MedElevator Войти в исследования
← Поиск публикаций
Science China. Life sciences · 2026

Polysocial risk score predicts chronic kidney disease incidence and prognosis: mechanistic insights from plasma metabolome, proteome and lifestyle.

СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Zhang Yanjun, Gan Xiaoqin, Ye Ziliang, Zhang Yuanyuan, Yang Sisi, Xiang Hao, Huang Yu, Zhang Yiwei, Wu Yiting, Nie Sheng, Hou Fan Fan, Qin Xianhui

Аннотация

The cumulative impact of multiple social determinants of health (SDHs) on chronic kidney disease (CKD) remains poorly understood. This prospective study examined the association of a polysocial risk score (PsRS) with CKD incidence and subsequent risks of cardiovascular disease (CVD) and mortality, and explored potential mediating pathways via multi-omics profiling and lifestyle factors. We analyzed 279,548 participants free of CKD at baseline and 19,761 patients with established CKD in the UK Biobank. The PsRS integrated 15 factors across economic, educational, healthcare, neighborhood, and social domains. Plasma metabolomic and proteomic profiles were analyzed to identify omics signatures associated with the PsRS. An unhealthy lifestyle score (uHLS) was derived based on body mass index, smoking, alcohol consumption, physical activity, sleep, and diet. Cox proportional hazards models were used to assess associations between the PsRS and outcomes. Mediation analyses were performed in subsets with available omics and lifestyle data. Over a median follow-up of 13 years, 6,628 incident CKD cases, 3,724 CVD events, and 2,486 deaths were documented. The PsRS demonstrated a positive association with incident CKD risk among CKD-free participants (per 1-point increase: HR=1.12; 95% CI: 1.11-1.14), as well as with CVD (HR=1.08; 95% CI: 1.07-1.10) and all-cause mortality (HR=1.12; 95% CI: 1.10-1.14) in CKD patients. The PsRS significantly improved the predictive performance of conventional clinical models across all outcomes, as indicated by increases in the C-index, net reclassification improvement, and integrated discrimination improvement. Multi-omics analyses revealed a PsRS-associated metabolomic signature (94 metabolites primarily involved in amino acids, fatty acids, and lipoproteins) and a proteomic signature (428 proteins primarily involved in immune/inflammatory responses, cellular signaling, and fibrosis). These omics signatures mediated substantial proportions of the PsRS-outcome associations (metabolomic: 16.64%-27.09%; proteomic: 53.09%-85.21%), as did the uHLS (8.26%-12.51%). In conclusion, the PsRS effectively predicts CKD development and prognosis, largely mediated through metabolomic and proteomic pathways.