Citations

Abstract Alzheimer’s disease (AD) emerges from multi-scale interactions between molecular pathology and disruptions in large-scale brain network dynamics. Understanding how these processes co-evolve and relate to disease stages is essential for advancing complex systems models of aging and AD, and for developing system-informed interventions. However, progress has been limited by a lack of large-scale longitudinal data. To address this, we examined the longitudinal relationship between subsystems of the default mode network (DMN) (posterior DMN, ventral DMN, anterior dorsal DMN) using task-free functional MRI (fMRI) and amyloid positron emission tomography (PET) imaging in a large longitudinal cohort spanning the clinico-biological spectrum of AD (n = 1,451; 2,763 time points) using mixed-effect models. We also assessed whether patterns of DMN connectivity predicted conversion to amyloid positivity, mild cognitive impairment (MCI), and dementia using Cox proportional hazards models. Our findings reveal a dynamic interplay between amyloid accumulation and connectivity within and between DMN subsystems, with both hyper- and hypoconnectivity emerging across DMN subsystems in association with increasing amyloid burden. Importantly, survival models showed that DMN connectivity patterns predicted conversion to critical stages of the disease, including not only conversion to MCI and dementia, but also conversion to amyloid positivity in otherwise clinically unimpaired individuals who were amyloid negative at baseline. These associations were independent of age, APOE4 status, sex, education, and in-scanner motion. These results support a model in which breakdowns in tightly regulated feedback loops governing DMN physiology represent a core systems-level pathophysiology of AD. Notably, this functional dyshomeostasis precedes detectable amyloidosis on imaging. Future studies should focus on the development of robust biomarkers of brain function that can be applied at the individual level, which could in turn help support the development of therapeutic approaches targeting system-level pathophysiology.

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.

Abstract Alzheimer's disease (AD) is neuropathologically defined by amyloid‐beta (Aβ) plaques and tau neurofibrillary tangles. However, co‐pathologies and other pathobiological processes are involved in the pathogenesis of AD, contributing to neurodegeneration and clinical symptoms. The most common co‐pathologies in people with AD are alpha‐synucleinopathy, vascular brain injury and transactive response DNA‐binding protein of 43 kDa‐related pathology. Neuroinflammation, iron accumulation, cholinergic dysfunction and cellular senescence are recognized pathobiological processes beyond Aβ‐ and tau‐related pathology. However, the exact mechanisms by which these co‐pathologies and pathobiological processes contribute to the neurodegeneration and clinical symptoms in people with AD remain unclear. The individual combination of these co‐pathologies and pathobiological processes increases phenotypical heterogeneity in people with AD. This highlights the unmet need to advance their current understanding, and the field strives to develop accurate biomarkers for personalized assessment and investigation. Elucidating this biologic‐clinical complexity and heterogeneity is crucial for increasing our current understanding of AD, with implications for diagnosis, prognosis and therapeutics.

Abstract In this systematic review, we aimed to assess the sensitivity of serum immunofixation (SIFE), urine immunofixation (UIFE), and serum free light chain (sFLC) in detecting plasma cell dyscrasia associated with light chain (AL) amyloidosis. We searched the literature using PubMed, Embase, and CENTRAL databases since inception through March 2024. We included studies reporting the diagnostic accuracy of immunofixation and/or sFLC in patients with AL amyloidosis. We used the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach to assess the certainty of the evidence and QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2) to assess the risk of bias. After deduplication, 29 237 records were screened, and 44 studies (n = 18 071) were included. For the meta-analysis, 28 studies reported sensitivity for SIFE (n = 3390), 24 studies for UIFE (n = 2830), 19 studies for SIFE and UIFE (n = 2819), 21 studies for sFLC ratio (n = 3678), 6 studies for SIFE and sFLC ratio (n = 372), 3 studies for UIFE and sFLC ratio (n = 242), and 10 studies for all 3 tests (n = 1430). Pooled sensitivities were as follows: SIFE, 0.68 (95% confidence interval [CI], 0.62-0.73); UIFE, 0.77 (95% CI, 0.72-0.81); SIFE and UIFE, 0.89 (95% CI, 0.84-0.93); and sFLC ratio, 0.82 (95% CI, 0.78-0.86). When SIFE, UIFE, and sFLC ratio were combined, the sensitivity reached 0.99 (95% CI, 0.96-1.00). The high sensitivity of combining SIFE, UIFE, and sFLC ratio supports their use as a reliable initial testing strategy to raise suspicion for AL amyloidosis and guide decisions regarding future diagnostic modalities.

Abstract Lung fibroblasts are key regulators of tissue homeostasis and extracellular matrix (ECM) remodeling, and their aberrant activation drives the progressive parenchymal scarring characteristic of idiopathic pulmonary fibrosis (IPF), a fatal disease with limited therapeutic options. Despite their central pathogenic role, lung fibroblasts are difficult to isolate due to their embedded position within the ECM, and standard in vitro culture conditions may lead to the loss of their native functional and transcriptional characteristics, hampering the study of fibroblast behavior in disease. The transcriptional heterogeneity of lung fibroblast subtypes and the extent to which culture-induced alterations diverge from native tissue signatures remain poorly understood. Here, we integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics of lung tissue from IPF patients and age-matched healthy donors with transcriptomic profiling of cultured fibroblasts collected at passages 1 and 6 after isolation using three optimized protocols: whole lung cell suspension (WLCS), negative fraction enrichment, and outgrowth. Tissue-based analysis identified six transcriptionally distinct mesenchymal subtypes: alveolar, adventitial, inflammatory, peribronchial, CTHRC1+ and smooth muscle cell (SMC). The fibroblast subtype CTHRC1+ represented the most transcriptionally activated pro-fibrotic subtype, showing the greatest upregulation of ECM biosynthesis genes, a prominent role in intercellular communication, and preferential enrichment within fibroblastic foci in IPF lung tissue. Pseudotime trajectory analysis supported a directional transcriptional continuum from alveolar and inflammatory fibroblasts toward the CTHRC1+ state, driven by coordinated activation of pro-fibrotic transcription factors, including RUNX2, CREB3L1, and SCX. In vitro culture progressively reshaped fibroblast transcriptional identity relative to native tissue, with increased collagen and matrix metalloproteinase (MMP) expression during passaging, loss of distinct CTHRC1+ fibroblasts, and gain of alveolar fibroblasts displaying pro-fibrotic activation across all isolation protocols. These findings provide a high-resolution transcriptional map of lung fibroblast heterogeneity in IPF and highlight critical limitations of standard in vitro culture systems for recapitulating native fibroblast diversity, with important implications for the development and evaluation of fibroblast-targeted therapeutic strategies in IPF.

Objective Immunohistochemically (IHC) measured transactive response DNA‐binding protein 43 (TDP‐43) inclusions are observed in Alzheimer's disease (AD) and are associated with medial temporal lobe atrophy. Accumulation of cryptic exons occurs in AD in response to TDP‐43 pathology. We aimed to assess relationships between IHC and biochemically measured insoluble TDP‐43 and cryptic exons and assess associations with hippocampal and amygdala volume loss and atrophy rates on magnetic resonance imaging (MRI). Methods Eighty‐one neuropathologically diagnosed AD cases were analyzed. For biochemistry, insoluble TDP‐43 was quantified using a Meso‐scale discovery (MSD) immunoassay. IHC‐TDP burden was quantified with digital histopathology. Cryptic RNAs were assessed via quantitative real‐time polymerase chain reaction (qRT‐PCR). Thirty‐eight cases had serial brain MRI. Hippocampal and amygdala volumes were calculated using FreeSurfer. Regression models were used to investigate associations among IHC‐TDP‐43 status/burden, MSD‐TDP status/levels, cryptic RNAs, and hippocampal and amygdala volumes and atrophy rates. Results IHC‐TDP(+) cases exhibited elevated levels of MSD‐TDP and cryptic RNAs ( KCNQ2 , STMN2 , and UNC13A ) and increased MSD‐TDP levels were associated with increased cryptic RNA levels, in the hippocampus and amygdala. IHC‐TDP(+) cases had smaller hippocampal and amygdala volumes compared to IHC‐TDP(−) cases. MSD‐TDP(+) cases had smaller hippocampal volumes and faster amygdala rates of atrophy compared with MSD‐TDP(−) cases. Higher KCNQ2 and UNC13A levels were associated with smaller amygdala volumes. Interpretation MSD‐TDP level is a reliable surrogate for IHC‐based TDP‐43 status. Both TDP‐43 and cryptic RNA levels are associated with reduced medial temporal volumes, suggesting cryptic exons may be playing a role in brain volume loss in AD. ANN NEUROL 2026;100:193–205

Abstract Pulmonary fibrosis (PF) involves excessive collagen accumulation, yet mechanisms shifting the balance of synthesis and degradation toward net deposition remain unclear. Myeloperoxidase (MPO) inversely correlates with survival in PF. Using the bleomycin model, we found MPO knockout (MPOko) mice were protected from fibrosis, and pharmacological MPO inhibition after peak inflammation (day 7) recapitulated this protection. MPO persisted in lung tissue 21 days post-injury despite neutrophil efflux, linking acute inflammation to sustained remodeling. Mechanistically, we identified that MPO inhibits Cathepsin K (CatK), a potent collagenolytic enzyme involved in fibrosis resolution. Notably, CatK gene expression ( CTSK ) is elevated in PF, suggesting post-translational inhibition of CatK. MPOko and inhibitor-treated mice exhibited elevated CatK activity after bleomycin; exogenous addition of pathophysiologic concentrations of MPO reduced CatK activity in mouse precision-cut lung slices and human fibroblasts. Biochemically, MPO reduced CatK activity to 33% of control. In two distinct cohorts of PF patients, we observed significantly increased MPO protein levels in platelet poor plasma and in lung tissue. In PF patients, 62% had MPO levels in platelet poor plasma exceeding healthy controls, while lung tissue from other PF patients showed significantly elevated MPO staining. Plasma levels were inversely correlated with decreased survival, FVC, and DLCO. These findings establish MPO as a post-translational inhibitor of CatK-mediated collagenolysis, revealing a mechanism linking acute inflammation to sustained fibrosis and suggest a patient subpopulation that may benefit from MPO-targeted therapy. Graphical Abstract Myeloperoxidase persists in lung tissue after injury and inhibits cathepsin K activity, impairing collagen degradation and promoting extracellular matrix accumulation during pulmonary fibrosis.

Abstract Different MRI image contrasts are designed to highlight various tissue properties and combining them allows extension of probabilistic segmentation beyond the commonly used “gray-white-CSF” models. This work describes a fully automated method that combines T1-weighted, T2-FLAIR, and conventional T2-weighted images to provide internal consistency across prediction of tissue segmentations including segmentation of superficial and deep gray matter, white matter hyperintensities, and MR-visible perivascular spaces. Results from 773 imaging datasets from 403 participants in the Mayo Clinic Study of Aging and Mayo Clinic Alzheimer’s Disease Research Center (ADRC) are presented.