM-MMSE: proportion: 2.74%, MoCA-b: proportion: 2.51%). Subgroup analyses revealed the influences of t-tau were especially evident in male (CM-MMSE: proportion: 5.45%, MoCA-b: proportion: 5.38%) and mid-life group (CM-MMSE: proportion: 9.83%, MoCA-b: proportion: 5.31%). Conclusions: These results delineated t-tau as a potential mediator for the influence of ICVD on cognition. Targeting brain ischemia and alleviating neuronal injury induced by ischemia may be a promising approach for preventing cognitive decline.

Clinical laboratory tests and dementia incidence: A prospective cohort study.

BACKGROUND: Dementia is a major public health issue and a heavy economic burden. It is urgently necessary to understand the underlying biological processes and to identify biomarkers predicting risk of dementia in the preclinical stage for prevention and treatment. METHODS: By using the data of the 367,093 white British individuals from UK Biobank, we investigated the relationship between 56 laboratory measures and 5-year dementia incidence using logistic regression. Adjusted odds ratios for dementia incidence with values below or above the 95 % confidence interval (<2.5th or > 97.5th percentile) on each of clinical laboratory tests were computed. RESULTS: We observed that markers of endocrine dysregulation: elevated hemoglobin A1C (AOR = 2.01 [1.35, 2.88]) was associated with increased dementia incidence. Indicators of liver dysfunction: elevated gamma glutamyltransferase (AOR = 2.28 [1.49, 3.32]), and albumin (AOR = 2.01 [1.15, 3.25]), indicators of renal impairment: high urea (AOR = 1.69 [1.15, 2.40]), and cystatin C (AOR = 1.89 [1.30, 2.67]), and some immune markers, like elevated neutrophill count, low lymphocyte count, and indicators of anemia were also observed to be associated with increased dementia incidence. Both low and high concentrations of insulin-like growth factor 1 were found to be risk factors for dementia. LIMITATIONS: This is an observational study. CONCLUSION: Several systemic biomarkers were associated with dementia incidence. These results implicate a contributory role of diverse biological processes to dementia onset, and enrich our understanding of potential dementia prevention strategy.

Associations of liver dysfunction with incident dementia, cognition, and brain structure: A prospective cohort study of 431 699 adults.

The relationship between liver dysfunction and dementia has been researched extensively but remains poorly understood. In this study, we investigate the longitudinal and cross-sectional associations between liver function and liver diseases and risk of incident dementia, impaired cognition, and brain structure abnormalities using Cox proportion hazard model and linear regression model. 431 699 participants with a mean of 8.65 (standard deviation [SD] 2.61) years of follow-up were included from the UK Biobank; 5542 all-cause dementia (ACD), 2427 Alzheimer's disease (AD), and 1282 vascular dementia (VaD) cases were documented. We observed that per SD decreases in alanine transaminase (ALT; hazard ratio [HR], 0.917; PFDR <0.001) and per SD increases in aspartate aminotransferase (AST; HR, 1.048; PFDR = 0.010), AST to ALT ratio (HR, 1.195; PFDR <0.001), gamma-glutamyl transpeptidase (GGT; HR, 1.066; PFDR <0.001), alcoholic liver disease (ALD; HR, 2.872; PFDR <0.001), and fibrosis and cirrhosis of liver (HR, 2.285; PFDR = 0.002), being significantly associated with a higher risk of incident ACD. Restricted cubic spline models identified a strong U-shaped association between Alb and AST and incident ACD (Pnonlinear <0.05). Worse cognition was positively correlated with AST, AST to ALT ratio, direct bilirubin (DBil), and GGT; negatively correlated with ALT, Alb, and total bilirubin (TBil); and ALD and fibrosis and cirrhosis of liver (PFDR <0.05). Moreover, changes in ALT, GGT, AST to ALT ratio, and ALD were significantly associated with altered cortical and subcortical regions, including hippocampus, amygdala, thalamus, pallidum, and fusiform (PFDR <0.05). In sensitivity analysis, metabolic dysfunction-associated steatotic liver disease (MASLD) was associated with the risk of ACD and brain subcortical changes. Our findings provide substantial evidence that liver dysfunction may be an important factor for incident dementia. Early intervention in the unhealthy liver may help prevent cognitive impairment and dementia incidence.

Inflammation and Brain Structure in Alzheimer's Disease and Other Neurodegenerative Disorders: a Mendelian Randomization Study.

Previous in vitro and post-mortem studies have reported the role of inflammation in neurodegenerative disorders. However, the association between inflammation and brain structure in vivo and the transcriptome-driven functional basis with relevance to neurodegenerative disorders remains elusive. The aim of the present study is to identify the association among inflammation, brain structure, and neurodegenerative disorders at genetic and transcriptomic levels. Genetic variants associated with inflammatory cytokines were selected from the latest and largest genome-wide association studies of European ancestry. Neurodegenerative disorders including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and dementia with Lewy bodies (DLB) and brain structure imaging measures were selected as the outcomes. Two-sample Mendelian randomization analyses were conducted to identify the causal associations. Single-nucleus transcriptome data of the occipitotemporal cortex was further analyzed to identify the differential expressed genes in AD, which were tested for biological processes and protein interaction network. MR analysis indicated that genetically predicted TREM2 and sTREM2 were significantly associated with AD (TREM2: z-score = -9.088, p-value = 1.02 × 10-19; sTREM2: z-score = -7.495, p-value = 6.61 × 10-14). The present study found no evidence to support the causal associations between other inflammatory cytokines and the risks of AD, PD, ALS, or DLB. Genetically predicted TREM2 was significantly associated with the cortical thickness of inferior temporal (z-score = -4.238, p-value = 2.26 × 10-5) and pole temporal (z-score = -4.549, p-value = 5.40 × 10-6). In the occipitotemporal cortex samples, microglia were the main source of TREM2 gene and showed increasing expression of genes associated with inflammation and immunity. The present study has leveraged genetic and transcriptomic data to identify the association among TREM2, temporal lobe, and AD and the underlying cellular and molecular basis, thus providing a new perspective on the role of TREM2 in AD and insights into the complex associations among inflammation, brain structure, and neurodegenerative disorders, particularly AD.

Exploring the links among peripheral immunity, biomarkers, cognition, and neuroimaging in Alzheimer's disease.

INTRODUCTION: We analyzed relationships among peripheral immunity markers, cognition, Alzheimer's disease (AD)-related biomarkers, and neuroimaging to understand peripheral immunity involvement in AD. METHODS: Peripheral immunity markers were assessed in AD, non-AD neurodegenerative disorders, and controls, examining their connections with cognition, AD-related biomarkers, and neuroimaging using multiple regression models. RESULTS: The study included 1579 participants. Higher levels of white blood cell, neutrophil, monocyte, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and lower lymphocyte-to-monocyte ratio (LMR) were associated with cognitive decline and more severe anxiety and depression. The impact of lower LMR, lymphocyte count, and higher NLR on cognitive decline is mediated through cerebrospinal fluid amyloid beta (Aß) levels. Additionally, increased PLR, NLR, and SII were associated with brain atrophy and hippocampal Aß deposition (amyloid positron emission tomography). DISCUSSION: Peripheral immunity markers offer a non-invasive and cost-effective means of studying AD-related pathophysiological changes, providing valuable insights into its pathogenesis and treatment. Highlights: Peripheral immunity markers linked to cognitive decline and anxiety/depression.Low LMR, LYM, and high NLR linked to reduced CSF Aß, impacting cognition.High PLR, NLR, SII associated with brain atrophy and hippocampal Aß deposition.

The application of generalized S-transform in the denoising of surface plasmon resonance (SPR) spectrum.

In order to obtain accurate resonance peaks from surface plasmon resonance (SPR) spectral curves, a reasonable denoising method is of great significance for SPR sensing systems. Therefore, the generalized S-transform is combined with the Bald Eagle Search algorithm (BES) in this study, and a denoising method based on the generalized S-transform optimized by BES is proposed and applied to the denoising processing of the SPR spectrum. First, a fiber SPR sensing system is used to obtain the original noised spectrum; then, the generalized S-transform is performed to obtain the corresponding S-domain spectrum. Next, the denoising threshold λn is optimized by the BES algorithm, which is used to denoise and reconstruct the SPR reflection spectrum. Finally, two fitness functions are evaluated until the optimal denoising threshold λn and denoising effect are obtained. The relevant validation experiments are completed, and the experimental results show that the proposed method has the best denoising performance when p is between 0.5 and 1, and λ is between 1.5 and 2.5. Meanwhile, compared to the other denoising methods, the BES-S method can maintain a relatively stable denoising effect on the SPR spectrum with high or low levels of noise; the average values of root mean square error (RMSE) and signal-to-noise ratio (SNR) are 0.27 and 23.61, respectively. Ranking first in terms of comprehensive denoising performance, it can also maintain the original shape of the SPR spectrum and better reflect its characteristic peak while filtering out noise. This method can overcome the problem of arbitrary selection of basic functions and thresholds in conventional denoising methods, and it can improve the detection accuracy of SPR sensors and provide a new idea for SPR spectrum denoising, which also lays the foundation for the application of substance composition detection based on SPR sensor.

Multipredictor risk models for predicting individual risk of Alzheimer's disease.

BACKGROUND: Early prevention of Alzheimer's disease (AD) is a feasible way to delay AD onset and progression. Information on AD prediction at the individual patient level will be useful in AD prevention. In this study, we aim to develop risk models for predicting AD onset at individual level using optimal set of predictors from multiple features. METHODS: A total of 487 cognitively normal (CN) individuals and 796 mild cognitive impairment (MCI) patients were included from Alzheimer's Disease Neuroimaging Initiative. All the participants were assessed for clinical, cognitive, magnetic resonance imaging and cerebrospinal fluid (CSF) markers and followed for mean periods of 5.6 years for CN individuals and 4.6 years for MCI patients to ascertain progression from CN to incident prodromal stage of AD or from MCI to AD dementia. Least Absolute Shrinkage and Selection Operator Cox regression was applied for predictors selection and model construction. RESULTS: During the follow-up periods, 139 CN participants had progressed to prodromal AD (CDR ≥ 0.5) and 321 MCI patients had progressed to AD dementia. In the prediction of individual risk of incident prodromal stage of AD in CN individuals, the AUC of the final CN model was 0.81 within 5 years. The final MCI model predicted individual risk of AD dementia in MCI patients with an AUC of 0.92 within 5 years. The models were also associated with longitudinal change of Mini-Mental State Examination (p < 0.001 for CN and MCI models). An Alzheimer's continuum model was developed which could predict the Alzheimer's continuum for individuals with normal AD biomarkers within 3 years with high accuracy (AUC = 0.91). CONCLUSIONS: The risk models were able to provide personalized risk for AD onset at each year after evaluation. The models may be useful for better prevention of AD.