Zhang, Ling

Abstract Introduction Defining the epidemiology of myelodysplastic syndromes/neoplasms (MDS) and precursor conditions, such as clonal cytopenia of undetermined significance (CCUS), is challenging due to inconsistent reporting, complex diagnostics, and evolving criteria. The National MDS Natural History Study (NHS) overcomes these challenges through central pathology review, prospective follow-up, and a nationally representative cohort enrolled at the time of suspected MDS, enabling robust analysis across the myeloid disease spectrum. We analyzed clinical, genetic, and pathologic features in NHS participants by race, ethnicity, and sex to characterize disease variation across populations. Methods The NHS (NCT02775383) enrolled individuals undergoing evaluation for suspected MDS from June 2016–July 2024 at 102 US sites. Participants underwent bone marrow assessment with centralized, adjudicated histopathology review. Those meeting WHO 2016 criteria for MDS, MDS/myeloproliferative neoplasm (MPN), CCUS, idiopathic cytopenia/dysplasia of undetermined significance (ICUS/IDUS), or oligoblastic AML were followed longitudinally. Demographics, comorbidities, exposures, and clinical data were collected at baseline and every 6 months. Deep DNA sequencing was performed on baseline marrow, with pathogenic variants manually curated (53 genes). Statistical analyses assessed associations using chi-squared, Fisher's exact, Kruskal-Wallis, logistic regression, and Cox models. A p-value <0.05 was considered significant. Results Among 2,021 participants, 1,174 (58%) were diagnosed with MDS or precursor conditions. Median age was 74 years (yrs) and 66% were male. Most identified as Non-Hispanic White (NHW, 92%), with 4% Black and 4% Hispanic. The most common diagnoses were MDS (42%) and CCUS (37%). Pathogenic somatic mutations were identified in 84% (774/918) of MDS/CCUS, with TET2 (26% of 918), DNMT3A (21%), and ASXL1 (16%) most frequent. Median follow-up was 1.8yrs and consistent across race, ethnicity, and sex (p≥0.6). Black, compared to NHW, participants were younger (69 vs 74 yrs, p=0.006) and trended toward more females (47% vs 34%, p=0.09) and more MDS diagnoses (51% vs 41%, p=0.07). Black participants showed more advanced disease (e.g., lower hemoglobin, higher peripheral blood blasts, higher variant allele frequencies (VAFs) of pathogenic mutations), yet received less MDS-directed treatment (14% vs 41%, p=0.01). Black, compared to NHW, participants had more mutations in RUNX1, TP53, BCOR, and DNMT3A, but fewer in TET2 and ASXL1. Hispanic, compared to Non-Hispanic, participants had fewer known pathogenic mutations, leading to more ICUS (19% vs 5%, p=0.02). Females, compared to males, were younger at diagnosis (72 vs 75yrs, p<0.001), had more ICUS/IDUS (20% vs 10%, p<0.001), fewer pathogenic mutations, especially in splicing/chromatin modifier genes (U2AF1, SRSF2, ASXL1, ZRSR2), more DNMT3A mutations, and lower VAFs (0.27 vs 0.33, p<0.001). Median overall survival (OS) was 6.4yrs, and shorter in MDS (4.2yrs) than CCUS (not reached). Worse OS was associated with age (adjusted hazard ratio (aHR) 1.06), MDS (vs CCUS; aHR 1.89), higher-risk disease by IPSS-R/CCRS (aHR 2.15), and TP53 mutations (aHR 2.17) (all p<0.001). A trend toward improved OS in Black participants was attenuated after adjustment (aHR 0.79, p=0.6). Progression (e.g., worsening of disease, increase in transfusion dependency, death) occurred in 53% of participants. Worse progression-free survival (PFS) was associated with MDS diagnosis (aHR 2.59), higher-risk disease by IPSS-R/CCRS (aHR 2.17), and TP53 mutations (aHR 1.86) (all p<0.001). Despite more advanced disease and less MDS therapy, Black participants trended toward improved PFS (aHR 0.62, p=0.14), while age was borderline significant (aHR 1.01, p=0.05). Conclusions For the first time, we show that among individuals evaluated for suspected MDS at sites across the US, 58% had MDS or precursor conditions. Differences across demographics underscore the heterogeneity of MDS. Black participants presented with more advanced MDS, received less treatment, but trended toward improved outcomes, particularly PFS, even after adjustment, suggesting biological rather than access-to-care differences driving disparities. These findings highlight the complex interplay of sex, race, and genetics in shaping MDS outcomes and reinforce the need for diverse, large-scale studies to improve risk stratification and personalized care.

Abstract Post-translational modifications (PTM) of tau are implicated in Alzheimer disease (AD) progression and are established biomarkers in cerebrospinal fluid and plasma; however, the labor-intensive nature of conventional proteomics limits their investigation in histology-specific contexts. We describe the findings of an artificial intelligence-guided laser capture microdissection (LCM) pipeline for harvesting neurofibrillary tangles (NFTs) by maturation level into pretangles (pre-NFTs), mature tangles (iNFTs), and ghost tangles (eNFTs) using 38 cases obtained from 2 independent biobanks. We evaluated the performance characteristics of proprietary machine learning algorithms for the subclassification of these NFT categories in anti-pTau217-stained whole slide images of entorhinal cortex, hippocampus, frontal, and parietal cortex sections. Overall precision/recall/F1 scores were highest for Classifier A (0.6/0.46/0.5). The best performing algorithm was used to guide LCM capture and inform NFT enrichment. Targeted proteomics on tau signature peptides (pTau181, pTau217, and TauMTBR) was performed on approximately 1250 NFT collections. The results demonstrated that their abundance increased from pretangles to mature tangles (∼2-11-fold increase), and that this was followed by a sharp reduction in ghost tangles (∼3-116-fold decrease), with pTau217 showing the most drastic change. Pathologist-trained NFT classifiers represent an objective albeit imperfect means to enrich specific morphologic forms permitting coupled LCM-MS (mass spectrometry) to investigate AD-associated PTM.