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Winchester, L. M.

Publications and source records attributed to Winchester, L. M..

2 recordsLinked to original sources

Mapping the circulating proteome across neurodegeneration: A harmonized, consortium-scale framework for uncovering molecular pathophysiology

Large-scale plasma proteomics offers unprecedented opportunities to investigate the systemic biology of neurodegeneration, yet technical heterogeneity, site-specific artifacts, and clinical confounding remain major barriers to reproducible discovery. Leveraging data from 13,733 individuals with Alzheimers disease (AD), Parkinsons disease (PD), frontotemporal dementia (FTD), Parkinsons disease dementia (PDD), amyotrophic lateral sclerosis (ALS), and non-impaired controls in the Global Neurodegeneration Proteomics Consortium (GNPC), we present a scalable and generalizable analytical framework for harmonizing and interpreting consortium-scale proteomic datasets. Using a high-dimensional perturbation framework, we systematically benchmark five commonly used batch correction methods across a range of realistic confounding structures, including site-disease imbalance, nonlinear effects, and heteroskedasticity. Empirical Bayes modelling via limma consistently emerged as the most robust method, optimally balancing removal of site-related technical variance with retention of disease-relevant biological signal. On this harmonized foundation, we resolve neurodegenerative disease plasma signatures, including a shared immune-metabolic axis in AD and PD, neuromuscular disruption in ALS, and proteostatic imbalance in PD. Tissue and cell-type enrichment highlight widespread immune-endocrine involvement in AD and hematopoietic activation in PD. Demographically matched analyses nominate distinct, candidate biomarkers across diseases, including lipid, redox, and complement factors in AD, lysosomal and cytoskeletal proteins in PD, and muscle-derived markers in ALS. This study establishes a scalable analytical framework for integrating real-world proteomic data and provides a disease-resolved catalogue of circulating signatures to inform biomarker development and targeted intervention across neurodegenerative diseases.

neuroscience↗

Longitudinal Proteomic Profiling Defines Robust Molecular Subtypes Underlying the Heterogeneity of Parkinson's Disease

Heterogeneity of Parkinsons disease (PD) pathology is a barrier to developing therapeutics and understanding progression and prognosis. High throughput proteomic measures can be used to better interpret PD pathophysiology and generate clusters to define disease subtypes. Identification of subtypes related to clinical phenotypes will help researchers understand PD progression. We analyzed longitudinal proteomic data from the Tracking Parkinsons Cohort, consisting of recent-onset PD patients across 72 UK sites. 794 patients were measured on the Somalogic platform (7596 proteins) for three time points. Weighted Gene Co-Expression Network Analysis (WGCNA) at each time point revealed consistent protein co-expression modules. Two modules were strongly preserved across all three time points and in validation in the Global Neurodegenerative Proteomics Consortia (GNPC) datasets. The brown module was enriched for metabolite pathways and the blue module with cellular signaling pathways and associated with quality of life scores. Conversely, the smaller red module had distinct cognitive function phenotypes and changed protein expression between visit time points. Using detailed characterization of proteomic clusters we have provided a comprehensive view of PD progression offering deeper insights into the conservation of proteomic expression, suggesting new module subsets and providing candidate target proteins for further study.

neuroscience↗