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

Front Endocrinol (Lausanne). 2023 Oct 5:14:1164822. doi: 10.3389/fendo.2023.1164822. eCollection 2023.

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 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 methods: The 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.

Results: In 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.

Conclusion: Our 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.

Keywords: biomarkers; cfDNA; endocrine disease; kidney disease; liquid biopsy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell-Free Nucleic Acids*
  • Diabetes Mellitus, Type 2* / complications
  • Diabetes Mellitus, Type 2* / genetics
  • Diabetes Mellitus, Type 2* / pathology
  • Diabetic Nephropathies* / etiology
  • Diabetic Nephropathies* / genetics
  • Humans
  • Kidney / pathology
  • Prospective Studies

Substances

  • Cell-Free Nucleic Acids

Grants and funding

This work was supported by the Guangdong-Hong Kong-Macao-Joint Labs Program from Guangdong Science and Technology (2019B121205005 to XY and XJ), National Natural Science Foundation of China grant (81920108008), GDPH Supporting Fund for Talent Program (KJ012020139), National Natural Science Foundation of China (Nos. 32171441, 81920108008 and 32000398), and Natural Science Foundation of Guangdong Province, China (2017A030306026).