Biomarkers for MODY subtypes

A confirmed diagnosis of MODY has important clinical implications for the individual patient and their families. Unfortunately the vast majority of patients with MODY remain misdiagnosed with more common types of diabetes. This partly reflects the availability and cost of molecular genetic investigation which prohibits universal testing for monogenic diabetes in all patients with diabetes. Therefore, there has been great interest in finding sensitive and specific biomarkers for MODY subtypes (ideally widely-available at low cost) which could be used to screen large numbers of patients with diabetes to identify which individuals should be prioritised for genetic testing. Potential biomarkers for MODY have emerged from various sources including knockout mouse models, genome-wide association studies and human physiological studies. Recently, subjects with HNF1A-MODY were found to have very low blood levels of highly-sensitive C-reactive protein (hsCRP). This finding has been subsequently confirmed in a large collaborative European study. HsCRP is the most promising biomarker for HNF1A-MODY identified to date and is currently being incorporated into diagnostic algorithms for HNF1-MODY.


The majority of patients with MODY are misdiagnosed as type 1 or type 2 diabetes. This reflects the significant overlap in clinical presentation of MODY with common types of diabetes, cost of genetic investigation and lack of awareness of MODY amongst clinicians. Non-genetic biomarkers specific for MODY could be used alongside clinical features to screen a large number of patients with diabetes, and prioritise patients who would benefit from molecular diagnostic testing[1].

Features of an ideal biomarker

A biomarker is considered clinically useful if it demonstrates a high sensitivity and specificity (and can therefore discriminate subjects with and without disease), is cheap and widely-available, and is not operator or assay dependent. The receiver operating characteristic (ROC) curve analysis is a plot of sensitivity versus 1-specificity. The area under the ROC curve (also known as the C-statistic) reflects the discriminatory power of a biomarker. A C-statistic of 0.5 indicates that the biomarker provides no discrimination between the two disease states, whereas a C-statistic of 1.0 indicates perfect discrimination.

Biomarkers and MODY

High-sensitivity C-reactive (hsCRP)

To date, the most promising biomarker for HNF1A-MODY is high-sensitivity C-reactive protein (hsCRP). Three independent genome wide association studies (GWAS) reported that common variation near HNF1A was reproducibly associated with modest differences in C-reactive protein (CRP) levels in healthy adults. Furthermore the CRP promoter contains binding sites for HNF1A and CRP expression is downregulated in hnf1a knockout mice. The hypothesis that loss-of-function HNF1A mutations are associated with lower hsCRP levels was confirmed in a pilot study: HNF1A-MODY patients had significantly lower levels of hsCRP compared with autoimmune diabetes, type 2 diabetes and GCK-MODY as well as healthy controls. These results were replicated in two large independent studies - see Fig ROC curve illustrating that hsCRP discriminates well between HNF1A-MODY and young-onset type 2 diabetes
ROC curve illustrating that hsCRP discriminates well between HNF1A-MODY and young-onset type 2 diabetes
ure 1. [2] [3]

Given the good discriminative power and common use in clinical practice, hsCRP has excellent potential to be used as a biomarker to select patients with young-onset diabetes for molecular diagnostic testing. One limitation is that CRP is an acute phase protein (i.e. levels rise during an infection) and is used to diagnose and monitor infection and inflammation. High hsCRP levels can be misleading in someone with a clinical suspicion of HNF1A-MODY but with a concurrent infection. It is advisable to repeat hsCRP after a few weeks in this situation.


C-peptide is co-secreted with insulin from beta-cells and detectable levels indicate residual beta-cell function. C-peptide levels decline and become undetectable in those with type 1 diabetes due to autoimmune destruction of beta-cells, whereas C-peptide levels persist in patients with MODY who retain endogenous beta-cell function. In one cross-sectional study, subjects with clinically-labelled type 1 diabetes with detectable C-peptide levels outside the honeymoon period (>3 years from diagnosis) underwent genetic testing for MODY. 10% (2 subjects) of those sequenced were found to have HNF1A-MODY [4]. In another study, urinary C-peptide to creatinine ratio (UCPCR) was significantly lower in long-standing type 1 diabetes compared with HNF1A/4A MODY with a C-statistic of 0.98 [5]. UCPCR has an advantage of being non-invasive test and can be measured in urine collected with boric acid preservative and sent by post.

Pancreatic islet antibodies

Almost all patients with type 1 diabetes have at least one pancreatic islet autoantibody present at diagnosis, either GAD (glutamic acid decarboxylase) or IA-2 (insulinoma antigen 2) antibody. MODY subjects would not be expected to have islet autoantibodies and diagnostic guidelines for MODY suggest testing those who are antibody negative. A recent study from the UK diagnostic testing centre reported < 1% prevalence of GAD and IA-2 antibodies in MODY [6]. However other studies report positive islet antibodies in up to 20% patients with confirmed MODY mutations, however, no IA-2 antibodies were detected [7]. This suggests that in the case of strong clinical suspicion, presence of islet autoantibodies should not preclude genetic testing.

Other biomarkers evaluated for MODY

Significant research efforts have been invested over the last decade to identify biomarkers specific for MODY. Several approaches have been used, including knockout mouse models, human physiological studies, bioinformatics and metabonomics.

The hnf1a knockout mouse has a striking phenotype of renal Fanconi syndrome with polyuria, glycosuria and increased renal fractional excretion of amino acids. Aminoaciduria is not specific to HNF1A-MODY and is seen in other diabetes groups due to glycosuria. Serum levels of amino acids particularly phenylalanine are altered in hnf1a knockout mice. However these changes were not observed in subjects with HNF1A-MODY.

HNF1A and HNF4A regulate the genes encoding complement 5 (C5), complement 8 (C8) and transthyretin (TTR). C5, C8 and TTR were evaluated as potential biomarkers for HNF1A/HNF4A MODY: although sensitivity was reasonable (60-90%), these candidate biomarkers had extremely poor specificity (2-10%).

Apolipoprotein M (apoM) is a ~25 kDa apolipoprotein found in all major lipoprotein classes especially high density lipoprotein (HDL). ApoM is transcriptionally regulated by HNF1A, and there is reduced expression of apoM in hnf1a knockout mice. An initial study reported lower levels of ApoM in HNF1A-MODY compared with healthy controls. These findings have not been replicated in two subsequent studies. More recently, the role of ApoM as a biomarker for HNF1A-MODY was reassessed using a new, highly sensitive and specific ELISA [8]. In this study, serum ApoM levels in HNF1A-MODY subjects were significantly lower compared with type 1 diabetes subjects or healthy controls, but were similar to subjects with type 2 diabetes.

A GWAS of the human glycome established the key role of HNF1A as a regulator of plasma protein glycosylation (i.e. the post-translational addition of complex oligosaccharide structures or glycans). The glycan profile of plasma proteins is substantially altered in HNF1A-MODY subjects, and these differences can reliably differentiate HNF1A-MODY from both type 1 and type 2 diabetes (ROC-curve derived C-statistic 0.91 and 0.94 respectively) [9]. Widespread translation of this finding is currently restricted by the cost and restricted availability of accurate glycan analysis.

HNF1A regulates the transcription of the high affinity low capacity sodium-glucose transporter-2 (SGLT2) in the proximal renal tubule. HNF1A haploinsufficiency results in reduced expression of SGLT2, decreased glucose reabsorption from the proximal tubule and a low renal threshold for glucose in HNF1A-MODY. 1,5 anhydroglucitol (1,5 AG) is a non-metabolised dietary monosaccharide with structural similarity to glucose. Usually 1,5 AG is re-absorbed in the proximal renal tubule by a AG/fructose/mannose common transport system. However when glycosuria is present, glucose competes with 1,5 AG for reabsorption via this monosaccharide transport system, leading to lowered plasma concentration of 1,5 AG. 1,5AG is available commercially as a marker of post-prandial hyperglycaemia (and is an alternative to HbA1c for measuring glycemic control in diabetes). Skupien et al hypothesised that the glycosuria seen in HNF1A-MODY would lower levels of 1,5 AG. This study reported that plasma 1,5 AG levels in HNF1A-MODY patients were 50% lower than type 2 diabetes subjects with matched glycaemic control [10]. A later study replicated this result by Skupien et al [11]. The C-statistic was 0.60 for HNF1A-MODY versus type 2 diabetes, suggesting that the discriminative power was insufficient for clinical use. An interesting finding in this study was that levels of 1,5 AG provided a good discrimination between GCK-MODY and HNF1A-MODY (C-statistic of 0.86). It was proposed that 1,5 AG could be used as a practical alternative to the oral glucose tolerance test which is currently being used to discriminate between GCK-MODY and HNF1A-MODY.

HDL has also been assessed as a candidate biomarker to discriminate HNF1A –MODY and type 2 diabetes. HDL was found to be significantly lower in patients with HNF1A-MODY than those with type 2 diabetes with a C-statistic of 0.76 indicating modest discrimination [12].

Cystatin C has also been investigated and is unlikely to be a useful biomarker for HNF1A-MODY.

A specific microRNA (miR-103) was reported to be significantly upregulated in HNF1A-MODY subjects compared with family control subjects. It is unlikely that this microRNA has potential as a biomarker for HNF1A-MODY due to the overlap in miR-103 copy number between the two groups of subjects.

Future prospects

Current diagnostic criteria are highly specific but have poor sensitivity, missing many cases of MODY. Clinical prediction models which combine clinical criteria and emerging biomarkers could provide improved sensitivity. Recently a prediction model has been developed by Shields and colleagues which is available via the website [13]. This model uses easily available clinical features including HbA1c, gender, age at diagnosis, parental history of diabetes and current treatment to calculate the probability of having MODY. Combinations of these clinical features resulted in in high sensitivity and specificity (both reaching up to 91%). This model is undergoing further evaluation. Biomarkers such as hsCRP, C-peptide, islet auto antibodies and HDL, that have been shown to discriminate HNF1A-MODY from type 1 and type 2 diabetes, are now being tested in this model.


  1. ^ Owen KR, Skupien J, Malecki MT; CEED3 Consortium. The clinical application of non-genetic biomarkers for differential diagnosis of monogenic diabetes. Diabetes Res Clin Pract. 2009;86 Suppl 1:S15-21

  2. ^ Thanabalasingham G, Shah N, Vaxillaire M, Hansen T, Tuomi T, Gašperíková D, Szopa M, Tjora E, James TJ, Kokko P, Loiseleur F, Andersson E, Gaget S, Isomaa B, Nowak N, Raeder H, Stanik J, Njolstad PR, Malecki MT, Klimes I, Groop L, Pedersen O, Froguel P, McCarthy MI, Gloyn AL, Owen KR. A large multi-centre European study validates high-sensitivity C-reactive protein (hsCRP) as a clinical biomarker for the diagnosis of diabetes subtypes. Diabetologia. 2011;54(11):2801-10

  3. ^ McDonald TJ, Shields BM, Lawry J, Owen KR, Gloyn AL, Ellard S, Hattersley AT. High-sensitivity CRP discriminates HNF1A-MODY from other subtypes of diabetes. Diabetes Care. 2011;34(8):1860-2.

  4. ^ Thanabalasingham G, Pal A, Selwood MP, Dudley C, Fisher K, Bingley PJ, Ellard S, Farmer AJ, McCarthy MI, Owen KR. Systematic assessment of etiology in adults with a clinical diagnosis of young-onset type 2 diabetes is a successful strategy for identifying maturity-onset diabetes of the young. Diabetes Care. 2012;35(6):1206-12

  5. ^ Besser RE, Shepherd MH, McDonald TJ, Shields BM, Knight BA, Ellard S, Hattersley AT. Urinary C-peptide creatinine ratio is a practical outpatient tool for identifying hepatocyte nuclear factor 1-{alpha}/hepatocyte nuclear factor 4-{alpha} maturity-onset diabetes of the young from long-duration type 1 diabetes. Diabetes Care. 2011;34(2):286-91

  6. ^ McDonald TJ, Colclough K, Brown R, Shields B, Shepherd M, Bingley P, Williams A, Hattersley AT, Ellard S. Islet autoantibodies can discriminate maturity-onset diabetes of the young (MODY) from Type 1 diabetes. Diabet Med. 2011;28(9):1028-33

  7. ^ Schober E, Rami B, Grabert M et al.: Phenotypical aspects of maturity-onset diabetes of the young (MODY diabetes) in comparison with Type 2 diabetes mellitus (T2DM) in children and adolescents: experience from a large multicentre database. Diabet Med 2009: 26; 466-473

  8. ^ Mughal SA, Park R, Nowak N, Gloyn AL, Karpe F, Matile H, Malecki MT, McCarthy MI, Stoffel M, Owen KR. Apolipoprotein M can discriminate HNF1A-MODY from Type 1 diabetes. Diabet Med. 2013 30(2):246-50.

  9. ^ Thanabalasingham G, Huffman JE, Kattla JJ et al. Mutations in HNF1A result in marked alterations of plasma glycan profile. Diabetes. 2013 62(4):1329-37.

  10. ^ Skupien J, Gorczynska-Kosiorz S, Klupa T, Wanic K, Button EA, Sieradzki J, Malecki MT. Clinical application of 1,5-anhydroglucitol measurements in patients with hepatocyte nuclear factor-1alpha maturity-onset diabetes of the young. Diabetes Care. 2008; 31(8):1496-501.

  11. ^ Pal A, Farmer AJ, Dudley C, Selwood MP, Barrow BA, Klyne R, Grew JP, McCarthy MI, Gloyn AL, Owen KR. Evaluation of serum 1,5 anhydroglucitol levels as a clinical test to differentiate subtypes of diabetes. Diabetes Care. 2010; 33(2):252-7

  12. ^ McDonald TJ, McEneny J, Pearson ER, Thanabalasingham G, Szopa M, Shields BM, Ellard S, Owen KR, Malecki MT, Hattersley AT, Young IS. Lipoprotein composition in HNF1A-MODY: differentiating between HNF1A-MODY and type 2 diabetes. Clin Chim Acta. 2012 18;413(9-10):927-32

  13. ^ Shields BM, McDonald TJ, Ellard S, Campbell MJ, Hyde C, Hattersley AT. The development and validation of a clinical prediction model to determine the probability of MODY in patients with young-onset diabetes. Diabetologia. 2012;55(5):1265-72


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