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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 Practice effects (PEs) are improvements in performance after repeated exposure to test materials, and typically viewed as a source of bias in repeated cognitive assessments. We aimed to determine whether characterizing PEs could also provide a useful marker of early cognitive decline. Methods We conducted a systematic review of the literature, searching PsycInfo (Ebsco) and PubMed databases for articles studying PEs in aging and dementia populations. Articles published between 1920 and 2019 were included. Result We identified 259 articles, of which 27 studied PEs as markers of cognitive performance. These studies consistently showed that smaller, less‐robust PEs were associated with current diagnostic status and/or future cognitive decline. In addition, lower PEs were associated with Alzheimer's disease risk factors and neurodegeneration biomarkers. Conclusion PEs provide a potentially useful marker of cognitive decline, and could prove valuable as part of a cost‐effective strategy to select individuals who are at‐risk for dementia for future interventions.

INTRODUCTION We sought to determine structural magnetic resonance imaging (MRI) characteristics across subgroups defined based on relative cognitive domain impairments using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and to compare cognitively defined to imaging‐defined subgroups. METHODS We used data from 584 people with Alzheimer's disease (AD) (461 amyloid positive, 123 unknown amyloid status) and 118 amyloid‐negative controls. We used voxel‐based morphometry to compare gray matter volume (GMV) for each group compared to controls and to AD‐Memory. RESULTS There was pronounced bilateral lower medial temporal lobe atrophy with relative cortical sparing for AD‐Memory, lower left hemisphere GMV for AD‐Language, anterior lower GMV for AD‐Executive, and posterior lower GMV for AD‐Visuospatial. Formal asymmetry comparisons showed substantially more asymmetry in the AD‐Language group than any other group (p = 1.15 × 10−10). For overlap between imaging‐defined and cognitively defined subgroups, AD‐Memory matched up with an imaging‐defined limbic predominant group. DISCUSSION MRI findings differ across cognitively defined AD subgroups.

INTRODUCTION Accurately assessing the temporal order of cognitive decline across multiple domains is critical in Alzheimer's disease (AD). Existing literature presents controversial conclusions likely due to the use of a single cohort and different analytical strategies. METHODS Harmonized composite cognitive measures in memory, language, and executive functions from 13 cohorts in the Alzheimer's Disease Sequencing Project Phenotype Harmonization Consortium (ADSP‐PHC) were used. A double anchoring events–based sigmoidal mixed model was developed using time to incident AD diagnosis as the time scale. RESULTS In general, decline in memory occurred before decline in language, followed by decline in executive function. This temporal order generally persisted within each subgroup of apolipoprotein E ε4 carrier status, sex, and race/ethnicity. DISCUSSION This study demonstrated the use of harmonized data across multiple cohorts to characterize the temporal order of cognitive decline along AD progression. Using time to incident AD diagnosis as the time scale can enhance research reproducibility and clinical practice. Highlights Alzheimer's Disease Sequencing Project Phenotype Harmonization Consortium's harmonized composite cognitive measures from 13 cohort studies fitted with a novel double anchoring event‐based sigmoidal mixed model reveal the following temporal order of cognitive decline toward AD progression: memory, language, and executive function. If only investigated using individual cohort studies, the temporal order of cognitive decline would vary due to the underlying heterogeneities across studies. This temporal order generally persisted within each subgroup of apolipoprotein E ε4 carrier status, sex, and race/ethnicity.

INTRODUCTION Early‐onset Alzheimer's disease dementia (EOAD) is characterized by more pronounced cognitive decline than late‐onset AD dementia (LOAD). Characteristic performance in spoken language remains undefined. METHOD A cross‐sectional analysis of 1189 people with EOAD and 4646 with LOAD from the National Alzheimer's Coordinating Center (NACC) was conducted. RESULT Based on data from their first NACC visit with AD, there was considerable heterogeneity in language performance across people with EOAD and LOAD. The distribution of naming ability was similar across these groups. On average, people with LOAD performed better than those with EOAD in category fluency, letter fluency, and spoken lexical retrieval, and had lower Clinical Dementia Rating (CDR) Language scores, although there was considerable overlap in the distributions for participants with EOAD and those with LOAD. DISCUSSION At diagnosis, the language profiles of EOAD and LOAD are distinct. There is substantial variability in both groups in multiple aspects of language. Highlights Early‐onset Alzheimer's disease (EOAD) is associated with significantly poorer category and phonemic fluency and global spoken lexical retrieval compared to late‐onset Alzheimer's disease (LOAD) at time of diagnosis. Participants with EOAD dementia show greater severity and variability in clinician‐rated language functioning, as measured by Clinical Dementia Rating (CDR) Language scores. No significant group differences were observed in confrontation naming performance between EOAD and LOAD dementia. Findings support that there are distinct profiles of language performance in EOAD and LOAD at time of dementia diagnosis.

Introduction Composite scores may be useful to summarize overall language or visuospatial functioning in studies of older adults. Methods We used item response theory to derive composite measures for language (ADNI‐Lan) and visuospatial functioning (ADNI‐VS) from the cognitive battery administered in the Alzheimer's Disease Neuroimaging Initiative (ADNI). We evaluated the scores among groups of people with normal cognition, mild cognitive impairment (MCI), and Alzheimer's disease (AD) in terms of responsiveness to change, association with imaging findings, and ability to differentiate between MCI participants who progressed to AD dementia and those who did not progress. Results ADNI‐Lan and ADNI‐VS were able to detect change over time and predict conversion from MCI to AD. They were associated with most of the pre‐specified magnetic resonance imaging measures. ADNI‐Lan had strong associations with a cerebrospinal fluid biomarker pattern. Discussion ADNI‐Lan and ADNI‐VS may be useful composites for language and visuospatial functioning in ADNI.

Diffusion and structural brain traits in the medial temporal lobe showed strongest genetic covariance with memory. Top functional brain traits highlighted connectivity in the default mode network. Shared genetic architecture between mid‐life brain imaging traits and late‐life memory parallels Alzheimer's disease vulnerability.

This study introduces a framework for estimating the optical scattering properties of thin-film phantoms using a custom-built Spectral-Domain Dental Optical Coherence Tomography (DEN-OCT) system operating within the 780–900 nm spectral range. The purpose of this work was to assess the performance of this system. The system exhibited high depth-resolved imaging performance with an axial resolution of approximately 16.30 µm, a signal-to-noise ratio of about 32.4 dB, and a 6 dB sensitivity roll-off depth near 2 mm, yielding an effective imaging range of 2.5 mm. Thin-film phantoms with controlled optical characteristics were fabricated and analyzed using Beer–Lambert and diffusion approximation models to evaluate attenuation behavior. Samples representing different tissue analogs demonstrated distinct scattering responses: one sample showed strong scattering similar to hard tissues, while the others exhibited lower scattering and higher transmission, resembling soft-tissue properties. Spectrophotometric measurements at 840 nm supported these trends through characteristic transmittance and reflectance profiles. While homogeneous samples conformed to analytical models, the highly scattering sample deviated due to structural non-uniformity, requiring Monte Carlo simulation to accurately describe photon transport. OCT A-scan analyses fitted with exponential decay models produced attenuation coefficients consistent with spectrophotometric data, confirming the dominance of scattering over absorption. The integration of OCT imaging, optical modeling, and Monte Carlo simulation establishes a reliable methodology for quantitative scattering estimation and demonstrates the potential of the developed DEN-OCT system for advanced dental and biomedical imaging applications. The innovation of this work lies in the integration of phantom-based optical calibration, multi-model scattering analysis, and depth-resolved OCT signal modeling, providing a validated pathway for quantitative parameter extraction in dental OCT applications.

INTRODUCTION The Uniform Data Set (UDS) version 3 neuropsychological battery replaced old tests used in UDS 1&2. Here, we validate domain scores for memory, executive functioning, and language co‐calibrated across UDS eras. METHODS We compared co‐calibrated and harmonized domain scores to traditional equipercentile equating in a crosswalk sample. We also validated domain scores by evaluating associations with magnetic resonance imaging (MRI) findings and APOE genotype across UDS eras. RESULTS We co‐calibrated cognitive domain scores for 49,396 participants, about 25% of whom had data spanning UDS 1&2 and UDS 3 eras. Crosswalk sample (n = 955) correlations between UDS 1&2 and UDS 3 domain scores and equipercentile scores were similar. Harmonized domain scores had statistically significant associations in imaging (n = 2458) and APOE validity assessments (n = 27,857). Significant differences in domain scores were found across UDS eras. DISCUSSION Longitudinal co‐calibrated and harmonized cognitive domain scores bridge the gap across UDS versions and are available from the National Alzheimer's Coordinating Center. Highlights Co‐calibrated domain scores are validated in the NACC crosswalk sample. Co‐calibrated domain scores are validated with neuroimaging measures. Co‐calibrated domains scores are validated with APOE genotype. Co‐calibrated domain scores reveal cognitive performance differences in enrollment visit depending on UDS era. Co‐calibrated domain scores are readily available to investigators utilizing NACC's rich dataset.

The National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) includes extensive cognitive data contributed by Alzheimer's Disease Research Centers (ADRCs) since 2005. The UDS has evolved over time and is on its fourth iteration. In addition to this core dataset, individual ADRCs have administered augmented neuropsychological batteries to research participants that go beyond the UDS. Here we describe ongoing efforts and future plans to optimize use of these data with modern psychometric methods. Modern psychometric methods address challenges from an evolving battery of cognitive tests. To date, most efforts using modern psychometric methods have focused on harmonization and co‐calibration of ADRCs’ UDS and non‐UDS cognitive data, while recent efforts address additional areas such as subjective cognitive impairment. Modern psychometric methods provide a workable framework for anticipated future developments, including digital cognitive testing and analyses of spoken responses. These methods facilitate optimal use of NACC's data riches to further its mission to facilitate collaborative research. Highlights National Alzheimer's Coordinating Center (NACC) data collection includes an extensive cognitive battery that has changed over time. An ambitious project has harmonized and co‐calibrated cognitive domain scores for memory, executive functioning, and language. Scores and their standard errors are available from the NACC. Those scores are co‐calibrated with domain scores from many additional studies, facilitating cross‐study scientific investigation. Future opportunities include digital data collection, consideration of neuropsychiatric symptoms and subjective cognitive impairment, and other uses of the granular cognitive data.