Circulating diabetes biomarkers have been identified with proteomics measured at a single timepoint, but what is additionally provided by longitudinal repeated measurements in the same individuals, over many years, is unknown. We studied participants in the Multi-Ethnic Study of Atherosclerosis (MESA; N=5,322, mean baseline age 61.7 years) at exams 1 (2000-2002), 5 (2010-2012), and 6 (2016-2018) profiled with Olink 3K. Associations with incident diabetes, mostly of type 2, were modeled using Cox proportional hazards with exam 1 proteins (i.e., single timepoint) and time-updating Cox with proteins from all 3 exams (i.e., longitudinal repeated) adjusted for clinical risk factors. We identified 27 novel single-timepoint associations and up to a 4-fold increase in longitudinal associations (FDR<0.05) with a proportional increase in the number consistent with causality via cis-Mendelian Randomization (~5%) and a smaller overlap in MESA longitudinal versus single associations with UK Biobank single timepoint findings (42% versus 87%, respectively). Compared to small molecule metabolism pathway enrichment among the shared proteins, proteins unique to the longitudinal analyses enriched for protein and cellular processing pathways. We conclude that longitudinal repeated measurements identify a number of distinct disease biomarkers, in part by revealing the progression of relevant biological processes within an individual closer to clinical diabetes diagnosis versus single measurements.
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 sequence constraints.
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.