No abstract available.
Adult ; Autoantibodies/*immunology ; Female ; Hashimoto Disease/*diagnosis ; Humans ; Luminescent Measurements ; Radioimmunoassay ; Republic of Korea ; Thyroid Function Tests ; Thyroxine/*blood/immunology ; Triiodothyronine/blood

No abstract available.
Prediabetic State*

No abstract available.
Diabetes, Gestational ; Female ; Korea ; Pregnancy ; Pregnancy Outcome ; Pregnancy

Peripheral artery disease (PAD) is the most frequent cause of reduced perfusion in peripheral arteries. Patients with PAD often have manifestations of atherosclerosis of the lower limb, although both symptomatic and asymptomatic disease is common. The clinical signs of PAD can differ in diabetic and non-diabetic patients. Diabetic patients are at high risk for PAD characterized by symptoms of intermittent claudication or critical limb ischemia. However, the majority of PAD patients are clinically asymptomatic. In addition to history taking, physical examinations including inspection of the skin, palpation of leg and foot pulses, and determination of the ankle-brachial index (ABI) are considered for diagnosis of PAD. The ABI measurement is the easiest and most common investigative technique for PAD. For hemodynamic assessment, additional diagnostic modalities could be considered.
Ankle Brachial Index ; Arteries ; Asymptomatic Diseases ; Atherosclerosis ; Cardiology ; Diabetes Mellitus ; Diagnosis ; Extremities ; Foot ; Heart ; Hemodynamics ; Humans ; Intermittent Claudication ; Investigative Techniques ; Ischemia ; Leg ; Lower Extremity ; Palpation ; Perfusion ; Peripheral Arterial Disease ; Physical Examination ; Skin

The most important change introduced in the pharmacotherapy session for the 2021 Clinical Practice Guidelines for Diabetes is the recommendation of two different strategies according to the patient’s condition. One approach is to optimize the blood glucose levels, while the other approach is to reduce adverse cardiovascular events or mortality, especially in patients with comorbidities (e.g., heart failure, atherosclerotic cardiovascular disease, or chronic kidney disease). We suggest four algorithms that take into account the patient’s condition (algorithms 1 to 4). The Korean Diabetes Association (KDA) developed a web-based clinical decision support system, known as the KDA support system (KDASS), which helps with the diagnosis of diabetes or gestational diabetes and whether to use glucose-lowering agents according to the patient’s condition.

The adult gut microbiota comprises 10~100 trillion microorganisms, which is equivalent to 10 times the number of total somatic and germ cells. Further, the collective genomes of gut microbiota (microbiome) contain 100~150-fold more genes than the human genome. The gut microbiota has coevolved with humans and has shown profound effects on various host responses. Recent findings have suggested that an altered gut microbial composition is associated with metabolic diseases, including obesity, diabetes, and non-alcoholic fatty liver disease. These findings indicate that the gut microbiota should be considered as an important factor to modulate host metabolism and metabolic disorders. If we could understand the alterations of the gut microbiota, in combination with dietary patterns, this might provide insights into how the gut microbiota contributes to disease progression and whether it could be a potential diagnostic, prognostic, and therapeutic target.
Adult ; Diet ; Disease Progression ; Gastrointestinal Microbiome* ; Genome ; Genome, Human ; Germ Cells ; Humans ; Metabolic Diseases ; Metabolism ; Non-alcoholic Fatty Liver Disease ; Obesity

BACKGROUND: Incretin hormone levels as a predictor of type 2 diabetes mellitus have not been fully investigated. Therefore, we measured incretin hormone levels to examine the relationship between circulating incretin hormones, diabetes, and future diabetes development in this study. METHODS: A nested case-control study was conducted in a Korean cohort. The study included the following two groups: the control group (n=149), the incident diabetes group (n=65). Fasting total glucagon-like peptide-1 (GLP-1) and total glucose-dependent insulinotropic peptide (GIP) levels were measured and compared between these groups. RESULTS: Fasting total GIP levels were higher in the incident diabetes group than in the control group (32.64±22.68 pmol/L vs. 25.54±18.37 pmol/L, P=0.034). There was no statistically significant difference in fasting total GLP-1 levels between groups (1.14±1.43 pmol/L vs. 1.39±2.13 pmol/L, P=0.199). In multivariate analysis, fasting total GIP levels were associated with an increased risk of diabetes (odds ratio, 1.005; P=0.012) independent of other risk factors. CONCLUSION: Fasting total GIP levels may be a risk factor for the development of type 2 diabetes mellitus. This association persisted even after adjusting for other metabolic parameters such as elevated fasting glucose, hemoglobin A1c, and obesity in the pre-diabetic period.
Case-Control Studies ; Cohort Studies ; Diabetes Mellitus, Type 2* ; Fasting ; Gastric Inhibitory Polypeptide* ; Glucagon-Like Peptide 1 ; Glucose ; Incretins ; Multivariate Analysis ; Obesity ; Risk Factors

Gut microbiota play critical physiological roles in energy extraction from the intestine and in the control of systemic immunity, as well as local intestinal immunity. Disturbance of gut microbiota leads to the development of several diseases, such as colitis, inflammatory bowel diseases, metabolic disorders, cancer, etc. From a metabolic point of view, the gut is a large metabolic organ and one of the first to come into contact with dietary fats. Interestingly, excessive dietary fat has been incriminated as a primary culprit of metabolic syndrome and obesity. After intake of high-fat diet or Western diet, extensive changes in gut microbiota have been observed, which may be an underlying cause of alterations in whole body metabolism and nutrient homeostasis. Here, we summarize recent data on changes in the gut microbiota and immunity associated with dietary fat, as well as their relationships with the pathogenesis of metabolic syndrome. These findings may provide insight into the understanding of the complex pathophysiology related to the development of metabolic diseases and offer an opportunity to develop novel candidates for therapeutic agents.
Colitis ; Diet, High-Fat ; Diet, Western ; Dietary Fats* ; Gastrointestinal Microbiome* ; Homeostasis ; Inflammatory Bowel Diseases ; Intestines ; Metabolic Diseases ; Metabolism ; Obesity

Gut microbiota plays critical physiological roles in the energy extraction and in the control of local or systemic immunity. Gut microbiota and its disturbance also appear to be involved in the pathogenesis of diverse diseases including metabolic disorders, gastrointestinal diseases, cancer, etc. In the metabolic point of view, gut microbiota can modulate lipid accumulation, lipopolysaccharide content and the production of short-chain fatty acids that affect food intake, inflammatory tone, or insulin signaling. Several strategies have been developed to change gut microbiota such as prebiotics, probiotics, certain antidiabetic drugs or fecal microbiota transplantation, which have diverse effects on body metabolism and on the development of metabolic disorders.
Eating ; Fatty Acids, Volatile ; Gastrointestinal Diseases ; Hypoglycemic Agents ; Insulin ; Metabolism ; Metformin ; Microbiota* ; Obesity ; Prebiotics ; Probiotics