Matthew Sperrin | PubMed Health

PubMed2026

Early-adulthood body mass index, mammographic density and post-menopausal breast cancer risk: a mediation analysis.

BACKGROUND: To explore potential mechanistic pathways and inform prevention strategies, this study examined whether mammographic density (MD) mediates the inverse association between higher early-adulthood body mass index (BMI) and lower post-menopausal breast cancer risk. METHODS: We analysed data from 33,816 post-menopausal women in the UK PROCAS cohort, with self-reported BMI at age 20. MD was measured using full-field digital mammography and assessed using the visual analogue scale (VAS) percentage density and Volpara®-derived fibroglandular volume (FGV). Counterfactual mediation modelling estimated natural direct and indirect effects. RESULTS: Over a median follow-up of 10.44 years, there were 1261 new post-menopausal breast cancers. Higher VAS and FGV were associated with increased breast cancer risk. BMI at age 20 was associated with lower VAS density and reduced breast cancer risk [Hazard Ratio per 5 kg/m²: 0.849 (0.771-0.938)]. The calculated proportion mediated by VAS density was 59.9% (32.6-150), after accounting for intermediate confounding by BMI in later adulthood. FGV was positively associated with higher BMI at cohort entry but not at age 20. CONCLUSIONS: Lower VAS density may partially explain the inverse association between early-adulthood BMI and post-menopausal breast cancer risk. The link between FGV and breast cancer risk may represent a different biological pathway.

Journal Article↗

PubMed2026

Evaluating Wearable Devices for Remote Monitoring in Psychosis: Pilot Study Nested Within the CONNECT Cohort Study.

BACKGROUND: Digital remote monitoring technologies, including smartphones and wearables, offer promising avenues for early detection of psychosis relapse. However, selecting devices that are acceptable to participants and produce high-quality data remains challenging. OBJECTIVE: The aim of this nested pilot study was to assess the acceptability and data quality of 3 commercially available wearable devices in people with psychosis recruited to the CONNECT cohort study. METHODS: Participants recruited to the CONNECT study before July 31, 2024, were included in the pilot study and selected 1 of 3 wearable devices: a Fitbit Charge 5, Samsung Galaxy Watch 5, or Apple Watch SE. Baseline demographics were compared between device groups. Acceptability of devices to participants was assessed through a Wearable Device Satisfaction Questionnaire after 3 months of use, with the proportion of positive responses to each question calculated and compared. Data completeness was also assessed by calculating the number (and percentage) of valid days of step count, heart rate, and sleep data, and comparing between groups. Data quality was assessed through summarizing the amount of troubleshooting required, additional metrics available from the wearables, and continuity of data completeness by calculating the proportion of participants with at least 3 days of heart rate data per week for the first 20 weeks of follow-up. Predefined criteria were used to determine the next steps for the wider CONNECT study: if one device was superior, this would be selected; if none were found to be superior and the Fitbit was found to be noninferior, then Fitbit would be retained. RESULTS: Of the first 107 participants recruited to CONNECT, 105 were included in the pilot study evaluation. The Samsung Galaxy Watch was selected most frequently by participants (46/105, 43.8%), followed by the Apple Watch (27/105, 25.7%), and Fitbit Charge (23/105, 21.9%). Differences in participant demographics were observed across device groups. Self-reported acceptability after use did not differ substantially between devices. However, in terms of data completeness, the median proportion of valid heart rate data days was significantly lower for Samsung Galaxy (median 31.2%, IQR 8.5%-46.0%) compared to Fitbit (median 80.1%, IQR 26.7%-95.0%; P=.003) and Apple Watch (median 49.3%, IQR 21.5%-86.0%; P=.02). There was no significant difference between Fitbit and Apple Watch. Similar patterns were observed for step count and sleep data. The Samsung Galaxy Watch required more frequent troubleshooting for data flow issues and lacked additional physiological metrics, available from the other devices. CONCLUSIONS: Due to comparatively lower data quality and technical performance, the Samsung Galaxy Watch was discontinued for use in the subsequent phase of the CONNECT study. The study highlights the importance of incorporating nested evaluations of devices in long-term research.

Humans↗

PubMed2025

Ophthalmic imaging as a measure of cardiovascular and neurological health: a multi-omic analysis of deep-learning derived phenotypes.

The eye is a recognised source of biomarkers for cardiovascular and neurodegenerative disease risk. Here, we characterise the breadth of these associations and identify biological axes that may mediate them. Using UK Biobank data, we developed a multi-omic analysis pipeline integrating physiological, radiomic, metabolomic, and genomic information. We trained adversarial autoencoders (Ret-AAE) to represent optical coherence tomography (OCT) images and colour fundus photographs as 256-dimensional embeddings. Ret-AAE derived embeddings were associated with a range of cardiovascular and neurodegenerative diseases, including ischaemic heart disease, cerebrovascular disease, Parkinson's disease, and dementia. Examining associations across diverse omics datasets, we provide evidence linking ophthalmic imaging features to neurological and cardiovascular anatomy and function, lipid metabolism, and gene sets associated with neurodegenerative pathology. Collectively, our findings demonstrate that ophthalmic features reflect complex, multisystem biological processes, and reinforce the role of the eye as a composite indicator of systemic health.

Journal Article↗