Impaired GK-GKRP interaction rather than direct GK activation worsens lipid profiles and contributes to long-term complications: a Mendelian randomization study.

BACKGROUND: Glucokinase (GK) plays a key role in glucose metabolism. In the liver, GK is regulated by GK regulatory protein (GKRP) with nuclear sequestration at low plasma glucose level. Some GK activators (GKAs) disrupt GK-GKRP interaction which increases hepatic cytoplasmic GK level. Excess hepatic GK activity may exceed the capacity of glycogen synthesis with excess triglyceride formation. It remains uncertain whether hypertriglyceridemia associated with some GKAs in previous clinical trials was due to direct GK activation or impaired GK-GKRP interaction. METHODS: Using publicly available genome-wide association study summary statistics, we selected independent genetic variants of GCKR and GCK associated with fasting plasma glucose (FPG) as instrumental variables, to mimic the effects of impaired GK-GKRP interaction and direct GK activation, respectively. We applied two-sample Mendelian Randomization (MR) framework to assess their causal associations with lipid-related traits, risks of metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular diseases. We verified these findings in one-sample MR analysis using individual-level statistics from the Hong Kong Diabetes Register (HKDR). RESULTS: Genetically-proxied impaired GK-GKRP interaction increased plasma triglycerides, low-density lipoprotein cholesterol and apolipoprotein B levels with increased odds ratio (OR) of 14.6 (95% CI 4.57-46.4) per 1 mmol/L lower FPG for MASLD and OR of 2.92 (95% CI 1.78-4.81) for coronary artery disease (CAD). Genetically-proxied GK activation was associated with decreased risk of CAD (OR 0.69, 95% CI 0.54-0.88) and not with dyslipidemia. One-sample MR validation in HKDR showed consistent results. CONCLUSIONS: Impaired GK-GKRP interaction, rather than direct GK activation, may worsen lipid profiles and increase risks of MASLD and CAD. Development of future GKAs should avoid interfering with GK-GKRP interaction.

Precision Medicine to Redefine Insulin Secretion and Monogenic Diabetes-Randomized Controlled Trial (PRISM-RCT) in Chinese patients with young-onset diabetes: design, methods and baseline characteristics.

INTRODUCTION: We designed and implemented a patient-centered, data-driven, holistic care model with evaluation of its impacts on clinical outcomes in patients with young-onset type 2 diabetes (T2D) for which there is a lack of evidence-based practice guidelines. RESEARCH DESIGN AND METHODS: In this 3-year Precision Medicine to Redefine Insulin Secretion and Monogenic Diabetes-Randomized Controlled Trial, we evaluate the effects of a multicomponent care model integrating use of information and communication technology (Joint Asia Diabetes Evaluation (JADE) platform), biogenetic markers and patient-reported outcome measures in patients with T2D diagnosed at ≤40 years of age and aged ≤50 years. The JADE-PRISM group received 1 year of specialist-led team-based management using treatment algorithms guided by biogenetic markers (genome-wide single-nucleotide polymorphism arrays, exome-sequencing of 34 monogenic diabetes genes, C-peptide, autoantibodies) to achieve multiple treatment goals (glycated hemoglobin (HbA1c) <6.2%, blood pressure <120/75 mm Hg, low-density lipoprotein-cholesterol <1.2 mmol/L, waist circumference <80 cm (women) or <85 cm (men)) in a diabetes center setting versus usual care (JADE-only). The primary outcome is incidence of all diabetes-related complications. RESULTS: In 2020-2021, 884 patients (56.6% men, median (IQR) diabetes duration: 7 (3-12) years, current/ex-smokers: 32.5%, body mass index: 28.40±5.77 kg/m2, HbA1c: 7.52%±1.66%, insulin-treated: 27.7%) were assigned to JADE-only (n=443) or JADE-PRISM group (n=441). The profiles of the whole group included positive family history (74.7%), general obesity (51.4%), central obesity (79.2%), hypertension (66.7%), dyslipidemia (76.4%), albuminuria (35.4%), estimated glomerular filtration rate <60 mL/min/1.73 m2 (4.0%), retinopathy (13.8%), atherosclerotic cardiovascular disease (5.2%), cancer (3.1%), emotional distress (26%-38%) and suboptimal adherence (54%) with 5-item EuroQol for Quality of Life index of 0.88 (0.87-0.96). Overall, 13.7% attained ≥3 metabolic targets defined in secondary outcomes. In the JADE-PRISM group, 4.5% had pathogenic/likely pathogenic variants of monogenic diabetes genes; 5% had autoantibodies and 8.4% had fasting C-peptide <0.2 nmol/L. Other significant events included low/large birth weight (33.4%), childhood obesity (50.7%), mental illness (10.3%) and previous suicide attempts (3.6%). Among the women, 17.3% had polycystic ovary syndrome, 44.8% required insulin treatment during pregnancy and 17.3% experienced adverse pregnancy outcomes. CONCLUSIONS: Young-onset diabetes is characterized by complex etiologies with comorbidities including mental illness and lifecourse events. TRIAL REGISTRATION NUMBER: NCT04049149.

Patient-reported outcomes and treatment adherence in type 2 diabetes using natural language processing: Wave 8 of the Observational International Diabetes Management Practices Study.

AIMS/INTRODUCTION: We analyzed patient-reported outcomes of people with type 2 diabetes to better understand perceptions and experiences contributing to treatment adherence. MATERIALS AND METHODS: In the ongoing International Diabetes Management Practices Study, we collected patient-reported outcomes data from structured questionnaires (chronic treatment acceptance questionnaire and Diabetes Self-Management Questionnaire) and free-text answers to open-ended questions to assess perceptions of treatment value and side-effects, as well as barriers to, and enablers for, adherence and self-management. Free-text answers were analyzed by natural language processing. RESULTS: In 2018-2020, we recruited 2,475 patients with type 2 diabetes (43.3% insulin-treated, glycated hemoglobin (HbA1c) 8.0 ± 1.8%; 30.9% with HbA1c <7%) from 13 countries across Africa, the Middle East, Europe, Latin America and Asia. Mean ± standard deviation scores of chronic treatment acceptance questionnaire (acceptance of medication, rated out of 100) and Diabetes Self-Management Questionnaire (self-management, rated out of 10) were 87.8 ± 24.5 and 3.3 ± 0.9, respectively. Based on free-text analysis and coded responses, one in three patients reported treatment non-adherence. Overall, although most patients accepted treatment values and side-effects, self-management was suboptimal. Treatment duration, regimen complexity and disruption of daily routines were major barriers to adherence, whereas habit formation was a key enabler. Treatment-adherent patients were older (60 ± 11.6 vs 55 ± 11.7 years, P < 0.001), and more likely to have longer disease duration (12 ± 8.6 vs 10 ± 7.7 years, P < 0.001), exposure to diabetes education (73.1% vs 67.8%, P < 0.05), lower HbA1c (7.9 ± 1.8% vs 8.3 ± 1.9%, P < 0.001) and attainment of HbA1c <7% (29.7% vs 23.3%, P < 0.01). CONCLUSIONS: Patient perceptions/experiences influence treatment adherence and self-management. Patient-centered education and support programs that consider patient-reported outcomes aimed at promoting empowerment and developing new routines might improve glycemic control.

One-hour post-load plasma glucose level predicts future type 2 diabetes in a community-based study of Hong Kong Chinese workforce.

BACKGROUND: We compared performance of high 1-hour PG level, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) in predicting type 2 diabetes in a longitudinal community-based cohort of Hong Kong Chinese. METHODS: Between 2001 and 2003, 472 adults aged 18-55 years without diabetes underwent 75-gram oral glucose tolerance test (OGTT). Between 2012 and 2014, progression to diabetes was ascertained by reviewing medical records or repeating OGTT and HbA1c. We defined high 1-hour PG as PG ≥ 8.6 mmol/L at 1-hour. RESULTS: In this cohort, 23.5% had normal glucose tolerance and high 1-hour PG, 10.0% had isolated IGT, 4.2% had isolated IFG. Over 12-year follow-up, 9.3% developed type 2 diabetes. In logistic regression, high 1-hour PG was associated with progression to type 2 diabetes with adjusted odds ratio (95% CI) of 4.20 (1.60, 12.40), independent of IFG, IGT and other clinical variables. Areas under ROC (95% CI) for type 2 diabetes were similar between 1-hour (0.84 [0.78, 0.89], 2-hour (0.79 [0.72, 0.86]) and fasting PG (0.79 [0.71, 0.86]). CONCLUSION: High 1-hour PG identified young Chinese with 5-fold increased risk of type 2 diabetes independent of other intermediate hyperglycaemia status and clinical factors. 1-hour PG is similar to fasting and 2-hour PG in predicting type 2 diabetes.

Monogenic diabetes in a Chinese population with young-onset diabetes: A 17-year prospective follow-up study in Hong Kong.

AIMS: Asians have a high prevalence of young-onset diabetes, but the pattern of monogenic diabetes is unknown. We aimed to determine the prevalence of monogenic diabetes in Chinese patients with young-onset diabetes and compare the clinical characteristics and outcome between patients with and without monogenic diabetes. MATERIALS AND METHODS: We sequenced a targeted panel of 33 genes related to monogenic diabetes in 1021 Chinese patients with non-type 1 diabetes diagnosed at age ≤40 years. Incident complications including cardiovascular disease (CVD), end-stage kidney disease (ESKD) and all-cause death were captured since enrolment (1995-2012) until 2019. RESULTS: In this cohort (mean ± SD age at diagnosis: 33.0 ± 6.0 years, median[IQR] diabetes duration 7.0[1.0-15.0] years at baseline, 44.9% men), 22(2.2%, 95% confidence interval[CI] 1.4%-3.2%) had monogenic diabetes. Pathogenic (P) or likely pathogenic (LP) variants were detected in GCK (n = 6), HNF1A (n = 9), HNF4A (n = 1), PLIN1 (n = 1) and PPARG (n = 2), together with copy number variations in HNF1B (n = 3). Over a median follow-up of 17.1 years, 5(22.7%) patients with monogenic diabetes (incidence rate 12.3[95% CI 5.1-29.4] per 1000 person-years) versus 254(25.4%) without monogenic diabetes (incidence rate 16.7[95% CI 14.8-18.9] per 1000 person-years) developed the composite outcome of CVD, ESKD and/or death (p = 0.490). The multivariable Cox model did not show any difference in hazards for composite events between groups. CONCLUSIONS: In Chinese with young-onset non-type 1 diabetes, at least 2% of cases were contributed by monogenic diabetes, over 80% of which were accounted for by P/LP variants in common MODY genes. The incidence of diabetes complications was similar between patients with and without monogenic diabetes.

Association of dipeptidyl peptidase-4 inhibitor initiation at glycated haemoglobin <7.5% with reduced major clinical events mediated by low glycated haemoglobin variability.

AIM: Therapeutic inertia, hypoglycaemia and poor treatment persistence can lead to glycaemic fluctuation and poor outcomes in type 2 diabetes (T2D). We compared glycated haemoglobin (HbA1c) variability, insulin initiation, severe hypoglycaemia and clinical events in patients with T2D initiated dipeptidyl peptidase-4 inhibitors (DPP4is) at low versus high HbA1c thresholds. METHODS: Using territory-wide electronic medical records in Hong Kong, we curated a propensity score-matched cohort of patients initiated DPP4i at HbA1c <7.5% versus ≥7.5% in 2007-2019. We expressed the HbA1c variability score (HVS) as a proportion of HbA1c varied by ≥0.5% compared with preceding values. We used the Cox model to compare the risks of insulin initiation and clinical outcomes, adjusted for time-varying variables between the two groups. Mediation analysis estimated the effects of HbA1c variability on outcomes. RESULTS: Among 6874 insulin-naïve patients who initiated DPP4i, 88.7% were treated with metformin and 79.6% with sulphonylureas at baseline (54.9% men; mean age 65.2 ± 11.4 years). After a median follow-up of 4.6 years, compared with the high-threshold plus high-HVS group (≥50%), the low-threshold plus low-HVS (<50%) group had reduced hazard ratios (95% confidence interval) of insulin initiation (0.35, 0.31-0.40), severe hypoglycaemia (0.38, 0.34-0.44), major adverse cardiovascular endpoints (0.76, 0.66-0.88), heart failure (0.42, 0.36-0.49), end-stage kidney disease (0.65, 0.36-0.49) and mortality (0.45, 0.35-0.57). Reduced HbA1c variability explained 31.1%-81.2% of the effect size of DPP4i initiation at HbA1c <7.5% versus ≥7.5% on outcomes. CONCLUSIONS: In Chinese patients with T2D, avoiding therapeutic inertia with intensified glycaemic control at HbA1c <7.5% using drugs with low risk of hypoglycaemia and good tolerability, such as DPP4i, delayed insulin treatment, reduced HbA1c variability and improved clinical events.

Associations of comorbid depression with cardiovascular-renal events and all-cause mortality accounting for patient reported outcomes in individuals with type 2 diabetes: a 6-year prospective analysis of the Hong Kong Diabetes Register.

Background: Psychosocial status and patient reported outcomes (PRO) [depression and health-related quality-of-life (HRQoL)] are major health determinants. We investigated the association between depression and clinical outcomes in Chinese patients with type 2 diabetes (T2D), adjusted for PRO. Methods: Using prospective data from Hong Kong Diabetes Register (2013-2019), we estimated the hazard-ratio (HR, 95%CI) of depression (validated Patient Health Questionnaire 9 (PHQ-9) score≥7) with incident cardiovascular disease (CVD), ischemic heart disease (IHD), chronic kidney disease (CKD: eGFR<60 ml/min/1.73m2) and all-cause mortality in 4525 Chinese patients with T2D adjusted for patient characteristics, renal function, medications, self-care and HRQoL domains (mobility, self-care, usual activities, pain/discomfort, anxiety/depression measured by EQ-5D-3L) in linear-regression models. Results: In this cohort without prior events [mean ± SD age:55.7 ± 10.6, 43.7% women, median (IQR) disease duration of 7.0 (2.0-13.0) years, HbA1c, 7.2% (6.6%-8.20%), 26.4% insulin-treated], 537(11.9%) patients had depressive symptoms and 1923 (42.5%) patients had some problems with HRQoL at baseline. After 5.6(IQR: 4.4-6.2) years, 141 patients (3.1%) died, 533(11.8%) developed CKD and 164(3.6%) developed CVD. In a fully-adjusted model (model 4) including self-care and HRQoL, the aHR of depression was 1.99 (95% confidence interval CI):1.25-3.18) for CVD, 2.29 (1.25-4.21) for IHD. Depression was associated with all-cause mortality in models 1-3 adjusted for demographics, clinical characteristics and self-care, but was attenuated after adjusting for HRQoL (model 4- 1.54; 95%CI: 0.91-2.60), though HR still indicated same direction with important magnitude. Patients who reported having regular exercise (3-4 times per week) had reduced aHR of CKD [0.61 (0.41-0.89)]. Item 4 of PHQ-9 (feeling tired, little energy) was independently associated with all-cause mortality with aHR of 1.66 (1.30-2.12). Conclusion: Depression exhibits significant association with CVD, IHD, and all-cause mortality in patients with diabetes, adjusting for their HRQoL and health behaviors. Despite the association between depression and all-cause mortality attenuated after adjusting for HRQoL, the effect size remains substantial. The feeling of tiredness or having little energy, as assessed by item Q4 of the PHQ-9 questionnaire, was found to be significantly associated with an increased risk of all-cause mortality after covariate adjustments. Our findings emphasize the importance of incorporating psychiatric evaluations into holistic diabetes management.

Clinical outcomes following discontinuation of metformin in patients with type 2 diabetes and advanced chronic kidney disease in Hong Kong: a territory-wide, retrospective cohort and target trial emulation study.

Background: Current labelling advises discontinuation of metformin when estimated glomerular filtration rate (eGFR) < 30 ml/min/1.73 m2 due to increased risk of lactic acidosis. However, in real-world practice, the risk-benefit ratios remain uncertain. We examined the risk associations of discontinued-metformin use with cardiorenal and clinical outcomes in patients with type 2 diabetes (T2D) and advanced chronic kidney disease. Methods: In this territory-wide, retrospective cohort and target trial emulation study, we included Chinese patients attending the Hong Kong Hospital Authority (HA) and enrolled in the Risk-Assessment-and-Management-Programme-for-Diabetes-Mellitus (RAMP-DM) from 2002 to 2019. Patients were stratified by discontinuation of metformin within six months after reaching eGFR < 30 ml/min/1.73 m2 from January 1, 2002 to December 31, 2018, and followed up until December 31 2019. We excluded patients who had observational time <6 months from eGFR < 30 ml/min/1.73 m2, and had their eGFR measured during a hospitalisation episode due to acute kidney injury, or missing diagnosis date of diabetes. We compared the risk associations of metformin discontinuation with clinical outcomes. The primary outcomes were major adverse cardiovascular events (MACE), end-stage kidney disease (ESKD), cancer, and all-cause mortality. A Cox-model with time-dependent exposure and covariates was used to estimate the hazard ratio (HR) of outcomes in a propensity-score overlap-weighted cohort. The risk of occurrence of lactic acidosis (serum lactate > 5.0 mmol/L with a concomitant blood pH < 7.35 or ICD-9 codes of 276.2) in discontinued-metformin versus continued-metformin users was assessed in a separate register-based cohort. Findings: A total of 33,586 metformin users with new-onset eGFR < 30 ml/min/1.73 m2 were included in the study, 7500 (22.3%) of whom discontinued metformin within 6 months whereas 26,086 (77.7%) continued use of metformin. During a median follow-up of 3.8 (IQR: 2.2-6.1) years, 16.4% (5505/33,586), 30.1% (10,113/33,586), and 7.1% (2171/30,682) had incident MACE, ESKD, and cancer respectively, and 44.4% (14,917/33,586) died. Compared to continued-metformin use, discontinuation was associated with higher risk of MACE (weighted and adjusted HR = 1.40, 95% CI: 1.29-1.52), ESKD (HR = 1.52, 1.42-1.62), and death (HR = 1.22, 1.18-1.27). No association was observed for cancer (HR = 0.93, 0.85-1.01). Discontinued-metformin users had higher change in HbA1c change at 6-month of follow-up versus continued-metformin users (weighted mean HbA1c level change: 0.5% [0.4-0.6%] versus 0.2% [0.1-0.2]). In the separate register-based cohort (n = 3235), null association was observed between metformin use and risk of lactic acidosis (weighted HR = 0.94 [0.53-1.64]). Interpretation: Our results suggest that discontinuation of metformin in patients with T2D and chronic kidney disease may be associated with increased risk of cardiovascular-renal events. Use of metformin below eGFR of 30 ml/min/1.73 m2 may be associated with cardiovascular, renal, and mortality benefits that need to be weighed against the risk of lactic acidosis, but further research is needed to validate these findings. Funding: CUHK Impact Research Fellowship Scheme.

A novel electronic health record-based, machine-learning model to predict severe hypoglycemia leading to hospitalizations in older adults with diabetes: A territory-wide cohort and modeling study.

BACKGROUND: Older adults with diabetes are at high risk of severe hypoglycemia (SH). Many machine-learning (ML) models predict short-term hypoglycemia are not specific for older adults and show poor precision-recall. We aimed to develop a multidimensional, electronic health record (EHR)-based ML model to predict one-year risk of SH requiring hospitalization in older adults with diabetes. METHODS AND FINDINGS: We adopted a case-control design for a retrospective territory-wide cohort of 1,456,618 records from 364,863 unique older adults (age ≥65 years) with diabetes and at least 1 Hong Kong Hospital Authority attendance from 2013 to 2018. We used 258 predictors including demographics, admissions, diagnoses, medications, and routine laboratory tests in a one-year period to predict SH events requiring hospitalization in the following 12 months. The cohort was randomly split into training, testing, and internal validation sets in a 7:2:1 ratio. Six ML algorithms were evaluated including logistic-regression, random forest, gradient boost machine, deep neural network (DNN), XGBoost, and Rulefit. We tested our model in a temporal validation cohort in the Hong Kong Diabetes Register with predictors defined in 2018 and outcome events defined in 2019. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC) statistics, and positive predictive value (PPV). We identified 11,128 SH events requiring hospitalization during the observation periods. The XGBoost model yielded the best performance (AUROC = 0.978 [95% CI 0.972 to 0.984]; AUPRC = 0.670 [95% CI 0.652 to 0.688]; PPV = 0.721 [95% CI 0.703 to 0.739]). This was superior to an 11-variable conventional logistic-regression model comprised of age, sex, history of SH, hypertension, blood glucose, kidney function measurements, and use of oral glucose-lowering drugs (GLDs) (AUROC = 0.906; AUPRC = 0.085; PPV = 0.468). Top impactful predictors included non-use of lipid-regulating drugs, in-patient admission, urgent emergency triage, insulin use, and history of SH. External validation in the HKDR cohort yielded AUROC of 0.856 [95% CI 0.838 to 0.873]. Main limitations of this study included limited transportability of the model and lack of geographically independent validation. CONCLUSIONS: Our novel-ML model demonstrated good discrimination and high precision in predicting one-year risk of SH requiring hospitalization. This may be integrated into EHR decision support systems for preemptive intervention in older adults at highest risk.

Young-Onset Diabetes in East Asians: From Epidemiology to Precision Medicine.

Precision diagnosis is the keystone of clinical medicine. In East Asians, classical type 1 diabetes is uncommon in patients with youngonset diabetes diagnosed before age of 40, in whom a family history, obesity, and beta-cell and kidney dysfunction are key features. Young-onset diabetes affects one in five Asian adults with diabetes in clinic settings; however, it is often misclassified, resulting in delayed or non-targeted treatment. Complex aetiologies, long disease duration, aggressive clinical course, and a lack of evidence-based guidelines have contributed to variable care standards and premature death in these young patients. The high burden of comorbidities, notably mental illness, highlights the numerous knowledge gaps related to this silent killer. The majority of adult patients with youngonset diabetes are managed as part of a heterogeneous population of patients with various ages of diagnosis. A multidisciplinary care team led by physicians with special interest in young-onset diabetes will help improve the precision of diagnosis and address their physical, mental, and behavioral health. To this end, payors, planners, and providers need to align and re-design the practice environment to gather data systematically during routine practice to elucidate the multicausality of young-onset diabetes, treat to multiple targets, and improve outcomes in these vulnerable individuals.

Health impacts of new-onset diabetes in women post-gestational diabetes mellitus: Insights from Hong Kong's territory-wide data.

AIMS/INTRODUCTION: To determine the population health burden attributable to the development of diabetes among women with a history of gestational diabetes mellitus (GDM). MATERIALS AND METHODS: We conducted a retrospective analysis of women with a history of GDM attending the Hong Kong Hospital Authority between 2000 and 2019. The time-varying population attributable fraction was calculated. RESULTS: A total of 76,181 women with a history of gestational diabetes mellitus were included, 6,606 of them developed diabetes during a median follow-up of 8.6 years. The respective hazard ratios (95% confidence interval) among women with GDM who developed diabetes vs those with GDM only were 2.8 (2.2, 3.7) for cardiovascular disease (CVD), 4.8 (3.0, 7.7) for end-stage kidney disease (ESKD), 2.2 (1.9, 2.6) for infection-related hospitalization, and 1.8 (1.3, 2.4) for all-cause mortality. The development of diabetes was associated with 1.3 (0.8, 1.7), 0.6 (0.3, 0.8), 3.2 (2.4, 4.0), and 0.5 (0.2, 0.9) additional incident cases per 1,000 person-years, accounting for 24.0% (13.2%, 35.9%), 42.0% (22.5%, 58.8%), 10.8% (7.1%, 14.9%), and 6.0% (-3.1%, 16.1%) of absolute number of CVD, ESKD, infection-related hospitalization, and all-cause mortality over 20 years after GDM, respectively. CONCLUSIONS: Diabetes is a significant contributor to the population health burden of some clinical outcomes in women with a history of gestational diabetes mellitus, but other risk factors need to be considered.

International Diabetes Federation Position Statement on the 1-hour post-load plasma glucose for the diagnosis of intermediate hyperglycaemia and type 2 diabetes.

Many individuals with intermediate hyperglycaemia (IH), including impaired fasting glycaemia (IFG) and impaired glucose tolerance (IGT), as presently defined, will progress to type 2 diabetes (T2D). There is confirmatory evidence that T2D can be prevented by lifestyle modification and/or medications, in people with IGT diagnosed by 2-h plasma glucose (PG) during a 75-gram oral glucose tolerance test (OGTT). Over the last 40 years, a wealth of epidemiological data has confirmed the superior value of 1-h plasma glucose (PG) over fasting PG (FPG), glycated haemoglobin (HbA1c) and 2-h PG in populations of different ethnicity, sex and age in predicting diabetes and associated complications including death. Given the relentlessly rising prevalence of diabetes, a more sensitive, practical method is needed to detect people with IH and T2D for early prevention or treatment in the often lengthy trajectory to T2D and its complications. The International Diabetes Federation (IDF) Position Statement reviews findings that the 1-h post-load PG ≥ 155 mg/dL (8.6 mmol/L) in people with normal glucose tolerance (NGT) during an OGTT is highly predictive for detecting progression to T2D, micro- and macrovascular complications, obstructive sleep apnoea, cystic fibrosis-related diabetes mellitus, metabolic dysfunction-associated steatotic liver disease, and mortality in individuals with risk factors. The 1-h PG of 209 mg/dL (11.6 mmol/L) is also diagnostic of T2D. Importantly, the 1-h PG cut points for diagnosing IH and T2D can be detected earlier than the recommended 2-h PG thresholds. Taken together, the 1-h PG provides an opportunity to avoid misclassification of glycaemic status if FPG or HbA1c alone are used. The 1-h PG also allows early detection of high-risk people for intervention to prevent progression to T2D which will benefit the sizeable and growing population of individuals at increased risk of T2D. Using a 1-h OGTT, subsequent to screening with a non-laboratory diabetes risk tool, and intervening early will favourably impact the global diabetes epidemic. Health services should consider developing a policy for screening for IH based on local human and technical resources. People with a 1-h PG ≥ 155 mg/dL (8.6 mmol/L) are considered to have IH and should be prescribed lifestyle intervention and referred to a diabetes prevention program. People with a 1-h PG ≥ 209 mg/dL (11.6 mmol/L) are considered to have T2D and should have a repeat test to confirm the diagnosis of T2D and then referred for further evaluation and treatment. The substantive data presented in the Position Statement provides strong evidence for redefining current diagnostic criteria for IH and T2D by adding the 1-h PG.

Comparison of ß-Cell Function and Insulin Sensitivity Between Normal-Weight and Obese Chinese With Young-Onset Type 2 Diabetes.

Normal-weight individuals with usual-onset type 2 diabetes have reduced ß-cell function and greater insulin sensitivity compared with their obese counterparts. The relative contribution of ß-cell dysfunction and insulin resistance to young-onset type 2 diabetes (YOD) among normal-weight individuals is not well established. In 44 individuals with YOD (24 with normal weight and 20 with obesity) and 24 healthy control individuals with normoglycemia (12 with normal weight and 12 with obesity), we conducted 2-h 12 mmol/L hyperglycemic clamps to measure acute (0-10 min) and steady-state (100-120 min) insulin and C-peptide responses, as well as insulin sensitivity index. Normal-weight individuals with YOD had lower acute insulin response, steady-state insulin and C-peptide responses, and a higher insulin sensitivity index compared with their obese counterparts with YOD. Compared with BMI-matched healthy control individuals, normal-weight individuals with YOD had lower acute and steady-state insulin and C-peptide responses but a similar insulin sensitivity index. The impairment of steady-state ß-cell response relative to healthy control individuals was more pronounced in normal-weight versus obese individuals with YOD. In conclusion, normal-weight Chinese with YOD exhibited worse ß-cell function but preserved insulin sensitivity relative to obese individuals with YOD and BMI-matched healthy individuals with normoglycemia. The selection of glucose-lowering therapy should account for pathophysiological differences underlying YOD between normal-weight and obese individuals.

Trends in all-cause and cause-specific mortality in older adults with and without diabetes: A territory-wide analysis in one million older adults in Hong Kong.

AIMS: Direct comparisons of population-level trends in all-cause and cause-specific mortalities among older adults with and without diabetes are lacking. METHODS: We performed a territory-wide analysis of 1,142,000 unique older adults aged ≥ 65 years (31.7 % with diabetes) with at least one attendance in the Hong Kong Hospital Authority in 2014-2018. We used Joinpoint regression to describe trends of age- and sex-standardised all-cause and cause-specific mortalities (cardiovascular disease [CVD], cancer, and non-CVD and non-cancer) in older adults with and without diabetes. RESULTS: All-cause mortality decreased in older adults with (average annual percent change [AAPC] = -1.6, 95 % confidence interval [-2.7, -0.4]) and without (AAPC = -3.1 [-4.2, -2.1]) diabetes. Largest declines were seen for CVD-cause mortalities for people with and without diabetes (AAPC = -5.5 [-6.8, -4.1] vs AAPC = -5.8 [-8.6, -2.9], respectively). Cancer-cause mortalities were similar in both groups with no change. Men with diabetes showed less favourable improvements. An increasing mortality trend was seen only in the 65-69 age-group regardless of diabetes status. CONCLUSIONS: Mortality continued to decline in older adults with and without diabetes, mainly driven by a decline in CVD deaths, with no narrowing of the mortality gap. Our findings call for continued actions to address excess mortalities especially in older men with diabetes and younger older adults.

Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank.

AIMS/HYPOTHESIS: The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers. METHODS: From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts. RESULTS: At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts. CONCLUSIONS/INTERPRETATION: Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.

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.

1-year weight change after diabetes diagnosis and long-term incidence and sustainability of remission of type 2 diabetes in real-world settings in Hong Kong: An observational cohort study.

BACKGROUND: Clinical trials have demonstrated that remission of type 2 diabetes can be achieved following sustained weight loss. However, the feasibility of achieving diabetes remission through weight management in real-world settings remains unclear. In this study, we aimed to examine the association of weight change at 1 year after diabetes diagnosis with long-term incidence and sustainability of type 2 diabetes remission in real-world settings in Hong Kong. METHODS AND FINDINGS: This was a population-based observational cohort study. The territory-wide Risk Assessment and Management Programme for Diabetes Mellitus (RAMP-DM) provides regular comprehensive assessments of metabolic control and complication screening for people with diabetes in Hong Kong. We included 37,326 people with newly diagnosed type 2 diabetes who were enrolled in the RAMP-DM between 2000 and 2017, followed until 2019. Diabetes remission was defined as 2 consecutive HbA1c <6.5% measurements at least 6 months apart in the absence of glucose-lowering drugs (GLDs) and with no record of GLDs at least 3 months before these measurements. During a median follow-up of 7.9 years, 6.1% (2,279) of people achieved diabetes remission, with an incidence rate of 7.8 (95% CI: 7.5, 8.1) per 1,000 person-years. After adjusting for age at diabetes diagnosis, sex, assessment year, body mass index, other metabolic indices, smoking, alcohol drinking, and medication use, the hazard ratio (HR) for diabetes remission was 3.28 (95% CI: 2.75, 3.92; p < 0.001) for people with ≥10% weight loss within 1 year of diagnosis, 2.29 (95% CI: 2.03, 2.59; p < 0.001) for those with 5% to 9.9% weight loss, and 1.34 (95% CI: 1.22, 1.47; p < 0.001) for those with 0% to 4.9% weight loss compared to people with weight gain. During a median follow-up of 3.1 years, 67.2% (1,531) of people who had achieved diabetes remission returned to hyperglycaemia, with an incidence rate of 184.8 (95% CI: 175.5, 194.0) per 1,000 person-years. The adjusted HR for returning to hyperglycaemia was 0.52 (95% CI: 0.41, 0.65; p < 0.001) for people with ≥10% weight loss, 0.78 (95% CI: 0.68, 0.92; p = 0.002) for those with 5% to 9.9% weight loss, and 0.90 (95% CI: 0.80, 1.01; p = 0.073) for those with 0% to 4.9% weight loss compared to people with weight gain. Diabetes remission was associated with a 31% (HR: 0.69, 95% CI: 0.52, 0.93; p = 0.014) decreased risk of all-cause mortality. The main limitation of the study is that the reliability of HbA1c used to define diabetes remission can be affected by other medical conditions. Furthermore, we did not have data on bariatric surgery. CONCLUSIONS: In this study, greater weight loss within the first year of diabetes diagnosis was associated with an increased likelihood of achieving diabetes remission and a decreased risk of returning to hyperglycaemia among those who had achieved diabetes remission. However, both the incidence of diabetes remission and the probability of its long-term sustainability were low with conventional management in real-world settings, in an era when the importance of weight loss was not fully appreciated. Our study provides evidence for policymakers to design and implement early weight management interventions and diabetes remission initiatives.

Lessons and Applications of Omics Research in Diabetes Epidemiology.

PURPOSE OF REVIEW: Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies. RECENT FINDINGS: We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.