1
|
Jiang J, Zhao K, Li W, Zheng P, Jiang S, Ren Q, Duan Y, Yu H, Kang X, Li J, Hu K, Jiang T, Zhao M, Wang L, Yang S, Zhang H, Liu Y, Wang A, Liu Y, Xu J. Multiomics Reveals Biological Mechanisms Linking Macroscale Structural Covariance Network Dysfunction With Neuropsychiatric Symptoms Across the Alzheimer's Disease Continuum. Biol Psychiatry 2025; 97:1067-1078. [PMID: 39419461 DOI: 10.1016/j.biopsych.2024.08.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 07/04/2024] [Accepted: 08/28/2024] [Indexed: 10/19/2024]
Abstract
BACKGROUND The high heterogeneity of neuropsychiatric symptoms (NPSs) hinders further exploration of their role in neurobiological mechanisms and Alzheimer's disease (AD). We aimed to delineate NPS patterns based on brain macroscale connectomics to understand the biological mechanisms of NPSs on the AD continuum. METHODS We constructed regional radiomics similarity networks for 550 participants (AD with NPSs [n = 376], AD without NPSs [n = 111], and normal control participants [n = 63]) from the CIBL (Chinese Imaging, Biomarkers, and Lifestyle) study. We identified regional radiomics similarity network connections associated with NPSs and then clustered distinct subtypes of AD with NPSs. An independent dataset (n = 189) and internal validation were performed to assess the robustness of the NPS subtypes. Subsequent multiomics analysis was performed to assess the distinct clinical phenotype and biological mechanisms in each NPS subtype. RESULTS AD patients with NPSs were clustered into severe (n = 187), moderate (n = 87), and mild (n = 102) NPS subtypes, each exhibiting distinct brain network dysfunction patterns. A high level of consistency in clustering NPSs was internally and externally validated. Severe and moderate NPS subtypes were associated with significant cognitive impairment, increased plasma p-tau181 (tau phosphorylated at threonine 181) levels, extensive decreased brain volume and cortical thickness, and accelerated cognitive decline. Gene set enrichment analysis revealed enrichment of differentially expressed genes in ion transport and synaptic transmission with variations for each NPS subtype. Genome-wide association study analysis defined the specific gene loci for each subtype of AD with NPSs (e.g., logical memory), consistent with clinical manifestations and progression patterns. CONCLUSIONS This study identified and validated 3 distinct NPS subtypes, underscoring the role of NPSs in neurobiological mechanisms and progression of the AD continuum.
Collapse
Affiliation(s)
- Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Kun Zhao
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China; Queen Mary School Hainan, Beijing University of Posts and Telecommunications, Hainan, China.
| | - Wenyi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Peiyang Zheng
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Shirui Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Qiwei Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yunyun Duan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huiying Yu
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Xiaopeng Kang
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Junjie Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ke Hu
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Tianlin Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Min Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Linlin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Shiyi Yang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Huiying Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yaou Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China; Queen Mary School Hainan, Beijing University of Posts and Telecommunications, Hainan, China.
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China.
| |
Collapse
|
2
|
Chatzikostopoulos A, Moraitou D, Papaliagkas V, Tsolaki M. Mapping the Neuropsychiatric Symptoms in Alzheimer's Disease Using Biomarkers, Cognitive Abilities, and Personality Traits: A Systematic Review. Diagnostics (Basel) 2025; 15:1082. [PMID: 40361900 PMCID: PMC12072134 DOI: 10.3390/diagnostics15091082] [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: 02/02/2025] [Revised: 04/13/2025] [Accepted: 04/21/2025] [Indexed: 05/15/2025] Open
Abstract
Background/Objectives: Symptoms (NPS) in Alzheimer's disease (AD) have multiple effects in daily living, not only for the patients but for their caregivers too. The present systematic review was performed in order to identify if biomarkers, cognitive functions, and personality traits can be considered as important factors for the development and maintenance of these symptoms. Methods: To achieve that, the existing literature spanning the period from 2018 to 2024 was critically analyzed. To be included in the review, a study had to investigate any of the factors mentioned above. In total, 182 articles were assessed for eligibility, and 50 met the inclusion criteria. Results: Most of the studies were focused on the role of biomarkers and found that amyloid β, tau and phospho-tau protein are closely related to the incidence and the severity of NPS. In fewer studies, cognitive function and personality traits were also associated with NPS. Conclusions: In conclusion, biomarkers, cognitive function and personality traits are associated with NPS, but the underlying mechanisms, still, mostly remain unknown.
Collapse
Affiliation(s)
- Athanasios Chatzikostopoulos
- Laboratory of Psychology, Department of Cognition, Brain and Behavior, School of Psychology, Faculty of Philosophy, Aristotle University of Thessaloniki (AUTh), 54124 Thessaloniki, Greece;
- Laboratory of Neurodegenerative Diseases, Center of Interdisciplinary Research and Innovation (CIRI-AUTH), Balcan Center, Buildings A & B, 57001 Thessaloniki, Greece;
- Greek Association of Alzheimer’s Disease and Related Disorders, 54643 Thessaloniki, Greece
| | - Despina Moraitou
- Laboratory of Psychology, Department of Cognition, Brain and Behavior, School of Psychology, Faculty of Philosophy, Aristotle University of Thessaloniki (AUTh), 54124 Thessaloniki, Greece;
- Laboratory of Neurodegenerative Diseases, Center of Interdisciplinary Research and Innovation (CIRI-AUTH), Balcan Center, Buildings A & B, 57001 Thessaloniki, Greece;
- Greek Association of Alzheimer’s Disease and Related Disorders, 54643 Thessaloniki, Greece
| | - Vasileios Papaliagkas
- Department of Biomedical Sciences, School of Health Sciences, International Hellenic University, Alexandrion University Campus, 57400 Thessaloniki, Greece;
| | - Magda Tsolaki
- Laboratory of Neurodegenerative Diseases, Center of Interdisciplinary Research and Innovation (CIRI-AUTH), Balcan Center, Buildings A & B, 57001 Thessaloniki, Greece;
- Greek Association of Alzheimer’s Disease and Related Disorders, 54643 Thessaloniki, Greece
- 1st Department of Neurology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece
| |
Collapse
|
3
|
Xu H, Mu S, Bao J, Davatzikos C, Shou H, Shen L. High-dimensional mediation analysis reveals the mediating role of physical activity patterns in genetic pathways leading to AD-like brain atrophy. BioData Min 2025; 18:24. [PMID: 40128806 PMCID: PMC11931790 DOI: 10.1186/s13040-025-00432-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Accepted: 02/07/2025] [Indexed: 03/26/2025] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is a complex disorder that affects multiple biological systems including cognition, behavior and physical health. Unfortunately, the pathogenic mechanisms behind AD are not yet clear and the treatment options are still limited. Despite the increasing number of studies examining the pairwise relationships between genetic factors, physical activity (PA), and AD, few have successfully integrated all three domains of data, which may help reveal mechanisms and impact of these genomic and phenomic factors on AD. We use high-dimensional mediation analysis as an integrative framework to study the relationships among genetic factors, PA and AD-like brain atrophy quantified by spatial patterns of brain atrophy. RESULTS We integrate data from genetics, PA and neuroimaging measures collected from 13,425 UK Biobank samples to unveil the complex relationship among genetic risk factors, behavior and brain signatures in the contexts of aging and AD. Specifically, we used a composite imaging marker, Spatial Pattern of Abnormality for Recognition of Early AD (SPARE-AD) that characterizes AD-like brain atrophy, as an outcome variable to represent AD risk. Through GWAS, we identified single nucleotide polymorphisms (SNPs) that are significantly associated with SPARE-AD as exposure variables. We employed conventional summary statistics and functional principal component analysis to extract patterns of PA as mediators. After constructing these variables, we utilized a high-dimensional mediation analysis method, Bayesian Mediation Analysis (BAMA), to estimate potential mediating pathways between SNPs, multivariate PA signatures and SPARE-AD. BAMA incorporates Bayesian continuous shrinkage prior to select the active mediators from a large pool of candidates. We identified a total of 22 mediation pathways, indicating how genetic variants can influence SPARE-AD by altering physical activity. By comparing the results with those obtained using univariate mediation analysis, we demonstrate the advantages of high-dimensional mediation analysis methods over univariate mediation analysis. CONCLUSION Through integrative analysis of multi-omics data, we identified several mediation pathways of physical activity between genetic factors and SPARE-AD. These findings contribute to a better understanding of the pathogenic mechanisms of AD. Moreover, our research demonstrates the potential of the high-dimensional mediation analysis method in revealing the mechanisms of disease.
Collapse
Affiliation(s)
- Hanxiang Xu
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Family Medicine and Public Health, University of California, San Diego, CA, 92093, USA
| | - Shizhuo Mu
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Jingxuan Bao
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Christos Davatzikos
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Haochang Shou
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| |
Collapse
|
4
|
Jiang J, Jiang T, Wang X, Zhao M, Shi H, Zhang H, Li W, Jiang S, Zhang X, Zhou J, Ren Q, Wang L, Yang S, Yao Z, Liu Y, Xu J. Malnutrition exacerbating neuropsychiatric symptoms on the Alzheimer's continuum is relevant to the cAMP signaling pathway: Human and mouse studies. Alzheimers Dement 2025; 21:e14506. [PMID: 39868480 PMCID: PMC11848410 DOI: 10.1002/alz.14506] [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: 04/23/2024] [Revised: 11/07/2024] [Accepted: 11/26/2024] [Indexed: 01/28/2025]
Abstract
INTRODUCTION Malnutrition correlates with neuropsychiatric symptoms (NPSs) in Alzheimer's disease (AD); however, the potential mechanism underlying this association remains unclear. METHODS Baseline and longitudinal associations of nutritional status with NPSs were analyzed in 374 patients on the AD continuum and 61 healthy controls. Serum biomarkers, behavioral tests, cerebral neurotransmitters, and differentially gene expression were evaluated in standard and malnourished diet-fed transgenic APPswe/PSEN1dE9 (APP/PS1) mice. RESULTS Poor nutritional status and increased cerebral blood flow in the midbrain and striatum were associated with severe general NPSs and subtypes, especially depression, anxiety, and apathy. APP/PS1 mice fed a malnourished diet showed poor nutritional status, depression- and anxiety-like behaviors, altered neurotransmitter levels, and downregulated c-Fos expression in the midbrain and striatum; these were associated with suppressed cyclic adenosine monophosphate (cAMP) signaling pathway. DISCUSSION Malnutrition exacerbating NPSs is relevant to suppressed cAMP pathway in the midbrain and striatum, suggesting the potential for targeted nutritional interventions to mitigate NPSs in the AD continuum. HIGHLIGHTS Poor nutritional status linked to general and specific neuropsychiatric symptom (NPS) deterioration. Malnutrition affects NPSs, usually involving the midbrain and striatum. Malnourished diet induces depression- and anxiety-like behaviors in APP/PS1 mice. Malnutrition exacerbates NPSs associated with cAMP signaling pathway in the midbrain and striatum.
Collapse
Affiliation(s)
- Jiwei Jiang
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Tianlin Jiang
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Xiaohong Wang
- Institute of Translational MedicineMedical CollegeYangzhou UniversityYangzhouChina
- Jiangsu Key Laboratory of Experimental & Translational Non‐coding RNA ResearchYangzhou UniversityYangzhouChina
| | - Min Zhao
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Hanping Shi
- Beijing Shijitan Hospital, Capital Medical UniversityBeijingChina
- Beijing International Science and Technology Cooperation Base for Cancer Metabolism and NutritionBeijingChina
| | - Huiying Zhang
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Wenyi Li
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Shirui Jiang
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Xiaoli Zhang
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Jiawei Zhou
- Institute of Translational MedicineMedical CollegeYangzhou UniversityYangzhouChina
- Jiangsu Key Laboratory of Experimental & Translational Non‐coding RNA ResearchYangzhou UniversityYangzhouChina
| | - Qiwei Ren
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Linlin Wang
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Shiyi Yang
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Zeshan Yao
- Beijing Institute of Collaborative InnovationBeijingChina
| | - Yaou Liu
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Jun Xu
- Beijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| |
Collapse
|
5
|
Jiang J, Zhuo Z, Wang A, Li W, Jiang S, Duan Y, Ren Q, Zhao M, Wang L, Yang S, Awan MUN, Liu Y, Xu J. Choroid plexus volume as a novel candidate neuroimaging marker of the Alzheimer's continuum. Alzheimers Res Ther 2024; 16:149. [PMID: 38961406 PMCID: PMC11221040 DOI: 10.1186/s13195-024-01520-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 06/25/2024] [Indexed: 07/05/2024]
Abstract
BACKGROUND Enlarged choroid plexus (ChP) volume has been reported in patients with Alzheimer's disease (AD) and inversely correlated with cognitive performance. However, its clinical diagnostic and predictive value, and mechanisms by which ChP impacts the AD continuum remain unclear. METHODS This prospective cohort study enrolled 607 participants [healthy control (HC): 110, mild cognitive impairment (MCI): 269, AD dementia: 228] from the Chinese Imaging, Biomarkers, and Lifestyle study between January 1, 2021, and December 31, 2022. Of the 497 patients on the AD continuum, 138 underwent lumbar puncture for cerebrospinal fluid (CSF) hallmark testing. The relationships between ChP volume and CSF pathological hallmarks (Aβ42, Aβ40, Aβ42/40, tTau, and pTau181), neuropsychological tests [Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Neuropsychiatric Inventory (NPI), and Activities of Daily Living (ADL) scores], and multimodal neuroimaging measures [gray matter volume, cortical thickness, and corrected cerebral blood flow (cCBF)] were analyzed using partial Spearman's correlation. The mediating effects of four neuroimaging measures [ChP volume, hippocampal volume, lateral ventricular volume (LVV), and entorhinal cortical thickness (ECT)] on the relationship between CSF hallmarks and neuropsychological tests were examined. The ability of the four neuroimaging measures to identify cerebral Aβ42 changes or differentiate among patients with AD dementia, MCI and HCs was determined using receiver operating characteristic analysis, and their associations with neuropsychological test scores at baseline were evaluated by linear regression. Longitudinal associations between the rate of change in the four neuroimaging measures and neuropsychological tests scores were evaluated on the AD continuum using generalized linear mixed-effects models. RESULTS The participants' mean age was 65.99 ± 8.79 years. Patients with AD dementia exhibited the largest baseline ChP volume than the other groups (P < 0.05). ChP volume enlargement correlated with decreased Aβ42 and Aβ40 levels; lower MMSE and MoCA and higher NPI and ADL scores; and lower volume, cortical thickness, and cCBF in other cognition-related regions (all P < 0.05). ChP volume mediated the association of Aβ42 and Aβ40 levels with MMSE scores (19.08% and 36.57%), and Aβ42 levels mediated the association of ChP volume and MMSE or MoCA scores (39.49% and 34.36%). ChP volume alone better identified cerebral Aβ42 changes than LVV alone (AUC = 0.81 vs. 0.67, P = 0.04) and EC thickness alone (AUC = 0.81 vs.0.63, P = 0.01) and better differentiated patients with MCI from HCs than hippocampal volume alone (AUC = 0.85 vs. 0.81, P = 0.01), and LVV alone (AUC = 0.85 vs.0.82, P = 0.03). Combined ChP and hippocampal volumes significantly increased the ability to differentiate cerebral Aβ42 changes and patients among AD dementia, MCI, and HCs groups compared with hippocampal volume alone (all P < 0.05). After correcting for age, sex, years of education, APOE ε4 status, eTIV, and hippocampal volume, ChP volume was associated with MMSE, MoCA, NPI, and ADL score at baseline, and rapid ChP volume enlargement was associated with faster deterioration in NPI scores with an average follow-up of 10.03 ± 4.45 months (all P < 0.05). CONCLUSIONS ChP volume may be a novel neuroimaging marker associated with neurodegenerative changes and clinical AD manifestations. It could better detect the early stages of the AD and predict prognosis, and significantly enhance the differential diagnostic ability of hippocampus on the AD continuum.
Collapse
Affiliation(s)
- Jiwei Jiang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhizheng Zhuo
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Anxin Wang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Wenyi Li
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Shirui Jiang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yunyun Duan
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Qiwei Ren
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Min Zhao
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Linlin Wang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Shiyi Yang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | | | - Yaou Liu
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- National Clinical Research Center for Neurological Diseases, Beijing, China.
| | - Jun Xu
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- National Clinical Research Center for Neurological Diseases, Beijing, China.
| |
Collapse
|
6
|
Angelopoulou E, Koros C, Hatzimanolis A, Stefanis L, Scarmeas N, Papageorgiou SG. Exploring the Genetic Landscape of Mild Behavioral Impairment as an Early Marker of Cognitive Decline: An Updated Review Focusing on Alzheimer's Disease. Int J Mol Sci 2024; 25:2645. [PMID: 38473892 PMCID: PMC10931648 DOI: 10.3390/ijms25052645] [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: 01/08/2024] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024] Open
Abstract
The clinical features and pathophysiology of neuropsychiatric symptoms (NPSs) in dementia have been extensively studied. However, the genetic architecture and underlying neurobiological mechanisms of NPSs at preclinical stages of cognitive decline and Alzheimer's disease (AD) remain largely unknown. Mild behavioral impairment (MBI) represents an at-risk state for incident cognitive impairment and is defined by the emergence of persistent NPSs among non-demented individuals in later life. These NPSs include affective dysregulation, decreased motivation, impulse dyscontrol, abnormal perception and thought content, and social inappropriateness. Accumulating evidence has recently begun to shed more light on the genetic background of MBI, focusing on its potential association with genetic factors related to AD. The Apolipoprotein E (APOE) genotype and the MS4A locus have been associated with affective dysregulation, ZCWPW1 with social inappropriateness and psychosis, BIN1 and EPHA1 with psychosis, and NME8 with apathy. The association between MBI and polygenic risk scores (PRSs) in terms of AD dementia has been also explored. Potential implicated mechanisms include neuroinflammation, synaptic dysfunction, epigenetic modifications, oxidative stress responses, proteosomal impairment, and abnormal immune responses. In this review, we summarize and critically discuss the available evidence on the genetic background of MBI with an emphasis on AD, aiming to gain insights into the potential underlying neurobiological mechanisms, which till now remain largely unexplored. In addition, we propose future areas of research in this emerging field, with the aim to better understand the molecular pathophysiology of MBI and its genetic links with cognitive decline.
Collapse
Affiliation(s)
- Efthalia Angelopoulou
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.G.P.)
| | - Christos Koros
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.G.P.)
| | - Alexandros Hatzimanolis
- 1st Department of Psychiatry, Aiginition University Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece;
| | - Leonidas Stefanis
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.G.P.)
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.G.P.)
- Department of Neurology, Columbia University, New York, NY 10032, USA
| | - Sokratis G. Papageorgiou
- 1st Department of Neurology, Aiginition University Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.G.P.)
| |
Collapse
|