Explore the vast range of titles available.

Neurofilament light chain (NfL) is a promising biomarker of active axonal injury and neuronal degeneration. We aimed to characterise cross-sectional and longitudinal plasma NfL measurements and determine the age at which NfL concentrations begin to differentiate between carriers of the presenilin 1 (PSEN1) E280A (Glu280Ala) mutation and age-matched non-carriers from the Colombian autosomal dominant Alzheimer's disease kindred. In this cross-sectional and longitudinal cohort study, members of the familial Alzheimer's disease Colombian kindred aged 8–75 years with no other neurological or health conditions were recruited from the Alzheimer's Prevention Initiative Registry at the University of Antioquia (Medellín, Colombia) between Aug 1, 1995, and Dec 15, 2018. We used a single molecule array immunoassay and log-transformed data to examine the relationship between plasma NfL concentrations and age, and establish the earliest age at which NfL concentrations begin to diverge between mutation carriers and non-carriers. We enrolled a cohort of 1070 PSEN1 E280A mutation carriers and 1074 non-carriers with baseline assessments; of these participants, longitudinal measures (with a mean follow-up of 6 years) were available for 242 mutation carriers and 262 non-carriers. Plasma NfL measurements increased with age in both groups (p<0·0001), and began to differentiate carriers from non-carriers when aged 22 years (22 years before the estimated median age at mild cognitive impairment onset of 44 years), although the ability of plasma NfL to discriminate between carriers and non-carriers only reached high sensitivity close to the age of clinical onset. Our findings further support the promise of plasma NfL as a biomarker of active neurodegeneration in the detection and tracking of Alzheimer's disease and the evaluation of disease-modifying therapies. National Institute on Aging, National Institute of Neurological Disorders and Stroke, Banner Alzheimer's Foundation, COLCIENCIAS, the Torsten Söderberg Foundation, the Swedish Research Council, the Swedish Alzheimer Foundation, the Swedish Brain Foundation, and the Swedish state under the ALF-agreement.

Autosomal dominant Alzheimer’s disease (ADAD) is genetically determined, but variability in age of symptom onset suggests additional factors may influence cognitive trajectories. Although apolipoprotein E ( APOE ) genotype and educational attainment both influence dementia onset in sporadic AD, evidence for these effects in ADAD is limited. To investigate the effects of APOE and educational attainment on age-related cognitive trajectories in ADAD, we analyzed data from 675 Presenilin-1 E280A mutation carriers and 594 non-carriers. Here we show that age-related cognitive decline is accelerated in ADAD mutation carriers who also have an APOE e4 allele compared to those who do not and delayed in mutation carriers who also have an APOE e2 allele compared to those who do not. Educational attainment is protective and moderates the effect of APOE on cognition. Despite ADAD mutation carriers being genetically determined to develop dementia, age-related cognitive decline may be influenced by other genetic and environmental factors. PSEN1 E280A carriers develop dementia by midlife, but there is variability in disease trajectory. Cognitive decline is accelerated in E280A carriers who also have an APOE e4 allele. Educational attainment moderates the effect of APOE on cognition.

Background Plasma neurofilament light (NfL) is an indicator of neurodegeneration and/or neuroaxonal injury in persons with Alzheimer’s disease (AD) and a wide range of other neurological disorders. Here, we characterized and compared plasma NfL concentrations in cognitively unimpaired (CU) late-middle-aged and older adults with two, one, or no copies of the APOE ε4 allele, the major genetic risk factor for AD. We then assessed plasma NfL associations with brain imaging measurements of AD-related neurodegeneration (hippocampal atrophy and a hypometabolic convergence index [HCI]), brain imaging measurements of amyloid-β plaque burden, tau tangle burden and white matter hyperintensity volume (WMHV), and delayed and total recall memory scores. Methods Plasma NfL concentrations were measured in 543 CU 69 ± 9 year-old participants in the Arizona APOE Cohort Study, including 66 APOE ε4 homozygotes (HM), 165 heterozygotes (HT), and 312 non-carriers (NC). Robust regression models were used to characterize plasma NfL associations with APOE ε4 allelic dose before and after adjustment for age, sex, and education. They were also used to characterize plasma NfL associations with MRI-based hippocampal volume and WMHV measurements, an FDG PET-based HCI, mean cortical PiB PET measurements of amyloid-β plaque burden and meta-region-of-interest (meta-ROI) flortaucipir PET measurements of tau tangle burden, and Auditory Verbal Learning Test (AVLT) Delayed and Total Recall Memory scores. Results After the adjustments noted above, plasma NfL levels were significantly greater in APOE ε4 homozygotes and heterozygotes than non-carriers and significantly associated with smaller hippocampal volumes ( r  =  − 0.43), greater tangle burden in the entorhinal cortex and inferior temporal lobes ( r  = 0.49, r  = 0.52, respectively), and lower delayed ( r  =  − 0.27), and total ( r  =  − 0.27) recall memory scores ( p  < 0.001). NfL levels were not significantly associated with PET measurements of amyloid-β plaque or total tangle burden. Conclusions Plasma NfL concentrations are associated with the APOE ε4 allele, brain imaging biomarkers of neurodegeneration, and less good recall memory in CU late-middle-aged and older adults, supporting its value as an indicator of neurodegeneration in the preclinical study of AD.

Background Recent genome-wide association studies for Alzheimer’s Disease and related dementias (ADRD) have increased statistical power via larger analysis datasets from biobanks by (1) including non-age-matched controls and prevalent cases, and/or (2) including individuals who report a family history of ADRD as proxy cases. However, these methods have the potential to increase noise and distort genetic associations which are important for genomic-informed prevention and treatment of ADRD. Here, we sought to understand how the effect sizes of genetic associations in ADRD could be sensitive to these methodological choices, using APOE genotypes as an example. Methods Participants in the All of Us Research Program over the age of 49 at enrollment ( n  = 229,722) were assigned one of four categories: incident ADRD (developed after enrollment in All of Us ), prevalent ADRD (present on enrollment), proxy ADRD (participant noted a family history of ADRD), and control (no history or diagnosis of ADRD). ADRD diagnoses were determined using available electronic health records and APOE genotype was determined using whole-genome sequencing. Effect sizes for the associations between APOE risk alleles and ADRD diagnoses were compared using polychotomous logistic regression and presented as adjusted generalized ratios (AGR). Results The mean age of the cohort was 64 ± 9 years, and it was 57% female; 65% clustered predominantly with European genetic reference populations. Among the participants, 733 (0.3%) had prevalent ADRD, 684 (0.3%) had incident ADRD, and 19,186 (8.4%) reported a family history of ADRD (proxy ADRD). The effect size for APOE ε4 heterozygote was similar for proxy ADRD (AGR [95% CI]: 2.10 [1.96–2.24]) but attenuated for prevalent ADRD (1.38 [1.17–1.63]) compared to incident ADRD (2.13 [1.81–2.50]). For APOE ε4 homozygotes, the effect sizes were significantly attenuated in both proxy (3.53 [2.93–4.26]) and prevalent (3.12 [2.20–4.45]) ADRD. Furthermore, APOE and ADRD association effect sizes increased when restricting the control (no ADRD) group to older age brackets. Conclusions Our study highlights how genetic associations with ADRD can be sensitive to how cases are defined in biobanks like All of Us , with effect sizes downwardly biased when using prevalent or by-proxy cases compared to incident cases.

Tau PET imaging has emerged as an important tool to detect and monitor tangle burden in vivo in the study of Alzheimer's disease (AD). Previous studies demonstrated the association of tau burden with cognitive decline in probable AD cohorts. This study introduces a novel approach to analyze tau PET data by constructing individualized tau network structure and deriving its graph theory-based measures. We hypothesize that the network- based measures are a measure of the total tau load and the stage through disease. Using tau PET data from the AD Neuroimaging Initiative from 369 participants, we determine the network measures, global efficiency, global strength, and limbic strength, and compare with two regional measures entorhinal and tau composite SUVR, in the ability to differentiate, cognitively unimpaired (CU), MCI and AD. We also investigate the correlation of these network and regional measures and a measure of memory performance, auditory verbal learning test for long-term recall memory (AVLT-LTM). Finally, we determine the stages based on global efficiency and limbic strength using conditional inference trees and compare with Braak staging. We demonstrate that the derived network measures are able to differentiate three clinical stages of AD, CU, MCI, and AD. We also demonstrate that these network measures are strongly correlated with memory performance overall. Unlike regional tau measurements, the tau network measures were significantly associated with AVLT-LTM even in cognitively unimpaired individuals. Stages determined from global efficiency and limbic strength, visually resembled Braak staging. The strong correlations with memory particularly in CU suggest the proposed technique may be used to characterize subtle early tau accumulation. Further investigation is ongoing to examine this technique in a longitudinal setting.

Background Apolipoprotein E ( APOE ) genotypes have been suggested to influence cognitive impairment and clinical onset in presenilin-1 ( PSEN1 ) E280A carriers for autosomal dominant Alzheimer’s disease (ADAD). Less is known about their impact on the trajectory of biomarker changes. Neurofilament light chain (NfL), a marker of neurodegeneration, begins to accumulate in plasma about 20 years prior to the clinical onset of ADAD. In this study we investigated the impact of APOE ε4 and ε2 variants on age-related plasma NfL increases and cognition in PSEN1 E280A mutation carriers. Methods We analyzed cross-sectional data from PSEN1 E280A mutation carriers and non-carriers recruited from the Alzheimer’s Prevention Initiative Registry of ADAD. All participants over 18 years with available APOE genotype, plasma NfL, and neuropsychological evaluation were included in this study. APOE genotypes and plasma NfL concentrations were characterized for each participant. Cubic spline models using a Hamiltonian Markov chain Monte Carlo method were used to characterize the respective impact of at least one APOE ε4 or ε2 allele on age-related log-transformed plasma NfL increases. Linear regression models were estimated to explore the impact of APOE ε4 and ε2 variants and plasma NfL on a composite cognitive test score in the ADAD mutation carrier and non-carrier groups. Results Analyses included 788 PSEN1 E280A mutation carriers (169 APOE ε4 + , 114 ε2 +) and 650 mutation non-carriers (165 APOE ε4 + , 80 ε2 +), aged 18–75 years. APOE ε4 allele carriers were distinguished from ε4 non-carriers by greater age-related NfL elevations in the ADAD mutation carrier group, beginning about three years after the mutation carriers’ estimated median age at mild cognitive impairment onset. APOE ε2 allele carriers had lower plasma NfL concentrations than ε2 non-carriers in both the ADAD mutation carrier and non-carrier groups, unrelated to age, and an attenuated relationship between higher NfL levels on cognitive decline in the ADAD mutation carrier group. Conclusions APOE ε4 accelerates age-related plasma NfL increases and APOE ε2 attenuates the relationship between higher plasma NfL levels and cognitive decline in ADAD. NfL may be a useful biomarker to assess clinical efficacy of APOE -modifying drugs with the potential to help in the treatment and prevention of ADAD.

INTRODUCTION Amyloid positron emission tomography (PET) allows in vivo measurement of amyloid plaque deposition; however, different tracers lead to different results. We test the hypothesis that the variability in amyloid measurements is related to white matter retention, and accounting for this variability can improve agreements. METHODS Data from the Centiloid project was downloaded and processed for four F18 tracer‐to‐Pittsburgh Compound B (PiB) pairs to obtain mean cortical standardized uptake value ratio (MCSUVR). Three approaches were examined to account for white matter contribution to the MCSUVR. Pearson's correlation was used to assess the between tracer agreements. Steiger's test was used to determine the significance of improvement. RESULTS Accounting for white matter signal improves the agreement. The regional spread function partial volume correction (RSF PVC) method was most consistent in achieving statistically significant improvements (p < 0.05) for all four tracer pairs. DISCUSSION Between‐tracer agreement of amyloid measure can be improved by accounting for white matter signal. Further investigation is ongoing for additional improvement. Highlights Analyzing head‐to‐head data for all four common F18‐labeled tracers against Pittsburgh Compound B (PiB). Evaluating three different techniques to correct for white matter signal. Steiger's test to determine the significance of improvements. White matter uptake contributes to the between‐tracer measurement difference.

INTRODUCTION Machine learning (ML) can optimize amyloid (Aβ) comparability among positron emission tomography (PET) radiotracers. Using multi‐regional florbetapir (FBP) measures and ML, we report better Pittsburgh compound‐B (PiB)/FBP harmonization of mean‐cortical Aβ (mcAβ) than Centiloid. METHODS PiB‐FBP pairs from 92 subjects in www.oasis‐brains.org and 46 in www.gaain.org/centiloid‐project were used as the training/testing sets. FreeSurfer‐extracted FBP multi‐regional Aβ and actual PiB mcAβ in the training set were used to train ML models generating synthetic PiB mcAβ. The correlation coefficient (R) between the synthetic/actual PiB mcAβ in the testing set was assessed. RESULTS In the testing set, the synthetic/actual PiB mcAβ correlation R = 0.985 (R2 = 0.970) using artificial neural network was significantly higher (p ≤ 6.6e‐4) than the FBP/PiB correlation R = 0.927 (R2 = 0.860), improving total variance percentage (R2) from 86% to 97%. Other ML models such as partial least square, ensemble, and relevance vector regressions also improved R (p = 9.677e−05/0.045/0.0017). DISCUSSION ML improved mcAβ comparability. Additional studies are needed for the generalizability to other amyloid tracers, and to tau PET. Highlights Centiloid is a calibration of the amyloid scale, not harmonization. Centiloid unifies the amyloid scale without improving inter‐tracer association (R2). Machine learning (ML) can harmonize the amyloid scale by improving R2. ML harmonization maps multi‐regional florbetapir SUVRs to PiB mean‐cortical SUVR. Artificial neural network ML increases Centiloid R2 from 86% to 97%.

Background Apolipoprotein E (APOE), the major genetic risk factor for Alzheimer's disease (AD), has three common alleles (2, 3 and 4), giving rise to genotypes that are associated with six levels of AD risk: (2/2<2/3<3/3<2/4<3/4<4/4). In our new Arizona APOE Cohort Study, we have begun to establish a longitudinal cohort of more than 300 cognitively unimpaired persons (50‐90 year‐old) stratified by APOE genotype and age decile, matched by age and sex, and have an extensive battery of cognitive, clinical, amyloid (NAV4694) and tau (MK6240) PET, MRI, cerebrospinal fluid (CSF), plasma, and DNA. The study is intended to clarify the impact of APOE4 and APOE2 allelic dose on the predisposition to and protection from AD and inform the design of secondary and primary prevention therapies. Here, we describe the study and the resource of data and samples that are now available to researchers. Methods Participants were recruited from across the United States using GeneMatch and other sources. Comprehensive clinical assessments, brain images, and lumbar punctures are performed every 2 years, 50mL blood samples are acquired annually, and whole genome sequencing is in progress. Results As of January 2025, baseline assessments were completed in 303 participants, 68±9 years of age, including 205 females and 98 males. Sixteen percent are from underrepresented groups. Baseline CSF samples were obtained in 89% of the participants. The complete cohort consists of 17, 63, 41, 65, 66, and 51 persons with the APOE 2/2, 2/3, 3/3, 2/4, 3/4, and 4/4 genotype, respectively. In the first 287 participants with available amyloid PET scans 6% of 2/2, 5% of 2/3, 14% of 3/3, 26% of 2/4, 29% of 3/4, and 52% of 4/4 participants had a positive amyloid PET (≥20 centiloids). Conclusions Building up on our decades of experience in APOE research, we launched the new Arizona APOE Cohort which promises to provide a valuable resource of data and samples to advance the study of APOE, its variants and interactions with other risk and protective factors, and the development, treatment, and prevention of AD. Baseline data are now available to interested and eligible research collaborators.

Apolipoprotein E (APOE), the major genetic risk factor for Alzheimer's disease (AD), has three common alleles (2, 3 and 4), giving rise to genotypes that are associated with six levels of AD risk: (2/2<2/3<3/3<2/4<3/4<4/4). In our new Arizona APOE Cohort Study, we have begun to establish a longitudinal cohort of more than 300 cognitively unimpaired persons (50-90 year-old) stratified by APOE genotype and age decile, matched by age and sex, and have an extensive battery of cognitive, clinical, amyloid (NAV4694) and tau (MK6240) PET, MRI, cerebrospinal fluid (CSF), plasma, and DNA. The study is intended to clarify the impact of APOE4 and APOE2 allelic dose on the predisposition to and protection from AD and inform the design of secondary and primary prevention therapies. Here, we describe the study and the resource of data and samples that are now available to researchers. Participants were recruited from across the United States using GeneMatch and other sources. Comprehensive clinical assessments, brain images, and lumbar punctures are performed every 2 years, 50mL blood samples are acquired annually, and whole genome sequencing is in progress. As of January 2025, baseline assessments were completed in 303 participants, 68±9 years of age, including 205 females and 98 males. Sixteen percent are from underrepresented groups. Baseline CSF samples were obtained in 89% of the participants. The complete cohort consists of 17, 63, 41, 65, 66, and 51 persons with the APOE 2/2, 2/3, 3/3, 2/4, 3/4, and 4/4 genotype, respectively. In the first 287 participants with available amyloid PET scans 6% of 2/2, 5% of 2/3, 14% of 3/3, 26% of 2/4, 29% of 3/4, and 52% of 4/4 participants had a positive amyloid PET (≥20 centiloids). Building up on our decades of experience in APOE research, we launched the new Arizona APOE Cohort which promises to provide a valuable resource of data and samples to advance the study of APOE, its variants and interactions with other risk and protective factors, and the development, treatment, and prevention of AD. Baseline data are now available to interested and eligible research collaborators.