Citations

Abstract Introduction Alzheimer’s disease (AD) is characterized by pathologies including amyloid, tau, neurodegeneration reflected in established blood biomarkers and track with clinical changes. However, the association between peripheral cell-specific signatures and AD-related phenotypes remain poorly characterized. Methods We analyzed bulk blood transcriptome data from the Mayo Clinic Study of Aging (MCSA) and Emory University Vascular study. We used BayesPrism, CIBERSORTx, and an in-house pipeline CNNreg to deconvolute these data and obtain peripheral cell proportions. Cell type specific transcripts were estimated with BayesPrism. We compared cell proportions between cases (AD/MCI) and controls. Association analysis was performed between cell type specific transcripts and AD-related phenotypes including diagnosis and cognition. Meta-analysis of transcripts associations and gene ontology analysis were conducted to assess the enriched pathways for significant genes. Results In MCSA, B and CD4+ T cells proportions are significantly lower while that of myeloid cells higher in cases. The Emory cohort had similar trends. We identified transcripts associated with AD-related phenotypes in CD4+ T and CD8+ T cells. In CD4+ T cells, transcripts downregulated in case are enriched in response to stimulus pathway, whereas those upregulated in negative regulation of immune response. Downregulation of CD4+ T genes enriched in extracellular matrix disassembly and epigenetic regulation and upregulation of those in protein localization associate with better cognition. In CD8+T cells, genes pertinent to vascular development were downregulated while those to metabolic processes were upregulated in cases. Downregulation of CD8+T genes involved in lipid transportation and upregulation of those in mitochondria associate with better cognition. Conclusion We identified peripheral cellular transcriptional changes associated with AD/MCI phenotypes and involved in important biological pathways, revealing potential disease mechanisms in AD. Funding Source RF1 AG051504 Topic Categories Neuroimmunology (NEUR)

Abstract Histopathological assessment has served as the gold standard for diagnosing Alzheimer’s disease (AD). Emerging technological advancements, including the development of amyloid positron emission tomography (PET), have enabled early detection of amyloid pathology, one of the neuropathological hallmarks of AD. Genome-wide association study (GWAS) across cohorts of aging and AD, leveraging different measurements of amyloid burden, may facilitate the identification of novel genetic variants that drive the earliest neuropathological changes in AD. This study presents the largest GWAS of brain amyloidosis to date, leveraging amyloid β (Aβ) measured by in vivo amyloid PET and postmortem histopathology from 13,555 individuals of European ancestry. Amyloid positivity was defined as moderate or frequent neuritic plaques according to the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) staging scores for each postmortem cohort. A Gaussian mixture model (GMM) was applied to each amyloid PET cohort to identify the cohort and tracer-specific cut-offs that differentiate amyloid positive and negative populations. In silico and ex vivo analyses further characterized implicated loci, including interrogating the association between bulk and single-nucleus gene expression profiles and AD-related traits. Genetic covariance analysis assessed the extent amyloid PET and postmortem measures reflect the shared genetic architecture of brain amyloidosis. Our combined amyloidosis GWAS identified three established AD risk loci: BIN1 (rs6733839, OR = 1.20, 95% CI 1.14-1.26, P = 1.32 × 10−11), CR1 (rs4844610, OR = 1.24, 95% CI = 1.16-1.32, P = 4.21 × 10−10), APOE (rs429358, OR = 4.01, 95% CI = 3.66-4.38, P = 4.54 × 10−201), and a newly identified brain amyloidosis-associated variant on chromosome 17 (rs35635959, OR = 1.18, 95% CI = 1.12-1.25, P = 1.47 × 10−8). SuSiE fine-mapping identified a single credible set of 15 putative causal variants with rs35635959 as the lead variant. Subsequent eQTL and SuSiE-based colocalization analyses prioritized rs35635959 as a strong eQTL for TUBG2, encoding tubulin gamma 2, which is involved in microtubule organization and synaptic plasticity. Further cell-type-specific characterization of this gene in neurons from dorsolateral prefrontal cortex tissue indicated that decreased TUBG2 expression was associated with increased Aβ burden and AD case status (PFDR < 0.045). Furthermore, our study is the first to report a modest genetic covariance (covariance=0.17, P < 6.54 × 10−8) between the genetic architecture of amyloid burden captured by different modalities. While APOE showed a strong association with both amyloid endophenotypes, the observed genetic covariance was not substantially attenuated after excluding variants within the APOE region (covariance=0.16, P < 1.32 × 10−7). Our results highlight the benefits of leveraging compatible, harmonized AD endophenotypes to increase power to uncover new molecular insights into the etiology of AD neuropathology. Wang et al. present the largest GWAS of brain amyloidosis to date, analysing 13,555 individuals using amyloid PET and postmortem Aβ measures. They identify a novel amyloidosis-associated variant on chromosome 17, demonstrate genetic covariance between modalities, and highlight complex traits sharing genetic architecture with Aβ burden.

Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently celebrated its 20th anniversary, reflecting two decades of major contributions to Alzheimer's research through open data sharing and longitudinal multimodal assessments. This review synthesizes 122 high‐impact studies using ADNI data or biospecimens from 2023 to mid‐2025 to clarify mechanisms of Alzheimer's disease (AD) progression. Studies describe impairment of glymphatic clearance and the impact of cerebral small vessel disease, trajectories of amyloid beta and tau deposition, inflammation, metabolic disturbances, synaptic dysfunction, and neurodegeneration, leading to cognitive impairment and neuropsychiatric symptoms. Multifactorial contributions from genetic and epigenetic influences, co‐pathologies and comorbidities, and mechanisms of resilience modulate disease progression. Finally, heterogeneity of clinical presentation and disease course is described in the context of multiple contributing factors, highlighting the complexity of AD. By integrating imaging, fluid biomarkers, genetics, and clinical measures, ADNI provides a comprehensive research dataset for unraveling mechanisms underlying AD progression.

Abstract Alzheimer's disease (AD) continues to pose a major public health challenge. Since its launch in 2004, the Alzheimer's Disease Neuroimaging Initiative (ADNI) has played a pivotal role in advancing the field by providing a comprehensive, open‐access, longitudinal dataset that integrates neuroimaging, biomarker, genetic, and clinical data related to AD. We used standard literature search methods to identify ∼1830 publications from 2023 to mid‐2025 that used ADNI data or samples. This review highlights key ADNI studies with direct clinical applications. We describe how these have impacted the development and validation of plasma biomarkers, improved clinical trials, assessed AD therapies, and developed methods for diagnosis and prediction using clinical, fluid, and imaging biomarkers. These contributions are underlain by an improved understanding of biological mechanisms of disease progression in AD and highlight ADNI's central role in advancing translational research and accelerating progress toward more effective, individualized care for patients with AD.

Importance Sex differences are increasingly recognized as modifiers of Alzheimer disease and related dementias, with women exhibiting greater tau burden and faster cognitive decline than men. Even though α-synuclein copathology frequently occurs in Alzheimer disease, its contribution to sex differences in disease progression is unclear. Objective To test whether α-synuclein positivity, measured using cerebrospinal fluid seed amplification assay (SAA), is differentially associated with tau accumulation in women vs men across the Alzheimer disease continuum. Design, Setting, and Participants This cohort study used longitudinal tau positron emission tomography from the Alzheimer’s Disease Neuroimaging Initiative collected between 2015 and 2023, with a median (IQR) follow-up of 1.23 (0.00-3.84) years. Participants were stratified by cerebrospinal fluid α-synuclein seed amplification assay status and sex. Participants were cognitively unimpaired or cognitively impaired (mild cognitive impairment or dementia) at baseline. Exposure Cerebrospinal fluid α-synuclein status determined by SAA and dichotomized as SAA negative or SAA positive. Main Outcomes and Measures Tau burden was quantified as standardized uptake value ratio (SUVr) in the medial temporal composite region of interest. Linear mixed-effects models tested SAA by sex by time interactions on longitudinal tau accumulation, adjusting for baseline age, baseline cognitive status, apolipoprotein E ε4 carrier status, and site. Sample size estimates were calculated to detect 25% and 50% treatment effects with 80% power in those with cognitive impairment. Results Among 415 participants (mean [SD] age, 72.3 [7.6] years; 220 women [53%]; 69 SAA positive [17%] and 346 SAA negative [83%]), there was a significant interaction between SAA status, sex, and time on tau accumulation (β, 0.061; 95% CI, 0.030-0.093; P < .001). Women with positive SAA results exhibited the fastest tau accumulation compared with other groups (0.066 SUVr per year; 95% CI, 0.043 to 0.089 SUVr per year; P < .001). Clinical trials targeting tau pathology in cognitively impaired individuals with 18-month follow-up would require 129 SAA-positive women to detect a 25% treatment effect with 80% power, compared with 518 SAA-negative women. Conclusions and Relevance In this cohort study of participants across the Alzheimer disease continuum, α-synuclein copathology was associated with faster tau accumulation in women than men. These findings may inform sex-specific interpretation of α-synuclein biomarkers and trial design.

Abstract INTRODUCTION The genetic basis of sporadic early‐onset Alzheimer's disease (EOAD) remains largely unknown, prompting evaluation of late‐onset Alzheimer's disease (LOAD) polygenic risk in EOAD. METHODS A LOAD polygenic score (PGS) was calculated in the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) and Alzheimer's Disease Neuroimaging Initiative (ADNI) study and tested for associations with AD risk, cognitive performance, and imaging and fluid biomarkers. RESULTS Though PGS was elevated in LOAD and EOAD, it was not a significant predictor of EOAD adjusting for APOE ε4 carrier status and was not associated with age of EOAD onset ( p = 0.106) or with cognitive performance ( p = 0.417). In LEADS, greater LOAD PGS was associated with differences in neuroimaging and fluid biomarkers, including elevated synaptosomal‐associated protein 25 (SNAP‐25) ( p = 2.3 × 10 −5 ). DISCUSSION While LOAD polygenic risk contributed minimally to EOAD onset and cognitive dysfunction, PGS association with fluid biomarkers in LEADS suggests a role for LOAD polygenic risk in EOAD pathophysiology. Highlights LOAD PGSs were elevated in both LOAD and EOAD compared to controls; however, LOAD PGS did not significantly predict EOAD risk, age at onset, or cognitive performance independent of APOE ε4 in the LEADS. Higher LOAD PGS was associated with lower amyloid PET Centiloids (less brain amyloid deposition) as well as lower CSF biomarker Aβ42 in LEADS (proxy marker suggesting higher brain amyloid deposition) in LEADS; these contradictory findings support the need for larger studies to further investigate whether LOAD PGS is associated with increased amyloid deposition in EOAD. Higher LOAD PGS was also associated with higher levels of CSF synaptosomal‐associated protein 25 (SNAP‐25), a key component of the SNARE complex, suggesting that LOAD genetic factors may contribute to dysregulation of synaptic transmission and/or pathological protein aggregation in EOAD.

Abstract Background Sex, education and race/ethnicity are all associated with risk of Alzheimer's disease dementia. Here, we assess the effects of self‐reported sex, educational attainment and race/ethnicity on amyloid‐positivity, and tau‐PET‐positivity in 12,048 (7,394 cognitively unimpaired [CU], 2,177 MCI, and 2,477 dementia) individuals from 42 cohorts worldwide. Method Logistic generalized estimating equations were used to estimate frequency of amyloid‐positivity (using cohort‐specific thresholds for amyloid‐PET [84%] or CSF) and tau‐PET‐positivity (cohort‐specific thresholds of 2SD above mean temporal uptake in amyloid‐negative controls). We assessed: i) sex and APOEε4 ( N = 10,098) associations, to complement earlier findings of a higher frequency of tau‐positivity in females, ii) effects of lower/higher education ( N = 10,970; cohort‐specific median‐split), and iii) effects of race/ethnicity (non‐Hispanic White [hereafter: White], N = 4880; Asian, N = 116; Black or African‐American [hereafter: Black], N = 353; Hispanic, N = 356, only from Northern‐American cohorts). Outcomes were frequency of amyloid‐positivity in CU individuals only, and tau‐PET‐positivity in both amyloid‐positive (AB+) CU and cognitively impaired (CI, i.e. MCI and dementia) individuals. Interaction effects on the relationship between age and amyloid/tau‐positivity were assessed and only retained in the models when significant. Result Female sex was associated with an APOEε4 ‐independent increased frequency of amyloid‐positivity (β=0.51[0.22], p = 0.02) in CU and increase of tau‐positivity in both AB+CU (β=0.27[0.08]) and AB+CI (β=0.37[0.08], both p <0.01). Remarkably, tau‐positivity frequencies of female APOEε4 non‐carriers were equivalent to male APOEε4 carriers in AB+CI (Figure 1). No significant sex* APOE interactions were observed. In CU, higher education was associated with lower amyloid‐positivity frequency (β=‐0.12[0.05], p = 0.02). In contrast, among AB+CU, there was an age*education interaction effect that indicated more pronounced age effects on tau‐positivity in individuals with higher education (age*education:β interaction =0.03[0.01], p <0.01). There were no education effects in AB+CI (Figure 2). In CU, an age*race/ethnicity interaction effect was observed across all non‐White groups compared to White (Hispanic:β interaction =‐0.05[0.01], p <0.01; Black:‐0.04[0.01], p <0.01; Asian:‐0.02[0.01], p = 0.04). This suggests that the impact of age on amyloid‐positivity was less pronounced in non‐White groups. Furthermore, in AB+CI, Hispanic ethnicity was related to higher tau‐positivity frequency than White (β=0.51[0.22], p = 0.02; Figure 3). Conclusion In this multi‐center initiative comprised of clinical and community‐based cohorts, we observed that self‐reported sex, educational attainment and race/ethnicity were related to positivity‐frequencies of Alzheimer's disease pathology.

Abstract INTRODUCTION We standardized positron emission tomography (PET) data across multiple cohorts and tracers to characterize the frequency of amyloid and tau PET severity along the clinical continuum. METHODS Clinical stage was defined using cohort‐specific criteria and included cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia. Amyloid severity was staged using Centiloids (CL). Tau severity was staged using a hierarchical Braak‐based schema. The cumulative probabilities of PET‐based stages were estimated using ordinal logistic regressions. RESULTS Among 10,396 individuals (mean [standard deviation] age: 71.9 [7.1] years), amyloid levels ≥ 25 CL increased with age among CU and MCI, while amyloid levels ≥ 100 CL were most common in dementia. In 3295 with tau PET, tau severity increased with amyloid and clinical stage and showed complex associations with age. Within each clinical stage, the full spectrum of amyloid and tau PET severity was observed. DISCUSSION PET‐based staging revealed heterogeneous amyloid and tau burden along the clinical continuum. Highlights PET‐based staging is feasible across multiple cohorts and PET tracers. There is heterogeneity in amyloid and tau severity across the clinical spectrum. The frequency of amyloid and tau PET severity increased with clinical severity. The likelihood of tau PET severity differed by age, amyloid, and clinical severity.

Abstract Background Most existing biomarkers for Alzheimer's disease (AD) inform on core AD pathologies in the central nervous system, namely amyloid, tau and neurodegeneration (ATN). However, molecular disease mechanisms underlying AD are complex and heterogeneous, highlighting the need for cost‐effective blood‐based biomarkers that reflect brain molecular changes in AD beyond ATN. Method Using peripheral blood transcriptome data from the Mayo Clinic Study of Aging(MCSA) and the Alzheimer's Disease Neuroimaging Initiative, we identified genes associated with AD or mild cognitive impairment (MCI) diagnosis, cognitive, and harmonized neuroimaging measures in two cohorts, followed by meta‐analysis. We identified consensus gene co‐expression modules in MCSA and ADNI using WGCNA and assessed the association between module eigengenes and aforementioned measures. Using seven bulk brain RNAseq cohorts, we confirmed the preservation of coexpression modules across blood and brain. Enrichment analyses of Gene Ontology (GO) terms and cell‐types were performed using significant and/or hub genes. The MCSA transcriptome was further deconvoluted to obtain cell‐type proportions and cell‐type specific expression. Result Blood transcriptome modules M5 and M8 are upregulated in AD/MCI and associate with worse cognition, whereas M1, M10, M13, M16, and M21 are downregulated in AD/MCI and associate with better cognition. M17 associates with more microhemorrhages. Cell‐type enrichment analysis revealed that M5 is enriched in basophils, monocytes, and neutrophils; M8 in monocytes and neutrophils; M13 in natural kills cells; M17 in megakaryocytes; M21 in B cells. GO analysis shows broad consistency with the cell‐type enrichment analysis. M1, 5, and 8 are preserved in the brain network modules. From these modules, we prioritized transcripts significantly associated with at least one AD‐related phenotype in both blood and brain. Cell‐type deconvolution analysis shows that prioritized transcripts in M1 associate with better cognition and higher metabolic activity in B cells. Conclusion We identified blood transcripts and modules associated with AD/MCI, cognition, or neuroimaging, with three preserved in brain networks. These three modules represent centrally linked peripheral molecular signatures that can reveal perturbed brain pathways and cell level transcriptional changes in AD/MCI. We aim to further investigate the prioritized transcripts in additional datasets to establish them as potential novel biomarkers and therapeutic targets.

Abstract Background Most existing biomarkers for Alzheimer’s disease (AD) inform on core AD pathologies in the central nervous system, namely amyloid, tau and neurodegeneration (ATN). However, molecular disease mechanisms underlying AD are complex and heterogeneous, highlighting the need for cost‐effective blood‐based biomarkers that reflect brain molecular changes in AD beyond ATN. Method Using peripheral blood transcriptome data from the Mayo Clinic Study of Aging(MCSA) and the Alzheimer's Disease Neuroimaging Initiative, we identified genes associated with AD or mild cognitive impairment (MCI) diagnosis, cognitive, and harmonized neuroimaging measures in two cohorts, followed by meta‐analysis. We identified consensus gene co‐expression modules in MCSA and ADNI using WGCNA and assessed the association between module eigengenes and aforementioned measures. Using seven bulk brain RNAseq cohorts, we confirmed the preservation of coexpression modules across blood and brain. Enrichment analyses of Gene Ontology (GO) terms and cell‐types were performed using significant and/or hub genes. The MCSA transcriptome was further deconvoluted to obtain cell‐type proportions and cell‐type specific expression. Result Blood transcriptome modules M5 and M8 are upregulated in AD/MCI and associate with worse cognition, whereas M1, M10, M13, M16, and M21 are downregulated in AD/MCI and associate with better cognition. M17 associates with more microhemorrhages. Cell‐type enrichment analysis revealed that M5 is enriched in basophils, monocytes, and neutrophils; M8 in monocytes and neutrophils; M13 in natural kills cells; M17 in megakaryocytes; M21 in B cells. GO analysis shows broad consistency with the cell‐type enrichment analysis. M1, 5, and 8 are preserved in the brain network modules. From these modules, we prioritized transcripts significantly associated with at least one AD‐related phenotype in both blood and brain. Cell‐type deconvolution analysis shows that prioritized transcripts in M1 associate with better cognition and higher metabolic activity in B cells. Conclusion We identified blood transcripts and modules associated with AD/MCI, cognition, or neuroimaging, with three preserved in brain networks. These three modules represent centrally linked peripheral molecular signatures that can reveal perturbed brain pathways and cell level transcriptional changes in AD/MCI. We aim to further investigate the prioritized transcripts in additional datasets to establish them as potential novel biomarkers and therapeutic targets.