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Morozova I, Zorkina Y, Berdalin A, Ikonnikova A, Emelyanova M, Fedoseeva E, Antonova O, Gryadunov D, Andryushchenko A, Ushakova V, Abramova O, Zeltser A, Kurmishev M, Savilov V, Osipova N, Preobrazhenskaya I, Kostyuk G, Morozova A. Dynamics of Cognitive Impairment in MCI Patients over a Three-Year Period: The Informative Role of Blood Biomarkers, Neuroimaging, and Genetic Factors. Diagnostics (Basel) 2024; 14:1883. [PMID: 39272668 PMCID: PMC11394601 DOI: 10.3390/diagnostics14171883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2024] [Revised: 08/23/2024] [Accepted: 08/25/2024] [Indexed: 09/15/2024] Open
Abstract
Given the high growth rates of cognitive decline among the elderly population and the lack of effective etiological treatments, early diagnosis of cognitive impairment progression is an imperative task for modern science and medicine. It is of particular interest to identify predictors of an unfavorable subsequent course of cognitive disorders, specifically, rapid progression. Our study assessed the informative role of various risk factors on the dynamics of cognitive impairment among mild cognitive impairment (MCI) patients. The study included patients with MCI (N = 338) who underwent neuropsychological assessment, magnetic resonance imaging (MRI) examination, blood sampling for general and biochemical analysis, APOE genotyping, and polygenic risk score (PRS) evaluation. The APOE ε4/ε4 genotype was found to be associated with a diminished overall cognitive scores initial assessment and negative cognitive dynamics. No associations were found between cognitive changes and the PRS. The progression of cognitive impairment was associated with the width of the third ventricle and hematological parameters, specifically, hematocrit and erythrocyte levels. The absence of significant associations between the dynamics of cognitive decline and PRS over three years can be attributed to the provided suitable medical care for the prevention of cognitive impairment. Adding other risk factors and their inclusion in panels assessing the risk of progression of cognitive impairment should be considered.
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Affiliation(s)
- Irina Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
| | - Yana Zorkina
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
- V. Serbsky National Medical Research Centre of Psychiatry and Narcology, 119034 Moscow, Russia
| | - Alexander Berdalin
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
| | - Anna Ikonnikova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Marina Emelyanova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Elena Fedoseeva
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Olga Antonova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Dmitry Gryadunov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Alisa Andryushchenko
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
- Department of Mental Health, Faculty of Psychology, M. V. Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Valeriya Ushakova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
- V. Serbsky National Medical Research Centre of Psychiatry and Narcology, 119034 Moscow, Russia
- Department of Mental Health, Faculty of Psychology, M. V. Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Olga Abramova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
- V. Serbsky National Medical Research Centre of Psychiatry and Narcology, 119034 Moscow, Russia
| | - Angelina Zeltser
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
| | - Marat Kurmishev
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
| | - Victor Savilov
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
| | - Natalia Osipova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
| | - Irina Preobrazhenskaya
- Department of Nervous Diseases and Neurosurgery, I. M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia
| | - Georgy Kostyuk
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
- Department of Mental Health, Faculty of Psychology, M. V. Lomonosov Moscow State University, 119991 Moscow, Russia
- Department of Psychiatry and Psychosomatics, I. M. Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia
- Department of Psychiatry, Federal State Budgetary Educational Institution of Higher Education Russian Biotechnological University, 125080 Moscow, Russia
| | - Anna Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, 115191 Moscow, Russia
- V. Serbsky National Medical Research Centre of Psychiatry and Narcology, 119034 Moscow, Russia
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Kikuchi M, Miyashita A, Hara N, Kasuga K, Saito Y, Murayama S, Kakita A, Akatsu H, Ozaki K, Niida S, Kuwano R, Iwatsubo T, Nakaya A, Ikeuchi T. Polygenic effects on the risk of Alzheimer's disease in the Japanese population. Alzheimers Res Ther 2024; 16:45. [PMID: 38414085 PMCID: PMC10898021 DOI: 10.1186/s13195-024-01414-x] [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: 08/10/2023] [Accepted: 02/11/2024] [Indexed: 02/29/2024]
Abstract
BACKGROUND Polygenic effects have been proposed to account for some disease phenotypes; these effects are calculated as a polygenic risk score (PRS). This score is correlated with Alzheimer's disease (AD)-related phenotypes, such as biomarker abnormalities and brain atrophy, and is associated with conversion from mild cognitive impairment (MCI) to AD. However, the AD PRS has been examined mainly in Europeans, and owing to differences in genetic structure and lifestyle, it is unclear whether the same relationships between the PRS and AD-related phenotypes exist in non-European populations. In this study, we calculated and evaluated the AD PRS in Japanese individuals using genome-wide association study (GWAS) statistics from Europeans. METHODS In this study, we calculated the AD PRS in 504 Japanese participants (145 cognitively unimpaired (CU) participants, 220 participants with late mild cognitive impairment (MCI), and 139 patients with mild AD dementia) enrolled in the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) project. In order to evaluate the clinical value of this score, we (1) determined the polygenic effects on AD in the J-ADNI and validated it using two independent cohorts (a Japanese neuropathology (NP) cohort (n = 565) and the North American ADNI (NA-ADNI) cohort (n = 617)), (2) examined the AD-related phenotypes associated with the PRS, and (3) tested whether the PRS helps predict the conversion of MCI to AD. RESULTS The PRS using 131 SNPs had an effect independent of APOE. The PRS differentiated between CU participants and AD patients with an area under the curve (AUC) of 0.755 when combined with the APOE variants. Similar AUC was obtained when PRS calculated by the NP and NA-ADNI cohorts was applied. In MCI patients, the PRS was associated with cerebrospinal fluid phosphorylated-tau levels (β estimate = 0.235, p value = 0.026). MCI with a high PRS showed a significantly increased conversion to AD in APOE ε4 noncarriers with a hazard rate of 2.22. In addition, we also developed a PRS model adjusted for LD and observed similar results. CONCLUSIONS We showed that the AD PRS is useful in the Japanese population, whose genetic structure is different from that of the European population. These findings suggest that the polygenicity of AD is partially common across ethnic differences.
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Affiliation(s)
- Masataka Kikuchi
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo, 6-2-3 Kashiwanoha, Kashiwa, Chiba, 277-0882, Japan.
- Department of Medical Informatics, Graduate School of Medicine, Osaka University, Osaka, Japan.
| | - Akinori Miyashita
- Department of Molecular Genetics, Brain Research Institute, Niigata University, 1-757 Asahimachi, Niigata, 951-8585, Japan
| | - Norikazu Hara
- Department of Molecular Genetics, Brain Research Institute, Niigata University, 1-757 Asahimachi, Niigata, 951-8585, Japan
| | - Kensaku Kasuga
- Department of Molecular Genetics, Brain Research Institute, Niigata University, 1-757 Asahimachi, Niigata, 951-8585, Japan
| | - Yuko Saito
- Brain Bank for Aging Research (Department of Neuropathology), Tokyo Metropolitan Institute of Geriatrics and Gerontology, Tokyo, Japan
| | - Shigeo Murayama
- Brain Bank for Aging Research (Department of Neuropathology), Tokyo Metropolitan Institute of Geriatrics and Gerontology, Tokyo, Japan
- Brain Bank for Neurodevelopmental, Neurological and Psychiatric Disorders, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - Akiyoshi Kakita
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Hiroyasu Akatsu
- Department of General Medicine & General Internal Medicine, Nagoya City University Graduate School of Medicine, Nagoya, Japan
| | - Kouichi Ozaki
- Medical Genome Center, National Center for Geriatrics and Gerontology, Research Institute, Aichi, Japan
- RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Shumpei Niida
- Core Facility Administration, National Center for Geriatrics and Gerontology, Research Institute, Aichi, Japan
| | - Ryozo Kuwano
- Social Welfare Corporation Asahigawaso, Asahigawaso Research Institute, Okayama, Japan
| | - Takeshi Iwatsubo
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akihiro Nakaya
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo, 6-2-3 Kashiwanoha, Kashiwa, Chiba, 277-0882, Japan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, 1-757 Asahimachi, Niigata, 951-8585, Japan.
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Li Q, Zhan J, Feng Y, Liao Z, Li X. The Association of Body Mass Index with Cognition and Alzheimer's Disease Biomarkers in the Elderly with Different Cognitive Status: A Study from the Alzheimer's Disease Neuroimaging Initiative Database. J Alzheimers Dis Rep 2024; 8:9-24. [PMID: 38229832 PMCID: PMC10789287 DOI: 10.3233/adr-230163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 12/04/2023] [Indexed: 01/18/2024] Open
Abstract
Background The association of body mass index (BMI) with cognition and Alzheimer's disease (AD) biomarkers of the elderly remains inconclusive. Objective To investigate the relationship between BMI and cognition as well as AD biomarkers in the elderly with different cognitive status. Methods Participants with cognitively normal (CN) were included as the CN group. Participants with mild cognitive impairment and mild dementia were included as the cognitive impairment (CI) group. The relationship between BMI and AD biomarkers (cerebrospinal fluid Aβ42 and p-tau181, hippocampal volume [HV]), global cognition (Mini-Mental State Examination [MMSE]), memory, and executive function were explored. Results In the CI group, BMI was associated with MMSE (β= 0.03, p = 0.009), Aβ42 (β= 0.006, p = 0.029), p-tau181/Aβ42 ratio (β= -0.001, p = 0.011), and HV (β= 0.05, p < 0.001). However in the CN group, BMI exhibited associations with p-tau181 (β= 0.012, p = 0.014) and memory composite score (β= -0.04, p = 0.038), but not with p-tau181/Aβ42 ratio and HV. Moreover, mediation analysis showed that in the CI group, the positive effect of BMI on HV and MMSE score was partially mediated by diastolic blood pressure. Conclusion The association of BMI with cognition and AD biomarkers varies across different cognitive status. In particular, a lower BMI was associated with worse cognition, higher Aβ burden, and lower HV in individuals with CI. Clinical practice should strengthen the monitoring and management of BMI in patients with AD.
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Affiliation(s)
- Qin Li
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jiehong Zhan
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuxue Feng
- Department of Neurology, The Fifth People’s Hospital of Chongqing, Chongqing, China
| | - Zixuan Liao
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaofeng Li
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Neurology, The Fifth People’s Hospital of Chongqing, Chongqing, China
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Veitch DP, Weiner MW, Miller M, Aisen PS, Ashford MA, Beckett LA, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Nho KT, Nosheny R, Okonkwo O, Perrin RJ, Petersen RC, Rivera Mindt M, Saykin A, Shaw LM, Toga AW, Tosun D. The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022. Alzheimers Dement 2024; 20:652-694. [PMID: 37698424 PMCID: PMC10841343 DOI: 10.1002/alz.13449] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/27/2023] [Accepted: 08/01/2023] [Indexed: 09/13/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Melanie Miller
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Miriam A. Ashford
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Laurel A. Beckett
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | - Robert C. Green
- Division of GeneticsDepartment of MedicineBrigham and Women's HospitalBroad Institute Ariadne Labs and Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | - Kwangsik T. Nho
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Center for Computational Biology and BioinformaticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Rachel Nosheny
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | - Monica Rivera Mindt
- Department of PsychologyLatin American and Latino Studies InstituteAfrican and African American StudiesFordham UniversityNew YorkNew YorkUSA
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Andrew Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine and the PENN Alzheimer's Disease Research CenterCenter for Neurodegenerative ResearchPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro ImagingInstitute of Neuroimaging and InformaticsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
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Ling Y, Crotti A. Emerging Microglial Therapies and Targets in Clinical Trial. ADVANCES IN NEUROBIOLOGY 2024; 37:623-637. [PMID: 39207717 DOI: 10.1007/978-3-031-55529-9_35] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Modulation of microglia function for treatment of neurodegenerative and neuropsychiatric disorders is an emerging field of neuroscience drug development. This is largely attributed to human genetic association studies combined with biological evidence indicating that the innate immune system acts as a causal contributor superimposed on the reactive component of neuronal loss in neurological dysfunction. The identification of disease risk gene variants that encode immune-modulatory proteins in microglia provides tools to evaluate how microglia cellular function or dysfunction affect neuronal health. The development of clinical stage therapeutic compounds that modify myeloid cell function enables us to investigate how modulating microglia function could become a transformational approach to mitigate neurological disorders. Improving our ability to boost microglia-promoting homeostatic and reparative functions hopefully will translate into achieving a better outcome for patients affected by neurological diseases. In this chapter, we aim to provide an overview of the microglial emerging therapies and targets being studied in current clinical trials.
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Affiliation(s)
- Yan Ling
- Neuroscience Translational Medicine, Takeda Pharmaceutical Co. Ltd., Tokyo, Japan
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Lee SM, Shivakumar M, Xiao B, Jung SH, Nam Y, Yun JS, Choe EK, Jung YM, Oh S, Park JS, Jun JK, Kim D. Genome-wide polygenic risk scores for hypertensive disease during pregnancy can also predict the risk for long-term cardiovascular disease. Am J Obstet Gynecol 2023; 229:298.e1-298.e19. [PMID: 36933686 PMCID: PMC10504416 DOI: 10.1016/j.ajog.2023.03.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 03/09/2023] [Accepted: 03/09/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND Hypertensive disorders during pregnancy are associated with the risk of long-term cardiovascular disease after pregnancy, but it has not yet been determined whether genetic predisposition for hypertensive disorders during pregnancy can predict the risk for long-term cardiovascular disease. OBJECTIVE This study aimed to evaluate the risk for long-term atherosclerotic cardiovascular disease according to polygenic risk scores for hypertensive disorders during pregnancy. STUDY DESIGN Among UK Biobank participants, we included European-descent women (n=164,575) with at least 1 live birth. Participants were divided according to genetic risk categorized by polygenic risk scores for hypertensive disorders during pregnancy (low risk, score ≤25th percentile; medium risk, score 25th∼75th percentile; high risk, score >75th percentile), and were evaluated for incident atherosclerotic cardiovascular disease, defined as the new occurrence of one of the following: coronary artery disease, myocardial infarction, ischemic stroke, or peripheral artery disease. RESULTS Among the study population, 2427 (1.5%) had a history of hypertensive disorders during pregnancy, and 8942 (5.6%) developed incident atherosclerotic cardiovascular disease after enrollment. Women with high genetic risk for hypertensive disorders during pregnancy had a higher prevalence of hypertension at enrollment. After enrollment, women with high genetic risk for hypertensive disorders during pregnancy had an increased risk for incident atherosclerotic cardiovascular disease, including coronary artery disease, myocardial infarction, and peripheral artery disease, compared with those with low genetic risk, even after adjustment for history of hypertensive disorders during pregnancy. CONCLUSION High genetic risk for hypertensive disorders during pregnancy was associated with increased risk for atherosclerotic cardiovascular disease. This study provides evidence on the informative value of polygenic risk scores for hypertensive disorders during pregnancy in prediction of long-term cardiovascular outcomes later in life.
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Affiliation(s)
- Seung Mi Lee
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea; Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Obstetrics and Gynecology, Seoul National University Hospital, Seoul, Korea
| | - Manu Shivakumar
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Brenda Xiao
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Sang-Hyuk Jung
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Yonghyun Nam
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jae-Seung Yun
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Internal Medicine, Catholic University of Korea School of Medicine, Seoul, Korea
| | - Eun Kyung Choe
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Surgery, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea
| | - Young Mi Jung
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Sohee Oh
- Department of Biostatistics, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea
| | - Joong Shin Park
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Jong Kwan Jun
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Dokyoon Kim
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
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Takeuchi H, Kawashima R. Effects of adult education on cognitive function and risk of dementia in older adults: a longitudinal analysis. Front Aging Neurosci 2023; 15:1212623. [PMID: 37680542 PMCID: PMC10480502 DOI: 10.3389/fnagi.2023.1212623] [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: 04/26/2023] [Accepted: 07/18/2023] [Indexed: 09/09/2023] Open
Abstract
Introduction Mid/late-life cognitive activities are associated with a lower rate of subsequent cognitive decline and lower subsequent dementia risk over time. Methods In this study, we investigated the association between adult education class participation and subsequent cognitive decline and dementia risk over time after adjusting for baseline cognitive function and genetic risk of dementia, correcting for several potential confounding variables, using a large prospective cohort data of participants from the UK Biobank study followed from 2006 to 2010. Results The results revealed that participation in adult education classes at baseline was associated with greater subsequent retention of fluid intelligence score. Cox proportional hazard models revealed that subjects who participated in adult education classes showed a significantly lower risk of incident dementia 5 years after baseline compared with those that did not at baseline. Discussion In this study, we show that participation in adult education classes preceded greater retention of subsequent fluid intelligence and a lower risk of developing dementia after 5 years: this association did not change after adjusting for cognitive function at baseline or genetic predisposition to dementia. Accordingly, participation in such classes could reduce the risk of developing dementia.
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Affiliation(s)
- Hikaru Takeuchi
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Ryuta Kawashima
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Smart Aging Research Center, Tohoku University, Sendai, Japan
- Department of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
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He XY, Wu BS, Kuo K, Zhang W, Ma Q, Xiang ST, Li YZ, Wang ZY, Dong Q, Feng JF, Cheng W, Yu JT. Association between polygenic risk for Alzheimer's disease and brain structure in children and adults. Alzheimers Res Ther 2023; 15:109. [PMID: 37312172 DOI: 10.1186/s13195-023-01256-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 06/01/2023] [Indexed: 06/15/2023]
Abstract
BACKGROUND The correlations between genetic risk for Alzheimer's disease (AD) with comprehensive brain regions at a regional scale are still not well understood. We aim to explore whether these associations vary across different age stages. METHODS This study used large existing genome-wide association datasets to calculate polygenic risk score (PRS) for AD in two populations from the UK Biobank (N ~ 23 000) and Adolescent Brain Cognitive Development Study (N ~ 4660) who had multimodal macrostructural and microstructural magnetic resonance imaging (MRI) metrics. We used linear mixed-effect models to assess the strength of the association between AD PRS and multiple MRI metrics of regional brain structures at different stages of life. RESULTS Compared to those with lower PRSs, adolescents with higher PRSs had thinner cortex in the caudal anterior cingulate and supramarginal. In the middle-aged and elderly population, AD PRS had correlations with regional structure shrink primarily located in the cingulate, prefrontal cortex, hippocampus, thalamus, amygdala, and striatum, whereas the brain expansion was concentrated near the occipital lobe. Furthermore, both adults and adolescents with higher PRSs exhibited widespread white matter microstructural changes, indicated by decreased fractional anisotropy (FA) or increased mean diffusivity (MD). CONCLUSIONS In conclusion, our results suggest genetic loading for AD may influence brain structures in a highly dynamic manner, with dramatically different patterns at different ages. This age-specific change is consistent with the classical pattern of brain impairment observed in AD patients.
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Affiliation(s)
- Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Kevin Kuo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Qing Ma
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Shi-Tong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Yu-Zhu Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Zi-Yi Wang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai, China
- ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai, China.
- ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China.
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9
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Migliore L, Coppedè F. Gene-environment interactions in Alzheimer disease: the emerging role of epigenetics. Nat Rev Neurol 2022; 18:643-660. [PMID: 36180553 DOI: 10.1038/s41582-022-00714-w] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/18/2022] [Indexed: 12/15/2022]
Abstract
With the exception of a few monogenic forms, Alzheimer disease (AD) has a complex aetiology that is likely to involve multiple susceptibility genes and environmental factors. The role of environmental factors is difficult to determine and, until a few years ago, the molecular mechanisms underlying gene-environment (G × E) interactions in AD were largely unknown. Here, we review evidence that has emerged over the past two decades to explain how environmental factors, such as diet, lifestyle, alcohol, smoking and pollutants, might interact with the human genome. In particular, we discuss how various environmental AD risk factors can induce epigenetic modifications of key AD-related genes and pathways and consider how epigenetic mechanisms could contribute to the effects of oxidative stress on AD onset. Studies on early-life exposures are helping to uncover critical time windows of sensitivity to epigenetic influences from environmental factors, thereby laying the foundations for future primary preventative approaches. We conclude that epigenetic modifications need to be considered when assessing G × E interactions in AD.
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Affiliation(s)
- Lucia Migliore
- Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy. .,Department of Laboratory Medicine, Pisa University Hospital, Pisa, Italy.
| | - Fabio Coppedè
- Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy
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10
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Hu Q, Wang Q, Li Y, Xie Z, Lin X, Huang G, Zhan L, Jia X, Zhao X. Intrinsic Brain Activity Alterations in Patients With Mild Cognitive Impairment-to-Normal Reversion: A Resting-State Functional Magnetic Resonance Imaging Study From Voxel to Whole-Brain Level. Front Aging Neurosci 2022; 13:788765. [PMID: 35111039 PMCID: PMC8802752 DOI: 10.3389/fnagi.2021.788765] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 12/08/2021] [Indexed: 12/25/2022] Open
Abstract
Mild cognitive impairment (MCI) reversion refers to patients with MCI who revert from MCI to a normal cognitive state. Exploring the underlying neuromechanism of MCI reverters may contribute to providing new insights into the pathogenesis of Alzheimer's disease and developing therapeutic interventions. Information on patients with MCI and healthy controls (HCs) was collected from the Alzheimer's Disease Neuroimaging Initiative database. We redefined MCI reverters as patients with MCI whose logical memory scores changed from MCI to normal levels using the logical memory criteria. We explored intrinsic brain activity alterations in MCI reverters from voxel, regional, and whole-brain levels by comparing resting-state functional magnetic resonance imaging metrics of the amplitude of low-frequency of fluctuation (ALFF), the fractional amplitude of low-frequency fluctuation (fALFF), percent amplitude of fluctuation (PerAF), regional homogeneity (ReHo), and degree centrality (DC) between MCI reverters and HCs. Finally, partial correlation analyses were conducted between cognitive scale scores and resting-state functional magnetic resonance imaging metrics of brain regions, revealing significant group differences. Thirty-two patients with MCI from the Alzheimer's Disease Neuroimaging Initiative database were identified as reverters. Thirty-seven age-, sex-, and education-matched healthy individuals were also enrolled. At the voxel level, compared with the HCs, MCI reverters had increased ALFF, fALFF, and PerAF in the frontal gyrus (including the bilateral orbital inferior frontal gyrus and left middle frontal gyrus), increased PerAF in the left fusiform gyrus, and decreased ALFF and fALFF in the right inferior cerebellum. Regarding regional and whole-brain levels, MCI reverters showed increased ReHo in the left fusiform gyrus and right median cingulate and paracingulate gyri; increased DC in the left inferior temporal gyrus and left medial superior frontal; decreased DC in the right inferior cerebellum and bilateral insular gyrus relative to HCs. Furthermore, significant correlations were found between cognitive performance and neuroimaging changes. These findings suggest that MCI reverters show significant intrinsic brain activity changes compared with HCs, potentially related to the cognitive reversion of patients with MCI. These results enhance our understanding of the underlying neuromechanism of MCI reverters and may contribute to further exploration of Alzheimer's disease.
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Affiliation(s)
- Qili Hu
- Department of Radiology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Qianqian Wang
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Yunfei Li
- Department of Radiology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Zhou Xie
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Xiaomei Lin
- Department of Radiology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Guofeng Huang
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - LinLin Zhan
- School of Western Language, Heilongjiang University, Heilongjiang, China
| | - Xize Jia
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Xiaohu Zhao
- Department of Radiology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
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