Citations

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.

Through a Delphi process, all 33 panelists reached consensus on topics relating to MRI reporting of knee meniscus lesions, demonstrating that interdisciplinary and multi-institutional standardization is possible.

Abstract Background Inflammatory bowel disease (IBD) can lead to a hypercoagulable state, particularly at initial diagnosis. Consequently, venous thromboembolism (VTE) represents a serious complication associated with IBD. For children, the risk of VTE near the time of IBD diagnosis has not yet been quantified, and guidance for VTE prophylaxis remains unclear. Methods This multisite matched case-control study examined pediatric patients with a new diagnosis of IBD from 2019-2024. Cases were those who developed VTE ≤30 days prior or ≤90 days post IBD diagnosis. Controls were newly diagnosed IBD patients without VTE. Each case was matched to 2-6 controls based on IBD subtype and age at IBD diagnosis. Demographics, laboratory values, prothrombotic risk factors and treatments were compared between matched cases and controls using conditional logistic regression stratified, by case sets. Results Study subjects included 15 cases and 52 controls, resulting in 70 matched pairs. Factors associated with early VTE included lower hemoglobin (P = .003), lower albumin (P = .002), corticosteroids use (P = .01), central line (P = .002), and any surgery ≤90 days post IBD diagnosis (P = .001). No association with VTE was detected for platelets, C-reactive protein, fecal calprotectin, family history of IBD or body mass index. Conclusions Albumin, hemoglobin, steroid use, central line, and any surgery ≤90 days post IBD diagnosis were associated with early VTE. These risk factors may be used in a future prediction model to stratify newly diagnosed pediatric IBD patients by their risk for early VTE development.

Abstract Myelodysplastic syndromes (MDS) are clinically and biologically diverse disorders, emphasizing the need for personalized treatment approaches. The International Working Group for Prognostication of MDS (IWG_PM) recently introduced a molecular classification, referred to as the MDS taxonomy, that categorizes patients into 16 subgroups based on 21 gene mutations, 6 cytogenetic abnormalities, and loss of heterozygosity (LOH) at TP53 and TET2 loci. This study sought to validate and enhance the clinical relevance of the MDS taxonomy by analyzing a large retrospective cohort ( n = 5136) and transcriptomic data from a prospective cohort ( n = 477). The taxonomy successfully identified subgroups with distinct clinical characteristics and disease progression patterns. However, incorporating gene interactions from taxonomy subgroups did not improve the prognostic performance of the Molecular International Prognostic Scoring System (IPSS‐M). We further assessed whether the taxonomy could guide management in patients receiving disease‐modifying therapies. Except for the “ TP53 ‐complex” subgroup, taxonomy classifications were not predictive of hypomethylating agent response or transplant outcomes. Nonetheless, they correlated with overall survival, suggesting that while both IPSS‐M and the taxonomy capture disease biology, other non‐genetic factors may influence treatment response. RNA sequencing confirmed the biological distinctiveness of the taxonomy groups. Transcriptomic profiling of CD34+ bone marrow cells revealed unique, homogeneous gene expression patterns, particularly within the AML‐like, bi TET2 , SF3B1 , and TP53 ‐complex subgroups. Further integration of multi‐omics data may refine MDS classification, improving clinical decision‐making and guiding the development of targeted therapies.

Abstract Background/Purpose Diagnosing wrist ligament injuries is challenging; early detection and treatment are important to prevent osteoarthritis progression. Interosseous proximity maps, a proxy measure for joint space, can be generated from volumetric imaging data and may provide important information about wrist health. Artificial intelligence (AI) could enhance accuracy of noninvasive diagnosis based on imaging-derived metrics. This work demonstrates feasibility of AI training using synthetic proximity map data generated from finite element models (FEMs). Methods Personalized wrist FEMs for two asymptomatic participants were created from four-dimensional computed tomography-derived anatomic and kinematic data. Monte Carlo sampling varied 22 ligament material properties and simulated 7,500 unique injury scenarios generating 9,000,000 labeled red, green, and blue (RGB) images of interosseous proximity vector fields from FEM-derived motions. Images were associated with 17 descriptive metrics, including gross wrist angles and bone surface pairs, and used to develop mixed-input convolutional neural networks (CNNs). Model performance was evaluated for identifying specific ligament injuries. Results Average area under receiver operating characteristic curve (AUROC) for CNNs was 0.757 across all injury types and kinematics. In a subset with clinically-relevant functional angles, the average AUROC was 0.824. Best-performing individual ligament AUROCs ranged from 0.807 to 0.999. Sensitivities and specificities exceeded 0.99 for some ligament injury simulations under specific wrist angles and bone surface pairs. Conclusion This study demonstrates the feasibility of using synthetic data from FEMs to train AI models for classifying wrist ligament injuries. Proximity-based RGB images may be a relevant biomarker of ligamentous injury.

Abstract The Tau Global Conference 2025, hosted by the Alzheimer's Association, CurePSP, and the Rainwater Charitable Foundation, convened international experts from academia, industry, government, and philanthropy to explore advances and challenges in tauopathy research. The meeting highlighted progress across tau biology, including emerging models of tau regulation, degradation, and propagation; advances in biomarker development for the diagnosis and staging of tauopathies; and evolving therapeutic strategies targeting diverse aspects of tau pathophysiology. Discussions also emphasized the importance of cross‐sector collaboration, and global initiatives to address disparities in tau research. This report synthesizes key insights from the conference and underscores the critical role of interdisciplinary, biomarker‐driven, and globally inclusive approaches in accelerating the translation of tau research into effective clinical applications.

Abstract Multiple myeloma (MM) is a heterogenous cancer that remains mostly incurable. A unifying feature of MM cells is a highly interconnected network of transcription factors and co-factors that coordinate the activity of super-enhancers to enforce myeloma cell identity. Targeting this network offers a promising avenue for therapeutic intervention across genetically diverse myeloma sub-types. Using integrated molecular and functional genomic approaches we identified Menin as a key driver of oncogenic gene expression in MM cells. Menin and its co-factor KMT2A bind at super-enhancers and maintain expression of essential myeloma genes, including IRF4. We demonstrate that Menin inhibitors, which have recently been approved for treatment of acute myeloid leukaemia, are highly active in myeloma cell lines and in vivo models. Combining Menin inhibitors with other super-enhancer targeting therapies such EP300/CREBBP inhibitors or immunomodulatory drugs (IMiDs) overcomes epigenetic plasticity in cells resistant to single agent treatment.

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.

Gephyrin is a postsynaptic scaffold protein essential for inhibitory neurotransmission. Gephyrin‐immunoglobulin G (IgG) was reported, decades ago, in a single case of paraneoplastic stiff‐person‐like syndrome, but its broader clinical relevance remains unknown. While investigating unclassified synaptic IgGs mimicking amphiphysin‐IgG, we identified gephyrin‐IgG in 3 patients using human protein microarray. Gephyrin specificity was confirmed using confocal tissue‐based immunofluorescence assay, cell‐based assay, and Western blot. The 3 patients, all female, had: encephalitis (2) and myeloneuropathy and breast cancer (1). All had inflammatory cerebrospinal fluid and abnormal magnetic resonance imaging, and improved following immunotherapy. Gephyrin‐IgG is associated with a treatable autoimmune neurological disease, sometimes paraneoplastic. ANN NEUROL 2026