AUTHOR=Yu Chaolun , Lin Yu , Luo Yuxue , Guo Yun , Ye Zhiming , Ou Rijing , Zhang Yan , Wang Xinxin , Qu Ruokai , Zhou Wenwen , Li Jie , Bai Yong , Yu Xueqing , Zhang Haiqiang , Yan Li , Jin Xin 

TITLE=The fragmentomic property of plasma cell-free DNA enables the non-invasive detection of diabetic nephropathy in patients with diabetes mellitus

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1164822

DOI=10.3389/fendo.2023.1164822

ISSN=1664-2392

ABSTRACT=Background: Diabetic nephropathy (DN) is one of the most prevalent complications of diabetes mellitus (DM). However, there is still a lack of effective methods for noninvasive diagnosis of DN in clinical practice. We aimed to explore biomarkers from plasma cell-free DNA as a surrogate of renal biopsy for the identification of DN from patients with DM.: We sequenced the plasma cell-free DNA (cfDNA) from 53 healthy individuals, 53 patients with DM but without DN, and 71 patients with both DM and DN. Multidimensional features of plasma DNA were analyzed to dissect the cfDNA profile in DM and DN patients and identify DN-specific cfDNA features. Finally, a classification model was constructed by integrating all informative cfDNA features to demonstrate the clinical utility in DN detection. Results: In comparison with DM patients, DN individuals exhibited significantly increased cfDNA concentration in plasma. The cfDNA from DN patients showed a distinct fragmentation pattern with altered size profile and preferred "CC" started motifs in the cfDNA ending sites, which were associated with deoxyribonuclease 1 Like 3 (DNASE1L3) expression in the kidney. Moreover, patients with DM or DN were found to carry more alterations in whole-genome cfDNA coverage compared with healthy individuals. We integrated DN-specific cfDNA features (cfDNA concentration, size and motif) into a classification model, which achieved an AUC of 0.928 for identification of DN patients from DM patients. Conclusions: Our findings showed plasma cfDNA as a reliable non-invasive biomarker for identifying DN from DM patients. The utility of cfDNA in clinical practice in large prospective cohorts are warranted.