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Preprint Aug 2026

Multimodal risk trajectories reveal heterogeneous paths to dementia

Dementia comprises biologically heterogeneous disorders, yet current risk assessment provides limited insight into how subtype-specific risk emerges and diverges before clinical diagnosis. We developed NetMoint, a multimodal framework integrating partially observed plasma proteomic, structural magnetic resonance imaging and cerebral haemodynamic phenotypes to predict individualized risks of Alzheimer's disease (AD), vascular dementia (VD) and frontotemporal dementia (FTD) across 1-, 5-, 10- and 20-year horizons. Among 104,120 UK Biobank participants free of dementia at baseline, NetMoint achieved mean area under the receiver operating characteristic curve (AUC) values of 0.937, 0.930 and 0.932 for AD, VD and FTD, respectively. The biological determinants of prediction shifted with time, from structural brain vulnerability at shorter horizons towards circulating molecular signatures at longer horizons, with distinct subtype-specific biological profiles. Multi-horizon risk profiling identified distinct temporal trajectories of dementia susceptibility. Among participants who subsequently developed AD, 0.7% followed a persistently very-high-risk trajectory, with predicted risk reaching 53.50% at 20 years, whereas 8.3% of those who developed FTD followed an increasing very-high-risk trajectory, reaching 67.17%. These high-risk trajectories were marked by distinct molecular signatures, with lower TGFB1 characterizing the AD group and higher NDRG1 the FTD group. In an independent ADNI-to-UK Biobank analysis, AD risk prediction remained informative after harmonization to 138 shared features, with an AUC of 0.741 at 20 years. Together, these findings establish a multimodal framework for trajectory-resolved dementia risk stratification, identifying small but high-risk populations within dementia subtypes and linking their divergent risk trajectories to distinct molecular signatures.

Zhiqi Lee, Hao-Wen Li, Tao Liu et al. · 0 citations
Review Open access Aug 2026

Advances in research on the association between global air pollution and atopic dermatitis

Background Escalating global air pollution poses severe threats to public health. Beyond respiratory and cardiovascular damage, air pollutants adversely affect cutaneous health. Atopic dermatitis (AD), a common chronic inflammatory skin disease, has been closely linked to environmental pollutant exposure in recent research, arousing widespread academic concern. Objective This narrative review aimed to comprehensively summarize current evidence on the correlation between air pollution and AD, and further elaborate the epidemiological features, potential pathogenic mechanisms, as well as targeted prevention and therapeutic strategies for pollution-related AD. Methods Literature was retrieved from PubMed, Web of Science and CNKI databases covering April 2021 to December 2025, with core keywords related to air pollutants, AD, pathogenesis, exposure and climate change. Following narrative review guidelines, high-quality peer-reviewed studies with an impact factor ≥ 3.0 were included, focusing on cutting-edge evidence regarding air pollutant-AD associations, climatic and geographical disparities, microbiome interactions, and novel therapies. Results Exposure to particulate matter, nitrogen dioxide, ozone and cigarette smoke significantly increases AD incidence and severity. Key mechanisms include skin barrier damage, skin microbiota dysbiosis, oxidative inflammatory stress, aryl hydrocarbon receptor pathway activation, and epigenetic gene–environment interactions. Urban residents, children, pregnant women and outdoor workers are high-risk populations. Biologics and JAK inhibitors effectively relieve AD symptoms, while antioxidants and medical ozone therapy are promising adjuvant or emerging interventions. Conclusion Air pollution is a critical modifiable risk factor for AD onset and exacerbation via multi-pathway mechanisms. Integrated prevention, skincare and clinical treatment can reduce AD burden. Current evidence is limited to observational studies, lacking definitive causal verification. Future multicenter prospective cohort studies, standardized novel therapy application and AI-assisted precise management will facilitate systematic AD prevention and control.

Bo-Yang Xue, Yicheng Zhang, Weihao Cheng et al. · 0 citations

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