High risk of conversion to diabetes in first-degree relatives of individuals with young-onset type 2 diabetes: a 12-year follow-up analysis

A comprehensive youth diabetes epidemiological dataset and web portal: Resource Development and Case Studies

BACKGROUND

The prevalence of Type 2 diabetes (DM) and prediabetes (preDM) has been increasing among youth in recent decades in the United States, prompting an urgent need for understanding and identifying their associated risk factors. Such efforts, however, have been hindered by the lack of easily accessible youth preDM/DM data.

OBJECTIVE

We aimed to first build a high quality, comprehensive epidemiological dataset focused on youth preDM/DM. Subsequently, we aimed to make this data accessible by creating a user-friendly web portal to share it and corresponding codes. Through this, we hope to address this significant gap and facilitate youth preDM/DM research.

METHODS

Building on data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we cleaned and harmonized hundreds of variables relevant to preDM/DM (fasting plasma glucose level ≥100 mg/dL and/or HbA1C ≥5.7%) for youth aged 12-19 years (n=15,149). We identified individual factors associated with preDM/DM risk using bivariate statistical analyses and predicted preDM/DM status using our Ensemble Integration (EI) framework for multi-domain machine learning. We then developed a user-friendly web portal named Prediabetes/diabetes in youth ONline Dashboard (POND) to share the data and codes.

RESULTS

We extracted 95 variables potentially relevant to preDM/DM risk organized into 4 domains (sociodemographic, health status, diet, and other lifestyle behaviors). The bivariate analyses identified 27 significant correlates of preDM/DM (P ≤0.0005, Bonferroni adjusted), including race/ethnicity, health insurance, BMI, added sugar intake, and screen time. Sixteen of these factors were also identified based on the EI methodology (Fisher's P of overlap=7.06x10^-6). In addition to those, the EI approach identified 11 additional predictive variables, including some known (e.g., meat and fruit intake and family income) and less recognized factors (e.g., number of rooms in homes). The factors identified in both analyses spanned over all 4 of the domains mentioned. These data and results, as well as other exploratory tools, can be accessed on POND (https://rstudio-connect.hpc.mssm.edu/POND/).

CONCLUSIONS

Using NHANES data, we built one of the largest public epidemiological datasets for studying youth preDM/DM and identified potential risk factors using complementary analytical approaches. Our results align with the multifactorial nature of preDM/DM with correlates across several domains. Also, our data-sharing platform, POND, facilitates a wide range of applications to inform future youth preDM/DM studies.

CLINICALTRIAL

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.

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.

Ten-year clinical characteristics of patients with early-onset type 2 diabetes: A single-center experience in China

AIMS

The incidence of type 2 diabetes in China has exhibited an increasing trend, including younger individuals, over the past years. Early-onset type 2 diabetes (EOT2D) refers to diabetes diagnosed before 40 years of age. These patients have poor metabolic control and are highly susceptible to diabetic complications, which poses challenges for treatment. However, few studies have reported on the treatment of EOT2D. We determined clinical features and trends in drug use in patients with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

This retrospective study was performed at the Endocrinology Ward, Peking Union Medical College Hospital (PUMCH). "Diabetes" was used when searching PUMCH's Electronic Medical Record Analytical Database to obtain clinical data of patients between January 2013 and May 2022.

RESULTS

The analysis included 1590 patients with T2DM. Among them, 609 (38.3%) had EOT2D. Compared with late-onset type 2 diabetes (LOT2D) patients, EOT2D patients exhibited worse glycemic control and higher body weight and lipid levels despite significant age differences. EOT2D patients also had a higher risk of diabetic retinopathy and nephropathy. Under the general trend of increasing use of dipeptidylpeptidase-4 inhibitors, sodium-glucose cotransporter-2 inhibitors, and glucagon-like peptide-1 agonists, patients with EOT2D were more likely to use organ-protective drugs.

CONCLUSIONS

Compared with LOT2D patients, EOT2D patients have a longer course of diabetes, worse metabolic control, and a higher rate of developing microvascular complications. The administration of combined therapy, including new agents, may require consideration when selecting hypoglycemic agents for treating EOT2D.

The role of high fat diet on serum uric acid level among healthy male first degree relatives of type 2 diabetes mellitus

First-degree relatives (FDR) of type 2 diabetes mellitus have increased risk of developing insulin resistance-related disorders including hyperuricemia. We investigated metabolic profile and serum uric acid (SUA) metabolism in response to high-fat diet among healthy male FDR in comparison to those without family history of diabetes. A total of 30 FDR and 30 non-FDR subjects completed a 5-days-hypercaloric diet with fat added to regular daily intake. Despite similar insulin response, FDR displayed different changes in SUA compared to non-FDR subjects (0.26 ± 0.83 mg/dL vs - 0.21 ± 0.78 mg/dL, p = 0.028). In subgroup analyses stratified by body mass index and waist circumference, significant different SUA changes between FDR and non-FDR subjects were only found in obese (0.48 ± 0.87 mg/dL vs - 0.70 ± 0.71 mg/dL, p = 0.001) and centrally obese (0.59 ± 0.83 mg/dL vs - 0.55 ± 0.82 mg/dL, p = 0.011) subgroups. In multivariate analysis, visceral adiposity seemed mediating the different response in SUA metabolism between FDR and non-FDR subjects induced by short-term obesogenic diet.

Facilitating youth diabetes studies with the most comprehensive epidemiological dataset available through a public web portal

The prevalence of type 2 diabetes mellitus (DM) and prediabetes (preDM) is rapidly increasing among youth, posing significant health and economic consequences. To address this growing concern, we created the most comprehensive youth-focused diabetes dataset to date derived from National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018. The dataset, consisting of 15,149 youth aged 12 to 19 years, encompasses preDM/DM relevant variables from sociodemographic, health status, diet, and other lifestyle behavior domains. An interactive web portal, POND (Prediabetes/diabetes in youth ONline Dashboard), was developed to provide public access to the dataset, allowing users to explore variables potentially associated with youth preDM/DM. Leveraging statistical and machine learning methods, we conducted two case studies, revealing established and lesser-known variables linked to youth preDM/DM. This dataset and portal can facilitate future studies to inform prevention and management strategies for youth prediabetes and diabetes.

Dysregulation of adipokines levels among healthy first-degree relatives of type 2 diabetes patients

Background

Leptin, adiponectin and its ratio (L/A), as well as adipocyte fatty acid binding protein (A-FABP) have shown association to type 2 diabetes and atherosclerosis. Since first degree relatives (FDR) of type 2 diabetes are known to have higher risks of developing aforementioned diseases, this study aimed to see differences in adipokines profiles between FDR of type 2 diabetes and non-FDR counterpart.

Methods

Age, sex and body mass index (BMI)-matched normotensive-normoglycemic subjects, aged 19-39 years with BMI<30 kg/m2, were included in this cross-sectional study. Serum adiponectin, leptin, and A-FABP levels were measured by sandwich ELISA while HOMA-IR was calculated from fasting blood glucose and insulin levels.

Results

Of 116 subjects recruited, there were significant difference of insulin level (6.00 vs 5.00 μIU/mL, P = 0.029) and HOMA-IR (1.27 vs 1.10, P = 0.028). Adiponectin, leptin, L/A ratio, and A-FABP levels were not statistically different between FDR and non-FDR groups. Stratified by BMI, non-obese FDR had higher L/A ratio (0.83 vs 0.49, P = 0.020) compared to those of corresponding non-FDR. In multivariate analysis, after adjusting for age, sex, waist circumference, BMI, and metabolic profiles (HbA1C, HOMA-IR, LDL-C, HDL-C, and triglyceride levels), FDR status became significantly associated with adiponectin level, and in non-obese subgroup, remained its significance with L/A ratio.

Conclusion

The FDR status was independently associated with adiponectin level. Furthermore, higher L/A ratio was more pronounced in non-obese FDR than those of non-FDR subjects, suggesting that FDR status may already contribute to the development of adipokines dysregulation before obesity occurs.

Associations of the HOMA2-%B and HOMA2-IR with progression to diabetes and glycaemic deterioration in young and middle-aged Chinese

AIMS

Insulin deficiency (ID) and resistance (IR) contribute to progression from normal glucose tolerance to diabetes to insulin requirement although their relative contributions in young-onset diabetes is unknown.

METHODS

We examined the associations of HOMA2 using fasting plasma glucose and C-peptide in Chinese aged 20-50 years with (1) progression to type 2 diabetes (T2D) in participants without diabetes in a community-based cohort (1998-2013) and (2) glycaemic deterioration in patients with T2D in a clinic-based cohort (1995-2014). We defined ID as HOMA2-%B below median and insulin IR as HOMA2-IR above median.

RESULTS

During 10-year follow-up, 62 (17.9%) of 347 community-dwelling participants progressed to T2D. After 8.6 years, 291 (48.1%) of 609 patients with T2D had glycaemic deterioration. At baseline, progressors for T2D had higher HOMA2-IR, while in patients with T2D, progressors for glycaemic deterioration had higher HOMA2-IR and lower HOMA2-%B than non-progressors. The non-ID/IR group and the ID/IR group had an adjusted odds ratios of 2.47 (95% CI: 1.28, 4.94) and 5.36 (2.26, 12.79), respectively, for incident T2D versus the ID/non-IR group. In patients with T2D, 50% of the ID/IR group required insulin at 6.7 years versus around 11 years in the non-ID/IR or ID/non-IR, and more than 15 years in the non-ID/non-IR group. Compared with the latter group, the adjusted hazard ratios were 2.74 (1.80, 4.16) in the ID/non-IR, 2.73 (1.78, 4.19) in the non-ID/IR and 4.46 (2.87, 6.91) in the ID/IR group (p-interaction = 0.049).

CONCLUSIONS

In young Chinese adults, IR and ID contributed to progression to T2D and glycaemic deterioration.

Health consequences of early-onset compared with late-onset type 2 diabetes mellitus

Background

Although cumulating evidence has suggested that early-onset type 2 diabetes mellitus (T2DM) conferred on patients a broader tendency for complications beyond vascular ones, a comprehensive analysis of patterns of complications across all relevant systems is currently lacking.

Method

We prospectively studied 1 777 early-onset (age at diagnosis ≤ 45 years) and 35 889 late-onset (>45 years) T2DM patients with matched unexposed individuals from the UK Biobank. Diabetes-specific and -related complications were examined using phenome-wide association analysis, with patterns identified by comorbidity network analysis. We also evaluated the effect of lifestyle modifications and glycemic control on complication development.

Results

The median follow-up times for early-onset and late-onset T2DM patients were 17.83 and 9.39 years, respectively. Compared to late-onset T2DM patients, patients with early-onset T2DM faced a significantly higher relative risk of developing subsequent complications that primarily affected sense organs [hazard ratio (HR) 3.46 vs. 1.72], the endocrine/metabolic system (HR 3.08 vs. 2.01), and the neurological system (HR 2.70 vs. 1.81). Despite large similarities in comorbidity patterns, a more complex and well-connected network was observed for early-onset T2DM. Furthermore, while patients with early-onset T2DM got fewer benefits (12.67% reduction in pooled HR for all studied complications) through fair glycemic control (median HbA_1c ≤ 53 mmol/mol) compared to late-onset T2DM patients (18.01% reduction), they seemed to benefit more from favorable lifestyles, including weight control, healthy diet, and adequate physical activity.

Conclusions

Our analyses reveal that early-onset T2DM is an aggressive disease resulting in more complex complication networks than late-onset T2DM. Aggressive glucose-lowering intervention, complemented by lifestyle modifications, are feasible strategies for controlling early-onset T2DM-related complications.

Detection of increased serum miR-122-5p and miR-455-3p levels before the clinical diagnosis of liver cancer in people with type 2 diabetes

People with type 2 diabetes (T2D) have increased cancer risk. Liver cancer (LC) has a high prevalence in East Asia and is one of the leading causes of cancer death globally. Diagnosis of LC at early stage carries good prognosis. We used stored serum from patients of Hong Kong Diabetes Register before cancer diagnosis to extract RNA to screen for microRNA markers for early detection of LC in T2D. After screening with Affymetrix GeneChip microarray with serum RNA from 19 incident T2D LC (T2D-LC), 20 T2D cancer free (T2D-CF) and 20 non-T2D non-cancer patients, top signals were validated in a 3-group comparison including 1888 T2D-CF, 127 T2D-LC, and 487 T2D patients with non-liver cancer patients using qPCR. We detected 2.55-fold increase in miR-122-5p and 9.21-fold increase in miR-455-3p in the T2D-LC group. Using ROC analysis, miR-122-5p and miR-455-3p jointly predicted LC with an area under the curve of 0.770. After adjustment for confounders, each unit increase of miR-455-3p increased the odds ratio for liver cancer by 1.022. Increased serum levels of miR-122-5p and miR-455-3p were independently associated with increased risk of incident LC in T2D and may serve as potential biomarkers for early detection of LC in T2D.

Migration and diabetes incidence among Chinese adults in Canada, China, Hong Kong, and Taiwan: An international population-based comparative study from 2000 to 2017

AIMS

We conducted an international population-based study comparing the incidence of young- (age 20-39 years) and usual- (age ≥ 40 years) onset diabetes among Chinese-Canadian immigrants; their source populations (mainland China, Hong Kong, Taiwan); and other Canadians.

METHODS

Using population-based data (2000-17; n = 3.4 million cases), we calculated incidence rates and incidence rate ratios comparing the average incidence for each cohort.

RESULTS

The average incidence of young-onset diabetes (YOD) among immigrants from China, Hong Kong, and Taiwan was 165.5, 121.0, and 78.4 per 100,000 person-years respectively. Immigrants from China and Hong Kong had higher YOD incidence than their source populations (RR China: 2.59, 2.44-2.74; Hong Kong: 1.64, 1.49-1.81), while immigrants from Taiwan had lower rates versus Taiwan (RR 0.63, 0.45-0.86). YOD incidence among immigrants from China increased sharply by 8.3% (3.3-13.6%) per year from 2011 onward-over twice the annual increase among non-Chinese Canadians. The average incidence rates of usual-onset diabetes among immigrants from China, Hong Kong, and Taiwan were higher than (RR 1.77, 1.73-1.81), similar to (0.98, 0.96-1.01), and lower than (0.36, 0.32-0.40) those in each source population respectively.

CONCLUSIONS

Diabetes incidence among Chinese migrants is unexpectedly heterogeneous, varying according age at migration, territory of origin, and the occurrence of diabetes in the source population.

Predicting youth diabetes risk using NHANES data and machine learning

Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screening tools to reliably assess diabetes risk are only available for adults, not youth. As a first step in developing such a tool, we used a large-scale dataset from the National Health and Nutritional Examination Survey (NHANES) to examine the performance of a published pediatric clinical screening guideline in identifying youth with preDM/DM based on American Diabetes Association diagnostic biomarkers. We assessed the agreement between the clinical guideline and biomarker criteria using established evaluation measures (sensitivity, specificity, positive/negative predictive value, F-measure for the positive/negative preDM/DM classes, and Kappa). We also compared the performance of the guideline to those of machine learning (ML) based preDM/DM classifiers derived from the NHANES dataset. Approximately 29% of the 2858 youth in our study population had preDM/DM based on biomarker criteria. The clinical guideline had a sensitivity of 43.1% and specificity of 67.6%, positive/negative predictive values of 35.2%/74.5%, positive/negative F-measures of 38.8%/70.9%, and Kappa of 0.1 (95%CI: 0.06–0.14). The performance of the guideline varied across demographic subgroups. Some ML-based classifiers performed comparably to or better than the screening guideline, especially in identifying preDM/DM youth (p = 5.23 × 10⁻⁵).We demonstrated that a recommended pediatric clinical screening guideline did not perform well in identifying preDM/DM status among youth. Additional work is needed to develop a simple yet accurate screener for youth diabetes risk, potentially by using advanced ML methods and a wider range of clinical and behavioral health data.

Young-onset diabetes, nutritional therapy and novel insulin delivery systems: a report from the 21st Hong Kong Diabetes and Cardiovascular Risk Factors - East Meets West Symposium

The prevalence and incidence of young-onset diabetes are increasing in many parts of the world, with the most rapid increase occurring in Asia, where one in five people with diabetes are diagnosed below the age of 40 years. Accumulation of glycaemic burden from an early age significantly increases the lifetime risks of developing complications from diabetes. Despite impending health threats, young people fare worse in the control of blood glucose and other metabolic risk factors. Challenges in the management of young-onset diabetes are compounded by heterogeneity of the underlying causes, pathophysiology and clinical phenotypes in this group. Effective characterization of people with diabetes has implications in steering the choice of glucose-lowering drugs, which, in turn, determines the clinical outcome. Medical nutritional therapy is key to effective management of people with diabetes but dietary adherence is often suboptimal among younger individuals. A recently published consensus report on nutritional therapy addresses dietary management in people with prediabetes as well as diabetes, and summarizes clinical evidence regarding macronutrient and micronutrient composition as well as eating patterns in people with diabetes. For people with type 1 diabetes, automated insulin delivery systems have rapidly evolved since the concept was first introduced at the National Institute of Health and the Juvenile Diabetes Research Foundation in 2005. The subsequent development of a type 1 diabetes simulator, developed using detailed human physiology data on carbohydrate metabolism replaced the need for pre-clinical animal studies and facilitated the seamless progression to artificial pancreas human clinical trials.

Progression of glucose intolerance and cardiometabolic risk factors over a decade in Chinese women with polycystic ovary syndrome: A case-control study

BACKGROUND

Polycystic ovary syndrome (PCOS) is associated with increased metabolic risk, though data on long-term follow-up of cardiometabolic traits are limited. We postulated that Chinese women with PCOS would have higher risk of incident diabetes and cardiometabolic abnormalities than those without PCOS during long-term follow-up.

METHODS AND FINDINGS

One hundred ninety-nine Chinese women with PCOS diagnosed by the Rotterdam criteria and with a mean age of 41.2 years (SD = 6.4) completed a follow-up evaluation after an average of 10.6 ± 1.3 years. Two hundred twenty-five women without PCOS (mean age: 54.1 ± 6.7 years) who underwent baseline and follow-up evaluation over the same period were used for comparison. Progression of glycaemic status of women both with and without PCOS was assessed by using 75-g oral glucose tolerance test (OGTT) screening with the adoption of 2009 American Diabetes Association diagnostic criteria. The frequency of impaired glucose regulation, hypertension, and hyperlipidaemia of women with PCOS at follow-up has increased from 31.7% (95% CI 25.2%-38.1%) to 47.2% (95% CI 40.3%-54.2%), 16.1% (95% CI 11.0%-21.2%) to 34.7% (95% CI 28.1%-41.3%), and 52.3% (95% CI 45.3%-59.2%) to 64.3% (95% CI 57.7%-71.0%), respectively. The cumulative incidence of diabetes mellitus (DM) in follow-up women with PCOS is 26.1% (95% CI 20.0%-32.2%), almost double that in the cohort of women without PCOS (p < 0.001). Age-standardised incidence of diabetes among women with PCOS was 22.12 per 1,000 person-years (95% CI 10.86-33.37) compared with the local female population incidence rate of 8.76 per 1,000 person-years (95% CI 8.72-8.80) and 10.09 per 1,000 person-years (95% CI 4.92-15.26, p < 0.001) for women without PCOS in our study. Incidence rate for women with PCOS aged 30-39 years was 20.56 per 1,000 person-years (95% CI 12.57-31.87), which is approximately 10-fold higher than that of the age-matched general female population in Hong Kong (1.88 per 1,000 person-years, [95% CI 1.85-1.92]). The incidence rate of type 2 DM (T2DM) of both normal-weight and overweight women with PCOS was around double that of corresponding control groups (normal weight: 8.96 [95% CI 3.92-17.72] versus 4.86 per 1,000 person-years [95% CI 2.13-9.62], p > 0.05; overweight/obese: 28.64 [95% CI 19.55-40.60] versus 14.1 per 1,000 person-years [95% CI 8.20-22.76], p < 0.05). Logistic regression analysis identified that baseline waist-to-hip ratio (odds ratio [OR] = 1.71 [95% CI 1.08-2.69], p < 0.05) and elevated triglyceride (OR = 6.63 [95% CI 1.23-35.69], p < 0.05) are associated with the progression to T2DM in PCOS. Limitations of this study include moderate sample size with limited number of incident diabetes during follow-up period and potential selection bias.

CONCLUSIONS

High risk of diabetes and increased cardiovascular disease risk factors among Chinese women with PCOS are highlighted in this long-term follow-up study. Diabetes onset was, on average, 10 years earlier among women with PCOS than in women without PCOS.

Evolution of Diabetes Care in Hong Kong: From the Hong Kong Diabetes Register to JADE-PEARL Program to RAMP and PEP Program

The rapid increase in diabetes prevalence globally has contributed to large increases in health care expenditure on diabetic complications, posing a major health burden to countries worldwide. Asians are commonly observed to have poorer β-cell function and greater insulin resistance compared to the Caucasian population, which is attributed by their lower lean body mass and central obesity. This "double phenotype" as well as the rising prevalence of young onset diabetes in Asia has placed Asians with diabetes at high risk of cardiovascular and renal complications, with cancer emerging as an important cause of morbidity and mortality. The experience from Hong Kong had demonstrated that a multifaceted approach, involving team-based integrated care, information technological advances, and patient empowerment programs were able to reduce the incidence of diabetic complications, hospitalizations, and mortality. System change and public policies to enhance implementation of such programs may provide solutions to combat the burgeoning health problem of diabetes at a societal level.