Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis.
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ABSTRACT:
SUBMITTER: Ossenkoppele R
PROVIDER: S-EPMC4517678 | biostudies-literature | 2015 May
REPOSITORIES: biostudies-literature
Publications
Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis.
Ossenkoppele Rik R Jansen Willemijn J WJ Rabinovici Gil D GD Knol Dirk L DL van der Flier Wiesje M WM van Berckel Bart N M BN Scheltens Philip P Visser Pieter Jelle PJ Verfaillie Sander C J SC Zwan Marissa D MD Adriaanse Sofie M SM Lammertsma Adriaan A AA Barkhof Frederik F Jagust William J WJ Miller Bruce L BL Rosen Howard J HJ Landau Susan M SM Villemagne Victor L VL Rowe Christopher C CC Lee Dong Y DY Na Duk L DL Seo Sang W SW Sarazin Marie M Roe Catherine M CM Sabri Osama O Barthel Henryk H Koglin Norman N Hodges John J Leyton Cristian E CE Vandenberghe Rik R van Laere Koen K Drzezga Alexander A Forster Stefan S Grimmer Timo T Sánchez-Juan Pascual P Carril Jose M JM Mok Vincent V Camus Vincent V Klunk William E WE Cohen Ann D AD Meyer Philipp T PT Hellwig Sabine S Newberg Andrew A Frederiksen Kristian S KS Fleisher Adam S AS Mintun Mark A MA Wolk David A DA Nordberg Agneta A Rinne Juha O JO Chételat Gaël G Lleo Alberto A Blesa Rafael R Fortea Juan J Madsen Karine K Rodrigue Karen M KM Brooks David J DJ
JAMA 20150501 19
<h4>Importance</h4>Amyloid-β positron emission tomography (PET) imaging allows in vivo detection of fibrillar plaques, a core neuropathological feature of Alzheimer disease (AD). Its diagnostic utility is still unclear because amyloid plaques also occur in patients with non-AD dementia.<h4>Objective</h4>To use individual participant data meta-analysis to estimate the prevalence of amyloid positivity on PET in a wide variety of dementia syndromes.<h4>Data sources</h4>The MEDLINE and Web of Scienc ...[more]
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Project description:Cerebral amyloid-? aggregation is an early pathological event in Alzheimer disease (AD), starting decades before dementia onset. Estimates of the prevalence of amyloid pathology in persons without dementia are needed to understand the development of AD and to design prevention studies.To use individual participant data meta-analysis to estimate the prevalence of amyloid pathology as measured with biomarkers in participants with normal cognition, subjective cognitive impairment (SCI), or mild cognitive impairment (MCI).Relevant biomarker studies identified by searching studies published before April 2015 using the MEDLINE and Web of Science databases and through personal communication with investigators.Studies were included if they provided individual participant data for participants without dementia and used an a priori defined cutoff for amyloid positivity.Individual records were provided for 2914 participants with normal cognition, 697 with SCI, and 3972 with MCI aged 18 to 100 years from 55 studies.Prevalence of amyloid pathology on positron emission tomography or in cerebrospinal fluid according to AD risk factors (age, apolipoprotein E [APOE] genotype, sex, and education) estimated by generalized estimating equations.The prevalence of amyloid pathology increased from age 50 to 90 years from 10% (95% CI, 8%-13%) to 44% (95% CI, 37%-51%) among participants with normal cognition; from 12% (95% CI, 8%-18%) to 43% (95% CI, 32%-55%) among patients with SCI; and from 27% (95% CI, 23%-32%) to 71% (95% CI, 66%-76%) among patients with MCI. APOE-?4 carriers had 2 to 3 times higher prevalence estimates than noncarriers. The age at which 15% of the participants with normal cognition were amyloid positive was approximately 40 years for APOE ?4?4 carriers, 50 years for ?2?4 carriers, 55 years for ?3?4 carriers, 65 years for ?3?3 carriers, and 95 years for ?2?3 carriers. Amyloid positivity was more common in highly educated participants but not associated with sex or biomarker modality.Among persons without dementia, the prevalence of cerebral amyloid pathology as determined by positron emission tomography or cerebrospinal fluid findings was associated with age, APOE genotype, and presence of cognitive impairment. These findings suggest a 20- to 30-year interval between first development of amyloid positivity and onset of dementia.
| S-EPMC4486209 | biostudies-literature
Project description:ObjectiveTo estimate the incidence of and to characterize cognitive and imaging findings associated with incident amyloid PET positivity.MethodsCognitively normal (CN) participants in the Mayo Clinic Study of Aging who had 2 or more serial imaging assessments, which included amyloid PET, FDG-PET, and MRI at each time point, were eligible for analysis (n = 207). Twelve subjects with Alzheimer disease dementia were included for comparison.ResultsOf the 123 CN participants who were amyloid-negative at baseline, 26 met criteria for incident amyloid PET positivity. Compared to the 69 subjects who remained stable amyloid-negative, on average these 26 did not differ on any imaging, demographic, or cognitive variables except amyloid PET (by definition) and task-free functional connectivity, which at baseline was greater in the incident amyloid-positive group. Eleven of the 26 incident amyloid-positive subjects had abnormal hippocampal volume, FDG-PET, or both at baseline.ConclusionsThe incidence of amyloid PET positivity is approximately 13% per year among CN participants over age 70 sampled from a population-based cohort. In 15/26 (58%), incident amyloid positivity occurred prior to abnormalities in FDG-PET and hippocampal volume. However, 11/26 (42%) incident amyloid-positive subjects had evidence of neurodegeneration prior to incident amyloid positivity. These 11 could be subjects with combinations of preexisting non-Alzheimer pathophysiologies and tau-mediated neurodegeneration who newly entered the amyloid pathway. Our findings suggest that both "amyloid-first" and "neurodegeneration-first" biomarker profile pathways to preclinical AD exist.
| S-EPMC3821718 | biostudies-literature
Project description:Importance:Brain amyloid deposition is a marker of Alzheimer disease (AD) pathology. The population-based prevalence and outcomes of amyloid positivity in a population without dementia are important for understanding the trajectory of amyloid positivity to clinically significant outcomes and for designing AD prevention trials. Objective:To determine prevalence and outcomes of amyloid positivity in a population without dementia. Design, Setting, and Participants:In the prospective, population-based Mayo Clinic Study of Aging in Olmsted County, Minnesota, participants without dementia were randomly selected from the county population and were clinically and cognitively evaluated at baseline and every 15 months from August 1, 2008, to September 18, 2018. They were also invited to undergo carbon11-Pittburgh compound B positron emission tomography (PET) imaging. Exposures:Amyloid positivity (defined as a standardized uptake value ratio >1.42 on PET). Main Outcomes and Measures:Prevalence of amyloid positivity in the Olmsted County population without dementia and risk of progression from no cognitive impairment (ie, normal cognition for age) to incident amnestic MCI (aMCI) and from MCI or aMCI to incident AD dementia. Results:Of 3894 participants, 1671 underwent PET imaging and were included in the study; 2198 did not undergo imaging, and 25 were excluded for other reasons. The mean (SD) age of participants was 71.3 (9.8) years; 892 (53.4%) were men, and 179 (10.7%) had prevalent MCI. The prevalence of amyloid positivity without cognitive impairment in the population without dementia increased from 2.7% (95% CI, 0.5% to 4.9%) in persons aged 50 to 59 years to 41.3% (95% CI, 33.4% to 49.2%) in those aged 80 to 89 years at baseline. Prevalence of amyloid-positive MCI in the population without dementia increased from 0% in persons aged 50 to 59 years to 16.4% (95% CI, 10.3% to 22.5%) in those aged 80 to 89 years. The incident aMCI risk increased more than 2-fold in participants without cognitive impairment who were amyloid positive vs those who were amyloid negative (hazard ratio [HR], 2.26; 95% CI, 1.52 to 3.35; P < .001). The risk of AD dementia was 1.86 (95% CI, 0.89 to 3.88; P = .10) for amyloid-positive participants with MCI vs amyloid-negative participants with MCI, 1.63 (95% CI, 0.78 to 3.41; P = .20) for participants with aMCI who were amyloid positive vs amyloid negative, and 2.56 (95% CI, 1.35 to 4.88; P = .004) for amyloid-positive participants who were either without cognitive impairment or had aMCI vs those who were amyloid negative. Global cognitive and memory domain z scores declined significantly in amyloid-positive individuals during follow-up. The mean (SD) follow-up time from baseline was 3.7 (1.9) years to incident aMCI and 3.8 (2.0) years to incident AD dementia. Conclusions and Relevance:Population-based prevalence of amyloid-positive status and progression rates of amyloid positivity provide valid information for designing AD prevention trials and assessing the public health outcomes of AD prevention and interventions.
| S-EPMC6142936 | biostudies-literature
Project description:BackgroundInconsistent positivity thresholds, image analysis pipelines, and quantitative outcomes are key challenges of multisite studies using more than one β-amyloid (Aβ) radiotracer in positron emission tomography (PET). Variability related to these factors contributes to disagreement and lack of replicability in research and clinical trials. To address these problems and promote Aβ PET harmonization, we used [18F]florbetaben (FBB) and [18F]florbetapir (FBP) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to derive (1) standardized Centiloid (CL) transformations and (2) internally consistent positivity thresholds based on separate young control samples.MethodsWe analyzed Aβ PET data using a native-space, automated image processing pipeline that is used for PET quantification in many large, multisite AD studies and trials and made available to the research community. With this pipeline, we derived SUVR-to-CL transformations using the Global Alzheimer's Association Interactive Network data; we used reference regions for cross-sectional (whole cerebellum) and longitudinal (subcortical white matter, brain stem, whole cerebellum) analyses. Finally, we developed a FBB positivity threshold using an independent young control sample (N=62) with methods parallel to our existing FBP positivity threshold and validated the FBB threshold using a data-driven approach in ADNI participants (N=295).ResultsThe FBB threshold based on the young sample (1.08; 18 CL) was consistent with that of the data-driven approach (1.10; 21 CL), and the existing FBP threshold converted to CL with the derived transformation (1.11; 20 CL). The following equations can be used to convert whole cerebellum- (cross-sectional) and composite- (longitudinal) normalized FBB and FBP data quantified with the native-space pipeline to CL units: [18F]FBB: CLwhole cerebellum = 157.15 × SUVRFBB - 151.87; threshold=1.08, 18 CL [18F]FBP: CLwhole cerebellum = 188.22 × SUVRFBP - 189.16; threshold=1.11, 20 CL [18F]FBB: CLcomposite = 244.20 × SUVRFBB - 170.80 [18F]FBP: CLcomposite = 300.66 × SUVRFBP - 208.84 CONCLUSIONS: FBB and FBP positivity thresholds derived from independent young control samples and quantified using an automated, native-space approach result in similar CL values. These findings are applicable to thousands of available and anticipated outcomes analyzed using this pipeline and shared with the scientific community. This work demonstrates the feasibility of harmonized PET acquisition and analysis in multisite PET studies and internal consistency of positivity thresholds in standardized units.
| S-EPMC8111744 | biostudies-literature
Project description:IntroductionThe diagnostic utility of in vivo amyloid ? (A?) imaging to aid in the clinical distinction between frontotemporal dementia (FTD) and Alzheimer's disease remains unclear without data on the prevalence and severity of A? in pathologically confirmed FTD syndromes.MethodsA? was assessed in 98 autopsy-confirmed FTD and 36 control cases, and the pathological accuracy of 11C-Pittsburgh compound B (PiB)-positron emission tomography imaging was assessed in a subset of FTD cases (n = 15).ResultsA? was identified in a similar proportion of FTD syndromes and age-matched controls and increases with age. Alzheimer's disease pathology was identified in all cases with high PiB retention and in one case with low PiB retention. We further demonstrate a strong regional correlation between volume fraction of histological A? with PiB standard uptake value ratio scaled to the white matter.DiscussionThe present study provides a pathologic reference to assist in the interpretation of in vivo assessments in FTD syndromes.
| S-EPMC5473545 | biostudies-literature
Project description:Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to facilitate prognostic prediction and appropriate treatment decisions. In this study, we applied two interpretable machine learning algorithms, gradient boosting machine (GBM) and random forest (RF), to predict Aβ PET positivity in patients with CAA MRI markers. In the GBM algorithm, the number of lobar cerebral microbleeds (CMBs), deep CMBs, lacunes, CMBs in dentate nuclei, and age were ranked as the most influential to predict Aβ positivity. In the RF algorithm, the absence of diabetes was additionally chosen. Cut-off values of the above variables predictive of Aβ positivity were as follows: (1) the number of lobar CMBs > 16.4(GBM)/14.3(RF), (2) no deep CMBs(GBM/RF), (3) the number of lacunes > 7.4(GBM/RF), (4) age > 74.3(GBM)/64(RF), (5) no CMBs in dentate nucleus(GBM/RF). The classification performances based on the area under the receiver operating characteristic curve were 0.83 in GBM and 0.80 in RF. Our study demonstrates the utility of interpretable machine learning in the clinical setting by quantifying the relative importance and cutoff values of predictive variables for Aβ positivity in patients with suspected CAA markers.
| S-EPMC7608617 | biostudies-literature
Project description:Reference region selection is important for proper amyloid PET analysis, especially in subcortical vascular dementia (SVaD) patients. We investigated reference region differences between SVaD and Alzheimer's disease (AD) using Centiloid scores. In 57 [C-11] Pittsburgh compound B (PiB) positive (+) AD and 23 PiB (+) SVaD patients, we assessed standardized PiB uptake and Centiloid scores in disease-specific cortical regions, with several reference regions: cerebellar gray (CG), whole cerebellum (WC), WC with brainstem (WC?+?B), pons, and white matter (WM). We calculated disease group differences from young controls (YC) and YC variance according to reference region. SVaD patients showed large effect sizes (Cohen's d?>?0.8) using all reference regions. WM and pons showed larger YC variances than other regions. Findings were similar for AD patients. CG, WC, and WC?+?B, but not WM or pons, are reliable reference regions for amyloid imaging analysis in SVaD.
| S-EPMC5701176 | biostudies-literature
Project description:Background: The tau positron emission tomography (PET) ligand 18F-flortaucipir binds to paired helical filaments of tau in aging and Alzheimer's disease (AD), but its utility in detecting tau aggregates in frontotemporal dementia (FTD) is uncertain.Methods: We performed 18F-flortaucipir imaging in patients with the FTD syndromes (n?=?45): nonfluent variant primary progressive aphasia (nfvPPA) (n?=?11), corticobasal syndrome (CBS) (n?=?10), behavioral variant frontotemporal dementia (bvFTD) (n?=?10), semantic variant primary progressive aphasia (svPPA) (n?=?2) and FTD associated pathogenic genetic mutations microtubule-associated protein tau (MAPT) (n?=?6), chromosome 9 open reading frame 72 (C9ORF72) (n?=?5), and progranulin (GRN) (n?=?1). All patients underwent MRI and ?-amyloid biomarker testing via 11C-PiB or cerebrospinal fluid. 18F-flortaucipir uptake in patients was compared to 53 ?-amyloid negative normal controls using voxelwise and pre-specified region of interest approaches.Results: On qualitative assessment, patients with nfvPPA showed elevated 18F-flortacupir binding in the left greater than right inferior frontal gyrus. Patients with CBS showed elevated binding in frontal white matter, with higher cortical gray matter uptake in a subset of ?-amyloid-positive patients. Five of ten patients with sporadic bvFTD demonstrated increased frontotemporal binding. MAPT mutation carriers had elevated 18F-flortaucipir retention primarily, but not exclusively, in mutations with Alzheimer's-like neurofibrillary tangles. However, tracer retention was also seen in patients with svPPA, and the mutations C9ORF72, GRN predicted to have TDP-43 pathology. Quantitative region-of-interest differences between patients and controls were seen only in inferior frontal gyrus in nfvPPA and left insula and bilateral temporal poles in MAPT carriers. No significant regional differences were found in CBS or sporadic bvFTD. Two patients underwent postmortem neuropathological examination. A patient with C9ORF72, TDP-43-type B pathology, and incidental co-pathology of scattered neurofibrillary tangles in the middle frontal, inferior temporal gyrus showed corresponding mild 18F-flortaucipir retention without additional uptake matching the widespread TDP-43 type B pathology. A patient with sporadic bvFTD demonstrated punctate inferior temporal and hippocampus tracer retention, corresponding to the area of severe argyrophilic grain disease pathology.Conclusions: 18F-flortaucipir in patients with FTD and predicted tauopathy or TDP-43 pathology demonstrated limited sensitivity and specificity. Further postmortem pathological confirmation and development of FTD tau-specific ligands are needed.
| S-EPMC6357510 | biostudies-literature
Project description:BackgroundSleep disorders are common in people with intellectual disability (ID) and autism, with growing evidence of diverse sleep profiles across ID associated genetic syndromes. Documenting the prevalence and profile of specific sleep disorders in syndromes will quantify syndrome-driven 'risk', inform prognosis and enhance understanding of aetiology of sleep disorders.MethodFollowing PRISMA guidelines for meta-analysis, we searched Ovid PsycINFO, Ovid MEDLINE, Ovid Embase, Web of Science and PubMed Central with use of syndrome-specific keywords and 60 sleep-related search terms. We screened and extracted papers that reported sleep disorder prevalence data for five or more individuals within a genetic syndrome, and applied quality criteria to produce a quality-effects prevalence model of six types of sleep disorder across nineteen syndromes. Relative risk estimates were calculated for the prevalence of each sleep disorder in each syndrome.ResultsTwo hundred and seventy three papers were identified, generating 463 prevalence estimates for Angelman, CHARGE, Cornelia de Lange, Down, fragile X, Prader-Willi, Rett, Smith-Magenis and Williams syndromes, mucopolysaccharidoses (MPS disorders), neurofibromatosis and tuberous sclerosis complex. Prevalence estimates were higher in genetic syndromes than published equivalents for typically developing individuals, with few exceptions. Between-syndrome differences for some disorders were evident; sleep-disordered breathing was most prevalent in MPS disorders (72-77%), while excessive daytime sleepiness was highest in Smith-Magenis syndrome (60%). Conversely, insomnia, which was reported at a higher rate than TD estimates in all syndromes except fragile X, was not associated with specific genetic risk. This suggests insomnia could emerge because of the individual's environment or associated developmental delay, rather than any specific genetic syndromes.LimitationsDue to the broad scope of the meta-analysis, only syndromes previously identified as reporting preliminary sleep research were included. Other syndromes may also experience elevated prevalence rates of specific types of sleep disorder. Only English language papers were included.ConclusionsDiffering prevalence rates between types of sleep disorder suggest differing causal mechanisms, such as cranio-facial morphology in Down and Prader-Willi syndromes and the build-up of mucopolysaccharides in MPS disorders. Priorities for clinical assessment and intervention for sleep disorders are discussed.
| S-EPMC7908701 | biostudies-literature
Project description:BackgroundStage 1 of the National Institute on Aging-Alzheimer's Association's proposed Alzheimer's disease continuum is defined as amyloid-β (Aβ) positive but cognitively normal. Identifying at-risk individuals before Aβ reaches pathological levels could have great benefits for early intervention. Although Aβ levels become abnormal long before severe cognitive impairments appear, increasing evidence suggests that subtle cognitive changes may begin early, potentially before Aβ surpasses the threshold for abnormality. We examined whether baseline cognitive performance would predict progression from normal to abnormal levels of Aβ.MethodsWe examined the association of baseline cognitive composites (Preclinical Alzheimer Cognitive Composite, Alzheimer's Disease Neuroimaging Initiative (ADNI) memory factor composite) with progression to Aβ positivity in 292 nondemented, Aβ-negative ADNI participants. Additional analyses included continuous cerebrospinal fluid biomarker levels to examine the effects of subthreshold pathology.ResultsForty participants progressed to Aβ positivity during follow-up. Poorer baseline performance on both cognitive measures was significantly associated with increased odds of progression. More abnormal levels of baseline cerebrospinal fluid phosphorylated tau and subthreshold Aβ were associated with increased odds of progression to Aβ positivity. Nevertheless, baseline ADNI memory factor composite performance predicted progression even after controlling for baseline biomarker levels and APOE genotype (Preclinical Alzheimer Cognitive Composite was trend level). Survival analyses were largely consistent: controlling for baseline biomarker levels, baseline Preclinical Alzheimer Cognitive Composite still significantly predicted progression time to Aβ positivity (ADNI memory factor composite was trend level).ConclusionsThe possibility of intervening before Aβ reaches pathological levels is of obvious benefit. Low-cost, noninvasive cognitive measures can be informative for determining who is likely to progress to Aβ positivity, even after accounting for baseline subthreshold biomarker levels.
| S-EPMC7166153 | biostudies-literature