1
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Yang Z, Wen J, Erus G, Govindarajan ST, Melhem R, Mamourian E, Cui Y, Srinivasan D, Abdulkadir A, Parmpi P, Wittfeld K, Grabe HJ, Bülow R, Frenzel S, Tosun D, Bilgel M, An Y, Yi D, Marcus DS, LaMontagne P, Benzinger TLS, Heckbert SR, Austin TR, Waldstein SR, Evans MK, Zonderman AB, Launer LJ, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Toga AW, O'Bryant S, Chakravarty MM, Villeneuve S, Johnson SC, Morris JC, Albert MS, Yaffe K, Völzke H, Ferrucci L, Nick Bryan R, Shinohara RT, Fan Y, Habes M, Lalousis PA, Koutsouleris N, Wolk DA, Resnick SM, Shou H, Nasrallah IM, Davatzikos C. Brain aging patterns in a large and diverse cohort of 49,482 individuals. Nat Med 2024:10.1038/s41591-024-03144-x. [PMID: 39147830 DOI: 10.1038/s41591-024-03144-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 06/20/2024] [Indexed: 08/17/2024]
Abstract
Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.
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Affiliation(s)
- Zhijian Yang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Graduate Group in Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, PA, USA
- GE Healthcare, Bellevue, WA, USA
| | - Junhao Wen
- Laboratory of AI and Biomedical Science (LABS), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Guray Erus
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sindhuja T Govindarajan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Randa Melhem
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth Mamourian
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yuhan Cui
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dhivya Srinivasan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ahmed Abdulkadir
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Paraskevi Parmpi
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Site Rostock/Greifswald, German Center for Neurodegenerative Diseases (DZNE), Greifswald, Germany
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center Seoul National University, Seoul, Republic of Korea
| | - Daniel S Marcus
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Pamela LaMontagne
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan R Heckbert
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Thomas R Austin
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Shari R Waldstein
- Department of Psychology, University of Maryland, Baltimore County, Baltimore, MD, USA
| | - Michele K Evans
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD, USA
| | - Alan B Zonderman
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD, USA
| | - Lenore J Launer
- Neuroepidemiology Section, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - Aristeidis Sotiras
- Department of Radiology and Institute for Informatics, Data Science & Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
| | - Mark A Espeland
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Colin L Masters
- Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Paul Maruff
- Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Brisbane, Queensland, Australia
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Sid O'Bryant
- Institute for Translational Research University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Mallar M Chakravarty
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada
| | - Sylvia Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Sterling C Johnson
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - John C Morris
- Knight Alzheimer Disease Research Center, Dept of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kristine Yaffe
- Departments of Neurology, Psychiatry and Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Luigi Ferrucci
- Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, Baltimore, MD, USA
| | - R Nick Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T Shinohara
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Yong Fan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, 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
| | - Paris Alexandros Lalousis
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nikolaos Koutsouleris
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Section for Precision Psychiatry, Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Munich, Germany
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Haochang Shou
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ilya M Nasrallah
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Rueda Beltz C, Muñoz Vargas BA, Davila Neri I, Diaz Quijano DM. Neuroprotective effect of hormone replacement therapy: a review of the literature. Climacteric 2024; 27:351-356. [PMID: 38863238 DOI: 10.1080/13697137.2024.2354759] [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: 11/22/2023] [Revised: 03/31/2024] [Accepted: 04/28/2024] [Indexed: 06/13/2024]
Abstract
OBJECTIVE Menopause is a physiological period characterized by the cessation of ovarian activity. Sequential changes during this transition affect multiple systems, including the brain. Sixty percent of women experience cognitive impairment. The objective of this review is to show the neuroprotective effect of hormone replacement therapy (HRT) through the different scales and whether there is a benefit of this in women. METHOD A search was conducted in six databases. Eligibility criteria included women within 10 years of menopause, receiving HRT controlled with placebo, studies lasting more than 6 months and women without a history of chronic underlying pathology. RESULTS A total of nine randomized controlled trials met the inclusion criteria. Regarding memory, two studies reported better performance of HRT with a significant odds ratio (OR) of 0.67; regarding attention, one study reported potential improvement in women receiving HRT with a significant OR of 0.87; and neuroimaging assessment found an increase in ventricular volume compared to placebo over a 3-year period. CONCLUSIONS The early initiation of menopausal HRT in healthy women appears to yield a positive effect on certain cognitive aspects, such as attention and cortical volume in the central nervous system. These findings should be confirmed through future prospective studies.
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Affiliation(s)
- Camilo Rueda Beltz
- Department of Gynecological Endocrinology, University of La Sabana, Bogotá, Colombia
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Petkus AJ, Wang X, Younan D, Salminen LE, Resnick SM, Rapp SR, Espeland MA, Gatz M, Widaman KF, Casanova R, Chui H, Barnard RT, Gaussoin SA, Goveas JS, Hayden KM, Henderson VW, Sachs BC, Saldana S, Shadyab AH, Shumaker SA, Chen J. 20-year depressive symptoms, dementia, and structural neuropathology in older women. Alzheimers Dement 2024; 20:3472-3484. [PMID: 38591250 PMCID: PMC11095467 DOI: 10.1002/alz.13781] [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: 09/07/2023] [Revised: 01/03/2024] [Accepted: 01/24/2024] [Indexed: 04/10/2024]
Abstract
INTRODUCTION The course of depressive symptoms and dementia risk is unclear, as are potential structural neuropathological common causes. METHODS Utilizing joint latent class mixture models, we identified longitudinal trajectories of annually assessed depressive symptoms and dementia risk over 21 years in 957 older women (baseline age 72.7 years old) from the Women's Health Initiative Memory Study. In a subsample of 569 women who underwent structural magnetic resonance imaging, we examined whether estimates of cerebrovascular disease and Alzheimer's disease (AD)-related neurodegeneration were associated with identified trajectories. RESULTS Five trajectories of depressive symptoms and dementia risk were identified. Compared to women with minimal symptoms, women who reported mild and stable and emerging depressive symptoms were at the highest risk of developing dementia and had more cerebrovascular disease and AD-related neurodegeneration. DISCUSSION There are heterogeneous profiles of depressive symptoms and dementia risk. Common neuropathological factors may contribute to both depression and dementia. Highlights The progression of depressive symptoms and concurrent dementia risk is heterogeneous. Emerging depressive symptoms may be a prodromal symptom of dementia. Cerebrovascular disease and AD are potentially shared neuropathological factors.
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Affiliation(s)
- Andrew J. Petkus
- Department of NeurologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Xinhui Wang
- Department of NeurologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Diana Younan
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Lauren E. Salminen
- Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Susan M. Resnick
- Laboratory of Behavioral NeuroscienceNational Institute on AgingBaltimoreMarylandUSA
| | - Stephen R. Rapp
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
- Department of Social Sciences and Health PolicyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Mark A. Espeland
- Department of Biostatistics and Data SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
- Department of Internal MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Margaret Gatz
- Center for Economic and Social ResearchUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Keith F. Widaman
- Graduate School of EducationUniversity of California, RiversideRiversideCaliforniaUSA
| | - Ramon Casanova
- Department of Biostatistics and Data SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Helena Chui
- Department of NeurologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Ryan T. Barnard
- Department of Biostatistics and Data SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Sarah A. Gaussoin
- Department of Biostatistics and Data SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Joseph S. Goveas
- Department of Psychiatry and Behavioral MedicineMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Kathleen M. Hayden
- Department of Social Sciences and Health PolicyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Victor W. Henderson
- Departments of Epidemiology and Population Health and of Neurology and Neurological SciencesStanford UniversityPalo AltoCaliforniaUSA
| | - Bonnie C. Sachs
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Santiago Saldana
- Department of Biostatistics and Data SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Aladdin H. Shadyab
- Herbert Wertheim School of Public Health and Human Longevity ScienceUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Sally A. Shumaker
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Jiu‐Chiuan Chen
- Department of NeurologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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4
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Yang Z, Wen J, Erus G, Govindarajan ST, Melhem R, Mamourian E, Cui Y, Srinivasan D, Abdulkadir A, Parmpi P, Wittfeld K, Grabe HJ, Bülow R, Frenzel S, Tosun D, Bilgel M, An Y, Yi D, Marcus DS, LaMontagne P, Benzinger TL, Heckbert SR, Austin TR, Waldstein SR, Evans MK, Zonderman AB, Launer LJ, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Toga A, O’Bryant S, Chakravarty MM, Villeneuve S, Johnson SC, Morris JC, Albert MS, Yaffe K, Völzke H, Ferrucci L, Bryan NR, Shinohara RT, Fan Y, Habes M, Lalousis PA, Koutsouleris N, Wolk DA, Resnick SM, Shou H, Nasrallah IM, Davatzikos C. Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.29.23300642. [PMID: 38234857 PMCID: PMC10793523 DOI: 10.1101/2023.12.29.23300642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.
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Affiliation(s)
- Zhijian Yang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Graduate Group in Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Junhao Wen
- Laboratory of AI and Biomedical Science (LABS), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Guray Erus
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sindhuja T. Govindarajan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Randa Melhem
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth Mamourian
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yuhan Cui
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dhivya Srinivasan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ahmed Abdulkadir
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Paraskevi Parmpi
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Germany
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University of Greifswald, Germany
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center Seoul National University, Seoul, Republic of Korea
| | - Daniel S. Marcus
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Pamela LaMontagne
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Thomas R. Austin
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Shari R. Waldstein
- Department of Psychology, University of Maryland, Baltimore County, Catonsville, MD, USA
| | - Michele K. Evans
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD, USA
| | - Alan B. Zonderman
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD, USA
| | - Lenore J. Launer
- Neuroepidemiology Section, Intramural Research Program, National Institute on Aging, Bethesda, Maryland, USA
| | - Aristeidis Sotiras
- Department of Radiology and Institute of Informatics, Washington University in St. Luis, St. Luis, MO63110, USA
| | - Mark A. Espeland
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Colin L. Masters
- Florey Institute, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Paul Maruff
- Florey Institute, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Brisbane, Queensland, Australia
| | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Sid O’Bryant
- Institute for Translational Research University of North Texas Health Science Center Fort Worth Texas USA
| | - Mallar M. Chakravarty
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada
| | - Sylvia Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - John C. Morris
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Marilyn S. Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kristine Yaffe
- Departments of Neurology, Psychiatry and Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Luigi Ferrucci
- Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, 3001 S. Hanover Street, Baltimore, MD, USA
| | - Nick R. Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T. Shinohara
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Yong Fan
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mohamad Habes
- Biggs Alzheimer’s Institute, University of Texas San Antonio Health Science Center, USA
| | - Paris Alexandros Lalousis
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Nikolaos Koutsouleris
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Section for Precision Psychiatry, Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Munich, Germany
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Haochang Shou
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ilya M. Nasrallah
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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5
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Wang X, Salminen LE, Petkus AJ, Driscoll I, Millstein J, Beavers DP, Espeland MA, Erus G, Braskie MN, Thompson PM, Gatz M, Chui HC, Resnick SM, Kaufman JD, Rapp SR, Shumaker S, Brown M, Younan D, Chen JC. Association between late-life air pollution exposure and medial temporal lobe atrophy in older women. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.28.23298708. [PMID: 38077091 PMCID: PMC10705610 DOI: 10.1101/2023.11.28.23298708] [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] [Indexed: 12/21/2023]
Abstract
Background Ambient air pollution exposures increase risk for Alzheimer's disease (AD) and related dementias, possibly due to structural changes in the medial temporal lobe (MTL). However, existing MRI studies examining exposure effects on the MTL were cross-sectional and focused on the hippocampus, yielding mixed results. Method To determine whether air pollution exposures were associated with MTL atrophy over time, we conducted a longitudinal study including 653 cognitively unimpaired community-dwelling older women from the Women's Health Initiative Memory Study with two MRI brain scans (MRI-1: 2005-6; MRI-2: 2009-10; Mage at MRI-1=77.3±3.5years). Using regionalized universal kriging models, exposures at residential locations were estimated as 3-year annual averages of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) prior to MRI-1. Bilateral gray matter volumes of the hippocampus, amygdala, parahippocampal gyrus (PHG), and entorhinal cortex (ERC) were summed to operationalize the MTL. We used linear regressions to estimate exposure effects on 5-year volume changes in the MTL and its subregions, adjusting for intracranial volume, sociodemographic, lifestyle, and clinical characteristics. Results On average, MTL volume decreased by 0.53±1.00cm3 over 5 years. For each interquartile increase of PM2.5 (3.26μg/m3) and NO2 (6.77ppb), adjusted MTL volume had greater shrinkage by 0.32cm3 (95%CI=[-0.43, -0.21]) and 0.12cm3 (95%CI=[-0.22, -0.01]), respectively. The exposure effects did not differ by APOE ε4 genotype, sociodemographic, and cardiovascular risk factors, and remained among women with low-level PM2.5 exposure. Greater PHG atrophy was associated with higher PM2.5 (b=-0.24, 95%CI=[-0.29, -0.19]) and NO2 exposures (b=-0.09, 95%CI=[-0.14, -0.04]). Higher exposure to PM2.5 but not NO2 was also associated with greater ERC atrophy. Exposures were not associated with amygdala or hippocampal atrophy. Conclusion In summary, higher late-life PM2.5 and NO2 exposures were associated with greater MTL atrophy over time in cognitively unimpaired older women. The PHG and ERC - the MTL cortical subregions where AD neuropathologies likely begin, may be preferentially vulnerable to air pollution neurotoxicity.
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Affiliation(s)
- Xinhui Wang
- Department of Neurology, University of Southern California, Los Angeles, California
| | - Lauren E Salminen
- Department of Neurology, University of Southern California, Los Angeles, California
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Andrew J Petkus
- Department of Neurology, University of Southern California, Los Angeles, California
| | - Ira Driscoll
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin
| | - Joshua Millstein
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California
| | - Daniel P Beavers
- Departments of Statistical Sciences, Wake Forest University, Winston-Salem, North Carolina
| | - Mark A Espeland
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Department of Biostatistics and Data Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Guray Erus
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, Pennsylvania
| | - Meredith N Braskie
- Department of Neurology, University of Southern California, Los Angeles, California
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Paul M Thompson
- Department of Neurology, University of Southern California, Los Angeles, California
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, California
| | - Helena C Chui
- Department of Neurology, University of Southern California, Los Angeles, California
| | - Susan M Resnick
- The Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland
| | - Joel D Kaufman
- Departments of Environmental & Occupational Health Sciences, Medicine (General Internal Medicine), and Epidemiology, University of Washington, Seattle, Washington
| | - Stephen R Rapp
- Departments of Psychiatry and Behavioral Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Sally Shumaker
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Mark Brown
- Department of Biostatistics and Data Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Diana Younan
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California
| | - Jiu-Chiuan Chen
- Department of Neurology, University of Southern California, Los Angeles, California
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California
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Petkus AJ, Salminen LE, Wang X, Driscoll I, Millstein J, Beavers DP, Espeland MA, Braskie MN, Thompson PM, Casanova R, Gatz M, Chui HC, Resnick SM, Kaufman JD, Rapp SR, Shumaker S, Younan D, Chen JC. Alzheimer's Related Neurodegeneration Mediates Air Pollution Effects on Medial Temporal Lobe Atrophy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.29.23299144. [PMID: 38076972 PMCID: PMC10705654 DOI: 10.1101/2023.11.29.23299144] [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] [Indexed: 12/21/2023]
Abstract
Exposure to ambient air pollution, especially particulate matter with aerodynamic diameter <2.5 μm (PM2.5) and nitrogen dioxide (NO2), are environmental risk factors for Alzheimer's disease and related dementia. The medial temporal lobe (MTL) is an important brain region subserving episodic memory that atrophies with age, during the Alzheimer's disease continuum, and is vulnerable to the effects of cerebrovascular disease. Despite the importance of air pollution it is unclear whether exposure leads to atrophy of the MTL and by what pathways. Here we conducted a longitudinal study examining associations between ambient air pollution exposure and MTL atrophy and whether putative air pollution exposure effects resembled Alzheimer's disease-related neurodegeneration or cerebrovascular disease-related neurodegeneration. Participants included older women (n = 627; aged 71-87) who underwent two structural brain MRI scans (MRI-1: 2005-6; MRI-2: 2009-10) as part of the Women's Health Initiative Memory Study of Magnetic Resonance Imaging. Regionalized universal kriging was used to estimate annual concentrations of PM2.5 and NO2 at residential locations aggregated to 3-year averages prior to MRI-1. The outcome was 5-year standardized change in MTL volumes. Mediators included voxel-based MRI measures of the spatial pattern of neurodegeneration of Alzheimer's disease (Alzheimer's disease pattern similarity scores [AD-PS]) and whole-brain white matter small-vessel ischemic disease (WM-SVID) volume as a proxy of global cerebrovascular damage. Structural equation models were constructed to examine whether the associations between exposures with MTL atrophy were mediated by the initial level or concurrent change in AD-PS score or WM-SVID while adjusting for sociodemographic, lifestyle, clinical characteristics, and intracranial volume. Living in locations with higher PM2.5 (per interquartile range [IQR]=3.17μg/m3) or NO2 (per IQR=6.63ppb) was associated with greater MTL atrophy (βPM2.5 = -0.29, 95% confidence interval [CI]=[-0.41,-0.18]; βNO2 =-0.12, 95%CI=[-0.23,-0.02]). Greater PM2.5 was associated with larger increases in AD-PS (βPM2.5 = 0.23, 95%CI=[0.12,0.33]) over time, which partially mediated associations with MTL atrophy (indirect effect= -0.10; 95%CI=[-0.15, -0.05]), explaining approximately 32% of the total effect. NO2 was positively associated with AD-PS at MRI-1 (βNO2=0.13, 95%CI=[0.03,0.24]), which partially mediated the association with MTL atrophy (indirect effect= -0.01, 95% CI=[-0.03,-0.001]). Global WM-SVID at MRI-1 or concurrent change were not significant mediators between exposures and MTL atrophy. Findings support the mediating role of Alzheimer's disease-related neurodegeneration contributing to MTL atrophy associated with late-life exposures to air pollutants. Alzheimer's disease-related neurodegeneration only partially explained associations between exposure and MTL atrophy suggesting the role of multiple neuropathological processes underlying air pollution neurotoxicity on brain aging.
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Affiliation(s)
- Andrew J. Petkus
- Department of Neurology, University of Southern California, Los Angeles, California, 90033, United States
| | - Lauren E. Salminen
- Department of Neurology, University of Southern California, Los Angeles, California, 90033, United States
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, 90033, United States
| | - Xinhui Wang
- Department of Neurology, University of Southern California, Los Angeles, California, 90033, United States
| | - Ira Driscoll
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, 53792, United States
| | - Joshua Millstein
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, 90033, United States
| | - Daniel P. Beavers
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, 27101, United States
| | - Mark A. Espeland
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, 27101, United States
| | - Meredith N. Braskie
- Department of Neurology, University of Southern California, Los Angeles, California, 90033, United States
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, 90033, United States
| | - Paul M. Thompson
- Department of Neurology, University of Southern California, Los Angeles, California, 90033, United States
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, 90033, United States
| | - Ramon Casanova
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, 27101, United States
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, California, 90089, United States
| | - Helena C. Chui
- Department of Neurology, University of Southern California, Los Angeles, California, 90033, United States
| | - Susan M Resnick
- The Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland, 20898, United States
| | - Joel D. Kaufman
- Departments of Environmental & Occupational Health Sciences, Medicine (General Internal Medicine), and Epidemiology, University of Washington, Seattle, Washington, 98195, United States
| | - Stephen R. Rapp
- Departments of Psychiatry and Behavioral Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina , 27101, United States
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina, 27101, United States
| | - Sally Shumaker
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina, 27101, United States
| | - Diana Younan
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, 90033, United States
| | - Jiu-Chiuan Chen
- Department of Neurology, University of Southern California, Los Angeles, California, 90033, United States
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, 90033, United States
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Cote S, Perron TL, Baillargeon JP, Bocti C, Lepage JF, Whittingstall K. Association of Cumulative Lifetime Exposure to Female Hormones With Cerebral Small Vessel Disease in Postmenopausal Women in the UK Biobank. Neurology 2023; 101:e1970-e1978. [PMID: 37758482 PMCID: PMC10662980 DOI: 10.1212/wnl.0000000000207845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 08/03/2023] [Indexed: 10/03/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Rates of cerebrovascular disease increase after menopause, which is often attributed to the absence of hormones. It remains unknown whether the cumulative exposure to hormones across a female person's premenopausal life extends the window of cerebrovascular protection to the postmenopausal period. To investigate this, we examined the relationship between lifetime hormone exposure (LHE) and cerebral small vessel disease in more than 9,000 postmenopausal women in the UK-Biobank. METHODS The cohort consisted of women (aged 40-69 years) who attended one of 22 research centers across the United Kingdom between 2006 and 2010. Women were excluded if they were premenopausal when scanned, had missing reproductive history data, self-reported neurologic disorders, brain cancer, cerebral vascular incidents, head or neurologic injury, and nervous system infection. Endogenous LHE (LHEEndo) was estimated by summing the number of years pregnant (LHEParity) with the duration of the reproductive period (LHECycle = age menopause - age menarche). Exogenous LHE (LHEExo) was estimated by summing the number of years on oral contraceptives and hormone replacement therapy. Cerebral small vessel disease was determined by estimating white matter hyperintensity volume (WMHV) from T2-fluid-attenuated inversion recovery brain MRI (acquired between 2014 and 2021), normalized to intracranial volume and log-transformed. Multiple linear regressions were used to assess the relationship between LHEEndo on WMHV adjusted for age, cardiovascular risk factors, sociodemographics, and LHEExo. RESULTS A total of 9,163 postmenopausal women (age 64.21 ± 6.81 years) were retained for analysis. Average LHEEndo was 39.77 ± 3.59 years. Women with higher LHEEndo showed smaller WMHV (adj-R 2 = 0.307, LHEEndo β = -0.007 [-0.012 to -0.002], p < 0.01). LHEParity and LHECycle were independent contributors to WMHV (adj-R 2 = 0.308, p << 0.001; LHEParity β = -0.022 [-0.042 to -0.002], p < 0.05; LHECycle β = -0.006 [-0.011 to -0.001], p < 0.05). LHEExo was not significantly related to WMHV (LHEExo β = 0.001 [-0.001 to 0.002], p > 0.05). DISCUSSION Women with more prolonged exposure to endogenous hormones show relatively smaller burden of cerebral small vessel disease independent of the history of oral contraceptive use or hormone replacement therapy. Our results highlight the critical role endogenous hormones play in female brain health and provide real-world evidence of the protective effects premenopausal endogenous hormone exposure plays on postmenopausal cerebrovascular health.
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Affiliation(s)
- Samantha Cote
- From the Department of Nuclear Medicine and Radiobiology (S.C.), Division of Neurology (T.-L.P., C.B.) and Endocrinology Division (J.-P.B.), Department of Medicine, Department of Pediatrics (J.-F.L.), and Diagnostic Radiology (K.W.), Department of Medicine, Université de Sherbrooke, Quebec, Canada
| | - Thomas-Louis Perron
- From the Department of Nuclear Medicine and Radiobiology (S.C.), Division of Neurology (T.-L.P., C.B.) and Endocrinology Division (J.-P.B.), Department of Medicine, Department of Pediatrics (J.-F.L.), and Diagnostic Radiology (K.W.), Department of Medicine, Université de Sherbrooke, Quebec, Canada
| | - Jean-Patrice Baillargeon
- From the Department of Nuclear Medicine and Radiobiology (S.C.), Division of Neurology (T.-L.P., C.B.) and Endocrinology Division (J.-P.B.), Department of Medicine, Department of Pediatrics (J.-F.L.), and Diagnostic Radiology (K.W.), Department of Medicine, Université de Sherbrooke, Quebec, Canada
| | - Christian Bocti
- From the Department of Nuclear Medicine and Radiobiology (S.C.), Division of Neurology (T.-L.P., C.B.) and Endocrinology Division (J.-P.B.), Department of Medicine, Department of Pediatrics (J.-F.L.), and Diagnostic Radiology (K.W.), Department of Medicine, Université de Sherbrooke, Quebec, Canada
| | - Jean-Francois Lepage
- From the Department of Nuclear Medicine and Radiobiology (S.C.), Division of Neurology (T.-L.P., C.B.) and Endocrinology Division (J.-P.B.), Department of Medicine, Department of Pediatrics (J.-F.L.), and Diagnostic Radiology (K.W.), Department of Medicine, Université de Sherbrooke, Quebec, Canada
| | - Kevin Whittingstall
- From the Department of Nuclear Medicine and Radiobiology (S.C.), Division of Neurology (T.-L.P., C.B.) and Endocrinology Division (J.-P.B.), Department of Medicine, Department of Pediatrics (J.-F.L.), and Diagnostic Radiology (K.W.), Department of Medicine, Université de Sherbrooke, Quebec, Canada.
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Bäckström T, Turkmen S, Das R, Doverskog M, Blackburn TP. The GABA system, a new target for medications against cognitive impairment-Associated with neuroactive steroids. J Intern Med 2023; 294:281-294. [PMID: 37518841 DOI: 10.1111/joim.13705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/01/2023]
Abstract
The prevalence of cognitive dysfunction, dementia, and neurodegenerative disorders such as Alzheimer's disease (AD) is increasing in parallel with an aging population. Distinct types of chronic stress are thought to be instrumental in the development of cognitive impairment in central nervous system (CNS) disorders where cognitive impairment is a major unmet medical need. Increased GABAergic tone is a mediator of stress effects but is also a result of other factors in CNS disorders. Positive GABA-A receptor modulating stress and sex steroids (steroid-PAMs) such as allopregnanolone (ALLO) and medroxyprogesterone acetate can provoke impaired cognition. As such, ALLO impairs memory and learning in both animals and humans. In transgenic AD animal studies, continuous exposure to ALLO at physiological levels impairs cognition and increases degenerative AD pathology, whereas intermittent ALLO injections enhance cognition, indicating pleiotropic functions of ALLO. We have shown that GABA-A receptor modulating steroid antagonists (GAMSAs) can block the acute negative cognitive impairment of ALLO on memory in animal studies and in patients with cognitive impairment due to hepatic encephalopathy. Here we describe disorders affected by steroid-PAMs and opportunities to treat these adverse effects of steroid-PAMs with novel GAMSAs.
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Affiliation(s)
| | - Sahruh Turkmen
- Department of Clinical Sciences, University of Umeå, Umeå, Sweden
| | - Roshni Das
- Department of Clinical Sciences, University of Umeå, Umeå, Sweden
- Umecrine Cognition AB, Solna, Sweden
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Ren XQ, Huang X, Xing SY, Long Y, Yuan DH, Hong H, Tang SS. Neuroprotective effects of novel compound FMDB on cognition, neurogenesis and apoptosis in APP/PS1 transgenic mouse model of Alzheimer's disease. Neurochem Int 2023; 165:105510. [PMID: 36893915 DOI: 10.1016/j.neuint.2023.105510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 02/02/2023] [Accepted: 03/05/2023] [Indexed: 03/09/2023]
Abstract
Clinical and experimental studies have shown that the sharp reduction of estrogen is one of the important reasons for the high incidence of Alzheimer's disease (AD) in elderly women, but there is currently no such drug for treatment of AD. Our group first designed and synthesized a novel compound R-9-(4fluorophenyl)-3-methyl-10,10,-Hydrogen-6-hydrogen-benzopyran named FMDB. In this study, our aim is to investigate the neuroprotective effects and mechanism of FMDB in APP/PS1 transgenic mice. 6 months old APP/PS1 transgenic mice were intragastrical administered with FMDB (1.25, 2.5 and 5 mg/kg) every other day for 8 weeks. LV-ERβ-shRNA was injected bilaterally into the hippocampus of APP/PS1 mice to knockdown estrogen receptor β (ERβ). We found that FMDB ameliorated cognitive impairment in the Morris water maze and novel object recognition tests, increased hippocampal neurogenesis and prevented hippocampal apoptotic responses in APP/PS1 mice. Importantly, FMDB activated nuclear ERβ mediated CBP/p300, CREB and brain-derived neurotrophic factor (BDNF) signaling, and membrane ERβ mediated PI3K/Akt, CREB and BDNF signaling in the hippocampus. Our study demonstrated the contributions and mechanism of FMDB to cognition, neurogenesis and apoptosis in APP/PS1 mice. These lay the experimental foundation for the development of new anti-AD drugs.
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Affiliation(s)
- Xiao-Qian Ren
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Xin Huang
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Shu-Yun Xing
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Yan Long
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Dan-Hua Yuan
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Hao Hong
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Su-Su Tang
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China.
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10
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Gordián-Arroyo A, Reame N, Gutierrez J, Liu J, Ganzhorn S, Igwe KC, Laing K, Schnall R. Do correlates of white matter features differ between older men and women living with human immunodeficiency virus? Menopause 2023; 30:149-155. [PMID: 36696639 PMCID: PMC9886314 DOI: 10.1097/gme.0000000000002102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
OBJECTIVE Given estrogen's role in human immunodeficiency virus (HIV) disease progression and the higher rates of neurocognitive decline in affected women, the purpose of this study was to assess whether the relationship of white matter features and reproductive hormone levels differed between men versus women (sex as a moderator), controlling for selected cardiometabolic risk factors, HIV-related health indicators, and demographics in an aging population of persons living with HIV (PLWH). METHODS Older PLWH (50 y and older; 44 women and 35 men; mean ± SD age, 59.8 ± 0.6 y; 55.7% women; 72.2% non-Hispanic Black) participated in a cross-sectional study involving a fasting blood draw and a demographic survey (visit 1) and a magnetic resonance imaging scan (visit 2) to determine white matter volume and white matter hyperintensity (WMH) volume. Associations between reproductive hormones (follicle-stimulating hormone [FSH], estradiol, testosterone, dehydroepiandrosterone sulfate [DHEA-S]) and white matter features were assessed in linear regression models. Covariates were age, body mass index, hypertension, diabetes, dyslipidemia, current smoking status, CD4 count, and cranial size. RESULTS For white matter volume, a sexually dimorphic interaction was seen for DHEA-S (B = 21.23; P = 0.012) and observed for FSH (B = -22.97, P = 0.08) with a trend for significance after controlling for risk factors. In women, higher white matter volume was associated with higher DHEA-S (B = 13.89, P = 0.017) and lower FSH (B = 23.58, P = 0.01). No hormone associations were shown in men for white matter volume. For WMH volume, no significant interaction effects between sex and reproductive hormones were identified. For WMH, sex did not predict associations with reproductive hormones after controlling for risk factors. CONCLUSIONS Although sexually dimorphic interactions of reproductive hormones and total white matter volume were demonstrated, our study findings do not support a role for sex-based differences in reproductive hormones as predictive correlates of WMH in a small sample of older PLWH.
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Affiliation(s)
| | - Nancy Reame
- Columbia University School of Nursing, New York, NY
| | - Jose Gutierrez
- Columbia University Irving Medical Center, Department of Neurology, New York, NY
| | - Jianfang Liu
- Columbia University School of Nursing, New York, NY
| | | | - Kay Chioma Igwe
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University
| | - Krystal Laing
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University
| | - Rebecca Schnall
- Columbia University School of Nursing, New York, NY
- Columbia University, Mailman School of Public Health, Department of Population and Family Health, New York, NY
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Wang C, Kravets S, Sethi A, Espeland MA, Pasquale LR, Rapp SR, Klein BE, Meuer SM, Haan MN, Maki PM, Hallak JA, Vajaranant TS. An Association Between Large Optic Cupping and Total and Regional Brain Volume: The Women's Health Initiative. Am J Ophthalmol 2023; 249:21-28. [PMID: 36638905 DOI: 10.1016/j.ajo.2022.12.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 12/02/2022] [Accepted: 12/04/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE To investigate the relationships between optic nerve cupping and total and regional brain volumes. DESIGN Secondary analysis of randomized clinical trial data. METHODS Women 65 to 79 years of age without glaucoma with cup-to-disc ratio (CDR) measurements from the Women's Health Initiative (WHI) Sight Examination study and magnetic resonance imaging (MRI)-based total and regional brain volumes from the WHI Memory Study MRI-1 were included. Large CDR was defined as 0.6 or greater in either eye. Generalized estimating equation models were used to account for intra-brain correlations between the right and left sides. The final analysis was adjusted for demographic and clinical characteristics and for total brain volume (for regional analyses). RESULTS Final analyses included 471 women, with the mean age ± SD was 69.2 ± 3.6 years; 92.8% of the subjects were white. Of 471 women, 34 (7.2%) had large CDR. Controlling for total brain volume and for demographic and clinical characteristics, lateral ventricle volume was 3.01 cc larger for subjects with large CDR compared to those without large CDR (95% CI = 0.02 to 5.99; P = .048). Furthermore, frontal lobe volume was 4.78 cc lower for subjects with large CDR compared to those without (95% CI = -8.71, -0.84; P = 0.02), and occipital lobe volume was 1.86 cc lower for those with large CDR compared to those without (95% CI = -3.39, -0.3; P =.02). CONCLUSIONS Our analysis suggests that in women aged 65 years or more, large CDR is associated with lower relative total brain volume and absolute regional volume in the frontal and occipital lobes. Enlarged CDR in individuals without glaucoma may represent a sign of optic nerve and brain aging, although more longitudinal data are needed.
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Affiliation(s)
- Catherine Wang
- From the Illinois Eye and Ear Infirmary (C.W., S.K., A.S., J.A.H., T.S.V.), Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, USA; College of Medicine (C.W., A.S.), University of Illinois at Chicago, Chicago, Ilinois, USA
| | - Sasha Kravets
- From the Illinois Eye and Ear Infirmary (C.W., S.K., A.S., J.A.H., T.S.V.), Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, USA; Division of Epidemiology and Biostatistics (S.K.), School of Public Health, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Abhishek Sethi
- From the Illinois Eye and Ear Infirmary (C.W., S.K., A.S., J.A.H., T.S.V.), Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, USA; College of Medicine (C.W., A.S.), University of Illinois at Chicago, Chicago, Ilinois, USA
| | - Mark A Espeland
- Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University Health Sciences, Winston Salem, North Carolina, USA
| | - Louis R Pasquale
- Department of Ophthalmology (L.R.P.), Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Stephen R Rapp
- Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest University Health Sciences, Winston Salem, North Carolina, USA
| | - Barbara E Klein
- Department of Ophthalmology and Visual Sciences (B.E.K., S.M.M.), University of Wisconsin, Madison, Wisconsin, USA
| | - Stacy M Meuer
- Department of Ophthalmology and Visual Sciences (B.E.K., S.M.M.), University of Wisconsin, Madison, Wisconsin, USA
| | - Mary N Haan
- Department of Epidemiology and Biostatistics (M.N.H.), University of California at San Francisco, San Francisco, California, USA
| | - Pauline M Maki
- Department of Psychiatry (P.M.M.), University of Illinois at Chicago, Chicago, Illinois, USA
| | - Joelle A Hallak
- From the Illinois Eye and Ear Infirmary (C.W., S.K., A.S., J.A.H., T.S.V.), Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Thasarat Sutabutr Vajaranant
- From the Illinois Eye and Ear Infirmary (C.W., S.K., A.S., J.A.H., T.S.V.), Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, USA.
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Jett S, Schelbaum E, Jang G, Boneu Yepez C, Dyke JP, Pahlajani S, Diaz Brinton R, Mosconi L. Ovarian steroid hormones: A long overlooked but critical contributor to brain aging and Alzheimer's disease. Front Aging Neurosci 2022; 14:948219. [PMID: 35928995 PMCID: PMC9344010 DOI: 10.3389/fnagi.2022.948219] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 06/28/2022] [Indexed: 01/19/2023] Open
Abstract
Ovarian hormones, particularly 17β-estradiol, are involved in numerous neurophysiological and neurochemical processes, including those subserving cognitive function. Estradiol plays a key role in the neurobiology of aging, in part due to extensive interconnectivity of the neural and endocrine system. This aspect of aging is fundamental for women's brains as all women experience a drop in circulating estradiol levels in midlife, after menopause. Given the importance of estradiol for brain function, it is not surprising that up to 80% of peri-menopausal and post-menopausal women report neurological symptoms including changes in thermoregulation (vasomotor symptoms), mood, sleep, and cognitive performance. Preclinical evidence for neuroprotective effects of 17β-estradiol also indicate associations between menopause, cognitive aging, and Alzheimer's disease (AD), the most common cause of dementia affecting nearly twice more women than men. Brain imaging studies demonstrated that middle-aged women exhibit increased indicators of AD endophenotype as compared to men of the same age, with onset in perimenopause. Herein, we take a translational approach to illustrate the contribution of ovarian hormones in maintaining cognition in women, with evidence implicating menopause-related declines in 17β-estradiol in cognitive aging and AD risk. We will review research focused on the role of endogenous and exogenous estrogen exposure as a key underlying mechanism to neuropathological aging in women, with a focus on whether brain structure, function and neurochemistry respond to hormone treatment. While still in development, this research area offers a new sex-based perspective on brain aging and risk of AD, while also highlighting an urgent need for better integration between neurology, psychiatry, and women's health practices.
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Affiliation(s)
- Steven Jett
- Department of Neurology, Weill Cornell Medical College, New York, NY, United States
| | - Eva Schelbaum
- Department of Neurology, Weill Cornell Medical College, New York, NY, United States
| | - Grace Jang
- Department of Neurology, Weill Cornell Medical College, New York, NY, United States
| | - Camila Boneu Yepez
- Department of Neurology, Weill Cornell Medical College, New York, NY, United States
| | - Jonathan P. Dyke
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Silky Pahlajani
- Department of Neurology, Weill Cornell Medical College, New York, NY, United States
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Roberta Diaz Brinton
- Department of Pharmacology, University of Arizona, Tucson, AZ, United States
- Department of Neurology, University of Arizona, Tucson, AZ, United States
| | - Lisa Mosconi
- Department of Neurology, Weill Cornell Medical College, New York, NY, United States
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
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Das R, Ragagnin G, Sjöstedt J, Johansson M, Haage D, Druzin M, Johansson S, Bäckström T. Medroxyprogesterone acetate positively modulates specific GABA A-receptor subtypes - affecting memory and cognition. Psychoneuroendocrinology 2022; 141:105754. [PMID: 35395561 DOI: 10.1016/j.psyneuen.2022.105754] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 02/14/2022] [Accepted: 03/28/2022] [Indexed: 11/28/2022]
Abstract
Medroxyprogesterone acetate (MPA) is a progestin widely used in humans as hormone replacement therapy and at other indications. Many progestin metabolites, as the progesterone metabolite allopregnanolone, have GABAA-receptor modulatory effects and are known to affect memory, learning, appetite, and mood. In women, 4 years chronic treatment with MPA doubles the frequency of dementia and in rats, MPA causes cognitive impairment related to the GABAergic system. Activation of the membrane bound GABAA receptor results in a chloride ion flux that can be studied by whole-cell patch-clamp electrophysiological recordings. The purpose of this study was to clarify the modulatory effects of MPA and specific MPA metabolites, with structures like known GABAA-receptor modulators, on different GABAA-receptor subtypes. An additional aim was to verify the results as steroid effects on GABA response in single cells taken from rat hypothalamus. HEK-293 cell-lines permanently expressing the recombinant human GABAA-receptor subtype α1β2γ2L or α5β3γ2L or α2β3γ2S were created. The MPA metabolites 3α5α-MPA,3β5α-MPA and 3β5β-MPA were synthesised and purified for electrophysiological patch-clamp measurements with a Dynaflow system. The effects of MPA and tetrahydrodeoxycorticosterone were also studied. None of the studied MPA metabolites affected the responses mediated by α1β2γ2L or α5β3γ2L GABAA receptors. Contrary, MPA clearly acted both as a positive modulator and as a direct activator of the α5β3γ2L and α2β3γ2S GABAA receptors. However, in concentrations up to 10 μM, MPA was inactive at the α1β2γ2L GABAA receptor. In the patch-clamp recordings from dissociated cells of the preoptic area in rats, MPA increased the amplitude of responses to GABA. In addition, MPA alone without added GABA, evoked a current response. In conclusion, MPA acts as a positive modulator of specific GABAA receptor subtypes expressed in HEK cells and at native GABA receptors in single cells from the hypothalamic preoptic area.
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Affiliation(s)
- Roshni Das
- Department of Integrative medical biology, Umeå University, SE-901 87 Umeå, Sweden; Umecrine AB, Norrlands University Hospital Umeå, Building 6 M 4th floor, Sweden
| | - Gianna Ragagnin
- Umeå Neurosteroid Research Center, Department of Clinical sciences, Umeå University, SE-901 85 Umeå, Sweden
| | - Jessica Sjöstedt
- Umeå Neurosteroid Research Center, Department of Clinical sciences, Umeå University, SE-901 85 Umeå, Sweden
| | - Maja Johansson
- Umeå Neurosteroid Research Center, Department of Clinical sciences, Umeå University, SE-901 85 Umeå, Sweden; Umecrine AB, Norrlands University Hospital Umeå, Building 6 M 4th floor, Sweden
| | - David Haage
- Umeå Neurosteroid Research Center, Department of Clinical sciences, Umeå University, SE-901 85 Umeå, Sweden; Department of Nursing Sciences, Mid Sweden University, Sundsvall, Sweden; Umecrine AB, Norrlands University Hospital Umeå, Building 6 M 4th floor, Sweden
| | - Michael Druzin
- Department of Integrative medical biology, Umeå University, SE-901 87 Umeå, Sweden
| | - Staffan Johansson
- Department of Integrative medical biology, Umeå University, SE-901 87 Umeå, Sweden
| | - Torbjörn Bäckström
- Umeå Neurosteroid Research Center, Department of Clinical sciences, Umeå University, SE-901 85 Umeå, Sweden; Umecrine AB, Norrlands University Hospital Umeå, Building 6 M 4th floor, Sweden.
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14
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Bäckström T, Das R, Bixo M. Positive GABA A receptor modulating steroids and their antagonists: Implications for clinical treatments. J Neuroendocrinol 2022; 34:e13013. [PMID: 34337790 DOI: 10.1111/jne.13013] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 07/09/2021] [Accepted: 07/09/2021] [Indexed: 01/02/2023]
Abstract
GABA is the main inhibitory neurotransmitter in the brain and GABAergic transmission has been shown to be of importance for regulation of mood, memory and food intake. The progesterone metabolite allopregnanolone (Allo) is a positive GABAA receptor modulating steroid with potent effects. In humans, disorders such as premenstrual dysphoric disorder (PMDD), hepatic encephalopathy and polycystic ovarian syndrome are associated with elevated Allo levels and increased negative mood, disturbed memory and increased food intake in some individuals. This is surprising because Allo shares many properties with benzodiazepines and is mainly considered to be anxiolytic and anti-depressant. However, it is well established that, in certain individuals, GABAA receptor activating compounds could have paradoxical effects and thus be anxiogenic in low physiological plasma concentrations but anxiolytic at high levels. We have demonstrated that isoallopregnanolone (Isoallo), the 3β-OH sibling of Allo, functions as a GABAA receptor modulating steroid antagonist (GAMSA) but without any effects of its own on GABAA receptors. The antagonistic effect is noted in most GABAA subtypes investigated in vitro to date. In vivo, Isoallo can inhibit Allo-induced anaesthesia in rats, as well as sedation or saccadic eye velocity in humans. Isoallo treatment has been studied in women with PMDD. In a first phase II study, Isoallo (Sepranolone; Asarina Pharma) injections significantly ameliorated negative mood in women with PMDD compared with placebo. Several GAMSAs for oral administration have also been developed. The GAMSA, UC1011, can inhibit Allo induced memory disturbances in rats and an oral GAMSA, GR3027, has been shown to restore learning and motor coordination in rats with hepatic encephalopathy. In humans, vigilance, cognition and pathological electroencephalogram were improved in patients with hepatic encephalopathy on treatment with GR3027. In conclusion GAMSAs are a new possible treatment for disorders and symptoms caused by hyperactivity in the GABAA system.
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Affiliation(s)
- Torbjörn Bäckström
- Department of Clinical Sciences, Obstetrics and Gynecology, Umeå University, Umea, Sweden
| | - Roshni Das
- Department of Integrative Medical Biology, Umeå University, Umea, Sweden
| | - Marie Bixo
- Department of Clinical Sciences, Obstetrics and Gynecology, Umeå University, Umea, Sweden
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15
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Zhang S, Fan W, Hu H, Wen L, Gong M, Liu B, Hu J, Li G, Zhang D. Subcortical Volume Changes in Early Menopausal Women and Correlation With Neuropsychological Tests. Front Aging Neurosci 2021; 13:738679. [PMID: 34955807 PMCID: PMC8692945 DOI: 10.3389/fnagi.2021.738679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 11/16/2021] [Indexed: 01/04/2023] Open
Abstract
Background: The aging process and declining estradiol levels are two important factors that cause structural brain alterations. Many prior studies have investigated these two elements and revealed controversial results in menopausal women. Here, a cross-sectional study was designed to individually evaluate estradiol-related structural changes in the brain. Methods: A total of 45 early menopausal women and 54 age-matched premenopausal controls were enrolled and subjected to magnetic resonance imaging (MRI) scans, blood biochemistry tests, and neuropsychological tests. MRI structural images were analyzed using FreeSurfer to detect changes in subcortical and cortical volumes as well as cortical thickness. Finally, structural brain data as well as clinical and neuropsychological data were used for Pearson's correlation analyses to individually determine estradiol-related structural and functional changes in the brains of early menopausal women. Results: Compared with the premenopausal controls, the early menopausal women showed significant subcortical volumetric loss in the left amygdala and right amygdala, higher serum follicle-stimulating hormone (FSH) levels, more recognizable climacteric and depressive symptoms, decreased quality of sleep, and decreased working memory and executive functions. Simultaneously, FSH levels were related to lower working memory accuracy and longer working memory reaction time. Decreased subcortical volume in the bilateral amygdala was also related to lower working memory accuracy and longer executive reaction time in early menopausal women. Conclusion: The data suggest that estradiol deficiency in early menopausal women can lead to subcortical volume and functional brain changes, which may contribute to further understanding the neurobiological role of declined estradiol levels in early menopausal women.
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Affiliation(s)
- Si Zhang
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Weijie Fan
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Hao Hu
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Li Wen
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Mingfu Gong
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Bo Liu
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Junhao Hu
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Guanghui Li
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Dong Zhang
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
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16
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Chen C, Hayden KM, Kaufman JD, Espeland MA, Whitsel EA, Serre ML, Vizuete W, Orchard TS, Wang X, Chui HC, D’Alton ME, Chen JC, Kahe K. Adherence to a MIND-Like Dietary Pattern, Long-Term Exposure to Fine Particulate Matter Air Pollution, and MRI-Based Measures of Brain Volume: The Women's Health Initiative Memory Study-MRI. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:127008. [PMID: 34939828 PMCID: PMC8698852 DOI: 10.1289/ehp8036] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 11/03/2021] [Accepted: 12/01/2021] [Indexed: 05/12/2023]
Abstract
BACKGROUND Previous studies suggest that certain dietary patterns and constituents may be beneficial to brain health. Airborne exposures to fine particulate matter [particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 )] are neurotoxic, but the combined effects of dietary patterns and PM 2.5 have not been investigated. OBJECTIVES We examined whether previously reported association between PM 2.5 exposure and lower white matter volume (WMV) differed between women whose usual diet during the last 3 months before baseline was more or less consistent with a Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND)-like diet, a dietary pattern that may slow neurodegenerative changes. METHODS This study included 1,302 U.S. women who were 65-79 y old and free of dementia in the period 1996-1998 (baseline). In the period 2005-2006, structural brain magnetic resonance imaging (MRI) scans were performed to estimate normal-appearing brain volumes (excluding areas with evidence of small vessel ischemic disease). Baseline MIND diet scores were derived from a food frequency questionnaire. Three-year average PM 2.5 exposure prior to MRI was estimated using geocoded participant addresses and a spatiotemporal model. RESULTS Average total and temporal lobe WMVs were 0.74 cm 3 [95% confidence interval (CI): 0.001, 1.48) and 0.19 cm 3 (95% CI: 0.002, 0.37) higher, respectively, with each 0.5-point increase in the MIND score and were 4.16 cm 3 (95% CI: - 6.99 , - 1.33 ) and 1.46 cm 3 (95% CI: - 2.16 , - 0.76 ) lower, respectively, with each interquartile range (IQR) (IQR = 3.22 μ g / m 3 ) increase in PM 2.5 . The inverse association between PM 2.5 per IQR and WMV was stronger (p -interaction < 0.001 ) among women with MIND scores below the median (for total WMV, - 12.47 cm 3 ; 95% CI: - 17.17 , - 7.78 ), but absent in women with scores above the median (0.16 cm 3 ; 95% CI: - 3.41 , 3.72), with similar patterns for WMV in the frontal, parietal, and temporal lobes. For total cerebral and hippocampus brain volumes or WMV in the corpus callosum, the associations with PM 2.5 were not significantly different for women with high MIND scores and women with low MIND scores. DISCUSSION In this cohort of U.S. women, PM 2.5 exposure was associated with lower MRI-based WMV, an indication of brain aging, only among women whose usual diet was less consistent with the MIND-like dietary pattern at baseline. https://doi.org/10.1289/EHP8036.
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Affiliation(s)
- Cheng Chen
- Department of Obstetrics and Gynecology, Vagelos College of Physician and Surgeons, Columbia University, New York, New York, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Kathleen M. Hayden
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Joel D. Kaufman
- Department of Environmental and Occupational Health Sciences; Department of Medicine; Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Mark A. Espeland
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, Department of Medicine, School of Medicine, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, USA
| | - Marc L. Serre
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - William Vizuete
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Tonya S. Orchard
- Department of Human Sciences, Human Nutrition Program, Ohio State University, Columbus, Ohio, USA
| | - Xinhui Wang
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Helena C. Chui
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Mary E. D’Alton
- Department of Obstetrics and Gynecology, Vagelos College of Physician and Surgeons, Columbia University, New York, New York, USA
| | - Jiu-Chiuan Chen
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Ka Kahe
- Department of Obstetrics and Gynecology, Vagelos College of Physician and Surgeons, Columbia University, New York, New York, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
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17
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Moreno GL, Ammann E, Kaseda ET, Espeland MA, Wallace R, Robinson J, Denburg NL. The influence of social support on cognitive health in older women: a Women's Health Initiative study. J Women Aging 2021; 34:394-410. [PMID: 34252006 PMCID: PMC8743299 DOI: 10.1080/08952841.2021.1945368] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Social support is associated prospectively with cognitive decline and dementia among the elderly; however, little is known about the impact of social support on healthy neurological aging. The current study investigates whether perceived social support has an influence on neurological health among a large sample of healthy postmenopausal women. Social support and neuropsychological outcomes were measured annually for six years through the Women's Health Initiative Study of Cognitive Aging. In postmenopausal women, higher perceived social support was associated with significantly better overall neuropsychological functioning at baseline, especially in the domains of short-delay figural memory, short-delay verbal memory, and semantic fluency. No significant associations were found between social support and longitudinal changes in neuropsychological function over a median follow-up period of six years. Additionally, there was no significant relationship between social support and regional brain volumes. These findings suggest that social support is related to performance in a subset of neuropsychological domains and contributes to the existing literature that points to the importance of social support as a modifiable lifestyle factor that has the potential to help protect against the decline of cognitive aging, specifically among older adult women.
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Affiliation(s)
- Georgina L Moreno
- Department of Psychology, University of Houston-Clear Lake, Houston, Texas, USA
| | - Eric Ammann
- Janssen Scientific Affairs, Johnson & Johnson, Titusville, New Jersey, USA
| | - Erin T Kaseda
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, Illinois, USA
| | - Mark A Espeland
- Department of Biostatistics and Data Science, Wake Forest University Health Sciences, Winston-Salem, North Carolina, USA
| | - Robert Wallace
- Department of Epidemiology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Jennifer Robinson
- Department of Epidemiology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Natalie L Denburg
- Department of Neurology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
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18
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Younan D, Wang X, Casanova R, Barnard R, Gaussoin SA, Saldana S, Petkus AJ, Beavers DP, Resnick SM, Manson JE, Serre ML, Vizuete W, Henderson VW, Sachs BC, Salinas J, Gatz M, Espeland MA, Chui HC, Shumaker SA, Rapp SR, Chen JC. PM 2.5 Associated With Gray Matter Atrophy Reflecting Increased Alzheimer Risk in Older Women. Neurology 2021; 96:e1190-e1201. [PMID: 33208540 PMCID: PMC8055348 DOI: 10.1212/wnl.0000000000011149] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 10/20/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To examine whether late-life exposure to PM2.5 (particulate matter with aerodynamic diameters <2.5 µm) contributes to progressive brain atrophy predictive of Alzheimer disease (AD) using a community-dwelling cohort of women (age 70-89 years) with up to 2 brain MRI scans (MRI-1, 2005-2006; MRI-2, 2010-2011). METHODS AD pattern similarity (AD-PS) scores, developed by supervised machine learning and validated with MRI data from the Alzheimer's Disease Neuroimaging Initiative, were used to capture high-dimensional gray matter atrophy in brain areas vulnerable to AD (e.g., amygdala, hippocampus, parahippocampal gyrus, thalamus, inferior temporal lobe areas, and midbrain). Using participants' addresses and air monitoring data, we implemented a spatiotemporal model to estimate 3-year average exposure to PM2.5 preceding MRI-1. General linear models were used to examine the association between PM2.5 and AD-PS scores (baseline and 5-year standardized change), accounting for potential confounders and white matter lesion volumes. RESULTS For 1,365 women 77.9 ± 3.7 years of age in 2005 to 2006, there was no association between PM2.5 and baseline AD-PS score in cross-sectional analyses (β = -0.004; 95% confidence interval [CI] -0.019 to 0.011). Longitudinally, each interquartile range increase of PM2.5 (2.82 µg/m3) was associated with increased AD-PS scores during the follow-up, equivalent to a 24% (hazard ratio 1.24, 95% CI 1.14-1.34) increase in AD risk over 5 years (n = 712, age 77.4 ± 3.5 years). This association remained after adjustment for sociodemographics, intracranial volume, lifestyle, clinical characteristics, and white matter lesions and was present with levels below US regulatory standards (<12 µg/m3). CONCLUSIONS Late-life exposure to PM2.5 is associated with increased neuroanatomic risk of AD, which may not be explained by available indicators of cerebrovascular damage.
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Affiliation(s)
- Diana Younan
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York.
| | - Xinhui Wang
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Ramon Casanova
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Ryan Barnard
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Sarah A Gaussoin
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Santiago Saldana
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Andrew J Petkus
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Daniel P Beavers
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Susan M Resnick
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - JoAnn E Manson
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Marc L Serre
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - William Vizuete
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Victor W Henderson
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Bonnie C Sachs
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Joel Salinas
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Margaret Gatz
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Mark A Espeland
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Helena C Chui
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Sally A Shumaker
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Stephen R Rapp
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
| | - Jiu-Chiuan Chen
- From the Departments of Preventive Medicine (D.Y., J.C.C) and Neurology (X.W., A.J.P., H.C.C., J.-C.C.) and the Center for Economic and Social Research (M.G.), University of Southern California, Los Angeles; Departments of Biostatistics and Data Science (R.C., R.B., S.A.G., S.S., D.P.B., M.A.E.), Psychiatry and Behavioral Medicine (S.R.R.), Social Sciences & Health Policy (S.A.S., S.R.R.), and Neurology (B.C.S.), Wake Forest School of Medicine, Winston-Salem, NC; Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD; Department of Environmental Sciences and Engineering (M.L.S., W.V.), University of North Carolina, Chapel Hill; Departments of Health Research and Policy (Epidemiology) and Neurology and Neurological Sciences (V.W.H.), Stanford University, CA; Department of Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Center for Cognitive Neurology, Department of Neurology (J.S.), New York University Grossman School of Medicine, New York
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Chen C, Xun P, Kaufman JD, Hayden KM, Espeland MA, Whitsel EA, Serre ML, Vizuete W, Orchard T, Harris WS, Wang X, Chui HC, Chen JC, He K. Erythrocyte omega-3 index, ambient fine particle exposure, and brain aging. Neurology 2020; 95:e995-e1007. [PMID: 32669395 PMCID: PMC7668549 DOI: 10.1212/wnl.0000000000010074] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 02/20/2020] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVE To examine whether long-chain omega-3 polyunsaturated fatty acid (LCn3PUFA) levels modify the potential neurotoxic effects of particle matter with diameters <2.5 µm (PM2.5) exposure on normal-appearing brain volumes among dementia-free elderly women. METHODS A total of 1,315 women (age 65-80 years) free of dementia were enrolled in an observational study between 1996 and 1999 and underwent structural brain MRI in 2005 to 2006. According to prospectively collected and geocoded participant addresses, we used a spatiotemporal model to estimate the 3-year average PM2.5 exposure before the MRI. We examined the joint associations of baseline LCn3PUFAs in red blood cells (RBCs) and PM2.5 exposure with brain volumes in generalized linear models. RESULTS After adjustment for potential confounders, participants with higher levels of RBC LCn3PUFA had significantly greater volumes of white matter and hippocampus. For each interquartile increment (2.02%) in omega-3 index, the average volume was 5.03 cm3 (p < 0.01) greater in the white matter and 0.08 cm3 (p = 0.03) greater in the hippocampus. The associations with RBC docosahexaenoic acid and eicosapentaenoic acid levels were similar. Higher LCn3PUFA attenuated the inverse associations between PM2.5 exposure and white matter volumes in the total brain and multimodal association areas (frontal, parietal, and temporal; all p for interaction <0.05), while the associations with other brain regions were not modified. Consistent results were found for dietary intakes of LCn3PUFAs and nonfried fish. CONCLUSIONS Findings from this prospective cohort study among elderly women suggest that the benefits of LCn3PUFAs on brain aging may include the protection against potential adverse effects of air pollution on white matter volumes.
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Affiliation(s)
- Cheng Chen
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles.
| | - Pengcheng Xun
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Joel D Kaufman
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Kathleen M Hayden
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Mark A Espeland
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Eric A Whitsel
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Marc L Serre
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - William Vizuete
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Tonya Orchard
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - William S Harris
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Xinhui Wang
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Helena C Chui
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles
| | - Jiu-Chiuan Chen
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles.
| | - Ka He
- From the Department of Obstetrics and Gynecology and Department of Epidemiology (C.C., K.H.), Columbia University Irving Medical Center, New York, NY; Department of Epidemiology and Biostatistics (P.X.), School of Public Health-Bloomington, Indiana University; Department of Environmental and Occupational Health Sciences (J.D.K.), Department of Medicine, and Department of Epidemiology (J.D.K.), School of Public Health, University of Washington, Seattle; Department of Social Sciences and Health Policy (K.M.H.) and Department of Biostatistics and Data Science (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.) and Department of Environmental Sciences and Engineering (M.L.S., W.V.), Gillings School of Global Public Health, and Department of Medicine (E.A.W.), School of Medicine, University of North Carolina Chapel Hill; Department of Human Sciences (T.O.), Human Nutrition Program, The Ohio State University, Columbus; Department of Internal Medicine (W.S.H.), Sanford School of Medicine, University of South Dakota; OmegaQuant Analytics LLC (W.S.H.), Sioux Falls, SD; and Department of Neurology (X.W., H.C.C., J.-C.C.) and Department of Preventive Medicine (J.-C.C.), Keck School of Medicine, University of Southern California, Los Angeles.
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GABA-A receptor modulating steroids in acute and chronic stress; relevance for cognition and dementia? Neurobiol Stress 2019; 12:100206. [PMID: 31921942 PMCID: PMC6948369 DOI: 10.1016/j.ynstr.2019.100206] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 11/13/2019] [Accepted: 12/18/2019] [Indexed: 01/10/2023] Open
Abstract
Cognitive dysfunction, dementia and Alzheimer's disease (AD) are increasing as the population worldwide ages. Therapeutics for these conditions is an unmet need. This review focuses on the role of the positive GABA-A receptor modulating steroid allopregnanolone (APα), it's role in underlying mechanisms for impaired cognition and of AD, and to determine options for therapy of AD. On one hand, APα given intermittently promotes neurogenesis, decreases AD-related pathology and improves cognition. On the other, continuous exposure of APα impairs cognition and deteriorates AD pathology. The disparity between these two outcomes led our groups to analyze the mechanisms underlying the difference. We conclude that the effects of APα depend on administration pattern and that chronic slightly increased APα exposure is harmful to cognitive function and worsens AD pathology whereas single administrations with longer intervals improve cognition and decrease AD pathology. These collaborative assessments provide insights for the therapeutic development of APα and APα antagonists for AD and provide a model for cross laboratory collaborations aimed at generating translatable data for human clinical trials.
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Abstract
OBJECTIVE Statins are a class of drugs that competitively bind to the active site of HMG-CoA reductase enzyme, thereby inhibiting the initial steps in cholesterol synthesis. Originally approved for use in lowering serum cholesterol, a risk factor for developing atherosclerosis and coronary heart disease, statins have subsequently been noted to have myriad extrahepatic effects, including potential effects on cognition, diabetes, breast cancer, bone, and muscle. This narrative review assesses the current state of the science regarding the risks and benefits of statin therapy in women to identify areas where additional research is needed. METHODS Basic and clinical studies were identified by searching PubMed with particular attention to inclusion of female animals, women, randomized controlled trials, and sex-specific analyses. RESULTS Statin therapy is generally recommended to reduce the risk of cardiovascular disease. None of the current clinical guidelines, however, offer sex-specific recommendations for women due to lack of understanding of sex differences and underlying mechanisms of disease processes. In addition, conclusions regarding efficacy of treatments do not consider lipid solubility for the drug, dosing, duration of treatment, interactions with estrogen, or comorbidities. Pleiotropic effects of statins are often derived from secondary analysis of studies with cardiovascular events as primary outcomes. CONCLUSIONS Many of the trials that have established the efficacy and safety of statins were conducted predominantly or entirely in men, with results extrapolated to women. Additional research is needed to guide clinical recommendations specific to women. : Video Summary:http://links.lww.com/MENO/A462.
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Affiliation(s)
- Stephanie S. Faubion
- Center for Women’s Health, Mayo Clinic, Rochester, MN
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN
| | - Ekta Kapoor
- Center for Women’s Health, Mayo Clinic, Rochester, MN
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN
| | - Ann M. Moyer
- Department of Pathology and Laboratory Medicine, Mayo Clinic, Rochester, MN
| | - Howard N. Hodis
- Atherosclerosis Research Unit, Departments of Medicine and Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Virginia M. Miller
- Departments of Surgery and Physiology & Biomedical Engineering, Women’s Health Research Center, Mayo Clinic, Rochester, MN
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Petkus AJ, Resnick SM, Rapp SR, Espeland MA, Gatz M, Widaman KF, Wang X, Younan D, Casanova R, Chui H, Barnard RT, Gaussoin S, Goveas JS, Hayden KM, Henderson VW, Sachs BC, Saldana S, Shadyab AH, Shumaker SA, Chen JC. General and domain-specific cognitive reserve, mild cognitive impairment, and dementia risk in older women. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2019; 5:118-128. [PMID: 31011622 PMCID: PMC6461572 DOI: 10.1016/j.trci.2019.02.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
INTRODUCTION In a geographically diverse sample of women, we asked whether cognitive reserve (CR) is best viewed as a general or cognitive domain-specific construct and whether some cognitive reserve domains but not others exert protective effects on risk of developing mild cognitive impairment (MCI) or dementia. METHODS Estimates of general and domain-specific CR were derived via variance decomposition in 972 cognitively intact women from the Women's Health Initiative Study of Cognitive Aging and Women's Health Memory Study Magnetic Resonance Imaging. Women were then followed up for 13 years. RESULTS General CR was the strongest predictor of reduced risk for both MCI and dementia, compared to domain-specific CR measures. Verbal memory, figural memory, and spatial CR were independently protective of MCI, but only verbal memory was independently associated with reduced risk for dementia. DISCUSSION Cognitive reserve is a heterogenous construct with valid quantitative measures identifiable across different neuropsychological processes associated with MCI and dementia.
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Affiliation(s)
- Andrew J. Petkus
- Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Susan M. Resnick
- National Institute on Aging, Laboratory of Behavioral Neuroscience, Baltimore, MD, USA
| | - Stephen R. Rapp
- Department of Psychiatry and Behavioral Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Mark A. Espeland
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Keith F. Widaman
- Graduate School of Education, University of California, Riverside, CA, USA
| | - Xinhui Wang
- Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Diana Younan
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ramon Casanova
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Helena Chui
- Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Ryan T. Barnard
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Sarah Gaussoin
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Joseph S. Goveas
- Department of Psychiatry, Medical College of Wisconsin, Tosa Health Center, Milwaukee, WI, USA
| | - Kathleen M. Hayden
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Victor W. Henderson
- Department of Health Research & Policy (Epidemiology), Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University, 259 Campus Drive, Stanford, CA, USA
| | - Bonnie C. Sachs
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
- Department of Neurology, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Santiago Saldana
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Aladdin H. Shadyab
- Department of Family Medicine and Public Health, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Sally A. Shumaker
- Department of Neurology, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, USA
| | - Jiu-Chiuan Chen
- Department of Neurology, University of Southern California, Los Angeles, CA, USA
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
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Haring B, Liu J, Salmoirago-Blotcher E, Hayden KM, Sarto G, Roussouw J, Kuller LH, Rapp SR, Wassertheil-Smoller S. Blood pressure variability and brain morphology in elderly women without cardiovascular disease. Neurology 2019; 92:e1284-e1297. [PMID: 30814325 DOI: 10.1212/wnl.0000000000007135] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 11/08/2018] [Indexed: 01/12/2023] Open
Abstract
OBJECTIVE To examine the relationship between blood pressure (BP) variability (BPV), brain volumes, and cognitive functioning in postmenopausal women with few modifiable cardiovascular risk factors. METHODS Study participants consisted of postmenopausal women enrolled in the Women's Health Initiative Memory MRI study (WHIMS-MRI) without cardiovascular disease, diabetes mellitus, hypertension, or current smoking at baseline (1996-1999). BP readings were taken at baseline and each annual follow-up visit. BPV was defined as the SD associated with a participant's mean BP across visits and the SD associated with the participant's regression line with BP regressed across visits. Brain MRI scans were performed between 2004 and 2006. Cognitive functioning was assessed at baseline and annually thereafter with the Modified Mini-Mental State Examination (3MSE) scoring until 2008. The final sample consisted of 558 women (mean age 69 years, median follow-up time [interquartile range] 8 [0.8] years). RESULTS In adjusted models including mean systolic BP, women in the highest tertile of systolic BPV had lower hippocampal volumes and higher lesion volumes compared to women in the lowest tertile. No relationship between BPV and 3MSE scoring was detected. CONCLUSIONS In postmenopausal women with few modifiable cardiovascular risk factors, greater visit-to-visit systolic BPV was associated with reductions in hippocampal volume and increases in lesion volumes at later life. These data add evidence to the emerging importance of BPV as a prognostic indicator even in the absence of documented cardiovascular risk factors.
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Affiliation(s)
- Bernhard Haring
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY.
| | - Jingmin Liu
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY
| | - Elena Salmoirago-Blotcher
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY
| | - Kathleen M Hayden
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY
| | - Gloria Sarto
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY
| | - Jacques Roussouw
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY
| | - Lew H Kuller
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY
| | - Steve R Rapp
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY
| | - Sylvia Wassertheil-Smoller
- From the Department of Internal Medicine I (B.H.), University of Würzburg, Germany; Women's Health Initiative Coordinating Center (J.L.), Seattle, WA; Departments of Medicine and Epidemiology (E.S.-B.), Brown University, Providence, RI; Department of Social Sciences and Health Policy (K.M.H.) and Department of Psychiatry and Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Obstetrics and Gynecology (G.S.), School of Medicine and Public Health, University of Wisconsin, Madison; Women's Health Initiative (J.R.), National Heart, Lung, and Blood Institute, Washington, DC; Department of Epidemiology (L.H.K.), University of Pittsburgh, PA; and Department of Epidemiology & Population Health (S.W.-S.), Albert Einstein College of Medicine, Bronx, NY
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Abstract
This article reviews the role of endogenous estrogen in neural and cognitive processing, followed by an examination of longitudinal cognitive data captured in various stages of the menopausal transition. The remaining text reviews the contradictory results from major hormone therapy trials to date, evidence for the "timing hypothesis," and closes with recommendations for future research and for practicing clinicians.
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Using high-dimensional machine learning methods to estimate an anatomical risk factor for Alzheimer's disease across imaging databases. Neuroimage 2018; 183:401-411. [PMID: 30130645 DOI: 10.1016/j.neuroimage.2018.08.040] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 08/12/2018] [Accepted: 08/16/2018] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION The main goal of this work is to investigate the feasibility of estimating an anatomical index that can be used as an Alzheimer's disease (AD) risk factor in the Women's Health Initiative Magnetic Resonance Imaging Study (WHIMS-MRI) using MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a well-characterized imaging database of AD patients and cognitively normal subjects. We called this index AD Pattern Similarity (AD-PS) scores. To demonstrate the construct validity of the scores, we investigated their associations with several AD risk factors. The ADNI and WHIMS imaging databases were collected with different goals, populations and data acquisition protocols: it is important to demonstrate that the approach to estimating AD-PS scores can bridge these differences. METHODS MRI data from both studies were processed using high-dimensional warping methods. High-dimensional classifiers were then estimated using the ADNI MRI data. Next, the classifiers were applied to baseline and follow-up WHIMS-MRI GM data to generate the GM AD-PS scores. To study the validity of the scores we investigated associations between GM AD-PS scores at baseline (Scan 1) and their longitudinal changes (Scan 2 -Scan 1) with: 1) age, cognitive scores, white matter small vessel ischemic disease (WM SVID) volume at baseline and 2) age, cognitive scores, WM SVID volume longitudinal changes respectively. In addition, we investigated their associations with time until classification of independently adjudicated status in WHIMS-MRI. RESULTS Higher GM AD-PS scores from WHIMS-MRI baseline data were associated with older age, lower cognitive scores, and higher WM SVID volume. Longitudinal changes in GM AD-PS scores (Scan 2 - Scan 1) were also associated with age and changes in WM SVID volumes and cognitive test scores. Increases in the GM AD-PS scores predicted decreases in cognitive scores and increases in WM SVID volume. GM AD-PS scores and their longitudinal changes also were associated with time until classification of cognitive impairment. Finally, receiver operating characteristic curves showed that baseline GM AD-PS scores of cognitively normal participants carried information about future cognitive status determined during follow-up. DISCUSSION We applied a high-dimensional machine learning approach to estimate a novel AD risk factor for WHIMS-MRI study participants using ADNI data. The GM AD-PS scores showed strong associations with incident cognitive impairment and cross-sectional and longitudinal associations with age, cognitive function, cognitive status and WM SVID volume lending support to the ongoing validation of the GM AD-PS score.
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Xiao Q, Luo Y, Lv F, He Q, Wu H, Chao F, Qiu X, Zhang L, Gao Y, Huang C, Wang S, Zhou C, Zhang Y, Jiang L, Tang Y. Protective Effects of 17β-Estradiol on Hippocampal Myelinated Fibers in Ovariectomized Middle-aged Rats. Neuroscience 2018; 385:143-153. [PMID: 29908214 DOI: 10.1016/j.neuroscience.2018.06.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 06/01/2018] [Accepted: 06/04/2018] [Indexed: 12/14/2022]
Abstract
Estrogen replacement therapy (ERT) improves hippocampus-dependent cognition. This study investigated the impact of estrogen on hippocampal volume, CA1 subfield volume and myelinated fibers in the CA1 subfield of middle-aged ovariectomized rats. Ten-month-old bilaterally ovariectomized (OVX) female rats were randomly divided into OVX + E2 and OVX + Veh groups. After four weeks of subcutaneous injection with 17β-estradiol or a placebo, the OVX + E2 rats exhibited significantly short mean escape latency in a spatial learning task than that in the OVX + Veh rats. Using stereological methods, we did not observe significant differences in the volumes of the hippocampus and CA1 subfields between the two groups. However, using stereological methods and electron microscopy techniques, the total length of myelinated fibers and the total volumes of myelinated fibers, myelin sheaths and myelinated axons in the CA1 subfields of OVX + E2 rats were significantly 38.1%, 34.2%, 36.1% and 32.5%, respectively, higher than those in the OVX + Veh rats. After the parameters were calculated according to different diameter ranges, the estrogen replacement-induced remodeling of myelinated fibers in CA1 was mainly manifested in the myelinated fibers with a diameter of <1.0 μm. Therefore, four weeks of continuous E2 replacement improved the spatial learning capabilities of middle-aged ovariectomized rats. The E2 replacement-induced protection of spatial learning abilities might be associated with the beneficial effects of estrogen on myelinated fibers, particularly those with the diameters less than 1.0 μm, in the hippocampal CA1 region of middle-aged ovariectomized rats.
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Affiliation(s)
- Qian Xiao
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Department of Laboratory Medicine, Key Laboratory of Diagnostic Medicine (Ministry of Education), Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Yanmin Luo
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Department of Laboratory Medicine, Key Laboratory of Diagnostic Medicine (Ministry of Education), Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Fulin Lv
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Qi He
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Hong Wu
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Fenglei Chao
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Xuan Qiu
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Lei Zhang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Yuan Gao
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Department of Geriatrics, First Affiliated Hospital, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Chunxia Huang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Department of Physiology, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Sanrong Wang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Chunni Zhou
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Department of Laboratory Medicine, Key Laboratory of Diagnostic Medicine (Ministry of Education), Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Yi Zhang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Department of Laboratory Medicine, Key Laboratory of Diagnostic Medicine (Ministry of Education), Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Lin Jiang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Department of Laboratory Medicine, Key Laboratory of Diagnostic Medicine (Ministry of Education), Chongqing Medical University, Chongqing 400016, People's Republic of China
| | - Yong Tang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China; Laboratory of Stem Cells and Tissue Engineering, Department of Histology and Embryology, Chongqing Medical University, Chongqing 400016, People's Republic of China.
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Leng X, Espeland MA, Manson JE, Stefanick ML, Gower EW, Hayden KM, Limacher MC, Vaughan L, Robinson J, Wallace R, Wassertheil-Smoller S, Yaffe K, Shumaker SA. Cognitive Function and Changes in Cognitive Function as Predictors of Incident Cardiovascular Disease: The Women's Health Initiative Memory Study. J Gerontol A Biol Sci Med Sci 2018; 73:779-785. [PMID: 28977360 PMCID: PMC5946937 DOI: 10.1093/gerona/glx138] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Indexed: 01/08/2023] Open
Abstract
Background Cognitive impairment and decline may signal the increased risk of incident cardiovascular disease (CVD). We examined associations of global cognitive function, as measured by the Modified Mini-Mental State Examination (3MS) and changes in 3MS over time, with incident CVD, individual CVD outcomes, CVD death, and all-cause mortality. Methods A total of 5,596 women (≥ 60) from the Women's Health Initiative Memory Study free of CVD at baseline were followed for an average of 7.1 years. The 3MS was measured at baseline and annually thereafter. Cox proportional hazards regressions were used to model associations between baseline 3MS and changes in 3MS and time to events. Results In the fully-adjusted models for every 5-point lower baseline 3MS score, the risk was 12% greater for incident CVD, 37% for HF, 35% for CVD death, and 24% for all-cause mortality. No significant relationships were found for coronary heart disease (CHD), angina, stroke/transient ischemic attack (TIA), or coronary revascularization. When change in 3MS was added as a time-varying covariate in the fully-adjusted models, for every 1-point/year greater decline in 3MS, the risk was 4% greater for incident CVD, 10% for CHD, 9% for Stroke/TIA, 17% for CVD death, and 13% for all-cause mortality. Conclusions In older women free of prevalent CVD at baseline, lower baseline global cognitive function or decline in global cognitive function over time, increased risk of incident CVD, CVD death, and all-cause mortality.
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Affiliation(s)
- Xiaoyan Leng
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Mark A Espeland
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - JoAnn E Manson
- Division of Preventive Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Marcia L Stefanick
- Center for Disease Prevention Research, Stanford University, Palo Alto, California
| | - Emily W Gower
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill
| | - Kathleen M Hayden
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Marian C Limacher
- Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville
| | - Leslie Vaughan
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Jennifer Robinson
- Department of Epidemiology, University of Iowa College of Medicine
- Department of Internal Medicine, University of Iowa College of Medicine
| | - Robert Wallace
- Department of Epidemiology, University of Iowa College of Medicine
- Department of Internal Medicine, University of Iowa College of Medicine
| | | | - Kristine Yaffe
- Departments of Epidemiology and Biostatistics and Psychiatry and Neurology, University of California, San Francisco
| | - Sally A Shumaker
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
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Kantarci K, Lowe VJ, Lesnick TG, Tosakulwong N, Bailey KR, Fields JA, Shuster LT, Zuk SM, Senjem ML, Mielke MM, Gleason C, Jack CR, Rocca WA, Miller VM. Early Postmenopausal Transdermal 17β-Estradiol Therapy and Amyloid-β Deposition. J Alzheimers Dis 2018; 53:547-56. [PMID: 27163830 PMCID: PMC4955514 DOI: 10.3233/jad-160258] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Background: It remains controversial whether hormone therapy in recently postmenopausal women modifies the risk of Alzheimer’s disease (AD). Objective: To investigate the effects of hormone therapy on amyloid-β deposition in recently postmenopausal women. Methods: Participants within 5–36 months past menopause in the Kronos Early Estrogen Prevention Study, a randomized, double blinded placebo-controlled clinical trial, were randomized to: 1) 0.45 mg/day oral conjugated equine estrogens (CEE); 2) 50μg/day transdermal 17β-estradiol; or 3) placebo pills and patch for four years. Oral progesterone (200 mg/day) was given to active treatment groups for 12 days each month. 11C Pittsburgh compound B (PiB) PET imaging was performed in 68 of the 118 participants at Mayo Clinic approximately seven years post randomization and three years after stopping randomized treatment. PiB Standard unit value ratio (SUVR) was calculated. Results: Women (age = 52–65) randomized to transdermal 17β-estradiol (n = 21) had lower PiB SUVR compared to placebo (n = 30) after adjusting for age [odds ratio (95% CI) = 0.31(0.11–0.83)]. In the APOEɛ4 carriers, transdermal 17β-estradiol treated women (n = 10) had lower PiB SUVR compared to either placebo (n = 5) [odds ratio (95% CI) = 0.04(0.004–0.44)], or the oral CEE treated group (n = 3) [odds ratio (95% CI) = 0.01(0.0006–0.23)] after adjusting for age. Hormone therapy was not associated with PiB SUVR in the APOEɛ4 non-carriers. Conclusion: In this pilot study, transdermal 17β-estradiol therapy in recently postmenopausal women was associated with a reduced amyloid-β deposition, particularly in APOEɛ4 carriers. This finding may have important implications for the prevention of AD in postmenopausal women, and needs to be confirmed in a larger sample.
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Affiliation(s)
- Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Timothy G Lesnick
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Kent R Bailey
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Lynne T Shuster
- Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Samantha M Zuk
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Michelle M Mielke
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.,Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Carey Gleason
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin and Geriatric Research, Education and Clinical Center (GRECC) William S. Middleton Memorial, Veterans' Hospital, Madison, WI, USA
| | | | - Walter A Rocca
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.,Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Virginia M Miller
- Departments of Surgery, Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
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Chen JC, Wang X, Serre M, Cen S, Franklin M, Espeland M. Particulate Air Pollutants, Brain Structure, and Neurocognitive Disorders in Older Women. Res Rep Health Eff Inst 2017; 2017:1-65. [PMID: 31898881 PMCID: PMC7266369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023] Open
Abstract
Introduction An increasing number of studies have suggested that exposure to particulate matter (PM) may represent a novel - and potentially amendable - environmental determinant of brain aging. The current longitudinal environmental epidemiological study addressed some important knowledge gaps in this emerging field, which combines the study of air pollution and neuroepidemiology. The investigators hypothesized that long-term PM exposure adversely influences global brain volume and brain regions (e.g., frontal lobe or hippocampus) that are critical to memory and complex cognitive processing or that are affected by neuropathological changes in dementia. It was also hypothesized that long-term PM exposure results in neurovascular damage and may increase the risk of mild cognitive impairment (MCI) and -dementia. Methods The investigators selected a well-characterized and geographically diverse population of older women (N = 7,479; average age = 71.0 ± 3.8 years at baseline) in the Women's Health Initiative (WHI) Memory Study (WHIMS) cohort (1996-2007), which included a subcohort (n = 1,403) enrolled in the WHIMS-Magnetic Resonance Imaging (WHIMS-MRI) study (2005-2006). Residence-specific yearly exposures to PM ≤ 2.5 µm in aerodynamic diameter (PM₂.₅) were estimated using a Bayesian maximum entropy spatiotemporal model of annual monitoring data (1999-2007) recorded in the U.S. Environmental Protection Agency (U.S. EPA) Air Quality System (AQS). Annual exposures (1996-2005) to diesel PM (DPM) were assigned to each residential census tract in a nationwide spatiotemporal mapping, based on a generalized additive model (GAM), to conduct census tract-specific temporal interpolation of DPM on-road estimates given by the U.S. EPA National-Scale Air Toxics Assessment Program. Multiple linear regression and multicovariate-adjusted Cox models were used to examine the associations, with statistical adjustment for multiple potential confounders. Results The investigators found that participants had smaller brain volumes, especially in the normal-appearing white matter (WM), if they lived in locations with higher levels of cumulative exposure (1999-2006) to PM ₂.₅ before the brain MRI scans were performed. The associations were not explained by sociodemographic factors, socioeconomic status, lifestyle factors, or other clinical characteristics. Analyses showed that the adverse effect on brain structure in the participants was driven primarily by the smaller WM volumes associated with cumulative PM₂.₅ exposures, which were present in the WM divisions of the association brain area (frontal, parietal, and temporal lobes) and corpus callosum. Increased DPM exposures were associated with larger ventricular volume, suggesting an overall atrophic effect on the aging brains. The participants tended to have smaller gray matter (GM) volumes if they lived in areas with the highest (i.e., fourth quartile) estimated cumulative DPM exposure in the 10 years before the brain MRI scans, compared with women in the first to third quartiles. This observed association was present in the total brain GM and in the association brain cortices. The associations with normal-appearing WM varied by DPM exposure range. For women with estimated cumulative exposure below that of the fourth quartile, increased DPM estimates were associated with smaller WM volumes. However, for women with increased cumulative DPM exposures estimates in the fourth quartile, WM volumes were larger. This pattern of association was found consistently in the association brain area; no measurable difference was found in the volume of the corpus callosum. These observed adverse effects of cumulative exposure to PM₂.₅ (linking exposure with smaller WM volumes) and to DPM (linking exposure in the highest quartile with smaller GM volumes) were not significantly modified by existing cardiovascular diseases, diabetes mellitus, obesity, or measured white blood cell (WBC) count. MRI measurements of the structural brain showed no differences in small-vessel ischemic diseases (SVID) in participants with varying levels of cumulative exposure to PM₂.₅ (1999-2006) or DPM (1996-2005), and no associations between PM exposures and SVID volumes were noted for total brain, association brain area, GM, or WM. For neurocognitive outcomes followed until 2007, the investigators found no evidence for increased risk of MCI/dementia associated with long-term PM exposures. Although exploratory secondary analyses showed different patterns of associations linking PM exposures separately with MCI and dementia, none of the -results was statistically significant. A similar lack of associations between PM exposures and MCI/dementia was found across the subgroups, with no strong indications for effect modification by cardiovascular diseases, diabetes mellitus, obesity, or WBC count. Conclusions The investigators concluded that their study findings support the hypothesized brain-structure neurotoxicity associated with PM exposures, a result that is in line with emerging neurotoxicological data. However, the investigators found no evidence of increased risk of MCI/dementia associated with long-term PM exposures. To better test the neurovascular effect hypothesis in PM-associated neurotoxic effects on the aging brain, the investigators recommend that future studies pay greater attention to selecting optimal populations with repeated measurements of cerebrovascular damage and address the possibility of selection biases accordingly. To further investigate the long-term consequence of brain-structure neurotoxicity on pathological brain aging, future researchers should take the pathobiologically heterogeneous neurocognitive outcomes into account and design adequately powered prospective cohort studies with improved exposure estimation and valid outcome ascertainment to assess whether PM-associated neurotoxicity increases the risks of pathological brain aging, including MCI and dementia.
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Affiliation(s)
- J-C Chen
- Keck School of Medicine, University of Southern California, Los Angeles
| | - X Wang
- Keck School of Medicine, University of Southern California, Los Angeles
| | - M Serre
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill
| | - S Cen
- Keck School of Medicine, University of Southern California, Los Angeles
| | - M Franklin
- Keck School of Medicine, University of Southern California, Los Angeles
| | - M Espeland
- Wake Forest University School of Medicine, Winston-Salem, North Carolina
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Chronic Use of Aspirin and Total White Matter Lesion Volume: Results from the Women's Health Initiative Memory Study of Magnetic Resonance Imaging Study. J Stroke Cerebrovasc Dis 2017; 26:2128-2136. [PMID: 28551293 DOI: 10.1016/j.jstrokecerebrovasdis.2017.04.034] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Accepted: 04/29/2017] [Indexed: 11/20/2022] Open
Abstract
OBJECTIVE To investigate the relationship between aspirin and subclinical cerebrovascular heath, we evaluated the effect of chronic aspirin use on white matter lesions (WML) volume among women. METHODS Chronic aspirin use was assessed in 1365 women who participated in the Women's Health Initiative Memory Study of Magnetic Resonance Imaging. Differences in WML volumes between aspirin users and nonusers were assessed with linear mixed models. A number of secondary analyses were performed, including lobe-specific analyses, subgroup analyses based on participants' overall risk of cerebrovascular disease, and a dose-response relationship analysis. RESULTS The mean age of the women at magnetic resonance imaging examination was 77.6 years. Sixty-one percent of participants were chronic aspirin users. After adjusting for demographic variables and comorbidities, chronic aspirin use was nonsignificantly associated with 4.8% (95% CI: -6.8%, 17.9%) larger WML volumes. These null findings were confirmed in secondary and sensitivity analyses, including an active comparator evaluation where aspirin users were compared to users of nonaspirin nonsteroidal anti-inflammatory drugs or acetaminophen. CONCLUSIONS There was a nonsignificant difference in WML volumes between aspirin users and nonusers. Further, our results suggest that chronic aspirin use may not have a clinically significant effect on WML volumes in women.
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Hiroi R, Weyrich G, Koebele SV, Mennenga SE, Talboom JS, Hewitt LT, Lavery CN, Mendoza P, Jordan A, Bimonte-Nelson HA. Benefits of Hormone Therapy Estrogens Depend on Estrogen Type: 17β-Estradiol and Conjugated Equine Estrogens Have Differential Effects on Cognitive, Anxiety-Like, and Depressive-Like Behaviors and Increase Tryptophan Hydroxylase-2 mRNA Levels in Dorsal Raphe Nucleus Subregions. Front Neurosci 2016; 10:517. [PMID: 28008302 PMCID: PMC5143618 DOI: 10.3389/fnins.2016.00517] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2016] [Accepted: 10/26/2016] [Indexed: 11/23/2022] Open
Abstract
Decreased serotonin (5-HT) function is associated with numerous cognitive and affective disorders. Women are more vulnerable to these disorders and have a lower rate of 5-HT synthesis than men. Serotonergic neurons in the dorsal raphe nucleus (DRN) are a major source of 5-HT in the forebrain and play a critical role in regulation of stress-related disorders. In particular, polymorphisms of tryptophan hydroxylase-2 (TpH2, the brain-specific, rate-limiting enzyme for 5-HT biosynthesis) are implicated in cognitive and affective disorders. Administration of 17β-estradiol (E2), the most potent naturally circulating estrogen in women and rats, can have beneficial effects on cognitive, anxiety-like, and depressive-like behaviors. Moreover, E2 increases TpH2 mRNA in specific subregions of the DRN. Although conjugated equine estrogens (CEE) are a commonly prescribed estrogen component of hormone therapy in menopausal women, there is a marked gap in knowledge regarding how CEE affects these behaviors and the brain 5-HT system. Therefore, we compared the effects of CEE and E2 treatments on behavior and TpH2 mRNA. Female Sprague-Dawley rats were ovariectomized, administered either vehicle, CEE, or E2 and tested on a battery of cognitive, anxiety-like, and depressive-like behaviors. The brains of these animals were subsequently analyzed for TpH2 mRNA. Both CEE and E2 exerted beneficial behavioral effects, although efficacy depended on the distinct behavior and for cognition, on the task difficulty. Compared to CEE, E2 generally had more robust anxiolytic and antidepressant effects. E2 increased TpH2 mRNA in the caudal and mid DRN, corroborating previous findings. However, CEE increased TpH2 mRNA in the caudal and rostral, but not the mid, DRN, suggesting that distinct estrogens can have subregion-specific effects on TpH2 gene expression. We also found differential correlations between the level of TpH2 mRNA in specific DRN subregions and behavior, depending on the type of behavior. These distinct associations imply that cognition, anxiety-like, and depressive-like behaviors are modulated by unique serotonergic neurocircuitry, opening the possibility of novel avenues of targeted treatment for different types of cognitive and affective disorders.
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Affiliation(s)
- Ryoko Hiroi
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Giulia Weyrich
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Stephanie V Koebele
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Sarah E Mennenga
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Joshua S Talboom
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Lauren T Hewitt
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Courtney N Lavery
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Perla Mendoza
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Ambra Jordan
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
| | - Heather A Bimonte-Nelson
- Department of Psychology, Arizona State UniversityTempe, AZ, USA; Arizona Alzheimer's ConsortiumPhoenix, AZ, USA
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Engler-Chiurazzi EB, Covey DF, Simpkins JW. A novel mechanism of non-feminizing estrogens in neuroprotection. Exp Gerontol 2016; 94:99-102. [PMID: 27818250 DOI: 10.1016/j.exger.2016.10.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 10/25/2016] [Accepted: 10/30/2016] [Indexed: 01/01/2023]
Abstract
Estrogens are potent and efficacious neuroprotectants both in vitro and in vivo in a variety of models of neurotoxicity. We determined the structural requirements for neuroprotection in an in vitro assay using a panel of >70 novel estratrienes, synthesized to reduce or eliminate estrogen receptor (ER) binding. We observed that neuroprotection could be enhanced by as much as 200-fold through modifications that positioned a large bulky group at the C2 or C4 position of the phenolic A ring of the estratriene. Further, substitutions on the B, C or D rings either reduced or did not markedly change neuroprotection. Collectively, there was a negative correlation between binding to ERs and neuroprotection with the more potent compounds showing no ER binding. In an in vivo model for neuroprotection, transient cerebral ischemia, efficacious compounds were active in protection of brain tissue from this pro-oxidant insult. We demonstrated that these non-feminizing estrogens engage in a redox cycle with glutathione, using the hexose monophosphate shunt to apply cytosolic reducing potential to cellular membranes. Together, these results demonstrate that non-feminizing estrogens are neuroprotective and protect brain from the induction of ischemic- and Alzheimer's disease (AD)-like neuropathology in an animal model. These features of non-feminizing estrogens make them attractive compounds for assessment of efficacy in AD and stroke, as they are not expected to show the side effects of chronic estrogen therapy that are mediated by ER actions in the liver, uterus and breast.
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Affiliation(s)
- Elizabeth B Engler-Chiurazzi
- Center for Basic and Translational Stroke Research, West Virginia University, Morgantown, WV 26505, United States.
| | - Douglas F Covey
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63130, United States
| | - James W Simpkins
- Center for Basic and Translational Stroke Research, West Virginia University, Morgantown, WV 26505, United States
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Casanova R, Wang X, Reyes J, Akita Y, Serre ML, Vizuete W, Chui HC, Driscoll I, Resnick SM, Espeland MA, Chen JC. A Voxel-Based Morphometry Study Reveals Local Brain Structural Alterations Associated with Ambient Fine Particles in Older Women. Front Hum Neurosci 2016; 10:495. [PMID: 27790103 PMCID: PMC5061768 DOI: 10.3389/fnhum.2016.00495] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Accepted: 09/20/2016] [Indexed: 12/19/2022] Open
Abstract
Objective: Exposure to ambient fine particulate matter (PM2.5: PM with aerodynamic diameters < 2.5 μm) has been linked with cognitive deficits in older adults. Using fine-grained voxel-wise analyses, we examined whether PM2.5 exposure also affects brain structure. Methods: Brain MRI data were obtained from 1365 women (aged 71–89) in the Women's Health Initiative Memory Study and local brain volumes were estimated using RAVENS (regional analysis of volumes in normalized space). Based on geocoded residential locations and air monitoring data from the U.S. Environmental Protection Agency, we employed a spatiotemporal model to estimate long-term (3-year average) exposure to ambient PM2.5 preceding MRI scans. Voxel-wise linear regression models were fit separately to gray matter (GM) and white matter (WM) maps to analyze associations between brain structure and PM2.5 exposure, with adjustment for potential confounders. Results: Increased PM2.5 exposure was associated with smaller volumes in both cortical GM and subcortical WM areas. For GM, associations were clustered in the bilateral superior, middle, and medial frontal gyri. For WM, the largest clusters were in the frontal lobe, with smaller clusters in the temporal, parietal, and occipital lobes. No statistically significant associations were observed between PM2.5 exposure and hippocampal volumes. Conclusions: Long-term PM2.5 exposures may accelerate loss of both GM and WM in older women. While our previous work linked smaller WM volumes to PM2.5, this is the first neuroimaging study reporting associations between air pollution exposure and smaller volumes of cortical GM. Our data support the hypothesized synaptic neurotoxicity of airborne particles.
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Affiliation(s)
- Ramon Casanova
- Department of Biostatistical Sciences, Wake Forest School of Medicine Winston-Salem, NC, USA
| | - Xinhui Wang
- Department of Preventive Medicine, University of Southern California Los Angeles, CA, USA
| | | | | | - Marc L Serre
- University of North Carolina Chapel Hill, NC, USA
| | | | - Helena C Chui
- Department of Neurology, University of Southern California Los Angeles, CA, USA
| | - Ira Driscoll
- Department of Psychology, University of Wisconsin-Milwaukee Milwaukee, WI, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, National Institutes of Health Baltimore, MD, USA
| | - Mark A Espeland
- Department of Biostatistical Sciences, Wake Forest School of Medicine Winston-Salem, NC, USA
| | - Jiu-Chiuan Chen
- Department of Preventive Medicine, University of Southern California Los Angeles, CA, USA
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Zhang T, Casanova R, Resnick SM, Manson JE, Baker LD, Padual CB, Kuller LH, Bryan RN, Espeland MA, Davatzikos C. Effects of Hormone Therapy on Brain Volumes Changes of Postmenopausal Women Revealed by Optimally-Discriminative Voxel-Based Morphometry. PLoS One 2016; 11:e0150834. [PMID: 26974440 PMCID: PMC4790922 DOI: 10.1371/journal.pone.0150834] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Accepted: 02/20/2016] [Indexed: 01/25/2023] Open
Abstract
Backgrounds The Women's Health Initiative Memory Study Magnetic Resonance Imaging (WHIMS-MRI) provides an opportunity to evaluate how menopausal hormone therapy (HT) affects the structure of older women’s brains. Our earlier work based on region of interest (ROI) analysis demonstrated potential structural changes underlying adverse effects of HT on cognition. However, the ROI-based analysis is limited in statistical power and precision, and cannot provide fine-grained mapping of whole-brain changes. Methods We aimed to identify local structural differences between HT and placebo groups from WHIMS-MRI in a whole-brain refined level, by using a novel method, named Optimally-Discriminative Voxel-Based Analysis (ODVBA). ODVBA is a recently proposed imaging pattern analysis approach for group comparisons utilizing a spatially adaptive analysis scheme to accurately locate areas of group differences, thereby providing superior sensitivity and specificity to detect the structural brain changes over conventional methods. Results Women assigned to HT treatments had significant Gray Matter (GM) losses compared to the placebo groups in the anterior cingulate and the adjacent medial frontal gyrus, and the orbitofrontal cortex, which persisted after multiple comparison corrections. There were no regions where HT was significantly associated with larger volumes compared to placebo, although a trend of marginal significance was found in the posterior cingulate cortical area. The CEE-Alone and CEE+MPA groups, although compared with different placebo controls, demonstrated similar effects according to the spatial patterns of structural changes. Conclusions HT had adverse effects on GM volumes and risk for cognitive impairment and dementia in older women. These findings advanced our understanding of the neurobiological underpinnings of HT effects.
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Affiliation(s)
- Tianhao Zhang
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- * E-mail:
| | - Ramon Casanova
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland, United States of America
| | - JoAnn E. Manson
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Laura D. Baker
- Department of Internal Medicine and Epidemiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Claudia B. Padual
- Sierra Pacific Mental Illness Research, Education and Clinical Center, VA Palo Alto Health Care System, Palo Alto, California, United States of America
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States of America
| | - Lewis H. Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - R. Nick Bryan
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Mark A. Espeland
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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Driscoll I, Gaussoin SA, Wassertheil-Smoller S, Limacher M, Casanova R, Yaffe K, Resnick SM, Espeland MA. Obesity and Structural Brain Integrity in Older Women: The Women's Health Initiative Magnetic Resonance Imaging Study. J Gerontol A Biol Sci Med Sci 2016; 71:1216-1222. [PMID: 26961581 DOI: 10.1093/gerona/glw023] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Midlife obesity has been linked to age-related brain atrophy and risk of dementia, but the relationships are less clear for older individuals. These associations may be explained by changes in appetite or metabolism in the dementia prodrome; thus, prospective studies with adequate follow-up are needed. We examined the associations that obesity (body mass index, BMI) and change in BMI over an average of 6.6 (1.0-9.1) years have with global and regional brain and white matter lesion volumes in a sample of 1,366 women aged 65-80. METHODS Least square means for regional brain volumes and white matter lesion loads for women grouped by BMI and changes in BMI were generated from multivariable linear models with and without adjustment for demographic and health covariates. RESULTS Both global obesity and increase in BMI were associated with lower cerebrospinal fluid and higher specific brain volumes (ps < .05), after controlling for diabetes and other cerebrovascular disease risk factors. Obesity, but not change in BMI, predicted lower lesion loads for the total, parietal, and occipital white matter (ps < .05). CONCLUSIONS Obesity in this cohort is associated with less brain atrophy and lower ischemic lesion loads. The findings are consistent with our previous report of worse cognitive performance in association with weight loss (probably not due to frailty) in this cohort and in line with the idea of the "obesity paradox" as differences in dementia risk vary across time, whereby midlife obesity seems to be a predictor of dementia, whereas weight loss seems to be a better predictor at older ages.
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Affiliation(s)
- Ira Driscoll
- Psychology Department, University of Wisconsin-Milwaukee.
| | - Sarah A Gaussoin
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | | | | | - Ramon Casanova
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Kristine Yaffe
- Department of Psychiatry, Neurology, and Epidemiology and Biostatistics, University of California, San Francisco
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Mark A Espeland
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
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Habes M, Erus G, Toledo JB, Zhang T, Bryan N, Launer LJ, Rosseel Y, Janowitz D, Doshi J, Van der Auwera S, von Sarnowski B, Hegenscheid K, Hosten N, Homuth G, Völzke H, Schminke U, Hoffmann W, Grabe HJ, Davatzikos C. White matter hyperintensities and imaging patterns of brain ageing in the general population. Brain 2016; 139:1164-79. [PMID: 26912649 DOI: 10.1093/brain/aww008] [Citation(s) in RCA: 275] [Impact Index Per Article: 34.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Accepted: 12/17/2015] [Indexed: 01/18/2023] Open
Abstract
White matter hyperintensities are associated with increased risk of dementia and cognitive decline. The current study investigates the relationship between white matter hyperintensities burden and patterns of brain atrophy associated with brain ageing and Alzheimer's disease in a large populatison-based sample (n = 2367) encompassing a wide age range (20-90 years), from the Study of Health in Pomerania. We quantified white matter hyperintensities using automated segmentation and summarized atrophy patterns using machine learning methods resulting in two indices: the SPARE-BA index (capturing age-related brain atrophy), and the SPARE-AD index (previously developed to capture patterns of atrophy found in patients with Alzheimer's disease). A characteristic pattern of age-related accumulation of white matter hyperintensities in both periventricular and deep white matter areas was found. Individuals with high white matter hyperintensities burden showed significantly (P < 0.0001) lower SPARE-BA and higher SPARE-AD values compared to those with low white matter hyperintensities burden, indicating that the former had more patterns of atrophy in brain regions typically affected by ageing and Alzheimer's disease dementia. To investigate a possibly causal role of white matter hyperintensities, structural equation modelling was used to quantify the effect of Framingham cardiovascular disease risk score and white matter hyperintensities burden on SPARE-BA, revealing a statistically significant (P < 0.0001) causal relationship between them. Structural equation modelling showed that the age effect on SPARE-BA was mediated by white matter hyperintensities and cardiovascular risk score each explaining 10.4% and 21.6% of the variance, respectively. The direct age effect explained 70.2% of the SPARE-BA variance. Only white matter hyperintensities significantly mediated the age effect on SPARE-AD explaining 32.8% of the variance. The direct age effect explained 66.0% of the SPARE-AD variance. Multivariable regression showed significant relationship between white matter hyperintensities volume and hypertension (P = 0.001), diabetes mellitus (P = 0.023), smoking (P = 0.002) and education level (P = 0.003). The only significant association with cognitive tests was with the immediate recall of the California verbal and learning memory test. No significant association was present with the APOE genotype. These results support the hypothesis that white matter hyperintensities contribute to patterns of brain atrophy found in beyond-normal brain ageing in the general population. White matter hyperintensities also contribute to brain atrophy patterns in regions related to Alzheimer's disease dementia, in agreement with their known additive role to the likelihood of dementia. Preventive strategies reducing the odds to develop cardiovascular disease and white matter hyperintensities could decrease the incidence or delay the onset of dementia.
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Affiliation(s)
- Mohamad Habes
- Institute for Community Medicine, University of Greifswald, Germany Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, USA Department of Psychiatry, University of Greifswald, Germany
| | - Guray Erus
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, USA
| | - Jon B Toledo
- Department of Pathology and Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania, USA
| | - Tianhao Zhang
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, USA
| | - Nick Bryan
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, USA
| | - Lenore J Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, USA
| | - Yves Rosseel
- Department of Data Analysis, Ghent University, Belgium
| | | | - Jimit Doshi
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, USA
| | - Sandra Van der Auwera
- Department of Psychiatry, University of Greifswald, Germany German Centre for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | | | | | - Norbert Hosten
- Department of Radiology, University of Greifswald, Germany
| | - Georg Homuth
- Institute for Genetics and Functional Genomics, University of Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University of Greifswald, Germany
| | - Ulf Schminke
- Department of Neurology, University of Greifswald, Germany
| | - Wolfgang Hoffmann
- Institute for Community Medicine, University of Greifswald, Germany German Centre for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry, University of Greifswald, Germany German Centre for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | - Christos Davatzikos
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, USA
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Chen JC, Wang X, Wellenius GA, Serre ML, Driscoll I, Casanova R, McArdle JJ, Manson JE, Chui HC, Espeland MA. Ambient air pollution and neurotoxicity on brain structure: Evidence from women's health initiative memory study. Ann Neurol 2015; 78:466-76. [PMID: 26075655 PMCID: PMC4546504 DOI: 10.1002/ana.24460] [Citation(s) in RCA: 163] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 06/12/2015] [Accepted: 06/12/2015] [Indexed: 12/31/2022]
Abstract
OBJECTIVE The aim of this study was to examine the putative adverse effects of ambient fine particulate matter (PM2.5 : PM with aerodynamic diameters <2.5μm) on brain volumes in older women. METHODS We conducted a prospective study of 1,403 community-dwelling older women without dementia enrolled in the Women's Health Initiative Memory Study, 1996-1998. Structural brain magnetic resonance imaging scans were performed at the age of 71-89 years in 2005-2006 to obtain volumetric measures of gray matter (GM) and normal-appearing white matter (WM). Given residential histories and air monitoring data, we used a spatiotemporal model to estimate cumulative PM2.5 exposure in 1999-2006. Multiple linear regression was employed to evaluate the associations between PM2.5 and brain volumes, adjusting for intracranial volumes and potential confounders. RESULTS Older women with greater PM2.5 exposures had significantly smaller WM, but not GM, volumes, independent of geographical region, demographics, socioeconomic status, lifestyles, and clinical characteristics, including cardiovascular risk factors. For each interquartile increment (3.49μg/m(3) ) of cumulative PM2.5 exposure, the average WM volume (WMV; 95% confidence interval) was 6.23cm(3) (3.72-8.74) smaller in the total brain and 4.47cm(3) (2.27-6.67) lower in the association areas, equivalent to 1 to 2 years of brain aging. The adverse PM2.5 effects on smaller WMVs were present in frontal and temporal lobes and corpus callosum (all p values <0.01). Hippocampal volumes did not differ by PM2.5 exposure. INTERPRETATION PM2.5 exposure may contribute to WM loss in older women. Future studies are needed to determine whether exposures result in myelination disturbance, disruption of axonal integrity, damages to oligodendrocytes, or other WM neuropathologies.
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Affiliation(s)
- Jiu-Chiuan Chen
- Department of Preventive Medicine, University of Southern California, Keck School of Medicine, Los Angeles, California, U.S.A
| | - Xinhui Wang
- Department of Preventive Medicine, University of Southern California, Keck School of Medicine, Los Angeles, California, U.S.A
| | - Gregory A. Wellenius
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, U.S.A
| | - Marc L. Serre
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, U.S.A
| | - Ira Driscoll
- Department of Psychology, University of Wisconsin, Milwaukee, Wisconsin, U.S.A
| | - Ramon Casanova
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, U.S.A
| | - John J. McArdle
- Department of Psychology, University of Southern California, Los Angeles, California, U.S.A
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Helena C. Chui
- Department of Neurology, University of Southern California, Keck School of Medicine, Los Angeles, California, U.S.A
| | - Mark A. Espeland
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, U.S.A
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McCarrey AC, Resnick SM. Postmenopausal hormone therapy and cognition. Horm Behav 2015; 74:167-72. [PMID: 25935728 PMCID: PMC4573348 DOI: 10.1016/j.yhbeh.2015.04.018] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Revised: 04/17/2015] [Accepted: 04/23/2015] [Indexed: 01/17/2023]
Abstract
This article is part of a Special Issue "Estradiol and cognition". Prior to the publication of findings from the Women's Health Initiative (WHI) in 2002, estrogen-containing hormone therapy (HT) was used to prevent age-related disease, especially cardiovascular disease, and to treat menopausal symptoms such as hot flushes and sleep disruptions. Some observational studies of HT in midlife and aging women suggested that HT might also benefit cognitive function, but randomized clinical trials have produced mixed findings in terms of health and cognitive outcomes. This review focuses on hormone effects on cognition and risk for dementia in naturally menopausal women as well as surgically induced menopause, and highlights findings from the large-scale WHI Memory Study (WHIMS) which, contrary to expectation, showed increased dementia risk and poorer cognitive outcomes in older postmenopausal women randomized to HT versus placebo. We consider the 'critical window hypothesis', which suggests that a window of opportunity may exist shortly after menopause during which estrogen treatments are most effective. In addition, we highlight emerging evidence that potential adverse effects of HT on cognition are most pronounced in women who have other health risks, such as lower global cognition or diabetes. Lastly, we point towards implications for future research and clinical treatments.
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Affiliation(s)
- Anna C McCarrey
- Laboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD, 21224, USA.
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD, 21224, USA.
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Daniel JM, Witty CF, Rodgers SP. Long-term consequences of estrogens administered in midlife on female cognitive aging. Horm Behav 2015; 74:77-85. [PMID: 25917862 PMCID: PMC4573273 DOI: 10.1016/j.yhbeh.2015.04.012] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Revised: 04/08/2015] [Accepted: 04/12/2015] [Indexed: 12/15/2022]
Abstract
This article is part of a Special Issue "Estradiol and cognition". Many of the biochemical, structural, and functional changes that occur as the female brain ages are influenced by changes in levels of estrogens. Administration of estrogens begun during a critical window near menopause is hypothesized to prevent or delay age-associated cognitive decline. However, due to potential health risks women often limit use of estrogen therapy to a few years to treat menopausal symptoms. The long-term consequences for the brain of short-term use of estrogens are unknown. Interestingly, there are preliminary data to suggest that short-term use of estrogens during the menopausal transition may afford long-term cognitive benefits to women as they age. Thus, there is the intriguing possibility that short-term estrogen therapy may provide lasting benefits to the brain and cognition. The focus of the current review is an examination of the long-term impact for cognition of midlife use of estrogens. We review data from our lab and others indicating that the ability of midlife estrogens to impact estrogen receptors in the hippocampus may contribute to its ability to exert lasting impacts on cognition in aging females.
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Affiliation(s)
- Jill M Daniel
- Department of Psychology, Tulane University New Orleans, LA 70118, USA; Program in Neuroscience, Tulane University New Orleans, LA 70118, USA.
| | - Christine F Witty
- Program in Neuroscience, Tulane University New Orleans, LA 70118, USA
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Espeland MA, Brinton RD, Manson JE, Yaffe K, Hugenschmidt C, Vaughan L, Craft S, Edwards BJ, Casanova R, Masaki K, Resnick SM. Postmenopausal hormone therapy, type 2 diabetes mellitus, and brain volumes. Neurology 2015; 85:1131-8. [PMID: 26163429 DOI: 10.1212/wnl.0000000000001816] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2015] [Accepted: 06/03/2015] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To examine whether the effect of postmenopausal hormone therapy (HT) on brain volumes in women aged 65-79 years differs depending on type 2 diabetes status during postintervention follow-up of a randomized controlled clinical trial. METHODS The Women's Health Initiative randomized clinical trials assigned women to HT (0.625 mg/day conjugated equine estrogens with or without 2.5 mg/day medroxyprogesterone acetate) or placebo for an average of 5.6 years. A total of 1,402 trial participants underwent brain MRI 2.4 years after the trials; these were repeated in 699 women 4.7 years later. General linear models were used to assess the interaction between diabetes status and HT assignment on brain volumes. RESULTS Women with diabetes at baseline or during follow-up who had been assigned to HT compared to placebo had mean decrement in total brain volume of -18.6 mL (95% confidence interval [CI] -29.6, -7.6). For women without diabetes, this mean decrement was -0.4 (95% CI -3.8, 3.0) (interaction p=0.002). This interaction was evident for total gray matter (p<0.001) and hippocampal (p=0.006) volumes. It was not evident for changes in brain volumes over follow-up or for ischemic lesion volumes and was not influenced by diabetes duration or oral medications. CONCLUSIONS For women aged 65 years or older who are at increased risk for brain atrophy due to type 2 diabetes, prescription of postmenopausal HT is associated with lower gray matter (total and hippocampal) volumes. Interactions with diabetes and insulin resistance may explain divergent findings on how estrogen influences brain volume among older women.
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Affiliation(s)
- Mark A Espeland
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD.
| | - Roberta Diaz Brinton
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - JoAnn E Manson
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - Kristine Yaffe
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - Christina Hugenschmidt
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - Leslie Vaughan
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - Suzanne Craft
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - Beatrice J Edwards
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - Ramon Casanova
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - Kamal Masaki
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
| | - Susan M Resnick
- From the Departments of Biostatistical Sciences (M.A.E., R.C.), Internal Medicine (C.H., S.C.), and Social Sciences and Health Policy (L.V.), Wake Forest School of Medicine, Winston-Salem, NC; Departments of Pharmacology and Pharmaceutical Sciences, Biomedical Engineering, and Neurology (R.D.B.), University of Southern California, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Departments of Epidemiology and Biostatistics, Psychiatry, and Neurology (K.Y.), University of California, San Francisco; Department of Internal Medicine (B.J.E.), The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Geriatric Medicine (K.M.), University of Hawaii at Manoa, Honolulu, HI; and Laboratory of Behavioral Neuroscience (S.M.R.), Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD
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Boardman HMP, Hartley L, Eisinga A, Main C, Roqué i Figuls M, Bonfill Cosp X, Gabriel Sanchez R, Knight B. Hormone therapy for preventing cardiovascular disease in post-menopausal women. Cochrane Database Syst Rev 2015:CD002229. [PMID: 25754617 PMCID: PMC10183715 DOI: 10.1002/14651858.cd002229.pub4] [Citation(s) in RCA: 158] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Evidence from systematic reviews of observational studies suggests that hormone therapy may have beneficial effects in reducing the incidence of cardiovascular disease events in post-menopausal women, however the results of randomised controlled trials (RCTs) have had mixed results. This is an updated version of a Cochrane review published in 2013. OBJECTIVES To assess the effects of hormone therapy for the prevention of cardiovascular disease in post-menopausal women, and whether there are differential effects between use in primary or secondary prevention. Secondary aims were to undertake exploratory analyses to (i) assess the impact of time since menopause that treatment was commenced (≥ 10 years versus < 10 years), and where these data were not available, use age of trial participants at baseline as a proxy (≥ 60 years of age versus < 60 years of age); and (ii) assess the effects of length of time on treatment. SEARCH METHODS We searched the following databases on 25 February 2014: Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library, MEDLINE, EMBASE and LILACS. We also searched research and trials registers, and conducted reference checking of relevant studies and related systematic reviews to identify additional studies. SELECTION CRITERIA RCTs of women comparing orally administered hormone therapy with placebo or a no treatment control, with a minimum of six months follow-up. DATA COLLECTION AND ANALYSIS Two authors independently assessed study quality and extracted data. We calculated risk ratios (RRs) with 95% confidence intervals (CIs) for each outcome. We combined results using random effects meta-analyses, and undertook further analyses to assess the effects of treatment as primary or secondary prevention, and whether treatment was commenced more than or less than 10 years after menopause. MAIN RESULTS We identified six new trials through this update. Therefore the review includes 19 trials with a total of 40,410 post-menopausal women. On the whole, study quality was good and generally at low risk of bias; the findings are dominated by the three largest trials. We found high quality evidence that hormone therapy in both primary and secondary prevention conferred no protective effects for all-cause mortality, cardiovascular death, non-fatal myocardial infarction, angina, or revascularisation. However, there was an increased risk of stroke in those in the hormone therapy arm for combined primary and secondary prevention (RR 1.24, 95% CI 1.10 to 1.41). Venous thromboembolic events were increased (RR 1.92, 95% CI 1.36 to 2.69), as were pulmonary emboli (RR 1.81, 95% CI 1.32 to 2.48) on hormone therapy relative to placebo.The absolute risk increase for stroke was 6 per 1000 women (number needed to treat for an additional harmful outcome (NNTH) = 165; mean length of follow-up: 4.21 years (range: 2.0 to 7.1)); for venous thromboembolism 8 per 1000 women (NNTH = 118; mean length of follow-up: 5.95 years (range: 1.0 to 7.1)); and for pulmonary embolism 4 per 1000 (NNTH = 242; mean length of follow-up: 3.13 years (range: 1.0 to 7.1)).We performed subgroup analyses according to when treatment was started in relation to the menopause. Those who started hormone therapy less than 10 years after the menopause had lower mortality (RR 0.70, 95% CI 0.52 to 0.95, moderate quality evidence) and coronary heart disease (composite of death from cardiovascular causes and non-fatal myocardial infarction) (RR 0.52, 95% CI 0.29 to 0.96; moderate quality evidence), though they were still at increased risk of venous thromboembolism (RR 1.74, 95% CI 1.11 to 2.73, high quality evidence) compared to placebo or no treatment. There was no strong evidence of effect on risk of stroke in this group. In those who started treatment more than 10 years after the menopause there was high quality evidence that it had little effect on death or coronary heart disease between groups but there was an increased risk of stroke (RR 1.21, 95% CI 1.06 to 1.38, high quality evidence) and venous thromboembolism (RR 1.96, 95% CI 1.37 to 2.80, high quality evidence). AUTHORS' CONCLUSIONS Our review findings provide strong evidence that treatment with hormone therapy in post-menopausal women overall, for either primary or secondary prevention of cardiovascular disease events has little if any benefit and causes an increase in the risk of stroke and venous thromboembolic events.
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Affiliation(s)
- Henry M P Boardman
- Department of Cardiovascular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK, OX3 9DU
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Hodis HN, Mack WJ. Hormone replacement therapy and the association with coronary heart disease and overall mortality: clinical application of the timing hypothesis. J Steroid Biochem Mol Biol 2014; 142:68-75. [PMID: 23851166 DOI: 10.1016/j.jsbmb.2013.06.011] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2012] [Revised: 06/10/2013] [Accepted: 06/28/2013] [Indexed: 11/27/2022]
Abstract
Conclusions from randomized controlled trial (RCT) data over the past 10 years has spanned from presumed harm to consistency with observational data that hormone replacement therapy (HRT) decreases the risk for coronary heart disease (CHD) as well as overall mortality in women who are recently postmenopausal. Multiple clinical studies including randomized trials and observational studies converge with animal experimentation to show a consistency that HRT decreases CHD risk and overall mortality in primary prevention when HRT is started at the time of or soon after menopause. The totality of data supports the "timing" hypothesis that posits that HRT effects are dependent on when HRT is started in relation to age and/or time-since-menopause. The totality of data shows that HRT decreases CHD and overall morality when started in women who are less than 60 years old and/or less than 10 years postmenopausal, providing a "window-of-opportunity". Further evidence shows that women who start HRT when in their 50s and continued for 5-30 years that there is an increase of 1.5 quality-adjusted life-years (QALYs). Additionally, HRT is highly cost-effective at $2438 per QALY gained. The totality of data converges to show a consistency between randomized trials and observational studies that when started in women at or near menopause and continued long-term, HRT decreases CHD and overall mortality compared with women who do not use HRT. This article is part of a Special Issue entitled 'Menopause'.
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Affiliation(s)
- Howard N Hodis
- Keck School of Medicine, University of Southern California, 2250 Alcazar Street, CSC 132, Los Angeles, CA 90033, United States.
| | - Wendy J Mack
- Keck School of Medicine, University of Southern California, 2001 Soto Street, SSB 202Y, Los Angeles, CA 90033, United States.
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Petrone AB, Gatson JW, Simpkins JW, Reed MN. Non-feminizing estrogens: a novel neuroprotective therapy. Mol Cell Endocrinol 2014; 389:40-7. [PMID: 24424441 PMCID: PMC4040321 DOI: 10.1016/j.mce.2013.12.017] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2013] [Revised: 12/17/2013] [Accepted: 12/17/2013] [Indexed: 12/16/2022]
Abstract
While the conflict between basic science evidence for estrogen neuroprotection and the lack of effectiveness in clinical trials is only now being resolved, it is clear that strategies for estrogen neuroprotection that avoid activation of ERs have the potential for clinical application. Herein we review the evidence from both in vitro and in vivo studies that describe high potency neuroprotection with non-feminizing estrogens. We have characterized many of the essential chemical features of non-feminizing estrogens that eliminate or reduce ER binding while maintaining or enhancing neuroprotection. Additionally, we provide evidence that these non-feminizing estrogens have efficacy in protecting the brain from AD neuropathology and traumatic brain injury. In conclusion, it appears that the non-feminizing estrogen strategy for neuroprotection is a viable option to achieve the beneficial neuroprotective effects of estrogens while eliminating the toxic off-target effects of chronic estrogen administration.
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Affiliation(s)
- Ashley B Petrone
- Department of Physiology and Pharmacology, West Virginia University School of Medicine, Morgantown, WV, United States; Center for Basic and Translational Stroke Research, West Virginia University, Morgantown, WV, United States
| | - Joshua W Gatson
- Department of Emergency Medicine, University of Texas Southwestern Medical School, Dallas, TX, United States
| | - James W Simpkins
- Department of Physiology and Pharmacology, West Virginia University School of Medicine, Morgantown, WV, United States; Center for Basic and Translational Stroke Research, West Virginia University, Morgantown, WV, United States
| | - Miranda N Reed
- Center for Basic and Translational Stroke Research, West Virginia University, Morgantown, WV, United States; Department of Psychology, West Virginia University, Morgantown, WV, United States.
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Bushnell C, McCullough LD, Awad IA, Chireau MV, Fedder WN, Furie KL, Howard VJ, Lichtman JH, Lisabeth LD, Piña IL, Reeves MJ, Rexrode KM, Saposnik G, Singh V, Towfighi A, Vaccarino V, Walters MR. Guidelines for the prevention of stroke in women: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 2014; 45:1545-88. [PMID: 24503673 PMCID: PMC10152977 DOI: 10.1161/01.str.0000442009.06663.48] [Citation(s) in RCA: 622] [Impact Index Per Article: 62.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
PURPOSE The aim of this statement is to summarize data on stroke risk factors that are unique to and more common in women than men and to expand on the data provided in prior stroke guidelines and cardiovascular prevention guidelines for women. This guideline focuses on the risk factors unique to women, such as reproductive factors, and those that are more common in women, including migraine with aura, obesity, metabolic syndrome, and atrial fibrillation. METHODS Writing group members were nominated by the committee chair on the basis of their previous work in relevant topic areas and were approved by the American Heart Association (AHA) Stroke Council's Scientific Statement Oversight Committee and the AHA's Manuscript Oversight Committee. The panel reviewed relevant articles on adults using computerized searches of the medical literature through May 15, 2013. The evidence is organized within the context of the AHA framework and is classified according to the joint AHA/American College of Cardiology and supplementary AHA Stroke Council methods of classifying the level of certainty and the class and level of evidence. The document underwent extensive AHA internal peer review, Stroke Council Leadership review, and Scientific Statements Oversight Committee review before consideration and approval by the AHA Science Advisory and Coordinating Committee. RESULTS We provide current evidence, research gaps, and recommendations on risk of stroke related to preeclampsia, oral contraceptives, menopause, and hormone replacement, as well as those risk factors more common in women, such as obesity/metabolic syndrome, atrial fibrillation, and migraine with aura. CONCLUSIONS To more accurately reflect the risk of stroke in women across the lifespan, as well as the clear gaps in current risk scores, we believe a female-specific stroke risk score is warranted.
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Pottala JV, Yaffe K, Robinson JG, Espeland MA, Wallace R, Harris WS. Higher RBC EPA + DHA corresponds with larger total brain and hippocampal volumes: WHIMS-MRI study. Neurology 2014; 82:435-42. [PMID: 24453077 DOI: 10.1212/wnl.0000000000000080] [Citation(s) in RCA: 109] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
OBJECTIVE To test whether red blood cell (RBC) levels of marine omega-3 fatty acids measured in the Women's Health Initiative Memory Study were related to MRI brain volumes measured 8 years later. METHODS RBC eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and MRI brain volumes were assessed in 1,111 postmenopausal women from the Women's Health Initiative Memory Study. The endpoints were total brain volume and anatomical regions. Linear mixed models included multiple imputations of fatty acids and were adjusted for hormone therapy, time since randomization, demographics, intracranial volume, and cardiovascular disease risk factors. RESULTS In fully adjusted models, a 1 SD greater RBC EPA + DHA (omega-3 index) level was correlated with 2.1 cm(3) larger brain volume (p = 0.048). DHA was marginally correlated (p = 0.063) with total brain volume while EPA was less so (p = 0.11). There were no correlations between ischemic lesion volumes and EPA, DHA, or EPA + DHA. A 1 SD greater omega-3 index was correlated with greater hippocampal volume (50 mm(3), p = 0.036) in fully adjusted models. Comparing the fourth quartile vs the first quartile of the omega-3 index confirmed greater hippocampal volume (159 mm(3), p = 0.034). CONCLUSION A higher omega-3 index was correlated with larger total normal brain volume and hippocampal volume in postmenopausal women measured 8 years later. While normal aging results in overall brain atrophy, lower omega-3 index may signal increased risk of hippocampal atrophy. Future studies should examine whether maintaining higher RBC EPA + DHA levels slows the rate of hippocampal or overall brain atrophy.
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Affiliation(s)
- James V Pottala
- From the Department of Internal Medicine (J.V.P., W.S.H.), Sanford School of Medicine, University of South Dakota, Sioux Falls; Health Diagnostic Laboratory Inc. (J.V.P., W.S.H.), Richmond, VA; Department of Psychiatry (K.Y.), University of California Medical Center, San Francisco; Departments of Epidemiology and Internal Medicine (J.R., R.W.), University of Iowa College of Public Health, Iowa City; Department of Biostatistical Services (M.A.E.), Wake Forest School of Medicine, Winston-Salem, NC; and OmegaQuant Analytics (W.S.H.), Sioux Falls, SD
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Coker LH, Espeland MA, Hogan PE, Resnick SM, Bryan RN, Robinson JG, Goveas JS, Davatzikos C, Kuller LH, Williamson JD, Bushnell CD, Shumaker SA. Change in brain and lesion volumes after CEE therapies: the WHIMS-MRI studies. Neurology 2014; 82:427-34. [PMID: 24384646 DOI: 10.1212/wnl.0000000000000079] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVES To determine whether smaller brain volumes in older women who had completed Women's Health Initiative (WHI)-assigned conjugated equine estrogen-based hormone therapy (HT), reported by WHI Memory Study (WHIMS)-MRI, correspond to a continuing increased rate of atrophy an average of 6.1 to 7.7 years later in WHIMS-MRI2. METHODS A total of 1,230 WHI participants were contacted: 797 (64.8%) consented, and 729 (59%) were rescanned an average of 4.7 years after the initial MRI scan. Mean annual rates of change in total brain volume, the primary outcome, and rates of change in ischemic lesion volumes, the secondary outcome, were compared between treatment groups using mixed-effect models with adjustment for trial, clinical site, age, intracranial volumes, and time between MRI measures. RESULTS Total brain volume decreased an average of 3.22 cm(3)/y in the active arm and 3.07 cm(3)/y in the placebo arm (p = 0.53). Total ischemic lesion volumes increased in both arms at a rate of 0.12 cm(3)/y (p = 0.88). CONCLUSIONS Conjugated equine estrogen-based postmenopausal HT, previously assigned at WHI baseline, did not affect rates of decline in brain volumes or increases in brain lesion volumes during the 4.7 years between the initial and follow-up WHIMS-MRI studies. Smaller frontal lobe volumes were observed as persistent group differences among women assigned to active HT compared with placebo. Women with a history of cardiovascular disease treated with active HT, compared with placebo, had higher rates of accumulation in white matter lesion volume and total brain lesion volume. Further study may elucidate mechanisms that explain these findings.
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Affiliation(s)
- Laura H Coker
- From the Division of Public Health Sciences (L.H.C., M.A.E., P.E.H., S.A.S.), and Departments of Internal Medicine and Geriatrics (J.D.W.) and Neurology (C.D.B.), Wake Forest School of Medicine, Winston-Salem, NC; Intramural Research Program (S.M.R.), National Institute on Aging, NIH, Baltimore, MD; Department of Radiology (R.N.B., C.D.), University of Pennsylvania, Philadelphia; Department of Internal Medicine and Epidemiology (J.G.R.), University of Iowa, Iowa City; Department of Psychiatry and Behavioral Medicine (J.S.G.), Medical College of Wisconsin, Milwaukee; and Department of Epidemiology (L.H.K.), University of Pittsburgh, PA
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Intraindividual variability in domain-specific cognition and risk of mild cognitive impairment and dementia. Curr Gerontol Geriatr Res 2013; 2013:495793. [PMID: 24454359 PMCID: PMC3881440 DOI: 10.1155/2013/495793] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2013] [Revised: 10/31/2013] [Accepted: 10/31/2013] [Indexed: 11/18/2022] Open
Abstract
Intraindividual variability among cognitive domains may predict dementia independently of interindividual differences in cognition. A multidomain cognitive battery was administered to 2305 older adult women (mean age 74 years) enrolled in an ancillary study of the Women's Health Initiative. Women were evaluated annually for probable dementia and mild cognitive impairment (MCI) for an average of 5.3 years using a standardized protocol. Proportional hazards regression showed that lower baseline domain-specific cognitive scores significantly predicted MCI (N = 74), probable dementia (N = 45), and MCI or probable dementia combined (N = 101) and that verbal and figural memory predicted each outcome independently of all other cognitive domains. The baseline intraindividual standard deviation across test scores (IAV Cognitive Domains) significantly predicted probable dementia and this effect was attenuated by interindividual differences in verbal episodic memory. Slope increases in IAV Cognitive Domains across measurement occasions (IAV Time) explained additional risk for MCI and MCI or probable dementia, beyond that accounted for by interindividual differences in multiple cognitive measures, but risk for probable dementia was attenuated by mean decreases in verbal episodic memory slope. These findings demonstrate that within-person variability across cognitive domains both at baseline and longitudinally independently accounts for risk of cognitive impairment and dementia in support of the predictive utility of within-person variability.
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Abstract
OBJECTIVE The critical window hypothesis of hormone therapy (HT) and cognitive function states that the effects of HT depend on timing of initiation with respect to age, the menopausal transition, or both, and that optimal effects are evident with early initiation. This article reviews clinical studies that bear on this hypothesis. METHODS Recognizing that the typical pattern of HT use is early HT initiation, this review describes findings from observational studies of ever use of HT and observational studies that looked specifically at the timing of HT on Alzheimer's disease (AD) and cognitive test performance. Randomized trials of HT and verbal memory are discussed, and neuroimaging studies bearing on the hypothesis are reviewed. RESULTS Observational data suggest that HT generally reduces the risk of AD. Three of three observational studies that specifically examined the timing of initiation in relation to AD risk each provide support for the window, whereas three of five observational studies of HT timing and cognitive test performance do. Randomized clinical trials of estrogen therapy in younger women find support for the hypothesis. Conjugated equine estrogens/medroxyprogesterone acetate increases risks regardless of timing. Little is known about the cognitive effects of other combination HT formulations. CONCLUSIONS A definitive trial to test the critical window hypothesis is not feasible. Evidence drawn from other sources provides initial support for the hypothesis. Although these findings are relevant to women who use HT to treat vasomotor symptoms, HT is currently not indicated for the treatment of cognitive complaints or for dementia prevention.
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Affiliation(s)
- Pauline M Maki
- Department of Psychiatry , University of Illinois at Chicago, Chicago, IL 60612, USA.
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Ohwaki K, Yano E, Tamura A, Inoue T, Saito I. Hypercholesterolemia is associated with a lower risk of cerebral ischemic small vessel disease detected on brain checkups. Clin Neurol Neurosurg 2013; 115:669-72. [DOI: 10.1016/j.clineuro.2012.07.025] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2012] [Revised: 07/05/2012] [Accepted: 07/21/2012] [Indexed: 11/29/2022]
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Hodis HN, Mack WJ. The timing hypothesis and hormone replacement therapy: a paradigm shift in the primary prevention of coronary heart disease in women. Part 2: comparative risks. J Am Geriatr Soc 2013; 61:1011-1018. [PMID: 23692449 DOI: 10.1111/jgs.12281] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
A major misperception concerning postmenopausal hormone replacement therapy (HRT) is that the associated risks are large in magnitude and unique to HRT, but over the past 10 years, sufficient data have accumulated so that the magnitude and perspective of risks associated with the primary coronary heart disease prevention therapies of statins, aspirin, and postmenopausal HRT have become more fully defined. Review of randomized controlled trials indicates that the risks of primary prevention therapies and other medications commonly used in women's health are of similar type and magnitude, with the majority of these risks categorized as rare to infrequent (<1 event per 100 treated women). Evidence-based data show that the risks of postmenopausal HRT are predominantly rare (<1 event per 1,000 treated women) and certainly no greater than other commonly used medications in women's health, including statins and aspirin. These risks, including breast cancer, stroke, and venous thromboembolism are common across medications and are rare, and even rarer when HRT is initiated in women younger than 60 or who are less than 10 years since menopause. In Part 1 of this series, the sex-specificity of statins and aspirin and timing of initiation of HRT as modifiers of efficacy in women were reviewed. Herein, the comparative risks of primary prevention therapies in women are discussed.
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Affiliation(s)
- Howard N Hodis
- Atherosclerosis Research Unit, University of Southern California, Los Angeles, California 90033, USA.
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