MODY probability calculator for GCK and HNF1A screening in a multiethnic background population

Objective We aimed to identify the frequency of monogenic diabetes, which is poorly studied in multiethnic populations, due to GCK or HNF1A mutations in patients with suggestive clinical characteristics from the Brazilian population, as well as investigate if the MODY probability calculator (MPC) could help patients with their selection. Subjects and methods Inclusion criteria were patients with DM diagnosed before 35 years; body mass index < 30 kg/m2; negative autoantibodies; and family history of DM in two or more generations. We sequenced HNF1A in 27 patients and GCK in seven subjects with asymptomatic mild fasting hyperglycemia. In addition, we calculated MODY probability with MPC. Results We identified 11 mutations in 34 patients (32.3%). We found three novel mutations. In the GCK group, six cases had mutations (85.7%), and their MODY probability on MPC was higher than 50%. In the HNF1A group, five of 27 individuals had mutations (18.5%). The MPC was higher than 75% in 11 subjects (including all five cases with HNF1A mutations). Conclusion Approximately one third of the studied patients have GCK or HNF1A mutations. Inclusion criteria included efficiency in detecting patients with GCK mutations but not for HNF1A mutations (< 20%). MPC was helpful in narrowing the number of candidates for HNF1A screening.

Cystatin C is not a good candidate biomarker for HNF1A-MODY

Cystatin C is a marker of glomerular filtration rate (GFR). Its level is influenced, among the others, by CRP whose concentration is decreased in HNF1A-MODY. We hypothesized that cystatin C level might be altered in HNF1A-MODY. We aimed to evaluate cystatin C in HNF1A-MODY both as a diagnostic marker and as a method of assessing GFR. We initially examined 51 HNF1A-MODY patients, 56 subjects with type 1 diabetes (T1DM), 39 with type 2 diabetes (T2DM) and 43 non-diabetic individuals (ND) from Poland. Subjects from two UK centres were used as replication panels: including 215 HNF1A-MODY, 203 T2DM, 39 HNF4A-MODY, 170 GCK-MODY, 17 HNF1B-MODY and 58 T1DM patients. The data were analysed with additive models, adjusting for gender, age, BMI and estimated GFR (creatinine). In the Polish subjects, adjusted cystatin C level in HNF1A-MODY was lower compared with T1DM, T2DM and ND (p < 0.05). Additionally, cystatin C-based GFR was higher than that calculated from creatinine level (p < 0.0001) in HNF1A-MODY, while the two GFR estimates were similar or cystatin C-based lower in the other groups. In the UK subjects, there were no differences in cystatin C between HNF1A-MODY and the other diabetic subgroups, except HNF1B-MODY. In UK HNF1A-MODY, cystatin C-based GFR estimate was higher than the creatinine-based one (p < 0.0001). Concluding, we could not confirm our hypothesis (supported by the Polish results) that cystatin C level is altered by HNF1A mutations; thus, it cannot be used as a biomarker for HNF1A-MODY. In HNF1A-MODY, the cystatin C-based GFR estimate is higher than the creatinine-based one.