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Wu Y, Fang Y, Li Y, Au R, Cheng C, Li W, Xu F, Cui Y, Zhu L, Shen H. A network pharmacology approach and experimental validation to investigate the anticancer mechanism of Qi-Qin-Hu-Chang formula against colitis-associated colorectal cancer through induction of apoptosis via JNK/p38 MAPK signaling pathway. J Ethnopharmacol 2024; 319:117323. [PMID: 37852337 DOI: 10.1016/j.jep.2023.117323] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/20/2023] [Accepted: 10/13/2023] [Indexed: 10/20/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE The Qi-Qin-Hu-Chang Formula (QQHCF) is a traditional Chinese medicine prescription that is clinically used at the Affiliated Hospital of Nanjing University of Chinese Medicine for the treatment of colitis-associated colorectal cancer (CAC). AIM OF THE STUDY To evaluate the potential therapeutic effects of QQHCF on a CAC mouse model and investigate its underlying mechanisms using network pharmacology and experimental validation. MATERIALS AND METHODS The active components and potential targets of QQHCF were obtained from Traditional Chinese Medicine Systems Pharmacology (TCMSP) and herb-ingredient-targets gene network were constructed by Cytoscape 3.9.2. Target genes of CAC were obtained from GeneCards, Online Mendelian Inheritance in Man, and DrugBank database. The drug disease target protein-protein interaction (PPI) network was constructed and the core targets were visualized and identified using Cytoscape. The Metascape database was used for GO and KEGG enrichment analysis. UHPLC-MS/MS was used to further identify the active compounds in QQHCF. Subsequently, the therapeutic effects and potential mechanism of QQHCF against CAC were investigated in AOM/DSS-induced CAC mouse in vivo, and HT-29 and HCT116 cells in vitro. Finally, interactions between JNK, p38, and active ingredients were assessed by molecular docking. RESULTS A total of 176 active compounds, 273 potential therapeutic targets, and 2460 CAC-related target genes were obtained. The number of common targets between QQHCF and CAC were 165. KEGG pathway analysis indicated that the MAPK signaling pathway was closely associated with CAC, which may be the potential mechanism of QQHCF against CAC. Network pharmacology and UHPLC-MS/MS analyses showed that the active compounds of QQHCF included quercetin, kaempferol, luteolin, wogonin, oxymatrine, lupanine, and baicalin. Animal experiments demonstrated that QQHCF reduced tumor load, number, and size in AOM/DSS-treated mice, and induced apoptosis in colon tissue. In vitro experiments further showed that QQHCF induced apoptosis and inhibited cell viability, migration, and invasion in HCT116 and HT-29 cells. Notably, QQHCF activated the JNK/p38 MAPK signaling pathway both in vivo and in vitro. Molecular docking analysis revealed an ability for the main components of QQHCF and JNK/p38 to bind. CONCLUSION The present study demonstrated that QQHCF could ameliorate AOM/DSS-induced CAC in mice by activating the JNK/p38 MAPK signaling pathway. These results have important implications for the development of effective treatment strategies for CAC.
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Affiliation(s)
- Yuguang Wu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yulai Fang
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China
| | - Yanan Li
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Ryan Au
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China; Academy of Chinese Culture and Health Sciences, Oakland, CA, 94612, USA
| | - Cheng Cheng
- School of Health Preservation and Rehabilitation, Nanjing University of Chinese Medicine, China
| | - Weiyang Li
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Feng Xu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yuan Cui
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Lei Zhu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China.
| | - Hong Shen
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China.
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Thompson LI, Cummings M, Emrani S, Libon DJ, Ang A, Karjadi C, Au R, Liu C. Digital Clock Drawing as an Alzheimer's Disease Susceptibility Biomarker: Associations with Genetic Risk Score and APOE in Older Adults. J Prev Alzheimers Dis 2024; 11:79-87. [PMID: 38230720 PMCID: PMC10794851 DOI: 10.14283/jpad.2023.48] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is the leading cause of dementia in older adults, but most people are not diagnosed until significant neuronal loss has likely occurred along with a decline in cognition. Non-invasive and cost-effective digital biomarkers for AD have the potential to improve early detection. OBJECTIVE We examined the validity of DCTclockTM (a digitized clock drawing task) as an AD susceptibility biomarker. DESIGN We used two primary independent variables, Apolipoprotein E (APOE) ε4 allele carrier status and polygenic risk score (PRS). We examined APOE and PRS associations with DCTclockTM composite scores as dependent measures. SETTING We used existing data from the Framingham Heart Study (FHS), a community-based study with the largest dataset of digital clock drawing data to date. PARTICIPANTS The sample consisted of 2,398 older adults ages 60-94 with DCTclockTM data (mean age of 72.3, 55% female and 92% White). MEASUREMENTS PRS was calculated using 38 variants identified in a recent large genome-wide association study (GWAS) and meta-analysis of late-onset AD (LOAD). RESULTS Results showed that DCTclockTM performance decreased with advancing age, lower education, and the presence of one or more copies of APOE ε4. Lower DCTclockTM Total Score as well as lower composite scores for Information Processing Speed (both command and copy conditions) and Drawing Efficiency (command condition) were significantly associated with higher PRS levels and more copies of APOE ε4. APOE and PRS associations displayed similar effect sizes in both men and women. CONCLUSIONS Our results indicate that higher AD genetic risk is associated with poorer DCTclockTM performance in older adults without dementia. This is the first study to demonstrate significant differences in clock drawing performance on the basis of APOE status or PRS.
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Affiliation(s)
- L I Thompson
- Louisa Thompson, Department of Psychiatry, Alpert Medical School, Brown University, Providence, RI. Address: 345 Blackstone Blvd., Providence, RI 02906, USA. Phone: 401-455-6402. E-mail:
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Cui Y, Hu J, Li Y, Au R, Fang Y, Cheng C, Xu F, Li W, Wu Y, Zhu L, Shen H. Integrated Network Pharmacology, Molecular Docking and Animal Experiment to Explore the Efficacy and Potential Mechanism of Baiyu Decoction Against Ulcerative Colitis by Enema. Drug Des Devel Ther 2023; 17:3453-3472. [PMID: 38024534 PMCID: PMC10680469 DOI: 10.2147/dddt.s432268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 11/09/2023] [Indexed: 12/01/2023] Open
Abstract
Background Baiyu Decoction (BYD), a clinical prescription of traditional Chinese medicine, has been proven to be valuable for treating ulcerative colitis (UC) by enema. However, the mechanism of BYD against UC remains unclear. Purpose A combination of bioinformatics methods including network pharmacology and molecular docking and animal experiments were utilized to investigate the potential mechanism of BYD in the treatment of UC. Materials and Methods Firstly, the representative compounds of each herb in BYD were detected by liquid chromatography-mass spectrometry. Subsequently, we predicted the core targets and potential pathways of BYD for treating UC through network pharmacology. And rat colitis model was established with dextran sodium sulfate. UC rats were subjected to BYD enema administration, during which we recorded body weight changes, disease activity index, and colon length to assess the effectiveness of BYD. Besides, quantitative real-time PCR, western blotting, ELISA and immunofluorescence were used to detect intestinal inflammatory factors, intestinal barrier biomarkers and TOLL-like receptor pathway in rats. Finally, the core components and targets of BYD were subjected to molecular docking so as to further validate the results of network pharmacology. Results A total of 41 active compositions and 203 targets related to BYD-UC were subjected to screening. The results of bioinformatics analysis showed that quercetin and kaempferol may be the main compounds. Additionally, AKT1, IL-6, TP53, TNF and IL-1β were regarded as potential therapeutic targets. KEGG results explained that TOLL-like receptor pathway might play a pivotal role in BYD protecting against UC. In addition, animal experiments and molecular docking validated the network pharmacology results. BYD enema treatment can reduce body weight loss, lower disease activity index score, reverse colon shortening, relieve intestinal inflammation, protect intestinal barrier, and inhibit TOLL-like receptor pathway in UC rats. Besides, molecular docking suggested that quercetin and kaempferol docked well with TLR4, AKT1, IL-6, TP53. Conclusion Utilizing network pharmacology, animal studies, and molecular docking, enema therapy with BYD was confirmed to have anti-UC efficacy by alleviating intestinal inflammation, protecting the intestinal barrier, and inhibiting the TOLL-like receptor pathway. Researchers should focus not only on oral medications but also on the rectal administration of medications in furtherance of the cure of ulcerative colitis.
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Affiliation(s)
- Yuan Cui
- Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Jingyi Hu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Yanan Li
- Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Ryan Au
- Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Yulai Fang
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Cheng Cheng
- Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Feng Xu
- Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Weiyang Li
- Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Yuguang Wu
- Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Lei Zhu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
| | - Hong Shen
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
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Ding H, Li Y, Ang T, Liu Y, Devine S, Au R, Doraiswamy P, Liu C. Reproductive Markers in Alzheimer’s Disease Progression: The Framingham Heart Study. J Prev Alzheimers Dis 2023. [DOI: 10.14283/jpad.2023.28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
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Cheng C, Hu J, Li Y, Ji Y, Lian Z, Au R, Xu F, Li W, Shen H, Zhu L. Qing-Chang-Hua-Shi granule ameliorates DSS-induced colitis by activating NLRP6 signaling and regulating Th17/Treg balance. Phytomedicine 2022; 107:154452. [PMID: 36150347 DOI: 10.1016/j.phymed.2022.154452] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/02/2022] [Accepted: 09/09/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Chinese herbal medicine Qing-Chang-Hua-Shi granule (QCHS) is widely used to treat ulcerative colitis in China. However, the molecular mechanisms of QCHS remains largely unknown. PURPOSE To assess the therapeutic effects of QCHS on colitis and to reveal its mechanisms of action. METHODS The main components of QCHS were identified using a UHPLC-QTOF-MS method and the efficacy of QCHS was evaluated using an DSS-induced mice model. The inflammatory responses and mucosal integrity in colon were comprehensively assessed. Flow cytometry was used to analysis the proportion of Th17 and Treg cells. Detect the signal transduction of the NOD-like receptor family pyrin domain containing 6 (NLRP6) both in vitro and in vivo. Furthermore, siNLRP6 transfection was used to validate the functional targets of QCHS. RESULTS QCHS treatment significantly alleviated colitis in mice by improving symptoms and pathological damage. Moreover, QCHS treatment suppressed the inflammatory response and preserved the integrity of colon tissue. Most importantly, QCHS balanced the Th17/Treg response of UC mice. Mechanistically, by activating NLRP6 inflammasome pathway, QCHS regulated the maturation of interleukin (IL)-1β and IL-18 to affect inflammation and drive Th17 cell differentiation. CONCLUSIONS The effect of QCHS on UC mice is dose-dependent, with high-dose QCHS being superior to 5-Aminosalicylic acid (200 mg/kg/day). QCHS acts through the NLRP6 signaling pathway to modulate Th17/Treg balance, resulting in the protective effects against colitis. This study investigated the relevant pharmacological mechanisms of QCHS, providing further evidence for the application of QCHS in UC treatment.
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Affiliation(s)
- Cheng Cheng
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Jingyi Hu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China
| | - Yanan Li
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Yuejin Ji
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Ziyu Lian
- Heping Hospital Affiliated to Changzhi Medical College, Changzhi 046000, China
| | - Ryan Au
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China; Academy of Chinese Culture and Health Sciences, Oakland, CA, 94612, USA
| | - Feng Xu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Weiyang Li
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Hong Shen
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China.
| | - Lei Zhu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China.
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Hu J, Tong Y, Shen Z, Li Y, Cheng C, Au R, Xu F, Liu Y, Zhu L, Shen H. Gegen Qinlian decoction ameliorates murine colitis by inhibiting the expansion of Enterobacteriaceae through activating PPAR-γ signaling. Biomed Pharmacother 2022; 154:113571. [PMID: 36007273 DOI: 10.1016/j.biopha.2022.113571] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/12/2022] [Accepted: 08/15/2022] [Indexed: 11/29/2022] Open
Abstract
Ulcerative colitis (UC) is a chronic and relapsing inflammatory disease of the intestine. Dysbiosis, especially the expansion of facultative anaerobic Enterobacteriaceae, maybe the main pathogenesis of UC. Gegen Qinlian decoction (GD), a traditional Chinese medicinal formula chronicled in the Shang Han Lun, is commonly used to treat UC and has shown an excellent effect on inducing disease remission. However, the role of GD in regulating gut microbiota has not been fully clarified. Herein, we investigated the potential effect of GD on inhibiting the expansion of Enterobacteriaceae and further explored the potential mechanism of this action. Our study demonstrated that GD remarkably reduced body weight loss of colitis mice, shortening of colon length, and inflammation of the colon. Peroxisome proliferator-activated receptor-γ (PPAR-γ) signaling was inactivated in colitis colon tissue, and the abundance of Escherichia coli (E. coli, family of Enterobacteriaceae) in colonic contents and the concentration of lipopolysaccharide (LPS) in colonic tissue were significantly upregulated after DSS-treatment. Notably, GD administration can result in the activation of PPAR-γ and inactivation of iNOS, which lead to the reduction of nitrate, the inhibition of E. coli, and less production of LPS. Combined GD with PPAR-γ antagonist, the effect of GD on the treatment of UC was weakened, and effectless in inhibiting the expansion of Enterobacteriaceae. Therefore, GD ameliorates UC by preventing a dysbiotic expansion of potentially pathogenic E. coli by reducing nitrate levels in the lumen through activating PPAR-γ signaling.
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Affiliation(s)
- Jingyi Hu
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Yiheng Tong
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Zhaofeng Shen
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Yanan Li
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Cheng Cheng
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Ryan Au
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Feng Xu
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Yajun Liu
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Lei Zhu
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China
| | - Hong Shen
- Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, China.
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Makimoto K, Au R, Moslemi A, Hogg JC, Bourbeau J, Tan WC, Kirby M. Comparison of Feature Selection Methods and Machine Learning Classifiers for Predicting Chronic Obstructive Pulmonary Disease Using Texture-Based CT Lung Radiomic Features. Acad Radiol 2022; 30:900-910. [PMID: 35965158 DOI: 10.1016/j.acra.2022.07.016] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/15/2022] [Accepted: 07/17/2022] [Indexed: 02/07/2023]
Abstract
RATIONALE Texture-based radiomics analysis of lung computed tomography (CT) images has been shown to predict chronic obstructive pulmonary disease (COPD) status using machine learning models. However, various approaches are used and it is unclear which provides the best performance. OBJECTIVES To compare the most commonly used feature selection and classification methods and determine the optimal models for classifying COPD status in a mild, population-based COPD cohort. MATERIALS AND METHODS CT images from the multi-center Canadian Cohort Obstructive Lung Disease (CanCOLD) study were pre-processed by resampling the image to a 1mm isotropic voxel volume, segmenting the lung and removing the airways (VIDA Diagnostics Inc.), and applying a threshold of -1000HU-to-0HU. A total of 95 texture features were then extracted from each CT image. Combinations of 17 feature selection methods and 9 classifiers were tested and evaluated. In addition, the role of data cleaning (outlier removal and highly correlated feature removal) was evaluated. The area under the curve (AUC) from the receiver operating characteristic curve was used to evaluate model performance. RESULTS A total of 1204 participants were evaluated (n = 602 no COPD, n = 602 COPD). There were no significant differences between the groups for female sex (no COPD = 46.3%; COPD = 38.5%; p = 0.77), or body mass index (no COPD = 27.7 kg/m2; COPD = 27.4 kg/m2; p = 0.21). The highest AUC value for predicting COPD status (AUC = 0.78 [0.73, 0.84]) was obtained following data cleaning and feature selection using Elastic Net with the Linear-SVM classifier. CONCLUSION In a population-based cohort, the optimal combination for radiomics-based prediction of COPD status was Elastic Net as the feature selection method and Linear-SVM as the classifier.
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Affiliation(s)
- Kalysta Makimoto
- Toronto Metropolitan University, Kerr Hall South Bldg. Room - KHS-344, 350 Victoria St., Toronto, M5B 2K3, Ontario, Canada
| | - Ryan Au
- Western University, London, Ontario, Canada
| | - Amir Moslemi
- Toronto Metropolitan University, Kerr Hall South Bldg. Room - KHS-344, 350 Victoria St., Toronto, M5B 2K3, Ontario, Canada
| | - James C Hogg
- Center for Heart, Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jean Bourbeau
- Montreal Chest Institute of the Royal Victoria Hospital, McGill University Health Centre, Montreal, Québec, Canada; Respiratory Epidemiology and Clinical Research Unit, Research Institute of McGill University Health Centre, Montreal, Québec, Canada
| | - Wan C Tan
- Center for Heart, Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - Miranda Kirby
- Toronto Metropolitan University, Kerr Hall South Bldg. Room - KHS-344, 350 Victoria St., Toronto, M5B 2K3, Ontario, Canada.
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Tavabi N, Stück D, Signorini A, Karjadi C, Al Hanai T, Sandoval M, Lemke C, Glass J, Hardy S, Lavallee M, Wasserman B, Ang TFA, Nowak CM, Kainkaryam R, Foschini L, Au R. Cognitive Digital Biomarkers from Automated Transcription of Spoken Language. J Prev Alzheimers Dis 2022; 9:791-800. [PMID: 36281684 DOI: 10.14283/jpad.2022.66] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
BACKGROUND Although patients with Alzheimer's disease and other cognitive-related neurodegenerative disorders may benefit from early detection, development of a reliable diagnostic test has remained elusive. The penetration of digital voice-recording technologies and multiple cognitive processes deployed when constructing spoken responses might offer an opportunity to predict cognitive status. OBJECTIVE To determine whether cognitive status might be predicted from voice recordings of neuropsychological testing. DESIGN Comparison of acoustic and (para)linguistic variables from low-quality automated transcriptions of neuropsychological testing (n = 200) versus variables from high-quality manual transcriptions (n = 127). We trained a logistic regression classifier to predict cognitive status, which was tested against actual diagnoses. SETTING Observational cohort study. PARTICIPANTS 146 participants in the Framingham Heart Study. MEASUREMENTS Acoustic and either paralinguistic variables (e.g., speaking time) from automated transcriptions or linguistic variables (e.g., phrase complexity) from manual transcriptions. RESULTS Models based on demographic features alone were not robust (area under the receiver-operator characteristic curve [AUROC] 0.60). Addition of clinical and standard acoustic features boosted the AUROC to 0.81. Additional inclusion of transcription-related features yielded an AUROC of 0.90. CONCLUSIONS The use of voice-based digital biomarkers derived from automated processing methods, combined with standard patient screening, might constitute a scalable way to enable early detection of dementia.
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Affiliation(s)
- N Tavabi
- Rhoda Au, 72 E. Concord Street, Boston University School of Medicine, Boston, MA 02118. Telephone: (617) 358-0089;
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Kaye J, Aisen P, Amariglio R, Au R, Ballard C, Carrillo M, Fillit H, Iwatsubo T, Jimenez-Maggiora G, Lovestone S, Natanegara F, Papp K, Soto ME, Weiner M, Vellas B. Using Digital Tools to Advance Alzheimer's Drug Trials During a Pandemic: The EU/US CTAD Task Force. J Prev Alzheimers Dis 2021; 8:513-519. [PMID: 34585227 PMCID: PMC8244451 DOI: 10.14283/jpad.2021.36] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The 2020 COVID-19 pandemic has disrupted Alzheimer’s disease (AD) clinical studies worldwide. Digital technologies may help minimize disruptions by enabling remote assessment of subtle cognitive and functional changes over the course of the disease. The EU/US Clinical Trials in Alzheimer’s Disease (CTAD) Task Force met virtually in November 2020 to explore the opportunities and challenges associated with the use of digital technologies in AD clinical research. While recognizing the potential of digital tools to accelerate clinical trials, improve the engagement of diverse populations, capture clinically meaningful data, and lower costs, questions remain regarding the stability, validity, generalizability, and reproducibility of digital data. Substantial concerns also exist regarding regulatory acceptance and privacy. Nonetheless, the Task Force supported further exploration of digital technologies through collaboration and data sharing, noting the need for standardization of digital readouts. They also concluded that while it may be premature to employ remote assessments for trials of novel experimental medications, remote studies of non-invasive, multi-domain approaches may be feasible at this time.
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Affiliation(s)
- J Kaye
- Jeffrey Kaye, Layton Aging and Alzheimer's Disease Center, School of Medicine, Oregon Health and Science University, Portland, OR, USA,
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Ekwe A, Au R, McEnroe B, Tan M, Saldan A, Henden A, Zhang P, Hutchins C, Henderson A, Mudie K, Western R, Fuery M, Kennedy G, Hill G, Tey S. Clinical scale facs-sorting and expansion of regulatory t cells (TREGS) for phase i clinical trial. Cytotherapy 2021. [DOI: 10.1016/s1465324921006150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Ritchie MM, Au R, Alosco ML, Mez J, Kohli M, Lin H, Pfeifer N, Comeau D. BRAIN HEALTH MONITORING PLATFORM: THE CLINICAL APPLICATIONS OF DIGITAL TECHNOLOGY IN NEUROLOGICAL DISORDERS. Innov Aging 2018. [DOI: 10.1093/geroni/igy023.270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- M M Ritchie
- Boston University, Boston, Massachusetts, United States
| | - R Au
- Department of Anatomy & Neurobiology, Neurology, & Epidemiology, Boston University Schools of Medicine & Public Health, Boston, MA, USA
| | - M L Alosco
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - J Mez
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - M Kohli
- Framingham Heart Study, Framingham, MA, USA
| | - H Lin
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - N Pfeifer
- Ryan Center for Sports Medicine, Boston University, Boston, MA, USA
| | - D Comeau
- Ryan Center for Sports Medicine, Boston University, Boston, MA, USA
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Sweigart B, Andersen SL, Wasserman B, Cosentino S, Wojczynski MK, Au R, Sebastiani P, Perls TT. DIGITAL COGNITIVE METRICS OF WRITTEN RESPONSES IN THE LONG LIFE FAMILY STUDY. Innov Aging 2018. [DOI: 10.1093/geroni/igy023.269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- B Sweigart
- Boston University, Boston, Massachusetts, United States
| | - S L Andersen
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - B Wasserman
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA
| | - S Cosentino
- Department of Neurology, Columbia University, New York, NY, USA
| | - M K Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - R Au
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA; Department of Anatomy & Neurobiology, Neurology, & Epidemiology, Boston University Schools of Medicine & Public Health, Boston, MA, USA
| | - P Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - T T Perls
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
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13
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Andersen SL, Wojczynski MK, Glynn NW, Thyagarajan B, Mengel-From J, Au R, Perls TT, Cosentino S. IMPLEMENTATION OF DIGITAL DATA COLLECTION FOR COGNITIVE PERFORMANCE IN THE LONG LIFE FAMILY STUDY. Innov Aging 2018. [DOI: 10.1093/geroni/igy023.268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- S L Andersen
- Section of Geriatrics, Department of Medicine, Boston University, Boston, MA, USA, Boston, Massachusetts, United States
| | - M K Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - N W Glynn
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - B Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - J Mengel-From
- Institute of Public Health, Epidemiology Unit, University of Southern Denmark, Odense, Denmark
| | - R Au
- Department of Anatomy & Neurobiology, Neurology, & Epidemiology, Boston University Schools of Medicine & Public Health, Boston, MA, USA
| | - T T Perls
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - S Cosentino
- Department of Neurology, Columbia University, New York, NY, USA
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Kim H, Thomas RJ, Kim S, Yun C, Au R, Lee S, Shin C. 0287 HABITUAL SLEEP DURATION, DEPRESSION SYMPTOMS, AND NEUROPSYCHOLOGICAL PERFORMANCE IN MIDDLE-AGED AND OLDER ADULTS: FINDINGS FROM A KOREAN COMMUNITY SAMPLE. Sleep 2017. [DOI: 10.1093/sleepj/zsx050.286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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15
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Salazar R, Heckman E, Liu Y, Au R, O’Connor G, Thomas R. 0770 THE FORD INSOMNIA RESPONSE TO STRESS TEST IN THE FRAMINGHAM HEART STUDY. Sleep 2017. [DOI: 10.1093/sleepj/zsx050.769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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16
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Heckman EJ, Salazar R, Hardy S, Manders E, Liu Y, Au R, O’Connor G, Thomas R. 0780 WEARABLE SLEEP EPIDEMIOLOGY IN THE FRAMINGHAM HEART STUDY. Sleep 2017. [DOI: 10.1093/sleepj/zsx050.779] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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17
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Ibrahim-Verbaas CA, Bressler J, Debette S, Schuur M, Smith AV, Bis JC, Davies G, Trompet S, Smith JA, Wolf C, Chibnik LB, Liu Y, Vitart V, Kirin M, Petrovic K, Polasek O, Zgaga L, Fawns-Ritchie C, Hoffmann P, Karjalainen J, Lahti J, Llewellyn DJ, Schmidt CO, Mather KA, Chouraki V, Sun Q, Resnick SM, Rose LM, Oldmeadow C, Stewart M, Smith BH, Gudnason V, Yang Q, Mirza SS, Jukema JW, deJager PL, Harris TB, Liewald DC, Amin N, Coker LH, Stegle O, Lopez OL, Schmidt R, Teumer A, Ford I, Karbalai N, Becker JT, Jonsdottir MK, Au R, Fehrmann RSN, Herms S, Nalls M, Zhao W, Turner ST, Yaffe K, Lohman K, van Swieten JC, Kardia SLR, Knopman DS, Meeks WM, Heiss G, Holliday EG, Schofield PW, Tanaka T, Stott DJ, Wang J, Ridker P, Gow AJ, Pattie A, Starr JM, Hocking LJ, Armstrong NJ, McLachlan S, Shulman JM, Pilling LC, Eiriksdottir G, Scott RJ, Kochan NA, Palotie A, Hsieh YC, Eriksson JG, Penman A, Gottesman RF, Oostra BA, Yu L, DeStefano AL, Beiser A, Garcia M, Rotter JI, Nöthen MM, Hofman A, Slagboom PE, Westendorp RGJ, Buckley BM, Wolf PA, Uitterlinden AG, Psaty BM, Grabe HJ, Bandinelli S, Chasman DI, Grodstein F, Räikkönen K, Lambert JC, Porteous DJ, Price JF, Sachdev PS, Ferrucci L, Attia JR, Rudan I, Hayward C, Wright AF, Wilson JF, Cichon S, Franke L, Schmidt H, Ding J, de Craen AJM, Fornage M, Bennett DA, Deary IJ, Ikram MA, Launer LJ, Fitzpatrick AL, Seshadri S, van Duijn CM, Mosley TH. GWAS for executive function and processing speed suggests involvement of the CADM2 gene. Mol Psychiatry 2016; 21:189-197. [PMID: 25869804 PMCID: PMC4722802 DOI: 10.1038/mp.2015.37] [Citation(s) in RCA: 103] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Revised: 01/21/2015] [Accepted: 02/11/2015] [Indexed: 01/20/2023]
Abstract
To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32,070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.
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Affiliation(s)
- CA Ibrahim-Verbaas
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - J Bressler
- Human Genetics Center, School of Public Health, University of
Texas Health Science Center at Houston, Houston, TX, USA,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - S Debette
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,Institut National de la Santé et de la Recherche
Médicale (INSERM), U897, Epidemiology and Biostatistics, University of Bordeaux,
Bordeaux, France,Department of Neurology, Bordeaux University Hospital, Bordeaux,
France,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - M Schuur
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - AV Smith
- Icelandic Heart Association, Kopavogur, Iceland,Faculty of Medicine, University of Iceland, Reykjavik,
Iceland,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - JC Bis
- Cardiovascular Health Research Unit, Department of Medicine,
University of Washington, Seattle, WA, USA,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - S Trompet
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands,Department of Gerontology and Geriatrics, Leiden University
Medical Center, Leiden, The Netherlands
| | - JA Smith
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - C Wolf
- RG Statistical Genetics, Max Planck Institute of Psychiatry,
Munich, Germany
| | - LB Chibnik
- Program in Translational Neuropsychiatric Genomics, Department
of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Y Liu
- Department of Epidemiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
| | - V Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - M Kirin
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - K Petrovic
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - O Polasek
- Department of Public Health, University of Split, Split,
Croatia
| | - L Zgaga
- Department of Public Health and Primary Care, Trinity College
Dublin, Dublin, Ireland
| | - C Fawns-Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
| | - P Hoffmann
- Institute of Neuroscience and Medicine (INM -1), Research
Center Juelich, Juelich, Germany,Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - J Karjalainen
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki,
Helsinki, Finland,Folkhälsan Research Centre, Helsinki, Finland
| | - DJ Llewellyn
- Institute of Biomedical and Clinical Sciences, University of
Exeter Medical School, Exeter, UK
| | - CO Schmidt
- Institute for Community Medicine, University Medicine
Greifswald, Greifswald, Germany
| | - KA Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia
| | - V Chouraki
- Inserm, U1167, Institut Pasteur de Lille, Université
Lille-Nord de France, Lille, France
| | - Q Sun
- Channing Division of Network Medicine, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - SM Resnick
- Laboratory of Behavioral Neuroscience, National Institute on
Aging, NIH, Baltimore, MD, USA
| | - LM Rose
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - C Oldmeadow
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - M Stewart
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - BH Smith
- Medical Research Institute, University of Dundee, Dundee,
UK
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland,Faculty of Medicine, University of Iceland, Reykjavik,
Iceland
| | - Q Yang
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - SS Mirza
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - JW Jukema
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands
| | - PL deJager
- Program in Translational Neuropsychiatric Genomics, Department
of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - TB Harris
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - DC Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - N Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
| | - LH Coker
- Division of Public Health Sciences and Neurology, Wake Forest
School of Medicine, Winston-Salem, NC, USA
| | - O Stegle
- Max Planck Institute for Developmental Biology, Max Planck
Institute for Intelligent Systems, Tübingen, Germany
| | - OL Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh,
PA, USA
| | - R Schmidt
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - A Teumer
- Interfaculty Institute for Genetics and Functional Genomics,
University Medicine Greifswald, Greifswald, Germany
| | - I Ford
- Robertson Center for biostatistics, University of Glasgow,
Glasgow, UK
| | - N Karbalai
- RG Statistical Genetics, Max Planck Institute of Psychiatry,
Munich, Germany
| | - JT Becker
- Department of Neurology, University of Pittsburgh, Pittsburgh,
PA, USA,Department of Psychiatry, University of Pittsburgh, Pittsburgh,
PA, USA,Department of Psychology, University of Pittsburgh, Pittsburgh,
PA, USA
| | | | - R Au
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - RSN Fehrmann
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - S Herms
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - M Nalls
- Laboratory of Neurogenetics, National Institute on Aging,
Bethesda, MD, USA
| | - W Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - ST Turner
- Division of Nephrology and Hypertension, Department of Internal
Medicine, Mayo Clinic, Rochester, MN, USA
| | - K Yaffe
- Departments of Psychiatry, Neurology and Epidemiology,
University of California, San Francisco and San Francisco VA Medical Center, San Francisco,
CA, USA
| | - K Lohman
- Department of Epidemiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
| | - JC van Swieten
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands
| | - SLR Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - DS Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - WM Meeks
- Department of Medicine, Division of Geriatrics, University of
Mississippi Medical Center, Jackson, MS, USA
| | - G Heiss
- Department of Epidemiology, Gillings School of Global Public
Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - EG Holliday
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - PW Schofield
- School of Medicine and Public Health, Faculty of Health,
University of Newcastle, Newcastle, SW, Australia
| | - T Tanaka
- Translational Gerontology Branch, National Institute on Aging,
Baltimore, MD, USA
| | - DJ Stott
- Department of Cardiovascular and Medical Sciences, University
of Glasgow, Glasgow, UK
| | - J Wang
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - P Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - AJ Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - A Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
| | - JM Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Alzheimer Scotland Research Centre, Edinburgh, UK
| | - LJ Hocking
- Division of Applied Medicine, University of Aberdeen, Aberdeen,
UK
| | - NJ Armstrong
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Cancer Research Program, Garvan Institute of Medical Research,
Sydney, NSW, Australia,School of Mathematics & Statistics and Prince of Wales
Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - S McLachlan
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - JM Shulman
- Department of Neurology, Baylor College of Medicine, Houston,
TX, USA,Department of Molecular and Human Genetics, The Jan and Dan
Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - LC Pilling
- Epidemiology and Public Health Group, University of Exeter
Medical School, Exeter, UK
| | | | - RJ Scott
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - NA Kochan
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Neuropsychiatric Institute, The Prince of Wales Hospital,
Sydney, NSW, Australia
| | - A Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus,
Cambridge, UK,Institute for Molecular Medicine Finland (FIMM), University of
Helsinki, Helsinki, Finland,Department of Medical Genetics, University of Helsinki and
University Central Hospital, Helsinki, Finland
| | - Y-C Hsieh
- School of Public Health, Taipei Medical University, Taipei,
Taiwan
| | - JG Eriksson
- Folkhälsan Research Centre, Helsinki, Finland,Department of General Practice and Primary Health Care,
University of Helsinki, Helsinki, Finland,National Institute for Health and Welfare, Helsinki,
Finland,Helsinki University Central Hospital, Unit of General Practice,
Helsinki, Finland,Vasa Central Hospital, Vasa, Finland
| | - A Penman
- Center of Biostatistics and Bioinformatics, University of
Mississippi Medical Center, Jackson, MS, USA
| | - RF Gottesman
- Department of Neurology, Johns Hopkins University School of
Medicine, Baltimore, MD, USA
| | - BA Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
| | - L Yu
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - AL DeStefano
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - A Beiser
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - M Garcia
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - JI Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los
Angeles, CA, USA,Institute for Translational Genomics and Population Sciences,
Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA,
USA,Division of Genetic Outcomes, Department of Pediatrics,
Harbor-UCLA Medical Center, Torrance, CA, USA
| | - MM Nöthen
- Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany,German Center for Neurodegenerative Diseases (DZNE), Bonn,
Germany
| | - A Hofman
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - PE Slagboom
- Department of Molecular Epidemiology, Leiden University Medical
Center, Leiden, The Netherlands
| | - RGJ Westendorp
- Leiden Academy of Vitality and Ageing, Leiden, The
Netherlands
| | - BM Buckley
- Department of Pharmacology and Therapeutics, University College
Cork, Cork, Ireland
| | - PA Wolf
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - AG Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands,Department of Internal Medicine, Erasmus University Medical
Center, Rotterdam, The Netherlands
| | - BM Psaty
- Cardiovascular Health Research Unit, Department of Medicine,
University of Washington, Seattle, WA, USA,Department of Epidemiology, University of Washington, Seattle,
WA, USA,Department of Health Services, University of Washington,
Seattle, WA, USA,Group Health Research Institute, Group Health, Seattle, WA,
USA
| | - HJ Grabe
- Department of Psychiatry and Psychotherapy, University Medicine
Greifswald, HELIOS-Hospital Stralsund, Stralsund, Germany
| | - S Bandinelli
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - DI Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - F Grodstein
- Channing Division of Network Medicine, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki,
Helsinki, Finland
| | - J-C Lambert
- Inserm, U1167, Institut Pasteur de Lille, Université
Lille-Nord de France, Lille, France
| | - DJ Porteous
- Centre for Genomic and Experimental Medicine, Institute of
Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - JF Price
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - PS Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Neuropsychiatric Institute, The Prince of Wales Hospital,
Sydney, NSW, Australia
| | - L Ferrucci
- Translational Gerontology Branch, National Institute on Aging,
Baltimore, MD, USA
| | - JR Attia
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - I Rudan
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - C Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - AF Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - JF Wilson
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - S Cichon
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany,Institute of Neuroscience and Medicine (INM-1), Research Center
Juelich, Juelich, Germany
| | - L Franke
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - H Schmidt
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - J Ding
- Department of Internal Medicine, Wake Forest University School
of Medicine, Winston-Salem, NC, USA
| | - AJM de Craen
- Department of Gerontology and Geriatrics, Leiden University
Medical Center, Leiden, The Netherlands
| | - M Fornage
- Institute for Molecular Medicine and Human Genetics Center,
University of Texas Health Science Center at Houston, Houston, TX, USA
| | - DA Bennett
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - IJ Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - MA Ikram
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands,Department of Radiology, Erasmus University Medical Center,
Rotterdam, The Netherlands
| | - LJ Launer
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - AL Fitzpatrick
- Department of Epidemiology, University of Washington, Seattle,
WA, USA
| | - S Seshadri
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - CM van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - TH Mosley
- Department of Medicine and Neurology, University of Mississippi
Medical Center, Jackson, MS, USA
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18
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Agbenyikey W, Karasek R, Cifuentes M, Wolf PA, Seshadri S, Taylor JA, Beiser AS, Au R. Job strain and cognitive decline: a prospective study of the framingham offspring cohort. Int J Occup Environ Med 2015; 6:79-94. [PMID: 25890602 PMCID: PMC5282587 DOI: 10.15171/ijoem.2015.534] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2014] [Accepted: 02/02/2015] [Indexed: 11/09/2022]
Abstract
BACKGROUND Workplace stress is known to be related with many behavioral and disease outcomes. However, little is known about its prospective relationship with measures of cognitive decline. OBJECTIVE To investigate the association of job strain, psychological demands and job control on cognitive decline. METHODS Participants from Framingham Offspring cohort (n=1429), were assessed on job strain, and received neuropsychological assessment approximately 15 years and 21 years afterwards. RESULTS High job strain and low control were associated with decline in verbal learning and memory. Job strain was associated with decline in word recognition skills. Active job and passive job predicted decline in verbal learning and memory relative to low strain jobs in the younger subgroup. Active job and demands were positively associated with abstract reasoning skills. CONCLUSIONS Job strain and job control may influence decline in cognitive performance.
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Affiliation(s)
- W Agbenyikey
- Department of Environmental and Occupational Health, Drexel University, Philadelphia, PA, USA.
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Davies G, Armstrong N, Bis JC, Bressler J, Chouraki V, Giddaluru S, Hofer E, Ibrahim-Verbaas CA, Kirin M, Lahti J, van der Lee SJ, Le Hellard S, Liu T, Marioni RE, Oldmeadow C, Postmus I, Smith AV, Smith JA, Thalamuthu A, Thomson R, Vitart V, Wang J, Yu L, Zgaga L, Zhao W, Boxall R, Harris SE, Hill WD, Liewald DC, Luciano M, Adams H, Ames D, Amin N, Amouyel P, Assareh AA, Au R, Becker JT, Beiser A, Berr C, Bertram L, Boerwinkle E, Buckley BM, Campbell H, Corley J, De Jager PL, Dufouil C, Eriksson JG, Espeseth T, Faul JD, Ford I, Scotland G, Gottesman RF, Griswold ME, Gudnason V, Harris TB, Heiss G, Hofman A, Holliday EG, Huffman J, Kardia SLR, Kochan N, Knopman DS, Kwok JB, Lambert JC, Lee T, Li G, Li SC, Loitfelder M, Lopez OL, Lundervold AJ, Lundqvist A, Mather KA, Mirza SS, Nyberg L, Oostra BA, Palotie A, Papenberg G, Pattie A, Petrovic K, Polasek O, Psaty BM, Redmond P, Reppermund S, Rotter JI, Schmidt H, Schuur M, Schofield PW, Scott RJ, Steen VM, Stott DJ, van Swieten JC, Taylor KD, Trollor J, Trompet S, Uitterlinden AG, Weinstein G, Widen E, Windham BG, Jukema JW, Wright AF, Wright MJ, Yang Q, Amieva H, Attia JR, Bennett DA, Brodaty H, de Craen AJM, Hayward C, Ikram MA, Lindenberger U, Nilsson LG, Porteous DJ, Räikkönen K, Reinvang I, Rudan I, Sachdev PS, Schmidt R, Schofield PR, Srikanth V, Starr JM, Turner ST, Weir DR, Wilson JF, van Duijn C, Launer L, Fitzpatrick AL, Seshadri S, Mosley TH, Deary IJ. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53949). Mol Psychiatry 2015; 20:183-92. [PMID: 25644384 PMCID: PMC4356746 DOI: 10.1038/mp.2014.188] [Citation(s) in RCA: 260] [Impact Index Per Article: 28.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Revised: 11/11/2014] [Accepted: 11/24/2014] [Indexed: 01/14/2023]
Abstract
General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53,949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10(-9), MIR2113; rs17522122, P=2.55 × 10(-8), AKAP6; rs10119, P=5.67 × 10(-9), APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10(-6)). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10(-17)). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C.
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Affiliation(s)
- G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - N Armstrong
- School of Mathematics and Statistics, University of Sydney, Sydney, NSW, Australia
| | - J C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - J Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - V Chouraki
- Inserm-UMR744, Institut Pasteur de Lille, Unité d'Epidémiologie et de Santé Publique, Lille, France,Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - S Giddaluru
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - E Hofer
- Department of Neurology, Medical University of Graz, Graz, Austria,Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - C A Ibrahim-Verbaas
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands,Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M Kirin
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland,Folkhälsan Research Centre, Helsinki, Finland
| | - S J van der Lee
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - S Le Hellard
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - T Liu
- Max Planck Institute for Human Development, Berlin, Germany,Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - C Oldmeadow
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - I Postmus
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - A V Smith
- Icelandic Heart Association, Kopavogur, Iceland,University of Iceland, Reykjavik, Iceland
| | - J A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - A Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - R Thomson
- Menzies Research Institute, Hobart, Tasmania
| | - V Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - J Wang
- Framingham Heart Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - L Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - L Zgaga
- Department of Public Health and Primary Care, Trinity College Dublin, Dublin, Ireland,Andrija Stampar School of Public Health, Medical School, University of Zagreb, Zagreb, Croatia
| | - W Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - R Boxall
- Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - W D Hill
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - M Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - H Adams
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - D Ames
- National Ageing Research Institute, Royal Melbourne Hospital, Melbourne, VIC, Australia,Academic Unit for Psychiatry of Old Age, St George's Hospital, University of Melbourne, Kew, Australia
| | - N Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - P Amouyel
- Inserm-UMR744, Institut Pasteur de Lille, Unité d'Epidémiologie et de Santé Publique, Lille, France
| | - A A Assareh
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - R Au
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - J T Becker
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA,Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - A Beiser
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - C Berr
- Inserm, U106, Montpellier, France,Université Montpellier I, Montpellier, France
| | - L Bertram
- Max Planck Institute for Molecular Genetics, Berlin, Germany,Faculty of Medicine, School of Public Health, Imperial College, London, UK
| | - E Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA,Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, University of Texas Health Science Center at Houston, Houston, TX, USA,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - B M Buckley
- Department of Pharmacology and Therapeutics, University College Cork, Cork, Ireland
| | - H Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - J Corley
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - P L De Jager
- Program in Translational NeuroPsychiatric Genomics, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA,Harvard Medical School, Boston, MA, USA,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - C Dufouil
- Inserm U708, Neuroepidemiology, Paris, France,Inserm U897, Université Bordeaux Segalen, Bordeaux, France
| | - J G Eriksson
- Folkhälsan Research Centre, Helsinki, Finland,National Institute for Health and Welfare, Helsinki, Finland,Department of General Practice and Primary health Care, University of Helsinki, Helsinki, Finland,Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland
| | - T Espeseth
- K.G. Jebsen Centre for Psychosis Research, Norwegian Centre For Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Psychology, University of Oslo, Oslo, Norway
| | - J D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - I Ford
- Robertson Center for Biostatistics, Glasgow, UK
| | - Generation Scotland
- Generation Scotland, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - R F Gottesman
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - M E Griswold
- Center of Biostatistics and Bioinformatics, University of Mississippi Medical Center, Jackson, MS, USA
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland,University of Iceland, Reykjavik, Iceland
| | - T B Harris
- Intramural Research Program National Institutes on Aging, National Institutes of Health, Bethesda, MD, USA
| | - G Heiss
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - A Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - E G Holliday
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - J Huffman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - S L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - N Kochan
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - J B Kwok
- Neuroscience Research Australia, Randwick, NSW, Australia,School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - J-C Lambert
- Inserm-UMR744, Institut Pasteur de Lille, Unité d'Epidémiologie et de Santé Publique, Lille, France
| | - T Lee
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - G Li
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - S-C Li
- Max Planck Institute for Human Development, Berlin, Germany,Technische Universität Dresden, Dresden, Germany
| | - M Loitfelder
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - O L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - A J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway,Kavli Research Centre for Aging and Dementia, Haraldsplass Deaconess Hospital, Bergen, Norway,K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway
| | - A Lundqvist
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
| | - K A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - S S Mirza
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - L Nyberg
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden,Department of Radiation Sciences, Umeå University, Umeå, Sweden,Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - B A Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - A Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland,Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland
| | - G Papenberg
- Max Planck Institute for Human Development, Berlin, Germany,Karolinska Institutet, Aging Research Center, Stockholm University, Stockholm, Sweden
| | - A Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - K Petrovic
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - O Polasek
- Faculty of Medicine, Department of Public Health, University of Split, Split, Croatia
| | - B M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA,Deparment of Epidemiology, University of Washington, Seattle, WA, USA,Deparment of Health Services, University of Washington, Seattle, WA, USA,Group Health Research Unit, Group Health Cooperative, Seattle, WA, USA
| | - P Redmond
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S Reppermund
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - J I Rotter
- Institute for Translational Genomics and Population Sciences Los Angeles BioMedical Research Institute, Harbor-UCLA Medical Center, Los Angeles, CA, USA,Division of Genetic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA, USA
| | - H Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria,Centre for Molecular Medicine, Institute of Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - M Schuur
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands,Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - P W Schofield
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - R J Scott
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - V M Steen
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Centre for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - D J Stott
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - J C van Swieten
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - K D Taylor
- Institute for Translational Genomics and Population Sciences Los Angeles BioMedical Research Institute, Harbor-UCLA Medical Center, Los Angeles, CA, USA,Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA, USA
| | - J Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - S Trompet
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands,Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
| | - A G Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands,Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - G Weinstein
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - E Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - B G Windham
- Division of Geriatrics, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - J W Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands,Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands,Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands
| | - A F Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - M J Wright
- Neuroimaging Genetics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Q Yang
- Framingham Heart Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - H Amieva
- Inserm U897, Université Bordeaux Segalen, Bordeaux, France
| | - J R Attia
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - D A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - H Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Dementia Collaborative Research Centre, University of New South Wales, Sydney, NSW, Australia
| | - A J M de Craen
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - C Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - M A Ikram
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands,Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands,Department of Radiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - U Lindenberger
- Max Planck Institute for Human Development, Berlin, Germany
| | - L-G Nilsson
- ARC, Karolinska Institutet, Stockholm and UFBI, Umeå University, Umeå, Sweden
| | - D J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK,Generation Scotland, University of Edinburgh Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - I Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - P S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - R Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - P R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia,Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - V Srikanth
- Menzies Research Institute, Hobart, Tasmania,Stroke and Ageing Research, Medicine, Southern Clinical School, Monash University, Melbourne, VIC, Australia
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - S T Turner
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - D R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - J F Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - C van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - L Launer
- Intramural Research Program National Institutes on Aging, National Institutes of Health, Bethesda, MD, USA
| | - A L Fitzpatrick
- Deparment of Epidemiology, University of Washington, Seattle, WA, USA,Department of Global Health, University of Washington, Seattle, WA, USA
| | - S Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - T H Mosley
- Division of Geriatrics, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, Scotland, UK. E-mail:
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20
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Tan ZS, Harris WS, Beiser AS, Au R, Himali JJ, Debette S, Pikula A, Decarli C, Wolf PA, Vasan RS, Robins SJ, Seshadri S. Red blood cell ω-3 fatty acid levels and markers of accelerated brain aging. Neurology 2012; 78:658-64. [PMID: 22371413 DOI: 10.1212/wnl.0b013e318249f6a9] [Citation(s) in RCA: 183] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE Higher dietary intake and circulating levels of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) have been related to a reduced risk for dementia, but the pathways underlying this association remain unclear. We examined the cross-sectional relation of red blood cell (RBC) fatty acid levels to subclinical imaging and cognitive markers of dementia risk in a middle-aged to elderly community-based cohort. METHODS We related RBC DHA and EPA levels in dementia-free Framingham Study participants (n = 1575; 854 women, age 67 ± 9 years) to performance on cognitive tests and to volumetric brain MRI, with serial adjustments for age, sex, and education (model A, primary model), additionally for APOE ε4 and plasma homocysteine (model B), and also for physical activity and body mass index (model C), or for traditional vascular risk factors (model D). RESULTS Participants with RBC DHA levels in the lowest quartile (Q1) when compared to others (Q2-4) had lower total brain and greater white matter hyperintensity volumes (for model A: β ± SE = -0.49 ± 0.19; p = 0.009, and 0.12 ± 0.06; p = 0.049, respectively) with persistence of the association with total brain volume in multivariable analyses. Participants with lower DHA and ω-3 index (RBC DHA+EPA) levels (Q1 vs. Q2-4) also had lower scores on tests of visual memory (β ± SE = -0.47 ± 0.18; p = 0.008), executive function (β ± SE = -0.07 ± 0.03; p = 0.004), and abstract thinking (β ± SE = -0.52 ± 0.18; p = 0.004) in model A, the results remaining significant in all models. CONCLUSION Lower RBC DHA levels are associated with smaller brain volumes and a "vascular" pattern of cognitive impairment even in persons free of clinical dementia.
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Affiliation(s)
- Z S Tan
- Department of Medicine, Division of Geriatric Medicine, Easton Center for Alzheimer’s Disease Research, David Geffen School of Medicine at the University of California at Los Angeles, Los Angeles, USA.
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21
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Camargo E, Beiser A, Tan Z, Au R, DeCarli C, Pikula A, Kelly-Hayes M, Kase C, Wolf P, Seshadri S. Walking Speed, Handgrip Strength and Risk of Dementia and Stroke: The Framingham Offspring Study (S24.003). Neurology 2012. [DOI: 10.1212/wnl.78.1_meetingabstracts.s24.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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Maillard P, Seshadri S, Beiser A, Fletcher E, Himali J, Preis S, Au R, Carmichael O, Wolf P, DeCarli C. Effects of Vascular Risk Factors on White Matter Integrity in Middle-Aged Adults: A Voxel-Based Diffusion Tensor Imaging Study (P03.089). Neurology 2012. [DOI: 10.1212/wnl.78.1_meetingabstracts.p03.089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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Debette S, Seshadri S, Beiser A, Au R, Himali JJ, Palumbo C, Wolf PA, DeCarli C. Midlife vascular risk factor exposure accelerates structural brain aging and cognitive decline. Neurology 2011; 77:461-8. [PMID: 21810696 DOI: 10.1212/wnl.0b013e318227b227] [Citation(s) in RCA: 557] [Impact Index Per Article: 42.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE Our aim was to test the association of vascular risk factor exposure in midlife with progression of MRI markers of brain aging and measures of cognitive decline. METHODS A total of 1,352 participants without dementia from the prospective Framingham Offspring Cohort Study were examined. Multivariable linear and logistic regressions were implemented to study the association of midlife vascular risk factor exposure with longitudinal change in white matter hyperintensity volume (WMHV), total brain volume (TBV), temporal horn volume, logical memory delayed recall, visual reproductions delayed-recall (VR-d), and Trail-Making Test B-A (TrB-A) performance a decade later. RESULTS Hypertension in midlife was associated with accelerated WMHV progression (p < 0.001) and worsening executive function (TrB-A score; p = 0.012). Midlife diabetes and smoking were associated with a more rapid increase in temporal horn volume, a surrogate marker of accelerated hippocampal atrophy (p = 0.017 and p = 0.008, respectively). Midlife smoking also predicted a more marked decrease in total brain volume (p = 0.025) and increased risk of extensive change in WMHV (odds ratio = 1.58 [95%confidence interval 1.07-2.33], p = 0.021). Obesity in midlife was associated with an increased risk of being in the top quartile of change in executive function (1.39 [1.02-1.88], p = 0.035) and increasing waist-to-hip ratio was associated with marked decline in TBV (10.81 [1.44-81.01], p = 0.021). Longitudinal changes in brain structure were significantly correlated with decline in memory and executive function. CONCLUSIONS Midlife hypertension, diabetes, smoking, and obesity were associated with an increased rate of progression of vascular brain injury, global and hippocampal atrophy, and decline in executive function a decade later.
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Affiliation(s)
- S Debette
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
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Lo AIL, Huang Y, Lam SY, Cheung AHK, Au R, Leung CC, Lam WK, Ip MSM, Chan-Yeung M, Lam B. Early detection of central airway lung cancer in smokers with silicosis. Int J Tuberc Lung Dis 2011; 15:523-7. [PMID: 21396213 DOI: 10.5588/ijtld.10.0461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Smokers with silicosis are at increased risk of lung cancer. OBJECTIVE To evaluate the feasibility of using autofluorescence bronchoscopy after sputum examination for early detection of large airway lung cancer and factors associated with the presence of cancerous and pre-cancerous lesions among smokers with silicosis. METHODS Subjects at the pneumoconiosis clinic were recruited if they fulfilled the following criteria: 1) age ≥40 years, 2) smoking history of ≥20 pack-years and 3) confirmed diagnosis of silicosis. Sputum specimens were collected for cytology/cytometry examination and autofluorescence bronchoscopy was performed in subjects with an abnormal sputum result. RESULTS A total of 48 subjects were recruited during the study period. The mean age and smoking history were respectively 63 ± 10 years and 51 ± 30 pack-years. Intraepithelial lung cancers and pre-neoplastic lesions (squamous metaplasia or above) were detected in respectively 2 (4.2%) and 14 (29.2%) subjects. The proportions of current smokers (75.0% vs. 40.6%, P = 0.03) and asbestos exposure (37.5% vs. 9.4%, P = 0.04) were significantly higher in subjects with the above lesions compared with those without. CONCLUSIONS Sputum examination followed by autofluorescence bronchoscopy may be a useful way of identifying cancerous/pre-cancerous lesions among silicotic smokers. Current smoking and asbestos exposure were associated with these lesions.
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Affiliation(s)
- A I L Lo
- Department of Respiratory Medicine, Centro Hospitalar Conde de São Januário, Macao SAR, China
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Amini E, Au R, Williams D. Ki67 expression in oestrogen receptor positive breast ductal carcinoma. Pathology 2011. [DOI: 10.1016/s0031-3025(16)33239-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Abstract
OBJECTIVES Depression may be associated with an increased risk for dementia, although results from population-based samples have been inconsistent. We examined the association between depressive symptoms and incident dementia over a 17-year follow-up period. METHODS In 949 Framingham original cohort participants (63.6% women, mean age = 79), depressive symptoms were assessed at baseline (1990-1994) using the 60-point Center for Epidemiologic Studies Depression Scale (CES-D). A cutpoint of > or = 16 was used to define depression, which was present in 13.2% of the sample. Cox proportional hazards models adjusting for age, sex, education, homocysteine, and APOE epsilon4 examined the association between baseline depressive symptoms and the risk of dementia and Alzheimer disease (AD). RESULTS During the 17-year follow-up period, 164 participants developed dementia; 136 of these cases were AD. A total of 21.6% of participants who were depressed at baseline developed dementia compared with 16.6% of those who were not depressed. Depressed participants (CES-D >/=16) had more than a 50% increased risk for dementia (hazard ratio [HR] 1.72, 95% confidence interval [CI] 1.04-2.84, p = 0.035) and AD (HR 1.76, 95% CI 1.03-3.01, p = 0.039). Results were similar when we included subjects taking antidepressant medications as depressed. For each 10-point increase on the CES-D, there was significant increase in the risk of dementia (HR 1.46, 95% CI 1.18-1.79, p < 0.001) and AD (HR 1.39, 95% CI 1.11-1.75, p = 0.005). Results were similar when we excluded persons with possible mild cognitive impairment. CONCLUSIONS Depression is associated with an increased risk of dementia and AD in older men and women over 17 years of follow-up.
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Affiliation(s)
- J S Saczynski
- Department of Medicine and Meyers Primary Care Institute, University of Massachusetts Medical School, Worcester, MA, USA.
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Debette S, Wolf PA, Beiser A, Au R, Himali JJ, Pikula A, Auerbach S, Decarli C, Seshadri S. Association of parental dementia with cognitive and brain MRI measures in middle-aged adults. Neurology 2009; 73:2071-8. [PMID: 20007524 DOI: 10.1212/wnl.0b013e3181c67833] [Citation(s) in RCA: 57] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVES Studies of autosomal dominant Alzheimer disease (AD) have shown structural and cognitive changes in mutation carriers decades prior to clinical disease. Whether such changes are detectable in offspring of persons with sporadic dementia remains unknown. We related prospectively verified parental dementia to brain MRI and cognitive testing in the offspring, within a 2-generational community-based cohort. METHODS A total of 717 Framingham offspring (mean age: 59 +/- 8 years) were studied. In multivariate analyses, we compared offspring with and without verified parental dementia (and AD) for 1) performance on tests of memory, abstract reasoning, and cognitive flexibility, and 2) volumetric brain MRI measures of total cerebral brain volume (TCBV), hippocampal volume (HV), and white matter hyperintensity volume (WMHV), assessed cross-sectionally and longitudinally. RESULTS When testing the association of parental dementia and AD with baseline cognitive performance, we observed an interaction of parental dementia and AD with APOE epsilon4 status (p < 0.002). In APOE epsilon4 carriers only (n = 165), parental dementia was associated with poorer scores on tests of verbal memory (beta = -1.81 +/- 0.53, p < 0.001) and visuospatial memory (beta = -1.73 +/- 0.47, p < 0.001). These associations were stronger for parental AD (beta = -1.97 +/- 0.52, p < 0.001, beta = -1.95 +/- 0.48, p < 0.001), equivalent to 14-16 years of brain aging. Among APOE epsilon4 carriers, offspring of participants with dementia were also more likely to show an annual decline in TCBV in the top quartile (odds ratio = 4.67 [1.26-17.30], p = 0.02). Regardless of APOE epsilon4 status, participants with parental dementia were more likely to be in the highest quartile of decline in executive function test scores (odds ratio = 1.61 [1.02-2.53], p = 0.04). CONCLUSIONS Among middle-aged carriers of the APOE epsilon4 allele, parental dementia and Alzheimer disease were associated with poorer verbal and visuospatial memory and a higher rate of global brain atrophy.
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Affiliation(s)
- S Debette
- Department of Neurology, Boston University School of Medicine, B602, 72 East Concord Street, Boston, MA 02118, USA
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Tan ZS, Beiser AS, Vasan RS, Roubenoff R, Dinarello CA, Harris TB, Benjamin EJ, Au R, Kiel DP, Wolf PA, Seshadri S. Inflammatory markers and the risk of Alzheimer disease: the Framingham Study. Neurology 2007; 68:1902-8. [PMID: 17536046 DOI: 10.1212/01.wnl.0000263217.36439.da] [Citation(s) in RCA: 313] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To examine whether serum cytokines and spontaneous production of peripheral blood mononuclear cell (PBMC) cytokines are associated with the risk of incident Alzheimer disease (AD). METHODS We followed 691 cognitively intact community-dwelling participants (mean age 79 years, 62% women) and related PBMC cytokine production (tertiles of spontaneous production of interleukin 1 [IL-1], IL-1 receptor antagonist, and tumor necrosis factor alpha [TNF-alpha]) and serum C-reactive protein and interleukin 6 (IL-6) to the risk of incident AD. RESULTS Adjusting for clinical covariates, individuals in the top two tertiles (T2 and T3) of PBMC production of IL-1 or the top tertile (T3) of PBMC production of TNF-alpha were at increased risk of developing AD (multivariable-adjusted hazard ratio [HR] for IL-1 T2 = 2.84, 95% CI 1.09 to 7.43; p = 0.03 and T3 = 2.61, 95% CI 0.96 to 7.07; p = 0.06; for TNF-alpha, adjusted HR for T2 = 1.30, 95% CI 0.53 to 3.17; p = 0.57 and T3 = 2.59, 95% CI 1.09 to 6.12; p = 0.031]) compared with those in the lowest tertile (T1). INTERPRETATION Higher spontaneous production of interleukin 1 or tumor necrosis factor alpha by peripheral blood mononuclear cells may be a marker of future risk of Alzheimer disease (AD) in older individuals. These data strengthen the evidence for a pathophysiologic role of inflammation in the development of clinical AD.
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Affiliation(s)
- Z S Tan
- Department of Medicine, Institute for Aging Research, Hebrew Senior Life, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02131, USA.
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Jefferson AL, Massaro JM, Wolf PA, Seshadri S, Au R, Vasan RS, Larson MG, Meigs JB, Keaney JF, Lipinska I, Kathiresan S, Benjamin EJ, DeCarli C. Inflammatory biomarkers are associated with total brain volume: the Framingham Heart Study. Neurology 2007; 68:1032-8. [PMID: 17389308 PMCID: PMC2758770 DOI: 10.1212/01.wnl.0000257815.20548.df] [Citation(s) in RCA: 200] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Systemic inflammation is associated with ischemia and Alzheimer disease (AD). We hypothesized that inflammatory biomarkers would be associated with neuroimaging markers of ischemia (i.e., white matter hyperintensities [WMH]) and AD (i.e., total brain volume [TCB]). METHODS MRI WMH and TCB were quantified on 1,926 Framingham Offspring participants free from clinical stroke, TIA, or dementia (mean age 60 +/- 9 years; range 35 to 85 years; 54% women) who underwent measurement of a circulating inflammatory marker panel, including CD40 ligand, C-reactive protein, interleukin-6 (IL-6), soluble intracellular adhesion molecule-1, monocyte chemoattractant protein-1, myeloperoxidase, osteoprotegerin (OPG), P-selectin, tumor necrosis factor-alpha (TNFalpha), and tumor necrosis factor receptor II. To account for head size, both TCB (TCBV) and WMH (WMH/TCV) were divided by total cranial volume. We used multivariable linear regression to relate 10 log-transformed inflammatory biomarkers to brain MRI measures. RESULTS In multivariable models, inflammatory markers as a group were associated with TCBV (p < 0.0001) but not WMH/TCV (p = 0.28). In stepwise models adjusted for clinical covariates with backwards elimination of markers, IL-6 and OPG were inversely associated with TCBV; TNFalpha was inversely related to TCBV in a subset of 1,430 participants. Findings were similar in analyses excluding individuals with prevalent cardiovascular disease. The relations between TCBV and inflammatory markers were modified by both sex and age, and generally were more pronounced in men and in older individuals. CONCLUSIONS Although our observational cross-sectional data cannot establish causality, they are consistent with the hypothesis that higher inflammatory markers are associated with greater atrophy than expected for age.
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Affiliation(s)
- A L Jefferson
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA.
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Seshadri S, Wolf PA, Beiser A, Elias MF, Au R, Kase CS, D'Agostino RB, DeCarli C. Stroke risk profile, brain volume, and cognitive function: the Framingham Offspring Study. Neurology 2005; 63:1591-9. [PMID: 15534241 DOI: 10.1212/01.wnl.0000142968.22691.70] [Citation(s) in RCA: 177] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Mid-life stroke risk factors have been related to late-life cognitive impairment. This association may result not only from clinical strokes but also from subclinical brain injury, such as a global atrophy demonstrable on quantitative brain MRI. METHODS The authors evaluated the community-based cohort of Framingham Offspring Study participants. A total of 1,841 subjects (mean age, 62 years; 857 men, 984 women) who underwent quantitative MRI and cognitive testing between 1999 and 2001 and were free of clinical stroke and dementia constituted our study sample. The authors used age- and sex-adjusted linear regression models to relate previous (1991 to 1995) and recent (1998 to 2001) Framingham Stroke Risk Profile (FSRP) scores to the total cerebral brain volume ratio (TCBVr) on follow-up MRI, and further to relate the TCBVr with education-adjusted scores on neuropsychological tests administered at the time of imaging. RESULTS There was an inverse association between FSRP scores and TCBVr. The TCBVr also showed a significant positive association with performance on tests of attention (Trails A), executive function (Trails B), and visuospatial function (visual reproduction, Hooper visual organization), but not with performance on tests of verbal memory or naming. CONCLUSIONS The Framingham Stroke Risk Profile may identify subjects with smaller brains and poorer cognitive function among stroke- and dementia-free subjects, reinforcing the importance of managing stroke risk factors.
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Affiliation(s)
- S Seshadri
- Department of Neurology, School of Medicine, Boston University, MA 02118-2526, USA
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Elias MF, Beiser A, Wolf PA, Au R, White RF, D'Agostino RB. The preclinical phase of alzheimer disease: A 22-year prospective study of the Framingham Cohort. Arch Neurol 2000; 57:808-13. [PMID: 10867777 DOI: 10.1001/archneur.57.6.808] [Citation(s) in RCA: 466] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
OBJECTIVES To relate performance on tests of cognitive ability to the subsequent development of probable Alzheimer disease (pAD) and to identify the pattern of earliest changes in cognitive functioning associated with a diagnosis of pAD. DESIGN From May 1975 to November 1979, a screening neuropsychological battery was administered to Framingham Study participants. They were followed up prospectively for 22 years and examined at least every 2 years for the development of pAD. SETTING A community-based center for epidemiological research. PARTICIPANTS Subjects were 1076 participants of the Framingham Study aged 65 to 94 years who were free of dementia and stroke at baseline (initial) neuropsychological testing. MAIN OUTCOME MEASURE Presence or absence of pAD during a 22-year surveillance period was related to test performance at initial neuropsychological testing. RESULTS Lower scores for measures of new learning, recall, retention, and abstract reasoning obtained during a dementia-free period were associated with the development of pAD. Lower scores for measures of abstract reasoning and retention predicted pAD after a dementia-free period of 10 years. CONCLUSIONS The "preclinical phase" of detectable lowering of cognitive functioning precedes the appearance of pAD by many years. Measures of retention of information and abstract reasoning are among the strongest predictors of pAD when the interval between initial assessment and the development of pAD is long. Arch Neurol. 2000.
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Affiliation(s)
- M F Elias
- Department of Mathematics and Statistics, Statistical Consulting Unit, 111 Cummington St, Boston University College of Arts and Sciences, Boston, MA 02215, USA.
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Nabholtz JM, North S, Smylie M, Mackey J, Au HJ, Au R, Morrish D, Salter E, Tonkin K. Docetaxel (Taxotere) in combination with anthracyclines in the treatment of breast cancer. Semin Oncol 2000; 27:11-8. [PMID: 10810933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Considering the single-agent activity of docetaxel (Taxotere; Rhône-Poulenc Rorer, Antony, France) and doxorubicin in breast cancer and their potential non-cross-resistance, several docetaxel/anthracycline-based combination chemotherapies were developed in phase I and II programs for metastatic breast cancer patients. The rationale for these combinations was also reinforced by the fact that docetaxel showed significant activity in phase III trials in patients previously exposed or having failed anthracycline chemotherapy. In a pivotal randomized phase III study of doxorubicin plus docetaxel versus doxorubicin plus cyclophosphamide as first-line chemotherapy for 429 patients with metastatic breast cancer, doxorubicin/docetaxel emerged as the more effective regimen. Despite a lower-dose intensity of doxorubicin, patients receiving doxorubicin/docetaxel experienced a higher response rate as well as a significantly longer time to progression and time to treatment failure. This difference was seen even in patients with poor-prognosis disease. Febrile neutropenia was more common in doxorubicin/docetaxel-treated patients. However, there were no septic deaths among 213 patients receiving doxorubicin/ docetaxel. Extrahematologic toxicity appeared mild for both regimens and the combination docetaxel/doxorubicin did not increase the cardiac toxicity expected for an anthracycline-containing regimen. Docetaxel plus doxorubicin is the first regimen, involving a newly developed agent, proven superior to a standard anthracycline-containing combination in metastatic breast cancer and its potential is now being investigated in the adjuvant setting.
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Affiliation(s)
- J M Nabholtz
- Northern Alberta Breast Cancer Program, Cross Cancer Institute, Edmonton, Canada
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Nabholtz JM, Smylie M, Mackey J, Au HJ, Tonkin K, Au R, Morrish D, Salter E. Docetaxel and anthracycline polychemotherapy in the treatment of breast cancer. Semin Oncol 1999; 26:47-52. [PMID: 10403474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
Given the single-agent activity of docetaxel and doxorubicin in metastatic breast cancer and their potential non-cross-resistance, several phase I/II pilot studies of either docetaxel/doxorubicin (TA) or TA plus cyclophosphamide (TAC) were conducted. The results of these studies show that the main toxicity is related to neutropenia and its consequences, although documented infections are rarely reported. Other toxicities are mild, while docetaxel-specific toxicities (fluid retention, nail changes, etc) are seldom seen. No significant cardiotoxicity, even when patients are exposed to a cumulative doxorubicin dose greater than 360 mg/m2, has been observed. In terms of efficacy, response rates in the range of 70% to 80% were noted in all studies, even for patients with visceral metastases. Preliminary data suggest that the combination of docetaxel with epirubicin is also feasible, with manageable toxicities and significant activity. Several phase III randomized trials using TA or TAC are presently being performed in first-line metastatic breast cancer and, most importantly, in the adjuvant setting to assess whether TA-based combinations will change the natural history of breast cancer.
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Affiliation(s)
- J M Nabholtz
- Northern Alberta Breast Cancer Program, Cross Cancer Institute, Edmonton, Canada
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Abstract
Few studies have examined verb naming in normal aging, although decline in the ability to name nouns has been well documented. In this study, we examined longitudinal performance on the Action Naming Test (ANT), a confrontation naming test for verbs. The purpose of this study was to confirm the verb naming deficit associated with aging, which was previously seen only in cross-sectional studies, and to provide additional normative data on verb naming ability that may prove useful to studies on verb naming in populations with brain dysfunction. Sixty-six healthy men and women aged 30 to 79 were each tested with the ANT 3 times over a 7-year span. ANT performance showed a significant decline over time for all participants except the youngest group. Longitudinal methodology supports the conclusion that this finding of a decline in verb naming ability arises from true age-related changes and not from cohort differences.
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Affiliation(s)
- C B Ramsay
- Department of Veterans Affairs Medical Center, Boston, Massachusetts 02130, USA
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Seshadri S, Wolf PA, Beiser A, Au R, McNulty K, White R, D'Agostino RB. Lifetime risk of dementia and Alzheimer's disease. The impact of mortality on risk estimates in the Framingham Study. Neurology 1997; 49:1498-504. [PMID: 9409336 DOI: 10.1212/wnl.49.6.1498] [Citation(s) in RCA: 340] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
We estimated the remaining lifetime risks of developing Alzheimer's disease (AD) and dementia from all causes, based on data from longitudinal population studies. The risk of developing AD during one's lifetime depends on both disease incidence and life expectancy. Conventional estimates of cumulative incidence overestimate the risk when there is a substantial probability of mortality due to competing causes. A total of 2,611 cognitively intact subjects (1,061 men, 1,550 women; mean age, 66 +/- 7 years) were prospectively evaluated for the development of AD or other dementia. A modified survival analysis was used to estimate both cumulative incidence and the sex-specific remaining lifetime risk estimates for quinquennial age groups above age 65 years. Over a 20-year follow-up period, 198 subjects developed dementia (120 with AD). The remaining lifetime risk of AD or other dementia depended on sex, being higher in women, but varied little with age between 65 and 80 years. In a 65-year-old man, the remaining lifetime risk of AD was 6.3% (95% CI, 3.9 to 8.7) and the remaining lifetime risk of developing any dementing illness was 10.9% (95% CI, 8.0 to 13.8); corresponding risks for a 65-year-old woman were 12% (95% CI, 9.2 to 14.8) and 19% (95% CI, 17.2 to 22.5). The cumulative incidence between age 65 and 100 years was much higher: for AD, 25.5% in men and 28.1% in women; for dementia, 32.8% in men and 45% in women. The actual remaining lifetime risk of AD or dementia varies with age, sex, and life expectancy and is lower than the hypothetical risk estimated by a cumulative incidence in the same population.
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Affiliation(s)
- S Seshadri
- Department of Neurology, Boston University School of Medicine, MA 02118, USA
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Abstract
This study investigated the nature of naming errors produced on the Boston Naming Test by patients with mild and moderate Alzheimer's disease (AD) and elderly and young controls, using a newly devised scoring system. This new approach involved ratings of error responses on a scale of semantic relatedness to the target name. Error responses of both mild and moderate AD subjects were no less semantically related to target names than were responses of age- and education-matched controls. We conclude that some available evidence of semantic loss in AD may be an artifact of the methodology chosen for evaluating naming errors.
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Affiliation(s)
- M Nicholas
- Medical Research Service, Department of Veterans Affairs Medical Center, Boston, Massachusetts
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Myers RH, Schaefer EJ, Wilson PW, D'Agostino R, Ordovas JM, Espino A, Au R, White RF, Knoefel JE, Cobb JL, McNulty KA, Beiser A, Wolf PA. Apolipoprotein E epsilon4 association with dementia in a population-based study: The Framingham study. Neurology 1996; 46:673-7. [PMID: 8618665 DOI: 10.1212/wnl.46.3.673] [Citation(s) in RCA: 244] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Apolipoprotein E type 4 allele (apoE epsilon4) is associated with Alzheimer's disease (AD) in the late-onset familial form and in sporadic cases, but the age-associated risk in a randomly sampled elderly population is not established. We examined the association of apoE epsilon4 with AD and other dementias (mainly multi-infarct or dementia following stroke) in 1,030 persons aged 71 to 100 years in the population-based Framingham Study cohort. Kaplan-Meier survival analysis revealed that 55% of the apoE epsilon4/epsilon4 homozygotes developed AD by age 80, whereas 27% of apoE epsilon3/epsilon4 heterozygotes developed AD by age 85, and 9% of those without a 4 allele developed AD by age 85 years. In comparison with persons without a 4 allele, the risk ration for AD was 3.7 (95% CI = 1.9 to 7.5) for apoE epsilon3/epsilon4 heterozygotes and 30.1 (95% CI = 10.7 to 84.4) for apoE epsilon4 homozygotes. ApoE epsilon2 (2/2, 2/3, or 2/4 genotypes) was associated with an absence of AD. One-half (n=21) of the 43 AD patients were either homozygous or heterozygous for apoE epsilon4. We found evidence for an association of apoE epsilon4 with other dementia, primarily multi-infarct dementia and stroke. The risk ratio was 2.3 (95% CI = 0.9 to 6.1) for non-AD dementias among persons with apoE epsilon3/epsilon4. Although the apoE epsilon4 allele is a potent risk factor for AD and may be associated with other forms of dementia, most apoE epsilon4 carriers do not develop dementia, and about one-half of AD is not apoE epsilon4 associated. The low positive predictive value of this marker (0.10) suggest that use of apoE genotyping as a screening test for AD is not supported.
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Affiliation(s)
- R H Myers
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
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Cobb JL, Wolf PA, Au R, White R, D'Agostino RB. The effect of education on the incidence of dementia and Alzheimer's disease in the Framingham Study. Neurology 1995; 45:1707-12. [PMID: 7675231 DOI: 10.1212/wnl.45.9.1707] [Citation(s) in RCA: 144] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
OBJECTIVE To evaluate whether low educational attainment is a risk factor for the incidence of dementia and Alzheimer's disease (AD) in the Framingham Study and to determine whether age at onset of dementia is earlier in persons with low educational levels. DESIGN A community-based cohort was studied longitudinally for the development of dementia. Diagnosis was made according to strict criteria by two neurologists and a neuropsychologist. Subtype of dementia and year at onset were determined. Incidence rates were compared in three education groups: < grade school, < high school, and > or = high school. PARTICIPANTS A total of 3,330 men and women aged 55 to 88 years. RESULTS During 17 years of follow-up, 258 incident cases of dementia, including 149 AD cases, were identified. Unadjusted incidence rates were significantly elevated (p < 0.05) for dementia and non-AD dementia among the least educated. The age-adjusted relative risk for subjects with a grade school education or less compared with those who earned a high school diploma was 1.31 (95% confidence interval [CI], 0.90 to 1.90) for dementia generally, 1.04 (95% CI, 0.62 to 1.74) for AD, and 1.75 (95% CI, 1.03 to 2.98) for non-AD dementia. Age at onset of dementia did not vary by educational attainment. CONCLUSIONS After age adjustment, low educational attainment was not a significant risk factor for the incidence of dementia generally or of AD. Low educational attainment was associated with increased risk of non-AD dementia, perhaps because of deleterious smoking habits and other risk factors for stroke in the least-educated individuals. Adequately adjusting for age and examining subtypes of dementia are important in assessing the influence of education on dementia incidence.
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Affiliation(s)
- J L Cobb
- Department of Mathematics, Boston University, MA, USA
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