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INTRODUCTION: Although dementia‐related proteinopathy has a strong negative impact on public health, and is highly heritable, understanding of the related genetic architecture is incomplete. METHODS: We applied multidimensional generalized partial credit modeling (GPCM) to test genetic associations with dementia‐related proteinopathies. Data were analyzed to identify candidate single nucleotide variants for the following proteinopathies: Aβ, tau, α‐synuclein, and TDP‐43. RESULTS: Final included data comprised 966 participants with neuropathologic and WGS data. Three continuous latent outcomes were constructed, corresponding to TDP‐43‐, Aβ/Tau‐, and α‐synuclein‐related neuropathology endophenotype scores. This approach helped validate known genotype/phenotype associations: for example, TMEM106B and GRN were risk alleles for TDP‐43 pathology; and GBA for α‐synuclein/Lewy bodies. Novel suggestive proteinopathy‐linked alleles were also discovered, including several (SDHAF1, TMEM68, and ARHGEF28) with colocalization analyses and/or high degrees of biologic credibility. DISCUSSION: A novel methodology using GPCM enabled insights into gene candidates for driving misfolded proteinopathies. Highlights: Latent factor scores for proteinopathies were estimated using a generalized partial credit model.The three latent continuous scores corresponded well with proteinopathy severity.Novel genes associated with proteinopathies were identified.Several genes had high degrees of biologic credibility for dementia risk factors. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Biomarkers remain mostly unavailable for non‐Alzheimer's disease neuropathological changes (non‐ADNC) such as transactive response DNA‐binding protein 43 (TDP‐43) proteinopathy, Lewy body disease (LBD), and cerebral amyloid angiopathy (CAA). METHODS: A multilabel non‐ADNC classifier using magnetic resonance imaging (MRI) signatures was developed for TDP‐43, LBD, and CAA in an autopsy‐confirmed cohort (N = 214). RESULTS: A model using demographic, genetic, clinical, MRI, and ADNC variables (amyloid positive [Aβ+] and tau+) in autopsy‐confirmed participants showed accuracies of 84% for TDP‐43, 81% for LBD, and 81% to 93% for CAA, outperforming reference models without MRI and ADNC biomarkers. In an ADNI cohort (296 cognitively unimpaired, 401 mild cognitive impairment, 188 dementia), Aβ and tau explained 33% to 43% of variance in cognitive decline; imputed non‐ADNC explained an additional 16% to 26%. Accounting for non‐ADNC decreased the required sample size to detect a 30% effect on cognitive decline by up to 28%. DISCUSSION: Our results lead to a better understanding of the factors that influence cognitive decline and may lead to improvements in AD clinical trial design. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Research‐oriented autopsy cohorts provide critical insights into dementia pathobiology. However, different studies sometimes report disparate findings, partially because each study has its own recruitment biases. We hypothesized that a straightforward metric, related to the percentage of research volunteers cognitively normal at recruitment, would predict other inter‐cohort differences. METHODS: The National Alzheimer's Coordinating Center (NACC) provided data on N = 7178 autopsied participants from 28 individual research centers. Research cohorts were grouped based on the proportion of participants with normal cognition at initial clinical visit. RESULTS: Cohorts with more participants who were cognitively normal at recruitment contained more individuals who were older, female, had lower frequencies of apolipoprotein E ε4, Lewy body disease, and frontotemporal dementia, but higher rates of cerebrovascular disease. Alzheimer's disease (AD) pathology was little different between groups. DISCUSSION: The percentage of participants recruited while cognitively normal predicted differences in findings in autopsy research cohorts. Most differences were in non‐AD pathologies. Highlights: Systematic differences exist between autopsy cohorts that serve dementia research.We propose a metric to use for gauging a research‐oriented autopsy cohort.It is essential to consider the characteristics of autopsy cohorts. [ABSTRACT FROM AUTHOR]

Background: We examined neuropsychiatric symptoms (NPS) and psychotropic medication use at the midway point of data collection of the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS). We compared amyloid‐positive early‐onset Alzheimer's disease (EOAD) participants and amyloid‐negative early‐onset non‐Alzheimer's disease [EOnonAD]) participants across NPS domains and psychotropic medication categories. Method: 282 participants enrolled in LEADS were compared across diagnostic groups – amyloid‐positive EOAD (n = 212) and amyloid‐negative EOnonAD (n = 70). All participants were between ages 40 and 64 at baseline. NPS were measured with the Neuropsychiatric Inventory – Questionnaire (NPI‐Q) and Geriatric Depression Scale – Short Form (GDS‐SF). Medications were categorized into psychotropic category (e.g., antidepressants, antipsychotics, benzodiazepines). Groups were compared on NPI‐Q using binary logistic regression adjusting for sex and disease severity, on GDS‐SF using linear regression adjusting for sex and disease severity, and on psychotropic medication use using Chi square or Fisher's exact test. Result: Demographic data are presented in Table 1. Average total NPI‐Q score was higher in EOnonAD than EOAD (p =.002, ŋp2 =.03). Regardless of diagnostic group, informants endorsed Affective behaviors most frequently (76.2%). EOAD informants endorsed fewer Distress‐Tension behaviors (p =.02, OR =.498) and Impulse Control behaviors (p =.01, OR =.438). EOAD informants also endorsed apathy (p <.001, OR =.316), irritability (p =.02, OR =.498), and disinhibition (p =.04, OR =.476) at lower frequency than EOnonAD. GDS‐SF showed that the EOnonAD participants self‐reported more symptoms of depression than the EOAD group (p =.002, ŋp2 =.03). (Table 2A). A minority of participants, regardless of diagnostic group, reported psychotropic medication use (35%). There was higher use in EOnonAD (38%) than EOAD (24%) (p =.03, Cohen W =.14) (Table 2B). Conclusion: NPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants, despite EOnonAD being less severely impaired. LEADS continues to collect data. Future studies will examine etiologies that may be larger drivers of NPS than AD neuropathology, mediators (e.g., race, ethnicity) in the association between NPS and diagnostic group classication, compare NPS in EOAD vs. LOAD, and examine longitudinal changes in neuropsychiatric profiles. [ABSTRACT FROM AUTHOR]

Background: Approximately 10‐25% of amnestic early‐onset dementia are negative for amyloid (Early‐onset non‐Alzheimer's Disease, EOnonAD). EOnonAD is a heterogenous group with various etiologies. In order to better understand the traits of EOnonAD, we clustered amnestic EOnonAD individuals according to cognitive patterns. Method: Cognitive data of 62 EOnonAD individuals from the Longitudinal Early‐onset AD study (LEADS) were Z‐normalized to 91 intact individuals after adjusting for age, sex, and education. This led to domain‐averaged composite Z‐scores for memory, language, speed/attention, visuospatial, and executive function. Cluster analysis using the Ward method on the residuals for the five composites was performed. We used Scree plot using the pseudo T‐squared to determine the optimal number of clusters. We compared demographics, imaging biomarkers (amyloid and tau PET SUVR, hippocampal volume), plasma (pTau231, Aß40, Aß42, glial fibrillary acidic protein, and neurofilament light chain (NfL)), and cerebrospinal fluid (CSF) biomarkers (Aß42/40, NfL, Neurogranin, Visinin‐like protein, YKL‐40, and Synaptosome Associated Protein 25) across the clusters after adjusting for age, sex, and education. We compared gray matter density of each EOnonAD cluster to controls (n = 84) using voxel‐wise multiple linear regressions in SPM12, adjusting for age, sex, education, and intracranial volume. Result: Scree plot using the pseudo‐T‐squared suggested three clusters. Cluster 1 (38/62, 61.3%) was characterized by having the mildest cognitive impairment in all domains. Cluster 2 (19/62, 30.6%) was characterized by more severe memory and language impairment. Cluster 3 (5/62, 8.1%) was characterized by more severe impairment in speed/attention, visuospatial, and executive function (Table 1). Cluster 3 showed significantly higher NfL for both plasma (Cluster 1 vs 3, p<0.001; Cluster 2 vs 3, p < 0.004) and CSF (Cluster 1 vs 3, p = 0.001). Other biomarkers did not show significant difference (Table 1). Only Cluster 3 showed significant atrophy in the bilateral fronto‐parietal areas at p<0.01, uncorrected (Figure 1). Conclusion: We identified heterogeneity in cognitive patterns among amnestic EOnonAD individuals. Cluster 1 had mildest cognitive impairment; Cluster 2 had predominant impairment in memory and language; and Cluster 3 had predominant impairment in speed/attention, visuospatial, and executive function, with significant fronto‐parietal atrophy and high NfL indicating active neurodegeneration. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is clinically characterized by disabling cognitive impairment, though substantial variability in cognitive symptoms and trajectories is observed in AD individuals. However, genetic predictors of domain‐specific cognitive performance remain undiscovered. We investigated cross‐sectional and longitudinal genetic architecture of harmonized memory, executive function, and language scores within and across ancestry groups. Method: Using data from 7 cohorts of cognitive aging and AD, individuals >60 years at baseline were included (mean age at baseline = 71.2). Cognitive scores for memory, executive function, and language were harmonized using latent variable models. Slopes for cognitive scores were calculated for each domain with linear mixed‐effects models. GWAS was performed on each cognitive domain for individual cohorts, both at baseline and longitudinally. Models covaried for baseline age, sex, and the first three genetic principal components. Individual models were assessed among non‐Hispanic Whites (NHW) (N = 26,455), non‐Hispanic Blacks (NHB) (N = 3,410), and cross‐ancestry (NHW + NHB) (N = 29,865). Results were meta‐analyzed across cohorts. Result: We identified six genetic loci showing a genome‐wide significant effect on cognition, in addition to well‐established associations between cognition and APOE: three loci in NHW, one locus in NHB, and two loci in cross‐ancestry results. In NHW, a chromosome 2 locus (rs6733839) near BIN1, a previously reported AD risk gene, was associated with longitudinal memory performance (MAF = 0.40, p = 3.36E‐08). Additionally, in NHW, two chromosome 2 loci (rs2940785 and rs2972059) were associated with memory decline (MAF = 0.05, = 3.92E‐09; MAF = 0.05, p = 5.06E‐09, respectively). Despite the small sample size, a chromosome 10 locus (rs77595416) was associated with longitudinal executive function in NHB (MAF = 0.01, p = 7.68E‐09). When analyzing cross‐ancestry results, two chromosome 2 loci near BIN1 (rs4663105 and rs6733839) were associated with memory decline (MAF = 0.44, p = 2.65E‐08; MAF = 0.40, p = 9.48E‐10, respectively). Conclusion: We elucidate novel and replicate known genetic predictors of domain‐specific cognition in older adults. Furthermore, we show that genetic architecture of multiple cognitive domains in older adults differs by ancestry, highlighting SNPs observed in longitudinal memory (NHW and cross‐ancestry) and executive function (NHB). While replication is warranted, our results underscore the contribution of genetic predictors beyond APOE to cognitive decline and suggest the importance of ancestry‐specific analyses of cognition. [ABSTRACT FROM AUTHOR]

Introduction: One goal of the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is to investigate the genetic etiology of early onset (40–64 years) cognitive impairment. Toward this goal, LEADS participants are screened for known pathogenic variants. Methods: LEADS amyloid‐positive early‐onset Alzheimer's disease (EOAD) or negative early‐onset non‐AD (EOnonAD) cases were whole exome sequenced (N = 299). Pathogenic variant frequency in APP, PSEN1, PSEN2, GRN, MAPT, and C9ORF72 was assessed for EOAD and EOnonAD. Gene burden testing was performed in cases compared to similar‐age cognitively normal controls in the Parkinson's Progression Markers Initiative (PPMI) study. Results: Previously reported pathogenic variants in the six genes were identified in 1.35% of EOAD (3/223) and 6.58% of EOnonAD (5/76). No genes showed enrichment for carriers of rare functional variants in LEADS cases. Discussion: Results suggest that LEADS is enriched for novel genetic causative variants, as previously reported variants are not observed in most cases. Highlights: Sequencing identified eight cognitively impaired pathogenic variant carriers.Pathogenic variants were identified in PSEN1, GRN, MAPT, and C9ORF72.Rare variants were not enriched in APP, PSEN1/2, GRN, and MAPT.The Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is a key resource for early‐onset Alzheimer's genetic research [ABSTRACT FROM AUTHOR]

INTRODUCTION: Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early‐onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker. METHODS: We analyzed MRI scans to define the sporadic EOAD‐signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early‐onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment. RESULTS: The EOAD‐signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD‐signature atrophy was associated with the severity of cognitive impairment. DISCUSSION: The EOAD‐signature atrophy is a reliable and clinically valid biomarker of AD‐related neurodegeneration that could be used in clinical trials for EOAD. Highlights: We developed an early‐onset Alzheimer's disease (EOAD)–signature of atrophy based on magnetic resonance imaging (MRI) scans.EOAD signature was robustly reproducible across two independent patient cohorts.EOAD signature included prominent atrophy in parietal and posterior temporal cortex.The EOAD‐signature atrophy was associated with the severity of cognitive impairment.EOAD signature is a reliable and clinically valid biomarker of neurodegeneration. [ABSTRACT FROM AUTHOR]

INTRODUCTION: The Rey Auditory Verbal Learning Test (RAVLT) is a useful neuropsychological test for describing episodic memory impairment in dementia. However, there is limited research on its utility in early‐onset Alzheimer's disease (EOAD). We assess the influence of amyloid and diagnostic syndrome on several memory scores in EOAD. METHODS: We transcribed RAVLT recordings from 303 subjects in the Longitudinal Early‐Onset Alzheimer's Disease Study. Subjects were grouped by amyloid status and syndrome. Primacy, recency, J‐curve, duration, stopping time, and speed score were calculated and entered into linear mixed effects models as dependent variables. RESULTS: Compared with amyloid negative subjects, positive subjects exhibited effects on raw score, primacy, recency, and stopping time. Inter‐syndromic differences were noted with raw score, primacy, recency, J‐curve, and stopping time. DISCUSSION: RAVLT measures are sensitive to the effects of amyloid and syndrome in EOAD. Future work is needed to quantify the predictive value of these scores. Highlights: RAVLT patterns characterize various presentations of EOAD and EOnonADAmyloid impacts raw score, primacy, recency, and stopping timeTiming‐based scores add value over traditional count‐based scores [ABSTRACT FROM AUTHOR]

INTRODUCTION: We compared white matter hyperintensities (WMHs) in early‐onset Alzheimer's disease (EOAD) with cognitively normal (CN) and early‐onset amyloid‐negative cognitively impaired (EOnonAD) groups in the Longitudinal Early‐Onset Alzheimer's Disease Study. METHODS: We investigated the role of increased WMH in cognition and amyloid and tau burden. We compared WMH burden of 205 EOAD, 68 EOnonAD, and 89 CN participants in lobar regions using t‐tests and analyses of covariance. Linear regression analyses were used to investigate the association between WMH and cognitive impairment and that between amyloid and tau burden. RESULTS: EOAD showed greater WMHs compared with CN and EOnonAD participants across all regions with no significant differences between CN and EOnonAD groups. Greater WMHs were associated with worse cognition. Tau burden was positively associated with WMH burden in the EOAD group. DISCUSSION: EOAD consistently showed higher WMH volumes. Overall, greater WMHs were associated with worse cognition and higher tau burden in EOAD. Highlights: This study represents a comprehensive characterization of WMHs in sporadic EOAD.WMH volumes are associated with tau burden from positron emission tomography (PET) in EOAD, suggesting WMHs are correlated with increasing burden of AD.Greater WMH volumes are associated with worse performance on global cognitive tests.EOAD participants have higher WMH volumes compared with CN and early‐onset amyloid‐negative cognitively impaired (EOnonAD) groups across all brain regions. [ABSTRACT FROM AUTHOR]

Introduction: One goal of the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) is to define the fluid biomarker characteristics of early‐onset Alzheimer's disease (EOAD). Methods: Cerebrospinal fluid (CSF) concentrations of Aβ1‐40, Aβ1‐42, total tau (tTau), pTau181, VILIP‐1, SNAP‐25, neurogranin (Ng), neurofilament light chain (NfL), and YKL‐40 were measured by immunoassay in 165 LEADS participants. The associations of biomarker concentrations with diagnostic group and standard cognitive tests were evaluated. Results: Biomarkers were correlated with one another. Levels of CSF Aβ42/40, pTau181, tTau, SNAP‐25, and Ng in EOAD differed significantly from cognitively normal and early‐onset non‐AD dementia; NfL, YKL‐40, and VILIP‐1 did not. Across groups, all biomarkers except SNAP‐25 were correlated with cognition. Within the EOAD group, Aβ42/40, NfL, Ng, and SNAP‐25 were correlated with at least one cognitive measure. Discussion: This study provides a comprehensive analysis of CSF biomarkers in sporadic EOAD that can inform EOAD clinical trial design. [ABSTRACT FROM AUTHOR]

Objective: The Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) seeks to provide comprehensive understanding of early‐onset Alzheimer's disease (EOAD; onset <65 years), with the current study profiling baseline clinical, cognitive, biomarker, and genetic characteristics of the cohort nearing the data‐collection mid‐point. Methods: Data from 371 LEADS participants were compared based on diagnostic group classification (cognitively normal [n = 89], amyloid‐positive EOAD [n = 212], and amyloid‐negative early‐onset non‐Alzheimer's disease [EOnonAD; n = 70]). Results: Cognitive performance was worse for EOAD than other groups, and EOAD participants were apolipoprotein E (APOE) ε4 homozygotes at higher rates. An amnestic presentation was common among impaired participants (81%), with several clinical phenotypes present. LEADS participants generally consented at high rates to optional trial procedures. Conclusions: We present the most comprehensive baseline characterization of sporadic EOAD in the United States to date. EOAD presents with widespread cognitive impairment within and across clinical phenotypes, with differences in APOE ε4 allele carrier status appearing to be relevant. HIGHLIGHTS: Findings represent the most comprehensive baseline characterization of sporadic early‐onset Alzheimer's disease (EOAD) to date. Cognitive impairment was widespread for EOAD participants and more severe than other groups.EOAD participants were homozygous apolipoprotein E (APOE) ε4 carriers at higher rates than the EOnonAD group.Amnestic presentation predominated in EOAD and EOnonAD participants, but other clinical phenotypes were present. [ABSTRACT FROM AUTHOR]

INTRODUCTION: We developed demographically‐adjusted normative data for Spanish‐ and English‐speaking Latinos on the Version 3.0 of the National Alzheimer's Coordinating Center Uniform Data Set Neuropsychological Battery (UDS3‐NB). METHODS: Healthy Latino adults (N = 437) age 50–94 (191 Spanish‐ and 246 English‐speaking) enrolled in Alzheimer's Disease Research Centers completed the UDS3‐NB in their preferred language. Normative data were developed via multiple linear regression models on UDS3‐NB raw scores stratified by language group with terms for demographic characteristics (age, years of formal education, and sex). RESULTS: Younger age and more years of education were associated with better performance on most tests in both language groups, with education being particularly influential on raw scores among Spanish‐speakers. Sex effects varied across tests and language groups. DISCUSSION: These normative data are a crucial step toward improving diagnostic accuracy of the UDS3‐NB for neurocognitive disorders among Latinos in the United States and addressing disparities in Alzheimer's disease and related dementias. Highlights: We developed normative data on the UDS3‐NB for Latinos in the US ages 50–94.Younger age and more years of education were linked to better raw scores in several cognitive tests.Education was particularly influential on raw scores among Spanish‐speakers.Sex effects varied across tests and between English‐ and Spanish‐speaking Latinos.These normative data might improve diagnostic accuracy of the UDS3‐NB among Latinos. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Over the past 30 years, MRI has become a ubiquitous tool for accurately visualizing the development of the brain's subcortical structures. However, the quantification of subcortical structures is still in its infancy due to challenges in shape extraction, representation, and modeling. Method: A simple and efficient framework of longitudinal elastic shape analysis (LESA) is developed for subcortical structures. By employing the elastic shape analysis of static surfaces using the square root normal field (SRNF) representations, we computed shape summaries of surfaces and represented the complex subcortical structures using a small number of basis functions. Further, we statistically modeled the sparse longitudinal data to predict the spatial‐temporal shape changes of subcortical structures. We also conducted the temporal registration using the square‐root velocity function (SRVF) framework to quantify the accelerated aging of Alzheimer's disease (AD). Result: We applied LESA to analyze longitudinal neuroimaging data sets and showcased its wide applications in estimating continuous shape trajectories, building life‐span growth patterns, and comparing shape differences among different groups. Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, we found that from 60 to 90 years old, the AD group always had the largest left ventricle (LV) surface area and the smallest left hippocampus (LHC) surface area, followed by the MCI and NC groups. The enlargement of LV and the atrophy of LHC had different speeds among different groups. Most of the shape‐changing differences between the AD and NC groups were visible in the anterior and posterior ends of LV. The atrophy of LHC happened mainly at the posterior end with aging. The AD group had the sharpest posterior end, and the NC group deformed the least with aging. Compared with the NC group, the AD group showed an average accelerated enlargement of 2.91 years and accelerated shape change of 2.76 years in LV; an average accelerated atrophy of 2.56 years and accelerated shape change of 2.59 years in LHC. By constructing the life‐span growth trajectories, we observed increases in shape changes' speed in both LV and LHC after 60 years old. Conclusion: AD can significantly speed up the shape change of ventricle and hippocampus compared with normal aging. [ABSTRACT FROM AUTHOR]

Background: The Standardized Centralized Alzheimer's & related dementias Neuroimaging (SCAN) project harmonizes processing of prospectively acquired PET and MRI scans from Alzheimer's disease research centers (ADRCs) across the USA. SCAN data will be integrated with other ADRC data streams within the National Alzheimer's Coordinating Center (NACC), including the Uniform Data Set which includes rich longitudinal demographic, cognitive, and neuropathological data, resulting in a large, potentially representative cohort. The project has sought to accommodate site‐to‐site variation in image acquisition while permitting harmonization of imaging data, necessitating new analytic approaches for different PET tracers and PET scans without MRIs. Method: PET scans underwent preprocessing for quality control and smoothing to a uniform resolution. MRI‐free processing pipelines and positivity thresholds were developed for each beta‐amyloid (Aβ)‐PET tracer: [11C]PiB, [18F]florbetaben (FBB), [18F]florbetapir (FBP) and [18F]flutafuranol (NAV). A generic Aβ‐PET template was used for spatial normalization and cortical summary SUVRs were calculated in template space. Aβ‐positivity thresholds were determined by examining both MRI‐dependent thresholds transformed into MRI‐free units and a young control mean+2SD. Centiloid (CL) conversions were completed for each Aβ‐PET tracer. Tau‐PET tracers ([18F]flortaucipir (FTP) and [18F]MK‐6240) required tracer‐specific warping templates for best performance relative to gold‐standard MRI‐dependent processing. Demographic and clinical data were obtained from NACC. Result: 15 ADRCs have contributed data to SCAN as of January 2023. 477 participants had preprocessed, SCAN‐compliant (https://scan.naccdata.org/) Aβ‐PET scans and NACC data; 219 of these participants (46%) also had tau‐PET scans (Table 1). This cohort included 18% of individuals from underrepresented groups. Clinical diagnostic groups ranged from cognitively unimpaired to MCI and dementia (74% of whom had AD dementia). Using pooled Aβ‐PET data across 4 tracers in CLs, there were expected differences in Aβ burden by diagnosis group (Fig. 1) and positive associations with tau (Fig. 2). Conclusion: SCAN has successfully harmonized PET data from more than a dozen US ADRCs yielding a large, clinically heterogeneous cohort of deeply phenotyped research participants. SCAN data will be compatible with ADNI data allowing for further pooling of data and greater statistical power to drive critical questions in AD and related dementias research. [ABSTRACT FROM AUTHOR]

Background: A recently recognized subset of older individuals are an anomaly of cognitive decline; the "SuperAgers", unsurprisingly named, achieve cognitive scores equivalent to much younger cognitively normal (CN) middle‐aged adults. Using longitudinal cognitive data harmonized across eight cohorts of aging and Alzheimer's Dementia (AD), we investigated the genetic drivers of SuperAging. Method: Harmonized memory, executive function, and language scores were estimated leveraging latent variable modeling and made available through the ADSP Phenotype Harmonization Consortium. SuperAgers (N = 1,095) were defined as individuals over 80 years with a mean sex‐adjusted memory score equal or exceeding CN individuals aged 50‐60, score within one age and sex‐adjusted standard deviation in the other two cognitive domains, and remain CN for all longitudinal visits. Young Cases (N = 1,906) were defined as individuals aged 50‐75 with a clinical diagnosis of AD. Old Controls (N = 3,247) were defined as CN individuals over 80, scoring within one age‐ and sex‐adjusted standard deviation in all three domains. We performed a GWAS on non‐Hispanic Whites using logistic regression comparing SuperAgers and their counterparts (Young Cases and Old Controls) with covaried adjustment for age, sex, education, and principal components for population substructure. Result: Comparing SuperAgers with Young Cases (Figure 1), only variants in the well‐established APOE region were associated with genome‐wide significance (GWAS; P<510−8). Additionally, we observed a locus on chromosome 13 approach GWS (rs138699163, P = 6.5610−8). The locus centered on a relatively uncharacterized ncRNA, MIR4500. Analyses comparing SuperAgers to Old Controls did not find any GWS associations, with the strongest association observed at rs116535931 on chromosome 5 (P = 1.5210−6). Conclusion: Our extreme‐phenotype GWAS comparing SuperAgers to Young Cases identified established and novel loci for AD. However, larger sample sizes may allow better characterization of the genetic architecture of SuperAging. Future analyses will extend to Case comparison groups to include Old Cases (age>80 years) and All Cases (age>50 years) and Control comparison groups to include Young Controls (age between 50‐60) and Agnostic Controls (age>50 years) with similar criteria. [ABSTRACT FROM AUTHOR]

Background: Genetic analyses of cognitive endophenotypes have led to discoveries of novel loci contributing to Alzheimer's disease (AD) risk. Sex differences are present in cognitive trajectories in aging and AD, and these may vary across cognitive domain. However, genetic drivers that may contribute to sex differences in cognitive trajectories have yet to be explored. Thus, we sought to investigate the sex‐specific genetic architecture of cognition. Method: We leveraged 10 cohorts of cognitive aging and AD to complete this sex‐aware genetic study (N = 31,800; mean age = 73 yrs.; 55% female). Harmonized cognitive scores for memory, executive functioning, and language were derived using confirmatory factor analysis models. We calculated change in cognitive scores over time using a mixed effects model, to facilitate analysis on cognitive decline. We performed GWAS of baseline score and of estimated rate of decline in each domain and in each cohort separately among non‐Hispanic white (NHW) individuals, adjusting for baseline age and genetic principal components. Then we meta‐analyzed the results. Result: In addition to the well‐characterized APOE locus, we identified a genome‐wide significant chromosome 2 locus that was associated with language decline among NHW women (rs13387871: MAF = 0.20; βwomen = 2.97×10−3; Pwomen = 2.65×10−9), but not among male counterparts (βmen = ‐3.14×10−4, Pmen = 0.60). This locus contains multiple eQTLs for VRK2, a serine/threonine kinase that has been previously linked to neuropsychiatric disorders, including schizophrenia. Furthermore, the top variant in this locus (rs13387871) was nominally significant for memory decline (βwomen = 1.74×10−3, Pwomen = 0.01) and for executive functioning decline (βwomen = 7.58×10−4, Pwomen = 0.02) in meta‐analyses among NHW women. Conclusion: Our genetic analysis suggests that there may be some genetic drivers of language performance that differ by sex, and that these drivers may be shared to an extent across domains. Our future sex‐aware meta‐analyses will also include 1) non‐Hispanic black (NHB) within ancestry (N = 4,200), 2) cross‐ancestry (NHW + NHB), 3) diagnosis‐stratified, and 4) analysis of X‐chromosome. Planned follow‐up analyses will include gene‐set analyses, heritability tests, and genetic correlation tests. Through our preliminary analysis, we identified a promising locus for further exploration, and this is the first of many steps in elucidating the sex‐specific genetic architecture of cognition across ancestry groups. [ABSTRACT FROM AUTHOR]

Introduction: Progranulin (GRN) mutations occur in frontotemporal lobar degeneration (FTLD) and in Alzheimer's disease (AD), often with TDP‐43 pathology. Methods: We determined the frequency of rs5848 and rare, pathogenic GRN mutations in two autopsy and one family cohort. We compared Braak stage, β‐amyloid load, hyperphosphorylated tau (PHFtau) tangle density and TDP‐43 pathology in GRN carriers and non‐carriers. Results: Pathogenic GRN mutations were more frequent in all cohorts compared to the Genome Aggregation Database (gnomAD), but there was no evidence for association with AD. Pathogenic GRN carriers had significantly higher PHFtau tangle density adjusting for age, sex and APOE ε4 genotype. AD patients with rs5848 had higher frequencies of hippocampal sclerosis and TDP‐43 deposits. Twenty‐two rare, pathogenic GRN variants were observed in the family cohort. Discussion: GRN mutations in clinical and neuropathological AD increase the burden of tau‐related brain pathology but show no specific association with β‐amyloid load or AD. [ABSTRACT FROM AUTHOR]

Introduction: Alzheimer disease (AD) and related dementias are characterized by damage caused by neuropathological lesions in the brain. These include AD lesions (plaques and tangles) and non‐AD lesions such as vascular injury or Lewy bodies. We report here an assessment of lesion association to dementia in a large clinic‐based population. Methods: We identified 5272 individuals with neuropathological data from the National Alzheimer's Coordinating Center. Individual lesions, as well as a neuropathological composite score (NPCS) were tested for association with dementia, and both functional and neurocognitive impairment using regression models. Results: Most individuals exhibited mixed pathologies, especially AD lesions in combination with non‐AD lesions. All lesion types were associated with one or more clinical outcomes; most even while controlling for AD pathology. The NPCS was also associated with clinical outcomes. Discussion: These data suggest mixed‐type pathologies are extremely common in a clinic‐based population and may contribute to dementia and cognitive impairment. [ABSTRACT FROM AUTHOR]

Background: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study is a prospective study collecting extensive cognitive, clinical, fluid, and imaging biomarkers data from older adults living in Australia. Integration of outcomes between large prospective studies of AD will provide greater precision in models of AD brain‐behavior relationships, so it is important to align composite scores for cognitive domains between such studies. Methods: Detailed methods for AIBL, the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the National Alzheimer's Coordinating Center (NACC) have been published. Briefly, AIBL participants had cognition assessed with an extensive neuropsychological test battery alongside health and biomarker assessments at entry and each 18‐months thereafter. Granular‐level cognitive data were obtained and an expert panel of two neuropsychologists and a behavioral neurologist categorized each element as assessing memory, executive functioning, language, visuospatial, or none of these, exactly as we have done previously. We also identified elements we had previously calibrated from other studies; after careful quality control and confirmation these served as anchors enabling co‐calibration. We used confirmatory factor analysis bi‐factor models to calibrate the AIBL battery with other studies. We used those calibrations to obtain co‐calibrated scores for all AIBL participants at every study visit. Here we show descriptive statistics for baseline visits, separately by diagnosis (normal cognition, mild cognitive impairment (MCI), dementia) for two enrollment waves for AIBL as well as for each phase of ADNI and across the Uniform Data Set (UDS) 1 & 2 (UDS1/2) and UDS3 time periods for NACC. Results: Box plots for memory, executive functioning, language, and visuospatial for people with normal cognition are in Figure 1, MCI in Figure 2, and dementia in Figure 3. These figures show there is substantial cognitive variation across waves within these disease stage groups and across studies. Conclusion: Co‐calibrated neuropsychological domain scores provide a common metric for integrating cognitive data across studies. Co‐calibrated scores aggregated across large prospective AD studies such as AIBL, ADNI, and NACC provide a foundation for large‐scale models of the development of AD and can serve as phenotypes for genetics studies. Co‐calibrated scores are available from AIBL, ADNI, and from NACC. [ABSTRACT FROM AUTHOR]

Patients with early‐onset Alzheimer's disease (EOAD) are commonly excluded from large‐scale observational and therapeutic studies due to their young age, atypical presentation, or absence of pathogenic mutations. The goals of the Longitudinal EOAD Study (LEADS) are to (1) define the clinical, imaging, and fluid biomarker characteristics of EOAD; (2) develop sensitive cognitive and biomarker measures for future clinical and research use; and (3) establish a trial‐ready network. LEADS will follow 400 amyloid beta (Aβ)‐positive EOAD, 200 Aβ‐negative EOnonAD that meet National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria for mild cognitive impairment (MCI) or AD dementia, and 100 age‐matched controls. Participants will undergo clinical and cognitive assessments, magnetic resonance imaging (MRI), [18F]Florbetaben and [18F]Flortaucipir positron emission tomography (PET), lumbar puncture, and blood draw for DNA, RNA, plasma, serum and peripheral blood mononuclear cells, and post‐mortem assessment. To develop more effective AD treatments, scientists need to understand the genetic, biological, and clinical processes involved in EOAD. LEADS will develop a public resource that will enable future planning and implementation of EOAD clinical trials. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is characterized by the presence of beta‐amyloid (Aβ) and tau in the brain. Understanding the interplay between these proteins and their spatial distribution may provide insights into disease progression. This study aims to investigate the topological features of Aβ and tau networks in AD, mild cognitive impairment (MCI), and normal cognition (NC) groups using PET images from the ADNI dataset. Method: Partial correlation matrices between the standardized uptake value ratio of 68 regions of interest (ROI's) were used to generate networks for the AD, MCI, and NC groups, with nodes representing ROI's and edges representing correlation coefficients. Topological features, including H0 features (connected components), H1 features (loops), and landscape functions of H1 features, were calculated for each sample's persistent homology. For each group, 100 bootstrapping samples were used to generate the 95% confidence intervals for landscape functions. The connected components were further studied by representing the samples as hierarchical tree structures. In the tree space, the first few generated connections, representing the most consistent pairs of regions positive for Aβ and tau, were compared across groups. Clustering performances were compared using Wasserstein distance of H0 features, Wasserstein distance of H1 features, landscape function distance, and geodesic distance in tree space respectively. Result: The geodesic distance in tree space showed the best clustering accuracy in both Aβ and tau analyses. Compared with Aβ, H1 features and the corresponding landscape functions performed better for tau. Unique connections in AD and MCI groups were identified, with AD showing more unique connections than MCI compared to NC samples. Dominant unique connections in the AD group included left‐right isthmus cingulate and left fusiform‐left inferior temporal for Aβ, and left‐right paracentral and left cuneus‐left pericalcarine for tau. These connections indicate region pairs with related concentrations of Aβ and tau in AD. Conclusion: Topological network analysis can reveal complex underlying structures in PET images and identify consistent patterns in ROI's associated with Aβ and tau localization. Tau aggregation exhibits more complex behavior than Aβ and is more strongly associated with AD. The identified unique connections in the AD group may serve as potential biomarkers for disease progression. [ABSTRACT FROM AUTHOR]

Background: LATE‐NC is a newly‐defined TDP‐43 proteinopathy that is common in older adults and associated with amnestic dementia syndrome. To our knowledge, no prior study has studied individuals resilient to LATE‐NC (participants with Stage 2 or 3 LATE‐NC but no cognitive impairment at autopsy). The extensive autopsy dataset at the National Alzheimer's Coordinator Center (NACC) uniquely positions us to examine these rare individuals. To determine if asymptomatic participants have lower levels of other neuropathologic diseases, we compared neuropathologic features against participants with clinical dementia. Method: We included autopsied participants from NACC's Uniform Data Set whose last visit was within two years of death or had clinical dementia at their last visit. Participants were excluded if they had rare neuropathologic diseases or were not evaluated for each neuropathologic feature. For asymptomatic (normal cognition, 75+ years old, stage 2 or 3 LATE‐NC) individuals, we calculated the odds of having non‐LATE pathologic features against a control group (stage 2 or 3 LATE‐NC, clinical dementia), adjusting for age at death, sex, education, and presence of APOE e4 allele(s). Features included Alzheimer's pathology (amyloid plaques and neurofibrillary tangles) vascular pathology (number of infarcts and microinfarcts; severity of arteriosclerosis, atherosclerosis, and cerebral amyloid angiopathy), and Lewy body disease (LBD) staging. Result: Of participants who met inclusion criteria, 20 were asymptomatic and 505 were controls. In unadjusted analyses, asymptomatic participants had lower severity of amyloid plaques, tau tangles, LBD, microinfarcts, and arteriosclerosis, and were less likely to have an APOE e4 allele. In adjusted logistic regression analysis, associations remained only for tau tangles, LBD, and APOE. Interestingly, we found no association of asymptomatic LATE‐NC with amyloid plaques (Thal phase or CERAD score). Conclusion: Resilience to LATE‐NC is associated with lower odds of other neuropathologic disease, including neurofibrillary tangles and Lewy bodies. This supports prior research indicating an interactive effect of multiple neuropathologic diseases on risk of dementia. Severity of amyloid plaques was not associated with risk of dementia in participants with LATE‐NC, indicating that amyloid‐reducing therapies may not be an effective way to prevent LATE symptoms. [ABSTRACT FROM AUTHOR]

Background: The Uniform Data Set Neuropsychological Battery, Version 3 (UDSv3) was designed for face‐to‐face assessment of cognition within Alzheimer's Disease Research Centers (ADRCs) in the USA. However, there are many reasons research participants may be unable to meet face‐to‐face for assessments. This inter‐ADRC, multi‐site study will validate a video‐administered adaptation of the UDSv3 battery in a diverse sample of ADRC participants. Here, we present study methods and summarize preliminary participant satisfaction ratings with VCog procedures. Method: Remote video cognitive assessments (Vcog) are being administered 4‐8 weeks before or after annual in‐person UDSv3 cognitive assessments, in counterbalanced order, to 500 participants from 12 ADRCs. Participants were previously classified as having normal cognition (NC), MCI, and mild dementia. Participant ratings of satisfaction, acceptability, and preference for test modality are being obtained, and psychometric characteristics of the video battery relative to face‐to‐face administration evaluated. Concordance between adjudicated outcomes (NC, MCI, dementia) between modalities is also being examined. Result: Of currently enrolled participants from four sites (N = 29 (NC = 14, MCI = 13 and dementia = 2); age: 72.9 (8.9) years; education: 16.2 (2.5) years; 62.1% female; 82.8% non‐Hispanic white), 85% report using video‐conferencing platforms more frequently because of COVID‐19 and 83% of that group anticipate continued use in the future. Participants reported (1 = very easy/likely to agree; 5 = very difficult/likely to disagree) that the testing was convenient (M = 1.14 (.44)), visits were very easy to initiate (M = 1.34 (.72)), technology was very easy to use (M = 1.00 (.00)), and task instructions were easily understood (M = 1.28 (.80)). Seventy‐six percent found video testing to be more convenient than in‐person testing and 24% found it equally convenient. Forty‐eight percent said they would choose video sessions in the future, 21% chose either video or in‐person, and 31% chose in person. Conclusion: Video‐based remote neuropsychological assessments have the potential to greatly benefit research and reduce participant burden. Initial findings from this large validation study of the UDSv3 suggest that older adults of varying cognitive statuses find the video‐adapted UDSv3 cognitive battery to be convenient and easy to use. Additional available data regarding participant satisfaction data will be reviewed. [ABSTRACT FROM AUTHOR]

Background: Version 3 of the Uniform Data Set (UDS) has been collected by the National Alzheimer's Coordinating Center (NACC) since 2015, which contains neuropsychological test scores on multiple domains. However, its potential utility as prevention trial outcomes needs to be examined, in comparison with other previously validated outcomes. Method: The analytical sample was extracted from the December 2022 data freeze from NACC, which includes baseline and follow‐up visits from participants who were cognitively normal during initial visits. Standardized z‐scores for each cognitive domain (attention/working memory, episodic memory, semantic memory/language, executive function, visuospatial function) were calculated. Linear mixed effects models with random intercepts and slopes were used for studying longitudinal changes comparing participants who progressed to MCI or AD (decline subgroup) and those who remained cognitively normal for up to 4 years of follow‐up (stable subgroup), controlling for baseline age, sex, race, education and APOE‐e4 carrier status. We then constructed an approximate effect size weighted average of domain‐specific scores as a global composite measure, obtain effect size estimates using the mini‐mental state examination (MMSE), the Montreal Cognitive Assessment (MoCA) and the composite measure as outcomes, and perform sample size calculations using the following assumptions: a significance level of 5%, 80% power, an equal proportion randomized in a hypothesized intervention and a placebo control arms, in which the intervention group has a 10% to 30% reduction of progression to MCI during the study period, each participant has a baseline visit and up to four annual follow‐up visits, a dropout rate of 10% per year. Result: The estimated difference of the annualized rate of change in z‐scores between the decline and stable subgroups ranged from 0.028 (attention) to 0.105 (executive function) standardized units for the domain‐specific scores, and 0.068 standard deviation units for the composite score. The composite score requires a smaller sample size for detecting the same level of reduction in progression compared to MoCA and MMSE. Conclusion: Using a global composite score of UDS version 3 neuropsychological tests as a prevention trial outcome would result in about 30‐50% reduction of sample size needed compared to MMSE and MoCA. [ABSTRACT FROM AUTHOR]

Background: Numerous genome‐wide association studies (GWASs) have been performed for the determination of genes and variants contributing to Alzheimer's disease (AD). We hypothesized that it is important to explore whether the previously‐reported AD‐associated genes in GWASs can have neuropathological effects in the brain and can be employed as potential biomarkers for neuropathological outcomes such as neuritic plaque development. Neuritic plaques (also known as amyloid plaques) are extracellular deposits of the amyloid beta protein primarily found in the grey matter of the brain and are the most discernible neuropathological alterations observed in individuals with dementia. Method: Here, we report the genetic association study of neuropathology data such as neuritic plaque measurements in an AD cohort at the National Alzheimer's Coordinating Center (NACC) using a sample of 1,283 individuals. We acquired the genetic data from the Alzheimer's Disease Sequencing Project (ADSP) which generated whole genome sequencing data through the ADSP Quality Control pipeline. We employed 18 loci where the associations of these loci with AD risk were validated by the recent GWASs. Analysis was obtained using a linear mixed model after adjustment for covariates including age at death, gender, the number of the APOE e4 allele (i.e., 0, 1, and 2), ancestry representative principle components (i.e., population structure), and a genetic relatedness matrix (i.e., a polygenic effect due to genetic relatedness among individuals). Result: From our analysis, we generalized to the NACC cohort significant associations after Bonferroni correction with neuritic plaque measurements and one previously identified locus such as BIN1 on chromosome 2 (p = 4.65×10−5). Furthermore, we detected, at the significance level after Bonferroni correction, a novel locus for neuritic plaque formation that has not previously been reported: PICALM (or nearby LINC02695 or nearby RNU6‐560P) on chromosome 11 (p = 1.02×10−3). PICALM is a strong candidate for playing a role in neuritic plaque formation because deficiency in PICALM results in diminished amyloid‐β clearance. Conclusion: The results from our genetic association study of neuritic plaque formation in the AD cohort underline the potential of utilizing neuropathology data to discover additional support for relevant loci being associated with AD across diverse populations. [ABSTRACT FROM AUTHOR]

Background: Cardio and cerebrovascular diseases co‐exist in up to a third of the Alzheimer's disease (AD) patients, and the presence of cardiovascular/cerebrovascular risk factors (CVRFs) are associated with the risk of AD in middle age and later. The relationship between CVRFs such as hypertension, body mass index, diabetes and coronary heart disease, and AD is well known, but there has been limited mechanistic evidence directly linking these vascular risk factors in AD to the presence of ischemic microvascular pathology. Each of these vascular factors has the capacity to impair the blood‐brain barrier and glio‐vascular units. Arterial pulses and flow are required for glymphatic clearance of molecules including amyloid β. Few studies have directly linked genetic variation related to the risk factors and the molecular mechanisms underlying the interplay of CVRF and genetics in AD. APOE plays a role in the metabolism of cholesterol and other lipids in the brain. Other genetic variants that have been found to interact with cardio and cerebrovascular risk factors include the CLU, PICALM, CR1, BIN1, ACE, AGT, and ALDH2. Methods: We analyzed several large multi‐ethnic AD cohorts to understand the role of cardiovascular risk in the disease. We created a CVRF score comprised of hypertension, diabetes, heart disease and body‐mass‐index and tested the interaction of the score with genetic variants in conferring risk of AD. Results: We found that genetic variants in FMNL2, BRINP1, RFC2, and IGFN1 interact with enhanced risk score for CVRFs, to modify the risk of developing AD. FMNL2 and BRINP1 brain expression is increased in patients that have pathological hallmark of AD and have chronic infarcts. Causal mediation analysis found that both amyloid and tau pathology increased FMNL2 expression which in turn resulted in higher risk of AD, suggesting that AD brains enhance the activity of this gene. Conclusions: We propose that that FMNL2 is part of a larger set of genetic and molecular network that underlies the interaction between CVRF and AD. Clinical studies and basic science with animal models could be harmonized to discover new disease mechanisms, which could open new clinical directions and drug development efforts. [ABSTRACT FROM AUTHOR]

Background: Alzheimer disease (AD) presents with two primary pathologies: neurofibrillary tangles (NFT) and neuritic plaques (NP). However, these hallmark pathologies typically co‐occur with pathologies from AD‐related dementias like cerebral amyloid angiopathy (CAA) [Godrich, 2022; PMID: 35142102]. While CAA is known to impact cognitive impairment, the role of CAA in AD dementia is still not well described [Rabin, 2022; PMID: 35759327]. Here we present an analysis of CAA, NP, and NFT to assess the interplay of these pathologies with cognitive decline and genetic risk factors for AD. Method: Data come from 4,915 autopsied individuals from the National Alzheimer's Coordinating Centers (NACC). NFT, NP, and CAA were measured ordinally. We used ordinal logistic regression to model and compare independent and interactive effects of CAA and NP on NFT and cognitive decline while adjusting for sex, AAD, and APOE. We also evaluate models with an APOE and NP interaction as a comparison to gauge whether it is more informative than CAA. Finally, we replicate causal mediation analysis from Rabin et al. and extend the path model to include APOE, stratifying both models by NP severity (Fig.1). Result: The model with CAA and NP interactions best explained NFT burden outcome (per AIC, pseudo‐R2, and F‐test), even when compared to models with APOE. We replicated Rabin et al. findings that CAA does not directly affect cognitive decline but rather indirectly via NFT mediation, but only in individuals in the high NP group. We saw this in a larger clinical cohort with ordinal measures of neuropathology, which are more commonly obtained than linear ones. We also extended the mediation analysis to include APOE and findings held. Conclusion: We replicated the relationship between CAA, AD pathologies, and cognitive decline [Rabin, 2022] and extend the findings to a more heterogeneous clinical population. Even when accounting for APOE, CAA still had an indirect effect on cognitive decline in the high NP group as mediated by NFT severity, showing that the findings are likely not due to APOE confounding. These findings continue to underscore the importance of the consideration of co‐occurring neuropathologies like CAA when developing novel AD therapeutics. [ABSTRACT FROM AUTHOR]

Background: Cerebral amyloid angiopathy (CAA) commonly co‐occurs with Alzheimer's disease (AD) pathologies, leading to an increased risk and severity of cognitive decline. While CAA is known to impact cognitive impairment, the genetics of CAA are not well understood, and most previous sample sizes have been small. To address this gap, we conducted a genome‐wide association study (GWAS) of CAA pathology to identify genetic factors that are associated with this understudied AD‐related amyloidosis. Method: We utilized data from 6,038 autopsied and genotyped individuals from the National Alzheimer's Coordinating Centers (NACC) who were evaluated for CAA pathology upon autopsy. Participants were age 50+ at death and non‐Hispanic white. Genetic data were available from SNP arrays imputed to TOPMed and analyses were conducted only on common variants (MAF >0.01). GWAS performed ordinal logistic regression to determine the effects of genetic variants on CAA pathology (coded as 0, none; 1, mild; 2, moderate; 3, severe). Models adjusted for sex, age at death, and the first three genetic principal components (PC‐AiR; GENESIS; R v4.2). We then meta‐analyzed across the cohorts (METAL). Result: We observed genome‐wide significant associations with CAA severity at established AD loci, including APOE (top SNP: rs429358, MAF = 0.155, P = 1.6E−86) and BIN1 (top SNP: rs6733839, MAF = 0.397, P = 3.9E−08). We observed a novel association with CAA pathology on chromosome 9 (top SNP: rs10908023, MAF = 0.258, P = 4.3E−11). Conclusion: This is the largest study to date aimed at identifying genetics factors associated with CAA pathology. Our findings offer new insights into the genetics of CAA, a common player in the AD landscape. We acknowledge the need for a larger dataset and are now expanding the study by sample size and by including additional ADRD phenotypes to gain a better understanding of the full spectrum AD/ADRD. Continuing to uncover the genetic underpinnings of CAA could potentially help us think about AD treatment in new ways and mitigate the negative side‐effects of brain swelling and bleeding that have been observed in recent clinical trials. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a heterogeneous proteinopathy. Co‐pathology with Lewy bodies (LB) is frequent and known to contribute to a differential pattern of executive cognitive impairment compared to typical AD. While primary age‐related tauopathy (PART) presents with neurofibrillary tangles, mainly restricted to the temporal lobe and in the absence of amyloid‐beta plaques, LB co‐pathology is also present. However, it is still unknown how the combination of these proteinopathies affects patterns of brain atrophy, which might help clarify the clinical importance and pathophysiology of combined pathology within these groups. Here we investigated the influence of LB on patterns of brain atrophy in AD and PART. Methods: We selected 214 patients with AD neuropathological change (ADNC) with no LB (n = 102), ADNC with LB (ADNC+LB) (n = 77), PART with no LB (n = 22) and PART with LB (PART+LB) (n = 13) with ante‐mortem volumetric MRI from the National Alzheimer's Coordinating Center, after exclusion of other neurodegenerative pathologies. Dementia severity was compared using Clinical Dementia Rating Scale Sum of Boxes (CDR‐SB). Cortical and subcortical MRI volume residuals were compared between groups after correction for age. Statistical significance was considered at p‐value < 0.05 after false discovery rate correction for multiple comparisons. Results: We found that ADNC, ADNC+LB and PART+LB presented similar levels of dementia severity, whereas PART with no LB was the least affected group. MRI revealed higher atrophy of the right frontal operculum and amygdala in ADNC+LB compared to ADNC. ADNC and ADNC+LB showed increased atrophy in regions across all cortical lobes, hippocampus, amygdala and putamen compared to PART, but did not reveal significant differences compared to PART+LB. Interestingly, PART+LB showed higher atrophy of the frontal poles bilaterally, right superior frontal gyrus, left frontal operculum and right putamen compared to PART. Conclusions: Altogether, these results suggest that LB co‐pathology contributes to frontal lobe regional atrophy in ADNC and likely drives it in PART. Particularly in PART+LB, it suggests that cognitive impairment might derive from alpha‐synuclein pathology rather than tauopathy. These findings indicate that LB pathology determines disease severity within the PART‐ and AD‐continuums. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular risk factors (CVRFs) increase the risk of cerebrovascular disease and AD, and over 30% of the patients with AD coincident cerebrovascular pathology. We previously found that FMNL2 interacts with CVRFs (p = 6.6e‐07) by altering the normal astroglial‐vascular mechanisms that underly amyloid clearance. The goal here was to identify additional genes that contribute to the interaction between CVRFs and AD. Method: A collection of eight multi‐ethnic cohorts was explored to study genome‐wide gene‐CVRF score interaction analysis for AD, in 7,441 AD patients and 10,453 controls. The cardiovascular risk factors score (CVRF score) was created from a first principal component of the four vascular risk factors; self‐reported history of hypertension, diabetes, and heart disease, and measured body mass index. Gene‐based interaction test was performed using the adaptive gene‐environment interaction (aGE) test. Results were summarized using a meta‐analysis. We investigated the association of gene expression with pathological AD and AD phenotype (amyloid‐β, tau, or brain infarcts) in 1,092 samples from the frontal cortex in ROSMAP. The pathway enrichment analysis was performed on the differentially expressed genes. Age and sex were adjusted in the models. Result: The previous interaction of CVRF score with FMNL2 (p = 3.64e‐07) was strengthened and additional genes were identified including BRINP1 (p = 2.45e‐06), CFAP99 (p = 3.3e‐06), and PRG3 (p = 3.71e‐06). FMNL2 encodes a formin‐related protein important in regulating actin and microtubules. FMNL2 and BRINP1 expressions were higher in the brains of patients with brain infarcts (p = 0.025 and p = 0.006, respectively). The expression level of BRINP1 interacted with brain infarcts on pathological AD (p = 0.02) and with amyloid‐β or tau on brain infarcts (p = 0.02 and p = 0.01, respectively). The pathways were relevant to cellular interactions between astrocytes and endothelia as well as the immune system reaction in the glio‐vascular niche. Conclusion: The four novel genes are likely to be involved in the complex interaction between Alzheimer's disease pathologies (amyloid and phosphorylated tau deposition) and cerebrovascular pathology, for example, at the glia‐vascular interface during AD progression. Understanding how these genes interfere with the mechanisms underlying the clearance of amyloid and tau increasing their deposition in brain will be essential. [ABSTRACT FROM AUTHOR]

Background: More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD‐related endophenotypes. Method: We conducted genome‐wide scans for cognitive domain performance using harmonized and co‐calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community‐based (FHS, ACT, ROSMAP) and clinic‐based (ADRCs, ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP×age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse‐variance meta‐analysis. Genome‐wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software. Result: Individual domain and pleiotropy analyses revealed genome‐wide significant (GWS) associations with five established loci for AD and AD‐related disorders (BIN1, CR1, GRN, MS4A6A, APOE) and eight novel loci. ULK2 was associated with executive function in the community‐based cohorts (rs157405, P = 2.19×10−9). GWS associations for language were identified with CDK14 in the clinic‐based cohorts (rs705353, P = 1.73×10−8) and LINC02712 in the total sample (rs145012974, P = 3.66×10−8). GRN (rs5848, P = 4.21×10−8) and PURG (rs117523305, P = 1.73×10−8) were associated with memory in the total and community‐based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12×10−8) in the clinic‐based cohorts, and with NCALD (rs56162098, P = 1.23×10−9) and PTPRD (rs145989094, P = 8.34×10−9) in the community‐based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09×10−8) and PTPRD (rs145989094, P = 3.85×10−8) in the community‐based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD. Conclusion: Our results provide some insight into genes associated with domain‐specific cognitive impairment and AD, as well as a conduit toward a syndrome‐specific precision medicine approach to AD. Increasing the size of datasets by applying the confirmatory factor analysis approach to derive harmonized measures of cognitive performance would likely enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias. [ABSTRACT FROM AUTHOR]