Browsing by Author "Kim, Hee Jin"
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Item Cerebral Amyloid Angiopathy and Downstream Alzheimer Disease Plasma Biomarkers(American Medical Association, 2025-05-01) Kang, Sung Hoon; Lee, Eun Hye; Kim, Young Ju; Jang, Hyemin; Shin, Daeun; Zetterberg, Henrik; Blennow, Kaj; Gonzalez-Ortiz, Fernando; Ashton, Nicholas J.; Yun, Jihwan; Kim, Hee Jin; Na, Duk L.; Kim, Jun Pyo; Seo, Sang Won; Radiology and Imaging Sciences, School of MedicineImportance: As amyloid-targeted therapies have become commercially available, the monitoring of cerebral amyloid angiopathy (CAA), which is an important risk factor for amyloid-related imaging abnormalities, has received increasing attention. However, comprehensive evidence on the association between Alzheimer disease (AD) plasma biomarkers and various CAA imaging markers is still lacking. Objective: To examine the association of CAA imaging markers with downstream AD plasma biomarkers in relation to amyloid-β (Aβ) uptake on positron emission tomography (PET) and whether their interplay is associated with cognitive changes. Design, setting, and participants: This registry-based cohort study in 25 hospitals across South Korea recruited participants aged 45 years or older who were registered between January 1, 2016, and December 31, 2023. Participants were categorized as having no cognitive impairment, mild cognitive impairment, or dementia of the Alzheimer type. Exposures: Cerebral amyloid angiopathy imaging markers assessed by magnetic resonance imaging, including cerebral microbleeds (CMBs), cortical superficial siderosis, white matter hyperintensities, lacunes, and enlarged perivascular spaces. Main outcomes and measures: Plasma phosphorylated tau-217 (p-tau217) was measured using a commercial assay. Glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) were measured using a single-molecule assay on a single platform. All participants underwent amyloid PET imaging. Associations of CAA and vascular imaging markers with downstream AD plasma biomarkers were investigated using linear regression. Results: A total of 1708 participants were included (mean [SD] age, 71.2 [8.4] years; 1044 female [61.1%]). The mean (SD) follow-up period was 4.3 (3.1) years. Lobar CMB counts and the presence of CAA were associated with downstream AD plasma biomarkers, including p-tau217 (β = 0.12 [95% CI, 0.05-0.18] and 0.29 [95% CI, 0.12-0.47], respectively), GFAP (β = 0.07 [95% CI, 0.03-0.12] and 0.20 [95% CI, 0.09-0.31], respectively), and NfL (β = 0.07 [95% CI, 0.03-0.11] and 0.16 [95% CI, 0.06-0.25], respectively) with and without the mediation of Aβ uptake on PET (indirect effect: lobar CMBs-p-tau217, 59.8% [β = 0.07 (95% CI, 0.03-0.11)]; lobar CMBs-GFAP, 49.3% [β = 0.04 (95% CI, 0.01-0.06)]; lobar CMBs-NfL, 20.9% [β = 0.01 (95% CI, 0.01-0.03)]; CAA-p-tau217, 50.9% [β = 0.15 (95% CI, 0.06-0.24)]; CAA-GFAP, 39.2% [β = 0.08 (95% CI, 0.03-0.13)]; CAA-NfL, 19.2% [β = 0.03 (95% CI, 0.01-0.05)]). Amyloid-β uptake fully mediated the associations between cortical superficial siderosis and downstream AD plasma markers. In contrast, hypertensive arteriosclerotic vascular imaging markers, including lacunes, deep CMBs, and enlarged perivascular spaces in basal ganglia, were associated with only NfL levels (β = 0.07 [95% CI, 0.01-0.13], 0.20 [95% CI, 0.08-0.32], and 0.14 [95% CI, 0.06-0.23], respectively), regardless of Aβ uptake on PET. Finally, there were interactive associations of lobar CMBs in conjunction with p-tau217 levels (β = -0.56 [95% CI, -0.79 to -0.34]) and GFAP levels (β = -0.44 [95% CI, -0.70 to -0.17]) with annual Mini-Mental State Examination changes. Conclusions and relevance: In this cohort study of participants with no cognitive impairment, mild cognitive impairment, or dementia of the Alzheimer type, a novel association was found among CAA imaging markers, downstream AD plasma biomarkers, and cognitive declines in relation to brain Aβ burdens. The findings emphasize the importance of understanding the clinical effects of amyloid-related imaging abnormality-like CAA imaging markers in light of upcoming amyloid-targeted therapies.Item Classification and prediction of cognitive trajectories of cognitively unimpaired individuals(Frontiers Media, 2023-03-13) Kim, Young Ju; Kim, Si Eun; Hahn, Alice; Jang, Hyemin; Kim, Jun Pyo; Kim, Hee Jin; Na, Duk L.; Chin, Juhee; Seo, Sang Won; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineObjectives: Efforts to prevent Alzheimer's disease (AD) would benefit from identifying cognitively unimpaired (CU) individuals who are liable to progress to cognitive impairment. Therefore, we aimed to develop a model to predict cognitive decline among CU individuals in two independent cohorts. Methods: A total of 407 CU individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and 285 CU individuals from the Samsung Medical Center (SMC) were recruited in this study. We assessed cognitive outcomes by using neuropsychological composite scores in the ADNI and SMC cohorts. We performed latent growth mixture modeling and developed the predictive model. Results: Growth mixture modeling identified 13.8 and 13.0% of CU individuals in the ADNI and SMC cohorts, respectively, as the "declining group." In the ADNI cohort, multivariable logistic regression modeling showed that increased amyloid-β (Aβ) uptake (β [SE]: 4.852 [0.862], p < 0.001), low baseline cognitive composite scores (β [SE]: -0.274 [0.070], p < 0.001), and reduced hippocampal volume (β [SE]: -0.952 [0.302], p = 0.002) were predictive of cognitive decline. In the SMC cohort, increased Aβ uptake (β [SE]: 2.007 [0.549], p < 0.001) and low baseline cognitive composite scores (β [SE]: -4.464 [0.758], p < 0.001) predicted cognitive decline. Finally, predictive models of cognitive decline showed good to excellent discrimination and calibration capabilities (C-statistic = 0.85 for the ADNI model and 0.94 for the SMC model). Conclusion: Our study provides novel insights into the cognitive trajectories of CU individuals. Furthermore, the predictive model can facilitate the classification of CU individuals in future primary prevention trials.Item Clinical outcomes of increased focal amyloid uptake in individuals with subthreshold global amyloid levels(Frontiers Media, 2023-03-02) Kim, Jaeho; Choe, Yeong Sim; Park, Yuhyun; Kim, Yeshin; Kim, Jun Pyo; Jang, Hyemin; Kim, Hee Jin; Na, Duk L.; Cho, Soo-Jin; Moon, Seung Hwan; Seo, Sang Won; Radiology and Imaging Sciences, School of MedicineBackground: Although the standardized uptake value ratio (SUVR) method is objective and simple, cut-off optimization using global SUVR values may not reflect focal increased uptake in the cerebrum. The present study investigated clinical and neuroimaging characteristics according to focally increased β-amyloid (Aβ) uptake and global Aβ status. Methods: We recruited 968 participants with cognitive continuum. All participants underwent neuropsychological tests and 498 18F-florbetaben (FBB) amyloid positron emission tomography (PET) and 470 18F-flutemetamol (FMM) PET. Each PET scan was assessed in 10 regions (left and right frontal, lateral temporal, parietal, cingulate, and striatum) with focal-quantitative SUVR-based cutoff values for each region by using an iterative outlier approach. Results: A total of 62 (6.4%) subjects showed increased focal Aβ uptake with subthreshold global Aβ status [global (-) and focal (+) Aβ group, G(-)F(+) group]. The G(-)F(+) group showed worse performance in memory impairment (p < 0.001), global cognition (p = 0.009), greater hippocampal atrophy (p = 0.045), compared to those in the G(-)F(-). Participants with widespread Aβ involvement in the whole region [G(+)] showed worse neuropsychological (p < 0.001) and neuroimaging features (p < 0.001) than those with focal Aβ involvement G(-)F(+). Conclusion: Our findings suggest that individuals show distinctive clinical outcomes according to focally increased Aβ uptake and global Aβ status. Thus, researchers and clinicians should pay more attention to focal increased Aβ uptake in addition to global Aβ status.Item Contribution of clinical information to the predictive performance of plasma β-amyloid levels for amyloid positron emission tomography positivity(Frontiers Media, 2023-03-14) Chun, Min Young; Jang, Hyemin; Kim, Hee Jin; Kim, Jun Pyo; Gallacher, John; Allué, José Antonio; Sarasa, Leticia; Castillo, Sergio; Pascual-Lucas, María; Na, Duk L.; Seo, Sang Won; DPUK; Radiology and Imaging Sciences, School of MedicineBackground: Early detection of β-amyloid (Aβ) accumulation, a major biomarker for Alzheimer's disease (AD), has become important. As fluid biomarkers, the accuracy of cerebrospinal fluid (CSF) Aβ for predicting Aβ deposition on positron emission tomography (PET) has been extensively studied, and the development of plasma Aβ is beginning to receive increased attention recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of plasma Aβ and CSF Aβ levels for Aβ PET positivity. Methods: We recruited 488 participants who underwent both plasma Aβ and Aβ PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) Aβ and Aβ PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest-MS, an antibody-free liquid chromatography-differential mobility spectrometry-triple quadrupole mass spectrometry method and INNOTEST enzyme-linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma Aβ and CSF Aβ, respectively, logistic regression and receiver operating characteristic analyses were performed. Results: When predicting Aβ PET status, both plasma Aβ42/40 ratio and CSF Aβ42 showed high accuracy (plasma Aβ area under the curve (AUC) 0.814; CSF Aβ AUC 0.848). In the plasma Aβ models, the AUC values were higher than plasma Aβ alone model, when the models were combined with either cognitive stage (p < 0.001) or APOE genotype (p = 0.011). On the other hand, there was no difference between the CSF Aβ models, when these variables were added. Conclusion: Plasma Aβ might be a useful predictor of Aβ deposition on PET status as much as CSF Aβ, particularly when considered with clinical information such as APOE genotype and cognitive stage.Item Differential effects of risk factors on the cognitive trajectory of early- and late-onset Alzheimer’s disease(BMC, 2021-06-14) Kim, Jaeho; Woo, Sook-Young; Kim, Seonwoo; Jang, Hyemin; Kim, Junpyo; Kim, Jisun; Kang, Sung Hoon; Na, Duk L.; Chin, Juhee; Apostolova, Liana G.; Seo, Sang Won; Kim, Hee Jin; Neurology, School of MedicineBackground: Although few studies have shown that risk factors for Alzheimer's disease (AD) are associated with cognitive decline in AD, not much is known whether the impact of risk factors differs between early-onset AD (EOAD, symptom onset < 65 years of age) versus late-onset AD (LOAD). Therefore, we evaluated whether the impact of Alzheimer's disease (AD) risk factors on cognitive trajectories differ in EOAD and LOAD. Methods: We followed-up 193 EOAD and 476 LOAD patients without known autosomal dominant AD mutation for 32.3 ± 23.2 months. Mixed-effects model analyses were performed to evaluate the effects of APOE ε4, low education, hypertension, diabetes, dyslipidemia, and obesity on cognitive trajectories. Results: APOE ε4 carriers showed slower cognitive decline in general cognitive function, language, and memory domains than APOE ε4 carriers in EOAD but not in LOAD. Although patients with low education showed slower cognitive decline than patients with high education in both EOAD and LOAD, the effect was stronger in EOAD, specifically in frontal-executive function. Patients with hypertension showed faster cognitive decline than did patients without hypertension in frontal-executive and general cognitive function in LOAD but not in EOAD. Patients with obesity showed slower decline in general cognitive function than non-obese patients in EOAD but not in LOAD. Conclusions: Known risk factors for AD were associated with slower cognitive decline in EOAD but rapid cognitive decline in LOAD.Item Distinctive Temporal Trajectories of Alzheimer's Disease Biomarkers According to Sex and APOE Genotype: Importance of Striatal Amyloid(Frontiers Media, 2022-02-07) Kim, Jun Pyo; Chun, Min Young; Kim, Soo-Jon; Jang, Hyemin; Kim, Hee Jin; Jeong, Jee Hyang; Na, Duk L.; Seo, Sang Won; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicinePurpose: Previously, sex and apolipoprotein E (APOE) genotype had distinct effects on the cognitive trajectory across the Alzheimer's disease (AD) continuum. We therefore aimed to investigate whether these trajectory curves including β-amyloid (Aβ) accumulation in the cortex and striatum, and tau accumulation would differ according to sex and APOE genotype. Methods: We obtained 534 subjects for 18F-florbetapir (AV45) PET analysis and 163 subjects for 18F-flortaucipir (AV1451) PET analysis from the Alzheimer's Disease Neuroimaging Initiative database. For cortical Aβ, striatal Aβ, and tau SUVR, we fitted penalized splines to model the slopes of SUVR value as a non-linear function of baseline SUVR value. By integrating the fitted splines, we obtained the predicted SUVR curves as a function of time. Results: The time from initial SUVR to the cutoff values were 14.9 years for cortical Aβ, 18.2 years for striatal Aβ, and 22.7 years for tau. Although there was no difference in cortical Aβ accumulation rate between women and men, striatal Aβ accumulation was found to be faster in women than in men, and this temporal difference according to sex was more pronounced in tau accumulation. However, APOE ε4 carriers showed faster progression than non-carriers regardless of kinds of AD biomarkers' trajectories. Conclusion: Our temporal trajectory models illustrate that there is a distinct progression pattern of AD biomarkers depending on sex and APOE genotype. In this regard, our models will be able to contribute to designing personalized treatment and prevention strategies for AD in clinical practice.Item Effect of genetic and vascular risk factors on rates of cognitive decline in early-onset and late-onset Alzheimer’s disease(Sage, 2025) Li, Yunyi; Sanjay, Apoorva Bharthur; Manchella, Mohit; Mishra, Aryan; Logan, Paige E.; Kim, Hee Jin; Risacher, Shannon L.; Gao, Sujuan; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthBackground: Although previous studies have shown that cognitive decline in Alzheimer's disease (AD) is associated with various risk factors, they primarily focused on late-onset AD (LOAD). Objective: We aim to evaluate the differential impact of risk factors on the cognitive decline between early-onset AD (EOAD, onset < 65 years) and LOAD (onset ≥ 65 years) and explore the longitudinal effect of Apolipoprotein E allele 4 (APOE ε4) on cortical atrophy in both cohorts. Methods: Using data from 212 EOAD and 1101 LOAD participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI), we conducted multivariable mixed-effect models to evaluate the impact of APOE ε4, education, hypertension, diabetes, dyslipidemia, and body mass index on cognitive performance. Preprocessed MRI data were utilized for longitudinal parametric mapping. Results: APOE ε4 carriers in both groups showed significantly accelerated declines in language, verbal memory, executive function, and general cognition. By controlling other significant risk factors, APOE ε4 carriers showed faster declines in language and verbal memory in both groups. Females exhibited accelerated declines in Language and verbal memory in the EOAD and LOAD cohorts respectively. LOAD individuals with hypertension showed faster declines while overweight and obese participants displayed slower declines in both cohorts across all domains except visuospatial. Notably, APOE ε4 status was associated with longitudinal cortical atrophy in the LOAD cohort but not in the EOAD cohort. Conclusions: Known risk factors for AD were associated with cognitive decline in both EOAD and LOAD cohorts.Item Effects of BDNF and COMT variants on cognitive decline in Early‐Onset Alzheimer’s Disease(Wiley, 2025-01-03) Hammers, Dustin B.; Foroud, Tatiana M.; Kim, Hee Jin; Musema, Jane; Dage, Jeffrey L.; Eloyan, Ani; Carrillo, Maria C.; Dickerson, Bradford C.; Rabinovici, Gil D.; Apostolova, Liana G.; Nudelman, Kelly N.; LEADS Consortium; Medical and Molecular Genetics, School of MedicineBackground: Early‐Onset Alzheimer’s Disease (EOAD) is a rare condition that affects only 5% of patients with Alzheimer’s Disease (AD). At present, only basic information is known about the impact of AD risk variants on EOAD, and the effects of more subtle genetic contributions to cognitive decline have yet to be investigated. Genetic variants for brain derived neurotrophic factor (BDNF) and catechol‐O‐methyltransferase (COMT) have both been implicated in cognitive change (Fiocco et al., 2010; Ferrer et al., 2019), consequently the aim of the current study was to examine the role of these genetic variants on cognitive decline in EOAD. Method: Data from 88 amyloid‐positive EOAD participants enrolled in the Longitudinal Early Onset Alzheimer’s Disease Study (LEADS; aged 40‐64) were analyzed. Exploratory multivariate analyses of covariance (MANCOVA) were conducted to investigate differences in 12‐month cognitive decline as a function of BDNF rs6265 (p.V66M) and COMT rs4680 (p.V158M) variants using dominant genetic models (Val/Val versus Val/Met or Met/Met). Cox Regression analyses were also conducted to consider the effect of genetic variants on age of onset. Result: See Table 1 for demographic characteristics of our sample. MANCOVA, controlling for age, education, sex, and race/ethnicity, showed significant effects for BDNF p.V66M on domains of Memory (p<0.001) and Executive Functioning (p = 0.04; Table 2). Specifically, greater 12‐month cognitive decline was observed for the CRAFT Immediate and Delayed Story Memory, with worse performance associated with BDNF minor alleles (ps. = 0.007 to 0.02). Conversely, worse decline was observed for the reference group for RAVLT Immediate Memory (p<0.006) and Digit Span Backwards (p<0.02). No significant effects were evident for domains of Language, Speed/Attention, or Visuospatial skills (ps = 0.34‐0.97), nor for any analyses of COMT carrier status (ps = 0.26‐0.87). Cox Regression analyses, controlling for race and ethnicity, were not significant for BDNF or COMT carrier status (ps = 0.59‐0.64; Figure 1). Conclusion: Results suggest subtle effects of BDNF p.V66M carrier status on memory decline in EOAD participants, which was not observed for disease progression/age‐of‐onset. No effects for COMT p.V158M carrier status were observed. Future investigation will replicate these effects in larger samples, permitting stratification of additional covariates including APOE genotype.Item The Effects of Longitudinal White Matter Hyperintensity Change on Cognitive Decline and Cortical Thinning over Three Years(MDPI, 2020-08-17) Kim, Seung Joo; Lee, Dong Kyun; Jang, Young Kyoung; Jang, Hyemin; Kim, Si Eun; Cho, Soo Hyun; Kim, Jun Pyo; Jung, Young Hee; Kim, Eun-Joo; Na, Duk L.; Lee, Jong-Min; Seo, Sang Won; Kim, Hee Jin; Radiology and Imaging Sciences, School of MedicineWhite matter hyperintensity (WMH) has been recognised as a surrogate marker of small vessel disease and is associated with cognitive impairment. We investigated the dynamic change in WMH in patients with severe WMH at baseline, and the effects of longitudinal change of WMH volume on cognitive decline and cortical thinning. Eighty-seven patients with subcortical vascular mild cognitive impairment were prospectively recruited from a single referral centre. All of the patients were followed up with annual neuropsychological tests and 3T brain magnetic resonance imaging. The WMH volume was quantified using an automated method and the cortical thickness was measured using surface-based methods. Participants were classified into WMH progression and WMH regression groups based on the delta WMH volume between the baseline and the last follow-up. To investigate the effects of longitudinal change in WMH volume on cognitive decline and cortical thinning, a linear mixed effects model was used. Seventy patients showed WMH progression and 17 showed WMH regression over a three-year period. The WMH progression group showed more rapid cortical thinning in widespread regions compared with the WMH regression group. However, the rate of cognitive decline in language, visuospatial function, memory and executive function, and general cognitive function was not different between the two groups. The results of this study indicated that WMH volume changes are dynamic and WMH progression is associated with more rapid cortical thinning.Item Effects of risk factors on the development and mortality of early- and late-onset dementia: an 11-year longitudinal nationwide population-based cohort study in South Korea(Springer Nature, 2024-04-25) Chun, Min Young; Chae, Wonjeong; Seo, Sang Won; Jang, Hyemin; Yun, Jihwan; Na, Duk L.; Kang, Dongwoo; Lee, Jungkuk; Hammers, Dustin B.; Apostolova, Liana G.; Jang, Sung-In; Kim, Hee Jin; Neurology, School of MedicineBackground: Early-onset dementia (EOD, onset age < 65) and late-onset dementia (LOD, onset age ≥ 65) exhibit distinct features. Understanding the risk factors for dementia development and mortality in EOD and LOD respectively is crucial for personalized care. While risk factors are known for LOD development and mortality, their impact on EOD remains unclear. We aimed to investigate how hypertension, diabetes mellitus, hyperlipidemia, atrial fibrillation, and osteoporosis influence the development and mortality of EOD and LOD, respectively. Methods: Using the Korean National Health Insurance Service (NHIS) database, we collected 546,709 dementia-free individuals and followed up for 11 years. In the two study groups, the Younger group (< 65 years old) and the Older group (≥ 65 years old), we applied Cox proportional hazard models to assess risk factors for development of EOD and LOD, respectively. Then, we assessed risk factors for mortality among EOD and LOD. Results: Diabetes mellitus and osteoporosis increased the risk of EOD and LOD development. Hypertension increased the risk of EOD, while atrial fibrillation increased the risk of LOD. Conversely, hyperlipidemia exhibited a protective effect against LOD development. Additionally, diabetes mellitus increased mortality in EOD and LOD. Hypertension and atrial fibrillation increased mortality in LOD, while hyperlipidemia decreased mortality in EOD and LOD. Conclusions: Risk factors influencing dementia development and mortality differed in EOD and LOD. Targeted public health interventions addressing age-related risk factors may reduce dementia incidence and mortality.