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Su C, Hou Y, Xu J, Xu Z, Zhou M, Ke A, Li H, Xu J, Brendel M, Maasch JRMA, Bai Z, Zhang H, Zhu Y, Cincotta MC, Shi X, Henchcliffe C, Leverenz JB, Cummings J, Okun MS, Bian J, Cheng F, Wang F. Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data. NPJ Digit Med 2024; 7:184. [PMID: 38982243 PMCID: PMC11233682 DOI: 10.1038/s41746-024-01175-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Accepted: 06/21/2024] [Indexed: 07/11/2024] Open
Abstract
Parkinson's disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals' phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.
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Grants
- R21 AG083003 NIA NIH HHS
- R01 AG082118 NIA NIH HHS
- R56 AG074001 NIA NIH HHS
- R01AG076448 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- RF1AG072449 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- MJFF-023081 Michael J. Fox Foundation for Parkinson's Research (Michael J. Fox Foundation)
- R01AG080991 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- P30 AG072959 NIA NIH HHS
- 3R01AG066707-01S1 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R21AG083003 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R01AG066707 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R35 AG071476 NIA NIH HHS
- RF1 AG082211 NIA NIH HHS
- R56AG074001 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R01AG082118 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R25 AG083721 NIA NIH HHS
- RF1AG082211 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- U01 NS093334 NINDS NIH HHS
- AG083721-01 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- RF1NS133812 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- P20GM109025 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- RF1 NS133812 NINDS NIH HHS
- R35AG71476 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- U01 AG073323 NIA NIH HHS
- R01 AG066707 NIA NIH HHS
- R01AG053798 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R01AG076234 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R01 AG076448 NIA NIH HHS
- R01 AG080991 NIA NIH HHS
- R01 AG076234 NIA NIH HHS
- U01NS093334 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- P20 GM109025 NIGMS NIH HHS
- P30AG072959 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- RF1 AG072449 NIA NIH HHS
- R01 AG053798 NIA NIH HHS
- 3R01AG066707-02S1 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- U01AG073323 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- ALZDISCOVERY-1051936 Alzheimer's Association
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Affiliation(s)
- Chang Su
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Yu Hou
- Department of Surgery, University of Minnesota, Minneapolis, MN, USA
| | - Jielin Xu
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Zhenxing Xu
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Manqi Zhou
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Alison Ke
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Haoyang Li
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Jie Xu
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Matthew Brendel
- Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Jacqueline R M A Maasch
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Department of Computer Science, Cornell Tech, Cornell University, New York, NY, USA
| | - Zilong Bai
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Haotan Zhang
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Yingying Zhu
- Department of Computer Science, University of Texas at Arlington, Arlington, TX, USA
| | - Molly C Cincotta
- Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA
| | - Xinghua Shi
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Claire Henchcliffe
- Department of Neurology, University of California Irvine, Irvine, CA, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Michael S Okun
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Fei Wang
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA.
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA.
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Chavarría-Elizondo P, Del Río-Torné C, Maturana-Quijada P, Martínez-Zalacaín I, Juaneda A, Del Cerro I, Guinea-Izquierdo A, Gascón-Bayarri J, Reñé-Ramírez R, Urretavizcaya M, Ferrer I, Menchón JM, Soria V, Soriano-Mas C. Altered activation of the dorsal anterior cingulate cortex during oddball performance in individuals at risk for Alzheimer's disease. SPANISH JOURNAL OF PSYCHIATRY AND MENTAL HEALTH 2024:S2950-2853(24)00038-3. [PMID: 38992346 DOI: 10.1016/j.sjpmh.2024.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 06/03/2024] [Accepted: 07/02/2024] [Indexed: 07/13/2024]
Abstract
INTRODUCTION The neural mechanisms underlying neurodegenerative disorders in the elderly remain elusive, despite extensive neuroimaging research in recent decades. Amnestic type mild cognitive impairment (aMCI) and late-life major depressive disorder (MDD) are two such conditions characterized by intersecting cognitive and affective symptomatology, and they are at a higher risk for Alzheimer's disease. MATERIALS AND METHODS This study analyzed the neural underpinnings of cognitive and depressive symptoms in a cohort comprising 12 aMCI subjects, 24 late-life MDD patients, and 26 healthy controls (HCs). Participants underwent a detailed neuropsychological assessment and completed a visual attentional oddball task during functional magnetic resonance imaging (fMRI), with evaluations at baseline and at 2-year follow-up. RESULTS Initial findings showed that aMCI subjects had reduced dACC activation during oddball (target) stimulus detection, a pattern that persisted in longitudinal analyses and correlated with cognitive functioning measures. For HCs, subsequent dACC activation was linked to depression scores. Furthermore, in the affective-cognitive altered groups, later dACC activation correlated with oddball and memory performance. CONCLUSIONS These findings enhance our comprehension of the neurobiological basis of cognitive and depressive disturbances in aging, indicating that dACC activation in response to a visual attentional oddball task could serve as a neural marker for assessing cognitive impairment and depression in conditions predisposing to Alzheimer's disease.
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Affiliation(s)
- Pamela Chavarría-Elizondo
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Department of Clinical Sciences, School of Medicine, University of Barcelona, L'Hospitalet de Llobregat, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Madrid, Spain
| | - Carla Del Río-Torné
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Department of Clinical Sciences, School of Medicine, University of Barcelona, L'Hospitalet de Llobregat, Spain
| | - Pablo Maturana-Quijada
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Department of Clinical Sciences, School of Medicine, University of Barcelona, L'Hospitalet de Llobregat, Spain
| | | | - Asier Juaneda
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain
| | - Inés Del Cerro
- Department of Psychology, Medical School, Catholic University of Murcia, Murcia, Spain; Worldwide Clinical Trials, Madrid, Spain
| | - Andrés Guinea-Izquierdo
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain
| | - Jordi Gascón-Bayarri
- Dementia Diagnostic and Treatment Unit, Department of Neurology, Bellvitge University Hospital, Barcelona, Spain
| | - Ramón Reñé-Ramírez
- Dementia Diagnostic and Treatment Unit, Department of Neurology, Bellvitge University Hospital, Barcelona, Spain
| | - Mikel Urretavizcaya
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Department of Clinical Sciences, School of Medicine, University of Barcelona, L'Hospitalet de Llobregat, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Madrid, Spain; Department of Psychiatry, Bellvitge University Hospital, Barcelona, Spain
| | - Isidre Ferrer
- Department of Pathology and Experimental Therapeutics, Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Bellvitge Biomedical Research Institute-IDIBELL, Department of Pathologic Anatomy, Bellvitge University Hospital, Barcelona, Spain; Network Center for Biomedical Research on Neurodegenerative Diseases (CIBERNED), Barcelona, Spain
| | - José M Menchón
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Department of Clinical Sciences, School of Medicine, University of Barcelona, L'Hospitalet de Llobregat, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Madrid, Spain
| | - Virginia Soria
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Madrid, Spain; Department of Mental Health, Parc Taulí University Hospital, Sabadell, Barcelona, Spain; Department of Psychiatry and Forensic Medicine, School of Medicine, Universitat Autònoma de Barcelona, Bellaterra, Spain.
| | - Carles Soriano-Mas
- Psychiatry and Mental Health Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Madrid, Spain; Department of Social Psychology and Quantitative Psychology, Institute of Neurosciences, University of Barcelona, Barcelona, Spain.
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Nguyen S, McEvoy LK, Espeland MA, Whitsel EA, Lu A, Horvath S, Manson JE, Rapp SR, Shadyab AH. Associations of Epigenetic Age Estimators With Cognitive Function Trajectories in the Women's Health Initiative Memory Study. Neurology 2024; 103:e209534. [PMID: 38857479 PMCID: PMC11226313 DOI: 10.1212/wnl.0000000000209534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 04/05/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Epigenetic age estimators indicating faster/slower biological aging vs chronological age independently associate with several age-related outcomes; however, longitudinal associations with cognitive function are understudied. We examined associations of epigenetic age estimators with cognitive function measured annually. METHODS This longitudinal study consisted of older women enrolled in the Women's Health Initiative Memory Study with DNA methylation (DNAm) collected at baseline (1995-1998) from 3 ancillary studies and were followed up to 13 years. Global cognitive function was measured annually by Modified Mini-Mental State Examination (3MS; baseline-2007) and by modified Telephone Interview for Cognitive Status (TICS-m, 2008-2021). We calculated 5 epigenetic age estimators: extrinsic AgeAccel, intrinsic AgeAccel, AgeAccelPheno, AgeAccelGrim2, Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE), and AgeAccelGrim2 components (DNA-based plasma protein surrogates). We estimated longitudinal epigenetic age estimator-cognitive function associations using linear mixed-effects models containing age, education, race or ethnicity, and subsequently alcohol, smoking, body mass index, and comorbidities. We examined effect modification by APOE ε4 carriage. RESULTS A total of 795 participants were enrolled. The mean baseline age was 70.8 ± 4 years (10.7% Black, 3.9% Hispanic or Latina, 85.4% White), A 1-SD (0.12) increment in DunedinPACE associated with faster annual declines in TICS-m scores in minimally adjusted (β = -0.118, 95% CI -0.202 to -0.034; p = 0.0006) and fully adjusted (β = -0.123, 95% CI -0.211 to -0.036; p = 0.006) models. AgeAccelPheno associated with faster annual declines in TICS-m with minimal adjustment (β = -0.091, 95% CI -0.176 to -0.006; p = 0.035) but not with full adjustment. No other epigenetic age estimators associated with changes in 3MS or TICS-m. Higher values of DNAm-based surrogates of growth differentiation factor 15, beta-2 microglobulin, Cystatin C, tissue inhibitor metalloproteinase 1, and adrenomedullin associated with faster annual declines in 3MS and TICS-m. Higher DNAm log A1c associated with faster annual declines in TICS-m only. DunedinPACE associated with faster annual declines in 3MS among APOE ε4 carriers but not among noncarriers (p-interaction = 0.020). DISCUSSION Higher DunedinPACE associated with faster declines in TICS-m and 3MS scores among APOE ε4 carriers. DunedinPACE may help identify older women at risk of future cognitive decline. Limitations include the ancillary studies that collected epigenetic data not designed to study epigenetics and cognitive function. We examined epigenetic age estimators with global cognitive function and not specific cognitive domains. Findings may not generalize to men and more diverse populations.
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Affiliation(s)
- Steve Nguyen
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Linda K McEvoy
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Mark A Espeland
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Eric A Whitsel
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Ake Lu
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Steve Horvath
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Joann E Manson
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Stephen R Rapp
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Aladdin H Shadyab
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
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Du Y, Niu J, Xing Y, Li B, Calhoun VD. Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade. Schizophr Bull 2024:sbae110. [PMID: 38982882 DOI: 10.1093/schbul/sbae110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years. STUDY DESIGN The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade. STUDY RESULTS Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders. CONCLUSIONS We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.
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Affiliation(s)
- Yuhui Du
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Ju Niu
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Ying Xing
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Bang Li
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Vince D Calhoun
- The Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, 30303, GA, USA
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Huang SS, Huang CH, Hsu NT, Ong HN, Lin JJ, Wu YW, Chen WT, Chen WJ, Chang WT, Tsai MS. Application of Phosphorylated Tau for Predicting Outcomes Among Sudden Cardiac Arrest Survivors. Neurocrit Care 2024:10.1007/s12028-024-02055-6. [PMID: 38982004 DOI: 10.1007/s12028-024-02055-6] [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: 03/19/2024] [Accepted: 06/21/2024] [Indexed: 07/11/2024]
Abstract
BACKGROUND Phosphorylated Tau (p-Tau), an early biomarker of neuronal damage, has emerged as a promising candidate for predicting neurological outcomes in cardiac arrest (CA) survivors. Despite its potential, the correlation of p-Tau with other clinical indicators remains underexplored. This study assesses the predictive capability of p-Tau and its effectiveness when used in conjunction with other predictors. METHODS In this single-center retrospective study, 230 CA survivors had plasma and brain computed tomography scans collected within 24 h after the return of spontaneous circulation (ROSC) from January 2016 to June 2023. The patients with prearrest Cerebral Performance Category scores ≥ 3 were excluded (n = 33). The neurological outcomes at discharge with Cerebral Performance Category scores 1-2 indicated favorable outcomes. Plasma p-Tau levels were measured using an enzyme-linked immunosorbent assay, diastolic blood pressure (DBP) was recorded after ROSC, and the gray-to-white matter ratio (GWR) was calculated from brain computed tomography scans within 24 h after ROSC. RESULTS Of 197 patients enrolled in the study, 54 (27.4%) had favorable outcomes. Regression analysis showed that higher p-Tau levels correlated with unfavorable neurological outcomes. The levels of p-Tau were significantly correlated with DBP and GWR. For p-Tau to differentiate between neurological outcomes, an optimal cutoff of 456 pg/mL yielded an area under the receiver operating characteristic curve of 0.71. Combining p-Tau, GWR, and DBP improved predictive accuracy (area under the receiver operating characteristic curve = 0.80 vs. 0.71, p = 0.008). CONCLUSIONS Plasma p-Tau levels measured within 24 h following ROSC, particularly when combined with GWR and DBP, may serve as a promising biomarker of neurological outcomes in CA survivors, with higher levels predicting unfavorable outcomes.
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Affiliation(s)
- Sih-Shiang Huang
- Department of Emergency Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan
| | - Chien-Hua Huang
- Department of Emergency Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan
| | | | - Hooi-Nee Ong
- Department of Emergency Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan
| | - Jr-Jiun Lin
- Department of Emergency Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan
| | | | - Wei-Ting Chen
- Department of Emergency Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan
| | - Wen-Jone Chen
- Department of Emergency Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan
- Cardiology Division, Department of Internal Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan
- Department of Internal Medicine, Min-Shen General Hospital, Taoyuan, Taiwan
| | - Wei-Tien Chang
- Department of Emergency Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan
| | - Min-Shan Tsai
- Department of Emergency Medicine, National Taiwan University Medical College and Hospital, Taipei, Taiwan.
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Shi H, Mirzaei N, Koronyo Y, Davis MR, Robinson E, Braun GM, Jallow O, Rentsendorj A, Ramanujan VK, Fert-Bober J, Kramerov AA, Ljubimov AV, Schneider LS, Tourtellotte WG, Hawes D, Schneider JA, Black KL, Kayed R, Selenica MLB, Lee DC, Fuchs DT, Koronyo-Hamaoui M. Identification of retinal oligomeric, citrullinated, and other tau isoforms in early and advanced AD and relations to disease status. Acta Neuropathol 2024; 148:3. [PMID: 38980423 PMCID: PMC11233395 DOI: 10.1007/s00401-024-02760-8] [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: 02/29/2024] [Revised: 06/07/2024] [Accepted: 06/26/2024] [Indexed: 07/10/2024]
Abstract
This study investigates various pathological tau isoforms in the retina of individuals with early and advanced Alzheimer's disease (AD), exploring their connection with disease status. Retinal cross-sections from predefined superior-temporal and inferior-temporal subregions and corresponding brains from neuropathologically confirmed AD patients with a clinical diagnosis of either mild cognitive impairment (MCI) or dementia (n = 45) were compared with retinas from age- and sex-matched individuals with normal cognition (n = 30) and non-AD dementia (n = 4). Retinal tau isoforms, including tau tangles, paired helical filament of tau (PHF-tau), oligomeric-tau (Oligo-tau), hyperphosphorylated-tau (p-tau), and citrullinated-tau (Cit-tau), were stereologically analyzed by immunohistochemistry and Nanostring GeoMx digital spatial profiling, and correlated with clinical and neuropathological outcomes. Our data indicated significant increases in various AD-related pretangle tau isoforms, especially p-tau (AT8, 2.9-fold, pS396-tau, 2.6-fold), Cit-tau at arginine residue 209 (CitR209-tau; 4.1-fold), and Oligo-tau (T22+, 9.2-fold), as well as pretangle and mature tau tangle forms like MC-1-positive (1.8-fold) and PHF-tau (2.3-fold), in AD compared to control retinas. MCI retinas also exhibited substantial increases in Oligo-tau (5.2-fold), CitR209-tau (3.5-fold), and pS396-tau (2.2-fold). Nanostring GeoMx analysis confirmed elevated retinal p-tau at epitopes: Ser214 (2.3-fold), Ser396 (2.6-fold), Ser404 (2.4-fold), and Thr231 (1.8-fold), particularly in MCI patients. Strong associations were found between retinal tau isoforms versus brain pathology and cognitive status: a) retinal Oligo-tau vs. Braak stage, neurofibrillary tangles (NFTs), and CDR cognitive scores (ρ = 0.63-0.71), b) retinal PHF-tau vs. neuropil threads (NTs) and ABC scores (ρ = 0.69-0.71), and c) retinal pS396-tau vs. NTs, NFTs, and ABC scores (ρ = 0.67-0.74). Notably, retinal Oligo-tau strongly correlated with retinal Aβ42 and arterial Aβ40 forms (r = 0.76-0.86). Overall, this study identifies and quantifies diverse retinal tau isoforms in MCI and AD patients, underscoring their link to brain pathology and cognition. These findings advocate for further exploration of retinal tauopathy biomarkers to facilitate AD detection and monitoring via noninvasive retinal imaging.
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Affiliation(s)
- Haoshen Shi
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Nazanin Mirzaei
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Yosef Koronyo
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Miyah R Davis
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Edward Robinson
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Gila M Braun
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Ousman Jallow
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Altan Rentsendorj
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - V Krishnan Ramanujan
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Justyna Fert-Bober
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Andrei A Kramerov
- Eye Program, Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Division of Applied Cell Biology and Physiology, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alexander V Ljubimov
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
- Eye Program, Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Division of Applied Cell Biology and Physiology, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Lon S Schneider
- Departments of Psychiatry and the Behavioral Sciences and Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Warren G Tourtellotte
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Division of Applied Cell Biology and Physiology, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA
| | - Debra Hawes
- Department of Pathology Program in Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Julie A Schneider
- Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Keith L Black
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Rakez Kayed
- Mitchell Center for Neurodegenerative Diseases, University of Texas Medical Branch, Galveston, TX, USA
- Departments of Neurology, Neuroscience, and Cell Biology, University of Texas Medical Branch, Galveston, TX, USA
| | - Maj-Linda B Selenica
- Sanders-Brown Center On Aging, Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
- Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA
| | - Daniel C Lee
- Sanders-Brown Center On Aging, Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
- Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA
| | - Dieu-Trang Fuchs
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA
| | - Maya Koronyo-Hamaoui
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., A6212, Los Angeles, CA, 90048, USA.
- Division of Applied Cell Biology and Physiology, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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Ogurcakova V, Kajsova M, Marusic P, Amlerova J. Social cognition in Idiopathic generalised epilepsies. Behav Brain Res 2024; 469:115044. [PMID: 38734033 DOI: 10.1016/j.bbr.2024.115044] [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: 01/24/2024] [Revised: 04/27/2024] [Accepted: 05/06/2024] [Indexed: 05/13/2024]
Abstract
Social cognition is a set of mental skills necessary to create satisfactory interpersonal relationships and feel a sense of belonging to a social group. Its deficits significantly reduce the quality of life in people with epilepsy. Studies on social cognition and its impairments focus predominantly on people with focal epilepsies. Idiopathic generalised epilepsies are a group of diseases that share similar clinical, prognostic and electrographic characteristics. Despite their typically normal intelligence, people with Idiopathic generalised epilepsies can suffer from learning disabilities and executive dysfunctions. Current studies also suggest social cognition impairments, but their results are inconsistent. This review offers the latest knowledge of social cognition in adults with Idiopathic generalised epilepsies. In addition, we provide an overview of the most frequently used assessment methods. We explain possible reasons for different outcomes and discuss future research perspectives.
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Affiliation(s)
- Viktoria Ogurcakova
- Department of Neurology, Second Faculty of Medicine and Motol University Hospital, Charles University, ERN EpiCARE, Prague, Czech Republic.
| | - Michaela Kajsova
- Department of Neurology, Second Faculty of Medicine and Motol University Hospital, Charles University, ERN EpiCARE, Prague, Czech Republic
| | - Petr Marusic
- Department of Neurology, Second Faculty of Medicine and Motol University Hospital, Charles University, ERN EpiCARE, Prague, Czech Republic
| | - Jana Amlerova
- Department of Neurology, Second Faculty of Medicine and Motol University Hospital, Charles University, ERN EpiCARE, Prague, Czech Republic
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208
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Wugalter KA, Schroeder RA, Thurston RC, Wu M, Aizenstein HJ, Cohen AD, Kamboh MI, Karikari TK, Derby CA, Maki PM. Associations of endogenous estrogens, plasma Alzheimer's disease biomarkers, and APOE4 carrier status on regional brain volumes in postmenopausal women. Front Aging Neurosci 2024; 16:1426070. [PMID: 39044806 PMCID: PMC11263297 DOI: 10.3389/fnagi.2024.1426070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 06/18/2024] [Indexed: 07/25/2024] Open
Abstract
Background Women carrying the APOE4 allele are at greater risk of developing Alzheimer's disease (AD) from ages 65-75 years compared to men. To better understand the elevated risk conferred by APOE4 carrier status among midlife women, we investigated the separate and interactive associations of endogenous estrogens, plasma AD biomarkers, and APOE4 carrier status on regional brain volumes in a sample of late midlife postmenopausal women. Methods Participants were enrolled in MsBrain, a cohort study of postmenopausal women (n = 171, mean age = 59.4 years, mean MoCA score = 26.9; race = 83.2% white, APOE4 carriers = 40). Serum estrone (E1) and estradiol (E2) levels were assessed using liquid chromatography-tandem mass spectrometry. APOE genotype was determined using TaqMan SNP genotyping assays. Plasma AD biomarkers were measured using single molecule array technology. Cortical volume was measured and segmented by FreeSurfer software using individual T1w MPRAGE images. Multiple linear regression models were conducted to determine whether separate and interactive associations between endogenous estrogen levels, plasma AD biomarkers (Aβ42/Aβ40, Aβ42/p-tau181), and APOE4 carrier status predict regional brain volume (21 regions per hemisphere, selected a priori); and, whether significant interactive associations between estrogens and AD biomarkers on brain volume differed by APOE4 carrier status. Results There was no main effect of APOE4 carrier status on regional brain volumes, endogenous estrogen levels, or plasma AD biomarkers. Estrogens did not associate with regional brain volumes, except for positive associations with left caudal middle frontal gyrus and fusiform volumes. The interactive association of estrogens and APOE4 carrier status on brain volume was not significant for any region. The interactive association of estrogens and plasma AD biomarkers predicted brain volume of several regions. Higher E1 and E2 were more strongly associated with greater regional brain volumes among women with a poorer AD biomarker profile (lower Aβ42/40, lower Aβ42/p-tau181 ratios). In APOE4-stratified analyses, these interactions were driven by non-APOE4 carriers. Conclusion We demonstrate that the brain volumes of postmenopausal women with poorer AD biomarker profiles benefit most from higher endogenous estrogen levels. These findings are driven by non-APOE4 carriers, suggesting that APOE4 carriers may be insensitive to the favorable effects of estrogens on brain volume in the postmenopause.
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Affiliation(s)
- Katrina A. Wugalter
- Department of Psychology, University of Illinois Chicago, Chicago, IL, United States
| | - Rachel A. Schroeder
- Department of Psychology, University of Illinois Chicago, Chicago, IL, United States
| | - Rebecca C. Thurston
- Departments of Psychiatry, Epidemiology, Psychology, and Clinical and Translational Science, University of Pittsburgh, Pittsburgh, PA, United States
| | - Minjie Wu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Ann D. Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - M. Ilyas Kamboh
- Departments of Psychiatry, Human Genetics, and Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Thomas K. Karikari
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Carol A. Derby
- The Saul R. Korey Department of Neurology, Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Pauline M. Maki
- Departments of Psychiatry, Psychology and Obstetrics & Gynecology, University of Illinois Chicago, Chicago, IL, United States
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209
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Tinelli M, Morton T, Bray J, Henderson C, Frost F, Evans S. Using choice modelling to inform service sustainability for dementia Meeting Centres for people living with dementia in the UK. Aging Ment Health 2024:1-12. [PMID: 38978482 DOI: 10.1080/13607863.2024.2375609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 06/24/2024] [Indexed: 07/10/2024]
Abstract
OBJECTIVES This study explores the preferences and willingness-to-pay (WTP) of carers for Meeting Centres (MCs) attributes in assisting individuals with mild to moderate dementia. METHOD Preferences from 108 carers, gathered through UK-wide MC networks, were collected using a Discrete Choice Experiment survey. The survey incorporated attributes derived from evidence synthesis and lay consultation. A regression model estimated preference weights and marginal WTP for a change in attributes one a time within the MC support 'package.' RESULTS Carers preferred MCs offering a balanced mix of practical activities and emotional support, along with flexibility without booking requirements and low costs. Social opportunities and the frequency of the meeting were not prioritised. Respondents expressed a WTP of £43 to stay with 'My MC,' the preferred option, compared to transitioning to an alternative in-person MC, all else being equal. Various factors, including attendance modality, the relationship with the supported person, age, and gender, influenced carers' choices. CONCLUSION These findings offer valuable insights into carers' preferences, priorities, and WTP within MC support for those with mild to moderate dementia. Understanding these factors can guide the implementation and sustainability of MCs, ensuring alignment with carers' needs and preferences and, ultimately, enhancing support for individuals with dementia.
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Affiliation(s)
- Michela Tinelli
- Care Policy Evaluation Centre (CPEC), the London School of Economics and Political Science, Houghton St, London, UK
| | - Thomas Morton
- The Association for Dementia Studies, St Johns Campus, University of Worcester, Worcester, UK
| | - Jennifer Bray
- The Association for Dementia Studies, St Johns Campus, University of Worcester, Worcester, UK
| | - Catherine Henderson
- Care Policy Evaluation Centre (CPEC), the London School of Economics and Political Science, Houghton St, London, UK
| | - Faith Frost
- The Association for Dementia Studies, St Johns Campus, University of Worcester, Worcester, UK
| | - Shirley Evans
- The Association for Dementia Studies, St Johns Campus, University of Worcester, Worcester, UK
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210
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Penalva YCM, Paschkowsky S, Recinto SJ, Duchesne A, Hammond T, Spiegler P, Jansen G, Levet C, Charron F, Freeman M, McKinney RA, Trempe JF, Munter LM. Eta-secretase-like processing of the amyloid precursor protein (APP) by the rhomboid protease RHBDL4. J Biol Chem 2024:107541. [PMID: 38992438 DOI: 10.1016/j.jbc.2024.107541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 06/17/2024] [Accepted: 06/20/2024] [Indexed: 07/13/2024] Open
Abstract
The amyloid precursor protein (APP) is a key protein in Alzheimer's disease synthesized in the endoplasmic reticulum (ER) and translocated to the plasma membrane where it undergoes proteolytic cleavages by several proteases. Conversely to other known proteases, we previously elucidated rhomboid protease RHBDL4 as a novel APP processing enzyme where several cleavages likely occur already in the ER. Interestingly, the pattern of RHBDL4-derived large APP C-terminal fragments resemble those generated by the η-secretase or MT5-MMP, which was described to generate so called Aη fragments. The similarity in large APP C-terminal fragments between both proteases raised the question whether RHBDL4 may contribute to η-secretase activity and Aη-like fragments. Here, we identified two cleavage sites of RHBDL4 in APP by mass spectrometry, which, intriguingly, lie in close proximity to the MT5-MMP cleavage sites. Indeed, we observed that RHBDL4 generates Aη-like fragments in vitro without contributions of α-, β-, or γ-secretases. Such Aη-like fragments are likely generated in the ER since RHBDL4-derived APP-C-terminal fragments do not reach the cell surface. Inherited, familial APP mutations appear to not affect this processing pathway. In RHBDL4 knockout mice, we observed increased cerebral full length APP in comparison to wild type (WT) in support of RHBDL4 being a physiologically relevant protease for APP. Furthermore, we found secreted Aη fragments in dissociated mixed cortical cultures from WT mice, however significantly less Aη fragments in RHBDL4 knockout cultures. Our data underscores that RHBDL4 contributes to η-secretease-like processing of APP and that RHBDL4 is a physiologically relevant protease for APP.
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Affiliation(s)
- Ylauna Christine Megane Penalva
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada H3A 2B4; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada
| | - Sandra Paschkowsky
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada
| | - Sherilyn Junelle Recinto
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada H3A 2B4; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada
| | - Anthony Duchesne
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada
| | - Thomas Hammond
- School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada
| | - Pascal Spiegler
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada
| | - Gregor Jansen
- School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada; Department of Biochemistry, McGill University, McIntyre Building, Montreal H3G 0B1, Quebec, Canada
| | - Clemence Levet
- Sir William Dunn School of Pathology, South Parks Road, Oxford OX1 3RE, UK
| | - François Charron
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada
| | - Matthew Freeman
- Sir William Dunn School of Pathology, South Parks Road, Oxford OX1 3RE, UK
| | - R Anne McKinney
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada
| | - Jean-Francois Trempe
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada; Centre de Recherche en Biologie Structurale (CRBS), McGill University, Montréal H3G 0B1, Québec, Canada
| | - Lisa Marie Munter
- Department of Pharmacology and Therapeutics, McGill University, Bellini Life Sciences, Complex, Montreal H3G 0B1, Quebec, Canada; School of Biomedical Sciences (SBMS), McGill University, Bellini Life Sciences Complex, Montreal H3G 0B1, Quebec, Canada; Centre de Recherche en Biologie Structurale (CRBS), McGill University, Montréal H3G 0B1, Québec, Canada.
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Cordeiro A, Gomes C, Bicker J, Fortuna A. Aging and cognitive resilience: Molecular mechanisms as new potential therapeutic targets. Drug Discov Today 2024; 29:104093. [PMID: 38992420 DOI: 10.1016/j.drudis.2024.104093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 06/25/2024] [Accepted: 07/04/2024] [Indexed: 07/13/2024]
Abstract
As the global population ages, the need to prolong lifespan and healthspan becomes increasingly imperative. Understanding the molecular determinants underlying cognitive resilience, together with changes during aging and the (epi)genetic factors that predispose an individual to decreased cognitive resilience, open avenues for researching novel therapies. This review provides a critical and timely appraisal of the molecular mechanisms underlying cognitive resilience, framed within a critical analysis of emerging therapeutic strategies to mitigate age-related cognitive decline. Significant insights from both animals and human subjects are discussed herein, directed either toward active pharmaceutical ingredients (drug repositioning or macromolecules), or, alternatively, advanced cellular therapies.
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Affiliation(s)
- Ana Cordeiro
- Laboratory of Pharmacology, Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal
| | - Catarina Gomes
- Laboratory of Pharmacology, Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal; CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal
| | - Joana Bicker
- Laboratory of Pharmacology, Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal; CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal
| | - Ana Fortuna
- Laboratory of Pharmacology, Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal; CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal.
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212
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Chen YH, Ren CY, Yu C. Causal relationship between Alzheimer's disease and unstable angina: a bidirectional Mendelian randomization analysis. Front Psychiatry 2024; 15:1435394. [PMID: 39045549 PMCID: PMC11263098 DOI: 10.3389/fpsyt.2024.1435394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 06/24/2024] [Indexed: 07/25/2024] Open
Abstract
Background Research from observational studies has demonstrated a link between Alzheimer's disease (AD) and a higher risk of cardiovascular disease (CVD). Uncertainty surrounds the exact genetic cause of AD and coronary heart disease, particularly unstable angina (UA). Mendelian randomization (MR) analysis was used to examine the causal genetic link between AD and UA to evaluate the impact of AD on UA. Methods The purpose of the bidirectional MR analysis was to investigate the link between exposure and illness causation. Genetic instrumental variables for AD were obtained from European populations using genome-wide association studies (GWAS). The primary causal conclusions were obtained using the inverse variance weighted approach (IVW), and other sensitivity analysis techniques were employed. Sensitivity analyses were carried out to evaluate heterogeneity and horizontal pleiotropy to guarantee accurate MR results. Results An elevated risk of UA was linked to genetically predicted AD (IVW: OR=3.439, 95% CI: 1.565-7.555, P=0.002). A substantial genetic relationship between UA and the risk of AD was not supported by any evidence in the reverse study (IVW: OR=0.998, 95% CI: 0.995-1.001, P=0.190). Various MR techniques produced consistent results. Sensitivity analysis revealed no discernible heterogeneity or horizontal pleiotropy. Conclusions One risk factor for UA that we found in our bidirectional Mendelian randomization trial was AD. This highlights the necessity of researching the underlying molecular mechanisms linked to AD and UA as well as the possibility of creating individualized treatment plans based on genetic data.
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Affiliation(s)
- Yu-hang Chen
- Department of Operations Management, Chongqing Mental Health Center, Chongqing, China
| | - Cong-ying Ren
- Department of Hospital Infection Control, Chongqing Mental Health Center, Chongqing, China
| | - Cao Yu
- Department of Cardiothoracic Surgery, Chongqing University Jiangjin Hospital, Chongqing, China
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Castillo-Vazquez SK, Massieu L, Rincón-Heredia R, García-delaTorre P, Quiroz-Baez R, Gomez-Verjan JC, Rivero-Segura NA. Glutamatergic Neurotransmission in Aging and Neurodegenerative Diseases: A Potential Target to Improve Cognitive Impairment in Aging. Arch Med Res 2024; 55:103039. [PMID: 38981341 DOI: 10.1016/j.arcmed.2024.103039] [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: 01/11/2024] [Revised: 06/10/2024] [Accepted: 06/26/2024] [Indexed: 07/11/2024]
Abstract
Aging is characterized by the decline in many of the individual's capabilities. It has been recognized that the brain undergoes structural and functional changes during aging that are occasionally associated with the development of neurodegenerative diseases. In this sense, altered glutamatergic neurotransmission, which involves the release, binding, reuptake, and degradation of glutamate (Glu) in the brain, has been widely studied in physiological and pathophysiological aging. In particular, changes in glutamatergic neurotransmission are exacerbated during neurodegenerative diseases and are associated with cognitive impairment, characterized by difficulties in memory, learning, concentration, and decision-making. Thus, in the present manuscript, we aim to highlight the relevance of glutamatergic neurotransmission during cognitive impairment to develop novel strategies to prevent, ameliorate, or delay cognitive decline. To achieve this goal, we provide a comprehensive review of the changes reported in glutamatergic neurotransmission components, such as Glu transporters and receptors during physiological aging and in the most studied neurodegenerative diseases. Finally, we describe the current therapeutic strategies developed to target glutamatergic neurotransmission.
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Affiliation(s)
- Selma Karime Castillo-Vazquez
- Dirección de Investigación, Instituto Nacional de Geriatría, Mexico City, Mexico; Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Lourdes Massieu
- Departamento de Neuropatología Molecular, División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Ruth Rincón-Heredia
- Unidad de Imagenología, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Ciudad Universitaria, Mexico City, Mexico
| | - Paola García-delaTorre
- 4 Unidad de Investigación Epidemiológica y en Servicios de Salud, Área de Envejecimiento, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City Mexico
| | - Ricardo Quiroz-Baez
- Dirección de Investigación, Instituto Nacional de Geriatría, Mexico City, Mexico
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214
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Li A, Zhao R, Zhang M, Sun P, Cai Y, Zhu L, Kung H, Han Y, Wang X, Guo T. [ 18F]-D3FSP β-amyloid PET imaging in older adults and alzheimer's disease. Eur J Nucl Med Mol Imaging 2024:10.1007/s00259-024-06835-2. [PMID: 38976036 DOI: 10.1007/s00259-024-06835-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 07/04/2024] [Indexed: 07/09/2024]
Abstract
PURPOSE [18F]-D3FSP is a new β-amyloid (Aβ) PET imaging tracer designed to decrease nonspecific signals in the brain by reducing the formation of the N-demethylated product. However, its optimal reference region for calculating the standardized uptake value ratio (SUVR) and its relation to the well-established biomarkers of Alzheimer's disease (AD) are still unclear. METHODS We recruited 203 participants from the Greater Bay Area Healthy Aging Brain Study (GHABS) to undergo [18F]-D3FSP Aβ PET imaging. We analyzed plasma Aβ42/Aβ40, p-Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) using the Simoa platform. We compared the standardized uptake value (SUV) of five reference regions (cerebellum, cerebellum cortex, brainstem/PONs, white matter, composite of the four regions above) and AD typical cortical region (COMPOSITE) SUVR among different clinical groups. The association of D3FSP SUVR with plasma biomarkers, imaging biomarkers, and cognition was also investigated. RESULTS Brainstem/PONs SUV showed the lowest fluctuation across diagnostic groups, and COMPOSITE D3FSP SUVR had an enormous effect distinguishing cognitively impaired (CI) individuals from cognitively unimpaired (CU) individuals. COMPOSITE SUVR (Referred to brainstem/PONs) was positively correlated with p-Tau181 (p < 0.001), GFAP (p < 0.001), NfL (p = 0.014) in plasma and temporal-metaROI tau deposition (p < 0.001), and negatively related to plasma Aβ42/Aβ40 (p < 0.001), temporal-metaROI cortical thickness (p < 0.01), residual hippocampal volume (p < 0.001) and cognition (p < 0.001). The voxel-wise analysis replicated these findings. CONCLUSION This study suggests brainstem/PONs as an optimal reference region for calculating D3FSP SUVR to quantify cortical Aβ plaques in the brain. [18F]-D3FSP could distinguish CI from CU and strongly correlates with well-established plasma biomarkers, tau PET, neurodegeneration, and cognitive decline. However, future head-to-head comparisons of [18F]-D3FSP PET images with other validated Aβ PET tracers or postmortem results are crucial.
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Affiliation(s)
- Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Ruiyue Zhao
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China
| | - Mingkai Zhang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Pan Sun
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Yue Cai
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Lin Zhu
- Beijing Normal University, Beijing, 100875, China
| | - Hank Kung
- University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ying Han
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China
- National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Xinlu Wang
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China.
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China.
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
- Institute of Biomedical Engineering, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China.
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215
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Faulkner ME, Gong Z, Guo A, Laporte JP, Bae J, Bouhrara M. Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review. J Neurochem 2024. [PMID: 38973579 DOI: 10.1111/jnc.16170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/12/2024] [Accepted: 06/19/2024] [Indexed: 07/09/2024]
Abstract
Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.
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Affiliation(s)
- Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Alex Guo
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Jonghyun Bae
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
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216
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Ye C, Zhang Y, Ran C, Ma T. Recent Progress in Brain Network Models for Medical Applications: A Review. HEALTH DATA SCIENCE 2024; 4:0157. [PMID: 38979037 PMCID: PMC11227951 DOI: 10.34133/hds.0157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 05/28/2024] [Indexed: 07/10/2024]
Abstract
Importance: Pathological perturbations of the brain often spread via connectome to fundamentally alter functional consequences. By integrating multimodal neuroimaging data with mathematical neural mass modeling, brain network models (BNMs) enable to quantitatively characterize aberrant network dynamics underlying multiple neurological and psychiatric disorders. We delved into the advancements of BNM-based medical applications, discussed the prevalent challenges within this field, and provided possible solutions and future directions. Highlights: This paper reviewed the theoretical foundations and current medical applications of computational BNMs. Composed of neural mass models, the BNM framework allows to investigate large-scale brain dynamics behind brain diseases by linking the simulated functional signals to the empirical neurophysiological data, and has shown promise in exploring neuropathological mechanisms, elucidating therapeutic effects, and predicting disease outcome. Despite that several limitations existed, one promising trend of this research field is to precisely guide clinical neuromodulation treatment based on individual BNM simulation. Conclusion: BNM carries the potential to help understand the mechanism underlying how neuropathology affects brain network dynamics, further contributing to decision-making in clinical diagnosis and treatment. Several constraints must be addressed and surmounted to pave the way for its utilization in the clinic.
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Affiliation(s)
- Chenfei Ye
- International Research Institute for Artificial Intelligence,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Yixuan Zhang
- Department of Electronic and Information Engineering,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Chen Ran
- Department of Electronic and Information Engineering,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Ting Ma
- International Research Institute for Artificial Intelligence,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
- Department of Electronic and Information Engineering,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
- Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology,
Harbin Institute of Technology at Shenzhen, China
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217
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Rajendran K, Krishnan UM. Biomarkers in Alzheimer's disease. Clin Chim Acta 2024; 562:119857. [PMID: 38986861 DOI: 10.1016/j.cca.2024.119857] [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: 05/13/2024] [Revised: 07/05/2024] [Accepted: 07/06/2024] [Indexed: 07/12/2024]
Abstract
Alzheimer's disease (AD) is among the most common neurodegenerative disorders. AD is characterized by deposition of neurofibrillary tangles and amyloid plaques, leading to associated secondary pathologies, progressive neurodegeneration, and eventually death. Currently used diagnostics are largely image-based, lack accuracy and do not detect early disease, ie, prior to onset of symptoms, thus limiting treatment options and outcomes. Although biomarkers such as amyloid-β and tau protein in cerebrospinal fluid have gained much attention, these are generally limited to disease progression. Unfortunately, identification of biomarkers for early and accurate diagnosis remains a challenge. As such, body fluids such as sweat, serum, saliva, mucosa, tears, and urine are under investigation as alternative sources for biomarkers that can aid in early disease detection. This review focuses on biomarkers identified through proteomics in various biofluids and their potential for early and accurate diagnosis of AD.
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Affiliation(s)
- Kayalvizhi Rajendran
- Centre for Nanotechnology & Advanced Biomaterials, SASTRA Deemed University, Thanjavur, India; School of Chemical & Biotechnology, SASTRA Deemed University, Thanjavur, India
| | - Uma Maheswari Krishnan
- Centre for Nanotechnology & Advanced Biomaterials, SASTRA Deemed University, Thanjavur, India; School of Arts, Sciences, Humanities, & Education, SASTRA Deemed University, Thanjavur, India.
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218
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Sethi P, Bhaskar R, Singh KK, Gupta S, Han SS, Avinash D, Abomughaid MM, Koul A, Rani B, Ghosh S, Jha NK, Sinha JK. Exploring advancements in early detection of Alzheimer's disease with molecular assays and animal models. Ageing Res Rev 2024; 100:102411. [PMID: 38986845 DOI: 10.1016/j.arr.2024.102411] [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: 06/14/2024] [Revised: 07/04/2024] [Accepted: 07/04/2024] [Indexed: 07/12/2024]
Abstract
Alzheimer's Disease (AD) is a challenging neurodegenerative condition, with overwhelming implications for affected individuals and healthcare systems worldwide. Animal models have played a crucial role in studying AD pathogenesis and testing therapeutic interventions. Remarkably, studies on the genetic factors affecting AD risk, such as APOE and TREM2, have provided valuable insights into disease mechanisms. Early diagnosis has emerged as a crucial factor in effective AD management, as demonstrated by clinical studies emphasizing the benefits of initiating treatment at early stages. Novel diagnostic technologies, including RNA sequencing of microglia, offer promising avenues for early detection and monitoring of AD progression. Therapeutic strategies remain to evolve, with a focus on targeting amyloid beta (Aβ) and tau pathology. Advances in animal models, such as APP-KI mice, and the advancement of anti-Aβ drugs signify progress towards more effective treatments. Therapeutically, the focus has shifted towards intricate approaches targeting multiple pathological pathways simultaneously. Strategies aimed at reducing Aβ plaque accumulation, inhibiting tau hyperphosphorylation, and modulating neuroinflammation are actively being explored, both in preclinical models and clinical trials. While challenges continue in developing validated animal models and translating preclinical findings to clinical success, the continuing efforts in understanding AD at molecular, cellular, and clinical levels offer hope for improved management and eventual prevention of this devastating disease.
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Affiliation(s)
- Paalki Sethi
- GloNeuro, Sector 107, Vishwakarma Road, Noida, Uttar Pradesh 201301, India
| | - Rakesh Bhaskar
- School of Chemical Engineering, Yeungnam University, Gyeonsang 38541, Republic of Korea; Research Institute of Cell Culture, Yeungnam University, Gyeonsang 38541, Republic of Korea
| | - Krishna Kumar Singh
- Symbiosis Centre for Information Technology (SCIT), Rajiv Gandhi InfoTech Park, Hinjawadi, Pune, Maharashtra 411057, India
| | - Saurabh Gupta
- Department of Biotechnology, GLA University, Mathura, Uttar Pradesh, India
| | - Sung Soo Han
- School of Chemical Engineering, Yeungnam University, Gyeonsang 38541, Republic of Korea; Research Institute of Cell Culture, Yeungnam University, Gyeonsang 38541, Republic of Korea
| | - D Avinash
- Center for Global Health Research, Saveetha Medical College, Saveetha Institute of Medical and Technical Sciences, India
| | - Mosleh Mohammad Abomughaid
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, University of Bisha, Bisha 61922, Saudi Arabia
| | - Apurva Koul
- Chandigarh Pharmacy College, Chandigarh Group of Colleges, Jhanjeri, Mohali, Punjab 140307, India
| | - Bindu Rani
- Department of Medicine, National Institute of Medical Sciences, NIMS University, Jaipur, Rajsthan, India
| | - Shampa Ghosh
- GloNeuro, Sector 107, Vishwakarma Road, Noida, Uttar Pradesh 201301, India.
| | - Niraj Kumar Jha
- Centre of Research Impact and Outcome, Chitkara University, Rajpura, Punjab 140401, India; School of Bioengineering & Biosciences, Lovely Professional University, Phagwara 144411, India; Department of Biotechnology, School of Applied & Life Sciences (SALS), Uttaranchal University, Dehradun 248007, India; Department of Biotechnology Engineering and Food Technology, Chandigarh University, Mohali, India.
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219
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Angelopoulou E, Bougea A, Hatzimanolis A, Scarmeas N, Papageorgiou SG. Unraveling the Potential Underlying Mechanisms of Mild Behavioral Impairment: Focusing on Amyloid and Tau Pathology. Cells 2024; 13:1164. [PMID: 38995015 PMCID: PMC11240615 DOI: 10.3390/cells13131164] [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: 05/27/2024] [Revised: 06/21/2024] [Accepted: 06/27/2024] [Indexed: 07/13/2024] Open
Abstract
The emergence of sustained neuropsychiatric symptoms (NPS) among non-demented individuals in later life, defined as mild behavioral impairment (MBI), is linked to a higher risk of cognitive decline. However, the underlying pathophysiological mechanisms remain largely unexplored. A growing body of evidence has shown that MBI is associated with alterations in structural and functional neuroimaging studies, higher genetic predisposition to clinical diagnosis of Alzheimer's disease (AD), as well as amyloid and tau pathology assessed in the blood, cerebrospinal fluid, positron-emission tomography (PET) imaging and neuropathological examination. These findings shed more light on the MBI-related potential neurobiological mechanisms, paving the way for the development of targeted pharmacological approaches. In this review, we aim to discuss the available clinical evidence on the role of amyloid and tau pathology in MBI and the potential underlying pathophysiological mechanisms. Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, disruption of neurotrophic factors, such as the brain-derived neurotrophic factor (BDNF), abnormal neuroinflammatory responses including the kynurenine pathway, dysregulation of transforming growth factor beta (TGF-β1), epigenetic alterations including micro-RNA (miR)-451a and miR-455-3p, synaptic dysfunction, imbalance in neurotransmitters including acetylcholine, dopamine, serotonin, gamma-aminobutyric acid (GABA) and norepinephrine, as well as altered locus coeruleus (LC) integrity are some of the potential mechanisms connecting MBI with amyloid and tau pathology. The elucidation of the underlying neurobiology of MBI would facilitate the design and efficacy of relative clinical trials, especially towards amyloid- or tau-related pathways. In addition, we provide insights for future research into our deeper understanding of its underlying pathophysiology of MBI, and discuss relative therapeutic implications.
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Affiliation(s)
- Efthalia Angelopoulou
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, Vasilissis Sofias Street 72-74, 11528 Athens, Greece
| | - Anastasia Bougea
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, Vasilissis Sofias Street 72-74, 11528 Athens, Greece
| | - Alexandros Hatzimanolis
- 1st Department of Psychiatry, Aiginition University Hospital, National and Kapodistrian University of Athens, Vasilissis Sofias Street 72-74, 11528 Athens, Greece
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, Vasilissis Sofias Street 72-74, 11528 Athens, Greece
| | - Sokratis G Papageorgiou
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, Vasilissis Sofias Street 72-74, 11528 Athens, Greece
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220
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Liao Z, Zhang Q, Ren N, Zhao H, Zheng X. Progress in mitochondrial and omics studies in Alzheimer's disease research: from molecular mechanisms to therapeutic interventions. Front Immunol 2024; 15:1418939. [PMID: 39040111 PMCID: PMC11260616 DOI: 10.3389/fimmu.2024.1418939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 06/21/2024] [Indexed: 07/24/2024] Open
Abstract
Alzheimer's disease (Alzheimer's disease, AD) is a progressive neurological disorder characterized by memory loss and cognitive impairment. It is characterized by the formation of tau protein neurofibrillary tangles and β-amyloid plaques. Recent studies have found that mitochondria in neuronal cells of AD patients exhibit various dysfunctions, including reduced numbers, ultrastructural changes, reduced enzyme activity, and abnormal kinetics. These abnormal mitochondria not only lead to the loss of normal neuronal cell function, but are also a major driver of AD progression. In this review, we will focus on the advances of mitochondria and their multi-omics in AD research, with particular emphasis on how mitochondrial dysfunction in AD drives disease progression. At the same time, we will focus on summarizing how mitochondrial genomics technologies have revealed specific details of these dysfunctions and how therapeutic strategies targeting mitochondria may provide new directions for future AD treatments. By delving into the key mechanisms of mitochondria in AD related to energy metabolism, altered kinetics, regulation of cell death, and dysregulation of calcium-ion homeostasis, and how mitochondrial multi-omics technologies can be utilized to provide us with a better understanding of these processes. In the future, mitochondria-centered therapeutic strategies will be a key idea in the treatment of AD.
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Affiliation(s)
- Zuning Liao
- Department of Neurology, Fourth People’s Hospital of Jinan, Jinan, China
| | - Qiying Zhang
- Department of Internal Medicine, Jinan Municipal Government Hospital, Jinan, China
| | - Na Ren
- Pharmacy Department, Jinan Municipal People’s Government Organs Outpatient Department, Jinan, China
| | - Haiyan Zhao
- Department of Pharmacy, Qihe County People’s Hospital, Dezhou, China
| | - Xueyan Zheng
- Department of Pharmacy, Jinan Second People’s Hospital, Jinan, China
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221
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Tsatali M, Gaspar De Almeida Santos A, Makri M, Santokhie RT, Boccaletti L, Caciula I, Caciula R, Trogu G, Tsolaki M, Johansen KJ. Peer Support Workers as an Innovative Force in Advocacy in Dementia Care: A Transnational Project Delivered in Norway, Greece, Italy, and Romania. J Multidiscip Healthc 2024; 17:3155-3165. [PMID: 39006874 PMCID: PMC11245633 DOI: 10.2147/jmdh.s464195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Accepted: 06/06/2024] [Indexed: 07/16/2024] Open
Abstract
Aim Peer Support Workers (PSW) as an Innovative Force in Advocacy in Dementia Care (PIA) project aimed to create sustainable and competency-enhancing services for people with dementia by finding new ways to involve former as well as current caregivers in dementia services and, therefore, provide their valuable perspective in dementia care and daily practice. Participants and Methods In order to achieve the aforementioned goals, the first step consisted in mapping the situation existing in the partners' countries, respectively, Norway, Greece, Italy, and Romania. Subsequently, specific and well-structured training material was created with the purpose of recruiting and engaging PSW, in order to contribute to dementia services. The training material was then transferred to a digital platform addressed to PSW, people living with dementia (PwD), caregivers, and health professionals. Results The PIA project proposed the introduction of PSW in dementia care, establishing a close collaboration across the contributing countries, and trained a total of fifty potential PSW. Each country identified a specific role and function of PSW in dementia practice, according to their national particulars. The training seminars and videos proposed by the PIA project are presented in the current study and therefore helped to the distribution of significant information about the contribution of (potential) PSW in dementia care. All the results were uploaded on the platform designed to increase communication and collaboration across health professionals as well as caregivers. Conclusion The PIA project developed and designed training materials and methodologies for establishing PSW in dementia care in Norway, Greece, Italy, and Romania. PIA aims at introducing PSW in the healthcare system of the aforementioned countries, whereas future studies will elaborate on novel ways to measure the efficacy of being a PSW, as well as the benefits to stakeholders.
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Affiliation(s)
- Marianna Tsatali
- Greek Alzheimer Association and Related Disorders, Thessaloniki, Greece
- Network Aging Research, Heidelberg University, Heidelberg, Germany
- Department of Psychology, School of Humanities and Social Sciences, University of Western Macedonia, Kozani, Greece
| | | | - Marina Makri
- Greek Alzheimer Association and Related Disorders, Thessaloniki, Greece
- Department of Neurology, Faculty of Health Sciences, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | | | - Ioana Caciula
- Asociatia Habilitas - Centru de Resurse si Formare Profesionala, Bucharest, Romania
| | - Rodica Caciula
- Asociatia Habilitas - Centru de Resurse si Formare Profesionala, Bucharest, Romania
| | - Giusy Trogu
- Anziani e non solo soc. coop. soc., Carpi, Italy
| | - Magda Tsolaki
- Greek Alzheimer Association and Related Disorders, Thessaloniki, Greece
- Center for Interdisciplinary Research and Innovation, Laboratory of Neurodegenerative Diseases, Aristotle, University of Thessaloniki (CIRI-Auth), Thessaloniki, Greece
| | - Karl Johan Johansen
- Kompetansesenter for brukererfaring og tjenesteutvikling, KBT, Trondheim, Norway
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Xu C, Cao J, Qiang H, Liu Y, Wu J, Luo Q, Wan M, Wang Y, Wang P, Cheng Q, Zhou G, Sima J, Guo Y, Xu S. TaqTth-hpRNA: a novel compact RNA-targeting tool for specific silencing of pathogenic mRNA. Genome Biol 2024; 25:179. [PMID: 38972974 PMCID: PMC11229350 DOI: 10.1186/s13059-024-03326-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 06/27/2024] [Indexed: 07/09/2024] Open
Abstract
Pathogenic allele silencing is a promising treatment for genetic hereditary diseases. Here, we develop an RNA-cleaving tool, TaqTth-hpRNA, consisting of a small, chimeric TaqTth, and a hairpin RNA guiding probe. With a minimal flanking sequence-motif requirement, in vitro and in vivo studies show TaqTth-hpRNA cleaves RNA efficiently and specifically. In an Alzheimer's disease model, we demonstrate silencing of mutant APPswe mRNA without altering the wild-type APP mRNA. Notably, due to the compact size of TaqTth, we are able to combine with APOE2 overexpression in a single AAV vector, which results in stronger inhibition of pathologies.
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Affiliation(s)
- Chong Xu
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
- Laboratory of Aging Neuroscience and Neuropharmacology, China Pharmaceutical University, Nanjing, 210009, China
| | - Jiyanuo Cao
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Huanran Qiang
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Yu Liu
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Jialin Wu
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
- Laboratory of Aging Neuroscience and Neuropharmacology, China Pharmaceutical University, Nanjing, 210009, China
| | - Qiudan Luo
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
- Laboratory of Aging Neuroscience and Neuropharmacology, China Pharmaceutical University, Nanjing, 210009, China
| | - Meng Wan
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Yujie Wang
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
- Laboratory of Aging Neuroscience and Neuropharmacology, China Pharmaceutical University, Nanjing, 210009, China
| | - Peiliang Wang
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Qian Cheng
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
- Laboratory of Aging Neuroscience and Neuropharmacology, China Pharmaceutical University, Nanjing, 210009, China
| | - Guohua Zhou
- Department of Pharmacology, Jinling Hospital, Medical School, Nanjing University, Nanjing, 210008, China
| | - Jian Sima
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China.
- Laboratory of Aging Neuroscience and Neuropharmacology, China Pharmaceutical University, Nanjing, 210009, China.
| | - Yongjian Guo
- School of Biopharmacy, China Pharmaceutical University, Nanjing, 210009, China.
| | - Shu Xu
- School of Basic Medical Science and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China.
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223
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Kim AS, Lee JM. The limited role of serum neurofilament light chain in predicting pain severity of patients with diabetic polyneuropathy. Sci Rep 2024; 14:15612. [PMID: 38971890 PMCID: PMC11227535 DOI: 10.1038/s41598-024-66444-9] [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: 02/27/2024] [Accepted: 07/01/2024] [Indexed: 07/08/2024] Open
Abstract
Pain is one of many complaints expressed by patients with diabetic polyneuropathy. However, no objective measure for pain severity has been available. Neurofilament light chains have been widely used for assessing axonal damage in the neuronal system. Hence, we sought to investigate whether neurofilament light chains can serve as a marker reflecting pain severity in diabetic polyneuropathy. We enrolled the patients with diabetic polyneuropathy. Serum concentrations of neurofilament light chain were then measured using a single-molecule array. Pain severity was evaluated using painDETECT and the Brief Pain Inventory. Moreover, laboratory results including, serum creatinine, HbA1c, and glomerular filtration rate. A correlation test was used to analyze each variable. A total of 42 patients were enrolled. Neurofilament light chain levels were unable to reflect current neuropathic pain severity. However, high levels of neurofilament light chain were a significant predictor of poor diabetes control (r = 0.41; p = 0.02) and kidney damage (r = 0.45; p = 0.01). Serum levels of neurofilament light chain could not reflect current pain severity but was strongly associated with kidney dysfunction and poor diabetes control. Other biomarkers that could predict pain severity need to be uncovered.
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Affiliation(s)
- A-Sol Kim
- Department of Family Medicine, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, South Korea
| | - Jong-Mok Lee
- Department of Neurology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, 680 Gukchaebosang-ro, Jung-gu, Daegu, 41944, South Korea.
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224
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Delvenne A, Gobom J, Schindler SE, Kate MT, Reus LM, Dobricic V, Tijms BM, Benzinger TLS, Cruchaga C, Teunissen CE, Ramakers I, Martinez-Lage P, Tainta M, Vandenberghe R, Schaeverbeke J, Engelborghs S, Roeck ED, Popp J, Peyratout G, Tsolaki M, Freund-Levi Y, Lovestone S, Streffer J, Barkhof F, Bertram L, Blennow K, Zetterberg H, Visser PJ, Vos SJB. CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease. Alzheimers Dement 2024. [PMID: 38970402 DOI: 10.1002/alz.14103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 06/05/2024] [Accepted: 06/06/2024] [Indexed: 07/08/2024]
Abstract
INTRODUCTION We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. METHODS Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. RESULTS Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. DISCUSSION Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. HIGHLIGHTS In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.
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Affiliation(s)
- Aurore Delvenne
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Johan Gobom
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Mara Ten Kate
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Lianne M Reus
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam University Medical Centers (AUMC), Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Inez Ramakers
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | | | - Mikel Tainta
- Fundación CITA-Alzhéimer Fundazioa, Donostia, Spain
| | - Rik Vandenberghe
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Jolien Schaeverbeke
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Bru-BRAIN, Universitair Ziekenhuis Brussel and NEUR Research Group, Center for Neurosciences (C4N), Vrije Universiteit Brussel, Brussels, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Julius Popp
- Old Age Psychiatry, University Hospital Lausanne, Lausanne, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatry University Hospital Zürich, Zürich, Switzerland
| | | | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Medical School, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Thessaloniki, Greece
| | - Yvonne Freund-Levi
- Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, Huddinge, Stockholm, Sweden
- Department of Psychiatry in Region Örebro County and School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Old Age Psychiatry, Psychology & Neuroscience, King's College, London, UK
| | - Simon Lovestone
- University of Oxford, United Kingdom (currently at Johnson and Johnson Medical Ltd., Oxford, UK
| | - Johannes Streffer
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- H. Lundbeck A/S, Valby, Denmark
| | - Frederik Barkhof
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
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Johansson L, Reyes JF, Ali T, Schätzl H, Gilch S, Hallbeck M. Lack of cellular prion protein causes Amyloid β accumulation, increased extracellular vesicle abundance, and changes to exosome biogenesis proteins. Mol Cell Biochem 2024:10.1007/s11010-024-05059-0. [PMID: 38970706 DOI: 10.1007/s11010-024-05059-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Accepted: 06/29/2024] [Indexed: 07/08/2024]
Abstract
Alzheimer's disease (AD) progression is closely linked to the propagation of pathological Amyloid β (Aβ), a process increasingly understood to involve extracellular vesicles (EVs), namely exosomes. The specifics of Aβ packaging into exosomes remain elusive, although evidence suggests an ESCRT (Endosomal Sorting Complex Required for Transport)-independent origin to be responsible in spreading of AD pathogenesis. Intriguingly, PrPC, known to influence exosome abundance and bind oligomeric Aβ (oAβ), can be released in exosomes via both ESCRT-dependent and ESCRT-independent pathways, raising questions about its role in oAβ trafficking. Thus, we quantified Aβ levels within EVs, cell medium, and intracellularly, alongside exosome biogenesis-related proteins, following deletion or overexpression of PrPC. The same parameters were also evaluated in the presence of specific exosome inhibitors, namely Manumycin A and GW4869. Our results revealed that deletion of PrPC increases intracellular Aβ accumulation and amplifies EV abundance, alongside significant changes in cellular levels of exosome biogenesis-related proteins Vps25, Chmp2a, and Rab31. In contrast, cellular expression of PrPC did not alter exosomal Aβ levels. This highlights PrPC's influence on exosome biogenesis, albeit not in direct Aβ packaging. Additionally, our data confirm the ESCRT-independent exosome release of Aβ and we show a direct reduction in Chmp2a levels upon oAβ challenge. Furthermore, inhibition of opposite exosome biogenesis pathway resulted in opposite cellular PrPC levels. In conclusion, our findings highlight the intricate relationship between PrPC, exosome biogenesis, and Aβ release. Specifically, they underscore PrPC's critical role in modulating exosome-associated proteins, EV abundance, and cellular Aβ levels, thereby reinforcing its involvement in AD pathogenesis.
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Affiliation(s)
- Lovisa Johansson
- Department of Biomedical and Clinical Sciences and Department of Clinical Pathology, Linköping University, Linköping, Sweden.
| | - Juan F Reyes
- Department of Biomedical and Clinical Sciences and Department of Clinical Pathology, Linköping University, Linköping, Sweden
| | - Tahir Ali
- Calgary Prion Research Unit, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Hermann Schätzl
- Calgary Prion Research Unit, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Sabine Gilch
- Calgary Prion Research Unit, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Martin Hallbeck
- Department of Biomedical and Clinical Sciences and Department of Clinical Pathology, Linköping University, Linköping, Sweden.
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226
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Rasing I, Voigt S, Koemans EA, de Kort AM, van Harten TW, van Etten ES, van Zwet EW, Stoops E, Francois C, Kuiperij HB, Klijn CJM, Schreuder FHBM, van der Weerd L, van Osch MJP, van Walderveen MAA, Verbeek MM, Terwindt GM, Wermer MJH. Correction: Serum and cerebrospinal fluid neurofilament light chain and glial fibrillary acid protein levels in early and advanced stages of cerebral amyloid angiopathy. Alzheimers Res Ther 2024; 16:155. [PMID: 38971821 PMCID: PMC11227145 DOI: 10.1186/s13195-024-01518-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/08/2024]
Affiliation(s)
- Ingeborg Rasing
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands.
| | - Sabine Voigt
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Emma A Koemans
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anna M de Kort
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Thijs W van Harten
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ellis S van Etten
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Erik W van Zwet
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | | | | | - H Bea Kuiperij
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Catharina J M Klijn
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Floris H B M Schreuder
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Louise van der Weerd
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | | | | | - Marcel M Verbeek
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Gisela M Terwindt
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marieke J H Wermer
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, University Medical Center Groningen, Groningen, The Netherlands
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227
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Frank B, Walsh M, Hurley L, Groh J, Blennow K, Zetterberg H, Tripodis Y, Budson AE, O'Connor MK, Martin B, Weller J, McKee A, Qiu W, Stein TD, Stern RA, Mez J, Henson R, Long J, Aschenbrenner AJ, Babulal GM, Morris JC, Schindler S, Alosco ML. Cognition Mediates the Association Between Cerebrospinal Fluid Biomarkers of Amyloid and P-Tau and Neuropsychiatric Symptoms. J Alzheimers Dis 2024:JAD240125. [PMID: 38995786 DOI: 10.3233/jad-240125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/14/2024]
Abstract
Background Neuropsychiatric symptoms (NPS) can be an early manifestation of Alzheimer's disease (AD). However, the associations among NPS, cognition, and AD biomarkers across the disease spectrum are unclear. Objective We analyzed cross-sectional mediation pathways between cerebrospinal fluid (CSF) biomarkers of AD (Aβ1-42, p-tau181), cognitive function, and NPS. Methods Primary models included 781 participants from the National Alzheimer's Coordinating Center (NACC) data set who had CSF analyzed for AD biomarkers using Lumipulse. NPS were assessed with the Neuropsychiatric Inventory Questionnaire (NPI-Q). We assessed cognition with the harmonized MMSE/MoCA, as well as neuropsychological tests sensitive to AD pathology: story recall, naming, animal fluency, and Trails B. The Clinical Dementia Rating (CDR®) scale assessed dementia severity. Mediation models were estimated with Kemeny metric covariance in a structural equation model framework, controlling for age, education, sex, and APOEɛ4. Results The sample was older adults (M = 73.85, SD = 6.68; 49.9% male, 390; 27.9% dementia, 218) who were predominantly white (n = 688, 88.1%). Higher p-tau181/Aβ1-42 ratio predicted higher NPI-Q, which was partially mediated by the MMSE/MoCA and, in a second model, story recall. No other pathway was statistically significant. Both the MMSE/MoCA and NPI-Q independently mediated the association between p-tau181/Aβ1-42 ratio and CDR global impairment. With dementia excluded, p-tau181/Aβ1-42 ratio was no longer associated with the NPI-Q. Conclusions NPS may be secondary to cognitive impairment and AD pathology through direct and indirect pathways. NPS independently predict dementia severity in AD. However, AD pathology likely plays less of a role in NPS in samples without dementia.
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Affiliation(s)
- Brandon Frank
- U.S. Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, USA
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Michael Walsh
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Landon Hurley
- U.S. Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, USA
| | - Jenna Groh
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Andrew E Budson
- U.S. Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, USA
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Maureen K O'Connor
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- VA Bedford Healthcare System, U.S. Department of Veteran Affairs, Bedford, MA, USA
| | - Brett Martin
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Jason Weller
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Ann McKee
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Wendy Qiu
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Rachel Henson
- Knight Alzheimer Disease Research Center (ADRC), Washington University, St. Louis, MO, USA
| | - Justin Long
- Knight Alzheimer Disease Research Center (ADRC), Washington University, St. Louis, MO, USA
| | - Andrew J Aschenbrenner
- Knight Alzheimer Disease Research Center (ADRC), Washington University, St. Louis, MO, USA
| | - Ganesh M Babulal
- Knight Alzheimer Disease Research Center (ADRC), Washington University, St. Louis, MO, USA
| | - John C Morris
- Knight Alzheimer Disease Research Center (ADRC), Washington University, St. Louis, MO, USA
| | - Suzanne Schindler
- Knight Alzheimer Disease Research Center (ADRC), Washington University, St. Louis, MO, USA
| | - Michael L Alosco
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
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228
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Hu Q, Shi M, Li Y, Zhao X. Elevated plasma neurofilament light was associated with multi-modal neuroimaging features in Alzheimer's disease signature regions and predicted future tau deposition. BMC Neurol 2024; 24:236. [PMID: 38971733 PMCID: PMC11227162 DOI: 10.1186/s12883-024-03728-7] [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: 02/10/2024] [Accepted: 06/14/2024] [Indexed: 07/08/2024] Open
Abstract
BACKGROUND Neurofilament Light (NfL) is a biomarker for early neurodegeneration in Alzheimer's disease (AD). This study aims to examine the association between plasma NfL and multi-modal neuroimaging features across the AD spectrum and whether NfL predicts future tau deposition. METHODS The present study recruited 517 participants comprising Aβ negative cognitively normal (CN-) participants (n = 135), Aβ positive cognitively normal (CN +) participants (n = 64), individuals with amnestic mild cognitive impairment (aMCI) (n = 212), and those diagnosed with AD dementia (n = 106). All the participants underwent multi-modal neuroimaging examinations. Cross-sectional and longitudinal associations between plasma NfL and multi-modal neuro-imaging features were evaluated using partial correlation analysis and linear mixed effects models. We also used linear regression analysis to investigate the association of baseline plasma NfL with future PET tau load. Mediation analysis was used to explore whether the effect of NfL on cognition was mediated by these imaging biomarkers. RESULTS The results showed that baseline NfL levels and the rate of change were associated with Aβ deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in AD signature regions (P<0.05). In both Aβ positive CN and MCI participants, baseline NfL showed a significant predictive value of elevating tau burden in the left medial orbitofrontal cortex and para-hippocampus (β = 0.336, P = 0.032; β = 0.313, P = 0.047). Lastly, the multi-modal neuroimaging features mediated the association between plasma NfL and cognitive performance. CONCLUSIONS The study supports the association between plasma NfL and multi-modal neuroimaging features in AD-vulnerable regions and its predictive value for future tau deposition.
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Affiliation(s)
- Qili Hu
- Department of Imaging, The Fifth People's Hospital of Shanghai, Fudan University, No.128 Ruili Road, Minhang District, Shanghai, 200240, China
| | - Mengqiu Shi
- Department of Imaging, The Fifth People's Hospital of Shanghai, Fudan University, No.128 Ruili Road, Minhang District, Shanghai, 200240, China
| | - Yunfei Li
- Department of Imaging, The Fifth People's Hospital of Shanghai, Fudan University, No.128 Ruili Road, Minhang District, Shanghai, 200240, China
| | - Xiaohu Zhao
- Department of Imaging, The Fifth People's Hospital of Shanghai, Fudan University, No.128 Ruili Road, Minhang District, Shanghai, 200240, China.
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Ghani U, Niazi I, Signal N, Kumari N, Amjad I, Haavik H, Taylor D. The influence of multiple cognitive workload levels of an exergame on dorsal attention network connectivity at the source level. Physiol Behav 2024; 284:114628. [PMID: 38977259 DOI: 10.1016/j.physbeh.2024.114628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 06/16/2024] [Accepted: 07/03/2024] [Indexed: 07/10/2024]
Abstract
This study investigates how adding a cognitive task on a balance board (exergame) affects connectivity in the dorsal attention network (DAN) during an exergame task. Healthy young adults performed a soccer ball-moving task by tilting a balance board with their feet while their brain activity was measured using electroencephalography (EEG). In this exergame, the speed of obstacles in front of the goal manipulated the cognitive workload. Higher speed means a higher cognitive workload. The study found significant changes in functional connectivity within DAN regions, specifically in the alpha band. During the shift from easy to medium cognitive task, we observed a significant increase in connectivity (p= 0.0436) between the right inferior temporal (ITG R) and the Left middle temporal (MTG L). During the transition from easy to hard cognitive tasks, strengthened interactions (p= 0.0324) between inferior temporal (ITG) and parsopercularis (pOPPER) were found. This suggests that the proposed balanceboard-based exergame enhances the functionality of specific brain regions, such as ITG and MTG regions, and improves connectivity in the frontal cortex. We also found a correlation between brain activity and performance data, highlighting that increased cognitive workload resulted in decreased performance and heightened frontal alpha activity. These findings align with research suggesting that adding cognitive games to physical activity-based tasks in rehabilitation programs can boost brain activity, resulting in improved decision-making and visual processing skills. This information can help clinicians tailor rehabilitation methods that target specific brain regions.
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Affiliation(s)
- Usman Ghani
- Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland, New Zealand; Department of health and sciences, Auckland University of Technology (AUT), New Zealand.
| | - Imran Niazi
- Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland, New Zealand; Department of health and sciences, Auckland University of Technology (AUT), New Zealand; Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Nada Signal
- Department of health and sciences, Auckland University of Technology (AUT), New Zealand
| | - Nitika Kumari
- Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland, New Zealand
| | - Imran Amjad
- Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland, New Zealand
| | - Heidi Haavik
- Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland, New Zealand
| | - Denise Taylor
- Department of health and sciences, Auckland University of Technology (AUT), New Zealand
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230
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Macoveanu J, Craciun S, Ketterer-Sykes EB, Ysbæk-Nielsen AT, Zarp J, Kessing LV, Jørgensen MB, Miskowiak KW. Amygdala and hippocampal substructure volumes and their association with improvement in mood symptoms in patients with mood disorders undergoing electroconvulsive therapy. Psychiatry Res Neuroimaging 2024; 343:111859. [PMID: 38986265 DOI: 10.1016/j.pscychresns.2024.111859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 07/05/2024] [Accepted: 07/05/2024] [Indexed: 07/12/2024]
Abstract
Electroconvulsive therapy (ECT) demonstrates favorable outcomes in the management of severe depressive disorders. ECT has been consistently associated with volumetric increases in the amygdala and hippocampus. However, the underlying mechanisms of these structural changes and their association to clinical improvement remains unclear. In this cross-sectional structural MRI study, we assessed the difference in amygdala subnuclei and hippocampus subfields in n = 37 patients with either unipolar or bipolar disorder immediately after eighth ECT sessions compared to (n = 40) demographically matched patients in partial remission who did not receive ECT (NoECT group). Relative to NoECT, the ECT group showed significantly larger bilateral amygdala volumes post-treatment, with the effect originating from the lateral, basal, and paralaminar nuclei and the left corticoamydaloid transition area. No significant group differences were observed for the hippocampal or cortical volumes. ECT was associated with a significant decrease in depressive symptoms. However, there were no significant correlations between amygdala subnuclei volumes and symptom improvement. Our study corroborates previous reports on increased amygdalae volumes following ECT and further identifies the subnuclei driving this effect. However, the therapeutic effect of ECT does not seem to be directly related to structural changes in the amygdala.
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Affiliation(s)
- Julian Macoveanu
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark; Neurocogntion and Emotion in Affective Disorders (NEAD) Centre, Psychiatric Centre Copenhagen, and Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
| | - Sabina Craciun
- DIS Copenhagen, Copenhagen, Denmark; Dickinson College, Carlisle, PA, USA
| | | | - Alexander Tobias Ysbæk-Nielsen
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark; Neurocogntion and Emotion in Affective Disorders (NEAD) Centre, Psychiatric Centre Copenhagen, and Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Jeff Zarp
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark; Neurocogntion and Emotion in Affective Disorders (NEAD) Centre, Psychiatric Centre Copenhagen, and Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Lars Vedel Kessing
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Denmark
| | - Martin Balslev Jørgensen
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Denmark
| | - Kamilla Woznica Miskowiak
- Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg Hospital, Copenhagen, Denmark; Neurocogntion and Emotion in Affective Disorders (NEAD) Centre, Psychiatric Centre Copenhagen, and Department of Psychology, University of Copenhagen, Copenhagen, Denmark
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231
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Mobaderi T, Kazemnejad A, Salehi M. Exploring the impacts of risk factors on mortality patterns of global Alzheimer's disease and related dementias from 1990 to 2021. Sci Rep 2024; 14:15583. [PMID: 38971870 PMCID: PMC11227499 DOI: 10.1038/s41598-024-65887-4] [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: 12/15/2023] [Accepted: 06/25/2024] [Indexed: 07/08/2024] Open
Abstract
Alzheimer's Disease and Related Dementias (ADRD) affect millions of people worldwide, with mortality rates influenced by several risk factors and exhibiting significant heterogeneity across geographical regions. This study aimed to investigate the impact of risk factors on global ADRD mortality patterns from 1990 to 2021, utilizing clustering and modeling techniques. Data on ADRD mortality rates, cardiovascular disease, and diabetes prevalence were obtained for 204 countries from the GBD platform. Additional variables such as HDI, life expectancy, alcohol consumption, and tobacco use prevalence were sourced from the UNDP and WHO. All the data were extracted for men, women, and the overall population. Longitudinal k-means clustering and generalized estimating equations were applied for data analysis. The findings revealed that cardiovascular disease had significant positive effects of 1.84, 3.94, and 4.70 on men, women, and the overall ADRD mortality rates, respectively. Tobacco showed positive effects of 0.92, 0.13, and 0.39, while alcohol consumption had negative effects of - 0.59, - 9.92, and - 2.32, on men, women, and the overall ADRD mortality rates, respectively. The countries were classified into five distinct subgroups. Overall, cardiovascular disease and tobacco use were associated with increased ADRD mortality rates, while moderate alcohol consumption exhibited a protective effect. Notably, tobacco use showed a protective effect in cluster A, as did alcohol consumption in cluster B. The effects of risk factors on ADRD mortality rates varied among the clusters, highlighting the need for further investigation into the underlying causal factors.
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Affiliation(s)
- Tofigh Mobaderi
- Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Anoshirvan Kazemnejad
- Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
| | - Masoud Salehi
- Nutritional Sciences Research Center, Iran University of Medical Sciences, Tehran, Iran
- Department of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
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232
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Nilsson J, Pichet Binette A, Palmqvist S, Brum WS, Janelidze S, Ashton NJ, Spotorno N, Stomrud E, Gobom J, Zetterberg H, Brinkmalm A, Blennow K, Hansson O. Cerebrospinal fluid biomarker panel for synaptic dysfunction in a broad spectrum of neurodegenerative diseases. Brain 2024; 147:2414-2427. [PMID: 38325331 PMCID: PMC11224614 DOI: 10.1093/brain/awae032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/31/2023] [Accepted: 01/21/2024] [Indexed: 02/09/2024] Open
Abstract
Synaptic dysfunction and degeneration is likely the key pathophysiology for the progression of cognitive decline in various dementia disorders. Synaptic status can be monitored by measuring synaptic proteins in CSF. In this study, both known and new synaptic proteins were investigated and compared as potential biomarkers of synaptic dysfunction, particularly in the context of Alzheimer's disease (AD). Seventeen synaptic proteins were quantified in CSF using two different targeted mass spectrometry assays in the prospective Swedish BioFINDER-2 study. The study included 958 individuals, characterized as having mild cognitive impairment (MCI, n = 205), AD dementia (n = 149) and a spectrum of other neurodegenerative diseases (n = 171), in addition to cognitively unimpaired individuals (CU, n = 443). Synaptic protein levels were compared between diagnostic groups and their associations with cognitive decline and key neuroimaging measures (amyloid-β-PET, tau-PET and cortical thickness) were assessed. Among the 17 synaptic proteins examined, 14 were specifically elevated in the AD continuum. SNAP-25, 14-3-3 zeta/delta, β-synuclein, and neurogranin exhibited the highest discriminatory accuracy in differentiating AD dementia from controls (areas under the curve = 0.81-0.93). SNAP-25 and 14-3-3 zeta/delta also had the strongest associations with tau-PET, amyloid-β-PET and cortical thickness at baseline and were associated with longitudinal changes in these imaging biomarkers [β(standard error, SE) = -0.056(0.0006) to 0.058(0.005), P < 0.0001]. SNAP-25 was the strongest predictor of progression to AD dementia in non-demented individuals (hazard ratio = 2.11). In contrast, neuronal pentraxins were decreased in all neurodegenerative diseases (except for Parkinson's disease), and NPTX2 showed the strongest associations with subsequent cognitive decline [longitudinal Mini-Mental State Examination: β(SE) = 0.57(0.1), P ≤ 0.0001; and mPACC: β(SE) = 0.095(0.024), P ≤ 0.001] across the AD continuum. Interestingly, utilizing a ratio of the proteins that displayed higher levels in AD, such as SNAP-25 or 14-3-3 zeta/delta, over NPTX2 improved the biomarkers' associations with cognitive decline and brain atrophy. We found 14-3-3 zeta/delta and SNAP-25 to be especially promising as synaptic biomarkers of pathophysiological changes in AD. Neuronal pentraxins were identified as general indicators of neurodegeneration and associated with cognitive decline across various neurodegenerative dementias. Cognitive decline and brain atrophy were best predicted by ratios of SNAP-25/NPTX2 and 14-3-3 zeta/delta/NPTX2.
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Affiliation(s)
- Johanna Nilsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 211 46 Malmö, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 211 46 Malmö, Sweden
- Memory Clinic, Skåne University Hospital, 205 02 Malmö, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre 90035-003, Brazil
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 211 46 Malmö, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, 4011 Stavanger, Norway
- Department of Old Age Psychiatry, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London SE5 9RX, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London SE5 8AF, UK
| | - Nicola Spotorno
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 211 46 Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 211 46 Malmö, Sweden
- Memory Clinic, Skåne University Hospital, 205 02 Malmö, Sweden
| | - Johan Gobom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 30 Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 30 Mölndal, Sweden
- Fluid Biomarker Laboratory, UK Dementia Research Institute at UCL, London WC1E 6BT, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London WC1N 3BG, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Ann Brinkmalm
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 30 Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 30 Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, 75646 Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei 230036, P.R. China
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 211 46 Malmö, Sweden
- Memory Clinic, Skåne University Hospital, 205 02 Malmö, Sweden
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233
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Reive BS, Lau V, Sánchez-Lafuente CL, Henri-Bhargava A, Kalynchuk LE, Tremblay MÈ, Caruncho HJ. The Inflammation-Induced Dysregulation of Reelin Homeostasis Hypothesis of Alzheimer's Disease. J Alzheimers Dis 2024:JAD240088. [PMID: 38995785 DOI: 10.3233/jad-240088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/14/2024]
Abstract
Alzheimer's disease (AD) accounts for most dementia cases, but we lack a complete understanding of the mechanisms responsible for the core pathology associated with the disease (e.g., amyloid plaque and neurofibrillary tangles). Inflammation has been identified as a key contributor of AD pathology, with recent evidence pointing towards Reelin dysregulation as being associated with inflammation. Here we describe Reelin signaling and outline existing research involving Reelin signaling in AD and inflammation. Research is described pertaining to the inflammatory and immunological functions of Reelin before we propose a mechanism through which inflammation renders Reelin susceptible to dysregulation resulting in the induction and exacerbation of AD pathology. Based on this hypothesis, it is predicted that disorders of both inflammation (including peripheral inflammation and neuroinflammation) and Reelin dysregulation (including disorders associated with upregulated Reelin expression and disorders of Reelin downregulation) have elevated risk of developing AD. We conclude with a description of AD risk in various disorders involving Reelin dysregulation and inflammation.
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Affiliation(s)
- Brady S Reive
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Victor Lau
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | | | - Alexandre Henri-Bhargava
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Vancouver Island Health Authority, Victoria, BC, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Lisa E Kalynchuk
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Marie-Ève Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Mental Health Research Cluster, University of Victoria, Victoria, BC, Canada
| | - Hector J Caruncho
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Mental Health Research Cluster, University of Victoria, Victoria, BC, Canada
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234
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Ghosh G, Neely BA, Bland AM, Whitmer ER, Field CL, Duignan PJ, Janech MG. Identification of Candidate Protein Biomarkers Associated with Domoic Acid Toxicosis in Cerebrospinal Fluid of California Sea Lions ( Zalophus californianus). J Proteome Res 2024; 23:2419-2430. [PMID: 38807289 PMCID: PMC11232103 DOI: 10.1021/acs.jproteome.4c00103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 05/10/2024] [Accepted: 05/20/2024] [Indexed: 05/30/2024]
Abstract
Since 1998, California sea lion (Zalophus californianus) stranding events associated with domoic acid toxicosis (DAT) have consistently increased. Outside of direct measurement of domoic acid in bodily fluids at the time of stranding, there are no practical nonlethal clinical tests for the diagnosis of DAT that can be utilized in a rehabilitation facility. Proteomics analysis was conducted to discover candidate protein markers of DAT using cerebrospinal fluid from stranded California sea lions with acute DAT (n = 8), chronic DAT (n = 19), or without DAT (n = 13). A total of 2005 protein families were identified experiment-wide. A total of 83 proteins were significantly different in abundance across the three groups (adj. p < 0.05). MDH1, PLD3, ADAM22, YWHAG, VGF, and CLSTN1 could discriminate California sea lions with or without DAT (AuROC > 0.75). IGKV2D-28, PTRPF, KNG1, F2, and SNCB were able to discriminate acute DAT from chronic DAT (AuROC > 0.75). Proteins involved in alpha synuclein deposition were over-represented as classifiers of DAT, and many of these proteins have been implicated in a variety of neurodegenerative diseases. These proteins should be considered potential markers for DAT in California sea lions and should be prioritized for future validation studies as biomarkers.
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Affiliation(s)
- Gautam Ghosh
- Department of Biology, Grice Marine Laboratory, College of Charleston, Charleston, South Carolina 29412, United States
| | - Benjamin A Neely
- National Institute of Standards and Technology (NIST) Charleston, Charleston, South Carolina 29412, United States
| | - Alison M Bland
- Department of Biology, Grice Marine Laboratory, College of Charleston, Charleston, South Carolina 29412, United States
- Hollings Marine Laboratory, College of Charleston, Charleston, South Carolina 29412, United States
| | - Emily R Whitmer
- The Marine Mammal Center, 2000 Bunker Road, Sausalito, California 94965, United States
| | - Cara L Field
- The Marine Mammal Center, 2000 Bunker Road, Sausalito, California 94965, United States
| | - Pádraig J Duignan
- The Marine Mammal Center, 2000 Bunker Road, Sausalito, California 94965, United States
| | - Michael G Janech
- Department of Biology, Grice Marine Laboratory, College of Charleston, Charleston, South Carolina 29412, United States
- Hollings Marine Laboratory, College of Charleston, Charleston, South Carolina 29412, United States
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235
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Dharsee S, Laliberté Durish C, Tang K, Brooks BL, Noel M, Ware AL, Beauchamp MH, Craig W, Doan Q, Freedman SB, Goodyear BG, Gravel J, Zemek R, Yeates KO. Association of Psychological Resilience, Cognitive Reserve, and Brain Reserve with Post-Concussive Symptoms in Children with Mild Traumatic Brain Injury and Orthopedic Injury: An A-CAP Study. J Neurotrauma 2024. [PMID: 38874919 DOI: 10.1089/neu.2024.0076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2024] Open
Abstract
Protective factors, including psychological resilience, cognitive reserve, and brain reserve, may be positively associated with recovery after pediatric mild traumatic brain injury (mTBI) but are yet to be studied concurrently. We sought to examine these factors as moderators of post-concussive symptoms (PCS) in pediatric mTBI compared with mild orthopedic injury (OI). Participants included 967 children (633 mTBI, 334 OI) aged 8-16.99 years, recruited from 5 Canadian pediatric emergency departments as part of a prospective longitudinal cohort study. At 10 days post-injury, psychological resilience was measured using the Connor-Davidson Resilience Scale and brain reserve was measured using total brain volume derived from structural magnetic resonance imaging. Cognitive reserve was measured at 3 months post-injury using IQ scores from the Wechsler Abbreviated Scale of Intelligence-Second Edition. Cognitive and somatic PCS were measured using child and parent ratings on the Health and Behavior Inventory, completed weekly for 3 months and biweekly to 6 months. Analyses involved generalized least-squares regression models using restricted cubic splines. Covariates included age at injury, sex, racialized identity, material and social deprivation, pre-injury migraine and concussion history, and retrospective pre-injury PCS. Psychological resilience moderated group differences in parent-reported PCS. At 30 days post-injury, estimated group differences in parent-reported cognitive and somatic PCS (mTBI > OI) were larger at higher (75th percentile) resilience scores (Est = 2.25 [0.87, 3.64] and Est = 2.38 [1.76, 3.00], respectively) than at lower (25th percentile) resilience scores (Est = 1.44 [0.01, 2.86] and Est = 2.08 [1.45, 2.71], respectively). Resilience did not moderate group differences in child-reported PCS but was negatively associated with child-reported PCS in both groups (ps ≤ 0.001). Brain reserve (i.e., total brain volume [TBV]) also moderated group differences, but only for parent-reported somatic PCS (p = 0.018). Group difference (mTBI > OI) at 30 days was larger at smaller (25th percentile) TBV (Est = 2.78 [2.17, 3.38]) than at larger (75th percentile) TBV (Est = 1.95 [1.31, 2.59]). TBV was not associated with parent-reported cognitive PCS or child-reported PCS. IQ did not moderate PCS in either group but had a significant non-linear association in both groups with child-reported somatic PCS (p = 0.018) and parent-reported PCS (p < 0.001), with higher PCS scores at both lower and higher IQs. These findings suggest that higher resilience predicts fewer PCS, but less strongly after mTBI than OI; greater brain reserve may reduce the effect of mTBI on somatic PCS; and cognitive reserve has an unexpected curvilinear association with PCS across injury types. The results highlight the importance of protective factors as predictors of recovery and potential targets for intervention following pediatric mTBI.
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Affiliation(s)
- Safira Dharsee
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | | | - Ken Tang
- Independent Statistical Consulting, Richmond, British Columbia, Canada
| | - Brian L Brooks
- Departments of Pediatrics, Clinical Neurosciences, and Psychology, Alberta Children's Hospital Research Institute, University of Calgary; Alberta Children's Hospital, Calgary, Alberta, Canada
| | - Melanie Noel
- Department of Psychology, Alberta Children's Hospital Research Institute, and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Ashley L Ware
- Department of Psychology, Georgia State University, Georgia, USA
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | | | - William Craig
- Department of Pediatrics, University of Alberta and Stollery Children's Hospital, Edmonton, Alberta, Canada
| | - Quynh Doan
- Department of Pediatrics, University of British Columbia and BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
| | - Stephen B Freedman
- Departments of Pediatrics and Emergency Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Bradley G Goodyear
- Department of Radiology, Cumming School of Medicine, and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Jocelyn Gravel
- Department of Pediatric Emergency Medicine, CHU Sainte-Justine Hospital Research Center, Montréal, Québec, Canada
- Department of Pediatrics, Université de Montréal, Montréal, Québec, Canada
| | - Roger Zemek
- Departments of Pediatrics and Emergency Medicine, University of Ottawa and Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Keith Owen Yeates
- Department of Psychology, Alberta Children's Hospital Research Institute, and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
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236
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Warmenhoven N, Salvadó G, Janelidze S, Mattsson-Carlgren N, Bali D, Dolado AO, Kolb H, Triana-Baltzer G, Barthélemy NR, Schindler SE, Aschenbrenner AJ, Raji CA, Benzinger TL, Morris JC, Ibanez L, Timsina J, Cruchaga C, Bateman RJ, Ashton N, Arslan B, Zetterberg H, Blennow K, Pichet Binette A, Hansson O. A Comprehensive Head-to-Head Comparison of Key Plasma Phosphorylated Tau 217 Biomarker Tests. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.02.24309629. [PMID: 39006421 PMCID: PMC11245081 DOI: 10.1101/2024.07.02.24309629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarkers for reliable detection of Alzheimer's disease (AD) pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-β (Aβ)-PET, tau-PET, and cognition as outcomes, and benchmarked them against cerebrospinal fluid (CSF) biomarker tests. Samples from 998 individuals (mean[range] age 68.5[20.0-92.5], 53% female) from the Swedish BioFINDER-2 cohort were analyzed. Plasma p-tau217 was measured with mass spectrometry (MS) assays (the ratio between phosphorylated and non-phosphorylated [%p-tau217WashU]and ptau217WashU) as well as with immunoassays (p-tau217Lilly, p-tau217Janssen, p-tau217ALZpath). CSF biomarkers included p-tau217Lilly, and the FDA-approved p-tau181/Aβ42Elecsys and p-tau181Elecsys. All plasma p-tau217 tests exhibited high ability to detect abnormal Aβ-PET (AUC range: 0.91-0.96) and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217WashU had the highest performance, with significantly higher AUCs than all the immunoassays (P diff<0.007). For detecting Aβ-PET status, %p-tau217WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 91% (immunoassays: 84-87%), and a specificity of 94% (immunoassays: 85-89%). Among immunoassays, p-tau217Lilly and plasma p-tau217ALZpath had higher AUCs than plasma p-tau217Janssen for Aβ-PET status (P diff<0.006), and p-tau217Lilly outperformed plasma p-tau217ALZpath for tau-PET status (P diff=0.025). Plasma %p-tau217WashU exhibited higher associations with all PET load outcomes compared to immunoassays; baseline Aβ-PET load (R2: 0.72; immunoassays: 0.47-0.58; Pdiff<0.001), baseline tau-PET load (R2: 0.51; immunoassays: 0.38-0.45; Pdiff<0.001), longitudinal Aβ-PET load (R2: 0.53; immunoassays: 0.31-0.38; Pdiff<0.001) and longitudinal tau-PET load (R2: 0.50; immunoassays: 0.35-0.43; Pdiff<0.014). Among immunoassays, plasma p-tau217Lilly was more strongly associated with Aβ-PET load than plasma p-tau217Janssen (P diff<0.020) and with tau-PET load than both plasma p-tau217Janssen and plasma p-tau217ALZpath (all P diff<0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination[MMSE]) than all immunoassays (R2 %p-tau217WashU: 0.33; immunoassays: 0.27-0.30; P diff<0.024). The main results were replicated in an external cohort from Washington University in St Louis (n =219). Finally, p-tau217Nulisa showed similar performance to other immunoassays in subsets of both cohorts. In summary, both MS- and immunoassay-based p-tau217 tests generally perform well in identifying Aβ-PET, tau-PET, and cognitive abnormalities, but %p-tau217WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for AD pathology, while some immunoassays might be better suited as triage tests where positive results are confirmed with a second test.
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Affiliation(s)
- Noëlle Warmenhoven
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Anna Orduña Dolado
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hartmuth Kolb
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA, USA
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA, USA
| | - Nicolas R. Barthélemy
- The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Cyrus A. Raji
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Randall J. Bateman
- The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicholas Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund University, Lund, Sweden
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237
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Baumeister H, Vogel JW, Insel PS, Kleineidam L, Wolfsgruber S, Stark M, Gellersen HM, Yakupov R, Schmid MC, Lüsebrink F, Brosseron F, Ziegler G, Freiesleben SD, Preis L, Schneider LS, Spruth EJ, Altenstein S, Lohse A, Fliessbach K, Vogt IR, Bartels C, Schott BH, Rostamzadeh A, Glanz W, Incesoy EI, Butryn M, Janowitz D, Rauchmann BS, Kilimann I, Goerss D, Munk MH, Hetzer S, Dechent P, Ewers M, Scheffler K, Wuestefeld A, Strandberg O, van Westen D, Mattsson-Carlgren N, Janelidze S, Stomrud E, Palmqvist S, Spottke A, Laske C, Teipel S, Perneczky R, Buerger K, Schneider A, Priller J, Peters O, Ramirez A, Wiltfang J, Heneka MT, Wagner M, Düzel E, Jessen F, Hansson O, Berron D. A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings. Brain 2024; 147:2400-2413. [PMID: 38654513 PMCID: PMC11224599 DOI: 10.1093/brain/awae118] [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: 02/02/2024] [Accepted: 03/03/2024] [Indexed: 04/26/2024] Open
Abstract
Memory clinic patients are a heterogeneous population representing various aetiologies of pathological ageing. It is not known whether divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease patients, are prevalent and clinically meaningful in this group of older adults. To uncover distinct atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to baseline structural MRI data from 813 participants enrolled in the DELCODE cohort (mean ± standard deviation, age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (n = 342), mild cognitive impairment (n = 118) or dementia of the Alzheimer's type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid Alzheimer's disease biomarker levels, the Preclinical Alzheimer Cognitive Composite (PACC-5) as well as episodic memory and executive functioning. PACC-5 trajectories over up to 240 weeks were examined. To test whether baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and mild cognitive impairment conversion rates of cognitively unimpaired participants and those with subjective cognitive decline. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy initially affected the medial temporal lobes, followed by further temporal regions and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological Alzheimer's disease biomarker levels, APOE ε4 carriership and an amnestic cognitive impairment. Hippocampal-sparing atrophy initially occurred outside the temporal lobe, with the medial temporal lobe spared up to advanced atrophy stages. This atrophy pattern also affected individuals with positive Alzheimer's disease biomarkers and was associated with more generalized cognitive impairment. Limbic-predominant atrophy, in all participants and in only unimpaired participants, was linked to more negative longitudinal PACC-5 slopes than observed in participants without or with hippocampal-sparing atrophy and increased the risk of mild cognitive impairment conversion. SuStaIn modelling was repeated in a sample from the Swedish BioFINDER-2 cohort. Highly similar atrophy progression patterns and associated cognitive profiles were identified. Cross-cohort model generalizability, at both the subject and the group level, was excellent, indicating reliable performance in previously unseen data. The proposed model is a promising tool for capturing heterogeneity among older adults at early at-risk states for Alzheimer's disease in applied settings. The implementation of atrophy subtype- and stage-specific end points might increase the statistical power of pharmacological trials targeting early Alzheimer's disease.
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Affiliation(s)
- Hannah Baumeister
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - Jacob W Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
| | - Philip S Insel
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University of Bonn Medical Center, 53127 Bonn, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University of Bonn Medical Center, 53127 Bonn, Germany
| | - Melina Stark
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University of Bonn Medical Center, 53127 Bonn, Germany
| | - Helena M Gellersen
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, 39120 Magdeburg, Germany
| | - Matthias C Schmid
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Institute for Medical Biometry, University Hospital Bonn, 53127 Bonn, Germany
| | - Falk Lüsebrink
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - Frederic Brosseron
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, 39120 Magdeburg, Germany
| | - Silka D Freiesleben
- German Center for Neurodegenerative Diseases (DZNE), 10117 Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Lukas Preis
- Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Luisa-Sophie Schneider
- Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Eike J Spruth
- German Center for Neurodegenerative Diseases (DZNE), 10117 Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Slawek Altenstein
- German Center for Neurodegenerative Diseases (DZNE), 10117 Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Andrea Lohse
- Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University of Bonn Medical Center, 53127 Bonn, Germany
| | - Ina R Vogt
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Claudia Bartels
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Björn H Schott
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, 37075 Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), 37075 Göttingen, Germany
- Leibniz Institute for Neurobiology, 39118 Magdeburg, Germany
| | - Ayda Rostamzadeh
- Department of Psychiatry, Medical Faculty, University of Cologne, 50937 Cologne, Germany
| | - Wenzel Glanz
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - Enise I Incesoy
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, 39120 Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, 39120 Magdeburg, Germany
| | - Michaela Butryn
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), Ludwig-Maximilians-Universität, 81377 Munich, Germany
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield S10 2HQ, UK
- Department of Neuroradiology, Ludwig-Maximilians-Universität, 81377 Munich, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), 18147 Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, 18147 Rostock, Germany
| | - Doreen Goerss
- German Center for Neurodegenerative Diseases (DZNE), 18147 Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, 18147 Rostock, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), 72076 Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, 72076 Tübingen, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Peter Dechent
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Göttingen, 37075 Göttingen, Germany
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), Ludwig-Maximilians-Universität, 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, 72076 Tübingen, Germany
| | - Anika Wuestefeld
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
| | - Danielle van Westen
- Diagnostic Radiology, Institution of Clinical Sciences Lund, Lund University, 211 84 Lund, Sweden
- Image and Function, Skåne University Hospital, 211 84 Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, 211 84 Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, 22184 Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 205 02 Malmö, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 205 02 Malmö, Sweden
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurology, University of Bonn, 53127 Bonn, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), 72076 Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, 72076 Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research, 72076 Tübingen, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), 18147 Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, 18147 Rostock, Germany
| | - Robert Perneczky
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London SW7 2AZ, UK
| | - Katharina Buerger
- Institute for Stroke and Dementia Research (ISD), Ludwig-Maximilians-Universität, 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University of Bonn Medical Center, 53127 Bonn, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), 10117 Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Department of Psychiatry and Psychotherapy, Technical University of Munich, 81675 Munich, Germany
- Centre for Clinical Brain Sciences, University of Edinburgh and UK DRI, Edinburgh EH16 4SB, UK
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), 10117 Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Alfredo Ramirez
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University of Bonn Medical Center, 53127 Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50931 Cologne, Germany
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, 50931 Cologne, Germany
- Department of Psychiatry & Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, The University of Texas at San Antonio, San Antonio, TX 78229, USA
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, 37075 Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), 37075 Göttingen, Germany
- Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Michael T Heneka
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 4362, Belvaux, Luxembourg
| | - Michael Wagner
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University of Bonn Medical Center, 53127 Bonn, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Psychiatry, Medical Faculty, University of Cologne, 50937 Cologne, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50931 Cologne, Germany
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 205 02 Malmö, Sweden
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 222 42 Lund, Sweden
- Center for Behavioral Brain Sciences (CBBS), Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany
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238
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Mencarelli L, Torso M, Borghi I, Assogna M, Pezzopane V, Bonnì S, Di Lorenzo F, Santarnecchi E, Giove F, Martorana A, Bozzali M, Ridgway GR, Chance SA, Koch G. Macro and micro structural preservation of grey matter integrity after 24 weeks of rTMS in Alzheimer's disease patients: a pilot study. Alzheimers Res Ther 2024; 16:152. [PMID: 38970141 PMCID: PMC11225141 DOI: 10.1186/s13195-024-01501-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 06/12/2024] [Indexed: 07/07/2024]
Abstract
Alzheimer's Disease (AD) is characterized by structural and functional dysfunction involving the Default Mode Network (DMN), for which the Precuneus (PC) is a key node. We proposed a randomized double-blind pilot study to determine neurobiological changes after 24 weeks of PC-rTMS in patients with mild-to-moderate AD. Sixteen patients were randomly assigned to SHAM or PC-rTMS, and received an intensive 2-weeks course with daily rTMS sessions, followed by a maintenance phase in which rTMS has been applied once a week. Before and after the treatment structural and functional MRIs were collected. Our results showed macro- and micro-structural preservation in PC-rTMS compared to SHAM-rTMS group after 24 weeks of treatment, correlated to an increase of functional connectivity (FC) within the PC in the PC-rTMS group. Even if preliminary, these results trigger the possibility of using PC-rTMS to arrest atrophy progression by manipulating distributed network connectivity patterns.
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Affiliation(s)
- Lucia Mencarelli
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
| | - Mario Torso
- Oxford Brain Diagnostics Ltd, New Rd, Oxford, OX1 1BY, UK
| | - Ilaria Borghi
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Luigi Borsari, 46, Ferrara, 44121, Italy
| | - Martina Assogna
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
| | - Valentina Pezzopane
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Via Fossato di Mortara, 19, Ferrara, 44121, Italy
| | - Sonia Bonnì
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
| | - Francesco Di Lorenzo
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
| | - Emiliano Santarnecchi
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Massachusetts General Hospital & Harvard Medical School, 125 Nashua Street, Boston, MA, 02114- 1107, USA
| | - Federico Giove
- Cognitive and Motor Rehabilitation and Neuroimaging Unit, IRCCS Fondazione Santa Lucia, Via Ardeatina 306, Rome, 00179, Italy
- MARBILab, Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Via Panisperna 89 A, Rome, 00184, Italy
| | - Alessandro Martorana
- Department of Systems Medicine, Memory Clinic, University of Tor Vergata, Via Montpellier 1, Rome, 00133, Italy
| | - Marco Bozzali
- Neuroscience Department "Rita Levi Montalcini", University of Turin, Via Cherasco, 15, Turin, 10126, Italy
| | | | | | - Giacomo Koch
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy.
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Luigi Borsari, 46, Ferrara, 44121, Italy.
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Via Fossato di Mortara, 19, Ferrara, 44121, Italy.
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Lerch O, Ferreira D, Stomrud E, van Westen D, Tideman P, Palmqvist S, Mattsson-Carlgren N, Hort J, Hansson O, Westman E. Predicting progression from subjective cognitive decline to mild cognitive impairment or dementia based on brain atrophy patterns. Alzheimers Res Ther 2024; 16:153. [PMID: 38970077 PMCID: PMC11225196 DOI: 10.1186/s13195-024-01517-5] [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: 09/05/2023] [Accepted: 06/24/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is a progressive neurodegenerative disorder where pathophysiological changes begin decades before the onset of clinical symptoms. Analysis of brain atrophy patterns using structural MRI and multivariate data analysis are an effective tool in identifying patients with subjective cognitive decline (SCD) at higher risk of progression to AD dementia. Atrophy patterns obtained from models trained to classify advanced AD versus normal subjects, may not be optimal for subjects at an early stage, like SCD. In this study, we compared the accuracy of the SCD progression prediction using the 'severity index' generated using a standard classification model trained on patients with AD dementia versus a new model trained on β-amyloid (Aβ) positive patients with amnestic mild cognitive impairment (aMCI). METHODS We used structural MRI data of 504 patients from the Swedish BioFINDER-1 study cohort (cognitively normal (CN), Aβ-negative = 220; SCD, Aβ positive and negative = 139; aMCI, Aβ-positive = 106; AD dementia = 39). We applied multivariate data analysis to create two predictive models trained to discriminate CN individuals from either individuals with Aβ positive aMCI or AD dementia. Models were applied to individuals with SCD to classify their atrophy patterns as either high-risk "disease-like" or low-risk "CN-like". Clinical trajectory and model accuracy were evaluated using 8 years of longitudinal data. RESULTS In predicting progression from SCD to MCI or dementia, the standard, dementia-based model, reached 100% specificity but only 10.6% sensitivity, while the new, aMCI-based model, reached 72.3% sensitivity and 60.9% specificity. The aMCI-based model was superior in predicting progression from SCD to MCI or dementia, reaching a higher receiver operating characteristic area under curve (AUC = 0.72; P = 0.037) in comparison with the dementia-based model (AUC = 0.57). CONCLUSION When predicting conversion from SCD to MCI or dementia using structural MRI data, prediction models based on individuals with milder levels of atrophy (i.e. aMCI) may offer superior clinical value compared to standard dementia-based models.
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Affiliation(s)
- Ondrej Lerch
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, 15006, Czech Republic.
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, 14183, Sweden.
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, 14183, Sweden
- Department of Radiology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, 20502, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, 21428, Sweden
| | - Danielle van Westen
- Diagnostic Radiology, Institution for Clinical Sciences Lund, Lund University, Lund, 22184, Sweden
| | - Pontus Tideman
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, 20502, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, 21428, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, 20502, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, 21428, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, 20502, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, 21428, Sweden
| | - Jakub Hort
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, 15006, Czech Republic
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, 20502, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, 21428, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, 14183, Sweden
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE58AF, UK
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He J, Wu J, Liu J, Wu H, Hua H. Cognitive impairment and the gut-brain axis during 2014-2023: a bibliometric analysis. Front Neurol 2024; 15:1407956. [PMID: 39036641 PMCID: PMC11257987 DOI: 10.3389/fneur.2024.1407956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 06/28/2024] [Indexed: 07/23/2024] Open
Abstract
Background The burden on society grows as the number of individuals with cognitive impairment rises. Numerous research have discovered a connection between cognitive impairment and the gut-brain axis, which is useful in examining the pathophysiology of cognitive impairment and potential therapeutic approaches. As a result, this article explores developments and trends in the research concerning the gut-brain axis and cognitive impairment through a bibliometric analysis of the contributions made by various countries/regions, institutions, authors, and journals. Methods We looked for articles on gut-brain axis and cognitive impairment from 2014 to 2023 in the Web of Science Core Collection. For the descriptive analysis, figures and tables were taken using GraphPad Prism 6 and WPS Office 2024. For the visual analysis of the countries/regions, institutions, authors, and keywords, VOSviewer was utilized. Results We obtained 458 publications from 1 January 2014 to 9 September 2023. The country with the most publications (175, 38.21%) was China. The country with the greatest total number of citations (3,138, 17.22%) was the United States of America. The highest number of articles (15, 3.26%) was issued by Zhejiang University. The most published first author is Karsas M. In this field, Nutrients have published the most articles (24). The most often occurring keywords include "Alzheimer's disease," "cognitive impairment," "gut microbiota," "inflammation," "diet," etc. "Stroke," "tau," "probiotics," "exercise," "fecal microbiota transplantation," etc. emerged later. Conclusion An increasing amount of research has focused on the connection between cognitive impairment and the gut-brain axis. In this area, the United States of America and China have both made significant contributions. The author team's collaboration has to be improved. Our study contributes to understanding the field's current state and predicting its future trend.
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Affiliation(s)
- Jindi He
- Rehabilitation Department, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, China
| | - Jiaxun Wu
- Digestive Department, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, China
| | - Juan Liu
- Rehabilitation Department, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, China
| | - Hangcai Wu
- Rehabilitation Department, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, China
| | - Heliu Hua
- Rehabilitation Department, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, China
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Xu Q, Wang J, Li H, Gao Y. Association between serum neurofilament light chains (sNfL) and neurologic disorders in a representative sample of US adults: a cross-sectional study. Rev Clin Esp 2024:S2254-8874(24)00092-4. [PMID: 38972635 DOI: 10.1016/j.rceng.2024.07.002] [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: 05/04/2024] [Accepted: 06/18/2024] [Indexed: 07/09/2024]
Abstract
BACKGROUND While increased neurofilament light chain (NfL) in serum concentrations are linked to the progression of several neurological conditions, their distribution and implications within the general adult population remain largely unexplored. The current research aims to clarify the relationship between serum NfL levels and neurological disorders in a broad and representative population sample. METHODS We utilized information gathered from 1751 adults involved in the 2013-2014 cycle of the National Health and Nutrition Examination Survey . Our analytical approach encompassed logistic regression, smoothed curve fitting, and subgroup analyses to identify potential correlations between serum NfL levels and neurological conditions, such as depression, severe hearing and visual impairments, stroke, subjective memory deficits, and sleep problems. RESULTS After adjusting for all confounders, we found that higher serum NfL levels were significantly associated with increased risks of depression, stroke, subjective memory deficits, and longer sleep duration (p < 0.05). Subgroup analyses supported these findings. Additionally, BMI significantly influenced the relationship between serum NfL levels and long-term subjective memory decline. CONCLUSION Our research shows that higher serum NfL levels are strongly related to an elevated risk for several neurological disorders. These findings highlight the role of serum NfL serving as a critical marker for early detection and monitoring of neurological conditions, emphasizing its importance in both clinical and public health settings.
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Affiliation(s)
- Qi Xu
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Nanyang Medical College, Nanyang, China; Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
| | - Jiale Wang
- Department of Internal Medicine, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China
| | - Hanzhi Li
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Nanyang Medical College, Nanyang, China
| | - Yuwan Gao
- Department of Ophthalmology, The First Affiliated Hospital of Nanyang Medical College, Nanyang, China
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Li L, Yang C, Jia M, Wang Y, Zhao Y, Li Q, Gong J, He Y, Xu K, Liu X, Chen X, Hu J, Liu Z. Synbiotic therapy with Clostridium sporogenes and xylan promotes gut-derived indole-3-propionic acid and improves cognitive impairments in an Alzheimer's disease mouse model. Food Funct 2024. [PMID: 38967039 DOI: 10.1039/d4fo00886c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/06/2024]
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized primarily by cognitive impairment. Recent investigations have highlighted the potential of nutritional interventions that target the gut-brain axis, such as probiotics and prebiotics, in forestalling the onset of AD. In this study, whole-genome sequencing was employed to identify xylan as the optimal carbon source for the tryptophan metabolism regulating probiotic Clostridium sporogenes (C. sporogenes). Subsequent in vivo studies demonstrated that administration of a synbiotic formulation comprising C. sporogenes (1 × 1010 CFU per day) and xylan (1%, w/w) over a duration of 30 days markedly enhanced cognitive performance and spatial memory faculties in the 5xFAD transgenic AD mouse model. The synbiotic treatment significantly reduced amyloid-β (Aβ) accumulation in the cortex and hippocampus of the brain. Importantly, synbiotic therapy substantially restored the synaptic ultrastructure in AD mice and suppressed neuroinflammatory responses. Moreover, the intervention escalated levels of the microbial metabolite indole-3-propionic acid (IPA) and augmented the relative prevalence of IPA-synthesizing bacteria, Lachnospira and Clostridium, while reducing the dominant bacteria in AD, such as Aquabacterium, Corynebacterium, and Romboutsia. Notably, synbiotic treatment also prevented the disruption of gut barrier integrity. Correlation analysis indicated a strong positive association between gut microbiota-generated IPA levels and behavioral changes. In conclusion, this study demonstrates that synbiotic supplementation significantly improves cognitive and intellectual deficits in 5xFAD mice, which could be partly attributed to enhanced IPA production by gut microbiota. These findings provide a theoretical basis for considering synbiotic therapy as a novel microbiota-targeted approach for the treatment of metabolic and neurodegenerative diseases.
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Affiliation(s)
- Ling Li
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Cong Yang
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mengzhen Jia
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yuhao Wang
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yu Zhao
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Qingyuan Li
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jun Gong
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ying He
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Kun Xu
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Xuebo Liu
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xuhui Chen
- Peking University Shenzhen Hospital, Shenzhen, Guangdong, 518004, China
| | - Jun Hu
- Peking University Shenzhen Hospital, Shenzhen, Guangdong, 518004, China
| | - Zhigang Liu
- Laboratory of Functional Chemistry and Nutrition of Food, College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
- Northwest A&F University Shenzhen Research Institute, Shenzhen, Guangdong, 518000, China
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Yang Y, Yu K, Gao S, Yu S, Xiong D, Qin C, Chen H, Tang J, Tang N, Zhu H. Alzheimer's Disease Knowledge Graph Enhances Knowledge Discovery and Disease Prediction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.03.601339. [PMID: 39005357 PMCID: PMC11245034 DOI: 10.1101/2024.07.03.601339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Background Alzheimer's disease (AD), a progressive neurodegenerative disorder, continues to increase in prevalence without any effective treatments to date. In this context, knowledge graphs (KGs) have emerged as a pivotal tool in biomedical research, offering new perspectives on drug repurposing and biomarker discovery by analyzing intricate network structures. Our study seeks to build an AD-specific knowledge graph, highlighting interactions among AD, genes, variants, chemicals, drugs, and other diseases. The goal is to shed light on existing treatments, potential targets, and diagnostic methods for AD, thereby aiding in drug repurposing and the identification of biomarkers. Results We annotated 800 PubMed abstracts and leveraged GPT-4 for text augmentation to enrich our training data for named entity recognition (NER) and relation classification. A comprehensive data mining model, integrating NER and relationship classification, was trained on the annotated corpus. This model was subsequently applied to extract relation triplets from unannotated abstracts. To enhance entity linking, we utilized a suite of reference biomedical databases and refine the linking accuracy through abbreviation resolution. As a result, we successfully identified 3,199,276 entity mentions and 633,733 triplets, elucidating connections between 5,000 unique entities. These connections were pivotal in constructing a comprehensive Alzheimer's Disease Knowledge Graph (ADKG). We also integrated the ADKG constructed after entity linking with other biomedical databases. The ADKG served as a training ground for Knowledge Graph Embedding models with the high-ranking predicted triplets supported by evidence, underscoring the utility of ADKG in generating testable scientific hypotheses. Further application of ADKG in predictive modeling using the UK Biobank data revealed models based on ADKG outperforming others, as evidenced by higher values in the areas under the receiver operating characteristic (ROC) curves. Conclusion The ADKG is a valuable resource for generating hypotheses and enhancing predictive models, highlighting its potential to advance AD's disease research and treatment strategies.
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Affiliation(s)
- Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill
| | - Kaixian Yu
- Independent Researcher, Shanghai, P.R. China
| | - Shan Gao
- Department of Mathematics and Statistics, Yunnan University
| | - Sheng Yu
- Center for Statistics Science, Tsinghua University
| | - Di Xiong
- Department of Statistics, Shanghai University
| | - Chuanyang Qin
- Department of Mathematics and Statistics, Yunnan University
| | - Huiyuan Chen
- Department of Mathematics and Statistics, Yunnan University
| | - Jiarui Tang
- Department of Biostatistics, University of North Carolina at Chapel Hill
| | - Niansheng Tang
- Department of Mathematics and Statistics, Yunnan University
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill
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Damsgaard L, Janbek J, Laursen TM, Vestergaard K, Gottrup H, Jensen-Dahm C, Waldemar G. Prescription medication use in the 10 years prior to diagnosis of young onset Alzheimer's disease: a nationwide nested case-control study. Alzheimers Res Ther 2024; 16:150. [PMID: 38970052 PMCID: PMC11225233 DOI: 10.1186/s13195-024-01523-7] [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: 04/10/2024] [Accepted: 06/28/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND Patients with young onset Alzheimer's disease (YOAD) face long diagnostic delays. Prescription medication use may provide insights into early signs and symptoms, which may help facilitate timely diagnosis. METHODS In a register-based nested case-control study, we examined medication use for everyone diagnosed with YOAD in a Danish memory clinic during 2016-2020 compared to cognitively healthy controls. Prescription medication use were grouped into 13 overall categories (alimentary tract and metabolism, blood and blood forming organs, cardiovascular system, dermatologicals, genitourinary system and sex hormones, systemic hormonal preparations, antiinfectives for systemic use, antineoplastic and immunomodulating agents, musculo-skeletal system, nervous system, antiparasitic products, respiratory system, and sensory organs). Further stratifications were done for predetermined subcategories with a use-prevalence of at least 5% in the study population. Conditional logistic regression produced odds ratios, which given the use of incidence-density matching is interpretable as incidence rate ratios (IRRs). The association between prescription medication use and subsequent YOAD diagnosis was examined in the entire 10-year study period and in three time-intervals. RESULTS The study included 1745 YOAD cases and 5235 controls. In the main analysis, several overall categories showed significant associations with YOAD in one or more time-intervals, namely blood and blood forming organs and nervous system. Prescription medication use in the nervous system category was increased for YOAD cases compared to controls already 10->5 years prior to diagnosis (IRR 1.17, 95% CI 1.05-1.31), increasing to 1.57 (95% CI 1.39-1.78) in the year preceding diagnosis. This was largely driven by antidepressant and antipsychotic use, and especially prominent for first-time users. CONCLUSIONS In this study, medication use in several categories was associated with YOAD. Onset of treatment-requiring psychiatric symptoms such as depression or psychosis in mid-life may serve as potential early indicators of YOAD.
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Affiliation(s)
- Line Damsgaard
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
| | - Janet Janbek
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Thomas Munk Laursen
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
| | - Karsten Vestergaard
- Dementia Clinic, Department of Neurology, Aalborg University Hospital, Aalborg, Denmark
| | - Hanne Gottrup
- Dementia Clinic, Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
| | - Christina Jensen-Dahm
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Gunhild Waldemar
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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de Souza Souto JJ, Edite Casé de Oliveira M, Silva GM, Nascimento de Sousa JM, Fernandes Franco CI, Dos Santos NA. Transcranial direct current stimulation and cognitive changes in Parkinson's disease, a systematic review with meta-analysis and meta-regression. APPLIED NEUROPSYCHOLOGY. ADULT 2024:1-11. [PMID: 38967481 DOI: 10.1080/23279095.2024.2367108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/06/2024]
Abstract
Parkinson's disease is the second most common neurodegenerative disease, but therapeutic options such as neuromodulation continue to show variable effects, making clinical management of the disease difficult. This systematic review with meta-analysis and meta-regression aimed to analyze the isolated effect of cortical modulation with transcranial direct current stimulation (tDCS) compared to sham stimulation on cognitive changes in people with Parkinson's disease. The databases used were: Web of Science, Scopus, PsycINFO, PubMed, and Cochrane. The results showed that tDCS can influence the improvement of cognition in PD (Inverse Variance:0.24 [95% Confidence Interval: 0.09 to -0.40], p < 0.00). The meta-analysis showed that active tDCS can influence cognitive function by improving aspects related to memory (Inverse Variance:0.34 [95% Confidence Interval: 0.07 to 0.61], p < 0.01) and reducing reaction time in cognitive tasks (Inverse Variance:0.42 [95% Confidence Interval: 0.07 to 0.76], p < 0.02). Innovative meta-regression analyses showed that variables such as age (Q = 2.54, df = 1, p < 0.11), education level (Q = 2.62, df = 1, p < 0.10), disease duration (Q = 0.01, df = 1, p < 0.92), and Unified PD Rating Scale stage (Q = 0.01, df = 1, p < 0.92) did not influence the results. Thus, tDCS may be a therapeutic option for cognitive changes in people with PD, and we suggest further studies to identify protocols that can be replicated.
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246
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Leo DG, Keller SS, Proietti R. "Close your eyes and relax": the role of hypnosis in reducing anxiety, and its implications for the prevention of cardiovascular diseases. Front Psychol 2024; 15:1411835. [PMID: 39035095 PMCID: PMC11258040 DOI: 10.3389/fpsyg.2024.1411835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 06/21/2024] [Indexed: 07/23/2024] Open
Abstract
Anxiety is the most common form of mental health disorder, affecting millions of people worldwide. Psychosocial interventions such as mindfulness and cognitive behavioral therapy (CBT) have been suggested as an effective treatment in the management of general anxiety and anxiety disorders, with emerging evidence also suggesting the effectiveness of hypnosis. Moreover, anxiety has shown to be linked to the onset and development of several cardiovascular diseases (CVD), which are the leading cause of global death. In this paper, we review the current literature to examine the role that anxiety has on the onset and development of CVD and summarize the current knowledge on the role that hypnosis and hypnotherapy have in reducing anxiety, also explaining how this can impact the cardiovascular system and the prevention of CVD. Review of the evidence suggests that hypnosis and hypnotherapy are effective in treating anxiety and may positively affect the heart and the cardiovascular system, reducing sympathetic activation and increasing parasympathetic tone, potentially preventing the onset of CVD related to increased sympathetic activation. However, further studies are required to further understand how hypnosis and hypnotherapy affect the cardiovascular system through investigation of the neurophysiological components of the hypnotic state and of the mind-body relationship. Healthcare systems should embed mental health screening in patients at risk of developing CVD as part of the clinical pathway and consider the role that hypnosis and hypnotherapy may play in the management of CVD.
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Affiliation(s)
- Donato Giuseppe Leo
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, Faculty of Health and Life Science, University of Liverpool, Liverpool, United Kingdom
- Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart and Chest Hospital, Liverpool, United Kingdom
| | - Simon S. Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Riccardo Proietti
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, Faculty of Health and Life Science, University of Liverpool, Liverpool, United Kingdom
- Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart and Chest Hospital, Liverpool, United Kingdom
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Harisinghani A, Cottrell C, Donelan K, Lam AD, Pulsifer M, Santoro SL. Practicalities (and real-life experiences) of dementia in adults with Down syndrome. AMERICAN JOURNAL OF MEDICAL GENETICS. PART C, SEMINARS IN MEDICAL GENETICS 2024:e32098. [PMID: 38967370 DOI: 10.1002/ajmg.c.32098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/06/2024] [Accepted: 06/15/2024] [Indexed: 07/06/2024]
Abstract
Adults with down syndrome (DS) have a lifetime dementia risk in excess of 95%, with a median age of onset of 55 years, due to trisomy 21. Co-occurring Alzheimer's disease (AD) has increased morbidity and mortality, and it is now recommended to screen for AD in all adults with DS beginning at 40 years of age. In this manuscript, we present two clinical cases of adults with DS who developed AD summarizing their medical histories, presenting symptoms, path to diagnosis and psychosocial aspects of care collected from retrospective chart review with caregiver consent. These two cases were chosen due to their complexity and interwoven nature of the medical and psychosocial aspects, and highlight the complexity and nuance of caring for patients with DS and AD.
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Affiliation(s)
- Ayesha Harisinghani
- Down Syndrome Program, Division of Medical Genetics and Metabolism, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Clorinda Cottrell
- Down Syndrome Program, Division of Medical Genetics and Metabolism, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Karen Donelan
- The Mongan Institute, Survey Research Unit, MGH, Boston, Massachusetts, USA
- Heller School for Social Policy and Management, Brandeis University, Waltham, Massachusetts, USA
| | - Alice D Lam
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Margaret Pulsifer
- Psychology Assessment Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephanie L Santoro
- Down Syndrome Program, Division of Medical Genetics and Metabolism, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
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248
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Gong Q, Fu M, Wang J, Zhao S, Wang H. Potential Immune-Inflammatory Proteome Biomarkers for Guiding the Treatment of Patients with Primary Acute Angle-Closure Glaucoma Caused by COVID-19. J Proteome Res 2024; 23:2587-2597. [PMID: 38836775 PMCID: PMC11232099 DOI: 10.1021/acs.jproteome.4c00325] [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: 04/16/2024] [Revised: 05/21/2024] [Accepted: 05/23/2024] [Indexed: 06/06/2024]
Abstract
Primary acute angle-closure glaucoma (PAACG) is a sight-threatening condition that can lead to blindness. With the increasing incidence of COVID-19, a multitude of people are experiencing acute vision loss and severe swelling of the eyes and head. These patients were then diagnosed with acute angle closure, with or without a history of PACG. However, the mechanism by which viral infection causes PACG has not been clarified. This is the first study to explore the specific inflammatory proteomic landscape in SARS-CoV-2-induced PAACG. The expression of 92 inflammation-related proteins in 19 aqueous humor samples from PAACGs or cataract patients was detected using the Olink Target 96 Inflammation Panel based on a highly sensitive and specific proximity extension assay technology. The results showed that 76 proteins were significantly more abundant in the PAACG group than in the cataract group. Notably, the top eight differentially expressed proteins were IL-8, MCP-1, TNFRSF9, DNER, CCL4, Flt3L, CXCL10, and CD40. Generally, immune markers are related to inflammation, macrophage activation, and viral infection, revealing the crucial role of macrophages in the occurrence of PAACGs caused by SARS-CoV-2.
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Affiliation(s)
- Qiaoyun Gong
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
| | - Mingshui Fu
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
| | - Jingyi Wang
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
| | - Shuzhi Zhao
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
| | - Haiyan Wang
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
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249
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Lee S, Ju IG, Eo H, Kim JH, Choi Y, Oh MS. Rhei Undulati Rhizoma attenuates memory decline and reduces amyloid-β induced neuritic dystrophy in 5xFAD mouse. Chin Med 2024; 19:95. [PMID: 38965625 PMCID: PMC11223309 DOI: 10.1186/s13020-024-00966-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 06/22/2024] [Indexed: 07/06/2024] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is a common type of dementia characterized by amyloid-β (Aβ) accumulation, lysosomal dysfunction, and tau hyperphosphorylation, leading to neurite dystrophy and memory loss. This study aimed to investigate whether Rhei Undulati Rhizoma (RUR), which has been reported to have anti-neuroinflammatory effect, attenuates Aβ-induced memory impairment, neuritic dystrophy, and tau hyperphosphorylation, and to reveal its mode of action. METHODS Five-month-old 5xFAD mice received RUR (50 mg/kg) orally for 2 months. The Y-maze test was used to assess working memory. After behavioral testing, brain tissue was analyzed using thioflavin S staining, western blotting, and immunofluorescence staining to investigate the mode of action of RUR. To confirm whether RUR directly reduces Aβ aggregation, a thioflavin T assay and dot blot were performed after incubating Aβ with RUR. RESULTS RUR administration attenuated the Aβ-induced memory impairment in 5xFAD mice. Furthermore, decreased accumulation of Aβ was observed in the hippocampus of the RUR-treated 5xFAD group compare to the vehicle-treated 5xFAD group. Moreover, RUR reduced the dystrophic neurites (DNs) that accumulate impaired endolysosomal organelles around Aβ. In particular, RUR treatment downregulated the expression of β-site amyloid precursor protein cleaving enzyme 1 and the hyperphosphorylation of tau within DNs. Additionally, RUR directly suppressed the aggregation of Aβ, and eliminated Aβ oligomers in vitro. CONCLUSIONS This study showed that RUR could attenuate Aβ-induced pathology and directly regulate the aggregation of Aβ. These results suggest that RUR could be an efficient material for AD treatment through Aβ regulation.
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Affiliation(s)
- Seungmin Lee
- Department of Biomedical and Pharmaceutical Sciences, Graduate School, Kyung Hee University, 26, Kyungheedae-Ro, Dongdaemun-Gu, Seoul, 02447, Republic of Korea
| | - In Gyoung Ju
- Department of Oriental Pharmaceutical Science and Kyung Hee East-West Pharmaceutical Research Institute, College of Pharmacy, Kyung Hee University, 26, Kyungheedae-Ro, Dongdaemun-Gu, Seoul, 02447, Republic of Korea
| | - Hyeyoon Eo
- Department of Biomedical and Pharmaceutical Sciences, Graduate School, Kyung Hee University, 26, Kyungheedae-Ro, Dongdaemun-Gu, Seoul, 02447, Republic of Korea
| | - Jin Hee Kim
- Department of Biomedical and Pharmaceutical Sciences, Graduate School, Kyung Hee University, 26, Kyungheedae-Ro, Dongdaemun-Gu, Seoul, 02447, Republic of Korea
| | - Yujin Choi
- Department of Biomedical and Pharmaceutical Sciences, Graduate School, Kyung Hee University, 26, Kyungheedae-Ro, Dongdaemun-Gu, Seoul, 02447, Republic of Korea
| | - Myung Sook Oh
- Department of Biomedical and Pharmaceutical Sciences, Graduate School, Kyung Hee University, 26, Kyungheedae-Ro, Dongdaemun-Gu, Seoul, 02447, Republic of Korea.
- Department of Oriental Pharmaceutical Science and Kyung Hee East-West Pharmaceutical Research Institute, College of Pharmacy, Kyung Hee University, 26, Kyungheedae-Ro, Dongdaemun-Gu, Seoul, 02447, Republic of Korea.
- Department of Integrated Drug Development and Natural Products, Graduate School, Kyung Hee University, 26, Kyungheedae-Ro, Dongdaemun-Gu, Seoul, 02447, Republic of Korea.
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250
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Shekari M, Vállez García D, Collij LE, Altomare D, Heeman F, Pemberton H, Roé Vellvé N, Bullich S, Buckley C, Stephens A, Farrar G, Frisoni G, Klunk WE, Barkhof F, Gispert JD. Stress testing the Centiloid: Precision and variability of PET quantification of amyloid pathology. Alzheimers Dement 2024. [PMID: 38961808 DOI: 10.1002/alz.13883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 03/21/2024] [Accepted: 03/22/2024] [Indexed: 07/05/2024]
Abstract
INTRODUCTION Assessing the potential sources of bias and variability of the Centiloid (CL) scale is fundamental for its appropriate clinical application. METHODS We included 533 participants from AMYloid imaging to Prevent Alzheimer's Disease (AMYPAD DPMS) and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts. Thirty-two CL pipelines were created using different combinations of reference region (RR), RR and target types, and quantification spaces. Generalized estimating equations stratified by amyloid positivity were used to assess the impact of the quantification pipeline, radiotracer, age, brain atrophy, and harmonization status on CL. RESULTS RR selection and RR type impact CL the most, particularly in amyloid-negative individuals. The standard CL pipeline with the whole cerebellum as RR is robust against brain atrophy and differences in image resolution, with 95% confidence intervals below ± 3.95 CL for amyloid beta positivity cutoffs (CL < 24). DISCUSSION The standard CL pipeline is recommended for most scenarios. Confidence intervals should be considered when operationalizing CL cutoffs in clinical and research settings. HIGHLIGHTS We developed a framework for evaluating Centiloid (CL) variability to different factors. Reference region selection and delineation had the highest impact on CL values. Whole cerebellum (WCB) and whole cerebellum plus brainstem (WCB+BSTM) as reference regions yielded consistent results across tracers. The standard CL pipeline is robust against atrophy and image resolution variation. Estimated within- and between-pipeline variability (95% confidence interval) in absolute CL units.
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Affiliation(s)
- Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - David Vállez García
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Daniele Altomare
- Memory Center, Department of Rehabilitation and Geriatrics, University Hospitals and University of Geneva, Genève, Switzerland
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, The University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Hugh Pemberton
- GE Healthcare Life Sciences, Amersham, UK
- Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | | | | | | | | | | | - Giovanni Frisoni
- Memory Center, Department of Rehabilitation and Geriatrics, University Hospitals and University of Geneva, Genève, Switzerland
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain
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