Citations

Abstract Our understanding of Alzheimer's disease (AD) and related dementias (ADRD) has grown exponentially, thanks to significant investments by the National Institute on Aging (NIA). This article celebrates the 40th anniversary of the NIA's Alzheimer's Disease Research Centers, highlighting the pivotal role of neuropathology as the bedrock for neurodegeneration research. Neuropathology has championed the key principles of proteinopathy, selective vulnerability, and stereotypic spread. Furthermore, neuropathologic studies advanced our understanding of ADRD prevalence, heterogeneity, clinical–pathological correlations, and genetic underpinnings, spurring biomarker development for target engagement and disease monitoring. Disease‐modifying therapies for AD were inspired and informed by neuropathology. The neuropathology community is poised to refine diagnostics, leveraging digital pathology and integrating genetics and pathomics to enhance subtyping for novel precision medicine approaches. Despite some common misconceptions and logistical challenges, neuropathology continues to be a critical component of the ADRD research infrastructure, serving as a key bridge between allied basic and clinical sciences. Highlights We celebrate 40 years of NIA‐funded ADRCs and their contributions through neuropathology studies that have significantly advanced our understanding and treatment of ADRD. Neuropathology uncovers principles of neurodegenerative disease: proteinopathy, selective vulnerability, and stereotypic spread, informing diagnostics and therapies. Development of AD biomarkers with reference to neuropathology enhances accuracy in diagnosis and monitoring, paving the way for targeted disease‐modifying therapies. Integration of digital pathology, genetics, and novel tools in neurodegeneration research promises advanced precision medicine approaches and refined diagnostics. Misconceptions and logistical challenges to neuropathological research are addressed to improve understanding and collaboration.

Abstract eSource – particularly EHR-to-EDC – is an emerging paradigm in clinical research that enables automated transfer of electronic health record (EHR) data into electronic data capture (EDC) systems, with the potential to reduce site burden, improve data quality and accelerate oncology clinical trial workflows. However, widespread implementation remains limited due to technical, regulatory and operational barriers. To address these challenges, the European Institute for Innovation through Health Data (i~HD) launched the eSource Scale-Up Task Force in 2024. This multi-stakeholder initiative brings together leading oncology centres and pharmaceutical sponsors to establish a consensus-driven roadmap for eSource adoption. Central to this effort are three foundational resources: readiness criteria for early adopters, a performance indicator framework for monitoring success and an operational playbook to guide implementation. This article provides a structured overview of the Task Force’s objectives, collaborative model and outputs, with specific attention to its focus on interoperability, regulatory alignment and real-world validation. While initially developed for oncology, the Task Force’s framework is applicable across therapeutic areas characterized by data-intensive workflows.

Purpose: This study assesses intersurgeon variability in proptosis reduction after orbital decompression for thyroid eye disease. Methods: This multicenter retrospective study included patients with thyroid eye disease who underwent orbital decompression from 1 of 7 surgeons at 7 different institutions between January 2002 and December 2018. Data were included if a single decompression technique was performed on ≥10 patients by ≥2 surgeons. The primary outcome was postoperative change in proptosis with emphasis on comparison among surgeons utilizing similar surgical techniques. Statistical analysis was performed with χ 2 and ANOVA testing, and a multivariable logistic regression model was generated. Results: Six hundred thirty-three orbits that underwent orbital decompression were included. Five different decompression techniques were analyzed: medial wall (n = 29), fat + lateral wall (n = 113), medial wall + floor (n = 123), fat + lateral wall + medial wall (n = 140), and fat + lateral wall + medial wall + floor (n = 228), without significant difference in proptosis reduction among surgeons. Surgeons did not demonstrate significant differences in outcomes at different time points compared with each other or themselves. Outcomes when comparing endoscopic versus open medial wall decompression varied among surgery types. Multivariate modeling revealed a statistically significant association between postoperative change in proptosis with preoperative proptosis ( p < 0.001). Conclusions: Postoperative change in proptosis did not differ significantly between surgeons utilizing similar orbital decompression techniques for patients with thyroid eye disease. This study may strengthen the statistical validity of multicenter clinical trials assessing orbital decompression outcomes performed by surgeons employing uniform surgical techniques, thereby advancing our understanding of optimal surgical management strategies for thyroid eye disease.

Importance Inherited pathogenic variants (PVs) in known predisposition genes can greatly increase breast cancer risk, but the combined impact of PV status, family history, and other factors on breast cancer risk in the general US population has not been well described. Objective To evaluate population-based breast cancer risk estimates for those with established PVs overall and stratified by first-degree family history of breast cancer and other factors. Design, Setting, and Participants This study used pooled data from 13 US-based breast cancer case-control studies participating in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Enrollment for individual studies occurred between 1976 and 2013, and results are based on data released March 2023, with analyses conducted from June 2022 to July 2025. Exposures PVs, breast cancer family history, self-reported race and ethnicity, and established risk factors. Main Outcomes and Measures Breast cancer rate ratios for PVs in 7 genes were estimated from the CARRIERS consortium. PV status and incidence and mortality statistics were combined using the Individualized Coherent Absolute Risk Estimation (iCARE) model to estimate conditional cumulative breast cancer risks and 95% CIs, stratified by family history and standardized to the US population. Models that incorporated population-based data and published estimates for established epidemiologic risk factors were also evaluated. Results A total of 67 692 women were studied, including 33 841 who were diagnosed with breast cancer. PVs in ATM , BRCA1 , BRCA2 , CHEK2 , and PALB2 were strongly associated with breast cancer risk, with BRCA1 and PALB2 PVs showing evidence of heterogeneity by family history. In models considering PVs, family history, and established risk factors, the estimated cumulative risks of breast cancer by age 50 years ranged from 2.4% (95% CI, 2.4-2.4) in women with no PVs and no family history to 35.5% (95% CI, 21.6-55.1) in PALB2 PV carriers with a family history. Among women who have not been diagnosed with breast cancer by age 50 years, the cumulative risk of breast cancer by age 80 years ranged from 11.1% (95% CI, 11.0-11.2) in noncarriers with no family history to 70.5% (95% CI, 52.8-83.5) for PALB2 carriers with a family history. PV-specific cumulative risk estimates varied across subgroups defined by race and ethnicity and potentially modifiable epidemiologic risk factors. Conclusions and Relevance In this study, population-based estimates of cumulative breast cancer risk for established PVs, as informed by the CARRIERS case-control sample, varied by family history and potentially modifiable risk factors. These estimates provide guidance for identifying individuals who will most benefit from enhanced screening and prevention strategies.

Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

Abstract INTRODUCTION Few African American (AA) donors have been included in post mortem Alzheimer's disease (AD) studies compared to European‐ancestry (EA) individuals. METHODS We generated transcriptome‐wide bulk pre‐frontal cortex (PFC) gene expression data from 125 AA donors with neuropathologically determined AD and 82 AA controls. RESULTS Transcriptome‐wide significant differential expression was observed with 482 genes. The most significant, ADAMTS2 , showed 1.52 times higher expression in AD cases ( p = 2.96x10 −8 ). Comparison of findings with those from a recent gene expression study of EA brain donors revealed substantial concordance, including ADAMTS2 . Other associations not observed in EA results may be especially relevant to AD risk in the AA population. Examination of AA AD GWAS‐implicated variants identified several expression quantitative trait loci. CONCLUSION This first large‐scale AA brain AD gene expression study identified many differentially expressed genes, including ADAMTS2 , and supports gene expression as a molecular pathway underlying the impact of several AA AD risk variants. Highlights We performed the largest African American brain tissue Alzheimer's disease (AD) gene expression study. Expression differences for 482 genes, notably ADAMTS2 , were study‐wide significant. Many significant differentially expressed genes are involved in energy metabolism. Several previously known AD‐associated variants in African Americans are eQTLs. These results advance knowledge of the genetic basis of AD in the AA population.