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  1. Tan JW, Gupta T, Manosroi W, Yao TM, Hopkins PN, Williams JS, et al.
    JCI Insight, 2017 12 07;2(23).
    PMID: 29212952 DOI: 10.1172/jci.insight.95992
    Compared with persons of European descent (ED), persons of African descent (AD) have lower aldosterone (ALDO) levels, with the assumption being that the increased cardiovascular disease (CVD) risk associated with AD is not related to ALDO. However, the appropriateness of the ALDO levels for the volume status in AD is unclear. We hypothesized that, even though ALDO levels are lower in AD, they are inappropriately increased, and therefore, ALDO could mediate the increased CVD in AD. To test this hypothesis, we analyzed data from HyperPATH - 1,788 individuals from the total cohort and 765 restricted to ED-to-AD in a 2:1 match and genotyped for the endothelin-1 gene (EDN1). Linear regression analyses with adjustments were performed. In the total and restricted cohorts, PRA, ALDO, and urinary potassium levels were significantly lower in AD. However, in the AD group, greater ALDO dysregulation was present as evidenced by higher ALDO/plasma renin activity (PRA) ratios (ARR) and sodium-modulated ALDO suppression-to-stimulation indices. Furthermore, EDN1 minor allele carriers had significantly greater ARRs than noncarriers but only in the AD group. ARR levels were modulated by a significant interaction between EDN1 and AD. Thus, EDN1 variants may identify particularly susceptible ADs who will be responsive to treatment targeting ALDO-dependent pathways (e.g., mineralocorticoid-receptor antagonists).
  2. Sang C, Yan H, Chan WK, Zhu X, Sun T, Chang X, et al.
    Front Med (Lausanne), 2021;8:637652.
    PMID: 33708783 DOI: 10.3389/fmed.2021.637652
    Non-alcoholic fatty liver disease (NAFLD) is one of the main causes of fibrosis. Liver biopsy remains the gold standard for the confirmation of fibrosis in NAFLD patients. Effective and non-invasive diagnosis of advanced fibrosis is essential to disease surveillance and treatment decisions. Herein we used routine medical test markers and logistic regression to differentiate early and advanced fibrosis in NAFLD patients from China, Malaysia, and India (n1 = 540, n2 = 147, and n3 = 97) who were confirmed by liver biopsy. Nine parameters, including age, body mass index, fasting blood glucose, presence of diabetes or impaired fasting glycemia, alanine aminotransferase, γ-glutamyl transferase, triglyceride, and aspartate transaminase/platelet count ratio, were selected by stepwise logistic regression, receiver operating characteristic curve (ROC), and hypothesis testing and were used for model construction. The area under the ROC curve (auROC) of the model was 0.82 for differentiating early and advanced fibrosis (sensitivity = 0.69, when specificity = 0.80) in the discovery set. Its diagnostic ability remained good in the two independent validation sets (auROC = 0.89 and 0.71) and was consistently superior to existing panels such as the FIB-4 and NAFLD fibrosis score. A web-based tool, LiveFbr, was developed for fast access to our model. The new model may serve as an attractive tool for fibrosis classification in NAFLD patients.
  3. Kong APS, Lew T, Lau ESH, Lim LL, Kesavadev J, Jia W, et al.
    Diabetes Obes Metab, 2020 04;22(4):669-679.
    PMID: 31903728 DOI: 10.1111/dom.13950
    AIMS: To explore the pattern of insulin use and glycaemic control in Asian people with type 2 diabetes, stratified by gender, young-onset diabetes (YOD; diagnosed before age 40 years), and diabetic kidney disease (DKD; estimated glomerular filtration rate [eGFR] 
  4. Sheng B, Guan Z, Lim LL, Jiang Z, Mathioudakis N, Li J, et al.
    Sci Bull (Beijing), 2024 Jan 04.
    PMID: 38220476 DOI: 10.1016/j.scib.2024.01.004
  5. Sheng B, Pushpanathan K, Guan Z, Lim QH, Lim ZW, Yew SME, et al.
    Lancet Diabetes Endocrinol, 2024 Aug;12(8):569-595.
    PMID: 39054035 DOI: 10.1016/S2213-8587(24)00154-2
    Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise care for people with diabetes and adapt treatments for complex presentations. However, the rapid advancement of AI also introduces challenges such as potential biases, ethical considerations, and implementation challenges in ensuring that its deployment is equitable. Ensuring inclusive and ethical developments of AI technology can empower both health-care providers and people with diabetes in managing the condition. In this Review, we explore and summarise the current and future prospects of AI across the diabetes care continuum, from enhancing screening and diagnosis to optimising treatment and predicting and managing complications.
  6. Lim LL, Lau ESH, Kong APS, Fu AWC, Lau V, Jia W, et al.
    Lancet Reg Health West Pac, 2023 Mar;32:100663.
    PMID: 36785858 DOI: 10.1016/j.lanwpc.2022.100663
    BACKGROUND: In Asia, diabetes-associated death due to cardiorenal diseases were 2-3 times higher in women than men which might be due to gender disparity in quality of care and health habits.

    METHODS: Adults with type 2 diabetes (T2D) from 11 Asian countries/areas were assessed using the same protocol (2007-2015). We compared treatment target attainment (HbA1c < 7%, blood pressure [BP] < 130/80 mmHg, risk-based LDL-cholesterol, lack of central obesity [waist circumference <90 cm in men or <80 cm in women), use of cardiorenal-protective drugs (renin-angiotensin system [RAS] inhibitors, statins), and self-reported health habits including self-monitoring blood glucose (SMBG) by gender. Analyses were stratified by countries/areas, age of natural menopause (<50 vs. ≥50 years), and comorbidities (atherosclerotic cardiovascular disease [ASCVD], heart failure, kidney impairment [eGFR < 60 mL/min/1.73 m2]).

    FINDINGS: Among 106,376 patients (53.2% men; median (interquartile range) diabetes duration: 6.0 (2.0-12.0) years; mean ± SD HbA1c 8.0 ± 1.9%; 27% insulin-treated), women were older and less likely to receive college education than men (28.9% vs. 48.8%). Women were less likely to smoke/drink alcohol and were physically less active than men. Women had lower BP (<130/80 mmHg: 29.4% vs. 25.7%), less general obesity (54.8% vs. 57.8%) but more central obesity than men (77.5% vs. 57.3%). Women were less likely to have ASCVD (12.8% vs. 17.0%) or heart failure (1.3% vs. 2.3%), but more likely to have kidney impairment (22.3% vs. 17.6%) and any-site cancer than men (2.5% vs. 1.6%). In most countries/areas, more men attained HbA1c <7% and risk-based LDL-cholesterol level than women. After adjusting for potential confounders including countries and centres, men had 1.63 odds ratio (95% CI 1.51, 1.74) of attaining ≥3 treatment targets than women.

    INTERPRETATION: Asian women with T2D had worse quality of care than men especially in middle-income countries/areas, calling for targeted implementation programs to close these care gaps.

    SPONSOR: Asia Diabetes Foundation.

    FUNDING: Nil.

  7. Lawrenson K, Song F, Hazelett DJ, Kar SP, Tyrer J, Phelan CM, et al.
    Gynecol Oncol, 2019 05;153(2):343-355.
    PMID: 30898391 DOI: 10.1016/j.ygyno.2019.02.023
    OBJECTIVE: Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women.

    METHODS: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations.

    RESULTS: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7).

    CONCLUSION: While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

  8. Ma RC, Hu C, Tam CH, Zhang R, Kwan P, Leung TF, et al.
    Diabetologia, 2013 Jun;56(6):1291-305.
    PMID: 23532257 DOI: 10.1007/s00125-013-2874-4
    AIMS/HYPOTHESIS: Most genetic variants identified for type 2 diabetes have been discovered in European populations. We performed genome-wide association studies (GWAS) in a Chinese population with the aim of identifying novel variants for type 2 diabetes in Asians.

    METHODS: We performed a meta-analysis of three GWAS comprising 684 patients with type 2 diabetes and 955 controls of Southern Han Chinese descent. We followed up the top signals in two independent Southern Han Chinese cohorts (totalling 10,383 cases and 6,974 controls), and performed in silico replication in multiple populations.

    RESULTS: We identified CDKN2A/B and four novel type 2 diabetes association signals with p 

  9. Li J, Guan Z, Wang J, Cheung CY, Zheng Y, Lim LL, et al.
    Nat Med, 2024 Jul 19.
    PMID: 39030266 DOI: 10.1038/s41591-024-03139-8
    Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP's accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n = 397) with those under the PCP+DeepDR-LLM arm (n = 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P 
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