The blind side of glucose control in type 1 diabetes; from pathogenesis to clinical implications

Type 1 diabetes (T1D) can be acquired at any age and accounts for about 5% to 10% of all diabetes mellitus cases. It is a metabolic disease caused by a cellular-mediated autoimmune destruction of pancreatic ß cells which results in a deficiency of insulin secretion. What causes the pathological autoimmune response is not yet fully understood but includes genetic susceptibility in combination with an environmental trigger. Insulin deficiency causes hyperglycaemia which is the main characteristic of T1D. In clinical practise, achieving a good glucose control represents the most important target. HbA1c and continuous glucose monitoring (CGM) parameters (Time in Range, Time Above the range and Time below the range) are currently used as glucose control indicators. HbA1c is a particular form of hemoglobin modified by glucose which determines the three-month average blood glucose level. It can be used both as a diagnostic test for diabetes and to assess glycaemic control. Time in range, time above the range and time below the range represent the amount of time a person spends in, above and below the target range (generally 70-180 mg/dl). Time in range should reach at least a value of 70%. Patients with long history of T1D can develop chronic complications, including ischemic cardiopathy, stroke and diabetic retinopatht, nephropathy and neuropathy. With the increasing use of CGM, TIR is expected to become a core indicator for short-term blood glucose assessment and for the risk of diabetic complications According to 2019 ADA guidelines a 5% increase in TIR is associated with significant clinical benefit in patients with T1DM. However, the relationship between TIR and diabetic complications has not been fully studied, and whether TIR value resulting from the extensive fingertip glucose monitoring and non-GCM is equally meaningful remains to be investigated. Study 1 Poor glucose control has been associated with markedly increased mortality in COVID-19 patients with Type 1 Diabetes (T1D), however, the impact of glucose control on immunogenicity to SARS-CoV2 vaccines is not clear. The aim of the present study was to assess the effect of glucose control on antibody response to SARS-CoV2 vaccination in T1D. 26 patients (14 males, mean age 39.3 ± 11, mean disease duration 21.4 ± 10.1), scheduled to receive two doses of the SARS-CoV2 mRNA vaccine BNT162b2, were enrolled in our single centre six-months cohort study. Patients underwent blood samples at 5 time-points T0-T4 (baseline within three days before the first vaccine dose; T1 just before the second vaccine dose; T2 two weeks after the second dose; T3 three months from baseline and T4 six months from baseline). The main outcomes were IgG antibodies to Spike glycoprotein by ELISA, HbA1c and CGM parameters. Longitudinal IgG response to spike reached a peak at T2, followed by a progressive decline across later timepoints (P <0.001). Peak IgG at T2 was not significantly correlated with baseline HbA1c, but strongly correlated with baseline glucose time in range (TIR) and glucose time above range (TAR) in patients wearing a CGM device for at least 10 days during the two weeks before baseline. Our findings indicate a strong relationship between glucose control and antibody response following SARS-CoV2 vaccine, highlighting the importance of achieving well-controlled blood glucose control. Study 2 According to Sims et al. (Diabetes Care 2018), 96% long-standing T1D had detectable serum proinsulin (>3.1 pmol/L) despite low or absent C-peptide (a marker of insulin secretion). The Proinsulin to C-peptide ratio is a marker of beta-cell stress, indicating the inability of Beta-cell to convert proinsulin to insulin and C-peptide. Residual Beta-cell function has been associated with lower risk of chronic complications in T1D. We hypothesized that the Beta-cell stress marker Proinsulin/C-peptide is higher in patients with complications. The aims of the present study were to evaluate whether proinsulin and the proinsulin/C-peptide ratio are associated with chronic complications and glucose control in patients with long standing T1D. 100 T1D patients (64 males, 36 females) were enrolled in our single-centre cross-sectional cohort study. Patients were divided in two groups: without complications (74 subjects, mean age 42.3 ± 15.8, mean disease duration 12.7 ± 7) and with complications (26 subjects, mean age 42.16 ± 8.58, mean disease duration 24.5 ± 8.89). Chronic complications assessment were performed to screen diabetic neuropathy, nephropathy and retinopathy according to international guidelines. The main outcomes were proinsulin, C-peptide, proinsulin to C-peptide ratio, HbA1c and CGM parameters. No significant correlation was observed between C-peptide and proinsulin. C peptide, proinsulin and the Proinsulin to C-peptide ratio (PI:CP) resulted unrelated to chronic complications and glucose control. Beta cell stress is present in most T1D patients, however, proinsulin/C-peptide ratio is not associated with T1D complications and glucose control. Study 3 Carbohydrate (CHO) counting is often performed inaccurately by patients with T1D. We hypothesized that mobile App "Dietrometro", that estimates CHO content of food figures, would ameliorate glucose control. Fifty-four T1D subjects (26 males), on multiple daily injections (n = 23) or continuous subcutaneous insulin infusion (n = 31), were randomly assigned to three groups: no counting (group 1; n = 19, mean age 44,37 ± 15,79), "self- managed" counting (group 2; n = 19, mean age 42,21 ± 15,09) and App-assisted counting (group 3; n = 16, mean age 38,31 ± 13,69). Outcomes were one- and three months follow-up CGM parameters, estimated by flash or continuous glucose monitoring, and HbA1c. At the baseline TIR were similar between groups, while HbA1c was lower in group 3 compared to group 1 (6.9 ± 1.06 vs. 7.8 ± 0.85%; p <0.05). At one-month follow-up, TIR was higher in group 2 and 3 compared to group 1 (63.58 ± 11.55 vs. 52.32 ± 13.22%; p = 0.014, and 71.25 ± 9.75 vs. 52.32 ± 13. 22%, respectively; p <0.001). TAR at one-month follow-up was significantly lower in group 3 (31.25 ± 19.18 vs. 22.31 ± 10.89%; p <0.001), while no differences were observed in TBR. At threemonths follow-up, groups 2 and 3 had a lower HbA1c than group 1 (7.16 ± 0.647 vs. 6.56 ± 1.91 vs. 7.96 ± 1.0%; p <0.05). App-assisted CHO counting might improve short-term glucose control. Patient’s counseling to increase compliance should be part of disease management to achieve a better long term glucose control. Study 4 Technological advances in glucose monitoring and continuous subcutaneous insulin infusion (CSII) should aim to improve glucose control and quality of life in type 1 diabetes (T1D). The primary aim of study 4 was to test the overall effect of new technologies in the treatment of type 1 diabetes in terms of quality of life. The exploratory aim was to compare the different devices (both sensors and insulin pumps) on patients' quality of life. Sixty-nine T1D patients (31 males, mean age 39 ± 12) were recruited. 36 were on multiple daily insulin injections (MDI), 33 on CSII devices including Medtronic Minimed 640G and 670G, Theras Omnipod, Roche Insight and Movy Tandem. Glucose monitoring was performed with Dexcom-G6, Guardian sensor and Flash Freestyle Libre. The Diabetes Treatment Satisfaction Questionnaire (DTSQ), the Diabetes Specific Quality Of Life Scale (DSQOLS) and The Short Form (36) Health Survey (SF-36) were administered to test quality of life. The main outcomes were HbA1c and CGM parameters. Patients belonging to CSII group had higher treatment-related satisfaction (84.8% vs 52.8%, p = 0.004), and better disease acceptance (84.8% vs 52.8%, p = 0.012) compared with patients on MDI, despite similar age (MDI mean age 38 ± 12.5, CSII 41 ± 11.6). No differences were observed among devices (p = ns). TIR resulted higher in the CSII group than in the MDI group (p = 0.001). Technological devices improve quality of life and glucose control, but not patient's self perception of disease.