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The clinical utility of a type 2 diabetes mellitus (T2DM) polygenic risk score (PRS) in the East Asian population remains underexplored. We aimed to examine the potential prognostic value of a T2DM PRS and assess its viability as a clinical instrument. We first established a T2DM PRS for 5490 Korean individuals using East Asian Biobank data (269,487 samples). Subsequently, we assessed the predictive capability of this T2DM PRS in a prospective longitudinal study with baseline data and data from seven additional follow-ups. Our analysis showed that the T2DM PRS could predict the transition of glucose tolerance stages from normal glucose tolerance to prediabetes and from prediabetes to T2DM. Moreover, T2DM patients in the top-decile PRS group were more likely to be treated with insulin (hazard ratio = 1.69, p value = 2.31E-02) than were those in the remaining PRS groups. T2DM PRS values were significantly high in the severe diabetes subgroup, characterized by insulin resistance and β -cell dysfunction (p value = 0.0012). The prediction models with the T2DM PRS had significantly greater Harrel's C-indices than did corresponding models without it. By utilizing prospective longitudinal study data and extensive clinical risk factor information, our analysis provides valuable insights into the multifaceted clinical utility of the T2DM PRS., (© 2024. The Author(s).)

Longitudinal deep multiomics profiling, which combines biomolecular, physiological, environmental and clinical measures data, shows great promise for precision health. However, integrating and understanding the complexity of such data remains a big challenge. Here we utilize an individual-focused bottom-up approach aimed at first assessing single individuals' multiomics time series, and using the individual-level responses to assess multi-individual grouping based directly on similarity of their longitudinal deep multiomics profiles. We used this individual-focused approach to analyze profiles from a study profiling longitudinal responses in type 2 diabetes mellitus. After generating periodograms for individual subject omics signals, we constructed within-person omics networks and analyzed personal-level immune changes. The results identified both individual-level responses to immune perturbation, and the clusters of individuals that have similar behaviors in immune response and which were associated to measures of their diabetic status., (© 2022. The Author(s).)

The aim of this study was to estimate the incidence of diabetes mellitus in the Basque Country and the risk factors involved in the disease by reassessing an adult population after 7 years of follow-up. In the previous prevalence study, 847 people older than 18 years were randomly selected from all over the Basque Country and were invited to answer a medical questionnaire, followed by a physical examination and an oral glucose tolerance test. In the reassessment, the same variables were collected and the resulting cohort comprised 517 individuals of whom 43 had diabetes at baseline. The cumulative incidence of diabetes was 4.64% in 7 years and the raw incidence rate was 6.56 cases/1000 person-years (95%CI: 4.11-9.93). Among the incident cases, 59% were undiagnosed. The most strongly associated markers by univariate analyses were age > 60 years, dyslipidaemia, prediabetes and insulin resistance. We also found association with hypertension, obesity, family history of diabetes and low education level. Multivariate analysis adjusted for age and sex showed that a set of risk factors assessed together (dyslipidaemia, waist-to-hip-ratio and family history of diabetes) had great predictive value (AUC-ROC = 0.899, 95%CI: 0.846-0.953, p = 0.942), which suggests the need for early intervention before the onset of prediabetes.

Type 2 diabetes mellitus (T2D) is a growing health problem, but little is known about its early disease stages, its effects on biological processes or the transition to clinical T2D. To understand the earliest stages of T2D better, we obtained samples from 106 healthy individuals and individuals with prediabetes over approximately four years and performed deep profiling of transcriptomes, metabolomes, cytokines, and proteomes, as well as changes in the microbiome. This rich longitudinal data set revealed many insights: first, healthy profiles are distinct among individuals while displaying diverse patterns of intra- and/or inter-personal variability. Second, extensive host and microbial changes occur during respiratory viral infections and immunization, and immunization triggers potentially protective responses that are distinct from responses to respiratory viral infections. Moreover, during respiratory viral infections, insulin-resistant participants respond differently than insulin-sensitive participants. Third, global co-association analyses among the thousands of profiled molecules reveal specific host-microbe interactions that differ between insulin-resistant and insulin-sensitive individuals. Last, we identified early personal molecular signatures in one individual that preceded the onset of T2D, including the inflammation markers interleukin-1 receptor agonist (IL-1RA) and high-sensitivity C-reactive protein (CRP) paired with xenobiotic-induced immune signalling. Our study reveals insights into pathways and responses that differ between glucose-dysregulated and healthy individuals during health and disease and provides an open-access data resource to enable further research into healthy, prediabetic and T2D states.

We aimed to explore whether changes in circulating levels of miRNAs according to type 2 diabetes mellitus (T2DM) or prediabetes status could be used as biomarkers to evaluate the risk of developing the disease. The study included 462 patients without T2DM at baseline from the CORDIOPREV trial. After a median follow-up of 60 months, 107 of the subjects developed T2DM, 30 developed prediabetes, 223 maintained prediabetes and 78 remained disease-free. Plasma levels of four miRNAs related to insulin signaling and beta-cell function were measured by RT-PCR. We analyzed the relationship between miRNAs levels and insulin signaling and release indexes at baseline and after the follow-up period. The risk of developing disease based on tertiles (T1-T2-T3) of baseline miRNAs levels was evaluated by COX analysis. Thus, we observed higher miR-150 and miR-30a-5p and lower miR-15a and miR-375 baseline levels in subjects with T2DM than in disease-free subjects. Patients with high miR-150 and miR-30a-5p baseline levels had lower disposition index (p = 0.047 and p = 0.007, respectively). The higher risk of disease was associated with high levels (T3) of miR-150 and miR-30a-5p (HR T3-T1  = 4.218 and HR T3-T1  = 2.527, respectively) and low levels (T1) of miR-15a and miR-375 (HR T1-T3  = 3.269 and HR T1-T3  = 1.604, respectively). In conclusion, our study showed that deregulated plasma levels of miR-150, miR-30a-5p, miR-15a, and miR-375 were observed years before the onset of T2DM and pre-DM and could be used to evaluate the risk of developing the disease, which may improve prediction and prevention among individuals at high risk for T2DM.

We sought to identify circulating microRNAs as biomarkers of prevalent or incident diabetes. In a pilot study of 18 sex- and age-matched patients with metabolic syndrome, nine of whom developed diabetes during 6 years of follow-up, an array of 372 microRNAs discovered significantly elevated serum levels of microRNAs -122, -192, -194, and -215 in patients who developed diabetes mellitus type 2 (T2DM). In two cross-sectional validation studies, one encompassing sex- and age-matched groups of patients with T2DM, impaired fasting glucose (IFG) and euglycemic controls (n = 43 each) and the other 53 patients with type 1 diabetes and 54 age- and BMI-matched euglycemic controls, serum levels of miR-192, miR-194, and mi215 were significantly higher in diabetic subjects than in probands with euglycemia or IFG. In a longitudinal study of 213 initially diabetes-free patients of whom 35 developed diabetes during 6 years of follow-up, elevated serum levels of microRNAs 192 and 194 were associated with incident T2DM, independently of fasting glucose, HbA1c and other risk factors. Serum levels of miR-192 and miR-194 were also elevated in diabetic Akt2 knockout mice compared to wild type mice. In conclusion, circulating microRNAs -192 and -194 are potential biomarkers for risk of diabetes.

We tested the hypothesis that the cumulative effects of common genetic variants related to elevated fasting glucose are collectively associated with oxidative stress. Using 25 single nucleotide polymorphisms (SNPs), a weighted genetic risk score (wGRS) was constructed by summing nine risk alleles based on nominal significance and a consistent effect direction in 1,395 controls and 718 patients with impaired fasting glucose (IFG) or newly diagnosed type 2 diabetes. All the participants were divided into the following three groups: low-wGRS, middle-wGRS, and high-wGRS groups. Among the nine SNPs, five SNPs were significantly associated with IFG and type 2 diabetes in this Korean population. wGRS was significantly associated with increased IFG and newly diagnosed type 2 diabetes (p = 6.83 × 10 -14 , odds ratio = 1.839) after adjusting for confounding factors. Among the IFG and type 2 diabetes patients, the fasting serum glucose and HbA 1c levels were significantly higher in the high-wGRS group than in the other groups. The urinary 8-epi-PGF 2α and malondialdehyde concentrations were significantly higher in the high-wGRS group than in the other groups. Moreover, general population-level instrumental variable estimation (using wGRS as an instrument) strengthened the causal effect regarding the largely adverse influence of high levels of fasting serum glucose on markers of oxidative stress in the Korean population. Thus, the combination of common genetic variants with small effects on IFG and newly diagnosed type 2 diabetes are significantly associated with oxidative stress.

Type 2 diabetes (T2DM) and pre-diabetes have become a major public health problem in China. We examined whether a higher dietary glycemic index (GI) or glycemic load (GL) was associated with a less favorable glucose homeostasis among Chinese adults and whether these associations were modified by their genetic predisposition or whether combined effects exist with their cereal fiber intake. Multivariable regression analyses were performed in 3918 adults aged 23-69 years for whom three 24-hour dietary recalls and information on glucose homeostasis, genetic background and potential confounders was available. Adults in the highest GI (GL) tertile had an approximately 9% (5%) higher fasting plasma glucose, 11% (3%) higher glycated haemoglobin, 12% (7%) higher insulin level, and 28% (22%) higher hepatic insulin resistance compared to those in the lowest tertile (adjusted p for-trend  ≤ 0.04). Moreover, a higher dietary GI or GL was associated with higher odds of pre-diabetes (p for-trend  = 0.03). These associations were more pronounced among persons with a high T2DM genetic risk score (p for-interaction  ≤ 0.06) or a low cereal fiber intake (p for-interaction  ≤ 0.05). In conclusion, our study indicates that the dietary GI or GL is of relevance for glucose homeostasis among Chinese adults, particularly among individuals genetically predisposed to T2DM.

Mitochondrial uncoupling protein 2 (UCP2) can affect oxidative stress levels. UCP2 polymorphisms are associated with leukocyte telomere length (LTL) in Type 2 Diabetes, which also induces considerable background oxidative stress. The effects of UCP2 polymorphisms on LTL in populations without diabetes have not been well described. Our aims are to evaluate the interaction between LTL and UCP2 polymorphisms in 950 subjects without diabetes. The monochrome multiplex quantitative PCR method was used to measure relative LTL. Taqman SNP genotyping assay was applied to genotypes for UCP2 rs659366 and rs660339. We found shorter LTL associated with increased age (P < 0.001) and triglyceride levels (P = 0.041). After adjustment for cardiovascular risk factors, rs659336 GG genotype carriers demonstrated a shorter LTL (1.257 ± 0.186), compared to GA carriers (1.288 ± 0.230, P = 0.022) and AA carriers (1.314 ± 0.253, P = 0.002). LTL was shorter in the CC rs660339 genotype (1.254 ± 0.187) compared to TT (1.297 ± 0.242, P = 0.007) and CT carriers (1.292 ± 0.229, P = 0.016). The T allele of rs660339 is associated with a longer LTL of approximately 0.04 compared to CC homozygotes. Thus, UCP2 rs659366 A allele and rs660339 T allele are both related to longer LTL in subjects without diabetes, independent of cardiovascular risk factors.

The clinical presentation of diabetes sometimes overlaps, contributing to ambiguity in the diagnosis. Thus, circulating pancreatic islet-enriched microRNAs (miRNAs) might be useful biomarkers of β-cell injury/dysfunction that would allow more accurate subtyping of diabetes. We measured plasma levels of selected miRNAs in subjects with prediabetes (n = 12), type 2 diabetes (T2D, n = 31), latent autoimmune diabetes of adults (LADA, n = 6) and type 1 diabetes (T1D, n = 16) and compared them to levels in healthy control subjects (n = 27). The study was conducted at the Translational Research Institute for Metabolism and Diabetes (TRI-MD), Florida Hospital. MiRNAs including miR-375 (linked to β-cell injury), miR-21 (associated with islet inflammation), miR-24.1, miR-30d, miR-34a, miR-126, miR-146, and miR-148a were significantly elevated in subjects with various forms of diabetes compared to healthy controls. Levels of several miRNAs were significantly correlated with glucose responses during oral glucose tolerance testing, HbA1c, β-cell function, and insulin resistance in healthy controls, prediabetes, and T2D. These data suggest that miRNAs linked to β-cell injury and islet inflammation might be useful biomarkers to distinguish between subtypes of diabetes. This information could be used to predict progression of the disease, guide selection of optimal therapy and monitor responses to interventions, thus improving outcomes in patients with diabetes.

We investigated the relationship between glycemic status and BMI and its interaction with obesity single-nucleotide polymorphisms (SNPs) in a multi-ethnic longitudinal cohort at high-risk for dysglycemia. We studied 17 394 participants from six ethnicities followed-up for 3.3 years. Twenty-three obesity SNPs were genotyped and an unweighted genotype risk score (GRS) was calculated. Glycemic status was defined using an oral glucose tolerance test. Linear regression models were adjusted for age, sex and population stratification. Normal glucose tolerance (NGT) to dysglycemia transition was associated with baseline BMI and BMI change. Impaired fasting glucose/impaired glucose tolerance to type 2 diabetes transition was associated with baseline BMI but not BMI change. No simultaneous significant main genetic effects and interactions between SNPs/GRS and glycemic status or transition on BMI level and BMI change were observed. Our data suggests that the interplay between glycemic status and BMI trajectory may be independent of the effects of obesity genes. This implies that individuals with different glycemic statuses may be combined together in genetic association studies on obesity traits, if appropriate adjustments for glycemic status are performed. Implementation of population-wide weight management programs may be more beneficial towards individuals with NGT than those at a later disease stage.

This work aimed to assess the maturation of the humoral immune response to insulin in preclinical type 1 diabetes by observing the emergence of various isotypes of insulin autoantibodies (IAA) in children with HLA-DQB1-conferred disease susceptibility. The series was derived from the Finnish Type 1 Diabetes Prediction and Prevention Study and comprised 15 IAA-positive children who presented with type 1 diabetes during prospective observation (progressors) and 30 children who remained nondiabetic (nonprogressors). An isotype-specific radiobinding assay was used to determine isotype-specific IAA (IgG1-4 and IgA) from samples obtained with an interval of 3-12 mo. The progressors had IAA of subclass IgG3 in their first IAA-positive sample more often than did the nonprogressors (13 of 15 versus 12 of 30; p = 0.003). Nine progressors had a dominant IgG1-IAA response initially, and six had a dominant IgG3-IAA response. The corresponding distribution among the nonprogressors was that 20 had a dominant IgG1-IAA response, none had an IgG3-IAA response, and three had a dominant response other than IgG1- or IgG3-IAA (chi(2)(df = 2) = 12.02; p = 0.002). The progressors had higher integrated levels (area under the curve) of IgG1-IAA (p = 0.05) and IgG3-IAA (p = 0.002). Nine progressors had a dominant integrated IgG1-IAA response and six had a dominant IgG3-IAA response over the observation period, whereas 22 nonprogressors had a dominant IgG1-IAA response, six had a dominant IgG2-IAA response, and one an IgG3-IAA response (chi(2)(df = 2) = 11.23; p = 0.004). Genetically susceptible young children who progress rapidly to clinical type 1 diabetes are characterized by strong IgG1 and IgG3 responses to insulin, whereas a weak or absent IgG3 response is associated with relative protection from disease.