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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
Advances in medical technology and improvements in living environments have steadily increased human lifespans. However, the increase in age-related diseases has become a serious problem in an aging society and research aimed at realizing healthy longevity is being actively conducted. Furthermore, rejuvenation, a dream of humanity, is becoming a reality. If these studies make it possible to make biological age, which is based on the function of the cells and tissues that make up the body, younger than chronological age, it is expected that the risk of developing age-related diseases will decrease. However, there is currently no standard index that can easily assess biological age, which differs from chronological age.
Our laboratory stores approximately 160,000 urine samples, including those from healthy individuals collected during workplace health checkups and other events with a wide range of ages, from 20 to over 80 years old. We have also performed quantitative proteomics using these urine samples, and have been able to identify and quantify over 3,000 proteins in urine.
In this study, we will select urinary proteins that increase or decrease with chronological age by quantitative proteomics, and examine whether they can be used as indicators for estimating biological age.
To avoid the possibility that urinary proteome profiles may change due to disease, only urine samples from healthy individuals of various ages were used. Healthy individuals who had been identified as having no illnesses requiring detailed testing or treatment for at least two years during annual workplace health checkups were selected, and urine samples from the first year of their studies were used. From these individuals, urine samples from 150 men and women aged 20 to 80 years were selected.
Proteins were extracted from 1 ml of urine using methanol-chloroform precipitation, digested with trypsin, and purified. 0.2 ug of peptides were measured by a mass spectrometer. and data were analyzed with DIA-NN software for quantification.
Among the approximately 3,000 proteins obtained from urine samples, proteins showing a high correlation between their quantitative values and chronological age were selected as indicators of chronological age. Then, proteins correlated with HbA1c, a representative of advanced glycation end products (AGEs), whose accumulation increases with age and is known to promote aging, were also selected. The correlation between proteins that showed a high correlation with chronological age and HbA1c was examined to determine whether these proteins could be used as indicators of biological age.
Approximately 3,000 proteins were quantified per sample, and proteins that significantly increased or decreased in correlation with chronological age were selected. Proteins that correlated with HbA1c were also selected, and proteins that showed a high correlation with both chronological age and HbA1c were selected as indicator proteins for estimating biological age.
Proteins that serve as indicators of chronological age were selected from proteins comprehensively detected by quantitative urinary proteomics, and it was suggested that among these, proteins highly correlated with HbA1c could be used as indicators for estimating biological age.
