Go to JCI Insight
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Advertising
  • Job board
  • Contact
  • Clinical Research and Public Health
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Gastroenterology
    • Immunology
    • Metabolism
    • Nephrology
    • Neuroscience
    • Oncology
    • Pulmonology
    • Vascular biology
    • All ...
  • Videos
    • Conversations with Giants in Medicine
    • Video Abstracts
  • Reviews
    • View all reviews ...
    • Complement Biology and Therapeutics (May 2025)
    • Evolving insights into MASLD and MASH pathogenesis and treatment (Apr 2025)
    • Microbiome in Health and Disease (Feb 2025)
    • Substance Use Disorders (Oct 2024)
    • Clonal Hematopoiesis (Oct 2024)
    • Sex Differences in Medicine (Sep 2024)
    • Vascular Malformations (Apr 2024)
    • View all review series ...
  • Viewpoint
  • Collections
    • In-Press Preview
    • Clinical Research and Public Health
    • Research Letters
    • Letters to the Editor
    • Editorials
    • Commentaries
    • Editor's notes
    • Reviews
    • Viewpoints
    • 100th anniversary
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • Reviews
  • Review series
  • Conversations with Giants in Medicine
  • Video Abstracts
  • In-Press Preview
  • Clinical Research and Public Health
  • Research Letters
  • Letters to the Editor
  • Editorials
  • Commentaries
  • Editor's notes
  • Reviews
  • Viewpoints
  • 100th anniversary
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Advertising
  • Job board
  • Contact
Reduced methylation correlates with diabetic nephropathy risk in type 1 diabetes
Ishant Khurana, … , Per-Henrik Groop, Assam El-Osta
Ishant Khurana, … , Per-Henrik Groop, Assam El-Osta
Published January 12, 2023
Citation Information: J Clin Invest. 2023;133(4):e160959. https://doi.org/10.1172/JCI160959.
View: Text | PDF
Research Article Metabolism Nephrology

Reduced methylation correlates with diabetic nephropathy risk in type 1 diabetes

  • Text
  • PDF
Abstract

Diabetic nephropathy (DN) is a polygenic disorder with few risk variants showing robust replication in large-scale genome-wide association studies. To understand the role of DNA methylation, it is important to have the prevailing genomic view to distinguish key sequence elements that influence gene expression. This is particularly challenging for DN because genome-wide methylation patterns are poorly defined. While methylation is known to alter gene expression, the importance of this causal relationship is obscured by array-based technologies since coverage outside promoter regions is low. To overcome these challenges, we performed methylation sequencing using leukocytes derived from participants of the Finnish Diabetic Nephropathy (FinnDiane) type 1 diabetes (T1D) study (n = 39) that was subsequently replicated in a larger validation cohort (n = 296). Gene body–related regions made up more than 60% of the methylation differences and emphasized the importance of methylation sequencing. We observed differentially methylated genes associated with DN in 3 independent T1D registries originating from Denmark (n = 445), Hong Kong (n = 107), and Thailand (n = 130). Reduced DNA methylation at CTCF and Pol2B sites was tightly connected with DN pathways that include insulin signaling, lipid metabolism, and fibrosis. To define the pathophysiological significance of these population findings, methylation indices were assessed in human renal cells such as podocytes and proximal convoluted tubule cells. The expression of core genes was associated with reduced methylation, elevated CTCF and Pol2B binding, and the activation of insulin-signaling phosphoproteins in hyperglycemic cells. These experimental observations also closely parallel methylation-mediated regulation in human macrophages and vascular endothelial cells.

Authors

Ishant Khurana, Harikrishnan Kaipananickal, Scott Maxwell, Sørine Birkelund, Anna Syreeni, Carol Forsblom, Jun Okabe, Mark Ziemann, Antony Kaspi, Haloom Rafehi, Anne Jørgensen, Keith Al-Hasani, Merlin C. Thomas, Guozhi Jiang, Andrea O.Y. Luk, Heung Man Lee, Yu Huang, Yotsapon Thewjitcharoen, Soontaree Nakasatien, Thep Himathongkam, Christopher Fogarty, Rachel Njeim, Assaad Eid, Tine Willum Hansen, Nete Tofte, Evy C. Ottesen, Ronald C.W. Ma, Juliana C.N. Chan, Mark E. Cooper, Peter Rossing, Per-Henrik Groop, Assam El-Osta

×

Figure 4

Validation of differentially methylated genes in replication cohorts.

Options: View larger image (or click on image) Download as PowerPoint
Validation of differentially methylated genes in replication cohorts.
(A...
(A) DNA methylation analysis of core genes was performed in a larger FinnDiane replication cohort (n = 296: 19 healthy, 65 Normo, 73 Micro, 66 Macro, and 73 ESRD) using a highly specific methyl-qPCR assay. Data show combined DNA methylation (%) for the 7 core genes: MTOR, RPTOR, IRS2 (insulin signaling), TXNRD1, LCAT, SMPD3 (lipid metabolism), and COL1A2 (integrin-cell interaction) using PCA loading analysis. Results show that reduced DNA methylation (%) is associated with DN. (B) Replication of FinnDiane-derived DDNs in samples from the Danish PROFIL study – Steno Diabetes Center Copenhagen. Methyl-qPCR methylation analysis includes 40 nondiabetic and T1D individuals with Normo (n = 170), Micro (n = 110), and Macro (n = 125). (C) Methylation analysis of the DDNs in 77 age-matched T1D individuals from the Hong Kong T1D registry and 30 healthy controls. Individuals with T1D include 39 Normo, 30 Micro, and 8 Macro. (D) Methylation analysis of the DDNs in age-matched nondiabetic and T1D individuals recruited from the Theptarin registry, Thailand. DNA methylation (%) was assessed for genes in 65 controls and 65 cases (56 without renal complications and 9 with renal complications). Significance was calculated using the Mann-Whitney U test by comparing T1D with no complications (Normo) to Micro, Macro, and ESRD (A) or by comparing T1D with Normo and 9 T1D with Micro/Macro (combined) (B–D). *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001. Error bars are SEM.

Copyright © 2025 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

Sign up for email alerts