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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 Extensive evidence links cognition, tau, and neurodegeneration in Alzheimer's disease (AD). However, in U.S. POINTER imaging (a community‐recruited clinical trial cohort selected for high cardiovascular risk, ethnoracial diversity, and increased risk of cognitive decline and dementia) tau PET is more closely linked to cognition than in ADNI. Here, we further explore how ADNI and POINTER differ with respect to relationships between cross‐sectional AD biomarkers, cortical thickness, and different cognitive domains. Method U.S. POINTER imaging (Baseline; N = 775; 68.9±5.2 years, 62.8% female) and ADNI ( N = 405; 69.9±5.4 years, 58% female) were matched by age, sex, clinical status, and APOE4 genotype (Table 1). We examined associations between baseline AD biomarkers (Amyloid‐beta (Aβ) PET in centiloids, harmonized tau PET measures of MK6240 in POINTER and FTP in ADNI), regional cortical thickness, and verbal memory (Delayed Story Recall), executive function (Trail‐Making B), and global cognition (Preclinical Alzheimer's Cognitive Composite scores) across each cohort, controlling for age, sex, and education. Result Aβ burden in ADNI was associated with worse executive function ( p < .001) and global cognition ( p < .001) but not memory, whereas in POINTER Aβ burden was not associated with any cognitive domain (Figure 1A). Among Aβ+ individuals, tau burden was associated with poorer performance across domains in ADNI, but only with poorer verbal memory in POINTER (Figures 1B&1C). Additionally, there were stronger positive associations between cortical thickness and executive function and global cognition compared to verbal memory, particularly in ADNI Aβ+ individuals even after adjusting for entorhinal tau ( p < .01; Figure 2). Conclusion Cognitive performance was linked to all biomarkers (Aβ, tau, cortical thickness) but these associations were consistently stronger in ADNI compared to POINTER, particularly in Aβ+ individuals. The stronger thickness‐cognition relationships in ADNI were not driven by tau, indicating that there is a tau‐independent role of thickness in explaining cognition. In ADNI, there were subtle differences between cognitive domains such that executive function was more closely linked than verbal memory to Aβ and cortical thickness, whereas verbal memory was linked to tau in both cohorts. Our study highlights that frequently‐reported AD biomarker associations may be attenuated in heterogeneous, community‐recruited cohorts.

Abstract Background Given low representation of diverse populations in Alzheimer's disease (AD) research, it remains unclear if AD biomarker relationships observed primarily in non‐Hispanic White (NHW) cohorts generalize to other groups. Here we evaluate associations between key AD biomarkers and cognitive performance among cognitively unimpaired non‐Hispanic Blck (NHB) and NHW participants across 2 cohorts with unique sample characteristics. Method Participants included cognitively unimpaired NHB and NHW participants with Aβ and tau PET in ADNI (69 NHB, 402 NHW) and POINTER Imaging (135 NHB, 637 NHW). We examined harmonized measures of global Aβ (in centiloids), entorhinal cortex (EC) tau (quantified with MK6240 in POINTER and FTP in ADNI) and Preclinical Alzheimer's Cognitive Composite (PACC) scores. Regression models within each ethnoracial group evaluated relationships between 1) Aβ and EC tau, and 2) EC tau and PACC performance. Interaction models within each cohort were also conducted to assess differences in these associations by ethnoracial group. All models were adjusted for age and gender. Models with PACC additionally adjusted for education. Result In US POINTER, NHBs had lower Aβ and EC tau burden compared to NHWs (Table 1). In ADNI, there was no difference in EC tau between groups, and no differenence in Aβ after adjusting for age and gender. In US POINTER, the positive Aβ‐EC tau relationship was observed in both ethnoracial groups whereas in ADNI, Aβ was associated with higher EC tau in the NHW but not the NHB group. In both cohorts, EC tau was associated with worse PACC performance in both NHB and NHW and there were no differences in this association by ethnoracial group in interaction models (Figure 1). Conclusion NHBs had lower Aβ and EC tau than NHWs in POINTER but not ADNI, and there were inconsistent associations between Aβ and EC tau across cohorts. Despite these differences, AD biomarkers appear similarly related to cognitive outcomes across ethnoracial groups in both cohorts. Future analyses will attempt to further determine the generalizability of AD biomarker relationships in diverse samples by considering matching on relevant health and demographic characteristics, and inclusion of additional cohorts with harmonized biomarker and cognitive measurements.

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen’s kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure‐1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure‐1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure‐2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure‐2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

Abstract INTRODUCTION New methods estimate amyloid positivity onset age (EAOA) from amyloid positron emission tomography (PET). We explore the genetics of EAOA to identify molecular factors underlying the earliest Alzheimer's disease (AD) changes. METHODS Harmonized amyloid PET data from 4216 participants were used in genome‐wide survival, tissue‐specific gene expression, and genetic covariance analyses of EAOA. RESULTS Variants in apolipoprotein E ( APOE ), ABCA7 , and RASGEF1C associated with earlier EAOA. APOE ε4/ε4 and ε3/ε4 converted 6.3 and 5 years earlier than ε3/ε3, respectively. ε2 was protective against earlier EAOA. rs4147929, an expression quantitative trait locus for ABCA7 , associated with a 4 year earlier EAOA. This variant was associated with lower brain expression of ABCA7 , which was associated with increased amyloid pathology at autopsy. Multiple immune‐related diseases shared genetic covariance with EAOA. DISCUSSION APOE , ABCA7 , and RASGEF1C associated with earlier EAOA, with supporting evidence from tissue‐specific expression analyses, offering insights into intervenable targets at early stages of AD. Highlights Novel methods estimate how long ago a patient converted to amyloid positivity. Estimating this amyloid clock allows us to determine the onset of the earliest Alzheimer's disease changes. We evaluated what genes influence when someone converts to amyloid positivity. Apolipoprotein E ( APOE ) , ABCA7 , and RASGEF1C associated with earlier age of amyloid positivity. Genetic results were supported by tissue‐specific expression analyses.

Abstract Introduction: Cilta-cel is approved in the US and the EU for the treatment of patients (pts) with lenalidomide-refractory multiple myeloma (MM) after ≥1 prior line of therapy (pLOT), including a proteasome inhibitor and an immunomodulatory agent based on the CARTITUDE-1 (CART-1, NCT03548207) and CARTITUDE-4 (CART-4, NCT04181827) studies. Cilta-cel led to deep and durable responses and significant survival benefit in pts with relapsed/refractory MM (RRMM) after ≥3 pLOT in CART-1. In CART-4, cilta-cel led to a significant overall survival benefit with a higher proportion of pts achieving deep, sustained minimal residual disease negativity vs standard of care in pts with lenalidomide-refractory MM after 1–3 pLOT. We investigated the mechanism of action of cilta-cel by correlating biomarkers from peripheral blood and the bone marrow TME with progression-free survival (PFS) and number of pLOT in pts with RRMM from CART-1 and CART-4. Methods: Biomarker analyses were performed using peripheral blood and bone marrow aspirates (BMAs) collected in both CART-1 and CART-4 studies. Immunophenotyping by flow cytometry was performed using peripheral blood at baseline/time of apheresis in samples from both studies. Immune fitness at baseline was assessed in pts by pLOT and in association with PFS. Gene set enrichment scores were derived from RNA sequencing data of the TME using BMAs. Mixed-effects models were used to identify signatures/pathways modulated over time (day [D] 28 and at 6 months [mo] post infusion vs screening) and in association with PFS and pLOT. Results: In total, 176 CART-4 and 97 CART-1 pts received cilta-cel as study treatment. Immunophenotyping data were available from 248 peripheral blood samples (1 pLOT, n=56; 2 pLOT, n=61; ≥3 pLOT, n=131). At apheresis, CD4+ naïve T cells (%) were higher in pts with 1 or 2 pLOT, compared with those with ≥3 pLOT, while no difference was found in pts with ≥3 pLOT with further breakdown (i.e., 3–4 vs 5–6 vs ≥7 pLOT). Further, higher baseline levels of CD4+ naïve T cells were associated with longer PFS. These data suggest that the negative impact on peripheral immune fitness with the addition of LOT may plateau when pts have received ≥3 pLOT. TME gene expression data were available from 148 BMA samples (screening, n=50; D28, n=50; 6 mo, n=48) from CART-4. Analyses of gene expression signatures suggest depletion of B cells and antibodies at D28 post cilta-cel infusion, with partial recovery at 6 mo. This was corroborated in parallel by flow cytometry and immunoglobulin quantification. Further, elevated expression of genes associated with myeloid cells, including tumor-associated macrophages (TAM, likely M1), and of genes associated with cytotoxic T cells were also observed at D28. Elevated expression of genes associated with B-cell receptors, T-cell differentiation and activation, and cytokine signaling pathways were found at both D28 and 6 mo. Pts with longer PFS (&gt;18 mo) had higher levels of M1 TAM at D28, while those with shorter PFS had higher levels of regulatory T cells and more suppressed interferon pathway genes at 6 mo, suggesting that relapse may be associated with a more suppressive immune response. In pts with fewer pLOT, more profound B-cell depletion on D28, better recovery at 6 mo, and elevated B-cell receptor signaling were inferred from gene expression data. Pts with 1 pLOT also demonstrated higher elevation of M1 TAM expression on D28 from screening as compared with pts with 3 pLOT, similar to what was observed in pts with longer PFS. Conclusions: Correlative biomarker data suggest that longer PFS is associated with better immune fitness at baseline and stronger immune responses post cilta-cel infusion, as observed in peripheral blood and within the TME of pts with RRMM in CART-1 and CART-4. The peripheral immune fitness was more pronounced in pts with 1 and 2 pLOT vs 3 pLOT and beyond, where deterioration plateaued. This suggests the impact of T-cell immune fitness on PFS may be limited beyond the third LOT. Importantly, other covariates, including factors within the immune TME and tumor burden, may play a significant role in balancing this compromised intrinsic T-cell immune fitness at apheresis, thereby contributing to PFS durability after 3 pLOT. Overall, these results support increased benefits in treating pts with MM with cilta-cel in earlier LOTs.

Abstract INTRODUCTION Glioblastoma (GBM) contains metabolically distinct cell lineages: treatment-sensitive cells (TSCs) dependent on glycolysis and treatment-resistant persister cells (TRPCs) reliant on lipid metabolism. Our integrative systems biology approach, combining spatial multi-omics and targeted analyses, uncovers lipid acquisition in TRPCs as a pivotal driver of GBM progression which is supported by a retrospective study of statin-treated patients, providing clinical evidence for the therapeutic potential of targeting lipid metabolism in GBM patients stratified based on high TRPC signatures. METHODS We applied spatial transcriptomics and proteomics combined with 3D reconstruction of the tumor microenvironment to map TRPC- and TSC-enriched regions. Immunohistochemically stained tissues were analyzed using CellProfiler and our custom SNAQ algorithm for single-cell neighborhood analysis. Lipid transfer from Tumor-Associated Myeloid Cells (TAMCs) to TRPCs was tracked via flow cytometry, holotomography, and time-lapse imaging. Genetic and pharmacological targeting of CCR2, CSF1R, and FABP3 was performed in vitro and in vivo. Finally, a retrospective analysis of 4,085 GBM patients assessed the impact of statin treatment in relation to TRPC signatures. RESULTS TRPCs exploit recruited TAMCs to acquire lipids, supporting their survival and immune evasion. These interactions are mediated by CCL2/7–CCR2 and CSF1–CSF1R signaling. Disruption of TRPC-TAM lipid homeostasis significantly remodeled the immune microenvironment, reduced tumor growth, and extended survival in preclinical models. Patients with high TRPC signatures typically had poor outcomes; however, retrospective analysis revealed that statin treatment was associated with improved survival in this subgroup. These findings position lipid trafficking as a metabolic vulnerability in GBM and highlight the therapeutic relevance of targeting TRPC–TAMC interactions. CONCLUSION Our study reveals lipid trafficking to TRPCs as a key mechanism driving GBM progression. Targeting TAMC-mediated lipid transfer disrupts immune suppression and tumor growth. Transcriptomic profiling may guide patient stratification, identifying those likely to benefit from lipid metabolism-targeted therapies such as statins.

Abstract INTRODUCTION The Consortium for Clarity in Alzheimer's disease related dementias (ADRD) Research Through Imaging (CLARiTI) is a study that aims to collect standardized imaging and plasma biomarkers on 2000 Clinical Core participants enrolled across all Alzheimer's Disease Research Centers (ADRC) sites. We sought to summarize the known heterogeneity across centers regarding scientific focus and initial enrollment plans for CLARiTI. METHODS We developed and distributed a survey capturing information on the 36 CLARiTI site's theme/expertise, recruitment plans, and the intersection of CLARiTI with other ADRC imaging efforts. RESULTS Anticipated CLARiTI enrollees spanned 11 different categories of suspected etiologies underlying impairment. A wide range of risk factors were endorsed across sites regarding the enrollment of unimpaired individuals. Variability also existed regarding site‐level strategies in enrollment into CLARiTI versus other imaging efforts. DISCUSSION We anticipate that the 2000 individuals that will enroll into CLARiTI will reflect the clinical heterogeneity already in place across the ADRC network. Highlights The ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) will leverage and contribute to the existing Alzheimer's Disease Research Centers (ADRC) program by supporting standardized imaging and plasma collection across all centers. We summarize the variation in scientific focus and enrollment plans across ADRC sites participating in CLARiTI. The anticipated CLARiTI cohort will reflect the clinical heterogeneity that already exists across the ADRC network. CLARiTI will contribute to scientific goals related to the detection of multi‐etiological signatures relevant for Alzheimer's disease and related disorders (ADRDs).

Abstract This brief report details the initial findings from a Phase 1b/2 trial of TN-201, an adeno-associated virus serotype 9 (AAV9) gene therapy for MYBPC3-associated hypertrophic cardiomyopathy (HCM), a condition with significant morbidity, increased risk of mortality, and no approved therapy for the majority of patients. TN-201 was well tolerated, and changes to the management of potential immune responses resulted in a shorter period of immunosuppression. These results show consistent transduction and expression of TN-201 in cardiomyocytes, corresponding with increases in MyBP-C levels, reductions or stabilization of cardiac biomarkers, and reductions in key measures of left ventricular (LV) hypertrophy.