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Beydoun MA, Beydoun HA, Fanelli-Kuczmarski MT, Hu YH, Shaked D, Weiss J, Waldstein SR, Launer LJ, Evans MK, Zonderman AB. Uncovering mediational pathways behind racial and socioeconomic disparities in brain volumes: insights from the UK Biobank study. GeroScience 2024:10.1007/s11357-024-01371-1. [PMID: 39388067 DOI: 10.1007/s11357-024-01371-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Accepted: 09/29/2024] [Indexed: 10/15/2024] Open
Abstract
Mediation pathways explaining racial/ethnic and socioeconomic (SES) disparities in structural MRI markers of brain health remain underexplored. We examined racial/ethnic and SES disparities in sMRI markers and tested total, direct, and indirect effects through lifestyle, health-related, and cognition factors using a structural equations modeling approach among 36,184 UK Biobank participants aged 40-70 years at baseline assessment (47% men). Race (non-White vs. White) and lower SES-predicted poorer brain sMRI volumetric outcomes at follow-up, with racial/ethnic disparities in sMRI outcomes involving multiple pathways and SES playing a central role in those pathways. Mediational patterns differed across outcomes, with the SES-sMRI total effect being partially mediated for all outcomes. Over 20% of the total effect (TE) of race/ethnicity on WMH was explained by the indirect effect (IE), by a combination of different pathways going through SES, lifestyle, health-related, and cognition factors. This is in contrast to < 10% for total brain, gray matter (GM), white matter (WM), and frontal GM left/right. Another significant finding is that around 57% of the total effect for SES and the normalized white matter hyperintensity (WMH) was attributed to an indirect effect. This effect encompasses many pathways that involve lifestyle, health-related, and cognitive aspects. Aside from WMH, the percent of TE of SES mediated through various pathways ranged from ~ 5% for WM to > 15% up to 36% for most of the remaining sMRI outcomes, which are composed mainly of GM phenotypes. Race and SES were important determinants of brain volumetric outcomes, with partial mediation of racial/ethnic disparities through SES, lifestyle, health-related, and cognition factors.
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Affiliation(s)
- May A Beydoun
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIA/NIH/IRP, 251 Bayview Blvd., Suite 100, Room #: 04B118, Baltimore, MD, 21224, USA.
| | - Hind A Beydoun
- Department of Research Programs, Fort Belvoir Community Hospital, Fort Belvoir, VA, 22060, USA
| | - Marie T Fanelli-Kuczmarski
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIA/NIH/IRP, 251 Bayview Blvd., Suite 100, Room #: 04B118, Baltimore, MD, 21224, USA
| | - Yi-Han Hu
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIA/NIH/IRP, 251 Bayview Blvd., Suite 100, Room #: 04B118, Baltimore, MD, 21224, USA
| | | | - Jordan Weiss
- Stanford Center On Longevity, Stanford University, Stanford, CA, 94305, USA
| | - Shari R Waldstein
- Department of Psychology, University of Maryland Baltimore County, Catonsville, MD, 21250, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIA/NIH/IRP, 251 Bayview Blvd., Suite 100, Room #: 04B118, Baltimore, MD, 21224, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIA/NIH/IRP, 251 Bayview Blvd., Suite 100, Room #: 04B118, Baltimore, MD, 21224, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIA/NIH/IRP, 251 Bayview Blvd., Suite 100, Room #: 04B118, Baltimore, MD, 21224, USA
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Lee M, Suh CH, Sohn JH, Kim C, Han SW, Sung JH, Yu KH, Lim JS, Lee SH. Impact of white matter hyperintensity volumes estimated by automated methods using deep learning on stroke outcomes in small vessel occlusion stroke. Front Aging Neurosci 2024; 16:1399457. [PMID: 38974905 PMCID: PMC11224430 DOI: 10.3389/fnagi.2024.1399457] [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: 03/12/2024] [Accepted: 05/31/2024] [Indexed: 07/09/2024] Open
Abstract
Introduction Although white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke. Materials and methods Using a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model. After propensity score matching (PSM), we evaluated the impact of WMH volume on early neurological deterioration (END) and poor functional outcomes at 3-month modified Ranking Scale (mRS), defined as mRS score >2 at 3 months, after an SVO stroke. Results Among 1,718 SVO stroke cases, the prevalence of subjects with severe WMH (Fazekas score ≥ 3) was 68.9%. After PSM, END and poor functional outcomes at 3-month mRS (mRS > 2) were higher in the severe WMH group (END: 6.9 vs. 13.5%, p < 0.001; 3-month mRS > 2: 11.4 vs. 24.7%, p < 0.001). The logistic regression analysis using the PSM cohort showed that total WMH volume increased the risk of END [odd ratio [OR], 95% confidence interval [CI]; 1.01, 1.00-1.02, p = 0.048] and 3-month mRS > 2 (OR, 95% CI; 1.02, 1.01-1.03, p < 0.001). Deep WMH was associated with both END and 3-month mRS > 2, but periventricular WMH was associated with 3-month mRS > 2 only. Conclusion This study used automated methods using a deep learning segmentation model to assess the impact of WMH burden on outcomes in SVO stroke. Our findings emphasize the significance of WMH burden in SVO stroke prognosis, encouraging tailored interventions for better patient care.
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Affiliation(s)
- Minwoo Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jong-Hee Sohn
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
| | - Chulho Kim
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
| | - Sang-Won Han
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
| | - Joo Hye Sung
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Jae-Sung Lim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sang-Hwa Lee
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
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Weiss J, Beydoun MA, Beydoun HA, Georgescu MF, Hu YH, Noren Hooten N, Banerjee S, Launer LJ, Evans MK, Zonderman AB. Pathways explaining racial/ethnic and socio-economic disparities in brain white matter integrity outcomes in the UK Biobank study. SSM Popul Health 2024; 26:101655. [PMID: 38562403 PMCID: PMC10982559 DOI: 10.1016/j.ssmph.2024.101655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 02/14/2024] [Accepted: 03/11/2024] [Indexed: 04/04/2024] Open
Abstract
Pathways explaining racial/ethnic and socio-economic status (SES) disparities in white matter integrity (WMI) reflecting brain health, remain underexplored, particularly in the UK population. We examined racial/ethnic and SES disparities in diffusion tensor brain magnetic resonance imaging (dMRI) markers, namely global and tract-specific mean fractional anisotropy (FA), and tested total, direct and indirect effects through lifestyle, health-related and cognition factors using a structural equations modeling approach among 36,184 UK Biobank participants aged 40-70 y at baseline assessment (47% men). Multiple linear regression models were conducted, testing independent associations of race/ethnicity, socio-economic and other downstream factors in relation to global mean FA, while stratifying by Alzheimer's Disease polygenic Risk Score (AD PRS) tertiles. Race (Non-White vs. White) and lower SES predicted poorer WMI (i.e. lower global mean FA) at follow-up, with racial/ethnic disparities in FAmean involving multiple pathways and SES playing a central role in those pathways. Mediational patterns differed across tract-specific FA outcomes, with SES-FAmean total effect being partially mediated (41% of total effect = indirect effect). Furthermore, the association of poor cognition with FAmean was markedly stronger in the two uppermost AD PRS tertiles compared to the lower tertile (T2 and T3: β±SE: -0.0009 ± 0.0001 vs. T1: β±SE: -0.0005 ± 0.0001, P < 0.001), independently of potentially confounding factors. Race and lower SES were generally important determinants of adverse WMI outcomes, with partial mediation of socio-economic disparities in global mean FA through lifestyle, health-related and cognition factors. The association of poor cognition with lower global mean FA was stronger at higher AD polygenic risk.
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Affiliation(s)
- Jordan Weiss
- Stanford Center on Longevity, Stanford University, Stanford, CA, USA
| | - May A. Beydoun
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, USA
| | - Hind A. Beydoun
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, USA
| | - Michael F. Georgescu
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, USA
| | - Yi-Han Hu
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, USA
| | - Nicole Noren Hooten
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, USA
| | - Sri Banerjee
- Public Health Doctoral Programs, Walden University, Minneapolis, MN, USA
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, USA
| | - Michele K. Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, USA
| | - Alan B. Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, USA
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Nance RM, Fohner AE, McClelland RL, Redline S, Nick Bryan R, Desiderio L, Habes M, Longstreth WT, Schwab RJ, Wiemken AS, Heckbert SR. The Association of Upper Airway Anatomy with Brain Structure: The Multi-Ethnic Study of Atherosclerosis. Brain Imaging Behav 2024; 18:510-518. [PMID: 38194040 PMCID: PMC11222025 DOI: 10.1007/s11682-023-00843-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2023] [Indexed: 01/10/2024]
Abstract
Sleep apnea, affecting an estimated 1 in 4 American adults, has been reported to be associated with both brain structural abnormality and impaired cognitive function. Obstructive sleep apnea is known to be affected by upper airway anatomy. To better understand the contribution of upper airway anatomy to pathways linking sleep apnea with impaired cognitive function, we investigated the association of upper airway anatomy with structural brain abnormalities. Based in the Multi-Ethnic Study of Atherosclerosis, a longitudinal cohort study of community-dwelling adults, a comprehensive sleep study and an MRI of the upper airway and brain were performed on 578 participants. Machine learning models were used to select from 74 upper airway measures those measures most associated with selected regional brain volumes and white matter hyperintensity volume. Linear regression assessed associations between the selected upper airway measures, sleep measures, and brain structure. Maxillary divergence was positively associated with hippocampus volume, and mandible length was negatively associated with total white and gray matter volume. Both coefficients were small (coefficients per standard deviation 0.063 mL, p = 0.04, and - 7.0 mL, p < 0.001 respectively), and not affected by adjustment for sleep study measures. Self-reported snoring >2 times per week was associated with larger hippocampus volume (coefficient 0.164 mL, p = 0.007), and higher percentage of time in the N3 sleep stage was associated with larger total white and gray matter volume (4.8 mL, p = 0.004). Despite associations of two upper airway anatomy measures with brain volume, the evidence did not suggest that these upper airway and brain structure associations were acting primarily through the pathway of sleep disturbance.
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Affiliation(s)
- Robin M Nance
- University of Washington, Seattle, WA, USA.
- , 325 9th Ave, Box 359931, Seattle, WA, 98104, USA.
| | - Alison E Fohner
- Department of Epidemiology & Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | | | - Susan Redline
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Nick Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Mohamad Habes
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - W T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, USA
| | - Richard J Schwab
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew S Wiemken
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Agyemang C, van der Linden EL, Chilunga F, van den Born BH. International Migration and Cardiovascular Health: Unraveling the Disease Burden Among Migrants to North America and Europe. J Am Heart Assoc 2024; 13:e030228. [PMID: 38686900 PMCID: PMC11179927 DOI: 10.1161/jaha.123.030228] [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: 07/03/2023] [Accepted: 12/26/2023] [Indexed: 05/02/2024]
Abstract
Europe and North America are the 2 largest recipients of international migrants from low-resource regions in the world. Here, large differences in cardiovascular disease (CVD) morbidity and death exist between migrants and the host populations. This review discusses the CVD burden and its most important contributors among the largest migrant groups in Europe and North America as well as the consequences of migration to high-income countries on CVD diagnosis and therapy. The available evidence indicates that migrants in Europe and North America generally have a higher CVD risk compared with the host populations. Cardiometabolic, behavioral, and psychosocial factors are important contributors to their increased CVD risk. However, despite these common denominators, there are important ethnic differences in the propensity to develop CVD that relate to pre- and postmigration factors, such as socioeconomic status, cultural factors, lifestyle, psychosocial stress, access to health care and health care usage. Some of these pre- and postmigration environmental factors may interact with genetic (epigenetics) and microbial factors, which further influence their CVD risk. The limited number of prospective cohorts and clinical trials in migrant populations remains an important culprit for better understanding pathophysiological mechanism driving health differences and for developing ethnic-specific CVD risk prediction and care. Only by improved understanding of the complex interaction among human biology, migration-related factors, and sociocultural determinants of health influencing CVD risk will we be able to mitigate these differences and truly make inclusive personalized treatment possible.
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Affiliation(s)
- Charles Agyemang
- Department of Public and Occupational Health, Amsterdam UMCUniversity of Amsterdam, Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
- Division of Endocrinology, Diabetes, and Metabolism, Department of MedicineJohns Hopkins University School of MedicineBaltimoreMDUSA
| | - Eva L. van der Linden
- Department of Public and Occupational Health, Amsterdam UMCUniversity of Amsterdam, Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
- Department of Vascular Medicine, Amsterdam UMCUniversity of Amsterdam, Amsterdam Cardiovascular SciencesAmsterdamThe Netherlands
| | - Felix Chilunga
- Department of Public and Occupational Health, Amsterdam UMCUniversity of Amsterdam, Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Bert‐Jan H. van den Born
- Department of Public and Occupational Health, Amsterdam UMCUniversity of Amsterdam, Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
- Department of Vascular Medicine, Amsterdam UMCUniversity of Amsterdam, Amsterdam Cardiovascular SciencesAmsterdamThe Netherlands
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Pradella M, Baraboo JJ, Prabhakaran S, Zhao L, Hijaz T, McComb EN, Naidich MJ, Heckbert SR, Nasrallah IM, Bryan RN, Passman RS, Markl M, Greenland P. MRI Investigation of the Association of Left Atrial and Left Atrial Appendage Hemodynamics with Silent Brain Infarction. J Magn Reson Imaging 2024. [PMID: 38490945 PMCID: PMC11401958 DOI: 10.1002/jmri.29349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 03/01/2024] [Accepted: 03/02/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Left atrial (LA) myopathy is thought to be associated with silent brain infarctions (SBI) through changes in blood flow hemodynamics leading to thrombogenesis. 4D-flow MRI enables in-vivo hemodynamic quantification in the left atrium (LA) and LA appendage (LAA). PURPOSE To determine whether LA and LAA hemodynamic and volumetric parameters are associated with SBI. STUDY TYPE Prospective observational study. POPULATION A single-site cohort of 125 Participants of the multiethnic study of atherosclerosis (MESA), mean age: 72.3 ± 7.2 years, 56 men. FIELD STRENGTH/SEQUENCE 1.5T. Cardiac MRI: Cine balanced steady state free precession (bSSFP) and 4D-flow sequences. Brain MRI: T1- and T2-weighted SE and FLAIR. ASSESSMENT Presence of SBI was determined from brain MRI by neuroradiologists according to routine diagnostic criteria in all participants without a history of stroke based on the MESA database. Minimum and maximum LA volumes and ejection fraction were calculated from bSSFP data. Blood stasis (% of voxels <10 cm/sec) and peak velocity (cm/sec) in the LA and LAA were assessed by a radiologist using an established 4D-flow workflow. STATISTICAL TESTS Student's t test, Mann-Whitney U test, one-way ANOVA, chi-square test. Multivariable stepwise logistic regression with automatic forward and backward selection. Significance level P < 0.05. RESULTS 26 (20.8%) had at least one SBI. After Bonferroni correction, participants with SBI were significantly older and had significantly lower peak velocities in the LAA. In multivariable analyses, age (per 10-years) (odds ratio (OR) = 1.99 (95% confidence interval (CI): 1.30-3.04)) and LAA peak velocity (per cm/sec) (OR = 0.87 (95% CI: 0.81-0.93)) were significantly associated with SBI. CONCLUSION Older age and lower LAA peak velocity were associated with SBI in multivariable analyses whereas volumetric-based measures from cardiac MRI or cardiovascular risk factors were not. Cardiac 4D-flow MRI showed potential to serve as a novel imaging marker for SBI. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Maurice Pradella
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Department of Radiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Justin J Baraboo
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Shyam Prabhakaran
- Department of Neurology, University of Chicago, Chicago, Illinois, USA
| | - Lihui Zhao
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Tarek Hijaz
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Erin N McComb
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Michelle J Naidich
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Susan R Heckbert
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Ilya M Nasrallah
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - R Nick Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Rod S Passman
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Michael Markl
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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Heckbert SR, Jensen PN, Erus G, Nasrallah IM, Rashid T, Habes M, Austin TR, Floyd JS, Schaich CL, Redline S, Bryan RN, Costa MD. Heart rate fragmentation and brain MRI markers of small vessel disease in MESA. Alzheimers Dement 2024; 20:1397-1405. [PMID: 38009395 PMCID: PMC10917025 DOI: 10.1002/alz.13554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 10/12/2023] [Accepted: 10/23/2023] [Indexed: 11/28/2023]
Abstract
INTRODUCTION Heart rate (HR) fragmentation indices quantify breakdown of HR regulation and are associated with atrial fibrillation and cognitive impairment. Their association with brain magnetic resonance imaging (MRI) markers of small vessel disease is unexplored. METHODS In 606 stroke-free participants of the Multi-Ethnic Study of Atherosclerosis (mean age 67), HR fragmentation indices including percentage of inflection points (PIP) were derived from sleep study recordings. We examined PIP in relation to white matter hyperintensity (WMH) volume, total white matter fractional anisotropy (FA), and microbleeds from 3-Tesla brain MRI completed 7 years later. RESULTS In adjusted analyses, higher PIP was associated with greater WMH volume (14% per standard deviation [SD], 95% confidence interval [CI]: 2, 27%, P = 0.02) and lower WM FA (-0.09 SD per SD, 95% CI: -0.16, -0.01, P = 0.03). DISCUSSION HR fragmentation was associated with small vessel disease. HR fragmentation can be measured automatically from ambulatory electrocardiogram devices and may be useful as a biomarker of vascular brain injury.
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Affiliation(s)
- Susan R. Heckbert
- Cardiovascular Health Research UnitUniversity of WashingtonSeattleWashingtonUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtonUSA
| | - Paul N. Jensen
- Cardiovascular Health Research UnitUniversity of WashingtonSeattleWashingtonUSA
- Department of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Guray Erus
- Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and AnalyticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ilya M. Nasrallah
- Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and AnalyticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of RadiologyPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Tanweer Rashid
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging CoreGlenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
| | - Mohamad Habes
- Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and AnalyticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging CoreGlenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
| | - Thomas R. Austin
- Cardiovascular Health Research UnitUniversity of WashingtonSeattleWashingtonUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtonUSA
| | - James S. Floyd
- Cardiovascular Health Research UnitUniversity of WashingtonSeattleWashingtonUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtonUSA
- Department of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Christopher L. Schaich
- Department of SurgeryHypertension and Vascular Research CenterWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Susan Redline
- Brigham and Women's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - R. Nick Bryan
- Department of RadiologyPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Madalena D. Costa
- Harvard Medical SchoolBostonMassachusettsUSA
- Department of MedicineBeth Israel Deaconess Medical CenterBostonMassachusettsUSA
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Farkhondeh V, DeCarli C. White matter hyperintensities in diverse populations: A systematic review of literature in the United States. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 6:100204. [PMID: 38298455 PMCID: PMC10828602 DOI: 10.1016/j.cccb.2024.100204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 12/20/2023] [Accepted: 01/11/2024] [Indexed: 02/02/2024]
Abstract
As the United States' (US) elderly population becomes increasingly diverse, it is imperative that research studies address cognitive health in diverse populations of older Americans. White Matter Hyperintensities (WMH) are useful imaging findings that can be studied in elderly individuals and have been linked to an increased risk of neurological conditions, such as stroke, cognitive impairment, and dementia. We performed a systematic review of literature using PubMed sources to compile all the studies that investigated the prevalence of ethnic and racial differences of WMH burden amongst diverse groups in the US. We identified 23 unique articles that utilized 16 distinct cohorts of which 94 % were prospective, longitudinal studies that included community-based and family-based populations. The overall results were heterogenous in all aspects of data collection and analysis, limiting our ability to run meta-analyses and draw definitive conclusions. General observations suggest increased vascular risk on African American populations, contributing to greater WMH burden in that population. Overall, the findings of this study indicate a need for a standardized approach to investigating WMH in efforts to measure its clinical impact on diverse populations.
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Affiliation(s)
- Vista Farkhondeh
- Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, United States
- Imaging of Dementia and Aging Laboratory and Center for Neurosciences, Davis, CA, United States
| | - Charles DeCarli
- Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, United States
- Imaging of Dementia and Aging Laboratory and Center for Neurosciences, Davis, CA, United States
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Lin K, Wen W, Lipnicki DM, Mewton L, Chen R, Du J, Wang D, Skoog I, Sterner TR, Najar J, Kim KW, Han JW, Kim JS, Ng TP, Ho R, Chua DQL, Anstey KJ, Cherbuin N, Mortby ME, Brodaty H, Kochan N, Sachdev PS, Jiang J. Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: The COSMIC consortium. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12567. [PMID: 38487075 PMCID: PMC10937819 DOI: 10.1002/dad2.12567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 01/18/2024] [Accepted: 02/06/2024] [Indexed: 03/17/2024]
Abstract
INTRODUCTION White matter hyperintensities (WMHs) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well documented in populations of different ethnicities and/or from different geographical regions. METHODS We investigated how WMHs were associated with vascular risk factors and cognition in both Whites and Asians, using data from five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1946). WMH volumes (whole brain, periventricular, and deep) were quantified with UBO Detector and harmonized using the ComBat model. We also harmonized various vascular risk factors and scores for global cognition and individual cognitive domains. RESULTS Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake, and insufficient physical activity. Hypertension and stroke had stronger associations with WMH volumes in Whites than in Asians. No associations between WMH volumes and cognitive performance were found after correction for multiple testing. CONCLUSION The current study highlights ethnic differences in the contributions of vascular risk factors to WMHs.
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Affiliation(s)
- Keshuo Lin
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Wei Wen
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Darren M. Lipnicki
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Louise Mewton
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Rory Chen
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Jing Du
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Dadong Wang
- Quantitative Imaging Research TeamCSIRO Informatics and StatisticsNorth RydeNew South WalesAustralia
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Psychiatry, Cognition and Old Age Psychiatry ClinicSahlgrenska University HospitalGothenburgSweden
| | - Therese Rydberg Sterner
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Aging Research CenterDepartment of NeurobiologyCare Sciences and SocietyKarolinska Institutet and Stockholm UniversityStockholmSweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Section Genomics of Neurodegenerative Diseases and AgingDepartment of Human GeneticsAmsterdam Universitair Medische CentraAmsterdamthe Netherlands
| | - Ki Woong Kim
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
- Department of PsychiatrySeoul National University College of MedicineSeoulSouth Korea
- Department of Brain and Cognitive SciencesSeoul National University College of Natural SciencesSeoulSouth Korea
| | - Ji Won Han
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
- Department of PsychiatrySeoul National University College of MedicineSeoulSouth Korea
| | - Jun Sung Kim
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
| | - Tze Pin Ng
- Department of Psychological MedicineKhoo Teck Puat HospitalYishunSingapore
- Geriatric Education and Research InstituteMinistry of HealthSingaporeSingapore
| | - Roger Ho
- Institute for Health Innovation and Technology (iHealthtech)National University of SingaporeSingaporeSingapore
| | - Denise Qian Ling Chua
- Department of Psychological MedicineNational University of SingaporeSingaporeSingapore
| | - Kaarin J. Anstey
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
- Department of NeurodegenerationNeuroscience Research AustraliaSydneyNew South WalesAustralia
- Ageing Futures InstituteUniversity of New South WalesSydneyNew South WalesAustralia
| | - Nicolas Cherbuin
- National Centre for Epidemiology and Population HealthCollege of Health and MedicineAustralian National UniversityCanberraAustralian Capital TerritoryAustralia
| | - Moyra E. Mortby
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
- Department of NeurodegenerationNeuroscience Research AustraliaSydneyNew South WalesAustralia
- Ageing Futures InstituteUniversity of New South WalesSydneyNew South WalesAustralia
| | - Henry Brodaty
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Nicole Kochan
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Perminder S. Sachdev
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- Neuropsychiatric InstituteThe Prince of Wales HospitalSydneyNew South WalesAustralia
| | - Jiyang Jiang
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
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10
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Roberts R, Huckstepp RT. Innate Sleep Apnea in Spontaneously Hypertensive Rats Is Associated With Microvascular Rarefaction and Neuronal Loss in the preBötzinger Complex. Stroke 2023; 54:3141-3152. [PMID: 38011231 PMCID: PMC10769171 DOI: 10.1161/strokeaha.123.044732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND Sleep apnea (SA) is a major threat to physical health and carries a significant economic burden. These impacts are worsened by its interaction with, and induction of, its comorbidities. SA holds a bidirectional relationship with hypertension, which drives atherosclerosis/arteriolosclerosis, ultimately culminating in vascular dementia. METHODS To enable a better understanding of these sequelae of events, we investigated innate SA and its effects on cognition in adult-aged spontaneously hypertensive rats, which have a range of cardiovascular disorders: plethysmography and electroencephalographic/electromyographic recordings were used to assess sleep-wake state, breathing parameters, and sleep-disordered breathing; immunocytochemistry was used to assess vascular and neural health; the forced alteration Y maze and Barnes maze were used to assess short- and long-term memories, respectively; and an anesthetized preparation was used to assess baroreflex sensitivity. RESULTS Spontaneously hypertensive rats displayed a higher degree of sleep-disordered breathing, which emanates from poor vascular health leading to a loss of preBötzinger Complex neurons. These rats also display small vessel white matter disease, a form of vascular dementia, which may be exacerbated by the SA-induced neuroinflammation in the hippocampus to worsen the related deficits in both long- and short-term memories. CONCLUSIONS Therefore, we postulate that hypertension induces SA through vascular damage in the respiratory column, culminating in neuronal loss in the inspiratory oscillator. This induction of SA, which, in turn, will independently exacerbate hypertension and neural inflammation, increases the rate of vascular dementia.
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Affiliation(s)
- Reno Roberts
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
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11
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Ambriz E, De Pierola C, Calderon NM, Calderon L, Kogut K, Deardorff J, Torres JM. Definitions of successful aging among middle-aged Latinas residing in a rural agricultural community. PLoS One 2023; 18:e0294887. [PMID: 38032988 PMCID: PMC10688629 DOI: 10.1371/journal.pone.0294887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 11/11/2023] [Indexed: 12/02/2023] Open
Abstract
INTRODUCTION Latinos are the fastest growing aging population in the U.S. However, there has been limited attention to conceptualizing successful aging among Latinos, especially those residing in rural communities. Latinos are the largest racial or ethnic group residing in rural underserved communities and rural Latinos experience significant structural barriers to access the conditions they need to age well. The goal of this study is to make unique contributions to the successful aging literature by describing what successful aging means for middle-aged Latinas residing in a rural community. METHODS This qualitative paper used inductive thematic content analysis to examine definitions of successful aging among Latina women (n = 40) residing in an underserved agricultural community and entering mid-life (mean = 49 years old; age range 40-64). RESULTS With regards to definitions of successful aging, four themes emerged: 1) Having good health; 2) maintaining an active lifestyle; 3) the wellbeing of one's children; and 4) being independent. DISCUSSION Participants' definitions of successful aging aligned to some extent with existing frameworks, specifically related to health and independence. However, middle-aged Latina participants' unique definitions of successful aging also diverged from existing frameworks, especially around the wellbeing of their children and the importance of work as a way of maintaining an active lifestyle. More research is needed to understand the unique social context and circumstances of middle-aged Latinos residing in rural communities and how they influence their aging journeys. This can provide important information for the development of culturally sensitive services, interventions, and policies to help Latinos age well.
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Affiliation(s)
- Elizabeth Ambriz
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California, United States of America
| | - Camila De Pierola
- School of Public Health, University of California Berkeley, Berkeley, California, United States of America
| | - Norma M. Calderon
- Center for Environmental Research and Community Health (CERCH), University of California Berkeley, Berkeley, California, United States of America
| | - Lucia Calderon
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California, United States of America
| | - Katherine Kogut
- School of Public Health, University of California Berkeley, Berkeley, California, United States of America
| | - Julianna Deardorff
- School of Public Health, University of California Berkeley, Berkeley, California, United States of America
| | - Jacqueline M. Torres
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California, United States of America
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12
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Nance RM, Fohner AE, McClelland RL, Redline S, Bryan RN, Fitzpatrick A, Habes M, Longstreth WT, Schwab RJ, Wiemken AS, Heckbert SR. The association of upper airway anatomy with cognitive test performance: the Multi-Ethnic Study of Atherosclerosis. BMC Neurol 2023; 23:394. [PMID: 37907860 PMCID: PMC10617161 DOI: 10.1186/s12883-023-03443-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 10/19/2023] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Numerous upper airway anatomy characteristics are risk factors for sleep apnea, which affects 26% of older Americans, and more severe sleep apnea is associated with cognitive impairment. This study explores the pathophysiology and links between upper airway anatomy, sleep, and cognition. METHODS Participants in the Multi-Ethnic Study of Atherosclerosis underwent an upper airway MRI, polysomnography to assess sleep measures including the apnea-hypopnea index (AHI) and completed the Cognitive Abilities Screening Instrument (CASI). Two model selection techniques selected from among 67 upper airway measures those that are most strongly associated with CASI score. The associations of selected upper airway measures with AHI, AHI with CASI score, and selected upper airway anatomy measures with CASI score, both alone and after adjustment for AHI, were assessed using linear regression. RESULTS Soft palate volume, maxillary divergence, and upper facial height were significantly positively associated with higher CASI score, indicating better cognition. The coefficients were small, with a 1 standard deviation (SD) increase in these variables being associated with a 0.83, 0.75, and 0.70 point higher CASI score, respectively. Additional adjustment for AHI very slightly attenuated these associations. Larger soft palate volume was significantly associated with higher AHI (15% higher AHI (95% CI 2%,28%) per SD). Higher AHI was marginally associated with higher CASI score (0.43 (95% CI 0.01,0.85) per AHI doubling). CONCLUSIONS Three upper airway measures were weakly but significantly associated with higher global cognitive test performance. Sleep apnea did not appear to be the mechanism through which these upper airway and cognition associations were acting. Further research on the selected upper airway measures is recommended.
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Affiliation(s)
- Robin M Nance
- University of Washington, 325 9th Ave, Box 359931, Seattle, 98104, USA.
| | - Alison E Fohner
- Department of Epidemiology & Cardiovascular Health Research Unit, University of Washington, Seattle, USA
| | | | - Susan Redline
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - R Nick Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | | | - Mohamad Habes
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - W T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, USA
| | - Richard J Schwab
- Department of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Andrew S Wiemken
- Department of Medicine, University of Pennsylvania, Philadelphia, USA
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13
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Jensen PN, Rashid T, Ware JB, Cui Y, Sitlani CM, Austin TR, Longstreth W, Bertoni AG, Mamourian E, Bryan RN, Nasrallah IM, Habes M, Heckbert SR. Association of brain microbleeds with risk factors, cognition, and MRI markers in MESA. Alzheimers Dement 2023; 19:4139-4149. [PMID: 37289978 PMCID: PMC11163989 DOI: 10.1002/alz.13346] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/11/2023] [Accepted: 05/17/2023] [Indexed: 06/10/2023]
Abstract
INTRODUCTION Little is known about the epidemiology of brain microbleeds in racially/ethnically diverse populations. METHODS In the Multi-Ethnic Study of Atherosclerosis, brain microbleeds were identified from 3T magnetic resonance imaging susceptibility-weighted imaging sequences using deep learning models followed by radiologist review. RESULTS Among 1016 participants without prior stroke (25% Black, 15% Chinese, 19% Hispanic, 41% White, mean age 72), microbleed prevalence was 20% at age 60 to 64.9 and 45% at ≥85 years. Deep microbleeds were associated with older age, hypertension, higher body mass index, and atrial fibrillation, and lobar microbleeds with male sex and atrial fibrillation. Overall, microbleeds were associated with greater white matter hyperintensity volume and lower total white matter fractional anisotropy. DISCUSSION Results suggest differing associations for lobar versus deep locations. Sensitive microbleed quantification will facilitate future longitudinal studies of their potential role as an early indicator of vascular pathology.
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Affiliation(s)
- Paul N. Jensen
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98195, USA
- Department of Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Tanweer Rashid
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas 78229, USA
| | - Jeffrey B. Ware
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19103, USA
| | - Yuhan Cui
- Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Colleen M. Sitlani
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98195, USA
- Department of Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Thomas R. Austin
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98195, USA
- Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA
| | - W.T. Longstreth
- Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA
- Department of Neurology, University of Washington, Seattle, Washington 98195, USA
| | - Alain G. Bertoni
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157, USA
| | - Elizabeth Mamourian
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19103, USA
- Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - R. Nick Bryan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19103, USA
| | - Ilya M. Nasrallah
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19103, USA
- Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Mohamad Habes
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas 78229, USA
- Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98195, USA
- Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA
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Lin K, Wen W, Lipnicki DM, Mewton L, Chen R, Du J, Wang D, Skoog I, Sterner TR, Najar J, Kim KW, Han JW, Kim JS, Ng TP, Ho R, Chua DQL, Anstey KJ, Cherbuin N, Mortby ME, Brodaty H, Kochan N, Sachdev PS, Jiang J. Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: the COSMIC consortium. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.30.23294876. [PMID: 37693599 PMCID: PMC10491386 DOI: 10.1101/2023.08.30.23294876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
INTRODUCTION White matter hyperintensities (WMH) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well-documented in populations of different ethnicities and/or from different geographical regions. METHOD Magnetic resonance imaging data of five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1,946) were examined for WMH and their associations with vascular risk factors and cognition. RESULT Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake and insufficient physical activity. Participants with moderate or higher physical activity had less WMH than those who never exercised, but the former two groups did not differ. Hypertension and stroke had stronger associations with WMH volumes in the White, compared to Asian subsample. DISCUSSION The current study highlighted the ethnic differences in the contributions of vascular risk factors to WMH.
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Affiliation(s)
- Keshuo Lin
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Darren M. Lipnicki
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Louise Mewton
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Rory Chen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Jing Du
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Dadong Wang
- CSIRO Informatics and Statistics, Locked Bag 17, North Ryde, NSW 1670, Australia
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Box 100, Goeteborg, Vaestra Goetaland 405 30, Sweden
| | - Therese Rydberg Sterner
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Nobels väg 6, 171 77 Stockholm, Sweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Human Genetics, Amsterdam Universitair Medische Centra, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul 03080, Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Korea
| | - Jun Sung Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
| | - Tze Pin Ng
- Khoo Teck Puat Hospital, 768828, Singapore
- Geriatric Education and Research Institute, Ministry of Health, 768024, Singapore
| | - Roger Ho
- Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, 119077, Singapore
| | - Denise Qian Ling Chua
- Department of Psychological Medicine, National University of Singapore, 119077, Singapore
| | - Kaarin J. Anstey
- School of Psychology, University of New South Wales, NSW 2052,Australia
- Neuroscience Research Australia, NSW 2031, Australia
- Ageing Futures Institute, University of New South Wales, NSW 2052,Australia
| | - Nicolas Cherbuin
- National Centre for Epidemiology and Population Health, College of Health and Medicine, Australian National University, ACT 2600, Canberra, Australia
| | - Moyra E. Mortby
- School of Psychology, University of New South Wales, NSW 2052,Australia
- Neuroscience Research Australia, NSW 2031, Australia
- Ageing Futures Institute, University of New South Wales, NSW 2052,Australia
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Nicole Kochan
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital, Sydney, NSW 2031, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
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15
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Guo R, Li X, Sun M, Wang Y, Wang X, Li J, Xie Z, Yao N, Yang Y, Li B, Jin L. Vision impairment, hearing impairment and functional Limitations of subjective cognitive decline: a population-based study. BMC Geriatr 2023; 23:230. [PMID: 37060058 PMCID: PMC10103414 DOI: 10.1186/s12877-023-03950-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 04/03/2023] [Indexed: 04/16/2023] Open
Abstract
BACKGROUND The association between sensory impairment including vision impairment (VI), hearing impairment (HI), dual impairment (DI) and the functional limitations of SCD (SCD-related FL) are still unclear in middle-aged and older people. METHODS 162,083 participants from BRFSS in 2019 to 2020 was used in this cross-sectional study. After adjusting the weights, multiple logistic regression was used to study the relationship between sensory impairment and SCD or SCD-related FL. In addition, we performed subgroup analysis on the basis of interaction between sensory impairment and covariates. RESULTS Participants who reported sensory impairment were more likely to report SCD or SCD-related FL compared to those without sensory impairment (p < 0.001). The association between dual impairment and SCD-related FL was the strongest, the adjusted odds ratios (aORs) and 95% confidence interval (95% CI) were [HI, 2.88 (2.41, 3.43); VI, 3.15(2.61, 3.81); DI, 6.78(5.43, 8.47)] respectively. In addition, subgroup analysis showed that men with sensory impairment were more likely to report SCD-related FL than women, the aORs and 95% CI were [HI, 3.15(2.48, 3.99) vs2.69(2.09, 3.46); VI,3.67(2.79, 4.83) vs. 2.86(2.22, 3.70); DI, 9.07(6.67, 12.35) vs. 5.03(3.72, 6.81)] respectively. The subject of married with dual impairment had a stronger association with SCD-related FL than unmarried subjects the aOR and 95% CI was [9.58(6.69, 13.71) vs. 5.33(4.14, 6.87)]. CONCLUSIONS Sensory impairment was strongly associated with SCD and SCD-related FL. Individuals with dual impairment had the greatest possibility to reported SCD-related FL, and the association was stronger for men or married subjects than other subjects.
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Affiliation(s)
- Ruirui Guo
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Xiaotong Li
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Mengzi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Yuxiang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Xuhan Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Jing Li
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Zechun Xie
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Nan Yao
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Yixue Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China
| | - Bo Li
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China.
| | - Lina Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, P. R. China.
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16
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Charisis S, Rashid T, Liu H, Ware JB, Jensen PN, Austin TR, Li K, Fadaee E, Hilal S, Chen C, Hughes TM, Romero JR, Toledo JB, Longstreth WT, Hohman TJ, Nasrallah I, Bryan RN, Launer LJ, Davatzikos C, Seshadri S, Heckbert SR, Habes M. Assessment of Risk Factors and Clinical Importance of Enlarged Perivascular Spaces by Whole-Brain Investigation in the Multi-Ethnic Study of Atherosclerosis. JAMA Netw Open 2023; 6:e239196. [PMID: 37093602 PMCID: PMC10126873 DOI: 10.1001/jamanetworkopen.2023.9196] [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: 11/20/2022] [Accepted: 03/07/2023] [Indexed: 04/25/2023] Open
Abstract
Importance Enlarged perivascular spaces (ePVSs) have been associated with cerebral small-vessel disease (cSVD). Although their etiology may differ based on brain location, study of ePVSs has been limited to specific brain regions; therefore, their risk factors and significance remain uncertain. Objective Toperform a whole-brain investigation of ePVSs in a large community-based cohort. Design, Setting, and Participants This cross-sectional study analyzed data from the Atrial Fibrillation substudy of the population-based Multi-Ethnic Study of Atherosclerosis. Demographic, vascular risk, and cardiovascular disease data were collected from September 2016 to May 2018. Brain magnetic resonance imaging was performed from March 2018 to July 2019. The reported analysis was conducted between August and October 2022. A total of 1026 participants with available brain magnetic resonance imaging data and complete information on demographic characteristics and vascular risk factors were included. Main Outcomes and Measures Enlarged perivascular spaces were quantified using a fully automated deep learning algorithm. Quantified ePVS volumes were grouped into 6 anatomic locations: basal ganglia, thalamus, brainstem, frontoparietal, insular, and temporal regions, and were normalized for the respective regional volumes. The association of normalized regional ePVS volumes with demographic characteristics, vascular risk factors, neuroimaging indices, and prevalent cardiovascular disease was explored using generalized linear models. Results In the 1026 participants, mean (SD) age was 72 (8) years; 541 (53%) of the participants were women. Basal ganglia ePVS volume was positively associated with age (β = 3.59 × 10-3; 95% CI, 2.80 × 10-3 to 4.39 × 10-3), systolic blood pressure (β = 8.35 × 10-4; 95% CI, 5.19 × 10-4 to 1.15 × 10-3), use of antihypertensives (β = 3.29 × 10-2; 95% CI, 1.92 × 10-2 to 4.67 × 10-2), and negatively associated with Black race (β = -3.34 × 10-2; 95% CI, -5.08 × 10-2 to -1.59 × 10-2). Thalamic ePVS volume was positively associated with age (β = 5.57 × 10-4; 95% CI, 2.19 × 10-4 to 8.95 × 10-4) and use of antihypertensives (β = 1.19 × 10-2; 95% CI, 6.02 × 10-3 to 1.77 × 10-2). Insular region ePVS volume was positively associated with age (β = 1.18 × 10-3; 95% CI, 7.98 × 10-4 to 1.55 × 10-3). Brainstem ePVS volume was smaller in Black than in White participants (β = -5.34 × 10-3; 95% CI, -8.26 × 10-3 to -2.41 × 10-3). Frontoparietal ePVS volume was positively associated with systolic blood pressure (β = 1.14 × 10-4; 95% CI, 3.38 × 10-5 to 1.95 × 10-4) and negatively associated with age (β = -3.38 × 10-4; 95% CI, -5.40 × 10-4 to -1.36 × 10-4). Temporal region ePVS volume was negatively associated with age (β = -1.61 × 10-2; 95% CI, -2.14 × 10-2 to -1.09 × 10-2), as well as Chinese American (β = -2.35 × 10-1; 95% CI, -3.83 × 10-1 to -8.74 × 10-2) and Hispanic ethnicities (β = -1.73 × 10-1; 95% CI, -2.96 × 10-1 to -4.99 × 10-2). Conclusions and Relevance In this cross-sectional study of ePVSs in the whole brain, increased ePVS burden in the basal ganglia and thalamus was a surrogate marker for underlying cSVD, highlighting the clinical importance of ePVSs in these locations.
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Affiliation(s)
- Sokratis Charisis
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
- Department of Neurology, University of Texas Health Science Center at San Antonio
| | - Tanweer Rashid
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
| | - Hangfan Liu
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
- AI2D Center for AI and Data Science for Integrated Diagnostics, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Jeffrey B. Ware
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Paul N. Jensen
- Department of Medicine, University of Washington, Seattle
| | | | - Karl Li
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
| | - Elyas Fadaee
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore
| | - Christopher Chen
- Memory Aging and Cognition Centre, National University Health System, Singapore
| | - Timothy M. Hughes
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jose Rafael Romero
- Department of Neurology, School of Medicine, Boston University, Boston, Massachusetts
| | - Jon B. Toledo
- Nantz National Alzheimer Center, Stanley Appel Department of Neurology, Houston Methodist Hospital, Houston, Texas
| | - Will T. Longstreth
- Department of Epidemiology, University of Washington, Seattle
- Department of Neurology, University of Washington, Seattle
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Ilya Nasrallah
- AI2D Center for AI and Data Science for Integrated Diagnostics, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - R. Nick Bryan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Lenore J. Launer
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland
| | - Christos Davatzikos
- AI2D Center for AI and Data Science for Integrated Diagnostics, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Sudha Seshadri
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
- Department of Neurology, University of Texas Health Science Center at San Antonio
| | | | - Mohamad Habes
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
- AI2D Center for AI and Data Science for Integrated Diagnostics, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
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17
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Rashid T, Li K, Toledo JB, Nasrallah I, Pajewski NM, Dolui S, Detre J, Wolk DA, Liu H, Heckbert SR, Bryan RN, Williamson J, Davatzikos C, Seshadri S, Launer LJ, Habes M. Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers: Post Hoc Secondary Analysis of the SPRINT MIND Randomized Clinical Trial. JAMA Netw Open 2023; 6:e231055. [PMID: 36857053 PMCID: PMC9978954 DOI: 10.1001/jamanetworkopen.2023.1055] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2023] Open
Abstract
IMPORTANCE Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers. OBJECTIVE To investigate the regional associations of intensive vs standard BP control with small vessel disease biomarkers, such as white matter lesions (WMLs), fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF). DESIGN, SETTING, AND PARTICIPANTS The Systolic Blood Pressure Intervention Trial (SPRINT) is a multicenter randomized clinical trial that compared intensive systolic BP (SBP) control (SBP target <120 mm Hg) vs standard control (SBP target <140 mm Hg) among participants aged 50 years or older with hypertension and without diabetes or a history of stroke. The study began randomization on November 8, 2010, and stopped July 1, 2016, with a follow-up duration of approximately 4 years. A total of 670 and 458 participants completed brain magnetic resonance imaging at baseline and follow-up, respectively, and comprise the cohort for this post hoc analysis. Statistical analyses for this post hoc analysis were performed between August 2020 and October 2022. INTERVENTIONS At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment. MAIN OUTCOMES AND MEASURES The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest). RESULTS At baseline, 355 participants (mean [SD] age, 67.7 [8.0] years; 200 men [56.3%]) received intensive BP treatment and 315 participants (mean [SD] age, 67.0 [8.4] years; 199 men [63.2%]) received standard BP treatment. Intensive treatment was associated with smaller mean increases in WML volume compared with standard treatment (644.5 mm3 vs 1258.1 mm3). The smaller mean increases were observed specifically in the deep white matter regions of the left anterior corona radiata (intensive treatment, 30.3 mm3 [95% CI, 16.0-44.5 mm3]; standard treatment, 80.5 mm3 [95% CI, 53.8-107.2 mm3]), left tapetum (intensive treatment, 11.8 mm3 [95% CI, 4.4-19.2 mm3]; standard treatment, 27.2 mm3 [95% CI, 19.4-35.0 mm3]), left superior fronto-occipital fasciculus (intensive treatment, 3.2 mm3 [95% CI, 0.7-5.8 mm3]; standard treatment, 9.4 mm3 [95% CI, 5.5-13.4 mm3]), left posterior corona radiata (intensive treatment, 26.0 mm3 [95% CI, 12.9-39.1 mm3]; standard treatment, 52.3 mm3 [95% CI, 34.8-69.8 mm3]), left splenium of the corpus callosum (intensive treatment, 45.4 mm3 [95% CI, 25.1-65.7 mm3]; standard treatment, 83.0 mm3 [95% CI, 58.7-107.2 mm3]), left posterior thalamic radiation (intensive treatment, 53.0 mm3 [95% CI, 29.8-76.2 mm3]; standard treatment, 106.9 mm3 [95% CI, 73.4-140.3 mm3]), and right posterior thalamic radiation (intensive treatment, 49.5 mm3 [95% CI, 24.3-74.7 mm3]; standard treatment, 102.6 mm3 [95% CI, 71.0-134.2 mm3]). CONCLUSIONS AND RELEVANCE This study suggests that intensive BP treatment, compared with standard treatment, was associated with a slower increase of WMLs, improved diffusion tensor imaging, and FA and CBF changes in several brain regions that represent vulnerable areas that may benefit from more strict BP control. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01206062.
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Affiliation(s)
- Tanweer Rashid
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Karl Li
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Jon B. Toledo
- Department of Neurology, University of Florida, Gainesville
- Department of Neurology, Houston Methodist Hospital, Houston, Texas
| | - Ilya Nasrallah
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Sudipto Dolui
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
| | - John Detre
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Department of Neurology, University of Pennsylvania, Philadelphia
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia
| | - Hangfan Liu
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | | | - R. Nick Bryan
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
| | - Jeff Williamson
- Section of Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Christos Davatzikos
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Sudha Seshadri
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Lenore J. Launer
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland
| | - Mohamad Habes
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
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18
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Sharp FR, DeCarli CS, Jin LW, Zhan X. White matter injury, cholesterol dysmetabolism, and APP/Abeta dysmetabolism interact to produce Alzheimer's disease (AD) neuropathology: A hypothesis and review. Front Aging Neurosci 2023; 15:1096206. [PMID: 36845656 PMCID: PMC9950279 DOI: 10.3389/fnagi.2023.1096206] [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: 11/11/2022] [Accepted: 01/30/2023] [Indexed: 02/12/2023] Open
Abstract
We postulate that myelin injury contributes to cholesterol release from myelin and cholesterol dysmetabolism which contributes to Abeta dysmetabolism, and combined with genetic and AD risk factors, leads to increased Abeta and amyloid plaques. Increased Abeta damages myelin to form a vicious injury cycle. Thus, white matter injury, cholesterol dysmetabolism and Abeta dysmetabolism interact to produce or worsen AD neuropathology. The amyloid cascade is the leading hypothesis for the cause of Alzheimer's disease (AD). The failure of clinical trials based on this hypothesis has raised other possibilities. Even with a possible new success (Lecanemab), it is not clear whether this is a cause or a result of the disease. With the discovery in 1993 that the apolipoprotein E type 4 allele (APOE4) was the major risk factor for sporadic, late-onset AD (LOAD), there has been increasing interest in cholesterol in AD since APOE is a major cholesterol transporter. Recent studies show that cholesterol metabolism is intricately involved with Abeta (Aβ)/amyloid transport and metabolism, with cholesterol down-regulating the Aβ LRP1 transporter and upregulating the Aβ RAGE receptor, both of which would increase brain Aβ. Moreover, manipulating cholesterol transport and metabolism in rodent AD models can ameliorate pathology and cognitive deficits, or worsen them depending upon the manipulation. Though white matter (WM) injury has been noted in AD brain since Alzheimer's initial observations, recent studies have shown abnormal white matter in every AD brain. Moreover, there is age-related WM injury in normal individuals that occurs earlier and is worse with the APOE4 genotype. Moreover, WM injury precedes formation of plaques and tangles in human Familial Alzheimer's disease (FAD) and precedes plaque formation in rodent AD models. Restoring WM in rodent AD models improves cognition without affecting AD pathology. Thus, we postulate that the amyloid cascade, cholesterol dysmetabolism and white matter injury interact to produce and/or worsen AD pathology. We further postulate that the primary initiating event could be related to any of the three, with age a major factor for WM injury, diet and APOE4 and other genes a factor for cholesterol dysmetabolism, and FAD and other genes for Abeta dysmetabolism.
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Affiliation(s)
- Frank R. Sharp
- Department of Neurology, The MIND Institute, University of California at Davis Medical Center, Sacramento, CA, United States
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19
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Morrison C, Dadar M, Manera AL, Collins DL. Racial differences in white matter hyperintensity burden in older adults. Neurobiol Aging 2023; 122:112-119. [PMID: 36543016 DOI: 10.1016/j.neurobiolaging.2022.11.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/17/2022] [Accepted: 11/19/2022] [Indexed: 11/27/2022]
Abstract
White matter hyperintensities (WMHs) may be one of the earliest pathological changes in aging. Race differences in WMH burden has been conflicting. This study examined if race influences WMHs and whether these differences are influenced by vascular risk factors. Alzheimer's Disease Neuroimaging Initiative participants were included if they had a baseline MRI, diagnosis, and WMH measurements. Ninety-one Blacks and 1937 Whites were included. Using bootstrap re-sampling, 91 Whites were randomly sampled and matched to Blacks based on age, sex, education, and diagnosis 1000 times. Linear models examined the influence of race on baseline WMHs, and change of WMHs over time, with and without vascular factors. Vascular risk factors had higher prevalence in Blacks than Whites. When not including vascular factors, Blacks had greater frontal, parietal, deep, and total WMH burden compared to Whites. There were no race differences in longitudinal progression of WMH accumulation. After controlling for vascular factors, only overall longitudinal parietal WMH group differences remained significant, suggesting that vascular factors contribute to racial group differences observed in WMHs.
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Affiliation(s)
- Cassandra Morrison
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.
| | - Mahsa Dadar
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Ana L Manera
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - D Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
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20
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Austin TR, Jensen PN, Nasrallah IM, Habes M, Rashid T, Ware JB, Chen LY, Greenland P, Hughes TM, Post WS, Shea SJ, Watson KE, Sitlani CM, Floyd JS, Kronmal RA, Longstreth WT, Bertoni AG, Shah SJ, Bryan RN, Heckbert SR. Left Atrial Function and Arrhythmias in Relation to Small Vessel Disease on Brain MRI: The Multi-Ethnic Study of Atherosclerosis. J Am Heart Assoc 2022; 11:e026460. [PMID: 36250665 PMCID: PMC9673671 DOI: 10.1161/jaha.122.026460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 09/12/2022] [Indexed: 11/29/2022]
Abstract
Background Atrial fibrillation (AF) is associated with increased stroke risk and accelerated cognitive decline, but the association of early manifestations of left atrial (LA) impairment with subclinical changes in brain structure is unclear. We investigated whether abnormal LA structure and function, greater supraventricular ectopy, and intermittent AF are associated with small vessel disease on magnetic resonance imaging of the brain. Methods and Results In the Multi-Ethnic Study of Atherosclerosis, 967 participants completed 14-day ambulatory electrocardiographic monitoring, speckle tracking echocardiography and, a median 17 months later, magnetic resonance imaging of the brain. We assessed associations of LA volume index and reservoir strain, supraventricular ectopy, and prevalent AF with brain magnetic resonance imaging measures of small vessel disease and atrophy. The mean age of participants was 72 years; 53% were women. In multivariable models, LA enlargement was associated with lower white matter fractional anisotropy and greater prevalence of microbleeds; reduced LA strain, indicating worse LA function, was associated with more microbleeds. More premature atrial contractions were associated with lower total gray matter volume. Compared with no AF, intermittent AF (prevalent AF with <100% AF during electrocardiographic monitoring) was associated with lower white matter fractional anisotropy (-0.25 SDs [95% CI, -0.44 to -0.07]) and greater prevalence of microbleeds (prevalence ratio: 1.42 [95% CI, 1.12-1.79]). Conclusions In individuals without a history of stroke or transient ischemic attack, alterations of LA structure and function, including enlargement, reduced strain, frequent premature atrial contractions, and intermittent AF, were associated with increased markers of small vessel disease. Detailed assessment of LA structure and function and extended ECG monitoring may enable early identification of individuals at greater risk of small vessel disease.
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Affiliation(s)
| | | | - Ilya M. Nasrallah
- Center for Biomedical Image Computing and Analytics, Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPA
| | - Mohamad Habes
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging CoreGlenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San AntonioTX
| | - Tanweer Rashid
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging CoreGlenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San AntonioTX
| | - Jeffrey B. Ware
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPA
| | - Lin Yee Chen
- Cardiovascular Division, Department of MedicineUniversity of Minnesota Medical SchoolMinneapolisMN
| | - Philip Greenland
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIL
- Division of Cardiology, Department of MedicineNorthwestern University Feinberg School of MedicineChicagoIL
| | - Timothy M. Hughes
- Department of Internal MedicineWake Forest School of MedicineWinston‐SalemNC
| | - Wendy S. Post
- Division of Cardiology, Department of MedicineJohns Hopkins UniversityBaltimoreMD
| | - Steven J. Shea
- Departments of Medicine and EpidemiologyColumbia UniversityNew YorkNY
| | - Karol E. Watson
- Department of Medicine, David Geffen School of MedicineUniversity of CaliforniaLos AngelesCA
| | | | - James S. Floyd
- Department of EpidemiologyUniversity of WashingtonSeattleWA
- Department of MedicineUniversity of WashingtonSeattleWA
| | | | - W. T. Longstreth
- Department of EpidemiologyUniversity of WashingtonSeattleWA
- Department of NeurologyUniversity of WashingtonSeattleWA
| | - Alain G. Bertoni
- Department of Epidemiology and PreventionWake Forest School of MedicineWinston‐SalemNC
| | - Sanjiv J. Shah
- Division of Cardiology, Department of MedicineNorthwestern University Feinberg School of MedicineChicagoIL
| | - R. Nick Bryan
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPA
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21
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Smith BM, Wiemken A, Hoffman EA, Keenan BT, Allen NB, Bertoni AG, Jacobs DR, Michos ED, Watson KE, Redline S, Schwab RJ, Barr RG, Heckbert SR. Upper and Lower Airway Dysanapsis and Airflow Obstruction Among Older Adults. Am J Respir Crit Care Med 2022; 206:913-917. [PMID: 35679318 DOI: 10.1164/rccm.202202-0353le] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Benjamin M Smith
- McGill University, Respiratory Medicine, Montreal, Quebec, Canada.,Columbia University, Medicine, New York, New York, United States;
| | - Andrew Wiemken
- University of Pennsylvania, 6572, Center for Sleep and Circadian Neurobiology, Philadelphia, Pennsylvania, United States
| | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - Brendan T Keenan
- University of Pennsylvania Perelman School of Medicine, 14640, Center for Sleep and Circadian Neurobiology, Philadelphia, Pennsylvania, United States
| | | | - Alain G Bertoni
- Wake Forest University, Department of Epidemiology and Prevention, Winston-Salem, North Carolina, United States
| | - David R Jacobs
- University of Minnesota, Epidemiology, Minneapolis, Minnesota, United States
| | - Erin D Michos
- Johns Hopkins University, Medicine, Baltimore, Maryland, United States
| | - Karol E Watson
- University of California at Los Angeles, Medicine, Los Angeles, California, United States
| | - Susan Redline
- Brigham and Women's Hospital, Division of Sleep and Circadian Disorders, Boston, Massachusetts, United States.,Harvard Medical School, Division of Sleep Medicine, Boston, Massachusetts, United States
| | - Richard J Schwab
- University of Pennsylvania Perelman School of Medicine, 14640, Philadelphia, Pennsylvania, United States
| | - R Graham Barr
- Columbia University, Epidemiology, New York, New York, United States
| | - Susan R Heckbert
- University of Washington, Cardiovascular Health Research Unit, Seattle, Washington, United States.,University of Washington, Department of Epidemiology, Seattle, Washington, United States.,Kaiser Permanente Washington Health Research Institute, Seattle, Washington, United States
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