Risk scores for predicting incidence of type 2 diabetes in the Chinese population: the Kailuan prospective study.
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SUBMITTER: Wang A
PROVIDER: S-EPMC4879553 | biostudies-other | 2016
REPOSITORIES: biostudies-other
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Project description:BackgroundBoth lifestyle and genetic predisposition determine the development of type 2 diabetes (T2D), and studies have indicated interactions between specific dietary components and individual genetic variants. However, it is unclear whether the importance of overall dietary habits, including T2D-related food intakes, differs depending on genetic predisposition to T2D. We examined interaction between a genetic risk score for T2D, constructed from 48 single nucleotide polymorphisms identified in genome-wide association studies, and a diet risk score of four foods consistently associated with T2D in epidemiological studies (processed meat, sugar-sweetened beverages, whole grain and coffee). In total, 25,069 individuals aged 45-74 years with genotype information and without prevalent diabetes from the Malmö Diet and Cancer cohort (1991-1996) were included. Diet data were collected with a modified diet history method.ResultsDuring 17-year follow-up, 3588 incident T2D cases were identified. Both the diet risk score (HR in the highest risk category 1.40; 95% CI 1.26, 1.58; P trend = 6 × 10-10) and the genetic risk score (HR in the highest tertile of the genetic risk score 1.67; 95% CI 1.54, 1.81; P trend = 7 × 10-35) were associated with increased incidence of T2D. No significant interaction between the genetic risk score and the diet risk score (P = 0.83) or its food components was observed. The highest risk was seen among the 6% of the individuals with both high genetic and dietary risk scores (HR 2.49; 95% CI 2.06, 3.01).ConclusionsThe findings thus show that both genetic heredity and dietary habits previously associated with T2D add to the risk of T2D, but they seem to act in an independent fashion, with the consequence that all individuals, whether at high or low genetic risk, would benefit from favourable food choices.
| S-EPMC5956794 | biostudies-literature
Project description:Type 2 diabetes (T2D) and cardiovascular disease (CVD) represent significant disease burdens for most societies and susceptibility to these diseases is strongly influenced by diet and lifestyle. Physiological changes associated with T2D or CVD, such has high blood pressure and cholesterol and glucose levels in the blood, are often apparent prior to disease incidence. Here we integrated genetics, lipidomics, and standard clinical diagnostics to assess future T2D and CVD risk for 4,067 participants from a large prospective population-based cohort, the Malmö Diet and Cancer-Cardiovascular Cohort. By training Ridge regression-based machine learning models on the measurements obtained at baseline when the individuals were healthy, we computed several risk scores for T2D and CVD incidence during up to 23 years of follow-up. We used these scores to stratify the participants into risk groups and found that a lipidomics risk score based on the quantification of 184 plasma lipid concentrations resulted in a 168% and 84% increase of the incidence rate in the highest risk group and a 77% and 53% decrease of the incidence rate in lowest risk group for T2D and CVD, respectively, compared to the average case rates of 13.8% and 22.0%. Notably, lipidomic risk correlated only marginally with polygenic risk, indicating that the lipidome and genetic variants may constitute largely independent risk factors for T2D and CVD. Risk stratification was further improved by adding standard clinical variables to the model, resulting in a case rate of 51.0% and 53.3% in the highest risk group for T2D and CVD, respectively. The participants in the highest risk group showed significantly altered lipidome compositions affecting 167 and 157 lipid species for T2D and CVD, respectively. Our results demonstrated that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence. The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays.
| S-EPMC8893343 | biostudies-literature
Project description:OBJECTIVE:To estimate the incidence densities and cumulative incidence of diabetes-related complications in patients with type 1 diabetes for a maximum of 15-year follow-up. The estimations were further stratified by gender and age at diagnosis (ie, early onset: 0-12 years, late onset:?13 years). DESIGN:A population-based retrospective longitudinal cohort study. SETTING:Taiwan's National Health Insurance medical claims. PARTICIPANTS:4007 patients newly diagnosed with type 1 diabetes were identified during 1999-2012. OUTCOME MEASURES:Acute complications included diabetic ketoacidosis (DKA) and hypoglycaemia. Chronic complications were cardiovascular diseases (CVD), retinopathy, neuropathy and nephropathy. RESULTS:The incidence density of retinopathy was greatest (97.74 per 1000 person-years), followed by those of nephropathy (31.36), neuropathy (23.93) and CVD (4.39). Among acute complications, the incidence density of DKA was greatest (121.11 per 1000 person-years). The cumulative incidences of acute complications after 12 years following diagnosis were estimated to be 52.1%, 36.1% and 4.1% for DKA, outpatient hypoglycaemia and hospitalised hypoglycaemia, respectively. For chronic complications, the cumulative incidence of retinopathy after 12 years following diagnosis was greatest (65.2%), followed by those of nephropathy (30.2%), neuropathy (23.7%) and CVD (4.1%). Females with late-onset diabetes were greatly affected by advanced retinopathy (ie, sight-threatening diabetic retinopathy) and hospitalised hypoglycaemia, whereas those with early-onset diabetes were more vulnerable to DKA. Chronic complications were more commonly seen in late-onset diabetes, whereas early-onset diabetes were most affected by acute complications. CONCLUSIONS:Ethnic Chinese patients with type 1 diabetes were greatly affected by DKA and retinopathy. The incidence of diabetes-related complications differed by age at diagnosis and sex.
| S-EPMC5791549 | biostudies-literature
Project description:Background: Around 0.3% of newborns will develop autoimmunity to pancreatic beta cells in childhood and subsequently develop type 1 diabetes before adulthood. Primary prevention of type 1 diabetes will require early intervention in genetically at-risk infants. The objective of this study was to determine to what extent genetic scores (two previous genetic scores and a merged genetic score) can improve the prediction of type 1 diabetes.Methods and findings: The Environmental Determinants of Diabetes in the Young (TEDDY) study followed genetically at-risk children at 3- to 6-monthly intervals from birth for the development of islet autoantibodies and type 1 diabetes. Infants were enrolled between 1 September 2004 and 28 February 2010 and monitored until 31 May 2016. The risk (positive predictive value) for developing multiple islet autoantibodies (pre-symptomatic type 1 diabetes) and type 1 diabetes was determined in 4,543 children who had no first-degree relatives with type 1 diabetes and either a heterozygous HLA DR3 and DR4-DQ8 risk genotype or a homozygous DR4-DQ8 genotype, and in 3,498 of these children in whom genetic scores were calculated from 41 single nucleotide polymorphisms. In the children with the HLA risk genotypes, risk for developing multiple islet autoantibodies was 5.8% (95% CI 5.0%-6.6%) by age 6 years, and risk for diabetes by age 10 years was 3.7% (95% CI 3.0%-4.4%). Risk for developing multiple islet autoantibodies was 11.0% (95% CI 8.7%-13.3%) in children with a merged genetic score of >14.4 (upper quartile; n = 907) compared to 4.1% (95% CI 3.3%-4.9%, P < 0.001) in children with a genetic score of ?14.4 (n = 2,591). Risk for developing diabetes by age 10 years was 7.6% (95% CI 5.3%-9.9%) in children with a merged score of >14.4 compared with 2.7% (95% CI 1.9%-3.6%) in children with a score of ?14.4 (P < 0.001). Of 173 children with multiple islet autoantibodies by age 6 years and 107 children with diabetes by age 10 years, 82 (sensitivity, 47.4%; 95% CI 40.1%-54.8%) and 52 (sensitivity, 48.6%, 95% CI 39.3%-60.0%), respectively, had a score >14.4. Scores were higher in European versus US children (P = 0.003). In children with a merged score of >14.4, risk for multiple islet autoantibodies was similar and consistently >10% in Europe and in the US; risk was greater in males than in females (P = 0.01). Limitations of the study include that the genetic scores were originally developed from case-control studies of clinical diabetes in individuals of mainly European decent. It is, therefore, possible that it may not be suitable to all populations.Conclusions: A type 1 diabetes genetic score identified infants without family history of type 1 diabetes who had a greater than 10% risk for pre-symptomatic type 1 diabetes, and a nearly 2-fold higher risk than children identified by high-risk HLA genotypes alone. This finding extends the possibilities for enrolling children into type 1 diabetes primary prevention trials.
| S-EPMC5882115 | biostudies-literature
Project description:ObjectiveTo establish a rapid, cost-effective, accurate, and acceptable osteoporosis (OP) screening model for the Chinese male population (age ≥ 40 years) based on data mining technology.Materials and methodsThis was a 3-year retrospective cohort study, which belonged to the sub-cohort of the Chinese Reaction Study. The research period was from March 2011 to December 2014. A total of 1834 subjects who did not have OP at the baseline and completed a 3-year follow-up were included in this study. All subjects underwent quantitative ultrasound examinations for calcaneus at the baseline and follow-ups that lasted for 3 years. We utilized the least absolute shrinkage and selection operator (LASSO) regression model to select feature variables. The characteristic variables selected in the LASSO regression were analyzed by multivariable logistic regression (MLR) to construct the predictive model. This predictive model was displayed through a nomogram. We used the receiver operating characteristic (ROC) curve, C-index, calibration curve, and clinical decision curve analysis (DCA) to evaluate model performance and the bootstrapping validation to internally validate the model.ResultsThe predictive factors included in the prediction model were age, neck circumference, waist-to-height ratio, BMI, triglyceride, impaired fasting glucose, dyslipidemia, osteopenia, smoking history, and strenuous exercise. The area under the ROC (AUC) curve of the risk nomogram was 0.882 (95% CI, 0.858-0.907), exhibiting good predictive ability and performance. The C-index for the risk nomogram was 0.882 in the prediction model, which presented good refinement. In addition, the nomogram calibration curve indicated that the prediction model was consistent. The DCA showed that when the threshold probability was between 1 and 100%, the nomogram had a good clinical application value. More importantly, the internally verified C-index of the nomogram was still very high, at 0.870.ConclusionsThis novel nomogram can effectively predict the 3-year incidence risk of OP in the male population. It also helps clinicians to identify groups at high risk of OP early and formulate personalized intervention measures.
| S-EPMC8494413 | biostudies-literature
Project description:BackgroundThe purpose of this study was to evaluate the effect of single-nucleotide polymorphisms (SNPs) of the GCKR and G6PC2 genes on risk for type 2 diabetes and the SNP-SNP and haplotype-based interactions between these genes.MethodsSubjects of this nested case-control study were selected from a prospective cohort residing in the rural area of Luoyang city in China. Cases (n = 538) were individually matched with controls. Six SNPs in the GCKR and G6PC2 genes were selected and genotyped using an SNPscan™ kit. Stratified Cox proportional hazards regression models were used to generate odds ratios (ORs) and 95% confidence intervals (CI) for different genotype models for the risk of T2DM. Generalized multifactor dimensionality reduction (GMDR) was used to analyze the interactions between two genes with among six SNPs. The linkage disequilibrium (LD) analysis and the haplotype analysis were carried out by SHEsis online.ResultsWe found that the C allele of rs780094 was associated with increased risk for T2DM in Han Chinese population. However, the rs492594-C allele in G6PC2 was associated with a decreased risk of T2DM. We also found a significant SNP-SNP interaction between rs2293572 and rs492594, and the CCCCGC and CGCCCA haplotypes significantly increased the risk of T2DM, however, the CCCCCA haplotype had lower susceptibility to T2DM.ConclusionThe results suggest that the GCKR and G6PC2 genes may contribute to the risk of T2DM independently and/or in an interactive manner in the Han Chinese population.
| S-EPMC6064617 | biostudies-literature
Project description:We compared the increases in the prevalence of gestational diabetes mellitus (GDM) based on the 1999 World Health Organization (WHO) criteria and its risk factors in Tianjin, China, over a 12-year period. We also examined the changes in the prevalence using the criteria of International Association of Diabetes and Pregnancy Study Group (IADPSG).In 2010-2012, 18589 women who registered within 12 weeks of gestation underwent a glucose challenge test (GCT) at 24-28 gestational weeks. Amongst them, 2953 women with 1-hour plasma glucose ≥ 7.8 mmol/L underwent a 75-gram 2-hour oral glucose tolerance test (OGTT) and 781 women had a positive GCT but absented from the standard OGTT. An adjusted prevalence of GDM was calculated for the whole cohort of women by including an estimate of the proportion of women with positive GCTs who did not have OGTTs but would have been expected to have GDM. Logistic regression was used to obtain odds ratios and 95% confidence intervals using the IADPSG criteria. The prevalence of GDM risk factors was compared to the 1999 survey.The adjusted prevalence of GDM by the 1999 WHO criteria was 8.1%, a 3.5-fold increase as in 1999. Using the IADPSG criteria increased the adjusted prevalence further to 9.3%. Advanced age, higher pre-pregnancy body mass index, Han-nationality, higher systolic blood pressure (BP), a family history of diabetes, weight gain during pregnancy and habitual smoking were risk factors for GDM. Compared to the 1999 survey, the prevalence of overweight plus obesity had increased by 1.8 folds, age ≥ 30 years by 2.3 folds, systolic BP by 2.3 mmHg over the 12-year period.Increasing prevalence of overweight/obesity and older age at pregnancy were accompanied by increasing prevalence of GDM, further increased by change in diagnostic criteria.
| S-EPMC4370728 | biostudies-other
Project description:Growing evidence has linked posttraumatic stress disorder (PTSD) to insulin resistance and type-2 diabetes, but most previous studies were cross-sectional. We examined the association between PTSD and incidence of diabetes in a prospective study of middle-aged male twins from the Vietnam Era Twin Registry. Lifetime PTSD was diagnosed at baseline with the Diagnostic Interview Schedule (DIS) according to DSM-III-R criteria. Subthreshold PTSD was defined by meeting some, but not all, criteria for PTSD. A total of 4340 respondents without self-reported diabetes at baseline were included. Of these, 658 reported a new diagnosis of treated diabetes over a median of 19.4 years of follow-up. At baseline, twins with PTSD showed more behavioral and metabolic risk factors such as overweight and hypertension. The age-adjusted cumulative incidence of diabetes was significantly higher in twins with PTSD (18.9%) than those without PTSD (14.4%), [odds ratio (OR) = 1.4, 95% confidence interval (CI) 1.03-1.8], and intermediate in those with subthreshold PTSD (16.4%) (OR = 1.2, 95% CI 0.9-1.5, p for trend = 0.03). Adjustment for military, lifestyle and metabolic factors diminished the association. No significant association was found comparing twin pairs discordant for PTSD. In conclusion, PTSD was prospectively associated with a 40% increased risk of new-onset type-2 diabetes which was partially explained by a cluster of metabolic and behavioral risk factors known to influence insulin resistance. Shared biological or behavioral precursors which occur within families may lead to both PTSD and insulin resistance/diabetes. Thus, PTSD could be a marker of neuroendocrine and metabolic dysregulation which may lead to type-2 diabetes.
| S-EPMC4086302 | biostudies-literature
Project description:To estimate the incidence of type 1 diabetes in all age groups in China during 2010-13.Population based, registry study using data from multiple independent sources.National registration system in all 505 hospitals providing diabetes care, and communities of patients with diabetes in 13 areas across China, covering more than 133 million person years at risk, approximately 10% of the whole population.5018 people of all ages with newly diagnosed type 1 diabetes and resident in the study areas from 1 January 2010 to 31 December 2013.Incidence of type 1 diabetes per 100?000 person years by age, sex, and study area. Type 1 diabetes was doctor diagnosed and further validated by onsite follow-up. Completeness of case ascertainment was assessed using the capture mark recapture method.5018 cases of newly diagnosed type 1 diabetes were ascertained: 1239 participants were aged <15 years, 1799 were aged 15-29 years, and 1980 were aged ?30 years. The proportion of new onset cases in participants aged ?20 years was 65.3%. The estimated incidence of type 1 diabetes per 100?000 persons years for all ages in China was 1.01 (95% confidence interval 0.18 to 1.84). Incidence per 100?000 persons years by age group was 1.93 (0.83 to 3.03) for 0-14 years, 1.28 (0.45 to 2.11) for 15-29 years, and 0.69 (0.00 to 1.51) for ?30 years, with a peak in age group 10-14 years. The incidence in under 15s was positively correlated with latitude (r=0.88, P<0.001), although this association was not observed in age groups 15-29 years or ?30 years.Most cases of new onset type 1 diabetes in China occurred among adults. The incidence of type 1 diabetes in Chinese children was among the lowest reported in the study.
| S-EPMC5750780 | biostudies-literature
Project description:Using data from the China Kadoorie Biobank Study, we conducted a prospective investigation on the association between type 2 diabetes mellitus (T2DM) and cancer risk in Chinese adults. A total of 508,892 participants (mean age = 51.5 (standard deviation, 10.7) years) without prior cancer diagnosis at baseline (2004-2008) were included. We documented 17,463 incident cancer cases during follow-up through December 31, 2013. Participants with T2DM had increased risks of total and certain site-specific cancers; hazard ratios were 1.13 (95% confidence interval (CI): 1.07, 1.19) for total cancer, 1.51 (95% CI: 1.29, 1.76) for liver cancer, 1.86 (95% CI: 1.43, 2.41) for pancreatic cancer, and 1.21 (95% CI: 1.01, 1.47) for female breast cancer. The associations were largely consistent when physician-diagnosed and screen-detected T2DM were analyzed separately, except for colorectal cancer (for physician-diagnosed T2DM, HR = 0.91 (95% CI: 0.73, 1.13), and for screen-detected T2DM, HR = 1.44 (95% CI: 1.18, 1.77)). In participants without a prior diagnosis of T2DM, higher random blood glucose levels were positively associated with risks of total cancer, liver cancer, and female breast cancer (all P's for trend ? 0.02). In conclusion, T2DM is associated with an increased risk of new-onset cancer in China, particularly cancers of the liver, pancreas, and female breast.
| S-EPMC6153481 | biostudies-literature