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Cui J, Robert C, Teh CM, Jun Yi EC, Chong JR, Tan BY, Venketasubramanian N, Lai MKP, Chen C, Hilal S. Interactive effect of diabetes mellitus and subclinical MRI markers of cerebrovascular disease on cognitive decline and incident dementia: a memory-clinic study. Alzheimers Res Ther 2024; 16:214. [PMID: 39363381 PMCID: PMC11448036 DOI: 10.1186/s13195-024-01577-7] [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: 06/06/2024] [Accepted: 09/14/2024] [Indexed: 10/05/2024]
Abstract
BACKGROUND Cognitive impairment is an increasingly recognized comorbidity of diabetes, yet the mechanisms underlying this association remain poorly understood. This knowledge gap has contributed to conflicting findings regarding the impact of diabetes on long-term cognitive outcomes in older adults. The presence of cerebrovascular disease (CeVD) may potentially modify this relationship. However, interactive effect between diabetes and subclinical MRI markers of CeVD on cognitive trajectories and incident dementia remains unexplored. METHODS A total of 654 participants underwent brain MRI at baseline, from whom 614 with at least one follow-up were selected for longitudinal analysis. Cognitive tests were performed annually up to 5 years. CeVD markers of interest were lacunes, white matter hyperintensities (WMHs), cerebral microbleeds (CMBs), cortical microinfarcts (CMIs), intracranial stenosis (ICS), and cortical infarcts. Blood-based Alzheimer biomarkers, including p-tau181 and p-tau181/Aβ42 ratio, were used as indicators of Alzheimer pathology. RESULTS At baseline, diabetes was associated with lower cognitive performance and higher burden of CeVD, but not p-tau181 or p-tau181/Aβ42 ratio. Longitudinally, we found an interactive effect of diabetes and WMHs, rather than an independent effect of diabetes, on cognitive decline and dementia risk. Subgroup analyses showed association of diabetes with cognitive outcomes was stronger in participants with high WMHs load but non-significant in those with low WMHs load. Moreover, these associations remained unchanged after adjusting for blood-based Alzheimer biomarkers. CONCLUSIONS The effect of diabetes on cognitive decline is contingent upon the presence of WMHs and independent of Alzheimer's pathology. This finding raises the possibility of utilizing WMHs as an imaging biomarker to identify diabetic subgroup at greater risk of developing cognitive impairment. Furthermore, therapeutic interventions targeting WMHs may prevent cognitive deterioration in older adults with diabetes.
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Affiliation(s)
- Jiangbo Cui
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore
| | - Caroline Robert
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore
| | - Chia May Teh
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore
| | - Eddie Chong Jun Yi
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore
| | - Joyce R Chong
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore
| | | | | | - Mitchell K P Lai
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore
| | - Christopher Chen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore
| | - Saima Hilal
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore.
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
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Uchida Y, Nishimaki K, Soldan A, Moghekar A, Albert M, Oishi K. Acceleration of Brain Atrophy and Progression From Normal Cognition to Mild Cognitive Impairment. JAMA Netw Open 2024; 7:e2441505. [PMID: 39476236 PMCID: PMC11525609 DOI: 10.1001/jamanetworkopen.2024.41505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2024] [Accepted: 08/27/2024] [Indexed: 11/02/2024] Open
Abstract
Importance It remains unclear which risk factors accelerate brain atrophy along with a progression from normal cognition to mild cognitive impairment (MCI). Objective To examine risk factors associated with the acceleration of brain atrophy and progression from normal cognition to MCI based on long-term longitudinal data for middle-aged and older adults. Design, Setting, and Participants Data for this cohort study were extracted from the Biomarkers for Older Controls at Risk for Dementia (BIOCARD) cohort, initiated at the National Institutes of Health from January 1, 1995, to December 31, 2005, and continued at Johns Hopkins University from January 1, 2015, to October 31, 2023. All participants were cognitively normal at baseline. The participants whose structural magnetic brain imaging (MRI) of the brain and cerebrospinal fluid (CSF) measures were available for over 10 years were included. Exposures Longitudinal structural MRI of the brain and measurement of CSF biomarkers for Alzheimer disease pathology (ratio of amyloid β peptide 42 [Aβ42] to Aβ40, tau phosphorylated at threonine 181, and total tau). Main Outcomes and Measures Annual change rates of segmental brain volumes, Kaplan-Meier survival curves plotting time to event for progression to MCI symptom onset, and hazard ratios (HRs) determined by Cox proportional hazards regression models. Results A total of 185 participants (mean [SD] age, 55.4 [8.4] years; 116 women [63%]) were included and followed up for a maximum of 27 years (median, 20 [IQR, 18-22] years). The groups with high levels of atrophy in the white matter and enlargement in the ventricles had an earlier progression from normal cognition to MCI symptom onset (HR for white matter, 1.86 [95% CI, 1.24-2.49]; P = .001; HR for ventricles, 1.71 [95% CI, 1.19-2.24]; P = .009). Diabetes was associated with progression to MCI (HR, 1.41 [95% CI, 1.06-1.76]; P = .04), as was a low CSF Aβ42:Aβ40 ratio (HR, 1.48 [95% CI, 1.09-1.88]; P = .04), and their combination had a higher HR of 1.55 (95% CI, 1.13-1.98]; P = .03), indicating a synergic association of diabetes and amyloid pathology with MCI progression. Conclusions and Relevance In this cohort study of middle-aged and older adults, higher rates of volume change in the white matter and ventricles, along with the presence of diabetes and a low CSF Aβ42:Aβ40 ratio, were identified as important risk factors for the progression to MCI. These results support the importance of identifying individuals who have accelerated brain atrophy to optimize preventive strategies for progression to MCI.
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Affiliation(s)
- Yuto Uchida
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Kei Nishimaki
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Abhay Moghekar
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Baltimore, Maryland
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Kenichi Oishi
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Baltimore, Maryland
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Eswaran S, Knopman DS, Koton S, Kucharska-Newton AM, Liu AC, Liu C, Lutsey PL, Mosley TH, Palta P, Sharrett AR, Sullivan KJ, Walker KA, Gottesman RF, Groechel RC. Psychosocial Health and the Association Between Cerebral Small Vessel Disease Markers With Dementia: The ARIC Study. Stroke 2024; 55:2449-2458. [PMID: 39193713 DOI: 10.1161/strokeaha.124.047455] [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: 04/12/2024] [Revised: 06/27/2024] [Accepted: 07/10/2024] [Indexed: 08/29/2024]
Abstract
BACKGROUND Associations between magnetic resonance imaging markers of cerebral small vessel disease (CSVD) and dementia risk in older adults have been established, but it remains unclear how lifestyle factors, including psychosocial health, may modify this association. METHODS Social support and social isolation were assessed among participants of the community-based ARIC (Atherosclerosis Risk in Communities) Study, via self-reported questionnaires (1990-1992). Following categorization of both factors, participants were classified as having strong or poor mid-life social relationships. At visit 5 (2011-2013), participants underwent 3T brain magnetic resonance imaging quantifying CSVD measures: white matter hyperintensity volume, microbleeds (subcortical), infarcts (lacunar), and white matter integrity (diffusion tensor imaging). Incident dementia cases were identified from the time of imaging through December 31, 2020 with ongoing surveillance. Associations between CSVD magnetic resonance imaging markers and incident dementia were evaluated using Cox proportional-hazard regressions adjusted for demographic and additional risk factors (from visit 2). Effect modification by mid-life social relationships was evaluated. RESULTS Of the 1977 participants with magnetic resonance imaging, 1617 participants (60.7% women; 26.5% Black participants; mean age at visit 2, 55.4 years) were examined. In this sample, mid-life social relationships significantly modified the association between white matter hyperintensity volume and dementia risk (P interaction=0.001). Greater white matter hyperintensity volume was significantly associated with risk of dementia in all participants, yet, more substantially in those with poor (hazard ratio, 1.84 [95% CI, 1.49-2.27]) versus strong (hazard ratio, 1.26 [95% CI, 1.08-1.47]) mid-life social relationships. Although not statistically significant, subcortical microbleeds in participants with poor mid-life social relationships were associated with a greater risk of dementia, relative to those with strong social relationships, in whom subcortical microbleeds were no longer associated with elevated dementia risk. CONCLUSIONS The elevated risk of dementia associated with CSVD may be reduced in participants with strong mid-life social relationships. Future studies evaluating psychosocial health through the life course and the mechanisms by which they modify the relationship between CSVD and dementia are needed.
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Affiliation(s)
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN (D.S.K.)
| | - Silvia Koton
- Department of Nursing, The Stanley Steyer School of Health Professions, Tel Aviv University, Israel (S.K.)
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD (S.K., A.R.S.)
| | - Anna M Kucharska-Newton
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill (A.M.K.-N., A.C.L.)
| | - Albert C Liu
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill (A.M.K.-N., A.C.L.)
| | - Chelsea Liu
- Department of Epidemiology, George Washington University-Milken Institute School of Public Health, DC (C.L.)
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis (P.L.L.)
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., K.J.S.)
| | - Priya Palta
- Department of Neurology, University of North Carolina at Chapel Hill (P.P.)
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD (S.K., A.R.S.)
| | - Kevin J Sullivan
- Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., K.J.S.)
| | - Keenan A Walker
- National Institute on Aging Intramural Research Program, Baltimore, MD (K.A.W.)
| | - Rebecca F Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD (R.F.G., R.C.G.)
| | - Renee C Groechel
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD (R.F.G., R.C.G.)
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Power MC, Lynch KM, Bennett EE, Ying Q, Park ES, Xu X, Smith RL, Stewart JD, Yanosky JD, Liao D, van Donkelaar A, Kaufman JD, Sheppard L, Szpiro AA, Whitsel EA. A comparison of PM 2.5 exposure estimates from different estimation methods and their associations with cognitive testing and brain MRI outcomes. ENVIRONMENTAL RESEARCH 2024; 256:119178. [PMID: 38768885 PMCID: PMC11186721 DOI: 10.1016/j.envres.2024.119178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 05/16/2024] [Accepted: 05/17/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Reported associations between particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) and cognitive outcomes remain mixed. Differences in exposure estimation method may contribute to this heterogeneity. OBJECTIVES To assess agreement between PM2.5 exposure concentrations across 11 exposure estimation methods and to compare resulting associations between PM2.5 and cognitive or MRI outcomes. METHODS We used Visit 5 (2011-2013) cognitive testing and brain MRI data from the Atherosclerosis Risk in Communities (ARIC) Study. We derived address-linked average 2000-2007 PM2.5 exposure concentrations in areas immediately surrounding the four ARIC recruitment sites (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; Washington County, MD) using 11 estimation methods. We assessed agreement between method-specific PM2.5 concentrations using descriptive statistics and plots, overall and by site. We used adjusted linear regression to estimate associations of method-specific PM2.5 exposure estimates with cognitive scores (n = 4678) and MRI outcomes (n = 1518) stratified by study site and combined site-specific estimates using meta-analyses to derive overall estimates. We explored the potential impact of unmeasured confounding by spatially patterned factors. RESULTS Exposure estimates from most methods had high agreement across sites, but low agreement within sites. Within-site exposure variation was limited for some methods. Consistently null findings for the PM2.5-cognitive outcome associations regardless of method precluded empirical conclusions about the potential impact of method on study findings in contexts where positive associations are observed. Not accounting for study site led to consistent, adverse associations, regardless of exposure estimation method, suggesting the potential for substantial bias due to residual confounding by spatially patterned factors. DISCUSSION PM2.5 estimation methods agreed across sites but not within sites. Choice of estimation method may impact findings when participants are concentrated in small geographic areas. Understanding unmeasured confounding by factors that are spatially patterned may be particularly important in studies of air pollution and cognitive or brain health.
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Affiliation(s)
- Melinda C Power
- Milken Institute School of Public Health, George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, USA.
| | - Katie M Lynch
- Milken Institute School of Public Health, George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, USA
| | - Erin E Bennett
- Milken Institute School of Public Health, George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, USA
| | - Qi Ying
- Zachry Department of Civil & Environmental Engineering, Texas A&M University, 201 Dwight Look, College Station, TX, 77840, USA
| | - Eun Sug Park
- Texas A&M Transportation Institute, Texas A&M University System, 3135 TAMU, College Station, TX, 77843, USA
| | - Xiaohui Xu
- Department of Epidemiology & Biostatistics, Texas A&M Health Science Center School of Public Health, 212 Adriance Lab Rd, College Station, TX, 77843, USA
| | - Richard L Smith
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, 318 E Cameron Ave, Chapel Hill, NC, 27599, USA; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Daur Dr, Chapel Hill, NC, 27516, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Daur Dr, Chapel Hill, NC, 27516, USA
| | - Jeff D Yanosky
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, 700 HMC Cres Rd, Hershey, PA, 17033, USA
| | - Duanping Liao
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, 700 HMC Cres Rd, Hershey, PA, 17033, USA
| | - Aaron van Donkelaar
- Department of Energy, Environmental, and Chemical Engineering McKelvey School of Engineering, 1 Brookings Dr, St. Louis, MO, 63130, USA
| | - Joel D Kaufman
- Department of Medicine, School of Medicine, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA; Department of Epidemiology, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA
| | - Lianne Sheppard
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA; Department of Biostatistics, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA
| | - Adam A Szpiro
- Department of Biostatistics, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Daur Dr, Chapel Hill, NC, 27516, USA; Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, 321 S Columbia St, Chapel Hill, NC, 27599, USA
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Tarhan M, Hartl T, Shchyglo O, Colitti-Klausnitzer J, Kuhla A, Breuer TM, Manahan-Vaughan D. Changes in hippocampal volume, synaptic plasticity and amylin sensitivity in an animal model of type 2 diabetes are associated with increased vulnerability to amyloid-beta in advancing age. Front Aging Neurosci 2024; 16:1373477. [PMID: 38974903 PMCID: PMC11224464 DOI: 10.3389/fnagi.2024.1373477] [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: 01/19/2024] [Accepted: 05/28/2024] [Indexed: 07/09/2024] Open
Abstract
Type-2 diabetes (T2D) is a metabolic disorder that is considered a risk factor for Alzheimer's disease (AD). Cognitive impairment can arise due to hypoglycemia associated with T2D, and hyperamylinemia associated with insulin resistance can enhance AD pathology. We explored whether changes occur in the hippocampus in aging (6-12 months old) female V-Lep○b-/- transgenic (tg) mice, comprising an animal model of T2D. We also investigated whether an increase in vulnerability to Aβ (1-42), a known pathological hallmark of AD, is evident. Using magnetic resonance imaging we detected significant decreases in hippocampal brain volume in female tg-mice compared to wild-type (wt) littermates. Long-term potentiation (LTP) was impaired in tg compared to wt mice. Treatment of the hippocampus with Aβ (1-42) elicited a stronger debilitation of LTP in tg compared to wt mice. Treatment with an amylin antagonist (AC187) significantly enhanced LTP in wt and tg mice, and rescued LTP in Aβ (1-42)-treated tg mice. Taken together our data indicate that a T2D-like state results in an increased vulnerability of the hippocampus to the debilitating effects of Aβ (1-42) and that effects are mediated in part by changes in amylin receptor signaling.
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Affiliation(s)
- Melih Tarhan
- Department of Neurophysiology, Institute of Physiology, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Bochum, Germany
| | - Tim Hartl
- Department of Neurophysiology, Institute of Physiology, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Bochum, Germany
| | - Olena Shchyglo
- Department of Neurophysiology, Institute of Physiology, Ruhr University Bochum, Bochum, Germany
| | | | - Angela Kuhla
- Rudolf Zenker Institute for Experimental Surgery, Rostock University Medical Center, Rostock, Germany
| | | | - Denise Manahan-Vaughan
- Department of Neurophysiology, Institute of Physiology, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Bochum, Germany
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Zhang XL, Cheng XR, Wang YL, Huang YX, Wang JL. Ophthalmic Artery Morphology and Hemodynamics Associated with White Matter Hyperintensity. Int J Med Sci 2024; 21:1604-1611. [PMID: 39006846 PMCID: PMC11241099 DOI: 10.7150/ijms.94677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 05/31/2024] [Indexed: 07/16/2024] Open
Abstract
Purpose: To investigate morphological and hemodynamic characteristics of the ophthalmic artery (OA) in patients with white matter hyperintensity (WMH), and the association of the presence and severity of WMH with OA characteristics. Methods: This cross-sectional study included 44 eyes of 25 patients with WMH and 38 eyes of 19 controls. The Fazekas scale was adopted as criteria for evaluating the severity of white matter hyperintensities. The morphological characteristics of the OA were measured on the basis of three-dimensional reconstruction. The hemodynamic parameters of the OA were calculated using computational fluid dynamics simulations. Results: Compared with the control group, the diameter (16.0±0.27 mm vs. 1.71±0.18 mm, P=0.029), median blood flow velocity (0.12 m/s vs. 0.22 m/s, P<0.001), mass flow ratio (2.16% vs. 3.94%, P=0.012) and wall shear stress (2.65 Pa vs. 9.31 Pa, P<0.001) of the OA in patients with WMH were significantly decreased. After adjusting for confounding factors, the diameter, blood flow velocity, wall shear stress, and mass flow ratio of the OA were significantly associated with the presence of WMH. Male sex and high low-density protein level were associated with moderate-to-severe total WMH, and smoking was associated with the moderate-to-severe periventricular WMH. Conclusions: The diameter, blood flow velocity, mass flow ratio, and wall shear stress of the OA were independently associated with the presence of WMH. Atherosclerosis might be involved in the common mechanism of the occurrence of WMH and the OA changes.
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Affiliation(s)
- Xiao-lei Zhang
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Xue-ru Cheng
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Institute of Ophthalmology, Capital Medical University, Beijing, China
| | - Yan-ling Wang
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Institute of Ophthalmology, Capital Medical University, Beijing, China
| | - Ying-xiang Huang
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Jia-lin Wang
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Institute of Ophthalmology, Capital Medical University, Beijing, China
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Lynch KM, Bennett EE, Ying Q, Park ES, Xu X, Smith RL, Stewart JD, Liao D, Kaufman JD, Whitsel EA, Power MC. Association of Gaseous Ambient Air Pollution and Dementia-Related Neuroimaging Markers in the ARIC Cohort, Comparing Exposure Estimation Methods and Confounding by Study Site. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:67010. [PMID: 38922331 PMCID: PMC11218707 DOI: 10.1289/ehp13906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 05/15/2024] [Accepted: 05/20/2024] [Indexed: 06/27/2024]
Abstract
BACKGROUND Evidence linking gaseous air pollution to late-life brain health is mixed. OBJECTIVE We explored associations between exposure to gaseous pollutants and brain magnetic resonance imaging (MRI) markers among Atherosclerosis Risk in Communities (ARIC) Study participants, with attention to the influence of exposure estimation method and confounding by site. METHODS We considered data from 1,665 eligible ARIC participants recruited from four US sites in the period 1987-1989 with valid brain MRI data from Visit 5 (2011-2013). We estimated 10-y (2001-2010) mean carbon monoxide (CO), nitrogen dioxide (NO 2 ), nitrogen oxides (NO x ), and 8- and 24-h ozone (O 3 ) concentrations at participant addresses, using multiple exposure estimation methods. We estimated site-specific associations between pollutant exposures and brain MRI outcomes (total and regional volumes; presence of microhemorrhages, infarcts, lacunes, and severe white matter hyperintensities), using adjusted linear and logistic regression models. We compared meta-analytically combined site-specific associations to analyses that did not account for site. RESULTS Within-site exposure distributions varied across exposure estimation methods. Meta-analytic associations were generally not statistically significant regardless of exposure, outcome, or exposure estimation method; point estimates often suggested associations between higher NO 2 and NO x and smaller temporal lobe, deep gray, hippocampal, frontal lobe, and Alzheimer disease signature region of interest volumes and between higher CO and smaller temporal and frontal lobe volumes. Analyses that did not account for study site more often yielded significant associations and sometimes different direction of associations. DISCUSSION Patterns of local variation in estimated air pollution concentrations differ by estimation method. Although we did not find strong evidence supporting impact of gaseous pollutants on brain changes detectable by MRI, point estimates suggested associations between higher exposure to CO, NO x , and NO 2 and smaller regional brain volumes. Analyses of air pollution and dementia-related outcomes that do not adjust for location likely underestimate uncertainty and may be susceptible to confounding bias. https://doi.org/10.1289/EHP13906.
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Affiliation(s)
- Katie M. Lynch
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
| | - Erin E. Bennett
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
| | - Qi Ying
- Zachry Department of Civil & Environmental Engineering, Texas A&M University, College Station, Texas, USA
| | - Eun Sug Park
- Texas A&M Transportation Institute, Texas A&M University System, College Station, Texas, USA
| | - Xiaohui Xu
- Department of Epidemiology & Biostatistics, Texas A&M Health Science Center School of Public Health, College Station, Texas, USA
| | - Richard L. Smith
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James D. Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Duanping Liao
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania, USA
| | - Joel D. Kaufman
- Departments of Environmental & Occupational Health Sciences, Medicine, and Epidemiology, University of Washington, Seattle, Washington, USA
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Melinda C. Power
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
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Grasset L, Frison E, Helmer C, Catheline G, Chêne G, Dufouil C. Understanding the relationship between type-2 diabetes, MRI markers of neurodegeneration and small vessel disease, and dementia risk: a mediation analysis. Eur J Epidemiol 2024; 39:409-417. [PMID: 38190014 PMCID: PMC11101545 DOI: 10.1007/s10654-023-01080-7] [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: 04/06/2023] [Accepted: 11/03/2023] [Indexed: 01/09/2024]
Abstract
To explore to which extent neurodegeneration and cerebral small vessel disease (SVD) could mediate the association between type-2 diabetes and higher dementia risk. The analytical sample consisted in 2228 participants, out of the Three-City study, aged 65 and older, free of dementia at baseline who underwent brain MRI. Diabetes was defined by medication intake or fasting or non-fasting elevated glucose levels. Dementia status was assessed every 2 to 3 years, during up to 12 years of follow-up. Brain parenchymal fraction (BPF) and white matter hyperintensities volume (WMHV) were selected as markers of neurodegeneration and cerebral SVD respectively. We performed a mediation analysis of the effect of baseline BPF and WMHV (mediators) on the association between diabetes and dementia risk using linear and Cox models adjusted for age, sex, education level, hypertension, hypercholesterolemia, BMI, smoking and alcohol drinking status, APOE-ε4 status, and study site. At baseline, 8.8% of the participants had diabetes. Diabetes (yes vs. no) was associated with higher WMHV (βdiab = 0.193, 95% CI 0.040; 0.346) and lower BPF (βdiab = -0.342, 95% CI -0.474; -0.210), as well as with an increased risk of dementia over 12 years of follow-up (HRdiab = 1.65, 95% CI 1.04; 2.60). The association between diabetes status and dementia risk was statistically mediated by higher WMHV (HRdiab=1.05, 95% CI 1.01; 1.11, mediated part = 10.8%) and lower BPF (HRdiab = 1.12, 95% CI 1.05; 1.20, mediated part = 22.9%). This study showed that both neurodegeneration and cerebral SVD statistically explained almost 30% of the association between diabetes and dementia.
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Affiliation(s)
- Leslie Grasset
- University of Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, CIC1401-EC, F-33000, Bordeaux, France.
- INSERM U1219, University of Bordeaux, 146 rue Léo Saignat, 33077, Bordeaux cedex, France.
| | - Eric Frison
- University of Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, CIC1401-EC, F-33000, Bordeaux, France
- Service d'Information Médicale, CHU Bordeaux, Bordeaux, France
| | - Catherine Helmer
- University of Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, CIC1401-EC, F-33000, Bordeaux, France
| | - Gwénaëlle Catheline
- INCIA, EPHE, CNRS, Université PSL, University of Bordeaux, 33076, Bordeaux, France
| | - Geneviève Chêne
- University of Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, CIC1401-EC, F-33000, Bordeaux, France
- Pole de sante publique Centre Hospitalier Universitaire (CHU) de Bordeaux, 33000, Bordeaux, France
| | - Carole Dufouil
- University of Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, CIC1401-EC, F-33000, Bordeaux, France
- Pole de sante publique Centre Hospitalier Universitaire (CHU) de Bordeaux, 33000, Bordeaux, France
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9
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Feng L, Gao L. The role of neurovascular coupling dysfunction in cognitive decline of diabetes patients. Front Neurosci 2024; 18:1375908. [PMID: 38576869 PMCID: PMC10991808 DOI: 10.3389/fnins.2024.1375908] [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: 01/24/2024] [Accepted: 03/05/2024] [Indexed: 04/06/2024] Open
Abstract
Neurovascular coupling (NVC) is an important mechanism to ensure adequate blood supply to active neurons in the brain. NVC damage can lead to chronic impairment of neuronal function. Diabetes is characterized by high blood sugar and is considered an important risk factor for cognitive impairment. In this review, we provide fMRI evidence of NVC damage in diabetic patients with cognitive decline. Combined with the exploration of the major mechanisms and signaling pathways of NVC, we discuss the effects of chronic hyperglycemia on the cellular structure of NVC signaling, including key receptors, ion channels, and intercellular connections. Studying these diabetes-related changes in cell structure will help us understand the underlying causes behind diabetes-induced NVC damage and early cognitive decline, ultimately helping to identify the most effective drug targets for treatment.
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Affiliation(s)
| | - Ling Gao
- Department of Endocrinology, Renmin Hospital of Wuhan University, Wuhan, China
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10
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Shrestha S, Zhu X, Sullivan KJ, Simino J, Lutsey PL, Gottesman RF, London SJ, Griswold ME, Mosley TH. Lung Function and Brain MRI Outcomes in the Atherosclerosis Risk in Communities Neurocognitive Study. J Alzheimers Dis 2024; 100:297-308. [PMID: 38848187 PMCID: PMC11223445 DOI: 10.3233/jad-240162] [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: 06/09/2024]
Abstract
Background Brain imaging studies may provide etiologic insight into observed links between lung function and dementia and stroke. Objective We evaluated associations of lung function measures with brain MRI markers of vascular and neurodegenerative disease in the ARIC Neurocognitive Study, as few studies have examined the associations. Methods Lung function was measured at participants' midlife in 1990-1992 (mean age = 56±5 years) and later-life in 2011-2013 (mean age = 76±5 years), and brain MRI was performed in 2011-2013. Linear regression models were used to examine the associations of lung function with brain and white matter hyperintensity (WMH) volumes, and logistic regression models were used for cerebral infarcts and microbleeds, adjusting for potential confounders. Results In cross-sectional analysis (i.e., examining later-life lung function and MRI markers, n = 1,223), higher forced-expiratory volume in one second (FEV1) and forced vital capacity (FVC) were associated with larger brain and lower WMH volumes [e.g., 8.62 (95% CI:2.54-14.71) cm3 greater total brain volume per one-liter higher FEV1]. No association was seen with microbleeds in the overall sample, but higher FVC was associated with lower odds of microbleeds in never-smokers and higher odds in ever-smokers. In the cross-temporal analysis (i.e., associations with midlife lung function, n = 1,787), higher FVC levels were significantly associated with lower later-life brain volumes. Conclusions Our results support modest associations of better lung function with less neurodegenerative and cerebrovascular pathology, although findings for microbleeds were unexpected in ever-smokers.
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Affiliation(s)
- Srishti Shrestha
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS
| | - Xiaoqian Zhu
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS
| | - Kevin J. Sullivan
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS
| | - Jeannette Simino
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS
- Department of Data Science, John D. Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Rebecca F. Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD
| | - Stephanie J. London
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC
| | - Michael E. Griswold
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS
| | - Thomas H. Mosley
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS
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11
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Bao C, Liu X, Li Y, Yang J, Wei F, Gong Y, Ma Z, Liu J. Region-specific hippocampal atrophy is correlated with poor glycemic control in type 2 diabetes: a cross-sectional study. Endocr J 2023; 70:1131-1140. [PMID: 37914275 DOI: 10.1507/endocrj.ej23-0211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2023] Open
Abstract
To examine the association between prediabetes/type 2 diabetes mellitus (T2DM) and hippocampal subfields and to investigate the effects of glycemic control (HbA1c and FBG)/diabetes duration on the volume of hippocampal subfields in T2DM patients. This cross-sectional study included 268 participants from Tianjin Union Medical Center between August 2019 and July 2022. The participants were divided into three groups: T2DM, prediabetes and no diabetes. All participants underwent brain MRI examination on a 3T MRI scanner. FreeSurfer was performed to segment hippocampus automatically based on T1 MPRAGE images. The relationships between glycemic status/glycemic control/diabetes duration and hippocampal subfield volumes were estimated by multiple linear regression analysis/generalized additive modeling (GAM). Among all participants, 76 (28.36%) had prediabetes, and 96 (35.82%) had T2DM. In multi-adjusted linear regression models, those with prediabetes had a significantly lower volume of bilateral parasubiculum (βright = -5.540; βleft = -6.497). Those with diabetes had lower volume of parasubiculum (βleft = -7.868), presubiculum-head (βleft = -6.244) and fimbria (βleft = -7.187). We did not find relationship between diabetes duration and hippocampal subfield volumes. In stratified analysis, long duration with high FBG related with lower volume of right fimbria (βright = -15.583). Long duration with high HbA1c related with lower volume of presubiculum-head (βright = -19.693), subiculum-head (βright = -28.303), subiculum-body (βleft = -38.599), CA1-head (βright = -62.300, βleft = -47.922), CA1-body (βright = -19.043), CA4-body (βright = -14.392), GC-ML-DG-head (βright = -20.521), GC-ML-DG-body (βright = -16.293, βleft = -12.799), molecular_layer_HP-head (βright = -44.202, βleft = -26.071) and molecular_layer_HP-body, (βright = -31.368), hippocampal_tail (βleft = -80.073). Prediabetes related with lower bilateral parasubiculum volume, and T2DM related with lower left parasubiculum, presubiculum-head and fimbria. T2DM with chronic poor glycemic control had lower volume in multiple hippocampal subregions.
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Affiliation(s)
- Cuiping Bao
- Department of Radiology, Tianjin Union Medical Center, Nankai University, Tianjin 300121, China
| | - Xuehuan Liu
- Department of Radiology, Tianjin Union Medical Center, Nankai University, Tianjin 300121, China
| | - Yiming Li
- Department of Radiology, Tianjin Union Medical Center, Nankai University, Tianjin 300121, China
| | - Jun Yang
- Department of Radiology, Tianjin Union Medical Center, Nankai University, Tianjin 300121, China
| | - Feng Wei
- Department of Radiology, Tianjin Union Medical Center, Nankai University, Tianjin 300121, China
| | - Yi Gong
- Department of Radiology, Tianjin Union Medical Center, Nankai University, Tianjin 300121, China
| | - Zhihui Ma
- Department of Radiology, Tianjin Union Medical Center, Nankai University, Tianjin 300121, China
| | - Jun Liu
- The Fourth Central Clinical College, Tianjin Medical University, Tianjin 300140, China
- The Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin 300121, China
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12
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Li R, Geng T, Li L, Lu Q, Li R, Chen X, Ou Y, Liu S, Lin X, Tian Q, Qiu Z, Zhu K, Tang Z, Yang K, Pan A, Liu G. Associations of Glucose Metabolism Status with Brain Macrostructure and Microstructure: Findings from the UK Biobank. J Clin Endocrinol Metab 2023; 109:e234-e242. [PMID: 37497611 DOI: 10.1210/clinem/dgad442] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/11/2023] [Accepted: 07/26/2023] [Indexed: 07/28/2023]
Abstract
CONTEXT Evidence linking glucose metabolism status with brain macro- and microstructure is limited and inconsistent. OBJECTIVE We aim to investigate the associations of glucose metabolism status with brain macrostructure and microstructure, including brain volumes, subcortical gray matter volumes, and white matter microstructural metrics. METHODS This study enrolled 29 251 participants from the UK Biobank. Glucose metabolism status was classified into normal glucose metabolism (NGM), prediabetes, type 2 diabetes (T2D) with HbA1c <7%, and T2D with HbA1c ≥7%. Brain macrostructural metrics included volumes of total and subcortical gray matter, white matter, white matter hyperintensity (WMH), cerebrospinal fluid, and brain stem. Brain microstructural metrics included fractional anisotropy (FA) and mean diffusivity in white matter tracts. Multivariable linear regression models were used to estimate β values and 95% CI. RESULTS After multivariable adjustment including demographic and lifestyle factors, medical history, and total intracranial volume, those with prediabetes had smaller total and subcortical gray matter volumes than participants with NGM, while atrophy of total and subcortical gray matter was more pronounced in those with T2D (all P trend < .05). Moreover, participants with T2D had larger volumes of white matter and WMH (both P trend < .05). For brain microstructure, participants with prediabetes had lower FA values in commissural fibers (β -0.04; 95% CI -0.08, -0.003). Global and tract-specific microstructural abnormalities of white matter were observed in participants with T2D, especially for T2D with HbA1c ≥ 7% (all P trend < .05), except for FA values in projection fibers. CONCLUSION These findings suggest that interventions for hyperglycemia at an earlier stage may help protect brain health.
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Affiliation(s)
- Ruyi Li
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tingting Geng
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China
| | - Lin Li
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qi Lu
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rui Li
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue Chen
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yunjing Ou
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sen Liu
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyu Lin
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qingying Tian
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zixin Qiu
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kai Zhu
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ziyue Tang
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kun Yang
- Department of Endocrinology, Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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13
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Tatsuo S, Watanabe K, Ide S, Tsushima F, Tatsuo S, Matsuzaka M, Murakami H, Ishida M, Iwane T, Daimon M, Yodono H, Nakaji S, Kakeda S. Association of prediabetes with reduced brain volume in a general elderly Japanese population. Eur Radiol 2023; 33:5378-5384. [PMID: 36892647 DOI: 10.1007/s00330-023-09509-z] [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: 06/14/2022] [Revised: 12/30/2022] [Accepted: 02/05/2023] [Indexed: 03/10/2023]
Abstract
OBJECTIVES Diabetes frequently results in cognitive impairment, but it is less clear if brain health is adversely affected during the prediabetic stage. Our aim is to identify possible changes in brain volume as measured by magnetic resonance imaging (MRI) in a large elderly population stratified according to level of "dysglycemia." METHODS This is a cross-sectional study of 2144 participants (median age 69 years, 60.9% female) who underwent 3-T brain MRI. Participants were divided into 4 dysglycemia groups based on HbA1c levels (%): normal glucose metabolism (NGM) (< 5.7%), prediabetes (5.7 to < 6.5%), undiagnosed diabetes (6.5% or higher), and known diabetes (defined by self-report). RESULTS Of the 2144 participants, 982 had NGM, 845 prediabetes, 61 undiagnosed diabetes, and 256 known diabetes. After adjustment for age, sex, education, body weight, cognitive status, smoking, drinking, and disease history, total gray matter volume was significantly lower among participants with prediabetes (0.41% lower, standardized β = - 0.0021 [95% CI - 0.0039, - 0.00039], p = 0.016), undiagnosed diabetes (1.4% lower, standardized β = - 0.0069 [95% CI - 0.012, - 0.002], p = 0.005), and known diabetes (1.1% lower, standardized β = - 0.0055 [95% CI - 0.0081, - 0.0029], p < 0.001) compared to the NGM group. After adjustment, total white matter volume and hippocampal volume did not differ significantly between the NGM group and either the prediabetes group or the diabetes group. CONCLUSION Sustained hyperglycemia may have deleterious effects on gray matter integrity even prior to the onset of clinical diabetes. KEY POINTS • Sustained hyperglycemia has deleterious effects on gray matter integrity even prior to the onset of clinical diabetes.
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Affiliation(s)
- Soichiro Tatsuo
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Keita Watanabe
- Open Innovation Institute, Kyoto University, Kyoto, Japan
| | - Satoru Ide
- Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Japan.
| | - Fumiyasu Tsushima
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Sayuri Tatsuo
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Masashi Matsuzaka
- Department of Medical Informatics and Clinical Research Support Center, Hirosaki University Hospital, Hirosaki, Japan
| | - Hiroshi Murakami
- Department of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Mizuri Ishida
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Takuro Iwane
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Makoto Daimon
- Department of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Hiraku Yodono
- Department of Radiology, Narumi Hospital, Hirosaki, Japan
| | - Shigeyuki Nakaji
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Shingo Kakeda
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
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14
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Li C, Guo J, Zhao Y, Sun K, Abdelrahman Z, Cao X, Zhang J, Zheng Z, Yuan C, Huang H, Chen Y, Liu Z, Chen Z. Visit-to-visit HbA1c variability, dementia, and hippocampal atrophy among adults without diabetes. Exp Gerontol 2023; 178:112225. [PMID: 37263368 DOI: 10.1016/j.exger.2023.112225] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/13/2023] [Accepted: 05/26/2023] [Indexed: 06/03/2023]
Abstract
OBJECTIVES Adults without diabetes are not completely healthy; they are probably heterogeneous with several potential health problems. The management of hemoglobin A1c (HbA1c) is crucial among patients with diabetes; but whether similar management strategy is needed for adults without diabetes is unclear. Thus, this study aimed to investigate the associations of visit-to-visit HbA1c variability with incident dementia and hippocampal volume among middle-aged and older adults without diabetes, providing potential insights into this question. METHODS We conducted a prospective analysis for incident dementia in 10,792 participants (mean age 58.9 years, 47.8 % men) from the UK Biobank. A subgroup of 3793 participants (mean age 57.8 years, 48.6 % men) was included in the analysis for hippocampal volume. We defined HbA1c variability as the difference in HbA1c divided by the mean HbA1c over the 2 sequential visits ([latter - former]/mean). Dementia was identified using hospital inpatient records with ICD-9 codes. T1-structural brain magnetic resonance imaging was conducted to derive hippocampal volume (normalized for head size). The nonlinear and linear associations were examined using restricted cubic spline (RCS) models, Cox regression models, and multiple linear regression models. RESULTS During a mean follow-up (since the second round) of 8.4 years, 90 (0.8 %) participants developed dementia. The RCS models suggested no significant nonlinear associations of HbA1c variability with incident dementia and hippocampal volume, respectively (All P > 0.05). Above an optimal cutoff of HbA1c variability at 0.08, high HbA1c variability (increment in HbA1c) was associated with an increased risk of dementia (Hazard Ratio, 1.88; 95 % Confidence Interval, 1.13 to 3.14, P = 0.015), and lower hippocampal volume (coefficient, -96.84 mm3, P = 0.037), respectively, in models with adjustment of covariates including age, sex, etc. Similar results were found for a different cut-off of 0. A series of sensitivity analyses verified the robustness of the findings. CONCLUSIONS Among middle-aged and older adults without diabetes, increasing visit-to-visit HbA1c variability was associated with an increased dementia risk and lower hippocampal volume. The findings highlight the importance of monitoring and controlling HbA1c fluctuation in apparently healthy adults without diabetes.
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Affiliation(s)
- Chenxi Li
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Junyan Guo
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Yining Zhao
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Kaili Sun
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Zeinab Abdelrahman
- Department of Neurobiology, Department of Orthopedics, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou 310058, Zhejiang, China; Department of Rehabilitation Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang, China
| | - Xingqi Cao
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Jingyun Zhang
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Zhoutao Zheng
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Changzheng Yuan
- Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Huiqian Huang
- Clinical Research Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang, China
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Zuyun Liu
- School of Public Health, The Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China.
| | - Zuobing Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang, China.
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15
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Monereo-Sánchez J, Jansen JFA, Köhler S, van Boxtel MPJ, Backes WH, Stehouwer CDA, Kroon AA, Kooman JP, Schalkwijk CG, Linden DEJ, Schram MT. The association of prediabetes and type 2 diabetes with hippocampal subfields volume: The Maastricht study. Neuroimage Clin 2023; 39:103455. [PMID: 37356423 PMCID: PMC10310479 DOI: 10.1016/j.nicl.2023.103455] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/13/2023] [Accepted: 06/18/2023] [Indexed: 06/27/2023]
Abstract
AIMS/HYPOTHESIS We investigated whether prediabetes, type 2 diabetes, and continuous measures of hyperglycemia are associated with tissue volume differences in specific subfields of the hippocampus. METHODS We used cross-sectional data from 4,724 participants (58.7 ± 8.5 years, 51.5% women) of The Maastricht Study, a population-based prospective cohort. Glucose metabolism status was assessed with an oral glucose tolerance test, and defined as type 2 diabetes (n = 869), prediabetes (n = 671), or normal glucose metabolism (n = 3184). We extracted 12 hippocampal subfield volumes per hemisphere with FreeSurfer v6.0 using T1w and FLAIR 3T MRI images. We used multiple linear regression and linear trend analysis, and adjusted for total intracranial volume, demographic, lifestyle, and cardiovascular risk factors. RESULTS Type 2 diabetes was significantly associated with smaller volumes in the hippocampal subfield fimbria (standardized beta coefficient ± standard error (β ± SE) = -0.195 ± 0.04, p-value < 0.001), the hippocampus proper, i.e. Cornu Ammonis (CA) 1, CA2/3, CA4, dentate gyrus, subiculum and presubiculum (β ± SE < -0.105 ± 0.04, p-value < 0.006); as well as the hippocampal tail (β ± SE = -0.162 ± 0.04, p-value < 0.001). Prediabetes showed no significant associations. However, linear trend analysis indicated a dose-response relation from normal glucose metabolism, to prediabetes, to type 2 diabetes. Multiple continuous measures of hyperglycemia were associated with smaller volumes of the subfields fimbria (β ± SE < -0.010 ± 0.011, p-value < 0.001), dentate gyrus (β ± SE < -0.013 ± 0.010, p-value < 0.002), CA3 (β ± SE < -0.014 ± 0.011, p-value < 0.001), and tail (β ± SE < -0.006 ± 0.012, p-value < 0.003). CONCLUSIONS/INTERPRETATION Type 2 diabetes and measures of hyperglycemia are associated with hippocampal subfield atrophy, independently of lifestyle and cardiovascular risk factors. We found evidence for a dose-response relationship from normal glucose metabolism, to prediabetes, to type 2 diabetes. Prediabetes stages could give a window of opportunity for the early prevention of brain disease.
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Affiliation(s)
- Jennifer Monereo-Sánchez
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, The Netherlands
| | - Jacobus F A Jansen
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, The Netherlands.
| | - Sebastian Köhler
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, The Netherlands; Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands.
| | - Martin P J van Boxtel
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, The Netherlands; Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands.
| | - Walter H Backes
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, The Netherlands; School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands.
| | - Coen D A Stehouwer
- School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Internal Medicine, Maastricht University Medical Center, The Netherlands.
| | - Abraham A Kroon
- School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Internal Medicine, Maastricht University Medical Center, The Netherlands.
| | - Jeroen P Kooman
- Department of Internal Medicine, Maastricht University Medical Center, The Netherlands; School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.
| | - Casper G Schalkwijk
- School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Internal Medicine, Maastricht University Medical Center, The Netherlands.
| | - David E J Linden
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands.
| | - Miranda T Schram
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Internal Medicine, Maastricht University Medical Center, The Netherlands; Maastricht Heart+Vascular Center, Maastricht University Medical Center, The Netherlands.
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Scheppach JB, Wu A, Gottesman RF, Mosley TH, Arsiwala-Scheppach LT, Knopman DS, Grams ME, Sharrett AR, Coresh J, Koton S. Association of Kidney Function Measures With Signs of Neurodegeneration and Small Vessel Disease on Brain Magnetic Resonance Imaging: The Atherosclerosis Risk in Communities (ARIC) Study. Am J Kidney Dis 2023; 81:261-269.e1. [PMID: 36179945 PMCID: PMC9974563 DOI: 10.1053/j.ajkd.2022.07.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 07/21/2022] [Indexed: 11/11/2022]
Abstract
RATIONALE & OBJECTIVE Chronic kidney disease (CKD) is a risk factor for cognitive decline, but evidence is limited on its etiology and morphological manifestation in the brain. We evaluated the association of estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio (UACR) with structural brain abnormalities visible on magnetic resonance imaging (MRI). We also assessed whether this association was altered when different filtration markers were used to estimate GFR. STUDY DESIGN Cross-sectional study nested in a cohort study. SETTING & PARTICIPANTS 1,527 participants in the Atherosclerosis Risk in Communities (ARIC) Study. PREDICTORS Log(UACR) and eGFR based on cystatin C, creatinine, cystatin C and creatinine in combination, or β2-microglobulin (B2M). OUTCOMES Brain volume reduction, infarcts, microhemorrhages, white matter lesions. ANALYTICAL APPROACH Multivariable linear and logistic regression models fit separately for each predictor based on a 1-IQR difference in the predictor value. RESULTS Each 1-IQR lower eGFR was associated with reduced cortex volume (regression coefficient: -0.07 [95% CI, -0.12 to-0.02]), greater white matter hyperintensity volume (logarithmically transformed; regression coefficient: 0.07 [95% CI, 0.01-0.15]), and lower white matter fractional anisotropy (regression coefficient: -0.08 [95% CI, -0.17 to-0.01]). The results were similar when eGFR was estimated with different equations based on cystatin C, creatinine, a combination of cystatin C and creatinine, or B2M. Higher log(UACR) was similarly associated with these outcomes as well as brain infarcts and microhemorrhages (odds ratios per 1-IQR-fold greater UACR of 1.31 [95% CI, 1.13-1.52] and 1.30 [95% CI, 1.12-1.51], respectively). The degree to which brain volume was lower in regions usually susceptible to Alzheimer disease and LATE (limbic-predominant age-related TDP-43 [Tar DNA binding protein 43] encephalopathy) was similar to that seen in the rest of the cortex. LIMITATIONS No inference about longitudinal effects due to cross-sectional design. CONCLUSIONS We found eGFR and UACR are associated with structural brain damage across different domains of etiology, and eGFR- and UACR-related brain atrophy is not selective for regions typically affected by Alzheimer disease and LATE. Hence, Alzheimer disease or LATE may not be leading contributors to neurodegeneration associated with CKD.
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Affiliation(s)
- Johannes B Scheppach
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland; Department of Nephrology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Aozhou Wu
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Rebecca F Gottesman
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland; Current affiliation: National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, Maryland
| | - Thomas H Mosley
- The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi
| | | | | | - Morgan E Grams
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland; Division of Nephrology, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - A Richey Sharrett
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Josef Coresh
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Silvia Koton
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland; Stanley Steyer School of Health Professions, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
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Lai M, Lee J, Li X, Kwok C, Chong M, Zee B. Lifestyle Changes Reduced Estimated White Matter Hyperintensities Based on Retinal Image Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3530. [PMID: 36834224 PMCID: PMC9962075 DOI: 10.3390/ijerph20043530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 02/11/2023] [Accepted: 02/15/2023] [Indexed: 06/18/2023]
Abstract
This study evaluates if there is an association between lifestyle changes and the risk of small vessel disease (SVD) as measured by cerebral white matter hyperintensities (WMH) estimated by the automatic retinal image analysis (ARIA) method. We recruited 274 individuals into a community cohort study. Subjects were assessed at baseline and annually with the Health-Promoting Lifestyle Profile II Questionnaire (HPLP-II) and underwent a simple physical assessment. Retinal images were taken using a non-mydriatic digital fundus camera to evaluate the level of WMH estimated by ARIA (ARIA-WMH) to measure the risk of small vessel disease. We calculated the changes from baseline to one year for the six domains of HPLP-II and analysed the relationship with the ARIA-WMH change. A total of 193 (70%) participants completed both the HPLP-II and ARIA-WMH assessments. The mean age was 59.1 ± 9.4 years, and 76.2% (147) were women. HPLP-II was moderate (Baseline, 138.96 ± 20.93; One-year, 141.97 ± 21.85). We observed a significant difference in ARIA-WMH change between diabetes and non-diabetes subjects (0.03 vs. -0.008, respectively, p = 0.03). A multivariate analysis model showed a significant interaction between the health responsibility (HR) domain and diabetes (p = 0.005). For non-diabetes subgroups, those with improvement in the HR domain had significantly decreased in ARIA-WMH than those without HR improvement (-0.04 vs. 0.02, respectively, p = 0.003). The physical activity domain was negatively related to the change in ARIA-WMH (p = 0.02). In conclusion, this study confirms that there is a significant association between lifestyle changes and ARIA-WMH. Furthermore, increasing health responsibility for non-diabetes subjects reduces the risk of having severe white matter hyperintensities.
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Affiliation(s)
- Maria Lai
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jack Lee
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Xinxin Li
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Chloe Kwok
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Marc Chong
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Benny Zee
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
- Centre for Clinical Trials and Biostatistics Lab, CUHK Shenzhen Research Institute, Shenzhen 518057, China
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Shirzadi Z, Rabin J, Launer LJ, Bryan RN, Al-Ozairi A, Chhatwal J, Al-Ozairi E, Detre JA, Black SE, Swardfager W, MacIntosh BJ. Metabolic and Vascular Risk Factor Variability Over 25 Years Relates to Midlife Brain Volume and Cognition. J Alzheimers Dis 2023; 91:627-635. [PMID: 36683514 PMCID: PMC11004795 DOI: 10.3233/jad-220340] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
BACKGROUND Metabolic and vascular risk factors (MVRF) are associated with neurodegeneration and poor cognition. There is a need to better understand the impact of these risk factors on brain health in the decades that precede cognitive impairment. Longitudinal assessments can provide new insight regarding changes in MVRFs that are related to brain imaging features. OBJECTIVE To investigate whether longitudinal changes in MVRF spanning up to 25 years would be associated with midlife brain volume and cognition. METHODS Participants were from the CARDIA study (N = 467, age at year 25 = 50.6±3.4, female/male = 232/235, black/white = 161/306). Three models were developed, each designed to capture change over time; however, we were primarily interested in the average real variability (ARV) as a means of quantifying MVRF variability across all available assessments. RESULTS Multivariate partial least squares that used ARV metrics identified two significant latent variables (partial correlations ranged between 0.1 and 0.26, p < 0.01) that related MVRF ARV and regional brain volumes. Both latent variables reflected associations between brain volume and MVRF ARV in obesity, cholesterol, blood pressure, and glucose. Subsequent bivariate correlations revealed associations among MVRF factors, aggregate brain volume and cognition. CONCLUSION This study demonstrates that MVRF variability over time is associated with midlife brain volume in regions that are relevant to later-life cognitive decline.
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Affiliation(s)
- Zahra Shirzadi
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Jennifer Rabin
- Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada
- Rehabilitation Sciences, University of Toronto, Toronto, ON, Canada
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, Maryland, USA
| | - R Nick Bryan
- Department of Diagnostic Medicine, University of Texas, Austin, Texas, USA
| | | | - Jasmeer Chhatwal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - John A. Detre
- Center for Functional Neuroimaging, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sandra E Black
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada
| | - Walter Swardfager
- Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
- KITE, UHN-Toronto Rehab, Toronto, ON, Canada
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
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Relationship between the Responsiveness of Amyloid β Protein to Platelet Activation by TRAP Stimulation and Brain Atrophy in Patients with Diabetes Mellitus. Int J Mol Sci 2022; 23:ijms232214100. [PMID: 36430576 PMCID: PMC9697742 DOI: 10.3390/ijms232214100] [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: 10/21/2022] [Revised: 11/11/2022] [Accepted: 11/11/2022] [Indexed: 11/17/2022] Open
Abstract
Type 2 DM is a risk factor for dementia, including Alzheimer's disease (AD), and is associated with brain atrophy. Amyloid β protein (Aβ) deposition in the brain parenchyma is implicated in the neurodegeneration that occurs in AD. Platelets, known as abundant storage of Aβ, are recognized to play important roles in the onset and progression of AD. We recently showed that Aβ negatively regulates platelet activation induced by thrombin receptor-activating protein (TRAP) in healthy people. In the present study, we investigated the effects of Aβ on the TRAP-stimulated platelet activation in DM patients, and the relationship between the individual responsiveness to Aβ and quantitative findings of MRI, the volume of white matter hyperintensity (WMH)/intracranial volume (IC) and the volume of parenchyma (PAR)/IC. In some DM patients, Aβ reduced platelet aggregation induced by TRAP, while in others it was unchanged or rather enhanced. The TRAP-induced levels of phosphorylated-Akt and phosphorylated-HSP27, the levels of PDGF-AB and the released phosphorylated-HSP27 correlated with the degree of platelet aggregability. The individual levels of not WMH/IC but PAR/IC was correlated with those of TRAP-stimulated PDGF-AB release. Collectively, our results suggest that the reactivity of TRAP-stimulated platelet activation to Aβ differs in DM patients from healthy people. The anti-suppressive feature of platelet activation to Aβ might be protective for brain atrophy in DM patients.
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Savelieff MG, Chen KS, Elzinga SE, Feldman EL. Diabetes and dementia: Clinical perspective, innovation, knowledge gaps. J Diabetes Complications 2022; 36:108333. [PMID: 36240668 PMCID: PMC10076101 DOI: 10.1016/j.jdiacomp.2022.108333] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 09/30/2022] [Indexed: 10/31/2022]
Abstract
The world faces a pandemic-level prevalence of type 2 diabetes. In parallel with this massive burden of metabolic disease is the growing prevalence of dementia as the population ages. The two health issues are intertwined. The Lancet Commission on dementia prevention, intervention, and care was convened to tackle the growing global concern of dementia by identifying risk factors. It concluded, along with other studies, that diabetes as well as obesity and the metabolic syndrome more broadly, which are frequently comorbid, raise the risk of developing dementia. Type 2 diabetes is a modifiable risk factor; however, it is uncertain whether anti-diabetic drugs mitigate risk of developing dementia. Reasons are manifold but constitute a critical knowledge gap in the field. This review outlines studies of type 2 diabetes on risk of dementia, illustrating key concepts. Moreover, it identifies knowledge gaps, reviews strategies to help fill these gaps, and concludes with a series of recommendations to mitigate risk and advance understanding of type 2 diabetes and dementia.
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Affiliation(s)
- Masha G Savelieff
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kevin S Chen
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Sarah E Elzinga
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Eva L Feldman
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA.
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Deng L, Liu H, Liu W, Liao Y, Liang Q, Wang W. Alteration in topological organization characteristics of gray matter covariance networks in patients with prediabetes. ZHONG NAN DA XUE XUE BAO. YI XUE BAN = JOURNAL OF CENTRAL SOUTH UNIVERSITY. MEDICAL SCIENCES 2022; 47:1375-1384. [PMID: 36411688 PMCID: PMC10930362 DOI: 10.11817/j.issn.1672-7347.2022.220085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Indexed: 06/16/2023]
Abstract
OBJECTIVES Prediabetes is associated with an increased risk of cognitive impairment and neurodegenerative diseases. However, the exact mechanism of prediabetes-related brain diseases has not been fully elucidated. The brain structure of patients with prediabetes has been damaged to varying degrees, and these changes may affect the topological characteristics of large-scale brain networks. The structural covariance of connected gray matter has been demonstrated valuable in inferring large-scale structural brain networks. The alterations of gray matter structural covariance networks in prediabetes remain unclear. This study aims to examine the topological features and robustness of gray matter structural covariance networks in prediabetes. METHODS A total of 48 subjects were enrolled in this study, including 23 patients with prediabetes (the PD group) and 25 age-and sex-matched healthy controls (the Ctr group). All subjects' high-resolution 3D T1 images of the brain were collected by a 3.0 Tesla MR machine. Mini-mental state examination was used to evaluate the cognitive status of each subject. We calculated the gray matter volume of 116 brain regions with automated anatomical labeling (AAL) template, and constructed gray matter structural covariance networks by thresholding interregional structural correlation matrices as well as graph theoretical analysis. The area under the curve (AUC) in conjunction with permutation testing was employed for testing the differences in network measures, which included small world parameter (Sigma), normalized clustering coefficient (Gamma), normalized path length (Lambda), global efficiency, characteristic path length, local efficiency, mean clustering coefficient, and network robustness parameters. RESULTS The network in both groups followed small-world characteristics, showing that Sigma was greater than 1, the Lambda was much higher than 1, and Gamma was close to 1. Compared with the Ctr group, the network of the PD group showed increased Sigma, Lambda, and Gamma across a range of network sparsity. The Gamma of the PD group was significantly higher than that in the Ctr group in the network sparsity range of 0.12-0.16, but there was no difference between the 2 groups (all P>0.05). The grey matter network showed an increased characteristic path length and a decreased global efficiency in the PD group, but AUC analysis showed that there was no significant difference between groups (all P>0.05). For the network separation measures, the local efficiency and mean clustering coefficient of the gray matter network in the PD group were significantly increased and AUC analysis also confirmed it (P=0.001 and P=0.004, respectively). In addition, network robustness analysis showed that the grey matter network of the PD group was more vulnerable to random damage (P=0.001). CONCLUSIONS The prediabetic gray matter network shows an increased average clustering coefficient and local efficiency, and is more vulnerable to random damage than the healthy control, suggesting that the topological characteristics of the prediabetes grey matter covariant network have changed (network separation enhanced and network robustness reduced), which may provide new insights into the brain damage relevant to the disease.
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Affiliation(s)
- Lingling Deng
- Department of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China.
| | - Huasheng Liu
- Department of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China
| | - Wen Liu
- Department of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China
| | - Yunjie Liao
- Department of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China
| | - Qi Liang
- Department of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China.
| | - Wei Wang
- Department of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China
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Yu M, Jia Y, Yang D, Zhang R, Jiang Y, Zhang G, Qiao H, Han H, Shen R, Ning Z, Zhao X, Liu G, Wang Y. Association between haemoglobin A1c and cerebral microbleeds in community-based stroke-free individuals: A cross-sectional study. Diabetes Metab Res Rev 2022; 38:e3557. [PMID: 35686956 DOI: 10.1002/dmrr.3557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/22/2022] [Accepted: 06/06/2022] [Indexed: 11/08/2022]
Abstract
AIMS The association between haemoglobin A1c (HbA1c) and cerebral microbleeds (CMBs) remains unclear. We aimed to investigate the association between HbA1c and CMBs in community-based individuals without stroke or transient ischaemic attack (TIA) and whether the association differs between individuals with and without diabetes mellitus (DM). MATERIALS AND METHODS All individuals were recruited from a community in Beijing, China, from January 2015 to September 2019. All individuals completed a questionnaire and underwent blood tests and brain magnetic resonance imaging. A susceptibility-weighted imaging sequence was acquired to detect CMBs, which were defined as small, round and low-signal lesions with <10 mm diameter. The association between HbA1c and CMBs was analysed using multivariable logistic regression adjusted for demographics, medical history and blood sample test results. Subgroup analyses stratified by history of DM were performed. RESULTS Of 544 recruited individuals, 119 (21.88%) had CMBs. HbA1c was independently associated with CMBs (odds ratio [OR], 1.51; 95% confidence interval [CI], 1.03-2.22). In 87 individuals with DM, multivariable logistic analysis showed that HbA1c was significantly associated with CMBs (OR, 1.67; 95% CI, 1.04-2.69), whereas in individuals without DM, no significant association was observed between HbA1c and CMBs (OR, 1.07; 95% CI, 0.50-2.30). CONCLUSIONS HbA1c was associated with CMBs in individuals without stroke or TIA, particularly in individuals with DM, suggesting that the status of glycaemic control warrants attention for the prevention of CMBs. It would be beneficial to manage HbA1c specifically to control the risk of CMBs, especially in individuals with DM.
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Affiliation(s)
- Miaoxin Yu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yanan Jia
- Department of Neurology, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Dandan Yang
- Department of Radiology, Beijing Geriatric Hospital, Beijing, China
| | - Runhua Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yong Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Guitao Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huiyu Qiao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Hualu Han
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Rui Shen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Zihan Ning
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Gaifen Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Beijing Institute of Brain Disorders, Capital Medical University, 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
- Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China
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Reduced white matter microstructural integrity in prediabetes and diabetes: A population-based study. EBioMedicine 2022; 82:104144. [PMID: 35810560 PMCID: PMC9278067 DOI: 10.1016/j.ebiom.2022.104144] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 06/06/2022] [Accepted: 06/22/2022] [Indexed: 11/27/2022] Open
Abstract
Background White matter (WM) microstructural abnormalities have been observed in diabetes. However, evidence of prediabetes is currently lacking. This study aims to investigate the WM integrity in prediabetes and diabetes. We also assess the association of WM abnormalities with glucose metabolism status and continuous glucose measures. Methods The WM integrity was analyzed using cross-sectional baseline data from a population-based PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study. The cohort, including a total of 2218 cases with the mean age of 61.3 ± 6.6 years and 54.1% female, consisted of 1205 prediabetes which are categorized into two subgroups (a group of 254 prediabetes with combined impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) and the other group of 951 prediabetes without combined IFG/IGT), 504 diabetes, and 509 normal control subjects. Alterations of WM integrity were determined by diffusion tensor imaging along with tract-based spatial statistics analysis to compare diffusion metrics on WM skeletons between groups. The mixed-effects multivariate linear regression models were used to assess the association between WM microstructural alterations and glucose status. Findings Microstructural abnormalities distributed in local WM tracts in prediabetes with combined IFG/IGT and spread widely in diabetes. These WM abnormalities are associated with higher glucose measures. Interpretation Our findings suggest that WM microstructural abnormalities are already present at the prediabetes with combined IFG/IGT stage. Preventative strategies should begin early to maintain normal glucose metabolism and avert further destruction of WM integrity. Funding Partially supported by National Key R&D Program of China (2016YFC0901002).
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Ji S, Zhao X, Zhu R, Dong Y, Huang L, Zhang T. Metformin and the risk of dementia based on an analysis of 396,332 participants. Ther Adv Chronic Dis 2022; 13:20406223221109454. [PMID: 35847477 PMCID: PMC9277541 DOI: 10.1177/20406223221109454] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 06/01/2022] [Indexed: 11/17/2022] Open
Abstract
Background: AMPK has attracted widespread interest as a potential therapeutic target for age-related diseases, given its key role in controlling energy homeostasis. Metformin (Met) has historically been used to treat Type 2 diabetes and has been shown to counteract age-related diseases. However, studies regarding the relationship between Met and a variety of age-related classifications of cognitive decline have reported mixed findings. Objective: To assess the potential effect of Met on the onset of dementia and discuss the possible biological mechanisms involved. Methods: This study was registered in the PROSPERO database (CRD420201251468). PubMed, Embase, and Cochrane Library were searched from inception to 25 May 2021, for population-based cohort studies. Effect estimates with 95% confidence intervals (CIs) were pooled using the random-effects model. Meta-regression and subgroup analyses were performed to explore sources of heterogeneity and the stability of the results. Results: Fourteen population-based cohort studies (17 individual comparisons) involving 396,332 participants were identified. Meta-analysis showed that Met exposure was significantly associated with reduced risk of all subtypes of dementias [relative risk (RR) = 0.79, 95% CI = 0.68–0.91; p < 0.001]. Conversely, no significant reduction in risk was observed for those who received Met monotherapy at the onset of vascular dementia (VD), Parkinson’s disease (PD), and Alzheimer’s disease (AD). The effect was more prominent in patients who had long-term Met exposure (⩾4 years) (RR = 0.38, 95% CI = 0.32–0.46; p < 0.001), while no such significant effect was found with short-term Met exposure (1–2 years) (RR = 1.20, 95% CI = 0.87–1.66; p < 0.001). Moreover, no association was observed for Met exposure in participants of European descent (RR = 1.01, 95% CI = 0.66–1.54; p = 0.003) compared with those from other countries. Conclusion: Based on the evidence from population-based cohort studies, our findings suggest that the AMPK activator, Met, is a potential geroprotective agent for dementias, particularly among long-term Met users. Due to the significant heterogeneity among the included studies, we should interpret the results with caution.
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Affiliation(s)
- Shiliang Ji
- Department of pharmacy, Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Xingxing Zhao
- Department of Neonatology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Gusu School, Nanjing Medical University, Suzhou, China
| | - Ruifang Zhu
- Department of pharmacy, Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Yongchao Dong
- Department of pharmacy, Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Lifeng Huang
- Department of pharmacy, Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou 215153, China
| | - Taiquan Zhang
- Department of pharmacy, Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou 215153, China
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Kilvert A, Fox C. Risk factor modification to reduce the risk of dementia in diabetes. PRACTICAL DIABETES 2022. [DOI: 10.1002/pdi.2401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Anne Kilvert
- Northamptonshire Community Diabetes MDT, Daventry UK
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Hirabayashi N, Hata J, Furuta Y, Ohara T, Shibata M, Hirakawa Y, Yamashita F, Yoshihara K, Kitazono T, Sudo N, Ninomiya T. Association Between Diabetes and Gray Matter Atrophy Patterns in a General Older Japanese Population: The Hisayama Study. Diabetes Care 2022; 45:1364-1371. [PMID: 35500069 DOI: 10.2337/dc21-1911] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 03/25/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To examine the association between diabetes and gray matter atrophy patterns in a general older Japanese population. RESEARCH DESIGN AND METHODS In 2012, a total of 1,189 community-dwelling Japanese aged ≥65 years underwent brain MRI scans. Regional gray matter volumes (GMV) and intracranial volume (ICV) were measured by applying voxel-based morphometry (VBM) methods. The associations of diabetes and related parameters with the regional GMV/ICV were examined using an ANCOVA. The regional gray matter atrophy patterns in the subjects with diabetes or elevated fasting plasma glucose (FPG) or 2-h postload glucose (2hPG) levels were investigated using VBM. RESULTS Subjects with diabetes had significantly lower mean values of GMV/ICV in the frontal lobe, temporal lobe, insula, deep gray matter structures, and cerebellum than subjects without diabetes after adjusting for potential confounders. A longer duration of diabetes was also significantly associated with lower mean values of GMV/ICV in these brain regions. The multivariable-adjusted mean values of the temporal, insular, and deep GMV/ICV decreased significantly with elevating 2hPG levels, whereas higher FPG levels were not significantly associated with GMV/ICV of any brain regions. In the VBM analysis, diabetes was associated with gray matter atrophy in the bilateral superior temporal gyri, right middle temporal gyrus, left inferior temporal gyrus, right middle frontal gyrus, bilateral thalami, right caudate, and right cerebellum. CONCLUSIONS The current study suggests that a longer duration of diabetes and elevated 2hPG levels are significant risk factors for gray matter atrophy in various brain regions.
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Affiliation(s)
- Naoki Hirabayashi
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Ito Clinic, Kyushu University, Fukuoka, Japan.,Department of Psychosomatic Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Jun Hata
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Center for Cohort Studies, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoshihiko Furuta
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of Medical-Engineering Collaboration for Healthy Longevity, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Tomoyuki Ohara
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Mao Shibata
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of Psychosomatic Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Center for Cohort Studies, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoichiro Hirakawa
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Fumio Yamashita
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Iwate, Japan
| | - Kazufumi Yoshihara
- Department of Psychosomatic Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takanari Kitazono
- Center for Cohort Studies, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Nobuyuki Sudo
- Department of Psychosomatic Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Center for Cohort Studies, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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Luo A, Xie Z, Wang Y, Wang X, Li S, Yan J, Zhan G, Zhou Z, Zhao Y, Li S. Type 2 diabetes mellitus-associated cognitive dysfunction: Advances in potential mechanisms and therapies. Neurosci Biobehav Rev 2022; 137:104642. [PMID: 35367221 DOI: 10.1016/j.neubiorev.2022.104642] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 03/24/2022] [Accepted: 03/27/2022] [Indexed: 12/22/2022]
Abstract
Type 2 diabetes (T2D) and its target organ injuries cause distressing impacts on personal health and put an enormous burden on the healthcare system, and increasing attention has been paid to T2D-associated cognitive dysfunction (TDACD). TDACD is characterized by cognitive dysfunction, delayed executive ability, and impeded information-processing speed. Brain imaging data suggest that extensive brain regions are affected in patients with T2D. Based on current findings, a wide spectrum of non-specific neurodegenerative mechanisms that partially overlap with the mechanisms of neurodegenerative diseases is hypothesized to be associated with TDACD. However, it remains unclear whether TDACD is a consequence of T2D or a complication that co-occurs with T2D. Theoretically, anti-diabetes methods are promising neuromodulatory approaches to reduce brain injury in patients with T2D. In this review, we summarize potential mechanisms underlying TDACD and promising neurotropic effects of anti-diabetes methods and some neuroprotective natural compounds. Constructing screening or diagnostic tools and developing targeted treatment and preventive strategies would be expected to reduce the burden of TDACD.
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Affiliation(s)
- Ailin Luo
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Zheng Xie
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Yue Wang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Xuan Wang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Shan Li
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Jing Yan
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Gaofeng Zhan
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Zhiqiang Zhou
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Yilin Zhao
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
| | - Shiyong Li
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
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28
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Casanova R, Hsu FC, Barnard RT, Anderson AM, Talluri R, Whitlow CT, Hughes TM, Griswold M, Hayden KM, Gottesman RF, Wagenknecht LE. Comparing data-driven and hypothesis-driven MRI-based predictors of cognitive impairment in individuals from the Atherosclerosis Risk in Communities (ARIC) study. Alzheimers Dement 2022; 18:561-571. [PMID: 34310039 PMCID: PMC8789939 DOI: 10.1002/alz.12427] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 06/15/2021] [Accepted: 06/15/2021] [Indexed: 01/10/2023]
Abstract
INTRODUCTION A data-driven index of dementia risk based on magnetic resonance imaging (MRI), the Alzheimer's Disease Pattern Similarity (AD-PS) score, was estimated for participants in the Atherosclerosis Risk in Communities (ARIC) study. METHODS AD-PS scores were generated for 839 cognitively non-impaired individuals with a mean follow-up of 4.86 years. The scores and a hypothesis-driven volumetric measure based on several brain regions susceptible to AD were compared as predictors of incident cognitive impairment in different settings. RESULTS Logistic regression analyses suggest the data-driven AD-PS scores to be more predictive of incident cognitive impairment than its counterpart. Both biomarkers were more predictive of incident cognitive impairment in participants who were White, female, and apolipoprotein E gene (APOE) ε4 carriers. Random forest analyses including predictors from different domains ranked the AD-PS scores as the most relevant MRI predictor of cognitive impairment. CONCLUSIONS Overall, the AD-PS scores were the stronger MRI-derived predictors of incident cognitive impairment in cognitively non-impaired individuals.
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Affiliation(s)
- Ramon Casanova
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem
| | - Fang-Chi Hsu
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem
| | - Ryan T. Barnard
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem
| | - Andrea M. Anderson
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem
| | - Rajesh Talluri
- University of Mississippi Medical Center, Jackson, MS, USA
| | | | - Timothy M. Hughes
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Kathleen M. Hayden
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem
| | | | - Lynne E. Wagenknecht
- Divison of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
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29
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Adam HS, Lakshminarayan K, Wang W, Norby FL, Mosley T, Walker KA, Gottesman RF, Meyer K, Hughes TM, Pankow JS, Wong DF, Jack CR, Sen S, Lutsey PL, Beck J, Demmer RT. The prospective association between periodontal disease and brain imaging outcomes: The Atherosclerosis Risk in Communities study. J Clin Periodontol 2022; 49:322-334. [PMID: 34905804 PMCID: PMC8934294 DOI: 10.1111/jcpe.13586] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 11/10/2021] [Accepted: 12/07/2021] [Indexed: 11/26/2022]
Abstract
AIM We investigate if periodontal disease is prospectively associated with cerebrovascular and neurodegenerative markers of dementia and Alzheimer's pathology. MATERIALS AND METHODS N = 1306 participants (Visit 5 mean age = 76.5 [standard deviation = 5.4] years) in the Atherosclerosis Risk in Communities study with completed dental exams at Visit 4 underwent brain magnetic resonance imaging scans at Visit 5 while N = 248 underwent positron emission tomography scans. Participants were classified as edentulous or, among the dentate, by the modified Periodontal Profile Class. Brain volumes were regressed on periodontal status in linear regressions. Cerebrovascular measures and β-amyloid positivity were regressed on periodontal status in logistic regressions. RESULTS Periodontal disease was not associated with brain volumes, microhaemorrhages, or elevated β-amyloid. Compared with periodontally healthy individuals, odds ratios [95% confidence interval] for all-type infarcts were 0.37 [0.20, 0.65] for severe tooth loss and 0.56 [0.31, 0.99] for edentulous participants. CONCLUSIONS Within the limitations of this study, periodontal disease was not associated with altered brain volumes, microhaemorrhages, or β-amyloid positivity. Tooth loss was associated with lower odds of cerebral infarcts.
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Affiliation(s)
- Hamdi S. Adam
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55455
| | - Kamakshi Lakshminarayan
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55455
| | - Wendy Wang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55455
| | - Faye L. Norby
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55455
| | - Thomas Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39216
| | - Keenan A. Walker
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, 21218
| | - Rebecca F. Gottesman
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, 21218
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, 21218
| | - Katie Meyer
- Department of Nutrition, University of North Carolina, Chapel Hill, Chapel Hill, NC, 27599
| | - Timothy M. Hughes
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, 27101
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55455
| | - Dean F. Wong
- Mallinckrodt Institute of Radiology, Washington University in St. Louis Missouri, St. Louis, MO, 63110
| | | | - Souvik Sen
- Department of Neurology, University of South Carolina, School of Medicine, Columbia, SC, 29203
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55455
| | - Jim Beck
- Division of Comprehensive Oral Health - Periodontology, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599
| | - Ryan T. Demmer
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55455
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, 10032
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30
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Fatih N, Chaturvedi N, Lane CA, Parker TD, Lu K, Cash DM, Malone IB, Silverwood R, Wong A, Barnes J, Sudre CH, Richards M, Fox NC, Schott JM, Hughes A, James SN. Sex-related differences in whole brain volumes at age 70 in association with hyperglycemia during adult life. Neurobiol Aging 2022; 112:161-169. [PMID: 35183802 DOI: 10.1016/j.neurobiolaging.2021.09.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 09/01/2021] [Accepted: 09/04/2021] [Indexed: 01/19/2023]
Abstract
Longitudinal studies of the relationship between hyperglycemia and brain health are rare and there is limited information on sex differences in associations. We investigated whether glycosylated hemoglobin (HbA1c) measured at ages of 53, 60-64 and 69 years, and cumulative glycemic index (CGI), a measure of cumulative glycemic burden, were associated with metrics of brain health in later life. Participants were from Insight 46, a substudy of the Medical Research Council National Survey of Health and Development (NSHD) who undertook volumetric MRI, florbetapir amyloid-PET imaging and cognitive assessments at ages of 69-71. Analyses were performed using linear and logistic regression as appropriate, with adjustment for potential confounders. We observed a sex interaction between HbA1c and whole brain volume (WBV) at all 3 time points. Following stratification of our sample, we observed that HbA1c at all ages, and CGI were positively associated with lower WBV exclusively in females. HbA1c (or CGI) was not associated with amyloid status, white matter hyperintensities (WMHs), hippocampal volumes (HV) or cognitive outcomes in either sex. Higher HbA1c in adulthood is associated with smaller WBV at 69-71 years in females but not in males. This suggests that there may be preferential target organ damage in the brain for females with hyperglycemia.
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Affiliation(s)
- Nasrtullah Fatih
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom.
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Christopher A Lane
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Thomas D Parker
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Kirsty Lu
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - David M Cash
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Ian B Malone
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Richard Silverwood
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Josephine Barnes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Nick C Fox
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Alun Hughes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
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31
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Gomez GT, Gottesman RF, Gabriel KP, Palta P, Gross AL, Soldan A, Albert MS, Sullivan KJ, Jack CR, Knopman DS, Windham BG, Walker KA. The association of motoric cognitive risk with incident dementia and neuroimaging characteristics: The Atherosclerosis Risk in Communities Study. Alzheimers Dement 2022; 18:434-444. [PMID: 34786837 PMCID: PMC10064850 DOI: 10.1002/alz.12412] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 05/05/2021] [Accepted: 06/01/2021] [Indexed: 11/10/2022]
Abstract
INTRODUCTION Motoric cognitive risk (MCR), a clinical syndrome characterized by slow gait speed and subjective cognitive complaints, has been associated with dementia risk. The neuropathological features underlying MCR remain poorly understood. METHODS The Atherosclerosis Risk in Communities (ARIC) community-based cohort study classified participants using standardized criteria as MCR+/- and mild cognitive impairment (MCI)+/- at study baseline (2011-2013). We examined the 5-year dementia risk and baseline brain structural/molecular abnormalities associated with MCR+ and MCI+ status. RESULTS Of 5023 nondemented participants included, 204 were MCR+ and 1030 were MCI+. Both MCR+ and MCI+ participants demonstrated increased dementia risk. The pattern of structural brain abnormalities associated with MCR+ differed from that of MCI+. Whereas MCI+ was associated with comparatively smaller volumes in brain regions vulnerable to Alzheimer's disease pathology, MCR+ status was associated with smaller volumes in frontoparietal regions and greater white matter abnormalities. DISCUSSION MCR may represent a predementia syndrome characterized by prominent white matter abnormalities and frontoparietal atrophy.
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Affiliation(s)
- Gabriela T. Gomez
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Rebecca F. Gottesman
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | | | - Priya Palta
- Department of Medicine, Columbia University Medical Center, New York, NY
| | - Alden L. Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Marilyn S. Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Kevin J. Sullivan
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS
| | | | | | - B. Gwen Windham
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS
| | - Keenan A. Walker
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
- Laboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, Baltimore, MD
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32
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Jean-Pierre P, Thimothée V, Winters P. Prevalence of self-reported memory problems in adults with type 2 diabetes mellitus and cancer in the USA. Support Care Cancer 2022; 30:3495-3501. [PMID: 35018521 DOI: 10.1007/s00520-022-06815-y] [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: 04/06/2021] [Accepted: 01/04/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE To determine the prevalence of memory problems in individuals with or without a history of DM and cancer and assess possible compounding effects of these diseases on self-reported memory problems (SRMP). METHODS We used data from the 2009-2018 National Health and Nutrition Examination Survey. We conducted logistic regression analyses to determine the associations among DM, cancer, and SRMP, adjusting for age, sex, race/ethnicity, education, and poverty level. We examined the interaction effects of comorbid DM and cancer on SRMP. We compared participants with both DM and cancer to those with cancer only and to those with no DM or cancer. RESULTS We included 26,842 adults ≥ 20 years old (N = 3374 with DM, N = 23,468 without DM) and 51.87% female. There were 10,434 Whites, 5730 Blacks, 6795 Hispanics, and 3883 other races/multiracial. More individuals with DM reported memory problems than those without DM (p < 0.0001). More individuals with cancer reported memory problems than those without cancer (p < 0.0001). Of those with both DM and cancer, 14.19% reported memory problems. More individuals with DM had cancer than those without DM (p < 0.0001). Of those with both diseases, 55.75% had DM before the cancer diagnosis. DM (odds ratio[OR] = 1.87, 95%CI, 1.55-2.26) and cancer (OR = 1.81, 95%CI, 1.43-2.30) predicted SRMP. The interaction between DM and cancer was significant, and the likelihood of having both diseases compared to having neither DM nor cancer was OR = 2.09, 95%CI, 1.41 - 3.11. CONCLUSION Strategies to mitigate SRMP in individuals with comorbid DM and cancer history should consider the impact of both diseases.
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Affiliation(s)
- Pascal Jean-Pierre
- Cancer Neurocognitive Translational Research Lab, Florida State University College of Medicine, 1115 W Call Street, Tallahassee, FL, 32306, USA.
| | - Valerie Thimothée
- Cancer Neurocognitive Translational Research Lab, Florida State University College of Medicine, 1115 W Call Street, Tallahassee, FL, 32306, USA
| | - Paul Winters
- Cancer Neurocognitive Translational Research Lab, Florida State University College of Medicine, 1115 W Call Street, Tallahassee, FL, 32306, USA
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33
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Alster P, Dunalska A, Migda B, Madetko N, Królicki L. The Rate of Decrease in Brain Perfusion in Progressive Supranuclear Palsy and Corticobasal Syndrome May Be Impacted by Glycemic Variability-A Pilot Study. Front Neurol 2021; 12:767480. [PMID: 34819913 PMCID: PMC8606811 DOI: 10.3389/fneur.2021.767480] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 10/06/2021] [Indexed: 11/13/2022] Open
Abstract
Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) are tauopathic parkinsonian syndromes, presently lacking disease-modifying treatments. Patients affected by these diseases suffer due to multidimensional deteriorations resulting in motor and cognitive impairment. Previously published research has confirmed risk factors that may impact the course of PSP and CBS, among them hypertension and diabetes. Less data is available regarding prediabetes and glycemic variability. In this study, 26 patients with clinical diagnoses of PSP and CBS were examined using glycated hemoglobin and perfusion single-photon emission tomography (SPECT). Patients were divided into two groups-PSP/CBS patients with glycated hemoglobin (HbA1c) below and above 5.7%. The results of the perfusion evaluation were compared with the values from healthy volunteers from the software's database. A decrease in perfusion in certain regions of interest was observed among patients affected by increased glycemic variability. A more pronounced decrement in perfusion was observed only in some regions of interest-the hippocampus, pons, left thalamus, right insula. The results indicated that, among PSP/CBS patients, individuals with more pronounced glycemic variability had more severe hypoperfusion in certain brain regions in comparison with PSP/CBS patients without carbohydrate metabolism disorders. Due to the fact that PSP and CBS are associated with cognitive impairment, an additional decrease in perfusion in the hippocampal area may impact the rate of cognitive deterioration.
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Affiliation(s)
- Piotr Alster
- Department of Neurology, Medical University of Warsaw, Warsaw, Poland
| | - Anna Dunalska
- Students' Scientific Circle of the Department of Neurology, Medical University of Warsaw, Warsaw, Poland
| | - Bartosz Migda
- Diagnostic Ultrasound Lab, Department of Pediatric Radiology, Medical Faculty, Medical University of Warsaw, Warsaw, Poland
| | - Natalia Madetko
- Department of Neurology, Medical University of Warsaw, Warsaw, Poland
| | - Leszek Królicki
- Department of Nuclear Medicine, University Clinical Center, Medical University of Warsaw, Warsaw, Poland
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34
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Oh DJ, Jung JJ, Shin SA, Kim H, Park S, Sohn BK, Koo BK, Moon MK, Kim YK, Lee JY. Brain Structural Alterations, Diabetes Biomarkers, and Cognitive Performance in Older Adults With Dysglycemia. Front Neurol 2021; 12:766216. [PMID: 34777234 PMCID: PMC8581483 DOI: 10.3389/fneur.2021.766216] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 09/30/2021] [Indexed: 12/30/2022] Open
Abstract
Despite the high risk of dementia in older adults with type 2 diabetes, the neuroanatomical correlates of cognitive dysfunction that are particularly affected by diabetes are not well characterized. This study is aimed to examine the structural brain alterations in dysglycemic older adults. Using voxel-based morphometric and tract-based spatial statistics, we examined changes in gray matter volume, white matter volume, and microstructural integrity in older adults with prediabetes and diabetes. We also assessed the correlation of these structural changes with diabetes biomarkers and cognitive performance. A total of 74 non-demented older adults (normal, n = 14; prediabetes, n = 37; and diabetes, n = 23) participated in this study and underwent structural and diffusion magnetic resonance imaging (MRI) scans and neuropsychological tests. Subjects with diabetes showed reduced volume of cerebellar gray matter and frontal white matter and diffuse white matter dysintegrity, while those with prediabetes only showed reduced volume of insular gray matter. Atrophic changes in the cerebellum and frontal lobe and frontal white matter dysintegrity were correlated with chronic hyperglycemia and insulin resistance and worse performance in verbal memory recognition and executive function tests. Our findings suggest that chronic hyperglycemia and insulin resistance may alter brain structures forming the fronto-cerebellar network, which may cause cognitive dysfunction in older adults.
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Affiliation(s)
- Dae Jong Oh
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea.,Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Ji-Jung Jung
- Department of Surgery, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Seong A Shin
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Hairin Kim
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Soowon Park
- Division of Teacher Education, College of General Education for Truth, Sincerity and Love, Kyonggi University, Suwon, South Korea
| | - Bo Kyung Sohn
- Department of Psychiatry, Inje University Sanggye Paik Hospital, Seoul, South Korea
| | - Bo Kyung Koo
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.,Department of Internal Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Min Kyong Moon
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.,Department of Internal Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Jun-Young Lee
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea.,Department of Psychiatry and Neuroscience Research Institute, Seoul Nation University College of Medicine, Seoul, South Korea
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van Gennip ACE, Stehouwer CDA, van Boxtel MPJ, Verhey FRJ, Koster A, Kroon AA, Köhler S, van Greevenbroek MMJ, Wesselius A, Eussen SJPM, Backes WH, Jansen JF, Schram MT, Henry RMA, Singh-Manoux A, van Sloten TT. Association of Type 2 Diabetes, According to the Number of Risk Factors Within Target Range, With Structural Brain Abnormalities, Cognitive Performance, and Risk of Dementia. Diabetes Care 2021; 44:2493-2502. [PMID: 34588209 PMCID: PMC9612883 DOI: 10.2337/dc21-0149] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 06/15/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Type 2 diabetes is associated with increased risks of cognitive dysfunction and brain abnormalities. The extent to which risk factor modification can mitigate these risks is unclear. We investigated the associations between incident dementia, cognitive performance, and brain abnormalities among individuals with type 2 diabetes, according to the number of risk factors on target, compared with control subjects without diabetes. RESEARCH DESIGN AND METHODS Prospective data were from UK Biobank of 87,856 individuals (n = 10,663 diabetes, n = 77,193 control subjects; baseline 2006-2010), with dementia follow-up until February 2018. Individuals with diabetes were categorized according to the number of seven selected risk factors within the guideline-recommended target range (nonsmoking; guideline-recommended levels of glycated hemoglobin, blood pressure, BMI, albuminuria, physical activity, and diet). Outcomes were incident dementia, domain-specific cognitive performance, white matter hyperintensities, and total brain volume. RESULTS After a mean follow-up of 9.0 years, 147 individuals (1.4%) with diabetes and 412 control subjects (0.5%) had incident dementia. Among individuals with diabetes, excess dementia risk decreased stepwise for a higher number of risk factors on target. Compared with control subjects (incidence rate per 1,000 person-years 0.62 [95% CI 0.56; 0.68]), individuals with diabetes who had five to seven risk factors on target had no significant excess dementia risk (absolute rate difference per 1,000 person-years 0.20 [-0.11; 0.52]; hazard ratio 1.32 [0.89; 1.95]). Similarly, differences in processing speed, executive function, and brain volumes were progressively smaller for a higher number of risk factors on target. These results were replicated in the Maastricht Study. CONCLUSIONS Among individuals with diabetes, excess dementia risk, lower cognitive performance, and brain abnormalities decreased stepwise for a higher number of risk factors on target.
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Affiliation(s)
- April C E van Gennip
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands.,School for Cardiovascular Diseases CARIM, Maastricht University, Maastricht, the Netherlands
| | - Coen D A Stehouwer
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands.,School for Cardiovascular Diseases CARIM, Maastricht University, Maastricht, the Netherlands
| | - Martin P J van Boxtel
- School for Mental Health and Neuroscience MHENS, Maastricht University, Maastricht, the Netherlands.,Department of Psychiatry and Neuropsychology, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Frans R J Verhey
- School for Mental Health and Neuroscience MHENS, Maastricht University, Maastricht, the Netherlands.,Department of Psychiatry and Neuropsychology, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Annemarie Koster
- Care and Public Health Research Institute CAPHRI, Maastricht University, Maastricht, the Netherlands.,Department of Social Medicine, Maastricht University, Maastricht, the Netherlands
| | - Abraham A Kroon
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands.,School for Cardiovascular Diseases CARIM, Maastricht University, Maastricht, the Netherlands
| | - Sebastian Köhler
- School for Mental Health and Neuroscience MHENS, Maastricht University, Maastricht, the Netherlands.,Department of Psychiatry and Neuropsychology, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Marleen M J van Greevenbroek
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands.,School for Cardiovascular Diseases CARIM, Maastricht University, Maastricht, the Netherlands
| | - Anke Wesselius
- School of Nutrition and Translational Research in Metabolism NUTRIM, Maastricht University, Maastricht, the Netherlands.,Department of Genetics and Cell Biology, Complex Genetics, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Simone J P M Eussen
- School for Cardiovascular Diseases CARIM, Maastricht University, Maastricht, the Netherlands.,Department of Epidemiology, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Walter H Backes
- School for Mental Health and Neuroscience MHENS, Maastricht University, Maastricht, the Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Jacobus F Jansen
- School for Mental Health and Neuroscience MHENS, Maastricht University, Maastricht, the Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Miranda T Schram
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands.,School for Cardiovascular Diseases CARIM, Maastricht University, Maastricht, the Netherlands.,School for Mental Health and Neuroscience MHENS, Maastricht University, Maastricht, the Netherlands.,Department of Psychiatry and Neuropsychology, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Ronald M A Henry
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands.,School for Cardiovascular Diseases CARIM, Maastricht University, Maastricht, the Netherlands
| | - Archana Singh-Manoux
- Epidemiology of Ageing and Neurodegenerative Diseases, Université de Paris, INSERM U1153, Paris, France.,Department of Epidemiology and Public Health, University College London, London, U.K
| | - Thomas T van Sloten
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands .,School for Cardiovascular Diseases CARIM, Maastricht University, Maastricht, the Netherlands
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Reagan L, Cowan H, Woodruff J, Piroli G, Erichsen J, Evans A, Burzynski H, Maxwell N, Loyo-Rosado F, Macht V, Grillo C. Hippocampal-specific insulin resistance elicits behavioral despair and hippocampal dendritic atrophy. Neurobiol Stress 2021; 15:100354. [PMID: 34258333 PMCID: PMC8252121 DOI: 10.1016/j.ynstr.2021.100354] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/04/2021] [Accepted: 06/11/2021] [Indexed: 01/02/2023] Open
Abstract
Insulin resistance is a major contributor to the neuroplasticity deficits observed in patients with metabolic disorders. However, the relative contribution of peripheral versus central insulin resistance in the development of neuroplasticity deficits remains equivocal. To distinguish between peripheral and central insulin resistance, we developed a lentiviral vector containing an antisense sequence selective for the insulin receptor (LV-IRAS). We previously demonstrated that intra-hippocampal injection of this vector impairs synaptic transmission and hippocampal-dependent learning and memory in the absence of peripheral insulin resistance. In view of the increased risk for the development of neuropsychiatric disorders in patients with insulin resistance, the current study examined depressive and anxiety-like behaviors, as well as hippocampal structural plasticity in rats with hippocampal-specific insulin resistance. Following hippocampal administration of either the LV-control virus or the LV-IRAS, anhedonia was evaluated by the sucrose preference test, despair behavior was assessed in the forced swim test, and anxiety-like behaviors were determined in the elevated plus maze. Hippocampal neuron morphology was studied by Golgi-Cox staining. Rats with hippocampal insulin resistance exhibited anxiety-like behaviors and behavioral despair without differences in anhedonia, suggesting that some but not all components of depressive-like behaviors were affected. Morphologically, hippocampal-specific insulin resistance elicited atrophy of the basal dendrites of CA3 pyramidal neurons and dentate gyrus granule neurons, and also reduced the expression of immature dentate gyrus granule neurons. In conclusion, hippocampal-specific insulin resistance elicits structural deficits that are accompanied by behavioral despair and anxiety-like behaviors, identifying hippocampal insulin resistance as a key factor in depressive illness.
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Affiliation(s)
- L.P. Reagan
- Columbia VA Health Care System, Columbia, SC, 29209, USA
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - H.B. Cowan
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - J.L. Woodruff
- Columbia VA Health Care System, Columbia, SC, 29209, USA
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - G.G. Piroli
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - J.M. Erichsen
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - A.N. Evans
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - H.E. Burzynski
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - N.D. Maxwell
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - F.Z. Loyo-Rosado
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - V.A. Macht
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
| | - C.A. Grillo
- Columbia VA Health Care System, Columbia, SC, 29209, USA
- University of South Carolina School of Medicine, Department of Pharmacology, Physiology, and Neuroscience, Columbia, SC, 29209, USA
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37
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Sullivan KJ, Ranadive R, Su D, Neyland BR, Hughes TM, Hugenschmidt CE, Lockhart SN, Wong DF, Jack CR, Gottesman RF, Mosley TH, Griswold ME, Windham BG. Imaging-based indices of Neuropathology and gait speed decline in older adults: the atherosclerosis risk in communities study. Brain Imaging Behav 2021; 15:2387-2396. [PMID: 33439369 PMCID: PMC9189901 DOI: 10.1007/s11682-020-00435-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/17/2020] [Indexed: 02/01/2023]
Abstract
Imaging markers of cerebrovascular disease and Alzheimer's disease (AD) are implicated in mobility impairment in older adults, but few studies have examined these relationships longitudinally in a racially-diverse population-based sample. At Visit 5 (2011-13) of the ARIC Study, 1859 participants had usual pace gait speed (cm/s) assessed and brain MRI (mean age = 76.3, 28.5% Black) and PET (n = 343; mean age = 75.9, 42.6% Black) measures including total/regional brain volume (cm3), white matter hyperintensities (WMH; cm3), infarcts (present/absent), microbleeds (count) and global beta-amyloid (Aβ). Participants returned at Visit 6 (n = 1264, 2016-17) and Visit 7 (n = 1108, 2018-19) for follow-up gait speed assessments. We used linear regression to estimate effects of baseline infarct presence, higher microbleed count, and a one interquartile range (IQR) poorer measures of continuous predictors (-1 IQR total brain volume, temporal-parietal lobe meta region of interest(ROI); +1 IQR WMH volume, global Aβ SUVR) on cross-sectional gait speed and change in gait speed adjusting for age, sex, education, study site, APOE e4, estimated intracranial volume, BMI, and cardiovascular risk factors. Cross-sectionally, slower gait speed outcome was associated with higher WMH volume, -3.38 cm/s (95%CI:-4.71, -2.04), infarct presence, -5.60 cm/s (-7.69, -3.51), microbleed count, -2.20 cm/s (-3.20, -0.91), smaller total brain volume, -9.26 cm/s (-12.1, -6.43), and smaller temporal-parietal lobe ROI -6.28 cm/s (-8.28, -4.28). Longitudinally, faster gait speed outcome decline was associated with higher WMH volume, -0.27 cm/s/year, (-0.51, -0.03) and higher global Aβ SUVR, -0.62 cm/s/year (-1.20, -0.03). Both cerebrovascular and AD pathology may contribute to mobility decline commonly seen with aging.
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Affiliation(s)
- Kevin J Sullivan
- Department of Medicine, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS, 39216, USA.
| | - Radhikesh Ranadive
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Dan Su
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Blake R Neyland
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Timothy M Hughes
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Samuel N Lockhart
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Dean F Wong
- Department of Radiology, Washington University in St Louis, St Louis, MO, USA
| | | | - Rebecca F Gottesman
- Department of Neurology, The Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, The Johns Hopkins University, Baltimore, MD, USA
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS, 39216, USA
| | - Michael E Griswold
- Department of Medicine, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS, 39216, USA
| | - B Gwen Windham
- Department of Medicine, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS, 39216, USA
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Fitzgerald KC, Damian A, Conway D, Mowry EM. Vascular comorbidity is associated with lower brain volumes and lower neuroperformance in a large multiple sclerosis cohort. Mult Scler 2021; 27:1914-1923. [PMID: 33416436 PMCID: PMC8263795 DOI: 10.1177/1352458520984746] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
OBJECTIVE The objective of this study is to assess the association between vascular comorbidity burden with clinical and imaging features of disease burden in a large population of people with multiple sclerosis (MS). METHODS We included participants from the MS Partners Advancing Technology Health Solutions (MS PATHS) cohort. We evaluated if vascular comorbidities (diabetes, hypertension, and dyslipidemia) or a composite sum of comorbidities was associated with MS characteristics, including objective neurologic function assessments and quantitative brain magnetic resonance imaging (MRI) measurements in propensity score-weighted models. RESULTS In total, 11,506 participants (6409 (55%) with brain MRI) were included. Individuals with 2+ vascular comorbidities had slower walking speed (standard deviation (SD) = -0.49; 95% confidence interval (CI) = -0.78, -0.19; p = 0.001), slower manual dexterity (SD = -0.41; 95% CI = -0.57, -0.26; p < 0.0001), and fewer correct scores on cognitive processing speed (SD = -0.11; 95% CI = -0.20, -0.02; p = 0.02) versus those with no comorbidities. Those with 2+ had lower brain parenchymal (-0.41%, 95% CI = -0.64, -0.17) and gray matter fractions (-0.30%, 95% CI = -0.49, -0.10), including reduced cortical (-10.10 mL, 95% CI = -15.42, -4.78) and deep (-0.44 mL, 95% CI = -0.84, -0.04) gray matter volumes versus those with no comorbidity. CONCLUSION Increased vascular comorbidity burden was associated with clinical and imaging markers of neurologic dysfunction and neurodegeneration in MS. Strategies to optimize comorbidity management in people with MS are warranted.
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Affiliation(s)
- Kathryn C Fitzgerald
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA/Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Anne Damian
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Devon Conway
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, USA
| | - Ellen M Mowry
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA/Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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39
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Diabetes and impaired fasting glucose in a population-based sample of individuals aged 75 + years: associations with cognition, major depressive disorder, functionality and quality of life-the Pietà study. Neurol Sci 2021; 42:3663-3671. [PMID: 33439392 DOI: 10.1007/s10072-020-05008-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 12/16/2020] [Indexed: 12/30/2022]
Abstract
OBJECTIVES To investigate the rates of diabetes mellitus (DM) and impaired fasting glucose (IFG) in a population-based sample of individuals aged 75 + years old and their associations with cognitive performance, depression, functionality, and quality of life (QoL). STUDY DESIGN Overall, 350 people participated in the study. Assessments of cognition, mood, functionality and QoL were performed using the mini-mental state examination (MMSE), clock-drawing, category fluency tests, the Mini-International Neuropsychiatric Interview, Pfeffer's Functional Activities Questionnaire, and the WHO Quality of Life-Old (WHOQOL-OLD). RESULTS IFG (ADA criteria) was identified in 42.1% of the sample, while the DM rate was 24.1%. Lack of knowledge of the DM diagnosis and lack of treatment occurred in 27% and 39% of the sample, respectively. Rates of dementia and depression, MMSE, category fluency scores, and previous cardiovascular events did not differ between the glycaemic groups. Individuals with DM performed worse on the clock-drawing test, functionality, and WHOQOL-OLD than the other participants. Individuals with IFG presented similar QoL and functionality when compared with the group without DM. CONCLUSIONS IFG and DM were common in this population-based sample aged 75 + years old, as were inadequate diagnoses and treatments of DM. DM individuals presented poor performance in the executive function test, functionality, and QoL. Further studies are recommended to investigate the value of an IFG diagnosis among the most elderly population.
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40
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Fang F, Cao R, Luo Q, Ge R, Lai M, Yang J, Ma M, Kang M, Zhang L, Wang Y, Peng Y. The silent occurrence of cerebral small vessel disease in nonelderly patients with type 2 diabetes mellitus. J Diabetes 2021; 13:735-743. [PMID: 33559402 DOI: 10.1111/1753-0407.13164] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Revised: 01/22/2021] [Accepted: 02/03/2021] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND The prevalence of cerebral small vessel disease (SVD) increases in elderly patients with type 2 diabetes (T2DM), exacerbating cognitive decline. However, the prevalence and the severity of SVD in dementia-free nonelderly T2DM patients were largely unknown. Our primary aim is to investigate SVD in such patients, with a specific focus on the correlation between SVD and diabetic peripheral sensorimotor polyneuropathy (DSP). METHODS We recruited 180 young and middle-aged subjects without cognitive impairment (106 with T2DM, 74 controls). Signs of cerebral SVD on magnetic resonance image were investigated, and the overall SVD burden was evaluated by a combined score. Patients with T2DM underwent further detailed DSP assessment. Regression models were used to investigate the association of SVD with the presence of T2DM, and the associations of the prevalence and severity of SVD and DSP were also explored in patients with T2DM. RESULTS The prevalence of microbleeds and overall burden of SVD were significantly higher in T2DM patients than in the controls. Further, the presence of DSP related to an increased risk of SVD after adjustment in diabetic group. Moreover, Toronto Clinical Scoring System values were positively associated with the increased SVD scores, and bilateral sural sensory nerve conduction velocities were negatively associated with increasingly severity of SVD scores. CONCLUSION The current findings extended the increasing prevalence of SVD to dementia-free nonelderly patients with T2DM, suggesting that the time for cognitive screening and prevention might be moved forward in T2DM patients, especially for those with DSP.
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Affiliation(s)
- Fang Fang
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Rong Cao
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Qian Luo
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Renbin Ge
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Mengyu Lai
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Jiaying Yang
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Mingming Ma
- Department of Ophthalmology, National Clinical Research Center for Eye Disease, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Mei Kang
- Clinical Research Center, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Lei Zhang
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yufan Wang
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yongde Peng
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
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41
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Frison E, Proust-Lima C, Mangin JF, Habert MO, Bombois S, Ousset PJ, Pasquier F, Hanon O, Paquet C, Gabelle A, Ceccaldi M, Annweiler C, Krolak-Salmon P, Béjot Y, Belin C, Wallon D, Sauvee M, Beaufils E, Bourdel-Marchasson I, Jalenques I, Chupin M, Chêne G, Dufouil C. Diabetes Mellitus and Cognition: Pathway Analysis in the MEMENTO Cohort. Neurology 2021; 97:e836-e848. [PMID: 34210821 PMCID: PMC8397583 DOI: 10.1212/wnl.0000000000012440] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Accepted: 05/25/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To assess the role of biomarkers of Alzheimer disease (AD), neurodegeneration, and small vessel disease (SVD) as mediators in the association between diabetes mellitus and cognition. METHODS The study sample was derived from MEMENTO, a cohort of French adults recruited in memory clinics and screened for either isolated subjective cognitive complaints or mild cognitive impairment. Diabetes was defined based on blood glucose assessment, use of antidiabetic agent, or self-report. We used structural equation modeling to assess whether latent variables of AD pathology (PET mean amyloid uptake, Aβ42/Aβ40 ratio, and CSF phosphorylated tau), SVD (white matter hyperintensities volume and visual grading), and neurodegeneration (mean cortical thickness, brain parenchymal fraction, hippocampal volume, and mean fluorodeoxyglucose uptake) mediate the association between diabetes and a latent variable of cognition (5 neuropsychological tests), adjusting for potential confounders. RESULTS There were 254 (11.1%) participants with diabetes among 2,288 participants (median age 71.6 years; 61.8% women). The association between diabetes and lower cognition was significantly mediated by higher neurodegeneration (standardized indirect effect: -0.061, 95% confidence interval: -0.089, -0.032), but not mediated by SVD and AD markers. Results were similar when considering latent variables of memory or executive functioning. CONCLUSION In a large clinical cohort in the elderly, diabetes is associated with lower cognition through neurodegeneration, independently of SVD and AD biomarkers.
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Affiliation(s)
- Eric Frison
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Cecile Proust-Lima
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Jean-Francois Mangin
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Marie-Odile Habert
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Stephanie Bombois
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Pierre-Jean Ousset
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Florence Pasquier
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Olivier Hanon
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Claire Paquet
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Audrey Gabelle
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Mathieu Ceccaldi
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Cédric Annweiler
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Pierre Krolak-Salmon
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Yannick Béjot
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Catherine Belin
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - David Wallon
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Mathilde Sauvee
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Emilie Beaufils
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Isabelle Bourdel-Marchasson
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Isabelle Jalenques
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Marie Chupin
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Geneviève Chêne
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France
| | - Carole Dufouil
- From INSERM, UMR 1219 (E.F., C.P.-L., G.C., C.D.), and INSERM, CIC1401-EC (E.F., G.C., C.D.), Université de Bordeaux; Pole de Sante Publique Centre (E.F., G.C., C.D.) and Pole de Gérontologie Clinique (I.B.-M.), Hospitalier Universitaire (CHU) de Bordeaux; CATI Multicenter Neuroimaging Platform (J.-F.M., M.-O.H., M. Ceccaldi), Paris; Neurospin CEA Paris Saclay University (J.-F.M.), Gif-sur-Yvette; Laboratoire d'Imagerie Biomédicale (M.-O.H.), INSERM, CNRS, Sorbonne Université; Médecine Nucléaire (M.-O.H.), AP-HP, Hôpital Pitié-Salpêtrière; IM2A, AP-HP, INSERM, UMR-S975, Groupe Hospitalier, Pitié-Salpêtrière Institut de la Mémoire et de la Maladie d'Alzheimer (S.B.), and INSERM, U-1127, 3 CNRS, UMR 7225, CATI (M. Chupin), Institut du Cerveau et de la Moelle Épinière, Sorbonne Université, Paris; INSERM UMR1027 (P.-J.O.), Université de Toulouse III Paul Sabatier; Centre Mémoire (CMRR) Distalz (F.P.), CHU, INSERM 1171, Université de Lille; Service de Gériatrie (O.H.), Hôpital Broca, Université Paris Descartes; Centre de Neurologie (C.P.), INSERM U1144, Cognitive Hôpital Lariboisière, Université de Paris; Department of Neurology, INSERM U1061, Clinical and Research Memory Center of Montpellier (A.G.), Gui de Chauliac Hospital, University of Montpellier; Institut de Neurosciences des Systèmes, CMMR, PACA Ouest (M. Ceccaldi), INSERM, CHU Timone APHM and Aix Marseille Université; Department of Geriatric Medicine (C.A.), Angers University Memory Clinic, Research Center on Autonomy and Longevity, UPRES EA 4638, Angers University Hospital, University of Angers, France; Department of Medical Biophysics (C.A.), Robarts Research Institute, Schulich School of Medicine and Dentistry, the University of Western Ontario, London, Canada; Centre Mémoire Ressource et Recherche de Lyon (CMRR) (P.K.-S.), Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Hôpital des Charpennes, Hospices Civils de Lyon, Université de Lyon; Centre Mémoire de Ressources et de Recherches (Y.B.), CHU Dijon Bourgogne, EA7460, Université de Bourgogne, Dijon; Service de Neurologie Hôpital Saint-Louis AP-HP (C.B.), Paris; Departement de Neurologie (D.W.), UNIROUEN, INSERM U1245, CNR-MAJ, CHU de Rouen, Université de Normandie; CMRR Grenoble Arc Alpin (M.S.), CHU Grenoble; CMRR (E.B.), University Hospital Tours; Centre de Résonance Magnétique des Systèmes Biologiques (I.B.-M.), UMR 5536 Université de Bordeaux/CNRS; and Memory Resource and Research Centre of Clermont-Ferrand (I.J.), CHU de Clermont-Ferrand, Clermont Auvergne University, Clermont-Ferrand, France.
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Wang JH, Soo Goh JO, Chang YL, Chen SC, Li YY, Yu YP, Lo RY. Multimorbidity and Regional Volumes of the Default Mode Network in Brain Aging. Gerontology 2021; 68:488-497. [PMID: 34320506 DOI: 10.1159/000517285] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 05/19/2021] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION The default mode network (DMN) is selectively vulnerable in brain aging. Little is known about the effect of multimorbidity as a whole onto the brain structural integrity. OBJECTIVE We aimed to investigate the association between multimorbidity and the structural integrity of DMN. METHODS We enrolled senior volunteers aged between 60 and 80 years in Hualien County during 2014-2018 and conducted in-person interview to collect information on chronic diseases. Fasting blood glucose and glycated hemoglobin (HbA1c) were tested. We assessed multimorbidity burden by the cumulative illness rating scale-geriatric (CIRS-G). MRI brain scans were standardized to measure the regional volume within the DMN. In a cross-sectional design, we employed stepwise regression models to evaluate the effects of age, sex, hyperglycemia, and multimorbidity on the DMN. RESULTS A total of 170 volunteers were enrolled with a mean age of 66.9 years, female preponderance (71%), an average mini-mental state examination score of 27.6, a mean HbA1c of 6.0, and a mean CIRS-G total score (TS) of 7.2. We found that older age was associated with reduced volumes in the hippocampus, left rostral anterior cingulate cortex, right posterior cingulate, right isthmus, precuneus, and right supramarginal. Higher levels of HbA1c and fasting glucose were associated with a reduced volume in the hippocampus only. A higher CIRS-G-TS was associated with reduced volumes in the left posterior cingulate cortex and right supramarginal gyrus; while a higher CIRS-G severity index was associated with a smaller right precuneus and right supramarginal. CONCLUSIONS In the DMN, hippocampal volume shows vulnerability to aging and hyperglycemia, whereas the posterior cingulate, supramarginal, and precuneus cortices may be the key sites to reflect the total effects of multimorbidity.
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Affiliation(s)
- Jen-Hung Wang
- Department of Medical Research, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan, .,Institute of Medical Sciences, Tzu Chi University, Hualien, Taiwan,
| | - Joshua Oon Soo Goh
- Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei, Taiwan
| | - Yu-Ling Chang
- Department of Psychology, National Taiwan University, Taipei, Taiwan
| | - Shu-Cin Chen
- Division of Cognitive/Geriatric Neurology, Department of Neurology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan
| | - Yu-Ying Li
- Division of Cognitive/Geriatric Neurology, Department of Neurology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan
| | - Yu-Ping Yu
- Division of Cognitive/Geriatric Neurology, Department of Neurology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan
| | - Raymond Y Lo
- Institute of Medical Sciences, Tzu Chi University, Hualien, Taiwan.,Division of Cognitive/Geriatric Neurology, Department of Neurology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan
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43
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Wardlaw JM, Debette S, Jokinen H, De Leeuw FE, Pantoni L, Chabriat H, Staals J, Doubal F, Rudilosso S, Eppinger S, Schilling S, Ornello R, Enzinger C, Cordonnier C, Taylor-Rowan M, Lindgren AG. ESO Guideline on covert cerebral small vessel disease. Eur Stroke J 2021; 6:CXI-CLXII. [PMID: 34414301 PMCID: PMC8370079 DOI: 10.1177/23969873211012132] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 04/02/2021] [Indexed: 12/11/2022] Open
Abstract
'Covert' cerebral small vessel disease (ccSVD) is common on neuroimaging in persons without overt neurological manifestations, and increases the risk of future stroke, cognitive impairment, dependency, and death. These European Stroke Organisation (ESO) guidelines provide evidence-based recommendations to assist with clinical decisions about management of ccSVD, specifically white matter hyperintensities and lacunes, to prevent adverse clinical outcomes. The guidelines were developed according to ESO standard operating procedures and Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. We prioritised the clinical outcomes of stroke, cognitive decline or dementia, dependency, death, mobility and mood disorders, and interventions of blood pressure lowering, antiplatelet drugs, lipid lowering, lifestyle modifications, glucose lowering and conventional treatments for dementia. We systematically reviewed the literature, assessed the evidence, formulated evidence-based recommendations where feasible, and expert consensus statements. We found little direct evidence, mostly of low quality. We recommend patients with ccSVD and hypertension to have their blood pressure well controlled; lower blood pressure targets may reduce ccSVD progression. We do not recommend antiplatelet drugs such as aspirin in ccSVD. We found little evidence on lipid lowering in ccSVD. Smoking cessation is a health priority. We recommend regular exercise which may benefit cognition, and a healthy diet, good sleep habits, avoiding obesity and stress for general health reasons. In ccSVD, we found no evidence for glucose control in the absence of diabetes or for conventional Alzheimer dementia treatments. Randomised controlled trials with clinical endpoints are a priority for ccSVD.
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Affiliation(s)
- Joanna M Wardlaw
- Centre for Clinical Brain Sciences, UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Stephanie Debette
- Bordeaux Population Health Center, University of Bordeaux, INSERM, UM1219, Team VINTAGE
- Department of Neurology, Institute for Neurodegenerative Disease, Bordeaux University Hospital, Bordeaux, France
| | - Hanna Jokinen
- HUS Neurocenter, Division of Neuropsychology, Helsinki University Hospital, University of Helsinki and Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland
| | - Frank-Erik De Leeuw
- Radboud University Medical Center, Department of Neurology; Donders Center for Medical Neuroscience, Nijmegen, The Netherlands
| | - Leonardo Pantoni
- Stroke and Dementia Lab, 'Luigi Sacco' Department of Biomedical and Clinical Sciences, University of Milan, Milano, Italy
| | - Hugues Chabriat
- Department of Neurology, Hopital Lariboisiere, APHP, INSERM U 1161, FHU NeuroVasc, University of Paris, Paris, France
| | - Julie Staals
- Department of Neurology, School for Cardiovascular Diseases (CARIM), Maastricht UMC+, AZ Maastricht, the Netherlands
| | - Fergus Doubal
- Centre for Clinical Brain Sciences, UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
- Dept of Medicine for the Elderly, University of Edinburgh, Edinburgh, UK
| | - Salvatore Rudilosso
- Comprehensive Stroke Center, Department of Neuroscience, Hospital Clínic, Barcelona, Spain
| | - Sebastian Eppinger
- University Clinic of Neurology, Medical University of Graz, Graz, Austria
| | - Sabrina Schilling
- Bordeaux Population Health Center, University of Bordeaux, INSERM, UM1219, Team VINTAGE
| | - Raffaele Ornello
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, L’Aquila, Italy
| | - Christian Enzinger
- University Clinic of Neurology, Medical University of Graz, Graz, Austria
| | - Charlotte Cordonnier
- Univ. Lille, INSERM, CHU Lille, U1172, LilNCog – Lille Neuroscience & Cognition, Lille, France
| | - Martin Taylor-Rowan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Arne G Lindgren
- Department of Clinical Sciences Lund, Neurology, Lund University; Section of Neurology, Skåne University Hospital, Lund, Sweden
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44
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Grosu S, Lorbeer R, Hartmann F, Rospleszcz S, Bamberg F, Schlett CL, Galie F, Selder S, Auweter S, Heier M, Rathmann W, Mueller-Peltzer K, Ladwig KH, Peters A, Ertl-Wagner BB, Stoecklein S. White matter hyperintensity volume in pre-diabetes, diabetes and normoglycemia. BMJ Open Diabetes Res Care 2021; 9:9/1/e002050. [PMID: 34183320 PMCID: PMC8240582 DOI: 10.1136/bmjdrc-2020-002050] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 06/01/2021] [Indexed: 02/07/2023] Open
Abstract
INTRODUCTION As white matter hyperintensities (WMHs) of the brain are associated with an increased risk of stroke, cognitive decline, and depression, elucidating the associated risk factors is important. In addition to age and hypertension, pre-diabetes and diabetes may play important roles in the development of WMHs. Previous studies have, however, shown conflicting results. We aimed to investigate the effect of diabetes status and quantitative markers of glucose metabolism on WMH volume in a population-based cohort without prior cardiovascular disease. RESEARCH DESIGN AND METHODS 400 participants underwent 3 T MRI. WMHs were manually segmented on 3D fluid-attenuated inversion recovery images. An oral glucose tolerance test (OGTT) was administered to all participants not previously diagnosed with diabetes to assess 2-hour serum glucose concentrations. Fasting glucose concentrations and glycated hemoglobin (HbA1c) levels were measured. Zero-inflated negative binomial regression analyses of WMH volume and measures of glycemic status were performed while controlling for cardiovascular risk factors and multiple testing. RESULTS The final study population comprised 388 participants (57% male; age 56.3±9.2 years; n=98 with pre-diabetes, n=51 with diabetes). Higher WMH volume was associated with pre-diabetes (p=0.001) and diabetes (p=0.026) compared with normoglycemic control participants after adjustment for cardiovascular risk factors. 2-hour serum glucose (p<0.001), but not fasting glucose (p=0.389) or HbA1c (p=0.050), showed a significant positive association with WMH volume after adjustment for cardiovascular risk factors. CONCLUSION Our results indicate that high 2-hour serum glucose concentration in OGTT, but not fasting glucose levels, may be an independent risk factor for the development of WMHs, with the potential to inform intensified prevention strategies in individuals at risk of WMH-associated morbidity.
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Affiliation(s)
- Sergio Grosu
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Roberto Lorbeer
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Felix Hartmann
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Susanne Rospleszcz
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Christopher L Schlett
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Franziska Galie
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Sonja Selder
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Sigrid Auweter
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Margit Heier
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- KORA Study Centre, University Hospital of Augsburg, Augsburg, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Duesseldorf, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Katharina Mueller-Peltzer
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Karl-Heinz Ladwig
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Department of Psychosomatic Medicine and Psychotherapy, Hospital Rechts der Isar, Technical University Munich, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Birgit B Ertl-Wagner
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
- Department of Radiology, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Sophia Stoecklein
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
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45
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Furlano JA, Horst BR, Nagamatsu LS. Brain deficits in prediabetic adults: A systematic review. J Neurosci Res 2021; 99:1725-1743. [PMID: 33819349 DOI: 10.1002/jnr.24830] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 03/04/2021] [Indexed: 12/14/2022]
Abstract
Previous findings on the relationship between prediabetes (the precursor stage of type 2 diabetes) and brain health in humans are inconsistent. Thus, this systematic review of cross-sectional and longitudinal studies aimed to summarize what is currently known about brain deficits in prediabetic adults. Following the PRISMA reporting standards for systematic reviews, we conducted a comprehensive review of peer-reviewed journal articles published from 2009 to present, focusing on studies that assessed brain volume, structural connectivity, and cerebrovascular health in prediabetic adults and older adults (i.e., 18 years or older). We systematically searched PsychINFO, Scopus, Web of Science, Ovid MEDLINE, CINAHL, and EMbase databases. Quality assessment was based on the NIH Quality Assessment Tool for Observational and Cross-sectional Studies. In total, 19 studies were included in our review. Results from these studies show that prediabetes may be associated with deficits in brain structure and pathology, however, several studies also refute these findings. Moreover, we identified clear inconsistencies in study methodologies, including diabetes measures and classification, across studies that may account for these conflicting findings.
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Affiliation(s)
- Joyla A Furlano
- Neuroscience, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Becky R Horst
- Neuroscience, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
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46
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Sundermann EE, Thomas KR, Bangen KJ, Weigand AJ, Eppig JS, Edmonds EC, Wong CG, Bondi MW, Delano-Wood L. Prediabetes Is Associated With Brain Hypometabolism and Cognitive Decline in a Sex-Dependent Manner: A Longitudinal Study of Nondemented Older Adults. Front Neurol 2021; 12:551975. [PMID: 33679574 PMCID: PMC7933503 DOI: 10.3389/fneur.2021.551975] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 01/25/2021] [Indexed: 11/13/2022] Open
Abstract
Although type 2 diabetes is a well-known risk factor for Alzheimer's disease (AD), little is known about how its precursor-prediabetes-impacts neuropsychological function and brain health. Thus, we examined the relationship between prediabetes and AD-related biological and cognitive/clinical markers in a well-characterized sample drawn from the Alzheimer's Disease Neuroimaging Initiative. Additionally, because women show higher rates of AD and generally more atherogenic lipid profiles than men, particularly in the context of diabetes, we examined whether sex moderates any observed associations. The total sample of 911 nondemented and non-diabetic participants [normal control = 540; mild cognitive impairment (MCI) = 371] included 391 prediabetic (fasting blood glucose: 100-125 mg/dL) and 520 normoglycemic individuals (age range: 55-91). Linear mixed effects models, adjusted for demographics and vascular and AD risk factors, examined the independent and interactive effects of prediabetes and sex on 2-6 year trajectories of FDG-PET measured cerebral metabolic glucose rate (CMRglu), hippocampal/intracranial volume ratio (HV/IV), cerebrospinal fluid phosphorylated tau-181/amyloid-β1-42 ratio (p-tau181/Aβ1-42), cognitive function (executive function, language, and episodic memory) and the development of dementia. Analyses were repeated in the MCI subsample. In the total sample, prediabetic status had an adverse effect on CMRglu across time regardless of sex, whereas prediabetes had an adverse effect on executive function across time in women only. Within the MCI subsample, prediabetic status was associated with lower CMRglu and poorer executive function and language performance across time within women, whereas these associations were not seen within men. In the total sample and MCI subsample, prediabetes did not relate to HV/IV, p-tau181/Aβ1-42, memory function or dementia risk regardless of sex; however, among incident dementia cases, prediabetic status related to earlier age of dementia onset in women but not in men. Results suggest that prediabetes may affect cognition through altered brain metabolism, and that women may be more vulnerable to the negative effects of glucose intolerance.
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Affiliation(s)
- Erin E Sundermann
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Kelsey R Thomas
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.,Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
| | - Katherine J Bangen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.,Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
| | - Alexandra J Weigand
- San Diego State University/University of California, San Diego (SDSU/UCSD) Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - Joel S Eppig
- San Diego State University/University of California, San Diego (SDSU/UCSD) Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - Emily C Edmonds
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.,Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
| | - Christina G Wong
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.,Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
| | - Mark W Bondi
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.,Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
| | - Lisa Delano-Wood
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.,Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
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47
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Sabbatinelli J, Ramini D, Giuliani A, Recchioni R, Spazzafumo L, Olivieri F. Connecting vascular aging and frailty in Alzheimer's disease. Mech Ageing Dev 2021; 195:111444. [PMID: 33539904 DOI: 10.1016/j.mad.2021.111444] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 01/05/2021] [Accepted: 01/26/2021] [Indexed: 12/15/2022]
Abstract
Aging plays an important role in the etiology of the most common age-related diseases (ARDs), including Alzheimer's disease (AD). The increasing number of AD patients and the lack of disease-modifying drugs warranted intensive research to tackle the pathophysiological mechanisms underpinning AD development. Vascular aging/dysfunction is a common feature of almost all ARDs, including cardiovascular (CV) diseases, diabetes and AD. To this regard, interventions aimed at modifying CV outcomes are under extensive investigation for their pleiotropic role in ameliorating and slowing down cognitive impairment in middle-life and elderly individuals. Evidence from observational and clinical studies confirm the notion that the earlier the interventions are conducted, the most favorable are the effects on cognitive function. Therefore, epidemiological research should focus on the early detection of deviations from a healthy cognitive aging trajectory, through the stratification of adult individuals according to the rate of aging. Here, we review the interplay between vascular and cognitive dysfunctions associated with aging, to disentangle the complex mechanisms underpinning the development and progression of neurodegenerative disorders, with a specific focus on AD.
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Affiliation(s)
- Jacopo Sabbatinelli
- Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy
| | - Deborah Ramini
- Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy
| | - Angelica Giuliani
- Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
| | - Rina Recchioni
- Center of Clinical Pathology and Innovative Therapy, IRCCS INRCA, Ancona, Italy
| | - Liana Spazzafumo
- Epidemiologic Observatory, Regional Health Agency, Regione Marche, Ancona, Italy
| | - Fabiola Olivieri
- Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Center of Clinical Pathology and Innovative Therapy, IRCCS INRCA, Ancona, Italy
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48
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Associated factors of white matter hyperintensity volume: a machine-learning approach. Sci Rep 2021; 11:2325. [PMID: 33504924 PMCID: PMC7840689 DOI: 10.1038/s41598-021-81883-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 01/11/2021] [Indexed: 01/08/2023] Open
Abstract
To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we used a data-driven machine-learning approach. We analysed two independent cohorts (KORA and SHIP). WMH volumes were derived from cMRI-images (FLAIR). 90 (KORA) and 34 (SHIP) potential determinants of WMH including measures of diabetes, blood-pressure, medication-intake, sociodemographics, life-style factors, somatic/depressive-symptoms and sleep were collected. Elastic net regression was used to identify relevant predictor covariates associated with WMH volume. The ten most frequently selected variables in KORA were subsequently examined for robustness in SHIP. The final KORA sample consisted of 370 participants (58% male; age 55.7 ± 9.1 years), the SHIP sample comprised 854 participants (38% male; age 53.9 ± 9.3 years). The most often selected and highly replicable parameters associated with WMH volume were in descending order age, hypertension, components of the social environment (i.e. widowed, living alone) and prediabetes. A systematic machine-learning based analysis of two independent, population-based cohorts showed, that besides age and hypertension, prediabetes and components of the social environment might play important roles in the development of WMH. Our results enable personal risk assessment for the development of WMH and inform prevention strategies tailored to the individual patient.
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Ekusheva EV, Biryukova EV. [The efficacy of ethylmethylhydroxypyridine succinate in patients with cerebrovascular pathology complicated with diabetes mellitus and metabolic syndrome]. Zh Nevrol Psikhiatr Im S S Korsakova 2021; 120:138-143. [PMID: 33459554 DOI: 10.17116/jnevro2020120121138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Arterial hypertension, diabetes mellitus, obesity and dyslipidemia continue to be the main risk factors for diseases of the circulatory system and the leading causes of mortality in the world, the combination of these diseases significantly increases the likelihood of the development and more rapid progression of cardiovascular and cerebrovascular pathology. Improving approaches to the diagnosis and treatment of these diseases is a priority problem in modern medicine. Currently, there is no universal drug that can influence all stages of pathological process in both cerebrovascular diseases and diabetes mellitus, and the problem of rational use of drugs in patients with comorbid pathology has not been completely resolved. A difficult clinical task includes not only the timely detection of the disease and the correct diagnosis, but also the choice of the safest and most effective medicine. A number of clinical studies have demonstrated the efficacy of mexidol in the treatment of this category of patients, which is determined by its complex, pleiotropic and multimodal mechanisms of action.
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Affiliation(s)
- E V Ekusheva
- Academy of Postgraduate Education under the Federal State Budgetary Unit «Federal Scientific and Clinical Center for Specialized Medical Assistance and Medical Technologies of the Federal Medical Biological Agency», Moscow, Russia.,Belgorod State National Research University, Belgorod, Russia
| | - E V Biryukova
- Evdokimov Moscow State University of Medicine and Dentistry, Moscow, Russia
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Frison E, Dufouil C, Helmer C, Berr C, Auriacombe S, Chêne G. Diabetes-Associated Dementia Risk and Competing Risk of Death in the Three-City Study. J Alzheimers Dis 2020; 71:1339-1350. [PMID: 31524165 DOI: 10.3233/jad-190427] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Diabetes is associated with a higher dementia and mortality risk. However, few studies have accounted for death when estimating the association between diabetes and dementia. We estimated absolute and relative risks of all-cause dementia according to diabetes exposure status in older adults while accounting for competing risk of death using illness-death models. Effect modification by specific characteristics (age, gender, education, cardiovascular risk factors, body mass index, cardiovascular history, depressive symptomatology, impaired renal function, and APOEɛ4 genotype) was also investigated. We analyzed the Three-City study data, a French population-based cohort of adults aged 65 years and above who were followed up for 12 years from 1999-2001. Among 8,328 participants selected in the analytical sample (median age, 73.3 years; 60.3% women), 809 (9.3%) presented with diabetes at baseline. Over a median follow-up period of 8.3 years, 836 participants developed incident dementia. Baseline diabetes was associated with a higher risk of dementia: hazard ratio, 1.79 [95% confidence interval, 1.46-2.19]. No effect modification was shown. Diabetes was associated with a higher 12-year absolute risk of dementia and a lower dementia-free life expectancy (e.g., 14.5% [11.2-18.1] versus 8.7% [7.6-10.2], and 13.4 [12.7-14.1] years versus 16.5 [16.0-17.1] years, respectively, for a 70-year-old woman with the highest level of education). These findings support the potential impact of preventing diabetes on reducing dementia risk in older adults, with a 2-3-year higher dementia-free life expectancy for individuals without diabetes, and inform the design of future interventional trials.
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Affiliation(s)
- Eric Frison
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219 and Inserm, CIC1401-EC, Bordeaux, France; CHU Bordeaux, Pôle de Santé Publique, Bordeaux, France
| | - Carole Dufouil
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219 and Inserm, CIC1401-EC, Bordeaux, France; CHU Bordeaux, Pôle de Santé Publique, Bordeaux, France
| | - Catherine Helmer
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, Team LEHA, UMR 1219, CHU Bordeaux, Bordeaux, France; Inserm, CIC1401-EC, Bordeaux, France
| | - Claudine Berr
- Université de Montpellier, Inserm, U1061, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France
| | - Sophie Auriacombe
- CHU Bordeaux Centre Mémoire Ressource et Recherche/ Institut des Maladies Neurodégénératives clinique (IMNc) Hopital Pellegrin, Bordeaux, France
| | - Geneviève Chêne
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219 and Inserm, CIC1401-EC, Bordeaux, France; CHU Bordeaux, Pôle de Santé Publique, Bordeaux, France
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