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Pittock RR, Aakre JA, Castillo AM, Ramanan VK, Kremers WK, Jack CR, Vemuri P, Lowe VJ, Knopman DS, Petersen RC, Graff-Radford J, Vassilaki M. Eligibility for Anti-Amyloid Treatment in a Population-Based Study of Cognitive Aging. Neurology 2023; 101:e1837-e1849. [PMID: 37586881 PMCID: PMC10663008 DOI: 10.1212/wnl.0000000000207770] [Citation(s) in RCA: 71] [Impact Index Per Article: 35.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 08/04/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Treatment options for Alzheimer disease (AD) are limited and have focused mainly on symptomatic therapy and improving quality of life. Recently, lecanemab, an anti-β-amyloid monoclonal antibody (mAb), received accelerated approval by the US Food and Drug Administration for treatment in the early stages of biomarker-confirmed symptomatic AD. An additional anti-β-amyloid mAb, aducanumab, was approved in 2021, and more will potentially become available in the near future. Research on the applicability and generalizability of the anti-β-amyloid mAb eligibility criteria on adults with biomarkers available in the general population has been lacking. The study's primary aim was to apply the clinical trial eligibility criteria for lecanemab treatment to participants with early AD of the population-based Mayo Clinic Study of Aging (MCSA) and assess the generalizability of anti-amyloid treatment. The secondary aim of this study was to apply the clinical trial eligibility criteria for aducanumab treatment in MCSA participants. METHODS This cross-sectional study aimed to apply the clinical trial eligibility criteria for lecanemab and aducanumab treatment to participants with early AD of the population-based MCSA and assess the generalizability of anti-amyloid treatment. RESULTS Two hundred thirty-seven MCSA participants (mean age [SD] 80.9 [6.3] years, 54.9% male, and 97.5% White) with mild cognitive impairment (MCI) or mild dementia and increased brain amyloid burden by PiB PET comprised the study sample. Lecanemab trial's inclusion criteria reduced the study sample to 112 (47.3% of 237) participants. The trial's exclusion criteria further narrowed the number of potentially eligible participants to 19 (overall 8% of 237). Modifying the eligibility criteria to include all participants with MCI (instead of applying additional cognitive criteria) resulted in 17.4% of participants with MCI being eligible for lecanemab treatment. One hundred four participants (43.9% of 237) fulfilled the aducanumab clinical trial's inclusion criteria. The aducanumab trial's exclusion criteria further reduced the number of available participants, narrowing those eligible to 12 (5.1% of 237). Common exclusions were related to other chronic conditions and neuroimaging findings. DISCUSSION Findings estimate the limited eligibility in typical older adults with cognitive impairment for anti-β-amyloid mAbs.
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Affiliation(s)
- Rioghna R Pittock
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Jeremiah A Aakre
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Anna M Castillo
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Vijay K Ramanan
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Walter K Kremers
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Prashanthi Vemuri
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Val J Lowe
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - David S Knopman
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Ronald C Petersen
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Jonathan Graff-Radford
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Maria Vassilaki
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN.
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Cogswell PM, Aakre JA, Castillo AM, Knopman DS, Kantarci K, Rabinstein AA, Petersen RC, Jack CR, Mielke MM, Vemuri P, Graff-Radford J. Population-Based Prevalence of Infarctions on 3D Fluid-Attenuated Inversion Recovery (FLAIR) Imaging. J Stroke Cerebrovasc Dis 2022; 31:106583. [PMID: 35689933 PMCID: PMC9329259 DOI: 10.1016/j.jstrokecerebrovasdis.2022.106583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 05/19/2022] [Accepted: 05/24/2022] [Indexed: 11/28/2022] Open
Abstract
OBJECTIVES To report population-based, age-specific prevalence of infarctions as identified via 3D fluid-attenuated inversion recovery (FLAIR) imaging. MATERIALS AND METHODS Participants without dementia in the Mayo Clinic Study of Aging (MCSA), a population-based study in Olmsted County, MN, age 50-89 who underwent 3D FLAIR imaging between 2017 and 2020 were included. Infarctions per participant were determined via visual interpretation. Inter- and intra-reader reliability were calculated. Infarction prevalence on 3D FLAIR was derived by standardization to the Olmsted County population and was compared to that previously reported on 2D FLAIR imaging. RESULTS Among 580 participants (mean age 71 years, 46% female) the prevalence (95% confidence interval) of any infarction was 5.0% (0.0%-9.9%) at age 50-59 years and 38.8% (28.6%-49.0%) at 80-89 years. In addition to increasing with age, the prevalence varied by sex and type of infarction. Prevalence estimates of cortical infarcts were 0.9% (0.0%-2.7%) at age 50-59 years and 20.2% (10.7%-29.7%) at 80-89 years and lacunar infarcts 4.1% (0.0%-8.8%) at age 50-59 years and 31.2% (21.5%-41.0%) at 80-89 years. Prevalence estimates of any infarction by sex were: men, 8.7% (0.0%-18.7%) at 50-59 years and 54.9% (41.0%-68.8%) at 80-89 years and women, 2.4% (0.0%-7.3%) at age 50-59 years and 27.3% (12.9%-41.7%) at 80-89 years. Intra- and inter- reader reliability were very good (kappa = 0.85 and 0.82, respectively). After adjusting for age, sex and education, individuals imaged with 3D FLAIR were 1.5 times (95% CI 1.2-1.8, p<0.001) more likely to be identified as positive for infarction compared to those imaged with 2D FLAIR. CONCLUSIONS Infarction prevalence increases with age and is greater in men than women. Infarction prevalence on 3D FLAIR imaging, which has become more widely implemented as an alternative to 2D FLAIR over the past several years, will be a useful reference in future work.
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Ramanan VK, Heckman MG, Lesnick TG, Przybelski SA, Cahn EJ, Kosel ML, Murray ME, Mielke MM, Botha H, Graff-Radford J, Jones DT, Lowe VJ, Machulda MM, Jack CR, Knopman DS, Petersen RC, Ross OA, Vemuri P. Tau polygenic risk scoring: a cost-effective aid for prognostic counseling in Alzheimer's disease. Acta Neuropathol 2022; 143:571-583. [PMID: 35412102 PMCID: PMC9109940 DOI: 10.1007/s00401-022-02419-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/07/2022] [Accepted: 04/07/2022] [Indexed: 11/28/2022]
Abstract
Tau deposition is one of two hallmark features of biologically defined Alzheimer's disease (AD) and is more closely related to cognitive decline than amyloidosis. Further, not all amyloid-positive individuals develop tauopathy, resulting in wide heterogeneity in clinical outcomes across the population with AD. We hypothesized that a polygenic risk score (PRS) based on tau PET (tau PRS) would capture the aggregate inherited susceptibility/resistance architecture influencing tau accumulation, beyond solely the measurement of amyloid-β burden. Leveraging rich multimodal data from a population-based sample of older adults, we found that this novel tau PRS was a strong surrogate of tau PET deposition and captured a significant proportion of the variance in tau PET levels as compared with amyloid PET burden, APOE (apolipoprotein E) ε4 (the most common risk allele for AD), and a non-APOE PRS of clinical case-control AD risk variants. In independent validation samples, the tau PRS was associated with cerebrospinal fluid phosphorylated tau levels in one cohort and with postmortem Braak neurofibrillary tangle stage in another. We also observed an association of the tau PRS with longitudinal cognitive trajectories, including a statistical interaction of the tau PRS with amyloid burden on cognitive decline. Although additional study is warranted, these findings demonstrate the potential utility of a tau PRS for capturing the collective genetic background influencing tau deposition in the general population. In the future, a tau PRS could be leveraged for cost-effective screening and risk stratification to guide trial enrollment and clinical interventions in AD.
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Affiliation(s)
- Vijay K Ramanan
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Michael G Heckman
- Department of Quantitative Health Sciences, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Elliot J Cahn
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Matthew L Kosel
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jonathan Graff-Radford
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
- Department of Clinical Genomics, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Prashanthi Vemuri
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA.
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA.
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Ramanan VK, Lesnick TG, Przybelski SA, Heckman MG, Knopman DS, Graff-Radford J, Lowe VJ, Machulda MM, Mielke MM, Jack CR, Petersen RC, Ross OA, Vemuri P. Coping with brain amyloid: genetic heterogeneity and cognitive resilience to Alzheimer's pathophysiology. Acta Neuropathol Commun 2021; 9:48. [PMID: 33757599 PMCID: PMC7986461 DOI: 10.1186/s40478-021-01154-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 03/08/2021] [Indexed: 12/13/2022] Open
Abstract
Although abnormal accumulation of amyloid in the brain is an early biomarker of Alzheimer's disease (AD), wide variation in cognitive trajectories during life can be seen in the setting of brain amyloidosis, ranging from maintenance of normal function to progression to dementia. It is widely presumed that cognitive resilience (i.e., coping) to amyloidosis may be influenced by environmental, lifestyle, and inherited factors, but relatively little in specifics is known about this architecture. Here, we leveraged multimodal longitudinal data from a large, population-based sample of older adults to discover genetic factors associated with differential cognitive resilience to brain amyloidosis determined by positron emission tomography (PET). Among amyloid-PET positive older adults, the AD risk allele APOE ɛ4 was associated with worse longitudinal memory trajectories as expected, and was thus covaried in the main analyses. Through a genome-wide association study (GWAS), we uncovered a novel association with cognitive resilience on chromosome 8 at the MTMR7/CNOT7/ZDHHC2/VPS37A locus (p = 4.66 × 10-8, β = 0.23), and demonstrated replication in an independent cohort. Post-hoc analyses confirmed this association as specific to the setting of elevated amyloid burden and not explained by differences in tau deposition or cerebrovascular disease. Complementary gene-based analyses and publically available functional data suggested that the causative variant at this locus may tag CNOT7 (CCR4-NOT Transcription Complex Subunit 7), a gene linked to synaptic plasticity and hippocampal-dependent learning and memory. Pathways related to cell adhesion and immune system activation displayed enrichment of association in the GWAS. Our findings, resulting from a unique study design, support the hypothesis that genetic heterogeneity is one of the factors that explains differential cognitive resilience to brain amyloidosis. Further characterization of the underlying biological mechanisms influencing cognitive resilience may facilitate improved prognostic counseling, therapeutic application, and trial enrollment in AD.
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Affiliation(s)
- Vijay K Ramanan
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Timothy G Lesnick
- Department of Health Sciences Research, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Scott A Przybelski
- Department of Health Sciences Research, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Michael G Heckman
- Division of Biomedical Statistics and Informatics, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jonathan Graff-Radford
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Health Sciences Research, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Health Sciences Research, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
- Department of Clinical Genomics, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA.
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Van Harten AC, Wiste HJ, Weigand SD, Mielke MM, Kremers WK, Eichenlaub U, Batrla-Utermann R, Dyer RB, Algeciras-Schimnich A, Knopman DS, Jack CR, Petersen RC. CSF biomarkers in Olmsted County: Evidence of 2 subclasses and associations with demographics. Neurology 2020; 95:e256-e267. [PMID: 32591471 PMCID: PMC7455353 DOI: 10.1212/wnl.0000000000009874] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 12/19/2019] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVE We studied interrelationships between CSF biomarkers and associations with APOE ε4 genotype, demographic variables, vascular variables, and clinical diagnosis in Olmsted County, Minnesota. METHODS We included 774 Mayo Clinic Study of Aging participants (693 cognitively unimpaired [CU]; 71 with mild cognitive impairment [MCI]). CSF β-amyloid 42 (Aβ42), total tau (t-tau), and hyperphosphorylated tau (p-tau) were analyzed using Aβ42 CSF, t-tau CSF, and p-tau (181P) CSF electrochemiluminescence immunoassays. Bivariate mixture models were used to evaluate latent classes. We used linear regression models to evaluate independent associations of APOE ε4, demographic factors, cardiovascular risk, and diagnosis with CSF biomarker levels. Results were weighted back to the Olmsted County population. RESULTS Interrelationships between CSF Aβ42 and p-tau/t-tau were consistent with 2 latent classes in the general population. In subgroup 1 (n = 547 [71%]), we found a strong positive correlation between Aβ42 and p-tau (ρ = 0.81), while the correlation was much smaller in group 2 (ρ = 0.26, n = 227 [29%]). Group 2 was associated with older age, APOE ε4 genotype, a diagnosis of MCI, and elevated amyloid PET. Overall, APOE ε4 genotype and MCI were associated with Aβ42, while age was associated with p-tau/t-tau. There were no associations with sex, education, or vascular risk. CONCLUSION We hypothesize the population without dementia can be subdivided into participants with and without biological Alzheimer disease (AD) based on the combination of CSF Aβ42 and p-tau/t-tau (represented also by the p-tau/t-tau/Aβ42 ratio). In those without biological AD, common factors such as CSF dynamics may cause a positive correlation between CSF Aβ42 and p-tau/t-tau, while AD leads to dissociation of these proteins.
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Affiliation(s)
- Argonde C Van Harten
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland.
| | - Heather J Wiste
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Stephen D Weigand
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Michelle M Mielke
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Walter K Kremers
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Udo Eichenlaub
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Richard Batrla-Utermann
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Roy B Dyer
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Alicia Algeciras-Schimnich
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - David S Knopman
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Clifford R Jack
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
| | - Ronald C Petersen
- From the Departments of Neurology (A.C.V.H., M.M.M., D.S.K., R.C.P.), Health Sciences Research (H.J.W., S.D.W., M.M.M., W.K.K., R.C.P.), Laboratory Medicine and Pathology (R.B.D.), and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Department of Neurology and Alzheimer Center Amsterdam UMC (A.C.V.H.), the Netherlands; and Roche Diagnostics (U.E., R.B.-U., A.A.-S.), Basel, Switzerland
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6
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Graff-Radford J, Aakre JA, Knopman DS, Schwarz CG, Flemming KD, Rabinstein AA, Gunter JL, Ward CP, Zuk SM, Spychalla AJ, Preboske GM, Petersen RC, Kantarci K, Huston J, Jack CR, Mielke MM, Vemuri P. Prevalence and Heterogeneity of Cerebrovascular Disease Imaging Lesions. Mayo Clin Proc 2020; 95:1195-1205. [PMID: 32498775 PMCID: PMC7316133 DOI: 10.1016/j.mayocp.2020.01.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 12/24/2019] [Accepted: 01/08/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVE To report population age-specific prevalence of core cerebrovascular disease lesions (infarctions, cerebral microbleeds, and white-matter hyperintensities detected with magnetic resonance imaging); estimate cut points for white-matter hyperintensity positivity; investigate sex differences in prevalence; and estimate prevalence of any core cerebrovascular disease features. PATIENTS AND METHODS Participants in the population-based Mayo Clinic Study of Aging aged 50 to 89 years underwent fluid-attenuated inversion recovery and T2* gradient-recalled echo magnetic resonance imaging to assess cerebrovascular disease between October 10, 2011, and September 29, 2017. We characterized each participant as having infarct, normal versus abnormal white-matter hyperintensity, cerebral microbleed, or a combination of lesions. Prevalence of cerebrovascular disease biomarkers was derived through adjustment for nonparticipation and standardization to the population of Olmsted County, Minnesota. RESULTS Among 1462 participants without dementia (median [range] age, 68 [50 to 89] y; men, 52.7%), core cerebrovascular disease features increased with age. Prevalence (95% CI) of cerebral microbleeds was 13.6% (11.6%-15.6%); infarcts, 11.7% (9.7%-13.8%); and abnormal white-matter hyperintensity, 10.7% (8.7%-12.6%). Infarcts and cerebral microbleeds were more common among men. In contrast, abnormal white-matter hyperintensity was more common among women ages 60 to 79 y and men, ages 80 y and older. Prevalence of any core cerebrovascular disease feature determined by presence of at least one cerebrovascular disease feature increased from 9.5% (ages 50 to 59 y) to 73.8% (ages 80 to 89 y). CONCLUSION Whereas this study focused on participants without dementia, the high prevalence of cerebrovascular disease imaging lesions in elderly persons makes assignment of clinical relevance to cognition and other downstream manifestations more probabilistic than deterministic.
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Affiliation(s)
| | - Jeremiah A Aakre
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | | | | | | | | | | | - John Huston
- Department of Radiology, Mayo Clinic, Rochester, MN
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7
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The A/T/N model applied through imaging biomarkers in a memory clinic. Eur J Nucl Med Mol Imaging 2019; 47:247-255. [PMID: 31792573 DOI: 10.1007/s00259-019-04536-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 09/12/2019] [Indexed: 12/14/2022]
Abstract
PURPOSE The A/T/N model is a research framework proposed to investigate Alzheimer's disease (AD) pathological bases (i.e., amyloidosis A, neurofibrillary tangles T, and neurodegeneration N). The application of this system on clinical populations is still limited. The aim of the study is to evaluate the topography of T distribution by 18F-flortaucipir PET in relation to A and N and to describe the A/T/N status through imaging biomarkers in memory clinic patients. METHODS Eighty-one patients with subjective and objective cognitive impairment were classified as A+/A- and N+/N- through amyloid PET and structural MRI. Tau deposition was compared across A/N subgroups at voxel level. T status was defined through a global cut point based on A/N subgroups and subjects were categorized following the A/T/N model. RESULTS A+N+ and A+N- subgroups showed higher tau burden compared to A-N- group, with A+N- showing significant deposition limited to the medial and lateral temporal regions. Global cut point discriminated A+N+ and A+N- from A-N- subjects. On A/T/N classification, 23% of patients showed a negative biomarker profile, 58% fell within the Alzheimer's continuum, and 19% of the sample was characterized by non-AD pathologic change. CONCLUSION Medial and lateral temporal regions represent a site of significant tau accumulation in A+ subjects and possibly a useful marker of early clinical changes. This is the first study in which the A/T/N model is applied using 18F-flortaucipir PET in a memory clinic population. The majority of patients showed a profile consistent with the Alzheimer's continuum, while a minor percentage showed a profile suggestive of possible other neurodegenerative diseases. These results support the applicability of the A/T/N model in clinical practice.
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8
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Vemuri P, Lesnick TG, Knopman DS, Przybelski SA, Reid RI, Mielke MM, Graff‐Radford J, Lowe VJ, Machulda MM, Petersen RC, Jack CR. Amyloid, Vascular, and Resilience Pathways Associated with Cognitive Aging. Ann Neurol 2019; 86:866-877. [PMID: 31509621 PMCID: PMC6899909 DOI: 10.1002/ana.25600] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2019] [Revised: 08/17/2019] [Accepted: 09/08/2019] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To investigate the multifactorial processes underlying cognitive aging based on the hypothesis that multiple causal pathways and mechanisms (amyloid, vascular, and resilience) influence longitudinal cognitive decline in each individual through worsening brain health. METHODS We identified 1,230 elderly subjects (aged ≥50 years) with an average of 4.9 years of clinical follow-up and with amyloid positron emission tomography, diffusion tensor imaging, and structural magnetic resonance imaging scans from the population-based Mayo Clinic Study of Aging. We examined imaging markers of amyloid and brain health (white matter microstructural integrity and cortical thinning), systemic vascular health preceding the imaging markers, and early to midlife intellectual enrichment to predict longitudinal cognitive trajectories. We used latent growth curve models for modeling longitudinal cognitive decline. RESULTS All the pathways (amyloid, vascular, resilience) converged through their effects on cortical thinning and worsening cognition and together explained patterns in cognitive decline. Resilience and vascular pathways (aging process, sex differences, education/occupation, and systemic vascular health) had significant impact on white matter microstructural integrity. Education/occupation levels contributed to white matter integrity through systemic vascular health. Worsening white matter integrity contributed to significant cortical thinning and subsequently longitudinal cognitive decline. Baseline amyloidosis contributed to a significant proportion of cognitive decline that accelerated with longer follow-up times, and its primary impact was through cortical thinning. INTERPRETATION We developed an integrated framework to help explain the dynamic and complex process of cognitive aging by considering key causal pathways. Such an approach is important for both better comprehension of cognitive aging processes and will aid in the development of successful intervention strategies. ANN NEUROL 2019;86:866-877.
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Affiliation(s)
| | | | | | | | - Robert I. Reid
- Department of Information TechnologyMayo ClinicRochesterMN
| | - Michelle M. Mielke
- Department of Health Sciences ResearchMayo ClinicRochesterMN
- Department of NeurologyMayo ClinicRochesterMN
| | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMN
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9
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Jack CR, Therneau TM, Weigand SD, Wiste HJ, Knopman DS, Vemuri P, Lowe VJ, Mielke MM, Roberts RO, Machulda MM, Graff-Radford J, Jones DT, Schwarz CG, Gunter JL, Senjem ML, Rocca WA, Petersen RC. Prevalence of Biologically vs Clinically Defined Alzheimer Spectrum Entities Using the National Institute on Aging-Alzheimer's Association Research Framework. JAMA Neurol 2019; 76:1174-1183. [PMID: 31305929 PMCID: PMC6632154 DOI: 10.1001/jamaneurol.2019.1971] [Citation(s) in RCA: 202] [Impact Index Per Article: 33.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 04/11/2019] [Indexed: 12/23/2022]
Abstract
Importance A National Institute on Aging-Alzheimer's Association (NIA-AA) workgroup recently published a research framework in which Alzheimer disease is defined by neuropathologic or biomarker evidence of β-amyloid plaques and tau tangles and not by clinical symptoms. Objectives To estimate the sex- and age-specific prevalence of 3 imaging biomarker-based definitions of the Alzheimer disease spectrum from the NIA-AA research framework and to compare these entities with clinically defined diagnostic entities commonly linked with Alzheimer disease. Design, Setting, and Participants The Mayo Clinic Study of Aging (MCSA) is a population-based cohort study of cognitive aging in Olmsted County, Minnesota. The MCSA in-person participants (n = 4660) and passively ascertained (ie, through the medical record rather than in-person) individuals with dementia (n = 553) aged 60 to 89 years were included. Subsets underwent amyloid positron emission tomography (PET) (n = 1524) or both amyloid and tau PET (n = 576). Therefore, this study included 3 nested cohorts examined between November 29, 2004, and June 5, 2018. Data were analyzed between February 19, 2018, and March 26, 2019. Main Outcomes and Measures The sex- and age-specific prevalence of the following 3 biologically defined diagnostic entities was estimated: Alzheimer continuum (abnormal amyloid regardless of tau status), Alzheimer pathologic change (abnormal amyloid but normal tau), and Alzheimer disease (abnormal amyloid and tau). These were compared with the prevalence of 3 clinically defined diagnostic groups (mild cognitive impairment or dementia, dementia, and clinically defined probable Alzheimer disease). Results The median (interquartile range) age was 77 (72-83) years in the clinical cohort (n = 5213 participants), 77 (70-83) years in the amyloid PET cohort (n = 1524 participants), and 77 (69-83) years in the tau PET cohort (n = 576 participants). There were roughly equal numbers of women and men. The prevalence of all diagnostic entities (biological and clinical) increased rapidly with age, with the exception of Alzheimer pathologic change. The prevalence of biological Alzheimer disease was greater than clinically defined probable Alzheimer disease for women and men. Among women, these values were 10% (95% CI, 6%-14%) vs 1% (95% CI, 1%-1%) at age 70 years and 33% (95% CI, 25%-41%) vs 10% (95% CI, 9%-12%) at age 85 years (P < .001). Among men, these values were 9% (95% CI, 5%-12%) vs 1% (95% CI, 0%-1%) at age 70 years and 31% (95% CI, 24%-38%) vs 9% (95% CI, 8%-11%) at age 85 years (P < .001). The only notable difference by sex was a greater prevalence of the mild cognitive impairment or dementia clinical category among men than women. Conclusions and Relevance Results of this study suggest that biologically defined Alzheimer disease is more prevalent than clinically defined probable Alzheimer disease at any age and is 3 times more prevalent at age 85 years among both women and men. This difference is mostly driven by asymptomatic individuals with biological Alzheimer disease. These findings illustrate the magnitude of the consequences on public health that potentially exist by intervening with disease-specific treatments to prevent symptom onset.
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Affiliation(s)
| | - Terry M. Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Stephen D. Weigand
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Heather J. Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | | | | | - Val J. Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, Minnesota
| | - Michelle M. Mielke
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | | | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota
| | | | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | - Walter A. Rocca
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | - Ronald C. Petersen
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
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10
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Jack CR, Wiste HJ, Therneau TM, Weigand SD, Knopman DS, Mielke MM, Lowe VJ, Vemuri P, Machulda MM, Schwarz CG, Gunter JL, Senjem ML, Graff-Radford J, Jones DT, Roberts RO, Rocca WA, Petersen RC. Associations of Amyloid, Tau, and Neurodegeneration Biomarker Profiles With Rates of Memory Decline Among Individuals Without Dementia. JAMA 2019; 321:2316-2325. [PMID: 31211344 PMCID: PMC6582267 DOI: 10.1001/jama.2019.7437] [Citation(s) in RCA: 222] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
IMPORTANCE A National Institute on Aging and Alzheimer's Association workgroup proposed a research framework for Alzheimer disease in which biomarker classification of research participants is labeled AT(N) for amyloid, tau, and neurodegeneration biomarkers. OBJECTIVE To determine the associations between AT(N) biomarker profiles and memory decline in a population-based cohort of individuals without dementia age 60 years or older, and to determine whether biomarkers provide incremental prognostic value beyond more readily available clinical and genetic information. DESIGN, SETTING, AND PARTICIPANTS Population-based cohort study of cognitive aging in Olmsted County, Minnesota, that included 480 nondemented Mayo Clinic Study of Aging participants who had a clinical evaluation and amyloid positron emission tomography (PET) (A), tau PET (T), and magnetic resonance imaging (MRI) cortical thickness (N) measures between April 16, 2015, and November 1, 2017, and at least 1 clinical evaluation follow-up by November 12, 2018. EXPOSURES Age, sex, education, cardiovascular and metabolic conditions score, APOE genotype, and AT(N) biomarker profiles. Each of A, T, or (N) can be abnormal (+) or normal (-), resulting in 8 AT(N) profiles. MAIN OUTCOMES AND MEASURES Primary outcome was a composite memory score measured longitudinally at 15-month intervals. Analyses measured the associations between predictor variables and the memory score, and whether AT(N) biomarker profiles significantly improved prediction of memory z score rates of change beyond a model with clinical and genetic variables only. RESULTS Participants were followed up for a median of 4.8 years (interquartile range [IQR], 3.8-5.1) and 44% were women (211/480). Median (IQR) ages ranged from 67 years (65-73) in the A-T-(N)- group to 83 years (76-87) in the A+T+(N)+ group. Of the participants, 92% (441/480) were cognitively unimpaired but the A+T+(N)+ group had the largest proportion of mild cognitive impairment (30%). AT(N) biomarkers improved the prediction of memory performance over a clinical model from an R2 of 0.26 to 0.31 (P < .001). Memory declined fastest in the A+T+(N)+, A+T+(N)-, and A+T-(N)+ groups compared with the other 5 AT(N) groups (P = .002). Estimated rates of decline in the 3 fastest declining groups were -0.13 (95% CI, -0.17 to -0.09), -0.10 (95% CI, -0.16 to -0.05), and -0.10 (95% CI, -0.13 to -0.06) z score units per year, respectively, for an 85-year-old APOE ε4 noncarrier. CONCLUSIONS AND RELEVANCE Among older persons without baseline dementia followed for a median of 4.8 years, a prediction model that included amyloid PET, tau PET, and MRI cortical thickness resulted in a small but statistically significant improvement in predicting memory decline over a model with more readily available clinical and genetic variables. The clinical importance of this difference is uncertain.
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Affiliation(s)
| | - Heather J. Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Terry M. Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Stephen D. Weigand
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | | | - Michelle M. Mielke
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Val J. Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, Minnesota
| | | | - Mary M. Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | | | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | - Rosebud O. Roberts
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Walter A. Rocca
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
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11
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Graff-Radford J, Botha H, Rabinstein AA, Gunter JL, Przybelski SA, Lesnick T, Huston J, Flemming KD, Preboske GM, Senjem ML, Brown RD, Mielke MM, Roberts RO, Lowe VJ, Knopman DS, Petersen RC, Kremers W, Vemuri P, Jack CR, Kantarci K. Cerebral microbleeds: Prevalence and relationship to amyloid burden. Neurology 2019; 92:e253-e262. [PMID: 30568001 PMCID: PMC6340386 DOI: 10.1212/wnl.0000000000006780] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 09/10/2018] [Indexed: 01/26/2023] Open
Abstract
OBJECTIVE To describe the prevalence of cerebral microbleeds (CMBs) and determine the association between CMBs and β-amyloid burden on PET. METHODS From the population-based Mayo Clinic Study of Aging, 1,215 participants (53% male) underwent 3-tesla MRI scans with T2* gradient recalled echo sequences from October 2011 to February 2017. A total of 1,123 participants (92%) underwent 11C-Pittsburgh compound B (PiB)-PET scans. The prevalence of CMBs was derived by adjusting for nonparticipation and standardizing to the Olmsted County, MN, population. The relationship between β-amyloid burden and CMB presence and location was tested using logistic regression models. Ordinal logistic models tested the relationship between CMB frequency and β-amyloid burden. RESULTS Two hundred seventy-four participants (22.6%) had at least one CMB. CMB frequency increased with age by decade (11% aged 60-69 years, 22% 70-79 years, and 39% 80 years and older). After adjusting for age, sex, and hypertension, PiB standardized uptake value ratio (SUVR) was associated with increased odds of a CMB. The association between PiB SUVR and CMBs was location-specific; PiB SUVR was associated with lobar CMBs but not deep CMBs. Age, hypertension, and PiB SUVR were associated with increasing CMB count. CMB density was greatest in parietal and occipital regions; β-amyloid burden correlated with concentration of CMBs in all lobar regions. Among participants with multiple CMBs, greater PiB uptake occurred in the pre- and postcentral gyri superiorly, the superior parietal lobe and precuneus, the angular gyrus, inferior temporal gyrus, and temporal poles. CONCLUSIONS The prevalence of CMBs increases with age. In this population-based sample, β-amyloid load was associated with lobar but not with deep CMBs.
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Affiliation(s)
- Jonathan Graff-Radford
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN.
| | - Hugo Botha
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Alejandro A Rabinstein
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Jeffrey L Gunter
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Scott A Przybelski
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Timothy Lesnick
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - John Huston
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Kelly D Flemming
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Gregory M Preboske
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Matthew L Senjem
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Robert D Brown
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Michelle M Mielke
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Rosebud O Roberts
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Val J Lowe
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - David S Knopman
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Ronald C Petersen
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Walter Kremers
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Prashanthi Vemuri
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
| | - Kejal Kantarci
- From the Departments of Neurology (J.G.-R., H.B., A.A.R., K.D.F., R.D.B., M.M.M., R.O.R., D.S.K., R.C.P.), Radiology (J.L.G., J.H., G.M.P., M.L.S., V.J.L., P.V., C.R.J., K.K.), and Health Sciences Research (S.A.P., T.L., M.M.M., R.O.R., W.K.), Mayo Clinic, Rochester, MN
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12
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Petersen RC, Lundt ES, Therneau TM, Weigand SD, Knopman DS, Mielke MM, Roberts RO, Lowe VJ, Machulda MM, Kremers WK, Geda YE, Jack CR. Predicting Progression to Mild Cognitive Impairment. Ann Neurol 2019; 85:155-160. [PMID: 30521086 PMCID: PMC6504922 DOI: 10.1002/ana.25388] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 11/30/2018] [Accepted: 12/03/2018] [Indexed: 12/31/2022]
Abstract
Despite much attention to the use of biomarkers for predicting Alzheimer disease, little information is available at the individual level. We used the population-based Mayo Clinic Study of Aging to estimate absolute risk of cognitive impairment by biomarker group. Risk increased with age and any biomarker abnormality. For example, a 75-year-old with abnormal amyloid and cortical thinning biomarkers has about a 20% chance of cognitive impairment by age 80 years, whereas with normal biomarkers the chance is <10%. Persons with only one abnormal biomarker had similar intermediate risks. ANN NEUROL 2019;85:155-160.
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Affiliation(s)
- Ronald C. Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Emily S. Lundt
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Terry M. Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Walter K. Kremers
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Yonas E. Geda
- Department of Psychiatry and Psychology, Mayo Clinic, Phoenix, AZ, USA
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13
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Precision medicine and drug development in Alzheimer's disease: the importance of sexual dimorphism and patient stratification. Front Neuroendocrinol 2018; 50:31-51. [PMID: 29902481 DOI: 10.1016/j.yfrne.2018.06.001] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 05/29/2018] [Accepted: 06/07/2018] [Indexed: 12/23/2022]
Abstract
Neurodegenerative diseases (ND) are among the leading causes of disability and mortality. Considerable sex differences exist in the occurrence of the various manifestations leading to cognitive decline. Alzheimer's disease (AD) exhibits substantial sexual dimorphisms and disproportionately affects women. Women have a higher life expectancy compared to men and, consequently, have more lifespan to develop AD. The emerging precision medicine and pharmacology concepts - taking into account the individual genetic and biological variability relevant for disease risk, prevention, detection, diagnosis, and treatment - are expected to substantially enhance our knowledge and management of AD. Stratifying the affected individuals by sex and gender is an important basic step towards personalization of scientific research, drug development, and care. We hypothesize that sex and gender differences, extending from genetic to psychosocial domains, are highly relevant for the understanding of AD pathophysiology, and for the conceptualization of basic/translational research and for clinical therapy trial design.
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14
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Lopez OL, Becker JT, Chang Y, Klunk WE, Mathis C, Price J, Aizenstein HJ, Snitz B, Cohen AD, DeKosky ST, Ikonomovic M, Kamboh MI, Kuller LH. Amyloid deposition and brain structure as long-term predictors of MCI, dementia, and mortality. Neurology 2018; 90:e1920-e1928. [PMID: 29695596 DOI: 10.1212/wnl.0000000000005549] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 03/14/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVES To test the hypothesis that brain structural integrity (i.e., hippocampal [HIP] volume), white matter lesions (WMLs), and β-amyloid deposition are associated with long-term increased risk of incident dementia and mortality in 183 cognitively normal individuals and patients with mild cognitive impairment (MCI) aged 80 years and older. METHODS All participants had a brain structural MRI scan and PET scan with 11C-labeled Pittsburgh compound B in 2009 and were reexamined yearly through 2015 (mean follow-up time 5.2 ± 1.3 years). RESULTS In the last evaluation through 2010-2015, 56 (31%) participants were cognitively normal, 67 (37%) had MCI, and 60 (33%) had dementia. Fifty-seven (31%) died during follow-up, and 20 (35%) developed dementia before their death. All 3 biomarkers were independent predictors of incident dementia in all participants. After adjusting for the risk of dying, amyloid deposition and WMLs remained strong predictors. Of the 60 participants with incident dementia, 54 (90%) had at least one imaging abnormality. Participants with no biomarker positivity had a very low risk of dementia (16%), while 75% of the participants with the 3 biomarkers progressed to dementia. HIP volume and β-amyloid deposition were associated with death only in participants with MCI. CONCLUSIONS This study showed the presence of more than one biomarker was a stronger long-term predictor of incident dementia than any biomarker alone. After adjusting for the risk of dying, amyloid deposition and WMLs were stronger predictors of dementia than HIP volume. The risk of dying during follow-up was associated with both neurodegeneration and amyloid deposition, especially in individuals with MCI.
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Affiliation(s)
- Oscar L Lopez
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville.
| | - James T Becker
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - YueFang Chang
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - William E Klunk
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - Chester Mathis
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - Julia Price
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - Howard J Aizenstein
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - Beth Snitz
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - Ann D Cohen
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - Steven T DeKosky
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - Milos Ikonomovic
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - M Ilyas Kamboh
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
| | - Lewis H Kuller
- From the Departments of Neurology (O.L.L., J.T.B., B.S., M.I.), Psychiatry (O.L.L., J.T.B., W.E.K., H.J.A., A.D.C.), Psychology (J.T.B.), Neurosurgery (Y.C.), Epidemiology, Graduate School of Public Health (Y.C., L.H.K.), Radiology (C.M., J.P.), Pharmaceutical Sciences (C.M.), and Genetics (M.I.K.), University of Pittsburgh, School of Medicine, PA; and Department of Neurology (S.T.D.), University of Florida, Gainesville
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15
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Fatemi F, Kantarci K, Graff-Radford J, Preboske GM, Weigand SD, Przybelski SA, Knopman DS, Machulda MM, Roberts RO, Mielke MM, Petersen RC, Jack CR, Vemuri P. Sex differences in cerebrovascular pathologies on FLAIR in cognitively unimpaired elderly. Neurology 2018; 90:e466-e473. [PMID: 29343465 DOI: 10.1212/wnl.0000000000004913] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Accepted: 10/27/2017] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVE To examine sex differences in cerebrovascular pathologies (CVPs) as seen on fluid-attenuated inversion recovery (FLAIR) MRI and in cardiovascular and metabolic risk factors in a population-based cognitively unimpaired cohort and to examine whether sex is independently associated with FLAIR findings after accounting for differences in important midlife risk factors. METHODS We identified 1,301 cognitively normal participants (663 men and 638 women) enrolled in the Mayo Clinic Study of Aging (age ≥70 years) who had FLAIR MRI and ascertained total burden of white matter (WM) hyperintensities (WMH), subcortical infarctions, and cortical infarctions. We compared CVPs and midlife and late-life vascular risk factors between men and women. We fit regression models with each CVP as an outcome, treating age, sex, and midlife risk factors as predictors. RESULTS Women had significantly greater WMH volume relative to their WM volume compared to men (2.8% vs 2.4% of WM, p < 0.001), while men had a greater frequency of cortical infarctions compared to women (9% vs 4%, p < 0.001). Subcortical infarctions were equally common in men and women (20%). In regression modeling after adjustment for WM volume, the mean WMH volume difference between men and women was of the same magnitude as a 7-year difference in age. In contrast, men had 2.2-greater relative odds of having a cortical infarction compared to women. These sex differences persisted even after adjustment for midlife vascular risk factors. CONCLUSIONS There were important sex differences in CVP findings on FLAIR in cognitively unimpaired elderly. Understanding these sex differences could aid in the development of sex-specific preventive strategies.
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Affiliation(s)
- Farzan Fatemi
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Kejal Kantarci
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Jonathan Graff-Radford
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Gregory M Preboske
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Stephen D Weigand
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Scott A Przybelski
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - David S Knopman
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Mary M Machulda
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Rosebud O Roberts
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Michelle M Mielke
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Ronald C Petersen
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Clifford R Jack
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis
| | - Prashanthi Vemuri
- From the Departments of Radiology (F.F., K.K., G.M.P., C.R.J., P.V.), Health Sciences Research (S.D.W., S.A.P., R.O.R., M.M. Mielke), Neurology (J.G.-R., D.S.K., R.O.R., M.M. Mielke, R.C.P.), and Psychology (M.M. Machulda), Mayo Clinic Rochester; and School of Medicine (F.F.), University of Minnesota, Minneapolis.
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