Approximately 30% of elderly adults are cognitively unimpaired at time of death despite the presence of Alzheimer's disease neuropathology at autopsy. Studying individuals who are resilient to the ...cognitive consequences of Alzheimer's disease neuropathology may uncover novel therapeutic targets to treat Alzheimer's disease. It is well established that there are sex differences in response to Alzheimer's disease pathology, and growing evidence suggests that genetic factors may contribute to these differences. Taken together, we sought to elucidate sex-specific genetic drivers of resilience. We extended our recent large scale genomic analysis of resilience in which we harmonized cognitive data across four cohorts of cognitive ageing, in vivo amyloid PET across two cohorts, and autopsy measures of amyloid neuritic plaque burden across two cohorts. These data were leveraged to build robust, continuous resilience phenotypes. With these phenotypes, we performed sex-stratified n (males) = 2093, n (females) = 2931 and sex-interaction n (both sexes) = 5024 genome-wide association studies (GWAS), gene and pathway-based tests, and genetic correlation analyses to clarify the variants, genes and molecular pathways that relate to resilience in a sex-specific manner. Estimated among cognitively normal individuals of both sexes, resilience was 20-25% heritable, and when estimated in either sex among cognitively normal individuals, resilience was 15-44% heritable. In our GWAS, we identified a female-specific locus on chromosome 10 rs827389, β (females) = 0.08, P (females) = 5.76 × 10-09, β (males) = -0.01, P(males) = 0.70, β (interaction) = 0.09, P (interaction) = 1.01 × 10-04 in which the minor allele was associated with higher resilience scores among females. This locus is located within chromatin loops that interact with promoters of genes involved in RNA processing, including GATA3. Finally, our genetic correlation analyses revealed shared genetic architecture between resilience phenotypes and other complex traits, including a female-specific association with frontotemporal dementia and male-specific associations with heart rate variability traits. We also observed opposing associations between sexes for multiple sclerosis, such that more resilient females had a lower genetic susceptibility to multiple sclerosis, and more resilient males had a higher genetic susceptibility to multiple sclerosis. Overall, we identified sex differences in the genetic architecture of resilience, identified a female-specific resilience locus and highlighted numerous sex-specific molecular pathways that may underly resilience to Alzheimer's disease pathology. This study illustrates the need to conduct sex-aware genomic analyses to identify novel targets that are unidentified in sex-agnostic models. Our findings support the theory that the most successful treatment for an individual with Alzheimer's disease may be personalized based on their biological sex and genetic context.
Objective: Studies use different instruments to measure cognitirating cognitive tests permit direct comparisons of individuals across studies and pooling data for joint analyses. Method: We began our ...legacy item bank with data from the Adult Changes in Thought study (n = 5,546), the Alzheimer's Disease Neuroimaging Initiative (n = 3,016), the Rush Memory and Aging Project (n = 2,163), and the Religious on such as the Mini-Mental State Examination, the Alzheimer's Disease Assessment Scale-Cognitive Subscale, the Wechsler Memory Scale, and the Boston Naming Test. CocalibOrders Study (n = 1,456). Our workflow begins with categorizing items administered in each study as indicators of memory, executive functioning, language, visuospatial functioning, or none of these domains. We use confirmatory factor analysis models with data from the most recent visit on the pooled sample across these four studies for cocalibration and derive item parameters for all items. Using these item parameters, we then estimate factor scores along with corresponding standard errors for each domain for each study. We added additional studies to our pipeline as available and focused on thorough consideration of candidate anchor items with identical content and administration methods across studies. Results: Prestatistical harmonization steps such qualitative and quantitative assessment of granular cognitive items and evaluating factor structure are important steps when trying to cocalibrate cognitive scores across studies. We have cocalibrated cognitive data and derived scores for four domains for 76,723 individuals across 10 studies. Conclusions: We have implemented a large-scale effort to harmonize and cocalibrate cognitive domain scores across multiple studies of cognitive aging. Scores on the same metric facilitate meta-analyses of cognitive outcomes across studies or the joint analysis of individual data across studies. Our systematic approach allows for cocalibration of additional studies as they become available and our growing item bank enables robust investigation of cognition in the context of aging and dementia.
Key Points
Question: What considerations were addressed in setting up and implementing a robust workflow that harmonizes and cocalibrates cognitive data across studies of older adults? Findings: Data from thousands of individuals at tens of thousands of study visits have been cocalibrated to the same metrics for four different cognitive domains. Importance: These data will facilitate analyses of cognition across studies, despite varying levels of overlap in cognitive tests used across studies. Next Steps: Cocalibrated scores and standard errors for the studies incorporated in our item banking efforts to date are available to investigators. Additional studies will be incorporated in the coming years using the same methods.
Inflammatory protein biomarkers induced by immune responses have been associated with cognitive decline and the pathogenesis of Alzheimer's disease (AD). Here, we investigate associations between a ...panel of inflammatory biomarkers and cognitive function and incident dementia outcomes in the well-characterized Framingham Heart Study Offspring cohort. Participants aged ≥40 years and dementia-free at Exam 7 who had a stored plasma sample were selected for profiling using the OLINK proteomics inflammation panel. Cross-sectional associations of the biomarkers with cognitive domain scores (N = 708, 53% female, 22% apolipoprotein E (APOE) ε4 carriers, 15% APOE ε2 carriers, mean age 61) and incident all-cause and AD dementia during up to 20 years of follow-up were tested. APOE genotype-stratified analyses were performed to explore effect modification. Higher levels of 12 and 3 proteins were associated with worse executive function and language domain factor scores, respectively. Several proteins were associated with more than one cognitive domain, including IL10, LIF-R, TWEAK, CCL19, IL-17C, MCP-4, and TGF-alpha. Stratified analyses suggested differential effects between APOE ε2 and ε4 carriers: most ε4 carrier associations were with executive function and memory domains, whereas most ε2 associations were with the visuospatial domain. Higher levels of TNFB and CDCP1 were associated with higher risks of incident all-cause and AD dementia. Our study found that TWEAK concentration was associated both with cognitive function and risks for AD dementia. The association of these inflammatory biomarkers with cognitive function and incident dementia may contribute to the discovery of therapeutic interventions for the prevention and treatment of cognitive decline.
Background
There is evidence that Alzheimer’s Disease (AD) may have distinct subtypes. Most approaches for identifying subgroups use cross‐sectional data. Here we use longitudinal cognitive test data ...from two large cohort studies to determine if there are distinct patterns of cognitive decline among those with AD and if those patterns differ across three domains of cognition.
Method
We used data from the Rush Memory and Aging Project and Religious Orders Study (Table 1). Previously, cognitive test items were assigned to a single domain of memory, language, or executive function and scores for each domain were estimated using confirmatory factor analysis. We used Growth Mixture Models to estimate trajectories of decline starting at AD diagnosis and identified subgroups with differing trajectories. Each domain was modeled individually and in a combined model that included distinct latent processes for each domain. Models with one to five classes were estimated and the number of classes was selected using Bayesian Information Criterion (BIC) and entropy.
Result
The two class models fit best for each of the individual domains (Figure 1). For memory and language one class was characterized by a higher intercept and steeper slope while the other had a lower intercept and flatter slope. For executive function the two classes had similar intercepts, but different slopes. Five classes best fit the data in the combined model. The pattern of decline within a class was similar across the three domains (Figure 2). For each domain, four of the classes were differentiated from each other by lower intercepts and increasingly steep slopes, while a fifth class had the lowest intercept, but a flatter trajectory over time.
Conclusion
We did not see different patterns across domains of cognition; knowing the trajectory of one cognitive domain explains the most likely trajectory of the other domains. Still, differences identified in patterns of overall decline may be important for AD treatment. Future work will focus on determining biological relevance of subgroups through association with genetic and other biomarkers as well as addressing methodological issues such as incorporating survival time and accounting for the presence of prevalent cases and floor scores.
Abstract
Background
We harmonized composite scores for memory, executive functioning (EF), and language from granular cognitive data from the National Alzheimer’s Coordinating Center (NACC) uniform ...dataset on 39,965 individuals. We explored if our cognitive scores correlated with APOE genotype and structural magnetic resonance imaging data.
Method
In our previously published harmonization methods we used confirmatory factor analysis models, guided by theoretical considerations from content experts, to estimate domain scores. For this cross‐sectional analysis of last visits in participants over age 60, we obtained APOE genotype data (n = 28,558 individuals) and FreeSurfer regional volume data (n = 2,404 individuals). We looked at relationship between cognitive performance and APOE genotype grouping by disease group (normal cognition, mild cognitive impairment (MCI), or AD dementia). We ran student’s two sample t‐test to assess the effect of APOE ε4 genotype on cognitive domain score. We also ran regression models for cognitive domain scores on each FreeSurfer region selected a priori on the basis of assumed association on that index domain adjusting for age, gender and APOE genotype.
Result
Relevant demographic and clinical data are summarized in Table 1. Associations with APOE genotype and each cognitive domain are shown in Figure 1. As expected, participants with at least one APOE ε4 alleles compared with none had lower composite memory scores (p<0.01, t‐test) compared with those with none in participants with dementia and MCI. APOE ε4 carriers also had lower language scores in participants with dementia (p = 0.037, t‐test). Among the FreeSurfer regions, composite memory scores were strongly associated with hippocampal volume, parahippocampus and entorhinal cortex thickness across all dementia categories (Table 2). EF scores were associated with 2 EF brain regions of interest in participants with dementia. Language scores were associated with 2 language regions of interest in participants with dementia.
Conclusion
Our analyses shows composite scores are associated with APOE genotype in participants with dementia and relevant brain regions in the memory domain across all dementia categories. Our analyses shows that our cognitive scores correlate with memory brain regions and APOE genotype in expected directions.
Background
Alzheimer’s Disease Research Centers (ADRCs) administer prescribed cognitive batteries – the Uniform Data Set (UDS) – and report UDS data to the National Alzheimer’s Coordinating Center ...(NACC). ADRCs may administer other items beyond the UDS. We used data from the University of Pittsburgh ADRC (Pitt) to determine psychometric implications of UDS items alone versus UDS items plus additional Pitt‐specific items.
Method
We used confirmatory factor analyses to co‐calibrate Uniform Data Set 1 and 2 (UDS1/2, broadly overlapping, 2005–2015) and UDS3 (2015‐2020) data for memory, executive functioning, and language. We added Pitt‐specific items for each domain. We compared measurement properties of UDS scores vs. UDS plus Pitt scores, including measurement precision and projected sample sizes needed to show a 25% reduction in rate of decline over 12 months for people with Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD).
Result
There were 2,726 participants with 8,602 visits across UDS1, 2, and 3 (Table 1). Figure 1 summarizes findings for memory. Figure 1a shows boxplots for memory scores for normal cognition (NC), MCI, and AD for UDS1/2 (green) and UDS3 (purple). Figure 1b shows corresponding boxplots and standard error of measurement (SEM) curves for UDS1/2 (left) and UDS3 (right). Incremental improvements in measurement precision can be seen with the lower SEM curve for the UDS plus Pitt curves. Figures 2 and 3 summarize similar findings for executive functioning and for language. In each case UDS Plus Pitt has less measurement error than UDS alone. Proportions of scores with standard errors >0.30 (a commonly used threshold for individual decision‐making) during UDS1/2 and UDS3 are in Table 2. Pitt‐specific items reduced the proportion with imprecise scores for every comparison with the exception of executive functioning in UDS1/2. Sample sizes needed to show a 25% reduction in the rate of decline are shown in Table 3. Improved precision from additional items was associated with greater power to show change over time.
Conclusion
Integrating additional data beyond UDS1/2 and UDS3 results in better measurement precision and increased statistical power.
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.
Objective: To calibrate cognitive assessment data across multiple waves of the Framingham Heart Study (FHS), addressing study design considerations, ceiling effects, and measurement precision. ...Method: FHS participants completed several cognitive assessments including screening instruments and more comprehensive batteries at different study visits. We used expert opinion to assign each cognitive test item to a single domain-memory, executive function, language, visuospatial abilities, or none of the above. As part of a larger cross-study harmonization effort, we calibrated each domain separately using bifactor confirmatory factor analysis (CFA) models, incorporating item parameters for anchor items previously calibrated from other studies and freely estimating item parameters for FHS-specific items. We obtained scores and standard errors (SEs) for each participant at each study visit. We addressed psychometric considerations of ceiling effects and measurement precision. Results: Overall, memory domain scores were the most precisely estimated. Scores for all domains from visits where the Mini-Mental State Examination (MMSE) was the only test administered were imprecisely estimated and suffered from ceiling effects. Scores from visits with a more extensive battery were estimated more precisely and better differentiated between ability levels. Conclusions: The harmonized and calibrated cognitive data from the FHS should prove useful for future analyses examining cognition and cognitive decline. They will be of particular interest when combining FHS with other studies that have been similarly calibrated. Researchers should be aware of varying levels of measurement precision and the possibility of ceiling effects in their planned analyses of data from the FHS and similar studies.
Key Points
Question: What methods and special considerations are needed to derive calibrated cognitive factor scores and use them in future analyses in the FHS, and other similar studies that have evolving cognitive batteries over time or different batteries administered at different study visits? Findings: The FHS used different cognitive instruments at different study visits. These instruments had different measurement properties, including ceiling effects and substantial differences in measurement precision. Importance: Cognitive domain scores from the FHS data can be used in subsequent research. Investigators should consider measurement precision and ceiling effects in their analyses. Next Steps: The calibrated cognitive data generated in this project have been integrated with other study data from the FHS. Interested investigators should integrate lessons from this article in their plans for analyses of the rich cognitive data available from the FHS.
Background
KBASE is a prospective cohort study launched at Seoul National University (SNU), South Korea, in 2014 using similar design and methods as the North American Alzheimer’s Disease ...Neuroimaging Initiative (ADNI). The KBASE cohort consists of well‐characterized participants (420 cognitively normal, 140 mild cognitive impairment, and 90 AD dementia) (Figure 1). It includes systematic longitudinal collection of comprehensive clinical, cognitive and lifestyle data, multimodal neuroimaging, and bio‐specimens for the first six years (“KBASE1”) at a single center. “KBASE2: Korean Brain Aging Study, Longitudinal Endophenotypes and Systems Biology” (NIH Grant U01AG072177) is the second phase of KBASE, launched in collaboration with Indiana University and other institutions. KBASE2 began in 2021, and has similar assessment protocols to the KBASE1. The NIA AD Sequencing Project (ADSP) will perform GWAS and whole genome sequencing (WGS).
Method
Neuropsychological data will be harmonized by the study team and members of the ADSP Phenotype Harmonization Consortium. Comprehensive cognitive data were collected using a battery of standardized tests (Table 1). Harmonization and co‐calibration will enable comparative analyses with cognitive data from similar studies with largely non‐Hispanic white (NHW) cohorts, including the ADNI and AIBL, and ultimately the range of other aging and dementia cohorts including those with underrepresented multi‐ethnic populations. WGS and GWAS data will be harmonized and shared by the ADSP.
Result
Cognitive data harmonization processes are underway and have begun to address the challenges of language and cultural differences. Initial steps include mapping tests and items into an English template. Harmonization and co‐calibration efforts will include identifying appropriate anchor items and accounting for differences in test items that were made to be more culturally and linguistically appropriate. Additional challenges include the wide range of educational attainment as well as gender effects on educational opportunities. A bilingual neuropsychologist who is trained and licensed in the U.S. and a bilingual psychometrics expert are deeply involved in harmonization processes.
Conclusion
Harmonized KBASE cognitive data will be shared with the ADSP and other investigators for use in quantitative phenotype analyses, as well as other pooled, integrative, and comparative studies of other multiethnic, multilingual, U.S., and international cohorts.
