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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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Yang A, Yang YT, Zhao XM. An augmented Mendelian randomization approach provides causality of brain imaging features on complex traits in a single biobank-scale dataset. PLoS Genet 2023; 19:e1011112. [PMID: 38150468 PMCID: PMC10775988 DOI: 10.1371/journal.pgen.1011112] [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: 06/08/2023] [Revised: 01/09/2024] [Accepted: 12/12/2023] [Indexed: 12/29/2023] Open
Abstract
Mendelian randomization (MR) is an effective approach for revealing causal risk factors that underpin complex traits and diseases. While MR has been more widely applied under two-sample settings, it is more promising to be used in one single large cohort given the rise of biobank-scale datasets that simultaneously contain genotype data, brain imaging data, and matched complex traits from the same individual. However, most existing multivariable MR methods have been developed for two-sample setting or a small number of exposures. In this study, we introduce a one-sample multivariable MR method based on partial least squares and Lasso regression (MR-PL). MR-PL is capable of considering the correlation among exposures (e.g., brain imaging features) when the number of exposures is extremely upscaled, while also correcting for winner's curse bias. We performed extensive and systematic simulations, and demonstrated the robustness and reliability of our method. Comprehensive simulations confirmed that MR-PL can generate more precise causal estimates with lower false positive rates than alternative approaches. Finally, we applied MR-PL to the datasets from UK Biobank to reveal the causal effects of 36 white matter tracts on 180 complex traits, and showed putative white matter tracts that are implicated in smoking, blood vascular function-related traits, and eating behaviors.
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Affiliation(s)
- Anyi Yang
- Department of Neurology, Zhongshan Hospital and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People’s Republic of China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People’s Republic of China
| | - Yucheng T. Yang
- Department of Neurology, Zhongshan Hospital and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People’s Republic of China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People’s Republic of China
| | - Xing-Ming Zhao
- Department of Neurology, Zhongshan Hospital and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People’s Republic of China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People’s Republic of China
- State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, People’s Republic of China
- International Human Phenome Institutes (Shanghai), Shanghai, People’s Republic of China
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Li J, Gao W, Liu J, Zhang X, Tao J, Zhang G. Red blood cell distribution width and maximum left ventricular wall thickness predict poor outcomes in patients with hypertrophic cardiomyopathy. Echocardiography 2022; 39:278-285. [PMID: 35066909 DOI: 10.1111/echo.15303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/05/2021] [Accepted: 01/04/2022] [Indexed: 11/29/2022] Open
Affiliation(s)
- Jia Li
- Department of Cardiology The Jiangmen Central Hospital The Jiangmen Central Hospital of Sun Yat‐Set University Jiangmen China
- Department of Cardiology The First Affiliated Hospital of Sun Yat‐sen University Guangzhou China
- Grade 17, Sun Yat‐sen University Zhongshan School of Medicine Sun Yat‐sen University Guangzhou China
| | - Weidong Gao
- Department of Cardiology The Jiangmen Central Hospital The Jiangmen Central Hospital of Sun Yat‐Set University Jiangmen China
| | - Jinxue Liu
- Department of Cardiology The Jiangmen Central Hospital The Jiangmen Central Hospital of Sun Yat‐Set University Jiangmen China
| | - Xuefang Zhang
- Department of Cardiology The Jiangmen Central Hospital The Jiangmen Central Hospital of Sun Yat‐Set University Jiangmen China
| | - Jun Tao
- Department of Cardiology The First Affiliated Hospital of Sun Yat‐sen University Guangzhou China
| | - Gaoxing Zhang
- Department of Cardiology The Jiangmen Central Hospital The Jiangmen Central Hospital of Sun Yat‐Set University Jiangmen China
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Fang Y, Doyle MF, Alosco ML, Mez J, Satizabal CL, Qiu WQ, Lunetta KL, Murabito JM. Cross-Sectional Association Between Blood Cell Phenotypes, Cognitive Function, and Brain Imaging Measures in the Community-Based Framingham Heart Study. J Alzheimers Dis 2022; 87:1291-1305. [PMID: 35431244 PMCID: PMC9969805 DOI: 10.3233/jad-215533] [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: 11/15/2022]
Abstract
BACKGROUND Peripheral inflammation is associated with increased risk for dementia. Neutrophil to lymphocyte ratio (NLR), red cell distribution width (RDW), and mean platelet volume (MPV), are easily measured circulating blood cell phenotypes reflecting chronic peripheral inflammation, but their association with dementia status is unclear. OBJECTIVE We sought to investigate the cross-sectional association of these inflammatory measures with neuropsychological (NP) test performance, and brain magnetic resonance imaging (MRI) measures in the Framingham Heart Study (FHS) Offspring, Third-generation, and Omni cohorts. METHODS We identified FHS participants who attended an exam that included a complete blood cell count (CBC) and underwent NP testing (n = 3,396) or brain MRI (n = 2,770) within five years of blood draw. We investigated the association between NLR, RDW, and MPV and NP test performance and structural MRI-derived volumetric measurements using linear mixed effect models accounting for family relationships and adjusting for potential confounders. RESULTS Participants were on average 60 years old, 53% female, and about 80% attended some college. Higher NLR was significantly associated with poorer performance on visual memory, and visuospatial abilities, as well as with larger white matter hyperintensity volume. We also observed associations for higher RDW with poorer executive function and smaller total cerebral brain volume. CONCLUSION Chronic peripheral inflammation as measured by NLR and RDW was associated with worse cognitive function, reduced brain volume, and greater microvascular disease in FHS participants. If confirmed in other samples, CBC may provide informative and cost-effective biomarkers of abnormal brain aging in the community.
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Affiliation(s)
- Yuan Fang
- Boston University School of Public Health, Department of Biostatistics, Boston, MA, USA
| | - Margaret F. Doyle
- University of Vermont, Larner College of Medicine, Department of Pathology and Laboratory Medicine, Burlington, VT
| | - Michael L. Alosco
- Boston University School of Medicine, Boston University Alzheimer’s Disease Research Center and CTE Center, Boston, MA, USA.,Boston University School of Medicine, Department of Neurology, Boston, MA, USA
| | - Jesse Mez
- Boston University School of Medicine, Boston University Alzheimer’s Disease Research Center and CTE Center, Boston, MA, USA.,Boston University School of Medicine, Department of Neurology, Boston, MA, USA.,Framingham Heart Study, National Heart, Lung, and Blood Institute and Boston University School of Medicine, Framingham, MA, USA
| | - Claudia L. Satizabal
- Boston University School of Medicine, Department of Neurology, Boston, MA, USA.,University of Texas Health Science Center at San Antonio, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, USA
| | - Wei Qiao Qiu
- Boston University School of Medicine, Boston University Alzheimer’s Disease Research Center and CTE Center, Boston, MA, USA.,Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA.,Boston University School of Medicine, Department of Pharmacology & Experimental Therapeutics, Boston, MA, USA
| | - Kathryn L. Lunetta
- Boston University School of Public Health, Department of Biostatistics, Boston, MA, USA
| | - Joanne M. Murabito
- Framingham Heart Study, National Heart, Lung, and Blood Institute and Boston University School of Medicine, Framingham, MA, USA.,Boston University School of Medicine, Department of Medicine, Section of General Internal Medicine, Boston, MA, USA
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