Cholinesterase inhibitor use in amyloid PET-negative mild cognitive impairment and cognitive changes.

BACKGROUND: Cholinesterase inhibitors (ChEIs) are prescribed for Alzheimer's disease (AD) and sometimes for mild cognitive impairment (MCI) without knowing underlying pathologies and its effect on cognition. We investigated the frequency of ChEI prescriptions in amyloid-negative MCI and their association with cognitive changes in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. METHODS: We included participants with amyloid positron emission tomography (PET)-negative MCI from the ADNI. We analyzed the associations of ChEI use with cognitive changes, brain volume, and cerebrospinal fluid (CSF) total tau (t-tau), hyperphosphorylated tau181 (p-tau181), and p-tau181/t-tau ratio. RESULTS: ChEIs were prescribed in 27.4% of amyloid PET-negative MCI and were associated with faster cognitive decline, reduced baseline hippocampal volume and entorhinal cortical thickness, and a longitudinal decrease in the frontal lobe cortical thickness. CONCLUSIONS: The association between ChEI use and accelerated cognitive decline may stem from underlying pathologies involving reduced hippocampal volume, entorhinal cortical thickness and faster frontal lobe atrophy. We suggest that ChEI use in amyloid PET-negative MCI patients might need further consideration, and studies investigating the causality between ChEI use and cognitive decline are warranted in the future.

Subthreshold amyloid deposition, cerebral small vessel disease, and functional brain network disruption in delayed cognitive decline after stroke.

Background: Although its incidence is relatively low, delayed-onset post-stroke cognitive decline (PSCD) may offer valuable insights into the "vascular contributions to cognitive impairment and dementia," particularly concerning the roles of vascular and neurodegenerative mechanisms. We postulated that the functional segregation observed during post-stroke compensation could be disrupted by underlying amyloid pathology or cerebral small vessel disease (cSVD), leading to delayed-onset PSCD. Methods: Using a prospective stroke registry, we identified patients who displayed normal cognitive function at baseline evaluation within a year post-stroke and received at least one subsequent assessment. Patients suspected of pre-stroke cognitive decline were excluded. Decliners [defined by a decrease of ≥3 Mini-Mental State Examination (MMSE) points annually or an absolute drop of ≥5 points between evaluations, confirmed with detailed neuropsychological tests] were compared with age- and stroke severity-matched non-decliners. Index-stroke MRI, resting-state functional MRI, and 18F-florbetaben PET were used to identify cSVD, functional network attributes, and amyloid deposits, respectively. PET data from age-, sex-, education-, and apolipoprotein E-matched stroke-free controls within a community-dwelling cohort were used to benchmark amyloid deposition. Results: Among 208 eligible patients, 11 decliners and 10 matched non-decliners were identified over an average follow-up of 5.7 years. No significant differences in cSVD markers were noted between the groups, except for white matter hyperintensities (WMHs), which were strongly linked with MMSE scores among decliners (rho = -0.85, p < 0.01). Only one decliner was amyloid-positive, yet subthreshold PET standardized uptake value ratios (SUVR) in amyloid-negative decliners inversely correlated with final MMSE scores (rho = -0.67, p = 0.04). Decliners exhibited disrupted modular structures and more intermingled canonical networks compared to non-decliners. Notably, the somato-motor network's system segregation corresponded with the decliners' final MMSE (rho = 0.67, p = 0.03) and was associated with WMH volume and amyloid SUVR. Conclusion: Disruptions in modular structures, system segregation, and inter-network communication in the brain may be the pathophysiological underpinnings of delayed-onset PSCD. WMHs and subthreshold amyloid deposition could contribute to these disruptions in functional brain networks. Given the limited number of patients and potential residual confounding, our results should be considered hypothesis-generating and need replication in larger cohorts in the future.

Enhancing Breast Cancer Detection through Advanced AI-Driven Ultrasound Technology: A Comprehensive Evaluation of Vis-BUS.

This study aims to enhance breast cancer detection accuracy through an AI-driven ultrasound tool, Vis-BUS, developed by Barreleye Inc., Seoul, South Korea. Vis-BUS incorporates Lesion Detection AI (LD-AI) and Lesion Analysis AI (LA-AI), along with a Cancer Probability Score (CPS), to differentiate between benign and malignant breast lesions. A retrospective analysis was conducted on 258 breast ultrasound examinations to evaluate Vis-BUS's performance. The primary methods included the application of LD-AI and LA-AI to b-mode ultrasound images and the generation of CPS for each lesion. Diagnostic accuracy was assessed using metrics such as the Area Under the Receiver Operating Characteristic curve (AUROC) and the Area Under the Precision-Recall curve (AUPRC). The study found that Vis-BUS achieved high diagnostic accuracy, with an AUROC of 0.964 and an AUPRC of 0.967, indicating its effectiveness in distinguishing between benign and malignant lesions. Logistic regression analysis identified that 'Fatty' lesion density had an extremely high odds ratio (OR) of 27.7781, suggesting potential convergence issues. The 'Unknown' density category had an OR of 0.3185, indicating a lower likelihood of correct classification. Medium and large lesion sizes were associated with lower likelihoods of correct classification, with ORs of 0.7891 and 0.8014, respectively. The presence of microcalcifications showed an OR of 1.360. Among Breast Imaging-Reporting and Data System categories, category C5 had a significantly higher OR of 10.173, reflecting a higher likelihood of correct classification. Vis-BUS significantly improves diagnostic precision and supports clinical decision-making in breast cancer screening. However, further refinement is needed in areas like lesion density characterization and calcification detection to optimize its performance.

Neuropsychological Correlates of Clinical Progression in Subjective Cognitive Decline.

Background: Subjective cognitive decline (SCD) refers to self-reported cognitive decline in individuals with normal performance on standardized cognitive tests. Understanding the factors predicting progression from SCD to mild cognitive impairment (MCI) is crucial, as approximately 14% of SCD cases progress to dementia and about 27% develop MCI over four years. Objective: This study aims to identify neuropsychological predictors of progression from SCD to MCI, focusing on cognitive domains assessed through neuropsychological tests. Methods: This retrospective study at Seoul National University Bundang Hospital analyzed a cohort of 107 patients diagnosed with SCD through comprehensive assessment. Patients underwent annual neuropsychological testing, including the Digit Span Test, Boston Naming Test, Rey Complex Figure Test, Seoul Verbal Learning Test, and Stroop Test. Results: Annually, these patients underwent neuropsychological tests over a 5-year period; 24 progressed to MCI per NIA-AA criteria. Key predictors of MCI progression included age, ischemic heart disease, and scores from the forward digit span, delayed recall, and Boston naming tests. Lower scores in delayed recall and Boston naming tests significantly correlated with a higher risk of MCI (p < 0.001). Conclusions: These findings suggest a need for targeted management of memory and language functions to monitor disease progression effectively.

Rapid quantitative high-throughput mouse embryoid body model for embryotoxicity assessment.

Individuals are exposed to a wide arrays of hazardous chemicals on a daily basis through various routes, many of which have not undergone comprehensive toxicity assessments. While traditional developmental toxicity tests involving pregnant animals are known for their reliability, they are also associated with high costs and time requirements. Consequently, there is an urgent demand for alternative, cost-efficient, and rapid in vitro testing methods. This study aims to address the challenges related to automating and streamlining the screening of early developmental toxicity of chemicals by introducing a mouse embryoid body test (EBT) model in a 384-ultra low attachment well format. Embryoid bodies (EBs) generated in this format were characterized by a spontaneous differentiation trajectory into cardiac mesoderm by as analyzed by RNA-seq. Assessing prediction accuracy using reference compounds suggested in the ICH S5(R3) guideline and prior studies resulted in the establishment of the acceptance criteria and applicability domain of the EBT model. The results indicated an 84.38% accuracy in predicting the developmental toxicity of 23 positive and 9 negative reference compounds, with an optimized cutoff threshold of 750 µM. Overall, the developed EBT model presents a promising approach for more rapid, high-throughput chemical screening, thereby facilitating well-informed decision-making in environmental management and safety assessments.

miR-133b as a potential regulator of a synaptic NPTX2 protein in Alzheimer's disease.

A synaptic protein, Neuronal Pentraxin 2 (NPTX2), has emerged as a pivotal biomarker for Alzheimer's dementia (AD). We identified candidate miRNAs targeting NPTX2 and performed association and mediation analyses using multi-omics data (N = 702). Among 44 candidate miRNAs, miR-133b was significantly associated with AD and Braak positivity. Higher miR-133b expression was also associated with higher NPTX2 gene expression and better cognition. Mediation analysis showed that miR-133b partially influences AD and cognition through the NPTX2 protein. Our integrated approach suggests a potential role of miR-133b in synaptic integrity and offers new insights into AD pathogenesis.

Predictive biomarkers for embryotoxicity: a machine learning approach to mitigating multicollinearity in RNA-Seq.

Multicollinearity, characterized by significant co-expression patterns among genes, often occurs in high-throughput expression data, potentially impacting the predictive model's reliability. This study examined multicollinearity among closely related genes, particularly in RNA-Seq data obtained from embryoid bodies (EB) exposed to 5-fluorouracil perturbation to identify genes associated with embryotoxicity. Six genes-Dppa5a, Gdf3, Zfp42, Meis1, Hoxa2, and Hoxb1-emerged as candidates based on domain knowledge and were validated using qPCR in EBs perturbed by 39 test substances. We conducted correlation studies and utilized the variance inflation factor (VIF) to examine the existence of multicollinearity among the genes. Recursive feature elimination with cross-validation (RFECV) ranked Zfp42 and Hoxb1 as the top two among the seven features considered, identifying them as potential early embryotoxicity assessment biomarkers. As a result, a t test assessing the statistical significance of this two-feature prediction model yielded a p value of 0.0044, confirming the successful reduction of redundancies and multicollinearity through RFECV. Our study presents a systematic methodology for using machine learning techniques in transcriptomics data analysis, enhancing the discovery of potential reporter gene candidates for embryotoxicity screening research, and improving the predictive model's predictive accuracy and feasibility while reducing financial and time constraints.

A Comparison of Item Characteristics and Test Information Between the K-MMSE~2:SV and K-MMSE.

Background and Purpose: The Korean-Mini Mental State Examination, 2nd edition (K-MMSE~2) was recently released. This study aimed to determine whether the K-MMSE~2: Standard Version (K-MMSE~2:SV) had the same test characteristics as the K-MMSE. Methods: A total of 1,514 healthy community-based participants aged 19 to 90 years were administered the K-MMSE~2:SV Blue Form along with the language items from the K-MMSE. The item and test characteristics and test information for the K-MMSE~2:SV and K-MMSE were compared using Item Response Theory analysis. Results: Item discriminations for the K-MMSE~2:SV and K-MMSE were above the moderate range for all items except Recall. Most of the items on the K-MMSE~2:SV and K-MMSE had item category difficulty in the very easy or easy range. The test information curve (TIC) showed that the K-MMSE~2:SV and K-MMSE provide almost the same amount of information (27.86 vs. 28.44), with both tests providing the most information at an ability level of -1.57. The generalizability (G) coefficient for the K-MMSE~2:SV and K-MMSE was 0.99. Conclusions: These results indicate that the K-MMSE~2:SV and K-MMSE are equally optimal tests for screening for mild cognitive impairment and early dementia. Given that the amount of test information provided by the two tests was almost identical, the shapes of the TICs were very similar, and the G coefficient was close to 1, we can conclude that the K-MMSE and K-MMSE~2:SV are equivalent tests.

Association of liver function markers and apolipoprotein E ε4 with pathogenesis and cognitive decline in Alzheimer's disease.

Background: Alzheimer's disease (AD) is a complex neurodegenerative disorder influenced by various factors, including liver function, which may impact the clearance of amyloid-ß (Aß) in the brain. This study aimed to explore how the apolipoprotein E (APOE) ε4 allele affects the relationship of liver function markers with AD pathology and cognition. Methods: We analyzed data from two independent cohorts, including 732 participants from the Hallym University Medical Center and 483 from the Alzheimer's Disease Neuroimaging Initiative, each group consisting of individuals with and without the APOE ε4 allele. Cross-sectional analyses evaluated the associations of liver enzymes (aspartate aminotransferase [AST], alanine aminotransferase [ALT], alkaline phosphatase, total bilirubin, and albumin) with AD diagnosis, amyloid positron emission tomography (PET) burden, and cerebrospinal fluid biomarkers for AD (Aß42, total tau, and phosphorylated tau181) at baseline. Longitudinally, we investigated the associations between these liver enzymes and changes in cognitive performance over the course of a year. Logistic and linear regression models were used to analyze these associations and mediation analyses were conducted to assess whether age and amyloid PET burden mediated these associations. Results: Only in the APOE ε4 carrier group, a high AST to ALT ratio and low ALT levels were significantly associated with AD diagnosis, increased amyloid PET burden, and faster longitudinal decline in cognitive function in both cohorts. In particular, the AST to ALT ratio was associated with cerebrospinal fluid Aß42 levels exclusively in the APOE ε4 carrier group in the Alzheimer's Disease Neuroimaging Initiative cohort but not with phosphorylated tau181 or total tau levels. Moreover, mediation analyses from both cohorts revealed that in the APOE ε4 carriers group, age did not mediate the associations between liver enzymes and AD diagnosis or amyloid PET burden. However, amyloid PET burden partially mediated the association between liver enzymes and AD diagnosis exclusively in the APOE ε4 carriers group. Conclusion: This study provides valuable insights into the significant association of the APOE ε4 allele with liver enzymes and their potential role in Aß-related pathogenesis and cognition in AD. Further research is required to elucidate the underlying mechanisms and potential therapeutic implications of these findings.

A Framework for Best Practices and Readiness in the Advent of Anti-Amyloid Therapy for Early Alzheimer's Disease in Asia.

Advances in biomarker-based diagnostic modalities, recent approval of anti-amyloid monoclonal antibodies for early Alzheimer's disease (AD; mild cognitive impairment or mild dementia due to AD) and late-stage clinical development of other disease-modifying therapies for AD necessitate a significant paradigm shift in the early detection, diagnosis and management of AD. Anti-amyloid monoclonal antibodies target the underlying pathophysiological mechanisms of AD and have demonstrated a significant reduction in the rate of clinical decline in cognitive and functional outcome measures in patients with early AD. With growing recognition of the benefit of early interventions in AD, an increasing number of people may seek diagnosis for their subjective cognitive problems in an already busy medical system. Various factors such as limited examination time, lack of expertise for cognitive assessment and limited access to specialized tests can impact diagnostic accuracy and timely detection of AD. To overcome these challenges, a new model of care will be required. In this paper, we provide practical guidance for institutional readiness for anti-amyloid therapies for early AD in Asia, in terms of best practices for identifying eligible patients and diagnosing them appropriately, safe administration of anti-amyloid monoclonal antibodies and monitoring of treatment, managing potential adverse events such as infusion reactions and amyloid-related imaging abnormalities, and cross-disciplinary collaboration. Education and training will be the cornerstone for the establishment of new pathways of care for the identification of patients with early AD and delivery of anti-amyloid therapies in a safe and efficient manner to eligible patients.

Application of Quantitative Ultrasonography and Artificial Intelligence for Assessing Severity of Fatty Liver: A Pilot Study.

Non-alcoholic fatty liver disease (NAFLD), prevalent among conditions like obesity and diabetes, is globally significant. Existing ultrasound diagnosis methods, despite their use, often lack accuracy and precision, necessitating innovative solutions like AI. This study aims to validate an AI-enhanced quantitative ultrasound (QUS) algorithm for NAFLD severity assessment and compare its performance with Magnetic Resonance Imaging Proton Density Fat Fraction (MRI-PDFF), a conventional diagnostic tool. A single-center cross-sectional pilot study was conducted. Liver fat content was estimated using an AI-enhanced quantitative ultrasound attenuation coefficient (QUS-AC) of Barreleye Inc. with an AI-based QUS algorithm and two conventional ultrasound techniques, FibroTouch Ultrasound Attenuation Parameter (UAP) and Canon Attenuation Imaging (ATI). The results were compared with MRI-PDFF values. The intraclass correlation coefficient (ICC) was also assessed. Significant correlation was found between the QUS-AC and the MRI-PDFF, reflected by an R value of 0.95. On other hand, ATI and UAP displayed lower correlations with MRI-PDFF, yielding R values of 0.73 and 0.51, respectively. In addition, ICC for QUS-AC was 0.983 for individual observations. On the other hand, the ICCs for ATI and UAP were 0.76 and 0.39, respectively. Our findings suggest that AC with AI-enhanced QUS could serve as a valuable tool for the non-invasive diagnosis of NAFLD.

Assessing systemic, developmental, and reproductive toxicity and estrogenicity of Korean red ginseng extract G1899 in juvenile Sprague-Dawley Rats.

Background: Korean red ginseng (KRG) is a product from ginseng roots, which is enriched with ginsenosides and has been utilized for a long time as an adaptogen to alleviate various physiological or disease conditions. While KRG is generally considered safe, conducting a thorough toxicological assessment of the spray-dried powder G1899 during the juvenile period is essential to establish its safety profile. This study aimed to assess the safety of G1899 during the juvenile period using Sprague-Dawley rats. Methods: Two studies were conducted separately: a juvenile toxicity study and a uterotrophic bioassay. To assess the potential toxicity at systemic, postnatal developmental, and reproductive levels, G1899 was orally gavaged once a day in post-weaning juvenile Sprague-Dawley (SD) rats at 0, 1250, 2500, or 5000 mg/kg/day. Estrogenicity was assessed by orally gavaging G1899 in immature female SD rats at 0, 2500, or 5000 mg/kg/day on postnatal days (PND) 19-21, followed by a uterotrophic bioassay. These studies were conducted in accordance with the Good Laboratory Practice (GLP) regulations and regulatory test guidelines. Results: Regarding juvenile toxicity, no abnormalities related to the G1899 treatment were observed in any group during the experiment. Moreover, no uterotrophic responses were observed in the dosed female group. Based on these results, the no observed adverse effect level (NOAEL) of G1899 was determined to be at least 5000 mg/kg/day for general systemic function, developmental/reproductive function, and estrogenic activity. Conclusion: Our results suggest that G1899 is not toxic to juveniles at doses of up to 5000 mg/kg/day.

Ventral Anterior Cingulate Atrophy as a Predisposing Factor for Transient Global Amnesia.

Background and Purpose: This study aimed to evaluate the brain magnetic resonance imaging (MRI) of patients with acute transient global amnesia (TGA) using volumetric analysis to verify whether the brains of TGA patients have pre-existing structural abnormalities. Methods: We evaluated the brain MRI data from 87 TGA patients and 20 age- and sex-matched control subjects. We included brain MRIs obtained from TGA patients within 72 hours of symptom onset to verify the pre-existence of structural change. For voxel-based morphometric analyses, statistical parametric mapping was employed to analyze the structural differences between patients with TGA and control subjects. Results: TGA patients exhibited significant volume reductions in the bilateral ventral anterior cingulate cortices (corrected p<0.05). Conclusions: TGA patients might have pre-existing structural changes in bilateral ventral anterior cingulate cortices prior to TGA attacks.

Artificial Intelligence-Enhanced Quantitative Ultrasound for Breast Cancer: Pilot Study on Quantitative Parameters and Biopsy Outcomes.

Traditional B-mode ultrasound has difficulties distinguishing benign from malignant breast lesions. It appears that Quantitative Ultrasound (QUS) may offer advantages. We examined the QUS imaging system's potential, utilizing parameters like Attenuation Coefficient (AC), Speed of Sound (SoS), Effective Scatterer Diameter (ESD), and Effective Scatterer Concentration (ESC) to enhance diagnostic accuracy. B-mode images and radiofrequency signals were gathered from breast lesions. These parameters were processed and analyzed by a QUS system trained on a simulated acoustic dataset and equipped with an encoder-decoder structure. Fifty-seven patients were enrolled over six months. Biopsies served as the diagnostic ground truth. AC, SoS, and ESD showed significant differences between benign and malignant lesions (p < 0.05), but ESC did not. A logistic regression model was developed, demonstrating an area under the receiver operating characteristic curve of 0.90 (95% CI: 0.78, 0.96) for distinguishing between benign and malignant lesions. In conclusion, the QUS system shows promise in enhancing diagnostic accuracy by leveraging AC, SoS, and ESD. Further studies are needed to validate these findings and optimize the system for clinical use.

Progesterone increases hepatic lipid content and plasma lipid levels through PR- B-mediated lipogenesis.

Progesterone (P4) is a crucial reproductive hormone that acts as a precursor for all other endogenous steroids. P4 modulates transcriptional activity during reproduction by binding to progesterone receptors (PR). However, the physiological role of P4 in the liver is understudied. P4-mediated lipid metabolism in the liver was investigated in this study, as P4 facilitates insulin resistance and influences energy metabolism. While exogenous lipids are mainly obtained from food, the liver synthesizes endogenous triglycerides and cholesterol from a carbohydrate diet. Hepatic de novo lipogenesis (DNL) is primarily determined by acetyl-CoA and its biosynthetic pathways, which involve fatty acid and cholesterol synthesis. While P4 increased the hepatic levels of sterol regulatory element-binding protein 1 C (SREBP-1 C), peroxisome proliferator-activated receptor-gamma (PPARγ), acetyl-CoA carboxylase (ACC), and CD36, co-treatment with the P4 receptor antagonist RU486 blocked these proteins and P4-mediated lipogenesis. RNA sequencing was used to assess the role of P4 in lipogenic events, such as fatty liver and fatty acid metabolism, lipoprotein signaling, and cholesterol metabolism. P4 induced hepatic DNL and lipid anabolism were confirmed in the liver of ovarian resection mice fed a high-fat diet or in pregnant mice. P4 increased lipogenesis directly in mice exposed to P4 and indirectly in fetuses exposed to maternal P4. The lipid balance between lipogenesis and lipolysis determines fat build-up and is linked to lipid metabolism dysfunction, which involves the breakdown and storage of fats for energy and the synthesis of structural and functional lipids. Therefore, P4 may impact the lipid metabolism and reproductive development during gestation.

Harnessing the Power of Voice: A Deep Neural Network Model for Alzheimer's Disease Detection.

Background and Purpose: Voice, reflecting cerebral functions, holds potential for analyzing and understanding brain function, especially in the context of cognitive impairment (CI) and Alzheimer's disease (AD). This study used voice data to distinguish between normal cognition and CI or Alzheimer's disease dementia (ADD). Methods: This study enrolled 3 groups of subjects: 1) 52 subjects with subjective cognitive decline; 2) 110 subjects with mild CI; and 3) 59 subjects with ADD. Voice features were extracted using Mel-frequency cepstral coefficients and Chroma. Results: A deep neural network (DNN) model showed promising performance, with an accuracy of roughly 81% in 10 trials in predicting ADD, which increased to an average value of about 82.0%±1.6% when evaluated against unseen test dataset. Conclusions: Although results did not demonstrate the level of accuracy necessary for a definitive clinical tool, they provided a compelling proof-of-concept for the potential use of voice data in cognitive status assessment. DNN algorithms using voice offer a promising approach to early detection of AD. They could improve the accuracy and accessibility of diagnosis, ultimately leading to better outcomes for patients.

Relationship Between Amyloid Positivity and Sleep Characteristics in the Elderly With Subjective Cognitive Decline.

Background and Purpose: Alzheimer's disease (AD) is a neurodegenerative disease characterized by a progressive decline in cognition and performance of daily activities. Recent studies have attempted to establish the relationship between AD and sleep. It is believed that patients with AD pathology show altered sleep characteristics years before clinical symptoms appear. This study evaluated the differences in sleep characteristics between cognitively asymptomatic patients with and without some amyloid burden. Methods: Sleep characteristics of 76 subjects aged 60 years or older who were diagnosed with subjective cognitive decline (SCD) but not mild cognitive impairment (MCI) or AD were measured using Fitbit® Alta HR, a wristwatch-shaped wearable device. Amyloid deposition was evaluated using brain amyloid plaque load (BAPL) and global standardized uptake value ratio (SUVR) from fluorine-18 florbetaben positron emission tomography. Each component of measured sleep characteristics was analyzed for statistically significant differences between the amyloid-positive group and the amyloid-negative group. Results: Of the 76 subjects included in this study, 49 (64.5%) were female. The average age of the subjects was 70.72±6.09 years when the study started. 15 subjects were classified as amyloid-positive based on BAPL. The average global SUVR was 1.598±0.263 in the amyloid-positive group and 1.187±0.100 in the amyloid-negative group. Time spent in slow-wave sleep (SWS) was significantly lower in the amyloid-positive group (39.4±13.1 minutes) than in the amyloid-negative group (49.5±13.1 minutes) (p=0.009). Conclusions: This study showed that SWS is different between the elderly SCD population with and without amyloid positivity. How SWS affects AD pathology requires further research.

Subsequent correlated changes in complement component 3 and amyloid beta oligomers in the blood of patients with Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) involves the complement cascade, with complement component 3 (C3) playing a key role. However, the relationship between C3 and amyloid beta (Aß) in blood is limited. METHODS: Plasma C3 and Aß oligomerization tendency (AßOt) were measured in 35 AD patients and 62 healthy controls. Correlations with cerebrospinal fluid (CSF) biomarkers, cognitive impairment, and amyloid positron emission tomography (PET) were analyzed. Differences between biomarkers were compared in groups classified by concordances of biomarkers. RESULTS: Plasma C3 and AßOt were elevated in AD patients and in CSF or amyloid PET-positive groups. Weak positive correlation was found between C3 and AßOt, while both had strong negative correlations with CSF Aß42 and cognitive performance. Abnormalities were observed for AßOt and CSF Aß42 followed by C3 changes. DISCUSSION: Increased plasma C3 in AD are associated with amyloid pathology, possibly reflecting a defense response for Aß clearance. Further studies on Aß-binding proteins will enhance understanding of Aß mechanisms in blood.