Search

Your search keyword '"Kim, Jun Pyo"' showing total 379 results
Start Over Author "Kim, Jun Pyo"
379 results on '"Kim, Jun Pyo"'

1. CYP1B1-RMDN2 Alzheimer’s disease endophenotype locus identified for cerebral tau PET

Author

Nho, Kwangsik, Risacher, Shannon L., Apostolova, Liana G., Bice, Paula J., Brosch, Jared R., Deardorff, Rachael, Faber, Kelley, Farlow, Martin R., Foroud, Tatiana, Gao, Sujuan, Rosewood, Thea, Kim, Jun Pyo, Nudelman, Kelly, Yu, Meichen, Aisen, Paul, Sperling, Reisa, Hooli, Basavaraj, Shcherbinin, Sergey, Svaldi, Diana, Jack, Jr., Clifford R., Jagust, William J., Landau, Susan, Vasanthakumar, Aparna, Waring, Jeffrey F., Doré, Vincent, Laws, Simon M., Masters, Colin L., Porter, Tenielle, Rowe, Christopher C., Villemagne, Victor L., Dumitrescu, Logan, Hohman, Timothy J., Libby, Julia B., Mormino, Elizabeth, Buckley, Rachel F., Johnson, Keith, Yang, Hyun-Sik, Petersen, Ronald C., Ramanan, Vijay K., Ertekin-Taner, Nilüfer, Vemuri, Prashanthi, Cohen, Ann D., Fan, Kang-Hsien, Kamboh, M. Ilyas, Lopez, Oscar L., Bennett, David A., Ali, Muhammad, Benzinger, Tammie, Cruchaga, Carlos, Hobbs, Diana, De Jager, Philip L., Fujita, Masashi, Jadhav, Vaishnavi, Lamb, Bruce T., Tsai, Andy P., Castanho, Isabel, Mill, Jonathan, Weiner, Michael W., and Saykin, Andrew J.

Published
2024
Full Text
View/download PDF

7. Genome-wide association study of brain biochemical phenotypes reveals distinct genetic architecture of Alzheimer’s disease related proteins

Author

Oatman, Stephanie R., Reddy, Joseph S., Quicksall, Zachary, Carrasquillo, Minerva M., Wang, Xue, Liu, Chia-Chen, Yamazaki, Yu, Nguyen, Thuy T., Malphrus, Kimberly, Heckman, Michael, Biswas, Kristi, Nho, Kwangsik, Baker, Matthew, Martens, Yuka A., Zhao, Na, Kim, Jun Pyo, Risacher, Shannon L., Rademakers, Rosa, Saykin, Andrew J., DeTure, Michael, Murray, Melissa E., Kanekiyo, Takahisa, Dickson, Dennis W., Bu, Guojun, Allen, Mariet, and Ertekin-Taner, Nilüfer

Published
2023
Full Text
View/download PDF

10. Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia

Author

Cho, Soo Hyun, Woo, Sookyoung, Kim, Changsoo, Kim, Hee Jin, Jang, Hyemin, Kim, Byeong C, Kim, Si Eun, Kim, Seung Joo, Kim, Jun Pyo, Jung, Young Hee, Lockhart, Samuel, Ossenkoppele, Rik, Landau, Susan, Na, Duk L, Weiner, Michael, Kim, Seonwoo, and Seo, Sang Won

Subjects
Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Neurosciences, Acquired Cognitive Impairment, Brain Disorders, Neurodegenerative, Dementia, Alzheimer's Disease, Neurological, Aged, Alzheimer Disease, Apolipoprotein E4, Cognitive Dysfunction, Cohort Studies, Disease Progression, Female, Heterozygote, Humans, Male, Neuropsychological Tests
Abstract

To characterize the course of Alzheimer's disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p

Published
2021

11. Association between APOE ε2 and Aβ burden in patients with Alzheimer- and vascular-type cognitive impairment.

Author

Lee, Jin San, Lee, Hyejoo, Park, Seongbeom, Choe, Yeongsim, Park, Yu Hyun, Cheon, Bo Kyoung, Hahn, Alice, Ossenkoppele, Rik, Kim, Hee Jin, Kim, Seonwoo, Yoo, Heejin, Jang, Hyemin, Cho, Soo Hyun, Kim, Seung Joo, Kim, Jun Pyo, Jung, Young Hee, Park, Key-Chung, DeCarli, Charles, Weiner, Michael W, Na, Duk L, and Seo, Sang Won

Subjects
Neurodegenerative, Brain Disorders, Genetics, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Acquired Cognitive Impairment, Aging, Neurosciences, Dementia, Alzheimer's Disease, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Aged, Aged, 80 and over, Alzheimer Disease, Amyloid beta-Peptides, Apolipoprotein E2, Body Burden, Cognitive Dysfunction, Cross-Sectional Studies, Dementia, Vascular, Female, Genetic Predisposition to Disease, Genotype, Heterozygote, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Positron-Emission Tomography, Prevalence, Clinical Sciences, Cognitive Sciences, Neurology & Neurosurgery
Abstract

ObjectiveTo investigate the association between APOE genotype and β-amyloid (Aβ) burden, as measured by PET in patients with subcortical vascular cognitive impairment (SVCI) and those with Alzheimer disease-related cognitive impairment (ADCI).MethodsThis was a cross-sectional study of 310 patients with SVCI and 999 with ADCI. To evaluate the effects of APOE genotype or diagnostic group on Aβ positivity, we performed multivariate logistic regression analyses. Further distinctive underlying features of latent subgroups were examined by employing a latent class cluster analysis approach.ResultsIn comparison with ε3 homozygotes, in the ADCI group, ε2 carriers showed a lower frequency of Aβ positivity (odds ratio [OR] 0.43, 95% confidence interval [CI] 0.23-0.79), while in the SVCI group, ε2 carriers showed a higher frequency of Aβ positivity (OR 2.26, 95% CI 1.02-5.01). In particular, we observed an interaction effect of ε2 carrier status and diagnostic group on Aβ positivity (OR 5.12, 95% CI 1.93-13.56), in that relative to ε3 homozygotes, there were more Aβ-positive ε2 carriers in the SVCI group than in the ADCI group. We also identified latent subgroups of Aβ-positive APOE ε2 carriers with SVCI and Aβ-positive APOE ε4 carriers with ADCI.ConclusionsOur findings suggest that APOE ε2 is distinctly associated with Aβ deposition in patients with SVCI and those with ADCI. Our findings further suggest that there is a distinctive subgroup of Aβ-positive APOE ε2 carriers with SVCI among patients with cognitive impairment.

Published
2020

16. Association between focal amyloid deposition and cognitive impairment in individuals below the amyloid threshold.

Author

Ham, Hongki, Kim, Byeong C., Lee, Eun Hye, Shin, Daeun, Jang, Hyemin, Kang, Sung Hoon, Yun, Jihwan, Kim, Hee Jin, Na, Duk L., Kim, Jun Pyo, Seo, Sang Won, and Cho, Soo Hyun

Abstract

Purpose: This study aimed to investigate the characteristics of individuals with amyloid levels below the threshold. To achieve this, we differentiated between two groups: those with global amyloid negativity but focal deposition [G(–)F(+)] and those without focal deposition [G(–)F(–)]. Materials and methods: A total of 2,677 participants were diagnosed with cognitive unimpairment (CU) or mild cognitive impairment (MCI). MRI-based regional centiloid (CL) values were used to establish threshold values for each brain region. After applying a cutoff of 20 rdcCL to identify amyloid positivity, participants who were globally amyloid-negative were grouped into three categories: those who showed focal amyloid uptake [G(–)F(+)], individuals without focal amyloid deposition but with relatively high CL(HC) levels comparable to those in the focal uptake group [G(–)F(–) HC)], and those with relatively low CL(LC) levels [G(–)F(–) LC]. We compared the neuropsychological test results and brain structural changes between these groups using ANCOVA. Results: The G(–)F(+) group demonstrated a lower cortical thickness (P < 0.001) than the G(–)F(–) HC group. In neuropsychological tests, the G(–)F(+) group exhibited lower the Seoul Verbal Learning Test delayed recall (SVLT-DR) and Mini Mental State Examination (MMSE), and showed progressed clinical status in the clinical dementia rating–sum of boxes (CDR-SOB) compared to the G(–)F(–) HC group (P < 0.001). The subsequent sensitivity analyses confirmed the persistence of these findings. Conclusions: Individuals with focal amyloid deposition [G(–)F(+)] exhibited higher rates of cognitive impairment compared to patients with similar levels of amyloid, underscoring the importance of monitoring the progression of focal uptake, even when it remains below the amyloid threshold. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

19. Difference in trajectories according to early amyloid accumulation in cognitively unimpaired elderly.

Author

Kim, Young Ju, Yun, Jihwan, Seo, Sang Won, Kim, Jun Pyo, Jang, Hyemin, Kim, Hee Jin, Na, Duk L., Woo, Sookyoung, and Chun, Min Young

Abstract

Background and purpose: Amyloid β (Aβ), a major biomarker of Alzheimer's disease, leads to tau accumulation, neurodegeneration and cognitive decline. Modelling the trajectory of Aβ accumulation in cognitively unimpaired (CU) individuals is crucial, as treatments targeting Aβ are anticipated. The evolution of Aβ levels was investigated to determine whether it could lead to classification into different groups by studying longitudinal Aβ changes in older CU individuals, and differences between the groups were compared. Methods: A total of 297 CU participants were included from the Alzheimer's Disease Neuroimaging Initiative database, and these participants underwent apolipoprotein E (APOE) genotyping, neuropsychological testing, brain magnetic resonance imaging, and an average of 3.03 follow‐up 18F‐florbetapir positron emission tomography scans. Distinct Aβ trajectory patterns were classified using latent class growth analysis, and longitudinal cognitive performances across these patterns were assessed with a linear mixed effects model. Results: The optimal model consisted of three classes, with a high entropy value of 0.947. The classes were designated as follows: class 1, non‐accumulation group (n = 197); class 2, late accumulation group (n = 70); and class 3, early accumulation group (n = 30). The late accumulation and early accumulation groups had more APOE ε4 carriers than the non‐accumulation group. The longitudinal analysis of cognitive performance revealed that the early accumulation group showed the steepest decline (modified Preclinical Alzheimer's Cognitive Composite with digit symbol substitution [mPACCdigit], p < 0.001; modified Preclinical Alzheimer's Cognitive Composite with trails B [mPACCtrailsB], p < 0.001) and the late accumulation group showed a steeper decline (mPACCdigit, p = 0.014; mPACCtrailsB, p = 0.007) compared to the non‐accumulation group. Conclusions: Our study showed the heterogeneity of Aβ accumulation trajectories in CU older individuals. The prognoses for cognitive decline differ according to the Aβ trajectory patterns. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

24. Genome‐wide association meta‐analysis identifies a novel LRBA locus for brain age acceleration in two independent Korean Cohorts

Author

Kim, Bo‐Hyun, primary, Nho, Kwangsik, additional, Huang, Yen‐Ning, additional, Risacher, Shannon L, additional, Kim, Jun Pyo, additional, Yi, Dahyun, additional, Byun, Min Soo, additional, Kim, Hee Jin, additional, Won, Hong‐Hee, additional, Saykin, Andrew J., additional, Lee, Dong Young, additional, and Seo, Sang Won, additional

Published
2023
Full Text
View/download PDF

27. Identifying novel genetic variants for brain amyloid deposition: a genome-wide association study in the Korean population

Author

Kim, Hang-Rai, Jung, Sang-Hyuk, Kim, Jaeho, Jang, Hyemin, Kang, Sung Hoon, Hwangbo, Song, Kim, Jun Pyo, Kim, So Yeon, Kim, Beomsu, Kim, Soyeon, Jeong, Jee Hyang, Yoon, Soo Jin, Park, Kyung Won, Kim, Eun-Joo, Yoon, Bora, Jang, Jae-Won, Hong, Jin Yong, Choi, Seong Hye, Noh, Young, Kim, Ko Woon, Kim, Si Eun, Lee, Jin San, Jung, Na-Yeon, Lee, Juyoun, Kim, Byeong C., Son, Sang Joon, Hong, Chang Hyung, Na, Duk L., Seo, Sang Won, Won, Hong-Hee, and Kim, Hee Jin

Published
2021
Full Text
View/download PDF

32. Application of an amyloid and tau classification system in subcortical vascular cognitive impairment patients

Author

Jang, Hyemin, Kim, Hee Jin, Park, Seongbeom, Park, Yu Hyun, Choe, Yeongsim, Cho, Hanna, Lyoo, Chul Hyoung, Yoon, Uicheul, Lee, Jin San, Kim, Yeshin, Kim, Seung Joo, Kim, Jun Pyo, Jung, Young Hee, Ryu, Young Hoon, Choi, Jae Yong, Moon, Seung Hwan, Seong, Joon-Kyung, DeCarli, Charles, Weiner, Michael W., Lockhart, Samuel N., Cho, Soo Hyun, Na, Duk L., and Seo, Sang Won

Published
2020
Full Text
View/download PDF

37. Emerging role of vascular burden in AT(N) classification in individuals with Alzheimer’s and concomitant cerebrovascular burdens

Author

Chun, Min Young, primary, Jang, Hyemin, additional, Kim, Soo-Jong, additional, Park, Yu Hyun, additional, Yun, Jihwan, additional, Lockhart, Samuel N, additional, Weiner, Michael, additional, De Carli, Charles, additional, Moon, Seung Hwan, additional, Choi, Jae Yong, additional, Nam, Kyung Rok, additional, Byun, Byung-Hyun, additional, Lim, Sang-Moo, additional, Kim, Jun Pyo, additional, Choe, Yeong Sim, additional, Kim, Young Ju, additional, Na, Duk L, additional, Kim, Hee Jin, additional, and Seo, Sang Won, additional

Published
2023
Full Text
View/download PDF

41. Transcriptional risk scores in Alzheimer's disease: From pathology to cognition.

Author

Pyun, Jung‐Min, Park, Young Ho, Wang, Jiebiao, Bennett, David A., Bice, Paula J., Kim, Jun Pyo, Kim, SangYun, Saykin, Andrew J., and Nho, Kwangsik

Abstract

INTRODUCTION: Our previously developed blood‐based transcriptional risk scores (TRS) showed associations with diagnosis and neuroimaging biomarkers for Alzheimer's disease (AD). Here, we developed brain‐based TRS. METHODS: We integrated AD genome‐wide association study summary and expression quantitative trait locus data to prioritize target genes using Mendelian randomization. We calculated TRS using brain transcriptome data of two independent cohorts (N = 878) and performed association analysis of TRS with diagnosis, amyloidopathy, tauopathy, and cognition. We compared AD classification performance of TRS with polygenic risk scores (PRS). RESULTS: Higher TRS values were significantly associated with AD, amyloidopathy, tauopathy, worse cognition, and faster cognitive decline, which were replicated in an independent cohort. The AD classification performance of PRS was increased with the inclusion of TRS up to 16% with the area under the curve value of 0.850. DISCUSSION: Our results suggest brain‐based TRS improves the AD classification of PRS and may be a potential AD biomarker. Highlights: Transcriptional risk score (TRS) is developed using brain RNA‐Seq data.Higher TRS values are shown in Alzheimer's disease (AD).TRS improves the AD classification power of PRS up to 16%.TRS is associated with AD pathology presence.TRS is associated with worse cognitive performance and faster cognitive decline. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

42. Circulating lipid profiles are associated with cross-sectional and longitudinal changes of central biomarkers for Alzheimer’s disease

Author

Kim, Jun Pyo, Nho, Kwangsik, Wang, Tingting, Huynh, Kevin, Arnold, Matthias, Risacher, Shannon L., Bice, Paula J., Han, Xianlin, Kristal, Bruce S., Blach, Colette, Baillie, Rebecca, Kastenmüller, Gabi, Meikle, Peter J., Saykin, Andrew J., and Kaddurah-Daouk, Rima

Subjects
Article
Abstract

Investigating the association of lipidome profiles with central Alzheimer’s disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD. We performed cross-sectional and longitudinal association analysis of serum lipidome profiles with AD biomarkers in the Alzheimer’s Disease Neuroimaging Initiative cohort (N=1,395). We identified lipid species, classes, and network modules that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers for AD. Notably, we identified the lysoalkylphosphatidylcholine (LPC(O)) as associated with “A/N” biomarkers at baseline at lipid species, class, and module levels. Also, G(M3) ganglioside showed significant association with baseline levels and longitudinal changes of the “N” biomarkers at species and class levels. Our study of circulating lipids and central AD biomarkers enabled identification of lipids that play potential roles in the cascade of AD pathogenesis. Our results suggest dysregulation of lipid metabolic pathways as precursors to AD development and progression.

Published
2023

47. Novel CYP1B1-RMDN2 Alzheimer’s disease locus identified by genome-wide association analysis of cerebral tau deposition on PET

Author

Nho, Kwangsik, Risacher, Shannon L., Apostolova, Liana, Bice, Paula J., Brosch, Jared, Deardorff, Rachael, Faber, Kelley, Farlow, Martin R., Foroud, Tatiana, Gao, Sujuan, Rosewood, Thea, Kim, Jun Pyo, Nudelman, Kelly, Yu, Meichen, Aisen, Paul, Sperling, Reisa, Hooli, Basavaraj, Shcherbinin, Sergey, Svaldi, Diana, Jack, Clifford R., Jagust, William J., Landau, Susan, Vasanthakumar, Aparna, Waring, Jeffrey F., Doré, Vincent, Laws, Simon M., Masters, Colin L., Porter, Tenielle, Rowe, Christopher C., Villemagne, Victor L, Dumitrescu, Logan, Hohman, Timothy J., Libby, Julia B., Mormino, Elizabeth, Buckley, Rachel F., Johnson, Keith, Yang, Hyun-Sik, Petersen, Ronald C., Ramanan, Vijay K., Vemuri, Prashanthi, Cohen, Ann D., Fan, Kang-Hsien, Kamboh, M. Ilyas, Lopez, Oscar L., Bennett, David A., Ali, Muhammad, Benzinger, Tammie, Cruchaga, Carlos, Hobbs, Diana, De Jager, Philip L., Fujita, Masashi, Jadhav, Vaishnavi, Lamb, Bruce T., Tsai, Andy P., Castanho, Isabel, Mill, Jonathan, Weiner, Michael W., and Saykin, Andrew J.

Subjects
Article
Abstract

Determining the genetic architecture of Alzheimer’s disease (AD) pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we performed a genome-wide association study of cortical tau quantified by positron emission tomography in 3,136 participants from 12 independent studies. The CYP1B1-RMDN2 locus was associated with tau deposition. The most significant signal was at rs2113389, which explained 4.3% of the variation in cortical tau, while APOE4 rs429358 accounted for 3.6%. rs2113389 was associated with higher tau and faster cognitive decline. Additive effects, but no interactions, were observed between rs2113389 and diagnosis, APOE4 , and Aβ positivity. CYP1B1 expression was upregulated in AD. rs2113389 was associated with higher CYP1B1 expression and methylation levels. Mouse model studies provided additional functional evidence for a relationship between CYP1B1 and tau deposition but not Aβ. These results may provide insight into the genetic basis of cerebral tau and novel pathways for therapeutic development in AD.

Published
2023

50. Emerging role of vascular burden in AT(N) classification in individuals with Alzheimer’s and concomitant cerebrovascular burdens

Author

Chun, Min Young, Jang, Hyemin, Kim, Soo-Jong, Park, Yu Hyun, Yun, Jihwan, Lockhart, Samuel N, Weiner, Michael, De Carli, Charles, Moon, Seung Hwan, Choi, Jae Yong, Nam, Kyung Rok, Byun, Byung-Hyun, Lim, Sang-Moo, Kim, Jun Pyo, Choe, Yeong Sim, Kim, Young Ju, Na, Duk L, Kim, Hee Jin, and Seo, Sang Won

Abstract

ObjectivesAlzheimer’s disease (AD) is characterised by amyloid-beta accumulation (A), tau aggregation (T) and neurodegeneration (N). Vascular (V) burden has been found concomitantly with AD pathology and has synergistic effects on cognitive decline with AD biomarkers. We determined whether cognitive trajectories of AT(N) categories differed according to vascular (V) burden.MethodsWe prospectively recruited 205 participants and classified them into groups based on the AT(N) system using neuroimaging markers. Abnormal V markers were identified based on the presence of severe white matter hyperintensities.ResultsIn A+ category, compared with the frequency of Alzheimer’s pathological change category (A+T–), the frequency of AD category (A+T+) was significantly lower in V+ group (31.8%) than in V– group (64.4%) (p=0.004). Each AT(N) biomarker was predictive of cognitive decline in the V+ group as well as in the V– group (p<0.001). Additionally, the V+ group showed more severe cognitive trajectories than the V– group in the non-Alzheimer’s pathological changes (A–T+, A–N+; p=0.002) and Alzheimer’s pathological changes (p<0.001) categories.ConclusionThe distribution and longitudinal outcomes of AT(N) system differed according to vascular burdens, suggesting the importance of incorporating a V biomarker into the AT(N) system.

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results