Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry.

INTRODUCTION: Type 2 diabetes is preventable in subjects with impaired glucose tolerance based on 2-hour plasma glucose (2hPG) during 75 g oral glucose tolerance test (OGTT). We incorporated routine biochemistry to improve the performance of a non-invasive diabetes risk score to identify individuals with abnormal glucose tolerance (AGT) defined by 2hPG≥7.8 mmol/L during OGTT. RESEARCH DESIGN AND METHODS: We used baseline data of 1938 individuals from the community-based "Better Health for Better Hong Kong - Hong Kong Family Diabetes Study (BHBHK-HKFDS) Cohort" recruited in 1998-2003. We incorporated routine biochemistry in a validated non-invasive diabetes risk score, and evaluated its performance using area under receiver operating characteristics (AUROC) with internal and external validation. RESULTS: The AUROC of the original non-invasive risk score to predict AGT was 0.698 (95% CI, 0.662 to 0.733). Following additional inclusion of fasting plasma glucose, serum potassium, creatinine, and urea, the AUROC increased to 0.778 (95% CI, 0.744 to 0.809, p<0.001). Net reclassification improved by 31.9% (p<0.001) overall, by 30.8% among people with AGT and 1.1% among people without AGT. The extended model showed good calibration (χ2=11.315, p=0.1845) and performance on external validation using an independent data set (AUROC=0.722, 95% CI, 0.680 to 0.764). CONCLUSIONS: The extended risk score incorporating clinical and routine biochemistry can be integrated into an electronic health records system to select high-risk subjects for evaluation of AGT using OGTT for prevention of diabetes.

Differential Associations of GAD Antibodies (GADA) and C-Peptide With Insulin Initiation, Glycemic Responses, and Severe Hypoglycemia in Patients Diagnosed With Type 2 Diabetes.

OBJECTIVE: We examined the associations of GAD antibodies (GADA) and C-peptide (CP) with insulin initiation, glycemic responses, and severe hypoglycemia in type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: In 5,230 Chinese patients (47.6% men) with T2D (mean ± SD age: 56.5 ± 13.9 years; median diabetes duration: 6 [interquartile range 1, 12] years), enrolled consecutively in 1996-2012 and prospectively observed until 2019, we retrospectively measured fasting CP and GADA in stored serum and examined their associations with aforementioned outcomes. RESULTS: At baseline, 28.6% (n = 1,494) had low CP (<200 pmol/L) and 4.9% (n = 257) had positive GADA (GADA+). In the low-CP group, 8.0% had GADA+, and, in the GADA+ group, 46.3% had low CP. The GADA+ group had an adjusted hazard ratio (aHR) of 1.46 (95% CI 1.15-1.84, P = 0.002) for insulin initiation versus the GADA- group, while the low-CP group had an aHR of 0.88 (0.77-1.00, P = 0.051) versus the high-CP group. Following insulin initiation, the GADA+ plus low-CP group had the largest decrements in HbA1c (-1.9% at month 6; -1.5% at month 12 vs. -1% in the other three groups). The aHR of severe hypoglycemia was 1.29 (95% CI 1.10-1.52, P = 0.002) in the low-CP group and 1.38 (95% CI 1.04-1.83, P = 0.024) in the GADA+ group. CONCLUSIONS: There is considerable heterogeneity in autoimmunity and ß-cell dysfunction in T2D with GADA+ and high CP associated with early insulin initiation, while GADA+ and low CP, increased the risk of severe hypoglycemia. Extended phenotyping is warranted to increase the precision of classification and treatment in T2D.

Glycemic Variability and Time in Range During Self-titration of Once Daily Insulin Glargine 300 U/ml Versus Neutral Protamine Hagedorn Insulin in Insulin-naïve Chinese Type 2 Diabetes Patients.

INTRODUCTION: To compare glycemic variability (GV) and time in range (TIR) in Chinese patients with type 2 diabetes (T2D) initiated on once-daily bedtime insulin glargine 300U/ml (Gla-300) versus neutral protamine Hagedorn (NPH) insulin using continuous glucose monitoring (CGM). METHODS: This was a 24-week, open-label exploratory study with 1:1 randomization comparing patient-adjusted titration of Gla-300 (n = 23) versus NPH (n = 23) at bedtime in insulin-naïve T2D patients on maximum oral glucose-lowering drugs. The starting dose was 0.2 U/kg/day and with self-titration of one unit per week to achieve a target fasting glucose of 4.4-6 mmol/l, without hypoglycemia. Participants had masked CGM at baseline, weeks 11 and 24. The primary outcome was between-treatment differences in CGM glucose standard deviation (SD) at week 24. RESULTS: HbA1c at week 24 were similar, with 21% of Gla-300 versus 4% of NPH-treated patients achieving HbA1c < 7% without confirmed hypoglycemia. There were no differences in anytime glucose SD at week 24 (LS mean difference - 0.08 mmol/l, 95% CI [- 0.42-0.26], p = 0.63). Anytime %TIRs (3.9-10.0 mmol/l) at week 24 were similar (p = 0.91). Nocturnal % time below range < 3.9 mmol/l was significantly lower in the Gla-300 group (least squares (LS) mean difference - 5.03% [- 9.92 to - 0.14], p = 0.04) with lower % coefficient of variation (LS mean difference - 4.5% [- 8.1 to - 0.8], p = 0.018). Diurnal TIR was higher in Gla-300 patients at week 11 but there were no differences at week 24. CONCLUSIONS: Once-daily bedtime Gla-300 was associated with lower nocturnal GV, time below range and self-reported hypoglycemia in insulin-naïve Chinese T2D patients over a 24-week study period, as compared with NPH insulin. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03389490.

Effects of CYP2D6*10, CYP3A5*3, CYP1A2*1F, and ABCB1 C3435T polymorphisms on the pharmacokinetics of flecainide in healthy Chinese subjects.

BACKGROUND: Although flecainide is thought to be meta-bolized predominantly by cytochrome P450 (CYP) 2D6, it shows pharmacokinetic interactions with drugs, such as verapamil and digoxin, which may suggest other CYP pathways or ATP-binding cassette (ABC) transporters might be involved. This study evaluated effects of common polymorphisms in Chinese in CYP2D6, CYP3A5, CYP1A2, and ABCB1 on flecainide pharmacokinetics. METHODS: Single oral 100-mg doses of flecainide were given to 15 healthy male Chinese subjects who were genotyped for the CYP2D6*2, *5, *10, CYP3A5*3, CYP1A2*1F and ABCB1 C1236T, G2677T/A, and C3435T polymorphisms. RESULTS: There was no significant difference in the pharmacokinetics of flecainide among CYP2D6 (mainly involving *10) genotypes. The CYP3A5*3/*3 subjects (n=8) had a 26% higher systemic exposure (AUC0-∞) and 17% lower apparent oral clearance of flecainide than the combined group of CYP3A5*1/*1 (n=6) and CYP3A5*1/*3 (n=1) subjects (p<0.05). Subjects homozygous for CYP1A2*1F tended to have lower systemic exposure and increased clearance of flecainide compared to those with CYP1A2*1A/1F in subjects with at least one CYP2D6 variant allele. CONCLUSIONS: The disposition of flecainide appeared to be influenced by the CYP3A5*3 and possibly the CYP1A2*1F polymorphisms, particularly in subjects with CYP2D6 variant alleles.

Pharmacogenetic analysis of lipid responses to rosuvastatin in Chinese patients.

Lipid changes with statin treatments vary greatly between individuals for reasons which are largely unknown. This study was performed to examine the genetic determinants of lipid responses to rosuvastatin in Chinese patients. A total of 125 polymorphisms in 61 candidate genes from 386 Chinese patients were analyzed for association with the lipid responses to rosuvastatin 10 mg daily. The polymorphisms most highly associated with the low-density lipoprotein cholesterol (LDL-C) response were 421C>A in the ATP-binding cassette G2 gene (P=9.2×10), followed by 18281G>A (V257M) in the flavin-containing monooxygenase 3 gene (P=0.0002), 1421C>G in the lipoprotein lipase gene (P=0.002), and rs4420638 in the apolipoprotein E/C-I/C-IV/C-II gene cluster (P=0.004). Patients with familial hypercholesterolemia had 2.6% smaller reductions in LDL-C compared with patients without familial hypercholesterolemia. This study identified some genetic determinants of LDL-C response to rosuvastatin in Chinese patients, which need to be replicated in other populations.