The most important predictors for outcomes after ischemic stroke, that is, for health deterioration and death, are chronological age and stroke severity gender, genetics and lifestyle / environmental factors also play a role. The model constructed by KIM-1 and the other 7 biomarkers can predict kidney age in healthy people. The level of urinary KIM-1 increases with age in healthy people. The predicted model was constructed with eGFR, Cl, ALD, CYSC, KIM-1, BUN, GLU and AngII, reaching an adjusted R2 of 69.5% and a standard error of the estimated 7.84 years. KIM-1 positively correlated with age in kidney healthy people (r = 0.41, p < 0.05), whether among females (r = 0.51, p < 0.05) or males (r = 0.27, p < 0.05). All variables were selected as independent variables for the prediction of age by multiple linear regression. Statistical correlated analyses for urinary KIM-1, creatinine (uCREA), potassium (K), sodium (Na) and chlorine (Cl), plasmic renin, angiotensin-2 (AngII) and aldosterone (ALD), and serum microalbuminuria (MALB), β2-microglobulin (B2MG), cystatin C (CYSC), urea nitrogen (BUN), creatinine (CREA), and glucose (GLU) were performed to assess the correlation between age and kidney biomarkers. KIM-1 and other kidney biomarkers were measured in 176 healthy individuals ranging from 26 to 91 years old. Moreover, we constructed a model to predict kidney age.Ī cross-sectional study was conducted by Huashan Hospital, Shanghai, China, between April 2020 and December 2020. Our study analyzed the levels of KIM-1 in the healthy population of different ages to explore the correlation between KIM-1 and age. Recent studies have focused on whether kidney injury molecule-1 (KIM-1) might serve as a marker of acute kidney tubular injury. Also, the results support previous conclusions that epigenetic ageing reflects non-disease-specific cellular alterations. Our data suggest caution when assigning a unidirectional DNA methylation age change to the atherosclerotic arterial wall. At CpG level, the Horvath epigenetic clock showed modest differential methylation between atherosclerotic and healthy aortic portions, weak association with atheroma histological grade and no clear evidence for participation in atherosclerosis-related cellular pathways. For the first time, we document dynamic DNA methylation age mosaicism of the vascular wall that is atherosclerosis-related, switches from acceleration to deceleration with chronological ageing, and is consistent in human aorta and carotid atheroma. The well-characterized pan-tissue Horvath epigenetic clock was used, together with the Weidner whole-blood-specific clock as validation. We surveyed DNA methylation age in two human artery samples: a set of donor-matched, paired atherosclerotic and healthy aortic portions, and a set of carotid artery atheromas. Understanding the trends of epigenetic ageing in the atheroma may provide insights into mechanisms of atherogenesis or identify targets for molecular therapy. Accelerated epigenetic ageing, a promising marker of disease risk, has been detected in peripheral blood cells of atherosclerotic patients, but evidence in the vascular wall is lacking.