1
|
Lee EH, Kang SH, Shin D, Kim YJ, Zetterberg H, Blennow K, Gonzalez‐Ortiz F, Ashton NJ, Cheon BK, Yoo H, Ham H, Yun J, Kim JP, Kim HJ, Na DL, Jang H, Seo SW. Plasma Alzheimer's disease biomarker variability: Amyloid-independent and amyloid-dependent factors. Alzheimers Dement 2025; 21:e14368. [PMID: 39535473 PMCID: PMC11782842 DOI: 10.1002/alz.14368] [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: 07/09/2024] [Revised: 10/02/2024] [Accepted: 10/03/2024] [Indexed: 11/16/2024]
Abstract
INTRODUCTION We aimed to investigate which factors affect plasma biomarker levels via amyloid beta (Aβ)-independent or Aβ-dependent effects and improve the predictive performance of these biomarkers for Aβ positivity on positron emission tomography (PET). METHODS A total of 2935 participants underwent blood sampling for measurements of plasma Aβ42/40 ratio, phosphorylated tau 217 (p-tau217; ALZpath), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) levels using single-molecule array and Aβ PET. Laboratory findings were collected using a routine blood test battery. RESULTS Aβ-independent factors included hemoglobin and estimated glomerular filtration rate (eGFR) for p-tau217 and hemoglobin, eGFR, and triiodothyronine (T3) for GFAP and NfL. Aβ-dependent factors included apolipoprotein E genotypes, body mass index status for Aβ42/40, p-tau217, GFAP, and NfL. However, these factors exhibited negligible or modest effects on Aβ positivity on PET. DISCUSSION Our findings highlight the importance of accurately interpreting plasma biomarkers for predicting Aβ uptake in real-world settings. HIGHLIGHTS We investigated factor-Alzheimer's disease plasma biomarker associations in a large Korean cohort. Hemoglobin and estimated glomerular filtration rate affect the biomarkers independently of brain amyloid beta (Aβ). Apolipoprotein E genotypes and body mass index status affect the biomarkers dependent on brain Aβ. Addition of Aβ-independent factors shows negligible effect in predicting Aβ positivity. Adjusting for Aβ-dependent factors shows a modest effect in predicting Aβ positivity.
Collapse
|
2
|
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.
Collapse
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.
| |
Collapse
|
3
|
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.
Collapse
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.
| |
Collapse
|
4
|
Kang SH, Choi Y, Chung SJ, Moon SJ, Kim CK, Kim JH, Oh K, Yoon JS, Seo SW, Cho GJ, Koh SB. Fasting glucose variability and risk of dementia in Parkinson's disease: a 9-year longitudinal follow-up study of a nationwide cohort. Front Aging Neurosci 2024; 15:1292524. [PMID: 38235038 PMCID: PMC10791804 DOI: 10.3389/fnagi.2023.1292524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/21/2023] [Indexed: 01/19/2024] Open
Abstract
Background Diabetes is associated with an increased risk of Parkinson's disease dementia (PDD); however, it is unknown whether this association is dependent on continuous hyperglycemia, hypoglycemic events, or glycemic variability. We aimed to investigate the relationship between visit-to-visit fasting glucose variability and PDD development in patients with Parkinson's disease (PD). Methods Using data from the Korean National Health Insurance Service, we examined 9,264 patients aged ≥40 years with de novo Parkinson's disease (PD) who underwent ≥3 health examinations and were followed up until December 2019. Glucose variability was measured using the coefficient of variation, variability independent of the mean, and average real variability. Fine and Gray competing regression analysis was performed to determine the effect of glucose variability on incident PDD. Results During the 9.5-year follow-up period, 1,757 of 9,264 (19.0%) patients developed PDD. Patients with a higher visit-to-visit glucose variability had a higher risk of future PDD. In the multivariable adjusted model, patients with PD in the highest quartile (subdistribution hazard ratio [SHR] = 1.50, 95% CI 1.19 to 1.88), quartile 3 (SHR = 1.29, 95% CI 1.02 to 1.62), and quartile 2 (SHR = 1.30, 95% CI 1.04 to 1.63) were independently associated with a higher risk of PDD than those in the lowest quartile. Conclusion We highlighted the effect of long-term glucose variability on the development of PDD in patients with PD. Furthermore, our findings suggest that preventive measures for constant glucose control may be necessary to prevent PDD.
Collapse
Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Yunjin Choi
- Biomedical Research Institute, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Su Jin Chung
- Department of Neurology, Myongji Hospital, Hanyang University College of Medicine, Goyang, Republic of Korea
| | - Seok-Joo Moon
- Smart Healthcare Center, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Chi Kyung Kim
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Ji Hyun Kim
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Joon Shik Yoon
- Department of Physical Medicine and Rehabilitation, Korea University Guro Hospital, 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
| | - Geum Joon Cho
- Department of Obstetrics and Gynecology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| |
Collapse
|
5
|
Kang SH, Yoo H, Cheon BK, Kim JP, Jang H, Kim HJ, Kang M, Oh K, Koh SB, Na DL, Chang Y, Seo SW. Sex-specific relationship between non-alcoholic fatty liver disease and amyloid-β in cognitively unimpaired individuals. Front Aging Neurosci 2023; 15:1277392. [PMID: 37901792 PMCID: PMC10603302 DOI: 10.3389/fnagi.2023.1277392] [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: 08/14/2023] [Accepted: 09/25/2023] [Indexed: 10/31/2023] Open
Abstract
Background Non-alcoholic fatty liver disease (NAFLD) is known to be associated with a high risk of clinically diagnosed Alzheimer's disease (AD). Additionally, the prevalence of NAFLD and AD is higher in elderly females than in males. However, a sex-specific association between NAFLD and amyloid-beta (Aβ) deposition remains unclear. Therefore, we investigated the sex-specific relationship between NAFLD and Aβ deposition in a large-sized cohort of cognitively unimpaired (CU) individuals. Methods We enrolled 673 (410 [60.9%] females and 263 [39.1%] males) CU individuals aged ≥45 years who underwent Aβ positron emission tomography (PET). The presence of NAFLD, assessed using the hepatic steatosis index, and the severity of NAFLD, assessed using the Fibrosis-4 index, were considered predictors. Aβ deposition on PET was considered as an outcome. Results Females had a higher frequency of NAFLD than males (48 and 23.2%, p < 0.001). Among females, the presence of NAFLD (β = 0.216, p < 0.001) was predictive of increased Aβ deposition, whereas among males, the presence of NAFLD (β = 0.191, p = 0.064) was not associated with Aβ deposition. Among females, the presence of NAFLD with low (β = 0.254, p = 0.039), intermediate (β = 0.201, p = 0.006), and high fibrosis (β = 0.257, p = 0.027) was predictive of increased Aβ deposition. Aβ deposition also increased as the severity of NAFLD increased in females (p for trend = 0.001). Conclusion We highlight the marked influence of NAFLD and its severity on the risk of Aβ deposition in relation to sex. Furthermore, our findings suggest that sex-specific strategies regarding the management of NAFLD are necessary for the prevention of Aβ deposition.
Collapse
Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Heejin Yoo
- 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
| | - Bo Kyoung Cheon
- 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
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Mira Kang
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, 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
| | - 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 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
| |
Collapse
|
6
|
Kang SH, Lee KH, Chang Y, Choe YS, Kim JP, Jang H, Shin HY, Kim HJ, Koh SB, Na DL, Seo SW, Kang M. Gender-specific relationship between thigh muscle and fat mass and brain amyloid-β positivity. Alzheimers Res Ther 2022; 14:145. [PMID: 36195949 PMCID: PMC9531420 DOI: 10.1186/s13195-022-01086-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 09/21/2022] [Indexed: 12/02/2022]
Abstract
BACKGROUND The relationship of specific body composition in the thighs and brain amyloid-beta (Aβ) deposition remained unclear, although there were growing evidence that higher muscle and fat mass in thighs had a protective effect against cardiometabolic syndromes. To determine whether muscle mass and fat mass in the thighs affected amyloid-beta (Aβ) positivity differently in relation to gender, we investigated the association of muscle mass and fat mass with Aβ positivity using positron emission tomography (PET) in individuals without dementia. METHODS We recruited 240 participants (134 [55.8%] males, 106 [44.2%] females) without dementia ≥45 years of age who underwent Aβ PET, bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DEXA) scans of the hip in the health promotion center at Samsung Medical Center in Seoul, Korea. Lower extremity skeletal muscle mass index (LASMI) was measured using BIA, and gluteofemoral fat percentage (GFFP) was estimated using DEXA scans of the hip. We investigated the associations of LASMI and GFFP with Aβ positivity using logistic regression analyses after controlling for age, APOE4 genotype, and cognitive stage. RESULTS Higher muscle mass in the thighs, measured as LASMI (odds ratio [OR]=0.27, 95% confidence interval [CI] 0.08 to 0.84, p=0.031) was associated with a lesser risk of Aβ positivity in only females. Higher fat mass in the thighs, measured as GFFP (OR=0.84, 95% CI 0.73 to 0.95, p=0.008) was associated with a lesser risk of Aβ positivity in only males. However, the association between LAMSI (p for interaction= 0.810), GFFP (p for interaction= 0.075) and Aβ positivity did not significantly differ by gender. Furthermore, LAMSI only negatively correlated with centiloid (CL) values in females (r=-0.205, p=0.037), and GFFP only negatively correlated with CL values only in males (r=-0.253, p=0.004). CONCLUSIONS Our findings highlight the importance of recognizing that gender differences exist with respect to the specific body composition to potentially protect against Aβ deposition. Therefore, our results may help in designing gender-specific strategies for controlling body composition to prevent Aβ deposition.
Collapse
Affiliation(s)
- Sung Hoon Kang
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea ,grid.222754.40000 0001 0840 2678Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Kyung Hyun Lee
- grid.264381.a0000 0001 2181 989XDepartment of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Yoosoo Chang
- grid.264381.a0000 0001 2181 989XCenter for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Yeong Sim Choe
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea ,grid.264381.a0000 0001 2181 989XDepartment of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Jun Pyo Kim
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hyemin Jang
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hee Young Shin
- grid.264381.a0000 0001 2181 989XCenter for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hee Jin Kim
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Seong-Beom Koh
- grid.222754.40000 0001 0840 2678Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Duk L. Na
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sang Won Seo
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea ,grid.264381.a0000 0001 2181 989XDepartment of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea ,grid.264381.a0000 0001 2181 989XDepartment of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea ,grid.264381.a0000 0001 2181 989XDepartment of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Mira Kang
- grid.264381.a0000 0001 2181 989XDepartment of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea ,grid.264381.a0000 0001 2181 989XCenter for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea ,grid.264381.a0000 0001 2181 989XDigital Innovation Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| |
Collapse
|