Metabolic syndrome (MetS) is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs), important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs), explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE) was used for analysis, which include 8,842 individuals (age, 52.2 +/- 8.9 years; body mass index, 24.6 +/- 3.2 kg/m2). A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA) to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < 5 x 10(-6)), and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < 1.38 x 10(-7), Bonferroni-adjusted p < 0.05). Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF), the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR) signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.
Body Mass Index ; Chromosomes, Human, Pair 12 ; Cohort Studies* ; Dataset ; DNA Repair ; Genome-Wide Association Study* ; Inflammation ; Insulin Resistance ; Korea ; Metabolic Syndrome X ; Obesity ; Peroxisome Proliferator-Activated Receptors ; Peroxisomes ; Phosphotransferases ; Platelet-Derived Growth Factor ; Polymorphism, Single Nucleotide ; Protein Binding ; Protein Kinases ; Quality Control

BACKGROUND: Long menstrual cycle is a risk factor for developing type 2 diabetes and cardiovascular disease in women. We aimed to evaluate the association between existing type 2 diabetes and oligomenorrhea before diagnosis of diabetes, and to observe the differences in this association among obese and non-obese Korean women. METHODS: Patients with type 2 diabetes (n=118) and without any clinical evidence of abnormal glucose regulation (n=258) who attended the outpatient clinic of a university hospital and were over age 30. Patients self-reporting a menstrual cycle over 40 days during their 20s were defined as oligomenorrhea before diagnosis of diabetes. Obesity was defined as having a body mass index (BMI) over 25 kg/m2. RESULTS: The frequency of oligomenorrhea before diagnosis of diabetes was almost two-fold higher in women with type 2 diabetes than in the control group (16.1% vs. 8.5%, P=0.03). Oligomenorrhea was associated with type 2 diabetes after adjusting for age, BMI, systolic blood pressure, triglycerides, and high density lipoprotein cholesterol (odds ratio, 3.89; 95% confidence interval, 1.37 to 11.04). Among women with oligomenorrhea before diagnosis of diabetes, the frequency of type 2 diabetes was significantly higher in obese subjects than in their non-obese counterparts (90.9% vs. 30.0%, P=0.03). CONCLUSION: Having a long menstrual cycle could be a risk factor for the development of type 2 diabetes, especially in obese women.
Ambulatory Care Facilities ; Blood Pressure ; Body Mass Index ; Cardiovascular Diseases ; Cholesterol ; Cholesterol, HDL ; Diabetes Mellitus ; Diabetes Mellitus, Type 2 ; Female ; Glucose ; Humans ; Lipoproteins ; Menstrual Cycle ; Obesity ; Oligomenorrhea ; Risk Factors ; Triglycerides

BACKGROUND/AIMS: Sleep disorder (SD) is associated with an increased risk of cardiovascular disease and is more prevalent among individuals with type 2 diabetes mellitus. These health problems not only frequently coexist but also exacerbate each other. We conducted a cross-sectional study to estimate the prevalence of SD among diabetic patients and to investigate the relationship between SD and cardiovascular risk among these patients. METHODS: We recruited 784 patients with type 2 diabetes and conducted a self-administered questionnaire. We assessed sleep quality using the Pittsburgh Sleep Quality Index and the risk of obstructive sleep apnea (OSA) using the Berlin Questionnaire. Additional information included blood pressure and metabolic profiles. RESULTS: Of the 784 diabetic patients, 301 (38.4%) patients had poor sleep quality, and 124 (15.8%) were at high risk for OSA. Patients at increased risk for OSA were more obese; they also had higher blood pressure, fasting plasma insulin levels, insulin resistance assessed by homeostasis model assessment (HOMA-IR), and serum triglycerides levels (p < 0.05). The frequency of risk for OSA was higher among obese patients compared with non-obese patients (34.8% vs. 9.4%, p < 0.05). Logistic regression analysis revealed that male sex and bone mass index were independent predictors of risk for OSA. CONCLUSIONS: SD was prevalent among type 2 diabetic patients, and OSA could aggravate their risk for cardiovascular disease. Clinical treatment of these patients should include evaluation and intervention for SD.
Adult ; Aged ; Analysis of Variance ; Body Mass Index ; Cardiovascular Diseases/*epidemiology ; Chi-Square Distribution ; Cross-Sectional Studies ; Diabetes Mellitus, Type 2/*epidemiology ; Female ; Humans ; Logistic Models ; Male ; Middle Aged ; Obesity/epidemiology ; Prevalence ; Questionnaires ; Republic of Korea/epidemiology ; Risk Assessment ; Risk Factors ; Sex Factors ; Sleep Apnea, Obstructive/epidemiology ; Sleep Disorders/diagnosis/*epidemiology