Yun Jeong Hong

Background and ObjectivesMild cognitive impairment (MCI) is a high-risk stage for progression to dementia. The SUPERBRAIN-MEET trial previously demonstrated cognitive benefits of a multidomain life...

Antidementia medications are widely prescribed for Alzheimer’s disease (AD), but their long-term real-world effectiveness remains uncertain. This stu

Ha HJ, et al. Dement Neurocogn Disord. 2026 Oct;25(4):210-227. https://doi.org/10.12779/dnd.2026.25.4.210

Yoon B, et al. J Clin Neurol. 2026 Sep;22(5):560-572. https://doi.org/10.3988/jcn.2025.0659

Hong YJ, et al. J Clin Neurol. 2026 ;22:e49. https://doi.org/10.3988/jcn.2026.0011

Apolipoprotein E (APOE) ε4 is a well-known risk factor for Alzheimer’s disease (AD), with ε4 carriers exhibiting distinct clinical and biological characteristics compared to non-carriers. This study investigated whether the predictive performance of plasma biomarkers for amyloid positron emission tomography (PET) outcomes varies by APOE ε4 carrier status in individuals with subjective cognitive decline (SCD). We retrospectively analyzed baseline data from the Cohort Study to Identify Predictors for the Clinical Progression to Mild Cognitive Impairment or Dementia from Subjective Cognitive Decline. Plasma levels of the amyloid beta (Aβ) 42/40 ratio, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau (pTau) 181 were quantified using Single Molecule Array technology. We assessed predictive performance of plasma biomarkers for amyloid PET outcomes using receiver operating characteristic analysis and linear regression models. The study included 104 participants, with 20 APOE ε4 carriers and 84 non-carriers. Among ε4 carriers, NfL (area under the curve [AUC] = 0.909), GFAP (AUC = 0.904), and pTau181 (AUC = 0.828) showed the highest predictive accuracy. For non-carriers, the most predictive biomarkers were pTau181/Aβ42 (AUC = 0.872), Aβ42/Aβ40 (AUC = 0.794), and pTau181 (AUC = 0.761). Significant interactions between APOE and biomarkers were noted for GFAP (P = 0.005) and NfL (P = 0.010) in predicting amyloid plaque burden. Plasma biomarkers exhibit differential predictive performance for amyloid pathology based on APOE genotype, with GFAP and NfL showing interaction with APOE genotype. These findings suggest the importance of considering APOE genotype when interpreting plasma biomarker results for AD diagnosis in individuals with SCD. Clinical Research Information Service Identifier: KCT0003397

Lim EY, et al. J Korean Med Sci. 2026 Jan;41(3):e36. https://doi.org/10.3346/jkms.2026.41.e36

Background: Subjective cognitive decline (SCD) has been recognized as a preclinical stage of Alzheimer’s disease. However, the identification of early functional brain changes remains challenging. This study investigated the functional brain changes in SCD using longitudinal EEG and evaluate the feasibility of EEG features as scalable biomarkers for identifying amyloid burden and cognitive decline using an interpretable machine learning framework. Methods: We analyzed 120 individuals with SCD enrolled in a multicenter prospective cohort (the CoSCo study) at baseline and after a 2-year follow-up. Participants were classified as amyloid-positive (A + SCD) or amyloid-negative (A − SCD). Spectral power and graph theory-based network analyses were conducted. Also, we trained machine learning classifiers to distinguish between the groups and interpreted the predictions of classifiers using SHAP. Results: At both baseline and follow-up, the A + SCD group exhibited elevated low-frequency (delta and theta) activity and reduced alpha activity compared to the A − SCD group. The EEG-based classifiers distinguished A + SCD from A-SCD individuals with high performance, outperforming a classifier based on demographic data. The results of SHAP analysis confirmed the importance and relative contribution of selected EEG features. Conclusions: Longitudinal EEG, when combined with interpretable machine learning, can detect and track the functional alterations of brain related to amyloid pathology in preclinical AD. Our findings support the feasibility of EEG as a non-invasive, scalable, and sensitive biomarker for risk stratification, before overt cognitive impairment emerges. Trial registration: This study was registered at the Clinical Research Information Service (CRIS) (cris.nih.go.kr/cris; # KCT0003397, Registration Date: December 21, 2018).

Background: Anti‐dementia medications are prescribed in Alzheimer's disease (AD). However, there have been frew studies that clarified long‐term outcomes according to dose and drug compliance. We investigated whether clinical outcomes, represented by incidences of moderate to severe dementia, institutionalization, or death, are different according to doses/ drug compliance in AD patients using big data from the National Health Insurance Service (NHIS). Method: We examined a population‐based cohort obtained from the NHIS Senior Cohort (NHIS‐SC) data that comprises approximately half a million recipients of medical insurance in South Korea during 2009‐2022. The medication information (acetylcholiesterase inhibitors and memantine) was analyzed with respect to treatment dose and persistence across 12 years. From the initial cohort of 1,704,547 patients diagnosed with dementia between 2010 and 2016, 486,398 patients were included in the analysis. To compare clinical outcomes, patients were divided into two groups according to the following categories: 1) drug compliance during the first 3 years: those with a medication possession ratio (MPR) below 70% vs those with 70% or more, 2) anti‐dementia medication dose during the first 3 years: those with low‐dose medications vs those with optimal dose (standard dose according to clinical guideline), 3) optimal treatment during the first 3 years: those receiving optimal treatments (MPR ≥70% with optimal dose) vs those with sub‐optimal treatments (low‐dose or low (n = 66103) showed better long‐term clinical outcomes (fewer death/ institutionalization/ lower progression rates) than those in low drug compliance group ( n = 64332). Optimal dose group ( n = 66103) showed better long‐term clinical outcomes than those in low dose group ( n = 34771). Optimal treatment group ( n = 66103) showed better long‐term clinical outcomes than those in sub‐optimal treatment group ( n = 420295). Progression to moderate to severe dementia within 5 years and death were related with baseline age, gender, drug compliance and optimal anti‐dementia medications during the first 3 years from dementia diagnosis. Conclusion: Long‐term clinical outcomes in AD dementia patients are different according to optimal doses of anti‐dementia medications/ drug compliance during the first 3 years from dementia diagnosis.

Eye movement abnormalities can provide valuable diagnostic insights across various neurodegenerative disorders. This review summarizes the characteristic oculomotor findings in different neurodegenerative conditions, focusing on cognitive disorders and parkinsonian syndromes. The neural control of eye movements involves complex networks across multiple cortical regions, including the frontal eye field, supplementary eye field, and dorsolateral prefrontal cortex, functioning in coordination with subcortical structures. In Alzheimer disease, patients exhibit impaired fixation with large saccadic intrusions, prolonged saccadic latency, and increased antisaccade errors, which correlate with cognitive decline. Frontotemporal dementia shows variant-specific patterns of oculomotor dysfunction, with behavioral variant particularly affecting antisaccade performance while maintaining the ability to self-correct errors. In parkinsonian syndromes, distinctive eye movement abnormalities aid in differential diagnosis. Idiopathic Parkinson disease typically presents with hypometric saccades and increased saccadic intrusions during fixation, which correlate with disease severity. Progressive supranuclear palsy characteristically shows early vertical saccade abnormalities and frequent macro–square-wave jerks. Multiple system atrophy demonstrates various central nystagmus patterns and perverted head-shaking nystagmus, while corticobasal degeneration presents with saccadic apraxia and asymmetric oculomotor abnormalities. While eye movement abnormalities can be nonspecific and overlap between conditions, careful evaluation of oculomotor function can provide important diagnostic clues, particularly for differentiating parkinsonian syndromes. Understanding these distinct patterns of oculomotor abnormalities provides critical insights into the underlying pathophysiology and serves as a valuable tool for differential diagnosis of neurodegenerative disorders.