OBJECTIVES

In Asia, younger individuals (below age 45) are diagnosed to have type 2 diabetes with increased rates of obesity defined by lower BMI yet with greater visceral adiposity (waist circumference and waisthip ratios). The prevalence data on type 1 diabetes is not well established, considered to be low, but is seen to be increasing as well. This changing phenotype therefore, presents a clinical dilemma in terms of correctly classifying diabetes and deciding on the consequent appropriate treatment. Distinguishing type 1 from type 2 diabetes has become more difficult with type 2 diabetes dramatically increasing in young adults and children. This study aims to define the characteristics of diabetes among young adults in the Philippines to provide a basis for appropriate management amidst changes in diabetes phenotypes seen globally.

METHODS

In this cross-sectional analytic study, we characterized the demographic, metabolic, and autoimmune features of diabetes among young adult Filipinos aged 18 to 45 years old consulting at a tertiary referral center in Manila, Philippines. Baseline serum A1c, FBS, 75-g oral glucose tolerance test, insulin, serum C-peptide, insulin autoantibodies, leptin, adiponectin, lipid profile, and thyroid function tests were obtained from the participants and analyzed. The homeostasis model assessment (HOMA) was used to estimate the insulin sensitivity.

RESULTS

A total of 348 patients with diabetes were included, with females comprising two-thirds of the participants. The mean age at diagnosis of diabetes was 35.9±7.22 years. The mean BMI was 28.12 kg/m2, with median waist to hip ratio (WHR) of 0·93. Metabolic syndrome was found in 60% of participants and 67.82% were obese by body mass index. The mean A1c was 9.07±2.52%. Good glucose control (A1c less than 7.0%) was seen in 23% of participants  while nearly half (48%) had HbA1c which was >9.0%. The median levels of fasting insulin and C-peptide were 12.62 (range 1.33–90.42) mIU/L and 0.78 ng/mL (range 0–16.2), respectively. 

Included participants were diagnosed with diabetes within a year and as such, majority did not have any micro- or macrovascular complications. The most common diabetes complication was sensory neuropathy detected by monofilament testing, which was found in 28% of participants, followed by non-proliferative diabetic retinopathy in 13%. A history of previous diabetic ketoacidosis was found in 10 patients (2.87%). Glutamic acid decarboxylase (GAD) and insulin auto-antibodies were found in 3.2% and 19.3% of participants, respectively. Approximately half (51.73%) of the participants were insulin resistant by HOMA-IR.

CONCLUSION

In contrast with Caucasians and other Asians, diabetes among young Filipino adults is associated with lower BMI but with a similarly high visceral adiposity as shown by an elevated WHR. Metabolic syndrome with insulin resistance as defined by a variety of indices is predominant. Type 1 diabetes with autoantibodies occur in only a small fraction of this population. Data derived from this work can provide a framework for cluster analysis towards personalized management specific to this population.

Human ; Acids ; Adiponectin ; Adiposity ; Adult ; Aged ; Antibodies ; Asia ; Asian ; Asian Continental Ancestry Group ; Autoantibodies ; Body Mass Index ; C-peptide ; Carboxy-lyases ; Child ; Cluster Analysis ; Demography ; Diabetes Complications ; Diabetes Mellitus ; Diabetes Mellitus, Type 1 ; Diabetes Mellitus, Type 2 ; Diabetic Ketoacidosis ; Diabetic Retinopathy ; Diagnosis ; Fasting ; Female ; Glucose ; Glucose Tolerance Test ; Glutamate Decarboxylase ; Glutamic Acid ; Insulin ; Insulin Resistance ; Ketosis ; Leptin ; Lipids ; Metabolic Syndrome ; Obesity ; Patients ; Peptides ; Phenotype ; Philippines ; Population ; Prevalence ; Serum ; Therapeutics ; Thyroid Gland ; Thyroid Function Tests ; Young Adult

To address the current issues of data imbalance and scarcity in photoplethysmography (PPG) data for type 2 diabetes mellitus (T2DM) prediction, this study proposes an improved conditional Wasserstein generative adversarial network with gradient penalty (CWGAN-GP). The algorithm integrated gated recurrent unit (GRU) networks and self-attention mechanisms to construct a generator, aiming to produce high-quality PPG signals. Various data augmentation methods, including the improved CWGAN-GP, were employed to expand the PPG dataset, and multiple classifiers were applied for T2DM prediction analysis. Experimental results showed that the model trained on data generated by the improved CWGAN-GP achieved the optimal prediction performance. The highest accuracy reached 0.895 0, and compared with other data enhancement methods, this approach exhibited significant advantages in terms of precision and F1-score. The generated data notably enhances the accuracy and generalization ability of T2DM prediction models, providing a more reliable technical basis for non-invasive early T2DM screening based on PPG signals.
Photoplethysmography/methods* ; Diabetes Mellitus, Type 2/diagnosis* ; Humans ; Algorithms ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Prediction Algorithms

OBJECTIVE: To establish and validate a novel diabetic retinopathy (DR) risk-prediction model using a whole-exome sequencing (WES)-based machine learning (ML) method. METHODS: WES was performed to identify potential single nucleotide polymorphism (SNP) or mutation sites in a DR pedigree comprising 10 members. A prediction model was established and validated in a cohort of 420 type 2 diabetic patients based on both genetic and demographic features. The contribution of each feature was assessed using Shapley Additive explanation analysis. The efficacies of the models with and without SNP were compared. RESULTS: WES revealed that seven SNPs/mutations ( rs116911833 in TRIM7, 1997T>C in LRBA, 1643T>C in PRMT10, rs117858678 in C9orf152, rs201922794 in CLDN25, rs146694895 in SH3GLB2, and rs201407189 in FANCC) were associated with DR. Notably, the model including rs146694895 and rs201407189 achieved better performance in predicting DR (accuracy: 80.2%; sensitivity: 83.3%; specificity: 76.7%; area under the receiver operating characteristic curve [AUC]: 80.0%) than the model without these SNPs (accuracy: 79.4%; sensitivity: 80.3%; specificity: 78.3%; AUC: 79.3%). CONCLUSION Novel SNP sites associated with DR were identified in the DR pedigree. Inclusion of rs146694895 and rs201407189 significantly enhanced the performance of the ML-based DR prediction model.
Diabetic Retinopathy/diagnosis* ; Humans ; Machine Learning ; Male ; Female ; Polymorphism, Single Nucleotide ; Middle Aged ; Exome Sequencing ; Aged ; Adult ; Pedigree ; Diabetes Mellitus, Type 2/complications* ; Genetic Predisposition to Disease ; Mutation

OBJECTIVES: To study the clinical manifestations and genetic characteristics of children with maturity-onset diabetes of the young type 2 (MODY2), aiming to enhance the recognition of MODY2 in clinical practice. METHODS: A retrospective analysis was conducted on the clinical data of 13 children diagnosed with MODY2 at the Department of Pediatrics of Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology from August 2017 to July 2023. RESULTS: All 13 MODY2 children had a positive family history of diabetes and were found to have mild fasting hyperglycemia [(6.4±0.5) mmol/L] during health examinations or due to infectious diseases. In the oral glucose tolerance test, two cases met the diagnostic criteria for diabetes with fasting blood glucose, while the others exhibited impaired fasting glucose or impaired glucose tolerance. The one-hour post-glucose load (1-hPG) fluctuated between 8.31 and 13.06 mmol/L, meeting the diagnostic criteria for diabetes recommended by the International Diabetes Federation. All 13 MODY2 children had heterozygous variants in the glucokinase (GCK) gene, with Cases 6 (GCK c.1047C>A, p.Y349X), 11 (GCK c.1146_1147ins GCAGAGCGTGTCTACGCGCGCTGCGCACATGTGC, p.S383Alafs*87), and 13 (GCK c.784_785insC, p.D262Alafs*13) presenting variants that had not been previously reported. CONCLUSIONS This study enriches the spectrum of genetic variations associated with MODY2. Clinically, children with a family history of diabetes, incidental findings of mild fasting hyperglycemia, and negative diabetes-related antibodies should be considered for the possibility of MODY2.
Humans ; Diabetes Mellitus, Type 2/diagnosis* ; Male ; Female ; Child ; Retrospective Studies ; Glucokinase/genetics* ; Adolescent ; Child, Preschool ; Glucose Tolerance Test

The prevalence of type 1 diabetes (T1DM) is increasing annually, and its complications seriously impair the quality of life of affected children. Early screening for T1DM helps reduce the occurrence of diabetic ketoacidosis, protect β-cell function, and delay disease onset in high-risk populations. This article summarizes current domestic and international screening technologies for T1DM. Screening methods remain centered on detection of diabetes-related antibodies and glycometabolic markers, while factors related to disease pathogenesis hold promise as sensitive screening markers. Expanding T1DM screening in China is expected to improve early diagnosis and treatment.
Diabetes Mellitus, Type 1/diagnosis* ; Humans ; Early Diagnosis ; Autoantibodies/blood* ; Mass Screening/methods*

Saliva is an important body fluid in the oral cavity containing lots of biomarkers, whose inherent micro-ecosystem holds significant value for early diagnosis and monitoring of oral diseases. Simultaneously, saliva has particular advantages, such as ease of sampling, painless and non-invasive collection, and suitability for repeated sampling, making it highly appropriate for surveillance and follow-up of diseases. In a series of studies conducted by the research group for preventive dentistry in Peking University School and Hospital of Stomatology, we compared different segments of saliva and those samples collected via different sampling methods using proteomic/peptidomic and microbiomic technologies to explore the stability of saliva samples. Besides, the significance of applying representative salivary biomarkers in early prevention and control of representative oral diseases (e.g. dental caries, periodontal diseases) and systemic conditions (e.g. type 2 diabetes mellitus, chronic kidney disease) was confirmed as well.
Humans ; Saliva/chemistry* ; Dental Caries/diagnosis* ; Biomarkers/analysis* ; Periodontal Diseases/diagnosis* ; Mouth Diseases/diagnosis* ; Proteomics/methods* ; Diabetes Mellitus, Type 2/diagnosis* ; Microbiota ; Renal Insufficiency, Chronic/prevention & control*

Diabetic Ketoacidosis/diagnosis* ; Humans ; Child ; Diabetes Mellitus, Type 1/diagnosis* ; China ; Insulin/administration & dosage* ; Hypoglycemic Agents/therapeutic use*

Blood glucose monitoring has become the weakest point in the overall management of diabetes in China. Long-term monitoring of blood glucose levels in diabetic patients has become an important means of controlling the development of diabetes and its complications, so that technological innovations in blood glucose testing methods have far-reaching implications for accurate blood glucose testing. This article discusses the basic principles of minimally invasive and non-invasive blood glucose testing assays, including urine glucose assays, tear assays, methods of extravasation of tissue fluid, and optical detection methods, etc., focuses on the advantages of minimally invasive and non-invasive blood glucose testing methods and the latest relevant results, and summarizes the current problems of various testing methods and prospects for future development trends.
Humans ; Blood Glucose ; Blood Glucose Self-Monitoring/methods* ; Diabetes Mellitus/diagnosis* ; Monitoring, Physiologic/methods* ; Tears

Several chronic disorders including type 2 diabetes (T2D), obesity, heart disease and cancer are preceded by a state of chronic low-grade inflammation. Biomarkers for the early assessment of chronic disorders encompass acute phase proteins (APP), cytokines and chemokines, pro-inflammatory enzymes, lipids and oxidative stress mediators. These substances enter saliva through the blood flow and, in some cases, there is a close relation between their salivary and serum concentration. Saliva can be easily collected and stored with non-invasive and cost-saving procedures, and it is emerging the concept to use it for the detection of inflammatory biomarkers. To this purpose, the present review aims to discuss the advantages and challenges of using standard and cutting-edge techniques to discover salivary biomarkers which may be used in diagnosis/therapy of several chronic diseases with inflammatory consequences with the pursuit to possibly replace conventional paths with detectable soluble mediators in saliva. Specifically, the review describes the procedures used for saliva collection, the standard approaches for the measurement of salivary biomarkers and the novel methodological strategies such as biosensors to improve the quality of care for chronically affected patients.
Humans ; Diabetes Mellitus, Type 2/diagnosis* ; Biomarkers ; Cytokines ; Inflammation/diagnosis* ; Oxidative Stress

Objective: To explore the associations of glycated hemoglobin (HbA1c) with FPG and oral glucose tolerance test 2-hour (OGTT-2 h) in areas at different altitude in China. Methods: Subjects who participated in 2018-2019 China Chronic Disease and Risk Factor Surveillance and had no prior type 2 diabetes diagnosis were included. Subsequently, they were categorized into three groups based on altitude of living area (<2 000, 2 000- and ≥3 000 m). With adjustment for intracluster correlation, multivariable linear regression analysis was performed to evaluate the associations of HbA1c with FPG and OGTT-2 h in the context of HbA1c was normal (<5.7%) or abnormal (≥5.7%). Furthermore, the shape of relationships between HbA1c and glucose indicators was examined using restricted cubic spline. Finally, receiver operating characteristic curve was used to evaluate the diagnostic performance of HbA1c for diabetes. Results: A total of 157 277 subjects were included in the analysis. While FPG and OGTT-2 h levels gradually decreased with increase of altitude, HbA1c level was similar among the three groups. When HbA1c was <5.7%, its association with FPG and OGTT-2 h was weak and no obvious difference was observed among the three groups. When HbA1c was ≥5.7%, the FPG and OGTT-2 h increased by 15.45% (95%CI:14.71%- 16.18%) and 24.54% (95%CI:23.18%-25.91%) respectively per one standard deviation increase in HbA1c in group in area at altitude <2 000 m. However, the FPG and OGTT-2 h increased by 13.08% (95%CI:10.46%-15.76%) and 21.72% (95%CI:16.39%-27.31%), respectively, in group in area at altitude 2 000- m, and increased by 11.41% (95%CI:9.32%-13.53%) and 20.03% (95%CI:15.38%- 24.86%), respectively, in group of altitude ≥3 000 m. The restricted cubic spline indicated that the curve showing the association of HbA1c with FPG and OGTT-2 h was flat when HbA1c was <5.7%, but showed a positive linear relationship when HbA1c was ≥5.7%. The area under curve for detecting diabetes was 0.808 (95%CI:0.803-0.812) in group of altitude <2 000 m and 0.728 (95%CI:0.660-0.796, P=0.022) in group of altitude ≥3 000 m. The relevant optimal cutoff value of HbA1c was 5.7%, with a sensitivity of 65.4% and a specificity of 83.0%, and 6.0%, with a sensitivity of 48.3% and a specificity of 93.7%, respectively. Conclusions: When HbA1c was ≥5.7%, the association between HbA1c and glucose indicators became weaker as the increase of altitude. In the area at altitude ≥3 000 m, it may not be appropriate to use HbA1c in the diagnosis of diabetes.
Adult ; Humans ; Glycated Hemoglobin ; Diabetes Mellitus, Type 2/diagnosis* ; Blood Glucose/analysis* ; Glucose ; Altitude ; Fasting ; China/epidemiology* ; Diabetes Mellitus/epidemiology*