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ImportanceCerebral 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.ObjectiveTo investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia.Design, setting, and participantsThis 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 measuresGlobal 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.ResultsAmong 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

OBJECTIVE: Type 2 diabetes and glucose metabolism have previously been linked to Alzheimer disease (AD). Yet, findings on the relation of glucose metabolism with amyloid-β and tau pathology later in life remain unclear. RESEARCH DESIGN AND METHODS: We included 288 participants (mean age 43.1 years, SD 10.7, range 20–70 years) without dementia, from the Framingham Heart Study, who had available measures of glucose metabolism (i.e., one-time fasting plasma glucose and insulin) and positron emission tomography (PET) measures of amyloid-β and/or tau 14 years later. We performed linear regression analyses to test associations of plasma glucose (continuously and categorically; elevated defined as >100 mg/dL), plasma insulin, homeostatic model assessment for insulin resistance (HOMA-IR) with amyloid-β or tau load on PET. When significant, we explored whether age, sex, and APOE ε4 allele carriership (AD genetic risk) modified these associations. RESULTS: Our findings indicated that elevated plasma glucose was associated with greater tau load 14 years later (B [95% CI] = 0.03 [0.01–0.05], P = 0.024 after false discovery rate [FDR] correction) but not amyloid-β. APOE ε4 carriership modified this association (B [95% CI] = −0.08 [−0.12 to −0.03], P = 0.001), indicating that the association was only present in APOE ε4 noncarriers (n = 225). Plasma insulin and HOMA-IR were not associated with amyloid-β or tau load 14 years later after FDR correction. CONCLUSIONS: Our findings suggest that glucose metabolism is associated with increased future tau but not amyloid-β load. This provides relevant knowledge for prevention strategies and prognostics to improve health care. [ABSTRACT FROM AUTHOR]

ImportanceCerebral amyloid-β 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.ObjectiveTo 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).Data sourcesRelevant biomarker studies identified by searching studies published before April 2015 using the MEDLINE and Web of Science databases and through personal communication with investigators.Study selectionStudies were included if they provided individual participant data for participants without dementia and used an a priori defined cutoff for amyloid positivity.Data extraction and synthesisIndividual records were provided for 2914 participants with normal cognition, 697 with SCI, and 3972 with MCI aged 18 to 100 years from 55 studies.Main outcomes and measuresPrevalence 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.ResultsThe 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-ε4 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 ε4ε4 carriers, 50 years for ε2ε4 carriers, 55 years for ε3ε4 carriers, 65 years for ε3ε3 carriers, and 95 years for ε2ε3 carriers. Amyloid positivity was more common in highly educated participants but not associated with sex or biomarker modality.Conclusions and relevanceAmong 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.

ImportanceAmyloid-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.ObjectiveTo use individual participant data meta-analysis to estimate the prevalence of amyloid positivity on PET in a wide variety of dementia syndromes.Data sourcesThe MEDLINE and Web of Science databases were searched from January 2004 to April 2015 for amyloid PET studies.Study selectionCase reports and studies on neurological or psychiatric diseases other than dementia were excluded. Corresponding authors of eligible cohorts were invited to provide individual participant data.Data extraction and synthesisData were provided for 1359 participants with clinically diagnosed AD and 538 participants with non-AD dementia. The reference groups were 1849 healthy control participants (based on amyloid PET) and an independent sample of 1369 AD participants (based on autopsy).Main outcomes and measuresEstimated prevalence of positive amyloid PET scans according to diagnosis, age, and apolipoprotein E (APOE) ε4 status, using the generalized estimating equations method.ResultsThe likelihood of amyloid positivity was associated with age and APOE ε4 status. In AD dementia, the prevalence of amyloid positivity decreased from age 50 to 90 years in APOE ε4 noncarriers (86% [95% CI, 73%-94%] at 50 years to 68% [95% CI, 57%-77%] at 90 years; n = 377) and to a lesser degree in APOE ε4 carriers (97% [95% CI, 92%-99%] at 50 years to 90% [95% CI, 83%-94%] at 90 years; n = 593; P

Perivascular spaces (PVS) and blood–brain barrier (BBB) disruption are two key features of cerebral small vessel disease (cSVD) and neurodegenerative diseases that have been linked to cognitive impairment and are involved in the cerebral waste clearance system. Magnetic resonance imaging (MRI) offers the possibility to study these pathophysiological processes noninvasively in vivo. This educational review provides an overview of the MRI techniques used to assess PVS functionality and BBB disruption. MRI‐visible PVS can be scored on structural images by either (subjectively) counting or (automatically) delineating the PVS. We highlight emerging (diffusion) techniques to measure proxies of perivascular fluid and its movement, which may provide a more comprehensive understanding of the role of PVS in diseases. For the measurement of BBB disruption, we explain the most commonly used MRI technique, dynamic contrast‐enhanced (DCE) MRI, as well as a more recently developed technique based on arterial spin labeling (ASL). DCE MRI and ASL are thought to measure complementary characteristics of the BBB. Furthermore, we describe clinical studies that have utilized these MRI techniques in cSVD and neurodegenerative diseases, particularly Alzheimer's disease (AD). These studies demonstrate the role of PVS and BBB dysfunction in these diseases and provide insight into the large overlap, but also into the differences between cSVD and AD. Overall, MRI techniques may provide valuable insights into the pathophysiological mechanisms underlying these diseases and have the potential to be used as markers for disease progression and treatment response. Level of Evidence: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Background: The relationship between cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD), APOE‐ε4 and longitudinal cortical amyloid deposition in preclinical AD is relevant for AD trial design but remains unclear. Thus, we aimed to investigate longitudinal cortical amyloid accumulation on PET as predicted by baseline CSF AD biomarker profiles and APOE‐ε4 carriership in cognitively unimpaired individuals. Method: We selected 330 cognitively unimpaired individuals from 6 cohorts of the AMYPAD study. All had available baseline data on CSF aß1‐42 (A), p‐tau181 (T), APOE‐ε4 carriership (yes/no), and baseline and follow‐up amyloid PET data. To evaluate different AD stages, individuals were classified as A‐T‐, A‐T+, A+T‐, or A+T+ based on CSF biomarker abnormality using center‐specific cut‐offs. We used a continuous outcome measure of global cortical amyloid deposition on PET expressed in centiloids. Analyses were performed in the total sample and stratified for APOE‐ε4, using generalized linear mixed models with random intercepts and slopes, adjusted for age and sex. Result: 58% were female, 49% APOE‐ε4 carriers, and mean age was 64+‐6.1 years, with an average follow‐up of 3 years. 170 individuals were A‐T‐, 70 A‐T+, 59 A+T‐, and 31 A+T+. Baseline cortical amyloid deposition was different between all groups, with A+T+ having the highest deposition, followed by A+T‐, A‐T+ and A‐T‐ (Figure 1, Table 1). Longitudinally, all groups showed increased amyloid deposition, except A‐T‐. Moreover, A+ groups showed greater increases in longitudinal amyloid deposition than A‐ groups. In APOE‐ε4 carriers, all AT groups showed increased longitudinal amyloid deposition, while in non‐carriers, A‐T+ and A‐T‐ did not (Figure 2, Table 1). Only in APOE‐ε4 carriers, A+T+ showed greater increases in longitudinal amyloid deposition than A+T‐, with A+T‐ showing a similar longitudinal deposition as A‐T+. Conclusion: APOE‐ε4 impacts the association between CSF AD biomarkers and longitudinal amyloid PET deposition in cognitively unimpaired persons. Amyloid‐negative APOE‐ε4 carriers could be at an early AD stage, as they showed increased cortical amyloid longitudinally, independent of baseline p‐tau status. In amyloid‐positive persons, p‐tau abnormality related to higher baseline cortical amyloid, but only in APOE‐ε4 carriers to steeper increases in cortical amyloid longitudinally. This has important implications for AD trial design. [ABSTRACT FROM AUTHOR]

Background: Diabetes and blood glucose markers have previously been linked to cognitive decline. However, findings on the relation of diabetes with underlying Alzheimer's disease (AD) biomarkers are inconclusive. We aimed to explore whether diabetes and blood glucose markers are associated with AD biomarkers in cerebrospinal fluid (CSF) by performing a meta‐analysis of existing studies. Method: A systematic search in PubMed and Embase with abstract and full‐text screening resulted in the inclusion of 13 studies with 5,052 participants in our meta‐analysis. We included studies that provided results on the association between a diabetes measure and an AD biomarker in CSF (Table 1). Diabetes measures included diabetes diagnosis or glucose measures, i.e. fasting blood glucose, HbA1c, or insulin resistance index. AD biomarkers included CSF amyloid‐beta42, p‐tau and/or t‐tau. Where needed, results were converted to partial or biserial correlation coefficients. We performed a random effects meta‐analysis on the correlation coefficients per CSF biomarker, using the DerSimonian and Laird procedure and Knapp‐Hartung method. Meta‐regression was used to test potential moderating effects of age, sex, setting (memory clinic or population), % dementia cases, correlation type (Pearson, partial, or biserial), diabetes measure (diabetes diagnosis or glucose marker), MMSE score, and APOEe4 carriership (yes/no). All analyses were performed using the metafor package in R. Result: Our meta‐analysis showed small but significant associations of diabetes measures with increased (more normal) levels of amyloid‐beta42 (r = 0.08, p = 0.04, Figure 1) and increased (more abnormal) levels of p‐tau (r = 0.09, p = 0.04, Figure 2) and t‐tau (r = 0.10, p = 0.04, graph not shown as comparable to p‐tau). Heterogeneity was high for all outcomes (I2>60%, p<0.05 for Q‐test, wide prediction intervals). Meta‐regression analyses showed that heterogeneity in CSF amyloid could partly be explained by setting, as the association between diabetes measures and amyloid was only present in memory clinic studies as compared to population studies (difference estimate = 0.14, p = 0.03). Similarly, studies with more dementia cases showed a stronger association with amyloid (slope estimate = 0.0029, p = 0.001). No other moderating effects were found. Conclusion: Our findings suggest that diabetes measures are associated with tau‐related neurodegeneration that is independent from amyloid. This is valuable for improving diagnostics and treatment of patients with diabetes and AD. [ABSTRACT FROM AUTHOR]

Background: Amyloid deposition and hippocampal atrophy have been linked to late‐life affective disorders, raising concerns for Alzheimer's Disease (AD). However, biomarker and autopsy studies have been inconclusive. It remains unclear if and in what way depressive symptoms imply an increased risk of amyloid positivity. Method: Using data from 49 centers in the Amyloid Biomarker Study, we investigated the association between depressive symptoms and amyloid positivity. We included participants with normal cognition (NC) (n = 9776) and MCI (n = 2995). Amyloid positivity was defined using standardized CSF (n = 5926) and PET (n = 6845) measures. Depressive symptoms were obtained through medical history (12%) and various rating scales (88%). Symptoms on rating scales were classified as (1) present/absent using established cut‐off values, (2) severity using center‐based trichotomisation. We examined associations between depressive symptoms and amyloid positivity using generalized estimating equations and evaluated potential moderation by age and APOE‐e4 status. Result: Mean age was 69 years and 33.8% were amyloid positive. In NC, no association between the presence or severity of depressive symptoms and amyloid positivity was observed, nor was there when including APOE‐e4, sex or education. In MCI, persons with depressive symptoms were ∼10% less often amyloid positive than those without depressive symptoms (p = 0.001), this was even more pronounced in persons with moderately severe symptoms (p = 0.01). We identified an interaction between depressive symptom severity and APOE‐e4 status (p = 0.034). In APOE‐e4 noncarriers with MCI, persons with moderate depressive symptoms were 20% less often amyloid positive than those with no or mild depressive symptoms. In APOE‐e4 carriers with MCI, depressive symptom severity was not associated with amyloid positivity. Conclusion: In persons with normal cognition, depressive symptoms are not associated with amyloid positivity. In MCI patients, however, those with depressive symptoms were ∼10% less often amyloid positive. This association increased in persons with moderately severe symptoms and appeared to pertain to APOE‐e4 noncarriers. These data suggest that the presence of depressive symptoms in MCI patients is no reliable indicator of amyloid positivity. This may have diagnostic implications for this group. [ABSTRACT FROM AUTHOR]

Background: Cerebral microbleeds (CMBs) are common in the elderly population and are associated with cognitive decline. The aim of the current study was to examine the association between CMBs and cerebral amyloid pathology in cognitively unimpaired (CU) and cognitively impaired (CI) individuals included in the Amyloid Biomarker Study. Method: We included 2550 CU and 1002 CI participants from 12 cohorts of the Amyloid Biomarker Study. Presence of amyloid pathology was determined based on Aß42 levels in CSF (n = 2873) or amyloid‐PET (n = 679) using data‐driven or center‐specific cutoffs. CMBs were assessed on in vivo MRI and were classified as present (≥1) or absent. The association of amyloid pathology with CMBs and its dependency on age, sex, APOE‐e4 carriership and hypertension was assessed using generalized‐estimating‐equations. Result: Thirty‐seven percent of participants were amyloid positive, 38% were APOE‐e4 carrier, 54% were female, 30% had hypertension and 17% had CMBs (20% of the amyloid positive and 16% of the amyloid negative group, respectively). The mean age was 66.7 years (SD9.2). In CU participants, there was no association between amyloid pathology and CMBs. In CI individuals, CMB prevalence was associated with amyloid pathology depending on age (p = 0.044). At younger ages (<75 years), CMBs were more common in amyloid positive rather than amyloid negative participants while at older ages, amyloid negative participants had CMBs more often. However, the interaction between amyloid status and age became insignificant when hypertension was considered. CMB prevalence was associated with amyloid pathology depending on hypertension (p = 0.006). In CI participants without hypertension, CMBs were more common in those that were amyloid positive rather than amyloid negative. In CI participants with hypertension, there was no significant difference in CMB prevalence between the amyloid positive and negative groups (Figure 1). Sex and APOE‐e4 status did not affect the observed associations between amyloid pathology and CMBs in participants with CI. Conclusion: CMB prevalence is associated with amyloid pathology and this association is dependent on hypertension. Knowledge on the background prevalence of CMBs considering AD biomarker and vascular risk factor status is needed to inform clinical trial design and safety evaluation of AD therapies. [ABSTRACT FROM AUTHOR]

Background: Prevalence estimates of amyloid positivity in persons across the AD clinical spectrum are important to reduce screen failure rates and improve recruitment efficiency in anti‐amyloid trials. We have previously estimated the prevalence according to age, sex, education and APOE genotype. It is however unknown whether these prevalence estimates generalize to diverse ethnoracial groups. We here aim to estimate the prevalence of amyloid abnormality in Black, White and Asian persons without dementia and examine associations with age, sex, educational level and APOE‐e4 carrier status. Method: We selected 7,419 participants (6,083 with normal cognition; 1,336 with MCI) from 9 Amyloid Biomarker Study cohorts, including 291 Black, 6,310 White and 818 Asian participants. Amyloid positivity was determined with a PET (n = 5,714) or CSF (n = 1,705) biomarker, using data‐driven or study‐specific cutoffs. Generalized estimating equations were used to estimate the age‐related prevalence by ethnoracial group and to evaluate moderation by APOE‐e4 carrier status while adjusting for sex and education. Result: The mean age was 70.9+‐7.4 years, 3,848 (57%) were women, and 20% were APOE‐e4 carriers. In persons with normal cognition, the age‐related prevalence of amyloid positivity was higher for White (25%) than for Black (17%) and Asian (16%) participants (p = 0.016). Among APOE‐e4 carriers with normal cognition, the prevalence of amyloid abnormality was again higher for White (46%) than for Black (29%) and Asian (30%) participants (Asian vs Black p‐value = 0.046, Asian vs White p‐value<0.001, Black vs White p‐value<0.001). Among APOE‐e4 noncarriers, no differences among the ethnoracial groups were identified (p = 0.56). In persons with MCI, White (59%) and Asian (60%) participants had abnormal amyloid more often than Black participants (43%; p<0.001). Ethnoracial differences were similar for APOE‐e4 carriers and noncarriers with MCI. Conclusion: In persons with normal cognition, the prevalence of amyloid abnormality among APOE‐e4 carriers was ∼15% higher for White than for Black and Asian participants, while among APOE‐e4 noncarriers no ethnoracial differences were found. In persons with MCI, both White and Asian participants ∼15% more often had abnormal amyloid than Black participants, irrespective of APOE‐e4 carrier status. Ethnoracial status may be an important factor to consider in the design of AD clinical trials. [ABSTRACT FROM AUTHOR]

Background: We have updated our previous amyloid positivity prevalence estimates (Jansen, 2015; Ossenkoppele, 2015; Table 1) with data from 19,097 individuals from 85 cohorts. We tested if prevalence estimates differed for positron emission tomography (PET) or cerebrospinal fluid (CSF) amyloid. We calculated data‐driven CSF cut‐points as previous studies suggested a drift in Innotest‐assay performance. Method: We included 9,908 participants with normal cognition (CN); 1,542 with subjective cognitive decline (SCD); 5,405 with mild cognitive impairment (MCI); and 2,260 with clinical Alzheimer's disease (AD) dementia. 10,139 participants had an amyloid‐PET measure and 8,958 participants had an amyloid‐CSF measure. Amyloid‐ß aggregation was originally dichotomized as normal or abnormal according to study‐specific cut‐points, and we defined data‐driven CSF cut‐points using Gaussian mixture modelling. Generalized‐estimating‐equations adjusting for within‐study clustering of individuals were used to estimate amyloid positivity prevalence according to age, cognitive status, and biomarker modality and compared original with updated cut‐points. Result: Amyloid positivity prevalence was higher with older age and advancing disease severity. Using original cut‐points as provided by the cohort, the prevalence of amyloid positivity at the median age of 70 was similar for PET and CSF estimates for CN (24%), SCD (26%), and MCI (51%), and was higher in PET (87%) than CSF (79%) for clinical AD dementia. Using the data‐driven CSF cut‐points, the prevalence of amyloid positivity was higher for CSF‐based estimates than PET‐based estimates in CN (CSF 33%, PET 24%), SCD (CSF 36%, PET 27%), and MCI (CSF 60%, PET 49%), but comparable in CSF and PET in clinically diagnosed AD dementia (CSF 83%, PET 87) (Table 1, Figure 1). Conclusion: We provide updated amyloid positivity estimates from the Amyloid Biomarker Study. CSF‐based estimates using a data‐driven approach resulted in higher estimates (up to 11% higher) in people without clinical AD dementia than PET‐based estimates. Whether CSF‐based estimates are more sensitive than PET‐based estimates for amyloid pathology among people without dementia needs to be explored in cohorts that use both modalities. These updated estimates may be useful to understand potential eligible patient population sizes for anti‐amyloid therapies and to inform recruitment strategies for clinical trials investigating anti‐amyloid therapies. [ABSTRACT FROM AUTHOR]