Changes in Serum Cystatin C Levels and the Associations With Cognitive Function in Alzheimer's Disease Patients

Longitudinal markers of cerebral amyloid angiopathy and related inflammation in rTg-DI rats

Cerebral amyloid angiopathy (CAA) is a prevalent vascular dementia and common comorbidity of Alzheimer's disease (AD). While it is known that vascular fibrillar amyloid β (Aβ) deposits leads to vascular deterioration and can drive parenchymal CAA related inflammation (CAA-ri), underlying mechanisms of CAA pathology remain poorly understood. Here, we conducted brain regional proteomic analysis of early and late disease stages in the rTg-DI CAA rat model to gain molecular insight to mechanisms of CAA/CAA-ri progression and identify potential brain protein markers of CAA/CAA-ri. Longitudinal brain regional proteomic analysis revealed increased differentially expressed proteins (DEP) including ANXA3, HTRA1, APOE, CST3, and CLU, shared between the cortex, hippocampus, and thalamus, at both stages of disease in rTg-DI rats. Subsequent pathway analysis indicated pathway enrichment and predicted activation of TGF-β1, which was confirmed by immunolabeling and ELISA. Further, we identified numerous CAA related DEPs associate with astrocytes (HSPB1 and MLC1) and microglia (ANXA3, SPARC, TGF-β1) not previously associated with astrocytes or microglia in other AD models, possibly indicating that they are specific to CAA-ri. Thus, the data presented here identify several potential brain protein biomarkers of CAA/CAA-ri while providing novel molecular and mechanistic insight to mechanisms of CAA and CAA-ri pathological progression and glial cell mediated responses.

The severity assessment of Parkinson's disease based on plasma inflammatory factors and third ventricle width by transcranial sonography

BACKGROUND

Predicting Parkinson's disease (PD) can provide patients with targeted therapies. However, disease severity can be roughly evaluated in clinical practice based on the patient's symptoms and signs.

OBJECTIVE

The current study attempted to explore the factors linked with PD severity and construct a predictive model.

METHOD

The PD patients and healthy controls were recruited from our study center while recording their basic demographic information. The serum inflammatory markers levels, such as Cystatin C (Cys C), C-reactive protein (CRP), RANTES (regulated on activation, normal T cell expressed and secreted), Interleukin-10 (IL-10), and Interleukin-6 (IL-6) were determined for all the participants. PD patients were categorized into early and mid-advanced groups based on the Hoehn and Yahr (H-Y) scale and evaluated using PD-related scales. LASSO logistic regression analysis (Model C) helped select variables based on clinical scale evaluations, serum inflammatory factor levels, and transcranial sonography measurements. The optimal harmonious model coefficient λ was determined via 10-fold cross-validation. Moreover, Model C was compared with multivariate (Model A) and stepwise (Model B) logistic regression. The area under the curve (AUC) of a receiver operator characteristic (ROC), brier score, calibration curve, and decision curve analysis (DCA) helped determine the discrimination and calibration of the predictive model, followed by configuring a forest plot and column chart.

RESULTS

The study included 113 healthy individuals and 102 PD patients, with 26 early and 76 mid-advanced patients. Univariate analysis of variance screened out statistically significant differences among inflammatory markers Cys C and RANTES. The average Cys C level in the mid-advanced stage was significantly higher than in the early stage (p < 0.001) but not for RANTES (p = 0.740). The LASSO logistic regression model (λ.1se = 0.061) associated with UPDRS-I, UPDRS-II, UPDRS-III, HAMA, PDQ-39, and Cys C as the included independent variables revealed that the Model C discrimination and calibration (AUC = 0.968, Brier = 0.049) were superior to Model A (AUC = 0.926, Brier = 0.079) and Model B (AUC = 0.929, Brier = 0.071) models.

CONCLUSION

The study results show multiple factors are linked with PD assessment. Moreover, the inflammatory marker Cys C and transcranial sonography measurement could objectively predict PD symptom severity, helping doctors monitor PD evolution in patients while targeting interventions.

Leukotriene B4 receptor knockdown affects PI3K/AKT/mTOR signaling and apoptotic responses in colorectal cancer

Colorectal cancer (CRC) presents a landscape of intricate molecular dynamics. In this study, we focused on the role of the leukotriene B4 receptor (LTB4R) in CRC, exploring its significance in the disease's progression and potential therapeutic approaches. Using bioinformatics analysis of the GSE164191 and the Cancer Genome Atlas-colorectal adenocarcinoma (TCGA-COAD) datasets, we identified LTB4R as a hub gene influencing CRC prognosis. Subsequently, we examined the relationship between LTB4R expression, apoptosis, and the phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway through cellular and mice experiments. Our findings revealed that LTB4R is highly expressed in CRC samples and is pivotal for determining prognosis. In vitro experiments demonstrated that silencing LTB4R significantly impeded CRC cell viability, migration, invasion, and colony formation. Correspondingly, in vivo tests indicated that LTB4R knockdown led to markedly slower tumor growth in mice models. Further in-depth investigation revealed that LTB4R knockdown significantly amplified the apoptosis in CRC cells and upregulated the expression of apoptosis-related proteins, such as caspase-3 and caspase-9, while diminishing p53 expression. Interestingly, silencing LTB4R also resulted in a significant downregulation of the PI3K/AKT/mTOR signaling pathway. Moreover, pretreatment with the PI3K activator 740Y-P only partially attenuated the effects of LTB4R knockdown on CRC cell behavior, emphasizing LTB4R's dominant influence in CRC cell dynamics and signaling pathways. LTB4R stands out as a critical factor in CRC progression, profoundly affecting cellular behavior, apoptotic responses, and the PI3K/AKT/mTOR signaling pathway. These findings not only shed light on LTB4R's role in CRC but also establish it as a potential diagnostic biomarker and a promising target for therapeutic intervention.

Cystatin C is associated with poor survival in amyotrophic lateral sclerosis patients

Background

Cystatin C (CysC) levels in amyotrophic lateral sclerosis (ALS) have been found changes, however, the associations between serum CysC levels and the progression and survival of ALS remain largely unknown.

Methods

A total of 1,086 ALS patients and 1,026 sex-age matched healthy controls (HCs) were enrolled in this study. Serum CysC, other renal function, and metabolic parameters were measured. Correlation analysis and binary logistic regression were used to explore the factors related to serum CysC. Kaplan-Meier curve and Cox regression model were used for survival analysis.

Results

CysC levels were significantly higher in ALS patients compared to HCs (0.94 vs. 0.85 mg/L, p < 0.001). Compared with ALS patients with lower CysC levels, those with higher CysC levels had an older age of onset, significantly lower ALSFRS-R scores (40.1 vs. 41.3, p < 0.001), a faster disease progression rate (0.75 vs. 0.67, p = 0.011), and lower frontal lobe function scores (15.8 vs. 16.1, p = 0.020). In the correlation analysis, CysC levels were significantly negatively correlated with ALSFRS-R scores (r = -0.16, p < 0.001). Additionally, ALS patients with higher CysC levels had significantly shorter survival time (40.0 vs. 51.8, p < 0.001) compared to patients with lower CysC levels. Higher CysC levels were associated with a higher risk of death in Cox analysis (HR: 1.204, 95% CI: 1.012-1.433). However, when treatment was included in the model, the result was no longer significant.

Conclusion

CysC levels in ALS patients were higher compared to HCs. Higher CysC levels were associated with greater disease severity, faster progression rate and shorter survival, needing early intervention.

Correlation between the Cognitive Status (SIRT1) and the Metabolic Function in Geriatric Patients Using the Indonesian Version of the Montreal Cognitive Assessment (MoCA-INA)

A growing life expectancy may result in a chronic medical condition and multimorbidity because the aging process leads to a decrease in cognitive and physiological function. These risks may affect the quality of life of geriatrics. The present study aims to determine the correlation between cognitive status (in terms of SIRT1, a nicotinamide adenine dinucleotide (NAD+)-dependent class III deacetylase) and metabolic function (in terms of the lipid profile, kidney function, and blood glucose) in geriatric patients. The differences in the parameters of metabolic function in the participants' cognitive status were determined by using the Indonesian version of the Montreal Cognitive Assessments (MoCA-Ina). The elderly participants (n = 120) were recruited at three sites in Indonesia from March to October 2022. Our study demonstrated a negative correlation between the cognitive status of geriatric patients and their metabolic function, represented by the MoCA-Ina score with a linear regression equation of y = 0.27 - 2.4 ×10-3x. Higher levels of LDL-C, cystatin C, and HbA1c were found in the Severe-Moderate Cognitive Impairment group. Determining the SIRT1 levels may be beneficial in predicting both the cognitive and metabolic status of geriatrics because this protein is among numerous metabolic sensors in the hypothalamus.

Human cystatin C induces the disaggregation process of selected amyloid beta peptides: a structural and kinetic view

Neurodegenerative diseases, such as Alzheimer's disease (AD) and various types of amyloidosis, are incurable; therefore, understanding the mechanisms of amyloid decomposition is crucial to develop an effective drug against them for future therapies. It has been reported that one out of three people over the age of 85 are suffering from dementia as a comorbidity to AD. Amyloid beta (Aβ), the hallmark of AD, transforms structurally from monomers into β-stranded aggregates (fibrils) via multiple oligomeric states. Astrocytes in the central nervous system secrete the human cystatin C protein (HCC) in response to various proteases and cytokines. The codeposition of Aβ and HCC in the brains of patients with AD led to the hypothesis that cystatin C is implicated in the disease process. In this study, we investigate the intermolecular interactions between different atomic structures of fibrils formed by Aβ peptides and HCC to understand the pathological aggregation of these polypeptides into neurotoxic oligomers and then amyloid plaques. To characterize the interactions between Aβ and HCC, we used a complementary approach based on the combination of small-angle neutron scattering analysis, atomic force microscopy and computational modelling, allowing the exploration of the structures of multicomponent protein complexes. We report here an optimized protocol to study that interaction. The results show a dependency of the sequence length of the Aβ peptide on the ability of the associated HCC to disaggregate it.

The Levels of Leptin, Cystatin C, Neuropilin-1 and Tau Protein in Relation to Dietary Habits in Patients with Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia in older people. Its prevalence is expected to increase, and therefore it poses a serious challenge to the healthcare system. The aim of the study was to assess the concentration of leptin, cystatin C, neuropilin-1 and tau protein, as well as the influence of dietary habits on these parameters, in a group of AD patients (n = 110) compared to 60 healthy people (n = 60). It has been shown that AD patients, compared to healthy people, are characterized by significantly higher median concentrations of leptin (9.97 vs. 3.08), cystatin c (1.53 vs. 0.56) and tau protein (8.46 vs. 4.19), but significantly lower median neuropilin-1 (69.94 vs. 167.28). Multiple regression analyses showed that leptin levels could be explained by dietary habits in 27%, cystatin C in 51%, neuropilin-1 in 41% and tau protein in 25% of cases. Modification of eating habits may contribute to improving the values of the discussed parameters.

Experimental Analysis of Tear Fluid and Its Processing for the Diagnosis of Multiple Sclerosis

A pilot analysis of the tear fluid of patients with multiple sclerosis (MS) collected by glass microcapillary was performed using various experimental methods: liquid chromatography-mass spectrometry, Raman spectroscopy, infrared spectroscopy, and atomic-force microscopy. Infrared spectroscopy found no significant difference between the tear fluid of MS patients and the control spectra; all three significant peaks were located at around the same positions. Raman analysis showed differences between the spectra of the tear fluid of MS patients and the spectra of healthy subjects, which indicated a decrease in tryptophan and phenylalanine content and changes in the relative contributions of the secondary structures of the polypeptide chains of tear proteins. Atomic-force microscopy exhibited a surface fern-shaped dendrite morphology of the tear fluid of patients with MS, with less roughness on both oriented silicon (100) and glass substrates compared to the tear fluid of control subjects. The results of liquid chromatography-mass spectrometry showed downregulation of glycosphingolipid metabolism, sphingolipid metabolism, and lipid metabolism. Proteomic analysis identified upregulated proteins in the tear fluid of patients with MS such as cystatine, phospholipid transfer protein, transcobalamin-1, immunoglobulin lambda variable 1-47, lactoperoxidase, and ferroptosis suppressor protein 1; and downregulated proteins such as haptoglobin, prosaposin, cytoskeletal keratin type I pre-mRNA-processing factor 17, neutrophil gelatinase-associated lipocalin, and phospholipase A2. This study showed that the tear proteome in patients with MS is modified and can reflect inflammation. Tear fluid is not a commonly used biological material in clinico-biochemical laboratories. Experimental proteomics has the potential to become a promising contemporary tool for personalized medicine, and it might be applied in clinical practice by providing a detailed analysis of the tear-fluid proteomic profile of patients with MS.

Decomposing interaction and mediating effects of race/ethnicity and circulating blood levels of cystatin C on cognitive status in the United States health and retirement study

Background and objectives

Elevated circulating cystatin C is associated with cognitive impairment in non-Hispanic Whites, but its role in racial disparities in dementia is understudied. In a nationally representative sample of older non-Hispanic White, non-Hispanic Black, and Hispanic adults in the United States, we use mediation-interaction analysis to understand how racial disparities in the cystatin C physiological pathway may contribute to racial disparities in prevalent dementia.

Methods

In a pooled cross-sectional sample of the Health and Retirement Study (n = 9,923), we employed Poisson regression to estimate prevalence ratios and to test the relationship between elevated cystatin C (>1.24 vs. ≤1.24 mg/L) and impaired cognition, adjusted for demographics, behavioral risk factors, other biomarkers, and chronic conditions. Self-reported racialized social categories were a proxy measure for exposure to racism. We calculated additive interaction measures and conducted four-way mediation-interaction decomposition analysis to test the moderating effect of race/ethnicity and mediating effect of cystatin C on the racial disparity.

Results

Overall, elevated cystatin C was associated with dementia (prevalence ratio [PR] = 1.2; 95% CI: 1.0, 1.5). Among non-Hispanic Black relative to non-Hispanic White participants, the relative excess risk due to interaction was 0.7 (95% CI: -0.1, 2.4), the attributable proportion was 0.1 (95% CI: -0.2, 0.4), and the synergy index was 1.1 (95% CI: 0.8, 1.8) in a fully adjusted model. Elevated cystatin C was estimated to account for 2% (95% CI: -0, 4%) for the racial disparity in prevalent dementia, and the interaction accounted for 8% (95% CI: -5, 22%). Analyses for Hispanic relative to non-white participants suggested moderation by race/ethnicity, but not mediation.

Discussion

Elevated cystatin C was associated with dementia prevalence. Our mediation-interaction decomposition analysis suggested that the effect of elevated cystatin C on the racial disparity might be moderated by race/ethnicity, which indicates that the racialization process affects not only the distribution of circulating cystatin C across minoritized racial groups, but also the strength of association between the biomarker and dementia prevalence. These results provide evidence that cystatin C is associated with adverse brain health and this effect is larger than expected for individuals racialized as minorities had they been racialized and treated as non-Hispanic White.

Serum cystatin C and mild cognitive impairment: The mediating role of glucose homeostasis

Background

This study explored the mediating role of glucose homeostasis indicators in the relationship between serum cystatin C and mild cognitive impairment (MCI).

Methods

The present study used a cross-sectional design and included 514 participants aged ≥50 years in Beijing, China. The Mini-Mental State Examination was used to assess cognitive function. Serum cystatin C and a comprehensive set of glucose homeostasis indicators were detected, including fasting blood glucose (FBG), glycosylated albumin percentage (GAP), glycated hemoglobin (HbAlc), insulin, and homeostatic model assessment of insulin resistance (HOMA-IR), and beta cell function (HOMA-β). Generalized linear models were used to investigate the associations among cystatin C, glucose homeostasis indicators, and cognitive function. Mediation analysis was conducted to explore potential mediator variables.

Results

In this study of 514 participants, 76 (14.8%) had MCI. Those with cystatin C levels ≥1.09 mg/L had a 1.98-fold higher risk of MCI than those with levels &lt;1.09 mg/L (95% CI, 1.05–3.69). FBG, GAP, and HbA1c increased the risk of MCI, while HOMA-β decreased the risk. Notably, the associations between MCI risk and cystatin C or glucose homeostasis were only founded in diabetes patients. Serum cystatin C was found to be positively associated with HOMA-β (beta (95% CI): 0.20 [0.06, 0.34]), HOMA-IR (0.23 [0.09, 0.36]), and insulin (0.22 [0.09, 0.34]) levels. Moreover, HOMA-β was identified as playing a negative mediating role (proportion mediated: −16%) in the relationship between cystatin C and MCI.

Conclusion

Elevated levels of cystatin C are associated with an increased risk of MCI. The glucose homeostasis indicator, HOMA-β, plays a negative mediating role in the relationship between cystatin C and MCI risk.

Association between serum cystatin C level and cognition in older adults: a cross-sectional analysis

Introduction

Serum Cystatin C level, an indication of kidney function, has been implicated in the pathogenesis of Alzheimer's disease and cognitive impairment. In this cross-sectional study, we looked into the relation between serum Cystatin C levels and cognition in a group of U.S. older adults.

Method

The data of this study were from the National Health and Nutrition Examination Survey (NHANES) 1999-2002. A total of 4,832 older adults aged ≥60 who met the inclusion criteria were included. The Dade Behring N Latex Cystatin C assay, which is a particle-enhanced nephelometric assay (PENIA), was utilized to assess Cystatin C levels in participants' blood samples. Participants' cognition was examined using the digit symbol substitution test (DSST). Z-scores of the DSST were calculated based on sample means and standard deviations (SD). To investigate the relationships between the quartiles of serum Cystatin C level and DSST z scores, multiple linear regression models were developed while controlling for age, sex, race/ethnicity, and education.

Results

The average age of the participants was 71.1 (SD 7.8). The participants were about half female (50.5%), non-Hispanic White (61.2%), and (36.1%) who had completed at least some college. They had an average serum Cystatin C level of 1.0 mg/dl (SD 0.44). After performing multiple linear regression with a reference group consisting of participants in quartile one of plasma Cystatin C levels, we found that serum Cystatin C levels in quartiles three and four were independently associated with lower DSST z scores (β = -0.059, 95% CI -0.200 to -0.074 and β = -0.108, 95% CI -0.319 to -0.184, respectively).

Conclusion

Higher serum Cystatin C level is associated with worse processing speed, sustained attention, and working memory in older adults. Cystatin C level may be a biomarker for cognitive decline in older adults.

Cystatin C predicts cognitive decline in multiple system atrophy: A 1-year prospective cohort study

BACKGROUND

Accumulating evidence has suggested that cystatin C is associated with cognitive impairment in patients with neurodegenerative diseases. However, the association between cystatin C and cognitive decline in patients with multiple system atrophy (MSA) remains largely unknown.

OBJECTIVES

The objective was to determine whether cystatin C was independently associated with cognitive decline in patients with early-stage MSA.

METHODS

Patients with MSA underwent evaluation at baseline and the 1-year follow-up. Cognitive function was evaluated with Montreal cognitive assessment (MoCA). Changes in the MoCA score and the absolute MoCA score at the 1-year assessment were considered the main cognitive outcome. The cystatin C concentrations in patients with MSA and age, sex, and body mass index matched-healthy controls (HCs) were measured. A multiple linear regression model was used to test the association between cystatin C and cognitive decline.

RESULTS

A total of 117 patients with MSA and 416 HCs were enrolled in the study. The cystatin C levels were significantly higher in patients with MSA than in HCs (p < 0.001). Cystatin C levels were negatively correlated with MoCA score at baseline and at 1-year follow-up. Multiple linear regression model adjusted for potential confounders showed that baseline cystatin C levels were significantly associated with the MoCA score (p = 0.004) or change in the MoCA score (p = 0.008) at 1-year follow-up.

CONCLUSION

Our results suggested that cystatin C may serve as a potential biomarker of cognitive decline in patients with early-stage MSA.

Salivary inflammatory biomarkers are predictive of mild cognitive impairment and Alzheimer's disease in a feasibility study

Alzheimer's disease (AD) is an insidious disease. Its distinctive pathology forms over a considerable length of time without symptoms. There is a need to detect this disease, before even subtle changes occur in cognition. Hallmark AD biomarkers, tau and amyloid-β, have shown promising results in CSF and blood. However, detecting early changes in these biomarkers and others will involve screening a wide group of healthy, asymptomatic individuals. Saliva is a feasible alternative. Sample collection is economical, non-invasive and saliva is an abundant source of proteins including tau and amyloid-β. This work sought to extend an earlier promising untargeted mass spectrometry study in saliva from individuals with mild cognitive impairment (MCI) or AD with age- and gender-matched cognitively normal from the South Australian Neurodegenerative Disease cohort. Five proteins, with key roles in inflammation, were chosen from this study and measured by ELISA from individuals with AD (n = 16), MCI (n = 15) and cognitively normal (n = 29). The concentrations of Cystatin-C, Interleukin-1 receptor antagonist, Stratifin, Matrix metalloproteinase 9 and Haptoglobin proteins had altered abundance in saliva from AD and MCI, consistent with the earlier study. Receiver operating characteristic analysis showed that combinations of these proteins demonstrated excellent diagnostic accuracy for distinguishing both MCI (area under curve = 0.97) and AD (area under curve = 0.97) from cognitively normal. These results provide evidence for saliva being a valuable source of biomarkers for early detection of cognitive impairment in individuals on the AD continuum and potentially other neurodegenerative diseases.

Machine Learning Analysis Reveals Biomarkers for the Detection of Neurological Diseases

It is critical to identify biomarkers for neurological diseases (NLDs) to accelerate drug discovery for effective treatment of patients of diseases that currently lack such treatments. In this work, we retrieved genotyping and clinical data from 1,223 UK Biobank participants to identify genetic and clinical biomarkers for NLDs, including Alzheimer's disease (AD), Parkinson's disease (PD), motor neuron disease (MND), and myasthenia gravis (MG). Using a machine learning modeling approach with Monte Carlo randomization, we identified a panel of informative diagnostic biomarkers for predicting AD, PD, MND, and MG, including classical liver disease markers such as alanine aminotransferase, alkaline phosphatase, and bilirubin. A multinomial model trained on accessible clinical markers could correctly predict an NLD diagnosis with an accuracy of 88.3%. We also explored genetic biomarkers. In a genome-wide association study of AD, PD, MND, and MG patients, we identified single nucleotide polymorphisms (SNPs) implicated in several craniofacial disorders such as apnoea and branchiootic syndrome. We found evidence for shared genetic risk loci among NLDs, including SNPs in cancer-related genes and SNPs known to be associated with non-brain cancers such as Wilms tumor, leukemia, and colon cancer. This indicates overlapping genetic characterizations among NLDs which challenges current clinical definitions of the neurological disorders. Taken together, this work demonstrates the value of data-driven approaches to identify novel biomarkers in the absence of any known or promising biomarkers.