scholarly journals Prenatal Malnutrition-Induced Epigenetic Dysregulation as a Risk Factor for Type 2 Diabetes

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Alexander Vaiserman ◽  
Oleh Lushchak
Keyword(s):  
Type 2 Diabetes ◽  
Critical Role ◽  
Regulation Of Gene Expression ◽  
Epidemiological Data ◽  
Later Life ◽  
Causal Link ◽  
Related Factors ◽  
Insulin Metabolism ◽  
Prenatal Malnutrition

Type 2 diabetes (T2D) is commonly regarded as a disease originating from lifestyle-related factors and typically occurring after the age of 40. There is, however, consistent experimental and epidemiological data evidencing that the risk for developing T2D may largely depend on conditions early in life. In particular, intrauterine growth restriction (IUGR) induced by poor or unbalanced nutrient intake can impair fetal growth and also cause fetal adipose tissue and pancreatic β-cell dysfunction. On account of these processes, persisting adaptive changes can occur in the glucose-insulin metabolism. These changes can include reduced ability for insulin secretion and insulin resistance, and they may result in an improved capacity to store fat, thereby predisposing to the development of T2D and obesity in adulthood. Accumulating research findings indicate that epigenetic regulation of gene expression plays a critical role in linking prenatal malnutrition to the risk of later-life metabolic disorders including T2D. In animal models of IUGR, changes in both DNA methylation and expression levels of key metabolic genes were repeatedly found which persisted until adulthood. The causal link between epigenetic disturbances during development and the risk for T2D was also confirmed in several human studies. In this review, the conceptual models and empirical data are summarized and discussed regarding the contribution of epigenetic mechanisms in developmental nutritional programming of T2D.

909-P: The Related Factors Accounting for the Discrepancy between Estimated Hemoglobin A1c Derived from CGMS and the Measured A1C in Patients with Type 2 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 909-P
Author(s):  
BEISI LIN ◽  
WEN XU ◽  
ZHIGU LIU ◽  
DAIZHI YANG ◽  
YANNA SU ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Hemoglobin A1c ◽  
Related Factors

scholarly journals MicroRNAs and Oxidative Stress: An Intriguing Crosstalk to Be Exploited in the Management of Type 2 Diabetes

Antioxidants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 802
Author(s):  
Teresa Vezza ◽  
Aranzazu M. de Marañón ◽  
Francisco Canet ◽  
Pedro Díaz-Pozo ◽  
Miguel Marti ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Type 2 Diabetes ◽  
Signaling Pathways ◽  
Current Knowledge ◽  
Critical Role ◽  
Cell Dysfunction ◽  
Non Coding Rnas ◽  
And Oxidative Stress ◽  
Molecular Crosstalk

Type 2 diabetes is a chronic disease widespread throughout the world, with significant human, social, and economic costs. Its multifactorial etiology leads to persistent hyperglycemia, impaired carbohydrate and fat metabolism, chronic inflammation, and defects in insulin secretion or insulin action, or both. Emerging evidence reveals that oxidative stress has a critical role in the development of type 2 diabetes. Overproduction of reactive oxygen species can promote an imbalance between the production and neutralization of antioxidant defence systems, thus favoring lipid accumulation, cellular stress, and the activation of cytosolic signaling pathways, and inducing β-cell dysfunction, insulin resistance, and tissue inflammation. Over the last few years, microRNAs (miRNAs) have attracted growing attention as important mediators of diverse aspects of oxidative stress. These small endogenous non-coding RNAs of 19–24 nucleotides act as negative regulators of gene expression, including the modulation of redox signaling pathways. The present review aims to provide an overview of the current knowledge concerning the molecular crosstalk that takes place between oxidative stress and microRNAs in the physiopathology of type 2 diabetes, with a special emphasis on its potential as a therapeutic target.

scholarly journals Dietary Copper/Zinc Ratio and Type 2 Diabetes Risk in Women: The E3N Cohort Study

Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2502
Author(s):  
Nasser Laouali ◽  
Conor-James MacDonald ◽  
Sanam Shah ◽  
Douae El Fatouhi ◽  
Francesca Romana Mancini ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cohort Study ◽  
Important Determinant ◽  
Epidemiological Data ◽  
Serum Copper ◽  
Obese Women ◽  
Dietary Copper ◽  
Zinc Intake ◽  
Copper Zinc

The serum copper (Cu) to zinc (Zn) ratio could be an important determinant of Type 2 diabetes (T2D) risk, but prospective epidemiological data are scarce. We aimed to investigate the association between T2D incidence and the dietary Cu/Zn ratio. A total of 70,991 women from the E3N cohort study were followed for 20 years. The intakes of copper and zinc were estimated at baseline using a validated food frequency questionnaire. We identified and validated 3292 incident T2D cases. Spline analysis showed that a Cu/Zn ratio < 0.55 was associated with a lower risk of T2D. Subgroup analyses comparing women in the highest versus the lowest quintile of Cu/Zn ratio showed the same pattern of association for obese women and those with zinc intake ≥8 mg/day. However, for women with zinc intake <8 mg/day, higher Cu/Zn ratio appeared to be associated with higher T2D risk. Our findings suggest that a lower dietary Cu/Zn ratio is associated with a lower T2D risk, especially among obese women and women with zinc intake >8 mg/day. Further studies are warranted to validate our results.

scholarly journals Psychometric evaluation of the DAILY EATS questionnaire in individuals living with obesity

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
John Fastenau ◽  
Heather Rozjabek ◽  
Shanshan Qin ◽  
Lori McLeod ◽  
Lauren Nelson ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Severe Obesity ◽  
Short Form ◽  
Psychometric Evaluation ◽  
Health Determinants ◽  
Measurement Information ◽  
Related Factors ◽  
Patient Global Impression ◽  
Patient Reported

Abstract Background Physiological and behavioral factors including hunger, satiety, food intake, and cravings are health determinants contributing to obesity. Patient-reported outcome (PRO) measures focused on eating-related factors provide insight into the relationships between food choice and quantity, weight change, and weight-loss treatment for individuals living with obesity. The DAILY EATS is a novel 5-item, patient-reported measure evaluating key eating-related factors (Worst and Average Hunger, Appetite, Cravings, and Satiety). Methods Psychometric analyses, consistent with regulatory standards, were conducted to evaluate the DAILY EATS using data from two randomized trials that included individuals with severe obesity without diabetes (NCT03486392) and with severe obesity and type 2 diabetes (NCT03586830). Additional measures included Patient Global Impression of Status (PGIS) and Patient Global Impression of Change items, Impact of Weight on Quality of Life-Lite, Ease of Weight Management, and Patient-Reported Outcomes Measurement Information System Physical Function Short Form 8b and 10a. The reliability, validity, and responsiveness of the DAILY EATS were assessed, and a scoring algorithm and thresholds to interpret meaningful score changes were developed. Results Item-level analyses of the DAILY EATS supported computation of an Eating Drivers Index (EDI), comprising the related items Worst Hunger, Appetite, and Cravings. Internal consistency (Cronbach’s coefficient alphas ≥0.80) and test-retest reliability (coefficients > 0.7) of the EDI were robust. Construct validity correlation patterns with other PRO measures were as hypothesized, with moderate to strong significant correlations between the EDI and PGIS-Hunger (0.30 ≤ r ≤ 0.68), PGIS-Cravings (0.33 ≤ r ≤ 0.77) and PGIS-Appetite (0.52 ≤ r ≤ 0.77). Anchor- and distribution-based analyses support reductions ranging from 1.6 to 2.1 as responder thresholds for the EDI, representing meaningful within-person improvement. Conclusions The DAILY EATS individual items and the composite EDI are reliable, sensitive, and valid in evaluating the concepts of hunger, appetite, and cravings for use in individuals with severe obesity with or without type 2 diabetes.

Determining the Cardiovascular Disease Risk Factor Knowledge and Related Factors Among Adults With Type 2 Diabetes Mellitus

2021 ◽  
pp. 105477382110464
Author(s):  
Emine Karaman ◽  
Aslı Kalkım ◽  
Banu Pınar Şarer Yürekli
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Related Factors

In this study was to determine knowledge of cardiovascular disease (CVD) risk factors and to explore related factors among adults with type 2 diabetes mellitus (DM) who have not been diagnosed with CVD. This descriptive study was conducted with 175 adults. Data were collected individual identification form and Cardiovascular Disease Risk Factors Knowledge Level (CARRF-KL) scale. A negative correlation was found between age and CARRF-KL score. A significant difference was found between educational status and CARRF-KL score. The individuals described their health status as good, managed their condition with diet and exercise, received information from nurses, adults with DM in their family and those with no DM complications had significantly higher scores in CARRF-KL. The knowledge of an individual with DM about CVD risk factors should be assessed, CVD risks should be identified at an early stage, and individuals at risk should be subjected to screening.

scholarly journals Applying decision tree for detection of a low risk population for type 2 diabetes: A population based study

2017 ◽  
Vol 1 (4) ◽  
pp. 132-132
Author(s):  
Habibollah Esmaeily ◽  
Maryam Tayefi ◽  
Hassan Doosti ◽  
Majid Ghayour-Mobarhan ◽  
Ali Reza Amirabadizadeh
Keyword(s):  
Type 2 Diabetes ◽  
Decision Tree ◽  
Prediction Model ◽  
Roc Curve ◽  
Population Based ◽  
Low Risk ◽  
Tree Model ◽  
Related Factors ◽  
Study Program

Introduction: The aim of current study was to create a prediction model using data mining approach, decision tree technique, to identify low risk individuals for incidence of Type 2 diabetes (T2DM), using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. Methods: a prediction model was developed using classification by the decision tree method on 9528 subjects recruited from MASHAD database. Moreover, the receiver operating characteristic (ROC) curve was applied. Results: The prevalence rate of T2DM was ~14% in our population. For decision tree model, the accuracy, sensitivity, and specificity value for identifying the related factors with T2DM were 78.7%, 47.8% and 83%, respectively. In addition, the area under the ROC curve (AUC) value for recognizing the risk factors associated with T2DM was 0.64. Moreover, we found that subjects with family history of T2DM, age>=48, SBP>=130, DBP>=81, HDL>=29, LDL>=148 and occupation=other have more than 59% chance of this disorder, while the chance of T2DM in subjects without history with TG>=184, age>=48 and hs-CRP>=2.2, have approximately 51% chance. Conclusion: Our findings demonstrated that decision tree analysis, using routine demographic, clinical, anthropometric and biochemical measurements, which combined with other risk score models, could create a simple strategy to predict individuals at low risk for type 2 diabetes in order to decrease substantially the number of subjects needing for screening and recognition of subject at high risk.

scholarly journals RFX6-mediated dysregulation defines human β cell dysfunction in early type 2 diabetes

2021 ◽  
Author(s):  
John T Walker ◽  
Diane C Saunders ◽  
Vivek Rai ◽  
Chunhua Dai ◽  
Peter Orchard ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Secretion ◽  
Association Studies ◽  
Critical Role ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Β Cells ◽  
Β Cell ◽  
Gene Regulatory

A hallmark of type 2 diabetes (T2D), a major cause of world-wide morbidity and mortality, is dysfunction of insulin-producing pancreatic islet β cells. T2D genome-wide association studies (GWAS) have identified hundreds of signals, mostly in the non-coding genome and overlapping β cell regulatory elements, but translating these into biological mechanisms has been challenging. To identify early disease-driving events, we performed single cell spatial proteomics, sorted cell transcriptomics, and assessed islet physiology on pancreatic tissue from short-duration T2D and control donors. Here, through integrative analyses of these diverse modalities, we show that multiple gene regulatory modules are associated with early-stage T2D β cell-intrinsic defects. One notable example is the transcription factor RFX6, which we show is a highly connected β cell hub gene that is reduced in T2D and governs a gene regulatory network associated with insulin secretion defects and T2D GWAS variants. We validated the critical role of RFX6 in β cells through direct perturbation in primary human islets followed by physiological and single nucleus multiome profiling, which showed reduced dynamic insulin secretion and large-scale changes in the β cell transcriptome and chromatin accessibility landscape. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs, and individuals and thus we anticipate this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits with GWAS data.

scholarly journals Interaction of Polygenetic Variants for Gestational Diabetes Mellitus Risk with Breastfeeding and Korean Balanced Diet to Influence Type 2 Diabetes Risk in Later Life in a Large Hospital-Based Cohort

2021 ◽  
Vol 11 (11) ◽  
pp. 1175
Author(s):  
Sunmin Park
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Gestational Diabetes ◽  
Genetic Variants ◽  
Genetic Variant ◽  
Later Life ◽  
Serum Glucose ◽  
Large Hospital ◽  
Balanced Diet

The etiologies of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) are similar. Genetic and environmental factors interact to influence the risk of both types of diabetes. We aimed to determine if the polygenetic risk scores (PRS) for GDM risk interacted with lifestyles to influence type 2 diabetes risk in women aged >40 years in a large hospital-based city cohort. The participants with GDM diagnosis without T2DM before pregnancy were considered the case group (n=384) and those without GDM and T2DM as the control (n=33,956) to explore GDM-related genetic variants. The participants with T2DM were the case (n=2550), and the control (n=33,956) was the same as GDM genetic analysis for the interaction analysis of GDM genetic risk with lifestyles to influence T2DM risk. The genetic variants for the GDM risk were selected from a genome-wide association study (GWAS), and their PRS from the best model with gene-gene interactions were generated. GDM was positively associated with age at first pregnancy, body mass index(BMI) at age 20, and education level. A previous GDM diagnosis increased the likelihood of elevated fasting serum glucose concentrations and HbA1c contents by 8.42 and 9.23 times in middle-aged and older women. However, it was not associated with the risk of any other metabolic syndrome components. Breast-feeding(≥1 year) was inversely associated with the T2DM risk in later life. In the genetic variant-genetic variant interaction, the best model with 5-SNPs included PTPRD_rs916855529, GPC6_rs9589710, CDKAL1_rs7754840, PRKAG2 _rs11975504, and PTPRM_rs80164908. The PRS calculated from the 5-SNP model was positively associated with the GDM risk by 3.259(2.17−4.89) times after adjusting GDM-related covariates. The GDM experience interacted with PRS for the T2DM risk. Only in non-GDM women PRS was positively associated with T2DM risk by 1.36-times. However, long breastfeeding did not interact with the PRS for T2DM risk. Among dietary patterns, only a Korean-style balanced diet (KBD) showed an interaction with PRS for the T2DM risk. Participants with a low-PRS had the lowest serum glucose concentrations in the high KBD intake but not low KBD intake. In conclusion, participants with a high PRS for GDM risk are positively associated with T2DM risk, and breastfeeding for ≥1 year and consuming KBD offset the PRS for GDM risk to influence T2DM risk in middle-aged and older.

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