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.

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 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.

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.

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.

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.

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.

Circulating polyunsaturated fatty acids, fish oil supplementation, and risk of incident dementia: a prospective cohort study of 440,750 participants.

Cohort studies report inconsistent associations between omega-3 polyunsaturated fatty acids (n-3 PUFA) or fish oil and dementia risk. Furthermore, evidence relating omega-6 polyunsaturated fatty acids (n-6 PUFA) with dementia is scarce. Here, we included 440,750 dementia-free participants from UK Biobank to comprehensively investigate the associations between plasma levels of different types of PUFA, fish oil supplementation, and dementia risk. During a median follow-up of 9.25 years, 7768 incident dementia events occurred. Higher plasma levels of five PUFA measures showed consistent associations with lower dementia risk (hazard ratios [95% confidence intervals] for per standard deviation increment of plasma concentrations 0.85 [0.81-0.89] for total PUFAs; 0.90 [0.86-0.95] for omega-3 PUFAs; 0.92 [0.87-0.96] for docosahexaenoic acid (DHA); 0.86 [0.82-0.90] for omega-6 PUFAs; 0.86 [0.82-0.90] for linoleic acid (LA); all p < 0.001). Compared with non-users, fish oil supplement users had a 7% decreased risk of developing all-cause dementia (0.93 [0.89-0.97], p = 0.002), and the relationship was partially mediated by plasma n-3 PUFA levels (omega-3 PUFAs: proportion of mediation = 57.99%; DHA: proportion of mediation = 56.95%). Furthermore, we observed significant associations of plasma n-3 PUFA levels and fish oil supplementation with peripheral immune markers that were related to dementia risk, as well as the positive associations of plasma PUFA levels with brain gray matter volumes and white matter microstructural integrity, suggesting they may affect dementia risk by affecting peripheral immunity and brain structure. Taken together, higher plasma PUFA levels and fish oil supplementation were associated with lower risk of incident dementia. This study may support the value of interventions to target PUFAs (specifically n-3 PUFAs) to prevent dementia.

Systematic assessment of plasma biomarkers in spinocerebellar ataxia.

BACKGROUND AND OBJECTIVES: Plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), phosphorylated-tau (p-tau), and ß-amyloid (Aß) have emerged as promising markers in several neurodegenerative disorders, but whether they can be used as biomarkers in spinocerebellar ataxias (SCA) is yet to be determined. This study aimed to identify sensitive plasma markers for SCA and investigate their effectiveness in tracking ataxia severity, cognition, non-motor symptoms, and brain atrophy. METHODS: This observational study recruited consecutive participants from Huashan Hospital and the CABLE study from November 2019. Patients with SCA were genetically diagnosed, grouped according to the ataxia severity, and compared with healthy older individuals and patients with multiple system atrophy type C (MSA-C). Plasma NfL, GFAP, p-tau, and Aß levels were measured by Simoa in all participants. Analysis of covariance, Spearman correlation, and multivariable regression were used to explore candidate markers in SCA. RESULTS: A total of 190 participants (60 SCA, 56 MSA-C, and 74 healthy controls) were enrolled. Plasma NfL level increased early in the pre-ataxic stage of SCA (32.23 ± 3.07 vs. 11.41 ± 6.62 pg/mL in controls), was positively associated with the ataxia severity (r = 0.45, P = 0.005) and CAG repeat length (r = 0.51, P = 0.001), varied among the different SCA subtypes (39.57 ± 13.50 pg/mL in SCA3, which was higher than 28.17 ± 8.02 pg/mL in SCA2, 17.08 ± 6.78 pg/mL in SCA8, and 24.44 ± 18.97 pg/mL in rare SCAs; P < 0.05), and was associated with brainstem atrophy. NfL alone (area under the curve [AUC] 0.867) or combined with p-tau181 and Aß (AUC 0.929), showed excellent performance in discriminating SCA patients from controls. Plasma GFAP distinguished SCA from MSA-C with moderate accuracy (AUC > 0.700) and correlated with cognitive performance and cortical atrophy. Changes in levels of p-tau181 and Aß were observed in SCA patients compared to controls. They were both correlated with cognition, while Aß was also associated with non-motor symptoms, such as anxiety and depression. DISCUSSION: Plasma NfL may serve as a sensitive biomarker for SCA, and its level is elevated in the pre-ataxic stage. The different performance of NfL and GFAP indicates differences in the underlying neuropathology of SCA and MSA-C. Moreover, amyloid markers may be useful for detecting memory dysfunction and other non-motor symptoms in SCA.

Associations of blood cell indices and anemia with risk of incident dementia: A prospective cohort study of 313,448 participants.

INTRODUCTION: Low hemoglobin and anemia are associated with cognitive impairment and Alzheimer's disease (AD). However, the associations of other blood cell indices with incident dementia risk and the underlined mechanisms are unknown. METHODS: Three hundred thirteen thousand four hundred forty-eight participants from the UK Biobank were included. Cox and restricted cubic spline models were used to investigate linear and non-linear longitudinal associations. Mendelian randomization analysis was used to identify causal associations. Linear regression models were used to explore potential mechanisms driven by brain structures. RESULTS: During a mean follow-up of 9.03 years, 6833 participants developed dementia. Eighteen indices were associated with dementia risk regarding erythrocytes, immature erythrocytes, and leukocytes. Anemia was associated with a 56% higher risk of developing dementia. Hemoglobin and red blood cell distribution width were causally associated with AD. Extensive associations exist between most blood cell indices and brain structures. DISCUSSION: These findings consolidated associations between blood cells and dementia. HIGHLIGHT: Anemia was associated with 56% higher risk for all-cause dementia. Hematocrit percentage, mean corpuscular volume, platelet crit, and mean platelet volume had U-shaped associations with incident dementia risk. Hemoglobin (HGB) and red blood cell distribution width had causal effects on Alzheimer's risk. HGB and anemia were associated with brain structure alterations.

Development of machine learning-based models to predict 10-year risk of cardiovascular disease: a prospective cohort study.

BACKGROUND: Previous prediction algorithms for cardiovascular diseases (CVD) were established using risk factors retrieved largely based on empirical clinical knowledge. This study sought to identify predictors among a comprehensive variable space, and then employ machine learning (ML) algorithms to develop a novel CVD risk prediction model. METHODS: From a longitudinal population-based cohort of UK Biobank, this study included 473 611 CVD-free participants aged between 37 and 73 years old. We implemented an ML-based data-driven pipeline to identify predictors from 645 candidate variables covering a comprehensive range of health-related factors and assessed multiple ML classifiers to establish a risk prediction model on 10-year incident CVD. The model was validated through a leave-one-center-out cross-validation. RESULTS: During a median follow-up of 12.2 years, 31 466 participants developed CVD within 10 years after baseline visits. A novel UK Biobank CVD risk prediction (UKCRP) model was established that comprised 10 predictors including age, sex, medication of cholesterol and blood pressure, cholesterol ratio (total/high-density lipoprotein), systolic blood pressure, previous angina or heart disease, number of medications taken, cystatin C, chest pain and pack-years of smoking. Our model obtained satisfied discriminative performance with an area under the receiver operating characteristic curve (AUC) of 0.762±0.010 that outperformed multiple existing clinical models, and it was well-calibrated with a Brier Score of 0.057±0.006. Further, the UKCRP can obtain comparable performance for myocardial infarction (AUC 0.774±0.011) and ischaemic stroke (AUC 0.730±0.020), but inferior performance for haemorrhagic stroke (AUC 0.644±0.026). CONCLUSION: ML-based classification models can learn expressive representations from potential high-risked CVD participants who may benefit from earlier clinical decisions.

Genome-wide Survival Study Identifies PARL as a Novel Locus for Clinical Progression and Neurodegeneration in Alzheimer's Disease.

BACKGROUND: Variability exists in the trajectories of Alzheimer's disease (AD). We aimed to identify genetic modulators of clinical progression in AD. METHODS: We conducted the first genome-wide survival study on AD using a two-stage approach. The discovery and replication stage separately included 1158 and 211,817 individuals without dementia from the Alzheimer's Disease Neuroimaging Initiative and the UK Biobank, respectively (325 and 1103 progressed in average follow-up of 4.33 and 8.63 years, respectively). Cox proportional hazards models were applied with time to AD dementia as the phenotype of clinical progression. A series of bioinformatic analyses and functional experiments was performed to validate the novel findings. RESULTS: We found that APOE and PARL, a novel locus tagged by rs6795172 (hazard ratio = 1.66, p = 1.45 × 10-9), were significantly associated with AD clinical progression and were successfully replicated. The novel locus was linked to accelerated cognitive changes, higher tau levels, and faster atrophy of AD-specific brain structures, which were also verified in UK Biobank neuroimaging follow-up. Gene analysis and summary data-based Mendelian randomization indicated PARL as the most functionally relevant gene in the locus. Expression quantitative trait locus analyses and dual-luciferase reporter assays confirmed that PARL expression could be regulated by rs6795172. Three different AD mouse models consistently showed decreased PARL expression accompanied by elevated tau levels, and in vitro experiments revealed that knockdown/overexpression of PARL inversely changed tau levels. CONCLUSIONS: Collectively, genetic, bioinformatic, and functional evidence suggests that PARL modulates clinical progression and neurodegeneration in AD. Targeting PARL may potentially modify AD progression and have implications for disease-modifying therapies.

Head-to-head comparison of 6 plasma biomarkers in early multiple system atrophy.

There is a dire need for reliable biomarkers to solidify an early and accurate diagnosis of multiple system atrophy (MSA). We sought to compare the ability of emerging plasma markers in distinguishing MSA from its mimics and healthy controls in early disease stages, and to evaluate their performance in detecting disease severity and brain atrophy. Plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), phosphorylated tau181, amyloid-ß (Aß)42, and Aß40 were measured using ultrasensitive Simoa in early-stage patients with MSA (n = 73), spinocerebellar ataxia (SCA, n = 29), Parkinson's disease (PD, n = 28), and healthy controls (n = 100). We observed that elevated NfL outperformed other biomarkers in distinguishing MSA and its subtypes (AUC = 0.9) versus controls. Intriguingly, when separating MSA from its mimics, increased GFAP (AUC = 0.717) in MSA-C and decreased Aß40 (AUC = 0.807) in MSA-P best discriminated from SCA and PD respectively. Plasma levels were comparable between MSA-C and MSA-P and the differentiation by plasma index alone was poor. Combining plasma markers noticeably improved the discriminatory efficacy. Of note, among MSA patients, higher GFAP and NfL were correlated with the atrophy of brain regions vulnerable to MSA (e.g., cerebellum, pons, or putamen). They could also aggravate the severity of MSA, and this association was partially mediated by cerebral volumes. In contrast, no obvious associations of phosphorylated tau and Aß with disease severity were observed. Collectively, plasma biomarkers, especially in combination, are useful to facilitate the discriminatory work-up of MSA at early stages. Moreover, NfL and GFAP may be promising biomarkers to monitor the disease severity of MSA.

Contribution of Alzheimer's disease pathology to biological and clinical progression: A longitudinal study across two cohorts.

INTRODUCTION: Amyloid beta (Aß) deposition, tau accumulation, and brain atrophy occurr in sequence, but the contribution of Alzheimer's disease (AD) pathology to biological and clinical progression remains unclear. METHODS: We included 290 and 70 participants with longitudinal assessment on Aß-positron emission tomography (PET), tau-PET, magnetic resonance imaging, and cognitive function from the Harvard Aging Brain Study (HABS) and Alzheimer's Disease Neuroimaging Initiative (ADNI) datasets, respectively. Partial least squares structural equation modeling (PLS-SEM) was used to determine the contribution of AD pathology to the biological and clinical longitudinal changes. RESULTS: Imaging biomarkers and cognitive function were significantly associated in cross-sectional and longitudinal analyses. At the final time point, the percentage of variance explained by PLS-SEM was 27% for Aß, 30% for tau (Aß accounted for 61%), 29% for brain atrophy (tau accounted for 37%), and 37% for cognitive decline (brain atrophy accounted for 35%). DISCUSSION: This study highlights distinctive contributing proportions of AD pathology to biological and clinical progression. Treatments targeting Aß and tau may partially block AD progression.

Differences between ante mortem Alzheimer's disease biomarkers in predicting neuropathology at autopsy.

INTRODUCTION: This study aimed to assess whether biomarkers related to amyloid, tau, and neurodegeneration can accurately predict Alzheimer's disease (AD) neuropathology at autopsy in early and late clinical stages. METHODS: We included 100 participants who had ante mortem biomarker measurements and underwent post mortem neuropathological examination. Based on ante mortem clinical diagnosis, participants were divided into non-dementia and dementia, as early or late clinical stages. RESULTS: Amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) amyloid beta (Aß)42/phosphorylated tau (p-tau)181 showed excellent performance in differentiating autopsy-confirmed AD and predicting the risk of neuropathological changes in early and late clinical stages. However, CSF Aß42 performed better in the early clinical stage, while CSF p-tau181, CSF t-tau, and plasma p-tau181 performed better in the late clinical stage. DISCUSSION: Our findings provide important clinical information that, if using PET, CSF, and plasma biomarkers to detect AD pathology, researchers must consider their differential performances at different clinical stages of AD. HIGHLIGHTS: Amyloid PET and CSF Aß42/p-tau181 were the most promising candidate biomarkers for predicting AD pathology. CSF Aß42 can serve as a candidate predictive biomarker in the early clinical stage of AD. CSF p-tau181, CSF t-tau, and plasma p-tau181 can serve as candidate predictive biomarkers in the late clinical stage of AD. Combining APOE ε4 genotypes can significantly improve the predictive accuracy of AD-related biomarkers for AD pathology.

Plasma Biomarkers and Positron Emission Tomography Tau Pathology in Progressive Supranuclear Palsy.

BACKGROUND: Development of disease-modifying therapeutic trials of progressive supranuclear palsy (PSP) urges the need for sensitive fluid biomarkers. OBJECTIVES: The objectives of this study were to explore the utility of plasma biomarkers in the diagnosis, differential diagnosis, and assessment of disease severity, brain atrophy, and tau deposition in PSP. METHODS: Plasma biomarkers were measured using a single-molecule array in a cohort composed of patients with PSP, Parkinson's disease (PD), multiple system atrophy with predominant parkinsonism (MSA-P), and healthy controls (HCs). RESULTS: Plasma neurofilament light chain (NfL) outperformed other plasma makers (ie, glial fibrillary acidic protein [GFAP], phosphorylated-tau 181 [p-tau181], amyloid-ß 1-40, amyloid-ß 1-42) in identifying PSP from HC (area under the curve [AUC] = 0.904) and from MSA-P (AUC = 0.711). Plasma GFAP aided in distinguishing PSP from HC (AUC = 0.774) and from MSA-P (AUC = 0.832). It correlated with brainstem atrophy and higher regional tau accumulation. However, plasma p-tau181 neither helped in diagnosis nor was it associated with clinical or neuroimaging measures. CONCLUSIONS: Plasma NfL and GFAP showed different values in differentiating PSP from HC or controls with other forms of neurodegenerative parkinsonism and detecting disease severity, brain atrophy, or tau deposition in PSP. © 2023 International Parkinson and Movement Disorder Society.