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The Link between Genetics and Metabolic Syndrome
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The Link between Genetics and Metabolic Syndrome

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 2360

Special Issue Editor

Prof. Dr. Ji Wan Park

E-Mail Website
Guest Editor
Department of Medical Genetics, College of Medicine, Hallym University, 1 Hallymdaehak-gil, Chuncheon, Gangwon-do 24252, Korea
Interests: genetic risk prediction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolic syndrome is a common condition diagnosed when three or more of the following five conditions are present: abdominal obesity, high blood pressure, elevated fasting blood glucose, high plasma triglycerides, and low HDL cholesterol. As a group of conditions, it increases the risk of various complex diseases, such as type 2 diabetes, hypertension, coronary heart disease, stroke, and nonalcoholic fatty liver. However, if an individual’s genetic risk can be predicted before the onset of the disease, the risk of developing severe metabolic disorders can be reduced by making lifestyle changes. Recent advances in genotyping technologies and genome-wide association studies have uncovered a number of susceptibility variants associated with metabolic traits and related diseases. This Special Issue invites submissions of high-quality, original research focused on the topics essential to preventing abnormal metabolic conditions from progressing to severe metabolic disorders. Related topics may include the contribution of heredity and environment to metabolic syndrome, the application of genetic or epigenetic variants for the prevention and treatment of metabolic diseases, and the evaluation of the usefulness of environmental changes or lifestyle interventions based on an individual’s genetic makeup.

Prof. Dr. Ji Wan Park
Guest Editor

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Keywords

  • metabolic syndrome and related disorders
  • biomarker discovery
  • genome-wide association study
  • omics data integration
  • gene–environment interaction
  • disease risk prediction
  • lifestyle intervention

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Published Papers (1 paper)

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Research

13 pages, 2180 KiB  
Article
Development of a Polygenic Risk Score for BMI to Assess the Genetic Susceptibility to Obesity and Related Diseases in the Korean Population
by Nara Yoon and Yoon Shin Cho
Int. J. Mol. Sci. 2023, 24(14), 11560; https://doi.org/10.3390/ijms241411560 - 17 Jul 2023
Cited by 2 | Viewed by 2132
Abstract
Hundreds of genetic variants for body mass index (BMI) have been identified from numerous genome-wide association studies (GWAS) in different ethnicities. In this study, we aimed to develop a polygenic risk score (PRS) for BMI for predicting susceptibility to obesity and related traits [...] Read more.
Hundreds of genetic variants for body mass index (BMI) have been identified from numerous genome-wide association studies (GWAS) in different ethnicities. In this study, we aimed to develop a polygenic risk score (PRS) for BMI for predicting susceptibility to obesity and related traits in the Korean population. For this purpose, we obtained base data resulting from a GWAS on BMI using 57,110 HEXA study subjects from the Korean Genome and Epidemiology Study (KoGES). Subsequently, we calculated PRSs in 13,504 target subjects from the KARE and CAVAS studies of KoGES using the PRSice-2 software. The best-fit PRS for BMI (PRSBMI) comprising 53,341 SNPs was selected at a p-value threshold of 0.064, at which the model fit had the greatest R2 score. The PRSBMI was tested for its association with obesity-related quantitative traits and diseases in the target dataset. Linear regression analyses demonstrated significant associations of PRSBMI with BMI, blood pressure, and lipid traits. Logistic regression analyses revealed significant associations of PRSBMI with obesity, hypertension, and hypo-HDL cholesterolemia. We observed about 2-fold, 1.1-fold, and 1.2-fold risk for obesity, hypertension, and hypo-HDL cholesterolemia, respectively, in the highest-risk group in comparison to the lowest-risk group of PRSBMI in the test population. We further detected approximately 26.0%, 2.8%, and 3.9% differences in prevalence between the highest and lowest risk groups for obesity, hypertension, and hypo-HDL cholesterolemia, respectively. To predict the incidence of obesity and related diseases, we applied PRSBMI to the 16-year follow-up data of the KARE study. Kaplan–Meier survival analysis showed that the higher the PRSBMI, the higher the incidence of dyslipidemia and hypo-HDL cholesterolemia. Taken together, this study demonstrated that a PRS developed for BMI may be a valuable indicator to assess the risk of obesity and related diseases in the Korean population. Full article
(This article belongs to the Special Issue The Link between Genetics and Metabolic Syndrome)
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