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The APOE 2/3/4 polymorphism is the greatest genetic risk factor for Alzheimer’s disease (AD). This polymorphism is also associated with variation in plasma ApoE level; while APOE*4 lowers, APOE*2 increases ApoE level. Lower plasma ApoE level has also been suggested to be a risk factor for incident dementia. To our knowledge, no large genome-wide association study (GWAS) has been reported on plasma ApoE level. This study aimed to identify new genetic variants affecting plasma ApoE level as well as to test if baseline ApoE level is associated with cognitive function and incident dementia in a longitudinally followed cohort of the Ginkgo Evaluation of Memory (GEM) study. Baseline plasma ApoE concentration was measured in 3031 participants (95.4% European Americans (EAs)). GWAS analysis was performed on 2580 self-identified EAs where both genotype and plasma ApoE data were available. Lower ApoE concentration was associated with worse cognitive function, but not with incident dementia. As expected, the risk for AD increased from E2/2 through to E4/4 genotypes ( P for trend = 4.8E-75). In addition to confirming the expected and opposite associations of APOE*2 ( P  = 4.73E-79) and APOE*4 ( P  = 8.73E-12) with ApoE level, GWAS analysis revealed nine additional independent signals in the APOE region, and together they explained about 22% of the variance in plasma ApoE level. We also identified seven new loci on chromosomes 1, 4, 5, 7, 11, 12 and 20 ( P range = 5.49E-08 to 5.36E-10) that explained about 9% of the variance in ApoE level. Plasma ApoE level-associated independent variants, especially in the APOE region, were also associated with AD risk and amyloid deposition in the brain, indicating that genetically determined ApoE level variation may be a risk factor for developing AD. These results improve our understanding of the genetic determinants of plasma ApoE level and their potential value in affecting AD risk.

The biomarker model of Alzheimer's disease postulates a dynamic sequence of amyloidosis, neurodegeneration, and cognitive decline as an individual progresses from preclinical Alzheimer's disease to dementia. Despite supportive evidence from cross-sectional studies, verification with long-term within-individual data is needed. For this prospective cohort study, carriers of autosomal dominant Alzheimer's disease mutations (aged ≥21 years) were recruited from across the USA through referrals by physicians or from affected families. People with mutations in PSEN1, PSEN2, or APP were assessed at the University of Pittsburgh Alzheimer's Disease Research Center every 1–2 years, between March 23, 2003, and Aug 1, 2014. We measured global cerebral amyloid β (Aβ) load using 11C-Pittsburgh Compound-B PET, posterior cortical metabolism with 18F-fluorodeoxyglucose PET, hippocampal volume (age and sex corrected) with T1-weighted MRI, verbal memory with the ten-item Consortium to Establish a Registry for Alzheimer's Disease Word List Learning Delayed Recall Test, and general cognition with the Mini Mental State Examination. We estimated overall biomarker trajectories across estimated years from symptom onset using linear mixed models, and compared these estimates with cross-sectional data from cognitively normal control individuals (age 65–89 years) who were negative for amyloidosis, hypometabolism, and hippocampal atrophy. In the mutation carriers who had the longest follow-up, we examined the within-individual progression of amyloidosis, metabolism, hippocampal volume, and cognition to identify progressive within-individual changes (a significant change was defined as an increase or decrease of more than two Z scores standardised to controls). 16 people with mutations in PSEN1, PSEN2, or APP, aged 28–56 years, completed between two and eight assessments (a total of 83 assessments) over 2–11 years. Significant differences in mutation carriers compared with controls (p<0·01) were detected in the following order: increased amyloidosis (7·5 years before expected onset), decreased metabolism (at time of expected onset), decreased hippocampal volume and verbal memory (7·5 years after expected onset), and decreased general cognition (10 years after expected onset). Among the seven participants with longest follow-up (seven or eight assessments spanning 6–11 years), three individuals had active amyloidosis without progressive neurodegeneration or cognitive decline, two amyloid-positive individuals showed progressive neurodegeneration and cognitive decline without further progressive amyloidosis, and two amyloid-positive individuals showed neither active amyloidosis nor progressive neurodegeneration or cognitive decline. Our results support amyloidosis as the earliest component of the biomarker model in autosomal dominant Alzheimer's disease. Our within-individual examination suggests three sequential phases in the development of autosomal dominant Alzheimer's disease—active amyloidosis, a stable amyloid-positive period, and progressive neurodegeneration and cognitive decline—indicating that Aβ accumulation is largely complete before progressive neurodegeneration and cognitive decline occur. These findings offer supportive evidence for efforts to target early Aβ deposition for secondary prevention in individuals with autosomal dominant Alzheimer's disease. National Institutes of Health and Howard Hughes Medical Institute.

Categorizing people with late-onset Alzheimer’s disease into biologically coherent subgroups is important for personalized medicine. We evaluated data from five studies (total n = 4050, of whom 2431 had genome-wide single-nucleotide polymorphism (SNP) data). We assigned people to cognitively defined subgroups on the basis of relative performance in memory, executive functioning, visuospatial functioning, and language at the time of Alzheimer’s disease diagnosis. We compared genotype frequencies for each subgroup to those from cognitively normal elderly controls. We focused on APOE and on SNPs with p < 10−5 and odds ratios more extreme than those previously reported for Alzheimer’s disease (<0.77 or >1.30). There was substantial variation across studies in the proportions of people in each subgroup. In each study, higher proportions of people with isolated substantial relative memory impairment had ≥1 APOE ε4 allele than any other subgroup (overall p = 1.5 × 10−27). Across subgroups, there were 33 novel suggestive loci across the genome with p < 10−5 and an extreme OR compared to controls, of which none had statistical evidence of heterogeneity and 30 had ORs in the same direction across all datasets. These data support the biological coherence of cognitively defined subgroups and nominate novel genetic loci.

Background Blood-based biomarkers are gaining grounds for the detection of Alzheimer’s disease (AD) and related disorders (ADRDs). However, two key obstacles remain: the lack of methods for multi-analyte assessments and the need for biomarkers for related pathophysiological processes like neuroinflammation, vascular, and synaptic dysfunction. A novel proteomic method for pre-selected analytes, based on proximity extension technology, was recently introduced. Referred to as the NULISAseq CNS disease panel, the assay simultaneously measures ~ 120 analytes related to neurodegenerative diseases, including those linked to both core (i.e., tau and amyloid-beta (Aβ)) and non-core AD processes. This study aimed to evaluate the technical and clinical performance of this novel targeted proteomic panel. Methods The NULISAseq CNS disease panel was applied to 176 plasma samples from 113 individuals in the MYHAT-NI cohort of predominantly cognitively normal participants from an economically underserved region in southwestern Pennsylvania, USA. Classical AD biomarkers, including p-tau181, p-tau217, p-tau231, GFAP, NEFL, Aβ40, and Aβ42, were independently measured using Single Molecule Array (Simoa) and correlations and diagnostic performances compared. Aβ pathology, tau pathology, and neurodegeneration (AT(N) statuses) were evaluated with [ 11 C] PiB PET, [ 18 F]AV-1451 PET, and an MRI-based AD-signature composite cortical thickness index, respectively. Linear mixed models were used to examine cross-sectional and Wilcoxon rank sum tests for longitudinal associations between NULISA and neuroimaging-determined AT(N) biomarkers. Results NULISA concurrently measured 116 plasma biomarkers with good technical performance (97.2 ± 13.9% targets gave signals above assay limits of detection), and significant correlation with Simoa assays for the classical biomarkers. Cross-sectionally, p-tau217 was the top hit to identify Aβ pathology, with age, sex, and APOE genotype-adjusted AUC of 0.930 (95%CI: 0.878–0.983). Fourteen markers were significantly decreased in Aβ-PET + participants, including TIMP3, BDNF, MDH1, and several cytokines. Longitudinally, FGF2, IL4, and IL9 exhibited Aβ PET-dependent yearly increases in Aβ-PET + participants. Novel plasma biomarkers with tau PET-dependent longitudinal changes included proteins associated with neuroinflammation, synaptic function, and cerebrovascular integrity, such as CHIT1, CHI3L1, NPTX1, PGF, PDGFRB, and VEGFA; all previously linked to AD but only reliable when measured in cerebrospinal fluid. The autophagosome cargo protein SQSTM1 exhibited significant association with neurodegeneration after adjusting age, sex, and APOE ε4 genotype. Conclusions Together, our results demonstrate the feasibility and potential of immunoassay-based multiplexing to provide a comprehensive view of AD-associated proteomic changes, consistent with the recently revised biological and diagnostic framework. Further validation of the identified inflammation, synaptic, and vascular markers will be important for establishing disease state markers in asymptomatic AD.

Alzheimer’s disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.

To estimate and compare the frequency and prevalence of mild cognitive impairment (MCI) and related entities using different classification approaches at the population level. Cross-sectional epidemiologic study of population-based cohort recruited by age-stratified random sampling from electoral rolls. Small-town communities in western Pennsylvania. Of 2,036 individuals aged 65 years and older, 1,982 participants with normal or mildly impaired cognition (age-education-corrected Mini-Mental State scores ≥21). Demographics, neuropsychological assessment expressed as cognitive domains, functional ability, and subjective reports of cognitive difficulties; based on these measurements, operational criteria for the Clinical Dementia Rating (CDR) scale, the 1999 criteria for amnestic MCI, the 2004 Expanded criteria for MCI, and new, purely cognitive criteria for MCI. A CDR rating of 0.5 (uncertain/very mild dementia) was obtained by 27.6% of participants, whereas 1.2% had CDR ≥1 (mild or moderate dementia). Among those with CDR <1, 2.27% had amnestic MCI and 17.66% had expanded MCI, whereas 35.17% had MCI by purely cognitive classification. Isolated executive function impairment was the least common, whereas impairment in multiple domains including executive function was the most common. Prevalence estimates weighted against the U.S. Census are also provided. The manner in which criteria for MCI are operationalized determines the proportion of individuals who are thus classified and the degree of overlap with other criteria. Prospective follow-up is needed to determine progression from MCI to dementia and thus empirically develop improved MCI criteria with good predictive value.

Sedentary behavior has been associated with poor health outcomes, especially in older adulthood. Given that sedentary behavior is a highly prevalent, modifiable health behavior, there has been a recent increased interest in examining how sedentary behavior relates to cognition and brain health. The current body of literature is limited and mixed. The purpose of this systematic review was to examine the associations of sedentary behavior with cognition and brain health in older adults across the cognitive spectrum. This study was pre-registered with PROSPERO (CRD42023477868). Six comprehensive databases were searched with pre-registered search terms. A total of 33 studies were included. Overall, results indicated that greater sedentary behavior was associated with worse cognition and brain health, although associations varied based on differences in measurement and classification of sedentary behavior. We discuss next steps and implications for future research.

Introduction Using the ATN framework, we evaluated the potential of plasma biomarkers to identify abnormal brain amyloid-beta (Aβ) positron emission tomography (PET), tau-PET and neurodegeneration in a socioeconomically disadvantaged population-based cohort. Methods Community-dwelling dementia-free ( n  = 113, including 102 (91%) cognitively normal) participants underwent ATN neuroimaging and plasma biomarker assessments. Results Plasma Aβ42/Aβ40, p-tau181, and p-tau217 showed significant associations with Aβ-PET status, (adjusted odds ratio [AOR] of 1.74*10 –24 , 1.47, and 3.43*10 3 , respectively ( p -values < 0.05), with p-tau217 demonstrating the highest classification accuracy for Aβ-PET status (AUC = 0.94). Plasma p-tau181 and p-tau217 showed significant associations with tau-PET status (AOR: 1.50 and 22.24, respectively ( p -values < 0.05), with comparable classification accuracies for tau-PET status (AUC = 0.74 and 0.70, respectively). Only plasma NfL showed significant association with neurodegeneration based on cortical thickness (AOR = 1.09, p -value < 0.05). Conclusion Our findings highlight the potential of plasma p-tau217 as a biomarker for brain Aβ and tau pathophysiology, p-tau181 for tau abnormalities, and NfL for neurodegeneration in the community.

A key component of successful aging is the ability to independently perform instrumental activities of daily living (IADL). We examined the ability to perform multiple IADL tasks in relation to mild cognitive impairment (MCI) defined on purely neuropsychological grounds. Cross-sectional study. Population-based cohort in southwestern Pennsylvania. One thousand seven hundred thirty-seven community-dwelling adults age 65 years and older. Classification of MCI based on performance with reference to norms in the cognitive domains of memory, language, attention, executive, and visuospatial functions. The ability to perform seven IADL tasks (traveling, shopping, preparing meals, doing housework, taking medications, handling personal finances, and using the telephone) as assessed by the Older Americans Resources and Services scale. Those with cognitively defined MCI were more likely to be dependent in at least one IADL task, as well as in each individual IADL task, than cognitively normal participants. Better memory and executive functioning were associated with lower odds of IADL dependence in MCI. Across the subtypes of MCI, those with the multiple-domain amnestic subtype were most likely to be dependent in all IADL tasks, with better executive functioning associated with lower risk of dependence in select IADL tasks in this group. Mild impairment in cognition is associated with difficulty performing IADL tasks at the population level. Understanding these associations may help improve prediction of the outcomes of MCI. It may also allow appropriate targeting of cognitive interventions in MCI to potentially help preserve functional independence.

The natural history of Alzheimer’s Disease (AD) includes significant alterations in the human connectome, and this disconnection results in the dementia of AD. The organizing principle of our research project is the idea that the expression of cognitive dysfunction in the elderly is the result of two independent processes — the neuropathology associated with AD, and second the neuropathological changes of cerebrovascular disease. Synaptic loss, senile plaques, and neurofibrillary tangles are the functional and diagnostic hallmarks of AD, but it is the structural changes as a consequence of vascular disease that reduce brain reserve and compensation, resulting in an earlier expression of the clinical dementia syndrome. This work is being completed under the auspices of the Human Connectome Project (HCP). We have achieved an equal representation of Black individuals (vs. White individuals) and enrolled 60% Women. Each of the participants contributes demographic, behavioral and laboratory data. We acquire data relative to vascular risk, and the participants also undergo in vivo amyloid imaging, and magnetoencephalography (MEG). All of the data are publicly available under the HCP guidelines using the Connectome Coordinating Facility and the NIMH Data Archive. Locally, we use these data to address specific questions related to structure, function, AD, aging and vascular disease in multi-modality studies leveraging the differential advantages of magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), MEG, and in vivo beta amyloid imaging.