APOE ε4 보인자의 지방 관련 체성분 수치 증가에 따른 휴지기 신경망 간 기능적 연결성 감소: 아밀로이드 베타 단백질 침착 기억성 경도인지장애 환자를 대상으로
Higher Fat-Related Body Composition Measurement and Lower Resting-State Inter-Network Functional Connectivity of APOE ε4 Carrier in Mild Cognitive Impairment Patients With Aβ Deposition
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Objective: We aimed to evaluate the impact of interaction between APOE ε4 carrier status and body composition measurements on intra- and inter-regional functional connectivity (FC) in mild cognitive impairment (MCI) patients with Aβ deposition. Methods: MCI patients with and without APOE ε4 allele (carrier, n=86; non-carrier, n=95) underwent neuropsychological battery, resting-state functional magnetic resonance imaging scans, positron emission tomography scans with [18F] flutemetamol, and bioelectrical impedance analysis for measuring body composition. We employed a priori defined regions of interest to investigate the intra- and inter-network FC profiles of default mode network (DMN), central executive network (CEN), and salience network (SN). Results: There was a significant interaction of APOE ε4 carrier status with body fat mass index, visceral fat area, and waist-hip circumference ratio for inter-network FC between DMN and CEN, contributing higher fat-related body composition measurements in the APOE ε4 carrier with lower DMN-CEN FC. Conclusion: The present results highlight the detrimental effect of APOE ε4 carrier status on the associations between the fat-related body composition measurements and FC in the MCI patients with Aβ accumulation.
Abstract
Objective: We aimed to evaluate the impact of interaction between APOE ε4 carrier status and body composition measurements on intra- and inter-regional functional connectivity (FC) in mild cognitive impairment (MCI) patients with Aβ deposition. Methods: MCI patients with and without APOE ε4 allele (carrier, n=86; non-carrier, n=95) underwent neuropsychological battery, resting-state functional magnetic resonance imaging scans, positron emission tomography scans with [18F] flutemetamol, and bioelectrical impedance analysis for measuring body composition. We employed a priori defined regions of interest to investigate the intra- and inter-network FC profiles of default mode network (DMN), central executive network (CEN), and salience network (SN). Results: There was a significant interaction of APOE ε4 carrier status with body fat mass index, visceral fat area, and waist-hip circumference ratio for inter-network FC between DMN and CEN, contributing higher fat-related body composition measurements in the APOE ε4 carrier with lower DMN-CEN FC. Conclusion: The present results highlight the detrimental effect of APOE ε4 carrier status on the associations between the fat-related body composition measurements and FC in the MCI patients with Aβ accumulation.
참고문헌 (47)
- Jack CR Jr, "NIA-AA research framework : toward a biological definition of Alzheimer’s disease", Alzheimers Dement, 14, pp.535~562 (2018)
- Menon V, "Large-scale brain networks and psychopathology : a unifying triple network model", Trends Cogn Sci, 15, pp.483~506 (2011)
- Hutchison RM, "Dynamic functional connectivity: promise, issues, and interpretations", Neuroimage, 80, pp.360~378 (2013)
- Brier MR, "Loss of intranetwork and internetwork resting state functional connections with Alzheimer’s disease progression", J Neurosci, 32, pp.8890~8899 (2012)
- Eyler LT, "Resting state abnormalities of the default mode network in mild cognitive impairment : a systematic review and meta-analysis", J Alzheimers Dis, 70, pp.107~120 (2019)
- Silva MVF, "Alzheimer’s disease : risk factors and potentially protective measures", J Biomed Sci, 26, pp.33~ (2019)
- Gunstad J, "Elevated body mass index is associated with executive dysfunction in otherwise healthy adults", Compr Psychiatry, 48, pp.57~61 (2007)
- Nilsson LG, "Overweight and cognition", Scand J Psychol, 50, pp.660~667 (2009)
- Cournot M, "Relation between body mass index and cognitive function in healthy middle-aged men and women", Neurology, 67, pp.1208~1214 (2006)
- Whitmer RA, "Central obesity and increased risk of dementia more than three decades later", Neurology, 71, pp.1057~1064 (2008)
- Whitmer RA, "Obesity in middle age and future risk of dementia : a 27 year longitudinal population based study", BMJ, 330, pp.1360~ (2005)
- Figley CR, "Effects of body mass index and body fat percent on default mode, executive control, and salience network structure and function", Front Neurosci, 10, pp.234~ (2016)
- Beyer F, "Higher body mass index is associated with reduced posterior default mode connectivity in older adults", Hum Brain Mapp, 38, pp.3502~3515 (2017)
- Corder EH, "Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families", Science, 261, pp.921~923 (1993)
- Sims R, "The multiplex model of the genetics of Alzheimer’s disease", Nat Neurosci, 23, pp.311~322 (2020)
- DeMattos RB, "ApoE and clusterin cooperatively suppress Aβ levels and deposition : evidence that ApoE regulates extracellular Aβ metabolism in vivo", Neuron, 41, pp.193~202 (2004)
- Castellano JM, "Human apoE isoforms differentially regulate brain amyloid-β peptide clearance", Sci Transl Med, 3, pp.8989ra57~ (2011)
- Ng KK, "Functional segregation loss over time is moderated by APOE genotype in healthy elderly", Hum Brain Mapp, 39, pp.2742~2752 (2018)
- Blautzik J, "Relationship between body mass index, ApoE4 status, and PET-based amyloid and neurodegeneration markers in amyloid-positive subjects with normal cognition or mild cognitive impairment", J Alzheimers Dis, 65, pp.781~791 (2018)
- Evans S, "Cognitive and neural signatures of the APOE E4 allele in mid-aged adults", Neurobiol Aging, 35, pp.1615~1623 (2014)
- Lee JH, "Development of the Korean version of the consortium to establish a registry for Alzheimer’s disease assessment packet(CERAD-K) : clinical and neuropsychological assessment batteries", J Gerontol B Psychol Sci Soc Sci, 57, pp.P47~53 (2002)
- Thurfjell L, "Automated quantification of 18F-flutemetamol PET activity for categorizing scans as negative or positive for brain amyloid : concordance with visual image reads", J Nucl Med, 55, pp.1623~1628 (2014)
- Fazekas F, "MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging", AJR Am J Roentgenol, 8, pp.421~426 (1987)
- Li Z, "APOE2 : protective mechanism and therapeutic implications for Alzheimer’s disease", Mol Neurodegener, 15, pp.63~ (2020)
- Chao-Gan Y, "DPARSF : a MATLAB toolbox for"pipeline"data analysis of resting-state fMRI", Front Syst Neurosci, 4, pp.13~ (2010)
- Kang DW, "Distinctive association of the functional connectivity of the posterior cingulate cortex on memory performances in early and late amnestic mild cognitive impairment patients", Front Aging Neurosci, 13, pp.696735~ (2021)
- Zhu DC, "Alzheimer’s disease and amnestic mild cognitive impairment weaken connections within the default-mode network : a multi-modal imaging study", J Alzheimers Dis, 34, pp.969~984 (2013)
- Greicius MD, "Default-mode network activity distinguishes Alzheimer’s disease from healthy aging : evidence from functional MRI", Proc Natl Acad Sci U S A, 101, pp.4637~4642 (2004)
- Weiler M, "Default mode, executive function, and language functional connectivity networks are compromised in mild Alzheimer’s disease", Curr Alzheimer Res, 11, pp.274~282 (2014)
- He X, "Abnormal salience network in normal aging and in amnestic mild cognitive impairment and Alzheimer’s disease", Hum Brain Mapp, 35, pp.3446~3464 (2014)
- Kim M, "Comparison of segmental multifrequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for the assessment of body composition in a community-dwelling older population", Geriatr Gerontol Int, 15, pp.1013~1022 (2015)
- Fang WH, "Accuracy augmentation of body composition measurement by bioelectrical impedance analyzer in elderly population", Medicine(Baltimore), 99, pp.e19103~ (2020)
- Liu CC, "Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy", Nat Rev Neurol, 9, pp.106~118 (2013)
- El-Lebedy D, "Apolipoprotein E gene polymorphism and risk of type 2 diabetes and cardiovascular disease", Cardiovasc Diabetol, 15, pp.12~ (2016)
- Matsuzaki T, "Insulin resistance is associated with the pathology of Alzheimer disease : the Hisayama study", Neurology, 75, pp.764~770 (2010)
- Liao C, "Associations of body composition measurements with serum lipid, glucose and insulin profile : a Chinese twin study", PLoS One, 10, pp.e0140595~ (2015)
- Pietrobelli A, "Establishing body composition in obesity", J Endocrinol Invest, 25, pp.884~892 (2002)
- Jones NS, "The synergistic effects of APOE genotype and obesity on Alzheimer’s disease risk", Int J Mol Sci, 20, pp.63~ (2018)
- Passamonti L, "Neuroinflammation and functional connectivity in Alzheimer’s disease : interactive influences on cognitive performance", J Neurosci, 39, pp.7218~7226 (2019)
- Contreras JA, "Functional connectivity among brain regions affected in Alzheimer’s disease is associated with CSF TNF-α in APOE4 carriers", Neurobiol Aging, 86, pp.112~122 (2020)
- Turner GR, "Prefrontal engagement and reduced default network suppression co-occur and are dynamically coupled in older adults : the default-executive coupling hypothesis of aging", J Cogn Neurosci, 27, pp.2462~2476 (2015)
- 서미혜, "Prevalence of Obesity and Incidence of Obesity-Related Comorbidities in Koreans Based on National Health Insurance Service Health Checkup Data 2006–2015", Journal of Obesity & Metabolic Syndrome, 27(1), pp.46~52 (2018), 대한비만학회
- Obesity: preventing and managing the global epidemic: report of a WHO consultation, "WHO Consultation on Obesity, World Health Organization", World Health Organization, 894~ (2000)
- Sasazuki S, "Body mass index and mortality from all causes and major causes in Japanese : results of a pooled analysis of 7 large-scale cohort studies", J Epidemiol, 21, pp.417~430 (2011)
- Xu W, "Weight loss is a preclinical signal of cerebral amyloid deposition and could predict cognitive impairment in elderly adults", J Alzheimers Dis, 77, pp.449~456 (2020)
- Marwarha G, "β-Amyloid regulates leptin expression and tau phosphorylation through the mTORC1 signaling pathway", J Neurochem, 115, pp.373~384 (2010)
- Elosua R, "Obesity modulates the association among APOE genotype, insulin, and glucose in men", Obes Res, 11, pp.1502~1508 (2003)
