ArticlePloS one2012
Metabolic profiling in Maturity-onset diabetes of the young (MODY) and young onset type 2 diabetes fails to detect robust urinary biomarkers.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 21 citations in OpenAlex.
- Effect of SGLT2 Inhibition on Glucosuria During a Hyperglycemic Clamp in HNF1A-MODY (MODY3) and Type 2 Diabetes.Diabetes care · 2025Trial
- Assessment of urinary betaine as a marker of diabetes mellitus in cardiovascular patients.PloS one · 2013Trial
- LC-MS-based metabolomics for detecting adulteration inFood chemistry: X · 2025Article
- Elevated level of lysophosphatidic acid among patients with HNF1B mutations and its role in RCAD syndrome: a multiomic study.Metabolomics : Official journal of the Metabolomic Society · 2022Article
- Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery.International journal of molecular sciences · 2020Review
- The Role of Lipidomics in Autism Spectrum Disorder.Molecular diagnosis & therapy · 2020Review
- Assessment of Newly Proposed Clinical Criteria to Identify HNF1A MODY in Patients with an Initial Diagnosis of Type 1 or Type 2 Diabetes Mellitus.Advances in medicine · 2016Article
- Potential serum biomarkers from a metabolomics study of autism.Journal of psychiatry & neuroscience : JPN · 2016Article
- Clinical and non-targeted metabolomic profiling of homozygous carriers of Transcription Factor 7-like 2 variant rs7903146.Scientific reports · 2014Article
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Authors and funding
9 authors at 5 institutions in 3 countries.
Funding
Abstract
It is important to identify patients with Maturity-onset diabetes of the young (MODY) as a molecular diagnosis determines both treatment and prognosis. Genetic testing is currently expensive and many patients are therefore not assessed and are misclassified as having either type 1 or type 2 diabetes. Biomarkers could facilitate the prioritisation of patients for genetic testing. We hypothesised that patients with different underlying genetic aetiologies for their diabetes could have distinct metabolic profiles which may uncover novel biomarkers. The aim of this study was to perform metabolic profiling in urine from patients with MODY due to mutations in the genes encoding glucokinase (GCK) or hepatocyte nuclear factor 1 alpha (HNF1A), type 2 diabetes (T2D) and normoglycaemic control subjects. Urinary metabolic profiling by Nuclear Magnetic Resonance (NMR) and ultra performance liquid chromatography hyphenated to Q-TOF mass spectrometry (UPLC-MS) was performed in a Discovery set of subjects with HNF1A-MODY (n = 14), GCK-MODY (n = 17), T2D (n = 14) and normoglycaemic controls (n = 34). Data were used to build a valid partial least squares discriminate analysis (PLS-DA) model where HNF1A-MODY subjects could be separated from the other diabetes subtypes. No single metabolite contributed significantly to the separation of the patient groups. However, betaine, valine, glycine and glucose were elevated in the urine of HNF1A-MODY subjects compared to the other subgroups. Direct measurements of urinary amino acids and betaine in an extended dataset did not support differences between patients groups. Elevated urinary glucose in HNF1A-MODY is consistent with the previously reported low renal threshold for glucose in this genetic subtype. In conclusion, we report the first metabolic profiling study in monogenic diabetes and show that, despite the distinct biochemical pathways affected, there are unlikely to be robust urinary biomarkers which distinguish monogenic subtypes from T2D. Our results have implications for studies investigating metabolic profiles in complex traits including T2D.
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