-ε4 allele[s]-associated adverse events reported from placebo arm in clinical trials for Alzheimer's disease: implications for anti-amyloid beta therapy.

-ε4 allele[s] is a risk factor for Alzheimer's disease (AD) and Amyloid-Related Imaging Abnormalities (ARIA) in anti-amyloid beta therapy, and is also associated with cerebrovascular risk factors such as hyperlipidemia or atherosclerosis. During AD clinical trials, -ε4 carriers may experience neuropsychiatric adverse events (AEs) related to these risks, complicating the differentiation of ARIA from cerebrovascular events based on symptoms. This study aimed to examine the hypothetical impact of considering the -ε4 allele's risk for non-ARIA AEs during AD clinical trials.

Different AT(N) profiles and clinical progression classified by two different N markers using total tau and neurofilament light chain in cerebrospinal fluid.

Background: The AT(N) classification was proposed for categorising individuals according to biomarkers. However, AT(N) profiles may vary depending on the markers chosen and the target population.

Methods: We stratified 177 individuals who participated in the Japanese Alzheimer's Disease Neuroimaging Initiative by AT(N) classification according to cerebrospinal fluid (CSF) biomarkers.

Treadmill Exercise During Cerebral Hypoperfusion Has Only Limited Effects on Cognitive Function in Middle-Aged Subcortical Ischemic Vascular Dementia Mice.

Clinical and basic research suggests that exercise is a safe behavioral intervention and is effective for improving cognitive function in cerebrovascular diseases, including subcortical ischemic vascular dementia (SIVD). However, most of the basic research uses young animals to assess the effects of exercise, although SIVD is an age-related disease. In this study, therefore, we used middle-aged mice to examine how treadmill exercise changes the cognitive function of SIVD mice.

Cohort-Specific Optimization of Models Predicting Preclinical Alzheimer's Disease, to Enhance Screening Performance in the Middle of Preclinical Alzheimer's Disease Clinical Studies.

Background: Models that can predict brain amyloid beta (Aβ) status more accurately have been desired to identify participants for clinical trials of preclinical Alzheimer's disease (AD). However, potential heterogeneity between different cohorts and the limited cohort size have been the reasons preventing the development of reliable models applicable to the Asian population, including Japan.

Objectives: We aim to propose a novel approach to predict preclinical AD while overcoming these constraints, by building models specifically optimized for ADNI or for J-ADNI, based on the larger samples from A4 study data.

Stress cardiomyopathy (Takotsubo syndrome) in patients who received adrenergic agonist drugs: A pharmacovigilance study using the Japanese Adverse Drug Event Report (JADER) database.

Introduction: Stress cardiomyopathy, or Takotsubo syndrome (TTS), is an acute and reversible syndrome developing in strong association with psychological or physiological stressors. While a surge in the circulating catecholamine level is suspected as one of its pathophysiologies, the contribution of treatment with sympathomimetic drugs to the development of TTS remains uncertain.

Methods: We conducted a disproportionality analysis using the Japanese Adverse Drug Event Report (JADER) database containing more than 500,000 patient cases recorded between April 2004 and March 2019, to detect TTS ('stress cardiomyopathy') as adverse event signals associated with adrenergic agonist drugs usage by calculating reporting odds ratio (ROR).

Facial nerve palsy following the administration of COVID-19 mRNA vaccines: analysis of a self-reporting database.

Objectives: Facial nerve palsy (or Bell's palsy) has occasionally been reported following the administration of coronavirus disease 2019 (COVID-19) mRNA vaccines (BNT162b2 and mRNA-1273). Our study investigated such cases using a large self-reporting database from the USA (Vaccine Adverse Event Reporting System [VAERS]).

Methods: A disproportionality analysis, adjusted for age and sex, was conducted for VAERS reports from individuals who were vaccinated at the age of 18 years or over, between January 2010 and April 2021.

Efficacy and Cost-effectiveness of Promotion Methods to Recruit Participants to an Online Screening Registry for Alzheimer Disease Prevention Trials: Observational Study.

Background: Web-based screening may be suitable for identifying individuals with presymptomatic latent diseases for recruitment to clinical studies, as such people do not often visit hospitals in the presymptomatic stage. The promotion of such online screening studies is critical to their success, although it remains uncertain how the effectiveness of such promotion can differ, depending on the different promotion methods, domains of interest, or countries of implementation.

Objective: The Japanese Trial-Ready Cohort (J-TRC) web study is our ongoing online screening registry to identify individuals with presymptomatic Alzheimer disease (AD), aimed at facilitating the clinical trials for AD prevention.

Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity.

Background: Google Trends (GT) is being used as an epidemiological tool to study coronavirus disease (COVID-19) by identifying keywords in search trends that are predictive for the COVID-19 epidemiological burden. However, many of the earlier GT-based studies include potential statistical fallacies by measuring the correlation between non-stationary time sequences without adjusting for multiple comparisons or the confounding of media coverage, leading to concerns about the increased risk of obtaining false-positive results. In this study, we aimed to apply statistically more favorable methods to validate the earlier GT-based COVID-19 study results.

Predicting amyloid risk by machine learning algorithms based on the A4 screen data: Application to the Japanese Trial-Ready Cohort study.

Background: Selecting cognitively normal elderly individuals with higher risk of brain amyloid deposition is critical to the success of prevention trials for Alzheimer's disease (AD).

Methods: Based on the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease study data, we built machine-learning models and applied them to our ongoing Japanese Trial-Ready Cohort (J-TRC) webstudy participants registered within the first 9 months ( = 3081) of launch to predict standard uptake value ratio (SUVr) of amyloid positron emission tomography.

Results: Age, family history, online Cognitive Function Instrument and CogState scores were important predictors.

Autocorrelation-based method to identify disordered rhythm in Parkinson's disease tasks: A novel approach applicable to multimodal devices.

Objective: We aim to propose a novel method of evaluating the degree of rhythmic irregularity during repetitive tasks in Parkinson's disease (PD) by using autocorrelation to extract serial perturbation in the periodicity of body part movements as recorded by objective devices.

Methods: We used publicly distributed sequential joint movement data recorded during a leg agility task or pronation-supination task. The sequences of body part trajectory were processed to extract their short-time autocorrelation (STACF) matrices; the sequences of single task conducted by participants were then divided into two clusters according to their similarity in terms of their STACF representation.

Attempt to Predict A/T/N-Based Alzheimer's Disease Cerebrospinal Fluid Biomarkers Using a Peripheral Blood DNA Methylation Clock.

Background: Although aging is the strongest risk factor for the development of Alzheimer's disease (AD), it remains uncertain if the blood DNA methylation clock, which reflects the effect of biological aging on DNA methylation (DNAme) status of blood cells, may be used as a surrogate biomarker for AD pathology in the central nervous system (CNS).

Objective: We aimed to develop a practical model to predict for A/T/N-based AD biomarkers as the prediction targets using the aging acceleration of blood cells.

Methods: We obtained data of North American ADNI study participants ( = 317) whose blood DNA methylation microarray (Illumina HumanMethylation EPIC Beadchips) and cerebrospinal fluid (CSF) AD biomarkers (A, t-tau, and p-tau) were recorded simultaneously.

Neuropsychiatric adverse events of chloroquine: a real-world pharmacovigilance study using the FDA Adverse Event Reporting System (FAERS) database.

In late March and early April 2020, the antimalarial drug, chloroquine, has been approved as an emergency treatment for the coronavirus disease 2019 (COVID-19) in the United States and in Europe. Although infrequent, neuropsychiatric symptoms have been reported in patients who received chloroquine for the treatment of malaria or autoimmune diseases. In this study, aiming to investigate these adverse events (AEs) using a large self-reporting database, we conducted a disproportionality analysis for the detection of neuropsychiatric AE signals associated with the use of chloroquine (or hydroxychloroquine), reported to FDA Adverse Event Reporting System (FAERS) database between the fourth quarter of 2012 and the fourth quarter of 2019.