Browsing by Author "Seo, Sang Won"
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Item BMI1 is associated with CS8F amyloid-β and rates of cognitive decline in Alzheimer's disease(Springer Nature, 2021-10-05) Kim, Jun Pyo; Kim, Bo‑Hyun; Bice, Paula J.; Seo, Sang Won; Bennett, David A.; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineBackground: Accumulating evidence suggests that BMI1 confers protective effects against Alzheimer's disease (AD). However, the mechanism remains elusive. Based on recent pathophysiological evidence, we sought for the first time to identify genetic variants in BMI1 as associated with AD biomarkers, including amyloid-β. Methods: We used genetic, longitudinal cognition, and cerebrospinal fluid (CSF) biomarker data from participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (N = 1565). First, we performed a gene-based association analysis of common single nucleotide polymorphisms (SNPs) (minor allele frequency (MAF) > 5%) located within ± 20 kb of the gene boundary of BMI1, an optimal width for including potential regulatory SNPs in the 5' and 3' untranslated regions (UTR) of BMI1, with CSF Aβ1-42 levels. Second, we performed cross-sectional and longitudinal association analyses of SNPs in BMI1 with cognitive performance using linear and mixed-effects models. We replicated association of SNPs in BMI1 with cognitive performance in an independent cohort (N=1084), Religious Orders Study and the Rush Memory and Aging Project (ROS/MAP). Results: Gene-based genetic association analysis showed that BMI1 was significantly associated with CSF Aβ1-42 levels after adjusting for multiple testing using permutation (permutation-corrected p value=0.005). rs17415557 in BMI1 showed the most significant association with CSF Aβ1-42 levels. Participants with minor alleles of rs17415557 have increased CSF Aβ1-42 levels compared to those with no minor alleles. Further analysis identified and replicated the minor allele of rs17415557 as being significantly associated with slower cognitive decline rates in AD. Conclusions: Our findings provide fundamental evidence that BMI1 rs17415557 may serve as a protective mechanism related to AD pathogenesis, which supports the results of previous studies linking BMI1 to protection against AD.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 Clinicopathological correlations in behavioural variant frontotemporal dementia(Oxford University Press, 2017-12-01) Perry, David C.; Brown, Jesse A.; Possin, Katherine L.; Datta, Samir; Trujillo, Andrew; Radke, Anneliese; Karydas, Anna; Kornak, John; Sias, Ana C.; Rabinovici, Gil D.; Gorno-Tempini, Maria Luisa; Boxer, Adam L.; May, Mary De; Rankin, Katherine P.; Sturm, Virginia E.; Lee, Suzee E.; Matthews, Brandy R.; Kao, Aimee W.; Vossel, Keith A.; Tartaglia, Maria Carmela; Miller, Zachary A.; Seo, Sang Won; Sidhu, Manu; Gaus, Stephanie E.; Nana, Alissa L.; Vargas, Jose Norberto S.; Hwang, Ji-Hye L.; Ossenkoppele, Rik; Brown, Alainna B.; Huang, Eric J.; Coppola, Giovanni; Rosen, Howard J.; Geschwind, Daniel; Trojanowski, John Q.; Grinberg, Lea T.; Kramer, Joel H.; Miller, Bruce L.; Seely, William W.; Neurology, School of MedicineAccurately predicting the underlying neuropathological diagnosis in patients with behavioural variant frontotemporal dementia (bvFTD) poses a daunting challenge for clinicians but will be critical for the success of disease-modifying therapies. We sought to improve pathological prediction by exploring clinicopathological correlations in a large bvFTD cohort. Among 438 patients in whom bvFTD was either the top or an alternative possible clinical diagnosis, 117 had available autopsy data, including 98 with a primary pathological diagnosis of frontotemporal lobar degeneration (FTLD), 15 with Alzheimer's disease, and four with amyotrophic lateral sclerosis who lacked neurodegenerative disease-related pathology outside of the motor system. Patients with FTLD were distributed between FTLD-tau (34 patients: 10 corticobasal degeneration, nine progressive supranuclear palsy, eight Pick's disease, three frontotemporal dementia with parkinsonism associated with chromosome 17, three unclassifiable tauopathy, and one argyrophilic grain disease); FTLD-TDP (55 patients: nine type A including one with motor neuron disease, 27 type B including 21 with motor neuron disease, eight type C with right temporal lobe presentations, and 11 unclassifiable including eight with motor neuron disease), FTLD-FUS (eight patients), and one patient with FTLD-ubiquitin proteasome system positive inclusions (FTLD-UPS) that stained negatively for tau, TDP-43, and FUS. Alzheimer's disease was uncommon (6%) among patients whose only top diagnosis during follow-up was bvFTD. Seventy-nine per cent of FTLD-tau, 86% of FTLD-TDP, and 88% of FTLD-FUS met at least 'possible' bvFTD diagnostic criteria at first presentation. The frequency of the six core bvFTD diagnostic features was similar in FTLD-tau and FTLD-TDP, suggesting that these features alone cannot be used to separate patients by major molecular class. Voxel-based morphometry revealed that nearly all pathological subgroups and even individual patients share atrophy in anterior cingulate, frontoinsula, striatum, and amygdala, indicating that degeneration of these regions is intimately linked to the behavioural syndrome produced by these diverse aetiologies. In addition to these unifying features, symptom profiles also differed among pathological subtypes, suggesting distinct anatomical vulnerabilities and informing a clinician's prediction of pathological diagnosis. Data-driven classification into one of the 10 most common pathological diagnoses was most accurate (up to 60.2%) when using a combination of known predictive factors (genetic mutations, motor features, or striking atrophy patterns) and the results of a discriminant function analysis that incorporated clinical, neuroimaging, and neuropsychological data.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 Correction to: BMI1 is associated with CSF amyloid-β and rates of cognitive decline in Alzheimer’s disease(BMC, 2022-01-20) Kim, Jun Pyo; Kim, Bo‑Hyun; Bice, Paula J.; Seo, Sang Won; Bennett, David A.; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineErratum for: BMI1 is associated with CS8F amyloid-β and rates of cognitive decline in Alzheimer's disease. Kim JP, Kim BH, Bice PJ, Seo SW, Bennett DA, Saykin AJ, Nho K; Alzheimer’s Disease Neuroimaging Initiative. Alzheimers Res Ther. 2021 Oct 5;13(1):164. doi: 10.1186/s13195-021-00906-4. PMID: 34610832Item 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 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.