Frontiers in Endocrinology (Oct 2023)

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

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

DOI
https://doi.org/10.3389/fendo.2023.1164822
Journal volume & issue
Vol. 14

Abstract

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BackgroundDiabetic nephropathy (DN) is one of the most prevalent complications of diabetes mellitus (DM). However, there is still a lack of effective methods for non-invasive diagnosis of DN in clinical practice. We aimed to explore biomarkers from plasma cell-free DNA as a surrogate of renal biopsy for the differentiation of DN patients from patients with DM.Materials and methodsThe plasma cell-free DNA (cfDNA) was sequenced 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 the 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.ResultsIn comparison with the DM patients, the DN individuals exhibited significantly increased cfDNA concentration in plasma. The cfDNA from the DN patients showed a distinct fragmentation pattern with an altered size profile and preferred motifs that start with “CC” 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 when compared with healthy individuals. We integrated DN-specific cfDNA features (cfDNA concentration, size, and motif) into a classification model, which achieved an area under the receiver operating characteristic curve (AUC) of 0.928 for the differentiation of DN patients from DM patients.ConclusionOur findings showed plasma cfDNA as a reliable non-invasive biomarker for differentiating DN patients from DM patients. The utility of cfDNA in clinical practice in large prospective cohorts is warranted.

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