Identification of type 2 diabetes loci in 433,540 East Asian individuals.

Meta-analyses of genome-wide association studies (GWAS) have identified more than 240 loci that are associated with type 2 diabetes (T2D)1,2; however, most of these loci have been identified in analyses of individuals with European ancestry. Here, to examine T2D risk in East Asian individuals, we carried out a meta-analysis of GWAS data from 77,418 individuals with T2D and 356,122 healthy control individuals. In the main analysis, we identified 301 distinct association signals at 183 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 61 loci that are newly implicated in predisposition to T2D. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. Previously undescribed associations include signals in or near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect the differentiation of muscle and adipose cells3. At another locus, expression quantitative trait loci at two overlapping T2D signals affect two genes-NKX6-3 and ANK1-in different tissues4-6. Association studies in diverse populations identify additional loci and elucidate disease-associated genes, biology, and pathways.

Glycaemic control is still central in the hierarchy of priorities in type 2 diabetes management.

A panel of primary care and diabetes specialists conducted focused literature searches on the current role of glycaemic control in the management of type 2 diabetes and revisited the evolution of evidence supporting the importance of early and intensive blood glucose control as a central strategy to reduce the risk of adverse long-term outcomes. The optimal approach to type 2 diabetes management has evolved over time as the evidence base has expanded from data from trials that established the role of optimising glycaemic control to recent data from cardiovascular outcomes trials (CVOTs) demonstrating organ-protective effects of newer glucose-lowering drugs (GLDs). The results from these CVOTs were derived mainly from people with type 2 diabetes and prior cardiovascular and kidney disease or multiple risk factors. In more recent years, earlier diagnosis in high-risk individuals has contributed to the large proportion of people with type 2 diabetes who do not have complications. In these individuals, a legacy effect of early and optimal control of blood glucose and cardiometabolic risk factors has been proven to reduce cardiovascular and kidney disease events and all-cause mortality. As there is a lack of RCTs investigating the potential synergistic effects of intensive glucose control and organ-protective effects of newer GLDs, this article re-evaluates the evolution of the scientific evidence and highlights the importance of integrating glycaemic control as a pivotal early therapeutic goal in most people with type 2 diabetes, while targeting existing cardiovascular and kidney disease. We also emphasise the importance of implementing multifactorial management using a multidisciplinary approach to facilitate regular review, patient empowerment and the possibility of tailoring interventions to account for the heterogeneity of type 2 diabetes.

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.

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.

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.

Higher risk of incident diabetes among patients with primary hyperparathyroidism.

OBJECTIVES: There is relatively scarce data regarding the association between primary hyperparathyroidism (PHPT) and incident diabetes in large population-based longitudinal studies. We aimed to evaluate the risk of incident diabetes in individuals with and without PHPT and investigate the association between serum calcium concentrations and the risk of incident diabetes in patients with PHPT. METHODS: We included 2749 PHPT patients and 13,745 age, sex and index year matched non-PHPT individuals during 2000-2019. We used Cox regression models to compare the risk of incident diabetes in individuals with and without PHPT, and the risk of incident diabetes in PHPT patients with serum calcium concentration above and below the median value. The association between serum calcium concentrations and the risk of incident diabetes was examined by restricted cubic spline analyses in patients with PHPT. RESULTS: During a median follow-up time of 5.17 years (IQR 2.17, 9.58), 433 patients (15.75%) with PHPT and 2110 individuals (15.35%) without PHPT developed diabetes, respectively. Patients with PHPT had a higher incidence rate of diabetes compared to non-PHPT individuals (27.60 [95% CI 25.00, 30.30] vs. 23.90 [95% CI 22.80, 24.90] per 1000 person-years, log-rank test p = .007]. Crude Cox regression model showed PHPT was associated with a 15% higher risk of incident diabetes (HR 1.15, 95%CI 1.04, 1.28). In patients with PHPT, a 44% higher risk of incident diabetes was found in patients with serum calcium concentrations above the median value (2.63 mmol/L), compared to those below the median value (HR 1.44, 95%CI 1.08, 1.90). Restricted cubic spline analyses confirmed a positive linear association between serum calcium concentrations and the risk of incident diabetes in those with PHPT (p-value for nonlinear = .751) CONCLUSIONS: Patients with PHPT had a higher risk of incident diabetes compared to non-PHPT individuals. A positive linear association was found between serum calcium concentrations and the risk of incident diabetes in patients with PHPT.

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.

Early treatment with dipeptidyl-peptidase 4 inhibitors reduces glycaemic variability and delays insulin initiation in type 2 diabetes: A propensity score-matched cohort study.

AIMS: To examine whether early treatment intensification using dipeptidyl-peptidase 4 inhibitors (DPP4i) delays insulin initiation in Chinese patients diagnosed with type 2 diabetes for less than 5 years. MATERIALS AND METHODS: In a territory-wide prospective cohort study, patients with type 2 diabetes initiating DPP4i at diabetes duration <2 years (early intensification) and 3-5 years (late intensification) were matched using 1:1 propensity-score matching (n = 908 in each arm). We used Cox regression to compare the risk of insulin initiation between the two groups. We explored the interactive and mediation effects of glycated haemoglobin (HbA1c) variability score (HVS), defined as the percentage of HbA1c varying by ≥0.5% compared with preceding values. RESULTS: Of 1816 patients (60.7% men, mean age 54.4 ± 11.9 years), 92.4% and 71.9% were treated with metformin and sulphonylureas respectively at DPP4i initiation. Early DPP4i intensification [hazard ratio (HR) 0.71, (95% CI 0.58-0.68)] and low HVS (<50%) (HR = 0.40, 0.33-0.50) were associated with delayed insulin initiation during a median 4.08 years of follow-up. Early intensification with low HVS had the lowest risk versus late intensification with high HVS (HR = 0.30, 0.22-0.40) (pinteraction  = 0.013). HVS mediated 19.5% of the total effect of early DPP4i intensification on delaying insulin initiation. The late and early intensification groups had similar HbA1c at month 0 (8.4 ± 1.3% vs. 8.4 ± 1.5%) and month 3 (7.6 ± 1.2% vs. 7.6 ± 1.3%) after DPP4i initiation. By month 12, HbA1c in the late intensification group deteriorated (7.9 ± 1.4%) but remained stable in the early intensification group (7.6 ± 1.4%, p = 0.001) with persistent between-group difference over 72 months (8.2 ± 1.7% vs. 7.7 ± 1.6%, p = 0.001). CONCLUSIONS: In type 2 diabetes, early DPP4i intensification delayed insulin initiation, partially explained by reduced glycaemic variability.

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.

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.

Current type 2 diabetes guidelines: Individualized treatment and how to make the most of metformin.

Evidence-based guidelines provide the premise for the delivery of quality care to preserve health and prevent disabilities and premature death. The systematic gathering of observational, mechanistic and experimental data contributes to the hierarchy of evidence used to guide clinical practice. In the field of diabetes, metformin was discovered more than 100 years ago, and with 60 years of clinical use, it has stood the test of time regarding its value in the prevention and management of type 2 diabetes. Although some guidelines have challenged the role of metformin as the first-line glucose-lowering drug, it is important to point out that the cardiovascular-renal protective effects of sodium-glucose co-transporter-2 inhibitors and glucagon-like peptide-1 receptor agonists were gathered from patients with type 2 diabetes, the majority of whom were treated with metformin. Most national, regional and international guidelines recommend metformin as a foundation therapy with emphasis on avoidance of therapeutic inertia and early attainment of multiple treatment goals. Moreover, real-world evidence has confirmed the glucose-lowering and cardiovascular-renal benefits of metformin accompanied by an extremely low risk of lactic acidosis. In patients with type 2 diabetes and advanced chronic kidney disease (estimated glomerular filtration rate 15-30 mL/min/1.73m2), metformin discontinuation was associated with an increased risk of cardiovascular-renal events compared with metformin persistence. Meanwhile, it is understood that microbiota, nutrients and metformin can interact through the gut-brain-kidney axis to modulate homeostasis of bioactive molecules, systemic inflammation and energy metabolism. While these biological changes contribute to the multisystem effects of metformin, they may also explain the gastrointestinal side effects and vitamin B12 deficiency associated with metformin intolerance. By understanding the interactions between metformin, foods and microbiota, healthcare professionals are in a better position to optimize the use of metformin and mitigate potential side effects. The United Kingdom Prospective Diabetes Study and the Da Qing Diabetes Prevention Program commenced 40 years ago provided the first evidence that type 2 diabetes is preventable and treatable. To drive real-world impact from this evidence, payors, practitioners and planners need to co-design and implement an integrated, data-driven, metformin-based programme to detect people with undiagnosed diabetes and prediabetes (intermediate hyperglycaemia), notably impaired glucose tolerance, for early intervention. The systematic data collection will create real-world evidence to bring out the best of metformin and make healthcare sustainable, affordable and accessible.

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.

Diabetes Management in Chronic Kidney Disease: Synopsis of the KDIGO 2022 Clinical Practice Guideline Update.

DESCRIPTION: The KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease is an update of the 2020 guideline from Kidney Disease: Improving Global Outcomes (KDIGO). METHODS: The KDIGO Work Group updated the guideline, which included reviewing and grading new evidence that was identified and summarized. As in the previous guideline, the Work Group used the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach to appraise evidence and rate the strength of recommendations and expert judgment to develop consensus practice points. New evidence led to updating of recommendations in the chapters Comprehensive Care in Patients With Diabetes and CKD (Chapter 1) and Glucose-Lowering Therapies in Patients With T2D and CKD (Chapter 4). New evidence did not change recommendations in the chapters Glycemic Monitoring and Targets in Patients With Diabetes and CKD (Chapter 2), Lifestyle Interventions in Patients With Diabetes and CKD (Chapter 3), and Approaches to Management of Patients With Diabetes and CKD (Chapter 5). RECOMMENDATIONS: The updated guideline includes 13 recommendations and 52 practice points for clinicians caring for patients with diabetes and chronic kidney disease (CKD). A focus on preserving kidney function and maintaining well-being is recommended using a layered approach to care, starting with a foundation of lifestyle interventions, self-management, and first-line pharmacotherapy (such as sodium-glucose cotransporter-2 inhibitors) demonstrated to improve clinical outcomes. To this are added additional drugs with heart and kidney protection, such as glucagon-like peptide-1 receptor agonists and nonsteroidal mineralocorticoid receptor antagonists, and interventions to control risk factors for CKD progression and cardiovascular events, such as blood pressure, glycemia, and lipids.

Age-specific population attributable risk factors for all-cause and cause-specific mortality in type 2 diabetes: An analysis of a 6-year prospective cohort study of over 360,000 people in Hong Kong.

BACKGROUND: The prevalence of type 2 diabetes has increased in both young and old people. We examined age-specific associations and population attributable fractions (PAFs) of risk factors for all-cause and cause-specific mortality in people with type 2 diabetes. METHODS AND FINDINGS: We analysed data from 360,202 Chinese with type 2 diabetes who participated in a territory-wide diabetes complication screening programme in Hong Kong between January 2000 and December 2019. We compared the hazard ratios and PAFs of eight risk factors, including three major comorbidities (cardiovascular disease [CVD], chronic kidney disease [CKD], all-site cancer) and five modifiable risk factors (suboptimal HbA1c, suboptimal blood pressure, suboptimal low-density lipoprotein cholesterol, smoking, and suboptimal weight), for mortality across four age groups (18 to 54, 55 to 64, 65 to 74, and ≥75 years). During a median 6.0 years of follow-up, 44,396 people died, with cancer, CVD, and pneumonia being the leading causes of death. Despite a higher absolute mortality risk in older people (crude all-cause mortality rate: 59.7 versus 596.2 per 10,000 person-years in people aged 18 to 54 years versus those aged ≥75 years), the relative risk of all-cause and cause-specific mortality associated with most risk factors was higher in younger than older people, after mutually adjusting for the eight risk factors and other potential confounders including sex, diabetes duration, lipid profile, and medication use. The eight risk factors explained a larger proportion of mortality events in the youngest (PAF: 51.6%, 95% confidence interval [CI] [39.1%, 64.0%], p < 0.001) than the oldest (PAF: 35.3%, 95% CI [27.2%, 43.4%], p < 0.001) age group. Suboptimal blood pressure (PAF: 16.9%, 95% CI [14.7%, 19.1%], p < 0.001) was the leading attributable risk factor for all-cause mortality in the youngest age group, while CKD (PAF: 15.2%, 95% CI [14.0%, 16.4%], p < 0.001) and CVD (PAF: 9.2%, 95% CI [8.3%, 10.1%], p < 0.001) were the leading attributable risk factors in the oldest age group. The analysis was restricted to Chinese, which might affect the generalisability to the global population with differences in risk profiles. Furthermore, PAFs were estimated under the assumption of a causal relationship between risk factors and mortality. However, reliable causality was difficult to establish in the observational study. CONCLUSIONS: Major comorbidities and modifiable risk factors were associated with a greater relative risk for mortality in younger than older people with type 2 diabetes and their associations with population mortality burden varied substantially by age. These findings highlight the importance of early control of blood pressure, which could reduce premature mortality in young people with type 2 diabetes and prevent the onset of later CKD and related mortality at older ages.

Age- and sex-specific hospital bed-day rates in people with and without type 2 diabetes: A territory-wide population-based cohort study of 1.5 million people in Hong Kong.

BACKGROUND: Type 2 diabetes affects multiple systems. We aimed to compare age- and sex-specific rates of all-cause and cause-specific hospital bed-days between people with and without type 2 diabetes. METHODS AND FINDINGS: Data were provided by the Hong Kong Hospital Authority. We included 1,516,508 one-to-one matched people with incident type 2 diabetes (n = 758,254) and those without diabetes during the entire follow-up period (n = 758,254) between 2002 and 2018, followed until 2019. People with type 2 diabetes and controls were matched for age at index date (±2 years), sex, and index year (±2 years). We defined hospital bed-day rate as total inpatient bed-days divided by follow-up time. We constructed negative binominal regression models to estimate hospital bed-day rate ratios (RRs) by age at diabetes diagnosis and sex. All RRs were stratified by sex and adjusted for age and index year. During a median of 7.8 years of follow-up, 60.5% (n = 459,440) of people with type 2 diabetes and 56.5% (n = 428,296) of controls had a hospital admission for any cause, with a hospital bed-day rate of 3,359 bed-days and 2,350 bed-days per 1,000 person-years, respectively. All-cause hospital bed-day rate increased with increasing age in controls, but showed a J-shaped relationship with age in people with type 2 diabetes, with 38.4% of bed-days in those diagnosed <40 years caused by mental health disorders. Type 2 diabetes was associated with increased risks for a wide range of medical conditions, with an RR of 1.75 (95% CI [confidence interval] [1.73, 1.76]; p < 0.001) for all-cause hospital bed-days in men and 1.87 (95% CI [1.85, 1.89]; p < 0.001) in women. The RRs were greater in people with diabetes diagnosed at a younger than older age and varied by sex according to medical conditions. Sex differences were most notable for a higher RR for urinary tract infection and peptic ulcer, and a lower RR for chronic kidney disease and pancreatic disease in women than men. The main limitation of the study was that young people without diabetes in the database were unlikely to be representative of those in the Hong Kong general population with potential selection bias due to inclusion of individuals in need of medical care. CONCLUSIONS: In this study, we observed that type 2 diabetes was associated with increased risks of hospital bed-days for a wide range of medical conditions, with an excess burden of mental health disorders in people diagnosed at a young age. Age and sex differences should be considered in planning preventive and therapeutic strategies for type 2 diabetes. Effective control of risk factors with a focus on mental health disorders are urgently needed in young people with type 2 diabetes. Healthcare systems and policymakers should consider allocating adequate resources and developing strategies to meet the mental health needs of young people with type 2 diabetes, including integrating mental health services into diabetes care.

Real world evidence of clinical predictors of glycaemic response to glucose-lowering drugs among Chinese with type 2 diabetes.

AIMS: To examine whether simple clinical features can predict the 1-year glycaemic response to glucose-lowering drugs (GLDs) among Chinese with type 2 diabetes. MATERIALS AND METHODS: We used data from a diabetes risk assessment and complication screening programme and electronic medical records. We used linear regression models to examine the association between clinical features and 1-year glycaemic response to GLDs. RESULTS: Use of metformin (n = 15,433), sulphonylureas (SU) (n = 15,190), dipeptidyl peptidase-4 inhibitor (DPP-4i) (n = 7947), thiazolidinedione (TZD) (n = 4107), and sodium-glucose cotransporter 2 inhibitors (SGLT-2i) (n = 1883) were associated with a mean reduction of HbA1c ranging from 0.7% to 1.3% at one year. Men had a greater response to SU but a poorer response to metformin and TZD. Older age predicted a better response to all GLDs but not SGLT-2i, whereas increasing diabetes duration was associated with a poorer response to all GLDs except for DPP-4i. Obese patients responded greater to TZD and SGLT-2i but poorer to SU than those with normal weight. Patients with a higher level of triglycerides to high-density lipoprotein cholesterol ratio had a greater glycaemic response to TZD but a smaller response to SU and DPP-4i. CONCLUSIONS: Glycaemic response to GLDs differed considerably by clinical features among Chinese patients with type 2 diabetes.

Team-Based Diabetes Care in Ontario and Hong Kong: a Comparative Review.

PURPOSE OF REVIEW: There are gaps in implementing and accessing team-based diabetes care. We reviewed and compared how team-based diabetes care was implemented in the primary care contexts of Ontario and Hong Kong. RECENT FINDINGS: Ontario's Diabetes Education Programs (DEPs) were scaled-up incrementally. Hong Kong's Multidisciplinary Risk Assessment and Management Program for Diabetes Mellitus (RAMP-DM) evolved from a research-driven quality improvement program. Each jurisdiction had a mixture of non-team and team-based primary care with variable accessibility. Referral procedures, follow-up processes, and financing models varied. DEPs used a flexible approach, while the RAMP-DM used structured assessment for quality assurance. Each approach depended on adequate infrastructure, processes, and staff. Diabetes care is most accessible and functional when integrated team-based services are automatically initiated upon diabetes diagnosis within a strong primary care system, ideally linked to a register with supports including specialist care. Structured assessment and risk stratification are the basis of a well-studied, evidence-based approach for achieving the standards of team-based diabetes care, although flexibility in care delivery may be needed to meet the unique needs of some individuals. Policymakers and funders should ensure investment in skilled health professionals, infrastructure, and processes to improve care quality.

Real-world usage of sulphonylureas in Asian patients with type 2 diabetes using the Joint Asia Diabetes Evaluation (JADE) register.

AIMS: To explore the patterns of use of oral glucose-lowering drugs (OGLDs) in Asian patients with type 2 diabetes (T2D), focusing on sulphonylureas (SUs), and to describe patient profiles according to treatment regimen. METHODS: We conducted a cross-sectional analysis of data from adults with T2D from 11 Asian countries/regions with structured assessment enrolled in the prospective Joint Asia Diabetes Evaluation (JADE) register between November 2007 and December 2019. Patients receiving insulin and/or injectable glucagon-like peptide-1 receptor agonists were excluded. RESULTS: Amongst 62 512 patients (mean ± standard deviation age: 57.3 ± 11.8 years; 53.6% men), 54 783 (87.6%) were treated with OGLDs at enrolment. Most received one (37.5%) or two (44.2%) OGLDs. In the entire cohort, 59.4% of treated patients received SU-based therapy with variations amongst countries/regions. Overall, 79.5% of SU regimens were based on SUs plus metformin, and 22.1% on SUs plus dipeptidyl peptidase-4 inhibitors. Among SU users, gliclazide was most commonly prescribed (46.7%), followed by glimepiride (40.0%) and glibenclamide (8.1%). More gliclazide users entered the cohort with glycated haemoglobin levels <53 mmol/mol (7%) than non-gliclazide SU users (odds ratio [OR] 1.09, 95% CI 1.02-1.17), with less frequent self-reported hypoglycaemia in the 3 months before registration (OR 0.81, 95% CI 0.72-0.92; adjusted for sociodemographic factors, cardiometabolic risk factors, complications, use of other OGLDs, country/region and year of registration). CONCLUSION: In Asia, SUs are a popular OGLD class, often combined with metformin. Good glycaemic control and safety profiles associated with the use of SUs, including gliclazide, support their position as a key treatment option in patients with T2D.

Relative leucocyte telomere length is associated with incident end-stage kidney disease and rapid decline of kidney function in type 2 diabetes: analysis from the Hong Kong Diabetes Register.

AIMS/HYPOTHESIS: Few large-scale prospective studies have investigated associations between relative leucocyte telomere length (rLTL) and kidney dysfunction in individuals with type 2 diabetes. We examined relationships between rLTL and incident end-stage kidney disease (ESKD) and the slope of eGFR decline in Chinese individuals with type 2 diabetes. METHODS: We studied 4085 Chinese individuals with type 2 diabetes observed between 1995 and 2007 in the Hong Kong Diabetes Register with stored baseline DNA and available follow-up data. rLTL was measured using quantitative PCR. ESKD was diagnosed based on the ICD-9 code and eGFR. RESULTS: In this cohort (mean ± SD age 54.3 ± 12.6 years) followed up for 14.1 ± 5.3 years, 564 individuals developed incident ESKD and had shorter rLTL at baseline (4.2 ± 1.2 vs 4.7 ± 1.2, p < 0.001) than the non-progressors (n = 3521). On Cox regression analysis, each ∆∆Ct decrease in rLTL was associated with an increased risk of incident ESKD (HR 1.21 [95% CI 1.13, 1.30], p < 0.001); the association remained significant after adjusting for baseline age, sex, HbA1c, lipids, renal function and other risk factors (HR 1.11 [95% CI 1.03, 1.19], p = 0.007). Shorter rLTL at baseline was associated with rapid decline in eGFR (>4% per year) during follow-up (unadjusted OR 1.22 [95% CI 1.15, 1.30], p < 0.001; adjusted OR 1.09 [95% CI 1.01, 1.17], p = 0.024). CONCLUSIONS/INTERPRETATION: rLTL is independently associated with incident ESKD and rapid eGFR loss in individuals with type 2 diabetes. Telomere length may be a useful biomarker for the progression of kidney function and ESKD in type 2 diabetes.

Lifetime risk of developing diabetes in Chinese people with normoglycemia or prediabetes: A modeling study.

BACKGROUND: Little is known about the lifetime risk of progression to diabetes in the Asian population. We determined remaining lifetime risk of diabetes and life years spent with diabetes in Chinese people with normoglycemia and prediabetes. METHODS AND FINDINGS: Using territory-wide diabetes surveillance data curated from electronic medical records of Hong Kong Hospital Authority (HA), we conducted a population-based cohort study in 2,608,973 individuals followed from 2001 to 2019. Prediabetes and diabetes were identified based on laboratory measurements, diagnostic codes, and medication records. Remaining lifetime risk and life years spent with diabetes were estimated using Monte Carlo simulations with state transition probabilities based on a Markov chain model. Validations were performed using several sensitivity analyses and modified survival analysis. External replication was performed using the China Health and Retirement Longitudinal Survey (CHARLS) cohort (2010 to 2015). The expected remaining lifetime risk of developing diabetes was 88.0 (95% confidence intervals: 87.2, 88.7)% for people with prediabetes and 65.9 (65.8, 65.9)% for people with normoglycemia at age 20 years. A 20-year-old person with prediabetes would live with diabetes for 32.5 (32.0, 33.1) years or 51.6 (50.8, 52.3)% of remaining life years, whereas a person with normoglycemia at 20 years would live 12.7 (12.7, 12.7) years with diabetes or 18.4 (18.4, 18.5)% of remaining life years. Women had a higher expected remaining lifetime risk and longer life years with diabetes compared to men. Results are subjected to possible selection bias as only people who undertook routine or opportunistic screening were included. CONCLUSIONS: These findings suggest that Hong Kong, an economically developed city in Asia, is confronted with huge challenge of high lifetime risk of diabetes and long life years spent with diabetes, especially in people with prediabetes. Effective public health policies and targeted interventions for preventing progression to diabetes are urgently needed.