Oct 2026· Journal of Alzheimer's Disease· pp.
13872877261502870
· 0 citations
Medicine
Abstract
BackgroundHearing loss (HL) is a potentially modifiable risk factor for dementia, but the circulating molecular features shared by hearing impairment and dementia remain unclear.ObjectiveTo derive a plasma proteomic signature of hearing impairment and examine its association with incident all-cause dementia and its statistical contribution to the hearing-dementia association.MethodsWe analyzed 13,941 UK Biobank participants with plasma proteomics and speech-in-noise hearing assessments. A proteomic signature of hearing impairment was derived using elastic-net regression with 10-fold cross-validation. A proteomic signature was constructed and tested for associations with incident all-cause dementia using Cox models. Mediation, functional enrichment, and exploratory drug-signature enrichment analyses were also performed.ResultsElastic-net regression selected 64 proteins, and the composite signature correlated with hearing impairment (point-biserial r = 0.232). Compared with normal hearing, insufficient (HR = 1.338, 95% CI: 1.015-1.763) and poor hearing (HR = 2.021, 95% CI: 1.244-3.283) were associated with higher dementia risk after multivariable adjustment. The proteomic signature was associated with incident dementia (HR = 1.791, 95% CI: 1.312-2.445). Estimated proportions mediated were 22.99% (95% bootstrap CI: 4.87%-129.05%) and 14.61% (95% bootstrap CI: 2.21%-64.21%), respectively. Drug-signature enrichment yielded exploratory compound-protein signals.ConclusionsIn this prospective cohort, hearing impairment and a derived plasma proteomic signature were associated with incident all-cause dementia. These findings provide hypothesis-generating evidence for circulating molecular features shared by hearing impairment and dementia but require external validation and mechanistic investigation before causal or clinical interpretation.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· SSE@SIGSOFT FSE· 56 citations· ⚡4
This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.