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GWAS Study

Exploring the Genetic Association between Obesity and Serum Lipid Levels Using Bivariate Methods.

Ke J, Gao W, Wang B et al.

36606461 PubMed ID
GWAS Study Type
746 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

KJ
Ke J
GW
Gao W
WB
Wang B
CW
Cao W
LJ
Lv J
YC
Yu C
HT
Huang T
SD
Sun D
LC
Liao C
PY
Pang Y
PZ
Pang Z
CL
Cong L
WH
Wang H
WX
Wu X
LY
Liu Y
LL
Li L
Chapter II

Abstract

Summary of the research findings

It is crucial to understand the genetic mechanisms and biological pathways underlying the relationship between obesity and serum lipid levels. Structural equation models (SEMs) were constructed to calculate heritability for body mass index (BMI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the genetic connections between BMI and the four classes of lipids using 1197 pairs of twins from the Chinese National Twin Registry (CNTR). Bivariate genomewide association studies (GWAS) were performed to identify genetic variants associated with BMI and lipids using the records of 457 individuals, and the results were further validated in 289 individuals. The genetic background affecting BMI may differ by gender, and the heritability of males and females was 71% (95% CI [.66, .75]) and 39% (95% CI [.15, .71]) respectively. BMI was positively correlated with TC, TG and LDL-C in phenotypic and genetic correlation, while negatively correlated with HDL-C. There were gender differences in the correlation between BMI and lipids. Bivariate GWAS analysis and validation stage found 7 genes (LOC105378740, LINC02506, CSMD1, MELK, FAM81A, ERAL1 and MIR144) that were possibly related to BMI and lipid levels. The significant biological pathways were the regulation of cholesterol reverse transport and the regulation of high-density lipoprotein particle clearance (p < .001). BMI and blood lipid levels were affected by genetic factors, and they were genetically correlated. There might be gender differences in their genetic correlation. Bivariate GWAS analysis found MIR144 gene and its related biological pathways may influence obesity and lipid levels.

457 Chinese ancestry individuals from twin pairs

Chapter III

Study Statistics

Key metrics and study information

746
Total Participants
GWAS
Study Type
Yes
Replicated
289 Chinese ancestry individuals from twin pairs
Replication Participants
East Asian
Ancestry
China
Recruitment Country
Chapter IV

Analysis

Comprehensive review of health and genetic findings

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