Biomarker panels associated with progression of renal disease in type 1 diabetes.
Clinical science
Epidemiology
Metabolomics
Nephropathy
Proteomics
Journal
Diabetologia
ISSN: 1432-0428
Titre abrégé: Diabetologia
Pays: Germany
ID NLM: 0006777
Informations de publication
Date de publication:
09 2019
09 2019
Historique:
received:
27
02
2019
accepted:
30
04
2019
pubmed:
22
6
2019
medline:
14
4
2020
entrez:
22
6
2019
Statut:
ppublish
Résumé
We aimed to identify a sparse panel of biomarkers for improving the prediction of renal disease progression in type 1 diabetes. We considered 859 individuals recruited from the Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) and 315 individuals from the Finnish Diabetic Nephropathy (FinnDiane) study. All had an entry eGFR between 30 and 75 ml min For final eGFR, 16 proteins and 30 metabolites or tryptic peptides showed significant association in SDRNT1BIO, and nine proteins and five metabolites or tryptic peptides in FinnDiane, beyond age, sex, diabetes duration, study day eGFR and length of follow-up (all at p < 10 Among a large set of associated biomarkers, a sparse panel of just CD27 and KIM-1 contains most of the predictive information for eGFR progression. The increment in prediction beyond clinical data was modest but potentially useful for oversampling individuals with rapid disease progression into clinical trials, especially where there is little information on prior eGFR trajectories.
Identifiants
pubmed: 31222504
doi: 10.1007/s00125-019-4915-0
pii: 10.1007/s00125-019-4915-0
pmc: PMC6677704
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1616-1627Subventions
Organisme : Diabetes UK
ID : 10/0004010
Pays : United Kingdom
Organisme : Chief Scientist Office
ID : ETM/47
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0600717
Pays : United Kingdom
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