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Fujita K, Kimura T, Yamakawa A, Niida S, Ozaki K, Sakurai T, Arai H, Shigemizu D, J-MINT study group. Genetic background and multidomain interventions in mild cognitive impairment. Alzheimers Res Ther 2025; 17:130. [PMID: 40490801 DOI: 10.1186/s13195-025-01764-0] [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: 12/11/2024] [Accepted: 05/13/2025] [Indexed: 06/11/2025]
Abstract
BACKGROUND The growing prevalence of dementia emphasizes the need for effective prevention strategies. Although the partial efficacy of multidomain interventions for dementia prevention has been demonstrated, understanding the characteristics of individuals who benefit most from these interventions is crucial for optimizing resource allocation. This study investigated the association between participants' genetic backgrounds and the effectiveness of multidomain interventions for preventing dementia. METHODS This study utilized data from the Japan-Multimodal Intervention Trial for the Prevention of Dementia (J-MINT), where older adults with mild cognitive impairment underwent 18 months of multidomain intervention. The intervention included exercise, nutrition, cognitive stimulation, social participation, and vascular risk management. Participants who completed the J-MINT intervention and had genetic data, including whole-genome sequencing (WGS), were analyzed. Using Japanese polygenic risk scores (PRSs) for Alzheimer's disease, participants were stratified into high- and low-genetic-risk groups. Cognitive composite score (CPS) improvement rates at 6-, 12-, and 18-months were compared between intervention and control groups, with subgroup analyses performed by age (< 75 and ≥ 75 years). Additionally, a comprehensive variant analysis using WGS was conducted to identify genetic signals potentially associated with the intervention's effectiveness. RESULTS Among 289 participants analyzed (168 aged < 75 years; 121 aged ≥ 75 years), 99 were classified into the high-risk PRS group (56 intervention, 43 control) and 190 into the low-risk PRS group (92 intervention, 98 control). For participants aged ≥ 75 years, no statistically significant differences in CPS improvement rates were observed between the intervention and control groups, regardless of PRS classification. However, in participants aged < 75, those in the high-risk PRS group showed significant CPS improvement at the 6-month follow-up. Additionally, analysis of 9,978,605 genetic variants identified two loci, ID3 and LMO1 (rs2067053 and rs201082658), with suggestive associations (P < 1 × 10⁻4) to reduced intervention effectiveness. CONCLUSIONS This study highlighted the utility of PRS in predicting cognitive improvement following multidomain interventions and identified genetic variants that may influence the intervention's effectiveness. The findings provide a valuable foundation for personalized dementia prevention strategies.
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Grants
- 22-23, 24-15, 24-11 and 23-7 National Center for Geriatrics and Gerontology
- 22-23, 24-15, 24-11 and 23-7 National Center for Geriatrics and Gerontology
- 22-23, 24-15, 24-11 and 23-7 National Center for Geriatrics and Gerontology
- 22-23, 24-15, 24-11 and 23-7 National Center for Geriatrics and Gerontology
- 22-23, 24-15, 24-11 and 23-7 National Center for Geriatrics and Gerontology
- 22-23, 24-15, 24-11 and 23-7 National Center for Geriatrics and Gerontology
- 22-23, 24-15, 24-11 and 23-7 National Center for Geriatrics and Gerontology
- 22-23, 24-15, 24-11 and 23-7 National Center for Geriatrics and Gerontology
- JP22de0107002, JP23ae0101077, JP23dk0207052, JP18kk0205009, JP21dk0207045 and JP23dk0207060 Japan Agency for Medical Research and Development
- JP22de0107002, JP23ae0101077, JP23dk0207052, JP18kk0205009, JP21dk0207045 and JP23dk0207060 Japan Agency for Medical Research and Development
- JP22de0107002, JP23ae0101077, JP23dk0207052, JP18kk0205009, JP21dk0207045 and JP23dk0207060 Japan Agency for Medical Research and Development
- JP22de0107002, JP23ae0101077, JP23dk0207052, JP18kk0205009, JP21dk0207045 and JP23dk0207060 Japan Agency for Medical Research and Development
- 23K21306 Japan Society for the Promotion of Science
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Affiliation(s)
- Kosuke Fujita
- Department of Prevention and Care Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Tetsuaki Kimura
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Akiko Yamakawa
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Shumpei Niida
- Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, 734-8551, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Takashi Sakurai
- Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Hidenori Arai
- National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Daichi Shigemizu
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan.
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, 734-8551, Japan.
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Lei L, Chen CY, Wang YF, Guo ZY, Zhang Y. Mangiferin: A natural neuroprotective polyphenol with anti-inflammatory and anti-oxidant properties for depression. Prog Neuropsychopharmacol Biol Psychiatry 2025; 139:111401. [PMID: 40379124 DOI: 10.1016/j.pnpbp.2025.111401] [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: 07/27/2024] [Revised: 04/16/2025] [Accepted: 05/13/2025] [Indexed: 05/19/2025]
Abstract
Depression is a severe global health problem accompanied by persistent low mood that harms the physical and mental health of people and places a substantial economic burden on society. Mangiferin (MGF), a natural polyphenol in the traditional Chinese herb Anemarrhena asphodeloides Bge., can improve neuronal damage, memory, and cognitive deficits, implicating the therapeutic potential of MGF for depression. MGF has a unique C-glycosyl and phenolic structure that endows it with multiple biological properties, e.g., anti-oxidant, anti-inflammatory, and anti-mitochondrial dysfunction. However, the pharmacological role of MGF in depression remains unclear. Therefore, this review describes the neuroprotective effects and the antidepressant mechanisms of MGF in preclinical depression studies. MGF ameliorates cognitive deficits in depression and neurodegenerative diseases animal models by reducing amyloid-beta deposition, ameliorating cholinergic dysfunction, and increasing neurotrophic factors. Also, MGF regulates molecular mechanisms in depressed animals mainly through anti-inflammation (by inhibiting NLRP3 inflammasome activation, mitogen-activated protein kinase phosphorylation and its downstream nuclear factor-кB signaling pathway, and indoleamine 2,3-dioxygenase activity), anti-oxidant (by increasing levels of anti-oxidant enzymes and inhibiting lipid peroxidation). Notably, the potential mechanisms of MGF in treating depression by modulating neurotransmission (e.g., glutamate, dopamine, norepinephrine, and serotonin) need to be further explored. It is hoped to explore further the potential molecular mechanisms of MGF's biological activity in depression and provide directions for further clinical applications.
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Affiliation(s)
- Lan Lei
- Department of Anatomy, School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Cong-Ya Chen
- Department of Anatomy, School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Yu-Fei Wang
- Department of Anatomy, School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Zhen-Yu Guo
- Department of Anatomy, School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Yi Zhang
- Department of Anatomy, School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China.
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Jellinger KA. Mild cognitive impairment in amyotrophic lateral sclerosis: current view. J Neural Transm (Vienna) 2025; 132:357-368. [PMID: 39470847 DOI: 10.1007/s00702-024-02850-7] [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: 09/17/2024] [Accepted: 10/10/2024] [Indexed: 11/01/2024]
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal multi-system neurodegenerative disorder with no effective treatment or cure. Although primarily characterized by motor degeneration, cognitive dysfunction is an important non-motor symptom that has a negative impact on patient and caregiver burden. Mild cognitive deficits are present in a subgroup of non-demented patients with ALS, often preceding motor symptoms. Detailed neuropsychological assessments reveal deficits in a variety of cognitive domains, including those of verbal fluency and retrieval, language, executive function, attention and verbal memory. Mild cognitive impairment (MCI), a risk factor for developing dementia, affects between 10% and over 50% of ALS patients. Neuroimaging revealed atrophy of frontal and temporal cortices, disordered white matter Integrity, volume reduction in amygdala and thalamus, hypometabolism in the frontal and superior temporal gyrus and anterior insula. Neuronal loss in non-motor brain areas, associated with TDP-43 deposition, one of the morphological hallmarks of ALS, is linked to functional disruption of frontostriatal and frontotemporo-limbic connectivities as markers for cognitive deficits in ALS, the pathogenesis of which is still poorly understood. Early diagnosis by increased cerebrospinal fluid or serum levels of neurofilament light/heavy chain or glial fibrillary acidic protein awaits confirmation for MCI in ALS. These fluid biomarkers and early detection of brain connectivity signatures before structural changes will be helpful not only in establishing early premature diagnosis but also in clarifying the pathophysiological mechanisms of MCI in ALS, which might serve as novel targets for prohibition/delay and future adequate treatment of this debilitating disorder.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, Vienna, A-1150, Austria.
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Gao PY, Ma LZ, Wang XJ, Wu BS, Huang YM, Wang ZB, Fu Y, Ou YN, Feng JF, Cheng W, Tan L, Yu JT. Physical frailty, genetic predisposition, and incident dementia: a large prospective cohort study. Transl Psychiatry 2024; 14:212. [PMID: 38802408 PMCID: PMC11130190 DOI: 10.1038/s41398-024-02927-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 05/10/2024] [Accepted: 05/13/2024] [Indexed: 05/29/2024] Open
Abstract
Physical frailty and genetic factors are both risk factors for increased dementia; nevertheless, the joint effect remains unclear. This study aimed to investigated the long-term relationship between physical frailty, genetic risk, and dementia incidence. A total of 274,194 participants from the UK Biobank were included. We applied Cox proportional hazards regression models to estimate the association between physical frailty and genetic and dementia risks. Among the participants (146,574 females [53.45%]; mean age, 57.24 years), 3,353 (1.22%) new-onset dementia events were recorded. Compared to non-frailty, the hazard ratio (HR) for dementia incidence in prefrailty and frailty was 1.396 (95% confidence interval [CI], 1.294-1.506, P < 0.001) and 2.304 (95% CI, 2.030-2.616, P < 0.001), respectively. Compared to non-frailty and low polygenic risk score (PRS), the HR for dementia risk was 3.908 (95% CI, 3.051-5.006, P < 0.001) for frailty and high PRS. Furthermore, among the participants, slow walking speed (HR, 1.817; 95% CI, 1.640-2.014, P < 0.001), low physical activity (HR, 1.719; 95% CI, 1.545-1.912, P < 0.001), exhaustion (HR, 1.670; 95% CI, 1.502-1.856, P < 0.001), low grip strength (HR, 1.606; 95% CI, 1.479-1.744, P < 0.001), and weight loss (HR, 1.464; 95% CI, 1.328-1.615, P < 0.001) were independently associated with dementia risk compared to non-frailty. Particularly, precise modulation for different dementia genetic risk populations can also be identified due to differences in dementia risk resulting from the constitutive pattern of frailty in different genetic risk populations. In conclusion, both physical frailty and high genetic risk are significantly associated with higher dementia risk. Early intervention to modify frailty is beneficial for achieving primary and precise prevention of dementia, especially in those at high genetic risk.
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Affiliation(s)
- Pei-Yang Gao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ling-Zhi Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xue-Jie Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 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, Fudan University, Shanghai, China
| | - Yi-Ming Huang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Zhi-Bo Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 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, 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 (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 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, Fudan University, Shanghai, China.
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Zhang J, Wang Y, Zhang Y, Yao J. Genome-wide association study in Alzheimer's disease: a bibliometric and visualization analysis. Front Aging Neurosci 2023; 15:1290657. [PMID: 38094504 PMCID: PMC10716290 DOI: 10.3389/fnagi.2023.1290657] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/08/2023] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Thousands of research studies concerning genome-wide association studies (GWAS) in Alzheimer's disease (AD) have been published in the last decades. However, a comprehensive understanding of the current research status and future development trends of GWAS in AD have not been clearly shown. In this study, we tried to gain a systematic overview of GWAS in AD by bibliometric and visualization analysis. METHODS The literature search terms are: ("genome-wide analysis" or "genome-wide association study" or "whole-genome analysis") AND ("Alzheimer's Disease" or "Alzheimer Disease"). Relevant publications were extracted from the Web of Science Core Collection (WoSCC) database. Collected data were further analyzed using VOSviewer, CiteSpace and R package Bibliometrix. The countries, institutions, authors and scholar collaborations were investigated. The co-citation analysis of publications was visualized. In addition, research hotspots and fronts were examined. RESULTS A total of 1,350 publications with 59,818 citations were identified. The number of publications and citations presented a significant rising trend since 2013. The United States was the leading country with an overwhelming number of publications (775) and citations (42,237). The University of Washington and Harvard University were the most prolific institutions with 101 publications each. Bennett DA was the most influential researcher with the highest local H-index. Neurobiology of Aging was the journal with the highest number of publications. Aβ, tau, immunity, microglia and DNA methylation were research hotspots. Disease and causal variants were research fronts. CONCLUSION The most frequently studied AD pathogenesis and research hotspots are (1) Aβ and tau, (2) immunity and microglia, with TREM2 as a potential immunotherapy target, and (3) DNA methylation. The research fronts are (1) looking for genetic similarities between AD and other neurological diseases and syndromes, and (2) searching for causal variants of AD. These hotspots suggest noteworthy directions for future studies on AD pathogenesis and genetics, in which basic research regarding immunity is promising for clinical conversion. The current under-researched directions are (1) GWAS in AD biomarkers based on large sample sizes, (2) studies of causal variants of AD, and (3) GWAS in AD based on non-European populations, which need to be strengthened in the future.
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Affiliation(s)
- Junyao Zhang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yinuo Wang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingying Zhang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junyan Yao
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Anesthesiology and Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
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6
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Reiter K, Butts AM, Janecek JK, Correro AN, Nencka A, Agarwal M, Franczak M, Glass Umfleet L. Relationship between cognitive reserve, brain volume, and neuropsychological performance in amnestic and nonamnestic MCI. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2023; 30:940-956. [PMID: 36573001 DOI: 10.1080/13825585.2022.2161462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 12/16/2022] [Indexed: 12/28/2022]
Abstract
Cognitive Reserve (CR) is a theoretical construct that influences the onset and course of cognitive and structural changes that occur with aging and mild cognitive impairment (MCI). There is a paucity of research that examines the relationship of CR and brain volumes in amnestic (aMCI) and nonamnestic (naMCI) separately. This study is a retrospective chart review of MCI patients who underwent neuropsychological evaluation and brain MRI with NeuroReader™ (NR). NR is an FDA-cleared software that standardizes MRI volumes to a control sample. Classifications of aMCI and naMCI were based on Petersen criteria. CR was measured as education, occupation, and word reading. Data analysis included bivariate correlations between CR, neuropsychological test scores, and NR-brain volumes by MCI subtype. The Benjamini-Hochberg method corrected for multiple comparisons. The sample included 91 participants with aMCI and 41 with naMCI. Within naMCI, positive correlations were observed between CR and whole brain volume, total gray matter, bifrontal, left parietal, left occipital, and bilateral cerebellum. Within aMCI, no significant correlations were observed between CR and brain volumes. Positive correlations with CR were observed in language, attention, and visual learning in both aMCI and naMCI groups. The current study adds to the minimal literature on CR and naMCI. Results revealed that CR is associated with volumetrics in naMCI only, though cognitive findings were similar in both MCI groups. Possible explanations include heterogeneous disease pathologies, disease stage, or a differential influence of CR on volumetrics in MCI. Additional longitudinal and biomarker studies will better elucidate this relationship.
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Affiliation(s)
- K Reiter
- Cleveland Clinic, Neurological Institute, Cleveland, OH, USA
| | - A M Butts
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - J K Janecek
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - A N Correro
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - A Nencka
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - M Agarwal
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - M Franczak
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - L Glass Umfleet
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
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Juul Rasmussen I, Frikke-Schmidt R. Modifiable cardiovascular risk factors and genetics for targeted prevention of dementia. Eur Heart J 2023; 44:2526-2543. [PMID: 37224508 PMCID: PMC10481783 DOI: 10.1093/eurheartj/ehad293] [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: 09/27/2022] [Revised: 02/22/2023] [Accepted: 05/04/2023] [Indexed: 05/26/2023] Open
Abstract
Dementia is a major global challenge for health and social care in the 21st century. A third of individuals >65 years of age die with dementia, and worldwide incidence numbers are projected to be higher than 150 million by 2050. Dementia is, however, not an inevitable consequence of old age; 40% of dementia may theoretically be preventable. Alzheimer's disease (AD) accounts for approximately two-thirds of dementia cases and the major pathological hallmark of AD is accumulation of amyloid-β. Nevertheless, the exact pathological mechanisms of AD remain unknown. Cardiovascular disease and dementia share several risk factors and dementia often coexists with cerebrovascular disease. In a public health perspective, prevention is crucial, and it is suggested that a 10% reduction in prevalence of cardiovascular risk factors could prevent more than nine million dementia cases worldwide by 2050. Yet this assumes causality between cardiovascular risk factors and dementia and adherence to the interventions over decades for a large number of individuals. Using genome-wide association studies, the entire genome can be scanned for disease/trait associated loci in a hypothesis-free manner, and the compiled genetic information is not only useful for pinpointing novel pathogenic pathways but also for risk assessments. This enables identification of individuals at high risk, who likely will benefit the most from a targeted intervention. Further optimization of the risk stratification can be done by adding cardiovascular risk factors. Additional studies are, however, highly needed to elucidate dementia pathogenesis and potential shared causal risk factors between cardiovascular disease and dementia.
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Affiliation(s)
- Ida Juul Rasmussen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
| | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Kong J, Zhou L, Li X, Ren Q. Sleep disorders affect cognitive function in adults: an overview of systematic reviews and meta-analyses. Sleep Biol Rhythms 2023; 21:133-142. [PMID: 38469285 PMCID: PMC10900040 DOI: 10.1007/s41105-022-00439-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 12/12/2022] [Indexed: 01/13/2023]
Abstract
Sleep disorders frequently result in poor memory, attention deficits, as well as a worse prognosis for neurodegenerative changes, such as Alzheimer's disease. The purpose of this study is to investigate the impact of sleep disorders on cognition. We screened four databases for all meta-analyses and systematic reviews from the establishment through March 2022. We have carried out quality evaluation and review the eligible systematic reviews. Evidence grading and quality assessment were performed on 22 eligible articles. Sleep deprivation primarily affects simple attention, complex attention, and working memory in cognition and alertness. The moderate-to-high-quality evidence proves optimal sleep time as 7-8 h. Sleep time outside this range increases the risk of impaired executive function, non-verbal memory, and working memory. Sleep-related breathing disorders is more likely to cause mild cognitive impairment and affects several cognitive domains. In older adults, insomnia primarily affects working memory, episodic memory, inhibitory control, cognitive flexibility, problem-solving, operational ability, perceptual function, alertness, and complex attention, and maintaining sensitivity. Sleep disturbances significantly impair cognitive function, and early detection and intervention may be critical steps in reducing poor prognosis. A simple neuropsychological memory test could be used to screen people with sleep disorders for cognitive impairment. Supplementary Information The online version contains supplementary material available at 10.1007/s41105-022-00439-9.
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Affiliation(s)
- Jingting Kong
- School of Medicine, Southeast University, No. 87 Dingjiaqiao, Gulou District, Nanjing, 210009 Jiangsu China
| | - Lv Zhou
- School of Medicine, Southeast University, No. 87 Dingjiaqiao, Gulou District, Nanjing, 210009 Jiangsu China
| | - Xiaoli Li
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, No. 87 Dingjiaqiao, Gulou District, Nanjing, 210009 China
| | - Qingguo Ren
- School of Medicine, Southeast University, No. 87 Dingjiaqiao, Gulou District, Nanjing, 210009 Jiangsu China
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, No. 87 Dingjiaqiao, Gulou District, Nanjing, 210009 China
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9
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Chen Y, Zhang Y, Li S, Zhou L, Li H, Li D, Wang Y, Yang H. Cardiometabolic diseases, polygenic risk score, APOE genotype, and risk of incident dementia: A population-based prospective cohort study. Arch Gerontol Geriatr 2023; 105:104853. [PMID: 36347157 DOI: 10.1016/j.archger.2022.104853] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/27/2022] [Accepted: 10/29/2022] [Indexed: 11/07/2022]
Abstract
Objective We aimed to prospective investigate the association between cardiometabolic diseases (CMDs) with dementia, and to examine whether genetic factors and CMDs jointly contribute to the incidence of dementia. Methods We used data from the UK biobank of 204,646 adults aged 37-73 free of dementia at baseline. Genetic risk for dementia including APOE ε4 status and polygenic risk score (PRS) categorized as low, intermediate, and high. CMDs including ischemic heart disease (IHD), stroke, and type 2 diabetes (T2D) were confirmed by touchscreen questionnaires, medical examinations, and hospital inpatient records. Results Over the follow-up (median: 12.5 years), 5,750 participants developed dementia. The HRs (95% CI) of those with APOE ε4 carriers and high PRS were 3.16 (3.00-3.33) and 1.50 (1.41-1.60), respectively. The risk of dementia was 70% higher among those with CMDs (HR: 1.70; 95% CI: 1.60-1.82). In joint effect analyses, compared to no CMDs and APOE ε4 non-carriers, the HRs (95% CIs) of dementia were 3.53 (3.31-3.76)/2.06 (1.89-2.23) in participants with only APOE ε4 carriers and CMDs, and 5.06 (4.64-5.53) for those with APOE ε4 carriers plus CMDs. Compared to no CMDs and low PRS, the HRs (95% CIs) of dementia were 1.29 (1.19-1.40)/1.60 (1.48-1.73) in participants with only intermediate and high PRS, and 2.00 (1.79-2.23)/2.63 (2.38-2.92) for those with intermediate, and high PRS plus CMDs. Moreover, there were significant additive and multiplication interactions between CMDs and APOE ε4 carriers of dementia, but only multiplication interaction was observed for PRS. Conclusions CMDs were associated with higher risk of dementia regardless of genetic risk for dementia.
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Affiliation(s)
- Yanchun Chen
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yuan Zhang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Shu Li
- School of Management, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lihui Zhou
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Huiping Li
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Dun Li
- The Discipline of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, Tianjin, China; The Discipline of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
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Jung SH, Kim HR, Chun MY, Jang H, Cho M, Kim B, Kim S, Jeong JH, Yoon SJ, Park KW, Kim EJ, Yoon B, Jang JW, Kim Y, Hong JY, Choi SH, Noh Y, Kim KW, Kim SE, Lee JS, Jung NY, Lee J, Lee AY, Kim BC, Cho SH, Cho H, Kim JH, Jung YH, Lee DY, Lee JH, Lee ES, Kim SJ, Moon SY, Son SJ, Hong CH, Bae JS, Lee S, Na DL, Seo SW, Cruchaga C, Kim HJ, Won HH. Transferability of Alzheimer Disease Polygenic Risk Score Across Populations and Its Association With Alzheimer Disease-Related Phenotypes. JAMA Netw Open 2022; 5:e2247162. [PMID: 36520433 PMCID: PMC9856322 DOI: 10.1001/jamanetworkopen.2022.47162] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/16/2022] [Indexed: 12/23/2022] Open
Abstract
Importance Polygenic risk scores (PRSs), which aggregate the genetic effects of single-nucleotide variants identified in genome-wide association studies (GWASs), can help distinguish individuals at a high genetic risk for Alzheimer disease (AD). However, genetic studies have predominantly focused on populations of European ancestry. Objective To evaluate the transferability of a PRS for AD in the Korean population using summary statistics from a prior GWAS of European populations. Design, Setting, and Participants This cohort study developed a PRS based on the summary statistics of a large-scale GWAS of a European population (the International Genomics of Alzheimer Project; 21 982 AD cases and 41 944 controls). This PRS was tested for an association with AD dementia and its related phenotypes in 1634 Korean individuals, who were recruited from 2013 to 2019. The association of a PRS based on a GWAS of a Japanese population (the National Center for Geriatrics and Gerontology; 3962 AD cases and 4074 controls) and a transancestry meta-analysis of European and Japanese GWASs was also evaluated. Data were analyzed from December 2020 to June 2021. Main Outcomes and Measures Risk of AD dementia, amnestic mild cognitive impairment (aMCI), earlier symptom onset, and amyloid β deposition (Aβ). Results A total of 1634 Korean patients (969 women [59.3%]), including 716 individuals (43.6%) with AD dementia, 222 (13.6%) with aMCI, and 699 (42.8%) cognitively unimpaired controls, were analyzed in this study. The mean (SD) age of the participants was 71.6 (9.0) years. Higher PRS was associated with a higher risk of AD dementia independent of APOE ɛ4 status in the Korean population (OR, 1.95; 95% CI, 1.40-2.72; P < .001). Furthermore, PRS was associated with aMCI, earlier symptom onset, and Aβ deposition independent of APOE ɛ4 status. The PRS based on a transancestry meta-analysis of data sets comprising 2 distinct ancestries showed a slightly improved accuracy. Conclusions and Relevance In this cohort study, a PRS derived from a European GWAS identified individuals at a high risk for AD dementia in the Korean population. These findings emphasize the transancestry transferability and clinical value of PRSs and suggest the importance of enriching diversity in genetic studies of AD.
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Affiliation(s)
- Sang-Hyuk Jung
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Hang-Rai Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Republic of Korea
| | - Min Young Chun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Minyoung Cho
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Beomsu Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Soyeon Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University Seoul Hospital, Ewha Womans University School of Medicine, Seoul, Republic of Korea
| | - Soo Jin Yoon
- Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A University College of Medicine, Department of Translational Biomedical Sciences, Graduate School of Dong-A University, Busan, Republic of Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Bora Yoon
- Department of Neurology, Konyang University College of Medicine, Daejeon, Republic of Korea
| | - Jae-Won Jang
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Republic of Korea
| | - Yeshin Kim
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Republic of Korea
| | - Jin Yong Hong
- Department of Neurology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Seong Hye Choi
- Department of Neurology, Inha University School of Medicine, Incheon, Republic of Korea
| | - Young Noh
- Department of Neurology, Gachon University College of Medicine, Gil Medical Center, Incheon, Republic of Korea
| | - Ko Woon Kim
- Department of Neurology, School of Medicine, Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - Si Eun Kim
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Republic of Korea
| | - Jin San Lee
- Department of Neurology, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea
| | - Na-Yeon Jung
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Juyoun Lee
- Department of Neurology, Chungnam National University Hospital, Daejeon, Republic of Korea
| | - Ae Young Lee
- Department of Neurology, Chungnam National University Hospital, Daejeon, Republic of Korea
| | - Byeong C. Kim
- Departmet of Neurology, Chonnam National University School of Medicine, Gwangju, Republic of Korea
| | - Soo Hyun Cho
- Departmet of Neurology, Chonnam National University School of Medicine, Gwangju, Republic of Korea
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jong Hun Kim
- Department of Neurology, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea
| | - Young Hee Jung
- Department of Neurology, Myongji Hospital, Hanyang University, Goyang, Republic of Korea
| | - Dong Young Lee
- Department of Psychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jae-Hong Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Eek-Sung Lee
- Department of Neurology, Soonchunhyang University Bucheon Hospital, Bucheon, Republic of Korea
| | - Seung Joo Kim
- Department of Neurology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - So Young Moon
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Sang Joon Son
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Chang Hyung Hong
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Jin-Sik Bae
- Eone-Diagnomics Genome Center (EDGC), Incheon, Republic of Korea
| | - Sunghoon Lee
- Eone-Diagnomics Genome Center (EDGC), Incheon, Republic of Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Seoul, Republic of Korea
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, Missouri
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri
| | - Hee Jin Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hong-Hee Won
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea
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11
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Yang J, Wang Z, Fu Y, Xu J, Zhang Y, Qin W, Zhang Q. Prediction value of the genetic risk of type 2 diabetes on the amnestic mild cognitive impairment conversion to Alzheimer’s disease. Front Aging Neurosci 2022; 14:964463. [PMID: 36185474 PMCID: PMC9521369 DOI: 10.3389/fnagi.2022.964463] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/23/2022] [Indexed: 11/23/2022] Open
Abstract
Amnestic mild cognitive impairment (aMCI) and Type 2 diabetes mellitus (T2DM) are both important risk factors for Alzheimer’s disease (AD). We aimed to investigate whether a T2DM-specific polygenic risk score (PRSsT2DM) can predict the conversion of aMCI to AD and further explore the underlying neurological mechanism. All aMCI patients were from the Alzheimer’s disease Neuroimaging Initiative (ADNI) database and were divided into conversion (aMCI-C, n = 164) and stable (aMCI-S, n = 222) groups. PRSsT2DM was calculated by PRSice-2 software to explore the predictive efficacy of the aMCI conversion to AD. We found that PRSsT2DM could independently predict the aMCI conversion to AD after removing the common variants of these two diseases. PRSsT2DM was significantly negatively correlated with gray matter volume (GMV) of the right superior frontal gyrus in the aMCI-C group. In all aMCI patients, PRSsT2DM was significantly negatively correlated with the cortical volume of the right superior occipital gyrus. The cortical volume of the right superior occipital gyrus could significantly mediate the association between PRSsT2DM and aMCI conversion. Gene-based analysis showed that T2DM-specific genes are highly expressed in cortical neurons and involved in ion and protein binding, neural development and generation, cell junction and projection, and PI3K-Akt and MAPK signaling pathway, which might increase the aMCI conversion by affecting the Tau phosphorylation and amyloid-beta (Aβ) accumulation. Therefore, the PRSsT2DM could be used as a measure to predict the conversion of aMCI to AD.
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Nordengen K, Pålhaugen L, Bettella F, Bahrami S, Selnes P, Jarholm J, Athanasiu L, Shadrin A, Andreassen OA, Fladby T. Phenotype-informed polygenic risk scores are associated with worse outcome in individuals at risk of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12350. [PMID: 35991219 PMCID: PMC9376972 DOI: 10.1002/dad2.12350] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 06/30/2022] [Accepted: 07/07/2022] [Indexed: 11/11/2022]
Abstract
Introduction Patients with predementia Alzheimer's disease (AD) and at-risk subjects are targets for promising disease-modifying treatments, and improved polygenic risk scores (PRSs) could improve early-stage case selection. Methods Phenotype-informed PRSs were developed by selecting AD-associated variants conditional on relevant inflammatory or cardiovascular traits. The primary outcome was longitudinal changes in measures of AD pathology, namely development of pathological amyloid deposition, medial temporal lobe atrophy, and cognitive decline in a prospective cohort study including 394 adults without AD dementia. Results High-risk groups defined by phenotype-informed AD PRSs had significantly steeper volume decline in medial temporal cortices, and the high-risk group defined by the cardiovascular-informed AD PRS had significantly increased hazard ratio of pathological amyloid deposition, compared to low-risk groups. Discussion AD PRSs informed by inflammatory disorders or cardiovascular risk factors and diseases are associated with development of AD pathology markers and may improve identification of subjects at risk for progression of AD.
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Affiliation(s)
- Kaja Nordengen
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Lene Pålhaugen
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Shahram Bahrami
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Per Selnes
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Jonas Jarholm
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Lavinia Athanasiu
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Alexey Shadrin
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Ole A. Andreassen
- Institute of Clinical MedicineUniversity of OsloOsloNorway
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Tormod Fladby
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
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13
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Xicota L, Gyorgy B, Grenier-Boley B, Lecoeur A, Fontaine G, Danjou F, Gonzalez JS, Colliot O, Amouyel P, Martin G, Levy M, Villain N, Habert MO, Dubois B, Lambert JC, Potier MC. Association of APOE-Independent Alzheimer Disease Polygenic Risk Score With Brain Amyloid Deposition in Asymptomatic Older Adults. Neurology 2022; 99:e462-e475. [PMID: 35606148 PMCID: PMC9421597 DOI: 10.1212/wnl.0000000000200544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 03/02/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Brain amyloid deposition, a major risk factor for Alzheimer disease (AD), is currently estimated by measuring CSF or plasma amyloid peptide levels or by PET imaging. Assessing genetic risks relating to amyloid deposition before any accumulation has occurred would allow for earlier intervention in persons at increased risk for developing AD. Previous work linking amyloid burden and genetic risk relied almost exclusively on APOE, a major AD genetic risk factor. Here, we ask whether a polygenic risk score (PRS) that incorporates an optimized list of common variants linked to AD and excludes APOE is associated with brain amyloid load in cognitively unimpaired older adults. METHODS We included 291 asymptomatic older participants from the INveStIGation of AlzHeimer's PredicTors (INSIGHT pre-AD) cohort who underwent amyloid imaging, including 83 amyloid-positive (+) participants. We used an Alzheimer's (A) PRS composed of 33 AD risk variants excluding APOE and selected the 17 variants that showed the strongest association with amyloid positivity to define an optimized (oA) PRS. Participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study (228 participants, 90 amyloid [+]) were tested as a validation cohort. Finally, 2,300 patients with AD and 6,994 controls from the European Alzheimer's Disease Initiative (EADI) were evaluated. RESULTS A-PRS was not significantly associated with amyloid burden in the INSIGHT or ADNI cohorts with or without correction for the APOE genotype. However, oA-PRS was significantly associated with amyloid status independently of APOE adjustment (INSIGHT odds ratio [OR]: 5.26 [1.71-16.88]; ADNI OR: 3.38 [1.02-11.63]). Of interest, oA-PRS accurately discriminated amyloid (+) and (-) APOE ε4 carriers (INSIGHT OR: 181.6 [7.53-10,674.6]; ADNI OR: 44.94 [3.03-1,277]). A-PRS and oA-PRS showed a significant association with disease status in the EADI cohort (OR: 1.68 [1.53-1.85] and 2.06 [1.73-2.45], respectively). Genes assigned to oA-PRS variants were enriched in ontologies related to β-amyloid metabolism and deposition. DISCUSSION PRSs relying on AD genetic risk factors excluding APOE may improve risk prediction for brain amyloid, allowing stratification of cognitively unimpaired individuals at risk of AD independent of their APOE status.
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Affiliation(s)
- Laura Xicota
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Beata Gyorgy
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Benjamin Grenier-Boley
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Alexandre Lecoeur
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Gaëlle Fontaine
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Fabrice Danjou
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Jorge Samper Gonzalez
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Olivier Colliot
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Philippe Amouyel
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Garance Martin
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Marcel Levy
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Nicolas Villain
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Marie-Odile Habert
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Bruno Dubois
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Jean-Charles Lambert
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Marie-Claude Potier
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France.
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Tin A, Bressler J, Simino J, Sullivan KJ, Mei H, Windham BG, Griswold M, Gottesman RF, Boerwinkle E, Fornage M, Mosley TH. Genetic Risk, Midlife Life's Simple 7, and Incident Dementia in the Atherosclerosis Risk in Communities Study. Neurology 2022; 99:e154-e163. [PMID: 35613930 PMCID: PMC9280991 DOI: 10.1212/wnl.0000000000200520] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 02/28/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Higher scores in Life's Simple 7 (LS7), a metric for cardiovascular and brain health, have been associated with lower risk of dementia. It is uncertain whether this association holds among those with high genetic risk of dementia. Our objective is to evaluate the extent that LS7 may offset dementia risk across the range of genetic risk. METHODS Participants in the Atherosclerosis Risk in Communities (ARIC) Study were followed from 1987-1989 to 2019. We derived midlife LS7 scores and generated genetic risk scores (GRS) using genome-wide summary statistics of Alzheimer disease, which have been used to study the genetic risk for dementia. Incident dementia was ascertained based on the criteria of the National Institute on Aging-Alzheimer's Association workgroups and Diagnostic and Statistical Manual of Mental Disorders. The associations of the GRS and LS7 with incident dementia were evaluated using Cox regression. RESULTS This study included 8,823 European American (EA) and 2,738 African American (AA) participants (mean age at baseline 54 years). We observed 1,603 cases of dementia among EA participants and 631 among AA participants (median follow-up 26.2 years). Higher GRS were associated with higher risk of dementia (EA, hazard ratio [HR] per SD 1.44, 95% CI 1.37, 1.51; AA, HR 1.26, 95% CI 1.16, 1.36). Among EA participants, higher LS7 scores were consistently associated with lower risk of dementia across quintiles of GRS, including the highest quintile (HR per point 0.91, 95% CI 0.87, 0.96). Among AA participants, the associations between LS7 and incident dementia within stratum of GRS had the same direction as among EA participants, although wide CIs and smaller sample sizes limited reliable inferences. DISCUSSION Across strata of GRS, higher midlife LS7 scores were associated with lower risk of dementia. Larger sample sizes from diverse populations are needed to obtain more reliable estimates of the effects of modifiable health factors on dementia risk within genetic risk strata in each ancestry group.
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Affiliation(s)
- Adrienne Tin
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD.
| | - Jan Bressler
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Jeannette Simino
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Kevin J Sullivan
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Hao Mei
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - B Gwen Windham
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Michael Griswold
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Rebecca F Gottesman
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Eric Boerwinkle
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Myriam Fornage
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Thomas H Mosley
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
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Georgakis MK, Ntanasi E, Ramirez A, Grenier-Boley B, Lambert JC, Sakka P, Yannakoulia M, Kosmidis MH, Dardiotis E, Hadjigeorgiou GM, Charissis S, Mourtzi N, Hatzimanolis A, Scarmeas N. Vascular burden and genetic risk in association with cognitive performance and dementia in a population-based study. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2022; 3:100145. [PMID: 36324400 PMCID: PMC9616333 DOI: 10.1016/j.cccb.2022.100145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 02/19/2022] [Accepted: 04/28/2022] [Indexed: 06/16/2023]
Abstract
Background and purpose Vascular risk factors may influence cognitive function and thus represent possible targets for preventive approaches against dementia. Yet it remains unknown, if they associate with cognition independently of the individual genetic risk for dementia. Methods In a population-based study of 1172 community-dwelling individuals aged ≥65 years in Greece, we constructed a vascular burden score (VBS; based on presence of hypertension, diabetes, hyperlipidemia, heart disease, and cerebrovascular disease, range 0-5) and a polygenic risk score (PRS) for clinically-diagnosed Alzheimer's disease (AD) based on 23 genetic variants. We then explored in joint models the associations of the PRS for AD and VBS with global cognitive performance, cognitive performance across multiple cognitive domains, and odds of dementia. Results The mean age of study participants was 73.9 ± 5.2 years (57.1% females). Both the PRS for AD and VBS were associated with worse global cognitive performance (beta per-SD-increment in PRS: -0.06, 95%CI: -0.10 to -0.02, beta per-point-increment in VBS: -0.05, 95%CI: -0.09 to -0.02), worse performance across individual cognitive domains (memory, executive function, attention, language, visuospatial ability), and higher odds of dementia (OR per-SD increment in PRS: 1.56, 95%CI: 1.17-2.09, OR per-point increment in VBS: 1.38, 95%CI: 1.05-1.81). There was no evidence of an interaction between the two scores. Higher VBS was associated with worse cognitive performance equally across tertiles of the PRS for AD, even among individuals at the highest tertile. Conclusions Both genetic risk and vascular burden are independently and additively associated with worse cognitive performance and higher odds of dementia.
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Affiliation(s)
- Marios K. Georgakis
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-University LMU, Feodor-Lynen-Str. 17, Munich 81377, Germany
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programme in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eva Ntanasi
- 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Alfredo Ramirez
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Benjamin Grenier-Boley
- U1167-RID-AGE Facteurs de Risque et Déterminants Moléculaires des Maladies Liés au Vieillissement, University of Lille, Inserm, CHU Lille, Institut Pasteur de Lille, Lille, France
| | - Jean-Charles Lambert
- U1167-RID-AGE Facteurs de Risque et Déterminants Moléculaires des Maladies Liés au Vieillissement, University of Lille, Inserm, CHU Lille, Institut Pasteur de Lille, Lille, France
| | - Paraskevi Sakka
- Athens Association of Alzheimer's Disease and Related Disorders, Marousi, Greece
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Mary H. Kosmidis
- Lab of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Efthimios Dardiotis
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | | | - Sokratis Charissis
- 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
| | - Niki Mourtzi
- 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
| | - Alexandros Hatzimanolis
- Department of Psychiatry, National and Kapodistrian University of Athens Medical School, Eginition Hospital, Athens, Greece
- Theodor-Theohari Cozzika Foundation, Neurobiology Research Institute, Athens, Greece
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA
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Polygenic Risk Scores Contribute to Personalized Medicine of Parkinson's Disease. J Pers Med 2021; 11:jpm11101030. [PMID: 34683174 PMCID: PMC8539098 DOI: 10.3390/jpm11101030] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 12/18/2022] Open
Abstract
Parkinson’s disease (PD) is the second most common neurodegenerative disorder characterized by the loss of dopaminergic neurons. The vast majority of PD patients develop the disease sporadically and it is assumed that the cause lies in polygenic and environmental components. The overall polygenic risk is the result of a large number of common low-risk variants discovered by large genome-wide association studies (GWAS). Polygenic risk scores (PRS), generated by compiling genome-wide significant variants, are a useful prognostic tool that quantifies the cumulative effect of genetic risk in a patient and in this way helps to identify high-risk patients. Although there are limitations to the construction and application of PRS, such as considerations of limited genetic underpinning of diseases explained by SNPs and generalizability of PRS to other populations, this personalized risk prediction could make a promising contribution to stratified medicine and tailored therapeutic interventions in the future.
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Ebenau JL, van der Lee SJ, Hulsman M, Tesi N, Jansen IE, Verberk IM, van Leeuwenstijn M, Teunissen CE, Barkhof F, Prins ND, Scheltens P, Holstege H, van Berckel BN, van der Flier WM. Risk of dementia in APOE ε4 carriers is mitigated by a polygenic risk score. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12229. [PMID: 34541285 PMCID: PMC8438688 DOI: 10.1002/dad2.12229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/09/2021] [Accepted: 06/28/2021] [Indexed: 12/22/2022]
Abstract
INTRODUCTION We investigated relationships among genetic determinants of Alzheimer's disease (AD), amyloid/tau/neurodegenaration (ATN) biomarkers, and risk of dementia. METHODS We studied cognitively normal individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort and SCIENCe project. We examined associations between genetic variants and ATN biomarkers, and evaluated their predictive value for incident dementia. A polygenic risk score (PRS) was calculated based on 39 genetic variants. The APOE gene was not included in the PRS and was analyzed separately. RESULTS The PRS and APOE ε4 were associated with amyloid-positive ATN profiles, and APOE ε4 additionally with isolated increased tau (A-T+N-). A high PRS and APOE ε4 separately predicted AD dementia. Combined, a high PRS increased while a low PRS attenuated the risk associated with ε4 carriers. DISCUSSION Genetic variants beyond APOE are clinically relevant and contribute to the pathophysiology of AD. In the future, a PRS might be used in individualized risk profiling.
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Affiliation(s)
- Jarith L. Ebenau
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Sven J. van der Lee
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
| | - Marc Hulsman
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Niccolò Tesi
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Iris E. Jansen
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Complex Trait GeneticsCenter for Neurogenomics and Cognitive ResearchAmsterdam NeuroscienceVU UniversityAmsterdamthe Netherlands
| | - Inge M.W. Verberk
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Mardou van Leeuwenstijn
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Niels D. Prins
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Philip Scheltens
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Henne Holstege
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Bart N.M. van Berckel
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Radiology & Nuclear MedicineAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Epidemiology and BiostatisticsAmsterdam UMCAmsterdamthe Netherlands
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18
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The potential roles of genetic factors in predicting ageing-related cognitive change and Alzheimer's disease. Ageing Res Rev 2021; 70:101402. [PMID: 34242808 DOI: 10.1016/j.arr.2021.101402] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 06/22/2021] [Accepted: 07/02/2021] [Indexed: 12/21/2022]
Abstract
Alzheimer's disease (AD) is a complex neurological disorder of uncertain aetiology, although substantial research has been conducted to explore important factors related to risk of onset and progression. Both lifestyle (e.g., complex mental stimulation, vascular health) and genetic factors (e.g., APOE, BDNF, PICALM, CLU, APP, PSEN1, PSEN2, and other genes) have been associated with AD risk. Despite more than thirty years of genetic research, much of the heritability of AD is not explained by measured loci. This suggests that the missing heritability of AD might be potentially related to rare variants, gene-environment and gene-gene interactions, and potentially epigenetic modulators. Moreover, while ageing is the most substantial factor risk for AD, there are limited longitudinal studies examining the association of genetic factors with decline in cognitive function due to ageing and the preclinical stages of this condition. This review summarises findings from currently available research on the genetic factors of ageing-related cognitive change and AD and suggests some future research directions.
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Pyun JM, Park YH, Lee KJ, Kim S, Saykin AJ, Nho K. Predictability of polygenic risk score for progression to dementia and its interaction with APOE ε4 in mild cognitive impairment. Transl Neurodegener 2021; 10:32. [PMID: 34465370 PMCID: PMC8406896 DOI: 10.1186/s40035-021-00259-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 08/14/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The combinatorial effect of multiple genetic factors calculated as a polygenic risk score (PRS) has been studied to predict disease progression to Alzheimer's disease (AD) from mild cognitive impairment (MCI). Previous studies have investigated the performance of PRS in the prediction of disease progression to AD by including and excluding single nucleotide polymorphisms within the region surrounding the APOE gene. These studies may have missed the APOE genotype-specific predictability of PRS for disease progression to AD. METHODS We analyzed 732 MCI from the Alzheimer's Disease Neuroimaging Initiative cohort, including those who progressed to AD within 5 years post-baseline (n = 270) and remained stable as MCI (n = 462). The predictability of PRS including and excluding the APOE region (PRS+APOE and PRS-APOE) on the conversion to AD and its interaction with the APOE ε4 carrier status were assessed using Cox regression analyses. RESULTS PRS+APOE (hazard ratio [HR] 1.468, 95% CI 1.335-1.615) and PRS-APOE (HR 1.293, 95% CI 1.157-1.445) were both associated with a significantly increased risk of MCI progression to dementia. The interaction between PRS+APOE and APOE ε4 carrier status was significant with a P-value of 0.0378. The association of PRSs with the progression risk was stronger in APOE ε4 non-carriers (PRS+APOE: HR 1.710, 95% CI 1.244-2.351; PRS-APOE: HR 1.429, 95% CI 1.182-1.728) than in APOE ε4 carriers (PRS+APOE: HR 1.167, 95% CI 1.005-1.355; PRS-APOE: HR 1.172, 95% CI 1.020-1.346). CONCLUSIONS PRS could predict the conversion of MCI to dementia with a stronger association in APOE ε4 non-carriers than APOE ε4 carriers. This indicates PRS as a potential genetic predictor particularly for MCI with no APOE ε4 alleles.
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Affiliation(s)
- Jung-Min Pyun
- Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University, Uijeongbu, Republic of Korea
| | - Young Ho Park
- Department of Neurology, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seongnam, Republic of Korea.
| | - Keon-Joo Lee
- Department of Neurology, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - SangYun Kim
- Department of Neurology, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
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20
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Frank M, Hensel J, Baak L, Schramm S, Dragano N, Weimar C, Hoffmann P, Nöthen MM, Erbel R, Jöckel KH, Jokisch M, Schmidt B. Interaction of Alzheimer's Disease-Associated Genetic Risk with Indicators of Socioeconomic Position on Mild Cognitive Impairment in the Heinz Nixdorf Recall Study. J Alzheimers Dis 2021; 82:1715-1725. [PMID: 34219719 PMCID: PMC8461721 DOI: 10.3233/jad-210244] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The apolipoprotein E (APOE) ɛ4 allele is reported to be a strong genetic risk factor for mild cognitive impairment (MCI) and Alzheimer's disease (AD). Additional genetic loci have been detected that influence the risk for late-onset AD. As socioeconomic position (SEP) is also strongly related to cognitive decline, SEP has been suggested to be a possible modifier of the genetic effect on MCI. OBJECTIVE To investigate whether APOEɛ4 and a genetic sum score of AD-associated risk alleles (GRSAD) interact with SEP indicators to affect MCI in a population-based cohort. METHODS Using data of 3,834 participants of the Heinz Nixdorf Recall Study, APOEɛ4 and GRSAD by SEP interactions were assessed using logistic regression models, as well as SEP-stratified genetic association analysis. Interaction on additive scale was calculated using the relative excess risk due to interaction (RERI). All analysis were additionally stratified by sex. RESULTS Indication for interaction on the additive scale was found between APOEɛ4 and low education on MCI (RERI: 0.52 [95% confidence interval (CI): 0.01; 1.03]). The strongest genetic effects of the APOEɛ4 genotype on MCI were observed in groups of low education (Odds ratio (OR): 1.46 [95% CI: 0.79; 2.63] for≤10 years of education versus OR: 1.00 [95% CI: 0.43; 2.14] for≥18 years of education). Sex stratified results showed stronger effects in women. No indication for interaction between the GRSAD and SEP indicators on MCI was observed. CONCLUSION Results indicate that low education may have an impact on APOEɛ4 expression on MCI, especially among women.
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Affiliation(s)
- Mirjam Frank
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Jonas Hensel
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Lisa Baak
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Sara Schramm
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Nico Dragano
- Institute of Medical Sociology, Centre for Health and Society, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Christian Weimar
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany.,BDH-clinic Elzach, Elzach, Germany
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Raimund Erbel
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Martha Jokisch
- Department of Neurology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
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21
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de Rojas I, Moreno-Grau S, Tesi N, Grenier-Boley B, Andrade V, Jansen IE, Pedersen NL, Stringa N, Zettergren A, Hernández I, Montrreal L, Antúnez C, Antonell A, Tankard RM, Bis JC, Sims R, Bellenguez C, Quintela I, González-Perez A, Calero M, Franco-Macías E, Macías J, Blesa R, Cervera-Carles L, Menéndez-González M, Frank-García A, Royo JL, Moreno F, Huerto Vilas R, Baquero M, Diez-Fairen M, Lage C, García-Madrona S, García-González P, Alarcón-Martín E, Valero S, Sotolongo-Grau O, Ullgren A, Naj AC, Lemstra AW, Benaque A, Pérez-Cordón A, Benussi A, Rábano A, Padovani A, Squassina A, de Mendonça A, Arias Pastor A, Kok AAL, Meggy A, Pastor AB, Espinosa A, Corma-Gómez A, Martín Montes A, Sanabria Á, DeStefano AL, Schneider A, Haapasalo A, Kinhult Ståhlbom A, Tybjærg-Hansen A, Hartmann AM, Spottke A, Corbatón-Anchuelo A, Rongve A, Borroni B, Arosio B, Nacmias B, Nordestgaard BG, Kunkle BW, Charbonnier C, Abdelnour C, Masullo C, Martínez Rodríguez C, Muñoz-Fernandez C, Dufouil C, Graff C, Ferreira CB, Chillotti C, Reynolds CA, Fenoglio C, Van Broeckhoven C, Clark C, Pisanu C, Satizabal CL, Holmes C, Buiza-Rueda D, Aarsland D, Rujescu D, Alcolea D, Galimberti D, Wallon D, Seripa D, Grünblatt E, Dardiotis E, Düzel E, Scarpini E, Conti E, Rubino E, Gelpi E, Rodriguez-Rodriguez E, et alde Rojas I, Moreno-Grau S, Tesi N, Grenier-Boley B, Andrade V, Jansen IE, Pedersen NL, Stringa N, Zettergren A, Hernández I, Montrreal L, Antúnez C, Antonell A, Tankard RM, Bis JC, Sims R, Bellenguez C, Quintela I, González-Perez A, Calero M, Franco-Macías E, Macías J, Blesa R, Cervera-Carles L, Menéndez-González M, Frank-García A, Royo JL, Moreno F, Huerto Vilas R, Baquero M, Diez-Fairen M, Lage C, García-Madrona S, García-González P, Alarcón-Martín E, Valero S, Sotolongo-Grau O, Ullgren A, Naj AC, Lemstra AW, Benaque A, Pérez-Cordón A, Benussi A, Rábano A, Padovani A, Squassina A, de Mendonça A, Arias Pastor A, Kok AAL, Meggy A, Pastor AB, Espinosa A, Corma-Gómez A, Martín Montes A, Sanabria Á, DeStefano AL, Schneider A, Haapasalo A, Kinhult Ståhlbom A, Tybjærg-Hansen A, Hartmann AM, Spottke A, Corbatón-Anchuelo A, Rongve A, Borroni B, Arosio B, Nacmias B, Nordestgaard BG, Kunkle BW, Charbonnier C, Abdelnour C, Masullo C, Martínez Rodríguez C, Muñoz-Fernandez C, Dufouil C, Graff C, Ferreira CB, Chillotti C, Reynolds CA, Fenoglio C, Van Broeckhoven C, Clark C, Pisanu C, Satizabal CL, Holmes C, Buiza-Rueda D, Aarsland D, Rujescu D, Alcolea D, Galimberti D, Wallon D, Seripa D, Grünblatt E, Dardiotis E, Düzel E, Scarpini E, Conti E, Rubino E, Gelpi E, Rodriguez-Rodriguez E, Duron E, Boerwinkle E, Ferri E, Tagliavini F, Küçükali F, Pasquier F, Sanchez-Garcia F, Mangialasche F, Jessen F, Nicolas G, Selbæk G, Ortega G, Chêne G, Hadjigeorgiou G, Rossi G, Spalletta G, Giaccone G, Grande G, Binetti G, Papenberg G, Hampel H, Bailly H, Zetterberg H, Soininen H, Karlsson IK, Alvarez I, Appollonio I, Giegling I, Skoog I, Saltvedt I, Rainero I, Rosas Allende I, Hort J, Diehl-Schmid J, Van Dongen J, Vidal JS, Lehtisalo J, Wiltfang J, Thomassen JQ, Kornhuber J, Haines JL, Vogelgsang J, Pineda JA, Fortea J, Popp J, Deckert J, Buerger K, Morgan K, Fließbach K, Sleegers K, Molina-Porcel L, Kilander L, Weinhold L, Farrer LA, Wang LS, Kleineidam L, Farotti L, Parnetti L, Tremolizzo L, Hausner L, Benussi L, Froelich L, Ikram MA, Deniz-Naranjo MC, Tsolaki M, Rosende-Roca M, Löwenmark M, Hulsman M, Spallazzi M, Pericak-Vance MA, Esiri M, Bernal Sánchez-Arjona M, Dalmasso MC, Martínez-Larrad MT, Arcaro M, Nöthen MM, Fernández-Fuertes M, Dichgans M, Ingelsson M, Herrmann MJ, Scherer M, Vyhnalek M, Kosmidis MH, Yannakoulia M, Schmid M, Ewers M, Heneka MT, Wagner M, Scamosci M, Kivipelto M, Hiltunen M, Zulaica M, Alegret M, Fornage M, Roberto N, van Schoor NM, Seidu NM, Banaj N, Armstrong NJ, Scarmeas N, Scherbaum N, Goldhardt O, Hanon O, Peters O, Skrobot OA, Quenez O, Lerch O, Bossù P, Caffarra P, Dionigi Rossi P, Sakka P, Mecocci P, Hoffmann P, Holmans PA, Fischer P, Riederer P, Yang Q, Marshall R, Kalaria RN, Mayeux R, Vandenberghe R, Cecchetti R, Ghidoni R, Frikke-Schmidt R, Sorbi S, Hägg S, Engelborghs S, Helisalmi S, Botne Sando S, Kern S, Archetti S, Boschi S, Fostinelli S, Gil S, Mendoza S, Mead S, Ciccone S, Djurovic S, Heilmann-Heimbach S, Riedel-Heller S, Kuulasmaa T, Del Ser T, Lebouvier T, Polak T, Ngandu T, Grimmer T, Bessi V, Escott-Price V, Giedraitis V, Deramecourt V, Maier W, Jian X, Pijnenburg YAL, Kehoe PG, Garcia-Ribas G, Sánchez-Juan P, Pastor P, Pérez-Tur J, Piñol-Ripoll G, Lopez de Munain A, García-Alberca JM, Bullido MJ, Álvarez V, Lleó A, Real LM, Mir P, Medina M, Scheltens P, Holstege H, Marquié M, Sáez ME, Carracedo Á, Amouyel P, Schellenberg GD, Williams J, Seshadri S, van Duijn CM, Mather KA, Sánchez-Valle R, Serrano-Ríos M, Orellana A, Tárraga L, Blennow K, Huisman M, Andreassen OA, Posthuma D, Clarimón J, Boada M, van der Flier WM, Ramirez A, Lambert JC, van der Lee SJ, Ruiz A. Common variants in Alzheimer's disease and risk stratification by polygenic risk scores. Nat Commun 2021; 12:3417. [PMID: 34099642 PMCID: PMC8184987 DOI: 10.1038/s41467-021-22491-8] [Show More Authors] [Citation(s) in RCA: 189] [Impact Index Per Article: 47.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 03/17/2021] [Indexed: 11/09/2022] Open
Abstract
Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease.
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Affiliation(s)
- Itziar de Rojas
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Sonia Moreno-Grau
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Niccolo Tesi
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Delft Bioinformatics Lab, Delft Univeristy of Technology, Delft, The Netherlands
| | - Benjamin Grenier-Boley
- Univ. Lille, Inserm, Institut Pasteur de Lille, CHU Lille, U1167-Labex DISTALZ-RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Victor Andrade
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany
| | - Iris E Jansen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Najada Stringa
- Amsterdam UMC-Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Anna Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AgeCap), University of Gothenburg, Gothenburg, Sweden
| | - Isabel Hernández
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Laura Montrreal
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Carmen Antúnez
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain
| | - Anna Antonell
- Alzheimer's disease and other cognitive disorders unit. Service of Neurology, Hospital Clínic of Barcelona. Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | - Rick M Tankard
- Mathematics and Statistics, Murdoch University, Perth, WA, Australia
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Rebecca Sims
- Division of Psychological Medicine and Clinial Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Céline Bellenguez
- Univ. Lille, Inserm, Institut Pasteur de Lille, CHU Lille, U1167-Labex DISTALZ-RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Inés Quintela
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | | | - Miguel Calero
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- UFIEC, Instituto de Salud Carlos III, Madrid, Spain
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Emilio Franco-Macías
- Unidad de Demencias, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Juan Macías
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, Sevilla, Spain
| | - Rafael Blesa
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Laura Cervera-Carles
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Manuel Menéndez-González
- Servicio de Neurología, Hospital Universitario Central de Asturias, Oviedo, Spain
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
- Departamento de Medicina, Universidad de Oviedo, Oviedo, Spain
| | - Ana Frank-García
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, La Paz University Hospital, Instituto de Investigación Sanitaria del Hospital Universitario La Paz, IdiPAZ, Madrid, Spain
- Hospital La Paz Institute for Health Research, IdiPAZ, Madrid, Spain
- Universidad Autónoma de Madrid, Madrid, Spain
| | - Jose Luís Royo
- Departamento de Especialidades Quirúrgicas, Bioquímicas e Inmunología, School of Medicine, University of Málaga, Málaga, Spain
| | - Fermin Moreno
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, Hospital Universitario Donostia, San Sebastian, Spain
- Neurosciences Area, Instituto Biodonostia, San Sebastian, Spain
| | - Raquel Huerto Vilas
- Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Lleida, Spain
- Institut de Recerca Biomedica de Lleida (IRBLLeida), Lleida, Spain
| | - Miquel Baquero
- Servei de Neurologia, Hospital Universitari i Politècnic La Fe, Valencia, Spain
| | - Mónica Diez-Fairen
- Fundació Docència i Recerca MútuaTerrassa, Terrassa, Barcelona, Spain
- Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Carmen Lage
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander, Spain
| | | | - Pablo García-González
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Emilio Alarcón-Martín
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- Departamento de Especialidades Quirúrgicas, Bioquímicas e Inmunología, School of Medicine, University of Málaga, Málaga, Spain
| | - Sergi Valero
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Oscar Sotolongo-Grau
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Abbe Ullgren
- Karolinska Institutet, Center for Alzheimer Research, Department NVS, Division of Neurogeriatrics, Stockholm, Sweden
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital-Solna, Stockholm, Sweden
| | - Adam C Naj
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Afina W Lemstra
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alba Benaque
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Alba Pérez-Cordón
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Alberto Benussi
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alberto Rábano
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
- BT-CIEN, Madrid, Spain
| | - Alessandro Padovani
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alessio Squassina
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | | | - Alfonso Arias Pastor
- Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Lleida, Spain
- Institut de Recerca Biomedica de Lleida (IRBLLeida), Lleida, Spain
| | - Almar A L Kok
- Amsterdam UMC-Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Alun Meggy
- UK Dementia Research Institute at Cardiff, Cardiff University, Cardiff, UK
| | - Ana Belén Pastor
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
- BT-CIEN, Madrid, Spain
| | - Ana Espinosa
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Anaïs Corma-Gómez
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, Sevilla, Spain
| | - Angel Martín Montes
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Hospital La Paz Institute for Health Research, IdiPAZ, Madrid, Spain
- Department of Neurology, La Paz University Hospital, Madrid, Spain
| | - Ángela Sanabria
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Anita L DeStefano
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Anja Schneider
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Annakaisa Haapasalo
- A.I Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Anne Kinhult Ståhlbom
- Karolinska Institutet, Center for Alzheimer Research, Department NVS, Division of Neurogeriatrics, Stockholm, Sweden
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital-Solna, Stockholm, Sweden
| | - Anne Tybjærg-Hansen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Annette M Hartmann
- Martin-Luther-University Halle-Wittenberg, University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Halle (Saale), Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Arturo Corbatón-Anchuelo
- Instituto de Investigación Sanitaria, Hospital Clínico San Carlos (IdISSC), Madrid, Spain
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
| | - Arvid Rongve
- Haugesund Hospital, Helse Fonna, Department of Research and Innovation, Haugesund, Norway
- University of Bergen, Institute of Clinical Medicine (K1), Bergen, Norway
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Beatrice Arosio
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
- Geriatic Unit, Fondazione Cà Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Børge G Nordestgaard
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev Gentofte Hospital, Herlev, Denmark
| | - Brian W Kunkle
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Camille Charbonnier
- Normandie Univ, UNIROUEN, Inserm U1245, CHU Rouen, Department of Genetics and CNR-MAJ, FHU G4 Génomique, F-76000 Rouen, France
| | - Carla Abdelnour
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Carlo Masullo
- Institute of Neurology, Catholic University of the Sacred Heart, School of Medicine, Milan, Italy
| | - Carmen Martínez Rodríguez
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
- Hospital de Cabueñes, Gijón, Spain
| | - Carmen Muñoz-Fernandez
- Servicio de Neurología, Hospital Universitario de Gran Canaria Dr.Negrín, Las Palmas, Spain
| | - Carole Dufouil
- Inserm, Bordeaux Population Health Research Center, UMR 1219, Univ. Bordeaux, ISPED, CIC 1401-EC, Univ Bordeaux, Bordeaux, France
- CHU de Bordeaux, Pole de Santé Publique, Bordeaux, France
| | - Caroline Graff
- Karolinska Institutet, Center for Alzheimer Research, Department NVS, Division of Neurogeriatrics, Stockholm, Sweden
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital-Solna, Stockholm, Sweden
| | - Catarina B Ferreira
- Instituto de Medicina Molecular João lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Caterina Chillotti
- Unit of Clinical Pharmacology, University Hospital of Cagliari, Cagliari, Italy
| | - Chandra A Reynolds
- Department of Psychology, University of California-Riverside, Riverside, CA, USA
| | | | - Christine Van Broeckhoven
- VIB Center for Molecular Neurology, Antwerp, Belgium
- Laboratory of Neurogenetics, Institute Born-Bunge, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp., Antwerp, Belgium
| | - Christopher Clark
- Insititute for Regenerative Medicine, University of Zürich, Zürich, Switzerland
| | - Claudia Pisanu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Claudia L Satizabal
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
- Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX, USA
| | - Clive Holmes
- Division of Clinical Neurosciences, School of Medicine, University of Southampton, Southampton, UK
| | - Dolores Buiza-Rueda
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Dag Aarsland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Centre of Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Dan Rujescu
- Martin-Luther-University Halle-Wittenberg, University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Halle (Saale), Germany
| | - Daniel Alcolea
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Daniela Galimberti
- University of Milan, Dino Ferrari Center, Milan, Italy
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy
| | - David Wallon
- Normandie Univ, UNIROUEN, Inserm U1245, CHU Rouen, Department of Neurology and CNR-MAJ, FHU G4 Génomique, F-76000 Rouen, France
| | - Davide Seripa
- Complex Structure of Geriatrics, Department of Medical Sciences Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy
| | - Edna Grünblatt
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich (PUK), University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | | | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Elio Scarpini
- University of Milan, Dino Ferrari Center, Milan, Italy
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy
| | - Elisa Conti
- School of Medicine and Surgery, University of Milano-Bicocca and Milan Center for Neuroscience, Milan, Italy
| | - Elisa Rubino
- Department of Neuroscience and Mental Health, AOU Città della Salute e della Scienza di Torino, Torino, Italy
| | - Ellen Gelpi
- Neurological Tissue Bank of the Biobanc-Hospital Clinic-IDIBAPS, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Eloy Rodriguez-Rodriguez
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander, Spain
| | - Emmanuelle Duron
- APHP, Hôpital Brousse, equipe INSERM 1178, MOODS, Villejuif, France
- Université Paris-Saclay, UVSQ, Inserm, CESP, Team MOODS, Le Kremlin-Bicêtre, Paris, France
- APHP, Hôpital Broca, Paris, France
| | - Eric Boerwinkle
- School of Public Health, Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Evelyn Ferri
- Geriatic Unit, Fondazione Cà Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Fahri Küçükali
- VIB Center for Molecular Neurology, Antwerp, Belgium
- Laboratory of Neurogenetics, Institute Born-Bunge, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp., Antwerp, Belgium
| | - Florence Pasquier
- Inserm U1172, CHU, DISTAlz, LiCEND, Univ Lille, Lille, France
- CHU CNR-MAJ, Lille, France
| | - Florentino Sanchez-Garcia
- Servicio de Inmunología, Hospital Universitario de Gran Canaria Dr. Negrín, Las Palmas de Gran Canaria, Spain
| | - Francesca Mangialasche
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | | | - Geir Selbæk
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gemma Ortega
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Geneviève Chêne
- Inserm, Bordeaux Population Health Research Center, UMR 1219, Univ. Bordeaux, ISPED, CIC 1401-EC, Univ Bordeaux, Bordeaux, France
- CHU de Bordeaux, Pole de Santé Publique, Bordeaux, France
| | | | - Giacomina Rossi
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
- Beth K. and Stuart C. Yudofsky Division of Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | | | - Giulia Grande
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Giuliano Binetti
- MAC-Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Goran Papenberg
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Harald Hampel
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Paris, France
| | - Henri Bailly
- APHP, Hôpital Broca, Paris, France
- EA 4468, Sorbonne Paris Cité, Université Paris Descartes, Paris, France
| | - 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, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Hilkka Soininen
- Institute of Clinical Medicine Neurology, University of Eastern Finland, Kuopio, Finland
- Neurocenter, neurology, Kuopio University Hospital, Kuopio, Finland
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute for Gerontology and Aging Research Network-Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Ignacio Alvarez
- Fundació Docència i Recerca MútuaTerrassa, Terrassa, Barcelona, Spain
- Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Ildebrando Appollonio
- School of Medicine and Surgery, University of Milano-Bicocca and Milan Center for Neuroscience, Milan, Italy
- Neurology Unit, 'San Gerardo' hospital, Monza, Italy
| | - Ina Giegling
- Martin-Luther-University Halle-Wittenberg, University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Halle (Saale), Germany
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AgeCap), University of Gothenburg, Gothenburg, Sweden
| | - Ingvild Saltvedt
- Department of Geriatrics, Clinic of Medicine, St Olavs Hospital, University Hospital of Trondheim, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technhology (NTNU), Trondheim, Norway
| | - Innocenzo Rainero
- Department of Neuroscience "Rita Levi Montalcini", University of Torino, Torino, Italy
| | - Irene Rosas Allende
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
- Laboratorio de Genética, Hospital Universitario Central de Asturias, Oviedo, Spain
| | - Jakub Hort
- Memory Clinic, Department of Neurology, 2nd Faculty of Medicine and Motol University Hospital, Charles University, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - Janine Diehl-Schmid
- Department of Psychiatry and Psychotherapy, School of Medicine Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jasper Van Dongen
- VIB Center for Molecular Neurology, Antwerp, Belgium
- Laboratory of Neurogenetics, Institute Born-Bunge, Antwerp, Belgium
| | - Jean-Sebastien Vidal
- APHP, Hôpital Broca, Paris, France
- EA 4468, Sorbonne Paris Cité, Université Paris Descartes, Paris, France
| | - Jenni Lehtisalo
- Institute of Clinical Medicine Neurology, University of Eastern Finland, Kuopio, Finland
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | | | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Jonathan L Haines
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Jonathan Vogelgsang
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen, Germany
- Translational Neuroscience Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Juan A Pineda
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, Sevilla, Spain
| | - Juan Fortea
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Julius Popp
- Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland
- University of Zürich, Zürich, Switzerland
- Old age Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Jürgen Deckert
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital, Wuerzburg, Germany
| | - Katharina Buerger
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Kevin Morgan
- Schools of Life Sciences and Medicine, University of Nottingham, Nottingham, UK
| | - Klaus Fließbach
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany
| | - Kristel Sleegers
- VIB Center for Molecular Neurology, Antwerp, Belgium
- Laboratory of Neurogenetics, Institute Born-Bunge, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp., Antwerp, Belgium
| | - Laura Molina-Porcel
- Alzheimer's disease and other cognitive disorders unit. Service of Neurology, Hospital Clínic of Barcelona. Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
- Neurological Tissue Bank of the Biobanc-Hospital Clinic-IDIBAPS, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Lena Kilander
- Department of Public Health and Caring Sciences/Geriatrics, Uppsala, Sweden
| | - Leonie Weinhold
- Institute of Medical Biometry, Informatics and Epidemiology, University Hospital of Bonn, Bonn, Germany
| | - Lindsay A Farrer
- Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Epidemiology, and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Luca Kleineidam
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany
| | - Lucia Farotti
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, University of Perugia, Perugia, Italy
| | - Lucilla Parnetti
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, University of Perugia, Perugia, Italy
| | - Lucio Tremolizzo
- School of Medicine and Surgery, University of Milano-Bicocca and Milan Center for Neuroscience, Milan, Italy
- Neurology Unit, 'San Gerardo' hospital, Monza, Italy
| | - Lucrezia Hausner
- Department of Geriatric Psychiatry, Central Institute for Mental Health Mannheim, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Luisa Benussi
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Lutz Froelich
- Department of Geriatric Psychiatry, Central Institute for Mental Health Mannheim, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - M Candida Deniz-Naranjo
- Servicio de Inmunología, Hospital Universitario de Gran Canaria Dr. Negrín, Las Palmas de Gran Canaria, Spain
| | - Magda Tsolaki
- 1st Department of Neurology Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Maitée Rosende-Roca
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Malin Löwenmark
- Department of Public Health and Caring Sciences/Geriatrics, Uppsala, Sweden
| | - Marc Hulsman
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | | | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Margaret Esiri
- Nuffield Department of Clinical Neurosciences, Oxford, UK
| | - María Bernal Sánchez-Arjona
- Unidad de Demencias, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Maria Carolina Dalmasso
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany
| | - María Teresa Martínez-Larrad
- Instituto de Investigación Sanitaria, Hospital Clínico San Carlos (IdISSC), Madrid, Spain
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
| | - Marina Arcaro
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Marta Fernández-Fuertes
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, Sevilla, Spain
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences/Geriatrics, Uppsala, Sweden
| | - Martin J Herrmann
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital, Wuerzburg, Germany
| | - Martin Scherer
- Department of Primary Medical Care, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Martin Vyhnalek
- Memory Clinic, Department of Neurology, 2nd Faculty of Medicine and Motol University Hospital, Charles University, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - Mary H Kosmidis
- Laboratory of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute of Medical Biometry, Informatics and Epidemiology, University Hospital of Bonn, Bonn, Germany
| | - Michael Ewers
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Michael T Heneka
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Michael Wagner
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Michela Scamosci
- Institute of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy
| | - Miia Kivipelto
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- Neuroepidemiology and Ageing Research Unit, School of Public Health, Imperial College London, London, UK
- Stockholms Sjukhem, Research & Development Unit, Stockholm, Sweden
| | - Mikko Hiltunen
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Miren Zulaica
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Neurosciences Area, Instituto Biodonostia, San Sebastian, Spain
| | - Montserrat Alegret
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Natalia Roberto
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Natasja M van Schoor
- Amsterdam UMC-Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Nazib M Seidu
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AgeCap), University of Gothenburg, Gothenburg, Sweden
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | | | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, Medical School, Athens, Greece
- Taub Institute for Research in Alzheimer's Disease and the Aging Brain, The Gertrude H. Sergievsky Center, Depatment of Neurology, Columbia University, New York, NY, USA
| | - Norbert Scherbaum
- LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - Oliver Goldhardt
- Department of Psychiatry and Psychotherapy, School of Medicine Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Oliver Hanon
- APHP, Hôpital Broca, Paris, France
- EA 4468, Sorbonne Paris Cité, Université Paris Descartes, Paris, France
| | - Oliver Peters
- Department of Psychiatry and Psychotherapy and Experimental and Clinical Research Center (ECRC), Charité-Universitätsmedizin Berlin, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Olivia Anna Skrobot
- Bristol Medical School (THS), University of Bristol, Southmead Hospital, Bristol, UK
| | - Olivier Quenez
- Normandie Univ, UNIROUEN, Inserm U1245, CHU Rouen, Department of Genetics and CNR-MAJ, FHU G4 Génomique, F-76000 Rouen, France
| | - Ondrej Lerch
- Memory Clinic, Department of Neurology, 2nd Faculty of Medicine and Motol University Hospital, Charles University, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - Paola Bossù
- Experimental Neuro-psychobiology Laboratory, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Paolo Caffarra
- Unit of Neuroscience, DIMEC, University of Parma, Parma, Italy
| | - Paolo Dionigi Rossi
- Geriatic Unit, Fondazione Cà Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | - Paraskevi Sakka
- Athens Association of Alzheimer's disease and Related Disorders, Athens, Greece
| | - Patrizia Mecocci
- Institute of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - Peter A Holmans
- Division of Psychological Medicine and Clinial Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Peter Fischer
- Department of Psychiatry, Social Medicine Center East- Donauspital, Vienna, Austria
| | - Peter Riederer
- Center of Mental Health, Clinic and Policlinic of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, Würzburg, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Rachel Marshall
- Division of Psychological Medicine and Clinial Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Rajesh N Kalaria
- Translational and Clincial Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Campus for Ageing anf Vitality, Newcastle upon Tyne, UK
| | - Richard Mayeux
- Taub Institute on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University, New York, NY, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
- Department of Neurology, Columbia University, New York, NY, USA
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, University of Leuven, Leuven, Belgium
- Neurology Department, University Hospitals Leuven, Leuven, Belgium
| | - Roberta Cecchetti
- Institute of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy
| | - Roberta Ghidoni
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastiaan Engelborghs
- Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
- Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Department of Neurology, VUB University Hospital Brussels (UZ Brussel), Brussels, Belgium
| | - Seppo Helisalmi
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Sigrid Botne Sando
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Silke Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AgeCap), University of Gothenburg, Gothenburg, Sweden
| | - Silvana Archetti
- Department of Laboratory Diagnostics, III Laboratory of Analysis, Brescia Hospital, Brescia, Italy
| | - Silvia Boschi
- Department of Neuroscience "Rita Levi Montalcini", University of Torino, Torino, Italy
| | - Silvia Fostinelli
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Silvia Gil
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Silvia Mendoza
- Alzheimer Research Center & Memory Clinic, Andalusian Institute for Neuroscience, Málaga, Spain
| | - Simon Mead
- MRC Prion Unit at UCL, Institute of Prion Diseases, London, UK
| | - Simona Ciccone
- Geriatic Unit, Fondazione Cà Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Steffi Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany
| | - Teemu Kuulasmaa
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Teodoro Del Ser
- Department of Neurology/CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Thibaud Lebouvier
- Inserm U1172, CHU, DISTAlz, LiCEND, Univ Lille, Lille, France
- CHU CNR-MAJ, Lille, France
| | - Thomas Polak
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital, Wuerzburg, Germany
| | - Tiia Ngandu
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Timo Grimmer
- Department of Psychiatry and Psychotherapy, School of Medicine Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health University of Florence, Florence, Italy
- Azienda Ospedaliero-Universitaria Careggi Largo Brambilla, Florence, Italy
| | - Valentina Escott-Price
- Division of Psychological Medicine and Clinial Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- UKDRI Cardiff, Cardiff University, Cardiff, UK
| | | | - Vincent Deramecourt
- Inserm U1172, CHU, DISTAlz, LiCEND, Univ Lille, Lille, France
- CHU CNR-MAJ, Lille, France
| | - Wolfgang Maier
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Xueqiu Jian
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Patrick Gavin Kehoe
- Bristol Medical School (THS), University of Bristol, Southmead Hospital, Bristol, UK
| | | | - Pascual Sánchez-Juan
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander, Spain
| | - Pau Pastor
- Fundació Docència i Recerca MútuaTerrassa, Terrassa, Barcelona, Spain
- Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Jordi Pérez-Tur
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Unitat de Genètica Molecular, Institut de Biomedicina de València-CSIC, Valencia, Spain
- Unidad Mixta de Neurologia Genètica, Instituto de Investigación Sanitaria La Fe, Valencia, Spain
| | - Gerard Piñol-Ripoll
- Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Lleida, Spain
- Institut de Recerca Biomedica de Lleida (IRBLLeida), Lleida, Spain
| | - Adolfo Lopez de Munain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, Hospital Universitario Donostia, San Sebastian, Spain
- Neurosciences Area, Instituto Biodonostia, San Sebastian, Spain
- Department of Neurosciences, Faculty of Medicine and Nursery, University of the Basque Country, San Sebastián, Spain
| | - Jose María García-Alberca
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Alzheimer Research Center & Memory Clinic, Andalusian Institute for Neuroscience, Málaga, Spain
| | - María J Bullido
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Universidad Autónoma de Madrid, Madrid, Spain
- Centro de Biología Molecular Severo Ochoa (UAM-CSIC), Madrid, Spain
- Instituto de Investigacion Sanitaria 'Hospital la Paz' (IdIPaz), Madrid, Spain
| | - Victoria Álvarez
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
- Laboratorio de Genética, Hospital Universitario Central de Asturias, Oviedo, Spain
| | - Alberto Lleó
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Luis M Real
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, Sevilla, Spain
- Departamento de Especialidades Quirúrgicas, Bioquímica e Inmunología. Facultad de Medicina, Universidad de Málaga, Málaga, Spain
| | - Pablo Mir
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Miguel Medina
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Henne Holstege
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marta Marquié
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | | | - Ángel Carracedo
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Fundación Pública Galega de Medicina Xenómica-CIBERER-IDIS, Santiago de Compostela, Spain
| | - Philippe Amouyel
- Univ. Lille, Inserm, Institut Pasteur de Lille, CHU Lille, U1167-Labex DISTALZ-RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Gerard D Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Julie Williams
- Division of Psychological Medicine and Clinial Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- UK Dementia Research Institute at Cardiff, Cardiff University, Cardiff, UK
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Karen A Mather
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Raquel Sánchez-Valle
- Alzheimer's disease and other cognitive disorders unit. Service of Neurology, Hospital Clínic of Barcelona. Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | - Manuel Serrano-Ríos
- Instituto de Investigación Sanitaria, Hospital Clínico San Carlos (IdISSC), Madrid, Spain
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
| | - Adelina Orellana
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Lluís Tárraga
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - 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
| | - Martijn Huisman
- Amsterdam UMC-Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Sociology, VU University, Amsterdam, The Netherlands
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - Jordi Clarimón
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mercè Boada
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
| | - Jean-Charles Lambert
- Univ. Lille, Inserm, Institut Pasteur de Lille, CHU Lille, U1167-Labex DISTALZ-RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Sven J van der Lee
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Agustín Ruiz
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain.
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain.
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22
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Lawingco T, Chaudhury S, Brookes KJ, Guetta-Baranes T, Guerreiro R, Bras J, Hardy J, Francis P, Thomas A, Belbin O, Morgan K. Genetic variants in glutamate-, Aβ-, and tau-related pathways determine polygenic risk for Alzheimer's disease. Neurobiol Aging 2021; 101:299.e13-299.e21. [PMID: 33303219 DOI: 10.1016/j.neurobiolaging.2020.11.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 10/29/2020] [Accepted: 11/07/2020] [Indexed: 12/14/2022]
Abstract
Synapse loss is an early event in late-onset Alzheimer's disease (LOAD). In this study, we have assessed the capacity of a polygenic risk score (PRS) restricted to synapse-encoding loci to predict LOAD. We used summary statistics from the International Genetics of Alzheimer's Project genome-wide association meta-analysis of 74,046 patients for model construction and tested the "synaptic PRS" in 2 independent data sets of controls and pathologically confirmed LOAD. The mean synaptic PRS was 2.3-fold higher in LOAD than that in controls (p < 0.0001) with a predictive accuracy of 72% in the target data set (n = 439) and 73% in the validation data set (n = 136), a 5%-6% improvement compared with the APOE locus (p < 0.00001). The model comprises 8 variants from 4 previously identified (BIN1, PTK2B, PICALM, APOE) and 2 novel (DLG2, MINK1) LOAD loci involved in glutamate signaling (p = 0.01) or APP catabolism or tau binding (p = 0.005). As the simplest PRS model with good predictive accuracy to predict LOAD, we conclude that synapse-encoding genes are enriched for LOAD risk-modifying loci. The synaptic PRS could be used to identify individuals at risk of LOAD before symptom onset.
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Affiliation(s)
- Ted Lawingco
- Human Genetics Group, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Sultan Chaudhury
- Human Genetics Group, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Keeley J Brookes
- Human Genetics Group, School of Life Sciences, University of Nottingham, Nottingham, UK; Biosciences School of Science & Technology, Nottingham Trent University, Nottingham, UK
| | - Tamar Guetta-Baranes
- Human Genetics Group, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Rita Guerreiro
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA; Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI, USA
| | - Jose Bras
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA; Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI, USA
| | - John Hardy
- UK Dementia Research Institute and Department of Neurodegenerative Disease and Reta Lila Weston Institute, UCL Institute of Neurology and UCL Movement Disorders Centre, University College London, London, UK; Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | | | - Alan Thomas
- Brains for Dementia Research Resource, Newcastle, UK
| | - Olivia Belbin
- Sant Pau Memory Unit and Biomedical Research Institute Sant Pau (IIB Sant Pau), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain.
| | - Kevin Morgan
- Human Genetics Group, School of Life Sciences, University of Nottingham, Nottingham, UK.
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23
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Bakulski KM, Vadari HS, Faul JD, Heeringa SG, Kardia SL, Langa KM, Smith JA, Manly JJ, Mitchell CM, Benke KS, Ware EB. Cumulative Genetic Risk and APOE ε4 Are Independently Associated With Dementia Status in a Multiethnic, Population-Based Cohort. Neurol Genet 2021; 7:e576. [PMID: 33688582 PMCID: PMC7938646 DOI: 10.1212/nxg.0000000000000576] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 10/29/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Alzheimer disease (AD) is a common and costly neurodegenerative disorder. A large proportion of AD risk is heritable, and many genetic risk factors have been identified. The objective of this study was to test the hypothesis that cumulative genetic risk of known AD markers contributed to odds of dementia in a population-based sample. METHODS In the US population-based Health and Retirement Study (waves 1995-2014), we evaluated the role of cumulative genetic risk of AD, with and without the APOE ε4 alleles, on dementia status (dementia, cognitive impairment without dementia, borderline cognitive impairment without dementia, and cognitively normal). We used logistic regression, accounting for demographic covariates and genetic principal components, and analyses were stratified by European and African genetic ancestry. RESULTS In the European ancestry sample (n = 8,399), both AD polygenic score excluding the APOE genetic region (odds ratio [OR] = 1.10; 95% confidence interval [CI]: 1.00-1.20) and the presence of any APOE ε4 alleles (OR = 2.42; 95% CI: 1.99-2.95) were associated with the odds of dementia relative to normal cognition in a mutually adjusted model. In the African ancestry sample (n = 1,605), the presence of any APOE ε4 alleles was associated with 1.77 (95% CI: 1.20-2.61) times higher odds of dementia, whereas the AD polygenic score excluding the APOE genetic region was not significantly associated with the odds of dementia relative to normal cognition 1.06 (95% CI: 0.97-1.30). CONCLUSIONS Cumulative genetic risk of AD and APOE ε4 are both independent predictors of dementia in European ancestry. This study provides important insight into the polygenic nature of dementia and demonstrates the utility of polygenic scores in dementia research.
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Affiliation(s)
- Kelly M. Bakulski
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Harita S. Vadari
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Jessica D. Faul
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Steven G. Heeringa
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Sharon L.R. Kardia
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Kenneth M. Langa
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Jennifer A. Smith
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Jennifer J. Manly
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Colter M. Mitchell
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Kelly S. Benke
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Erin B. Ware
- From the Department of Epidemiology (K.M.B., S.L.R.K., J.A.S.), School of Public Health, University of Michigan; Survey Research Center (H.S.V., J.D.F., S.G.H., K.M.L., C.M.M., E.B.W.), Institute for Social Research, University of Michigan; VA Center for Clinical Management Research (K.M.L.), Ann Arbor, MI; Department of Neurology (J.J.M.), Columbia University, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain (J.J.M.), New York; and Department of Mental Health (K.S.B.), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
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24
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Creese B, Arathimos R, Brooker H, Aarsland D, Corbett A, Lewis C, Ballard C, Ismail Z. Genetic risk for Alzheimer's disease, cognition, and mild behavioral impairment in healthy older adults. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12164. [PMID: 33748395 PMCID: PMC7968121 DOI: 10.1002/dad2.12164] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 01/22/2021] [Accepted: 01/26/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND The neuropsychiatric syndrome mild behavioral impairment (MBI) describes an at-risk state for dementia and may be a useful screening tool for sample enrichment. We hypothesized that stratifying a cognitively normal sample on MBI status would enhance the association between genetic risk for Alzheimer's disease (AD) and cognition. METHODS Data from 4458 participants over age 50 without dementia was analyzed. A cognitive composite score was constructed and the MBI Checklist was used to stratify those with MBI and those without. Polygenic scores for AD were generated using summary statistics from the IGAP study. RESULTS AD genetic risk was associated with worse cognition in the MBI group but not in the no MBI group (MBI: β = -0.09, 95% confidence interval: -0.13 to -0.03, P = 0.002, R2 = 0.003). The strongest association was in those with more severe MBI aged ≥65. CONCLUSIONS MBI is an important feature of aging; screening on MBI may be a useful sample enrichment strategy for clinical research.
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Affiliation(s)
- Byron Creese
- Medical SchoolCollege of Medicine and HealthUniversity of ExeterExeterUK
| | - Ryan Arathimos
- King's College LondonSocial Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceLondonUK
| | - Helen Brooker
- Medical SchoolCollege of Medicine and HealthUniversity of ExeterExeterUK
| | - Dag Aarsland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
- Centre for Age‐Related MedicineStavanger University HospitalStavangerNorway
| | - Anne Corbett
- Medical SchoolCollege of Medicine and HealthUniversity of ExeterExeterUK
| | - Cathryn Lewis
- King's College LondonSocial Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceLondonUK
| | - Clive Ballard
- Medical SchoolCollege of Medicine and HealthUniversity of ExeterExeterUK
| | - Zahinoor Ismail
- Medical SchoolCollege of Medicine and HealthUniversity of ExeterExeterUK
- Departments of Psychiatry, Clinical Neurosciences, and Community Health SciencesHotchkiss Brain Institute and O'Brien Institute for PublicHealthUniversity of CalgaryCalgaryAlbertaCanada
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25
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Skoog I, Kern S, Najar J, Guerreiro R, Bras J, Waern M, Zetterberg H, Blennow K, Zettergren A. A Non-APOE Polygenic Risk Score for Alzheimer's Disease Is Associated With Cerebrospinal Fluid Neurofilament Light in a Representative Sample of Cognitively Unimpaired 70-Year Olds. J Gerontol A Biol Sci Med Sci 2021; 76:983-990. [PMID: 33512503 PMCID: PMC8140047 DOI: 10.1093/gerona/glab030] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Indexed: 01/01/2023] Open
Abstract
The effect of Alzheimer's disease (AD) polygenic risk scores (PRS) on amyloid and tau pathophysiology and neurodegeneration in cognitively unimpaired older adults is not known in detail. This study aims to investigate non-APOE AD-PRS and APOE ε4 in relation to AD pathophysiology evaluated by cerebrospinal fluid (CSF) biomarkers in a population-based sample of 70-year olds. A total of 303 dementia-free individuals from the Gothenburg H70 Birth Cohort Studies were included. Genotyping was performed using the NeuroChip, and AD-PRS were calculated. CSF levels of amyloid-β (Aβ42), total tau (t-tau), phosphorylated tau (p-tau), neurogranin (Ng), and neurofilament light (NfL) were measured with enzyme-linked immunosorbent assay. Associations were found between non-APOE PRS and both NfL (p = .001) and Aβ42 (p = .02), and between APOE ε4 and Aβ42 (p = 1e-10), t-tau (p = 5e-4), and p-tau (p = .002). Similar results were observed when only including individuals with CDR = 0, except for no evidence of an association between non-APOE PRS and Aβ42. There was an interaction between non-APOE PRS and Aβ42 pathology status in relation to NfL (p = .005); association was only present in individuals without Aβ42 pathology (p = 3e-4). In relation to Aβ42, there was a borderline interaction (p = .06) between non-APOE PRS and APOE ε4; association was present in ε4 carriers only (p = .03). Similar results were observed in individuals with CDR = 0 (n = 246). In conclusion, among cognitively healthy 70-year olds from the general population, genetic risk of AD beyond the APOE locus was associated with NfL in individuals without Aβ42 pathology, and with Aβ42 in APOE ε4 carriers, suggesting these associations are driven by different mechanisms.
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Affiliation(s)
- Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Sweden,Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Silke Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Sweden,Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Sweden,Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Rita Guerreiro
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, USA
| | - Jose Bras
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, USA
| | - Margda Waern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Sweden,Region Västra Götaland, Sahlgrenska University Hospital, Psychosis Clinic, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom,UK Dementia Research Institute at UCL, London, United Kingdom,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Anna Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Sweden,Address correspondence to: Anna Zettergren, PhD, Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP), University of Gothenburg, Wallinsgatan 6, 431 41 Mölndal, Sweden. E-mail:
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26
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Zhou X, Li YYT, Fu AKY, Ip NY. Polygenic Score Models for Alzheimer's Disease: From Research to Clinical Applications. Front Neurosci 2021; 15:650220. [PMID: 33854414 PMCID: PMC8039467 DOI: 10.3389/fnins.2021.650220] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 03/09/2021] [Indexed: 12/13/2022] Open
Abstract
The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.
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Affiliation(s)
- Xiaopu Zhou
- Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen, China
| | - Yolanda Y. T. Li
- Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Amy K. Y. Fu
- Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen, China
| | - Nancy Y. Ip
- Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen, China
- *Correspondence: Nancy Y. Ip,
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27
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Hannon E, Shireby GL, Brookes K, Attems J, Sims R, Cairns NJ, Love S, Thomas AJ, Morgan K, Francis PT, Mill J. Genetic risk for Alzheimer's disease influences neuropathology via multiple biological pathways. Brain Commun 2020; 2:fcaa167. [PMID: 33376986 PMCID: PMC7750986 DOI: 10.1093/braincomms/fcaa167] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 09/11/2020] [Accepted: 09/14/2020] [Indexed: 12/26/2022] Open
Abstract
Alzheimer’s disease is a highly heritable, common neurodegenerative disease characterized neuropathologically by the accumulation of β-amyloid plaques and tau-containing neurofibrillary tangles. In addition to the well-established risk associated with the APOE locus, there has been considerable success in identifying additional genetic variants associated with Alzheimer’s disease. Major challenges in understanding how genetic risk influences the development of Alzheimer’s disease are clinical and neuropathological heterogeneity, and the high level of accompanying comorbidities. We report a multimodal analysis integrating longitudinal clinical and cognitive assessment with neuropathological data collected as part of the Brains for Dementia Research study to understand how genetic risk factors for Alzheimer’s disease influence the development of neuropathology and clinical performance. Six hundred and ninety-three donors in the Brains for Dementia Research cohort with genetic data, semi-quantitative neuropathology measurements, cognitive assessments and established diagnostic criteria were included in this study. We tested the association of APOE genotype and Alzheimer’s disease polygenic risk score—a quantitative measure of genetic burden—with survival, four common neuropathological features in Alzheimer’s disease brains (neurofibrillary tangles, β-amyloid plaques, Lewy bodies and transactive response DNA-binding protein 43 proteinopathy), clinical status (clinical dementia rating) and cognitive performance (Mini-Mental State Exam, Montreal Cognitive Assessment). The APOE ε4 allele was significantly associated with younger age of death in the Brains for Dementia Research cohort. Our analyses of neuropathology highlighted two independent pathways from APOE ε4, one where β-amyloid accumulation co-occurs with the development of tauopathy, and a second characterized by direct effects on tauopathy independent of β-amyloidosis. Although we also detected association between APOE ε4 and dementia status and cognitive performance, these were all mediated by tauopathy, highlighting that they are a consequence of the neuropathological changes. Analyses of polygenic risk score identified associations with tauopathy and β-amyloidosis, which appeared to have both shared and unique contributions, suggesting that different genetic variants associated with Alzheimer’s disease affect different features of neuropathology to different degrees. Taken together, our results provide insight into how genetic risk for Alzheimer’s disease influences both the clinical and pathological features of dementia, increasing our understanding about the interplay between APOE genotype and other genetic risk factors.
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Affiliation(s)
- Eilis Hannon
- College of Medicine and Health, University of Exeter, Exeter, Devon, EX2 5DW, UK
| | - Gemma L Shireby
- College of Medicine and Health, University of Exeter, Exeter, Devon, EX2 5DW, UK
| | - Keeley Brookes
- School of Science & Technology, Nottingham Trent University, Nottingham, NG11 8NF, UK
| | - Johannes Attems
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK
| | - Rebecca Sims
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, CF24 4HQ, UK
| | - Nigel J Cairns
- College of Medicine and Health, University of Exeter, Exeter, Devon, EX2 5DW, UK
| | - Seth Love
- Bristol Medical School (THS), University of Bristol, Bristol, BS2 8DZ, UK
| | - Alan J Thomas
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK
| | - Kevin Morgan
- Human Genetics Group, School of Life Sciences, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Paul T Francis
- College of Medicine and Health, University of Exeter, Exeter, Devon, EX2 5DW, UK
| | - Jonathan Mill
- College of Medicine and Health, University of Exeter, Exeter, Devon, EX2 5DW, UK
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28
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Miao X, Liu W, Fan B, Lin H. Transcriptomic Heterogeneity of Alzheimer's Disease Associated with Lipid Genetic Risk. Neuromolecular Med 2020; 22:534-541. [PMID: 32862331 DOI: 10.1007/s12017-020-08610-6] [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: 09/06/2019] [Accepted: 08/21/2020] [Indexed: 10/23/2022]
Abstract
Alzheimer's disease (AD) is a multifactorial disease that affects more than 5 million Americans. Multiple pathways might be involved in the AD pathogenesis. The implication of lipid genetic susceptibility on brain gene expression is yet to be investigated. The current study included 192 brain samples from AD patients who were enrolled in the ROSMAP study. The samples were genotyped and imputed to the HRC Reference Panel. Lipid polygenetic risk score was constructed from the weighted sum of genetic variants associated with low-density lipoprotein cholesterol (LDL-C). The gene expression was profiled by RNA sequencing, and the association of gene expression with lipid polygenetic risk scores was tested by linear regression models adjusted for age, sex and APOE e4 alleles. Three genes were found to associate with lipid polygenetic risk scores, including HMCN2 (P = 3.6 × 10-7), PDLIM5 (P = 1.2 × 10-6), and FHL5 (P = 2.0 × 10-6). Network analysis revealed multiple related pathways, including dopaminergic synapse (P = 4.5 × 10-5), circadian entrainment (P = 1.1 × 10-4), and cholinergic synapse (P = 2.3 × 10-4). Our study underscores the importance of lipid regulation and metabolism to AD heterogeneity.
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Affiliation(s)
- Xiao Miao
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Innovation Research Institute of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Weifeng Liu
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Bin Fan
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, 72 East Concord Street, E-632, Boston, MA, 02118, USA.
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29
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De Marco M, Manca R, Kirby J, Hautbergue GM, Blackburn DJ, Wharton SB, Venneri A, Alzheimer's Disease Neuroimaging Initiative. The Association between Polygenic Hazard and Markers of Alzheimer's Disease Following Stratification for APOE Genotype. Curr Alzheimer Res 2020; 17:667-679. [PMID: 33023447 DOI: 10.2174/1567205017666201006161800] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 08/05/2020] [Accepted: 09/03/2020] [Indexed: 12/27/2022]
Abstract
BACKGROUND Research indicates that polygenic indices of risk of Alzheimer's disease are linked to clinical profiles. OBJECTIVE Given the "genetic centrality" of the APOE gene, we tested whether this held true for both APOE-ε4 carriers and non-carriers. METHODS A polygenic hazard score (PHS) was extracted from 784 non-demented participants recruited in the Alzheimer's Disease Neuroimaging Initiative and stratified by APOE ε4 status. Datasets were split into sub-cohorts defined by clinical (unimpaired/MCI) and amyloid status (Aβ+/Aβ-). Linear models were devised in each sub-cohort and for each APOE-ε4 status to test the association between PHS and memory, executive functioning and grey-matter volumetric maps. RESULTS PHS predicted memory and executive functioning in ε4ε3 MCI patients, memory in ε3ε3 MCI patients, and memory in ε4ε3 Aβ+ participants. PHS also predicted volume in sensorimotor regions in ε3ε3 Aβ+ participants. CONCLUSION The link between polygenic hazard and neurocognitive variables varies depending on APOE-ε4 allele status. This suggests that clinical phenotypes might be influenced by complex genetic interactions.
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Affiliation(s)
- Matteo De Marco
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, United Kingdom
| | - Riccardo Manca
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, United Kingdom
| | - Janine Kirby
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, United Kingdom
| | | | - Daniel J Blackburn
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, United Kingdom
| | - Stephen B Wharton
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, United Kingdom
| | - Annalena Venneri
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, United Kingdom
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30
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Badhwar A, McFall GP, Sapkota S, Black SE, Chertkow H, Duchesne S, Masellis M, Li L, Dixon RA, Bellec P. A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap. Brain 2020; 143:1315-1331. [PMID: 31891371 PMCID: PMC7241959 DOI: 10.1093/brain/awz384] [Citation(s) in RCA: 113] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2019] [Revised: 10/04/2019] [Accepted: 10/07/2019] [Indexed: 11/14/2022] Open
Abstract
Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput 'omics' are unbiased data-driven techniques that probe the complex aetiology of Alzheimer's disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer's disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer's disease.
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Affiliation(s)
- AmanPreet Badhwar
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Montreal, Canada
- Université de Montréal, Montreal, Canada
| | - G Peggy McFall
- Department of Psychology, University of Alberta, Edmonton, Canada
| | - Shraddha Sapkota
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Howard Chertkow
- Baycrest Health Sciences and the Rotman Research Institute, University of Toronto, Toronto, Canada
| | - Simon Duchesne
- Centre CERVO, Quebec City Mental Health Institute, Quebec, Quebec City, Canada
- Department of Radiology, Faculty of Medicine, Université Laval, Quebec City, Canada
| | - Mario Masellis
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Liang Li
- Department of Chemistry, University of Alberta, Edmonton, Canada
| | - Roger A Dixon
- Department of Psychology, University of Alberta, Edmonton, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Pierre Bellec
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Montreal, Canada
- Université de Montréal, Montreal, Canada
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31
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Harrison JR, Mistry S, Muskett N, Escott-Price V. From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review. J Alzheimers Dis 2020; 74:1271-1283. [PMID: 32250305 PMCID: PMC7242840 DOI: 10.3233/jad-191233] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/12/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD. OBJECTIVE This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration. METHODS We searched the literature from July 2008-July 2018 following PRISMA guidelines. RESULTS 57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes. CONCLUSION PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.
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Affiliation(s)
- Judith R. Harrison
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
| | - Sumit Mistry
- MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
| | - Natalie Muskett
- Cardiff University Medical School, University Hospital of Wales, Cardiff, UK
| | - Valentina Escott-Price
- Dementia Research Institute & the MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
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Gomez L, Odom GJ, Young JI, Martin ER, Liu L, Chen X, Griswold AJ, Gao Z, Zhang L, Wang L. coMethDMR: accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies with continuous phenotypes. Nucleic Acids Res 2019; 47:e98. [PMID: 31291459 PMCID: PMC6753499 DOI: 10.1093/nar/gkz590] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2019] [Revised: 06/09/2019] [Accepted: 07/08/2019] [Indexed: 12/12/2022] Open
Abstract
Recent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying differentially methylated regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the regions that contain consecutive highly significantly differentially methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic regions, and is available as an open-source R package.
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Affiliation(s)
- Lissette Gomez
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Gabriel J Odom
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Juan I Young
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA.,Dr. John T. Macdonald Foundation, Department of Human Genetics, University of Miami, Miami, FL 33136, USA
| | - Eden R Martin
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA.,Dr. John T. Macdonald Foundation, Department of Human Genetics, University of Miami, Miami, FL 33136, USA
| | - Lizhong Liu
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Xi Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA.,Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Anthony J Griswold
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA.,Dr. John T. Macdonald Foundation, Department of Human Genetics, University of Miami, Miami, FL 33136, USA
| | - Zhen Gao
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lanyu Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lily Wang
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA.,Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA.,Dr. John T. Macdonald Foundation, Department of Human Genetics, University of Miami, Miami, FL 33136, USA.,Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
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33
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Potential Fluid Biomarkers for the Diagnosis of Mild Cognitive Impairment. Int J Mol Sci 2019; 20:ijms20174149. [PMID: 31450692 PMCID: PMC6747411 DOI: 10.3390/ijms20174149] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 08/20/2019] [Accepted: 08/23/2019] [Indexed: 02/07/2023] Open
Abstract
Mild cognitive impairment (MCI) is characterized by a level of cognitive impairment that is lower than normal for a person’s age, but a higher function than that that observed in a demented person. MCI represents a transitional state between normal aging and dementia disorders, especially Alzheimer’s disease (AD). Much effort has been made towards determining the prognosis of a person with MCI who will convert to AD. It is now clear that cerebrospinal fluid (CSF) levels of Aβ40, Aβ42, total tau and phosphorylated tau are useful for predicting the risk of progression from MCI to AD. This review highlights the advantages of the current blood-based biomarkers in MCI, and discusses some of these challenges, with an emphasis on recent studies to provide an overview of the current state of MCI.
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Lourida I, Hannon E, Littlejohns TJ, Langa KM, Hyppönen E, Kuźma E, Llewellyn DJ. Association of Lifestyle and Genetic Risk With Incidence of Dementia. JAMA 2019; 322:430-437. [PMID: 31302669 PMCID: PMC6628594 DOI: 10.1001/jama.2019.9879] [Citation(s) in RCA: 530] [Impact Index Per Article: 88.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
IMPORTANCE Genetic factors increase risk of dementia, but the extent to which this can be offset by lifestyle factors is unknown. OBJECTIVE To investigate whether a healthy lifestyle is associated with lower risk of dementia regardless of genetic risk. DESIGN, SETTING, AND PARTICIPANTS A retrospective cohort study that included adults of European ancestry aged at least 60 years without cognitive impairment or dementia at baseline. Participants joined the UK Biobank study from 2006 to 2010 and were followed up until 2016 or 2017. EXPOSURES A polygenic risk score for dementia with low (lowest quintile), intermediate (quintiles 2 to 4), and high (highest quintile) risk categories and a weighted healthy lifestyle score, including no current smoking, regular physical activity, healthy diet, and moderate alcohol consumption, categorized into favorable, intermediate, and unfavorable lifestyles. MAIN OUTCOMES AND MEASURES Incident all-cause dementia, ascertained through hospital inpatient and death records. RESULTS A total of 196 383 individuals (mean [SD] age, 64.1 [2.9] years; 52.7% were women) were followed up for 1 545 433 person-years (median [interquartile range] follow-up, 8.0 [7.4-8.6] years). Overall, 68.1% of participants followed a favorable lifestyle, 23.6% followed an intermediate lifestyle, and 8.2% followed an unfavorable lifestyle. Twenty percent had high polygenic risk scores, 60% had intermediate risk scores, and 20% had low risk scores. Of the participants with high genetic risk, 1.23% (95% CI, 1.13%-1.35%) developed dementia compared with 0.63% (95% CI, 0.56%-0.71%) of the participants with low genetic risk (adjusted hazard ratio, 1.91 [95% CI, 1.64-2.23]). Of the participants with a high genetic risk and unfavorable lifestyle, 1.78% (95% CI, 1.38%-2.28%) developed dementia compared with 0.56% (95% CI, 0.48%-0.66%) of participants with low genetic risk and favorable lifestyle (hazard ratio, 2.83 [95% CI, 2.09-3.83]). There was no significant interaction between genetic risk and lifestyle factors (P = .99). Among participants with high genetic risk, 1.13% (95% CI, 1.01%-1.26%) of those with a favorable lifestyle developed dementia compared with 1.78% (95% CI, 1.38%-2.28%) with an unfavorable lifestyle (hazard ratio, 0.68 [95% CI, 0.51-0.90]). CONCLUSIONS AND RELEVANCE Among older adults without cognitive impairment or dementia, both an unfavorable lifestyle and high genetic risk were significantly associated with higher dementia risk. A favorable lifestyle was associated with a lower dementia risk among participants with high genetic risk.
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Affiliation(s)
- Ilianna Lourida
- University of Exeter Medical School, Exeter, United Kingdom
- NIHR CLAHRC South West Peninsula (PenCLAHRC), University of Exeter Medical School, Exeter, United Kingdom
| | - Eilis Hannon
- University of Exeter Medical School, Exeter, United Kingdom
| | - Thomas J. Littlejohns
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Kenneth M. Langa
- Institute for Healthcare Policy and Innovation, Division of General Medicine, Institute for Social Research, University of Michigan, Ann Arbor
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, Adelaide, South Australia, Australia
- Population, Policy and Practice, University College London, Great Ormond Street, Institute of Child Health, London, United Kingdom
| | - Elżbieta Kuźma
- University of Exeter Medical School, Exeter, United Kingdom
- Albertinen-Haus Centre for Geriatrics and Gerontology, Scientific Department at the University of Hamburg, Hamburg, Germany
- Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - David J. Llewellyn
- University of Exeter Medical School, Exeter, United Kingdom
- The Alan Turing Institute, London, United Kingdom
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Xu J, Li Q, Qin W, Jun Li M, Zhuo C, Liu H, Liu F, Wang J, Schumann G, Yu C. Neurobiological substrates underlying the effect of genomic risk for depression on the conversion of amnestic mild cognitive impairment. Brain 2019; 141:3457-3471. [PMID: 30445590 DOI: 10.1093/brain/awy277] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 09/12/2018] [Indexed: 12/28/2022] Open
Abstract
Depression increases the conversion risk from amnestic mild cognitive impairment to Alzheimer's disease with unknown mechanisms. We hypothesize that the cumulative genomic risk for major depressive disorder may be a candidate cause for the increased conversion risk. Here, we aimed to investigate the predictive effect of the polygenic risk scores of major depressive disorder-specific genetic variants (PRSsMDD) on the conversion from non-depressed amnestic mild cognitive impairment to Alzheimer's disease, and its underlying neurobiological mechanisms. The PRSsMDD could predict the conversion from amnestic mild cognitive impairment to Alzheimer's disease, and amnestic mild cognitive impairment patients with high risk scores showed 16.25% higher conversion rate than those with low risk. The PRSsMDD was correlated with the left hippocampal volume, which was found to mediate the predictive effect of the PRSsMDD on the conversion of amnestic mild cognitive impairment. The major depressive disorder-specific genetic variants were mapped into genes using different strategies, and then enrichment analyses and protein-protein interaction network analysis revealed that these genes were involved in developmental process and amyloid-beta binding. They showed temporal-specific expression in the hippocampus in middle and late foetal developmental periods. Cell type-specific expression analysis of these genes demonstrated significant over-representation in the pyramidal neurons and interneurons in the hippocampus. These cross-scale neurobiological analyses and functional annotations indicate that major depressive disorder-specific genetic variants may increase the conversion from amnestic mild cognitive impairment to Alzheimer's disease by modulating the early hippocampal development and amyloid-beta binding. The PRSsMDD could be used as a complementary measure to select patients with amnestic mild cognitive impairment with high conversion risk to Alzheimer's disease.
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Affiliation(s)
- Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P.R. China
| | - Qiaojun Li
- College of Information Engineering, Tianjin University of Commerce, Tianjin, P.R. China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P.R. China
| | - Mulin Jun Li
- Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Department of Pharmacology, Tianjin Medical University, Tianjin, P.R. China
| | - Chuanjun Zhuo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P.R. China.,Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, P.R. China
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P.R. China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P.R. China
| | - Junping Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P.R. China
| | - Gunter Schumann
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Medical Research Council Social, Genetic and Developmental Psychiatry Centre, London, UK
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P.R. China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, P.R. China
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36
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Leonenko G, Shoai M, Bellou E, Sims R, Williams J, Hardy J, Escott-Price V. Genetic risk for alzheimer disease is distinct from genetic risk for amyloid deposition. Ann Neurol 2019; 86:427-435. [PMID: 31199530 PMCID: PMC6771864 DOI: 10.1002/ana.25530] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 06/11/2019] [Accepted: 06/12/2019] [Indexed: 12/11/2022]
Abstract
Objective Alzheimer disease (AD) is the most common form of dementia and is responsible for a huge and growing health care burden in the developed and developing world. The polygenic risk score (PRS) approach has shown 75 to 84% prediction accuracy of identifying individuals with AD risk. Methods In this study, we tested the prediction accuracy of AD, mild cognitive impairment (MCI), and amyloid deposition risks with PRS, including and excluding APOE genotypes in a large publicly available dataset with extensive phenotypic data, the Alzheimer's Disease Neuroimaging Initiative cohort. Among MCI individuals with amyloid‐positive status, we examined PRS prediction accuracy in those who converted to AD. In addition, we divided polygenic risk score by biological pathways and tested them independently for distinguishing between AD, MCI, and amyloid deposition. Results We found that AD and MCI are predicted by both APOE genotype and PRS (area under the curve [AUC] = 0.82% and 68%, respectively). Amyloid deposition is predicted by APOE only (AUC = 79%). Further progression to AD of individuals with MCI and amyloid‐positive status is predicted by PRS over and above APOE (AUC = 67%). In pathway‐specific PRS analyses, the protein–lipid complex has the strongest association with AD and amyloid deposition even when genes in the APOE region were removed (p = 0.0055 and p = 0.0079, respectively). Interpretation The results showed different pattern of APOE contribution in PRS risk predictions of AD/MCI and amyloid deposition. Our study suggests that APOE mostly contributes to amyloid accumulation and the PRS affects risk of further conversion to AD. ANN NEUROL 2019;86:427–435
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Affiliation(s)
- Ganna Leonenko
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff
| | - Maryam Shoai
- Reta Lilla Research Laboratories, Department of Neurodegeneration and UK Dementia Research Institute, University College London Institute of Neurology, London
| | - Eftychia Bellou
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff
| | - Rebecca Sims
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff
| | - Julie Williams
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff.,UK Dementia Research Institute at Cardiff University, Cardiff
| | - John Hardy
- Reta Lilla Research Laboratories, Department of Neurodegeneration and UK Dementia Research Institute, University College London Institute of Neurology, London.,UK Dementia Research Institute at University College London, London, United Kingdom
| | - Valentina Escott-Price
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff.,UK Dementia Research Institute at Cardiff University, Cardiff
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Bouts MJRJ, van der Grond J, Vernooij MW, Koini M, Schouten TM, de Vos F, Feis RA, Cremers LGM, Lechner A, Schmidt R, de Rooij M, Niessen WJ, Ikram MA, Rombouts SARB. Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification. Hum Brain Mapp 2019; 40:2711-2722. [PMID: 30803110 PMCID: PMC6563478 DOI: 10.1002/hbm.24554] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 01/30/2019] [Accepted: 02/09/2019] [Indexed: 01/18/2023] Open
Abstract
Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)-based classification may aid early diagnosis of MCI, but has only been applied within clinical cohorts. We aimed to determine the generalizability of MRI-based classification probability scores to detect MCI on an individual basis within a general population. To determine classification probability scores, an AD, mild-AD, and moderate-AD detection model were created with anatomical and diffusion MRI measures calculated from a clinical Alzheimer's Disease (AD) cohort and subsequently applied to a population-based cohort with 48 MCI and 617 normal aging subjects. Each model's ability to detect MCI was quantified using area under the receiver operating characteristic curve (AUC) and compared with an MCI detection model trained and applied to the population-based cohort. The AD-model and mild-AD identified MCI from controls better than chance level (AUC = 0.600, p = 0.025; AUC = 0.619, p = 0.008). In contrast, the moderate-AD-model was not able to separate MCI from normal aging (AUC = 0.567, p = 0.147). The MCI-model was able to separate MCI from controls better than chance (p = 0.014) with mean AUC values comparable with the AD-model (AUC = 0.611, p = 1.0). Within our population-based cohort, classification models detected MCI better than chance. Nevertheless, classification performance rates were moderate and may be insufficient to facilitate robust MRI-based MCI detection on an individual basis. Our data indicate that multiparametric MRI-based classification algorithms, that are effective in clinical cohorts, may not straightforwardly translate to applications in a general population.
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Affiliation(s)
- Mark J. R. J. Bouts
- Institute of PsychologyLeiden UniversityLeidenthe Netherlands
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Leiden Institute for Brain and CognitionLeiden UniversityLeidenthe Netherlands
| | | | - Meike W. Vernooij
- Department of EpidemiologyErasmus MC University Medical CenterRotterdamthe Netherlands
- Department of Radiology and Nuclear MedicineErasmus MC University Medical CenterRotterdamthe Netherlands
| | - Marisa Koini
- Department of NeurologyMedical University of GrazAustria
| | - Tijn M. Schouten
- Institute of PsychologyLeiden UniversityLeidenthe Netherlands
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Leiden Institute for Brain and CognitionLeiden UniversityLeidenthe Netherlands
| | - Frank de Vos
- Institute of PsychologyLeiden UniversityLeidenthe Netherlands
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Leiden Institute for Brain and CognitionLeiden UniversityLeidenthe Netherlands
| | - Rogier A. Feis
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Leiden Institute for Brain and CognitionLeiden UniversityLeidenthe Netherlands
| | - Lotte G. M. Cremers
- Department of EpidemiologyErasmus MC University Medical CenterRotterdamthe Netherlands
- Department of Radiology and Nuclear MedicineErasmus MC University Medical CenterRotterdamthe Netherlands
| | - Anita Lechner
- Department of NeurologyMedical University of GrazAustria
| | | | - Mark de Rooij
- Institute of PsychologyLeiden UniversityLeidenthe Netherlands
- Leiden Institute for Brain and CognitionLeiden UniversityLeidenthe Netherlands
| | - Wiro J. Niessen
- Department of Radiology and Nuclear MedicineErasmus MC University Medical CenterRotterdamthe Netherlands
- Department of Medical InformaticsErasmus MC University Medical CenterRotterdamthe Netherlands
- Faculty of Applied SciencesDelft University of TechnologyDelftthe Netherlands
| | - M. Arfan Ikram
- Department of EpidemiologyErasmus MC University Medical CenterRotterdamthe Netherlands
- Department of Radiology and Nuclear MedicineErasmus MC University Medical CenterRotterdamthe Netherlands
- Department of NeurologyErasmus MC University Medical CenterRotterdamthe Netherlands
| | - Serge A. R. B. Rombouts
- Institute of PsychologyLeiden UniversityLeidenthe Netherlands
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Leiden Institute for Brain and CognitionLeiden UniversityLeidenthe Netherlands
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38
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Chaudhury S, Brookes KJ, Patel T, Fallows A, Guetta-Baranes T, Turton JC, Guerreiro R, Bras J, Hardy J, Francis PT, Croucher R, Holmes C, Morgan K, Thomas AJ. Alzheimer's disease polygenic risk score as a predictor of conversion from mild-cognitive impairment. Transl Psychiatry 2019; 9:154. [PMID: 31127079 PMCID: PMC6534556 DOI: 10.1038/s41398-019-0485-7] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 04/05/2019] [Accepted: 04/10/2019] [Indexed: 11/08/2022] Open
Abstract
Mild-cognitive impairment (MCI) occurs in up to one-fifth of individuals over the age of 65, with approximately a third of MCI individuals converting to dementia in later life. There is a growing necessity for early identification for those at risk of dementia as pathological processes begin decades before onset of symptoms. A cohort of 122 individuals diagnosed with MCI and followed up for a 36-month period for conversion to late-onset Alzheimer's disease (LOAD) were genotyped on the NeuroChip array along with pathologically confirmed cases of LOAD and cognitively normal controls. Polygenic risk scores (PRS) for each individual were generated using PRSice-2, derived from summary statistics produced from the International Genomics of Alzheimer's Disease Project (IGAP) genome-wide association study. Predictability models for LOAD were developed incorporating the PRS with APOE SNPs (rs7412 and rs429358), age and gender. This model was subsequently applied to the MCI cohort to determine whether it could be used to predict conversion from MCI to LOAD. The PRS model for LOAD using area under the precision-recall curve (AUPRC) calculated a predictability for LOAD of 82.5%. When applied to the MCI cohort predictability for conversion from MCI to LOAD was 61.0%. Increases in average PRS scores across diagnosis group were observed with one-way ANOVA suggesting significant differences in PRS between the groups (p < 0.0001). This analysis suggests that the PRS model for LOAD can be used to identify individuals with MCI at risk of conversion to LOAD.
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Affiliation(s)
| | | | - Tulsi Patel
- Human Genetics Group, University of Nottingham, Nottingham, UK
| | - Abigail Fallows
- Human Genetics Group, University of Nottingham, Nottingham, UK
| | | | - James C Turton
- Human Genetics Group, University of Nottingham, Nottingham, UK
| | - Rita Guerreiro
- UK Dementia Research Institute at University College London and ION Department of Neurodegenerative Disease, London, UK
| | - Jose Bras
- UK Dementia Research Institute at University College London and ION Department of Neurodegenerative Disease, London, UK
| | - John Hardy
- UK Dementia Research Institute at University College London and ION Department of Neurodegenerative Disease, London, UK
| | - Paul T Francis
- Brains for Dementia Research Resource, Wolfson CARD, King's College London, London, UK
| | | | - Clive Holmes
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - Kevin Morgan
- Human Genetics Group, University of Nottingham, Nottingham, UK
| | - A J Thomas
- Institute of Neuroscience Biomedical Research Building Campus for Ageing and Vitality Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
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Chasioti D, Yan J, Nho K, Saykin AJ. Progress in Polygenic Composite Scores in Alzheimer's and Other Complex Diseases. Trends Genet 2019; 35:371-382. [PMID: 30922659 PMCID: PMC6475476 DOI: 10.1016/j.tig.2019.02.005] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 02/12/2019] [Accepted: 02/22/2019] [Indexed: 11/25/2022]
Abstract
Advances in high-throughput genotyping and next-generation sequencing (NGS) coupled with larger sample sizes brings the realization of precision medicine closer than ever. Polygenic approaches incorporating the aggregate influence of multiple genetic variants can contribute to a better understanding of the genetic architecture of many complex diseases and facilitate patient stratification. This review addresses polygenic concepts, methodological developments, hypotheses, and key issues in study design. Polygenic risk scores (PRSs) have been applied to many complex diseases and here we focus on Alzheimer's disease (AD) as a primary exemplar. This review was designed to serve as a starting point for investigators wishing to use PRSs in their research and those interested in enhancing clinical study designs through enrichment strategies.
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Affiliation(s)
- Danai Chasioti
- Department of BioHealth Informatics, Indiana University-Purdue University, Indianapolis, IN 46202, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA; Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Jingwen Yan
- Department of BioHealth Informatics, Indiana University-Purdue University, Indianapolis, IN 46202, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA; Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Kwangsik Nho
- Department of BioHealth Informatics, Indiana University-Purdue University, Indianapolis, IN 46202, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA; Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Andrew J Saykin
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA; Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
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Vasconcellos LFR, Pereira JS, Charchat‐Fichman H, Greca D, Cruz M, Blum AL, Spitz M. Mild cognitive impairment in Parkinson's disease: Characterization and impact on quality of life according to subtype. Geriatr Gerontol Int 2019; 19:497-502. [DOI: 10.1111/ggi.13649] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 01/14/2019] [Accepted: 02/07/2019] [Indexed: 11/30/2022]
Affiliation(s)
- Luiz Felipe R Vasconcellos
- Movement Disorders Section, Neurology DepartmentPedro Ernesto University Hospital, State University of Rio de Janeiro Rio de Janeiro Brazil
| | - João S Pereira
- Movement Disorders Section, Neurology DepartmentPedro Ernesto University Hospital, State University of Rio de Janeiro Rio de Janeiro Brazil
| | | | - Denise Greca
- Psychology DepartmentPontifical Catholic University of Rio de Janeiro Rio de Janeiro Brazil
| | - Manuela Cruz
- Psychology DepartmentPontifical Catholic University of Rio de Janeiro Rio de Janeiro Brazil
| | - Ana Lara Blum
- Psychology DepartmentPontifical Catholic University of Rio de Janeiro Rio de Janeiro Brazil
| | - Mariana Spitz
- Movement Disorders Section, Neurology DepartmentPedro Ernesto University Hospital, State University of Rio de Janeiro Rio de Janeiro Brazil
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Logue MW, Panizzon MS, Elman JA, Gillespie NA, Hatton SN, Gustavson DE, Andreassen OA, Dale AM, Franz CE, Lyons MJ, Neale MC, Reynolds CA, Tu X, Kremen WS. Use of an Alzheimer's disease polygenic risk score to identify mild cognitive impairment in adults in their 50s. Mol Psychiatry 2019; 24:421-430. [PMID: 29487403 PMCID: PMC6110977 DOI: 10.1038/s41380-018-0030-8] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Revised: 11/02/2017] [Accepted: 11/21/2017] [Indexed: 01/30/2023]
Abstract
Early identification of younger, non-demented adults at elevated risk for Alzheimer's disease (AD) is crucial because the pathological process begins decades before dementia onset. Toward that end, we showed that an AD polygenic risk score (PRS) could identify mild cognitive impairment (MCI) in adults who were only in their 50s. Participants were 1176 white, non-Hispanic community-dwelling men of European ancestry in the Vietnam Era Twin Study of Aging (VETSA): 7% with amnestic MCI (aMCI); 4% with non-amnestic MCI (naMCI). Mean age was 56 years, with 89% <60 years old. Diagnosis was based on the Jak-Bondi actuarial/neuropsychological approach. We tested six P-value thresholds (0.05-0.50) for single nucleotide polymorphisms included in the ADPRS. After controlling for non-independence of twins and non-MCI factors that can affect cognition, higher PRSs were associated with significantly greater odds of having aMCI than being cognitively normal (odds ratios (ORs) = 1.36-1.43 for thresholds P < 0.20-0.50). The highest OR for the upper vs. lower quartile of the ADPRS distribution was 3.22. ORs remained significant after accounting for APOE-related SNPs from the ADPRS or directly genotyped APOE. Diabetes was associated with significantly increased odds of having naMCI (ORs = 3.10-3.41 for thresholds P < 0.05-0.50), consistent with naMCI having more vascular/inflammation components than aMCI. Analysis of sensitivity, specificity, and negative and positive predictive values supported some potential of ADPRSs for selecting participants in clinical trials aimed at early intervention. With participants 15+ years younger than most MCI samples, these findings are promising with regard to efforts to more effectively treat or slow AD progression.
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Affiliation(s)
- Mark W. Logue
- Research Service, VA Boston Healthcare System, Boston, MA, USA,Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Jeremy A. Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Sean N. Hatton
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Daniel E. Gustavson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine University of Oslo Oslo, Norway,Division of Mental Health and Addiction Oslo University Hospital Oslo, Norway
| | - Anders M. Dale
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA,Department of Radiology, University of California, San Diego, La Jolla, CA, USA,Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Carol E. Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Xin Tu
- Department of Family Medicine and Public Health, VA San Diego Healthcare System, La Jolla, CA, USA
| | - William S. Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA, USA
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Sapkota S, Dixon RA. A Network of Genetic Effects on Non-Demented Cognitive Aging: Alzheimer's Genetic Risk (CLU + CR1 + PICALM) Intensifies Cognitive Aging Genetic Risk (COMT + BDNF) Selectively for APOEɛ4 Carriers. J Alzheimers Dis 2019; 62:887-900. [PMID: 29480189 DOI: 10.3233/jad-170909] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Trajectories of complex neurocognitive phenotypes in preclinical aging may be produced differentially through selective and interactive combinations of genetic risk. OBJECTIVE We organize three possible combinations into a "network" of genetic risk indices derived from polymorphisms associated with normal and impaired cognitive aging, as well as Alzheimer's disease (AD). Specifically, we assemble and examine three genetic clusters relevant to non-demented cognitive trajectories: 1) Apolipoprotein E (APOE), 2) a Cognitive Aging Genetic Risk Score (CA-GRS; Catechol-O-methyltransferase + Brain-derived neurotrophic factor), and 3) an AD-Genetic Risk Score (AD-GRS; Clusterin + Complement receptor 1 + Phosphatidylinositol-binding clathrin assembly protein). METHOD We use an accelerated longitudinal design (n = 634; age range = 55-95 years) to test whether AD-GRS (low versus high) moderates the effect of increasing CA-GRS risk on executive function (EF) performance and change as stratified by APOE status (ɛ4+ versus ɛ4-). RESULTS APOEɛ4 carriers with high AD-GRS had poorer EF performance at the centering age (75 years) and steeper 9-year decline with increasing CA-GRS but this association was not present in APOEɛ4 carriers with low AD-GRS. CONCLUSIONS APOEɛ4 carriers with high AD-GRS are at elevated risk of cognitive decline when they also possess higher CA-GRS risk. Genetic risk from both common cognitive aging and AD-related indices may interact in intensification networks to differentially predict (1) level and trajectories of EF decline and (2) potential selective vulnerability for transitions into impairment and dementia.
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Affiliation(s)
- Shraddha Sapkota
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Roger A Dixon
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada.,Department of Psychology, University of Alberta, Edmonton, Canada
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Stephan Y, Sutin AR, Luchetti M, Caille P, Terracciano A. Polygenic Score for Alzheimer Disease and cognition: The mediating role of personality. J Psychiatr Res 2018; 107:110-113. [PMID: 30384091 PMCID: PMC6346269 DOI: 10.1016/j.jpsychires.2018.10.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 09/03/2018] [Accepted: 10/22/2018] [Indexed: 01/19/2023]
Abstract
Alzheimer's disease (AD) polygenic risk score (PGS) is associated with lower cognitive functioning even among older individuals without dementia. We tested the hypothesis that personality traits mediate the association between AD genetic risk and cognitive functioning. Participants (N > 7,000, aged 50-99 years old) from the Health and Retirement Study were genotyped and completed personality and cognition tests at baseline. Cognition was assessed again four years later. Bootstrap analysis revealed that a higher AD polygenic risk score was associated with lower cognitive scores at baseline through higher neuroticism, lower conscientiousness, and lower levels of the industriousness facet of conscientiousness. In addition, a higher polygenic score for AD was associated with decline in cognition over four years in part through higher neuroticism and lower conscientiousness. The findings support the hypothesis that the genetic vulnerability for AD contributes to cognitive functioning in part through its association with personality traits.
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Porter T, Burnham SC, Milicic L, Savage G, Maruff P, Lim YY, Li QX, Ames D, Masters CL, Rainey-Smith S, Rowe CC, Salvado O, Groth D, Verdile G, Villemagne VL, Laws SM. Utility of an Alzheimer’s Disease Risk-Weighted Polygenic Risk Score for Predicting Rates of Cognitive Decline in Preclinical Alzheimer’s Disease: A Prospective Longitudinal Study. J Alzheimers Dis 2018; 66:1193-1211. [DOI: 10.3233/jad-180713] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Tenielle Porter
- Collaborative Genomics Group, Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Co-operative Research Centre for Mental Health,
| | - Samantha C. Burnham
- eHealth, CSIRO Health and Biosecurity, Parkville, VIC, Australia
- Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Lidija Milicic
- Collaborative Genomics Group, Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Co-operative Research Centre for Mental Health,
| | - Greg Savage
- Department of Psychology, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, NSW, Australia
| | - Paul Maruff
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- CogState Ltd., Melbourne, VIC, Australia
| | - Yen Ying Lim
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Qiao-Xin Li
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - David Ames
- Academic Unit for Psychiatry of Old Age, St. Vincent’s Health, The University of Melbourne, Kew, VIC, Australia
- National Ageing Research Institute, Parkville, VIC, Australia
| | - Colin L. Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Stephanie Rainey-Smith
- Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Christopher C. Rowe
- Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Olivier Salvado
- Collaborative Genomics Group, Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - David Groth
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, Australia
| | - Giuseppe Verdile
- Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, Australia
| | - Victor L. Villemagne
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Simon M. Laws
- Collaborative Genomics Group, Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Co-operative Research Centre for Mental Health,
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, Australia
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Song YN, Wang P, Xu W, Li JQ, Cao XP, Yu JT, Tan L. Risk Factors of Rapid Cognitive Decline in Alzheimer’s Disease and Mild Cognitive Impairment: A Systematic Review and Meta-Analysis. J Alzheimers Dis 2018; 66:497-515. [PMID: 30320579 DOI: 10.3233/jad-180476] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Ya-Nan Song
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ping Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Wei Xu
- College of Medicine and Pharmaceutics, Ocean University of China, Qingdao, China
| | - Jie-Qiong Li
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xi-Peng Cao
- Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- College of Medicine and Pharmaceutics, Ocean University of China, Qingdao, China
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Strafella C, Caputo V, Galota MR, Zampatti S, Marella G, Mauriello S, Cascella R, Giardina E. Application of Precision Medicine in Neurodegenerative Diseases. Front Neurol 2018; 9:701. [PMID: 30190701 PMCID: PMC6115491 DOI: 10.3389/fneur.2018.00701] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 08/03/2018] [Indexed: 12/24/2022] Open
Abstract
One of the main challenges for healthcare systems is the increasing prevalence of neurodegenerative pathologies together with the rapidly aging populations. The enormous progresses made in the field of biomedical research and informatics have been crucial for improving the knowledge of how genes, epigenetic modifications, aging, nutrition, drugs and microbiome impact health and disease. In fact, the availability of high technology and computational facilities for large-scale analysis enabled a deeper investigation of neurodegenerative disorders, providing a more comprehensive overview of disease and encouraging the development of a precision medicine approach for these pathologies. On this subject, the creation of collaborative networks among medical centers, research institutes and highly qualified specialists can be decisive for moving the precision medicine from the bench to the bedside. To this purpose, the present review has been thought to discuss the main components which may be part of precise and personalized treatment programs applied to neurodegenerative disorders. Parkinson Disease will be taken as an example to understand how precision medicine approach can be clinically useful and provide substantial benefit to patients. In this perspective, the realization of web-based networks can be decisive for the implementation of precision medicine strategies across different specialized centers as well as for supporting clinical/therapeutical decisions and promoting a more preventive and participative medicine for neurodegenerative disorders. These collaborative networks are essentially addressed to find innovative, sustainable and effective strategies able to provide optimal and safer therapies, discriminate at risk individuals, identify patients at preclinical or early stage of disease, set-up individualized and preventative strategies for improving prognosis and patient's quality of life.
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Affiliation(s)
- Claudia Strafella
- Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.,Emotest Laboratory, Pozzuoli, Italy
| | - Valerio Caputo
- Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy
| | - Maria R Galota
- Molecular Genetics Laboratory UILDM, Santa Lucia Foundation, Rome, Italy
| | - Stefania Zampatti
- Molecular Genetics Laboratory UILDM, Santa Lucia Foundation, Rome, Italy
| | | | | | - Raffaella Cascella
- Molecular Genetics Laboratory UILDM, Santa Lucia Foundation, Rome, Italy.,Department of Chemical-Toxicological and Pharmacological Evaluation of Drugs, Catholic University Our Lady of Good Counsel, Tirana, Albania
| | - Emiliano Giardina
- Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.,Molecular Genetics Laboratory UILDM, Santa Lucia Foundation, Rome, Italy
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A new device-aided cognitive function test, User eXperience-Trail Making Test (UX-TMT), sensitively detects neuropsychological performance in patients with dementia and Parkinson's disease. BMC Psychiatry 2018; 18:220. [PMID: 29976167 PMCID: PMC6034323 DOI: 10.1186/s12888-018-1795-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Accepted: 06/18/2018] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND A newer generation neuropsychological tests can take advantage of touch screen and mobile technology. We have developed a new Android application termed "User eXperience-Trail Making Test (UX-TMT)" for neurocognitive assessment and training. This study investigated the utility, including the reliability and the validity, of the UX-TMT as a screening test for cognitive decline in adults. METHODS A total of 84 individuals aged 27-86 years were divided into three groups; healthy controls ([HC] n = 29), people with Parkinson's disease (PD; n = 28), and people with mild cognitive impairment (MCI) and dementia (MCI&D; n = 27). We examined the distributions of the scores and the time required, and the effects of age and group on these distributions. We analyzed internal consistency and convergent validity in all samples and applied receiver operator characteristic (ROC) analysis to determine a cutoff score that could differentiate the MCI & D group from the HC group. RESULTS 97.6% of the participants completed all of the tasks, and the average total test time required for UX-TMT was 428.8 (± 109.1) s in the HC, 542.0 (± 168.7) s in the PD, and 777.5 (± 256.1) s in the MCI&D groups, respectively. The MCI&D group showed significantly lower UX-TMT scores and longer total time in completing the task than the HC group. In an ROC analysis, a score of 21 showed high sensitivity (.83) and specificity (.92), and the UX-TMT score plus age improved sensitivity to .96. Additionally, the UX-TMT scores showed significant correlation with the Mini-Mental State Examination (Japanese version) scores (r = .77, p = .001), and Cronbach's alpha (.71-.83) indicated acceptable internal consistency. CONCLUSION The UX-TMT demonstrated high reliability and validity to detect cognitive decline in Japanese adults, highlighting its utility as a screening tool for epidemiological and clinical research.
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van der Lee SJ, Wolters FJ, Ikram MK, Hofman A, Ikram MA, Amin N, van Duijn CM. The effect of APOE and other common genetic variants on the onset of Alzheimer's disease and dementia: a community-based cohort study. Lancet Neurol 2018; 17:434-444. [DOI: 10.1016/s1474-4422(18)30053-x] [Citation(s) in RCA: 190] [Impact Index Per Article: 27.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 01/22/2018] [Accepted: 01/31/2018] [Indexed: 12/14/2022]
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Ahmad S, Bannister C, Lee SJ, Vojinovic D, Adams HH, Ramirez A, Escott‐Price V, Sims R, Baker E, Williams J, Holmans P, Vernooij MW, Ikram MA, Amin N, Duijn CM. Disentangling the biological pathways involved in early features of Alzheimer's disease in the Rotterdam Study. Alzheimers Dement 2018; 14:848-857. [DOI: 10.1016/j.jalz.2018.01.005] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Revised: 07/31/2017] [Accepted: 01/18/2018] [Indexed: 10/17/2022]
Affiliation(s)
- Shahzad Ahmad
- Department of EpidemiologyErasmus Medical CentreRotterdamThe Netherlands
| | - Christian Bannister
- MRC Centre for Neuropsychiatric Genetics & GenomicsInstitute of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUnited Kingdom
| | - Sven J. Lee
- Department of EpidemiologyErasmus Medical CentreRotterdamThe Netherlands
| | - Dina Vojinovic
- Department of EpidemiologyErasmus Medical CentreRotterdamThe Netherlands
| | - Hieab H.H. Adams
- Department of EpidemiologyErasmus Medical CentreRotterdamThe Netherlands
- Department of Radiology and Nuclear MedicineErasmus Medical CentreRotterdamThe Netherlands
| | - Alfredo Ramirez
- Department for Neurodegenerative Diseases and Geriatric PsychiatryUniversity Hospital BonnBonnGermany
- Department of Psychiatry and PsychotherapyUniversity Hospital CologneCologneGermany
- Institute of Human GeneticsUniversity of BonnBonnGermany
| | - Valentina Escott‐Price
- MRC Centre for Neuropsychiatric Genetics & GenomicsInstitute of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUnited Kingdom
| | - Rebecca Sims
- MRC Centre for Neuropsychiatric Genetics & GenomicsInstitute of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUnited Kingdom
| | - Emily Baker
- MRC Centre for Neuropsychiatric Genetics & GenomicsInstitute of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUnited Kingdom
| | - Julie Williams
- MRC Centre for Neuropsychiatric Genetics & GenomicsInstitute of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUnited Kingdom
| | - Peter Holmans
- MRC Centre for Neuropsychiatric Genetics & GenomicsInstitute of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUnited Kingdom
| | - Meike W. Vernooij
- Department of EpidemiologyErasmus Medical CentreRotterdamThe Netherlands
- Department of Radiology and Nuclear MedicineErasmus Medical CentreRotterdamThe Netherlands
| | - M. Arfan Ikram
- Department of EpidemiologyErasmus Medical CentreRotterdamThe Netherlands
- Department of Radiology and Nuclear MedicineErasmus Medical CentreRotterdamThe Netherlands
| | - Najaf Amin
- Department of EpidemiologyErasmus Medical CentreRotterdamThe Netherlands
| | - Cornelia M. Duijn
- Department of EpidemiologyErasmus Medical CentreRotterdamThe Netherlands
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