Nature Communications (Dec 2022)
Epigenome-wide meta-analysis identifies DNA methylation biomarkers associated with diabetic kidney disease
- Laura J. Smyth,
- Emma H. Dahlström,
- Anna Syreeni,
- Katie Kerr,
- Jill Kilner,
- Ross Doyle,
- Eoin Brennan,
- Viji Nair,
- Damian Fermin,
- Robert G. Nelson,
- Helen C. Looker,
- Christopher Wooster,
- Darrell Andrews,
- Kerry Anderson,
- Gareth J. McKay,
- Joanne B. Cole,
- Rany M. Salem,
- Peter J. Conlon,
- Matthias Kretzler,
- Joel N. Hirschhorn,
- Denise Sadlier,
- Catherine Godson,
- Jose C. Florez,
- GENIE consortium,
- Carol Forsblom,
- Alexander P. Maxwell,
- Per-Henrik Groop,
- Niina Sandholm,
- Amy Jayne McKnight
Affiliations
- Laura J. Smyth
- Molecular Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast
- Emma H. Dahlström
- Folkhälsan Institute of Genetics, Folkhälsan Research Center
- Anna Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center
- Katie Kerr
- Molecular Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast
- Jill Kilner
- Molecular Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast
- Ross Doyle
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin
- Eoin Brennan
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin
- Viji Nair
- Department of Medicine-Nephrology, University of Michigan School of Medicine
- Damian Fermin
- Department of Pediatrics-Nephrology, University of Michigan School of Medicine
- Robert G. Nelson
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases
- Helen C. Looker
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases
- Christopher Wooster
- Molecular Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast
- Darrell Andrews
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin
- Kerry Anderson
- Molecular Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast
- Gareth J. McKay
- Molecular Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast
- Joanne B. Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute
- Rany M. Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego
- Peter J. Conlon
- Department of Nephrology and Transplantation, Beaumont Hospital and Department of Medicine Royal College of Surgeons in Ireland
- Matthias Kretzler
- Department of Internal Medicine, University of Michigan
- Joel N. Hirschhorn
- Programs in Metabolism and Medical & Population Genetics, Broad Institute
- Denise Sadlier
- Mater Misericordiae Hospital
- Catherine Godson
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin
- Jose C. Florez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute
- GENIE consortium
- Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center
- Alexander P. Maxwell
- Molecular Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast
- Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center
- Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center
- Amy Jayne McKnight
- Molecular Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast
- DOI
- https://doi.org/10.1038/s41467-022-34963-6
- Journal volume & issue
-
Vol. 13,
no. 1
pp. 1 – 16
Abstract
Approximately 40 percent of people with type 1 diabetes develop kidney disease, but the risk factors are not well understood. Here, the authors identify DNA methylation signatures associated with diabetic kidney disease, of which 21 biomarkers predict the development of kidney failure.
