21 research outputs found

    The central biobank and virtual biobank of BIOMARKAPD: A resource for studies on neurodegenerative diseases

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    Biobanks are important resources for biomarker discovery and assay development. Biomarkers for Alzheimer's and Parkinson's disease (BIOMARKAPD) is a European multicenter study, funded by the EU Joint Programme-Neurodegenerative Disease Research, which aims to improve the clinical use of body fluid markers for the diagnosis and prognosis of Alzheimer's disease (AD) and Parkinson's disease (PD). The objective was to standardize the assessment of existing assays and to validate novel fluid biomarkers for AD and PD. To support the validation of novel biomarkers and assays, a central and a virtual biobank for body fluids and associated data from subjects with neurodegenerative diseases have been established. In the central biobank, cerebrospinal fluid (CSF) and blood samples were collected according to the BIOMARKAPD standardized pre-analytical procedures and stored at Integrated BioBank of Luxembourg. The virtual biobank provides an overview of available CSF, plasma, serum, and DNA samples at each site. Currently, at the central biobank of BIOMARKAPD samples are available from over 400 subjects with normal cognition, mild cognitive impairment (MCI), AD, frontotemporal dementia (FTD), vascular dementia, multiple system atrophy, progressive supranuclear palsy, PD, PD with dementia, and dementia with Lewy bodies. The virtual biobank contains information on over 8,600 subjects with varying diagnoses from 21 local biobanks. A website has been launched to enable sample requests from the central biobank and virtual biobank. © 2015 Reijs, Teunissen, Goncharenko, Betsou, Blennow, Baldeiras, Brosseron, Cavedo, Fladby, Froelich, Gabryelewicz, Gurvit, Kapaki, Koson, Kulic, Lehmann, Lewczuk, Lleó, Maetzler, de Mendonça, Miller, Molinuevo, Mollenhauer, Parnetti, Rot, Schneider, Simonsen, Tagliavini, Tsolaki, Verbeek, Verhey, Zboch, Winblad, Scheltens, Zetterberg and Visser

    The central biobank and virtual biobank of BiOMarKaPD: a resource for studies on neurodegenerative diseases

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    Biobanks are important resources for biomarker discovery and assay development. Biomarkers for Alzheimer's and Parkinson's disease (BIOMARKAPD) is a European multi-center study, funded by the EU Joint Programme-Neurodegenerative Disease Research, which aims to improve the clinical use of body fluid markers for the diagnosis and prognosis of Alzheimer's disease (AD) and Parkinson's disease (PD). The objective was to standardize the assessment of existing assays and to validate novel fluid biomarkers for AD and PD. To support the validation of novel biomarkers and assays, a central and a virtual biobank for body fluids and associated data from subjects with neurodegenerative diseases have been established. In the central biobank, cerebrospinal fluid (CSF) and blood samples were collected according to the BIOMARKAPD standardized pre-analytical procedures and stored at Integrated BioBank of Luxembourg. The virtual biobank provides an overview of available CSF, plasma, serum, and DNA samples at each site. Currently, at the central biobank of BIOMARKAPD samples are available from over 400 subjects with normal cognition, mild cognitive impairment (MCI), AD, frontotemporal dementia (FTD), vascular dementia, multiple system atrophy, progressive supranuclear palsy, PD, PD with dementia, and dementia with Lewy bodies. The virtual biobank contains information on over 8,600 subjects with varying diagnoses from 21 local biobanks. A website has been launched to enable sample requests from the central biobank and virtual biobank

    Association of Cerebral Amyloid-beta Aggregation With Cognitive Functioning in Persons Without Dementia

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    IMPORTANCE Cerebral amyloid-beta aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials. OBJECTIVE To investigate whether amyloid-beta aggregation is associated with cognitive functioning in persons without dementia. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017. MAIN OUTCOMES AND MEASURES Global cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score <= 27 or memory z score <=-1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype. RESULTS Among 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4%[95% CI, 0%-7%] at 72 years and 21% [95% CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3%[95% CI, -1% to 6%], P =.16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16%[95% CI, 12%-20%], P < .001) and low MMSE (mean difference, 14%[95% CI, 12%-17%], P < .001) scores, and this association decreased with age. Low cognitive scores had limited utility for screening of amyloid positivity in persons with normal cognition and those with MCI. In persons with normal cognition, the age-related increase in low memory score paralleled the age-related increase in amyloid positivity with an intervening period of 10 to 15 years. CONCLUSIONS AND RELEVANCE Although low memory scores are an early marker of amyloid positivity, their value as a screening measure for early AD among persons without dementia is limited

    Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia

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    Importance: Cerebral amyloid-β aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials. // Objective: To investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia. // Design, Setting, and Participants: This cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017. // Main Outcomes and Measures: Global cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score ≤27 or memory z score≤−1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype. // Results: Among 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4% [95% CI, 0%-7%] at 72 years and 21% [95% CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3% [95% CI, −1% to 6%], P = .16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16% [95% CI, 12%-20%], P < .001) and low MMSE (mean difference, 14% [95% CI, 12%-17%], P < .001) scores, and this association decreased with age. Low cognitive scores had limited utility for screening of amyloid positivity in persons with normal cognition and those with MCI. In persons with normal cognition, the age-related increase in low memory score paralleled the age-related increase in amyloid positivity with an intervening period of 10 to 15 years. // Conclusions and Relevance: Although low memory scores are an early marker of amyloid positivity, their value as a screening measure for early AD among persons without dementia is limited

    Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

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    Importance: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design. Objective: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates. Design, Setting, and Participants: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria. Exposures: Alzheimer disease biomarkers detected on PET or in CSF. Main Outcomes and Measures: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations. Results: Among the 19097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P =.04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P =.004), subjective cognitive decline (9%; 95% CI, 3%-15%; P =.005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P =.004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P =.18). Conclusions and Relevance: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies. © 2022 American Medical Association. All rights reserved

    Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.

    No full text
    One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design. To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates. This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria. Alzheimer disease biomarkers detected on PET or in CSF. Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations. Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18). This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies
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