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Chun MY, Park YH, Kim HJ, Na DL, Kim JP, Seo SW, Jang H. Distinct Characteristics of Suspected Non-Alzheimer Pathophysiology in Relation to Cognitive Status and Cerebrovascular Burden. Clin Nucl Med 2025; 50:368-380. [PMID: 40025666 PMCID: PMC11969373 DOI: 10.1097/rlu.0000000000005793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2024] [Accepted: 01/23/2025] [Indexed: 03/04/2025]
Abstract
PURPOSE OF THE REPORT This study investigated the prevalence and clinical characteristics of suspected non-Alzheimer disease pathophysiology (SNAP) across varying cognitive statuses and cerebral small vessel disease (CSVD) burden. PATIENTS AND METHODS We included 1992 participants with cognitive status categorized as cognitively unimpaired, mild cognitive impairment, or dementia. β-amyloid (Aβ, A) positivity was assessed by Aβ PET, and neurodegeneration (N) positivity was determined through hippocampal volume. Participants were further divided by the presence or absence of severe CSVD. The clinical and imaging characteristics of A-N+ (SNAP) group were compared with those of the A-N- and A+N+ groups. RESULTS SNAP participants were older and had more vascular risk factors compared with A-N- and A+N+ in the CSVD(-) cohort. SNAP and A+N+ showed similar cortical thinning. At the dementia stage, SNAP had a cognitive trajectory similar to A+N+ in the CSVD(-) cohort. However, SNAP exhibited less cognitive decline than A+N+ in the CSVD(+) cohort. CONCLUSIONS SNAP is characterized by distinct clinical and imaging characteristics; however, it does not necessarily indicate a benign prognosis, particularly at the dementia stage. These findings highlight the need to assess SNAP in relation to the cognitive stage and CSVD presence to better understand its progression and guide interventions.
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Affiliation(s)
- Min Young Chun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine
- Department of Neurology, Yonsei University College of Medicine
| | - Yu Hyun Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine
- Neuroscience Center, Samsung Medical Center
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University
- Department of Digital Health, SAIHST, Sungkyunkwan University
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University
- Department of Digital Health, SAIHST, Sungkyunkwan University
- Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Gangnam-gu
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Jongno-gu, Seoul, South Korea
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Lee WJ, Cho KJ, Kim GW. Mitigation of Atherosclerotic Vascular Damage and Cognitive Improvement Through Mesenchymal Stem Cells in an Alzheimer's Disease Mouse Model. Int J Mol Sci 2024; 25:13210. [PMID: 39684920 DOI: 10.3390/ijms252313210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2024] [Revised: 12/05/2024] [Accepted: 12/05/2024] [Indexed: 12/18/2024] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative condition characterized by progressive memory loss and other cognitive disturbances. Patients with AD can be vulnerable to vascular damage, and damaged vessels can lead to cognitive impairment. Mesenchymal stem cell (MSC) treatment has shown potential in ameliorating AD pathogenesis, but its effect on vascular function remains unclear. This study aimed to improve cognitive function by alleviating atherosclerosis-induced vessel damage using MSCs in mice with a genetic AD background. In this study, a 5xFAD mouse model of AD was used, and atherosclerotic vessel damage was induced by high-fat diets (HFDs). MSCs were injected into the tail vein along with mannitol in 5xFAD mice on an HFD. MSCs were detected in the brain, and vascular damage was improved following MSC treatment. Behavioral tests showed that MSCs enhanced cognitive function, as measured by the Y-maze and passive avoidance tests. Additionally, muscle strength measured by the rotarod test was also increased by MSCs in AD mice with vessel damage induced by HFDs. Overall, our results suggest that stem cells can alleviate vascular damage caused by metabolic diseases, including HFDs, and vascular disease in individuals carrying the AD gene. Consequently, this alleviates cognitive decline related to vascular dementia symptoms.
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Affiliation(s)
- Woong Jin Lee
- Department of Neurology, College of Medicine, Yonsei University, Seoul 03722, Republic of Korea
| | - Kyoung Joo Cho
- Department of Life Science, Kyonggi University, Suwon 16227, Republic of Korea
| | - Gyung Whan Kim
- Department of Neurology, College of Medicine, Yonsei University, Seoul 03722, Republic of Korea
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Kim J, Suh SI, Park YJ, Kang M, Chung SJ, Lee ES, Jung HN, Eo JS, Koh SB, Oh K, Kang SH. Sarcopenia is a predictor for Alzheimer's continuum and related clinical outcomes. Sci Rep 2024; 14:21074. [PMID: 39256402 PMCID: PMC11387779 DOI: 10.1038/s41598-024-62918-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/22/2024] [Indexed: 09/12/2024] Open
Abstract
Low body mass index is closely related to a high risk of Alzheimer's disease (AD) and related biomarkers including amyloid-β (Aβ) deposition. However, the association between sarcopenia and Aβ-confirmed AD remains controversial. Therefore, we investigated the relationship between sarcopenia and the AD continuum. We explored sarcopenia's association with clinical implications of participants on the AD continuum. We prospectively enrolled 142 participants on the AD continuum (19 with preclinical AD, 96 with mild cognitive impairment due to AD, and 28 with AD dementia) and 58 Aβ-negative cognitively unimpaired participants. Sarcopenia, assessed using dual-energy X-ray absorptiometry and hand grip measurements, was considered a predictor. AD continuum, defined by Aβ deposition on positron emission tomography served as an outcome. Clinical severity in participants on the AD continuum assessed using hippocampal volume, Mini-Mental State Examination (MMSE), Seoul Verbal Learning Test (SVLT), and Clinical Dementia Rating Scale Sum of Boxes Scores (CDR-SOB) were also considered an outcome. Sarcopenia (odds ratio = 4.99, p = 0.004) was associated independently with the AD continuum after controlling for potential confounders. Moreover, sarcopenia was associated with poor downstream imaging markers (decreased hippocampal volume, β = - 0.206, p = 0.020) and clinical outcomes (low MMSE, β = - 1.364, p = 0.025; low SVLT, β = - 1.077, p = 0.025; and high CDR-SOB scores, β = 0.783, p = 0.022) in participants on the AD continuum. Sarcopenia was associated with the AD continuum and poor clinical outcome in individuals with AD continuum. Therefore, our results provide evidence for future studies to confirm whether proper management of sarcopenia can effective strategies are required for sarcopenia management to prevent the AD continuum and its clinical implications.
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Affiliation(s)
- Jeonghun Kim
- Korea Testing Laboratory, Bio and Medical Health Division, Seoul, Korea
| | - Sang-Il Suh
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Yu Jeong Park
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea
| | - Minwoong Kang
- Department of Biomedical Research Center, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Su Jin Chung
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea
| | - Eun Seong Lee
- Department of Nuclear Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Hye Na Jung
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Jae Seon Eo
- Department of Nuclear Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea.
| | - Sung Hoon Kang
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea.
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Lee EH, Yoo H, Kim YJ, Cheon BK, Ryu S, Chang Y, Yun J, Jang H, Kim JP, Kim HJ, Koh SB, Jeong JH, Na DL, Seo SW, Kang SH. Different associations between body mass index and Alzheimer's markers depending on metabolic health. Alzheimers Res Ther 2024; 16:194. [PMID: 39210402 PMCID: PMC11363444 DOI: 10.1186/s13195-024-01563-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Accepted: 08/21/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Increasing evidence supports the association between body mass index (BMI), Alzheimer's disease, and vascular markers. Recently, metabolically unhealthy conditions have been reported to affect the expression of these markers. We aimed to investigate the effects of BMI status on Alzheimer's and vascular markers in relation to metabolic health status. METHODS We recruited 1,736 Asians without dementia (71.6 ± 8.0 years). Participants were categorized into underweight, normal weight, or obese groups based on their BMI. Each group was further divided into metabolically healthy (MH) and unhealthy (MU) groups based on the International Diabetes Foundation definition of metabolic syndrome. The main outcome was Aβ positivity, defined as a Centiloid value of 20.0 or above and the presence of vascular markers, defined as severe white matter hyperintensities (WMH). Logistic regression analyses were performed for Aβ positivity and severe WMH with BMI status or interaction terms between BMI and metabolic health status as predictors. Mediation analyses were performed with hippocampal volume (HV) and baseline Mini-Mental State Examination (MMSE) scores as the outcomes, and linear mixed models were performed for longitudinal change in MMSE scores. RESULTS Being underweight increased the risk of Aβ positivity (odds ratio [OR] = 2.37, 95% confidence interval [CI] 1.13-4.98), whereas obesity decreased Aβ positivity risk (OR = 0.63, 95% CI 0.50-0.80). Especially, obesity decreased the risk of Aβ positivity (OR = 0.38, 95% CI 0.26-0.56) in the MH group, but not in the MU group. Obesity increased the risk of severe WMH (OR = 1.69, 1.16-2.47). Decreased Aβ positivity mediate the relationship between obesity and higher HV and MMSE scores, particularly in the MH group. Obesity demonstrated a slower decline in MMSE (β = 1.423, p = 0.037) compared to being normal weight, especially in the MH group. CONCLUSIONS Our findings provide new evidence that metabolic health has a significant effect on the relationship between obesity and Alzheimer's markers, which, in turn, lead to better clinical outcomes.
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Affiliation(s)
- Eun Hye Lee
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Heejin Yoo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Young Ju Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Bo Kyoung Cheon
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Seungho Ryu
- Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yoosoo Chang
- Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jihwan Yun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Department of Neurology, Soonchunhyang University Bucheon Hospital, Gyeonggi-do, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Seoul National University Hospital, Seoul National University college of Medicine, Seoul, Republic of Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Republic of Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University Seoul Hospital, Ewha Womans University College of Medicine, Seoul, Republic of Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.
| | - Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Republic of Korea.
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Im Y, Kang SH, Park G, Yoo H, Chun MY, Kim CH, Park CJ, Kim JP, Jang H, Kim HJ, Oh K, Koh SB, Lee JM, Na DL, Seo SW, Kim H. Ethnic differences in the effects of apolipoprotein E ɛ4 and vascular risk factors on accelerated brain aging. Brain Commun 2024; 6:fcae213. [PMID: 39007039 PMCID: PMC11242459 DOI: 10.1093/braincomms/fcae213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/30/2024] [Accepted: 07/09/2024] [Indexed: 07/16/2024] Open
Abstract
The frequency of the apolipoprotein E ɛ4 allele and vascular risk factors differs among ethnic groups. We aimed to assess the combined effects of apolipoprotein E ɛ4 and vascular risk factors on brain age in Korean and UK cognitively unimpaired populations. We also aimed to determine the differences in the combined effects between the two populations. We enrolled 2314 cognitively unimpaired individuals aged ≥45 years from Korea and 6942 cognitively unimpaired individuals from the UK, who were matched using propensity scores. Brain age was defined using the brain age index. The apolipoprotein E genotype (ɛ4 carriers, ɛ2 carriers and ɛ3/ɛ3 homozygotes) and vascular risk factors (age, hypertension and diabetes) were considered predictors. Apolipoprotein E ɛ4 carriers in the Korean (β = 0.511, P = 0.012) and UK (β = 0.302, P = 0.006) groups had higher brain age index values. The adverse effects of the apolipoprotein E genotype on brain age index values increased with age in the Korean group alone (ɛ2 carriers × age, β = 0.085, P = 0.009; ɛ4 carriers × age, β = 0.100, P < 0.001). The apolipoprotein E genotype, age and ethnicity showed a three-way interaction with the brain age index (ɛ2 carriers × age × ethnicity, β = 0.091, P = 0.022; ɛ4 carriers × age × ethnicity, β = 0.093, P = 0.003). The effects of apolipoprotein E on the brain age index values were more pronounced in individuals with hypertension in the Korean group alone (ɛ4 carriers × hypertension, β = 0.777, P = 0.038). The apolipoprotein E genotype, age and ethnicity showed a three-way interaction with the brain age index (ɛ4 carriers × hypertension × ethnicity, β=1.091, P = 0.014). We highlight the ethnic differences in the combined effects of the apolipoprotein E ɛ4 genotype and vascular risk factors on accelerated brain age. These findings emphasize the need for ethnicity-specific strategies to mitigate apolipoprotein E ɛ4-related brain aging in cognitively unimpaired individuals.
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Affiliation(s)
- Yanghee Im
- USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea
| | - Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul 08308, Korea
| | - Gilsoon Park
- USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - Heejin Yoo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
| | - Min Young Chun
- Department of Neurology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin 16995, Korea
| | - Chi-Hun Kim
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang 14068, Korea
| | - Chae Jung Park
- Research Institute, National Cancer Center, Goyang 10408, Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul 08308, Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul 08308, Korea
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul 06355, Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul 06355, Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon 16419, Korea
| | - Hosung Kim
- USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
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Lee S, Kim SE, Jang H, Kim JP, Sohn G, Park YH, Ham H, Gu Y, Park CJ, Kim HJ, Na DL, Kim K, Seo SW. Distinct effects of blood pressure parameters on Alzheimer's and vascular markers in 1,952 Asian individuals without dementia. Alzheimers Res Ther 2024; 16:125. [PMID: 38863019 PMCID: PMC11167921 DOI: 10.1186/s13195-024-01483-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 05/15/2024] [Indexed: 06/13/2024]
Abstract
BACKGROUND Risk factors for cardiovascular disease, including elevated blood pressure, are known to increase risk of Alzheimer's disease. There has been increasing awareness of the relationship between long-term blood pressure (BP) patterns and their effects on the brain. We aimed to investigate the association of repeated BP measurements with Alzheimer's and vascular disease markers. METHODS We recruited 1,952 participants without dementia between August 2015 and February 2022. During serial clinic visits, we assessed both systolic BP (SBP) and diastolic BP (DBP), and visit-to-visit BP variability (BPV) was quantified from repeated measurements. In order to investigate the relationship of mean SBP (or DBP) with Alzheimer's and vascular markers and cognition, we performed multiple linear and logistic regression analyses after controlling for potential confounders (Model 1). Next, we investigated the relationship of with variation of SBP (or DBP) with the aforementioned variables by adding it into Model 1 (Model 2). In addition, mediation analyses were conducted to determine mediation effects of Alzheimer's and vascular makers on the relationship between BP parameters and cognitive impairment. RESULTS High Aβ uptake was associated with greater mean SBP (β = 1.049, 95% confidence interval 1.016-1.083). High vascular burden was positively associated with mean SBP (odds ratio = 1.293, 95% CI 1.015-1.647) and mean DBP (1.390, 1.098-1.757). High tau uptake was related to greater systolic BPV (0.094, 0.001-0.187) and diastolic BPV (0.096, 0.007-0.184). High Aβ uptake partially mediated the relationship between mean SBP and the Mini-Mental State Examination (MMSE) scores. Hippocampal atrophy mediated the relationship between diastolic BPV and MMSE scores. CONCLUSIONS Each BP parameter affects Alzheimer's and vascular disease markers differently, which in turn leads to cognitive impairment. Therefore, it is necessary to appropriately control specific BP parameters to prevent the development of dementia. Furthermore, a better understanding of pathways from specific BP parameters to cognitive impairments might enable us to select the managements targeting the specific BP parameters to prevent dementia effectively.
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Affiliation(s)
- Sungjoo Lee
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, 48108, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Gyeongmo Sohn
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, 48108, Republic of Korea
| | - Yu Hyun Park
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Hongki Ham
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Yuna Gu
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Chae Jung Park
- Research Institute, National Cancer Center, Goyang, 10408, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Kyunga Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Department of Data Convergence & Future Medicine, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea.
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea.
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7
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van Gils V, Rizzo M, Côté J, Viechtbauer W, Fanelli G, Salas-Salvadó J, Wimberley T, Bulló M, Fernandez-Aranda F, Dalsgaard S, Visser PJ, Jansen WJ, Vos SJB. The association of glucose metabolism measures and diabetes status with Alzheimer's disease biomarkers of amyloid and tau: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 159:105604. [PMID: 38423195 DOI: 10.1016/j.neubiorev.2024.105604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/21/2024] [Accepted: 02/23/2024] [Indexed: 03/02/2024]
Abstract
Conflicting evidence exists on the relationship between diabetes mellitus (DM) and Alzheimer's disease (AD) biomarkers. Therefore, we conducted a random-effects meta-analysis to evaluate the correlation of glucose metabolism measures (glycated hemoglobin, fasting blood glucose, insulin resistance indices) and DM status with AD biomarkers of amyloid-β and tau measured by positron emission tomography or cerebrospinal fluid. We selected 37 studies from PubMed and Embase, including 11,694 individuals. More impaired glucose metabolism and DM status were associated with higher tau biomarkers (r=0.11[0.03-0.18], p=0.008; I2=68%), but were not associated with amyloid-β biomarkers (r=-0.06[-0.13-0.01], p=0.08; I2=81%). Meta-regression revealed that glucose metabolism and DM were specifically associated with tau biomarkers in population settings (p=0.001). Furthermore, more impaired glucose metabolism and DM status were associated with lower amyloid-β biomarkers in memory clinic settings (p=0.004), and in studies with a higher prevalence of dementia (p<0.001) or lower cognitive scores (p=0.04). These findings indicate that DM is associated with biomarkers of tau but not with amyloid-β. This knowledge is valuable for improving dementia and DM diagnostics and treatment.
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Affiliation(s)
- Veerle van Gils
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| | - Marianna Rizzo
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Jade Côté
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Wolfgang Viechtbauer
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Giuseppe Fanelli
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy; Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Nijmegen, the Netherlands
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental (ANUT-DSM), Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Alimentació, Nutrició, Desenvolupament i Salut Mental, Reus, Spain; CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid 28029, Spain
| | - Theresa Wimberley
- The National Center for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Mònica Bulló
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid 28029, Spain; Nutrition and Metabolic Health Research Group (NuMeH). Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), Reus 43201, Spain; Center of Environmental, Food and Toxicological Technology - TecnATox, Rovira i Virgili University, Reus 43201, Spain
| | - Fernando Fernandez-Aranda
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid 28029, Spain; Department of Clinical Psychology, Bellvitge University Hospital-IDIBELL, Barcelona, Spain; Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Spain
| | - Søren Dalsgaard
- The National Center for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark; iPSYCH - The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Pieter Jelle Visser
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Alzheimer Center and Department of Neurology, Amsterdam Neuroscience Campus, VU University Medical Center, Amsterdam, the Netherlands
| | - Willemijn J Jansen
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
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Yoon JM, Lim CY, Noh H, Nam SW, Jun SY, Kim MJ, Song MY, Jang H, Kim HJ, Seo SW, Na DL, Chung MJ, Ham DI, Kim K. Enhancing foveal avascular zone analysis for Alzheimer's diagnosis with AI segmentation and machine learning using multiple radiomic features. Sci Rep 2024; 14:1841. [PMID: 38253722 PMCID: PMC10810355 DOI: 10.1038/s41598-024-51612-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 01/07/2024] [Indexed: 01/24/2024] Open
Abstract
We propose a hybrid technique that employs artificial intelligence (AI)-based segmentation and machine learning classification using multiple features extracted from the foveal avascular zone (FAZ)-a retinal biomarker for Alzheimer's disease-to improve the disease diagnostic performance. Imaging data of optical coherence tomography angiography from 37 patients with Alzheimer's disease and 48 healthy controls were investigated. The presence or absence of brain amyloids was confirmed using amyloid positron emission tomography. In the superficial capillary plexus of the angiography scans, the FAZ was automatically segmented using an AI method to extract multiple biomarkers (area, solidity, compactness, roundness, and eccentricity), which were paired with clinical data (age and sex) as common correction variables. We used a light-gradient boosting machine (a light-gradient boosting machine is a machine learning algorithm based on trees utilizing gradient boosting) to diagnose Alzheimer's disease by integrating the corresponding multiple radiomic biomarkers. Fivefold cross-validation was applied for analysis, and the diagnostic performance for Alzheimer's disease was determined by the area under the curve. The proposed hybrid technique achieved an area under the curve of [Formula: see text]%, outperforming the existing single-feature (area) criteria by over 13%. Furthermore, in the holdout test set, the proposed technique exhibited a 14% improvement compared to single features, achieving an area under the curve of 72.0± 4.8%. Based on these facts, we have demonstrated the effectiveness of our technology in achieving significant performance improvements in FAZ-based Alzheimer's diagnosis research through the use of multiple radiomic biomarkers (area, solidity, compactness, roundness, and eccentricity).
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Affiliation(s)
- Je Moon Yoon
- Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
| | - Chae Yeon Lim
- Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea
| | - Hoon Noh
- Hangil Eye Hospital, 35 Bupyeong-daero, Bupyeong-gu, Incheon, 21388, Republic of Korea
| | - Seung Wan Nam
- Hangil Eye Hospital, 35 Bupyeong-daero, Bupyeong-gu, Incheon, 21388, Republic of Korea
- Department of Ophthalmology, Catholic Kwandong University College of Medicine, 35 Bupyeong-daero, Bupyeong-gu, Incheon, 21388, Republic of Korea
| | - Sung Yeon Jun
- Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
| | - Min Ji Kim
- Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
| | - Mi Yeon Song
- Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
| | - Hyemin Jang
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hee Jin Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
| | - Sang Won Seo
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Duk L Na
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
- Happymind Clinic, Seoul, Republic of Korea
| | - Myung Jin Chung
- Department of Data Convergence and Future Medicine, Sungkyunkwan University School of Medicine, Suwon, 16419, Republic of Korea
- Department of Radiology and AI Research Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
| | - Don-Il Ham
- Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea.
| | - Kyungsu Kim
- Medical AI Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Department of Data Convergence and Future Medicine, Sungkyunkwan University School of Medicine, Suwon, 16419, Republic of Korea.
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9
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Jang H, Lee S, An S, Park Y, Kim SJ, Cheon BK, Kim JH, Kim HJ, Na DL, Kim JP, Kim K, Seo SW. Association of Glycemic Variability With Imaging Markers of Vascular Burden, β-Amyloid, Brain Atrophy, and Cognitive Impairment. Neurology 2024; 102:e207806. [PMID: 38165363 PMCID: PMC10834128 DOI: 10.1212/wnl.0000000000207806] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 09/27/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVE We aimed to investigate the association between glycemic variability (GV) and neuroimaging markers of white matter hyperintensities (WMH), beta-amyloid (Aβ), brain atrophy, and cognitive impairment. METHODS This was a retrospective cohort study that included participants without dementia from a memory clinic. They all had Aβ PET, brain MRI, and standardized neuropsychological tests and had fasting glucose (FG) levels tested more than twice during the study period. We defined GV as the intraindividual visit-to-visit variability in FG levels. Multivariable linear regression and logistic regression were used to identify whether GV was associated with the presence of severe WMH and Aβ uptake with DM, mean FG levels, age, sex, hypertension, and presence of APOE4 allele as covariates. Mediation analyses were used to investigate the mediating effect of WMH and Aβ uptake on the relationship between GV and brain atrophy and cognition. RESULTS Among the 688 participants, the mean age was 72.2 years, and the proportion of female participants was 51.9%. Increase in GV was predictive of the presence of severe WMH (coefficient [95% CI] 1.032 [1.012-1.054]; p = 0.002) and increased Aβ uptake (1.005 [1.001-1.008]; p = 0.007). Both WMH and increased Aβ uptake partially mediated the relationship between GV and frontal-executive dysfunction (GV → WMH → frontal-executive; direct effect, -0.319 [-0.557 to -0.080]; indirect effect, -0.050 [-0.091 to -0.008]) and memory dysfunction (GV → Aβ → memory; direct effect, -0.182 [-0.338 to -0.026]; indirect effect, -0.067 [-0.119 to -0.015]), respectively. In addition, increased Aβ uptake completely mediated the relationship between GV and hippocampal volume (indirect effect, -1.091 [-2.078 to -0.103]) and partially mediated the relationship between GV and parietal thickness (direct effect, -0.00101 [-0.00185 to -0.00016]; indirect effect, -0.00016 [-0.00032 to -0.000002]). DISCUSSION Our findings suggest that increased GV is related to vascular and Alzheimer risk factors and neurodegenerative markers, which in turn leads to subsequent cognitive impairment. Furthermore, GV can be considered a potentially modifiable risk factor for dementia prevention.
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Affiliation(s)
- Hyemin Jang
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Sungjoo Lee
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Sungsik An
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Yuhyun Park
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Soo-Jong Kim
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Bo Kyoung Cheon
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Ji Hyun Kim
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Hee Jin Kim
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Duk L Na
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Jun Pyo Kim
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Kyunga Kim
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
| | - Sang Won Seo
- From the Alzheimer's Disease Convergence Research Center (H.J., S.A., Y.P., S.-J.K., B.K.C., J.H.K., H.J.K., D.L.N., J.P.K., S.W.S.), Samsung Medical Center; Department of Digital Health (H.J., S.L., K.K., S.W.S.), Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University; Department of Neurology (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center, Sungkyunkwan University School of Medicine; Neuroscience Center (H.J., H.J.K., J.P.K., S.W.S.), Samsung Medical Center; Happymind Clinic (D.L.N.); Biomedical Statistics Center (K.K.), Research Institute for Future Medicine, Samsung Medical Center; and Department of Data Convergence and Future Medicine (K.K.), Sungkyunkwan University School of Medicine, Seoul, Korea. Dr. Jang is currently at the Department of Neurology, Seoul National University Hospital, Korea
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10
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Moon H, Ham H, Yun J, Shin D, Lee EH, Kim HJ, Seo SW, Na DL, Jang H. Prediction of Amyloid Positivity in Patients with Subcortical Vascular Cognitive Impairment. J Alzheimers Dis 2024; 99:1117-1127. [PMID: 38788077 DOI: 10.3233/jad-240196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
Background Amyloid-β (Aβ) commonly coexists and impacts prognosis in subcortical vascular cognitive impairment (SVCI). Objective This study aimed to examine the differences in clinical and neuroimaging variables between Aβ-positive and Aβ-negative SVCI and to propose a prediction model for Aβ positivity in clinically diagnosed SVCI patients. Methods A total of 130 patients with SVCI were included in model development, and a separate cohort of 70 SVCI patients was used in external validation. The variables for the prediction model were selected by comparing the characteristics of the Aβ-negative and Aβ-positive SVCI groups. The final model was determined using a stepwise method. The model performance was evaluated using the receiver operating characteristic (ROC) curve and a calibration curve. A nomogram was used for visualization. Results Among 130 SVCI patients, 70 (53.8%) were Aβ-positive. The Aβ-positive SVCI group was characterized by older age, tendency to be in the dementia stage, a higher prevalence of APOEɛ4, a lower prevalence of lacune, and more severe medial temporal atrophy (MTA). The final prediction model, which excluded MTA grade following the stepwise method for variable selection, demonstrated good accuracy in distinguishing between Aβ-positive and Aβ-negative SVCI, with an area under the curve (AUC) of 0.80. The external validation demonstrated an AUC of 0.71. Conclusions The findings suggest that older age, dementia stage, APOEɛ4 carrier, and absence of lacunes may be predictive of Aβ positivity in clinically diagnosed SVCI patients.
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Affiliation(s)
- Hasom Moon
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Neurology, Seoul National University Hospital, Seoul National University School of Medicine, Seoul, South Korea
| | - Hongki Ham
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Jihwan Yun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Neurology, Soonchunhyang University Bucheon Hospital, Gyeonggi-do, South Korea
| | - Daeun Shin
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Eun Hye Lee
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Happymind Clinic, Seoul, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Neurology, Seoul National University Hospital, Seoul National University School of Medicine, Seoul, South Korea
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11
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Chun MY, Jang H, Kim SJ, Park YH, Yun J, Lockhart SN, Weiner M, De Carli C, Moon SH, Choi JY, Nam KR, Byun BH, Lim SM, Kim JP, Choe YS, Kim YJ, Na DL, Kim HJ, Seo SW. Emerging role of vascular burden in AT(N) classification in individuals with Alzheimer's and concomitant cerebrovascular burdens. J Neurol Neurosurg Psychiatry 2023; 95:44-51. [PMID: 37558399 PMCID: PMC10803958 DOI: 10.1136/jnnp-2023-331603] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 07/22/2023] [Indexed: 08/11/2023]
Abstract
OBJECTIVES Alzheimer'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. METHODS We 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. RESULTS In 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. CONCLUSION The 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.
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Affiliation(s)
- Min Young Chun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Soo-Jong Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Yu Hyun Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Jihwan Yun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
| | - Samuel N Lockhart
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Michael Weiner
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Charles De Carli
- Department of Neurology, University of California-Davis, Davis, California, USA
| | - Seung Hwan Moon
- Departmentof Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jae Yong Choi
- Division of Applied RI, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Kyung Rok Nam
- Division of Applied RI, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Byung-Hyun Byun
- Department of Nuclear Medicine, Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Sang-Moo Lim
- Department of Nuclear Medicine, Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Center for Neuroimaging, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Yeong Sim Choe
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
| | - Young Ju Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Cell and Gene Therapy Institute (CGTI), Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
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12
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Kang SH, Yoo H, Cheon BK, Park YH, Kim SJ, Ham H, Jang H, Kim HJ, Oh K, Koh SB, Na DL, Kim JP, Seo SW. Distinct effects of cholesterol profile components on amyloid and vascular burdens. Alzheimers Res Ther 2023; 15:197. [PMID: 37950256 PMCID: PMC10636929 DOI: 10.1186/s13195-023-01342-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 10/25/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Cholesterol plays important roles in β-amyloid (Aβ) metabolism and atherosclerosis. However, the relationships of plasma cholesterol levels with Aβ and cerebral small vessel disease (CSVD) burdens are not fully understood in Asians. Herein, we investigated the relationships between plasma cholesterol profile components and Aβ and CSVD burdens in a large, non-demented Korean cohort. METHODS We enrolled 1,175 non-demented participants (456 with unimpaired cognition [CU] and 719 with mild cognitive impairment [MCI]) aged ≥ 45 years who underwent Aβ PET at the Samsung Medical Center in Korea. We performed linear regression analyses with each cholesterol (low-density lipoprotein cholesterol [LDL-c], high-density lipoprotein cholesterol [HDL-c], and triglyceride) level as a predictor and each image marker (Aβ uptake on PET, white matter hyperintensity [WMH] volume, and hippocampal volume) as an outcome after controlling for potential confounders. RESULTS Increased LDL-c levels (β = 0.014 to 0.115, p = 0.013) were associated with greater Aβ uptake, independent of the APOE e4 allele genotype and lipid-lowering medication. Decreased HDL-c levels (β = - 0.133 to - 0.006, p = 0.032) were predictive of higher WMH volumes. Increased LDL-c levels were also associated with decreased hippocampal volume (direct effect β = - 0.053, p = 0.040), which was partially mediated by Aβ uptake (indirect effect β = - 0.018, p = 0.006). CONCLUSIONS Our findings highlight that increased LDL-c and decreased HDL-c levels are important risk factors for Aβ and CSVD burdens, respectively. Furthermore, considering that plasma cholesterol profile components are potentially modified by diet, exercise, and pharmacological agents, our results provide evidence that regulating LDL-c and HDL-c levels is a potential strategy to prevent dementia.
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Grants
- 2022R1I1A1A01056956 Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education
- HI19C1132 a grant of the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea
- grant number: HU20C0111, HU22C0170 a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare and Ministry of science and ICT, Republic of Korea
- NRF-2019R1A5A2027340, NRF-2022R1F1A1063966 the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT)
- 2021-ER1006-01 the "National Institute of Health" research project
- a grant of the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea
- a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare and Ministry of science and ICT, Republic of Korea
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Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Heejin Yoo
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Bo Kyoung Cheon
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea
| | - Yu Hyun Park
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Soo-Jong Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Hongki Ham
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea
| | - Hyemin Jang
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
| | - Hee Jin Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Duk L Na
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
| | - Jun Pyo Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.
| | - Sang Won Seo
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea.
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.
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13
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Kang SH, Kang M, Han JH, Lee ES, Lee KJ, Chung SJ, Suh SI, Koh SB, Eo JS, Kim CK, Oh K. Independent effect of Aβ burden on cognitive impairment in patients with small subcortical infarction. Alzheimers Res Ther 2023; 15:178. [PMID: 37838715 PMCID: PMC10576878 DOI: 10.1186/s13195-023-01307-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 09/17/2023] [Indexed: 10/16/2023]
Abstract
BACKGROUND The effect of amyloid-β (Aβ) on cognitive impairment in patients with small subcortical infarction remains controversial, although a growing body of evidence shows a substantial overlap between Alzheimer's disease (AD) and subcortical ischemic vascular dementia, another form of cerebral small vessel disease (cSVD). Therefore, we investigated the relationships between Aβ positivity and the development of post-stroke cognitive impairment (PSCI) in patients with small subcortical infarction. METHODS We prospectively recruited 37 patients aged ≥ 50 years, with first-ever small subcortical infarction, who underwent amyloid positron emission tomography, 3 months after stroke at Korea University Guro Hospital. We also enrolled CU participants matched for age and sex with stroke patients for comparison of Aβ positivity. Patients were followed up at 3 and 12 months after the stroke to assess cognitive decline. Logistic and linear mixed-effect regression analyses were performed to identify the effect of Aβ positivity on PSCI development and long-term cognitive trajectories. RESULTS At 3 months after stroke, 12/37 (32.4%) patients developed PSCI, and 11/37 (29.7%) patients had Aβ deposition. Aβ positivity (odds ratio [OR] = 72.2, p = 0.024) was predictive of PSCI development regardless of cSVD burden. Aβ positivity (β = 0.846, p = 0.014) was also associated with poor cognitive trajectory, assessed by the Clinical Dementia Rating-Sum of Box, for 1 year after stroke. CONCLUSIONS Our findings highlight that Aβ positivity is an important predictor for PSCI development and cognitive decline over 1 year. Furthermore, our results provide evidence that anti-AD medications may be a strategy for preventing cognitive decline in patients with small subcortical infarctions.
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Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, South Korea
| | - Minwoong Kang
- Department of Biomedical Research Center, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Jung Hoon Han
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, South Korea
| | - Eun Seong Lee
- Department of Nuclear Medicine, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, South Korea
| | - Keon-Joo Lee
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, South Korea
| | - Su Jin Chung
- Department of Neurology, Myongji Hospital, Hanyang University College of Medicine, Goyang, South Korea
| | - Sang-Il Suh
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, South Korea
| | - Jae Seon Eo
- Department of Nuclear Medicine, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, South Korea.
| | - Chi Kyung Kim
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, South Korea.
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, South Korea
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14
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Kim BH, Lee H, Ham H, Kim HJ, Jang H, Kim JP, Park YH, Kim M, Seo SW. Clinical effects of novel susceptibility genes for beta-amyloid: a gene-based association study in the Korean population. Front Aging Neurosci 2023; 15:1278998. [PMID: 37901794 PMCID: PMC10602697 DOI: 10.3389/fnagi.2023.1278998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 09/25/2023] [Indexed: 10/31/2023] Open
Abstract
Amyloid-beta (Aβ) is a pathological hallmark of Alzheimer's disease (AD). We aimed to identify genes related to Aβ uptake in the Korean population and investigate the effects of these novel genes on clinical outcomes, including neurodegeneration and cognitive impairments. We recruited a total of 759 Korean participants who underwent neuropsychological tests, brain magnetic resonance imaging, 18F-flutemetamol positron emission tomography, and microarray genotyping data. We performed gene-based association analysis, and also performed expression quantitative trait loci and network analysis. In genome-wide association studies, no single nucleotide polymorphism (SNP) passed the genome-wide significance threshold. In gene-based association analysis, six genes (LCMT1, SCRN2, LRRC46, MRPL10, SP6, and OSBPL7) were significantly associated with Aβ standardised uptake value ratio in the brain. The three most significant SNPs (rs4787307, rs9903904, and rs11079797) on these genes are associated with the regulation of the LCMT1, OSBPL7, and SCRN2 genes, respectively. These SNPs are involved in decreasing hippocampal volume and cognitive scores by mediating Aβ uptake. The 19 enriched gene sets identified by pathway analysis included axon and chemokine activity. Our findings suggest novel susceptibility genes associated with the uptake of Aβ, which in turn leads to worse clinical outcomes. Our findings might lead to the discovery of new AD treatment targets.
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Affiliation(s)
- Bo-Hyun Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - HyunWoo Lee
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hongki Ham
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Hee Jin Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hyemin Jang
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Neurology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jun Pyo Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yu Hyun Park
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Mansu Kim
- Artificial Intelligence Graduate School, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
| | - Sang Won Seo
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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15
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Kim HR, Jung SH, Kim B, Kim J, Jang H, Kim JP, Kim SY, Na DL, Kim HJ, Nho K, Won HH, Seo SW. Identifying genetic variants for amyloid β in subcortical vascular cognitive impairment. Front Aging Neurosci 2023; 15:1160536. [PMID: 37143691 PMCID: PMC10151714 DOI: 10.3389/fnagi.2023.1160536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 03/31/2023] [Indexed: 05/06/2023] Open
Abstract
Background The genetic basis of amyloid β (Aβ) deposition in subcortical vascular cognitive impairment (SVCI) is still unknown. Here, we investigated genetic variants involved in Aβ deposition in patients with SVCI. Methods We recruited a total of 110 patients with SVCI and 424 patients with Alzheimer's disease-related cognitive impairment (ADCI), who underwent Aβ positron emission tomography and genetic testing. Using candidate AD-associated single nucleotide polymorphisms (SNPs) that were previously identified, we investigated Aβ-associated SNPs that were shared or distinct between patients with SVCI and those with ADCI. Replication analyses were performed using the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study and Rush Memory and Aging Project cohorts (ROS/MAP). Results We identified a novel SNP, rs4732728, which showed distinct associations with Aβ positivity in patients with SVCI (P interaction = 1.49 × 10-5); rs4732728 was associated with increased Aβ positivity in SVCI but decreased Aβ positivity in ADCI. This pattern was also observed in ADNI and ROS/MAP cohorts. Prediction performance for Aβ positivity in patients with SVCI increased (area under the receiver operating characteristic curve = 0.780; 95% confidence interval = 0.757-0.803) when rs4732728 was included. Cis-expression quantitative trait loci analysis demonstrated that rs4732728 was associated with EPHX2 expression in the brain (normalized effect size = -0.182, P = 0.005). Conclusion The novel genetic variants associated with EPHX2 showed a distinct effect on Aβ deposition between SVCI and ADCI. This finding may provide a potential pre-screening marker for Aβ positivity and a candidate therapeutic target for SVCI.
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Affiliation(s)
- Hang-Rai Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Sang-Hyuk Jung
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Beomsu Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Jaeho Kim
- Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, United States
| | - So Yeon Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
- Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea
- Department of Artificial Intelligence, Ajou University, Suwon, Republic of Korea
- Department of Software and Computer Engineering, Ajou University, Suwon, Republic of Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Cell and Gene Therapy Institute, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Hong-Hee Won
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
- Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Intelligent Precision Healthcare Convergence, Seoul, Republic of Korea
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16
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Atay LO, Saka E, Akdemir UO, Yetim E, Balcı E, Arsava EM, Topcuoglu MA. Hybrid PET/MRI with Flutemetamol and FDG in Alzheimer's Disease Clinical Continuum. Curr Alzheimer Res 2023; 20:481-495. [PMID: 38050727 DOI: 10.2174/0115672050243131230925034334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 07/26/2023] [Accepted: 08/17/2023] [Indexed: 12/06/2023]
Abstract
AIMS We aimed to investigate the interaction between β -amyloid (Aβ) accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes in the Alzheimer's disease (AD) clinical continuum. BACKGROUND Utility of positron emission tomography (PET) / magnetic resonance imaging (MRI) hybrid imaging for diagnostic categorization of the AD clinical continuum including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI) and Alzheimer's disease dementia (ADD) has not been fully crystallized. OBJECTIVE To evaluate the interaction between Aβ accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes such as cortex thickness or cerebral white matter disease burden and to detect the discriminative yields of these imaging modalities in the AD clinical continuum. METHODS Fifty patients (20 women and 30 men; median age: 64 years) with clinical SCD (n=11), aMCI (n=17) and ADD (n=22) underwent PET/MRI with [18F]-fluoro-D-glucose (FDG) and [18F]- Flutemetamol in addition to cerebral blood flow (CBF) and quantitative structural imaging along with detailed cognitive assessment. RESULTS High Aβ deposition (increased temporal [18F]-Flutemetamol standardized uptake value ratio (SUVr) and centiloid score), low glucose metabolism (decreased temporal lobe and posterior cingulate [18F]-FDG SUVr), low parietal CBF and right hemispheric cortical thickness were independent predictors of low cognitive test performance. CONCLUSION Integrated use of structural, metabolic, molecular (Aβ) and perfusion (CBF) parameters contribute to the discrimination of SCD, aMCI, and ADD.
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Affiliation(s)
- Lutfiye Ozlem Atay
- Department of Nuclear Medicine, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - Esen Saka
- Department of Neurology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Umit Ozgur Akdemir
- Department of Nuclear Medicine, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - Ezgi Yetim
- Department of Neurology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Erdem Balcı
- Department of Nuclear Medicine, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - Ethem Murat Arsava
- Department of Neurology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
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17
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White Matter Lesions Predominantly Located in Deep White Matter Represent Embolic Etiology Rather Than Small Vessel Disease. Dement Neurocogn Disord 2023; 22:28-42. [PMID: 36814699 PMCID: PMC9939570 DOI: 10.12779/dnd.2023.22.1.28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 01/15/2023] [Accepted: 01/28/2023] [Indexed: 02/17/2023] Open
Abstract
Background and Purpose We investigated the correlation between the deep distribution of white matter hyperintensity (WMH) (dWMH: WMH in deep and corticomedullary areas, with minimal periventricular WMH) and a positive agitated saline contrast echocardiography result. Methods We retrospectively recruited participants with comprehensive dementia evaluations, an agitated saline study, and brain imaging. The participants were classified into two groups according to WMH-distributions: dWMH and dpWMH (mainly periventricular WMH with or without deep WMH.) We hypothesized that dWMH is more likely associated with embolism, whereas dpWMH is associated with small-vessel diseases. We compared the clinical characteristics, WMH-distributions, and positive rate of agitated saline studies between the two groups. Results Among 90 participants, 27 and 12 met the dWMH and dpWMH criteria, respectively. The dWMH-group was younger (62.2±7.5 vs. 78.9±7.3, p<0.001) and had a lower prevalence of hypertension (29.6% vs. 75%, p=0.008), diabetes mellitus (3.7% vs. 25%, p=0.043), and hyperlipidemia (33.3% vs. 83.3%, p=0.043) than the dpWMH-group. Regarding deep white matter lesions, the number of small lesions (<3 mm) was higher in the dWMH-group(10.9±9.7) than in the dpWMH-group (3.1±6.4) (p=0.008), and WMH was predominantly distributed in the border-zones and corticomedullary areas. Most importantly, the positive agitated saline study rate was higher in the dWMH-group than in the dpWMH-group (81.5% vs. 33.3%, p=0.003). Conclusions The dWMH-group with younger participants had fewer cardiovascular risk factors, showed more border-zone-distributions, and had a higher agitated saline test positivity rate than the dpWMH-group, indicating that corticomedullary or deep WMH-distribution with minimal periventricular WMH suggests embolic etiologies.
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18
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Cerebrovascular damage in subjective cognitive decline: A systematic review and meta-analysis. Ageing Res Rev 2022; 82:101757. [PMID: 36240992 DOI: 10.1016/j.arr.2022.101757] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 10/05/2022] [Accepted: 10/09/2022] [Indexed: 01/31/2023]
Abstract
BACKGROUND Subjective cognitive decline (SCD) has been postulated as an early marker of Alzheimer's Disease (AD) but it can also be associated to other non-AD pathologies such as Vascular Dementia (VaD). Nevertheless, there is scarce data about SCD as a potential harbinger of cerebrovascular pathology. Thus, we conducted a systematic review and meta-analysis on the association between SCD and cerebrovascular damage measured by neuroimaging markers. METHOD This study was performed following the PRISMA guidelines. The search was conducted in 3 databases (PubMed, Scopus and Web of Science) from origin to December 8th, 2021. Primary studies including cognitively unimpaired adults with SCD and neuroimaging markers of cerebrovascular damage (i.e., white matter signal abnormalities, WMSA) were selected. Qualitative synthesis and meta-analysis of studies with a case-control design was performed. RESULTS Of 241 articles identified, 21 research articles were selected. Eight case-control studies were included for the meta-analysis. A significant overall effect-size was observed for the mean WMSA burden in SCD relative to controls, where the WMSA burden was higher in SCD. CONCLUSION Our findings show the potential usefulness of SCD as a harbinger of cerebrovascular disease in cognitively healthy individuals. Further research is needed in order to elucidate the role of SCD as a preclinical marker of vascular cognitive impairment.
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Kim SE, Kim HJ, Jang H, Weiner MW, DeCarli C, Na DL, Seo SW. Interaction between Alzheimer's Disease and Cerebral Small Vessel Disease: A Review Focused on Neuroimaging Markers. Int J Mol Sci 2022; 23:10490. [PMID: 36142419 PMCID: PMC9499680 DOI: 10.3390/ijms231810490] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/07/2022] [Accepted: 09/07/2022] [Indexed: 11/26/2022] Open
Abstract
Alzheimer's disease (AD) is characterized by the presence of β-amyloid (Aβ) and tau, and subcortical vascular cognitive impairment (SVCI) is characterized by cerebral small vessel disease (CSVD). They are the most common causes of cognitive impairment in the elderly population. Concurrent CSVD burden is more commonly observed in AD-type dementia than in other neurodegenerative diseases. Recent developments in Aβ and tau positron emission tomography (PET) have enabled the investigation of the relationship between AD biomarkers and CSVD in vivo. In this review, we focus on the interaction between AD and CSVD markers and the clinical effects of these two markers based on molecular imaging studies. First, we cover the frequency of AD imaging markers, including Aβ and tau, in patients with SVCI. Second, we discuss the relationship between AD and CSVD markers and the potential distinct pathobiology of AD markers in SVCI compared to AD-type dementia. Next, we discuss the clinical effects of AD and CSVD markers in SVCI, and hemorrhagic markers in cerebral amyloid angiopathy. Finally, this review provides both the current challenges and future perspectives for SVCI.
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Affiliation(s)
- Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan 48108, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Michael W. Weiner
- Center for Imaging of Neurodegenerative Diseases, University of California, San Francisco, CA 94121, USA
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA 95616, USA
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul 06355, Korea
- Stem Cell and Regenerative Medicine Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul 06355, Korea
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul 06351, Korea
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Doi T, Nakakubo S, Tsutsumimoto K, Kurita S, Kiuchi Y, Nishimoto K, Shimada H. The association of white matter hyperintensities with motoric cognitive risk syndrome. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2022; 3:100150. [PMID: 36324398 PMCID: PMC9616382 DOI: 10.1016/j.cccb.2022.100150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/06/2022] [Accepted: 07/12/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND The motoric cognitive risk syndrome (MCR) was characterized by slow gait and subjective cognitive complaints. MCR was associated with brain structural changes. However, the association between white matter hyperintensities (WMH) and MCR was unclear and the aim of this study was to examine this association. MATERIAL AND METHODS The study participants were 1227 older adults (mean age: 72.0 ± 6.0 yrs, women: 52.6%). We collected magnetic resonance imaging (MRI) data to assess WMH. To assess MCR, data on gait speed and subjective cognitive complaints were collected. Demographical and medical data was collected as covariates. RESULTS Among participants, the proportion of MCR was 5.0% (n = 61) and severe WMH was 16.8% (n = 206). From logistic regression analysis, severe WMH associated with MCR even when adjusted for covariates (odds ratio 2.18 [95% confidential interval 1.15-4.16], p = 0.017). This association was observed in subgroups stratified by the participants' characteristics: higher age, not having fall history, not obesity, not being physical inactivity and not having depressive symptom. CONCLUSIONS Our findings revealed that vascular pathophysiological changes in the brain were associated with MCR. The association was pronounced by several factors. Further evaluation was required to clarify pathophysiology of MCR.
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Affiliation(s)
- Takehiko Doi
- Corresponding author at: Department of Preventive Gerontology, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, 7-430, Morioka, Obu, Aichi 474-8511, Japan.
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Hwangbo S, Kim YJ, Park YH, Kim HJ, Na DL, Jang H, Seo SW. Relationships between educational attainment, hypertension, and amyloid negative subcortical vascular dementia: The brain-battering hypothesis. Front Neurosci 2022; 16:934149. [PMID: 35992915 PMCID: PMC9388911 DOI: 10.3389/fnins.2022.934149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/08/2022] [Indexed: 11/20/2022] Open
Abstract
Purpose Many epidemiological studies suggest that lower education levels and vascular risk factors increase the likelihood of developing Alzheimer's disease dementia (ADD) and subcortical vascular dementia (SVaD). However, whether the brain-battering hypothesis can explain the relationship between education levels and the clinical diagnosis of dementia remains controversial. The objective of this study was to investigate whether vascular risk factors mediate the association between education level and the diagnosis of amyloid-beta positive (Aβ+) ADD and amyloid-beta negative (Aβ-) SVaD. Methods We analyzed 376 participants with Aβ normal cognition (Aβ- NC), 481 with Aβ+ ADD, and 102 with Aβ- SVaD. To investigate the association of education level and vascular risk factors with these diagnoses, multivariable logistic regression analysis was used, with age, sex, and APOE ε4 carrier status used as covariates. Path analysis was performed to investigate the mediation effects of hypertension on the diagnosis of Aβ- SVaD. Results The Aβ- SVaD group (7.9 ± 5.1 years) had lower education levels than did the Aβ- NC (11.8 ± 4.8 years) and Aβ+ ADD (11.2 ± 4.9 years) groups. The frequencies of hypertension and diabetes mellitus were higher in the Aβ- SVaD group (78.4 and 32.4%, respectively) than in the Aβ- NC (44.4 and 20.8%) and Aβ+ ADD (41.8 and 15.8%, respectively) groups. Increased education level was associated with a lower risk of Aβ- SVaD [odds ratio (OR) 0.866, 95% confidence interval (CI), 0.824–0.911], but not Aβ+ ADD (OR 0.971, 95% CI 0.940–1.003). The frequency of hypertension was associated with a higher risk of developing Aβ- SVaD (OR 3.373, 95% CI, 1.908–5.961), but not Aβ+ ADD (OR 0.884, 95% CI, 0.653–1.196). In the path analysis, the presence of hypertension partially mediated the association between education level and the diagnosis of Aβ- SVaD. Conclusion Our findings revealed that education level might influence the development of Aβ- SVaD through the brain-battering hypothesis. Furthermore, our findings suggest that suitable strategies, such as educational attainment and prevention of hypertension, are needed for the prevention of Aβ- SVaD.
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Affiliation(s)
- Song Hwangbo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Young Ju Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Yu Hyun Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, South Korea
- Stem Cell and Regenerative Medicine Institute, Samsung Medical Center, Seoul, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- *Correspondence: Hyemin Jang
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, South Korea
- Samsung Alzheimer Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University School of Medicine, Suwon, South Korea
- Sang Won Seo ;
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Kang SH, Kim JH, Chang Y, Cheon BK, Choe YS, Jang H, Kim HJ, Koh SB, Na DL, Kim K, Seo SW. Independent effect of body mass index variation on amyloid-β positivity. Front Aging Neurosci 2022; 14:924550. [PMID: 35936766 PMCID: PMC9354132 DOI: 10.3389/fnagi.2022.924550] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/04/2022] [Indexed: 11/16/2022] Open
Abstract
Objectives The relationship of body mass index (BMI) changes and variability with amyloid-β (Aβ) deposition remained unclear, although there were growing evidence that BMI is associated with the risk of developing cognitive impairment or AD dementia. To determine whether BMI changes and BMI variability affected Aβ positivity, we investigated the association of BMI changes and BMI variability with Aβ positivity, as assessed by PET in a non-demented population. Methods We retrospectively recruited 1,035 non-demented participants ≥50 years of age who underwent Aβ PET and had at least three BMI measurements in the memory clinic at Samsung Medical Center. To investigate the association between BMI change and variability with Aβ deposition, we performed multivariable logistic regression. Further distinctive underlying features of BMI subgroups were examined by employing a cluster analysis model. Results Decreased (odds ratio [OR] = 1.68, 95% confidence interval [CI] 1.16–2.42) or increased BMI (OR = 1.60, 95% CI 1.11–2.32) was associated with a greater risk of Aβ positivity after controlling for age, sex, APOE e4 genotype, years of education, hypertension, diabetes, baseline BMI, and BMI variability. A greater BMI variability (OR = 1.73, 95% CI 1.07–2.80) was associated with a greater risk of Aβ positivity after controlling for age, sex, APOE e4 genotype, years of education, hypertension, diabetes, baseline BMI, and BMI change. We also identified BMI subgroups showing a greater risk of Aβ positivity. Conclusion Our findings suggest that participants with BMI change, especially those with greater BMI variability, are more vulnerable to Aβ deposition regardless of baseline BMI. Furthermore, our results may contribute to the design of strategies to prevent Aβ deposition with respect to weight control.
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Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Jong Hyuk Kim
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Yoosoo Chang
- Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea
| | - Bo Kyoung Cheon
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Yeong Sim Choe
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences & Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Kyunga Kim
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea
- Department of Data Convergence and Future Medicine, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- *Correspondence: Kyunga Kim,
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences & Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Samsung Alzheimer Research Center, Center for Clinical Epidemiology Medical Center, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Sang Won Seo,
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Kim HJ, Oh JS, Lim JS, Lee S, Jo S, Chung EN, Shim WH, Oh M, Kim JS, Roh JH, Lee JH. The impact of subthreshold levels of amyloid deposition on conversion to dementia in patients with amyloid-negative amnestic mild cognitive impairment. Alzheimers Res Ther 2022; 14:93. [PMID: 35821150 PMCID: PMC9277922 DOI: 10.1186/s13195-022-01035-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 06/25/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND About 40-50% of patients with amnestic mild cognitive impairment (MCI) are found to have no significant Alzheimer's pathology based on amyloid PET positivity. Notably, conversion to dementia in this population is known to occur much less often than in amyloid-positive MCI. However, the relationship between MCI and brain amyloid deposition remains largely unknown. Therefore, we investigated the influence of subthreshold levels of amyloid deposition on conversion to dementia in amnestic MCI patients with negative amyloid PET scans. METHODS This study was a retrospective cohort study of patients with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center. All participants underwent detailed neuropsychological testing, brain magnetic resonance imaging, and [18F]-florbetaben (FBB) positron emission tomography scan (PET). Conversion to dementia was determined by a neurologist based on a clinical interview with a detailed neuropsychological test or a decline in the Korean version of the Mini-Mental State Examination score of more than 4 points per year combined with impaired activities of daily living. Regional cortical amyloid levels were calculated, and a receiver operating characteristic (ROC) curve for conversion to dementia was obtained. To increase the reliability of the results of the study, we analyzed the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset together. RESULTS During the follow-up period, 36% (39/107) of patients converted to dementia from amnestic MCI. The dementia converter group displayed increased standardized uptake value ratio (SUVR) values of FBB on PET in the bilateral temporal, parietal, posterior cingulate, occipital, and left precuneus cortices as well as increased global SUVR. Among volume of interests, the left parietal SUVR predicted conversion to dementia with the highest accuracy in the ROC analysis (area under the curve [AUC] = 0.762, P < 0.001). The combination of precuneus, parietal cortex, and FBB composite SUVRs also showed a higher accuracy in predicting conversion to dementia than other models (AUC = 0.763). Of the results of ADNI data, the SUVR of the left precuneus SUVR showed the highest AUC (AUC = 0.596, P = 0.006). CONCLUSION Our findings suggest that subthreshold amyloid levels may contribute to conversion to dementia in patients with amyloid-negative amnestic MCI.
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Affiliation(s)
- Hyung-Ji Kim
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
- Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, South Korea
| | - Jungsu S Oh
- Department of Nuclear Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Jae-Sung Lim
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Sunju Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Sungyang Jo
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - E-Nae Chung
- Health Innovation Bigdata Center, Asan Institute for Lifesciences, Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Woo-Hyun Shim
- Health Innovation Bigdata Center, Asan Institute for Lifesciences, Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
- Asan Institute for Life Sciences, Asan Medical Center, Seoul, South Korea
| | - Minyoung Oh
- Department of Nuclear Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Jae Seung Kim
- Department of Nuclear Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Jee Hoon Roh
- Neuroscience Institute, Korea University College of Medicine and School of Medicine, Seoul, South Korea
| | - Jae-Hong Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea.
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Azevedo R, Jacquemin C, Villain N, Fenaille F, Lamari F, Becher F. Mass Spectrometry for Neurobiomarker Discovery: The Relevance of Post-Translational Modifications. Cells 2022; 11:1279. [PMID: 35455959 PMCID: PMC9031030 DOI: 10.3390/cells11081279] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 04/01/2022] [Accepted: 04/06/2022] [Indexed: 12/10/2022] Open
Abstract
Neurodegenerative diseases are incurable, heterogeneous, and age-dependent disorders that challenge modern medicine. A deeper understanding of the pathogenesis underlying neurodegenerative diseases is necessary to solve the unmet need for new diagnostic biomarkers and disease-modifying therapy and reduce these diseases' burden. Specifically, post-translational modifications (PTMs) play a significant role in neurodegeneration. Due to its proximity to the brain parenchyma, cerebrospinal fluid (CSF) has long been used as an indirect way to measure changes in the brain. Mass spectrometry (MS) analysis in neurodegenerative diseases focusing on PTMs and in the context of biomarker discovery has improved and opened venues for analyzing more complex matrices such as brain tissue and blood. Notably, phosphorylated tau protein, truncated α-synuclein, APP and TDP-43, and many other modifications were extensively characterized by MS. Great potential is underlying specific pathological PTM-signatures for clinical application. This review focuses on PTM-modified proteins involved in neurodegenerative diseases and highlights the most important and recent breakthroughs in MS-based biomarker discovery.
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Affiliation(s)
- Rita Azevedo
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (C.J.); (N.V.); (F.F.)
| | - Chloé Jacquemin
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (C.J.); (N.V.); (F.F.)
| | - Nicolas Villain
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (C.J.); (N.V.); (F.F.)
- Institut du Cerveau (ICM), Pitié-Salpêtrière Hospital, 75013 Paris, France
- Department of Neurology, Institute of Memory and Alzheimer’s Disease, Pitié-Salpêtrière Hospital, AP-HP Sorbonne Université, CEDEX 13, 75651 Paris, France
| | - François Fenaille
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (C.J.); (N.V.); (F.F.)
| | - Foudil Lamari
- Department of Metabolic Biochemistry (AP-HP Sorbonne), Pitié-Salpêtrière Hospital, CEDEX 13, 75651 Paris, France;
| | - François Becher
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (C.J.); (N.V.); (F.F.)
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Kang SH, Lee J, Koh SB. Constipation is Associated With Mild Cognitive Impairment in Patients With de novo Parkinson's Disease. J Mov Disord 2021; 15:38-42. [PMID: 34781630 PMCID: PMC8820884 DOI: 10.14802/jmd.21074] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 08/22/2021] [Indexed: 11/24/2022] Open
Abstract
Objective The association between gastrointestinal (GI) symptoms and cognitive profile in patients with Parkinson's disease (PD) at diagnosis remains unclear, although GI symptoms and cognitive impairment are highly prevalent in patients with PD. We investigated the relationship between constipation and cognitive status. We also aimed to identify the correlation between constipation and each neuropsychological dysfunction. Methods A total of 427 patients with de novo Parkinson's disease with normal cognition (PD-NC, n = 170) and Parkinson's disease with mild cognitive impairment (PD-MCI, n = 257) at Korea University Guro Hospital in Seoul, Korea were included. All patients underwent comprehensive neuropsychological tests and completed the Non-Motor Symptoms Scale (NMSS). The frequency and severity of constipation were assessed using the NMSS GI symptoms scale, we used logistic regression analysis and partial correlation analysis to determine the associations between constipation score, MCI, and each neuropsychological dysfunction. Results Frequent and severe constipation was associated with MCI in patients with PD at diagnosis regardless of disease severity. Specifically, constipation was related to poor performance in frontal-executive and visuospatial functions after controlling for age and sex. Conclusion Our findings may provide an understanding of constipation as a marker associated with cognitive impairment in individuals with PD. Therefore, the evaluation of cognitive function is warranted in PD patients with constipation, while further studies are necessary to investigate the detailed mechanism of our results.
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Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Jungyeun Lee
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
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Kang SH, Woo SY, Kim S, Kim JP, Jang H, Koh SB, Na DL, Kim HJ, Seo SW. Independent effects of amyloid and vascular markers on long-term functional outcomes: An 8-year longitudinal study of subcortical vascular cognitive impairment. Eur J Neurol 2021; 29:413-421. [PMID: 34716964 DOI: 10.1111/ene.15159] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 09/11/2021] [Accepted: 09/18/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND PURPOSE Subcortical vascular cognitive impairment (SVCI) is characterized by the presence of cerebral small vessel disease (CSVD) markers. Some SVCI patients also show Alzheimer's disease and cerebral amyloid angiopathy markers. However, the effects of these imaging markers on long-term clinical outcomes have not yet been established. The present study, therefore, aimed to determine how these imaging markers influence functional disability and/or mortality. METHODS We recruited 194 participants with SVCI from the memory clinic and followed them up. All participants underwent brain magnetic resonance imaging at baseline, and 177 (91.2%) participants underwent beta-amyloid (Aβ) positron emission tomography. We examined the occurrence of ischemic or hemorrhagic strokes. We also evaluated functional disability and mortality using the modified Rankin scale. To determine the effects of imaging markers on functional disability or mortality, we used Fine and Gray competing regression or Cox regression analysis. RESULTS During a 8.6-year follow-up period, 46 of 194 patients (23.7%) experienced a stroke, 110 patients (56.7%) developed functional disabilities and 75 (38.6%) died. Aβ positivity (subdistribution hazard ratio [SHR] = 2.73), greater white matter hyperintensity (WMH) volume (SHR = 3.11) and ≥3 microbleeds (SHR = 2.29) at baseline were independent predictors of functional disability regardless of the occurrence of stroke. Greater WMH volume (hazard ratio = 2.07) was an independent predictor of mortality. CONCLUSIONS Our findings suggest that diverse imaging markers may predict long-term functional disability and mortality in patients with SVCI, which in turn may provide clinicians with a more insightful understanding of the long-term outcomes of SVCI.
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Affiliation(s)
- Sung Hoon Kang
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea.,Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Sook-Young Woo
- Statistics and Data Center, Samsung Medical Center, Seoul, South Korea
| | - Seonwoo Kim
- Statistics and Data Center, Samsung Medical Center, Seoul, South Korea
| | - Jun Pyo Kim
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Hyemin Jang
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Duk L Na
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Hee Jin Kim
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Sang Won Seo
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea.,Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea.,Samsung Alzheimer Research Center and Center for Clinical Epidemiology Medical Center, Seoul, South Korea.,Department of Intelligent Precision Healthcare Convergence, SAIHST, Sungkyunkwan University, Suwon, South Korea
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