Dataset Information

New Common and Rare Variants Influencing Metabolic Syndrome and Its Individual Components in a Korean Population.

ABSTRACT: To identify novel loci for susceptibility to MetS, we conducted genome-wide association and exome wide association studies consisting of a discovery stage cohort (KARE, 1946 cases and 6427 controls), and a replication stage cohort (HEXA, 430 cases and 3,264 controls). For finding genetic variants for MetS, with its components, we performed multivariate analysis for common and rare associations, using a standard logistic regression analysis for MetS. From the discovery and replication GWA studies, we confirmed 21 genome-wide signals significantly associated with MetS. Of these 21, four were previously unreported to associate with any MetS components: rs765547 near LPL; rs3782889 in MYL2; and rs11065756 and rs10849915 in CCDC63. Using exome chip variants, gene-based analysis of rare variants revealed three genes, CETP, SH2B1, and ZFP2, in the discovery stage, among which only CETP was confirmed in the replication stage. Finally, CETP D442G (rs2303790) associated, as a less common variant, with decreased risk of MetS. In conclusion, we discovered a total of five new MetS-associated loci, and their overlap with other disease-related components, suggest roles in the various etiologies of MetS, and its possible preventive strategies.

SUBMITTER: Lee HS

PROVIDER: S-EPMC5890262 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

New Common and Rare Variants Influencing Metabolic Syndrome and Its Individual Components in a Korean Population.

Lee Ho-Sun HS Kim Yongkang Y Park Taesung T

Scientific reports 20180409 1

To identify novel loci for susceptibility to MetS, we conducted genome-wide association and exome wide association studies consisting of a discovery stage cohort (KARE, 1946 cases and 6427 controls), and a replication stage cohort (HEXA, 430 cases and 3,264 controls). For finding genetic variants for MetS, with its components, we performed multivariate analysis for common and rare associations, using a standard logistic regression analysis for MetS. From the discovery and replication GWA studies ...[more]

PMID: 29632305

Similar Datasets

Project description:Past studies have shown an association between metabolic syndrome and polyneuropathy, but the precise components that drive this association remain unclear.To determine the prevalence of polyneuropathy stratified by glycemic status in well-characterized obese and lean participants and investigate the association of specific components of metabolic syndrome with polyneuropathy.We performed a cross-sectional, observational study from November 1, 2010, to December 31, 2014, in obese participants (body mass index [calculated as weight in kilograms divided by height in meters squared] of 35 or more with no comorbid conditions or 32 or more with at least 1 comorbid condition) from a weight management program and lean controls from a research website. The prevalence of neuropathy, stratified by glycemic status, was determined, and a Mantel-Haenszel ?2 test was used to investigate for a trend. Logistic regression was used to model the primary outcome of polyneuropathy as a function of the components of metabolic syndrome after adjusting for demographic factors. Participants also completed quantitative sudomotor axon reflex testing, quantitative sensory testing, the neuropathy-specific Quality of Life in Neurological Disorders instrument, and the short-form McGill Pain Questionnaire.Components of metabolic syndrome (as defined by the National Cholesterol Education Program Adult Treatment Panel III), including glycemic status (as defined by the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus).Toronto consensus definition of probable polyneuropathy. Secondary outcomes included intraepidermal nerve fiber density and nerve conduction study parameters.We enrolled 102 obese participants (mean [SD] age, 52.9 [10.2] years; 48 men and 54 women; 45 with normoglycemia [44.1%], 31 with prediabetes [30.4%], and 26 with type 2 diabetes [25.5%]) and 53 lean controls (mean [SD] age, 48.5 [9.9] years; 16 men and 37 women). The prevalence of polyneuropathy was 3.8% in lean controls (n?=?2), 11.1% in the obese participants with normoglycemia (n?=?5), 29% in the obese participants with prediabetes (n?=?9), and 34.6% in the obese participants with diabetes (n?=?9) (P?<?.01 for trend). Age (odds ratio, 1.09; 95% CI, 1.02-1.16), diabetes (odds ratio, 4.90; 95% CI, 1.06-22.63), and waist circumference (odds ratio, 1.24; 95% CI, 1.00-1.55) were significantly associated with neuropathy in multivariable models. Prediabetes (odds ratio, 3.82; 95% CI, 0.95-15.41) was not significantly associated with neuropathy.The prevalence of polyneuropathy is high in obese individuals, even those with normoglycemia. Diabetes, prediabetes, and obesity are the likely metabolic drivers of this neuropathy.clinicaltrials.gov Identifier: NCT02689661.

Project description:Background:Metabolic syndrome is associated with an increased risk of diabetes. This study investigated the associations between the number of metabolic syndrome components and diabetes risk by age, sex and BMI. Methods:Data for 19,475,643 participants ??20 years old with no history of diabetes were obtained between 2009 and 2012 and were accessed using the South Korean National Health Insurance Service. Metabolic syndrome was defined according to the modified criteria of the National Cholesterol Education Program Adult Treatment Panel III. We assessed the risk of diabetes according to the number of metabolic syndrome components after stratifying the study participants into groups by age (20-39, 46-64, ??65 years), sex, and BMI (below or above 25). Results:During an average of 5.13 years of follow-up, the incidence rates of diabetes increased with the number of metabolic syndrome components. Age and BMI gradually increased with the number of metabolic syndrome components. The multivariable-adjusted hazard ratios (HRs) for incident diabetes were 1.401, 1.862, 2.47, 3.164 and 4.501 for participants with one through five components, respectively, compared with those without metabolic syndrome components. The risk of diabetes was 1.79-, 2.18-, and 3.05-times higher for participants ??65 years; 2.57-, 3.45-, and 5.18-times higher for participants 40-64 years; and 2.55-, 3.89-, and 6.31-times higher for participants 20-39 years of age with three through five components, respectively, compared to those with no components. There was no difference in the risk of diabetes between men and women. The HRs were 5.63 for participants with a BMI ??25 and 3.98 for those with a BMI <?25 among individuals with five components. Conclusions:The risk of diabetes was more strongly associated with the number of metabolic syndrome components among younger adults. In addition, the risk of diabetes across the number of metabolic syndrome components was greater in participants with a BMI ??25.

Dataset Information

New Common and Rare Variants Influencing Metabolic Syndrome and Its Individual Components in a Korean Population.

Publications

New Common and Rare Variants Influencing Metabolic Syndrome and Its Individual Components in a Korean Population.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets