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Charisis S, Short MI, Bernal R, Kautz TF, Treviño HA, Mathews J, Dediós AGV, Muhammad JAS, Luckey AM, Aslam A, Himali JJ, Shipp EL, Habes M, Beiser AS, DeCarli C, Scarmeas N, Ramachandran VS, Seshadri S, Maillard P, Satizabal CL. Leptin bioavailability and markers of brain atrophy and vascular injury in the middle age. Alzheimers Dement 2024. [PMID: 39132759 DOI: 10.1002/alz.13879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/01/2024] [Accepted: 03/24/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION We investigated the associations of leptin markers with cognitive function and magnetic resonance imaging (MRI) measures of brain atrophy and vascular injury in healthy middle-aged adults. METHODS We included 2262 cognitively healthy participants from the Framingham Heart Study with neuropsychological evaluation; of these, 2028 also had available brain MRI. Concentrations of leptin, soluble leptin receptor (sOB-R), and their ratio (free leptin index [FLI]), indicating leptin bioavailability, were measured using enzyme-linked immunosorbent assays. Cognitive and MRI measures were derived using standardized protocols. RESULTS Higher sOB-R was associated with lower fractional anisotropy (FA, β = -0.114 ± 0.02, p < 0.001), and higher free water (FW, β = 0.091 ± 0.022, p < 0.001) and peak-width skeletonized mean diffusivity (PSMD, β = 0.078 ± 0.021, p < 0.001). Correspondingly, higher FLI was associated with higher FA (β = 0.115 ± 0.027, p < 0.001) and lower FW (β = -0.096 ± 0.029, p = 0.001) and PSMD (β = -0.085 ± 0.028, p = 0.002). DISCUSSION Higher leptin bioavailability was associated with better white matter (WM) integrity in healthy middle-aged adults, supporting the putative neuroprotective role of leptin in late-life dementia risk. HIGHLIGHTS Higher leptin bioavailability was related to better preservation of white matter microstructure. Higher leptin bioavailability during midlife might confer protection against dementia. Potential benefits might be even stronger for individuals with visceral obesity. DTI measures might be sensitive surrogate markers of subclinical neuropathology.
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Affiliation(s)
- Sokratis Charisis
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Meghan I Short
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts, USA
| | - Rebecca Bernal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Tiffany F Kautz
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Hector A Treviño
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Julia Mathews
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Angel Gabriel Velarde Dediós
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Jazmyn A S Muhammad
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Alison M Luckey
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Asra Aslam
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Jayandra J Himali
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
- The Framingham Heart Study, Framingham, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Eric L Shipp
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Alexa S Beiser
- The Framingham Heart Study, Framingham, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, Sacramento, California, USA
| | - Nikolaos Scarmeas
- 1st Department of Neurology, National and Kapodistrian University of Athens, Athens, Greece
- Taub Institute for Research in Alzheimer's Disease and the Aging Brain, the Gertrude H. Sergievsky Center, Columbia University, New York, New York, USA
| | - Vasan S Ramachandran
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
- The Framingham Heart Study, Framingham, Massachusetts, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
- The Framingham Heart Study, Framingham, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Pauline Maillard
- Department of Neurology, University of California, Davis, Sacramento, California, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
- The Framingham Heart Study, Framingham, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
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Akhter-Khan SC, Tao Q, Ang TFA, Karjadi C, Itchapurapu IS, Libon DJ, Alosco M, Mez J, Qiu WQ, Au R. Cerebral Microbleeds in Different Brain Regions and Their Associations With the Digital Clock-Drawing Test: Secondary Analysis of the Framingham Heart Study. J Med Internet Res 2024; 26:e45780. [PMID: 39073857 PMCID: PMC11319892 DOI: 10.2196/45780] [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: 01/17/2023] [Revised: 03/18/2024] [Accepted: 03/31/2024] [Indexed: 07/30/2024] Open
Abstract
BACKGROUND Cerebral microbleeds (CMB) increase the risk for Alzheimer disease. Current neuroimaging methods that are used to detect CMB are costly and not always accessible. OBJECTIVE This study aimed to explore whether the digital clock-drawing test (DCT) may provide a behavioral indicator of CMB. METHODS In this study, we analyzed data from participants in the Framingham Heart Study offspring cohort who underwent both brain magnetic resonance imaging scans (Siemens 1.5T, Siemens Healthcare Private Limited; T2*-GRE weighted sequences) for CMB diagnosis and the DCT as a predictor. Additionally, paper-based clock-drawing tests were also collected during the DCT. Individuals with a history of dementia or stroke were excluded. Robust multivariable linear regression models were used to examine the association between DCT facet scores with CMB prevalence, adjusting for relevant covariates. Receiver operating characteristic (ROC) curve analyses were used to evaluate DCT facet scores as predictors of CMB prevalence. Sensitivity analyses were conducted by further including participants with stroke and dementia. RESULTS The study sample consisted of 1020 (n=585, 57.35% female) individuals aged 45 years and older (mean 72, SD 7.9 years). Among them, 64 (6.27%) participants exhibited CMB, comprising 46 with lobar-only, 11 with deep-only, and 7 with mixed (lobar+deep) CMB. Individuals with CMB tended to be older and had a higher prevalence of mild cognitive impairment and higher white matter hyperintensities compared to those without CMB (P<.05). While CMB were not associated with the paper-based clock-drawing test, participants with CMB had a lower overall DCT score (CMB: mean 68, SD 23 vs non-CMB: mean 76, SD 20; P=.009) in the univariate comparison. In the robust multiple regression model adjusted for covariates, deep CMB were significantly associated with lower scores on the drawing efficiency (β=-0.65, 95% CI -1.15 to -0.15; P=.01) and simple motor (β=-0.86, 95% CI -1.43 to -0.30; P=.003) domains of the command DCT. In the ROC curve analysis, DCT facets discriminated between no CMB and the CMB subtypes. The area under the ROC curve was 0.76 (95% CI 0.69-0.83) for lobar CMB, 0.88 (95% CI 0.78-0.98) for deep CMB, and 0.98 (95% CI 0.96-1.00) for mixed CMB, where the area under the ROC curve value nearing 1 indicated an accurate model. CONCLUSIONS The study indicates a significant association between CMB, especially deep and mixed types, and reduced performance in drawing efficiency and motor skills as assessed by the DCT. This highlights the potential of the DCT for early detection of CMB and their subtypes, providing a reliable alternative for cognitive assessment and making it a valuable tool for primary care screening before neuroimaging referral.
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Affiliation(s)
- Samia C Akhter-Khan
- Department of Global Health & Social Medicine, King's College London, London, United Kingdom
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, United States
| | - Qiushan Tao
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, United States
- Pharmacology, Physiology & Biophysics, Boston University School of Medicine, Boston, MA, United States
| | - Ting Fang Alvin Ang
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, United States
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
- Slone Epidemiology Center, Boston University School of Medicine, Boston, MA, United States
| | - Cody Karjadi
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, United States
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, United States
| | - Indira Swetha Itchapurapu
- Pharmacology, Physiology & Biophysics, Boston University School of Medicine, Boston, MA, United States
| | - David J Libon
- Department of Geriatrics and Gerontology, Rowan University, Glassboro, NJ, United States
- Department of Psychology, New Jersey Institute for Successful Aging, School of Osteopathic Medicine, Rowan University, Glassboro, NJ, United States
| | - Michael Alosco
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
- Alzheimer's Disease and Chronic Traumatic Encephalopathy Centers, Boston University, Boston, MA, United States
| | - Jesse Mez
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
- Alzheimer's Disease and Chronic Traumatic Encephalopathy Centers, Boston University, Boston, MA, United States
| | - Wei Qiao Qiu
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, United States
- Pharmacology, Physiology & Biophysics, Boston University School of Medicine, Boston, MA, United States
- Alzheimer's Disease and Chronic Traumatic Encephalopathy Centers, Boston University, Boston, MA, United States
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States
| | - Rhoda Au
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, United States
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
- Slone Epidemiology Center, Boston University School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
- Alzheimer's Disease and Chronic Traumatic Encephalopathy Centers, Boston University, Boston, MA, United States
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Ballvé A, Pizarro J, Maisterra O, Riba-Llena I, Pujadas F, Jiménez-Balado J, Palasi A, Cirach M, Turner MC, Sunyer J, Delgado P. Ambient air pollution, covert cerebrovascular disease and cognition: results from the ISSYS study. Eur J Neurol 2024:e16404. [PMID: 39031977 DOI: 10.1111/ene.16404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 06/19/2024] [Accepted: 06/20/2024] [Indexed: 07/22/2024]
Abstract
BACKGROUND AND PURPOSE Although air pollution (AP) has been associated with stroke and dementia, data regarding its relationship with covert cerebrovascular disease (cCVD) and cognition over time are sparse. The aim of this study was to explore these relationships. METHODS A prospective population-based study of 976 stroke-free and non-demented individuals living in Barcelona, Spain, was conducted during 2010-2016. A land use regression model was used to estimate the exposure of each participant to AP: NOx, NO2, PM2.5, PM10, PMcoarse and PM2.5 absorbance. Cognitive function and cCVD were assessed at baseline (n = 976) and 4 years after (n = 317). Multivariate-adjusted models were developed. RESULTS At baseline, 99 participants (10.1%) had covert brain infarcts and 91 (9.3%) had extensive periventricular white matter hyperintensities (WMHs). Marked subcortical WMH progression was seen in 19.7%; the incidence of other covert cerebrovascular lessons ranged between 5% and 6% each. PM2.5 was related to higher odds of having a covert brain infarct (odds ratio [OR] 2.21; 95% confidence interval [CI] 1.06-4.60). PM2.5 absorbance was related to higher odds of having extensive subcortical WMHs (OR 1.72; 95% CI 1.13-2.60), whereas NO2 was related to higher odds of having extensive subcortical (OR 1.66; 95% CI 1.17-2.35) or periventricular (OR 1.96; 95% CI 1.10-3.50) WMHs and to higher odds of developing marked subcortical WMH progression (OR 1.40; 95% CI 1.05-1.90). NOx was related to incident cerebral microbleeds (OR 1.36; 95% CI 1.04-1.79). There was no association between AP and cognition. CONCLUSIONS Air pollutant predicts the presence and accumulation of cCVD. Its impact on cognitive impairment remains to be determined.
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Affiliation(s)
- A Ballvé
- Dementia Unit, Vall d'Hebron University Hospital, Barcelona, Spain
- Neurovascular Research Laboratory, Vall Hebron Research Institute (VHIR), Barcelona, Spain
- Institute of Neuroscience, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | - J Pizarro
- Dementia Unit, Vall d'Hebron University Hospital, Barcelona, Spain
- Neurovascular Research Laboratory, Vall Hebron Research Institute (VHIR), Barcelona, Spain
| | - O Maisterra
- Dementia Unit, Vall d'Hebron University Hospital, Barcelona, Spain
- Neurovascular Research Laboratory, Vall Hebron Research Institute (VHIR), Barcelona, Spain
| | - I Riba-Llena
- Dementia Unit, Vall d'Hebron University Hospital, Barcelona, Spain
- Unitat de Trastorns Cognitius, Hospital Universitari Santa Maria, Lleida, Spain
| | - F Pujadas
- Dementia Unit, Vall d'Hebron University Hospital, Barcelona, Spain
| | - J Jiménez-Balado
- Dementia Unit, Vall d'Hebron University Hospital, Barcelona, Spain
- Neurovascular Research Group, Neurology Department, Hospital del Mar, Barcelona, Spain
| | - A Palasi
- Dementia Unit, Vall d'Hebron University Hospital, Barcelona, Spain
- Neurovascular Research Laboratory, Vall Hebron Research Institute (VHIR), Barcelona, Spain
| | - M Cirach
- Neurovascular Research Group, Neurology Department, Hospital del Mar, Barcelona, Spain
- Institut de Salut Global de Barcelona, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - M C Turner
- Institut de Salut Global de Barcelona, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), Madrid, Spain
| | - J Sunyer
- Institut de Salut Global de Barcelona, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), Madrid, Spain
| | - P Delgado
- Dementia Unit, Vall d'Hebron University Hospital, Barcelona, Spain
- Neurovascular Research Laboratory, Vall Hebron Research Institute (VHIR), Barcelona, Spain
- Institute of Neuroscience, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
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Sapkota S, Maillard P, Stickel AM, Tarraf W, Gonzalez KA, Ivanovic V, Morlett‐Paredes A, Cai J, Isasi CR, Lipton RB, Daviglus M, Testai FD, Lamar M, Gallo LC, Talavera GA, Agudelo C, Ramos AR, González HM, DeCarli C. Neurocognitive profiles are associated with subsequent brain integrity in a sample of Hispanics/Latinos: Findings from the SOL-INCA-MRI study (HCHS/SOL). ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12622. [PMID: 39021586 PMCID: PMC11253828 DOI: 10.1002/dad2.12622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 06/21/2024] [Indexed: 07/20/2024]
Abstract
The Hispanic/Latino population is one of the largest and most diverse ethnoracial groups in the United States at high risk for dementia. We examined cognitive constructs and associations with subsequent hippocampal volume (HV) and white matter hyperintensity volume (WMHV). Participants were from the Hispanic Community Health Study/Study of Latinos-Magnetic Resonance Imaging Study (n = 2029). We examined confirmatory factor analysis and longitudinal invariance using neurocognitive scores at Visits 1 (2008-2011) and 2 (2014-2018) and path analyses. We obtained a longitudinally invariant two-factor episodic memory (EM) and working memory (WM) construct. Lower EM profile at both visits was associated with greater WMHV and smaller HV at Visit 2. Lower WM profile at both visits was associated with larger WMHV and smaller HV at Visit 2. Neurocognitive profiles were associated with subsequent neurodegeneration in a sample of Hispanics/Latinos. Identifying neurocognitive risk profiles may lead to early detection and intervention, and significantly impact the course of neurodegeneration. Highlights Cognitive profiles predict brain integrity up to 10 years later.We observed two-factor latent memory constructs and longitudinal invariance.These findings were observed in a Hispanic/Latino cohort.
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Affiliation(s)
- Shraddha Sapkota
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Pauline Maillard
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | | | | | | | | | | | - Jianwen Cai
- The University of North CarolinaChapel HillNorth CarolinaUSA
| | | | | | | | | | | | | | | | | | | | | | - Charles DeCarli
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
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Lee HK, Basak C, Grant SJ, Ray NR, Skolasinska PA, Oehler C, Qin S, Sun A, Smith ET, Sherard GH, Rivera-Dompenciel A, Merzenich M, Voss MW. The Effects of Computerized Cognitive Training in Older Adults' Cognitive Performance and Biomarkers of Structural Brain Aging. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae075. [PMID: 38686621 PMCID: PMC11165429 DOI: 10.1093/geronb/gbae075] [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: 07/24/2023] [Indexed: 05/02/2024] Open
Abstract
OBJECTIVES Cognitive training (CT) has been investigated as a means of delaying age-related cognitive decline in older adults. However, its impact on biomarkers of age-related structural brain atrophy has rarely been investigated, leading to a gap in our understanding of the linkage between improvements in cognition and brain plasticity. This study aimed to explore the impact of CT on cognitive performance and brain structure in older adults. METHODS One hundred twenty-four cognitively normal older adults recruited from 2 study sites were randomly assigned to either an adaptive CT (n = 60) or a casual game training (active control, AC, n = 64). RESULTS After 10 weeks of training, CT participants showed greater improvements in the overall cognitive composite score (Cohen's d = 0.66, p < .01) with nonsignificant benefits after 6 months from the completion of training (Cohen's d = 0.36, p = .094). The CT group showed significant maintenance of the caudate volume as well as significant maintained fractional anisotropy in the left internal capsule and in left superior longitudinal fasciculus compared to the AC group. The AC group displayed an age-related decrease in these metrics of brain structure. DISCUSSION Results from this multisite clinical trial demonstrate that the CT intervention improves cognitive performance and helps maintain caudate volume and integrity of white matter regions that are associated with cognitive control, adding to our understanding of the changes in brain structure contributing to changes in cognitive performance from adaptive CT. CLINICAL TRIAL REGISTRATION NCT03197454.
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Affiliation(s)
- Hyun Kyu Lee
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | | | - Sarah-Jane Grant
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | - Nicholas R Ray
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | | | - Chris Oehler
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
| | - Shuo Qin
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - Andrew Sun
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - Evan T Smith
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - G Hulon Sherard
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | | | - Mike Merzenich
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | - Michelle W Voss
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
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Martirosian RA, Wiedner CD, Sanchez J, Mun KT, Marla K, Teran C, Thirion M, Liebeskind DS, McGrath ER, Zucker JM, Bernal R, Beiser AS, DeCarli C, Himali JJ, Seshadri S, Hinman JD. Association of Incident Stroke Risk With an IL-18-Centered Inflammatory Network Biomarker Composite. Stroke 2024; 55:1601-1608. [PMID: 38690658 DOI: 10.1161/strokeaha.123.044719] [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: 08/28/2023] [Accepted: 03/20/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND A coordinated network of circulating inflammatory molecules centered on the pleotropic pro-atherogenic cytokine interleukin-18 (IL-18) is linked to cerebral small vessel disease. We sought to validate the association of this inflammatory biomarker network with incident stroke risk, cognitive impairment, and imaging metrics in a sample of the Framingham Offspring Cohort. METHODS Using available baseline measurements of serum levels of IL-18, GDF (growth and differentiation factor)-15, soluble form of receptor for advanced glycation end products, myeloperoxidase, and MCP-1 (monocyte chemoattractant protein-1) from Exam 7 of the Framingham Offspring Cohort (1998-2001), we constructed a population-normalized, equally weighted log-transformed mean Z-score value representing the average level of each serum analyte to create an inflammatory composite score (ICS5). Multivariable regression models were used to determine the association of ICS5 with incident stroke, brain magnetic resonance imaging features, and cognitive testing performance. RESULTS We found a significant association between ICS5 score and increased risk for incident all-cause stroke (hazard ratio, 1.48 [95% CI, 1.05-2.08]; P=0.024) and ischemic stroke (hazard ratio, 1.51 [95% CI, 1.03-2.21]; P=0.033) in the Exam 7 cohort of 2201 subjects (mean age 62±9 years; 54% female) aged 45+ years with an all-cause incident stroke rate of 6.1% (135/2201) and ischemic stroke rate of 4.9% (108/2201). ICS5 and its component serum markers are all associated with the Framingham Stroke Risk Profile score (β±SE, 0.19±0.02; P<0.0001). In addition, we found a significant inverse association of ICS5 with a global cognitive score, derived from a principal components analysis of the neuropsychological battery used in the Framingham cohort (-0.08±0.03; P=0.019). No association of ICS5 with magnetic resonance imaging metrics of cerebral small vessel disease was observed. CONCLUSIONS Circulating serum levels of inflammatory biomarkers centered on IL-18 are associated with an increased risk of stroke and cognitive impairment in the Framingham Offspring Cohort. Linking specific inflammatory pathways to cerebral small vessel disease may enhance individualized quantitative risk assessment for future stroke and vascular cognitive impairment.
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Affiliation(s)
- Richard A Martirosian
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Crystal D Wiedner
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.D.W., R.B., J.J.H., S.S.), University of Texas Health Science Center at San Antonio
| | - Jasmin Sanchez
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Katherine T Mun
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Kiran Marla
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Cristina Teran
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Marissa Thirion
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - David S Liebeskind
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
| | - Emer R McGrath
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- HRB Clinical Research Facility, School of Medicine, University of Galway, Ireland (E.R.M.G.)
| | - Jared M Zucker
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
| | - Rebecca Bernal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.D.W., R.B., J.J.H., S.S.), University of Texas Health Science Center at San Antonio
| | - Alexa S Beiser
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- Department of Neurology, Boston University School of Medicine, MA (A.S.B., J.J.H., S.S.)
- Department of Biostatistics, Boston University School of Public Health, MA (A.S.B., J.J.H.)
| | - Charles DeCarli
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- Department of Neurology, University of California Davis, Sacramento (C.D.C.)
| | - Jayandra J Himali
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.D.W., R.B., J.J.H., S.S.), University of Texas Health Science Center at San Antonio
- Department of Population Health Sciences (J.J.H.), University of Texas Health Science Center at San Antonio
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- Department of Neurology, Boston University School of Medicine, MA (A.S.B., J.J.H., S.S.)
- Department of Biostatistics, Boston University School of Public Health, MA (A.S.B., J.J.H.)
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.D.W., R.B., J.J.H., S.S.), University of Texas Health Science Center at San Antonio
- Framingham Heart Study, MA (E.R.M.G., J.M.Z., A.S.B., C.D.C., J.J.H., S.S.)
- Department of Neurology, Boston University School of Medicine, MA (A.S.B., J.J.H., S.S.)
| | - Jason D Hinman
- David Geffen School of Medicine, University of California Los Angeles (R.A.M., J.S., K.T.M., K.M., C.T., M.T., D.S.L., J.D.H.)
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Escalante YY, Adams JN, Yassa MA, Janssen N. Age-related constraints on the spatial geometry of the brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594753. [PMID: 38798452 PMCID: PMC11118588 DOI: 10.1101/2024.05.17.594753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Age-related structural brain changes may be better captured by assessing complex spatial geometric differences rather than isolated changes to individual regions. We applied a novel analytic method to quantify age-related changes to the spatial anatomy of the brain by measuring expansion and compression of global brain shape and the distance between cross-hemisphere homologous regions. To test how global brain shape and regional distances are affected by aging, we analyzed 2,603 structural MRIs (range: 30-97 years). Increasing age was associated with global shape expansion across inferior-anterior gradients, global compression across superior-posterior gradients, and regional expansion between frontotemporal homologues. Specific patterns of global and regional expansion and compression were further associated with clinical impairment and distinctly related to deficits in various cognitive domains. These findings suggest that changes to the complex spatial anatomy and geometry of the aging brain may be associated with reduced efficiency and cognitive dysfunction in older adults.
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8
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Stickel AM, Tarraf W, Gonzalez KA, Paredes AM, Zeng D, Cai J, Isasi CR, Kaplan R, Lipton RB, Daviglus ML, Testai FD, Lamar M, Gallo LC, Talavera GA, Gellman MD, Ramos AR, Ivanovic V, Seiler S, González HM, DeCarli C. Cardiovascular disease risk exacerbates brain aging among Hispanic/Latino adults in the SOL-INCA-MRI Study. Front Aging Neurosci 2024; 16:1390200. [PMID: 38778863 PMCID: PMC11110680 DOI: 10.3389/fnagi.2024.1390200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 04/09/2024] [Indexed: 05/25/2024] Open
Abstract
Background Cardiovascular disease (CVD) risk factors are highly prevalent among Hispanic/Latino adults, while the prevalence of MRI infarcts is not well-documented. We, therefore, sought to examine the relationships between CVD risk factors and infarcts with brain structure among Hispanic/Latino individuals. Methods Participants included 1,886 Hispanic/Latino adults (50-85 years) who underwent magnetic resonance imaging (MRI) as part of the Study of Latinos-Investigation of Neurocognitive Aging-MRI (SOL-INCA-MRI) study. CVD risk was measured approximately 10.5 years before MRI using the Framingham cardiovascular risk score, a measure of 10-year CVD risk (low (<10%), medium (10- < 20%), and high (≥20%)). MR infarcts were determined as present or absent. Outcomes included total brain, cerebral and lobar cortical gray matter, hippocampal, lateral ventricle, and total white matter hyperintensity (WMH) volumes. Linear regression models tested associations between CVD risk and infarct with MRI outcomes and for modifications by age and sex. Results Sixty percent of participants were at medium or high CVD risk. Medium and high CVD risk were associated with lower total brain and frontal gray matter and higher WMH volumes compared to those with low CVD risk. High CVD risk was additionally associated with lower total cortical gray matter and parietal volumes and larger lateral ventricle volumes. Men tended to have greater CVDRF-related differences in total brain volumes than women. The association of CVD risk factors on total brain volumes increased with age, equal to an approximate 7-year increase in total brain aging among the high-CVD-risk group compared to the low-risk group. The presence of infarct(s) was associated with lower total brain volumes, which was equal to an approximate 5-year increase in brain aging compared to individuals without infarcts. Infarcts were also associated with smaller total cortical gray matter, frontal and parietal volumes, and larger lateral ventricle and WMH volumes. Conclusion The high prevalence of CVD risk among Hispanic/Latino adults may be associated with accelerated brain aging.
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Affiliation(s)
- Ariana M. Stickel
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Wassim Tarraf
- Department of Healthcare Sciences, Institute of Gerontology, Wayne State University, Detroit, MI, United States
| | - Kevin A. Gonzalez
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | | | - Donglin Zeng
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Carmen R. Isasi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Robert Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Richard B. Lipton
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Martha L. Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, College of Medicine, Chicago, IL, United States
| | - Fernando D. Testai
- Department of Neurology & Neurorehabilitation, College of Medicine, University of Illinois at Chicago, Chicago, IL, United States
| | - Melissa Lamar
- Institute for Minority Health Research, University of Illinois at Chicago, College of Medicine, Chicago, IL, United States
- Rush Alzheimer’s Disease Research Center, Rush University Medical Center, Chicago, IL, United States
| | - Linda C. Gallo
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Gregory A. Talavera
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Marc D. Gellman
- Department of Psychology, University of Miami, Miami, FL, United States
| | - Alberto R. Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Vladimir Ivanovic
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Stephan Seiler
- Department of Neurology, Klinikum Klagenfurt, Klagenfurt, Austria
| | - Hector M. González
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Davis, CA, United States
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9
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Schmithorst V, Bais A, Badaly D, Williams K, Gabriel G, Ceschin R, Wallace J, Lee V, Lopez O, Cohen A, Martin LJ, Lo C, Panigrahy A. Complex Regulation of Protocadherin Epigenetics on Aging-Related Brain Health. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.21.24306143. [PMID: 38712165 PMCID: PMC11071558 DOI: 10.1101/2024.04.21.24306143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Life expectancy continues to increase in the high-income world due to advances in medical care; however, quality of life declines with increasing age due to normal aging processes. Current research suggests that various aspects of aging are genetically modulated and thus may be slowed via genetic modification. Here, we show evidence for epigenetic modulation of the aging process in the brain from over 1800 individuals as part of the Framingham Heart Study. We investigated the methylation of genes in the protocadherin (PCDH) clusters, including the alpha (PCHDA), beta (PCDHB), and gamma (PCDHG) clusters. Reduced PCDHG, elevated PCDHA, and elevated PCDHB methylation levels were associated with substantial reductions in the rate of decline of regional white matter volume as well as certain cognitive skills, independent of overall accelerated or retarded aging as estimated by a DNA clock. These results are likely due to the different effects of the expression of genes in the alpha, beta, and gamma PCHD clusters and suggest that experience-based aging processes related to a decline in regional brain volume and select cognitive skills may be slowed via targeted epigenetic modifications.
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Affiliation(s)
- Vanessa Schmithorst
- UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Department of Radiology
| | - Abha Bais
- University of Pittsburgh Department of Developmental Biology
| | | | | | | | - Rafael Ceschin
- UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Department of Radiology
| | - Julia Wallace
- UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Department of Radiology
| | - Vince Lee
- UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Department of Radiology
| | - Oscar Lopez
- University of Pittsburgh Department of Neurology
| | - Annie Cohen
- University of Pittsburgh Department of Psychiatry
| | - Lisa J. Martin
- Department of Pediatrics Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine
| | - Cecilia Lo
- University of Pittsburgh Integrative Systems Biology
| | - Ashok Panigrahy
- UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Department of Radiology
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10
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Wang Y, Huang J, Ang TFA, Zhu Y, Tao Q, Mez J, Alosco M, Denis GV, Belkina A, Gurnani A, Ross M, Gong B, Han J, Lunetta KL, Stein TD, Au R, Farrer LA, Zhang X, Qiu WQ. The association between circulating CD34+CD133+ endothelial progenitor cells and reduced risk of Alzheimer's disease in the Framingham Heart Study. EXPLORATION OF MEDICINE 2024; 5:193-214. [PMID: 38854406 PMCID: PMC11160969 DOI: 10.37349/emed.2024.00216] [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: 12/19/2023] [Accepted: 02/22/2024] [Indexed: 06/11/2024] Open
Abstract
Aim Endothelial dysfunction has been associated with both cerebrovascular pathology and Alzheimer's disease (AD). However, the connection between circulating endothelial cells and the risk of AD remains uncertain. The objective was to leverage data from the Framingham Heart Study to investigate various circulating endothelial subtypes and their potential correlations with the risk of AD. Methods The study conducted data analyses using Cox proportional hazard regression and linear regression methods. Additionally, genome-wide association study (GWAS) was carried out to further explore the data. Results Among the eleven distinct circulating endothelial subtypes, only circulating endothelial progenitor cells (EPCs) expressing CD34+CD133+ were found to be negatively and dose-dependently associated with reduced AD risk. This association persisted even after adjusting for age, sex, years of education, apolipoprotein E (APOE) ε4 status, and various vascular diseases. Particularly noteworthy was the significant association observed in individuals with hypertension and cerebral microbleeds. Consistently, positive associations were identified between CD34+CD133+ EPCs and specific brain regions, such as higher proportions of circulating CD34+CD133+ cells correlating with increased volumes of white matter and the hippocampus. Additionally, a GWAS study unveiled that CD34+CD133+ cells influenced AD risk specifically in individuals with homozygous genotypes for variants in two stem cell-related genes: kirre like nephrin family adhesion molecule 3 (KIRREL3, rs580382 CC and rs4144611 TT) and exocyst complex component 6B (EXOC6B, rs61619102 CC). Conclusions The findings suggest that circulating CD34+CD133+ EPCs possess a protective effect and may offer a new therapeutic avenue for AD, especially in individuals with vascular pathology and those carrying specific genotypes of KIRREL3 and EXOC6B genes.
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Affiliation(s)
- Yixuan Wang
- Biomedical Genetics, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Jinghan Huang
- Biomedical Genetics, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Chemical Pathology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Ting Fang Alvin Ang
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Yibo Zhu
- Biomedical Genetics, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Qiushan Tao
- Department of Pharmacology, Physiology and Biophysics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Jesse Mez
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Michael Alosco
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Gerald V. Denis
- Hematology & Medical Oncology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Anna Belkina
- Department of Pathology & Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Ashita Gurnani
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Mark Ross
- School of Energy, Geosciences, Infrastructure and Society, Institute of Life and Earth Sciences, Heriot-Watt University, EH14 4AS Edinburgh, UK
| | - Bin Gong
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Jingyan Han
- Vascular Biology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Kathryn L. Lunetta
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Thor D. Stein
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Pathology & Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- VA Boston Healthcare System, Boston, MA 02132, USA
| | - Rhoda Au
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Departments of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
| | - Lindsay A. Farrer
- Biomedical Genetics, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- Departments of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Xiaoling Zhang
- Biomedical Genetics, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Wei Qiao Qiu
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Pharmacology, Physiology and Biophysics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
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11
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Lundy ME, Zhang B, Ditillo M. Management of the Geriatric Trauma Patient. Surg Clin North Am 2024; 104:423-436. [PMID: 38453311 DOI: 10.1016/j.suc.2023.09.010] [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: 03/09/2024]
Abstract
With a rapidly aging worldwide population, the care of geriatric trauma patients will be at the forefront of every career in Trauma and Acute Care Surgery. The unique intersection of advanced age, comorbidities, frailty, and physiologic changes presents a challenge in the care of elderly injured patients. It is well established that increasing age is associated with higher mortality and worse outcomes after injury, but it is also clear that there is room for improvement in the management of this special patient population.
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Affiliation(s)
- Megan Elizabeth Lundy
- University of Arizona Division of Trauma, Surgical Critical Care, Burns, and Acute Care Surgery, 1501 North Campbell Avenue, Tucson, AZ 85724, USA. https://twitter.com/MLundyMD
| | - Bo Zhang
- University of Arizona Division of Trauma, Surgical Critical Care, Burns, and Acute Care Surgery, 1501 North Campbell Avenue, Tucson, AZ 85724, USA. https://twitter.com/bo_zhang1
| | - Michael Ditillo
- University of Arizona Division of Trauma, Surgical Critical Care, Burns, and Acute Care Surgery, 1501 North Campbell Avenue, Tucson, AZ 85724, USA.
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12
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Wang J, Sims KD, Ackley SF, Chen R, Kobayashi LC, Hayes‐Larson E, Mayeda ER, Buto P, Zimmerman SC, Graff RE, Glymour MM. Association of cancer history with structural brain aging markers of Alzheimer's disease and related dementias risk. Alzheimers Dement 2024; 20:880-889. [PMID: 37811979 PMCID: PMC10916958 DOI: 10.1002/alz.13497] [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: 05/15/2023] [Revised: 08/22/2023] [Accepted: 09/14/2023] [Indexed: 10/10/2023]
Abstract
INTRODUCTION Cancer survivors are less likely than comparably aged individuals without a cancer history to develop Alzheimer's disease and related dementias (ADRD). METHODS In the UK Biobank, we investigated associations between cancer history and five structural magnetic resonance imaging (MRI) markers for ADRD risk, using linear mixed-effects models to assess differences in mean values and quantile regression to examine whether associations varied across the distribution of MRI markers. RESULTS Cancer history was associated with smaller mean hippocampal volume (b = -19 mm3 , 95% CI = -36, -1) and lower mean cortical thickness in the Alzheimer's disease signature region (b = -0.004 mm, 95% CI = -0.007, -0.000). Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history. DISCUSSION Some brain MRI markers associated with ADRD risk were elevated in adults with a history of cancer. The magnitude of the adverse associations varied across quantiles of neuroimaging markers, and the pattern suggests possible harmful associations for individuals already at high ADRD risk. HIGHLIGHTS We found no evidence of an inverse association between cancer history and ADRD-related neurodegeneration. Cancer history was associated with smaller mean hippocampal volume and lower mean cortical thickness in the Alzheimer's disease signature region. Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history.
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Affiliation(s)
- Jingxuan Wang
- Department of Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Kendra D. Sims
- Department of Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Sarah F. Ackley
- Department of Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Ruijia Chen
- Department of Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Lindsay C. Kobayashi
- Department of EpidemiologyUniversity of Michigan School of Public HealthAnn ArborMichiganUSA
| | - Eleanor Hayes‐Larson
- Department of EpidemiologyFielding School of Public HealthUniversity of California, Los AngelesLos AngelesCaliforniaUSA
| | - Elizabeth Rose Mayeda
- Department of EpidemiologyFielding School of Public HealthUniversity of California, Los AngelesLos AngelesCaliforniaUSA
| | - Peter Buto
- Department of Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Scott C. Zimmerman
- Department of Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Rebecca E. Graff
- Department of Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - M. Maria Glymour
- Department of Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
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13
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Farkhondeh V, DeCarli C. White matter hyperintensities in diverse populations: A systematic review of literature in the United States. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 6:100204. [PMID: 38298455 PMCID: PMC10828602 DOI: 10.1016/j.cccb.2024.100204] [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: 08/14/2023] [Revised: 12/20/2023] [Accepted: 01/11/2024] [Indexed: 02/02/2024]
Abstract
As the United States' (US) elderly population becomes increasingly diverse, it is imperative that research studies address cognitive health in diverse populations of older Americans. White Matter Hyperintensities (WMH) are useful imaging findings that can be studied in elderly individuals and have been linked to an increased risk of neurological conditions, such as stroke, cognitive impairment, and dementia. We performed a systematic review of literature using PubMed sources to compile all the studies that investigated the prevalence of ethnic and racial differences of WMH burden amongst diverse groups in the US. We identified 23 unique articles that utilized 16 distinct cohorts of which 94 % were prospective, longitudinal studies that included community-based and family-based populations. The overall results were heterogenous in all aspects of data collection and analysis, limiting our ability to run meta-analyses and draw definitive conclusions. General observations suggest increased vascular risk on African American populations, contributing to greater WMH burden in that population. Overall, the findings of this study indicate a need for a standardized approach to investigating WMH in efforts to measure its clinical impact on diverse populations.
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Affiliation(s)
- Vista Farkhondeh
- Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, United States
- Imaging of Dementia and Aging Laboratory and Center for Neurosciences, Davis, CA, United States
| | - Charles DeCarli
- Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, United States
- Imaging of Dementia and Aging Laboratory and Center for Neurosciences, Davis, CA, United States
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14
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Baril AA, Kojis DJ, Himali JJ, Decarli CS, Sanchez E, Johnson KA, El Fakhri G, Thibault E, Yiallourou SR, Himali D, Cavuoto MG, Pase MP, Beiser AS, Seshadri S. Association of Sleep Duration and Change Over Time With Imaging Biomarkers of Cerebrovascular, Amyloid, Tau, and Neurodegenerative Pathology. Neurology 2024; 102:e207807. [PMID: 38165370 PMCID: PMC10834132 DOI: 10.1212/wnl.0000000000207807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 10/13/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Both short and long sleep duration were previously associated with incident dementia, but underlying mechanisms remain unclear. We evaluated how self-reported sleep duration and its change over time associate with (A)myloid, (T)au, (N)eurodegeneration, and (V)ascular neuroimaging markers of Alzheimer disease. METHODS Two Framingham Heart Study overlapping samples were studied: participants who underwent 11C-Pittsburg Compound B amyloid and 18F-flortaucipir tau PET imaging and participants who underwent an MRI. MRI metrics estimated neurodegeneration (total brain volume) and cerebrovascular injuries (white matter hyperintensities [WMHs] volume, covert brain infarcts, free-water [FW] fraction). Self-reported sleep duration was assessed and split into categories both at the time of neuroimaging testing and approximately 13 years before: short ≤6 hours. average 7-8 hours, and long ≥9 hours. Logistic and linear regression models were used to examine sleep duration and neuroimaging metrics. RESULTS The tested cohort was composed of 271 participants (age 53.6 ± 8.0 years; 51% male) in the PET imaging sample and 2,165 participants (age 61.3 ± 11.1 years; 45% male) in the MRI sample. No fully adjusted association was observed between cross-sectional sleep duration and neuroimaging metrics. In fully adjusted models compared with consistently sleeping 7-8 hours, groups transitioning to a longer sleep duration category over time had higher FW fraction (short to average β [SE] 0.0062 [0.0024], p = 0.009; short to long β [SE] 0.0164 [0.0076], p = 0.031; average to long β [SE] 0.0083 [0.0022], p = 0.002), and those specifically going from average to long sleep duration also had higher WMH burden (β [SE] 0.29 [0.11], p = 0.007). The opposite associations (lower WMH and FW) were observed in participants consistently sleeping ≥9 hours as compared with people consistently sleeping 7-8 hours in fully adjusted models (β [SE] -0.43 [0.20], p = 0.028; β [SE] -0.019 [0.004], p = 0.020). Each hour of increasing sleep (continuous, β [SE] 0.12 [0.04], p = 0.003; β [SE] 0.002 [0.001], p = 0.021) and extensive increase in sleep duration (≥2 hours vs 0 ± 1 hour change; β [SE] 0.24 [0.10], p = 0.019; β [SE] 0.0081 [0.0025], p = 0.001) over time was associated with higher WMH burden and FW fraction in fully adjusted models. Sleep duration change was not associated with PET amyloid or tau outcomes. DISCUSSION Longer self-reported sleep duration over time was associated with neuroimaging biomarkers of cerebrovascular pathology as evidenced by higher WMH burden and FW fraction. A longer sleep duration extending over time may be an early change in the neurodegenerative trajectory.
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Affiliation(s)
- Andrée-Ann Baril
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Daniel J Kojis
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Jayandra J Himali
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Charles S Decarli
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Erlan Sanchez
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Keith A Johnson
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Georges El Fakhri
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Emma Thibault
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Stephanie R Yiallourou
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Dibya Himali
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Marina G Cavuoto
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Matthew P Pase
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Alexa S Beiser
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
| | - Sudha Seshadri
- From the Douglas Mental Health University Institute (A.-A.B.), McGill University, Montreal, Quebec, Canada; The Framingham Heart Study (A.-A.B., D.J.K., J.J.H., D.H., M.P.P., A.S.B., S.S.); Boston University School of Public Health (D.J.K., J.J.H.), MA; Boston University School of Medicine (J.J.H., S.S.), MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (J.J.H., S.S.), UT Health San Antonio, TX; UC Davis Center for Neuroscience (C.S.D.), CA; Sunnybrook Research Institute (E.S.), University of Toronto, Ontario, Canada; Harvard Aging Brain Institute (K.A.J.), Harvard Medical School, Boston, MA; Gordon Center for Medical Imaging (G.E.F., E.T.), Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston; Turner Institute for Brain and Mental Health (S.R.Y., M.G.C., M.P.P.), Monash University, Clayton, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Harvard University, Boston, MA
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15
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Petrea RE, Pinheiro A, Demissie S, Ekenze O, Aparicio HJ, Satizabal C, Maillard P, DeCarli C, Beiser AS, Seshadri S, Lioutas VA, Romero JR. Hypertension Trends and White Matter Brain Injury in the Offspring Framingham Heart Study Cohort. Hypertension 2024; 81:87-95. [PMID: 37855140 PMCID: PMC10896002 DOI: 10.1161/hypertensionaha.123.21264] [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: 03/23/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND Hypertension is the most potent stroke risk factor and is also related to cerebral small vessel disease. We studied the relation between mid-to-late-life hypertension trends and cerebral white matter injury in community-dwelling individuals from the FHS (Framingham Heart Study). METHODS FHS Offspring cohort participants with available mid-life and late-life blood pressure measurements and brain magnetic resonance imaging were included. Multiple regression analyses were used to relate hypertension trends (normotension-normotension [reference], normotension-hypertension, and hypertension-hypertension) to white matter injury metrics on diffusion tensor imaging (free water, fractional anisotropy, and peak skeletonized mean diffusivity) and Fluid Attenuated Inversion Recovery (white matter hyperintensity volume) by different blood pressure cutoffs (130/80, 140/90, and 150/90 mm Hg). RESULTS We included 1018 participants (mean age 47.3±7.4 years at mid-life and 73.2±7.3 at late-life). At the 140/90 mm Hg cutoff, the hypertension-hypertension trend was associated with higher free water (β, 0.16 [95% CI, 0.03-0.30]; P=0.021) and peak skeletonized mean diffusivity (β, 0.15 [95% CI, 0.01-0.29]; P=0.033). At a 130/80 mm Hg cutoff, the hypertension-hypertension trend had significantly higher free water (β, 0.16 [95% CI, 0.01-0.30]; P=0.035); and the normotension-hypertension (β, 0.24 [95% CI, 0.03-0.44]; P=0.027) and hypertension-hypertension (β, 0.22 [95% CI, 0.04-0.41]; P=0.022) trends had significantly increased white matter hyperintensity volume. Exploratory stratified analysis showed effect modifications by APOE ɛ4 allele and age. CONCLUSIONS Mid-to-late-life hypertension exposure is significantly associated with microstructural and to a lesser extent, visible white matter injury; the effects are observed at both conventional and lower blood pressure cutoffs and are associated with longer duration of hypertension.
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Affiliation(s)
- Rodica Elena Petrea
- Department of Medicine, Section of Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, USA
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
| | - Adlin Pinheiro
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Serkalem Demissie
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Oluchi Ekenze
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Graduate medical sciences, Boston University School of Medicine
| | - Hugo J. Aparicio
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Claudia Satizabal
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Pauline Maillard
- Alzheimer’s Disease Center and Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology and Center for Neuroscience, University of California at Davis School of Medicine, Sacramento, CA, USA
| | - Charles DeCarli
- Alzheimer’s Disease Center and Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology and Center for Neuroscience, University of California at Davis School of Medicine, Sacramento, CA, USA
| | - Alexa S Beiser
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sudha Seshadri
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Vasileios-Arsenios Lioutas
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, MA, USA
| | - Jose Rafael Romero
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
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16
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Ding H, Hamel AP, Karjadi C, Ang TFA, Lu S, Thomas RJ, Au R, Lin H. Association Between Acoustic Features and Brain Volumes: the Framingham Heart Study. FRONTIERS IN DEMENTIA 2023; 2:1214940. [PMID: 38911669 PMCID: PMC11192548 DOI: 10.3389/frdem.2023.1214940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/25/2024]
Abstract
Introduction Although brain magnetic resonance imaging (MRI) is a valuable tool for investigating structural changes in the brain associated with neurodegeneration, the development of non-invasive and cost-effective alternative methods for detecting early cognitive impairment is crucial. The human voice has been increasingly used as an indicator for effectively detecting cognitive disorders, but it remains unclear whether acoustic features are associated with structural neuroimaging. Methods This study aims to investigate the association between acoustic features and brain volume and compare the predictive power of each for mild cognitive impairment (MCI) in a large community-based population. The study included participants from the Framingham Heart Study (FHS) who had at least one voice recording and an MRI scan. Sixty-five acoustic features were extracted with the OpenSMILE software (v2.1.3) from each voice recording. Nine MRI measures were derived according to the FHS MRI protocol. We examined the associations between acoustic features and MRI measures using linear regression models adjusted for age, sex, and education. Acoustic composite scores were generated by combining acoustic features significantly associated with MRI measures. The MCI prediction ability of acoustic composite scores and MRI measures were compared by building random forest models and calculating the mean area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation. Results The study included 4,293 participants (age 57 ± 13 years, 53.9% women). During 9.3±3.7 years follow-up, 106 participants were diagnosed with MCI. Seven MRI measures were significantly associated with more than 20 acoustic features after adjusting for multiple testing. The acoustic composite scores can improve the AUC for MCI prediction to 0.794, compared to 0.759 achieved by MRI measures. Discussion We found multiple acoustic features were associated with MRI measures, suggesting the potential for using acoustic features as easily accessible digital biomarkers for the early diagnosis of MCI.
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Affiliation(s)
- Huitong Ding
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Alexander P Hamel
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Cody Karjadi
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Ting F. A. Ang
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sophia Lu
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Robert J. Thomas
- Department of Medicine, Division of Pulmonary, Critical Care & Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Departments of Neurology and Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Honghuang Lin
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
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Bangen KJ, Calcetas AT, Thomas KR, Wierenga C, Smith CN, Bordyug M, Brenner EK, Wing D, Chen C, Liu TT, Zlatar ZZ. Greater accelerometer-measured physical activity is associated with better cognition and cerebrovascular health in older adults. J Int Neuropsychol Soc 2023; 29:859-869. [PMID: 36789631 PMCID: PMC10425574 DOI: 10.1017/s1355617723000140] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
OBJECTIVES Physical activity (PA) may help maintain brain structure and function in aging. Since the intensity of PA needed to effect cognition and cerebrovascular health remains unknown, we examined associations between PA and cognition, regional white matter hyperintensities (WMH), and regional cerebral blood flow (CBF) in older adults. METHOD Forty-three older adults without cognitive impairment underwent magnetic resonance imaging (MRI) and comprehensive neuropsychological assessment. Waist-worn accelerometers objectively measured PA for approximately one week. RESULTS Higher time spent in moderate to vigorous PA (MVPA) was uniquely associated with better memory and executive functioning after adjusting for all light PA. Higher MVPA was also uniquely associated with lower frontal WMH volume although the finding was no longer significant after additionally adjusting for age and accelerometer wear time. MVPA was not associated with CBF. Higher time spent in all light PA was uniquely associated with higher CBF but not with cognitive performance or WMH volume. CONCLUSIONS Engaging in PA may be beneficial for cerebrovascular health, and MVPA in particular may help preserve memory and executive function in otherwise cognitively healthy older adults. There may be differential effects of engaging in lighter PA and MVPA on MRI markers of cerebrovascular health although this needs to be confirmed in future studies with larger samples. Future randomized controlled trials that increase PA are needed to elucidate cause-effect associations between PA and cerebrovascular health.
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Affiliation(s)
- Katherine J Bangen
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Amanda T Calcetas
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Kelsey R Thomas
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Christina Wierenga
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Christine N Smith
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA
| | - Maria Bordyug
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Einat K Brenner
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - David Wing
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
| | - Conan Chen
- Center for Functional MRI and Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Thomas T Liu
- Center for Functional MRI and Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Zvinka Z Zlatar
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
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18
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Li T, Ye M, Yang G, Diao S, Zhou Y, Qin Y, Ding D, Zhu M, Fang Q. Regional white matter hyperintensity volume predicts persistent cognitive impairment in acute lacunar infarct patients. Front Neurol 2023; 14:1265743. [PMID: 37881309 PMCID: PMC10595143 DOI: 10.3389/fneur.2023.1265743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 09/15/2023] [Indexed: 10/27/2023] Open
Abstract
Background White matter hyperintensity (WMH) is often described in acute lacunar stroke (ALS) patients. However, the specific relationship between regional WMH volume and persistent cognitive impairment remains unclear. Methods We enrolled patients with ALS who were hospitalized at the First Affiliated Hospital of Soochow University between January 2020 and November 2022. All patients were assessed for global cognitive function using the Montreal Cognitive Assessment (MoCA) scale at 14 ± 2 days and 6 months after the onset of ALS. Manifestations of chronic cerebral small vessel disease (CSVD) were assessed via MRI scan. The distributions of regional WMH were segmented, and their relationship with cognitive impairment was evaluated. Results A total of 129 patients were enrolled. Baseline frontal WMH volume (OR = 1.18, P = 0.04) was an independent risk factor for long-term cognitive impairment after ALS. Furthermore, the presence of WMH at the genu of the corpus callosum (GCC) at baseline (OR = 3.1, P = 0.033) was strongly associated with persistent cognitive decline. Multivariable logistic regression analysis showed that depression (OR = 6.252, P = 0.029), NIHSS score (OR = 1.24, P = 0.011), and albumin at admission (OR = 0.841, P = 0.032) were also important determinants of long-term cognitive impairment after ALS. Conclusions Our study found that WMH, especially frontal WMH volume and the presence of WMH at the GCC at baseline, independently contributed to long-term cognitive decline in ALS patients. This study provides new evidence of the clinical relationship between regional WMH volume and cognitive impairment in ALS patients.
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Affiliation(s)
- Tan Li
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Mengfan Ye
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Guopeng Yang
- Suzhou Jiasheng Medical Instrument Co., Ltd., Suzhou, Jiangsu, China
| | - Shanshan Diao
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Yun Zhou
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Yiren Qin
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Dongxue Ding
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Mo Zhu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Qi Fang
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
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Membreno R, Thomas KR, Calcetas AT, Edwards L, Bordyug M, Showell M, Stanfill M, Brenner EK, Walker KS, Rotblatt LJ, Brickman AM, Edmonds EC, Bangen KJ. Regional White Matter Hyperintensities Relate to Specific Cognitive Abilities in Older Adults Without Dementia. Alzheimer Dis Assoc Disord 2023; 37:303-309. [PMID: 38015423 PMCID: PMC10664788 DOI: 10.1097/wad.0000000000000585] [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: 07/03/2023] [Accepted: 09/06/2023] [Indexed: 11/29/2023]
Abstract
INTRODUCTION White matter hyperintensities (WMHs) are magnetic resonance imaging markers of small vessel cerebrovascular disease that are associated with cognitive decline and clinical Alzheimer disease. Previous studies have often focused on global or total WMH; less is known about associations of regional WMHs and cognitive abilities among older adults without dementia. METHODS A total of 610 older adults with normal cognition (n=302) or mild cognitive impairment (n=308) from the Alzheimer's Disease Neuroimaging Initiative underwent neuropsychological testing and magnetic resonance imaging. Linear regression models examined associations between regional WMH volumes and cognition, adjusting for age, sex, education, apolipoprotein E ε4 allele frequency, and pulse pressure. RESULTS Among all participants, greater regional WMH volume in all lobes was associated with poorer performance on memory and speed/executive functioning. Among participants with normal cognition, greater temporal and occipital WMH volumes were associated with poorer memory, whereas no regional WMH volumes were associated with speed/executive function. DISCUSSION Results show that greater regional WMH volume relates to poorer cognitive functioning-even among those with normal cognition. Together with results from previous studies, our findings raise the possibility that WMH may be a useful therapeutic target and/or important effect modifier in treatment or prevention dementia trials.
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Affiliation(s)
| | - Kelsey R. Thomas
- Research Service, VA San Diego Healthcare System
- Department of Psychiatry, University of California San Diego
| | | | - Lauren Edwards
- San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA
| | - Maria Bordyug
- Department of Psychiatry, University of California San Diego
| | - Maya Showell
- Research Service, VA San Diego Healthcare System
| | | | | | | | - Lindsay J. Rotblatt
- Psychology Service, VA San Diego Healthcare System
- Department of Psychiatry, University of California San Diego
| | - Adam M. Brickman
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University
- Gertrude H. Sergievsky Center, Columbia University
- Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY
| | - Emily C. Edmonds
- Banner Alzheimer’s Institute
- Department of Psychology, University of Arizona, Tucson, AZ
| | - Katherine J. Bangen
- Research Service, VA San Diego Healthcare System
- Department of Psychiatry, University of California San Diego
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20
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Yang Y, Cai X, Zhou M, Chen Y, Pi J, Zhao M, Shi Y, Wang S, Jing J, Chen W, Meng X, Wang Y, Pan Y, Wang Y. Prevalence and Risk Factors of Cerebral Small Vessel Disease from a Population-Based Cohort in China. Neuroepidemiology 2023; 57:413-422. [PMID: 37734325 DOI: 10.1159/000533678] [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: 02/12/2023] [Accepted: 07/25/2023] [Indexed: 09/23/2023] Open
Abstract
INTRODUCTION Cerebral small vessel disease (CSVD) is a significant burden of morbidity and mortality among elderly people around the world. Epidemiological data with complete CSVD evaluations and a large sample size in the general population are still limited. METHODS Community-dwelling residents in Lishui city in China from the cross-sectional survey of the Polyvascular Evaluation for Cognitive Impairment and Vascular Events (PRECISE) study were included in this study from 2017 to 2019. All participants underwent 3 Tesla brain magnetic resonance images to assess CSVD imaging markers. Demographic and risk factor data were collected. The general and age-specific prevalence of lacune, confluent white matter hyperintensity (WMH), moderate-severe enlarged perivascular spaces (EPVS), cerebral microbleed (CMB), and total CSVD score (an ordinal scale from 0 to 4, counting the presence of four imaging markers of CSVD) was evaluated. Associations between vascular risk factors and these markers were analyzed by multivariable logistic regression. RESULTS A total of 3,063 participants were enrolled. The mean age was 61.2 years and 46.5% were men. The most prevalent CSVD marker was confluent WMH (16.7%), followed by CMB (10.2%), moderate-severe EPVS in the basal ganglia (BG-EPVS) (9.8%), and lacune (5.6%). 30.5% of the participants have at least one of the four markers (total CSVD score ≥1 points). The prevalence of CSVD markers increases as age increases. Age and hypertension were independent risk factors for four CSVD markers and the total CSVD score. CONCLUSIONS In this Chinese cohort with community-based adults aged 50-75 years, our findings showed a prevalence of 30.5% for CSVD. The most prevalent CSVD marker was confluent WMH, followed by CMB, moderate-severe BG-EPVS, and lacune. The risk factors for CSVD must be strictly screened and controlled in adults living in the community.
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Affiliation(s)
- Yingying Yang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China,
- China National Clinical Research Center for Neurological Diseases, Beijing, China,
| | - Xueli Cai
- Department of Neurology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Mengyuan Zhou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yiyi Chen
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jingtao Pi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Mengxi Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yulu Shi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Suying Wang
- Cerebrovascular Research Lab, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Weiqi Chen
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xia Meng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
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21
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Sukumar S, Mazepa MA, Chaturvedi S. Cardiovascular Disease and Stroke in Immune TTP-Challenges and Opportunities. J Clin Med 2023; 12:5961. [PMID: 37762903 PMCID: PMC10531888 DOI: 10.3390/jcm12185961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/29/2023] [Accepted: 09/09/2023] [Indexed: 09/29/2023] Open
Abstract
Advances in the management of immune thrombotic thrombocytopenic purpura (iTTP) have dramatically improved outcomes of acute TTP episodes, and TTP is now treated as a chronic, relapsing disorder. It is now recognized that iTTP survivors are at high risk for vascular disease, with stroke and myocardial infarction occurring at younger ages than in the general population, and cardiovascular disease is the leading cause of premature death in this population. iTTP appears to have a phenotype of accelerated vascular aging with a particular predilection for cerebral circulation, and stroke is much more common than myocardial infarction. In addition to traditional cardiovascular risk factors, low ADAMTS13 activity during clinical remission may be a risk factor for some of these outcomes, such as stroke. Recent studies also suggest that Black patients, who are disproportionately affected by iTTP in the United States, are at higher risk of adverse cardiovascular outcomes, likely due to multifactorial reasons. Additional research is required to establish the risk factors and mechanisms underlying these complications in order to institute optimal screening strategies and identify interventions to improve outcomes.
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Affiliation(s)
- Senthil Sukumar
- Division of Hematology/Oncology, Department of Medicine, Baylor College of Medicine, Houston, TX 77098, USA;
| | - Marshall A. Mazepa
- Division of Hematology, Oncology, and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, MN 55455, USA;
| | - Shruti Chaturvedi
- Division of Hematology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
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22
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Rodriguez Lara F, Toro AR, Pinheiro A, Demissie S, Ekenze O, Martinez O, Parva P, Charidimou A, Ghosh S, DeCarli C, Seshadri S, Habes M, Maillard P, Romero JR. Relation of MRI-Visible Perivascular Spaces and Other MRI Markers of Cerebral Small Vessel Disease. Brain Sci 2023; 13:1323. [PMID: 37759924 PMCID: PMC10527297 DOI: 10.3390/brainsci13091323] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Revised: 09/10/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Perivascular spaces (PVS) visible on brain MRI signal cerebral small vessel disease (CSVD). The coexistence of PVS with other CSVD manifestations likely increases the risk of adverse neurological outcomes. We related PVS to other CSVD manifestations and brain volumes that are markers of vascular brain injury and neurodegeneration. Framingham Heart Study (FHS) participants with CSVD ratings on brain MRI were included. PVS were rated in the basal ganglia (BG) and centrum semiovale (CSO) into grades I-IV and a category reflecting high burden in single or mixed CSO-BG regions. We related PVS to covert brain infarcts (CBI), white matter hyperintensities (WMH), cerebral microbleeds (CMB), total brain, hippocampal, and cortical gray matter volumes using adjusted multivariable regression analyses. In 2454 participants (mean age 54 ± 12 years), we observed that higher PVS burden in both BG and CSO was related to CMB in lobar and deep brain regions and increased WMH. Greater CSO PVS burden was associated with decreased total cortical gray volumes. PVS are associated with ischemic markers of CSVD and neurodegeneration markers. Further studies should elucidate the causality between PVS and other CSVD manifestations.
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Affiliation(s)
- Frances Rodriguez Lara
- Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (F.R.L.); (A.R.T.)
| | - Arturo Ruben Toro
- Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (F.R.L.); (A.R.T.)
| | - Adlin Pinheiro
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA; (A.P.); (S.D.)
- Framingham Heart Study, National Heart Lung and Blood Institute, Framingham, MA 01702, USA; (O.E.); (S.G.); (S.S.)
| | - Serkalem Demissie
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA; (A.P.); (S.D.)
- Framingham Heart Study, National Heart Lung and Blood Institute, Framingham, MA 01702, USA; (O.E.); (S.G.); (S.S.)
| | - Oluchi Ekenze
- Framingham Heart Study, National Heart Lung and Blood Institute, Framingham, MA 01702, USA; (O.E.); (S.G.); (S.S.)
- Graduate Medical Sciences, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA
| | - Oliver Martinez
- Department of Neurology, University of California Davis, Davis, CA 95817, USA; (O.M.); (C.D.); (P.M.)
| | - Pedram Parva
- Department of Radiology, Veterans Affairs Boston Healthcare System, Boston, MA 02118, USA;
- Department of Radiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA
| | - Andreas Charidimou
- Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
| | - Saptaparni Ghosh
- Framingham Heart Study, National Heart Lung and Blood Institute, Framingham, MA 01702, USA; (O.E.); (S.G.); (S.S.)
- Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
| | - Charles DeCarli
- Department of Neurology, University of California Davis, Davis, CA 95817, USA; (O.M.); (C.D.); (P.M.)
| | - Sudha Seshadri
- Framingham Heart Study, National Heart Lung and Blood Institute, Framingham, MA 01702, USA; (O.E.); (S.G.); (S.S.)
- Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA;
| | - Mohamad Habes
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA;
| | - Pauline Maillard
- Department of Neurology, University of California Davis, Davis, CA 95817, USA; (O.M.); (C.D.); (P.M.)
| | - Jose Rafael Romero
- Framingham Heart Study, National Heart Lung and Blood Institute, Framingham, MA 01702, USA; (O.E.); (S.G.); (S.S.)
- Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
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23
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Vered S, Beiser AS, Sulimani L, Sznitman S, Gonzales MM, Aparicio HJ, DeCarli C, Scott MR, Ghosh S, Lewitus GM, Meiri D, Seshadri S, Weinstein G. The association of circulating endocannabinoids with neuroimaging and blood biomarkers of neuro-injury. Alzheimers Res Ther 2023; 15:154. [PMID: 37700370 PMCID: PMC10496329 DOI: 10.1186/s13195-023-01301-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 08/29/2023] [Indexed: 09/14/2023]
Abstract
BACKGROUND Preclinical studies highlight the importance of endogenous cannabinoids (endocannabinoids; eCBs) in neurodegeneration. Yet, prior observational studies focused on limited outcome measures and assessed only few eCB compounds while largely ignoring the complexity of the eCB system. We examined the associations of multiple circulating eCBs and eCB-like molecules with early markers of neurodegeneration and neuro-injury and tested for effect modification by sex. METHODS This exploratory cross-sectional study included a random sample of 237 dementia-free older participants from the Framingham Heart Study Offspring cohort who attended examination cycle 9 (2011-2014), were 65 years or older, and cognitively healthy. Forty-four eCB compounds were quantified in serum, via liquid chromatography high-resolution mass spectrometry. Linear regression models were used to examine the associations of eCB levels with brain MRI measures (i.e., total cerebral brain volume, gray matter volume, hippocampal volume, and white matter hyperintensities volume) and blood biomarkers of Alzheimer's disease and neuro-injury (i.e., total tau, neurofilament light, glial fibrillary acidic protein and Ubiquitin C-terminal hydrolase L1). All models were adjusted for potential confounders and effect modification by sex was examined. RESULTS Participants mean age was 73.3 ± 6.2 years, and 40% were men. After adjustment for potential confounders and correction for multiple comparisons, no statistically significant associations were observed between eCB levels and the study outcomes. However, we identified multiple sex-specific associations between eCB levels and the various study outcomes. For example, high linoleoyl ethanolamide (LEA) levels were related to decreased hippocampal volume among men and to increased hippocampal volume among women (β ± SE = - 0.12 ± 0.06, p = 0.034 and β ± SE = 0.08 ± 0.04, p = 0.026, respectively). CONCLUSIONS Circulating eCBs may play a role in neuro-injury and may explain sex differences in susceptibility to accelerated brain aging. Particularly, our results highlight the possible involvement of eCBs from the N-acyl amino acids and fatty acid ethanolamide classes and suggest specific novel fatty acid compounds that may be implicated in brain aging. Furthermore, investigation of the eCBs contribution to neurodegenerative disease such as Alzheimer's disease in humans is warranted, especially with prospective study designs and among diverse populations, including premenopausal women.
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Affiliation(s)
- Shiraz Vered
- School of Public Health, University of Haifa, 199 Aba Khoushy Ave., Haifa, 3498838, Israel
| | - Alexa S Beiser
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
- The Framingham Study, Framingham, MA, 01702, USA
| | - Liron Sulimani
- The Kleifeld Laboratory, Department of Biology, Technion-Israel Institute of Technology, 3200003, Haifa, Israel
| | - Sharon Sznitman
- School of Public Health, University of Haifa, 199 Aba Khoushy Ave., Haifa, 3498838, Israel
| | - Mitzi M Gonzales
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
| | - Hugo J Aparicio
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- The Framingham Study, Framingham, MA, 01702, USA
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Sacramento, CA, 95816, USA
| | - Matthew R Scott
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Saptaparni Ghosh
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- The Framingham Study, Framingham, MA, 01702, USA
| | - Gil M Lewitus
- The Laboratory of Cancer Biology and Cannabinoid Research, Department of Biology, Technion-Israel Institute of Technology, 3200003, Haifa, Israel
| | - David Meiri
- The Laboratory of Cancer Biology and Cannabinoid Research, Department of Biology, Technion-Israel Institute of Technology, 3200003, Haifa, Israel
| | - Sudha Seshadri
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- The Framingham Study, Framingham, MA, 01702, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
| | - Galit Weinstein
- School of Public Health, University of Haifa, 199 Aba Khoushy Ave., Haifa, 3498838, Israel.
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24
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Collins AM, Molina-Hidalgo C, Aghjayan SL, Fanning J, Erlenbach ED, Gothe NP, Velazquez-Diaz D, Erickson KI. Differentiating the influence of sedentary behavior and physical activity on brain health in late adulthood. Exp Gerontol 2023; 180:112246. [PMID: 37356467 DOI: 10.1016/j.exger.2023.112246] [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: 01/30/2023] [Revised: 05/22/2023] [Accepted: 06/22/2023] [Indexed: 06/27/2023]
Abstract
Public health messaging calls for individuals to be more physically active and less sedentary, yet these lifestyle behaviors have been historically studied independently. Both physical activity (PA) and sedentary behavior (SB) are linked through time-use in a 24-hour day and are related to health outcomes, such as neurocognition. While the benefits of PA on brain health in late adulthood have been well-documented, the influence of SB remains to be understood. The purpose of this paper was to critically review the evolving work on SB and brain health in late adulthood and emphasize key areas of consideration to inform potential research. Overall, the existing literature studying the impact of SB on the components and mechanisms of brain health are mixed and inconclusive, provided largely by cross-sectional and observational work employing a variety of measurement techniques of SB and brain health outcomes. Further, many studies did not conceptually or statistically account for the role of PA in the proposed relationships. Therefore, our understanding of the way in which SB may influence neurocognition in late adulthood is limited. Future efforts should include more prospective longitudinal and randomized clinical trials with intentional methodological approaches to better understand the relationships between SB and the brain in late adulthood, and how these potential links are differentiated from PA.
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Affiliation(s)
- Audrey M Collins
- AdventHealth Research Institute, Department of Neuroscience, AdventHealth, Orlando, FL, USA.
| | | | - Sarah L Aghjayan
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jason Fanning
- Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, USA
| | - Emily D Erlenbach
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Neha P Gothe
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA
| | - Daniel Velazquez-Diaz
- AdventHealth Research Institute, Department of Neuroscience, AdventHealth, Orlando, FL, USA; Exphy Research Group, Department of Physical Education, Faculty of Education Sciences, University Hospital, University of Cadiz, 11009 Cadiz, Spain; Biomedical Research and Innovation Institute of Cadiz (INiBICA) Research Unit, Puerta del Mar University Hospital, University of Cadiz, 11009 Cadiz, Spain
| | - Kirk I Erickson
- AdventHealth Research Institute, Department of Neuroscience, AdventHealth, Orlando, FL, USA; Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
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25
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Hinman JD, Elahi F, Chong D, Radabaugh H, Ferguson A, Maillard P, Thompson JF, Rosenberg GA, Sagare A, Moghekar A, Lu H, Lee T, Wilcock D, Satizabal CL, Tracy R, Seshadri S, Schwab K, Helmer K, Singh H, Kivisäkk P, Greenberg S, DeCarli C, Kramer J. Placental growth factor as a sensitive biomarker for vascular cognitive impairment. Alzheimers Dement 2023; 19:3519-3527. [PMID: 36815663 PMCID: PMC10440207 DOI: 10.1002/alz.12974] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 11/14/2022] [Accepted: 12/19/2022] [Indexed: 02/24/2023]
Abstract
INTRODUCTION High-performing biomarkers measuring the vascular contributions to cognitive impairment and dementia are lacking. METHODS Using a multi-site observational cohort study design, we examined the diagnostic accuracy of plasma placental growth factor (PlGF) within the MarkVCID Consortium (n = 335; CDR 0-1). Subjects underwent clinical evaluation, cognitive testing, MRI, and blood sampling as defined by Consortium protocols. RESULTS In the prospective population of 335 subjects (72.2 ± 7.8 years of age, 49.3% female), plasma PlGF (pg/mL) shows an ordinal odds ratio (OR) of 1.16 (1.07-1.25; P = .0003) for increasing Fazekas score and ordinal OR of 1.22 (1.14-1.32; P < .0001) for functional cognitive impairment measured by the Clinical Dementia Rating scale. We achieved the primary study outcome of a site-independent association of plasma PlGF (pg/mL) with white matter injury and cognitive impairment in two of three study cohorts. Secondary outcomes using the full MarkVCID cohort demonstrated that plasma PlGF can significantly discriminate individuals with Fazekas ≥ 2 and CDR = 0.5 (area under the curve [AUC] = 0.74) and CDR = 1 (AUC = 0.89) from individuals with CDR = 0. DISCUSSION Plasma PlGF measured by standardized immunoassay functions as a stable, reliable, diagnostic biomarker for cognitive impairment associated with substantial white matter burden.
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Affiliation(s)
- Jason D. Hinman
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles
- Department of Neurology, West Los Angeles Veterans Association Medical Center, Department of Veterans Affairs
| | - Fanny Elahi
- Memory and Aging Center, Weill Institute for Neuroscience, University of California San Francisco
- Department of Neurology, San Francisco Veterans Association Medical Center, Department of Veterans Affairs
| | - Davis Chong
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles
| | - Hannah Radabaugh
- Department of Neurological Surgery, Weill Institute for Neuroscience, University of California San Francisco
| | - Adam Ferguson
- Department of Neurology, San Francisco Veterans Association Medical Center, Department of Veterans Affairs
- Department of Neurological Surgery, Weill Institute for Neuroscience, University of California San Francisco
| | | | | | | | - Abhay Sagare
- Zilkha Neurogenetic Institute, University of Southern California
| | | | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University
| | - Tiffany Lee
- Sanders-Brown Center on Aging, Department of Physiology, University of Kentucky
| | - Donna Wilcock
- Sanders-Brown Center on Aging, Department of Physiology, University of Kentucky
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio
| | - Russell Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio
| | - Kristin Schwab
- Department of Neurology, Massachusetts General Hospital, Harvard University
| | - Karl Helmer
- Department of Neurology, Massachusetts General Hospital, Harvard University
| | - Herpreet Singh
- Department of Neurology, Massachusetts General Hospital, Harvard University
| | - Pia Kivisäkk
- Department of Neurology, Massachusetts General Hospital, Harvard University
| | - Steve Greenberg
- Department of Neurology, Massachusetts General Hospital, Harvard University
| | | | - Joel Kramer
- Memory and Aging Center, Weill Institute for Neuroscience, University of California San Francisco
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26
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Torres-Espin A, Rabadaugh H, Fitzsimons S, Harvey D, Chou A, Lindberg C, Casaletto KB, Goldberger L, Staffaroni AM, Maillard P, Miller BL, DeCarli C, Hinman JD, Ferguson AR, Kramer JH, Elahi FM. Sexually dimorphic differences in angiogenesis markers predict brain aging trajectories. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.16.549192. [PMID: 37503183 PMCID: PMC10370093 DOI: 10.1101/2023.07.16.549192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Aberrant angiogenesis could contribute to cognitive impairment, representing a therapeutic target for preventing dementia. However, most angiogenesis studies focus on model organisms. To test the relevance of angiogenesis to human cognitive aging, we evaluated associations of circulating blood markers of angiogenesis with brain aging trajectories in two deeply phenotyped human cohorts (n=435, age 74 + 9) with longitudinal cognitive assessments, biospecimens, structural brain imaging, and clinical data. Machine learning and traditional statistics revealed sex dimorphic associations of plasma angiogenic growth factors with brain aging outcomes. Specifically, angiogenesis is associated with higher executive function and less brain atrophy in younger women (not men), a directionality of association that reverses around age 75. Higher levels of basic fibroblast growth factor, known for pleiotropic effects on multiple cell types, predicted favorable cognitive trajectories. This work demonstrates the relevance of angiogenesis to brain aging with important therapeutic implications for vascular cognitive impairment and dementia.
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27
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Stickel AM, Tarraf W, González KA, Ivanovic V, Morlett Paredes A, Zeng D, Cai J, Isasi CR, Kaplan R, Lipton RB, Daviglus M, Testai FD, Lamar M, Gallo LC, Talavera GA, Gellman MD, Ramos AR, González HM, DeCarli C. Characterizing age- and sex-related differences in brain structure among middle-aged and older Hispanic/Latino adults in the study of Latinos- investigation of neurocognitive aging magnetic resonance imaging (SOL-INCA MRI). Neurobiol Aging 2023; 126:58-66. [PMID: 36933278 PMCID: PMC10363333 DOI: 10.1016/j.neurobiolaging.2023.02.007] [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: 08/29/2022] [Revised: 02/15/2023] [Accepted: 02/15/2023] [Indexed: 02/25/2023]
Abstract
Hispanic/Latino adults are a growing segment of the older U.S. population yet are underrepresented in brain aging research. We aimed to characterize brain aging among diverse Hispanic/Latino individuals. Hispanic/Latino individuals (unweighted n = 2273 ages 35-85 years; 56% female) from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) population-based study underwent magnetic resonance imaging (MRI) as part of the SOL- Investigation of Neurocognitive Aging MRI (SOL-INCA-MRI) ancillary study (2018-2022). We performed linear regressions to calculate age associations with brain volumes for each outcome (total (global) brain, hippocampal, lateral ventricle, total white matter hyperintensity (WMH), individual cortical lobar, and total cortical gray matter) and tested modification by sex. Older age was associated with smaller gray matter volumes and larger lateral ventricle and WMH volumes. Age-related differences in global brain volumes and gray matter volumes in specific regions (i.e., the hippocampus and temporal and occipital lobes) were less pronounced among women. Our findings warrant further investigation into sex-specific mechanisms of brain aging using longitudinal studies.
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Affiliation(s)
- Ariana M Stickel
- Department of Neurosciences and Shiley-Marcos Alzheimer's Disease Research Center, University of California, San Diego, La Jolla, CA, USA; Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Wassim Tarraf
- Institute of Gerontology & Department of Healthcare Sciences, Wayne State University, Detroit, MI, USA
| | - Kevin A González
- Department of Neurosciences and Shiley-Marcos Alzheimer's Disease Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Vladamir Ivanovic
- Department of Neurology and Center for Neuroscience, University of California at Davis, Davis, CA, USA
| | - Alejandra Morlett Paredes
- Department of Neurosciences and Shiley-Marcos Alzheimer's Disease Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Donglin Zeng
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Carmen R Isasi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Robert Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Richard B Lipton
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, The Bronx, NY, USA; Department of Neurology, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, College of Medicine, Chicago, IL, USA
| | - Fernando D Testai
- Department of Neurology & Neurorehabilitation, University of Illinois at Chicago, College of Medicine, Chicago, IL, USA
| | - Melissa Lamar
- Institute for Minority Health Research, University of Illinois at Chicago, College of Medicine, Chicago, IL, USA; Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Gregory A Talavera
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Marc D Gellman
- Department of Psychology, University of Miami, Miami, FL, USA
| | - Alberto R Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Hector M González
- Department of Neurosciences and Shiley-Marcos Alzheimer's Disease Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Davis, CA, USA.
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28
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 77] [Impact Index Per Article: 77.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Huang J, Stein TD, Wang Y, Ang TFA, Tao Q, Lunetta KL, Massaro J, Akhter-Khan SC, Mez J, Au R, Farrer LA, Zhang X, Qiu WQ. Blood levels of MCP-1 modulate the genetic risks of Alzheimer's disease mediated by HLA-DRB1 and APOE for Alzheimer's disease. Alzheimers Dement 2023; 19:1925-1937. [PMID: 36396603 PMCID: PMC10182187 DOI: 10.1002/alz.12851] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/13/2022] [Accepted: 10/05/2022] [Indexed: 11/19/2022]
Abstract
INTRODUCTION C-Reactive protein (CRP) and monocyte chemoattractant protein-1 (MCP-1) are both implicated in the peripheral proinflammatory cascade and blood-brain barrier (BBB) disruption. Since the blood CRP level increases Alzheimer's disease (AD) risk depending on the apolipoprotein E (APOE) genotype, we hypothesized that the blood MCP-1 level exerts different effects on the AD risk depending on the genotypes. METHODS Using multiple regression analyses, data from the Framingham Heart Study (n = 2884) and Alzheimer's Disease Neuroimaging Initiative study (n = 231) were analyzed. RESULTS An elevated blood MCP-1 level was associated with AD risk in major histocompatibility complex, Class II, DR beta 1 (HLA-DRB1) rs9271192-AC/CC (hazard ratio [HR] = 3.07, 95% confidence interval [CI] = 1.50-6.28, p = 0.002) and in APOE ε4 carriers (HR = 3.22, 95% CI = 1.59-6.53, p = 0.001). In contrast, among HLA-DRB1 rs9271192-AA and APOE ε4 noncarriers, blood MCP-1 levels were not associated with these phenotypes. DISCUSSION Since HLA-DRB1 and APOE are expressed in the BBB, blood MCP-1 released in the peripheral inflammatory cascade may function as a mediator of the effects of HLA-DRB1 rs9271192-AC/CC and APOE ε4 genotypes on AD pathogenesis in the brain via the BBB pathways.
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Affiliation(s)
- Jinghan Huang
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Thor D. Stein
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA
- Alzheimer’s Disease Research Center, Boston University School of Medicine, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Yixuan Wang
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Ting Fang Alvin Ang
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Qiushan Tao
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
| | - Kathryn L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Joseph Massaro
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Boston University School of Medicine, Framingham, MA, USA
| | - Samia C. Akhter-Khan
- Framingham Heart Study, Boston University School of Medicine, Framingham, MA, USA
- Department of Health Service & Population Research, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Jesse Mez
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Boston University School of Medicine, Framingham, MA, USA
- Alzheimer’s Disease Research Center, Boston University School of Medicine, Boston, MA, USA
| | - Rhoda Au
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Boston University School of Medicine, Framingham, MA, USA
- Alzheimer’s Disease Research Center, Boston University School of Medicine, Boston, MA, USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Ophthalmology, Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Boston University School of Medicine, Framingham, MA, USA
- Alzheimer’s Disease Research Center, Boston University School of Medicine, Boston, MA, USA
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Wei Qiao Qiu
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
- Alzheimer’s Disease Research Center, Boston University School of Medicine, Boston, MA, USA
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30
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Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, Milà-Alomà M, Lorenzini L, Ingala S, Meije Wink A, Mutsaerts HJMM, Minguillón C, Fauria K, Molinuevo JL, Haller S, Chetelat G, Waldman A, Schwarz AJ, Barkhof F, Suridjan I, Kollmorgen G, Bayfield A, Zetterberg H, Blennow K, Suárez-Calvet M, Vilaplana V, Gispert JD. Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer's disease and neurodegeneration stratified by sex. eLife 2023; 12:e81067. [PMID: 37067031 PMCID: PMC10181824 DOI: 10.7554/elife.81067] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 04/10/2023] [Indexed: 04/18/2023] Open
Abstract
Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD, and OASIS. Brain-age delta was associated with abnormal amyloid-β, more advanced stages (AT) of AD pathology and APOE-ε4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury.
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Affiliation(s)
- Irene Cumplido-Mayoral
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
| | - Marina García-Prat
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
| | - Grégory Operto
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - Carles Falcon
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN)MadridSpain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
| | - Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Henk JMM Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - Karine Fauria
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
| | - Sven Haller
- CIRD Centre d'Imagerie Rive DroiteGenevaSwitzerland
| | - Gael Chetelat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and BrainCyceronFrance
| | - Adam Waldman
- Centre for Dementia Prevention, Edinburgh Imaging, and UK Dementia Research Institute at The University of EdinburghEdinburghUnited Kingdom
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Institutes of Neurology and Healthcare Engineering, University College LondonLondonUnited Kingdom
| | | | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, University of GothenburgMölndalSweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of NeurologyLondonUnited Kingdom
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- UK Dementia Research Institute at UCLLondonUnited Kingdom
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, University of GothenburgMölndalSweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University HospitalMölndalSweden
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
- Servei de Neurologia, Hospital del MarBarcelonaSpain
| | - Verónica Vilaplana
- Department of Signal Theory and Communications, Universitat Politècnica de CatalunyaBarcelonaSpain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN)MadridSpain
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Baeuchl C, Glöckner F, Koch C, Petzold J, Schuck NW, Smolka MN, Li SC. Dopamine differentially modulates medial temporal lobe activity and behavior during spatial navigation in young and older adults. Neuroimage 2023; 273:120099. [PMID: 37037380 DOI: 10.1016/j.neuroimage.2023.120099] [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: 09/15/2022] [Revised: 01/13/2023] [Accepted: 04/07/2023] [Indexed: 04/12/2023] Open
Abstract
Aging is associated with changes in spatial navigation behavior. In addition to an overall performance decline, older adults tend to rely more on proximal location cue information than on environmental boundary information during spatial navigation compared to young adults. The fact that older adults are more susceptible to errors during spatial navigation might be partly attributed to deficient dopaminergic modulation of hippocampal and striatal functioning. Hence, elevating dopamine levels might differentially modulate spatial navigation and memory performance in young and older adults. In this work, we administered levodopa (L-DOPA) in a double-blind within-subject, placebo-controlled design and recorded functional neuroimaging while young and older adults performed a 3D spatial navigation task in which boundary geometry or the position of a location cue were systematically manipulated. An age by intervention interaction on the neural level revealed an upregulation of brain responses in older adults and a downregulation of responses in young adults within the medial temporal lobe (including hippocampus and parahippocampus) and brainstem, during memory retrieval. Behaviorally, L-DOPA had no effect on older adults' overall memory performance; however, older adults whose spatial memory improved under L-DOPA also showed a shift towards more boundary processing under L-DOPA. In young adults, L-DOPA induced a decline in spatial memory performance in task-naïve participants. These results are consistent with the inverted-U-shaped hypothesis of dopamine signaling and cognitive function and suggest that increasing dopamine availability improves hippocampus-dependent place learning in some older adults.
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Affiliation(s)
- Christian Baeuchl
- Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.
| | - Franka Glöckner
- Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Christoph Koch
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany; International Max Planck Research School on the Life Course (LIFE), Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Aging Research, Berlin, Germany
| | - Johannes Petzold
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Nicolas W Schuck
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Aging Research, Berlin, Germany; Institute of Psychology, Universität Hamburg, Hamburg, German
| | - Michael N Smolka
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Shu-Chen Li
- Faculty of Psychology, Technische Universität Dresden, Dresden, Germany; Centre for Tactile Internet with Human-in-the-Loop, Technische Universität Dresden, Dresden, Germany
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32
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Dhana A, DeCarli C, Aggarwal NT, Dhana K, Desai P, Evans DA, Rajan KB. Serum neurofilament light chain, brain infarcts, and the risk of stroke: a prospective population-based cohort study. Eur J Epidemiol 2023; 38:427-434. [PMID: 36867286 PMCID: PMC10081967 DOI: 10.1007/s10654-023-00978-6] [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: 10/05/2022] [Accepted: 02/17/2023] [Indexed: 03/04/2023]
Abstract
Neurofilament light chain (NfL), a neuron-specific protein, has been related to several neurodegenerative diseases. In addition, elevated levels of NfL have also been observed in patients admitted to the hospital for stroke, suggesting that NfL as a biomarker may extend well beyond neurodegenerative diseases. Therefore, using data from the Chicago Health and Aging Project (CHAP), a population-based cohort study, we prospectively investigated the association of serum NfL levels with incident stroke and brain infarcts. During a follow-up of 3603 person-years, 133 (16.3%) individuals developed incident stroke, including ischemic and hemorrhagic. The HR (95%CI) of incident stroke was 1.28 (95%CI 1.10-1.50) per 1 standard deviation (SD) increase of log10 NfL serum levels. Compared to participants in the first tertile of NfL (i.e., lower levels), the risk of stroke was 1.68 times higher (95%CI 1.07-2.65) in those in the second tertile and 2.35 times higher (95%CI 1.45-3.81) in those in the third tertile of NfL. NfL levels were also positively associated with brain infarcts; 1-SD in log10 NfL levels was associated with 1.32 (95%CI 1.06-1.66) higher odds of one or more brain infarcts. These results suggest that NfL may serve as a biomarker of stroke in older adults.
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Affiliation(s)
- Anisa Dhana
- Rush Institute for Healthy Aging, Rush University Medical Center, 1700 W Van Buren, Suite 245, Chicago, IL, 60612, US.
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, US.
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Sacramento, CA, US
| | - Neelum T Aggarwal
- Department of Neurological Sciences and the Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, US
- Department of Neurology, Rush University Medical Center, Chicago, IL, US
| | - Klodian Dhana
- Rush Institute for Healthy Aging, Rush University Medical Center, 1700 W Van Buren, Suite 245, Chicago, IL, 60612, US
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, US
| | - Pankaja Desai
- Rush Institute for Healthy Aging, Rush University Medical Center, 1700 W Van Buren, Suite 245, Chicago, IL, 60612, US
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, US
| | - Denis A Evans
- Rush Institute for Healthy Aging, Rush University Medical Center, 1700 W Van Buren, Suite 245, Chicago, IL, 60612, US
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, US
| | - Kumar B Rajan
- Rush Institute for Healthy Aging, Rush University Medical Center, 1700 W Van Buren, Suite 245, Chicago, IL, 60612, US
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, US
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33
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Chung CP, Ihara M, Hilal S, Chen LK. Targeting cerebral small vessel disease to promote healthy aging: Preserving physical and cognitive functions in the elderly. Arch Gerontol Geriatr 2023; 110:104982. [PMID: 36868073 DOI: 10.1016/j.archger.2023.104982] [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: 12/23/2022] [Revised: 02/15/2023] [Accepted: 02/22/2023] [Indexed: 02/27/2023]
Abstract
Cerebral small vessel disease (SVD), which is highly age-related, is the most common neuroimaging finding in community-dwelling elderly individuals. In addition to increasing the risk of dementia and stroke, SVD is associated with cognitive and physical (particularly gait speed) functional impairments in the elderly. Here, we provide evidence suggesting covert SVD, e.g. without clinically evident stroke or dementia, as a critical target to preserve the functional ability that enables well-being in older age. First, we discuss the relationship between covert SVD and geriatric syndrome. SVD lesions found in non-demented, stroke-free elderly are actually not "silent" but are associated with accelerated age-related functional decline. We also review the brain structural and functional abnormalities associated with covert SVD and the possible mechanisms underlying their contributions to SVD-related cognitive and physical functional impairments. Finally, we reveal current data, though limited, on the management of elderly patients with covert SVD to prevent SVD lesion progression and functional decline. Although it is important in aging health, covert SVD is still under-recognized or misjudged by physicians in both neurological and geriatric professions. Improving the acknowledgment, detection, interpretation, and understanding of SVD would be a multidisciplinary priority to maintain cognitive and physical functions in the elderly. The dilemmas and future directions of clinical practice and research for the elderly with covert SVD are also included in the present review.
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Affiliation(s)
- Chih-Ping Chung
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Center for Health Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
| | - Masafumi Ihara
- Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Saima Hilal
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore; Memory Aging and Cognition Center, National University Health System, Singapore
| | - Liang-Kung Chen
- Center for Health Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; Taipei Municipal Gan-Dau Hospital (managed by Taipei Veterans General Hospital), Taipei, Taiwan.
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34
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Liampas I, Folia V, Ntanasi E, Yannakoulia M, Sakka P, Hadjigeorgiou G, Scarmeas N, Dardiotis E, Kosmidis MH. Longitudinal episodic memory trajectories in older adults with normal cognition. Clin Neuropsychol 2023; 37:304-321. [PMID: 35400289 DOI: 10.1080/13854046.2022.2059011] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
OBJECTIVE To determine the longitudinal trajectories and normative standards of episodic memory in older adults. METHODS Participants were drawn from the cognitively normal(CN) subgroup of the population-based HELIAD cohort, a fairly representative cohort of the older Greek population. Verbal and non-verbal memory were assessed using the Greek Verbal Learning Test and Medical College of Georgia-Complex Figure Test. Baseline and longitudinal associations of memory performance with age, sex and formal education were explored with linear regression analysis and generalized estimated equations. RESULTS A total of 1607 predominantly female (60%) individuals (73.82 ± 5.43 years), with a mean educational attainment of 8.17(±4.86) years were CN at baseline. Baseline analysis revealed a continuum of memory decline with aging and lower educational attainment. Women performed better in composite and verbal memory measures, while men performed better in non-verbal memory tasks. A subgroup of 761 participants with available assessments after 3.07(±0.82) years remained CN at follow-up. Composite memory scores yearly diminished by an additional 0.007 of a SD for each additional year of age at baseline. Regarding verbal learning, immediate free verbal recall, delayed free verbal recall and delayed cued verbal recall, an additional yearly decrease of 0.107, 0.043, 0.036 and 0.026 words were respectively recorded at follow-up, for each additional year of age at baseline. Women underwent steeper yearly decreases of 0.227 words in delayed cued verbal recall. No significant longitudinal associations emerged for immediate non-verbal memory, delayed non-verbal memory and immediate cued verbal recall. CONCLUSIONS In the present study, aging (but not educational attainment) was consistently associated with steeper verbal memory decline. Supplemental data for this article is available online at https://doi.org/10.1080/13854046.2022.2059011 .
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Affiliation(s)
- Ioannis Liampas
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa, Greece
| | - Vasiliki Folia
- Lab of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Eva Ntanasi
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece.,1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Paraskevi Sakka
- Athens Association of Alzheimer's Disease and Related Disorders, Marousi, Greece
| | - Georgios Hadjigeorgiou
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa, Greece.,Department of Neurology, Medical School, University of Cyprus, Nicosia, Cyprus
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece.,Taub Institute for Research in Alzheimer's Disease and the Aging Brain, the Gertrude H. Sergievsky Center, Department of Neurology, Columbia University, New York, NY, USA
| | - Efthimios Dardiotis
- Department of Neurology, University Hospital of Larissa, School of Medicine, University of Thessaly, Larissa, Greece
| | - Mary H Kosmidis
- Lab of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Oyoshi T, Maekawa K, Mitsuta Y, Hirata N. Predictors of early postoperative cognitive dysfunction in middle-aged patients undergoing cardiac surgery: retrospective observational study. J Anesth 2023; 37:357-363. [PMID: 36658371 DOI: 10.1007/s00540-023-03164-w] [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: 10/21/2022] [Accepted: 01/10/2023] [Indexed: 01/21/2023]
Abstract
PURPOSE This study aimed to identify the incidence and risk factors of early post-operative cognitive dysfunction (POCD) in middle-aged patients undergoing cardiac surgery. METHODS Data were examined retrospectively from 71 patients aged 46-64 years who underwent elective cardiac surgery. Magnetic resonance imaging (MRI) and MR angiography were obtained preoperatively to assess prior cerebral infarctions, carotid artery stenosis, and intracranial arterial stenosis. Patients also completed six neuropsychological tests of memory, attention, and executive function before and after surgery. Mild cognitive impairment (MCI) was defined as performance 1.5 standard deviations (SD) below the population means on any neurocognitive battery, whereas POCD was defined as a decrease of 1 SD population means on at least two in the test battery. Patient characteristics were analyzed using univariate analysis, and independent predictors were analyzed using multivariate logistic regression analysis. RESULTS After surgery, 25 patients (35%) were assessed with POCD. Patients with POCD had significantly higher rates of preoperative MCI and cerebral infarcts on MRI. Multivariate logistic regression analysis identified preoperative MCI and cerebral infarctions detected by MRI as a predictor of POCD. CONCLUSION More than one-third of middle-aged patients undergoing cardiac surgery developed POCD. Our findings suggested preoperative MCI and infarcts detected by MRI were risk factors for POCD in these middle-aged patients.
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Affiliation(s)
- Takafumi Oyoshi
- Departments of Anesthesiology, Kumamoto Chuo Hospital, 1-5-1 Tainoshima, Minami-ku, Kumamoto, 862-0965, Japan.,Department of Anesthesiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Chuo-ku, Kumamoto, 860-8556, Japan
| | - Kengo Maekawa
- Departments of Anesthesiology, Kumamoto Chuo Hospital, 1-5-1 Tainoshima, Minami-ku, Kumamoto, 862-0965, Japan
| | - Yuki Mitsuta
- Departments of Anesthesiology, Kumamoto Chuo Hospital, 1-5-1 Tainoshima, Minami-ku, Kumamoto, 862-0965, Japan.,Department of Anesthesiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Chuo-ku, Kumamoto, 860-8556, Japan
| | - Naoyuki Hirata
- Department of Anesthesiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Chuo-ku, Kumamoto, 860-8556, Japan.
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Chwa WJ, Lopez OL, Longstreth W, Dai W, Raji CA. Longitudinal Patterns of Brain Changes in a Community Sample in Relation to Aging and Cognitive Status. J Alzheimers Dis 2023; 94:1035-1045. [PMID: 37355895 PMCID: PMC10674101 DOI: 10.3233/jad-230080] [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] [Indexed: 06/26/2023]
Abstract
BACKGROUND Aging and Alzheimer's disease (AD) are characterized by widespread cortical and subcortical atrophy. Though atrophy patterns between aging and AD overlap considerably, regional differences between these two conditions may exist. Few studies, however, have investigated these patterns in large community samples. OBJECTIVE Elaborate longitudinal changes in brain morphometry in relation to aging and cognitive status in a well-characterized community cohort. METHODS Clinical and neuroimaging data were compiled from 72 participants from the Cardiovascular Health Study-Cognition Study, a community cohort of healthy aging and probable AD participants. Two time points were identified for each participant with a mean follow-up time of 5.36 years. MRI post-processing, morphometric measurements, and statistical analyses were performed using FreeSurfer, Version 7.1.1. RESULTS Cortical volume was significantly decreased in the bilateral superior frontal, bilateral inferior parietal, and left superior parietal regions, among others. Cortical thickness was significantly reduced in the bilateral superior frontal and left inferior parietal regions, among others. Overall gray and white matter volumes and hippocampal subfields also demonstrated significant reductions. Cortical volume atrophy trajectories between cognitively stable and cognitively declined participants were significantly different in the right postcentral region. CONCLUSION Observed volume reductions were consistent with previous studies investigating morphometric brain changes. Patterns of brain atrophy between AD and aging may be different in magnitude but exhibit widespread spatial overlap. These findings help characterize patterns of brain atrophy that may reflect the general population. Larger studies may more definitively establish population norms of aging and AD-related neuroimaging changes.
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Affiliation(s)
- Won Jong Chwa
- Saint Louis University School of Medicine, St. Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Oscar L. Lopez
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - W.T. Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, USA
| | - Weiying Dai
- Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, USA
| | - Cyrus A. Raji
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
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Ekenze O, Pinheiro A, Demissie S, Aparicio HJ, Charidimou A, Beiser AS, Satizabal CL, Kautz T, DeCarli C, Greenberg S, Seshadri S, Romero JR. Association of MRI Visible Perivascular Spaces and Neurofilament Light Chain: The Framingham Heart Study. J Alzheimers Dis 2023; 95:1133-1145. [PMID: 37661877 PMCID: PMC11298784 DOI: 10.3233/jad-221260] [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] [Indexed: 09/05/2023]
Abstract
BACKGROUND Neurofilament light chain (NfL) is a marker of neuronal injury. Perivascular spaces (PVS) visible on magnetic resonance imaging (MRI) represent cerebral small vessel disease (CSVD) but their role as markers of neuronal injury needs further clarification. OBJECTIVE To relate PVS burden according to brain topography and plasma NfL. METHODS Framingham Heart Study (FHS) participants with brain MRI and NfL measurements were included. PVS were rated in the basal ganglia (BG) and centrum semiovale (CSO) using validated methods and categorized based on counts. A mixed region variable representing high burden PVS in either BG or CSO was assessed. Multivariable linear regression analyses were used to relate PVS burden to log-transformed NfL levels in models adjusted for age, sex, FHS cohort, time between MRI and clinic exam, and image view (model 1), vascular risk factors (model 2), and white matter hyperintensity volume, covert brain infarcts, and cerebral microbleeds (model 3). RESULTS Among 1,457 participants (68.1±8.5 years, 45% males), NfL levels increased with higher PVS burden. Multivariable analysis showed an association of high PVS burden strictly in BG with NfL (β= 0.117, 95% CI 0.014-0.221; p = 0.027), but attenuated in model 3. The associations were mainly in participants≥65 years (β= 0.122, 95% CI 0.015-0.229, p = 0.026), women (β= 0.156, 95% CI 0.024-0.288, p = 0.021), and APOE ɛ4 non-carriers (β= 0.140, 95% CI 0.017-0.263, p = 0.026). CONCLUSIONS The association of strictly BG high PVS burden with NfL suggests a role for PVS as markers of neuroaxonal injury, but our results are hypothesis generating and require further replication.
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Affiliation(s)
- Oluchi Ekenze
- Graduate Medical Sciences, Boston University School of Medicine, Boston, MA, USA
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
| | - Adlin Pinheiro
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Serkalem Demissie
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Hugo J. Aparicio
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Andreas Charidimou
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Alexa S. Beiser
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Claudia L. Satizabal
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
- Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX, USA
| | - Tiffany Kautz
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Davis, CA, USA
| | - Steven Greenberg
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Sudha Seshadri
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Jose R. Romero
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
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Pase MP, Pinheiro A, Rowsthorn E, Demissie S, Hurmez S, Aparicio HJ, Rodriguez-Lara F, Gonzales MM, Beiser A, DeCarli C, Seshadri S, Romero JR. MRI Visible Perivascular Spaces and the Risk of Incident Mild Cognitive Impairment in a Community Sample. J Alzheimers Dis 2023; 96:103-112. [PMID: 37742645 PMCID: PMC10846532 DOI: 10.3233/jad-230445] [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] [Indexed: 09/26/2023]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) visible perivascular spaces (PVS) are associated with the risk of incident dementia but their association with the early stages of cognitive impairment remains equivocal. OBJECTIVE We examined the association between MRI visible PVS and the risk of incident mild cognitive impairment (MCI) in the community-based Framingham Heart Study (FHS). METHODS FHS participants aged at least 50 years free of stroke, cognitive impairment, and dementia at the time of MRI were included. PVS were rated according to severity in the basal ganglia and centrum semiovale (CSO) using established criteria. Cox regression analyses were used to relate PVS to incident MCI adjusted for demographic and cardiovascular variables. RESULTS The mean age of the sample (1,314 participants) at MRI was 68 years (SD, 9; 54% women). There were 263 cases of incident MCI over a median 7.4 years follow-up (max, 19.8 years). MCI risk increased with higher PVS severity in the CSO. Relative to persons with the lowest severity rating, persons with the highest severity rating in the CSO had a higher risk of incident MCI (hazard ratio [HR] = 2.55; 95% confidence interval [CI], 1.48-4.37; p = 0.0007). In secondary analysis, this association seemed stronger in women. Risk of incident MCI was nominally higher for participants with the highest severity grade of PVS in the basal ganglia, though not statistically significant relative to the lowest grade (HR = 2.19; 95% CI, 0.78-6.14; p = 0.14). CONCLUSIONS PVS burden in the CSO may be a risk marker for early cognitive impairment.
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Affiliation(s)
- Matthew P. Pase
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
| | - Adlin Pinheiro
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ella Rowsthorn
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
| | - Serkalem Demissie
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Saoresho Hurmez
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
| | - Hugo J. Aparicio
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | | | - Mitzi M. Gonzales
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Alexa Beiser
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Charles DeCarli
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, University of California at Davis, Davis, CA, USA
| | - Sudha Seshadri
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Jose Rafael Romero
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
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Nair P, Prasad K, Balasundaram P, Vibha D, Nand Dwivedi S, Gaikwad SB, Srivastava AK, Verma V. Multimodal imaging of the aging brain: Baseline findings of the LoCARPoN study. AGING BRAIN 2023; 3:100075. [PMID: 37180873 PMCID: PMC10173278 DOI: 10.1016/j.nbas.2023.100075] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/07/2023] [Accepted: 04/11/2023] [Indexed: 05/16/2023] Open
Abstract
We quantified and investigated multimodal brain MRI measures in the LoCARPoN Study due to lack of normative data among Indians. A total of 401 participants (aged 50-88 years) without stroke or dementia completed MRI investigation. We assessed 31 brain measures in total using four brain MRI modalities, including macrostructural (global & lobar volumes, white matter hyperintensities [WMHs]), microstructural (global and tract-specific white matter fractional anisotropy [WM-FA] and mean diffusivity [MD]) and perfusion measures (global and lobar cerebral blood flow [CBF]). The absolute brain volumes of males were significantly larger than those of females, but such differences were relatively small (<1.2% of intracranial volume). With increasing age, lower macrostructural brain volumes, lower WM-FA, greater WMHs, higher WM-MD were found (P = 0.00018, Bonferroni threshold). Perfusion measures did not show significant differences with increasing age. Hippocampal volume showed the greatest association with age, with a reduction of approximately 0.48%/year. This preliminary study augments and provides insight into multimodal brain measures during the nascent stages of aging among the Indian population (South Asian ethnicity). Our findings establish the groundwork for future hypothetical testing studies.
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Affiliation(s)
- Pallavi Nair
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, India
| | - Kameshwar Prasad
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, India
- Department of Neurology, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India
- Corresponding author at: Director’s Cell, Rajendra Institute of Medical Sciences, Ranchi 834009, Jharkhand, India.
| | - Parthiban Balasundaram
- Department of Neuroradiology, All India Institute of Medical Sciences, New Delhi, India
- Department of Neuroradiology, Kings College Hospital, London, UK
| | - Deepti Vibha
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, India
| | - Sada Nand Dwivedi
- Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India
| | | | - Achal K. Srivastava
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, India
| | - Vivek Verma
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, India
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Short MI, Fohner AE, Skjellegrind HK, Beiser A, Gonzales MM, Satizabal CL, Austin TR, Longstreth W, Bis JC, Lopez O, Hveem K, Selbæk G, Larson MG, Yang Q, Aparicio HJ, McGrath ER, Gerszten RE, DeCarli CS, Psaty BM, Vasan RS, Zare H, Seshadri S. Proteome Network Analysis Identifies Potential Biomarkers for Brain Aging. J Alzheimers Dis 2023; 96:1767-1780. [PMID: 38007645 PMCID: PMC10741337 DOI: 10.3233/jad-230145] [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] [Accepted: 10/04/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND Alzheimer's disease and related dementias (ADRD) involve biological processes that begin years to decades before onset of clinical symptoms. The plasma proteome can offer insight into brain aging and risk of incident dementia among cognitively healthy adults. OBJECTIVE To identify biomarkers and biological pathways associated with neuroimaging measures and incident dementia in two large community-based cohorts by applying a correlation-based network analysis to the plasma proteome. METHODS Weighted co-expression network analysis of 1,305 plasma proteins identified four modules of co-expressed proteins, which were related to MRI brain volumes and risk of incident dementia over a median 20-year follow-up in Framingham Heart Study (FHS) Offspring cohort participants (n = 1,861). Analyses were replicated in the Cardiovascular Health Study (CHS) (n = 2,117, mean 6-year follow-up). RESULTS Two proteomic modules, one related to protein clearance and synaptic maintenance (M2) and a second to inflammation (M4), were associated with total brain volume in FHS (M2: p = 0.014; M4: p = 4.2×10-5). These modules were not significantly associated with hippocampal volume, white matter hyperintensities, or incident all-cause or AD dementia. Associations with TCBV did not replicate in CHS, an older cohort with a greater burden of comorbidities. CONCLUSIONS Proteome networks implicate an early role for biological pathways involving inflammation and synaptic function in preclinical brain atrophy, with implications for clinical dementia.
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Affiliation(s)
- Meghan I. Short
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
- Department of Medicine, Tufts University School of Medicine, Boston, MA, USA
| | - Alison E. Fohner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Håvard K. Skjellegrind
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, NTNU, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Alexa Beiser
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center, San Antonio, TX, USA
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
| | - Thomas R. Austin
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - W.T. Longstreth
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Oscar Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kristian Hveem
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, NTNU, Levanger, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Geir Selbæk
- Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Martin G. Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Hugo J. Aparicio
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Emer R. McGrath
- Framingham Heart Study, Framingham, MA, USA
- School of Medicine, National University of Ireland Galway, Galway, Ireland
- HRB Clinical Research Facility, National University of Ireland Galway, Galway, Ireland
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Charles S. DeCarli
- Department of Neurology, School of Medicine and Imaging of Dementia and Aging Laboratory, Center for Neuroscience, University of California, Davis, Sacramento, CA, USA
| | - Bruce M. Psaty
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Boston University Center for Computing and Data Science, Boston, MA, USA
| | - Habil Zare
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Cell Systems and Anatomy, University of Texas Health Science Center, San Antonio, TX, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
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Spartano NL, Wang R, Yang Q, Chernofsky A, Murabito JM, Levy D, Vasan RS, DeCarli C, Maillard P, Seshadri S, Beiser AS. Association of Physical Inactivity with MRI Markers of Brain Aging: Assessing Mediation by Cardiometabolic and Epigenetic Factors. J Alzheimers Dis 2023; 95:561-572. [PMID: 37574733 DOI: 10.3233/jad-230289] [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] [Indexed: 08/15/2023]
Abstract
INTRODUCTION Cardiometabolic risk factors and epigenetic patterns, increased in physically inactive individuals, are associated with an accelerated brain aging process. OBJECTIVE To determine whether cardiometabolic risk factors and epigenetic patterns mediate the association of physical inactivity with unfavorable brain morphology. METHODS We included dementia and stroke free participants from the Framingham Heart Study Third Generation and Offspring cohorts who had accelerometery and brain MRI data (n = 2,507, 53.9% women, mean age 53.9 years). We examined mediation by the 2017-revised Framingham Stroke Risk Profile (FSRP, using weights for age, cardiovascular disease, atrial fibrillation, diabetes and smoking status, antihypertension medications, and systolic blood pressure) and the homeostatic model of insulin resistance (HOMA-IR) in models of the association of physical inactivity with brain aging, adjusting for age, age-squared, sex, accelerometer wear time, cohort, time from exam-to-MRI, and season. We similarly assessed mediation by an epigenetic age-prediction algorithm, GrimAge, in a smaller sample of participants who had DNA methylation data (n = 1,418). RESULTS FSRP and HOMA-IR explained 8.3-20.5% of associations of higher moderate-to-vigorous physical activity (MVPA), higher steps, and lower sedentary time with higher brain volume. Additionally, FSRP and GrimAge explained 10.3-22.0% of associations of physical inactivity with lower white matter diffusivity and FSRP explained 19.7% of the association of MVPA with lower free water accumulation. CONCLUSION Our results suggest that cardiometabolic risk factors and epigenetic patterns partially mediate the associations of physical inactivity with lower brain volume, higher white matter diffusivity, and aggregation of free water in the extracellular compartments of the brain.
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Affiliation(s)
- Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University Chobanian & Avedisian School of Medicine (BUCASM), Boston, MA, USA
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Ariel Chernofsky
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Joanne M Murabito
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine, Department of Medicine, BUCASM, Boston, MA, USA
| | - Daniel Levy
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ramachandran S Vasan
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Section of Preventive Medicine and Epidemiology, Evans Department of Medicine, BUSM, Boston, MA, USA
- Department of Epidemiology, BUSPH, Boston, MA, USA
- UT School of Public Health in San Antonio, TX, and UT Health Sciences Center in San Antonio, TX, USA
| | - Charles DeCarli
- Department of Neurology University of California Davis, Davis, CA, USA
| | - Pauline Maillard
- Department of Neurology University of California Davis, Davis, CA, USA
| | - Sudha Seshadri
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Alexa S Beiser
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
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Sungura R, Shirima G, Spitsbergen J, Mpolya E, Vianney JM. A case-control study on the driving factors of childhood brain volume loss: What pediatricians must explore. PLoS One 2022; 17:e0276433. [PMID: 36584214 PMCID: PMC9803277 DOI: 10.1371/journal.pone.0276433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 10/07/2022] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND The brain volume loss also known as brain atrophy is increasingly observed among children in the course of performing neuroimaging using CT scan and MRI brains. While severe forms of brain volume loss are frequently associated with neurocognitive changes due to effects on thought processing speed, reasoning and memory of children that eventually alter their general personality, most clinicians embark themselves in managing the neurological manifestations of brain atrophy in childhood and less is known regarding the offending factors responsible for developing pre-senile brain atrophy. It was therefore the goal of this study to explore the factors that drive the occurrence of childhood brain volume under the guidance of brain CT scan quantitative evaluation. METHODS This study was a case-control study involving 168 subjects with brain atrophy who were compared with 168 age and gender matched control subjects with normal brains on CT scan under the age of 18 years. All the children with brain CT scan were subjected to an intense review of their birth and medical history including laboratory investigation reports. RESULTS Results showed significant and influential risk factors for brain atrophy in varying trends among children including age between 14-17(OR = 1.1), male gender (OR = 1.9), birth outside facility (OR = 0.99), immaturity (OR = 1.04), malnutrition (OR = 0.97), head trauma (OR = 1.02), maternal alcoholism (OR = 1.0), antiepileptic drugs & convulsive disorders (OR = 1.0), radiation injury (OR = 1.06), space occupying lesions and ICP (OR = 1.01) and birth injury/asphyxia (OR = 1.02). CONCLUSIONS Pathological reduction of brain volume in childhood exhibits a steady trend with the increase in pediatric age, with space occupying lesions & intracranial pressure being the most profound causes of brain atrophy.
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Affiliation(s)
- Richard Sungura
- Department of Health and Biomedical Sciences, School of Life Science, Nelson Mandela- African Institution of Science and Technology, Arusha, Tanzania
- * E-mail:
| | - Gabriel Shirima
- Department of Health and Biomedical Sciences, School of Life Science, Nelson Mandela- African Institution of Science and Technology, Arusha, Tanzania
| | - John Spitsbergen
- Department of Neuroscience, Western Michigan University, Kalamazoo, MI, United States of America
| | - Emmanuel Mpolya
- Department of Health and Biomedical Sciences, School of Life Science, Nelson Mandela- African Institution of Science and Technology, Arusha, Tanzania
| | - John-Mary Vianney
- Department of Health and Biomedical Sciences, School of Life Science, Nelson Mandela- African Institution of Science and Technology, Arusha, Tanzania
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Hormonal factors moderate the associations between vascular risk factors and white matter hyperintensities. Brain Imaging Behav 2022; 17:172-184. [PMID: 36542288 DOI: 10.1007/s11682-022-00751-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/27/2022] [Indexed: 12/24/2022]
Abstract
To examine the moderation effects of hormonal factors on the associations between vascular risk factors and white matter hyperintensities in men and women, separately. White matter hyperintensities were automatically segmented and quantified in the UK Biobank dataset (N = 18,294). Generalised linear models were applied to examine (1) the main effects of vascular and hormonal factors on white matter hyperintensities, and (2) the moderation effects of hormonal factors on the relationship between vascular risk factors and white matter hyperintensities volumes. In men with testosterone levels one standard deviation higher than the mean value, smoking was associated with 27.8% higher white matter hyperintensities volumes in the whole brain. In women with a shorter post-menopause duration (one standard deviation below the mean), diabetes and higher pulse wave velocity were associated with 28.8% and 2.0% more deep white matter hyperintensities, respectively. These findings highlighted the importance of considering hormonal risk factors in the prevention and management of white matter hyperintensities.
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Romero JR, Pinheiro A, Aparicio HJ, DeCarli CS, Demissie S, Seshadri S. MRI-Visible Perivascular Spaces and Risk of Incident Dementia: The Framingham Heart Study. Neurology 2022; 99:e2561-e2571. [PMID: 36175148 PMCID: PMC9754649 DOI: 10.1212/wnl.0000000000201293] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 08/10/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Perivascular spaces (PVS) visible on MRI scans may represent key aspects in the pathophysiology of stroke and dementia, including cerebral small vessel disease and glymphatic dysfunction. This study aimed to determine the association between MRI-visible PVS burden and the risk of incident dementia. METHODS This study included community-dwelling Framingham Heart Study Original and Offspring cohort participants with available brain MRI-PVS ratings, free of stroke and dementia. Multivariable Cox proportional hazard regression was used to obtain hazard ratios (HRs) and 95% CIs of the association between MRI-visible PVS and incident dementia. PVS were rated using validated methods in the basal ganglia (BG) and centrum semiovale (CSO). The outcomes included all-cause dementia, Alzheimer dementia (AD), and vascular dementia (VaD). RESULTS One thousand four hundred forty-nine participants 50 years or older (46% male) were included. Over a median follow-up period of 8.3 years, the incidence of all-cause dementia, AD, and VaD was 15.8%, 12.5%, and 2.5%, respectively. In models that adjusted for vascular risk factors and cardiovascular disease, the hazard for dementia increased steadily as PVS burden increased, rising 2-fold for those with grade II PVS (HR 2.44, 95% CI 1.51-3.93) to 5-fold in participants with grade IV (HR 5.05, 95% CI 2.75-9.26) compared with grade I PVS in CSO. In the BG, hazards increased 1.6-fold (HR 1.62, 95% CI 1.15-2.27) for grade II to 2.6-fold (HR 2.67, 95% CI 1.04-6.88) for grade IV compared with grade I PVS. The association remained significant for CSO but not for BG, after adjustment for white matter hyperintensity volume (WMHV), covert infarcts, and total brain volume. Similar findings were observed for AD, but VaD, limited by a small number of events, was not statistically significant. DISCUSSION Higher burden of PVS in CSO was associated with increased risk of developing dementia, independent of vascular risk factors, total brain volume, WMHVs, and covert infarcts. This finding supports a role for PVS as a subclinical MRI marker to identify individuals in subclinical stages at high risk of developing dementia who may benefit from early intervention.
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Affiliation(s)
- Jose Rafael Romero
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA.
| | - Adlin Pinheiro
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| | - Hugo J Aparicio
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| | - Charles S DeCarli
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| | - Serkalem Demissie
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| | - Sudha Seshadri
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
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Baril AA, Pinheiro AA, Himali JJ, Beiser A, Sanchez E, Pase MP, Seshadri S, Demissie S, Romero JR. Lighter sleep is associated with higher enlarged perivascular spaces burden in middle-aged and elderly individuals. Sleep Med 2022; 100:558-564. [PMID: 36308914 PMCID: PMC9815141 DOI: 10.1016/j.sleep.2022.10.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/31/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND While healthy sleep is suggested to promote glymphatic clearance in the brain, poorer sleep may be associated with higher enlarged perivascular spaces (ePVS) burden, potentially representing impaired perivascular drainage. This study aims to evaluate the association between ePVS burden and polysomnographic sleep characteristics in a large community-based sample. METHODS 552 dementia and stroke-free Framingham Heart Study participants (age: 58.6 ± 8.9 years; 50.4% men) underwent a full-night in-home polysomnography. Three years later on average, participants underwent a brain MRI. ePVS were rated in the basal ganglia and centrum semiovale, and dichotomized as low burden (<20 counts, grades 1 and 2) or high burden (>20 counts, grades 3 and 4). Logistic regression analyses relating sleep variables to subsequent ePVS burden were used, adjusted for age, sex, time interval between polysomnography and MRI, ApoE ε4 allele carrier status, hypertension, and smoking. RESULTS Longer N1 sleep and shorter N3 sleep duration were associated with higher ePVS burden in the centrum semiovale. When stratifying these associations by subpopulations, longer N1 sleep duration with ePVS burden was observed especially in older individuals and hypertensive participants. Associations between ePVS burden and other sleep characteristics such as total sleep time and REM sleep duration varied according to ApoE ε4 allele carrier status. CONCLUSIONS Lighter sleep, as characterized by longer N1 sleep and shorter slow-wave sleep, is associated with higher ePVS burden. These findings suggest that sleep architecture may be involved in glymphatic clearance and cerebral small vessel disease, which could be an important biological link between sleep and dementia risk.
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Affiliation(s)
- Andrée-Ann Baril
- The Framingham Heart Study, Framingham, USA; Douglas Mental Health University Institute, Montreal, Canada; Department of Psychiatry, McGill University, Montreal, Canada
| | - Adlin A Pinheiro
- The Framingham Heart Study, Framingham, USA; Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - Jayandra J Himali
- The Framingham Heart Study, Framingham, USA; Department of Biostatistics, Boston University School of Public Health, Boston, USA; Department of Neurology, Boston University School of Medicine, Boston, USA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, USA; Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
| | - Alexa Beiser
- The Framingham Heart Study, Framingham, USA; Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - Erlan Sanchez
- Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Matthew P Pase
- The Framingham Heart Study, Framingham, USA; Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, VIC, Australia; Harvard T.H. Chan School of Public Health, Boston, USA
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, USA; Department of Neurology, Boston University School of Medicine, Boston, USA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, USA
| | - Serkalem Demissie
- The Framingham Heart Study, Framingham, USA; Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - Jose R Romero
- The Framingham Heart Study, Framingham, USA; Department of Neurology, Boston University School of Medicine, Boston, USA.
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Cooper LL, Rong J, Maillard P, Beiser A, Hamburg NM, Larson MG, DeCarli C, Vasan RS, Seshadri S, Mitchell GF. Relations of postural change in blood pressure with hypertension-mediated organ damage in middle-aged adults of the Framingham heart study: A cross-sectional study. Front Cardiovasc Med 2022; 9:1013876. [PMID: 36386360 PMCID: PMC9663798 DOI: 10.3389/fcvm.2022.1013876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 10/13/2022] [Indexed: 11/05/2022] Open
Abstract
Background Dysregulation of compensatory mechanisms to regulate blood pressure (BP) upon postural change is a phenotype of BP variability and an emerging risk factor for cardiovascular outcomes. Materials and methods We assessed postural change in BP (starting 2 min after standing from a supine position), carotid-femoral pulse wave velocity (cfPWV), and markers of hypertension-mediated organ damage (HMOD) in the heart, kidney, and brain in Framingham Third Generation, Omni-2, and New Offspring Spouse Cohort participants. We related vascular measures (postural change in BP measures and cfPWV) with HMOD in 3,495 participants (mean age 47 years, 53% women) using multivariable logistic and linear regression models. Results In multivariable-adjusted models, we did not observe significant associations of vascular measures with presence of left ventricular hypertrophy, albuminuria, covert brain infarcts, or white matter hyperintensities (Bonferroni-adjusted P-values > 0.05/20 > 0.0025). In multivariable models, greater cfPWV (est. β = 0.11 ± 0.03; P < 0.001), but not postural change in BP measures (Bonferroni-adjusted P-values > 0.05/20 > 0.0025), was associated with higher white matter free water using brain magnetic resonance imaging. In multivariable models, greater postural change in pulse pressure was associated with higher urinary albumin-creatinine ratio (est. β = 0.07 ± 0.02; P < 0.001). No other postural change in BP measure was associated with urinary albumin-creatinine ratio (Bonferroni-adjusted P-values > 0.05/20 > 0.0025). In sex-specific analyses, higher cfPWV was associated with higher urinary albumin-creatinine ratio in men (est. β: 0.11 ± 0.04; P = 0.002) but not in women (est. β: 0.03 ± 0.03; P = 0.44). We also observed marginal to strong effect modification by above vs. at/below median postural change in BP for the association of cfPWV with urinary albumin-creatinine ratio (Bonferroni-adjusted interaction P < 0.001-0.01). Vascular measures were not related to left ventricular mass index or fractional anisotropy (Bonferroni-adjusted P-values > 0.05/20 > 0.0025). Conclusion Baroreflex dysfunction is associated with greater subclinical kidney damage. Additionally, relations of higher aortic stiffness with greater kidney damage may be modified by associated baroreflex dysregulation.
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Affiliation(s)
- Leroy L. Cooper
- Department of Biology, Vassar College, Poughkeepsie, NY, United States
| | - Jian Rong
- Boston University and NHLBI’s Framingham Study, Framingham, MA, United States
| | - Pauline Maillard
- Department of Neurology and Center for Neurosciences, University of California, Davis, Davis, CA, United States
| | - Alexa Beiser
- Boston University and NHLBI’s Framingham Study, Framingham, MA, United States
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - Naomi M. Hamburg
- Evans Department of Medicine, Boston University School of Medicine, Boston, MA, United States
- Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA, United States
| | - Martin G. Larson
- Boston University and NHLBI’s Framingham Study, Framingham, MA, United States
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
- Department of Mathematics and Statistics, Boston University, Boston, MA, United States
| | - Charles DeCarli
- Department of Neurology and Center for Neurosciences, University of California, Davis, Davis, CA, United States
| | - Ramachandran S. Vasan
- Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA, United States
- Section of Cardiology, Department of Medicine, Boston University Schools of Medicine, Boston, MA, United States
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston, University Schools of Medicine, Boston, MA, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - Sudha Seshadri
- Boston University and NHLBI’s Framingham Study, Framingham, MA, United States
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX, United States
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Tao Q, Akhter-Khan SC, Ang TFA, DeCarli C, Alosco ML, Mez J, Killiany R, Devine S, Rokach A, Itchapurapu IS, Zhang X, Lunetta KL, Steffens DC, Farrer LA, Greve DN, Au R, Qiu WQ. Different loneliness types, cognitive function, and brain structure in midlife: Findings from the Framingham Heart Study. EClinicalMedicine 2022; 53:101643. [PMID: 36105871 PMCID: PMC9465265 DOI: 10.1016/j.eclinm.2022.101643] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/11/2022] [Accepted: 08/12/2022] [Indexed: 11/29/2022] Open
Abstract
Background It remains unclear whether persistent loneliness is related to brain structures that are associated with cognitive decline and development of Alzheimer's disease (AD). This study aimed to investigate the relationships between different loneliness types, cognitive functioning, and regional brain volumes. Methods Loneliness was measured longitudinally, using the item from the Center for Epidemiologic Studies Depression Scale in the Framingham Heart Study, Generation 3, with participants' average age of 46·3 ± 8·6 years. Robust regression models tested the association between different loneliness types with longitudinal neuropsychological performance (n = 2,609) and regional magnetic resonance imaging brain data (n = 1,829) (2002-2019). Results were stratified for sex, depression, and Apolipoprotein E4 (ApoE4). Findings Persistent loneliness, but not transient loneliness, was strongly associated with cognitive decline, especially memory and executive function. Persistent loneliness was negatively associated with temporal lobe volume (β = -0.18, 95%CI [-0.32, -0.04], P = 0·01). Among women, persistent loneliness was associated with smaller frontal lobe (β = -0.19, 95%CI [-0.38, -0.01], P = 0·04), temporal lobe (β = -0.20, 95%CI [-0.37, -0.03], P = 0·02), and hippocampus volumes (β = -0.23, 95%CI [-0.40, -0.06], P = 0·007), and larger lateral ventricle volume (β = 0.15, 95%CI [0.02, 0.28], P = 0·03). The higher cumulative loneliness scores across three exams, the smaller parietal, temporal, and hippocampus volumes and larger lateral ventricle were evident, especially in the presence of ApoE4. Interpretation Persistent loneliness in midlife was associated with atrophy in brain regions responsible for memory and executive dysfunction. Interventions to reduce the chronicity of loneliness may mitigate the risk of age-related cognitive decline and AD. Funding US National Institute on Aging.
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Affiliation(s)
- Qiushan Tao
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Boston University School of Medicine, USA
| | - Samia C. Akhter-Khan
- Department of Health Service & Population Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ting Fang Alvin Ang
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Slone Epidemiology Center, Boston University School of Medicine, USA
| | - Charles DeCarli
- Alzheimer's Disease Center, University of California Davis Medical Center, CA, USA
| | - Michael L. Alosco
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Alzheimer's Diesease and Chronic Traumatic Encephalopathy Research Centers, Boston University, Boston, MA, USA
| | - Jesse Mez
- Framingham Heart Study, Boston University School of Medicine, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Alzheimer's Diesease and Chronic Traumatic Encephalopathy Research Centers, Boston University, Boston, MA, USA
| | - Ronald Killiany
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Sherral Devine
- Framingham Heart Study, Boston University School of Medicine, USA
- Department of Psychiatry, Boston University School of Medicine, USA
| | - Ami Rokach
- Department of Psychology, York University, Toronto, Canada
| | - Indira Swetha Itchapurapu
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Medicine, USA
| | | | - David C. Steffens
- Department of Psychiatry, University of Connecticut School of Medicine, USA
| | - Lindsay A. Farrer
- Framingham Heart Study, Boston University School of Medicine, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Medicine, USA
| | - Douglas N. Greve
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard University School of Medicine, USA
| | - Rhoda Au
- Framingham Heart Study, Boston University School of Medicine, USA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Slone Epidemiology Center, Boston University School of Medicine, USA
| | - Wei Qiao Qiu
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
- Alzheimer's Diesease and Chronic Traumatic Encephalopathy Research Centers, Boston University, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, USA
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Hazany S, Nguyen KL, Lee M, Zhang A, Mokhtar P, Crossley A, Luthra S, Butani P, Dergalust S, Ellingson B, Hinman JD. Regional Cerebral Small Vessel Disease (rCSVD) Score: A clinical MRI grading system validated in a stroke cohort. J Clin Neurosci 2022; 105:131-136. [PMID: 36183571 PMCID: PMC10163829 DOI: 10.1016/j.jocn.2022.09.014] [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: 07/27/2022] [Revised: 09/06/2022] [Accepted: 09/20/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Current methods for quantitative assessment of cerebral small vessel disease (CSVD) ignore critical aspects of the disease, namely lesion type and regionality. We developed and tested a new scoring system for CSVD, "regional Cerebral Small Vessel Disease" (rCSVD) based on regional assessment of magnetic resonance imaging (MRI) features. METHODS 141 patients were retrospectively included with a derivation cohort of 46 consecutive brain MRI exams and a validation cohort of 95 patients with known cerebrovascular disease. We compared the predictive value of rCSVD against existing scoring methods. We determined the predictive value of rCSVD score for all-cause mortality and recurrent strokes. RESULTS 46 (44 male) veteran patients (age: 66-93 years), were included for derivation of the rCSVD score. A non-overlapping validation cohort consisted of 95 patients (89 male; age: 34-91 years) with known cerebrovascular disease were enrolled. Based on ROC analysis with comparison of AUC (Area Under the Curve), "rCSVD" score performed better compared to "total SVD score" and Fazekas score for predicting all-cause mortality (0.75 vs 0.68 vs 0.69; p = 0.046). "rCSVD" and total SVD scores were predictive of recurrent strokes in our validation cohort (p-values 0.004 and 0.001). At a median of 5.1 years (range 2-17 years) follow-up, Kaplan-Meier survival analysis demonstrated an rCSVD score of 2 to be a significant predictor of all-cause-mortality. CONCLUSION "rCSVD" score can be derived from routine brain MRI, has value in risk stratification of patients at risk of CSVD, and has potential in clinical trials once fully validated in a larger patient cohort.
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Affiliation(s)
- Saman Hazany
- Department of Radiology, VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, USA.
| | - Kim-Lien Nguyen
- Division of Cardiology and Radiology, VA Greater Los Angeles Healthcare System and David, Geffen School of Medicine at UCLA, USA
| | - Martin Lee
- Department of Biostatistics, Fielding School of Public Health at UCLA, USA
| | - Andrew Zhang
- Department of Radiology, VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, USA
| | - Parsa Mokhtar
- Department of Psychobiology, University of California Los Angeles, USA
| | - Alexander Crossley
- Department of Neurology, VA Greater Los Angeles Healthcare System and David Geffen, School of Medicine at UCLA, USA
| | - Sakshi Luthra
- College of Letters and Sciences, University of California Los Angeles, USA
| | - Pooja Butani
- Department of Neurology, VA Greater Los Angeles Healthcare System and David Geffen, School of Medicine at UCLA, USA
| | - Sunita Dergalust
- Department of Pharmacy, VA Greater Los Angeles Healthcare System, USA
| | - Benjamin Ellingson
- Department of Radiology and Psychiatry, David Geffen School of Medicine at UCLA, USA
| | - Jason D Hinman
- Department of Neurology, VA Greater Los Angeles Healthcare System and David Geffen, School of Medicine at UCLA, USA
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Nerland S, Stokkan TS, Jørgensen KN, Wortinger LA, Richard G, Beck D, van der Meer D, Westlye LT, Andreassen OA, Agartz I, Barth C. A comparison of intracranial volume estimation methods and their cross-sectional and longitudinal associations with age. Hum Brain Mapp 2022; 43:4620-4639. [PMID: 35708198 PMCID: PMC9491281 DOI: 10.1002/hbm.25978] [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: 04/06/2022] [Revised: 05/28/2022] [Accepted: 05/30/2022] [Indexed: 11/05/2022] Open
Abstract
Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI) studies, both as a covariate and as a variable of interest. Findings of associations between ICV and age have varied, potentially due to differences in ICV estimation methods. Here, we compared five commonly used ICV estimation methods and their associations with age. T1-weighted cross-sectional MRI data was included for 651 healthy individuals recruited through the NORMENT Centre (mean age = 46.1 years, range = 12.0-85.8 years) and 2410 healthy individuals recruited through the UK Biobank study (UKB, mean age = 63.2 years, range = 47.0-80.3 years), where longitudinal data was also available. ICV was estimated with FreeSurfer (eTIV and sbTIV), SPM12, CAT12, and FSL. We found overall high correlations across ICV estimation method, with the lowest observed correlations between FSL and eTIV (r = .87) and between FSL and CAT12 (r = .89). Widespread proportional bias was found, indicating that the agreement between methods varied as a function of head size. Body weight, age, sex, and mean ICV across methods explained the most variance in the differences between ICV estimation methods, indicating possible confounding for some estimation methods. We found both positive and negative cross-sectional associations with age, depending on dataset and ICV estimation method. Longitudinal ICV reductions were found for all ICV estimation methods, with annual percentage change ranging from -0.293% to -0.416%. This convergence of longitudinal results across ICV estimation methods offers strong evidence for age-related ICV reductions in mid- to late adulthood.
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Affiliation(s)
- Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
| | - Therese S Stokkan
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
| | - Kjetil N Jørgensen
- NORMENT, University of Oslo, Oslo, Norway.,Department of Psychiatry, Telemark Hospital, Skien, Norway
| | - Laura A Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
| | - Geneviève Richard
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dani Beck
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway.,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
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50
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Baril AA, Beiser AS, DeCarli C, Himali D, Sanchez E, Cavuoto M, Redline S, Gottlieb DJ, Seshadri S, Pase MP, Himali JJ. Self-reported sleepiness associates with greater brain and cortical volume and lower prevalence of ischemic covert brain infarcts in a community sample. Sleep 2022; 45:zsac185. [PMID: 35917199 PMCID: PMC9548673 DOI: 10.1093/sleep/zsac185] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 07/19/2022] [Indexed: 11/13/2022] Open
Abstract
STUDY OBJECTIVES We evaluated if self-reported sleepiness was associated with neuroimaging markers of brain aging and ischemic damage in a large community-based sample. METHODS Participants from the Framingham Heart Study Offspring cohort (n = 468, 62.5 ± 8.7 years old, 49.6%M) free of dementia, stroke, and neurological diseases, completed sleep questionnaires and polysomnography followed by magnetic resonance imaging (MRI), 3 years later on average. We used linear and logistic regression models to evaluate the associations between Epworth Sleepiness Scale (ESS) scores and total brain, cortical and subcortical gray matter, and white matter hyperintensities volumes, and the presence of covert brain infarcts. RESULTS Higher sleepiness scores were associated with larger total brain volume, greater cortical gray matter volume, and a lower prevalence of covert brain infarcts, even when adjusting for a large array of potential confounders, including demographics, sleep profiles and disorders, organic health diseases, and proxies for daytime cognitive and physical activities. Interactions indicated that more sleepiness was associated with larger cortical gray matter volume in men only and in APOE ε4 noncarriers, whereas a trend for smaller cortical gray matter volume was observed in carriers. In longitudinal analyses, those with stable excessive daytime sleepiness over time had greater total brain and cortical gray matter volumes, whereas baseline sleepiness scores were not associated with subsequent atrophy or cognitive decline. CONCLUSION Our findings suggest that sleepiness is not necessarily a marker of poor brain health when not explained by diseases or sleep debt and sleep disorders. Rather, sleepiness could be a marker of preserved sleep-regulatory processes and brain health in some cases.
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Affiliation(s)
- Andrée-Ann Baril
- The Framingham Heart Study, Framingham, MA, USA
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Alexa S Beiser
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, CA, USA
| | | | - Erlan Sanchez
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Marina Cavuoto
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, VIC, Australia
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Daniel J Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Matthew P Pase
- The Framingham Heart Study, Framingham, MA, USA
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, VIC, Australia
- Harvard T.H. Chan School of Public Health, MA, USA
| | - Jayandra J Himali
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
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