1
|
Carvalho DZ, St. Louis EK, Schwarz CG, Bradley BF, Lowe VJ, Przybelski SA, Reddy A, Mielke MM, Knopman DS, Petersen RC, Jack CR, Vemuri P. 0355 Neurobiological Correlates of Sleepiness in Middle Aged and Older Adults: A FDG-PET Study. Sleep 2020. [DOI: 10.1093/sleep/zsaa056.352] [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: 11/14/2022] Open
Abstract
Abstract
Introduction
Sleepiness has been associated with functional and cognitive decline, and may present with excessive daytime sleepiness (EDS) and/or increased sleep duration. We investigated whether sleepiness and changes in sleep patterns are associated with FDG-PET levels in wake-promoting regions.
Methods
From the Mayo Clinic Study of Aging cohort, we identified 373 cognitively-unimpaired middle-aged and older adults (mean +/- s.d. 66.1 +/- 13.2 yo) who underwent FDG-PET. EDS was defined as ESS score >=10. Changes in sleep patterns (sleeping more, less, or no change) were assessed using question #16 of the Beck Depression Inventory-2. We used probabilistic maps to create regions of interest (ROIs): the locus coeruleus (LC), posterior lateral hypothalamus (PLH), and the basal forebrain divided in 1) medial septum/diagonal band of Broca (MS/DB) and 2) nucleus basalis of Meynert (nbM). FDG-PET levels were referenced to the pons (SUVR). In this cross-sectional analysis, we fit linear models to assess the association between EDS and changes in sleeping patterns with FDG SUVR in in each ROI, while controlling for age, sex, education, BMI, witnessed apneas, and cardiovascular risk factors.
Results
10.5% had EDS, 15% reported sleeping more and 21% reported sleeping less than usual. 30.7% of participants with EDS reported sleeping more, 25.6% less, and 43.5% the same. EDS was associated with an elevation in FDG-PET SUVR in the MS/DB region (.035 [95% CI .008; .063], p=.012), while sleeping more was associated with a decrease in FDG-PET SUVR in the same region (-.027 [95%CI -.052; -.002], p=.036). Sleeping less was associated with an increase in FDG-PET SUVR in the PLH (.021 [95% CI .005; .03], p=.019). No associations were found in other ROIs.
Conclusion
Our results suggest that sleepiness and changes in sleep patterns in cognitively-unimpaired middle-aged and older adults were associated with measurable metabolic changes in areas of the brain involved in sleep and wakefulness. Further research should clarify whether these findings could represent different phenotypes of sleepiness with potential diagnostic and prognostic implications.
Support
NIA/NIH
Collapse
|
2
|
Stricker NH, Lundt ES, Alden EC, Albertson SM, Machulda MM, Kremers WK, Knopman DS, Petersen RC, Mielke MM. Longitudinal Comparison of in Clinic and at Home Administration of the Cogstate Brief Battery and Demonstrated Practice Effects in the Mayo Clinic Study of Aging. J Prev Alzheimers Dis 2020; 7:21-28. [PMID: 32010922 DOI: 10.14283/jpad.2019.35] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
BACKGROUND The Cogstate Brief Battery (CBB) is a computerized cognitive assessment that can be completed in clinic or at home. Design/Objective: This retrospective study investigated whether practice effects / performance trajectories of the CBB differ by location of administration. PARTICIPANTS/SETTING Participants included 1439 cognitively unimpaired individuals age 50-75 at baseline participating in the Mayo Clinic Study of Aging (MCSA), a population-based study of cognitive aging. Sixty three percent of participants completed the CBB in clinic only and 37% completed CBB both in clinic and at home. MEASUREMENTS The CBB consists of four subtests: Detection, Identification, One Card Learning, and One Back. Linear mixed effects models were used to evaluate performance trajectories in clinic and at home. RESULTS Results demonstrated significant practice effects between sessions 1 to 2 for most CBB measures. Practice effects continued over subsequent testing sessions, to a lesser degree. Average practice effects/trajectories were similar for each location (home vs. clinic). One Card Learning and One Back accuracy performances were lower at home than in clinic, and this difference was large in magnitude for One Card Learning accuracy. Participants performed faster at home on Detection reaction time, although this difference was small in magnitude. CONCLUSIONS Results suggest the location where the CBB is completed has an important impact on performance, particularly for One Card Learning accuracy, and there are practice effects across repeated sessions that are similar regardless of where testing is completed.
Collapse
Affiliation(s)
- N H Stricker
- Nikki H. Stricker, Ph.D., Mayo Clinic, 200 First Street SW, Rochester, MN 55905; 507-284-2649 (phone), 507-284-4158 (fax),
| | | | | | | | | | | | | | | | | |
Collapse
|
3
|
Evered L, Silbert B, Knopman DS, Scott DA, DeKosky ST, Rasmussen LS, Oh ES, Crosby G, Berger M, Eckenhoff RG. Recommendations for the Nomenclature of Cognitive Change Associated with Anaesthesia and Surgery-20181. J Alzheimers Dis 2019; 66:1-10. [PMID: 30347621 DOI: 10.3233/jad-189004] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Cognitive change affecting patients after anaesthesia and surgery has been recognised for more than 100 yr. Research into cognitive change after anaesthesia and surgery accelerated in the 1980s when multiple studies utilised detailed neuropsychological testing for assessment of cognitive change after cardiac surgery. This body of work consistently documented decline in cognitive function in elderly patients after anaesthesia and surgery, and cognitive changes have been identified up to 7.5 yr afterwards. Importantly, other studies have identified that the incidence of cognitive change is similar after non-cardiac surgery. Other than the inclusion of non-surgical control groups to calculate postoperative cognitive dysfunction, research into these cognitive changes in the perioperative period has been undertaken in isolation from cognitive studies in the general population. The aim of this work is to develop similar terminology to that used in cognitive classifications of the general population for use in investigations of cognitive changes after anaesthesia and surgery. A multispecialty working group followed a modified Delphi procedure with no prespecified number of rounds comprised of three face-to-face meetings followed by online editing of draft versions.Two major classification guidelines [Diagnostic and Statistical Manual for Mental Disorders, fifth edition (DSM-5) and National Institute for Aging and the Alzheimer Association (NIA-AA)] are used outside of anaesthesia and surgery, and may be useful for inclusion of biomarkers in research. For clinical purposes, it is recommended to use the DSM-5 nomenclature. The working group recommends that 'perioperative neurocognitive disorders' be used as an overarching term for cognitive impairment identified in the preoperative or postoperative period. This includes cognitive decline diagnosed before operation (described as neurocognitive disorder); any form of acute event (postoperative delirium) and cognitive decline diagnosed up to 30 days after the procedure (delayed neurocognitive recovery) and up to 12 months (postoperative neurocognitive disorder).
Collapse
Affiliation(s)
- L Evered
- St Vincent's Hospital, Melbourne, Fitzroy, VIC, Australia.,University of Melbourne, Fitzroy, VIC, Australia
| | - B Silbert
- St Vincent's Hospital, Melbourne, Fitzroy, VIC, Australia.,University of Melbourne, Fitzroy, VIC, Australia
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - D A Scott
- St Vincent's Hospital, Melbourne, Fitzroy, VIC, Australia.,University of Melbourne, Fitzroy, VIC, Australia
| | - S T DeKosky
- Department of Neurology, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - L S Rasmussen
- Department of Anaesthesia, Center of Head and Orthopaedics, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - E S Oh
- Division of Geriatric Medicine and Gerontology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - G Crosby
- Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
| | - M Berger
- Neurologic Outcomes Research Group, Anesthesiology Department, Duke University Medical Center, Durham, NC, USA
| | - R G Eckenhoff
- Department of Anesthesiology and Critical Care, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | | |
Collapse
|
4
|
Evered L, Silbert B, Knopman DS, Scott DA, DeKosky ST, Rasmussen LS, Oh ES, Crosby G, Berger M, Eckenhoff RG. Recommendations for the Nomenclature of Cognitive Change Associated With Anaesthesia and Surgery-2018. Anesth Analg 2019; 127:1189-1195. [PMID: 30325748 DOI: 10.1213/ane.0000000000003634] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Cognitive change affecting patients after anaesthesia and surgery has been recognised for more than 100 yr. Research into cognitive change after anaesthesia and surgery accelerated in the 1980s when multiple studies utilised detailed neuropsychological testing for assessment of cognitive change after cardiac surgery. This body of work consistently documented decline in cognitive function in elderly patients after anaesthesia and surgery, and cognitive changes have been identified up to 7.5 yr afterwards. Importantly, other studies have identified that the incidence of cognitive change is similar after non-cardiac surgery. Other than the inclusion of non-surgical control groups to calculate postoperative cognitive dysfunction, research into these cognitive changes in the perioperative period has been undertaken in isolation from cognitive studies in the general population. The aim of this work is to develop similar terminology to that used in cognitive classifications of the general population for use in investigations of cognitive changes after anaesthesia and surgery. A multispecialty working group followed a modified Delphi procedure with no prespecified number of rounds comprised of three face-to-face meetings followed by online editing of draft versions.Two major classification guidelines [Diagnostic and Statistical Manual for Mental Disorders, fifth edition (DSM-5) and National Institute for Aging and the Alzheimer Association (NIA-AA)] are used outside of anaesthesia and surgery, and may be useful for inclusion of biomarkers in research. For clinical purposes, it is recommended to use the DSM-5 nomenclature. The working group recommends that 'perioperative neurocognitive disorders' be used as an overarching term for cognitive impairment identified in the preoperative or postoperative period. This includes cognitive decline diagnosed before operation (described as neurocognitive disorder); any form of acute event (postoperative delirium) and cognitive decline diagnosed up to 30 days after the procedure (delayed neurocognitive recovery) and up to 12 months (postoperative neurocognitive disorder).
Collapse
Affiliation(s)
- L Evered
- St Vincent's Hospital, Melbourne, Fitzroy, Victoria, Australia.,University of Melbourne, Fitzroy, Victoria, Australia
| | - B Silbert
- St Vincent's Hospital, Melbourne, Fitzroy, Victoria, Australia.,University of Melbourne, Fitzroy, Victoria, Australia
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - D A Scott
- St Vincent's Hospital, Melbourne, Fitzroy, Victoria, Australia.,University of Melbourne, Fitzroy, Victoria, Australia
| | - S T DeKosky
- Department of Neurology, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - L S Rasmussen
- Department of Anaesthesia, Center of Head and Orthopaedics, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - E S Oh
- Division of Geriatric Medicine and Gerontology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - G Crosby
- Harvard Medical School, Brigham & Women's Hospital, Boston, MA, USA
| | - M Berger
- Neurologic Outcomes Research Group, Anesthesiology Department, Duke University Medical Center, Durham, NC, USA
| | - R G Eckenhoff
- Department of Anesthesiology and Critical Care, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | | |
Collapse
|
5
|
Utianski RL, Whitwell JL, Schwarz CG, Duffy JR, Botha H, Clark HM, Machulda MM, Senjem ML, Knopman DS, Petersen RC, Jack CR, Lowe VJ, Josephs KA. Tau uptake in agrammatic primary progressive aphasia with and without apraxia of speech. Eur J Neurol 2018; 25:1352-1357. [PMID: 29935044 DOI: 10.1111/ene.13733] [Citation(s) in RCA: 12] [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: 03/22/2018] [Accepted: 06/20/2018] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND PURPOSE The non-fluent/agrammatic variant of primary progressive aphasia (agPPA) is a heterogeneous diagnosis wherein some individuals have apraxia of speech (AOS). When agPPA includes AOS, a tauopathy is the likely underlying pathology. Recently, [18F]AV-1451 was developed for the in-vivo assessment of tau. In this study, we compared patterns of tau tracer uptake in patients with agPPA with and without AOS. METHODS Nine patients with agPPA (four without AOS) underwent tau positron emission tomography imaging with [18F]AV-1451. Uptake of [18F]AV-1451 was assessed as cortical to cerebellar crus ratio (standard uptake value ratio) in cortical regions of interest measured using the MCALT atlas and compared voxel-wise in SPM12. Each patient was age- and sex-matched to three controls. RESULTS The agPPA without AOS showed uptake in the left frontal and temporal lobes, whereas agPPA with AOS showed uptake in the bilateral supplementary motor areas, frontal lobes, precuneus and precentral gyrus relative to controls. The left precentral gyrus had uptake in agPPA with AOS relative to those without AOS. CONCLUSIONS This cross-sectional study suggests that [18F]AV-1451 uptake in the precentral gyrus is implicated in AOS in agPPA.
Collapse
Affiliation(s)
- R L Utianski
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - J L Whitwell
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - C G Schwarz
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - J R Duffy
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - H Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - H M Clark
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - M M Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - M L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.,Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R C Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - V J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - K A Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| |
Collapse
|
6
|
Schulte PJ, Roberts RO, Knopman DS, Petersen RC, Hanson AC, Schroeder DR, Weingarten TN, Martin DP, Warner DO, Sprung J. Association between exposure to anaesthesia and surgery and long-term cognitive trajectories in older adults: report from the Mayo Clinic Study of Aging. Br J Anaesth 2018; 121:398-405. [PMID: 30032878 DOI: 10.1016/j.bja.2018.05.060] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 05/04/2018] [Accepted: 05/28/2018] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The link between exposure to general anaesthesia and surgery (exposure) and cognitive decline in older adults is debated. We hypothesised that it is associated with cognitive decline. METHODS We analysed the longitudinal cognitive function trajectory in a cohort of older adults. Models assessed the rate of change in cognition over time, and its association with exposure to anaesthesia and surgery. Analyses assessed whether exposure in the 20 yr before enrolment is associated with cognitive decline when compared with those unexposed, and whether post-enrolment exposure is associated with a change in cognition in those unexposed before enrolment. RESULTS We included 1819 subjects with median (25th and 75th percentiles) follow-up of 5.1 (2.7-7.6) yr and 4 (3-6) cognitive assessments. Exposure in the previous 20 yr was associated with a greater negative slope compared with not exposed (slope: -0.077 vs -0.059; difference: -0.018; 95% confidence interval: -0.032, -0.003; P=0.015). Post-enrolment exposure in those previously unexposed was associated with a change in slope after exposure (slope: -0.100 vs -0.059 for post-exposure vs pre-exposure, respectively; difference: -0.041; 95% confidence interval: -0.074, -0.008; P=0.016). Cognitive impairment could be attributed to declines in memory and attention/executive cognitive domains. CONCLUSIONS In older adults, exposure to general anaesthesia and surgery was associated with a subtle decline in cognitive z-scores. For an individual with no prior exposure and with exposure after enrolment, the decline in cognitive function over a 5 yr period after the exposure would be 0.2 standard deviations more than the expected decline as a result of ageing. This small cognitive decline could be meaningful for individuals with already low baseline cognition.
Collapse
Affiliation(s)
- P J Schulte
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - R O Roberts
- Division of Epidemiology, Mayo Clinic College of Medicine and Science, Rochester, MN, USA; Department of Neurology, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - D S Knopman
- Department of Neurology, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - R C Petersen
- Division of Epidemiology, Mayo Clinic College of Medicine and Science, Rochester, MN, USA; Department of Neurology, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - A C Hanson
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - D R Schroeder
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - T N Weingarten
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - D P Martin
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - D O Warner
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - J Sprung
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA.
| |
Collapse
|
7
|
Evered L, Silbert B, Knopman DS, Scott DA, DeKosky ST, Rasmussen LS, Oh ES, Crosby G, Berger M, Eckenhoff RG. Recommendations for the nomenclature of cognitive change associated with anaesthesia and surgery-2018. Br J Anaesth 2018; 121:1005-1012. [PMID: 30336844 DOI: 10.1016/j.bja.2017.11.087] [Citation(s) in RCA: 376] [Impact Index Per Article: 62.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Revised: 09/12/2017] [Accepted: 10/02/2017] [Indexed: 12/11/2022] Open
Abstract
Cognitive change affecting patients after anaesthesia and surgery has been recognised for more than 100 yr. Research into cognitive change after anaesthesia and surgery accelerated in the 1980s when multiple studies utilised detailed neuropsychological testing for assessment of cognitive change after cardiac surgery. This body of work consistently documented decline in cognitive function in elderly patients after anaesthesia and surgery, and cognitive changes have been identified up to 7.5 yr afterwards. Importantly, other studies have identified that the incidence of cognitive change is similar after non-cardiac surgery. Other than the inclusion of non-surgical control groups to calculate postoperative cognitive dysfunction, research into these cognitive changes in the perioperative period has been undertaken in isolation from cognitive studies in the general population. The aim of this work is to develop similar terminology to that used in cognitive classifications of the general population for use in investigations of cognitive changes after anaesthesia and surgery. A multispecialty working group followed a modified Delphi procedure with no prespecified number of rounds comprised of three face-to-face meetings followed by online editing of draft versions. Two major classification guidelines [Diagnostic and Statistical Manual for Mental Disorders, fifth edition (DSM-5) and National Institute for Aging and the Alzheimer Association (NIA-AA)] are used outside of anaesthesia and surgery, and may be useful for inclusion of biomarkers in research. For clinical purposes, it is recommended to use the DSM-5 nomenclature. The working group recommends that 'perioperative neurocognitive disorders' be used as an overarching term for cognitive impairment identified in the preoperative or postoperative period. This includes cognitive decline diagnosed before operation (described as neurocognitive disorder); any form of acute event (postoperative delirium) and cognitive decline diagnosed up to 30 days after the procedure (delayed neurocognitive recovery) and up to 12 months (postoperative neurocognitive disorder).
Collapse
Affiliation(s)
- L Evered
- St Vincent's Hospital, Melbourne, Fitzroy, Victoria, Australia; University of Melbourne, Fitzroy, Victoria, Australia.
| | - B Silbert
- St Vincent's Hospital, Melbourne, Fitzroy, Victoria, Australia; University of Melbourne, Fitzroy, Victoria, Australia
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - D A Scott
- St Vincent's Hospital, Melbourne, Fitzroy, Victoria, Australia; University of Melbourne, Fitzroy, Victoria, Australia
| | - S T DeKosky
- Department of Neurology, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - L S Rasmussen
- Department of Anaesthesia, Center of Head and Orthopaedics, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - E S Oh
- Division of Geriatric Medicine and Gerontology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - G Crosby
- Harvard Medical School, Brigham & Women's Hospital, Boston, MA, USA
| | - M Berger
- Neurologic Outcomes Research Group, Anesthesiology Department, Duke University Medical Center, Durham, NC, USA
| | - R G Eckenhoff
- Department of Anesthesiology and Critical Care, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | | |
Collapse
|
8
|
Ali F, Whitwell JL, Martin PR, Senjem ML, Knopman DS, Jack CR, Lowe VJ, Petersen RC, Boeve BF, Josephs KA. [ 18F] AV-1451 uptake in corticobasal syndrome: the influence of beta-amyloid and clinical presentation. J Neurol 2018; 265:1079-1088. [PMID: 29497818 DOI: 10.1007/s00415-018-8815-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [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: 10/29/2017] [Revised: 02/09/2018] [Accepted: 02/26/2018] [Indexed: 12/12/2022]
Abstract
Corticobasal syndrome (CBS) is a phenotypic manifestation of diverse pathologies, including Alzheimer's disease and 4-repeat tauopathies. Predicting pathology in CBS is unreliable and, hence, molecular neuroimaging may prove to be useful. The aim of this study was to assess regional patterns of uptake on [18F] AV-1451 PET in CBS and determine whether patterns of uptake differ according to beta-amyloid deposition or differing clinical presentations. Fourteen patients meeting criteria for CBS underwent Pittsburgh Compound B (PiB) and [18F] AV-1451 PET. Seven patients presented as CBS and seven presented with apraxia of speech (AOS) and later evolved into CBS. A global PiB summary was calculated and used to classify patients as PiB (-) or PiB (+). AV-1451 uptake was calculated in fourteen regions-of-interest, with values divided by uptake in cerebellar crus grey matter to generate standard uptake value ratios. AV-1451 uptake was considered elevated if it fell above the 95th percentile from a group of 476 cognitively unimpaired normal controls. Six of the 14 CBS patients (43%) were PiB (+), with three of these patients showing strikingly elevated AV-1451 uptake across many cortical regions. Of the eight PiB (-) patients, only those with AOS showed elevated AV-1451 uptake in supplementary motor area and precentral cortex compared to controls. No region of elevated AV-1451 uptake were observed in PiB (-) typical CBS patients without AOS. These results suggest that regional [18F] AV-1451 is variable in CBS and depends on the presence of beta-amyloid as well as clinical presentation such as AOS. PiB (+) CBS does not necessarily reflect underlying Alzheimer's disease; however, the possibility some of these patients will evolve into Alzheimer's disease over time cannot be excluded.
Collapse
Affiliation(s)
- F Ali
- Department of Neurology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA.
| | - J L Whitwell
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - P R Martin
- Department of Health Sciences Research (Biostatistics), Mayo Clinic, Rochester, MN, USA
| | - M L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - D S Knopman
- Department of Neurology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - V J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - R C Petersen
- Department of Neurology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA
| | - B F Boeve
- Department of Neurology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA
| | - K A Josephs
- Department of Neurology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA
| |
Collapse
|
9
|
Bressler J, Yu B, Mosley TH, Knopman DS, Gottesman RF, Alonso A, Sharrett AR, Wruck LM, Boerwinkle E. Metabolomics and cognition in African American adults in midlife: the atherosclerosis risk in communities study. Transl Psychiatry 2017; 7:e1173. [PMID: 28934192 PMCID: PMC5538110 DOI: 10.1038/tp.2017.118] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Revised: 04/05/2017] [Accepted: 04/20/2017] [Indexed: 12/21/2022] Open
Abstract
Clinical studies have shown alterations in metabolic profiles when patients with mild cognitive impairment and Alzheimer's disease dementia were compared to cognitively normal subjects. Associations between 204 serum metabolites measured at baseline (1987-1989) and cognitive change were investigated in 1035 middle-aged community-dwelling African American participants in the biracial Atherosclerosis Risk in Communities (ARIC) Study. Cognition was evaluated using the Delayed Word Recall Test (DWRT; verbal memory), the Digit Symbol Substitution Test (DSST; processing speed) and the Word Fluency Test (WFT; verbal fluency) at visits 2 (1990-1992) and 4 (1996-1998). In addition, Cox regression was used to analyze the metabolites as predictors of incident hospitalized dementia between baseline and 2011. There were 141 cases among 1534 participants over a median 17.1-year follow-up period. After adjustment for established risk factors, one standard deviation increase in N-acetyl-1-methylhistidine was significantly associated with greater 6-year change in DWRT scores (β=-0.66 words; P=3.65 × 10-4). Two metabolites (one unnamed and a long-chain omega-6 polyunsaturated fatty acid found in vegetable oils (docosapentaenoate (DPA, 22:5 n-6)) were significantly associated with less decline on the DSST (DPA: β=1.25 digit-symbol pairs, P=9.47 × 10-5). Two unnamed compounds and three sex steroid hormones were associated with an increased risk of dementia (all P<3.9 × 10-4). The association of 4-androstene-3beta, 17beta-diol disulfate 1 with dementia was replicated in European Americans. These results demonstrate that screening the metabolome in midlife can detect biologically plausible biomarkers that may improve risk stratification for cognitive impairment at older ages.
Collapse
Affiliation(s)
- J Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - B Yu
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - T H Mosley
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R F Gottesman
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - A Alonso
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - A R Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - L M Wruck
- Department of Biostatistics, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - E Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| |
Collapse
|
10
|
Carvalho DZ, St. Louis EK, Boeve BF, Knopman DS, Lowe VJ, Roberts RO, Mielke MM, Przybelski SA, Petersen RC, Jack CR, Vemuri P. 0273 BASELINE EXCESSIVE DAYTIME SLEEPINESS ASSOCIATED WITH AN INCREASE IN BRAIN METABOLISM IN NON-DEMENTED ELDERLY: A LONGITUDINAL FDG-PET STUDY. Sleep 2017. [DOI: 10.1093/sleepj/zsx050.272] [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: 11/12/2022] Open
|
11
|
Jung Y, Silber MH, Tippmann-Peikert M, St Louis EK, Smith GE, Ferman TJ, Knopman DS, Petersen RC, Boeve BF. 1154 THE EFFECTS OF CPAP ON COGNITIVE AND FUNCTIONAL MEASURES IN PATIENTS WITH MILD COGNITIVE IMPAIRMENT AND ALZHEIMER’S DEMENTIA. Sleep 2017. [DOI: 10.1093/sleepj/zsx050.1153] [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
|
12
|
Tacik P, Sanchez-Contreras M, DeTure M, Murray ME, Rademakers R, Ross OA, Wszolek ZK, Parisi JE, Knopman DS, Petersen RC, Dickson DW. Clinicopathologic heterogeneity in frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17) due to microtubule-associated protein tau (MAPT) p.P301L mutation, including a patient with globular glial tauopathy. Neuropathol Appl Neurobiol 2017; 43:200-214. [PMID: 27859539 DOI: 10.1111/nan.12367] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [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: 08/19/2016] [Revised: 10/13/2016] [Accepted: 10/31/2016] [Indexed: 12/11/2022]
Abstract
AIM The p.P301L mutation in microtubule-associated protein tau (MAPT) is a common cause of frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17). We compare clinicopathologic features of five unrelated and three related (brother, sister and cousin) patients with FTDP-17 due to p.P301L mutation. METHODS Genealogical, clinical, neuropathologic and genetic data were reviewed from eight individuals. RESULTS The series consisted of five men and three women with an average age of death of 58 years (52-65 years) and average disease duration of 9 years (3-14 years). The first symptoms were those of behavioural variant frontotemporal dementia in seven patients and semantic variant of primary progressive aphasia in one. Three patients were homozygous for the MAPT H1 haplotype; five had H1/H2 genotype. The apolipoprotein E genotype was ϵ3/ϵ3 in seven and ϵ3/ϵ4 in one. The average brain weight was 1015 g (876-1188 g). All had frontotemporal lobar or more diffuse cortical atrophy. Except for one patient, the hippocampus and parahippocampal gyrus had minimal atrophy, whereas there was atrophy of middle and inferior temporal gyri. Dentate fascia neuronal dispersion was identified in three patients, two of whom had epilepsy. In one patient there was extensive white matter tau involvement with Gallyas-positive globular glial inclusions typical of globular glial tauopathy (GGT). CONCLUSIONS This clinicopathologic study shows inter- and intra-familial clinicopathologic heterogeneity of FTDP-17 due to MAPT p.P301L mutation, including GGT in one patient.
Collapse
Affiliation(s)
- P Tacik
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | | | - M DeTure
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - M E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - R Rademakers
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - O A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Z K Wszolek
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - J E Parisi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R C Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - D W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| |
Collapse
|
13
|
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.
Collapse
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
| |
Collapse
|
14
|
Whitwell JL, Boeve BF, Weigand SD, Senjem ML, Gunter JL, Baker MC, DeJesus-Hernandez M, Knopman DS, Wszolek ZK, Petersen RC, Rademakers R, Jack CR, Josephs KA. Brain atrophy over time in genetic and sporadic frontotemporal dementia: a study of 198 serial magnetic resonance images. Eur J Neurol 2015; 22:745-52. [PMID: 25683866 DOI: 10.1111/ene.12675] [Citation(s) in RCA: 89] [Impact Index Per Article: 9.9] [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: 10/23/2014] [Accepted: 12/15/2014] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND PURPOSE The aim of our study was to determine the utility of longitudinal magnetic resonance imaging (MRI) measurements as potential biomarkers in the main genetic variants of frontotemporal dementia (FTD), including microtubule-associated protein tau (MAPT) and progranulin (GRN) mutations and C9ORF72 repeat expansions, as well as sporadic FTD. METHODS In this longitudinal study, 58 subjects were identified who had at least two MRI and MAPT mutations (n = 21), GRN mutations (n = 11), C9ORF72 repeat expansions (n = 11) or sporadic FTD (n = 15). A total of 198 serial MRI measurements were analyzed. Rates of whole brain atrophy were calculated using the boundary shift integral. Regional rates of atrophy were calculated using tensor-based morphometry. Sample size estimates were calculated. RESULTS Progressive brain atrophy was observed in all groups, with fastest rates of whole brain atrophy in GRN, followed by sporadic FTD, C9ORF72 and MAPT. All variants showed greatest rates in the frontal and temporal lobes, with parietal lobes also strikingly affected in GRN. Regional rates of atrophy across all lobes were greater in GRN compared to the other groups. C9ORF72 showed greater rates of atrophy in the left cerebellum and right occipital lobe than MAPT, and sporadic FTD showed greater rates in the anterior cingulate than C9ORF72 and MAPT. Sample size estimates were lowest using temporal lobe rates in GRN, ventricular rates in MAPT and C9ORF72, and whole brain rates in sporadic FTD. CONCLUSION These data support the utility of using rates of atrophy as outcome measures in future drug trials in FTD and show that different imaging biomarkers may offer advantages in the different variants of FTD.
Collapse
Affiliation(s)
- J L Whitwell
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
15
|
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.
Collapse
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:
| |
Collapse
|
16
|
Gross RA, Knopman DS, Amato AA, Cascino GD, Ciccarelli O, Corboy JR, Elkind MSV, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our Reviewers. Neurology 2014. [DOI: 10.1212/wnl.0000000000001148] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
|
17
|
Gross RA, Knopman DS, Amato AA, Cascino GD, Ciccarelli O, Corboy JR, Elkind MSV, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our Reviewers. Neurology 2014. [DOI: 10.1212/wnl.0000000000000633] [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
|
18
|
Schneider ALC, Lutsey PL, Alonso A, Gottesman RF, Sharrett AR, Carson KA, Gross M, Post WS, Knopman DS, Mosley TH, Michos ED. Vitamin D and cognitive function and dementia risk in a biracial cohort: the ARIC Brain MRI Study. Eur J Neurol 2014; 21:1211-8, e69-70. [PMID: 24846449 DOI: 10.1111/ene.12460] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [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: 02/05/2014] [Accepted: 04/07/2014] [Indexed: 02/04/2023]
Abstract
BACKGROUND AND PURPOSE Some recent studies in older, largely white populations suggest that vitamin D, measured by 25-hydroxyvitamin D [25(OH)D], is important for cognition, but such results may be affected by reverse causation. Measuring 25(OH)D in late middle age before poor cognition affects behavior may provide clearer results. METHODS This was a prospective cohort analysis of 1652 participants (52% white, 48% black) in the Atherosclerosis Risk in Communities (ARIC) Brain MRI Study. 25(OH)D was measured from serum collected in 1993-1995. Cognition was measured by the delayed word recall test (DWRT), the digit symbol substitution test (DSST) and the word fluency test (WFT). Dementia hospitalization was defined by ICD-9 codes. Adjusted linear, logistic and Cox proportional hazards models were used. RESULTS Mean age of participants was 62 years and 60% were female. Mean 25(OH)D was higher in whites than blacks (25.5 vs. 17.3 ng/ml, P < 0.001). Lower 25(OH)D was not associated with lower baseline scores or with greater DWRT, DSST or WFT decline over a median of 3 or 10 years of follow-up (P > 0.05). Over a median of 16.6 years, there were 145 incident hospitalized dementia cases. Although not statistically significant, lower levels of 25(OH)D were suggestive of an association with increased dementia risk [hazard ratio for lowest versus highest race-specific tertile: whites 1.32 (95% confidence interval 0.69, 2.55); blacks 1.53 (95% confidence interval 0.84, 2.79)]. CONCLUSIONS In contrast to prior studies performed in older white populations, our study of late middle age white and black participants did not find significant associations between lower levels of 25(OH)D with lower cognitive test scores at baseline, change in scores over time or dementia risk.
Collapse
Affiliation(s)
- A L C Schneider
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
19
|
Gross RA, Knopman DS, Amato AA, Cascino GD, Corboy JR, Elkind MSV, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our Reviewers. Neurology 2013. [DOI: 10.1212/01.wnl.0000438249.50033.41] [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: 11/15/2022] Open
|
20
|
Gross RA, Knopman DS, Cascino GD, Corboy JR, Elkind MSV, Engel AG, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our Reviewers. Neurology 2013. [DOI: 10.1212/wnl.0b013e31829d3e4e] [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
|
21
|
|
22
|
Graff-Radford NR, Knopman DS, Penman AD, Coker LH, Mosley TH. Do systolic BP and pulse pressure relate to ventricular enlargement? Eur J Neurol 2013; 20:720-4. [PMID: 23294486 DOI: 10.1111/ene.12067] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2012] [Accepted: 11/07/2012] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND PURPOSE To evaluate the association between systolic, diastolic and pulse pressure, and increase in ventricular size (VS). Observations in laboratory animals suggest intraventricular pulse pressure (systolic-diastolic) may play a role in ventricular enlargement. METHODS Initial magnetic resonance (MR) scans and vascular risk factors evaluation were performed in 1812 Atherosclerosis Risk in Communities participants in 1994-1995. In 2004-2006, 1130 participants underwent repeat MR. VS was rated using a validated nine-point scale. Multiple logistic regression analysis assessed association between blood pressure measures and pulse pressure, and the change between the MR scans of VS controlling for age, sex and race. RESULTS At baseline 1112 participants (385 black women, 200 black men, 304 white women and 223 white men) had a mean age of 61.7 ± 4.3 years. In adjusted models pulse pressure at baseline was associated with an increase in VS [odds ratio (OR) 1.19, 95% confidence interval (CI) 1.01-1.40], as was systolic pressure (OR 1.28, 95% CI 1.03-1.58). CONCLUSIONS Systolic pressure and pulse pressure are associated with future development of increased VS. The findings are consistent with the animal literature that increased pulse pressure predisposes to risk of future increased VS. High pulse pressure might play a role in the pathogenesis of normal pressure hydrocephalus.
Collapse
|
23
|
Gross RA, Knopman DS, Cascino GD, Corboy JR, Elkind MSV, Engel AG, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our Reviewers. Neurology 2012. [DOI: 10.1212/wnl.0b013e31827ec551] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
|
24
|
|
25
|
Gross RA, Knopman DS, Cascino GD, Corboy JR, Elkind MSV, Engel AG, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our Reviewers. Neurology 2012. [DOI: 10.1212/wnl.0b013e3182619224] [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
|
26
|
Knopman DS, Jack CR, Wiste HJ, Weigand SD, Vemuri P, Lowe V, Kantarci K, Gunter JL, Senjem ML, Ivnik RJ, Roberts RO, Boeve BF, Petersen RC. Short-term clinical outcomes for stages of NIA-AA preclinical Alzheimer disease. Neurology 2012; 78:1576-82. [PMID: 22551733 DOI: 10.1212/wnl.0b013e3182563bbe] [Citation(s) in RCA: 203] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE Recommendations for the diagnosis of preclinical Alzheimer disease (AD) have been formulated by a workgroup of the National Institute on Aging and Alzheimer's Association. Three stages of preclinical AD were described. Stage 1 is characterized by abnormal levels of β-amyloid. Stage 2 represents abnormal levels of β-amyloid and evidence of brain neurodegeneration. Stage 3 includes the features of stage 2 plus subtle cognitive changes. Stage 0, not explicitly defined in the criteria, represents subjects with normal biomarkers and normal cognition. The ability of the recommended criteria to predict progression to cognitive impairment is the crux of their validity. METHODS Using previously developed operational definitions of the 3 stages of preclinical AD, we examined the outcomes of subjects from the Mayo Clinic Study of Aging diagnosed as cognitively normal who underwent brain MRI or [(18)F]fluorodeoxyglucose and Pittsburgh compound B PET, had global cognitive test scores, and were followed for at least 1 year. RESULTS Of the 296 initially normal subjects, 31 (10%) progressed to a diagnosis of mild cognitive impairment (MCI) or dementia (27 amnestic MCI, 2 nonamnestic MCI, and 2 non-AD dementias) within 1 year. The proportion of subjects who progressed to MCI or dementia increased with advancing stage (stage 0, 5%; stage 1, 11%; stage 2, 21%; stage 3, 43%; test for trend, p < 0.001). CONCLUSIONS Despite the short follow-up period, our operationalization of the new preclinical AD recommendations confirmed that advancing preclinical stage led to higher proportions of subjects who progressed to MCI or dementia.
Collapse
Affiliation(s)
- D S Knopman
- Department of Neurology, Mayo Clinic Alzheimer’s Disease Research Center, Rochester, MN, USA.
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
27
|
Perry DC, Whitwell JL, Boeve BF, Pankratz VS, Knopman DS, Petersen RC, Jack CR, Josephs KA. Voxel-based morphometry in patients with obsessive-compulsive behaviors in behavioral variant frontotemporal dementia. Eur J Neurol 2012; 19:911-7. [PMID: 22284815 DOI: 10.1111/j.1468-1331.2011.03656.x] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND PURPOSE Obsessions and compulsive (OC) behaviors are a frequent feature of behavioral variant frontotemporal dementia (bvFTD), but their structural correlates have not been definitively established. METHODS Patients with bvFTD presenting to the Mayo Clinic Alzheimer's Disease Research Center were recruited. Each patient's caregiver was given the Yale-Brown Obsessive-Compulsive scale (YBOCS) to document the type and presence of OC behaviors and to rate their severity. All subjects underwent standardized magnetic resonance imaging (MRI) that was evaluated using voxel-based morphometry (VBM). Seventeen patients with bvFTD were recruited, and 11 were included in the study and compared with 11 age- and gender-matched controls. Six were excluded for lack of MRI at the time of survey or a pre-existing neurodegenerative condition. RESULTS Nine of the 11 reported OC behaviors, with the most frequent compulsions being checking, hoarding, ordering/arranging, repeating rituals, and cleaning. In the VBM analysis, total YBOCS score correlated with gray matter loss in the bilateral globus pallidus, left putamen, and in the lateral temporal lobe, particularly the left middle and inferior temporal gyri (P < 0.001 uncorrected for multiple comparisons). CONCLUSIONS Obsessive-compulsive behaviors were frequent among these patients. The correlation with basal ganglia atrophy may point to involvement of frontal subcortical neuronal networks. Left lateral temporal lobe volume loss probably reflects the number of MAPT mutation patients included but also provides additional data implicating temporal lobe involvement in OC behaviors.
Collapse
Affiliation(s)
- D C Perry
- Department of Neurology, Mayo Clinic, Rochester, MN, USA.
| | | | | | | | | | | | | | | |
Collapse
|
28
|
Roberts RO, Geda YE, Knopman DS, Cha RH, Pankratz VS, Boeve BF, Tangalos EG, Ivnik RJ, Rocca WA, Petersen RC. The incidence of MCI differs by subtype and is higher in men: the Mayo Clinic Study of Aging. Neurology 2012; 78:342-51. [PMID: 22282647 DOI: 10.1212/wnl.0b013e3182452862] [Citation(s) in RCA: 196] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE Although incidence rates for mild cognitive impairment (MCI) have been reported, few studies were specifically designed to measure the incidence of MCI and its subtypes using published criteria. We estimated the incidence of amnestic MCI (aMCI) and nonamnestic MCI (naMCI) in men and women separately. METHODS A population-based prospective cohort of Olmsted County, MN, residents ages 70-89 years on October 1, 2004, underwent baseline and 15-month interval evaluations that included the Clinical Dementia Rating scale, a neurologic evaluation, and neuropsychological testing. A panel of examiners blinded to previous diagnoses reviewed data at each serial evaluation to assess cognitive status according to published criteria. RESULTS Among 1,450 subjects who were cognitively normal at baseline, 296 developed MCI. The age- and sex-standardized incidence rate of MCI was 63.6 (per 1,000 person-years) overall, and was higher in men (72.4) than women (57.3) and for aMCI (37.7) than naMCI (14.7). The incidence rate of aMCI was higher for men (43.9) than women (33.3), and for subjects with ≤12 years of education (42.6) than higher education (32.5). The risk of naMCI was also higher for men (20.0) than women (10.9) and for subjects with ≤12 years of education (20.3) than higher education (10.2). CONCLUSIONS The incidence rates for MCI are substantial. Differences in incidence rates by clinical subtype and by sex suggest that risk factors for MCI should be investigated separately for aMCI and naMCI, and in men and women.
Collapse
Affiliation(s)
- R O Roberts
- Division of Epidemiology, Department of Health Sciences Research, College of Medicine, Mayo Clinic, Rochester, MN, USA.
| | | | | | | | | | | | | | | | | | | |
Collapse
|
29
|
Gross RA, Knopman DS, Cascino GD, Corboy JR, Elkind MSV, Engel AG, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our Reviewers. Neurology 2011. [DOI: 10.1212/wnl.0b013e31824154d9] [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
|
30
|
Kantarci K, Lowe V, Przybelski SA, Weigand SD, Senjem ML, Ivnik RJ, Preboske GM, Roberts R, Geda YE, Boeve BF, Knopman DS, Petersen RC, Jack CR. APOE modifies the association between Aβ load and cognition in cognitively normal older adults. Neurology 2011; 78:232-40. [PMID: 22189452 DOI: 10.1212/wnl.0b013e31824365ab] [Citation(s) in RCA: 129] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
OBJECTIVE To determine the relationship between β-amyloid (Aβ) load as measured by [(11)C]-Pittsburgh compound B (PiB) PET and cognitive function in cognitively normal older adults. METHODS We studied 408 cognitively normal older adults who participated in the population-based Mayo Clinic Study of Aging (MCSA) from January 2009 through March 2011. The participants underwent PiB PET and neuropsychometric testing within 6 months. The association between PiB retention and cognitive function was measured by partial correlation and an interaction with APOE status was tested using linear regression after adjusting for age, sex, and education. RESULTS Higher PiB retention was associated with cognitive performance (Spearman partial r = -0.18; p < 0.01), specifically the memory, language, attention/executive, and visual-spatial processing domains in the whole group of participants. The association between PiB retention and cognition was modified by the APOE status on linear regression analysis even after controlling for the differences in the distribution of PiB values among APOE ε4 carriers and noncarriers (p = 0.02). Cognitive performance was associated with the Aβ deposition in the frontal, temporal, and parietal lobe association cortices in APOE ε4 carriers on SPM analysis (p < 0.001). CONCLUSION There is a modest association between PiB retention and cognitive function in cognitively normal older adults and this relationship between Aβ load and cognitive function is modified by APOE status. Whereas Aβ load is associated with greater cognitive impairment in APOE ε4 carriers, the cognitive function in APOE ε4 noncarriers is influenced less by the Aβ load, suggesting that APOE isoforms modulate the harmful effects of Aβ on cognitive function.
Collapse
Affiliation(s)
- K Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
31
|
Frank SA, Megerian JT, Baskin PK, Knopman DS, Pieper K, Quimby S, Gross RA. Reporting potential bias: Neurology's evolving policies. Neurology 2011; 77:1500; author reply 1500-1. [DOI: 10.1212/wnl.0b013e318230afba] [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
|
32
|
Jones DT, Machulda MM, Vemuri P, McDade EM, Zeng G, Senjem ML, Gunter JL, Przybelski SA, Avula RT, Knopman DS, Boeve BF, Petersen RC, Jack CR. Age-related changes in the default mode network are more advanced in Alzheimer disease. Neurology 2011; 77:1524-31. [PMID: 21975202 DOI: 10.1212/wnl.0b013e318233b33d] [Citation(s) in RCA: 255] [Impact Index Per Article: 19.6] [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 To investigate age-related default mode network (DMN) connectivity in a large cognitively normal elderly cohort and in patients with Alzheimer disease (AD) compared with age-, gender-, and education-matched controls. METHODS We analyzed task-free-fMRI data with both independent component analysis and seed-based analysis to identify anterior and posterior DMNs. We investigated age-related changes in connectivity in a sample of 341 cognitively normal subjects. We then compared 28 patients with AD with 56 cognitively normal noncarriers of the APOE ε4 allele matched for age, education, and gender. RESULTS The anterior DMN shows age-associated increases and decreases in fontal lobe connectivity, whereas the posterior DMN shows mainly age-associated declines in connectivity throughout. Relative to matched cognitively normal controls, subjects with AD display an accelerated pattern of the age-associated changes described above, except that the declines in frontal lobe connectivity did not reach statistical significance. These changes survive atrophy correction and are correlated with cognitive performance. CONCLUSIONS The results of this study indicate that the DMN abnormalities observed in patients with AD represent an accelerated aging pattern of connectivity compared with matched controls.
Collapse
Affiliation(s)
- D T Jones
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
33
|
Kim SYH, Kim HM, Knopman DS, De Vries R, Damschroder L, Appelbaum PS. Effect of public deliberation on attitudes toward surrogate consent for dementia research. Neurology 2011; 77:2097-104. [PMID: 21975207 DOI: 10.1212/wnl.0b013e31823648cb] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [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 To assess the informed, deliberative views of the older general public toward a policy of allowing surrogate consent for Alzheimer disease (AD) research. METHODS A total of 503 persons aged 50+ recruited by random digit dialing were randomly assigned to 1 of 3 groups: deliberation, education, or control. The deliberation group attended an all-day education/peer deliberation session; the education group received written information only. Participants were surveyed at baseline, after deliberation session (or equivalent time), and 1 month after the session, regarding their attitudes toward a policy of allowing surrogate consent for research studies of varying risks and potential benefits (a lumbar puncture study, a drug randomized controlled trial, a vaccine randomized controlled trial, and an early phase gene transfer trial). RESULTS At baseline, a policy of surrogate consent for AD research was supported by 55%-91%, depending on the scenario. The education group had a transient increase in support for one research scenario after receiving the information materials. In the deliberation group, support for surrogate consent was higher after deliberation for all scenarios (67% to 97%), with much of the increase sustained 1 month after the deliberation session. No changes occurred in the control group. The study's limitations include self-selection of participants due to the demanding nature of attendance at the deliberation sessions. CONCLUSIONS This sample of the older general public generally supported a policy of surrogate consent for AD research at baseline. Their support increased with democratic deliberation involving informed, in-depth exploration of the relevant scientific and ethical issues.
Collapse
Affiliation(s)
- S Y H Kim
- Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor 48109, USA
| | | | | | | | | | | |
Collapse
|
34
|
Kantarci K, Lowe V, Przybelski SA, Senjem ML, Weigand SD, Ivnik RJ, Roberts R, Geda YE, Boeve BF, Knopman DS, Petersen RC, Jack CR. Magnetic resonance spectroscopy, β-amyloid load, and cognition in a population-based sample of cognitively normal older adults. Neurology 2011; 77:951-8. [PMID: 21865577 DOI: 10.1212/wnl.0b013e31822dc7e1] [Citation(s) in RCA: 49] [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
OBJECTIVE To determine the relationship between proton magnetic resonance spectroscopy ((1)H MRS) metabolites and β-amyloid (Aβ) load and the effects of Aβ load on the association between (1)H MRS metabolites and cognitive function in cognitively normal older adults. METHODS We studied 311 cognitively normal older adults who participated in the population-based Mayo Clinic Study of Aging from January 2009 through September 2010. Participants underwent (11)C-Pittsburgh compound B (PiB) PET, (1)H MRS from the posterior cingulate gyri, and neuropsychometric testing to assess memory, attention/executive, language, and visual-spatial domain functions within 6 months. Partial Spearman rank order correlations were adjusted for age, sex, and education. RESULTS Higher PiB retention was associated with abnormal elevations in myoinositol (mI)/creatine (Cr) (partial r(s) = 0.17; p = 0.003) and choline (Cho)/Cr (partial r(s) = 0.13; p = 0.022) ratios. Higher Cho/Cr was associated with worse performance on Auditory Verbal Learning Test Delayed Recall (partial r(s) = -0.12; p = 0.04), Trail Making Test Part B (partial r(s) = 0.12; p = 0.04), Wechsler Adult Intelligence Scale-Revised (WAIS-R) Digit Symbol (partial r(s) = -0.18; p < 0.01), and WAIS-R Block Design (partial r(s) = -0.12; p = 0.03). Associations between (1)H MRS metabolites and cognitive function were not different among participants with high vs low PiB retention. CONCLUSION In cognitively normal older adults, the (1)H MRS metabolite ratios mI/Cr and Cho/Cr are associated with the preclinical pathologic processes in the Alzheimer disease cascade. Higher Cho/Cr is associated with worse performance on domain-specific cognitive tests independent of Aβ load, suggesting that Cho/Cr elevation may also be dependent on other preclinical dementia pathologies characterized by Cho/Cr elevation such as Lewy body or ischemic vascular disease in addition to Aβ load.
Collapse
Affiliation(s)
- Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA.
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
35
|
Whitwell JL, Josephs KA, Avula R, Tosakulwong N, Weigand SD, Senjem ML, Vemuri P, Jones DT, Gunter JL, Baker M, Wszolek ZK, Knopman DS, Rademakers R, Petersen RC, Boeve BF, Jack CR. Altered functional connectivity in asymptomatic MAPT subjects: a comparison to bvFTD. Neurology 2011; 77:866-74. [PMID: 21849646 DOI: 10.1212/wnl.0b013e31822c61f2] [Citation(s) in RCA: 108] [Impact Index Per Article: 8.3] [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 To determine whether functional connectivity is altered in subjects with mutations in the microtubule associated protein tau (MAPT) gene who were asymptomatic but were destined to develop dementia, and to compare these findings to those in subjects with behavioral variant frontotemporal dementia (bvFTD). METHODS In this case-control study, we identified 8 asymptomatic subjects with mutations in MAPT and 8 controls who screened negative for mutations in MAPT. Twenty-one subjects with a clinical diagnosis of bvFTD were also identified and matched to 21 controls. All subjects had resting-state fMRI. In-phase functional connectivity was assessed between a precuneus seed in the default mode network (DMN) and a fronto-insular cortex seed in the salience network, and the rest of the brain. Atlas-based parcellation was used to assess functional connectivity and gray matter volume across specific regions of interest. RESULTS The asymptomatic MAPT subjects and subjects with bvFTD showed altered functional connectivity in the DMN, with reduced in-phase connectivity in lateral temporal lobes and medial prefrontal cortex, compared to controls. Increased in-phase connectivity was also observed in both groups in the medial parietal lobe. Only the bvFTD group showed altered functional connectivity in the salience network, with reduced connectivity in the fronto-insular cortex and anterior cingulate. Gray matter loss was observed across temporal, frontal, and parietal regions in bvFTD, but not in the asymptomatic MAPT subjects. CONCLUSIONS Functional connectivity in the DMN is altered in MAPT subjects before the occurrence of both atrophy and clinical symptoms, suggesting that changes in functional connectivity are early features of the disease.
Collapse
Affiliation(s)
- J L Whitwell
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
36
|
Abstract
OBJECTIVE To determine whether clinical and demographic features are associated with prognosis in patients with frontotemporal dementia and motor neuron disease (FTD-MND). METHODS This was a case series of FTD-MND categorized according to behavioral- or language-dominant symptoms at presentation and throughout the disease course. Demographic, clinical, imaging, and survival data were analyzed with respect to dominant FTD-MND type. Voxel-based morphometry was used to assess and compare regional patterns of atrophy in behavioral- and language-dominant FTD-MND types. RESULTS Of the 56 patients with FTD-MND who were identified, 31 had dominant behavioral symptoms and 25 had dominant language symptoms; 53 patients had died. A survival difference was present between types, with patients with behavioral-dominant symptoms surviving 506 days longer than patients with language-dominant symptoms (mean 1,397 vs 891 days; p = 0.002). There was also a difference in time from diagnosis to death (p = 0.02) between groups. Patients with language-dominant disease were more likely to have bulbar-onset than limb-onset motor neuron disease (MND) (p = 0.01). There was a similar pattern of frontal and temporal lobe atrophy in both types, although there was some evidence for the behavioral type to have more frontal atrophy and the language type to have more left temporal atrophy. CONCLUSIONS In our series of patients with FTD-MND, language-dominant FTD-MND was associated with bulbar-onset MND and a shorter survival. There was also evidence that the dominant FTD-MND type is related to differences in brain atrophy patterns.
Collapse
Affiliation(s)
- E A Coon
- Department of Behavioral Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | | |
Collapse
|
37
|
Whitwell JL, Weigand SD, Gunter JL, Boeve BF, Rademakers R, Baker M, Knopman DS, Wszolek ZK, Petersen RC, Jack CR, Josephs KA. Trajectories of brain and hippocampal atrophy in FTD with mutations in MAPT or GRN. Neurology 2011; 77:393-8. [PMID: 21753165 DOI: 10.1212/wnl.0b013e318227047f] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.2] [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 To use multiple serial MRI to assess rates and trajectories of brain and hippocampal atrophy in subjects with frontotemporal dementia (FTD) with progranulin (GRN) or microtubule-associated protein tau (MAPT) gene mutations. METHODS In this case-control study, we identified 8 subjects with mutations in GRN and 12 subjects with mutations in MAPT who had at least 2 serial MRIs. Serial MRIs were registered to baseline MRI for each subject using 9 df registration and rate of whole brain atrophy was calculated using the boundary-shift integral. Hippocampal volume was measured using Freesurfer. Mixed effects linear regression models were used to model volume change over time in both groups after adjusting for head size, age at baseline, and disease duration at baseline. RESULTS The annual rate of whole brain atrophy in the MAPT subjects was 2.4% per year (95% confidence interval [CI] 1.9-2.8). The GRN subjects showed a higher rate of whole brain atrophy at 3.5% per year (95% CI 2.8-4.2; p = 0.01). Rates of hippocampal atrophy were not different across the groups (MAPT = 7.8% [95% CI 3.9-12], GRN = 6.5% [95% CI 1.7-11], p = 0.66). Rates of whole brain atrophy in GRN, and hippocampal atrophy in MAPT, were associated with age, with older subjects showing slower rates of atrophy (p = 0.01 and p < 0.001). CONCLUSIONS Subjects with FTD with GRN mutations have a faster rate of whole brain atrophy than subjects with FTD with MAPT mutations, with similar rates of hippocampal atrophy. Rates of atrophy in both groups were associated with age. These findings are important for future treatment trials in FTD that use rates of atrophy as an outcome measure.
Collapse
Affiliation(s)
- J L Whitwell
- Department of Radiology, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, USA.
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
38
|
Gross RA, Knopman DS, Cascino GD, Corboy JR, Elkind MSV, Engel AG, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our Reviewers. Neurology 2011. [DOI: 10.1212/wnl.0b013e3182260341] [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
|
39
|
Kantarci K, Senjem ML, Avula R, Zhang B, Samikoglu AR, Weigand SD, Przybelski SA, Edmonson HA, Vemuri P, Knopman DS, Boeve BF, Ivnik RJ, Smith GE, Petersen RC, Jack CR. Diffusion tensor imaging and cognitive function in older adults with no dementia. Neurology 2011; 77:26-34. [PMID: 21593440 DOI: 10.1212/wnl.0b013e31822313dc] [Citation(s) in RCA: 128] [Impact Index Per Article: 9.8] [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 To determine the patterns of diffusivity associated with cognitive domain functions in older adults without dementia. METHODS We studied older adults without dementia (n = 220) who underwent neuropsychometric testing and a diffusion tensor imaging (DTI) examination at 3 T in a cross-sectional study. Memory, language, attention/executive function, and visual-spatial processing domains were assessed within 4 months of the MRI examination. A fluid-attenuated inversion recovery-based DTI sequence that enabled uncontaminated cortical diffusion measurements was performed. Associations between cortical mean diffusivity (MD) and cognitive function were tested using voxel-based regression analysis. Association between tract diffusivity and cognitive function was tested with regions of interest drawn on color-coded fractional anisotropy (FA) maps. RESULTS Memory function was associated with the medial temporal lobe cortical MD on voxel-based analysis (p < 0.001, corrected for multiple comparisons), and inferior longitudinal fasciculus and posterior and anterior cingulum FA on tract-based analysis (p < 0.001). Language function was associated with the left temporal lobe cortical MD (p < 0.001, corrected for multiple comparisons), inferior longitudinal fasciculus, fornix, and posterior cingulum FA (p < 0.05). Attention and executive function was associated with the posterior and anterior cingulum FA, and visual-spatial function was associated with posterior cingulum FA (p < 0.01). CONCLUSION Specific cognitive domain functions are associated with distinct patterns of cortical and white matter diffusivity in elderly with no dementia. Posterior cingulum tract FA was associated with all 4 cognitive domain functions, in agreement with the hypothesis that the posterior cingulate cortex is the main connectivity hub for cognitive brain networks. Microstructural changes identified on DTI may be associated with neurodegenerative pathologies underlying cognitive changes in older adults without dementia.
Collapse
Affiliation(s)
- K Kantarci
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
40
|
Knopman DS, Penman AD, Catellier DJ, Coker LH, Shibata DK, Sharrett AR, Mosley TH. Vascular risk factors and longitudinal changes on brain MRI: the ARIC study. Neurology 2011; 76:1879-85. [PMID: 21543737 DOI: 10.1212/wnl.0b013e31821d753f] [Citation(s) in RCA: 127] [Impact Index Per Article: 9.8] [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 To evaluate associations between vascular risk factors and changes in burden of infarcts, ventricular size (VS), sulcal widening (SW), and white matter hyperintensities (WMH) in an initially middle-aged, biracial cohort from the Atherosclerosis Risk in Communities (ARIC) study. METHODS Initial brain magnetic resonance (MR) scans and evaluations for vascular risk factors were performed in 1,812 ARIC participants in 1994-1995. In 2004-2006, 1,130 ARIC participants underwent repeat MR scans. MR scans were rated using a validated 9-point scale for VS, SW, and WMH. Infarcts were recorded. Multiple logistic regression analysis was used to assess associations between vascular risk factors and change between MR scans of one or more grades in VS, SW, WMH, or appearance of new infarcts, controlling for age, sex, and race. RESULTS At baseline, the 1,112 participants with usable scans (385 black women, 200 black men, 304 white women, 223 white men) had a mean age of 61.7 ± 4.3 years. In adjusted models, diabetes at baseline was associated with incident infarcts (odds ratio [OR] 1.95, 95% confidence interval [CI] 1.29-2.95) and worsening SW (OR 2.10, 95% CI 1.36-3.24). Hypertension at baseline was associated with incident infarcts (OR 1.73, 95% CI 1.23-2.42). In subjects with the highest tertile of fasting blood sugar and systolic blood pressure at baseline, the risk of incident infarcts was 3.68 times higher (95% CI 1.89-7.19) than those in the lowest tertile for both. CONCLUSION Both atrophic and ischemic imaging changes were driven by altered glycemic and blood pressure control beginning in midlife.
Collapse
Affiliation(s)
- D S Knopman
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
| | | | | | | | | | | | | |
Collapse
|
41
|
Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, Ogar JM, Rohrer JD, Black S, Boeve BF, Manes F, Dronkers NF, Vandenberghe R, Rascovsky K, Patterson K, Miller BL, Knopman DS, Hodges JR, Mesulam MM, Grossman M. Classification of primary progressive aphasia and its variants. Neurology 2011; 76:1006-14. [PMID: 21325651 DOI: 10.1212/wnl.0b013e31821103e6] [Citation(s) in RCA: 3018] [Impact Index Per Article: 232.2] [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
This article provides a classification of primary progressive aphasia (PPA) and its 3 main variants to improve the uniformity of case reporting and the reliability of research results. Criteria for the 3 variants of PPA--nonfluent/agrammatic, semantic, and logopenic--were developed by an international group of PPA investigators who convened on 3 occasions to operationalize earlier published clinical descriptions for PPA subtypes. Patients are first diagnosed with PPA and are then divided into clinical variants based on specific speech and language features characteristic of each subtype. Classification can then be further specified as "imaging-supported" if the expected pattern of atrophy is found and "with definite pathology" if pathologic or genetic data are available. The working recommendations are presented in lists of features, and suggested assessment tasks are also provided. These recommendations have been widely agreed upon by a large group of experts and should be used to ensure consistency of PPA classification in future studies. Future collaborations will collect prospective data to identify relationships between each of these syndromes and specific biomarkers for a more detailed understanding of clinicopathologic correlations.
Collapse
Affiliation(s)
- M L Gorno-Tempini
- Memory and Aging Center, Department of Neurology, UCSF, 350 Parnassus Avenue, Suite 905, San Francisco, CA 94143-1207, USA.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
42
|
Whitwell JL, Jack CR, Parisi JE, Senjem ML, Knopman DS, Boeve BF, Rademakers R, Baker M, Petersen RC, Dickson DW, Josephs KA. Does TDP-43 type confer a distinct pattern of atrophy in frontotemporal lobar degeneration? Neurology 2011; 75:2212-20. [PMID: 21172844 DOI: 10.1212/wnl.0b013e31820203c2] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE To determine whether TDP-43 type is associated with distinct patterns of brain atrophy on MRI in subjects with pathologically confirmed frontotemporal lobar degeneration (FTLD). METHODS In this case-control study, we identified all subjects with a pathologic diagnosis of FTLD with TDP-43 immunoreactive inclusions (FTLD-TDP) and at least one volumetric head MRI scan (n = 42). In each case we applied published criteria for subclassification of FTLD-TDP into FTLD-TDP types 1-3. Voxel-based morphometry was used to compare subjects with each of the different FTLD-TDP types to age- and gender-matched normal controls (n = 30). We also assessed different pathologic and genetic variants within, and across, the different types. RESULTS Twenty-two subjects were classified as FTLD-TDP type 1, 9 as type 2, and 11 as type 3. We identified different patterns of atrophy across the types with type 1 showing frontotemporal and parietal atrophy, type 2 predominantly anterior temporal lobe atrophy, and type 3 predominantly posterior frontal atrophy. Within the FTLD-TDP type 1 group, those with a progranulin mutation had significantly more lateral temporal lobe atrophy than those without. All type 2 subjects were diagnosed with semantic dementia. Subjects with a pathologic diagnosis of FTLD with motor neuron degeneration had a similar pattern of atrophy, regardless of whether they were type 1 or type 3. CONCLUSIONS Although there are different patterns of atrophy across the different FTLD-TDP types, it appears that genetic and pathologic factors may also affect the patterns of atrophy.
Collapse
Affiliation(s)
- J L Whitwell
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
43
|
Pathan SS, Gottesman RF, Mosley TH, Knopman DS, Sharrett AR, Alonso A. Association of lung function with cognitive decline and dementia: the Atherosclerosis Risk in Communities (ARIC) Study. Eur J Neurol 2011; 18:888-98. [PMID: 21244584 DOI: 10.1111/j.1468-1331.2010.03340.x] [Citation(s) in RCA: 74] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Previous studies reported a higher risk of cognitive decline and dementia amongst individuals with impaired lung function. However, many did not adjust for important confounders or did not include women and non-whites. METHODS We studied 10,975 men and women aged 47-70 years (23% African-Americans) enrolled in the Atherosclerosis Risk in Communities Study. Pulmonary function tests and a cognitive assessment, including the Delayed Word Recall, the Digit Symbol Substitution, and the World Fluency Tests, were carried out in 1990-1992. Repeated cognitive assessments were performed in 1996-1998 for the entire cohort, and in 1993-1995, and 2004-2006 in 904 eligible individuals. Dementia hospitalization was ascertained through 2005. RESULTS In analysis adjusted for lifestyles, APOE genotype, and cardiovascular risk factors, impaired lung function was associated with worse cognitive function at baseline. No association was found between lung function and cognitive decline over time. Impaired lung function at baseline was associated with higher risk of dementia hospitalization during follow-up, particularly amongst younger individuals. The hazard ratios (95% confidence intervals) of dementia hospitalization were 1.6 (0.9, 2.8) and 2.1 (1.2, 3.7) comparing the lowest with the highest quartile of forced expiratory volume in 1 s and forced vital capacity, respectively. Presence of a restrictive ventilatory pattern, but not of an obstructive pattern, was associated with reduced cognitive scores and higher dementia risk. CONCLUSION Reduced lung function was associated with worse performance in cognitive assessments and with an increased risk of dementia hospitalization. Future research should determine whether maintaining optimal pulmonary health might prevent cognitive impairment and dementia.
Collapse
Affiliation(s)
- S S Pathan
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | | | | | | | | | | |
Collapse
|
44
|
|
45
|
|
46
|
Whitwell JL, Jack CR, Boeve BF, Parisi JE, Ahlskog JE, Drubach DA, Senjem ML, Knopman DS, Petersen RC, Dickson DW, Josephs KA. Imaging correlates of pathology in corticobasal syndrome. Neurology 2011; 75:1879-87. [PMID: 21098403 DOI: 10.1212/wnl.0b013e3181feb2e8] [Citation(s) in RCA: 151] [Impact Index Per Article: 11.6] [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
BACKGROUND Corticobasal syndrome (CBS) can be associated with different underlying pathologies that are difficult to predict based on clinical presentation. The aim of this study was to determine whether patterns of atrophy on imaging could be useful to help predict underlying pathology in CBS. METHODS This was a case-control study of 24 patients with CBS who had undergone MRI during life and came to autopsy. Pathologic diagnoses included frontotemporal lobar degeneration (FTLD) with TDP-43 immunoreactivity in 5 (CBS-TDP), Alzheimer disease (AD) in 6 (CBS-AD), corticobasal degeneration in 7 (CBS-CBD), and progressive supranuclear palsy in 6 (CBS-PSP). Voxel-based morphometry and atlas-based parcellation were used to assess atrophy across the CBS groups and compared to 24 age- and gender-matched controls. RESULTS All CBS pathologic groups showed gray matter loss in premotor cortices, supplemental motor area, and insula on imaging. However, CBS-TDP and CBS-AD showed more widespread patterns of loss, with frontotemporal loss observed in CBS-TDP and temporoparietal loss observed in CBS-AD. CBS-TDP showed significantly greater loss in prefrontal cortex than the other groups, whereas CBS-AD showed significantly greater loss in parietal lobe than the other groups. The focus of loss was similar in CBS-CBD and CBS-PSP, although more severe in CBS-CBD. CONCLUSIONS Imaging patterns of atrophy in CBS vary according to pathologic diagnosis. Widespread atrophy points toward a pathologic diagnosis of FTLD-TDP or AD, with frontotemporal loss suggesting FTLD-TDP and temporoparietal loss suggesting AD. On the contrary, more focal atrophy predominantly involving the premotor and supplemental motor area suggests CBD or PSP pathology.
Collapse
Affiliation(s)
- J L Whitwell
- Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55905, USA.
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
47
|
Gross RA, Knopman DS, Cascino GD, Elkind MSV, Engel AG, Mink JW, Ransohoff RM, Uitti RJ, Worrall BB. Message from the Editors to our US and International Reviewers. Neurology 2010. [DOI: 10.1212/wnl.0b013e3182071791] [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
|
48
|
Finch N, Carrasquillo MM, Baker M, Rutherford NJ, Coppola G, Dejesus-Hernandez M, Crook R, Hunter T, Ghidoni R, Benussi L, Crook J, Finger E, Hantanpaa KJ, Karydas AM, Sengdy P, Gonzalez J, Seeley WW, Johnson N, Beach TG, Mesulam M, Forloni G, Kertesz A, Knopman DS, Uitti R, White CL, Caselli R, Lippa C, Bigio EH, Wszolek ZK, Binetti G, Mackenzie IR, Miller BL, Boeve BF, Younkin SG, Dickson DW, Petersen RC, Graff-Radford NR, Geschwind DH, Rademakers R. TMEM106B regulates progranulin levels and the penetrance of FTLD in GRN mutation carriers. Neurology 2010; 76:467-74. [PMID: 21178100 DOI: 10.1212/wnl.0b013e31820a0e3b] [Citation(s) in RCA: 183] [Impact Index Per Article: 13.1] [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
OBJECTIVES To determine whether TMEM106B single nucleotide polymorphisms (SNPs) are associated with frontotemporal lobar degeneration (FTLD) in patients with and without mutations in progranulin (GRN) and to determine whether TMEM106B modulates GRN expression. METHODS We performed a case-control study of 3 SNPs in TMEM106B in 482 patients with clinical and 80 patients with pathologic FTLD-TAR DNA-binding protein 43 without GRN mutations, 78 patients with FTLD with GRN mutations, and 822 controls. Association analysis of TMEM106B with GRN plasma levels was performed in 1,013 controls and TMEM106B and GRN mRNA expression levels were correlated in peripheral blood samples from 33 patients with FTLD and 150 controls. RESULTS In our complete FTLD patient cohort, nominal significance was identified for 2 TMEM106B SNPs (top SNP rs1990622, p(allelic) = 0.036). However, the most significant association with risk of FTLD was observed in the subgroup of GRN mutation carriers compared to controls (corrected p(allelic) = 0.0009), where there was a highly significant decrease in the frequency of homozygote carriers of the minor alleles of all TMEM106B SNPs (top SNP rs1990622, CC genotype frequency 2.6% vs 19.1%, corrected p(recessive) = 0.009). We further identified a significant association of TMEM106B SNPs with plasma GRN levels in controls (top SNP rs1990622, corrected p = 0.002) and in peripheral blood samples a highly significant correlation was observed between TMEM106B and GRN mRNA expression in patients with FTLD (r = -0.63, p = 7.7 × 10(-5)) and controls (r = -0.49, p = 2.2 × 10(-10)). CONCLUSIONS In our study, TMEM106B SNPs significantly reduced the disease penetrance in patients with GRN mutations, potentially by modulating GRN levels. These findings hold promise for the development of future protective therapies for FTLD.
Collapse
Affiliation(s)
- N Finch
- Department of Neuroscience, Mayo Clinic College of Medicine, 4500 San Pablo Road, Jacksonville, FL 32224, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
49
|
Petersen RC, Roberts RO, Knopman DS, Geda YE, Cha RH, Pankratz VS, Boeve BF, Tangalos EG, Ivnik RJ, Rocca WA. Prevalence of mild cognitive impairment is higher in men. The Mayo Clinic Study of Aging. Neurology 2010; 75:889-97. [PMID: 20820000 DOI: 10.1212/wnl.0b013e3181f11d85] [Citation(s) in RCA: 517] [Impact Index Per Article: 36.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVE We investigated the prevalence of mild cognitive impairment (MCI) in Olmsted County, MN, using in-person evaluations and published criteria. METHODS We evaluated an age- and sex-stratified random sample of Olmsted County residents who were 70-89 years old on October 1, 2004, using the Clinical Dementia Rating Scale, a neurologic evaluation, and neuropsychological testing to assess 4 cognitive domains: memory, executive function, language, and visuospatial skills. Information for each participant was reviewed by an adjudication panel and a diagnosis of normal cognition, MCI, or dementia was made using published criteria. RESULTS Among 1,969 subjects without dementia, 329 subjects had MCI, with a prevalence of 16.0% (95% confidence interval [CI] 14.4-17.5) for any MCI, 11.1% (95% CI 9.8-12.3) for amnestic MCI, and 4.9% (95% CI 4.0-5.8) for nonamnestic MCI. The prevalence of MCI increased with age and was higher in men. The prevalence odds ratio (OR) in men was 1.54 (95% CI 1.21-1.96; adjusted for age, education, and nonparticipation). The prevalence was also higher in subjects who never married and in subjects with an APOE epsilon3epsilon4 or epsilon4epsilon4 genotype. MCI prevalence decreased with increasing number of years of education (p for linear trend <0.0001). CONCLUSIONS Our study suggests that approximately 16% of elderly subjects free of dementia are affected by MCI, and amnestic MCI is the most common type. The higher prevalence of MCI in men may suggest that women transition from normal cognition directly to dementia at a later age but more abruptly.
Collapse
Affiliation(s)
- R C Petersen
- Department of Neurology, College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
| | | | | | | | | | | | | | | | | | | |
Collapse
|
50
|
Kantarci K, Boeve BF, Wszolek ZK, Rademakers R, Whitwell JL, Baker MC, Senjem ML, Samikoglu AR, Knopman DS, Petersen RC, Jack CR. MRS in presymptomatic MAPT mutation carriers: a potential biomarker for tau-mediated pathology. Neurology 2010; 75:771-8. [PMID: 20805522 PMCID: PMC2938968 DOI: 10.1212/wnl.0b013e3181f073c7] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.9] [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: 02/07/2023] Open
Abstract
OBJECTIVE To determine the proton magnetic resonance spectroscopy ((1)H MRS) changes in carriers of microtubule-associated protein (MAPT) mutations in a case-control study. METHODS Patients with MAPT mutations (N279K, V337M, R406W, IVS9-10G>T, P301L) from 5 different families (n = 24) underwent MRI and single voxel (1)H MRS from the posterior cingulate gyrus inferior precuneus at 3 T. Ten of the patients were symptomatic with median Clinical Dementia Rating sum of boxes score (CDR-SOB) of 6.5 and 14 patients were presymptomatic with CDR-SOB of 0. Age- and sex-matched controls (n = 24) were recruited. RESULTS Symptomatic MAPT mutation carriers were characterized by decreased N-acetylaspartate/creatine (NAA/Cr) ratio, an index of neuronal integrity, increased myoinositol (mI)/Cr ratio, a possible marker for glial activity, decreased NAA/mI, and hippocampal atrophy (p < 0.001). Whereas presymptomatic MAPT mutation carriers had elevated mI/Cr and decreased NAA/mI (p < 0.001), NAA/Cr levels and hippocampal volumes were not different from controls. Decrease in NAA/Cr (R(2) = 0. 22; p = 0.021) and hippocampal volumes (R(2) = 0.46; p < 0.001) were associated with proximity to the expected or actual age at symptom onset in MAPT mutation carriers. CONCLUSION (1)H MRS metabolite abnormalities characterized by an elevated mI/Cr and decreased NAA/mI are present several years before the onset of symptoms in MAPT mutation carriers. The data suggest an ordered sequencing of the (1)H MRS and MRI biomarkers. MI/Cr, a possible index of glial proliferation, precedes the decrease in neuronal integrity marker NAA/Cr and hippocampal atrophy. (1)H MRS may be a useful inclusion biomarker for preventive trials in presymptomatic carriers of MAPT mutations and possibly other proteinopathies.
Collapse
Affiliation(s)
- K Kantarci
- Departmentsof Radiology, Mayo Clinic, Rochester, MN 55905, USA. kantarci.kejal@mayo
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|