{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T19:28:42Z","timestamp":1784230122252,"version":"3.55.0"},"reference-count":45,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T00:00:00Z","timestamp":1781568000000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Social isolation (SI) is associated with a higher risk of cardiovascular disease (CVD). One mechanism linking SI and CVD is accelerated biological ageing, which can be assessed using artificial intelligence-enabled electrocardiography (AI-ECG). We investigated whether longitudinal changes in SI status are associated with changes in biological ageing patterns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>A retrospective longitudinal cohort study including 17 663 individuals without significant CVD who completed \u22652 Berkman and Syme Social Network Index and had paired ECGs within 1 year of each questionnaire. Longitudinal SI status was defined by comparing baseline and follow-up SI status. Ageing trends were assessed using \u0394age-gap, defined as the change in the gap between AI-ECG-predicted age and chronological age from baseline to follow-up. Linear regression models predicting \u0394age-gap and survival analyses with Kaplan\u2013Meier and multivariable Cox regression for all-cause mortality were performed. Persistently connected individuals were older [63.1 (52.1, 70.6) years] and had a higher prevalence of hyperlipidaemia and hypertension, yet demonstrated more favourable ageing trajectories. Similarly, those who became connected showed a non-significant attenuation of accelerated ageing. In multivariable linear regression, being persistently isolated [\u03b2 = +0.412 years, P &amp;lt; 0.001] or becoming isolated [\u03b2 = +0.438 years, P = 0.012] was associated with accelerated ageing compared to being persistently connected. In survival analyses, becoming isolated (aHR = 1.94, 95% CI = 1.53\u20132.46, P &amp;lt; 0.001) and being persistently isolated (aHR = 1.66, 95% CI = 1.40\u20131.96, P &amp;lt; 0.001) were associated with significantly higher all-cause mortality, independent of chronological age and comorbidities.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Persistent social connection is associated with slower biological ageing and lower mortality. The effects of SI on ageing and survival appear to be potentially reversible, calling for a prospective study to evaluate interventions aimed at improving both the social and biological burden of SI.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/eurjpc\/zwag212","type":"journal-article","created":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T11:52:49Z","timestamp":1781092369000},"source":"Crossref","is-referenced-by-count":1,"title":["Persistent social connection over time is associated with attenuated biological ageing assessed by AI-enabled electrocardiography"],"prefix":"10.1093","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-9080-2183","authenticated-orcid":false,"given":"Matteo","family":"Manzato","sequence":"first","affiliation":[{"name":"Department of Cardiovascular Medicine, Mayo Clinic , 200 First St SW, Rochester, MN 55905 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