Nutrition & Diabetes最新文献

Analyzing changes in gene expression within specific brain regions of individuals with Type 2 Diabetes (T2DM) who do not exhibit significant cognitive deficits can yield valuable insights into the mechanisms underlying the progression towards a more severe phenotype. In this study, transcriptomic analysis of the cortex and hippocampus of mice with long-term T2DM revealed alterations in the expression of 28 genes in the cerebral cortex and 15 genes in the hippocampus. Among these genes, six displayed consistent changes in both the cortex and hippocampus: Interferon regulatory factor 7 (Irf7), Hypoxia-inducible factor 3 alpha (Hif-3α), period circadian clock 2 (Per2), xanthine dehydrogenase (Xdh), and Transforming growth factor β-stimulated clone 22/TSC22 (Tsc22d3) were upregulated, while Claudin-5 (Cldn5) was downregulated. Confirmation of these changes was achieved through RT-qPCR. At the protein level, CLDN5 and IRF7 exhibited similar alterations, with CLDN5 being downregulated and IRF7 being upregulated. In addition, the hippocampus and cortex of the T2DM mice showed decreased levels of IκBα, implying the involvement of NF-κB pathways as well. Taken together, these results suggest that the weakening of the blood-brain barrier and an abnormal inflammatory response via the Interferon 1 and NF-κB pathways underlie cognitive impairment in individuals with long-standing T2DM.

Background: With the fast pace of modern life, people have less time for meals, but few studies have examined the association between the habit of fast eating and metabolic diseases.

Objective: Combining the results of the current study and the prior ones, we aimed to investigate the possible relationship between fast eating and the risk of metabolic dysfunction-associated steatotic liver disease (MASLD).

Methods: This is a sub-analysis of a multicenter cross-sectional study of 1965 participants investigated the association between fast eating and MASLD in Chinese. Fast eating was defined as meal time less than five minutes and participants were divided into three categories based on their self-reported frequency of fast eating: ≤1 time/month, ≤1 time/week and ≥2 times/week. We further conducted a literature search for available studies published before November, 2023 as well as a meta-analysis to investigate the association between fast eating and MASLD.

Results: The proportion of MASLD was 59.3%, 50.5%, and 46.2% in participants with fast eating ≥2 times/week, ≤1 time/week and ≤1 time/month, respectively (P for trend <0.001). The frequency of fast eating was independently associated with risk of MASLD after multiple adjustment for sex, age, demographics, smoking and drinking status, BMI and clinical metabolic parameters (OR, 1.29; 95%CI, 1.09-1.53). Participants who ate fast frequently (≥2 times/week) had 81% higher risk of MASLD (P = 0.011). A meta-analysis of five eligible studies confirmed that frequent fast eating was associated with increased risk of MASLD (pooled OR, 1.22; 95%CI, 1.07-1.39).

Conclusions: Frequent fast eating was associated with an increased risk of MASLD.

Background & aim: Chronic kidney disease (CKD) is a heterogeneous disorder that affects the kidney structure and function. This study investigated the effect of the interaction between genetic factors and dietary pattern on kidney dysfunction in Korean adults.

Methods: Baseline data were obtained from the Ansan and Ansung Study of the Korean Genome and Epidemiology Study involving 8230 participants aged 40-69 years. Kidney dysfunction was defined as an estimated glomerular filtration rate < 90 mL/minute/1.73 m². Genomic DNAs genotyped on the Affymetrix® Genome-Wide Human SNP array 5.0 were isolated from peripheral blood. A genome-wide association study using a generalized linear model was performed on 1,590,162 single-nucleotide polymorphisms (SNPs). To select significant SNPs, the threshold criterion was set at P-value < 5 × 10^-8. Linkage disequilibrium clumping was performed based on the R² value, and 94 SNPs had a significant effect. Participants were divided into two groups based on their generic risk score (GRS): the low-GR group had GRS > 0, while the high-GR group had GRS ≤ 0.

Results: Three distinct dietary patterns were extracted, namely, the "prudent pattern," "flour-based and animal food pattern," and "white rice pattern," to analyze the effect of dietary pattern on kidney function. In the "flour-based and animal food pattern," higher pattern scores were associated with a higher prevalence of kidney dysfunction in both the low and high GR groups (P for trend < 0.0001 in the low-, high-GR groups of model 1; 0.0050 and 0.0065 in the low-, high-GR groups of model 2, respectively).

Conclusions: The results highlight a significant association between the 'flour-based and animal food pattern' and higher kidney dysfunction prevalence in individuals with both low and high GR. These findings suggest that personalized nutritional interventions based on GR profiles may become the basis for presenting GR-based individual dietary patterns for kidney dysfunction.

Background: Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction. This imbalance often results in models performing poorly in predicting minority classes, affecting overall diagnostic performance.

Objectives: To address this issue, this study employs a combination of Synthetic Minority Over-sampling Technique (SMOTE) and Random Under-Sampling (RUS) for data balancing and uses Optuna for hyperparameter optimization of machine learning models. This approach aims to fill the gap in current research concerning data balancing and model optimization, thereby improving prediction accuracy and computational efficiency.

Methods: First, the study uses SMOTE and RUS methods to process the imbalanced diabetes dataset, balancing the data distribution. Then, Optuna is utilized to optimize the hyperparameters of the LightGBM model to enhance its performance. During the experiment, the effectiveness of the proposed methods is evaluated by comparing the training results of the dataset before and after balancing.

Results: The experimental results show that the enhanced LightGBM-Optuna model improves the accuracy from 97.07% to 97.11%, and the precision from 97.17% to 98.99%. The time required for a single search is only 2.5 seconds. These results demonstrate the superiority of the proposed method in handling imbalanced datasets and optimizing model performance.

Conclusions: The study indicates that combining SMOTE and RUS data balancing algorithms with Optuna for hyperparameter optimization can effectively enhance machine learning models, especially in dealing with imbalanced datasets for diabetes prediction.

Background: Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) are prevalent metabolic disorders with overlapping pathophysiological mechanisms. A comprehensive understanding of the shared molecular pathways involved in these conditions can advance the development of effective therapeutic interventions.

Methods: We used two datasets sourced from the Gene Expression Omnibus (GEO) database to identify common differentially expressed genes (DEGs) between T2D and NAFLD. Subsequently, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to identify the enriched biological processes and signaling pathways. In addition, we performed a protein-protein interaction (PPI) network analysis to identify hub genes with pivotal roles. To validate our findings, we established a type 2 diabetic mouse model with NAFLD.

Results: Our analysis identified 53 DEGs shared between T2D and NAFLD. Enrichment analysis revealed their involvement in signal transduction, transcriptional regulation, and cell proliferation as well as in the ferroptosis signaling pathways. PPI network analysis identified ten hub genes, namely CD44, CASP3, FYN, KLF4, HNRNPM, HNRNPU, FUBP1, RUNX1, NOTCH3, and ANXA2. We validated the differential expression of FYN, HNRNPU, and FUBP1 in liver tissues of a type 2 diabetic mouse model with NAFLD.

Conclusions: Our study offers valuable insights into the shared molecular mechanisms underlying T2D and NAFLD. The identified hub genes and pathways present promising prospects as therapeutic targets to address these prevalent metabolic disorders.

Background: Due to the essential role of calcium in vital biological functions, diet low in calcium (DLC) is associated with various diseases. However, there is a lack of study about the current prevalence and health burden due to DLC using reliable data sources.

Methods: We used data from the Global Burden of Disease study 2019 (GBD 2019) to estimate the prevalence and health burden of DLC in 204 countries from 1990 to 2019, by age, sex, and sociodemographic index (SDI). The estimates were produced in DisMod-MR 2.1, a Bayesian meta-regression tool. Summary exposure value (SEV) was used to show the prevalence of DLC, while diseases adjusted life year (DALY) was used to represent the disease burden. The disease burden was estimated for DLC-induced colorectal cancer. Spearman Rank Order correlation was used for correlation analysis, and estimated annual percentage (EAPC) was used to reflect the temporal trends.

Results: From 1990 to 2019, the global prevalence of DLC decreased (EAPC of SEV, -0.47; 95% CI, -0.5 to -0.43), but have increased in Oceania region and in many countries, such as United Arab Emirates, New Zealand, Japan, and France. The global DALYs associated with low in calcium were estimated to be 3.14 million (95% uncertainty interval (UI), 2.25-4.26 million) in 2019, with an age standardized rate of 38.2 (95% UI, 27.2-51.8) per 100,000. Unlike the prevalence, the global age standardized DALY rates has remained unchanged (EAPC, -0.03; 95% CI, -0.12 to 0.07), but has increased in over 80 of the 204 countries, located mainly in Asia, Africa, and South America. In all years and regions, the age standardized SEV and DALY rates were higher in male people than that in female people. The prevalence (rho = -0.823; P < 0.001) and disease burden (rho = -0.433; P < 0.001) associated with diet in low calcium were strongly correlated to SDI. The prevalence decreased with age, but the DALY rates increased with age and peaked at about 90 years. The prevalence of DLC has decreased worldwide and in most countries, but the disease burden of DLC induced colorectal cancer has increased in over 40% of countries worldwide.

Conclusion: Countries with low sociodemographic level and male people are more likely to experience the risk of DLC and related disease burden. Related measures in improve dietary calcium intake are in need to address diet in low calcium related health problems.

The development of advanced diabetes technology has permitted persons with type 1 diabetes mellitus to improve metabolic control significantly, particularly with the development of advanced hybrid closed-loop systems which have improved the quality of life by reducing hypoglycemia, decreasing macroangiopathy and microangiopathy-related complications, ameliorating HbA1c and improving glycemic variability. Despite the progression made over the past few decades, there is still significant margin for improvement to be made in terms of attaining appropriate metabolic control. Various factors are responsible for poor glycemic control including inappropriate carbohydrate counting, repeated bouts of hypoglycemia, hypoglycemia unawareness, cutaneous manifestations due to localized insulin use and prolonged use of diabetes technology, psychosocial comorbidities such as eating disorders or 'diabulimia', the coexistence of insulin resistance among people with type 1 diabetes and the inability to mirror physiological endogenous pancreatic insulin secretion appropriately. Hence, the aim of this review is to highlight and overcome the barriers in attaining appropriate metabolic control among people with type 1 diabetes by driving research into adjunctive treatment for coexistent insulin resistance and developing new advanced diabetic technologies to preserve β cell function and mirror as much as possible endogenous pancreatic functions.

Background/objectives: Adherence to dietary recommendations is a critical component in the management of type 1 diabetes (T1D). Taste and flavor significantly influence food choices. The aim of this study was to investigate taste sensitivity and flavor recognition ability in adults with T1D compared to healthy individuals.

Subjects/methods: Seventy-two people with T1D and 72 matched healthy controls participated in the study. Participants underwent the gustometry test for sweet, sour, salty, and bitter tastes and the flavor test, which consisted of oral administration of aqueous aromatic solutions identifying 21 different compounds.

Results: Participants with T1D had significantly lower flavor scores and gustometry scores than controls (p < 0.0001 and p = 0.0063, respectively). T1D individuals showed a lower perception of sour, bitter and salty tastes than controls, while the perception of sweet taste was similar. The sex differences and age-related decline in flavor perception observed in controls were not present in the participants with T1D. Neither BMI nor disease-related parameters such as fasting blood glucose on the day of the study, glycosylated hemoglobin, age at onset of diabetes, duration of diabetes, or type of insulin treatment (insulin pump or multiple daily injections) correlated with flavor and taste perception in the T1D participants.

Conclusions: Flavor and taste perception are impaired in adults with T1D, potentially affecting dietary adherence and food choices. This highlights the need for further research into the mechanisms underlying sensory changes in T1D and emphasizes the importance of targeted dietary interventions to improve health outcomes and quality of life in this population.

Background and aim: Gestational diabetes mellitus (GDM) is one of the most prevalent disorders occurring during pregnancy, which confers significant risk of short and long-term adverse outcomes in both mothers and offspring. Recently, more attention has been paid to the association of pre-pregnancy and early pregnancy healthy dietary patterns, such as Mediterranean dietary pattern with GDM. However, there is a lack of systematic review and meta-analysis summarizing findings in this regard. Hence, we sought to assess the association of MedDiet and GDM in observational studies by performing a systematic review and meta-analysis.

Methods: A comprehensive systematic literature search of observational studies was conducted via PubMed, Scopus, and Google Scholar, up to August 2023. Studies were included in our review if they evaluated the association of MedDiet and GDM, following an observational study design.

Results: Ten studies were included in this study. Combining effect sizes, we found that adherence to MedDiet was inversely associated with GDM risk (OR = 0.64; CI: 0.52-0.78); implying that higher adherence to the MedDiet could reduce the risk of GDM by about 36%. Stratification by the geographic area, Mediterranean countries, time of dietary assessment and study design, showed a consistent significant association between MedDiet and GDM.

Conclusion: We conclude that adhering to diets resembling MedDiet, before or in early pregnancy, could be associated with lower risks or odds of GDM.